WorldWideScience

Sample records for sensing based agrometeorological

  1. Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?

    DEFF Research Database (Denmark)

    Diouf, Abdoul Aziz; Hiernaux, Pierre; Brandt, Martin Stefan

    2016-01-01

    evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483...... kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase...

  2. Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

    Science.gov (United States)

    Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

    2014-05-01

    By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

  3. IMPACT OF THE ATATÜRK DAM LAKE ON AGRO-METEOROLOGICAL ASPECTS OF THE SOUTHEASTERN ANATOLIA REGION USING REMOTE SENSING AND GIS ANALYSIS

    Directory of Open Access Journals (Sweden)

    O. Ozcan

    2012-07-01

    Full Text Available The Atatürk Dam is the fourth largest clay-cored rock fill dam in the world. It was constructed on the Euphrates River located in semi-arid Southeastern Turkey in the 1980s as the central component of a large-scale regional development project for the Southeastern Anatolia region (referred to as GAP. The construction began in 1983 and was completed in 1990. The dam and the hydroelectric power plant, which went into service after filling up the reservoir was accomplished in 1992. The Atatürk Dam, which has a height of 169 m, a total storage capacity of 48.7 million m3, and a surface area of about 817 km2 plays an important role in the development of Turkey's energy and agriculture sectors. In this study, the spatial and temporal impacts of the Atatürk Dam on agro-meteorological aspects of the Southeastern Anatolia region have been investigated. Change detection and environmental impacts due to water-reserve changes in Atatürk Dam Lake have been determined and evaluated using multi-temporal Landsat satellite imageries and meteorological datasets within a period of 1984 to 2011. These time series have been evaluated for three time periods. Dam construction period constitutes the first part of the study. Land cover/use changes especially on agricultural fields under the Atatürk Dam Lake and its vicinity have been identified between the periods of 1984 to 1992. The second period comprises the 10-year period after the completion of filling up the reservoir in 1992. At this period, Landsat and meteorological time-series analyses are examined to assess the impact of the Atatürk Dam Lake on selected irrigated agricultural areas. For the last 9-year period from 2002 to 2011, the relationships between seasonal water-reserve changes and irrigated plains under changing climatic factors primarily driving vegetation activity (monthly, seasonal, and annual fluctuations of rainfall rate, air temperature, humidity on the watershed have been investigated

  4. Optimal use of agrometeorological information for sustainable agricultural production in semi-arid regions of India

    International Nuclear Information System (INIS)

    Surender, S.; Diwan, S.; Rao, V.U.M.

    2006-05-01

    The concept of sustainable agriculture encompasses ecological, economic and social problems in which weather and climate can be of great importance. Despite considerable technological advancement and improved irrigation facilities, Indian farmers are still dependent on seasonal rains, which are highly variable both in time and space. Inclement weather events like droughts, floods, cold and heat waves, hails, squalls, tropical storms severely affect the agricultural production. Their harmful effects may be partially reduced if the occurrence of these events is predicted in advance and farmers are suitably advised to take preventive/corrective measures. With the objective to help the farmers maximize profits by decreasing weather related losses, increasing the timeliness of farm operations and to reduce environmental pollution through the optimal use of agricultural chemicals, the location specific/regional Agrometeorological Advisory Service was initiated in the year 1991. The forecasting skills of most of the weather parameters at Hisar have improved considerably over the years. Now, it is time to integrate and make use of vast agrometeorological information available online in preparing weather based advisories for in-season agricultural operations both for single locations and on a meso or regional scale as desired. This can be further strengthened through input from new technologies such as neural network, remote sensing, GIS, ground measurements and modeling applications along with traditional wisdom available with the farming communities should be integrated to further strengthen the location specific weather forecasting system for the development of sustainable and more efficient crop production systems. (author)

  5. Possible uses of satellite remote sensing in agrometeorology; Possibilités d'utilisation de la télédétection satellitaire en agrométéorologie

    Energy Technology Data Exchange (ETDEWEB)

    Guyot, G.; Seguin, B.

    1988-07-01

    Remote sensing offers new possibilities in agrometeorology. Meteorological satellites (which have good revisit capability but low spatial resolution) and earth observation satellites (which have good spatial resolution but poor revisit capability) give complementary information on crop growth conditions and on the biological status of plants. Thermal infrared data can be used to map local climates, to estimate water balance at the scale of a small region and to determine the extent and the seriousness of damage caused by major climatic accidents (frost, drought). Visible near, near and middle infrared data are well adapted to crop identification and monitoring, biomass estimation and yield forecasting. The combination of information given by these 2 types of satellites should in future provide better knowledge and better control of agricultural production. However the application of such techniques may be limited by the cloud cover [French] La télédétection offre des possibilités nouvelles dans le domaine de l’agrométéorologie. Les satellites météorologiques (qui ont une bonne répétitivité dans le temps mais une faible résolution spatiale) et les satellites d’observation de la terre (qui ont une bonne résolution spatiale mais une faible répétitivité dans le temps) permettent d’obtenir des informations complémentaires sur les conditions dans lesquelles se développent les cultures et sur leur état. Les données de l’infrarouge thermique peuvent être utilisées pour cartographier les climats locaux, estimer les bilans hydriques à l’échelle de la petite région et déterminer l’extension spatiale et l’ampleur des accidents climatiques majeurs (gel, sécheresse). Les données du visible, du proche et du moyen infrarouge permettent d’identifier les cultures, de déterminer leur stade phénologique, de suivre leur évolution, d’estimer leur biomasse et de prévoir leur production. La combinaison des informations fournies par ces 2

  6. Agrometeorology and water needs of crops

    Directory of Open Access Journals (Sweden)

    Gabriele Cola

    2006-07-01

    Full Text Available This paper aims to present some agrometeorological methods useful for water management in agriculture discussing the existing technology and giving some insights about research and development activities in this field. After a general discussion about the importance of water for plants and more generally for the ecosystem the agrometerological aspects of water balance are discussed and opportunities of use of forecasts are also presented. Some effects of climatic change on water needs of crops are also discussed.

  7. Extension Agrometeorology as the Answer to Stakeholder Realities: Response Farming and the Consequences of Climate Change

    Directory of Open Access Journals (Sweden)

    Durton Nanja

    2013-08-01

    Full Text Available Extension agrometeorology is applied in agrometeorological extension work to advice and serve farmers. In agrometeorology, response farming has been developed decades ago. Climate change complicates response farming, but does not alter it. This paper reports on new operationalization of that response farming in new educational commitments in agroclimatology. It is explained how “Science Field Shops” are an example in Indonesia. This was based on a thorough analysis of what climate change means for farmers in Asia. For Africa, we report on eying the training of agrometeorological extension trainers (“product intermediaries” in West Africa, based on a thorough analysis of what climate change means for farmers in Africa. We also compare experience with reaching farmers in South Africa and farmer communities in Zambia, as new forms of supporting response farming, all under conditions of a changing climate. The paper, for the first time, connects results from four different programs the senior author is taking part in. There is first and foremost the need for training material to make it possible for the product intermediaries to participate in training extension intermediaries. This should, particularly, bring new knowledge to farmers. With what is presently available and with new approaches, climate extension should be developed and tested with farmers in ways that improve farmer preparedness and decision making.

  8. Nonparametric Integrated Agrometeorological Drought Monitoring: Model Development and Application

    Science.gov (United States)

    Zhang, Qiang; Li, Qin; Singh, Vijay P.; Shi, Peijun; Huang, Qingzhong; Sun, Peng

    2018-01-01

    Drought is a major natural hazard that has massive impacts on the society. How to monitor drought is critical for its mitigation and early warning. This study proposed a modified version of the multivariate standardized drought index (MSDI) based on precipitation, evapotranspiration, and soil moisture, i.e., modified multivariate standardized drought index (MMSDI). This study also used nonparametric joint probability distribution analysis. Comparisons were done between standardized precipitation evapotranspiration index (SPEI), standardized soil moisture index (SSMI), MSDI, and MMSDI, and real-world observed drought regimes. Results indicated that MMSDI detected droughts that SPEI and/or SSMI failed to do. Also, MMSDI detected almost all droughts that were identified by SPEI and SSMI. Further, droughts detected by MMSDI were similar to real-world observed droughts in terms of drought intensity and drought-affected area. When compared to MMSDI, MSDI has the potential to overestimate drought intensity and drought-affected area across China, which should be attributed to exclusion of the evapotranspiration components from estimation of drought intensity. Therefore, MMSDI is proposed for drought monitoring that can detect agrometeorological droughts. Results of this study provide a framework for integrated drought monitoring in other regions of the world and can help to develop drought mitigation.

  9. Agrometeorological services for smallholder farmers in West Africa

    Directory of Open Access Journals (Sweden)

    V. Tarchiani

    2018-04-01

    Full Text Available Climate variability and change are recognised as a major threat for West African agriculture, particularly for smallholder farmers. Moreover, population pressure, poverty, and food insecurity, are worsening the vulnerability of production systems to climate risks. Application of Climate Services in agriculture, specifically Agrometeorological Services, is acknowledged as a valuable innovation to assist decision-making and develop farmers' specific adaptive capacities. In West Africa, the World Meteorological Organisation and National Meteorological Services deployed considerable efforts in the development of Agrometeorological Services. Nevertheless, the impacts of such services on West African farming communities are still largely unknown. This paper aims to delineate the added value of agrometeorological services for farmers within the Agriculture Innovation System of Mauritania. The results of this quali-quantitative assessment demonstrate that farmers use agrometeorological information for a variety of choices: making strategic choice on the seed variety and on the geographical distribution of plots, choosing the most appropriate planting date, better tuning crop development cycle with the rhythm of the rains and choosing favourable periods for different cultural operations. Globally, the effects of all these good practices can be summarized by an increase of crops productivity and a decrease of cropping costs (including opportunity cost in terms of inputs and working time.

  10. Utilization of Agro-meteorological Services among Arable Crop ...

    African Journals Online (AJOL)

    Thomas Kehinde Adesina

    The study assessed arable crop farmers' utilization of agro-meteorological services in ... The Intergovernmental Panel on Climate Change, IPCC's Fourth ... the patterns of impact of climate change on agriculture can be classified into ... temperature rise causing fish to inhabit in different ranges. ..... Journal of Human Ecology.

  11. Agrometeorological services for smallholder farmers in West Africa

    Science.gov (United States)

    Tarchiani, Vieri; Camacho, José; Coulibaly, Hamidou; Rossi, Federica; Stefanski, Robert

    2018-04-01

    Climate variability and change are recognised as a major threat for West African agriculture, particularly for smallholder farmers. Moreover, population pressure, poverty, and food insecurity, are worsening the vulnerability of production systems to climate risks. Application of Climate Services in agriculture, specifically Agrometeorological Services, is acknowledged as a valuable innovation to assist decision-making and develop farmers' specific adaptive capacities. In West Africa, the World Meteorological Organisation and National Meteorological Services deployed considerable efforts in the development of Agrometeorological Services. Nevertheless, the impacts of such services on West African farming communities are still largely unknown. This paper aims to delineate the added value of agrometeorological services for farmers within the Agriculture Innovation System of Mauritania. The results of this quali-quantitative assessment demonstrate that farmers use agrometeorological information for a variety of choices: making strategic choice on the seed variety and on the geographical distribution of plots, choosing the most appropriate planting date, better tuning crop development cycle with the rhythm of the rains and choosing favourable periods for different cultural operations. Globally, the effects of all these good practices can be summarized by an increase of crops productivity and a decrease of cropping costs (including opportunity cost) in terms of inputs and working time.

  12. Studying Sensing-Based Systems

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun

    2013-01-01

    Recent sensing-based systems involve a multitude of users, devices, and places. These types of systems challenge existing approaches for conducting valid system evaluations. Here, the author discusses such evaluation challenges and revisits existing system evaluation methodologies....

  13. Collaborative Innovation in Agrometeorology: Coordination Strategies to Develop a Monitoring IT System for Brazil

    Directory of Open Access Journals (Sweden)

    Martha Delphino Bambini

    2014-04-01

    Full Text Available This case-study article presents the results from a morphology analysis of a knowledge and information network, focusing on the coordination mechanisms employed to generate a convergent arrangement. Agritempo was the first information system to offer (in 2003 free access to a broad range of agrometeorological data comprising all the Brazilian territory, representing an important technological innovation to the agricultural sector. To study this phenomenon an analytical framework of the Techno-Economic Network (TEN and concepts from the Innovation Sociology field was employed. Results indicate that the durability of this arrangement – from 2003 to 2014 – can be explained by the effectiveness of the coordination strategies established in the network such as: trust based relationships; institutional and individual leadership actions; contracting; software applications and shared common working procedures.

  14. Generalized eigenvalue based spectrum sensing

    KAUST Repository

    Shakir, Muhammad

    2012-01-01

    Spectrum sensing is one of the fundamental components in cognitive radio networks. In this chapter, a generalized spectrum sensing framework which is referred to as Generalized Mean Detector (GMD) has been introduced. In this context, we generalize the detectors based on the eigenvalues of the received signal covariance matrix and transform the eigenvalue based spectrum sensing detectors namely: (i) the Eigenvalue Ratio Detector (ERD) and two newly proposed detectors which are referred to as (ii) the GEometric Mean Detector (GEMD) and (iii) the ARithmetic Mean Detector (ARMD) into an unified framework of generalize spectrum sensing. The foundation of the proposed framework is based on the calculation of exact analytical moments of the random variables of the decision threshold of the respective detectors. The decision threshold has been calculated in a closed form which is based on the approximation of Cumulative Distribution Functions (CDFs) of the respective test statistics. In this context, we exchange the analytical moments of the two random variables of the respective test statistics with the moments of the Gaussian (or Gamma) distribution function. The performance of the eigenvalue based detectors is compared with the several traditional detectors including the energy detector (ED) to validate the importance of the eigenvalue based detectors and the performance of the GEMD and the ARMD particularly in realistic wireless cognitive radio network. Analytical and simulation results show that the newly proposed detectors yields considerable performance advantage in realistic spectrum sensing scenarios. Moreover, the presented results based on proposed approximation approaches are in perfect agreement with the empirical results. © 2012 Springer Science+Business Media Dordrecht.

  15. Understanding the relationship between the variability in agrometeorological indices and adaptation practices across the Canadian Prairies

    Science.gov (United States)

    Chipanshi, A.; Qi, D.; Zhang, Y.; Cherneski, P.

    2017-12-01

    In an attempt to understand how agriculture will adapt to the changing and variable climate, crop based agrometeorological indices including the Effective Growing Degree Days (EGDDs), Growing Season Length (GSL), Heat waves, Water Demand (Precipitation - Evapotranspiration) and the Standardized Precipitation Evapotranspiration Index (SPEI) were analyzed in terms of frequency, duration and trend over a 63-year timeframe (1950 to 2012) from the Canadian Prairies and related to crop production. The heat based indices (EGDD, GSL and Heat waves) increased over the analysis period due to an upward increase in the observed mean temperature. The change was most noticeable in the northern portion of the study area where agriculture is limited by insufficient heat units under the present climate. Heat waves became more frequent in the southern parts of the study area (there were more days above the 30oC threshold). Water availability as assessed from water demand (P-PE) and SPEI trended downward especially in Alberta and Saskatchewan. In spite of the increased severity and frequency in water deficits, there was a noticeable reduction in the variability of crop yield over time. This was attributed to the increased adaptive capacity that has been gained through the use of improved seed hybrids, fertilizer, the use of fungicides and adoption of best management practices such as zero till and direct seeding. After crop yields were de-trended to remove effects of technology, the cumulative precipitation during the growing season explained the majority of the variance in crop yield. This initial analysis has set the stage for analyzing the characteristics of agrometeorological indices under climate change scenarios and how accumulated precipitation during the growing season will affect crop yield and production.

  16. Linking the M&Rfi Weather Generator with Agrometeorological Models

    Science.gov (United States)

    Dubrovsky, Martin; Trnka, Miroslav

    2015-04-01

    Realistic meteorological inputs (representing the present and/or future climates) for the agrometeorological model simulations are often produced by stochastic weather generators (WGs). This contribution presents some methodological issues and results obtained in our recent experiments. We also address selected questions raised in the synopsis of this session. The input meteorological time series for our experiments are produced by the parametric single site weather generator (WG) Marfi, which is calibrated from the available observational data (or interpolated from surrounding stations). To produce meteorological series representing the future climate, the WG parameters are modified by climate change scenarios, which are prepared by the pattern scaling method: the standardised scenarios derived from Global or Regional Climate Models are multiplied by the change in global mean temperature (ΔTG) determined by the simple climate model MAGICC. The presentation will address following questions: (i) The dependence of the quality of the synthetic weather series and impact results on the WG settings. An emphasis will be put on an effect of conditioning the daily WG on monthly WG (presently being one of our hot topics), which aims at improvement of the reproduction of the low-frequency weather variability. Comparison of results obtained with various WG settings is made in terms of climatic and agroclimatic indices (including extreme temperature and precipitation characteristics and drought indices). (ii) Our methodology accounts for the uncertainties coming from various sources. We will show how the climate change impact results are affected by 1. uncertainty in climate modelling, 2. uncertainty in ΔTG, and 3. uncertainty related to the complexity of the climate change scenario (focusing on an effect of inclusion of changes in variability into the climate change scenarios). Acknowledgements: This study was funded by project "Building up a multidisciplinary scientific

  17. Agrometeorological parameters for prediction of the maturation period of Arabica coffee cultivars

    Science.gov (United States)

    Pezzopane, José Ricardo Macedo; Salva, Terezinha de Jesus Garcia; de Lima, Valéria Bittencourt; Fazuoli, Luiz Carlos

    2012-09-01

    The objective of this study was to determine the harvest period of coffee fruits based on the relationship between agrometeorological parameters and sucrose accumulation in the seeds. Over the crop years 2004/2005 and 2006/2007, from 150 days after flowering (DAF) onwards, samples of 50 fruits of cultivars Mundo Novo IAC 376-4, Obatã IAC 1669-20 and Catuaí Vermelho IAC 144 were collected from coffee trees located in Campinas, Brazil. The endosperm of the fruits was freeze-dried, ground and analyzed for sucrose content by high-performance liquid chromatography. A weather station provided data to calculate the accumulated growing degree-day (GDD) units, and the reference (ETo) and actual (ETr) evapotranspiration rates. The results showed that the highest rates of sucrose accumulation occurred at the transition from the cane-green to the cherry phenological stage. Models for the estimation of sucrose content during maturation based on meteorological variables exhibited similar or better performance than the DAF variable, with better results for the variables GDD and ETo. The Mundo Novo cultivar reached the highest sucrose level in the endosperm after 2,790 GDD, while cultivar Catuaí attained its maximum sucrose concentration after the accumulated evapotranspiration rate has reached a value of 870 mm. As for cultivar Obatã, the maximum sucrose concentration was predicted with the same degree of accuracy using any of the parameters investigated. For the Obatã cultivar, the values of the variables calculated for the maximum sucrose concentration to be reached were 249 DAF, 3,090 GDD, 1,020 ETo and 900 ETr.

  18. Improving Agricultural Productivity in Tonga through Ensuring Data Availability and Enhancing Agro-meteorological Services

    Science.gov (United States)

    Kim, K. H.

    2015-12-01

    The project was first conceived in the Global Framework for Climate Services Regional Consultation in the Cook Islands in March 2014. In this meeting, key officials from the Ministry of Agriculture and Food, Forests, and Fisheries and the Tonga Meteorological Services had a meeting with the APEC Climate Center scientists with the idea to collaborate on a joint project. The project evolved to include the following components: assessment of users' needs and capacities, development of an agricultural database, research on the core relationships between agriculture and climate through modeling and field trials, and the development and delivery of agro-meteorological services. Envisioned outputs include a 2-7 day warning for pests and diseases, a suite of tools supporting decisions on planting dates and crop varieties, and other advisory services derived from seasonal climate forecasts. As one of the climate adaptation projects under its Pacific Island portfolio, the project will deliver urgent information services for Tongan agricultural growers and exporters. The project comes into greater importance and urgency, as the 2014 drought event resulted in the destruction of 80% of squash in Tonga, a main export crop from which the country derives foreign exchange earnings. Since 2014, some of the project achievements include the first agro-met data collection in Tonga, the development of an agricultural DB management system that houses archived agriculture data, and key meetings with stakeholders to ensure alignment of the project objectives and design with the interests of the Tongan government and other stakeholders. In addition, rigorous scientific research through modeling and field trials has been conducted to address the twin goals of supporting Tonga's economy as well as food security. Based on the findings from the research, tools will be developed to translate the science into knowledge that supports decisions on the farm scale.

  19. Handheld Microneedle-Based Electrolyte Sensing Platform.

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Philip R. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Rivas, Rhiana [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Johnson, David [Aquila Technologies Group, Inc., Albuquerque, NM (United States); Edwards, Thayne L. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Koskelo, Markku [Aquila Technologies Group, Inc., Albuquerque, NM (United States); Shawa, Luay [Aquila Technologies Group, Inc., Albuquerque, NM (United States); Brener, Igal [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Chavez, Victor H. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Polsky, Ronen [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2015-11-01

    Sandia National Laboratories will provide technical assistance, within time and budget, to Requester on testing and analyzing a microneedle-based electrolyte sensing platform. Hollow microneedles will be fabricated at Sandia and integrated with a fluidic chip using plastic laminate prototyping technology available at Sandia. In connection with commercial ion selective electrodes the sensing platform will be tested for detection of electrolytes (sodium and/or potassium) within physiological relevant concent ration ranges.

  20. Generalized eigenvalue based spectrum sensing

    KAUST Repository

    Shakir, Muhammad; Alouini, Mohamed-Slim

    2012-01-01

    of the decision threshold of the respective detectors. The decision threshold has been calculated in a closed form which is based on the approximation of Cumulative Distribution Functions (CDFs) of the respective test statistics. In this context, we exchange

  1. The possibilities of compressed sensing based migration

    KAUST Repository

    Aldawood, Ali; Hoteit, Ibrahim; Alkhalifah, Tariq Ali

    2013-01-01

    Linearized waveform inversion or Least-square migration helps reduce migration artifacts caused by limited acquisition aperture, coarse sampling of sources and receivers, and low subsurface illumination. However, leastsquare migration, based on L2-norm minimization of the misfit function, tends to produce a smeared (smoothed) depiction of the true subsurface reflectivity. Assuming that the subsurface reflectivity distribution is a sparse signal, we use a compressed-sensing (Basis Pursuit) algorithm to retrieve this sparse distribution from a small number of linear measurements. We applied a compressed-sensing algorithm to image a synthetic fault model using dense and sparse acquisition geometries. Tests on synthetic data demonstrate the ability of compressed-sensing to produce highly resolved migrated images. We, also, studied the robustness of the Basis Pursuit algorithm in the presence of Gaussian random noise.

  2. The possibilities of compressed sensing based migration

    KAUST Repository

    Aldawood, Ali

    2013-09-22

    Linearized waveform inversion or Least-square migration helps reduce migration artifacts caused by limited acquisition aperture, coarse sampling of sources and receivers, and low subsurface illumination. However, leastsquare migration, based on L2-norm minimization of the misfit function, tends to produce a smeared (smoothed) depiction of the true subsurface reflectivity. Assuming that the subsurface reflectivity distribution is a sparse signal, we use a compressed-sensing (Basis Pursuit) algorithm to retrieve this sparse distribution from a small number of linear measurements. We applied a compressed-sensing algorithm to image a synthetic fault model using dense and sparse acquisition geometries. Tests on synthetic data demonstrate the ability of compressed-sensing to produce highly resolved migrated images. We, also, studied the robustness of the Basis Pursuit algorithm in the presence of Gaussian random noise.

  3. Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

    Science.gov (United States)

    Tarnavsky, E.

    2016-12-01

    The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

  4. Nanocontainer-based corrosion sensing coating

    International Nuclear Information System (INIS)

    Maia, F; Tedim, J; Bastos, A C; Ferreira, M G S; Zheludkevich, M L

    2013-01-01

    The present paper reports on the development of new sensing active coating on the basis of nanocontainers containing pH-indicating agent. The coating is able to detect active corrosion processes on different metallic substrates. The corrosion detection functionality based on the local colour change in active cathodic zones results from the interaction of hydroxide ions with phenolphthalein encapsulated in mesoporous nanocontainers which function as sensing nanoreactors. The mesoporous silica nanocontainers are synthesized and loaded with pH indicator phenolphthalein in a one-stage process. The resulting system is mesoporous, which together with bulkiness of the indicator molecules limits their leaching. At the same time, penetration of water molecules and ions inside the container is still possible, allowing encapsulated phenolphthalein to be sensitive to the pH in the surrounding environment and outperforming systems when an indicator is directly dispersed in the coating layer. The performed tests demonstrate the pH sensitivity of the developed nanocontainers being dispersed in aqueous solutions. The corrosion sensing functionality of the protective coatings with nanocontainers are proven for aluminium- and magnesium-based metallic substrates. As a result, the developed nanocontainers show high potential to be used in a new generation of active protective coatings with corrosion-sensing coatings. (paper)

  5. Asymmetric cryptography based on wavefront sensing.

    Science.gov (United States)

    Peng, Xiang; Wei, Hengzheng; Zhang, Peng

    2006-12-15

    A system of asymmetric cryptography based on wavefront sensing (ACWS) is proposed for the first time to our knowledge. One of the most significant features of the asymmetric cryptography is that a trapdoor one-way function is required and constructed by analogy to wavefront sensing, in which the public key may be derived from optical parameters, such as the wavelength or the focal length, while the private key may be obtained from a kind of regular point array. The ciphertext is generated by the encoded wavefront and represented with an irregular array. In such an ACWS system, the encryption key is not identical to the decryption key, which is another important feature of an asymmetric cryptographic system. The processes of asymmetric encryption and decryption are formulized mathematically and demonstrated with a set of numerical experiments.

  6. Optical/Infrared Signatures for Space-Based Remote Sensing

    National Research Council Canada - National Science Library

    Picard, R. H; Dewan, E. M; Winick, J. R; O'Neil, R. R

    2007-01-01

    This report describes work carried out under the Air Force Research Laboratory's basic research task in optical remote-sensing signatures, entitled Optical / Infrared Signatures for Space-Based Remote Sensing...

  7. Sensing capabilities of graphite based MR elastomers

    International Nuclear Information System (INIS)

    Tian, T F; Li, W H; Deng, Y M

    2011-01-01

    This paper presents both experimental and theoretical investigations of the sensing capabilities of graphite based magnetorheological elastomers (MREs). In this study, eight MRE samples with varying graphite weight fractions were fabricated and their resistance under different magnetic fields and external loadings were measured with a multi-meter. With an increment of graphite weight fraction, the resistance of MRE sample decreases steadily. Higher magnetic fields result in a resistance increase. Based on an ideal assumption of a perfect chain structure, a mathematical model was developed to investigate the relationship between the MRE resistance with external loading. In this model, the current flowing through the chain structure consists of both a tunnel current and a conductivity current, both of which depend on external loadings. The modelling parameters have been identified and reconstructed from comparison with experimental results. The comparison indicates that both experimental results and modelling predictions agree favourably well

  8. Aptamer-Based Electrochemical Sensing of Lysozyme

    Directory of Open Access Journals (Sweden)

    Alina Vasilescu

    2016-06-01

    Full Text Available Protein analysis and quantification are required daily by thousands of laboratories worldwide for activities ranging from protein characterization to clinical diagnostics. Multiple factors have to be considered when selecting the best detection and quantification assay, including the amount of protein available, its concentration, the presence of interfering molecules, as well as costs and rapidity. This is also the case for lysozyme, a 14.3-kDa protein ubiquitously present in many organisms, that has been identified with a variety of functions: antibacterial activity, a biomarker of several serious medical conditions, a potential allergen in foods or a model of amyloid-type protein aggregation. Since the design of the first lysozyme aptamer in 2001, lysozyme became one of the most intensively-investigated biological target analytes for the design of novel biosensing concepts, particularly with regards to electrochemical aptasensors. In this review, we discuss the state of the art of aptamer-based electrochemical sensing of lysozyme, with emphasis on sensing in serum and real samples.

  9. Compressive sensing based ptychography image encryption

    Science.gov (United States)

    Rawat, Nitin

    2015-09-01

    A compressive sensing (CS) based ptychography combined with an optical image encryption is proposed. The diffraction pattern is recorded through ptychography technique further compressed by non-uniform sampling via CS framework. The system requires much less encrypted data and provides high security. The diffraction pattern as well as the lesser measurements of the encrypted samples serves as a secret key which make the intruder attacks more difficult. Furthermore, CS shows that the linearly projected few random samples have adequate information for decryption with a dramatic volume reduction. Experimental results validate the feasibility and effectiveness of our proposed technique compared with the existing techniques. The retrieved images do not reveal any information with the original information. In addition, the proposed system can be robust even with partial encryption and under brute-force attacks.

  10. Accelerated Compressed Sensing Based CT Image Reconstruction.

    Science.gov (United States)

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  11. Accelerated Compressed Sensing Based CT Image Reconstruction

    Directory of Open Access Journals (Sweden)

    SayedMasoud Hashemi

    2015-01-01

    Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  12. MEMS based impedimetric sensing of phthalates

    KAUST Repository

    Zia, Asif I.

    2013-05-01

    Phthalate esters are known ubiquitous teratogenic and carcinogenic environmental and food pollutants. Their detection and quantification is strictly laboratory based, time consuming, expensive and professionally handled procedure. Presented research work describes a real time non-invasive detection technique for phthalates detection in ethanol, water and drinks. The new type of inter-digital sensor design incorporating multiple sensing gold electrodes were fabricated on silicon substrate based on thin film micro-electromechanical system (MEMS) using semiconductor device fabrication technology. A passivation layer of Silicon Nitride (Si3N4) was used to functionalize the sensor. Various concentrations (0.1 to 20ppm) of DINP (di-isononyl phthalates) in ethanol and di (2-ethylhexyl) phthalate (DEHP) in deionized MilliQ water were subjected to the testing system by dip testing method. Electrochemical impedance spectroscopy (EIS) technique was used to obtain impedance spectra in order to determine sample conductance for evaluation of its dielectric properties. The impedance spectra so obtained showed that the sensor was able to detect the presence of phthalates in the samples distinctively. Electrochemical Spectrum Analyser was used to model the experimentally obtained impedance spectra by curve fitting technique to figure out Constant Phase Element (CPE) equivalent circuit. Locally available energy drink and juice was added with phthalates in concentrations of 2, 6 and 10ppm to observe the performance of the sensor in such products. Experimental results showed that the new sensor was able to detect different concentrations of phthalates in energy drinks. © 2013 IEEE.

  13. Compressed Sensing, Pseudodictionary-Based, Superresolution Reconstruction

    Directory of Open Access Journals (Sweden)

    Chun-mei Li

    2016-01-01

    Full Text Available The spatial resolution of digital images is the critical factor that affects photogrammetry precision. Single-frame, superresolution, image reconstruction is a typical underdetermined, inverse problem. To solve this type of problem, a compressive, sensing, pseudodictionary-based, superresolution reconstruction method is proposed in this study. The proposed method achieves pseudodictionary learning with an available low-resolution image and uses the K-SVD algorithm, which is based on the sparse characteristics of the digital image. Then, the sparse representation coefficient of the low-resolution image is obtained by solving the norm of l0 minimization problem, and the sparse coefficient and high-resolution pseudodictionary are used to reconstruct image tiles with high resolution. Finally, single-frame-image superresolution reconstruction is achieved. The proposed method is applied to photogrammetric images, and the experimental results indicate that the proposed method effectively increase image resolution, increase image information content, and achieve superresolution reconstruction. The reconstructed results are better than those obtained from traditional interpolation methods in aspect of visual effects and quantitative indicators.

  14. EIT-based fabric pressure sensing.

    Science.gov (United States)

    Yao, A; Yang, C L; Seo, J K; Soleimani, M

    2013-01-01

    This paper presents EIT-based fabric sensors that aim to provide a pressure mapping using the current carrying and voltage sensing electrodes attached to the boundary of the fabric patch. Pressure-induced shape change over the sensor area makes a change in the conductivity distribution which can be conveyed to the change of boundary current-voltage data. This boundary data is obtained through electrode measurements in EIT system. The corresponding inverse problem is to reconstruct the pressure and deformation map from the relationship between the applied current and the measured voltage on the fabric boundary. Taking advantage of EIT in providing dynamical images of conductivity changes due to pressure induced shape change, the pressure map can be estimated. In this paper, the EIT-based fabric sensor was presented for circular and rectangular sensor geometry. A stretch sensitive fabric was used in circular sensor with 16 electrodes and a pressure sensitive fabric was used in a rectangular sensor with 32 electrodes. A preliminary human test was carried out with the rectangular sensor for foot pressure mapping showing promising results.

  15. EIT-Based Fabric Pressure Sensing

    Directory of Open Access Journals (Sweden)

    A. Yao

    2013-01-01

    Full Text Available This paper presents EIT-based fabric sensors that aim to provide a pressure mapping using the current carrying and voltage sensing electrodes attached to the boundary of the fabric patch. Pressure-induced shape change over the sensor area makes a change in the conductivity distribution which can be conveyed to the change of boundary current-voltage data. This boundary data is obtained through electrode measurements in EIT system. The corresponding inverse problem is to reconstruct the pressure and deformation map from the relationship between the applied current and the measured voltage on the fabric boundary. Taking advantage of EIT in providing dynamical images of conductivity changes due to pressure induced shape change, the pressure map can be estimated. In this paper, the EIT-based fabric sensor was presented for circular and rectangular sensor geometry. A stretch sensitive fabric was used in circular sensor with 16 electrodes and a pressure sensitive fabric was used in a rectangular sensor with 32 electrodes. A preliminary human test was carried out with the rectangular sensor for foot pressure mapping showing promising results.

  16. Compressive sensing based algorithms for electronic defence

    CERN Document Server

    Mishra, Amit Kumar

    2017-01-01

    This book details some of the major developments in the implementation of compressive sensing in radio applications for electronic defense and warfare communication use. It provides a comprehensive background to the subject and at the same time describes some novel algorithms. It also investigates application value and performance-related parameters of compressive sensing in scenarios such as direction finding, spectrum monitoring, detection, and classification.

  17. Torsion sensing based on patterned piezoelectric beams

    Science.gov (United States)

    Cha, Youngsu; You, Hangil

    2018-03-01

    In this study, we investigated the sensing characteristics of piezoelectric beams under torsional loads. We used partially patterned piezoelectric beams to sense torsion. In particular, the piezoelectric patches are located symmetrically with respect to the line of the shear center of the beam. The patterned piezoelectric beam is modeled as a slender beam, and its electrical responses are obtained by piezoelectric electromechanical equations. To validate the modeling framework, experiments are performed using a setup that forces pure torsional deformation. Three different geometric configurations of the patterned piezoelectric layer are used for the experiments. The frequency and amplitude of the forced torsional load are systematically varied in order to study the behavior of the piezoelectric sensor. Experimental results demonstrate that two voltage outputs of the piezoelectric beam are approximately out of phase with identical amplitude. Moreover, the length of the piezoelectric layers has a significant influence on the sensing properties. Our theoretical predictions using the model support the experimental findings.

  18. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  19. Resistive and Capacitive Based Sensing Technologies

    Directory of Open Access Journals (Sweden)

    Winncy Y. Du

    2008-04-01

    Full Text Available Resistive and capacitive (RC sensors are the most commonly used sensors. Their applications span homeland security, industry, environment, space, traffic control, home automation, aviation, and medicine. More than 30% of modern sensors are direct or indirect applications of the RC sensing principles. This paper reviews resistive and capacitive sensing technologies. The physical principles of resistive sensors are governed by several important laws and phenomena such as Ohm’s Law, Wiedemann-Franz Law; Photoconductive-, Piezoresistive-, and Thermoresistive Effects. The applications of these principles are presented through a variety of examples including accelerometers, flame detectors, pressure/flow rate sensors, RTDs, hygristors, chemiresistors, and bio-impedance sensors. The capacitive sensors are described through their three configurations: parallel (flat, cylindrical (coaxial, and spherical (concentric. Each configuration is discussed with respect to its geometric structure, function, and application in various sensor designs. Capacitance sensor arrays are also presented in the paper.

  20. A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing

    OpenAIRE

    Fengling Zhang; Tianyi Cai; Liang Ma; Liyuan Zhan; Hong Liu

    2017-01-01

    We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensin...

  1. Compressed Sensing-Based Direct Conversion Receiver

    DEFF Research Database (Denmark)

    Pierzchlewski, Jacek; Arildsen, Thomas; Larsen, Torben

    2012-01-01

    Due to the continuously increasing computational power of modern data receivers it is possible to move more and more processing from the analog to the digital domain. This paper presents a compressed sensing approach to relaxing the analog filtering requirements prior to the ADCs in a direct......-converted radio signals. As shown in an experiment presented in the article, when the proposed method is used, it is possible to relax the requirements for the quadrature down-converter filters. A random sampling device and an additional digital signal processing module is the price to pay for these relaxed...

  2. Use of Traditional Weather/Climate Knowledge by Farmers in the South-Western Free State of South Africa: Agrometeorological Learning by Scientists

    Directory of Open Access Journals (Sweden)

    Gugulethu Zuma-Netshiukhwi

    2013-11-01

    Full Text Available The variety of natural indicators, associated with weather forecasting and climate prediction, as used by farmers in the South-Western Free State province of South Africa, is described. Most farmers in this area were not familiar with the application of weather forecasts/climate predictions for agricultural production, or with other science-based agrometeorological products. They relied almost fully on their experience and traditional knowledge for farming decision making. The indicators for traditional knowledge are demonstrated here in broad terms, relying on the stories and indications from observations and years of experience of their use by the farmers. These means of engagement with the natural environment, are skills not well understood by most scientists, but useful to the farmers. They range from the constellation of stars, animal behavior, cloud cover and type, blossoming of certain indigenous trees, appearance and disappearance of reptiles, to migration of bird species and many others. It is suggested that some short-term traditional forecasts/predictions may be successfully merged with science-based climate predictions. The traditional knowledge and its use, reported on in this paper, is what scientists learned from farmers. Berkes was right that scholars have wasted too much time and effort on a science versus traditional knowledge debate; we should reframe it instead as a science and traditional knowledge dialogue and partnership. The complications of a changing climate make this even more necessary.

  3. Microfiber-Based Bragg Gratings for Sensing Applications: A Review

    Directory of Open Access Journals (Sweden)

    Jun-Long Kou

    2012-06-01

    Full Text Available Microfiber-based Bragg gratings (MFBGs are an emerging concept in ultra-small optical fiber sensors. They have attracted great attention among researchers in the fiber sensing area because of their large evanescent field and compactness. In this review, the basic techniques for the fabrication of MFBGs are introduced first. Then, the sensing properties and applications of MFBGs are discussed, including measurement of refractive index (RI, temperature, and strain/force. Finally a summary of selected MFBG sensing elements from previous literature are tabulated.

  4. Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Caiyun Huang

    2014-07-01

    Full Text Available As a newly proposed theory, compressive sensing (CS is commonly used in signal processing area. This paper investigates the applications of compressed sensing (CS in wireless sensor networks (WSNs. First, the development and research status of compressed sensing technology and wireless sensor networks are described, then a detailed investigation of WSNs research based on CS are conducted from aspects of data fusion, signal acquisition, signal routing transmission, and signal reconstruction. At the end of the paper, we conclude our survey and point out the possible future research directions.

  5. The morphometric parameters of seeds of genus Echinacea Moench representatives and their association with agrometeorological factors

    Directory of Open Access Journals (Sweden)

    С. В. Поспєлов

    2015-12-01

    Full Text Available Purpose. To study morphometric parameters of fruits (cypselae of purple coneflower (Echinacea purpurea (L. Moench of ‘Zirka Mykoly Vavylova’ cultivar and pale coneflower (Echinacea pallida (Nutt. Nutt of ‘Krasunia Prerii’ cultivar and determine the impact of agro-meteorological factors on their performance according to long-term data. Methods. Laboratory, Mathematics and Statistics. Results. It was found that the parameters of cypselae and its weight in various types of coneflowers varied considerably from year to year. In this context the indicators of cypselae width and thickness had a larger variability as compared with the length. Mean length of Echinacea purpurea ranged from 4,57 to 6,16 mm, width – 2,30–2,97 mm, thickness – 1,74–2,28 mm. Weight of a cypselae made up 4,40–6,50 mg. Length of a fruit of Echinacea pallida was 4,57–5,74 mm, width – 2,51–3,18 mm, thickness – 1,76–2,37 mm, and a fruit weight varied from 5,65 to 7,70 mg. The correlation analysis revealed reliable connection of agro-climatic parameters and the parameters of the fruit. Conclusions. Using long-term data, the morphology of cypselaes of two Echinacea species introduced to Ukraine were studied, their basic parameters and the variability of indicators, connection with agro-climatic factors that is necessary to consider in crop growing for seeds .

  6. Fabrication of Porous Silicon Based Humidity Sensing Elements on Paper

    Directory of Open Access Journals (Sweden)

    Tero Jalkanen

    2015-01-01

    Full Text Available A roll-to-roll compatible fabrication process of porous silicon (pSi based sensing elements for a real-time humidity monitoring is described. The sensing elements, consisting of printed interdigitated silver electrodes and a spray-coated pSi layer, were fabricated on a coated paper substrate by a two-step process. Capacitive and resistive responses of the sensing elements were examined under different concentrations of humidity. More than a three orders of magnitude reproducible decrease in resistance was measured when the relative humidity (RH was increased from 0% to 90%. A relatively fast recovery without the need of any refreshing methods was observed with a change in RH. Humidity background signal and hysteresis arising from the paper substrate were dependent on the thickness of sensing pSi layer. Hysteresis in most optimal sensing element setup (a thick pSi layer was still noticeable but not detrimental for the sensing. In addition to electrical characterization of sensing elements, thermal degradation and moisture adsorption properties of the paper substrate were examined in connection to the fabrication process of the silver electrodes and the moisture sensitivity of the paper. The results pave the way towards the development of low-cost humidity sensors which could be utilized, for example, in smart packaging applications or in smart cities to monitor the environment.

  7. Bridge SHM system based on fiber optical sensing technology

    Science.gov (United States)

    Li, Sheng; Fan, Dian; Fu, Jiang-hua; Huang, Xing; Jiang, De-sheng

    2015-09-01

    The latest progress of our lab in recent 10 years on the area of bridge structural health monitoring (SHM) based on optical fiber sensing technology is introduced. Firstly, in the part of sensing technology, optical fiber force test-ring, optical fiber vibration sensor, optical fiber smart cable, optical fiber prestressing loss monitoring method and optical fiber continuous curve mode inspection system are developed, which not only rich the sensor types, but also provides new monitoring means that are needed for the bridge health monitoring system. Secondly, in the optical fiber sensing network and computer system platform, the monitoring system architecture model is designed to effectively meet the integration scale and effect requirement of engineering application, especially the bridge expert system proposed integration of sensing information and informatization manual inspection to realize the mode of multi index intelligence and practical monitoring, diagnosis and evaluation. Finally, the Jingyue bridge monitoring system as the representative, the research on the technology of engineering applications are given.

  8. Remote Sensing Image Classification Based on Stacked Denoising Autoencoder

    Directory of Open Access Journals (Sweden)

    Peng Liang

    2017-12-01

    Full Text Available Focused on the issue that conventional remote sensing image classification methods have run into the bottlenecks in accuracy, a new remote sensing image classification method inspired by deep learning is proposed, which is based on Stacked Denoising Autoencoder. First, the deep network model is built through the stacked layers of Denoising Autoencoder. Then, with noised input, the unsupervised Greedy layer-wise training algorithm is used to train each layer in turn for more robust expressing, characteristics are obtained in supervised learning by Back Propagation (BP neural network, and the whole network is optimized by error back propagation. Finally, Gaofen-1 satellite (GF-1 remote sensing data are used for evaluation, and the total accuracy and kappa accuracy reach 95.7% and 0.955, respectively, which are higher than that of the Support Vector Machine and Back Propagation neural network. The experiment results show that the proposed method can effectively improve the accuracy of remote sensing image classification.

  9. A motion sensing-based framework for robotic manipulation.

    Science.gov (United States)

    Deng, Hao; Xia, Zeyang; Weng, Shaokui; Gan, Yangzhou; Fang, Peng; Xiong, Jing

    2016-01-01

    To data, outside of the controlled environments, robots normally perform manipulation tasks operating with human. This pattern requires the robot operators with high technical skills training for varied teach-pendant operating system. Motion sensing technology, which enables human-machine interaction in a novel and natural interface using gestures, has crucially inspired us to adopt this user-friendly and straightforward operation mode on robotic manipulation. Thus, in this paper, we presented a motion sensing-based framework for robotic manipulation, which recognizes gesture commands captured from motion sensing input device and drives the action of robots. For compatibility, a general hardware interface layer was also developed in the framework. Simulation and physical experiments have been conducted for preliminary validation. The results have shown that the proposed framework is an effective approach for general robotic manipulation with motion sensing control.

  10. Challenges in paper-based fluorogenic optical sensing with smartphones

    Science.gov (United States)

    Ulep, Tiffany-Heather; Yoon, Jeong-Yeol

    2018-05-01

    Application of optically superior, tunable fluorescent nanotechnologies have long been demonstrated throughout many chemical and biological sensing applications. Combined with microfluidics technologies, i.e. on lab-on-a-chip platforms, such fluorescent nanotechnologies have often enabled extreme sensitivity, sometimes down to single molecule level. Within recent years there has been a peak interest in translating fluorescent nanotechnology onto paper-based platforms for chemical and biological sensing, as a simple, low-cost, disposable alternative to conventional silicone-based microfluidic substrates. On the other hand, smartphone integration as an optical detection system as well as user interface and data processing component has been widely attempted, serving as a gateway to on-board quantitative processing, enhanced mobility, and interconnectivity with informational networks. Smartphone sensing can be integrated to these paper-based fluorogenic assays towards demonstrating extreme sensitivity as well as ease-of-use and low-cost. However, with these emerging technologies there are always technical limitations that must be addressed; for example, paper's autofluorescence that perturbs fluorogenic sensing; smartphone flash's limitations in fluorescent excitation; smartphone camera's limitations in detecting narrow-band fluorescent emission, etc. In this review, physical optical setups, digital enhancement algorithms, and various fluorescent measurement techniques are discussed and pinpointed as areas of opportunities to further improve paper-based fluorogenic optical sensing with smartphones.

  11. MEMS based impedimetric sensing of phthalates

    KAUST Repository

    Zia, Asif I.; Mohd. Syaifudin, A. R.; Mukhopadhyay, Subhas Chandra; Al-Bahadly, Ibrahim H.; Yu, Paklam; Gooneratne, Chinthaka Pasan; Kosel, Jü rgen; Liao, Taishan

    2013-01-01

    Phthalate esters are known ubiquitous teratogenic and carcinogenic environmental and food pollutants. Their detection and quantification is strictly laboratory based, time consuming, expensive and professionally handled procedure. Presented research

  12. Model-based Prognostics under Limited Sensing

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics is crucial to providing reliable condition-based maintenance decisions. To obtain accurate predictions of component life, a variety of sensors are often...

  13. Intelligent Chiral Sensing Based on Supramolecular and Interfacial Concepts

    Directory of Open Access Journals (Sweden)

    Hironori Izawa

    2010-07-01

    Full Text Available Of the known intelligently-operating systems, the majority can undoubtedly be classed as being of biological origin. One of the notable differences between biological and artificial systems is the important fact that biological materials consist mostly of chiral molecules. While most biochemical processes routinely discriminate chiral molecules, differentiation between chiral molecules in artificial systems is currently one of the challenging subjects in the field of molecular recognition. Therefore, one of the important challenges for intelligent man-made sensors is to prepare a sensing system that can discriminate chiral molecules. Because intermolecular interactions and detection at surfaces are respectively parts of supramolecular chemistry and interfacial science, chiral sensing based on supramolecular and interfacial concepts is a significant topic. In this review, we briefly summarize recent advances in these fields, including supramolecular hosts for color detection on chiral sensing, indicator-displacement assays, kinetic resolution in supramolecular reactions with analyses by mass spectrometry, use of chiral shape-defined polymers, such as dynamic helical polymers, molecular imprinting, thin films on surfaces of devices such as QCM, functional electrodes, FET, and SPR, the combined technique of magnetic resonance imaging and immunoassay, and chiral detection using scanning tunneling microscopy and cantilever technology. In addition, we will discuss novel concepts in recent research including the use of achiral reagents for chiral sensing with NMR, and mechanical control of chiral sensing. The importance of integration of chiral sensing systems with rapidly developing nanotechnology and nanomaterials is also emphasized.

  14. User Classification in Crowdsourcing-Based Cooperative Spectrum Sensing

    Directory of Open Access Journals (Sweden)

    Linbo Zhai

    2017-07-01

    Full Text Available This paper studies cooperative spectrum sensing based on crowdsourcing in cognitive radio networks. Since intelligent mobile users such as smartphones and tablets can sense the wireless spectrum, channel sensing tasks can be assigned to these mobile users. This is referred to as the crowdsourcing method. However, there may be some malicious mobile users that send false sensing reports deliberately, for their own purposes. False sensing reports will influence decisions about channel state. Therefore, it is necessary to classify mobile users in order to distinguish malicious users. According to the sensing reports, mobile users should not just be divided into two classes (honest and malicious. There are two reasons for this: on the one hand, honest users in different positions may have different sensing outcomes, as shadowing, multi-path fading, and other issues may influence the sensing results; on the other hand, there may be more than one type of malicious users, acting differently in the network. Therefore, it is necessary to classify mobile users into more than two classes. Due to the lack of prior information of the number of user classes, this paper casts the problem of mobile user classification as a dynamic clustering problem that is NP-hard. The paper uses the interdistance-to-intradistance ratio of clusters as the fitness function, and aims to maximize the fitness function. To cast this optimization problem, this paper proposes a distributed algorithm for user classification in order to obtain bounded close-to-optimal solutions, and analyzes the approximation ratio of the proposed algorithm. Simulations show the distributed algorithm achieves higher performance than other algorithms.

  15. Tamper indicating and sensing optical-based smart structures

    International Nuclear Information System (INIS)

    Sliva, P.; Anheier, N.C.; Gordon, N.R.; Simmons, K.L.; Stahl, K.A.; Undem, H.A.

    1995-05-01

    This paper has presented an overview of the type of optical-based structures that can be designed and constructed. These smart structures are capable of responding to their environment. The examples given represent a modest sampling of the complexity that can be achieved in both design and practice. Tamper-indicating containers and smart, sensing windows demonstrate just a few of the applications. We have shown that optical-based smart structures can be made multifunctional with the sensing built in. The next generation smart structure will combine the sensing functionality of these optical-based smart structures with other sensors such as piezoelectrics and electro-rheological fluids to not only be able to respond to the environment, but to adapt to it as well. An example of functionality in this regime would be a piezosensor that senses pressure changes (e.g., shock waves), which then causes an electro-rheological fluid to change viscosity. A fiber sensor located in or near the electro-rheological fluid senses the stiffness change and sends a signal through a feedback loop back to the piezosensor for additional adjustments to the electro-rheological fluid

  16. Sapphire-fiber-based distributed high-temperature sensing system.

    Science.gov (United States)

    Liu, Bo; Yu, Zhihao; Hill, Cary; Cheng, Yujie; Homa, Daniel; Pickrell, Gary; Wang, Anbo

    2016-09-15

    We present, for the first time to our knowledge, a sapphire-fiber-based distributed high-temperature sensing system based on a Raman distributed sensing technique. High peak power laser pulses at 532 nm were coupled into the sapphire fiber to generate the Raman signal. The returned Raman Stokes and anti-Stokes signals were measured in the time domain to determine the temperature distribution along the fiber. The sensor was demonstrated from room temperature up to 1200°C in which the average standard deviation is about 3.7°C and a spatial resolution of about 14 cm was achieved.

  17. Optical touch screen based on waveguide sensing

    DEFF Research Database (Denmark)

    Pedersen, Henrik Chresten; Jakobsen, Michael Linde; Hanson, Steen Grüner

    2011-01-01

    We disclose a simple, optical touch screen technique based on a planar injection molded polymer waveguide, a single laser, and a small linear detector array. The solution significantly reduces the complexity and cost as compared to existing optical touch technologies. Force detection of a touching...

  18. A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing

    Directory of Open Access Journals (Sweden)

    Fengling Zhang

    2017-01-01

    Full Text Available We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensing. Both the preloaded analyte and the analyte in the sample initiate the color change of Prussian Blue to Prussian White. With a reaction time of 60 s, the number of electrochemical cells with complete color changes is correlated to the concentration of analyte in the sample. As a proof-of-concept analyte, lactic acid was detected semi-quantitatively using the naked eye.

  19. A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing.

    Science.gov (United States)

    Zhang, Fengling; Cai, Tianyi; Ma, Liang; Zhan, Liyuan; Liu, Hong

    2017-01-31

    We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensing. Both the preloaded analyte and the analyte in the sample initiate the color change of Prussian Blue to Prussian White. With a reaction time of 60 s, the number of electrochemical cells with complete color changes is correlated to the concentration of analyte in the sample. As a proof-of-concept analyte, lactic acid was detected semi-quantitatively using the naked eye.

  20. QR-decomposition based SENSE reconstruction using parallel architecture.

    Science.gov (United States)

    Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

    2018-04-01

    Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. A Situated Cultural Festival Learning System Based on Motion Sensing

    Science.gov (United States)

    Chang, Yi-Hsing; Lin, Yu-Kai; Fang, Rong-Jyue; Lu, You-Te

    2017-01-01

    A situated Chinese cultural festival learning system based on motion sensing is developed in this study. The primary design principle is to create a highly interactive learning environment, allowing learners to interact with Kinect through natural gestures in the designed learning situation to achieve efficient learning. The system has the…

  2. Remote sensing image segmentation based on Hadoop cloud platform

    Science.gov (United States)

    Li, Jie; Zhu, Lingling; Cao, Fubin

    2018-01-01

    To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

  3. Identification of Coupled Map Lattice Based on Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Dong Xie

    2016-01-01

    Full Text Available A novel approach for the parameter identification of coupled map lattice (CML based on compressed sensing is presented in this paper. We establish a meaningful connection between these two seemingly unrelated study topics and identify the weighted parameters using the relevant recovery algorithms in compressed sensing. Specifically, we first transform the parameter identification problem of CML into the sparse recovery problem of underdetermined linear system. In fact, compressed sensing provides a feasible method to solve underdetermined linear system if the sensing matrix satisfies some suitable conditions, such as restricted isometry property (RIP and mutual coherence. Then we give a low bound on the mutual coherence of the coefficient matrix generated by the observed values of CML and also prove that it satisfies the RIP from a theoretical point of view. If the weighted vector of each element is sparse in the CML system, our proposed approach can recover all the weighted parameters using only about M samplings, which is far less than the number of the lattice elements N. Another important and significant advantage is that if the observed data are contaminated with some types of noises, our approach is still effective. In the simulations, we mainly show the effects of coupling parameter and noise on the recovery rate.

  4. Development of Polymethylmethacrylate Based Composite for Gas Sensing Application

    OpenAIRE

    Devikala, S.; Kamaraj, P.

    2011-01-01

    Gas detection instruments are increasingly needed for industrial health and safety, environmental monitoring and process control. Conductive polymer composites have various industrial applications. The composite prepared by mixing carbon black with polymethylmethacrylate (PMMA) has very good gas sensing applications. The gas sensors based on carbon nanotube/polymer, ceramic and metal oxide composites such as epoxy, polyimide, PMMA / Barium titanate and tin oxide have also been developed. In t...

  5. Knowledge-based biomedical word sense disambiguation: comparison of approaches

    Directory of Open Access Journals (Sweden)

    Aronson Alan R

    2010-11-01

    Full Text Available Abstract Background Word sense disambiguation (WSD algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature. Statistical learning approaches have produced good results, but the size of the UMLS makes the production of training data infeasible to cover all the domain. Methods We present research on existing WSD approaches based on knowledge bases, which complement the studies performed on statistical learning. We compare four approaches which rely on the UMLS Metathesaurus as the source of knowledge. The first approach compares the overlap of the context of the ambiguous word to the candidate senses based on a representation built out of the definitions, synonyms and related terms. The second approach collects training data for each of the candidate senses to perform WSD based on queries built using monosemous synonyms and related terms. These queries are used to retrieve MEDLINE citations. Then, a machine learning approach is trained on this corpus. The third approach is a graph-based method which exploits the structure of the Metathesaurus network of relations to perform unsupervised WSD. This approach ranks nodes in the graph according to their relative structural importance. The last approach uses the semantic types assigned to the concepts in the Metathesaurus to perform WSD. The context of the ambiguous word and semantic types of the candidate concepts are mapped to Journal Descriptors. These mappings are compared to decide among the candidate concepts. Results are provided estimating accuracy of the different methods on the WSD test collection available from the NLM. Conclusions We have found that the last approach achieves better results compared to the other methods. The graph-based approach, using the structure of the Metathesaurus network to estimate the relevance of the Metathesaurus concepts, does not perform well

  6. Learning-based compressed sensing for infrared image super resolution

    Science.gov (United States)

    Zhao, Yao; Sui, Xiubao; Chen, Qian; Wu, Shaochi

    2016-05-01

    This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.

  7. On-Chip Neural Data Compression Based On Compressed Sensing With Sparse Sensing Matrices.

    Science.gov (United States)

    Zhao, Wenfeng; Sun, Biao; Wu, Tong; Yang, Zhi

    2018-02-01

    On-chip neural data compression is an enabling technique for wireless neural interfaces that suffer from insufficient bandwidth and power budgets to transmit the raw data. The data compression algorithm and its implementation should be power and area efficient and functionally reliable over different datasets. Compressed sensing is an emerging technique that has been applied to compress various neurophysiological data. However, the state-of-the-art compressed sensing (CS) encoders leverage random but dense binary measurement matrices, which incur substantial implementation costs on both power and area that could offset the benefits from the reduced wireless data rate. In this paper, we propose two CS encoder designs based on sparse measurement matrices that could lead to efficient hardware implementation. Specifically, two different approaches for the construction of sparse measurement matrices, i.e., the deterministic quasi-cyclic array code (QCAC) matrix and -sparse random binary matrix [-SRBM] are exploited. We demonstrate that the proposed CS encoders lead to comparable recovery performance. And efficient VLSI architecture designs are proposed for QCAC-CS and -SRBM encoders with reduced area and total power consumption.

  8. Adaptive Sensing Based on Profiles for Sensor Systems

    Directory of Open Access Journals (Sweden)

    Yoshiteru Ishida

    2009-10-01

    Full Text Available This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

  9. An ecological assessment of pasturelands in the Balkhash area of Kazakhstan with remote sensing and models

    International Nuclear Information System (INIS)

    Lebed, L; Qi, J; Heilman, P

    2012-01-01

    The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation’s economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation. (letter)

  10. Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot

    Directory of Open Access Journals (Sweden)

    Yajing Shen

    2015-12-01

    Full Text Available Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.

  11. Smartphone Based Platform for Colorimetric Sensing of Dyes

    Science.gov (United States)

    Dutta, Sibasish; Nath, Pabitra

    We demonstrate the working of a smartphone based optical sensor for measuring absorption band of coloured dyes. By integration of simple laboratory optical components with the camera unit of the smartphone we have converted it into a visible spectrometer with a pixel resolution of 0.345 nm/pixel. Light from a broadband optical source is allowed to transmit through a specific dye solution. The transmitted light signal is captured by the camera of the smartphone. The present sensor is inexpensive, portable and light weight making it an ideal handy sensor suitable for different on-field sensing.

  12. Optical Fiber Sensing Based on Reflection Laser Spectroscopy

    Directory of Open Access Journals (Sweden)

    Gianluca Gagliardi

    2010-03-01

    Full Text Available An overview on high-resolution and fast interrogation of optical-fiber sensors relying on laser reflection spectroscopy is given. Fiber Bragg-gratings (FBGs and FBG resonators built in fibers of different types are used for strain, temperature and acceleration measurements using heterodyne-detection and optical frequency-locking techniques. Silica fiber-ring cavities are used for chemical sensing based on evanescent-wave spectroscopy. Various arrangements for signal recovery and noise reduction, as an extension of most typical spectroscopic techniques, are illustrated and results on detection performances are presented.

  13. Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing

    Directory of Open Access Journals (Sweden)

    Jiayin Liu

    2017-06-01

    Full Text Available Remote sensing technologies have been widely applied in urban environments’ monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the “salt and pepper” phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC, which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF, which is estimated by Kernel Density Estimation (KDE with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

  14. Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing.

    Science.gov (United States)

    Liu, Jiayin; Tang, Zhenmin; Cui, Ying; Wu, Guoxing

    2017-06-12

    Remote sensing technologies have been widely applied in urban environments' monitoring, synthesis and modeling. Incorporating spatial information in perceptually coherent regions, superpixel-based approaches can effectively eliminate the "salt and pepper" phenomenon which is common in pixel-wise approaches. Compared with fixed-size windows, superpixels have adaptive sizes and shapes for different spatial structures. Moreover, superpixel-based algorithms can significantly improve computational efficiency owing to the greatly reduced number of image primitives. Hence, the superpixel algorithm, as a preprocessing technique, is more and more popularly used in remote sensing and many other fields. In this paper, we propose a superpixel segmentation algorithm called Superpixel Segmentation with Local Competition (SSLC), which utilizes a local competition mechanism to construct energy terms and label pixels. The local competition mechanism leads to energy terms locality and relativity, and thus, the proposed algorithm is less sensitive to the diversity of image content and scene layout. Consequently, SSLC could achieve consistent performance in different image regions. In addition, the Probability Density Function (PDF), which is estimated by Kernel Density Estimation (KDE) with the Gaussian kernel, is introduced to describe the color distribution of superpixels as a more sophisticated and accurate measure. To reduce computational complexity, a boundary optimization framework is introduced to only handle boundary pixels instead of the whole image. We conduct experiments to benchmark the proposed algorithm with the other state-of-the-art ones on the Berkeley Segmentation Dataset (BSD) and remote sensing images. Results demonstrate that the SSLC algorithm yields the best overall performance, while the computation time-efficiency is still competitive.

  15. Harmonic analysis in integrated energy system based on compressed sensing

    International Nuclear Information System (INIS)

    Yang, Ting; Pen, Haibo; Wang, Dan; Wang, Zhaoxia

    2016-01-01

    Highlights: • We propose a harmonic/inter-harmonic analysis scheme with compressed sensing theory. • Property of sparseness of harmonic signal in electrical power system is proved. • The ratio formula of fundamental and harmonic components sparsity is presented. • Spectral Projected Gradient-Fundamental Filter reconstruction algorithm is proposed. • SPG-FF enhances the precision of harmonic detection and signal reconstruction. - Abstract: The advent of Integrated Energy Systems enabled various distributed energy to access the system through different power electronic devices. The development of this has made the harmonic environment more complex. It needs low complexity and high precision of harmonic detection and analysis methods to improve power quality. To solve the shortages of large data storage capacities and high complexity of compression in sampling under the Nyquist sampling framework, this research paper presents a harmonic analysis scheme based on compressed sensing theory. The proposed scheme enables the performance of the functions of compressive sampling, signal reconstruction and harmonic detection simultaneously. In the proposed scheme, the sparsity of the harmonic signals in the base of the Discrete Fourier Transform (DFT) is numerically calculated first. This is followed by providing a proof of the matching satisfaction of the necessary conditions for compressed sensing. The binary sparse measurement is then leveraged to reduce the storage space in the sampling unit in the proposed scheme. In the recovery process, the scheme proposed a novel reconstruction algorithm called the Spectral Projected Gradient with Fundamental Filter (SPG-FF) algorithm to enhance the reconstruction precision. One of the actual microgrid systems is used as simulation example. The results of the experiment shows that the proposed scheme effectively enhances the precision of harmonic and inter-harmonic detection with low computing complexity, and has good

  16. Compact silicon photonics-based multi laser module for sensing

    Science.gov (United States)

    Ayotte, S.; Costin, F.; Babin, A.; Paré-Olivier, G.; Morin, M.; Filion, B.; Bédard, K.; Chrétien, P.; Bilodeau, G.; Girard-Deschênes, E.; Perron, L.-P.; Davidson, C.-A.; D'Amato, D.; Laplante, M.; Blanchet-Létourneau, J.

    2018-02-01

    A compact three-laser source for optical sensing is presented. It is based on a low-noise implementation of the Pound Drever-Hall method and comprises high-bandwidth optical phase-locked loops. The outputs from three semiconductor distributed feedback lasers, mounted on thermo-electric coolers (TEC), are coupled with micro-lenses into a silicon photonics (SiP) chip that performs beat note detection and several other functions. The chip comprises phase modulators, variable optical attenuators, multi-mode-interference couplers, variable ratio tap couplers, integrated photodiodes and optical fiber butt-couplers. Electrical connections between a metallized ceramic and the TECs, lasers and SiP chip are achieved by wirebonds. All these components stand within a 35 mm by 35 mm package which is interfaced with 90 electrical pins and two fiber pigtails. One pigtail carries the signals from a master and slave lasers, while another carries that from a second slave laser. The pins are soldered to a printed circuit board featuring a micro-processor that controls and monitors the system to ensure stable operation over fluctuating environmental conditions. This highly adaptable multi-laser source can address various sensing applications requiring the tracking of up to three narrow spectral features with a high bandwidth. It is used to sense a fiber-based ring resonator emulating a resonant fiber optics gyroscope. The master laser is locked to the resonator with a loop bandwidth greater than 1 MHz. The slave lasers are offset frequency locked to the master laser with loop bandwidths greater than 100 MHz. This high performance source is compact, automated, robust, and remains locked for days.

  17. Regional Analysis of Remote Sensing Based Evapotranspiration Information

    Science.gov (United States)

    Geli, H. M. E.; Hain, C.; Anderson, M. C.; Senay, G. B.

    2017-12-01

    Recent research findings on modeling actual evapotranspiration (ET) using remote sensing data and methods have proven the ability of these methods to address wide range of hydrological and water resources issues including river basin water balance for improved water resources management, drought monitoring, drought impact and socioeconomic responses, agricultural water management, optimization of land-use for water conservations, water allocation agreement among others. However, there is still a critical need to identify appropriate type of ET information that can address each of these issues. The current trend of increasing demand for water due to population growth coupled with variable and limited water supply due to drought especially in arid and semiarid regions with limited water supply have highlighted the need for such information. To properly address these issues different spatial and temporal resolutions of ET information will need to be used. For example, agricultural water management applications require ET information at field (30-m) and daily time scales while for river basin hydrologic analysis relatively coarser spatial and temporal scales can be adequate for such regional applications. The objective of this analysis is to evaluate the potential of using an integrated ET information that can be used to address some of these issues collectively. This analysis will highlight efforts to address some of the issues that are applicable to New Mexico including assessment of statewide water budget as well as drought impact and socioeconomic responses which all require ET information but at different spatial and temporal scales. This analysis will provide an evaluation of four remote sensing based ET models including ALEXI, DisALEXI, SSEBop, and SEBAL3.0. The models will be compared with ground-based observations from eddy covariance towers and water balance calculations. Remote sensing data from Landsat, MODIS, and VIIRS sensors will be used to provide ET

  18. Organic electrochemical transistors for cell-based impedance sensing

    International Nuclear Information System (INIS)

    Rivnay, Jonathan; Ramuz, Marc; Hama, Adel; Huerta, Miriam; Owens, Roisin M.; Leleux, Pierre

    2015-01-01

    Electrical impedance sensing of biological systems, especially cultured epithelial cell layers, is now a common technique to monitor cell motion, morphology, and cell layer/tissue integrity for high throughput toxicology screening. Existing methods to measure electrical impedance most often rely on a two electrode configuration, where low frequency signals are challenging to obtain for small devices and for tissues with high resistance, due to low current. Organic electrochemical transistors (OECTs) are conducting polymer-based devices, which have been shown to efficiently transduce and amplify low-level ionic fluxes in biological systems into electronic output signals. In this work, we combine OECT-based drain current measurements with simultaneous measurement of more traditional impedance sensing using the gate current to produce complex impedance traces, which show low error at both low and high frequencies. We apply this technique in vitro to a model epithelial tissue layer and show that the data can be fit to an equivalent circuit model yielding trans-epithelial resistance and cell layer capacitance values in agreement with literature. Importantly, the combined measurement allows for low biases across the cell layer, while still maintaining good broadband signal

  19. Towards highly sensitive strain sensing based on nanostructured materials

    International Nuclear Information System (INIS)

    Dao, Dzung Viet; Nakamura, Koichi; Sugiyama, Susumu; Bui, Tung Thanh; Dau, Van Thanh; Yamada, Takeo; Hata, Kenji

    2010-01-01

    This paper presents our recent theoretical and experimental study of piezo-effects in nanostructured materials for highly sensitive, high resolution mechanical sensors. The piezo-effects presented here include the piezoresistive effect in a silicon nanowire (SiNW) and single wall carbon nanotube (SWCNT) thin film, as well as the piezo-optic effect in a Si photonic crystal (PhC) nanocavity. Firstly, the electronic energy band structure of the silicon nanostructure is discussed and simulated by using the First-Principles Calculations method. The result showed a remarkably different energy band structure compared with that of bulk silicon. This difference in the electronic state will result in different physical, chemical, and therefore, sensing properties of silicon nanostructures. The piezoresistive effects of SiNW and SWCNT thin film were investigated experimentally. We found that, when the width of ( 110 ) p-type SiNW decreases from 500 to 35 nm, the piezoresistive effect increases by more than 60%. The longitudinal piezoresistive coefficient of SWCNT thin film was measured to be twice that of bulk p-type silicon. Finally, theoretical investigations of the piezo-optic effect in a PhC nanocavity based on Finite Difference Time Domain (FDTD) showed extremely high resolution strain sensing. These nanostructures were fabricated based on top-down nanofabrication technology. The achievements of this work are significant for highly sensitive, high resolution and miniaturized mechanical sensors

  20. The study of active tectonic based on hyperspectral remote sensing

    Science.gov (United States)

    Cui, J.; Zhang, S.; Zhang, J.; Shen, X.; Ding, R.; Xu, S.

    2017-12-01

    As of the latest technical methods, hyperspectral remote sensing technology has been widely used in each brach of the geosciences. However, it is still a blank for using the hyperspectral remote sensing to study the active structrure. Hyperspectral remote sensing, with high spectral resolution, continuous spectrum, continuous spatial data, low cost, etc, has great potentialities in the areas of stratum division and fault identification. Blind fault identification in plains and invisible fault discrimination in loess strata are the two hot problems in the current active fault research. Thus, the study of active fault based on the hyperspectral technology has great theoretical significance and practical value. Magnetic susceptibility (MS) records could reflect the rhythm alteration of the formation. Previous study shown that MS has correlation with spectral feature. In this study, the Emaokou section, located to the northwest of the town of Huairen, in Shanxi Province, has been chosen for invisible fault study. We collected data from the Emaokou section, including spectral data, hyperspectral image, MS data. MS models based on spectral features were established and applied to the UHD185 image for MS mapping. The results shown that MS map corresponded well to the loess sequences. It can recognize the stratum which can not identity by naked eyes. Invisible fault has been found in this section, which is useful for paleoearthquake analysis. The faults act as the conduit for migration of terrestrial gases, the fault zones, especially the structurally weak zones such as inrtersections or bends of fault, may has different material composition. We take Xiadian fault for study. Several samples cross-fault were collected and these samples were measured by ASD Field Spec 3 spectrometer. Spectral classification method has been used for spectral analysis, we found that the spectrum of the fault zone have four special spectral region(550-580nm, 600-700nm, 700-800nm and 800-900nm

  1. Graphite paper-based bipolar electrode electrochemiluminescence sensing platform.

    Science.gov (United States)

    Zhang, Xin; Ding, Shou-Nian

    2017-08-15

    In this work, aiming at the construction of a disposable, wireless, low-cost and sensitive system for bioassay, we report a closed bipolar electrode electrochemiluminescence (BPE-ECL) sensing platform based on graphite paper as BPE for the first time. Graphite paper is qualified as BPE due to its unique properties such as excellent electrical conductivity, uniform composition and ease of use. This simple BPE-ECL device was applied to the quantitative analysis of oxidant (H 2 O 2 ) and biomarker (CEA) respectively, according to the principle of BPE sensing-charge balance. For the H 2 O 2 analysis, Pt NPs were electrodeposited onto the cathode through a bipolar electrodeposition approach to promote the sensing performance. As a result, this BPE-ECL device exhibited a wide linear range of 0.001-15mM with a low detection limit of 0.5µM (S/N=3) for H 2 O 2 determination. For the determination of CEA, chitosan-multi-walled carbon nanotubes (CS-MWCNTs) were employed to supply a hydrophilic interface for immobilizing primary antibody (Ab 1 ); and Au@Pt nanostructures were conjugated with secondary antibody (Ab 2 ) as catalysts for H 2 O 2 reduction. Under the optimal conditions, the BPE-ECL immunodevice showed a wide linear range of 0.01-60ngmL -1 with a detection limit of 5.0pgmL -1 for CEA. Furthermore, it also displayed satisfactory selectivity, excellent stability and good reproducibility. The developed method opened a new avenue to clinical bioassay. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Graphene-based hybrid for enantioselective sensing applications.

    Science.gov (United States)

    Zor, Erhan; Morales-Narváez, Eden; Alpaydin, Sabri; Bingol, Haluk; Ersoz, Mustafa; Merkoçi, Arben

    2017-01-15

    Chirality is a major field of research of chemical biology and is essential in pharmacology. Accordingly, approaches for distinguishing between different chiral forms of a compound are of great interest. We report on an efficient and generic enantioselective sensor that is achieved by coupling reduced graphene oxide with γ-cyclodextrin (rGO/γ-CD). The enantioselective sensing capability of the resulting structure was operated in both electrical and optical mode for of tryptophan enantiomers (D-/L-Trp). In this sense, voltammetric and photoluminescence measurements were conducted and the experimental results were compared to molecular docking method. We gain insight into the occurring recognition mechanism with selectivity toward D- and L-Trp as shown in voltammetric, photoluminescence and molecular docking responses. As an enantioselective solid phase on an electrochemical transducer, thanks to the different dimensional interaction of enantiomers with hybrid material, a discrepancy occurs in the Gibbs free energy leading to a difference in oxidation peak potential as observed in electrochemical measurements. The optical sensing principle is based on the energy transfer phenomenon that occurs between photoexcited D-/L-Trp enantiomers and rGO/γ-CD giving rise to an enantioselective photoluminescence quenching due to the tendency of chiral enantiomers to form complexes with γ-CD in different molecular orientations as demonstrated by molecular docking studies. The approach, which is the first demonstration of applicability of molecular docking to show both enantioselective electrochemical and photoluminescence quenching capabilities of a graphene-related hybrid material, is truly new and may have broad interest in combination of experimental and computational methods for enantiosensing of chiral molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Using NOAA-AVHRR estimates of land surface temperature for regional agrometeoro[lo]gical modelling

    NARCIS (Netherlands)

    Wit, de A.J.W.; Boogaard, H.L.; Diepen, van C.A.

    2004-01-01

    This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature

  4. 129 Xe NMR Relaxation-Based Macromolecular Sensing

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Muller D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Dao, Phuong [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Jeong, Keunhong [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Slack, Clancy C. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Vassiliou, Christophoros C. [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Finbloom, Joel A. [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Francis, Matthew B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Wemmer, David E. [Univ. of California, Berkeley, CA (United States). Dept. of Chemistry; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical Biosciences Division; Pines, Alexander [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Materials Sciences Division; Univ. of California, Berkeley, CA (United States). Dept. of Chemistry

    2016-07-29

    A 129Xe NMR relaxation-based sensing approach is reported on that exploits changes in the bulk xenon relaxation rate induced by slowed tumbling of a cryptophane-based sensor upon target binding. The amplification afforded by detection of the bulk dissolved xenon allows sensitive detection of targets. The sensor comprises a xenon-binding cryptophane cage, a target interaction element, and a metal chelating agent. Xenon associated with the target-bound cryptophane cage is rapidly relaxed and then detected after exchange with the bulk. Here we show that large macromolecular targets increase the rotational correlation time of xenon, increasing its relaxation rate. Upon binding of a biotin-containing sensor to avidin at 1.5 μM concentration, the free xenon T2 is reduced by a factor of 4.

  5. Compressive sensing based wireless sensor for structural health monitoring

    Science.gov (United States)

    Bao, Yuequan; Zou, Zilong; Li, Hui

    2014-03-01

    Data loss is a common problem for monitoring systems based on wireless sensors. Reliable communication protocols, which enhance communication reliability by repetitively transmitting unreceived packets, is one approach to tackle the problem of data loss. An alternative approach allows data loss to some extent and seeks to recover the lost data from an algorithmic point of view. Compressive sensing (CS) provides such a data loss recovery technique. This technique can be embedded into smart wireless sensors and effectively increases wireless communication reliability without retransmitting the data. The basic idea of CS-based approach is that, instead of transmitting the raw signal acquired by the sensor, a transformed signal that is generated by projecting the raw signal onto a random matrix, is transmitted. Some data loss may occur during the transmission of this transformed signal. However, according to the theory of CS, the raw signal can be effectively reconstructed from the received incomplete transformed signal given that the raw signal is compressible in some basis and the data loss ratio is low. This CS-based technique is implemented into the Imote2 smart sensor platform using the foundation of Illinois Structural Health Monitoring Project (ISHMP) Service Tool-suite. To overcome the constraints of limited onboard resources of wireless sensor nodes, a method called random demodulator (RD) is employed to provide memory and power efficient construction of the random sampling matrix. Adaptation of RD sampling matrix is made to accommodate data loss in wireless transmission and meet the objectives of the data recovery. The embedded program is tested in a series of sensing and communication experiments. Examples and parametric study are presented to demonstrate the applicability of the embedded program as well as to show the efficacy of CS-based data loss recovery for real wireless SHM systems.

  6. Analysis of Plasmonics Based Fiber Optic Sensing Structures

    Science.gov (United States)

    Moayyed, Hamed

    The work described in this PhD Thesis focuses on the post-processing of optical fibers and their enhancement as sensing element. Since the majority of sensors presented are based in Fabry-Perot interferometers, an historical overview of this category of optical fiber sensors is firstly presented. This review considers the works published since the early years, in the beginning of the 1980s, until the middle of 2015. The incorporation of microcavities at the tip of a single mode fiber was extensively studied, particularly for the measurement of nitrogen and methane gas pressure. These cavities were fabricated using hollow core silica tubes and a hollow core photonic crystal fiber. Following a different approach, the microcavities were incorporated between two sections of single mode fiber. In this case, the low sensitivity to temperature makes these microcavities highly desirable for the measurement of strain at high temperatures. Competences in post-processing techniques such as the chemical etching and the writing of periodical structures in the fiber core by means of an excimer or a femtosecond laser were also acquired in the course of the PhD programme. One of the works consisted in the design and manufacturing of a double clad optical fiber. The refractive index of the inner cladding was higher than the one of the outer cladding and the core. Thus, light was guided in the inner cladding instead of propagating in the core. This situation was overcome by applying chemical etching, thus removing the inner cladding. The core, surrounded by air, was then able to guide light. Two different applications were found for this fiber, as a temperature sensor and as an optical refractometer. In the last, the optical phase changes with the liquid refractive index. Two different types of fiber Bragg gratings were characterized in strain and temperature. Sensing structures obtained through the phase mask technique at the tip of an optical fiber were subjected to chemical

  7. Nitrite sensing composite systems based on a core-shell emissive-superamagnetic structure: Construction, characterization and sensing behavior

    Science.gov (United States)

    Yang, Yan; Liu, Liang; Zha, Jianhua; Yuan, Ningyi

    2017-04-01

    Two recyclable nitrite sensing composite samples were designed and constructed through a core-shell structure, with Fe3O4 nanoparticles as core, silica molecular sieve MCM-41 as shell and two rhodamine derivatives as chemosensors, respectively. These samples and their structure were identified with their electron microscopy images, N2 adsorption/desorption isotherms, magnetic response, IR spectra and thermogravimetric analysis. Their nitrite sensing behavior was discussed based on emission intensity quenching, their limit of detection was found as low as 1.2 μM. Further analysis suggested a static sensing mechanism between nitrite and chemosensors through an additive reaction between NO+ and chemosensors. After finishing their nitrite sensing, these composite samples and their emission could be recycled and recovered by sulphamic acid.

  8. FRACTAL DIMENSION OF URBAN EXPANSION BASED ON REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    IACOB I. CIPRIAN

    2012-11-01

    Full Text Available Fractal Dimension of Urban Expansion Based on Remote Sensing Images: In Cluj-Napoca city the process of urbanization has been accelerated during the years and implication of local authorities reflects a relevant planning policy. A good urban planning framework should take into account the society demands and also it should satisfy the natural conditions of local environment. The expansion of antropic areas it can be approached by implication of 5D variables (time as a sequence of stages, space: with x, y, z and magnitude of phenomena into the process, which will allow us to analyse and extract the roughness of city shape. Thus, to improve the decision factor we take a different approach in this paper, looking at geometry and scale composition. Using the remote sensing (RS and GIS techniques we manage to extract a sequence of built-up areas (from 1980 to 2012 and used the result as an input for modelling the spatialtemporal changes of urban expansion and fractal theory to analysed the geometric features. Taking the time as a parameter we can observe behaviour and changes in urban landscape, this condition have been known as self-organized – a condition which in first stage the system was without any turbulence (before the antropic factor and during the time tend to approach chaotic behaviour (entropy state without causing an disequilibrium in the main system.

  9. Vibration-based monitoring and diagnostics using compressive sensing

    Science.gov (United States)

    Ganesan, Vaahini; Das, Tuhin; Rahnavard, Nazanin; Kauffman, Jeffrey L.

    2017-04-01

    Vibration data from mechanical systems carry important information that is useful for characterization and diagnosis. Standard approaches rely on continually streaming data at a fixed sampling frequency. For applications involving continuous monitoring, such as Structural Health Monitoring (SHM), such approaches result in high volume data and rely on sensors being powered for prolonged durations. Furthermore, for spatial resolution, structures are instrumented with a large array of sensors. This paper shows that both volume of data and number of sensors can be reduced significantly by applying Compressive Sensing (CS) in vibration monitoring applications. The reduction is achieved by using random sampling and capitalizing on the sparsity of vibration signals in the frequency domain. Preliminary experimental results validating CS-based frequency recovery are also provided. By exploiting the sparsity of mode shapes, CS can also enable efficient spatial reconstruction using fewer spatially distributed sensors. CS can thereby reduce the cost and power requirement of sensing as well as streamline data storage and processing in monitoring applications. In well-instrumented structures, CS can enable continued monitoring in case of sensor or computational failures.

  10. Non-Topographic Space-Based Laser Remote Sensing

    Science.gov (United States)

    Yu, Anthony W.; Abshire, James B.; Riris, Haris; Purucker, Michael; Janches, Diego; Getty, Stephanie; Krainak, Michael A.; Stephen, Mark A.; Chen, Jeffrey R.; Li, Steve X.; hide

    2016-01-01

    In the past 20+ years, NASA Goddard Space Flight Center (GSFC) has successfully developed and flown lidars for mapping of Mars, the Earth, Mercury and the Moon. As laser and electro-optics technologies expand and mature, more sophisticated instruments that once were thought to be too complicated for space are being considered and developed. We will present progress on several new, space-based laser instruments that are being developed at GSFC. These include lidars for remote sensing of carbon dioxide and methane on Earth for carbon cycle and global climate change; sodium resonance fluorescence lidar to measure environmental parameters of the middle and upper atmosphere on Earth and Mars and a wind lidar for Mars orbit; in situ laser instruments include remote and in-situ measurements of the magnetic fields; and a time-of-flight mass spectrometer to study the diversity and structure of nonvolatile organics in solid samples on missions to outer planetary satellites and small bodies.

  11. Development of Polymethylmethacrylate Based Composite for Gas Sensing Application

    Directory of Open Access Journals (Sweden)

    S. Devikala

    2011-01-01

    Full Text Available Gas detection instruments are increasingly needed for industrial health and safety, environmental monitoring and process control. Conductive polymer composites have various industrial applications. The composite prepared by mixing carbon black with polymethylmethacrylate (PMMA has very good gas sensing applications. The gas sensors based on carbon nanotube/polymer, ceramic and metal oxide composites such as epoxy, polyimide, PMMA / Barium titanate and tin oxide have also been developed. In the present work, a new composite has been prepared by using PMMA and ammonium dihydrogen phosphate (ADP. The PMMA/Ammonium dihydrogen phosphate (PMADP composites PMADP 1 and PMADP 2 were characterized by using Powder XRD. The thick films of the composite on glass plates were prepared by using a spin coating unit at 9000 rpm. The application of the thick film as gas sensor has been studied between 0 and 2000 seconds. The results reveal that the thick film of PMADP composite can function as a very good gas sensor.

  12. Nanoparticles doped film sensing based on terahertz metamaterials

    Science.gov (United States)

    Liu, Weimin; Fan, Fei; Chang, Shengjiang; Hou, Jiaqing; Chen, Meng; Wang, Xianghui; Bai, Jinjun

    2017-12-01

    A nanoparticles concentration sensor based on doped film and terahertz (THz) metamaterial has been proposed. By coating the nanoparticles doped polyvinyl alcohol (PVA) film on the surface of THz metamaterial, the effects of nanoparticle concentration on the metamaterial resonances are investigated through experiments and numerical simulations. Results show that resonant frequency of the metamaterial linearly decreases with the increment of doping concentration. Furthermore, numerical simulations illustrate that the redshift of resonance results from the changes of refractive index of the doped film. The concentration sensitivity of this sensor is 3.12 GHz/0.1%, and the refractive index sensitivity reaches 53.33 GHz/RIU. This work provides a non-contact, nondestructive and sensitive method for the detection of nanoparticles concentration and brings out a new application on THz film metamaterial sensing.

  13. Agrometeorology and plant disease management: a happy marriage Agrometeorologia e manejo de doenças de plantas: um casamento feliz

    Directory of Open Access Journals (Sweden)

    Terry James Gillespie

    2008-12-01

    Full Text Available Many plant disease outbreaks are triggered by suitably warm temperatures during periods of leaf wetness. Measurements or estimations of leaf wetness duration provided by Agrometeorologists have allowed Plant Pathologists to devise weather timed spray schemes which often reduce the number of sprays required to control plant diseases, thus lowering costs and benefitting the environment. In the near future, tools such as numerical weather models with small grid spacings, and improved weather radar, are expected to reduce the need for tight networks of surface observations. The weather models will also provide growers with forecast warnings of potential upcoming disease outbreaks, which will further enhance the contribution of agrometeorology to plant disease management.A disseminação de muitas doenças de plantas é influenciada por condições favoráveis de temperatura durante o período de molhamento foliar. As medidas e estimativas da duração do período de molhamento foliar fornecidas pelos Agrometeorologistas têm permitido aos Fitopatologistas dar alertas sobre a necessidade de pulverizações com base nas condições meteorológicas, o que normalmente reduz o número de aplicações para o controle de doenças, resultando em menor custo de produção e menor contaminação do ambiente. Em um futuro próximo, ferramentas como os modelos numéricos de tempo, com alta resolução espacial, e os radares meteorológicos mais avançados, deverão reduzir a necessidade de redes de observação meteorológica de superfície mais densas. Os modelos meteorológicos também possibilitarão a previsão de disseminação potencial das doenças de plantas, o que irá aumentar ainda mais a contribuição da agrometeorologia para o controle fitossanitário mais racional.

  14. Making sense of shared sense-making in an inquiry-based science classroom: Toward a sociocultural theory of mind

    Science.gov (United States)

    Ladewski, Barbara G.

    Despite considerable exploration of inquiry and reflection in the literatures of science education and teacher education/teacher professional development over the past century, few theoretical or analytical tools exist to characterize these processes within a naturalistic classroom context. In addition, little is known regarding possible developmental trajectories for inquiry or reflection---for teachers or students---as these processes develop within a classroom context over time. In the dissertation, I use a sociocultural lens to explore these issues with an eye to the ways in which teachers and students develop shared sense-making, rather than from the more traditional perspective of individual teacher activity or student learning. The study includes both theoretical and empirical components. Theoretically, I explore the elaborations of sociocultural theory needed to characterize teacher-student shared sense-making as it develops within a classroom context, and, in particular, the role of inquiry and reflection in that sense-making. I develop a sociocultural model of shared sense-making that attempts to represent the dialectic between the individual and the social, through an elaboration of existing sociocultural and psychological constructs, including Vygotsky's zone of proximal development and theory of mind. Using this model as an interpretive framework, I develop a case study that explores teacher-student shared sense-making within a middle-school science classroom across a year of scaffolded introduction to inquiry-based science instruction. The empirical study serves not only as a test case for the theoretical model, but also informs our understanding regarding possible developmental trajectories and important mechanisms supporting and constraining shared sense-making within inquiry-based science classrooms. Theoretical and empirical findings provide support for the idea that perspectival shifts---that is, shifts of point-of-view that alter relationships

  15. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining

    Directory of Open Access Journals (Sweden)

    Paul F.M.J. Verschure

    2008-11-01

    Full Text Available Antipersonnel mines, weapons of cheap manufacture but lethal effect, have a high impact on the population even decades after the conflicts have finished. Here we investigate the use of a chemo-sensing Unmanned Aerial Vehicle (cUAV for demining tasks. We developed a blimp based UAV that is equipped with a broadly tuned metal-thin oxide chemo-sensor. A number of chemical mapping strategies were investigated including two biologically based localization strategies derived from the moth chemical search that can optimize the efficiency of the detection and localization of explosives and therefore be used in the demining process. Additionally, we developed a control layer that allows for both fully autonomous and manual controlled flight, as well as for the scheduling of a fleet of cUAVs. Our results confirm the feasibility of this technology for demining in real-world scenarios and give further support to a biologically based approach where the understanding of biological systems is used to solve difficult engineering problems.

  16. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining

    Directory of Open Access Journals (Sweden)

    Sergi Bermúdez i Badia

    2007-06-01

    Full Text Available Antipersonnel mines, weapons of cheap manufacture but lethal effect, have a high impact on the population even decades after the conflicts have finished. Here we investigate the use of a chemo-sensing Unmanned Aerial Vehicle (cUAV for demining tasks. We developed a blimp based UAV that is equipped with a broadly tuned metal-thin oxide chemo-sensor. A number of chemical mapping strategies were investigated including two biologically based localization strategies derived from the moth chemical search that can optimize the efficiency of the detection and localization of explosives and therefore be used in the demining process. Additionally, we developed a control layer that allows for both fully autonomous and manual controlled flight, as well as for the scheduling of a fleet of cUAVs. Our results confirm the feasibility of this technology for demining in real-world scenarios and give further support to a biologically based approach where the understanding of biological systems is used to solve difficult engineering problems.

  17. Thin metal films in resistivity-based chemical sensing

    Czech Academy of Sciences Publication Activity Database

    Podešva, Pavel; Foret, František

    2013-01-01

    Roč. 9, č. 4 (2013), s. 642-652 ISSN 1573-4110 R&D Projects: GA ČR(CZ) GAP301/11/2055 Institutional support: RVO:68081715 Keywords : voltohmmetric sensing * chemiresistor * thin metal film * gas sensing Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 1.194, year: 2013

  18. An Enhanced Sensing Application Based on a Flexible Projected Capacitive-Sensing Mattress

    Directory of Open Access Journals (Sweden)

    Wen-Ying Chang

    2014-04-01

    Full Text Available This paper presents a cost-effective sensor system for mattresses that can classify the sleeping posture of an individual and prevent pressure ulcers. This system applies projected capacitive sensing to the field of health care. The charge time (CT method was used to sensitively and accurately measure the capacitance of the projected electrodes. The required characteristics of the projected capacitor were identified to develop large-area applications for sensory mattresses. The area of the electrodes, the use of shielding, and the increased length of the transmission line were calibrated to more accurately measure the capacitance of the electrodes in large-size applications. To offer the users comfort in the prone position, a flexible substrate was selected and covered with 16 × 20 electrodes. Compared with the static charge sensitive bed (SCSB, our proposed system-flexible projected capacitive-sensing mattress (FPCSM comes with more electrodes to increase the resolution of posture identification. As for the body pressure system (BPS, the FPCSM has advantages such as lower cost, higher aging-resistance capability, and the ability to sense the capacitance of the covered regions without physical contact. The proposed guard ring design effectively absorbs the noise and interrupts leakage paths. The projected capacitive electrode is suitable for proximity-sensing applications and succeeds at quickly recognizing the sleeping pattern of the user.

  19. Interference Information Based Power Control for Cognitive Radio with Multi-Hop Cooperative Sensing

    Science.gov (United States)

    Yu, Youngjin; Murata, Hidekazu; Yamamoto, Koji; Yoshida, Susumu

    Reliable detection of other radio systems is crucial for systems that share the same frequency band. In wireless communication channels, there is uncertainty in the received signal level due to multipath fading and shadowing. Cooperative sensing techniques in which radio stations share their sensing information can improve the detection probability of other systems. In this paper, a new cooperative sensing scheme that reduces the false detection probability while maintaining the outage probability of other systems is investigated. In the proposed system, sensing information is collected using multi-hop transmission from all sensing stations that detect other systems, and transmission decisions are based on the received sensing information. The proposed system also controls the transmit power based on the received CINRs from the sensing stations. Simulation results reveal that the proposed system can reduce the outage probability of other systems, or improve its link success probability.

  20. The possibilities of compressed-sensing-based Kirchhoff prestack migration

    KAUST Repository

    Aldawood, Ali; Hoteit, Ibrahim; Alkhalifah, Tariq Ali

    2014-01-01

    An approximate subsurface reflectivity distribution of the earth is usually obtained through the migration process. However, conventional migration algorithms, including those based on the least-squares approach, yield structure descriptions that are slightly smeared and of low resolution caused by the common migration artifacts due to limited aperture, coarse sampling, band-limited source, and low subsurface illumination. To alleviate this problem, we use the fact that minimizing the L1-norm of a signal promotes its sparsity. Thus, we formulated the Kirchhoff migration problem as a compressed-sensing (CS) basis pursuit denoise problem to solve for highly focused migrated images compared with those obtained by standard and least-squares migration algorithms. The results of various subsurface reflectivity models revealed that solutions computed using the CS based migration provide a more accurate subsurface reflectivity location and amplitude. We applied the CS algorithm to image synthetic data from a fault model using dense and sparse acquisition geometries. Our results suggest that the proposed approach may still provide highly resolved images with a relatively small number of measurements. We also evaluated the robustness of the basis pursuit denoise algorithm in the presence of Gaussian random observational noise and in the case of imaging the recorded data with inaccurate migration velocities.

  1. The possibilities of compressed-sensing-based Kirchhoff prestack migration

    KAUST Repository

    Aldawood, Ali

    2014-05-08

    An approximate subsurface reflectivity distribution of the earth is usually obtained through the migration process. However, conventional migration algorithms, including those based on the least-squares approach, yield structure descriptions that are slightly smeared and of low resolution caused by the common migration artifacts due to limited aperture, coarse sampling, band-limited source, and low subsurface illumination. To alleviate this problem, we use the fact that minimizing the L1-norm of a signal promotes its sparsity. Thus, we formulated the Kirchhoff migration problem as a compressed-sensing (CS) basis pursuit denoise problem to solve for highly focused migrated images compared with those obtained by standard and least-squares migration algorithms. The results of various subsurface reflectivity models revealed that solutions computed using the CS based migration provide a more accurate subsurface reflectivity location and amplitude. We applied the CS algorithm to image synthetic data from a fault model using dense and sparse acquisition geometries. Our results suggest that the proposed approach may still provide highly resolved images with a relatively small number of measurements. We also evaluated the robustness of the basis pursuit denoise algorithm in the presence of Gaussian random observational noise and in the case of imaging the recorded data with inaccurate migration velocities.

  2. Comparative VOCs sensing performance for conducting polymer and porphyrin functionalized carbon nanotubes based sensors

    Science.gov (United States)

    Datta, Kunal; Rushi, Arti; Ghosh, Prasanta; Shirsat, Mahendra

    2018-05-01

    We report sensors for detection of ethyl alcohol, a prominent volatile organic compound (VOC). Single walled carbon nanotubes were selected as main sensing backbone. As efficiency of sensor is dependent upon the choice of sensing materials, the performances of conducting polymer and porphyrin based sensors were compared. Chemiresistive sensing modality was adopted to observe the performance of sensors. It has been found that porphyrin based sensor shows higher affinity towards ethyl alcohol.

  3. Sensing Landscape History with an Interactive Location Based Service

    Science.gov (United States)

    van Lammeren, Ron; Goossen, Martin; Roncken, Paul

    2009-01-01

    This paper introduces the STEAD approach for interpreting data acquired by a “human sensor”, who uses an informal interactive location-based service (iLBS) to sense cultural-historic facts and anecdotes of, and in the landscape. This user-generated data is collected outdoors and in situ. The approach consists of four related facets (who, what, where, when). Three of the four facets are discussed and illustrated by user generated data collected during a Dutch survey in 2008. These data represent the personal cultural-historic knowledge and anecdotes of 150 people using a customized iLBS for experiencing the cultural history of a landscape. The “who” facet shows three dominant mentality groups (cosmopolitans, modern materialists and post modern hedonists) that generated user content. The “what” facet focuses on three subject types of pictures and four picture framing classes. Pictures of the place type showed to be dominant and foreground framing class was slightly favourite. The “where” facet is explored via density, distribution, and distance of the pictures made. The illustrations of the facets indirectly show the role of the “human sensor” with respect to the domain of interest. The STEAD approach needs further development of the when-facet and of the relations between the four facets. Finally the results of the approach may support data archives of iLBS applications. PMID:22399994

  4. Ground-Based Correction of Remote-Sensing Spectral Imagery

    Science.gov (United States)

    Alder-Golden, Steven M.; Rochford, Peter; Matthew, Michael; Berk, Alexander

    2007-01-01

    Software has been developed for an improved method of correcting for the atmospheric optical effects (primarily, effects of aerosols and water vapor) in spectral images of the surface of the Earth acquired by airborne and spaceborne remote-sensing instruments. In this method, the variables needed for the corrections are extracted from the readings of a radiometer located on the ground in the vicinity of the scene of interest. The software includes algorithms that analyze measurement data acquired from a shadow-band radiometer. These algorithms are based on a prior radiation transport software model, called MODTRAN, that has been developed through several versions up to what are now known as MODTRAN4 and MODTRAN5 . These components have been integrated with a user-friendly Interactive Data Language (IDL) front end and an advanced version of MODTRAN4. Software tools for handling general data formats, performing a Langley-type calibration, and generating an output file of retrieved atmospheric parameters for use in another atmospheric-correction computer program known as FLAASH have also been incorporated into the present soft-ware. Concomitantly with the soft-ware described thus far, there has been developed a version of FLAASH that utilizes the retrieved atmospheric parameters to process spectral image data.

  5. Transcriptome analysis of acyl-homoserine lactone-based quorum sensing regulation in Yersinia pestis [corrected].

    Directory of Open Access Journals (Sweden)

    Christopher N LaRock

    Full Text Available The etiologic agent of bubonic plague, Yersinia pestis, senses self-produced, secreted chemical signals in a process named quorum sensing. Though the closely related enteric pathogen Y. pseudotuberculosis uses quorum sensing system to regulate motility, the role of quorum sensing in Y. pestis has been unclear. In this study we performed transcriptional profiling experiments to identify Y. pestis quorum sensing regulated functions. Our analysis revealed that acyl-homoserine lactone-based quorum sensing controls the expression of several metabolic functions. Maltose fermentation and the glyoxylate bypass are induced by acyl-homoserine lactone signaling. This effect was observed at 30°C, indicating a potential role for quorum sensing regulation of metabolism at temperatures below the normal mammalian temperature. It is proposed that utilization of alternative carbon sources may enhance growth and/or survival during prolonged periods in natural habitats with limited nutrient sources, contributing to maintenance of plague in nature.

  6. Structural mapping based on potential field and remote sensing data ...

    Indian Academy of Sciences (India)

    Swarnapriya Chowdari

    2017-08-31

    Aug 31, 2017 ... to comprehend the tectonic development of the ... software for the analysis and interpretation of G– .... The application of remote sensing for mapping ..... Pf1 and Pf2 show profile locations adopted for joint G–M modelling.

  7. Nanomaterial-based electrochemical sensing of neurological drugs and neurotransmitters

    International Nuclear Information System (INIS)

    Sanghavi, Bankim J.; Swami, Nathan S.; Wolfbeis, Otto S.; Hirsch, Thomas

    2015-01-01

    Nanomaterial-modified detection systems represent a chief driver towards the adoption of electrochemical methods, since nanomaterials enable functional tunability, ability to self-assemble, and novel electrical, optical and catalytic properties that emerge at this scale. This results in tremendous gains in terms of sensitivity, selectivity and versatility. We review the electrochemical methods and mechanisms that may be applied to the detection of neurological drugs. We focus on understanding how specific nano-sized modifiers may be applied to influence the electron transfer event to result in gains in sensitivity, selectivity and versatility of the detection system. This critical review is structured on the basis of the Anatomical Therapeutic Chemical (ATC) Classification System, specifically ATC Code N (neurotransmitters). Specific sections are dedicated to the widely used electrodes based on the carbon materials, supporting electrolytes, and on electrochemical detection paradigms for neurological drugs and neurotransmitters within the groups referred to as ATC codes N01 to N07. We finally discuss emerging trends and future challenges such as the development of strategies for simultaneous detection of multiple targets with high spatial and temporal resolutions, the integration of microfluidic strategies for selective and localized analyte pre-concentration, the real-time monitoring of neurotransmitter secretions from active cell cultures under electro- and chemotactic cues, aptamer-based biosensors, and the miniaturization of the sensing system for detection in small sample volumes and for enabling cost savings due to manufacturing scale-up. The Electronic Supporting Material (ESM) includes review articles dealing with the review topic in last 40 years, as well as key properties of the analytes, viz., pK a values, half-life of drugs and their electrochemical mechanisms. The ESM also defines analytical figures of merit of the drugs and neurotransmitters. The

  8. Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure.

    Science.gov (United States)

    Tang, Yongsheng; Wu, Zhishen

    2016-02-25

    Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced polymer (FRP) bar was developed by embedding the packaged long-gauge OF sensors into FRP bar, followed by experimental studies on strain sensing, temperature sensing and basic mechanical properties. The results confirmed the superior strain sensing properties, namely satisfied accuracy, repeatability and linearity, as well as excellent mechanical performance. At the same time, the temperature sensing property was not influenced by the long-gauge package, making temperature compensation easy. Furthermore, the bonding performance between self-sensing FRP bar and concrete was investigated to study its influence on the sensing. Lastly, the sensing performance was further verified with static experiments of concrete beam reinforced with the proposed self-sensing FRP bar. Therefore, the self-sensing FRP bar has potential applications for long-term structural health monitoring (SHM) as embedded sensors as well as reinforcing materials for concrete structures.

  9. Dual sensing-actuation artificial muscle based on polypyrrole-carbon nanotube composite

    Science.gov (United States)

    Schumacher, J.; Otero, Toribio F.; Pascual, Victor H.

    2017-04-01

    Dual sensing artificial muscles based on conducting polymer are faradaic motors driven by electrochemical reactions, which announce the development of proprioceptive devices. The applicability of different composites has been investigated with the aim to improve the performance. Addition of carbon nanotubes may reduce irreversible reactions. We present the testing of a dual sensing artificial muscle based on a conducting polymer and carbon nanotubes composite. Large bending motions (up to 127 degrees) in aqueous solution and simultaneously sensing abilities of the operation conditions are recorded. The sensing and actuation equations are derived for incorporation into a control system.

  10. A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2015-08-01

    Full Text Available In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

  11. Research on Remote Sensing Image Template Processing Based on Global Subdivision Theory

    OpenAIRE

    Xiong Delan; Du Genyuan

    2013-01-01

    Aiming at the questions of vast data, complex operation, and time consuming processing for remote sensing image, subdivision template was proposed based on global subdivision theory, which can set up high level of abstraction and generalization for remote sensing image. The paper emphatically discussed the model and structure of subdivision template, and put forward some new ideas for remote sensing image template processing, key technology and quickly applied demonstration. The research has ...

  12. Carbon Nanotube Yarn-Based Glucose Sensing Artificial Muscle.

    Science.gov (United States)

    Lee, Junghan; Ko, Sachan; Kwon, Cheong Hoon; Lima, Márcio D; Baughman, Ray H; Kim, Seon Jeong

    2016-04-01

    Boronic acid (BA), known to be a reversible glucose-sensing material, is conjugated to a nanogel (NG) derived from hyaluronic acid biopolymer and used as a guest material for a carbon multiwalled nanotube (MWNT) yarn. By exploiting the swelling/deswelling of the NG that originates from the internal anionic charge changes resulting from BA binding to glucose, a NG MWNT yarn artificial muscle is obtained that provides reversible torsional actuation that can be used for glucose sensing. This actuator shows a short response time and high sensitivity (in the 5-100 × 10(-3) m range) for monitoring changes in glucose concentration in physiological buffer, without using any additional auxiliary substances or an electrical power source. It may be possible to apply the glucose-sensing MWNT yarn muscles as implantable glucose sensors that automatically release drugs when needed or as an artificial pancreas. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Magnetoseismology ground-based remote sensing of Earth's magnetosphere

    CERN Document Server

    Menk, Frederick W

    2013-01-01

    Written by a researcher at the forefront of the field, this first comprehensive account of magnetoseismology conveys the physics behind these movements and waves, and explains how to detect and investigate them. Along the way, it describes the principles as applied to remote sensing of near-Earth space and related remote sensing techniques, while also comparing and intercalibrating magnetoseismology with other techniques. The example applications include advanced data analysis techniques that may find wider used in areas ranging from geophysics to medical imaging, and remote sensing using radar systems that are of relevance to defense surveillance systems. As a result, the book not only reviews the status quo, but also anticipates new developments. With many figures and illustrations, some in full color, plus additional computational codes for analysis and evaluation. Aimed at graduate readers, the text assumes knowledge of electromagnetism and physical processes at degree level, but introductory chapters wil...

  14. Sensing line effects on PWR-based differential pressure measurements

    International Nuclear Information System (INIS)

    Evans, R.P.; Neff, G.G.

    1982-01-01

    An incorrrect configuration of the fluid-filled pressure sensing lines connecting differential pressure transducers to the pressure taps in a pressurized water reactor system can cause errors in the measurement and, during rapid pressure transients, could cause the transducer to fail. Testing was performed in both static and dynamic modes to experimentally determine the effects of sensing lines of various lengths, diameters, and materials. Testing was performed at ambient temperature with absolute line pressures at about 17 MPa using water as the pressure transmission fluid

  15. Review of commonly used remote sensing and ground-based ...

    African Journals Online (AJOL)

    This review provides an overview of the use of remote sensing data, the development of spectral reflectance indices for detecting plant water stress, and the usefulness of field measurements for ground-truthing purposes. Reliable measurements of plant water stress over large areas are often required for management ...

  16. Fabrication of nano piezoelectric based vibration accelerometer for mechanical sensing

    Science.gov (United States)

    Murugan, S.; Prasad, M. V. N.; Jayakumar, K.

    2016-05-01

    An electromechanical sensor unit has been fabricated using nano PZT embedded in PVDF polymer. Such a polymer nano composite has been used as vibration sensor element and sensitivity, detection of mechanical vibration, and linearity measurements have been investigated. It is found from its performance, that this nano composite sensor is suitable for mechanical sensing applications.

  17. Polarimetric and Indoor Imaging Fusion Based on Compressive Sensing

    Science.gov (United States)

    2013-04-01

    34 in Proc. IEEE Radar Conf, Rome, Italy , May 2008. [17] M. G. Amin, F. Ahmad, W. Zhang, "A compressive sensing approach to moving target... Ferrara , J. Jackson, and M. Stuff, "Three-dimensional sparse-aperture moving-target imaging," in Proc. SPIE, vol. 6970, 2008. [43] M. Skolnik (Ed

  18. Supervised Gaussian mixture model based remote sensing image ...

    African Journals Online (AJOL)

    Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test the Gaussian mixture model algorithm. For the purpose of validating the experiment, the resulting classified satellite image is compared with the ground truth data. For the simulated modelling, ...

  19. A Web GIS Framework for Participatory Sensing Service: An Open Source-Based Implementation

    Directory of Open Access Journals (Sweden)

    Yu Nakayama

    2017-04-01

    Full Text Available Participatory sensing is the process in which individuals or communities collect and analyze systematic data using mobile phones and cloud services. To efficiently develop participatory sensing services, some server-side technologies have been proposed. Although they provide a good platform for participatory sensing, they are not optimized for spatial data management and processing. For the purpose of spatial data collection and management, many web GIS approaches have been studied. However, they still have not focused on the optimal framework for participatory sensing services. This paper presents a web GIS framework for participatory sensing service (FPSS. The proposed FPSS enables an integrated deployment of spatial data capture, storage, and data management functions. In various types of participatory sensing experiments, users can collect and manage spatial data in a unified manner. This feature is realized by the optimized system architecture and use case based on the general requirements for participatory sensing. We developed an open source GIS-based implementation of the proposed framework, which can overcome financial difficulties that are one of the major problems of deploying sensing experiments. We confirmed with the prototype that participatory sensing experiments can be performed efficiently with the proposed FPSS.

  20. Sense of Community in a Blended Technology Integration Course: A Design-Based Research Study

    Science.gov (United States)

    Harrison, J. Buckley; West, Richard E.

    2014-01-01

    This design-based research study explored whether "sense of community" was maintained while flexibility in the course was increased through an adoption of a unique blended learning model. Data collected in this study show a significant drop in the sense of connectedness score from a mean of 50.8 out of 66 to a mean of 39.68 in the first…

  1. A filter bank approach for LED illumintaion sensing based on frequency division multiplexing

    NARCIS (Netherlands)

    Yang, Hongming; Bergmans, J.W.M.; Schenk, T.C.W.

    2009-01-01

    In this work, we consider illumination sensing in a light emitting diode (LED) based illumination system that normally consists of a large number of LEDs. Illumination sensing is used in order to facilitate the control of such system whose complexity, due to the large number of LEDs, can be quite

  2. Electrical impedance tomography-based sensing skin for quantitative imaging of damage in concrete

    International Nuclear Information System (INIS)

    Hallaji, Milad; Pour-Ghaz, Mohammad; Seppänen, Aku

    2014-01-01

    This paper outlines the development of a large-area sensing skin for damage detection in concrete structures. The developed sensing skin consists of a thin layer of electrically conductive copper paint that is applied to the surface of the concrete. Cracking of the concrete substrate results in the rupture of the sensing skin, decreasing its electrical conductivity locally. The decrease in conductivity is detected with electrical impedance tomography (EIT) imaging. In previous works, electrically based sensing skins have provided only qualitative information on the damage on the substrate surface. In this paper, we study whether quantitative imaging of the damage is possible. We utilize application-specific models and computational methods in the image reconstruction, including a total variation (TV) prior model for the damage and an approximate correction of the modeling errors caused by the inhomogeneity of the painted sensing skin. The developed damage detection method is tested experimentally by applying the sensing skin to polymeric substrates and a reinforced concrete beam under four-point bending. In all test cases, the EIT-based sensing skin provides quantitative information on cracks and/or other damages on the substrate surface: featuring a very low conductivity in the damage locations, and a reliable indication of the lengths and shapes of the cracks. The results strongly support the applicability of the painted EIT-based sensing skin for damage detection in reinforced concrete elements and other substrates. (paper)

  3. Advanced laser sensing receiver concepts based on FPA technology

    International Nuclear Information System (INIS)

    Jacobson, Phillip L.; Petrin, Roger R.; Jolin, John L.; Foy, Bernard R.; Lowrance, J.L.; Renda, George

    2002-01-01

    The ultimate performance of any remote sensor is ideally governed by the hardware signal-to-noise capability and allowed signal-averaging time. In real-world scenarios, this may not be realizable and the limiting factors may suggest the need for more advanced capabilities. Moving from passive to active remote sensors offers the advantage of control over the illumination source, the laser. Added capabilities may include polarization discrimination, instantaneous imaging, range resolution, simultaneous multi-spectral measurement, or coherent detection. However, most advanced detection technology has been engineered heavily towards the straightforward passive sensor requirements, measuring an integrated photon flux. The need for focal plane array technology designed specifically for laser sensing has been recognized for some time, but advances have only recently made the engineering possible. This paper will present a few concepts for laser sensing receiver architectures, the driving specifications behind those concepts, and test/modeling results of such designs.

  4. Camera-based micro interferometer for distance sensing

    Science.gov (United States)

    Will, Matthias; Schädel, Martin; Ortlepp, Thomas

    2017-12-01

    Interference of light provides a high precision, non-contact and fast method for measurement method for distances. Therefore this technology dominates in high precision systems. However, in the field of compact sensors capacitive, resistive or inductive methods dominates. The reason is, that the interferometric system has to be precise adjusted and needs a high mechanical stability. As a result, we have usual high-priced complex systems not suitable in the field of compact sensors. To overcome these we developed a new concept for a very small interferometric sensing setup. We combine a miniaturized laser unit, a low cost pixel detector and machine vision routines to realize a demonstrator for a Michelson type micro interferometer. We demonstrate a low cost sensor smaller 1cm3 including all electronics and demonstrate distance sensing up to 30 cm and resolution in nm range.

  5. Pyrolytic carbon microelectrodes for impedance based cell sensing

    DEFF Research Database (Denmark)

    Hassan, Yasmin Mohamed; Caviglia, Claudia; Hemanth, Suhith

    2016-01-01

    Electrically conductive glass-like carbon structures can be obtained from a polymer template through a pyrolysis process. These structures can be used as electrodes for bio sensing applications such as electrochemical evaluation of cell adhesion and proliferation. This study focuses on the optimi...... to decrease the resistivity of the resulting carbon material and improve the performance in cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Finally, EIS was used to monitor adhesion and proliferation of HeLa cells....

  6. Revisiting the probabilistic definition of drought: strengths, limitations and an agrometeorological adaptation

    Directory of Open Access Journals (Sweden)

    Gabriel Constantino Blain

    2012-01-01

    Full Text Available Drought is a slow-moving hazard that occurs in virtually all countries of the world. In the light of this, several indices have been developed to improve the detection of drought's onset, as well as quantifying other features of this phenomenon. The Standardized Precipitation Index (SPI is often used in order to characterize meteorological droughts. In addition, this index is largely used by Brazilian's agricultural institutions. In order to add important information to the drought literature, this review article described a general definition of drought, evaluated it from a statistical point of view, and also described the SPI strengths and limitations. An adaptation of the SPI that aims to develop a probability-based agricultural drought index was also presented. The results obtained herein, associated with several studies carried out throughout the world, demonstrated that the SPI is not an agricultural index. It is just a mathematical approach developed to transforming skewed distributions into the Gaussian form. If this standardization cannot be achieved, the use of this index becomes meaningless. Therefore, a normality test should be used in establishing a temporal lower limit for the SPI computations. It was also verified that for periods in which the probability associated with the zero precipitation value is close to 0.5, the SPI may erroneously indicate the end of an existing drought (or a decrease in its severity in the presence of a decrease in the actual evapotranspiration values.

  7. A Support-Based Reconstruction for SENSE MRI

    Directory of Open Access Journals (Sweden)

    Bradley S. Peterson

    2013-03-01

    Full Text Available A novel, rapid algorithm to speed up and improve the reconstruction of sensitivity encoding (SENSE MRI was proposed in this paper. The essence of the algorithm was that it iteratively solved the model of simple SENSE on a pixel-by-pixel basis in the region of support (ROS. The ROS was obtained from scout images of eight channels by morphological operations such as opening and filling. All the pixels in the FOV were paired and classified into four types, according to their spatial locations with respect to the ROS, and each with corresponding procedures of solving the inverse problem for image reconstruction. The sensitivity maps, used for the image reconstruction and covering only the ROS, were obtained by a polynomial regression model without extrapolation to keep the estimation errors small. The experiments demonstrate that the proposed method improves the reconstruction of SENSE in terms of speed and accuracy. The mean square errors (MSE of our reconstruction is reduced by 16.05% for a 2D brain MR image and the mean MSE over the whole slices in a 3D brain MRI is reduced by 30.44% compared to those of the traditional methods. The computation time is only 25%, 45%, and 70% of the traditional method for images with numbers of pixels in the orders of 103, 104, and 105–107, respectively.

  8. Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

    Science.gov (United States)

    Hong, Liang

    2013-10-01

    The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

  9. Distributed Schemes for Crowdsourcing-Based Sensing Task Assignment in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Linbo Zhai

    2017-01-01

    Full Text Available Spectrum sensing is an important issue in cognitive radio networks. The unlicensed users can access the licensed wireless spectrum only when the licensed wireless spectrum is sensed to be idle. Since mobile terminals such as smartphones and tablets are popular among people, spectrum sensing can be assigned to these mobile intelligent terminals, which is called crowdsourcing method. Based on the crowdsourcing method, this paper studies the distributed scheme to assign spectrum sensing task to mobile terminals such as smartphones and tablets. Considering the fact that mobile terminals’ positions may influence the sensing results, a precise sensing effect function is designed for the crowdsourcing-based sensing task assignment. We aim to maximize the sensing effect function and cast this optimization problem to address crowdsensing task assignment in cognitive radio networks. This problem is difficult to be solved because the complexity of this problem increases exponentially with the growth in mobile terminals. To assign crowdsensing task, we propose four distributed algorithms with different transition probabilities and use a Markov chain to analyze the approximation gap of our proposed schemes. Simulation results evaluate the average performance of our proposed algorithms and validate the algorithm’s convergence.

  10. Pipeline Structural Damage Detection Using Self-Sensing Technology and PNN-Based Pattern Recognition

    International Nuclear Information System (INIS)

    Lee, Chang Gil; Park, Woong Ki; Park, Seung Hee

    2011-01-01

    In a structure, damage can occur at several scales from micro-cracking to corrosion or loose bolts. This makes the identification of damage difficult with one mode of sensing. Hence, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In the self sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this study, an experimental study on the pipeline system is carried out to verify the effectiveness and the robustness of the proposed structural health monitoring approach. Different types of structural damage are artificially inflicted on the pipeline system. To classify the multiple types of structural damage, a supervised learning-based statistical pattern recognition is implemented by composing a two-dimensional space using the damage indices extracted from the impedance and guided wave features. For more systematic damage classification, several control parameters to determine an optimal decision boundary for the supervised learning-based pattern recognition are optimized. Finally, further research issues will be discussed for real-world implementation of the proposed approach

  11. Elaborate analysis and design of filter-bank-based sensing for wideband cognitive radios

    Science.gov (United States)

    Maliatsos, Konstantinos; Adamis, Athanasios; Kanatas, Athanasios G.

    2014-12-01

    The successful operation of a cognitive radio system strongly depends on its ability to sense the radio environment. With the use of spectrum sensing algorithms, the cognitive radio is required to detect co-existing licensed primary transmissions and to protect them from interference. This paper focuses on filter-bank-based sensing and provides a solid theoretical background for the design of these detectors. Optimum detectors based on the Neyman-Pearson theorem are developed for uniform discrete Fourier transform (DFT) and modified DFT filter banks with root-Nyquist filters. The proposed sensing framework does not require frequency alignment between the filter bank of the sensor and the primary signal. Each wideband primary channel is spanned and monitored by several sensor subchannels that analyse it in narrowband signals. Filter-bank-based sensing is proved to be robust and efficient under coloured noise. Moreover, the performance of the weighted energy detector as a sensing technique is evaluated. Finally, based on the Locally Most Powerful and the Generalized Likelihood Ratio test, real-world sensing algorithms that do not require a priori knowledge are proposed and tested.

  12. A Web-Based Airborne Remote Sensing Telemetry Server, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A Web-based Airborne Remote Sensing Telemetry Server (WARSTS) is proposed to integrate UAV telemetry and web-technology into an innovative communication, command,...

  13. Using optical remote sensing model to estimate oil slick thickness based on satellite image

    International Nuclear Information System (INIS)

    Lu, Y C; Tian, Q J; Lyu, C G; Fu, W X; Han, W C

    2014-01-01

    An optical remote sensing model has been established based on two-beam interference theory to estimate marine oil slick thickness. Extinction coefficient and normalized reflectance of oil are two important parts in this model. Extinction coefficient is an important inherent optical property and will not vary with the background reflectance changed. Normalized reflectance can be used to eliminate the background differences between in situ measured spectra and remotely sensing image. Therefore, marine oil slick thickness and area can be estimated and mapped based on optical remotely sensing image and extinction coefficient

  14. Electroanalytical Sensing of Flunitrazepam Based on Screen Printed Graphene Electrodes

    Directory of Open Access Journals (Sweden)

    Enriqueta Garcia-Gutierrez

    2013-12-01

    Full Text Available We present a new electrochemical sensor for Flunitrazepam using disposable and economic Screen Printed Graphene Electrodes. It was found that the electrochemical response of this sensor was improved compared to Screen Printed Graphite Electrodes and displayed an excellent analytical performance for the detection of Flunitrazepam. Those characteristics could be attributed to the high Flunitrazepam loading capacity on the electrode surface and the outstanding electric conductivity of graphene. The methodology is shown to be useful for quantifying low levels of Flunitrazepam in a buffer solution. The protocol is also shown to be applicable for the sensing of Flunitrazepam in an alcoholic beverage e.g., Gordon’s Gin & Tonic.

  15. A Semantic Lexicon-Based Approach for Sense Disambiguation and Its WWW Application

    Science.gov (United States)

    di Lecce, Vincenzo; Calabrese, Marco; Soldo, Domenico

    This work proposes a basic framework for resolving sense disambiguation through the use of Semantic Lexicon, a machine readable dictionary managing both word senses and lexico-semantic relations. More specifically, polysemous ambiguity characterizing Web documents is discussed. The adopted Semantic Lexicon is WordNet, a lexical knowledge-base of English words widely adopted in many research studies referring to knowledge discovery. The proposed approach extends recent works on knowledge discovery by focusing on the sense disambiguation aspect. By exploiting the structure of WordNet database, lexico-semantic features are used to resolve the inherent sense ambiguity of written text with particular reference to HTML resources. The obtained results may be extended to generic hypertextual repositories as well. Experiments show that polysemy reduction can be used to hint about the meaning of specific senses in given contexts.

  16. Phase sensitive distributed vibration sensing based on ultraweak fiber Bragg grating array using double-pulse

    Science.gov (United States)

    Liu, Tao; Wang, Feng; Zhang, Xuping; Zhang, Lin; Yuan, Quan; Liu, Yu; Yan, Zhijun

    2017-08-01

    A distributed vibration sensing technique using double-optical-pulse based on phase-sensitive optical time-domain reflectometry (ϕ-OTDR) and an ultraweak fiber Bragg grating (UWFBG) array is proposed for the first time. The single-mode sensing fiber is integrated with the UWFBG array that has uniform spatial interval and ultraweak reflectivity. The relatively high reflectivity of the UWFBG, compared with the Rayleigh scattering, gains a high signal-to-noise ratio for the signal, which can make the system achieve the maximum detectable frequency limited by the round-trip time of the probe pulse in fiber. A corresponding experimental ϕ-OTDR system with a 4.5 km sensing fiber integrated with the UWFBG array was setup for the evaluation of the system performance. Distributed vibration sensing is successfully realized with spatial resolution of 50 m. The sensing range of the vibration frequency can cover from 3 Hz to 9 kHz.

  17. [Estimation of desert vegetation coverage based on multi-source remote sensing data].

    Science.gov (United States)

    Wan, Hong-Mei; Li, Xia; Dong, Dao-Rui

    2012-12-01

    Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study areaAbstract: Taking the lower reaches of Tarim River in Xinjiang of Northwest China as study area and based on the ground investigation and the multi-source remote sensing data of different resolutions, the estimation models for desert vegetation coverage were built, with the precisions of different estimation methods and models compared. The results showed that with the increasing spatial resolution of remote sensing data, the precisions of the estimation models increased. The estimation precision of the models based on the high, middle-high, and middle-low resolution remote sensing data was 89.5%, 87.0%, and 84.56%, respectively, and the precisions of the remote sensing models were higher than that of vegetation index method. This study revealed the change patterns of the estimation precision of desert vegetation coverage based on different spatial resolution remote sensing data, and realized the quantitative conversion of the parameters and scales among the high, middle, and low spatial resolution remote sensing data of desert vegetation coverage, which would provide direct evidence for establishing and implementing comprehensive remote sensing monitoring scheme for the ecological restoration in the study area.

  18. Light sensing in a photoresponsive, organic-based complementary inverter.

    Science.gov (United States)

    Kim, Sungyoung; Lim, Taehoon; Sim, Kyoseung; Kim, Hyojoong; Choi, Youngill; Park, Keechan; Pyo, Seungmoon

    2011-05-01

    A photoresponsive organic complementary inverter was fabricated and its light sensing characteristics was studied. An organic circuit was fabricated by integrating p-channel pentacene and n-channel copper hexadecafluorophthalocyanine (F16CuPc) organic thin-film transistors (OTFTs) with a polymeric gate dielectric. The F16CuPc OTFT showed typical n-type characteristics and a strong photoresponse under illumination. Whereas under illumination, the pentacene OTFT showed a relatively weak photoresponse with typical p-type characteristics. The characteristics of the organic electro-optical circuit could be controlled by the incident light intensity, a gate bias, or both. The logic threshold (V(M), when V(IN) = V(OUT)) was reduced from 28.6 V without illumination to 19.9 V at 6.94 mW/cm². By using solely optical or a combination of optical and electrical pulse signals, light sensing was demonstrated in this type of organic circuit, suggesting that the circuit can be potentially used in various optoelectronic applications, including optical sensors, photodetectors and electro-optical transceivers.

  19. Dynamical-Decoupling-Based Quantum Sensing: Floquet Spectroscopy

    Directory of Open Access Journals (Sweden)

    J. E. Lang

    2015-10-01

    Full Text Available Sensing the internal dynamics of individual nuclear spins or clusters of nuclear spins has recently become possible by observing the coherence decay of a nearby electronic spin: the weak magnetic noise is amplified by a periodic, multipulse decoupling sequence. However, it remains challenging to robustly infer underlying atomic-scale structure from decoherence traces in all but the simplest cases. We introduce Floquet spectroscopy as a versatile paradigm for analysis of these experiments and argue that it offers a number of general advantages. In particular, this technique generalizes to more complex situations, offering physical insight in regimes of many-body dynamics, strong coupling, and pulses of finite duration. As there is no requirement for resonant driving, the proposed spectroscopic approach permits physical interpretation of striking, but overlooked, coherence decay features in terms of the form of the avoided crossings of the underlying quasienergy eigenspectrum. This is exemplified by a set of “diamond-shaped” features arising for transverse-field scans in the case of single-spin sensing by nitrogen-vacancy centers in diamond. We also investigate applications for donors in silicon, showing that the resulting tunable interaction strengths offer highly promising future sensors.

  20. Some Insights on Grassland Health Assessment Based on Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dandan Xu

    2015-01-01

    Full Text Available Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  1. Some insights on grassland health assessment based on remote sensing.

    Science.gov (United States)

    Xu, Dandan; Guo, Xulin

    2015-01-29

    Grassland ecosystem is one of the largest ecosystems, which naturally occurs on all continents excluding Antarctica and provides both ecological and economic functions. The deterioration of natural grassland has been attracting many grassland researchers to monitor the grassland condition and dynamics for decades. Remote sensing techniques, which are advanced in dealing with the scale constraints of ecological research and provide temporal information, become a powerful approach of grassland ecosystem monitoring. So far, grassland health monitoring studies have mostly focused on different areas, for example, productivity evaluation, classification, vegetation dynamics, livestock carrying capacity, grazing intensity, natural disaster detecting, fire, climate change, coverage assessment and soil erosion. However, the grassland ecosystem is a complex system which is formed by soil, vegetation, wildlife and atmosphere. Thus, it is time to consider the grassland ecosystem as an entity synthetically and establish an integrated grassland health monitoring system to combine different aspects of the complex grassland ecosystem. In this review, current grassland health monitoring methods, including rangeland health assessment, ecosystem health assessment and grassland monitoring by remote sensing from different aspects, are discussed along with the future directions of grassland health assessment.

  2. Flexible Tactile Sensing Based on Piezoresistive Composites: A Review

    Science.gov (United States)

    Stassi, Stefano; Cauda, Valentina; Canavese, Giancarlo; Pirri, Candido Fabrizio

    2014-01-01

    The large expansion of the robotic field in the last decades has created a growing interest in the research and development of tactile sensing solutions for robot hand and body integration. Piezoresistive composites are one of the most widely employed materials for this purpose, combining simple and low cost preparation with high flexibility and conformability to surfaces, low power consumption, and the use of simple read-out electronics. This work provides a review on the different type of composite materials, classified according to the conduction mechanism and analyzing the physics behind it. In particular piezoresistors, strain gauges, percolative and quantum tunnelling devices are reviewed here, with a perspective overview on the most used filler types and polymeric matrices. A description of the state-of-the-art of the tactile sensor solutions from the point of view of the architecture, the design and the performance is also reviewed, with a perspective outlook on the main promising applications. PMID:24638126

  3. Yb:YAG Lasers for Space Based Remote Sensing

    Science.gov (United States)

    Ewing, J.J.; Fan, T. Y.

    1998-01-01

    Diode pumped solid state lasers will play a prominent role in future remote sensing missions because of their intrinsic high efficiency and low mass. Applications including altimetry, cloud and aerosol measurement, wind velocity measurement by both coherent and incoherent methods, and species measurements, with appropriate frequency converters, all will benefit from a diode pumped primary laser. To date the "gold standard" diode pumped Nd laser has been the laser of choice for most of these concepts. This paper discusses an alternate 1 micron laser, the YB:YAG laser, and its potential relevance for lidar applications. Conceptual design analysis and, to the extent possible at the time of the conference, preliminary experimental data on the performance of a bread board YB:YAG oscillator will be presented. The paper centers on application of YB:YAG for altimetry, but extension to other applications will be discussed.

  4. Underwater Acoustic Matched Field Imaging Based on Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Huichen Yan

    2015-10-01

    Full Text Available Matched field processing (MFP is an effective method for underwater target imaging and localizing, but its performance is not guaranteed due to the nonuniqueness and instability problems caused by the underdetermined essence of MFP. By exploiting the sparsity of the targets in an imaging area, this paper proposes a compressive sensing MFP (CS-MFP model from wave propagation theory by using randomly deployed sensors. In addition, the model’s recovery performance is investigated by exploring the lower bounds of the coherence parameter of the CS dictionary. Furthermore, this paper analyzes the robustness of CS-MFP with respect to the displacement of the sensors. Subsequently, a coherence-excluding coherence optimized orthogonal matching pursuit (CCOOMP algorithm is proposed to overcome the high coherent dictionary problem in special cases. Finally, some numerical experiments are provided to demonstrate the effectiveness of the proposed CS-MFP method.

  5. WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Zhouzhou Liu

    2015-01-01

    Full Text Available For wireless network microseismic monitoring and the problems of low compression ratio and high energy consumption of communication, this paper proposes a segmentation compression algorithm according to the characteristics of the microseismic signals and the compression perception theory (CS used in the transmission process. The algorithm will be collected as a number of nonzero elements of data segmented basis, by reducing the number of combinations of nonzero elements within the segment to improve the accuracy of signal reconstruction, while taking advantage of the characteristics of compressive sensing theory to achieve a high compression ratio of the signal. Experimental results show that, in the quantum chaos immune clone refactoring (Q-CSDR algorithm for reconstruction algorithm, under the condition of signal sparse degree higher than 40, to be more than 0.4 of the compression ratio to compress the signal, the mean square error is less than 0.01, prolonging the network life by 2 times.

  6. Ultrafast Paper Thermometers Based on a Green Sensing Ink.

    Science.gov (United States)

    Tao, Xinglei; Jia, Hanyu; He, Yonglin; Liao, Shenglong; Wang, Yapei

    2017-03-24

    With the use of an ionic liquid as the ultrathermosensitive fluid, a paper thermometer is successfully developed with intrinsic ability of ultrafast response and high stability upon temperature change. The fluidic nature allows the ionic liquid to be easily deposited on paper by pen writing or inkjet printing, affording great promise for large-scale fabrication of low-cost paper sensors. Owing to the advantages of nonvolatilization, excellent continuity and deformability, the thermosensitive ink trapped within the cellulose fibers of paper matrix has no leakage or evaporation at open states, ensuring the excellent stability and repeatability of thermal sensing against arbitrary bending and folding operation. By shortening the heat exchange distance between ionic liquid and samples, it takes only 8 s for the thermometer to reach an electrical equilibrium at a given temperature. Moreover, the paper thermometer can be applied to remotely monitor temperature change with the combination of a wireless communication technology.

  7. Ratiometric glucose sensing based on fluorescent oxygen films and glucose oxidase

    OpenAIRE

    Fengyu Su; Liqiang Zhang; Xiangxing Kong; Fred Lee; Yanqing Tian; Deirdre R. Meldrum

    2017-01-01

    A new two-layer sensor film was constructed for sensing glucose based on glucose oxidase and oxygen sensing material. The first layer of film containing the oxygen sensor and intra-reference material was polymerized, then the second layer of glucose oxidase and glutaraldehyde was formed on the oxygen sensor layer. The two-layer sensor film has a resolution up to 0.05 mM and a detection range from 0 to 5 mM to glucose. The effects of pH and temperature on the sensing performance were systemati...

  8. Ultrafast Laser-Based Spectroscopy and Sensing: Applications in LIBS, CARS, and THz Spectroscopy

    Science.gov (United States)

    Leahy-Hoppa, Megan R.; Miragliotta, Joseph; Osiander, Robert; Burnett, Jennifer; Dikmelik, Yamac; McEnnis, Caroline; Spicer, James B.

    2010-01-01

    Ultrafast pulsed lasers find application in a range of spectroscopy and sensing techniques including laser induced breakdown spectroscopy (LIBS), coherent Raman spectroscopy, and terahertz (THz) spectroscopy. Whether based on absorption or emission processes, the characteristics of these techniques are heavily influenced by the use of ultrafast pulses in the signal generation process. Depending on the energy of the pulses used, the essential laser interaction process can primarily involve lattice vibrations, molecular rotations, or a combination of excited states produced by laser heating. While some of these techniques are currently confined to sensing at close ranges, others can be implemented for remote spectroscopic sensing owing principally to the laser pulse duration. We present a review of ultrafast laser-based spectroscopy techniques and discuss the use of these techniques to current and potential chemical and environmental sensing applications. PMID:22399883

  9. Ultrafast Laser-Based Spectroscopy and Sensing: Applications in LIBS, CARS, and THz Spectroscopy

    Directory of Open Access Journals (Sweden)

    Megan R. Leahy-Hoppa

    2010-04-01

    Full Text Available Ultrafast pulsed lasers find application in a range of spectroscopy and sensing techniques including laser induced breakdown spectroscopy (LIBS, coherent Raman spectroscopy, and terahertz (THz spectroscopy. Whether based on absorption or emission processes, the characteristics of these techniques are heavily influenced by the use of ultrafast pulses in the signal generation process. Depending on the energy of the pulses used, the essential laser interaction process can primarily involve lattice vibrations, molecular rotations, or a combination of excited states produced by laser heating. While some of these techniques are currently confined to sensing at close ranges, others can be implemented for remote spectroscopic sensing owing principally to the laser pulse duration. We present a review of ultrafast laser-based spectroscopy techniques and discuss the use of these techniques to current and potential chemical and environmental sensing applications.

  10. Apollo 16 landing site: Summary of earth based remote sensing data, part W

    Science.gov (United States)

    Zisk, S. H.; Masursky, H.; Milton, D. J.; Schaber, G. G.; Shorthill, R. W.; Thompson, T. W.

    1972-01-01

    Infrared and radar studies of the Apollo 16 landing site are summarized. Correlations and comparisons between earth based remote sensing data, IR observations, and other data are discussed in detail. Remote sensing studies were devoted to solving two problems: (1) determining the physical difference between Cayley and Descartes geologic units near the landing site; and (2) determining the nature of the bright unit of Descartes mountain material.

  11. Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure

    OpenAIRE

    Tang, Yongsheng; Wu, Zhishen

    2016-01-01

    Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced p...

  12. Multiple Fano-Like MIM Plasmonic Structure Based on Triangular Resonator for Refractive Index Sensing

    OpenAIRE

    Jankovic, Nikolina; Cselyuszka, Norbert

    2018-01-01

    In this paper, we present a Fano metal-insulator-metal (MIM) structure based on an isosceles triangular cavity resonator for refractive index sensing applications. Due to the specific feeding scheme and asymmetry introduced in the triangular cavity, the resonator exhibits four sharp Fano-like resonances. The behavior of the structure is analyzed in detail and its sensing capabilities demonstrated through the responses for various refractive indices. The results show that the sensor has very g...

  13. Relationships between soil-based management zones and canopy sensing for corn nitrogen management

    Science.gov (United States)

    Integrating soil-based management zones (MZ) with crop-based active canopy sensors to direct spatially variable nitrogen (N) applications has been proposed for improving N fertilizer management of corn (Zea mays L.). Analyses are needed to evaluate relationships between canopy sensing and soil-based...

  14. Hard Fusion Based Spectrum Sensing over Mobile Fading Channels in Cognitive Vehicular Networks.

    Science.gov (United States)

    Qian, Xiaomin; Hao, Li; Ni, Dadong; Tran, Quang Thanh

    2018-02-06

    An explosive growth in vehicular wireless applications gives rise to spectrum resource starvation. Cognitive radio has been used in vehicular networks to mitigate the impending spectrum starvation problem by allowing vehicles to fully exploit spectrum opportunities unoccupied by licensed users. Efficient and effective detection of licensed user is a critical issue to realize cognitive radio applications. However, spectrum sensing in vehicular environments is a very challenging task due to vehicle mobility. For instance, vehicle mobility has a large effect on the wireless channel, thereby impacting the detection performance of spectrum sensing. Thus, gargantuan efforts have been made in order to analyze the fading properties of mobile radio channel in vehicular environments. Indeed, numerous studies have demonstrated that the wireless channel in vehicular environments can be characterized by a temporally correlated Rayleigh fading. In this paper, we focus on energy detection for spectrum sensing and a counting rule for cooperative sensing based on Neyman-Pearson criteria. Further, we go into the effect of the sensing and reporting channel conditions on the sensing performance under the temporally correlated Rayleigh channel. For local and cooperative sensing, we derive some alternative expressions for the average probability of misdetection. The pertinent numerical and simulating results are provided to further validate our theoretical analyses under a variety of scenarios.

  15. Thermal Remote Sensing with Uav-Based Workflows

    Science.gov (United States)

    Boesch, R.

    2017-08-01

    Climate change will have a significant influence on vegetation health and growth. Predictions of higher mean summer temperatures and prolonged summer draughts may pose a threat to agriculture areas and forest canopies. Rising canopy temperatures can be an indicator of plant stress because of the closure of stomata and a decrease in the transpiration rate. Thermal cameras are available for decades, but still often used for single image analysis, only in oblique view manner or with visual evaluations of video sequences. Therefore remote sensing using a thermal camera can be an important data source to understand transpiration processes. Photogrammetric workflows allow to process thermal images similar to RGB data. But low spatial resolution of thermal cameras, significant optical distortion and typically low contrast require an adapted workflow. Temperature distribution in forest canopies is typically completely unknown and less distinct than for urban or industrial areas, where metal constructions and surfaces yield high contrast and sharp edge information. The aim of this paper is to investigate the influence of interior camera orientation, tie point matching and ground control points on the resulting accuracy of bundle adjustment and dense cloud generation with a typically used photogrammetric workflow for UAVbased thermal imagery in natural environments.

  16. Research on Coal Exploration Technology Based on Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Dong Xiao

    2016-01-01

    Full Text Available Coal is the main source of energy. In China and Vietnam, coal resources are very rich, but the exploration level is relatively low. This is mainly caused by the complicated geological structure, the low efficiency, the related damage, and other bad situations. To this end, we need to make use of some advanced technologies to guarantee the resource exploration is implemented smoothly and orderly. Numerous studies show that remote sensing technology is an effective way in coal exploration and measurement. In this paper, we try to measure the distribution and reserves of open-air coal area through satellite imagery. The satellite picture of open-air coal mining region in Quang Ninh Province of Vietnam was collected as the experimental data. Firstly, the ENVI software is used to eliminate satellite imagery spectral interference. Then, the image classification model is established by the improved ELM algorithm. Finally, the effectiveness of the improved ELM algorithm is verified by using MATLAB simulations. The results show that the accuracies of the testing set reach 96.5%. And it reaches 83% of the image discernment precision compared with the same image from Google.

  17. Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources

    Directory of Open Access Journals (Sweden)

    Paweł Kędzia

    2015-12-01

    Full Text Available Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources Lexical resources can be applied in many different Natural Language Engineering tasks, but the most fundamental task is the recognition of word senses used in text contexts. The problem is difficult, not yet fully solved and different lexical resources provided varied support for it. Polish CLARIN lexical semantic resources are based on the plWordNet — a very large wordnet for Polish — as a central structure which is a basis for linking together several resources of different types. In this paper, several Word Sense Disambiguation (henceforth WSD methods developed for Polish that utilise plWordNet are discussed. Textual sense descriptions in the traditional lexicon can be compared with text contexts using Lesk’s algorithm in order to find best matching senses. In the case of a wordnet, lexico-semantic relations provide the main description of word senses. Thus, first, we adapted and applied to Polish a WSD method based on the Page Rank. According to it, text words are mapped on their senses in the plWordNet graph and Page Rank algorithm is run to find senses with the highest scores. The method presents results lower but comparable to those reported for English. The error analysis showed that the main problems are: fine grained sense distinctions in plWordNet and limited number of connections between words of different parts of speech. In the second approach plWordNet expanded with the mapping onto the SUMO ontology concepts was used. Two scenarios for WSD were investigated: two step disambiguation and disambiguation based on combined networks of plWordNet and SUMO. In the former scenario, words are first assigned SUMO concepts and next plWordNet senses are disambiguated. In latter, plWordNet and SUMO are combined in one large network used next for the disambiguation of senses. The additional knowledge sources used in WSD improved the performance

  18. Array-based sensing using nanoparticles: an alternative approach for cancer diagnostics.

    Science.gov (United States)

    Le, Ngoc D B; Yazdani, Mahdieh; Rotello, Vincent M

    2014-07-01

    Array-based sensing using nanoparticles (NPs) provides an attractive alternative to specific biomarker-focused strategies for cancer diagnosis. The physical and chemical properties of NPs provide both the recognition and transduction capabilities required for biosensing. Array-based sensors utilize a combined response from the interactions between sensors and analytes to generate a distinct pattern (fingerprint) for each analyte. These interactions can be the result of either the combination of multiple specific biomarker recognition (specific binding) or multiple selective binding responses, known as chemical nose sensing. The versatility of the latter array-based sensing using NPs can facilitate the development of new personalized diagnostic methodologies in cancer diagnostics, a necessary evolution in the current healthcare system to better provide personalized treatments. This review will describe the basic principle of array-based sensors, along with providing examples of both invasive and noninvasive samples used in cancer diagnosis.

  19. Pressure sensing element based on the BN-graphene-BN heterostructure

    Science.gov (United States)

    Li, Mengwei; Wu, Chenggen; Zhao, Shiliang; Deng, Tao; Wang, Junqiang; Liu, Zewen; Wang, Li; Wang, Gao

    2018-04-01

    In this letter, we report a pressure sensing element based on the graphene-boron nitride (BN) heterostructure. The heterostructure consists of monolayer graphene sandwiched between two layers of vertically stacked dielectric BN nanofilms. The BN layers were used to protect the graphene layer from oxidation and pollution. Pressure tests were performed to investigate the characteristics of the BN-graphene-BN pressure sensing element. A sensitivity of 24.85 μV/V/mmHg is achieved in the pressure range of 130-180 kPa. After exposing the BN-graphene-BN pressure sensing element to the ambient environment for 7 days, the relative resistance change in the pressure sensing element is only 3.1%, while that of the reference open-faced graphene device without the BN protection layers is 15.7%. Thus, this strategy is promising for fabricating practical graphene pressure sensors with improved performance and stability.

  20. Ratiometric glucose sensing based on fluorescent oxygen films and glucose oxidase

    Directory of Open Access Journals (Sweden)

    Fengyu Su

    2017-06-01

    Full Text Available A new two-layer sensor film was constructed for sensing glucose based on glucose oxidase and oxygen sensing material. The first layer of film containing the oxygen sensor and intra-reference material was polymerized, then the second layer of glucose oxidase and glutaraldehyde was formed on the oxygen sensor layer. The two-layer sensor film has a resolution up to 0.05 mM and a detection range from 0 to 5 mM to glucose. The effects of pH and temperature on the sensing performance were systematically investigated. The selective detection of glucose among other monosaccharides, such as fructose, mannose and galactose indicated that the sensing film has excellent selectivity. The prepared sensor was successfully applied for glucose sample detection of glucose concentration in artificial tears. Keywords: Glucose sensor, Glucose oxidase, Fluorescence, Oxygen film, Diabetes

  1. Cluster-based spectrum sensing for cognitive radios with imperfect channel to cluster-head

    KAUST Repository

    Ben Ghorbel, Mahdi

    2012-04-01

    Spectrum sensing is considered as the first and main step for cognitive radio systems to achieve an efficient use of spectrum. Cooperation and clustering among cognitive radio users are two techniques that can be employed with spectrum sensing in order to improve the sensing performance by reducing miss-detection and false alarm. In this paper, within the framework of a clustering-based cooperative spectrum sensing scheme, we study the effect of errors in transmitting the local decisions from the secondary users to the cluster heads (or the fusion center), while considering non-identical channel conditions between the secondary users. Closed-form expressions for the global probabilities of detection and false alarm at the cluster head are derived. © 2012 IEEE.

  2. Cluster-based spectrum sensing for cognitive radios with imperfect channel to cluster-head

    KAUST Repository

    Ben Ghorbel, Mahdi; Nam, Haewoon; Alouini, Mohamed-Slim

    2012-01-01

    Spectrum sensing is considered as the first and main step for cognitive radio systems to achieve an efficient use of spectrum. Cooperation and clustering among cognitive radio users are two techniques that can be employed with spectrum sensing in order to improve the sensing performance by reducing miss-detection and false alarm. In this paper, within the framework of a clustering-based cooperative spectrum sensing scheme, we study the effect of errors in transmitting the local decisions from the secondary users to the cluster heads (or the fusion center), while considering non-identical channel conditions between the secondary users. Closed-form expressions for the global probabilities of detection and false alarm at the cluster head are derived. © 2012 IEEE.

  3. A simple self-restored fiber Bragg grating (FBG)-based passive sensing ring network

    International Nuclear Information System (INIS)

    Yeh, Chien-Hung; Chow, Chi-Wai; Wang, Chia-Husan; Shih, Fu-Yuan; Wu, Yu-Fu; Chi, Sien

    2009-01-01

    In this investigation, we propose and experimentally investigate a simple self-restored fiber Bragg grating (FBG)-based sensor ring system. This proposed multi-ring passive sensing architecture does not require active components in the network. In this experiment, the network survivability and capacity for the multi-point sensor systems are also enhanced. Besides, the tunable laser source (TLS) is adopted in a central office (CO) for FBG sensing. The survivability of an eight-point FBG sensor is examined and analyzed. It is cost effective since the sensing system is entirely centralized in the CO. Experimental results show that the proposed system can enhance the reliability of the FBG sensing network for large-scale and multi-point architecture. (rapid communication)

  4. Traffic Management for Emergency Vehicle Priority Based on Visual Sensing

    Directory of Open Access Journals (Sweden)

    Kapileswar Nellore

    2016-11-01

    Full Text Available Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence, therefore the green light sequence is determined without taking the presence of the emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic. The approach combines the measurement of the distance between the emergency vehicle and an intersection using visual sensing methods, vehicle counting and time sensitive alert transmission within the sensor network. The distance between the emergency vehicle and the intersection is calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance techniques. The experimental results have shown that the Euclidean distance outperforms other distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle information, it is very important to have a Medium Access Control (MAC protocol to deliver the emergency vehicle information to the Traffic Management Center (TMC with less delay. Then only the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the transmission delay for emergency messages. We have modified the medium access procedure used in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p and the proposed PE-MAC is analysed in detail. The NS-2

  5. Traffic Management for Emergency Vehicle Priority Based on Visual Sensing.

    Science.gov (United States)

    Nellore, Kapileswar; Hancke, Gerhard P

    2016-11-10

    Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence, therefore the green light sequence is determined without taking the presence of the emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic. The approach combines the measurement of the distance between the emergency vehicle and an intersection using visual sensing methods, vehicle counting and time sensitive alert transmission within the sensor network. The distance between the emergency vehicle and the intersection is calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance techniques. The experimental results have shown that the Euclidean distance outperforms other distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle information, it is very important to have a Medium Access Control (MAC) protocol to deliver the emergency vehicle information to the Traffic Management Center (TMC) with less delay. Then only the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the transmission delay for emergency messages. We have modified the medium access procedure used in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p and the proposed PE-MAC is analysed in detail. The NS-2 simulation results

  6. Agricultural biomass monitoring on watersheds based on remotely sensed data.

    Science.gov (United States)

    Tamás, János; Nagy, Attila; Fehér, János

    2015-01-01

    There is a close quality relationship between the harmful levels of all three drought indicator groups (meteorological, hydrological and agricultural). However, the numerical scale of the relationships between them is unclear and the conversion of indicators is unsolved. Different areas or an area with different forms of drought cannot be compared. For example, from the evaluation of meteorological drought using the standardized precipitation index (SPI) values of a river basin, it cannot be stated how many tonnes of maize will be lost during a given drought period. A reliable estimated rate of yield loss would be very important information for the planned interventions (i.e. by farmers or river basin management organisations) in terms of time and cost. The aim of our research project was to develop a process which could provide information for estimating relevant drought indexes and drought related yield losses more effectively from remotely sensed spectral data and to determine the congruency of data derived from spectral data and from field measurements. The paper discusses a new calculation method, which provides early information on physical implementation of drought risk levels. The elaborated method provides improvement in setting up a complex drought monitoring system, which could assist hydrologists, meteorologists and farmers to predict and more precisely quantify the yield loss and the role of vegetation in the hydrological cycle. The results also allow the conversion of different-purpose drought indices, such as meteorological, agricultural and hydrological ones, as well as allow more water-saving agricultural land use alternatives to be planned in the river basins.

  7. Micro- and nanostructured sol-gel-based materials for optical chemical sensing (2005–2015)

    International Nuclear Information System (INIS)

    Barczak, Mariusz; McDonagh, Colette; Wencel, Dorota

    2016-01-01

    This review (with 172 references) highlights the progress made in the past 10 years in silica sol-gel-based materials for use in optical chemical sensing. Following an introduction, the processes leading to the sol-gel-based and ormosil materials, their printability and methods for characterisation are discussed. Then various classes of optical sensors, with a focus on sensors for pH values, oxygen, carbon dioxide, ammonia (also in dissolved form), and heavy metal ions are described. A further section covers nanoparticle-based optical sensors mainly for use in intracellular sensing of the above species. Recent developments in this area are also emphasised and future trends discussed. (author)

  8. An Interactive Web-Based Analysis Framework for Remote Sensing Cloud Computing

    Science.gov (United States)

    Wang, X. Z.; Zhang, H. M.; Zhao, J. H.; Lin, Q. H.; Zhou, Y. C.; Li, J. H.

    2015-07-01

    Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users' private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook. Users can write

  9. Highly Sensitive Temperature Sensors Based on Fiber-Optic PWM and Capacitance Variation Using Thermochromic Sensing Membrane

    Directory of Open Access Journals (Sweden)

    Md. Rajibur Rahaman Khan

    2016-07-01

    Full Text Available In this paper, we propose a temperature/thermal sensor that contains a Rhodamine-B sensing membrane. We applied two different sensing methods, namely, fiber-optic pulse width modulation (PWM and an interdigitated capacitor (IDC-based temperature sensor to measure the temperature from 5 °C to 100 °C. To the best of our knowledge, the fiber-optic PWM-based temperature sensor is reported for the first time in this study. The proposed fiber-optic PWM temperature sensor has good sensing ability; its sensitivity is ~3.733 mV/°C. The designed temperature-sensing system offers stable sensing responses over a wide dynamic range, good reproducibility properties with a relative standard deviation (RSD of ~0.021, and the capacity for a linear sensing response with a correlation coefficient of R2 ≈ 0.992 over a wide sensing range. In our study, we also developed an IDC temperature sensor that is based on the capacitance variation principle as the IDC sensing element is heated. We compared the performance of the proposed temperature-sensing systems with different fiber-optic temperature sensors (which are based on the fiber-optic wavelength shift method, the long grating fiber-optic Sagnac loop, and probe type fiber-optics in terms of sensitivity, dynamic range, and linearity. We observed that the proposed sensing systems have better sensing performance than the above-mentioned sensing system.

  10. Building and Using Large Common Sense Knowledge Bases

    National Research Council Canada - National Science Library

    Forbus, Kenneth D

    2001-01-01

    .... We developed techniques that enabled realistic-sized situations to be compared, for automatically extracting and extending cases dynamically based on task constraints from a general purpose knowledge...

  11. The Physics of Compressive Sensing and the Gradient-Based Recovery Algorithms

    OpenAIRE

    Dai, Qi; Sha, Wei

    2009-01-01

    The physics of compressive sensing (CS) and the gradient-based recovery algorithms are presented. First, the different forms for CS are summarized. Second, the physical meanings of coherence and measurement are given. Third, the gradient-based recovery algorithms and their geometry explanations are provided. Finally, we conclude the report and give some suggestion for future work.

  12. Poly (N-isopropylacrylamide Microgel-Based Optical Devices for Sensing and Biosensing

    Directory of Open Access Journals (Sweden)

    Molla R. Islam

    2014-05-01

    Full Text Available Responsive polymer-based materials have found numerous applications due to their ease of synthesis and the variety of stimuli that they can be made responsive to. In this review, we highlight the group’s efforts utilizing thermoresponsive poly (N-isopropylacrylamide (pNIPAm microgel-based optical devices for various sensing and biosensing applications.

  13. Statistical inference for remote sensing-based estimates of net deforestation

    Science.gov (United States)

    Ronald E. McRoberts; Brian F. Walters

    2012-01-01

    Statistical inference requires expression of an estimate in probabilistic terms, usually in the form of a confidence interval. An approach to constructing confidence intervals for remote sensing-based estimates of net deforestation is illustrated. The approach is based on post-classification methods using two independent forest/non-forest classifications because...

  14. Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

    Science.gov (United States)

    Ren, Shengwei; Zhang, Li; Zhang, Shibing

    2016-10-01

    Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

  15. Meat and Fish Freshness Inspection System Based on Odor Sensing

    OpenAIRE

    Hasan, Najam ul; Ejaz, Naveed; Ejaz, Waleed; Kim, Hyung Seok

    2012-01-01

    We propose a method for building a simple electronic nose based on commercially available sensors used to sniff in the market and identify spoiled/contaminated meat stocked for sale in butcher shops. Using a metal oxide semiconductor-based electronic nose, we measured the smell signature from two of the most common meat foods (beef and fish) stored at room temperature. Food samples were divided into two groups: fresh beef with decayed fish and fresh fish with decayed beef. The prime objective...

  16. A Robust FLOM Based Spectrum Sensing Scheme under Middleton Class A Noise in IoT

    Directory of Open Access Journals (Sweden)

    Enwei Xu

    2017-01-01

    Full Text Available Accessibility to remote users in dynamic environment, high spectrum utilization, and no spectrum purchase make Cognitive Radio (CR a feasible solution of wireless communications in the Internet of Things (IoT. Reliable spectrum sensing becomes the prerequisite for the establishment of communication between IoT-capable objects. Considering the application environment, spectrum sensing not only has to cope with man-made impulsive noises but also needs to overcome noise fluctuations. In this paper, we study the Fractional Lower Order Moments (FLOM based spectrum sensing method under Middleton Class A noise and incorporate a Noise Power Estimation (NPE module into the sensing system to deal with the issue of noise uncertainty. Moreover, the NPE process does not need noise-only samples. The analytical expressions of the probabilities of detection and the probability of false alarm are derived. The impact on sensing performance of the parameters of the NPE module is also analyzed. The theoretical analysis and simulation results show that our proposed sensing method achieves a satisfactory performance at low SNR.

  17. Event-based Sensing for Space Situational Awareness

    Science.gov (United States)

    Cohen, G.; Afshar, S.; van Schaik, A.; Wabnitz, A.; Bessell, T.; Rutten, M.; Morreale, B.

    A revolutionary type of imaging device, known as a silicon retina or event-based sensor, has recently been developed and is gaining in popularity in the field of artificial vision systems. These devices are inspired by a biological retina and operate in a significantly different way to traditional CCD-based imaging sensors. While a CCD produces frames of pixel intensities, an event-based sensor produces a continuous stream of events, each of which is generated when a pixel detects a change in log light intensity. These pixels operate asynchronously and independently, producing an event-based output with high temporal resolution. There are also no fixed exposure times, allowing these devices to offer a very high dynamic range independently for each pixel. Additionally, these devices offer high-speed, low power operation and a sparse spatiotemporal output. As a consequence, the data from these sensors must be interpreted in a significantly different way to traditional imaging sensors and this paper explores the advantages this technology provides for space imaging. The applicability and capabilities of event-based sensors for SSA applications are demonstrated through telescope field trials. Trial results have confirmed that the devices are capable of observing resident space objects from LEO through to GEO orbital regimes. Significantly, observations of RSOs were made during both day-time and nighttime (terminator) conditions without modification to the camera or optics. The event based sensor’s ability to image stars and satellites during day-time hours offers a dramatic capability increase for terrestrial optical sensors. This paper shows the field testing and validation of two different architectures of event-based imaging sensors. An eventbased sensor’s asynchronous output has an intrinsically low data-rate. In addition to low-bandwidth communications requirements, the low weight, low-power and high-speed make them ideally suitable to meeting the demanding

  18. Ontology-based classification of remote sensing images using spectral rules

    Science.gov (United States)

    Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

    2017-05-01

    Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

  19. Remote sensing of high-latitude ionization profiles by ground-based and spaceborne instrumentation

    International Nuclear Information System (INIS)

    Vondrak, R.R.

    1981-01-01

    Ionospheric specification and modeling are now largely based on data provided by active remote sensing with radiowave techniques (ionosondes, incoherent-scatter radars, and satellite beacons). More recently, passive remote sensing techniques have been developed that can be used to monitor quantitatively the spatial distribution of high-latitude E-region ionization. These passive methods depend on the measurement, or inference, of the energy distribution of precipitating kilovolt electrons, the principal source of the nighttime E-region at high latitudes. To validate these techniques, coordinated measurements of the auroral ionosphere have been made with the Chatanika incoherent-scatter radar and a variety of ground-based and spaceborne sensors

  20. Biomedical and sensing applications of a multi-mode biodegradable phosphate-based optical fiber

    Science.gov (United States)

    Podrazky, Ondřej; Peterka, Pavel; Vytykáčová, SoÅa.; Proboštová, Jana; Kuneš, Martin; Lyutakov, Oleksiy; Ceci-Ginistrelli, Edoardo; Pugliese, Diego; Boetti, Nadia G.; Janner, Davide; Milanese, Daniel

    2018-02-01

    We report on the employment of a biodegradable phosphate-based optical fiber as a pH sensing probe in physiological environment. The phosphate-based optical fiber preform was fabricated by the rod-in-tube technique. The fiber biodegradability was first tested in-vitro and then its biodegradability and toxicity were tested in-vivo. Optical probes for pH sensing were prepared by the immobilization of a fluorescent dye on the fiber tip by a sol-gel method. The fluorescence response of the pH-sensor was measured as a ratio of the emission intensities at the excitation wavelengths of 405 and 450 nm.

  1. Meat and fish freshness inspection system based on odor sensing.

    Science.gov (United States)

    Najam ul Hasan; Ejaz, Naveed; Ejaz, Waleed; Kim, Hyung Seok

    2012-11-09

    We propose a method for building a simple electronic nose based on commercially available sensors used to sniff in the market and identify spoiled/contaminated meat stocked for sale in butcher shops. Using a metal oxide semiconductor-based electronic nose, we measured the smell signature from two of the most common meat foods (beef and fish) stored at room temperature. Food samples were divided into two groups: fresh beef with decayed fish and fresh fish with decayed beef. The prime objective was to identify the decayed item using the developed electronic nose. Additionally, we tested the electronic nose using three pattern classification algorithms (artificial neural network, support vector machine and k-nearest neighbor), and compared them based on accuracy, sensitivity, and specificity. The results demonstrate that the k-nearest neighbor algorithm has the highest accuracy.

  2. Meat and Fish Freshness Inspection System Based on Odor Sensing

    Directory of Open Access Journals (Sweden)

    Hyung Seok Kim

    2012-11-01

    Full Text Available We propose a method for building a simple electronic nose based on commercially available sensors used to sniff in the market and identify spoiled/contaminated meat stocked for sale in butcher shops. Using a metal oxide semiconductor-based electronic nose, we measured the smell signature from two of the most common meat foods (beef and fish stored at room temperature. Food samples were divided into two groups: fresh beef with decayed fish and fresh fish with decayed beef. The prime objective was to identify the decayed item using the developed electronic nose. Additionally, we tested the electronic nose using three pattern classification algorithms (artificial neural network, support vector machine and k-nearest neighbor, and compared them based on accuracy, sensitivity, and specificity. The results demonstrate that the k-nearest neighbor algorithm has the highest accuracy.

  3. Signal Recovery in Compressive Sensing via Multiple Sparsifying Bases

    DEFF Research Database (Denmark)

    Wijewardhana, U. L.; Belyaev, Evgeny; Codreanu, M.

    2017-01-01

    is sparse is the key assumption utilized by such algorithms. However, the basis in which the signal is the sparsest is unknown for many natural signals of interest. Instead there may exist multiple bases which lead to a compressible representation of the signal: e.g., an image is compressible in different...... wavelet transforms. We show that a significant performance improvement can be achieved by utilizing multiple estimates of the signal using sparsifying bases in the context of signal reconstruction from compressive samples. Further, we derive a customized interior-point method to jointly obtain multiple...... estimates of a 2-D signal (image) from compressive measurements utilizing multiple sparsifying bases as well as the fact that the images usually have a sparse gradient....

  4. Reconfigurable pipelined sensing for image-based control

    NARCIS (Netherlands)

    Medina, R.; Stuijk, S.; Goswami, D.; Basten, T.

    2016-01-01

    Image-based control systems are becoming common in domains such as robotics, healthcare and industrial automation. Coping with a long sample period because of the latency of the image processing algorithm is an open challenge. Modern multi-core platforms allow to address this challenge by pipelining

  5. Model-based remote sensing algorithms for particulate organic carbon

    Indian Academy of Sciences (India)

    PCA algorithms based on the first three, four, and five modes accounted for 90, 95, and 98% of total variance and yielded significant correlations with POC with 2 = 0.89, 0.92, and 0.93. These full waveband approaches provided robust estimates of POC in various water types. Three different analyses (root mean square ...

  6. Compact multichannel MEMS based spectrometer for FBG sensing

    DEFF Research Database (Denmark)

    Ganziy, Denis; Rose, Bjarke; Bang, Ole

    2017-01-01

    We propose a novel type of compact multichannel MEMS based spectrometer, where we replace the linear detector with a Digital Micromirror Device (DMD). The DMD is typically cheaper and has better pixel sampling than an InGaAs detector used in the 1550 nm range, which leads to cost reduction...

  7. CoP Sensing Framework on Web-Based Environment

    Science.gov (United States)

    Mustapha, S. M. F. D. Syed

    The Web technologies and Web applications have shown similar high growth rate in terms of daily usages and user acceptance. The Web applications have not only penetrated in the traditional domains such as education and business but have also encroached into areas such as politics, social, lifestyle, and culture. The emergence of Web technologies has enabled Web access even to the person on the move through PDAs or mobile phones that are connected using Wi-Fi, HSDPA, or other communication protocols. These two phenomena are the inducement factors toward the need of building Web-based systems as the supporting tools in fulfilling many mundane activities. In doing this, one of the many focuses in research has been to look at the implementation challenges in building Web-based support systems in different types of environment. This chapter describes the implementation issues in building the community learning framework that can be supported on the Web-based platform. The Community of Practice (CoP) has been chosen as the community learning theory to be the case study and analysis as it challenges the creativity of the architectural design of the Web system in order to capture the presence of learning activities. The details of this chapter describe the characteristics of the CoP to understand the inherent intricacies in modeling in the Web-based environment, the evidences of CoP that need to be traced automatically in a slick manner such that the evidence-capturing process is unobtrusive, and the technologies needed to embrace a full adoption of Web-based support system for the community learning framework.

  8. Research on distributed optical fiber sensing data processing method based on LabVIEW

    Science.gov (United States)

    Li, Zhonghu; Yang, Meifang; Wang, Luling; Wang, Jinming; Yan, Junhong; Zuo, Jing

    2018-01-01

    The pipeline leak detection and leak location problem have gotten extensive attention in the industry. In this paper, the distributed optical fiber sensing system is designed based on the heat supply pipeline. The data processing method of distributed optical fiber sensing based on LabVIEW is studied emphatically. The hardware system includes laser, sensing optical fiber, wavelength division multiplexer, photoelectric detector, data acquisition card and computer etc. The software system is developed using LabVIEW. The software system adopts wavelet denoising method to deal with the temperature information, which improved the SNR. By extracting the characteristic value of the fiber temperature information, the system can realize the functions of temperature measurement, leak location and measurement signal storage and inquiry etc. Compared with traditional negative pressure wave method or acoustic signal method, the distributed optical fiber temperature measuring system can measure several temperatures in one measurement and locate the leak point accurately. It has a broad application prospect.

  9. Pulse Based Time-of-Flight Range Sensing.

    Science.gov (United States)

    Sarbolandi, Hamed; Plack, Markus; Kolb, Andreas

    2018-05-23

    Pulse-based Time-of-Flight (PB-ToF) cameras are an attractive alternative range imaging approach, compared to the widely commercialized Amplitude Modulated Continuous-Wave Time-of-Flight (AMCW-ToF) approach. This paper presents an in-depth evaluation of a PB-ToF camera prototype based on the Hamamatsu area sensor S11963-01CR. We evaluate different ToF-related effects, i.e., temperature drift, systematic error, depth inhomogeneity, multi-path effects, and motion artefacts. Furthermore, we evaluate the systematic error of the system in more detail, and introduce novel concepts to improve the quality of range measurements by modifying the mode of operation of the PB-ToF camera. Finally, we describe the means of measuring the gate response of the PB-ToF sensor and using this information for PB-ToF sensor simulation.

  10. Glucose sensing based on Pt-MWCNT and MWCNT

    Science.gov (United States)

    Aryasomayajula, Lavanya; Xie, Jining; Wang, Shouyan; Varadan, Vijay K.

    2007-04-01

    It is known that multi walled carbon nanotubes (MWCNTs) is an excellent materials for biosensing applications and with the introduction of Pt nanoparticles (Pt-MWCNTs) of about 3nm in diameter in MWCNTs greatly increases the current sensitivity and also the signal to noise ratio. We fabricated the CNT- based glucose sensor by immobilization the bio enzyme, glucose oxidase (GoX), on the Pt-MWCNT and electrode were prepared. The sensor has been tested effectively for both the abnormal blood glucose levels- greater than 6.9 mM and less than 3.5 mM which are the prediabetic and diabetic glucose levels, respectively. The current signal obtained from the Pt-MWCNT was much higher compared to the MWCNT based sensors.

  11. Verification-Based Interval-Passing Algorithm for Compressed Sensing

    OpenAIRE

    Wu, Xiaofu; Yang, Zhen

    2013-01-01

    We propose a verification-based Interval-Passing (IP) algorithm for iteratively reconstruction of nonnegative sparse signals using parity check matrices of low-density parity check (LDPC) codes as measurement matrices. The proposed algorithm can be considered as an improved IP algorithm by further incorporation of the mechanism of verification algorithm. It is proved that the proposed algorithm performs always better than either the IP algorithm or the verification algorithm. Simulation resul...

  12. Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin

    Directory of Open Access Journals (Sweden)

    William Taube Navaraj

    2017-09-01

    Full Text Available This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs based hardware-implementable neural network (HNN approach for tactile data processing in electronic skin (e-skin. The viability of Si nanowires (NWs as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

  13. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

    OpenAIRE

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history si...

  14. Six-Port Based Interferometry for Precise Radar and Sensing Applications

    Directory of Open Access Journals (Sweden)

    Alexander Koelpin

    2016-09-01

    Full Text Available Microwave technology plays a more important role in modern industrial sensing applications. Pushed by the significant progress in monolithic microwave integrated circuit technology over the past decades, complex sensing systems operating in the microwave and even millimeter-wave range are available for reasonable costs combined with exquisite performance. In the context of industrial sensing, this stimulates new approaches for metrology based on microwave technology. An old measurement principle nearly forgotten over the years has recently gained more and more attention in both academia and industry: the six-port interferometer. This paper reviews the basic concept, investigates promising applications in remote, as well as contact-based sensing and compares the system with state-of-the-art metrology. The significant advantages will be discussed just as the limitations of the six-port architecture. Particular attention will be paid to impairment effects and non-ideal behavior, as well as compensation and linearization concepts. It will be shown that in application fields, like remote distance sensing, precise alignment measurements, as well as interferometrically-evaluated mechanical strain analysis, the six-port architecture delivers extraordinary measurement results combined with high measurement data update rates for reasonable system costs. This makes the six-port architecture a promising candidate for industrial metrology.

  15. Simultaneous detection of lactate and glucose by integrated printed circuit board based array sensing chip

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xuelian [Institute for Clean Energy and Advanced Materials, Southwest University, Chongqing 400715 (China); School of Chemistry and Chemical Engineering, Southwest University, Chongqing 400715 (China); Zang, Jianfeng [Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708 (United States); Liu, Yingshuai; Lu, Zhisong [Institute for Clean Energy and Advanced Materials, Southwest University, Chongqing 400715 (China); Li, Qing, E-mail: Qli@swu.edu.cn [School of Chemistry and Chemical Engineering, Southwest University, Chongqing 400715 (China); Li, Chang Ming, E-mail: ecmli@swu.edu.cn [Institute for Clean Energy and Advanced Materials, Southwest University, Chongqing 400715 (China)

    2013-04-10

    Highlights: ► An integrated printed circuit board (PCB) based array sensing chip was developed. ► Simultaneous detection of lactate and glucose in serum has been demonstrated. ► The array electronic biochip has high signal to noise ratio and high sensitivity. ► Additional electrodes were designed on the chip to correct interferences. -- Abstract: An integrated printed circuit board (PCB) based array sensing chip was developed to simultaneously detect lactate and glucose in mouse serum. The novelty of the chip relies on a concept demonstration of inexpensive high-throughput electronic biochip, a chip design for high signal to noise ratio and high sensitivity by construction of positively charged chitosan/redox polymer Polyvinylimidazole-Os (PVI-Os)/carbon nanotube (CNT) composite sensing platform, in which the positively charged chitosan/PVI-Os is mediator and electrostatically immobilizes the negatively charged enzyme, while CNTs function as an essential cross-linker to network PVI-Os and chitosan due to its negative charged nature. Additional electrodes on the chip with the same sensing layer but without enzymes were prepared to correct the interferences for high specificity. Low detection limits of 0.6 μM and 5 μM were achieved for lactate and glucose, respectively. This work could be extended to inexpensive array sensing chips with high sensitivity, good specificity and high reproducibility for various sensor applications.

  16. SenseSeer, mobile-cloud-based lifelogging framework

    OpenAIRE

    Albatal, Rami; Gurrin, Cathal; Zhou, Jiang; Yang, Yang; Carthy, Denise; LI, Na

    2013-01-01

    Smart-phones are becoming our constant companions, they are with us all of the time, being used for calling, web surfing, apps, music listening, TV viewing, social networking, buying, gaming, and a myriad of other uses. Smart-phones are a technology that knows us much better than most of us could imagine. Based on our usage and the fact that we are never far away from our smart phones, they know where we go, who we interact with, what information we consume, and with a little clever software,...

  17. Graphene Paper Based Nanomaterials for Electrochemical Sensing and Energy Conversion

    DEFF Research Database (Denmark)

    Zhang, Minwei

    of graphene-based materials to real world, graphene nanosheets must be assembled into macroscopic architecture with desired structures and functionality. To this end, graphene oxide (GO) is a very useful building block because it contains a significant number of oxygen-containing groups on the planar surface...... of hydrogen peroxide (H2O2). Graphene paper was finally explored as a sacrificial template for the synthesis of 2D ultra-fined nanostructured porous metal oxide (MO), as described in Chapters 6-8. In Chapter 6, we demonstrated that crystalline MO can be prepared by using GO papers as sacrificial templates...

  18. Electromagnetism based atmospheric ice sensing technique - A conceptual review

    Directory of Open Access Journals (Sweden)

    U Mughal

    2016-09-01

    Full Text Available Electromagnetic and vibrational properties of ice can be used to measure certain parameters such as ice thickness, type and icing rate. In this paper we present a review of the dielectric based measurement techniques for matter and the dielectric/spectroscopic properties of ice. Atmospheric Ice is a complex material with a variable dielectric constant, but precise calculation of this constant may form the basis for measurement of its other properties such as thickness and strength using some electromagnetic methods. Using time domain or frequency domain spectroscopic techniques, by measuring both the reflection and transmission characteristics of atmospheric ice in a particular frequency range, the desired parameters can be determined.

  19. All-polymer photonic sensing platform based on whispering-gallery mode microgoblet lasers

    OpenAIRE

    Wienhold, T.; Kraemmer, S.; Wondimu, S.F.; Siegle, T.; Bog, U.; Weinzierl, U.; Schmidt, S.; Becker, H.; Kalt, H.; Mappes, T.; Koeber, S.; Koos, C.

    2015-01-01

    We present an all-polymer photonic sensing platform based on whispering-gallery mode microgoblet lasers integrated into a microfluidic chip. The chip is entirely made from polymers, enabling the use of the devices as low-cost disposables. The microgoblet cavities feature quality factors exceeding 105 and are fabricated from poly(methyl methacrylate) (PMMA) using spin-coating, mask-based optical lithography, wet chemical etching, and thermal reflow. In contrast to silica-based microtoroid reso...

  20. Characterization of subarctic vegetation using ground based remote sensing methods

    Science.gov (United States)

    Finnell, D.; Garnello, A.; Palace, M. W.; Sullivan, F.; Herrick, C.; Anderson, S. M.; Crill, P. M.; Varner, R. K.

    2014-12-01

    Stordalen mire is located at 68°21'N and 19°02'E in the Swedish subarctic. Climate monitoring has revealed a warming trend spanning the past 150 years affecting the mires ability to hold stable palsa/hummock mounds. The micro-topography of the landscape has begun to degrade into thaw ponds changing the vegetation cover from ombrothrophic to minerotrophic. Hummocks are ecologically important due to their ability to act as a carbon sinks. Thaw ponds and sphagnum rich transitional zones have been documented as sources of atmospheric CH4. An objective of this project is to determine if a high resolution three band camera (RGB) and a RGNIR camera could detect differences in vegetation over five different site types. Species composition was collected for 50 plots with ten repetitions for each site type: palsa/hummock, tall shrub, semi-wet, tall graminoid, and wet. Sites were differentiated based on dominating species and features consisting of open water presence, sphagnum spp. cover, graminoid spp. cover, or the presence of dry raised plateaus/mounds. A pole based camera mount was used to collect images at a height of ~2.44m from the ground. The images were cropped in post-processing to fit a one-square meter quadrat. Texture analysis was performed on all images, including entropy, lacunarity, and angular second momentum. Preliminary results suggested that site type influences the number of species present. The p-values for the ability to predict site type using a t-test range from use of a stepwise regression of texture variables, actual vs. predicted percent of vegetation coverage provided R squared values of 0.73, 0.71, 0.67, and 0.89 for C. bigelowii, R. chamaemorus, Sphagnum spp., and open water respectively. These data have provided some support to the notion that texture analyses can be used for classification of mire site types. Future work will involve scaling up from the 50 plots through the use of data collected from two unmanned aerial systems (UAS), as

  1. An Anthracene-Based Tripodal Chemosensor for Anion Sensing

    Directory of Open Access Journals (Sweden)

    Whitney A. Quinn

    2010-05-01

    Full Text Available An anthracene-based tripodal ligand was synthesized from the condensation of tren with 9-anthraldehyde, and the subsequent reduction with sodium borohydride. The neutral ligand was protonated from the reaction with p-toluenesulfonic acid to give a triply charged chemosensor that was examined for its anion binding ability toward fluoride, chloride, bromide, sulfate and nitrate by the fluorescence spectroscopy in DMSO. The addition of an anion to the ligand resulted in an enhancement in fluorescence intensity at the excitation of 310 nm. Analysis of the spectral changes suggested that the ligand formed a 1:1 complex with each of the anions, showing strong affinity for fluoride and sulfate in DMSO. The unsubstituted tren was reacted with sulfuric acid to form a sulfate complex and the structure was determined by the X-ray crystallography. Analysis of the complex revealed that three sulfates are held between two ligands by multiple hydrogen bonding interactions with protonated amines.

  2. Motion-Based pH Sensing Based on the Cartridge-Case-like Micromotor.

    Science.gov (United States)

    Su, Yajun; Ge, Ya; Liu, Limei; Zhang, Lina; Liu, Mei; Sun, Yunyu; Zhang, Hui; Dong, Bin

    2016-02-17

    In this paper, we report a novel cartridge-case-like micromotor. The micromotor, which is fabricated by the template synthesis method, consists of a gelatin shell with platinum nanoparticles decorating its inner surface. Intriguingly, the resulting cartridge-case-like structure exhibits a pH-dependent "open and close" feature, which originates from the pH responsiveness of the gelatin material. On the basis of the catalytic activity of the platinum nanoparticle inside the gelatin shell, the resulting cartridge-case-like structure is capable of moving autonomously in the aqueous solution containing the hydrogen peroxide fuel. More interestingly, we find out that the micromotor can be utilized as a motion-based pH sensor over the whole pH range. The moving velocity of the micromotor increases monotonically with the increase of pH of the analyte solution. Three different factors are considered to be responsible for the proportional relation between the motion speed and pH of the analyte solution: the peroxidase-like and oxidase-like catalytic behavior of the platinum nanoparticle at low and high pH, the volumetric decomposition of the hydrogen peroxide under the basic condition and the pH-dependent catalytic activity of the platinum nanoparticle caused by the swelling/deswelling behavior of the gelatin material. The current work highlights the impact of the material properties on the motion behavior of a micromotor, thus paving the way toward its application in the motion-based sensing field.

  3. Compressed sensing techniques for receiver based post-compensation of transmitter's nonlinear distortions in OFDM systems

    KAUST Repository

    Owodunni, Damilola S.; Ali, Anum Z.; Quadeer, Ahmed Abdul; Al-Safadi, Ebrahim B.; Hammi, Oualid; Al-Naffouri, Tareq Y.

    2014-01-01

    -domain, and three compressed sensing based algorithms are presented to estimate and compensate for these distortions at the receiver using a few and, at times, even no frequency-domain free carriers (i.e. pilot carriers). The first technique is a conventional

  4. Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS experiment

    NARCIS (Netherlands)

    Curnel, Y.; Wit, de A.J.W.; Duveiller, G.; Defourny, P.

    2011-01-01

    An Observing System Simulation Experiment (OSSE) has been defined to assess the potentialities of assimilating winter wheat leaf area index (LAI) estimations derived from remote sensing into the crop growth model WOFOST. Two assimilation strategies are considered: one based on Ensemble Kalman Filter

  5. Development of semiconductor laser based Doppler lidars for wind-sensing applications

    DEFF Research Database (Denmark)

    Rodrigo, Peter John; Hu, Qi; Pedersen, Christian

    2015-01-01

    We summarize the progress we have made in the development of semiconductor laser (SL) based Doppler lidar systems for remote wind speed and direction measurements. The SL emitter used in our wind-sensing lidar is an integrated diode laser with a tapered (semiconductor) amplifier. The laser source...

  6. Application of remote sensing and Geographic Information Systems to ecosystem-based urban natural resource management

    Science.gov (United States)

    Xiaohui Zhang; George Ball; Eve Halper

    2000-01-01

    This paper presents an integrated system to support urban natural resource management. With the application of remote sensing (RS) and geographic information systems (GIS), the paper emphasizes the methodology of integrating information technology and a scientific basis to support ecosystem-based management. First, a systematic integration framework is developed and...

  7. Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy.

    Science.gov (United States)

    Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

    2017-10-01

    A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  8. Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

    Directory of Open Access Journals (Sweden)

    Yvonne Walz

    2015-11-01

    Full Text Available Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

  9. Accurate Quantitative Sensing of Intracellular pH based on Self-ratiometric Upconversion Luminescent Nanoprobe

    NARCIS (Netherlands)

    Li, C.; Zuo, J.; Zhang, L.; Chang, Y.; Zhang, Y.; Tu, L.; Liu, X.; Xue, B.; Li, Q.; Zhao, H.; Zhang, H.; Kong, X.

    2016-01-01

    Accurate quantitation of intracellular pH (pHi) is of great importance in revealing the cellular activities and early warning of diseases. A series of fluorescence-based nano-bioprobes composed of different nanoparticles or/and dye pairs have already been developed for pHi sensing. Till now,

  10. Dual-modal cancer detection based on optical pH sensing and Raman spectroscopy

    Science.gov (United States)

    Kim, Soogeun; Lee, Seung Ho; Min, Sun Young; Byun, Kyung Min; Lee, Soo Yeol

    2017-10-01

    A dual-modal approach using Raman spectroscopy and optical pH sensing was investigated to discriminate between normal and cancerous tissues. Raman spectroscopy has demonstrated the potential for in vivo cancer detection. However, Raman spectroscopy has suffered from strong fluorescence background of biological samples and subtle spectral differences between normal and disease tissues. To overcome those issues, pH sensing is adopted to Raman spectroscopy as a dual-modal approach. Based on the fact that the pH level in cancerous tissues is lower than that in normal tissues due to insufficient vasculature formation, the dual-modal approach combining the chemical information of Raman spectrum and the metabolic information of pH level can improve the specificity of cancer diagnosis. From human breast tissue samples, Raman spectra and pH levels are measured using fiber-optic-based Raman and pH probes, respectively. The pH sensing is based on the dependence of pH level on optical transmission spectrum. Multivariate statistical analysis is performed to evaluate the classification capability of the dual-modal method. The analytical results show that the dual-modal method based on Raman spectroscopy and optical pH sensing can improve the performance of cancer classification.

  11. Three-Dimensional Inverse Transport Solver Based on Compressive Sensing Technique

    Science.gov (United States)

    Cheng, Yuxiong; Wu, Hongchun; Cao, Liangzhi; Zheng, Youqi

    2013-09-01

    According to the direct exposure measurements from flash radiographic image, a compressive sensing-based method for three-dimensional inverse transport problem is presented. The linear absorption coefficients and interface locations of objects are reconstructed directly at the same time. It is always very expensive to obtain enough measurements. With limited measurements, compressive sensing sparse reconstruction technique orthogonal matching pursuit is applied to obtain the sparse coefficients by solving an optimization problem. A three-dimensional inverse transport solver is developed based on a compressive sensing-based technique. There are three features in this solver: (1) AutoCAD is employed as a geometry preprocessor due to its powerful capacity in graphic. (2) The forward projection matrix rather than Gauss matrix is constructed by the visualization tool generator. (3) Fourier transform and Daubechies wavelet transform are adopted to convert an underdetermined system to a well-posed system in the algorithm. Simulations are performed and numerical results in pseudo-sine absorption problem, two-cube problem and two-cylinder problem when using compressive sensing-based solver agree well with the reference value.

  12. Retrieval of liquid water cloud properties from ground-based remote sensing observations

    NARCIS (Netherlands)

    Knist, C.L.

    2014-01-01

    Accurate ground-based remotely sensed microphysical and optical properties of liquid water clouds are essential references to validate satellite-observed cloud properties and to improve cloud parameterizations in weather and climate models. This requires the evaluation of algorithms for retrieval of

  13. Palladium and platinum-based nanoparticle functional sensor layers for selective H2 sensing

    Science.gov (United States)

    Ohodnicki, Jr., Paul R.; Baltrus, John P.; Brown, Thomas D.

    2017-07-04

    The disclosure relates to a plasmon resonance-based method for H.sub.2 sensing in a gas stream utilizing a hydrogen sensing material. The hydrogen sensing material is comprises Pd-based or Pt-based nanoparticles having an average nanoparticle diameter of less than about 100 nanometers dispersed in an inert matrix having a bandgap greater than or equal to 5 eV, and an oxygen ion conductivity less than approximately 10.sup.-7 S/cm at a temperature of 700.degree. C. Exemplary inert matrix materials include SiO.sub.2, Al.sub.2O.sub.3, and Si.sub.3N.sub.4 as well as modifications to modify the effective refractive indices through combinations and/or doping of such materials. The hydrogen sensing material utilized in the method of this disclosure may be prepared using means known in the art for the production of nanoparticles dispersed within a supporting matrix including sol-gel based wet chemistry techniques, impregnation techniques, implantation techniques, sputtering techniques, and others.

  14. Historical feature pattern extraction based network attack situation sensing algorithm.

    Science.gov (United States)

    Zeng, Yong; Liu, Dacheng; Lei, Zhou

    2014-01-01

    The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE). First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

  15. Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm

    Directory of Open Access Journals (Sweden)

    Yong Zeng

    2014-01-01

    Full Text Available The situation sequence contains a series of complicated and multivariate random trends, which are very sudden, uncertain, and difficult to recognize and describe its principle by traditional algorithms. To solve the above questions, estimating parameters of super long situation sequence is essential, but very difficult, so this paper proposes a situation prediction method based on historical feature pattern extraction (HFPE. First, HFPE algorithm seeks similar indications from the history situation sequence recorded and weighs the link intensity between occurred indication and subsequent effect. Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. This algorithm can continuously promote the adaptability of HFPE through gradual fine-tuning. The method preserves the rules in sequence at its best, does not need data preprocessing, and can track and adapt to the variation of situation sequence continuously.

  16. Particle filtering based structural assessment with acoustic emission sensing

    Science.gov (United States)

    Yan, Wuzhao; Abdelrahman, Marwa; Zhang, Bin; Ziehl, Paul

    2017-02-01

    Nuclear structures are designed to withstand severe loading events under various stresses. Over time, aging of structural systems constructed with concrete and steel will occur. This deterioration may reduce service life of nuclear facilities and/or lead to unnecessary or untimely repairs. Therefore, online monitoring of structures in nuclear power plants and waste storage has drawn significant attention in recent years. Of many existing non-destructive evaluation and structural monitoring approaches, acoustic emission is promising for assessment of structural damage because it is non-intrusive and is sensitive to corrosion and crack growth in reinforced concrete elements. To provide a rapid, actionable, and graphical means for interpretation Intensity Analysis plots have been developed. This approach provides a means for classification of damage. Since the acoustic emission measurement is only an indirect indicator of structural damage, potentially corrupted by non-genuine data, it is more suitable to estimate the states of corrosion and cracking in a Bayesian estimation framework. In this paper, we will utilize the accelerated corrosion data from a specimen at the University of South Carolina to develop a particle filtering-based diagnosis and prognosis algorithm. Promising features of the proposed algorithm are described in terms of corrosion state estimation and prediction of degradation over time to a predefined threshold.

  17. Optical Sensing Material for pH Detection based on the Use of Roselle Extract

    International Nuclear Information System (INIS)

    Nurul Huda Abd Karim; Musa Ahmad; Mohammad Osman Herman; Ahmad Mahir Mokhtar

    2008-01-01

    This research assessed the potential of natural colour extract of Hibiscus Sabdariffa L. (roselle) as sensing material.The pH sensor was developed based on the use of natural reddish colour in roselle calyx, delphinidin-3-sambubioside immobilised in a glass fibre filter paper. In free solution, roselle extract was characterised by using UV-visible spectrophotometer to study the effect of pH, extract concentration, response time, repeatability and photo stability. The study showed that natural colour extract can be used as sensing material for the development of an optical pH sensor. (author)

  18. Space-Based Remote Sensing of the Earth: A Report to the Congress

    Science.gov (United States)

    1987-01-01

    The commercialization of the LANDSAT Satellites, remote sensing research and development as applied to the Earth and its atmosphere as studied by NASA and NOAA is presented. Major gaps in the knowledge of the Earth and its atmosphere are identified and a series of space based measurement objectives are derived. The near-term space observations programs of the United States and other countries are detailed. The start is presented of the planning process to develop an integrated national program for research and development in Earth remote sensing for the remainder of this century and the many existing and proposed satellite and sensor systems that the program may include are described.

  19. A fast combinatorial enhancement technique for earthquake damage identification based on remote sensing image

    Science.gov (United States)

    Dou, Aixia; Wang, Xiaoqing; Ding, Xiang; Du, Zecheng

    2010-11-01

    On the basis of the study on the enhancement methods of remote sensing images obtained after several earthquakes, the paper designed a new and optimized image enhancement model which was implemented by combining different single methods. The patterns of elementary model units and combined types of model were defined. Based on the enhancement model database, the algorithm of combinatorial model was brought out via C++ programming. The combined model was tested by processing the aerial remote sensing images obtained after 1976 Tangshan earthquake. It was proved that the definition and implementation of combined enhancement model can efficiently improve the ability and flexibility of image enhancement algorithm.

  20. Methods for Enhancing Geological Structures in Spectral Spatial Difference-Based on Remote-Sensing Image

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    @@In this paper, some image processing methods such as directional template (mask) matching enhancement, pseudocolor or false color enhancement, K-L transform enhancement are used to enhance a geological structure, one of important ore-controlling factors, shown in the remote-sensing images.This geological structure is regarded as image anomaly in the remote-sensing image, since considerable differences, based on the spatial spectral distribution pattern, in gray values (spectral), color tones and texture, are always present between the geological structure and background. Therefore,the enhancement of the geological structure in the remotesensing image is that of the spectral spatial difference.

  1. Displacement sensing based on modal interference in polymer optical fibers with partially applied strain

    Science.gov (United States)

    Mizuno, Yosuke; Hagiwara, Sonoko; Kawa, Tomohito; Lee, Heeyoung; Nakamura, Kentaro

    2018-05-01

    Strain sensing based on modal interference in multimode fibers (MMFs) has been extensively studied, but no experimental or theoretical reports have been given as to how the system works when strain is applied not to the whole MMF but only to part of the MMF. Here, using a perfluorinated graded-index polymer optical fiber as the MMF, we investigate the strain sensing characteristics of this type of sensor when strain is partially applied to fiber sections with different lengths. The strain sensitivity dependence on the length of the strained section reveals that this strain sensor actually behaves as a displacement sensor.

  2. A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

    Science.gov (United States)

    Schwartz, Noah; Drucker, Nick; Campbell, Kenyth

    2012-01-01

    Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

  3. Single Mode SU8 Polymer Based Mach-Zehnder Interferometer for Bio-Sensing Application

    Science.gov (United States)

    Boiragi, Indrajit; Kundu, Sushanta; Makkar, Roshan; Chalapathi, Krishnamurthy

    2011-10-01

    This paper explains the influence of different parameters to the sensitivity of an optical waveguide Mach-Zehnder Interferometer (MZI) for real time detection of biomolecules. The sensing principle is based on the interaction of evanescence field with the biomolecules that get immobilized on sensing arm. The sensitivity has been calculated by varying the sensing window length, wavelength and concentration of bio-analyte. The maximum attainable sensitivity for the preferred design is the order of 10-8 RIU at 840 nm wavelength with a sensing window length of 1cm. All the simulation work has been carried out with Opti-BPMCAD for the optimization of MZI device parameters. The SU8 polymers are used as a core and clad material to fabricate the waveguide. The refractive index of cladding layer is optimized by varying the curing temperature for a fixed time period and the achieved index difference between core and clad is Δn = 0.0151. The fabricated MZI device has been characterized with LASER beam profiler at 840 nm wavelength. This study demonstrates the effectiveness of the different parameter to the sensitivity of a single mode optical waveguide Mach-Zehnder Interferometer for bio-sensing application.

  4. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  5. A mobile-agent-based wireless sensing network for structural monitoring applications

    International Nuclear Information System (INIS)

    Taylor, Stuart G; Farinholt, Kevin M; Figueiredo, Eloi; Moro, Erik A; Park, Gyuhae; Farrar, Charles R; Flynn, Eric B; Mascarenas, David L; Todd, Michael D

    2009-01-01

    A new wireless sensing network paradigm is presented for structural monitoring applications. In this approach, both power and data interrogation commands are conveyed via a mobile agent that is sent to sensor nodes to perform intended interrogations, which can alleviate several limitations of the traditional sensing networks. Furthermore, the mobile agent provides computational power to make near real-time assessments on the structural conditions. This paper will discuss such prototype systems, which are used to interrogate impedance-based sensors for structural health monitoring applications. Our wireless sensor node is specifically designed to accept various energy sources, including wireless energy transmission, and to be wirelessly triggered on an as-needed basis by the mobile agent or other sensor nodes. The capabilities of this proposed sensing network paradigm are demonstrated in the laboratory and the field

  6. A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map

    International Nuclear Information System (INIS)

    Xiao Di; Cai Hong-Kun; Zheng Hong-Ying

    2015-01-01

    In this paper, a compressive sensing (CS) and chaotic map-based joint image encryption and watermarking algorithm is proposed. The transform domain coefficients of the original image are scrambled by Arnold map firstly. Then the watermark is adhered to the scrambled data. By compressive sensing, a set of watermarked measurements is obtained as the watermarked cipher image. In this algorithm, watermark embedding and data compression can be performed without knowing the original image; similarly, watermark extraction will not interfere with decryption. Due to the characteristics of CS, this algorithm features compressible cipher image size, flexible watermark capacity, and lossless watermark extraction from the compressed cipher image as well as robustness against packet loss. Simulation results and analyses show that the algorithm achieves good performance in the sense of security, watermark capacity, extraction accuracy, reconstruction, robustness, etc. (paper)

  7. Multiple Fano-Like MIM Plasmonic Structure Based on Triangular Resonator for Refractive Index Sensing.

    Science.gov (United States)

    Jankovic, Nikolina; Cselyuszka, Norbert

    2018-01-19

    In this paper, we present a Fano metal-insulator-metal (MIM) structure based on an isosceles triangular cavity resonator for refractive index sensing applications. Due to the specific feeding scheme and asymmetry introduced in the triangular cavity, the resonator exhibits four sharp Fano-like resonances. The behavior of the structure is analyzed in detail and its sensing capabilities demonstrated through the responses for various refractive indices. The results show that the sensor has very good sensitivity and maximal figure of merit (FOM) value of 3.2 × 10⁵. In comparison to other similar sensors, the proposed one has comparable sensitivity and significantly higher FOM, which clearly demonstrates its high sensing potential.

  8. A method of vehicle license plate recognition based on PCANet and compressive sensing

    Science.gov (United States)

    Ye, Xianyi; Min, Feng

    2018-03-01

    The manual feature extraction of the traditional method for vehicle license plates has no good robustness to change in diversity. And the high feature dimension that is extracted with Principal Component Analysis Network (PCANet) leads to low classification efficiency. For solving these problems, a method of vehicle license plate recognition based on PCANet and compressive sensing is proposed. First, PCANet is used to extract the feature from the images of characters. And then, the sparse measurement matrix which is a very sparse matrix and consistent with Restricted Isometry Property (RIP) condition of the compressed sensing is used to reduce the dimensions of extracted features. Finally, the Support Vector Machine (SVM) is used to train and recognize the features whose dimension has been reduced. Experimental results demonstrate that the proposed method has better performance than Convolutional Neural Network (CNN) in the recognition and time. Compared with no compression sensing, the proposed method has lower feature dimension for the increase of efficiency.

  9. Remote Impedance-based Loose Bolt Inspection Using a Radio-Frequency Active Sensing Node

    Energy Technology Data Exchange (ETDEWEB)

    Park, Seung Hee; Yun, Chung Bang [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Inman, Daniel J. [Virginia Polytechnic Institute and State University, Virginia (United States)

    2007-06-15

    This paper introduces an active sensing node using radio-frequency (RF) telemetry. This device has brought the traditional impedance-based structural health monitoring (SHM) technique to a new paradigm. The RF active sensing node consists of a miniaturized impedance measuring device (AD5933), a microcontroller (ATmega128L), and a radio frequency (RF) transmitter (XBee). A macro-fiber composite (MFC) patch interrogates a host structure by using a self-sensing technique of the miniaturized impedance measuring device. All the process including structural interrogation, data acquisition, signal processing, and damage diagnostic is being performed at the sensor location by the microcontroller. The RF transmitter is used to communicate the current status of the host structure. The feasibility of the proposed SHM strategy is verified through an experimental study inspecting loose bolts in a bolt-jointed aluminum structure

  10. Remote Impedance-based Loose Bolt Inspection Using a Radio-Frequency Active Sensing Node

    International Nuclear Information System (INIS)

    Park, Seung Hee; Yun, Chung Bang; Inman, Daniel J.

    2007-01-01

    This paper introduces an active sensing node using radio-frequency (RF) telemetry. This device has brought the traditional impedance-based structural health monitoring (SHM) technique to a new paradigm. The RF active sensing node consists of a miniaturized impedance measuring device (AD5933), a microcontroller (ATmega128L), and a radio frequency (RF) transmitter (XBee). A macro-fiber composite (MFC) patch interrogates a host structure by using a self-sensing technique of the miniaturized impedance measuring device. All the process including structural interrogation, data acquisition, signal processing, and damage diagnostic is being performed at the sensor location by the microcontroller. The RF transmitter is used to communicate the current status of the host structure. The feasibility of the proposed SHM strategy is verified through an experimental study inspecting loose bolts in a bolt-jointed aluminum structure

  11. A Plasmonic Temperature-Sensing Structure Based on Dual Laterally Side-Coupled Hexagonal Cavities

    Directory of Open Access Journals (Sweden)

    Yiyuan Xie

    2016-05-01

    Full Text Available A plasmonic temperature-sensing structure, based on a metal-insulator-metal (MIM waveguide with dual side-coupled hexagonal cavities, is proposed and numerically investigated by using the finite-difference time-domain (FDTD method in this paper. The numerical simulation results show that a resonance dip appears in the transmission spectrum. Moreover, the full width of half maximum (FWHM of the resonance dip can be narrowed down, and the extinction ratio can reach a maximum value by tuning the coupling distance between the waveguide and two cavities. Based on a linear relationship between the resonance dip and environment temperature, the temperature-sensing characteristics are discussed. The temperature sensitivity is influenced by the side length and the coupling distance. Furthermore, for the first time, two concepts—optical spectrum interference (OSI and misjudge rate (MR—are introduced to study the temperature-sensing resolution based on spectral interrogation. This work has some significance in the design of nanoscale optical sensors with high temperature sensitivity and a high sensing resolution.

  12. Estimation of sensing characteristics for refractory nitrides based gain assisted core-shell plasmonic nanoparticles

    Science.gov (United States)

    Shishodia, Manmohan Singh; Pathania, Pankaj

    2018-04-01

    Refractory transition metal nitrides such as zirconium nitride (ZrN), hafnium nitride (HfN) and titanium nitride (TiN) have emerged as viable alternatives to coinage metals based plasmonic materials, e.g., gold (Au) and silver (Ag). The present work assesses the suitability of gain assisted ZrN-, HfN- and TiN-based conventional core-shell nanoparticles (CCSNPs) and multilayered core-shell nanoparticles (MCSNPs) for refractive index sensing. We report that the optical gain incorporation in the dielectric layer leads to multifold enhancement of the scattering efficiency (Qsca), substantial reduction of the spectral full width at half maximum, and a higher figure of merit (FOM). In comparison with CCSNPs, the MCSNP system exhibits superior sensing characteristics such as higher FOM, ˜ 45% reduction in the critical optical gain, response shift towards the biological window, and higher degree of tunability. Inherent biocompatibility, growth compatibility, chemical stability and flexible spectral tuning of refractory nitrides augmented by superior sensing properties in the present work may pave the way for refractory nitrides based low cost sensing.

  13. Efficient Bayesian Compressed Sensing-based Channel Estimation Techniques for Massive MIMO-OFDM Systems

    OpenAIRE

    Al-Salihi, Hayder Qahtan Kshash; Nakhai, Mohammad Reza

    2017-01-01

    Efficient and highly accurate channel state information (CSI) at the base station (BS) is essential to achieve the potential benefits of massive multiple input multiple output (MIMO) systems. However, the achievable accuracy that is attainable is limited in practice due to the problem of pilot contamination. It has recently been shown that compressed sensing (CS) techniques can address the pilot contamination problem. However, CS-based channel estimation requires prior knowledge of channel sp...

  14. AN INTERACTIVE WEB-BASED ANALYSIS FRAMEWORK FOR REMOTE SENSING CLOUD COMPUTING

    Directory of Open Access Journals (Sweden)

    X. Z. Wang

    2015-07-01

    Full Text Available Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users’ private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook

  15. A patch-based convolutional neural network for remote sensing image classification.

    Science.gov (United States)

    Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

    2017-11-01

    Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Glucose Sensing

    CERN Document Server

    Geddes, Chris D

    2006-01-01

    Topics in Fluorescence Spectroscopy, Glucose Sensing is the eleventh volume in the popular series Topics in Fluorescence Spectroscopy, edited by Drs. Chris D. Geddes and Joseph R. Lakowicz. This volume incorporates authoritative analytical fluorescence-based glucose sensing reviews specialized enough to be attractive to professional researchers, yet also appealing to the wider audience of scientists in related disciplines of fluorescence. Glucose Sensing is an essential reference for any lab working in the analytical fluorescence glucose sensing field. All academics, bench scientists, and industry professionals wishing to take advantage of the latest and greatest in the continuously emerging field of glucose sensing, and diabetes care & management, will find this volume an invaluable resource. Topics in Fluorescence Spectroscopy Volume 11, Glucose Sensing Chapters include: Implantable Sensors for Interstitial Fluid Smart Tattoo Glucose Sensors Optical Enzyme-based Glucose Biosensors Plasmonic Glucose Sens...

  17. An Adaptive Web-Based Learning Environment for the Application of Remote Sensing in Schools

    Science.gov (United States)

    Wolf, N.; Fuchsgruber, V.; Riembauer, G.; Siegmund, A.

    2016-06-01

    Satellite images have great educational potential for teaching on environmental issues and can promote the motivation of young people to enter careers in natural science and technology. Due to the importance and ubiquity of remote sensing in science, industry and the public, the use of satellite imagery has been included into many school curricular in Germany. However, its implementation into school practice is still hesitant, mainly due to lack of teachers' know-how and education materials that align with the curricula. In the project "Space4Geography" a web-based learning platform is developed with the aim to facilitate the application of satellite imagery in secondary school teaching and to foster effective student learning experiences in geography and other related subjects in an interdisciplinary way. The platform features ten learning modules demonstrating the exemplary application of original high spatial resolution remote sensing data (RapidEye and TerraSAR-X) to examine current environmental issues such as droughts, deforestation and urban sprawl. In this way, students will be introduced into the versatile applications of spaceborne earth observation and geospatial technologies. The integrated web-based remote sensing software "BLIF" equips the students with a toolset to explore, process and analyze the satellite images, thereby fostering the competence of students to work on geographical and environmental questions without requiring prior knowledge of remote sensing. This contribution presents the educational concept of the learning environment and its realization by the example of the learning module "Deforestation of the rainforest in Brasil".

  18. [An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

    Science.gov (United States)

    Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

    2009-10-01

    Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

  19. Wireless Sensing Based on RFID and Capacitive Technologies for Safety in Marble Industry Process Control

    Directory of Open Access Journals (Sweden)

    Fabrizio Iacopetti

    2013-01-01

    Full Text Available This paper presents wireless sensing systems to increase safety and robustness in industrial process control, particularly in industrial machines for marble slab working. The process is performed by abrasive or cutting heads activated independently by the machine controller when the slab, transported on a conveyer belt, is under them. Current slab detection systems are based on electromechanical or optical devices at the machine entrance stage, suffering from deterioration and from the harsh environment. Slab displacement or break inside the machine due to the working stress may result in safety issues and damages to the conveyer belt due to incorrect driving of the working tools. The experimented contactless sensing techniques are based on four RFID and two capacitive sensing technologies and on customized hardware/software. The proposed solutions aim at overcoming some limitations of current state-of-the-art detection systems, allowing for reliable slab detection, outside and/or inside the machine, while maintaining low complexity and at the same time robustness to industrial harsh conditions. The proposed sensing devices may implement a wireless or wired sensor network feeding detection data to the machine controller. Data integrity check and process control algorithms have to be implemented for the safety and reliability of the overall industrial process.

  20. A flexible dual-mode proximity sensor based on cooperative sensing for robot skin applications

    Science.gov (United States)

    Huang, Ying; Cai, Xia; Kan, Wenqing; Qiu, Shihua; Guo, Xiaohui; Liu, Caixia; Liu, Ping

    2017-08-01

    A flexible dual-mode proximity sensor has been designed and implemented, which is capable of combining capacitive-resistive detection in this paper. The capacitive type proximity sensor detecting is defined as mode-C, and the resistive type proximity sensor detecting is defined as mode-R. The characteristics of the proximity sensor are as follows: (1) the theoretical mode is developed which indicates that this proximity sensor can reflect proximity information accurately; (2) both sensing modes are vertically integrated into a sandwich-like chip with an 8 mm × 12 mm unit area. The thickness of a mode-R sensing material (graphene nanoplatelets) and mode-C dielectric (the mixture of carbon black and silicone rubber) is 1 mm and 2.5 mm, respectively; (3) for mode-R, the linearity of temperature-resistance curve can achieve 0.998 in the temperature range from 25°C to 65°C. And for mode-C, various materials can be successfully detected with fast response and high reversibility. Meanwhile, the study compensated the influence of object temperature to ensure mode-C properly works. A cooperative sensing test shows that R-C dual modes sense effectively which can enlarge the sensing distance compared with the single mode proximity sensor. The fabrication of this sensor is convenient, and the integrity of a flexible sandwich-like structure based on dual modes is beneficial to form arrays, which is suitable to be used in skin-like sensing applications.

  1. Novel developments in mobile sensing based on the integration of microfluidic devices and smartphones.

    Science.gov (United States)

    Yang, Ke; Peretz-Soroka, Hagit; Liu, Yong; Lin, Francis

    2016-03-21

    Portable electronic devices and wireless communication systems enable a broad range of applications such as environmental and food safety monitoring, personalized medicine and healthcare management. Particularly, hybrid smartphone and microfluidic devices provide an integrated solution for the new generation of mobile sensing applications. Such mobile sensing based on microfluidic devices (broadly defined) and smartphones (MS(2)) offers a mobile laboratory for performing a wide range of bio-chemical detection and analysis functions such as water and food quality analysis, routine health tests and disease diagnosis. MS(2) offers significant advantages over traditional platforms in terms of test speed and control, low cost, mobility, ease-of-operation and data management. These improvements put MS(2) in a promising position in the fields of interdisciplinary basic and applied research. In particular, MS(2) enables applications to remote in-field testing, homecare, and healthcare in low-resource areas. The marriage of smartphones and microfluidic devices offers a powerful on-chip operating platform to enable various bio-chemical tests, remote sensing, data analysis and management in a mobile fashion. The implications of such integration are beyond telecommunication and microfluidic-related research and technology development. In this review, we will first provide the general background of microfluidic-based sensing, smartphone-based sensing, and their integration. Then, we will focus on several key application areas of MS(2) by systematically reviewing the important literature in each area. We will conclude by discussing our perspectives on the opportunities, issues and future directions of this emerging novel field.

  2. Novel Developments of Mobile Sensing Based on the Integration of Microfluidic Devices and Smartphone

    Science.gov (United States)

    Yang, Ke; Peretz-Soroka, Hagit; Liu, Yong; Lin, Francis

    2016-01-01

    Portable electronic devices and wireless communication systems enable a broad range of applications such as environmental and food safety monitoring, personalized medicine and healthcare management. Particularly, hybrid smartphone and microfluidic devices provide an integrated solution for the new generation of mobile sensing applications. Such mobile sensing based on microfluidic devices (broadly defined) and smartphones (MS2) offers a mobile laboratory for performing a wide range of bio-chemical detection and analysis functions such as water and food quality analysis, routine health tests and disease diagnosis. MS2 offers significant advantages over traditional platforms in terms of test speed and control, low cost, mobility, ease-of-operation and data management. These improvements put MS2 in a promising position in the fields of interdisciplinary basic and applied research. In particular, MS2 enables applications to remote infield testing, homecare, and healthcare in low-resource areas. The marriage of smartphones and microfluidic devices offers a powerful on-chip operating platform to enable various bio-chemical tests, remote sensing, data analysis and management in a mobile fashion. The implications of such integration are beyond telecommunication and microfluidic-related research and technology development. In this review, we will first provide the general background of microfluidic-based sensing, smartphone-based sensing, and their integration. Then, we will focus on several key application areas of MS2 by systematically reviewing the important literature in each area. We will conclude by discussing our perspectives on the opportunities, issues and future directions of this emerging novel field. PMID:26899264

  3. Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

    Science.gov (United States)

    Mendiguren, Gorka; Koch, Julian; Stisen, Simon

    2017-11-01

    Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

  4. Spatiotemporal access model based on reputation for the sensing layer of the IoT.

    Science.gov (United States)

    Guo, Yunchuan; Yin, Lihua; Li, Chao; Qian, Junyan

    2014-01-01

    Access control is a key technology in providing security in the Internet of Things (IoT). The mainstream security approach proposed for the sensing layer of the IoT concentrates only on authentication while ignoring the more general models. Unreliable communications and resource constraints make the traditional access control techniques barely meet the requirements of the sensing layer of the IoT. In this paper, we propose a model that combines space and time with reputation to control access to the information within the sensing layer of the IoT. This model is called spatiotemporal access control based on reputation (STRAC). STRAC uses a lattice-based approach to decrease the size of policy bases. To solve the problem caused by unreliable communications, we propose both nondeterministic authorizations and stochastic authorizations. To more precisely manage the reputation of nodes, we propose two new mechanisms to update the reputation of nodes. These new approaches are the authority-based update mechanism (AUM) and the election-based update mechanism (EUM). We show how the model checker UPPAAL can be used to analyze the spatiotemporal access control model of an application. Finally, we also implement a prototype system to demonstrate the efficiency of our model.

  5. Object-based Morphological Building Index for Building Extraction from High Resolution Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    LIN Xiangguo

    2017-06-01

    Full Text Available Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. In this article, an object-based morphological building index (OBMBI is constructed based on both image segmentation and graph-based top-hat reconstruction, and OBMBI is used for building extraction from high resolution remote sensing images. First, bidirectional mapping relationship between pixels, objects and graph-nodes are constructed. Second, the OBMBI image is built based on both graph-based top-hat reconstruction and the above mapping relationship. Third, a binary thresholding is performed on the OBMBI image, and the binary image is converted into vector format to derive the building polygons. Finally, the post-processing is made to optimize the extracted building polygons. Two images, including an aerial image and a panchromatic satellite image, are used to test both the proposed method and classic PanTex method. The experimental results suggest that our proposed method has a higher accuracy in building extraction than the classic PanTex method. On average, the correctness, the completeness and the quality of our method are respectively 9.49%, 11.26% and 14.11% better than those of the PanTex.

  6. Spatiotemporal Access Model Based on Reputation for the Sensing Layer of the IoT

    Directory of Open Access Journals (Sweden)

    Yunchuan Guo

    2014-01-01

    Full Text Available Access control is a key technology in providing security in the Internet of Things (IoT. The mainstream security approach proposed for the sensing layer of the IoT concentrates only on authentication while ignoring the more general models. Unreliable communications and resource constraints make the traditional access control techniques barely meet the requirements of the sensing layer of the IoT. In this paper, we propose a model that combines space and time with reputation to control access to the information within the sensing layer of the IoT. This model is called spatiotemporal access control based on reputation (STRAC. STRAC uses a lattice-based approach to decrease the size of policy bases. To solve the problem caused by unreliable communications, we propose both nondeterministic authorizations and stochastic authorizations. To more precisely manage the reputation of nodes, we propose two new mechanisms to update the reputation of nodes. These new approaches are the authority-based update mechanism (AUM and the election-based update mechanism (EUM. We show how the model checker UPPAAL can be used to analyze the spatiotemporal access control model of an application. Finally, we also implement a prototype system to demonstrate the efficiency of our model.

  7. Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

    Science.gov (United States)

    Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

    2016-05-01

    Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

  8. Systematic review of smartphone-based passive sensing for health and wellbeing.

    Science.gov (United States)

    Cornet, Victor P; Holden, Richard J

    2018-01-01

    To review published empirical literature on the use of smartphone-based passive sensing for health and wellbeing. A systematic review of the English language literature was performed following PRISMA guidelines. Papers indexed in computing, technology, and medical databases were included if they were empirical, focused on health and/or wellbeing, involved the collection of data via smartphones, and described the utilized technology as passive or requiring minimal user interaction. Thirty-five papers were included in the review. Studies were performed around the world, with samples of up to 171 (median n = 15) representing individuals with bipolar disorder, schizophrenia, depression, older adults, and the general population. The majority of studies used the Android operating system and an array of smartphone sensors, most frequently capturing accelerometry, location, audio, and usage data. Captured data were usually sent to a remote server for processing but were shared with participants in only 40% of studies. Reported benefits of passive sensing included accurately detecting changes in status, behavior change through feedback, and increased accountability in participants. Studies reported facing technical, methodological, and privacy challenges. Studies in the nascent area of smartphone-based passive sensing for health and wellbeing demonstrate promise and invite continued research and investment. Existing studies suffer from weaknesses in research design, lack of feedback and clinical integration, and inadequate attention to privacy issues. Key recommendations relate to developing passive sensing strategies matching the problem at hand, using personalized interventions, and addressing methodological and privacy challenges. As evolving passive sensing technology presents new possibilities for health and wellbeing, additional research must address methodological, clinical integration, and privacy issues. Doing so depends on interdisciplinary collaboration

  9. Indium oxide octahedrons based on sol–gel process enhance room temperature gas sensing performance

    Energy Technology Data Exchange (ETDEWEB)

    Mu, Xiaohui [Key Laboratory of Chemical Sensing & Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan 250022, Shandong (China); Chen, Changlong, E-mail: chem.chencl@hotmail.com [Key Laboratory of Chemical Sensing & Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan 250022, Shandong (China); Han, Liuyuan [Key Laboratory of Chemical Sensing & Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan 250022, Shandong (China); Shao, Baiqi [State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022 (China); Graduate School of the Chinese Academy of Sciences, Beijing 100049 (China); Wei, Yuling [Instrumental Analysis Center, Qilu University of Technology, Jinan 250353, Shandong (China); Liu, Qinglong; Zhu, Peihua [Key Laboratory of Chemical Sensing & Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan 250022, Shandong (China)

    2015-07-15

    Highlights: • In{sub 2}O{sub 3} octahedron films are prepared based on sol–gel technique for the first time. • The preparation possesses merits of low temperature, catalyst-free and large production. • It was found that the spin-coating process in film fabrication was key to achieve the octahedrons. • The In{sub 2}O{sub 3} octahedrons could significantly enhance room temperature NO{sub 2} gas sensing performance. - Abstract: Indium oxide octahedrons were prepared on glass substrates through a mild route based on sol–gel technique. The preparation possesses characteristics including low temperature, catalyst-free and large production, which is much distinguished from the chemical-vapor-deposition based methods that usually applied to prepare indium oxide octahedrons. Detailed characterization revealed that the indium oxide octahedrons were single crystalline, with {1 1 1} crystal facets exposed. It was found that the spin-coating technique was key for achieving the indium oxide crystals with octahedron morphology. The probable formation mechanism of the indium oxide octahedrons was proposed based on the experiment results. Room temperature NO{sub 2} gas sensing measurements exhibited that the indium oxide octahedrons could significantly enhance the sensing performance in comparison with the plate-like indium oxide particles that prepared from the dip-coated gel films, which was attributed to the abundant sharp edges and tips as well as the special {1 1 1} crystal facets exposed that the former possessed. Such a simple wet-chemical based method to prepare indium oxide octahedrons with large-scale production is promising to provide the advanced materials that can be applied in wide fields like gas sensing, solar energy conversion, field emission, and so on.

  10. Indium oxide octahedrons based on sol–gel process enhance room temperature gas sensing performance

    International Nuclear Information System (INIS)

    Mu, Xiaohui; Chen, Changlong; Han, Liuyuan; Shao, Baiqi; Wei, Yuling; Liu, Qinglong; Zhu, Peihua

    2015-01-01

    Highlights: • In 2 O 3 octahedron films are prepared based on sol–gel technique for the first time. • The preparation possesses merits of low temperature, catalyst-free and large production. • It was found that the spin-coating process in film fabrication was key to achieve the octahedrons. • The In 2 O 3 octahedrons could significantly enhance room temperature NO 2 gas sensing performance. - Abstract: Indium oxide octahedrons were prepared on glass substrates through a mild route based on sol–gel technique. The preparation possesses characteristics including low temperature, catalyst-free and large production, which is much distinguished from the chemical-vapor-deposition based methods that usually applied to prepare indium oxide octahedrons. Detailed characterization revealed that the indium oxide octahedrons were single crystalline, with {1 1 1} crystal facets exposed. It was found that the spin-coating technique was key for achieving the indium oxide crystals with octahedron morphology. The probable formation mechanism of the indium oxide octahedrons was proposed based on the experiment results. Room temperature NO 2 gas sensing measurements exhibited that the indium oxide octahedrons could significantly enhance the sensing performance in comparison with the plate-like indium oxide particles that prepared from the dip-coated gel films, which was attributed to the abundant sharp edges and tips as well as the special {1 1 1} crystal facets exposed that the former possessed. Such a simple wet-chemical based method to prepare indium oxide octahedrons with large-scale production is promising to provide the advanced materials that can be applied in wide fields like gas sensing, solar energy conversion, field emission, and so on

  11. Hierarchical fiber-optic-based sensing system: impact damage monitoring of large-scale CFRP structures

    International Nuclear Information System (INIS)

    Minakuchi, Shu; Banshoya, Hidehiko; Takeda, Nobuo; Tsukamoto, Haruka

    2011-01-01

    This study proposes a novel fiber-optic-based hierarchical sensing concept for monitoring randomly induced damage in large-scale composite structures. In a hierarchical system, several kinds of specialized devices are hierarchically combined to form a sensing network. Specifically, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with an optical fiber network through transducing mechanisms. The distributed devices detect damage, and the fiber-optic network gathers the damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of a hierarchical sensing system through comparison with existing fiber-optic-based systems, and an impact damage detection system was then proposed to validate the new concept. The sensor devices were developed based on comparative vacuum monitoring (CVM), and Brillouin-based distributed strain measurement was utilized to identify damaged areas. Verification tests were conducted step-by-step, beginning with a basic test using a single sensor unit, and, finally, the proposed monitoring system was successfully verified using a carbon fiber reinforced plastic (CFRP) fuselage demonstrator. It was clearly confirmed that the hierarchical system has better repairability, higher robustness, and a wider monitorable area compared to existing systems

  12. A robust power spectrum split cancellation-based spectrum sensing method for cognitive radio systems

    International Nuclear Information System (INIS)

    Qi Pei-Han; Li Zan; Si Jiang-Bo; Gao Rui

    2014-01-01

    Spectrum sensing is an essential component to realize the cognitive radio, and the requirement for real-time spectrum sensing in the case of lacking prior information, fading channel, and noise uncertainty, indeed poses a major challenge to the classical spectrum sensing algorithms. Based on the stochastic properties of scalar transformation of power spectral density (PSD), a novel spectrum sensing algorithm, referred to as the power spectral density split cancellation method (PSC), is proposed in this paper. The PSC makes use of a scalar value as a test statistic, which is the ratio of each subband power to the full band power. Besides, by exploiting the asymptotic normality and independence of Fourier transform, the distribution of the ratio and the mathematical expressions for the probabilities of false alarm and detection in different channel models are derived. Further, the exact closed-form expression of decision threshold is calculated in accordance with Neyman—Pearson criterion. Analytical and simulation results show that the PSC is invulnerable to noise uncertainty, and can achive excellent detection performance without prior knowledge in additive white Gaussian noise and flat slow fading channels. In addition, the PSC benefits from a low computational cost, which can be completed in microseconds. (interdisciplinary physics and related areas of science and technology)

  13. A robust power spectrum split cancellation-based spectrum sensing method for cognitive radio systems

    Science.gov (United States)

    Qi, Pei-Han; Li, Zan; Si, Jiang-Bo; Gao, Rui

    2014-12-01

    Spectrum sensing is an essential component to realize the cognitive radio, and the requirement for real-time spectrum sensing in the case of lacking prior information, fading channel, and noise uncertainty, indeed poses a major challenge to the classical spectrum sensing algorithms. Based on the stochastic properties of scalar transformation of power spectral density (PSD), a novel spectrum sensing algorithm, referred to as the power spectral density split cancellation method (PSC), is proposed in this paper. The PSC makes use of a scalar value as a test statistic, which is the ratio of each subband power to the full band power. Besides, by exploiting the asymptotic normality and independence of Fourier transform, the distribution of the ratio and the mathematical expressions for the probabilities of false alarm and detection in different channel models are derived. Further, the exact closed-form expression of decision threshold is calculated in accordance with Neyman—Pearson criterion. Analytical and simulation results show that the PSC is invulnerable to noise uncertainty, and can achive excellent detection performance without prior knowledge in additive white Gaussian noise and flat slow fading channels. In addition, the PSC benefits from a low computational cost, which can be completed in microseconds.

  14. Information Extraction of Tourist Geological Resources Based on 3d Visualization Remote Sensing Image

    Science.gov (United States)

    Wang, X.

    2018-04-01

    Tourism geological resources are of high value in admiration, scientific research and universal education, which need to be protected and rationally utilized. In the past, most of the remote sensing investigations of tourism geological resources used two-dimensional remote sensing interpretation method, which made it difficult for some geological heritages to be interpreted and led to the omission of some information. This aim of this paper is to assess the value of a method using the three-dimensional visual remote sensing image to extract information of geological heritages. skyline software system is applied to fuse the 0.36 m aerial images and 5m interval DEM to establish the digital earth model. Based on the three-dimensional shape, color tone, shadow, texture and other image features, the distribution of tourism geological resources in Shandong Province and the location of geological heritage sites were obtained, such as geological structure, DaiGu landform, granite landform, Volcanic landform, sandy landform, Waterscapes, etc. The results show that using this method for remote sensing interpretation is highly recognizable, making the interpretation more accurate and comprehensive.

  15. Context Sensing System Analysis for Privacy Preservation Based on Game Theory.

    Science.gov (United States)

    Wang, Shengling; Li, Luyun; Sun, Weiman; Guo, Junqi; Bie, Rongfang; Lin, Kai

    2017-02-10

    In a context sensing system in which a sensor-equipped mobile phone runs an unreliable context-aware application, the application can infer the user's contexts, based on which it provides personalized services. However, the application may sell the user's contexts to some malicious adversaries to earn extra profits, which will hinder its widespread use. In the real world, the actions of the user, the application and the adversary in the context sensing system affect each other, so that their payoffs are constrained mutually. To figure out under which conditions they behave well (the user releases, the application does not leak and the adversary does not retrieve the context), we take advantage of game theory to analyze the context sensing system. We use the extensive form game and the repeated game, respectively, to analyze two typical scenarios, single interaction and multiple interaction among three players, from which Nash equilibriums and cooperation conditions are obtained. Our results show that the reputation mechanism for the context-sensing system in the former scenario is crucial to privacy preservation, so is the extent to which the participants are concerned about future payoffs in the latter one.

  16. [Research on symmetrical optical waveguide based surface plasmon resonance sensing with spectral interrogation].

    Science.gov (United States)

    Zhang, Yi-long; Liu, Le; Guo, Jun; Zhang, Peng-fei; Guo, Ji-hua; Ma, Hui; He, Yong-hong

    2015-02-01

    Surface plasmon resonance (SPR) sensors with spectral interrogation can adopt fiber to transmit light signals, thus leaving the sensing part separated, which is very convenient for miniaturization, remote-sensing and on-site analysis. Symmetrical optical waveguide (SOW) SPR has the same refractive index of the-two buffer media layers adjacent to the metal film, resulting in longer propagation distance, deeper penetration depth and better performance compared to conventional SPR In the present paper, we developed a symmetrical optical, waveguide (SOW) SPR sensor with wavelength interrogation. In the system, MgF2-Au-MgF2 film was used as SOW module for glucose sensing, and a fiber based light source and detection was used in the spectral interrogation. In the experiment, a refractive index resolution of 2.8 x 10(-7) RIU in fluid protocol was acquired. This technique provides advantages of high resolution and could have potential use in compact design, on-site analysis and remote sensing.

  17. Compressed sensing techniques for receiver based post-compensation of transmitter's nonlinear distortions in OFDM systems

    KAUST Repository

    Owodunni, Damilola S.

    2014-04-01

    In this paper, compressed sensing techniques are proposed to linearize commercial power amplifiers driven by orthogonal frequency division multiplexing signals. The nonlinear distortion is considered as a sparse phenomenon in the time-domain, and three compressed sensing based algorithms are presented to estimate and compensate for these distortions at the receiver using a few and, at times, even no frequency-domain free carriers (i.e. pilot carriers). The first technique is a conventional compressed sensing approach, while the second incorporates a priori information about the distortions to enhance the estimation. Finally, the third technique involves an iterative data-aided algorithm that does not require any pilot carriers and hence allows the system to work at maximum bandwidth efficiency. The performances of all the proposed techniques are evaluated on a commercial power amplifier and compared. The error vector magnitude and symbol error rate results show the ability of compressed sensing to compensate for the amplifier\\'s nonlinear distortions. © 2013 Elsevier B.V.

  18. Protecting Mobile Crowd Sensing against Sybil Attacks Using Cloud Based Trust Management System

    Directory of Open Access Journals (Sweden)

    Shih-Hao Chang

    2016-01-01

    Full Text Available Mobile crowd sensing (MCS arises as a new sensing paradigm, which leverages citizens for large-scale sensing by various mobile devices to efficiently collect and share local information. Unlike other MCS application challenges that consider user privacy and data trustworthiness, this study focuses on the network trustworthiness problem, namely, Sybil attacks in MCS network. The Sybil attack in computer security is a type of security attack, which illegally forges multiple identities in peer-to-peer networks, namely, Sybil identities. These Sybil identities will falsify multiple identities that negatively influence the effectiveness of sensing data in this MCS network or degrading entire network performance. To cope with this problem, a cloud based trust management scheme (CbTMS was proposed to detect Sybil attacks in the MCS network. The CbTMS was proffered for performing active and passive checking scheme, in addition to the mobile PCS trustworthiness management, and includes a decision tree algorithm, to verify the covered nodes in the MCS network. Simulation studies show that our CbTMS can efficiently detect the malicious Sybil nodes in the network and cause 6.87 Wh power reduction compared with other malicious Sybil node attack mode.

  19. High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

    Science.gov (United States)

    Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

    2018-04-01

    With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

  20. The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing.

    Science.gov (United States)

    Ma, Teng; Li, Hui; Yang, Hao; Lv, Xulin; Li, Peiyang; Liu, Tiejun; Yao, Dezhong; Xu, Peng

    2017-01-01

    Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong background EEG activities, and an effective approach is needed to extract the corresponding mVEP features to perform task recognition for BCI control. In the current study, we combine deep learning with compressed sensing to mine discriminative mVEP information to improve the mVEP BCI performance. The deep learning and compressed sensing approach can generate the multi-modality features which can effectively improve the BCI performance with approximately 3.5% accuracy incensement over all 11 subjects and is more effective for those subjects with relatively poor performance when using the conventional features. Compared with the conventional amplitude-based mVEP feature extraction approach, the deep learning and compressed sensing approach has a higher classification accuracy and is more effective for subjects with relatively poor performance. According to the results, the deep learning and compressed sensing approach is more effective for extracting the mVEP feature to construct the corresponding BCI system, and the proposed feature extraction framework is easy to extend to other types of BCIs, such as motor imagery (MI), steady-state visual evoked potential (SSVEP)and P300. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. A high spatial resolution distributed optical fiber grating sensing system based on OFDR

    Science.gov (United States)

    Dong, Ke; Xiong, Yuchuan; Wen, Hongqiao; Tong, Xinlin; Zhang, Cui; Deng, Chengwei

    2017-10-01

    A distributed optical fiber grating sensing system with large capacity and high spatial resolution is presented. Since highdensity identical weak grating array was utilized as sensing fiber, the multiplexing number was greatly increased, meanwhile, optical frequency domain reflectometry (OFDR) technology was used to implement high resolution distributed sensing system. In order to eliminate the nonlinear effect of tunable light source, a windowed FFT algorithm based on cubic spline interpolation was applied. The feasibility of the algorithm was experimentally testified, ultimately, the spatial resolution of system can reach mm-level. The influence of the crosstalk signal in the grating array on the OFDR system was analyzed. A method that a long enough delay fiber was added before the first FBG to remove crosstalk signal was proposed. The experiment was verified using an optical fiber with 113 uniform Bragg gratings at an interval of 10cm whose reflectivity are less than 1%. It demonstrates that crosstalk signal and measurement signal can be completely separated in the distance domain after adding a long enough delay fiber. Finally, the temperature experiment of distributed grating sensing system was carried out. The results display that each raster's center wavelength in the fiber link is independent of each other and the center wavelength drift has a good linear relationship with the temperature. The sensitivity of linear fitting is equal to 11.1pm/°C.

  2. A compressed sensing based method with support refinement for impulse noise cancelation in DSL

    KAUST Repository

    Quadeer, Ahmed Abdul

    2013-06-01

    This paper presents a compressed sensing based method to suppress impulse noise in digital subscriber line (DSL). The proposed algorithm exploits the sparse nature of the impulse noise and utilizes the carriers, already available in all practical DSL systems, for its estimation and cancelation. Specifically, compressed sensing is used for a coarse estimate of the impulse position, an a priori information based maximum aposteriori probability (MAP) metric for its refinement, followed by least squares (LS) or minimum mean square error (MMSE) estimation for estimating the impulse amplitudes. Simulation results show that the proposed scheme achieves higher rate as compared to other known sparse estimation algorithms in literature. The paper also demonstrates the superior performance of the proposed scheme compared to the ITU-T G992.3 standard that utilizes RS-coding for impulse noise refinement in DSL signals. © 2013 IEEE.

  3. Micro-patterned graphene-based sensing skins for human physiological monitoring

    Science.gov (United States)

    Wang, Long; Loh, Kenneth J.; Chiang, Wei-Hung; Manna, Kausik

    2018-03-01

    Ultrathin, flexible, conformal, and skin-like electronic transducers are emerging as promising candidates for noninvasive and nonintrusive human health monitoring. In this work, a wearable sensing membrane is developed by patterning a graphene-based solution onto ultrathin medical tape, which can then be attached to the skin for monitoring human physiological parameters and physical activity. Here, the sensor is validated for monitoring finger bending/movements and for recognizing hand motion patterns, thereby demonstrating its future potential for evaluating athletic performance, physical therapy, and designing next-generation human-machine interfaces. Furthermore, this study also quantifies the sensor’s ability to monitor eye blinking and radial pulse in real-time, which can find broader applications for the healthcare sector. Overall, the printed graphene-based sensing skin is highly conformable, flexible, lightweight, nonintrusive, mechanically robust, and is characterized by high strain sensitivity.

  4. A facile fluorescent "turn-off" method for sensing paraquat based on pyranine-paraquat interaction

    Science.gov (United States)

    Zhao, Zuzhi; Zhang, Fengwei; Zhang, Zipin

    2018-06-01

    Development of a technically simple yet effective method for paraquat (PQ) detection is of great importance due to its high clinical and environmental relevance. In this study, we developed a pyranine-based fluorescent "turn-off" method for PQ sensing based on pyranine-PQ interaction. We investigated the dependence of analytical performance of this method on the experimental conditions, such as the ion strength, medium pH, and so on. Under the optimized conditions, the method is sensitive and selective, and could be used for PQ detection in real-world sample. This study essentially provides a readily accessible fluorescent system for PQ sensing which is cheap, robust, and technically simple, and it is envisaged to find more interesting clinical and environmental applications.

  5. Advances in electrospun carbon fiber-based electrochemical sensing platforms for bioanalytical applications.

    Science.gov (United States)

    Mao, Xianwen; Tian, Wenda; Hatton, T Alan; Rutledge, Gregory C

    2016-02-01

    Electrochemical sensing is an efficient and inexpensive method for detection of a range of chemicals of biological, clinical, and environmental interest. Carbon materials-based electrodes are commonly employed for the development of electrochemical sensors because of their low cost, biocompatibility, and facile electron transfer kinetics. Electrospun carbon fibers (ECFs), prepared by electrospinning of a polymeric precursor and subsequent thermal treatment, have emerged as promising carbon systems for biosensing applications since the electrochemical properties of these carbon fibers can be easily modified by processing conditions and post-treatment. This review addresses recent progress in the use of ECFs for sensor fabrication and analyte detection. We focus on the modification strategies of ECFs and identification of the key components that impart the bioelectroanalytical activities, and point out the future challenges that must be addressed in order to advance the fundamental understanding of the ECF electrochemistry and to realize the practical applications of ECF-based sensing devices.

  6. Magnetic Field Sensing Based on Bi-Tapered Optical Fibers Using Spectral Phase Analysis.

    Science.gov (United States)

    Herrera-Piad, Luis A; Haus, Joseph W; Jauregui-Vazquez, Daniel; Sierra-Hernandez, Juan M; Estudillo-Ayala, Julian M; Lopez-Dieguez, Yanelis; Rojas-Laguna, Roberto

    2017-10-20

    A compact, magnetic field sensor system based on a short, bi-tapered optical fiber (BTOF) span lying on a magnetic tape was designed, fabricated, and characterized. We monitored the transmission spectrum from a broadband light source, which displayed a strong interference signal. After data collection, we applied a phase analysis of the interference optical spectrum. We here report the results on two fabricated, BTOFs with different interference spectrum characteristics; we analyzed the signal based on the interference between a high-order modal component and the core fiber mode. The sensor exhibited a linear response for magnetic field increments, and we achieved a phase sensitivity of around 0.28 rad/mT. The sensing setup presented remote sensing operation and low-cost transducer magnetic material.

  7. Magnetic Field Sensing Based on Bi-Tapered Optical Fibers Using Spectral Phase Analysis

    Directory of Open Access Journals (Sweden)

    Luis A. Herrera-Piad

    2017-10-01

    Full Text Available A compact, magnetic field sensor system based on a short, bi-tapered optical fiber (BTOF span lying on a magnetic tape was designed, fabricated, and characterized. We monitored the transmission spectrum from a broadband light source, which displayed a strong interference signal. After data collection, we applied a phase analysis of the interference optical spectrum. We here report the results on two fabricated, BTOFs with different interference spectrum characteristics; we analyzed the signal based on the interference between a high-order modal component and the core fiber mode. The sensor exhibited a linear response for magnetic field increments, and we achieved a phase sensitivity of around 0.28 rad/mT. The sensing setup presented remote sensing operation and low-cost transducer magnetic material.

  8. Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

    Science.gov (United States)

    Sofina, N.; Ehlers, M.

    2012-08-01

    High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

  9. GEOGRAPHIC INFORMATION SYSTEM AND REMOTE SENSING BASED DISASTER MANAGEMENT AND DECISION SUPPORT PLATFORM: AYDES

    OpenAIRE

    Keskin, İ.; Akbaba, N.; Tosun, M.; Tüfekçi, M. K.; Bulut, D.; Avcı, F.; Gökçe, O.

    2018-01-01

    The accelerated developments in information technology in recent years, increased the amount of usage of Geographic Information Systems (GIS) and Remote Sensing (RS) in disaster management considerably and the access from mobile and web-based platforms to continuous, accurate and sufficient data needed for decision-making became easier accordingly. The Disaster Management and Decision Support System (AYDES) has been developed with the purpose of managing the disaster and emergency manageme...

  10. Connotations of pixel-based scale effect in remote sensing and the modified fractal-based analysis method

    Science.gov (United States)

    Feng, Guixiang; Ming, Dongping; Wang, Min; Yang, Jianyu

    2017-06-01

    Scale problems are a major source of concern in the field of remote sensing. Since the remote sensing is a complex technology system, there is a lack of enough cognition on the connotation of scale and scale effect in remote sensing. Thus, this paper first introduces the connotations of pixel-based scale and summarizes the general understanding of pixel-based scale effect. Pixel-based scale effect analysis is essentially important for choosing the appropriate remote sensing data and the proper processing parameters. Fractal dimension is a useful measurement to analysis pixel-based scale. However in traditional fractal dimension calculation, the impact of spatial resolution is not considered, which leads that the scale effect change with spatial resolution can't be clearly reflected. Therefore, this paper proposes to use spatial resolution as the modified scale parameter of two fractal methods to further analyze the pixel-based scale effect. To verify the results of two modified methods (MFBM (Modified Windowed Fractal Brownian Motion Based on the Surface Area) and MDBM (Modified Windowed Double Blanket Method)); the existing scale effect analysis method (information entropy method) is used to evaluate. And six sub-regions of building areas and farmland areas were cut out from QuickBird images to be used as the experimental data. The results of the experiment show that both the fractal dimension and information entropy present the same trend with the decrease of spatial resolution, and some inflection points appear at the same feature scales. Further analysis shows that these feature scales (corresponding to the inflection points) are related to the actual sizes of the geo-object, which results in fewer mixed pixels in the image, and these inflection points are significantly indicative of the observed features. Therefore, the experiment results indicate that the modified fractal methods are effective to reflect the pixel-based scale effect existing in remote sensing

  11. In-service communication channel sensing based on reflectometry for TWDM-PON systems

    Science.gov (United States)

    Iida, Daisuke; Kuwano, Shigeru; Terada, Jun

    2014-05-01

    Many base stations are accommodated in TWDM-PON based mobile backhaul and fronthaul networks for future radio access, and failed connections in an optical network unit (ONU) wavelength channel severely degrade system performance. A cost effective in-service ONU wavelength channel monitor is essential to ensure proper system operation without failed connections. To address this issue we propose a reflectometry-based remote sensing method that provides wavelength channel information with the optical line terminal (OLT)-ONU distance. The method realizes real-time monitoring of ONU wavelength channels without signal quality degradation. Experimental results show it achieves wavelength channel distinction with high distance resolution.

  12. Crack identification for reinforced concrete using PZT based smart rebar active sensing diagnostic network

    Science.gov (United States)

    Song, N. N.; Wu, F.

    2016-04-01

    An active sensing diagnostic system using PZT based smart rebar for SHM of RC structure has been currently under investigation. Previous test results showed that the system could detect the de-bond of concrete from reinforcement, and the diagnostic signals were increased exponentially with the de-bonding size. Previous study also showed that the smart rebar could function well like regular reinforcement to undertake tension stresses. In this study, a smart rebar network has been used to detect the crack damage of concrete based on guided waves. Experimental test has been carried out for the study. In the test, concrete beams with 2 reinforcements have been built. 8 sets of PZT elements were mounted onto the reinforcement bars in an optimized way to form an active sensing diagnostic system. A 90 kHz 5-cycle Hanning-windowed tone burst was used as input. Multiple cracks have been generated on the concrete structures. Through the guided bulk waves propagating in the structures from actuators and sensors mounted from different bars, crack damage could be detected clearly. Cases for both single and multiple cracks were tested. Different crack depths from the surface and different crack numbers have been studied. Test result shows that the amplitude of sensor output signals is deceased linearly with a propagating crack, and is decreased exponentially with increased crack numbers. From the study, the active sensing diagnostic system using PZT based smart rebar network shows a promising way to provide concrete crack damage information through the "talk" among sensors.

  13. Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

    Directory of Open Access Journals (Sweden)

    M. Schneider

    2012-12-01

    Full Text Available Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water, long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change. We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere to 8 km (in the upper troposphere and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model. We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

  14. Ground-based remote sensing of tropospheric water vapour isotopologues within the project MUSICA

    Science.gov (United States)

    Schneider, M.; Barthlott, S.; Hase, F.; González, Y.; Yoshimura, K.; García, O. E.; Sepúlveda, E.; Gomez-Pelaez, A.; Gisi, M.; Kohlhepp, R.; Dohe, S.; Blumenstock, T.; Wiegele, A.; Christner, E.; Strong, K.; Weaver, D.; Palm, M.; Deutscher, N. M.; Warneke, T.; Notholt, J.; Lejeune, B.; Demoulin, P.; Jones, N.; Griffith, D. W. T.; Smale, D.; Robinson, J.

    2012-12-01

    Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

  15. Soybean yield estimation by an agrometeorological model in a GIS Produtividade de soja estimada por modelo agrometeorológico num SIG

    Directory of Open Access Journals (Sweden)

    Luciana Miura Sugawara Berka

    2003-01-01

    Full Text Available Agrometeorological models interfaced with the Geographic Information System - GIS are an alternative to simulate and quantify the effect of weather spatial and temporal variability on crop yield. The objective of this work was to adapt and interface an agrometeorological model with a GIS to estimate soybean [Glycine max (L. Merr.] yield. Yield estimates were generated for 144 municipalities in the State of Paraná, Brazil, responsible for 90% of the soybean production in the State, from 1996/1997 to 2000/2001. The model uses agronomical parameters and meteorological data to calculate maximum yield which will be penalized under drought stress. Comparative analyses between the yield estimated by the model and that reported by the Paraná State Department of Agriculture (SEAB were performed using the "t" test for paired observations. For the 1996/1997 year the model overestimated yield by 10.8%, which may be attributed to the occurrence of fungal diseases not considered by the model. For 1997/1998, 1998/1999 and 1999/2000 no differences (P > 0.05 were found between the yield estimated by the model and SEAB's data. For 2000/2001 the model underestimated yield by 10.5% and the cause for this difference needs further investigation. The model interfaced with a GIS is an useful tool to monitor soybean crop during growing season to estimate crop yield.Os modelos agrometeorológicos integrados em Sistemas de Informação Geográfica - SIG são uma alternativa para simular e quantificar o efeito da variabilidade espacial e temporal do clima sobre a produtividade agrícola. O objetivo deste trabalho foi adaptar e integrar um modelo agrometeorológico num SIG para estimar a produtividade da soja [Glycine max (L. Merr.]. Foram geradas estimativas de produtividade para 144 municípios do Estado do Paraná, responsáveis por 90% da produção de soja no Estado, em cinco anos-safra no período de 1996/1997 a 2000/2001. O modelo utiliza parâmetros agronômicos e

  16. Uniform competency-based local feature extraction for remote sensing images

    Science.gov (United States)

    Sedaghat, Amin; Mohammadi, Nazila

    2018-01-01

    Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

  17. A droplet-based passive force sensor for remote tactile sensing applications

    Science.gov (United States)

    Nie, Baoqing; Yao, Ting; Zhang, Yiqiu; Liu, Jian; Chen, Xinjian

    2018-01-01

    A droplet-based flexible wireless force sensor has been developed for remote tactile-sensing applications. By integration of a droplet-based capacitive sensing unit and two circular planar coils, this inductor-capacitor (LC) passive sensor offers a platform for the mechanical force detection in a wireless transmitting mode. Under external loads, the membrane surface of the sensor deforms the underlying elastic droplet uniformly, introducing a capacitance response in tens of picofarads. The LC circuit transduces the applied force into corresponding variations of its resonance frequency, which is detected by an external electromagnetic coupling coil. Specifically, the liquid droplet features a mechanosensitive plasticity, which results in an increased device sensitivity as high as 2.72 MHz N-1. The high dielectric property of the droplet endows our sensor with high tolerance for noise and large capacitance values (20-40 pF), the highest value in the literature for the LC passive devices in comparable dimensions. It achieves excellent reproducibility under periodical loads ranging from 0 to 1.56 N and temperature fluctuations ranging from 10 °C to 55 °C. As an interesting conceptual demonstration, the flexible device has been configured into a fingertip-amounted setting in a highly compact package (of 11 mm × 11 mm × 0.25 mm) for remote contact force sensing in the table tennis game.

  18. Magnetic resonance imaging-compatible tactile sensing device based on a piezoelectric array.

    Science.gov (United States)

    Hamed, Abbi; Masamune, Ken; Tse, Zion Tsz Ho; Lamperth, Michael; Dohi, Takeyoshi

    2012-07-01

    Minimally invasive surgery is a widely used medical technique, one of the drawbacks of which is the loss of direct sense of touch during the operation. Palpation is the use of fingertips to explore and make fast assessments of tissue morphology. Although technologies are developed to equip minimally invasive surgery tools with haptic feedback capabilities, the majority focus on tissue stiffness profiling and tool-tissue interaction force measurement. For greatly increased diagnostic capability, a magnetic resonance imaging-compatible tactile sensor design is proposed, which allows minimally invasive surgery to be performed under image guidance, combining the strong capability of magnetic resonance imaging soft tissue and intuitive palpation. The sensing unit is based on a piezoelectric sensor methodology, which conforms to the stringent mechanical and electrical design requirements imposed by the magnetic resonance environment The sensor mechanical design and the device integration to a 0.2 Tesla open magnetic resonance imaging scanner are described, together with the device's magnetic resonance compatibility testing. Its design limitations and potential future improvements are also discussed. A tactile sensing unit based on a piezoelectric sensor principle is proposed, which is designed for magnetic resonance imaging guided interventions.

  19. An Adaptive Joint Sparsity Recovery for Compressive Sensing Based EEG System

    Directory of Open Access Journals (Sweden)

    Hamza Djelouat

    2017-01-01

    Full Text Available The last decade has witnessed tremendous efforts to shape the Internet of things (IoT platforms to be well suited for healthcare applications. These platforms are comprised of a network of wireless sensors to monitor several physical and physiological quantities. For instance, long-term monitoring of brain activities using wearable electroencephalogram (EEG sensors is widely exploited in the clinical diagnosis of epileptic seizures and sleeping disorders. However, the deployment of such platforms is challenged by the high power consumption and system complexity. Energy efficiency can be achieved by exploring efficient compression techniques such as compressive sensing (CS. CS is an emerging theory that enables a compressed acquisition using well-designed sensing matrices. Moreover, system complexity can be optimized by using hardware friendly structured sensing matrices. This paper quantifies the performance of a CS-based multichannel EEG monitoring. In addition, the paper exploits the joint sparsity of multichannel EEG using subspace pursuit (SP algorithm as well as a designed sparsifying basis in order to improve the reconstruction quality. Furthermore, the paper proposes a modification to the SP algorithm based on an adaptive selection approach to further improve the performance in terms of reconstruction quality, execution time, and the robustness of the recovery process.

  20. Plant response-based sensing for control starategies in sustainable greenhouse production

    International Nuclear Information System (INIS)

    Kacira, M.; Sase, S.; Okushima, L.; Ling, P.P.

    2005-01-01

    The effect of environmental variability is one of the major concerns in experimental design for both research in plant systems and greenhouse plant production. Microclimates surrounding plants are not usually uniform. Therefore, many samples and sensors are required to obtain a true representation of the plant population. A plant monitoring system capable of reducing the required number of samples by reducing environmental variability would be more advantageous. To better understand plant-environment interaction, it is essential to study plants, microclimate surrounding the plants and the growth media. To achieve this, the monitoring system must be equipped with proper instrumentation. To achieve proper management practices and sustainable greenhouse production, it is essential first to understand plants and their interactions with their surroundings and then establish plant response-based sensing and control strategies for greenhouse processes. Therefore, an effort was conducted to review and discuss current sensing and control strategies in greenhouse research and plant production and provide recommendations on plant response-based sensing and control strategies for sustainable greenhouse production

  1. SERS-Fluorescence Dual-Mode pH-Sensing Method Based on Janus Microparticles.

    Science.gov (United States)

    Yue, Shuai; Sun, Xiaoting; Wang, Ning; Wang, Yaning; Wang, Yue; Xu, Zhangrun; Chen, Mingli; Wang, Jianhua

    2017-11-15

    A surface-enhanced Raman scattering (SERS)-fluorescence dual-mode pH-sensing method based on Janus microgels was developed, which combined the advantages of high specificity offered by SERS and fast imaging afforded by fluorescence. Dual-mode probes, pH-dependent 4-mercaptobenzoic acid, and carbon dots were individually encapsulated in the independent hemispheres of Janus microparticles fabricated via a centrifugal microfluidic chip. On the basis of the obvious volumetric change of hydrogels in different pHs, the Janus microparticles were successfully applied for sensitive and reliable pH measurement from 1.0 to 8.0, and the two hemispheres showed no obvious interference. The proposed method addressed the limitation that sole use of the SERS-based pH sensing usually failed in strong acidic media. The gastric juice pH and extracellular pH change were measured separately in vitro using the Janus microparticles, which confirmed the validity of microgels for pH sensing. The microparticles exhibited good stability, reversibility, biocompatibility, and ideal semipermeability for avoiding protein contamination, and they have the potential to be implantable sensors to continuously monitor pH in vivo.

  2. RF Spectrum Sensing Based on an Overdamped Nonlinear Oscillator Ring for Cognitive Radios

    Directory of Open Access Journals (Sweden)

    Zhi-Ling Tang

    2016-06-01

    Full Text Available Existing spectrum-sensing techniques for cognitive radios require an analog-to-digital converter (ADC to work at high dynamic range and a high sampling rate, resulting in high cost. Therefore, in this paper, a spectrum-sensing method based on a unidirectionally coupled, overdamped nonlinear oscillator ring is proposed. First, the numerical model of such a system is established based on the circuit of the nonlinear oscillator. Through numerical analysis of the model, the critical condition of the system’s starting oscillation is determined, and the simulation results of the system’s response to Gaussian white noise and periodic signal are presented. The results show that once the radio signal is input into the system, it starts oscillating when in the critical region, and the oscillating frequency of each element is fo/N, where fo is the frequency of the radio signal and N is the number of elements in the ring. The oscillation indicates that the spectrum resources at fo are occupied. At the same time, the sampling rate required for an ADC is reduced to the original value, 1/N. A prototypical circuit to verify the functionality of the system is designed, and the sensing bandwidth of the system is measured.

  3. gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks

    KAUST Repository

    Al-Halafi, Abdullah

    2016-09-08

    Wireless sensor networks (WSN) are widely used to sense and measure physical conditions for different purposes and within different regions. However due to the limited lifetime of the sensor\\'s energy source, many efforts are made to design energy efficient WSN. As a result, many techniques were presented in the literature such as power adaptation, sleep and wake-up, and scheduling in order to enhance WSN lifetime. These techniques where presented separately and shown to achieve some gain in terms of energy efficiency. In this paper, we present an energy efficient cross layer design for WSN that we named \\'green Task-Based Sensing\\' (gTBS) scheme. The gTBS design is a task based sensing scheme that not only prevents wasting power in unnecessary signaling, but also utilizes several techniques for achieving reliable and energy efficient WSN. The proposed gTBS combines the power adaptation with a sleep and wake-up technique that allows inactive nodes to sleep. Also, it adopts a gradient-oriented unicast approach to overcome the synchronization problem, minimize network traffic hurdles, and significantly reduce the overall power consumption of the network. We implement the gTBS on a testbed and we show that it reduces the power consumption by a factor of 20%-55% compared to traditional TBS. It also reduces the delay by 54%-145% and improves the delivery ratio by 24%-73%. © 2016 IEEE.

  4. Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

    International Nuclear Information System (INIS)

    Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Chenwei, Nie; Dong, Ren

    2014-01-01

    To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps

  5. Secondary access based on sensing and primary ARQ feedback in spectrum sharing systems

    KAUST Repository

    Hamza, Doha R.

    2012-04-01

    In the context of primary/secondary spectrum sharing, we propose a randomized secondary access strategy with access probabilities that are a function of both the primary automatic repeat request (ARQ) feedback and the spectrum sensing outcome. The primary terminal operates in a time slotted fashion and is active only when it has a packet to send. The primary receiver can send a positive acknowledgment (ACK) when the received packet is decoded correctly. Lack of ARQ feedback is interpreted as erroneous reception or inactivity. We call this the explicit ACK scheme. The primary receiver may also send a negative acknowledgment (NACK) when the packet is received in error. Lack of ARQ feedback is interpreted as an ACK or no-transmission. This is called the explicit NACK scheme. Under both schemes, when the primary feedback is interpreted as a NACK, the secondary user assumes that there will be retransmission in the next slot and accesses the channel with a certain probability. When the primary feedback is interpreted as an ACK, the secondary user accesses the channel with either one of two probabilities based on the sensing outcome. Under these settings, we find the three optimal access probabilities via maximizing the secondary throughput given a constraint on the primary throughput. We compare the performance of the explicit ACK and explicit NACK schemes and contrast them with schemes based on either sensing or primary ARQ feedback only. © 2012 IEEE.

  6. RESEARCH ON REMOTE SENSING GEOLOGICAL INFORMATION EXTRACTION BASED ON OBJECT ORIENTED CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Gao

    2018-04-01

    Full Text Available The northern Tibet belongs to the Sub cold arid climate zone in the plateau. It is rarely visited by people. The geological working conditions are very poor. However, the stratum exposures are good and human interference is very small. Therefore, the research on the automatic classification and extraction of remote sensing geological information has typical significance and good application prospect. Based on the object-oriented classification in Northern Tibet, using the Worldview2 high-resolution remote sensing data, combined with the tectonic information and image enhancement, the lithological spectral features, shape features, spatial locations and topological relations of various geological information are excavated. By setting the threshold, based on the hierarchical classification, eight kinds of geological information were classified and extracted. Compared with the existing geological maps, the accuracy analysis shows that the overall accuracy reached 87.8561 %, indicating that the classification-oriented method is effective and feasible for this study area and provides a new idea for the automatic extraction of remote sensing geological information.

  7. A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition.

    Science.gov (United States)

    Ciotti, Simone; Battaglia, Edoardo; Carbonaro, Nicola; Bicchi, Antonio; Tognetti, Alessandro; Bianchi, Matteo

    2016-06-02

    Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.

  8. A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition

    Directory of Open Access Journals (Sweden)

    Simone Ciotti

    2016-06-01

    Full Text Available Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements of wearable hand pose reconstruction (HPR systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.

  9. Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

    Science.gov (United States)

    Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

    2017-12-01

    In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

  10. DrivingSense: Dangerous Driving Behavior Identification Based on Smartphone Autocalibration

    Directory of Open Access Journals (Sweden)

    Chunmei Ma

    2017-01-01

    Full Text Available Since pervasive smartphones own advanced computing capability and are equipped with various sensors, they have been used for dangerous driving behaviors detection, such as drunk driving. However, sensory data gathered by smartphones are noisy, which results in inaccurate driving behaviors estimations. Some existing works try to filter noise from sensor readings, but usually only the outlier data are filtered. The noises caused by hardware of the smartphone cannot be removed from the sensor reading. In this paper, we propose DrivingSense, a reliable dangerous driving behavior identification scheme based on smartphone autocalibration. We first theoretically analyze the impact of the sensor error on the vehicle driving behavior estimation. Then, we propose a smartphone autocalibration algorithm based on sensor noise distribution determination when a vehicle is being driven. DrivingSense leverages the corrected sensor parameters to identify three kinds of dangerous behaviors: speeding, irregular driving direction change, and abnormal speed control. We evaluate the effectiveness of our scheme under realistic environments. The results show that DrivingSense, on average, is able to detect the driving direction change event and abnormal speed control event with 93.95% precision and 90.54% recall, respectively. In addition, the speed estimation error is less than 2.1 m/s, which is an acceptable range.

  11. A real-time MTFC algorithm of space remote-sensing camera based on FPGA

    Science.gov (United States)

    Zhao, Liting; Huang, Gang; Lin, Zhe

    2018-01-01

    A real-time MTFC algorithm of space remote-sensing camera based on FPGA was designed. The algorithm can provide real-time image processing to enhance image clarity when the remote-sensing camera running on-orbit. The image restoration algorithm adopted modular design. The MTF measurement calculation module on-orbit had the function of calculating the edge extension function, line extension function, ESF difference operation, normalization MTF and MTFC parameters. The MTFC image filtering and noise suppression had the function of filtering algorithm and effectively suppressing the noise. The algorithm used System Generator to design the image processing algorithms to simplify the design structure of system and the process redesign. The image gray gradient dot sharpness edge contrast and median-high frequency were enhanced. The image SNR after recovery reduced less than 1 dB compared to the original image. The image restoration system can be widely used in various fields.

  12. Symmetric and asymmetric hybrid cryptosystem based on compressive sensing and computer generated holography

    Science.gov (United States)

    Ma, Lihong; Jin, Weimin

    2018-01-01

    A novel symmetric and asymmetric hybrid optical cryptosystem is proposed based on compressive sensing combined with computer generated holography. In this method there are six encryption keys, among which two decryption phase masks are different from the two random phase masks used in the encryption process. Therefore, the encryption system has the feature of both symmetric and asymmetric cryptography. On the other hand, because computer generated holography can flexibly digitalize the encrypted information and compressive sensing can significantly reduce data volume, what is more, the final encryption image is real function by phase truncation, the method favors the storage and transmission of the encryption data. The experimental results demonstrate that the proposed encryption scheme boosts the security and has high robustness against noise and occlusion attacks.

  13. Paper-based electrochemical sensing platform with integral battery and electrochromic read-out.

    Science.gov (United States)

    Liu, Hong; Crooks, Richard M

    2012-03-06

    We report a battery-powered, microelectrochemical sensing platform that reports its output using an electrochromic display. The platform is fabricated based on paper fluidics and uses a Prussian blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. The integrated metal/air battery powers both the electrochemical sensor and the electrochromic read-out, which are in electrical contact via a paper reservoir. The sample activates the battery and the presence of analyte in the sample initiates the color change of the Prussian blue spot. The entire system is assembled on the lab bench, without the need for cleanroom facilities. The applicability of the device to point-of-care sensing is demonstrated by qualitative detection of 0.1 mM glucose and H(2)O(2) in artificial urine samples.

  14. Portable laser spectrometer for airborne and ground-based remote sensing of geological CO2 emissions.

    Science.gov (United States)

    Queisser, Manuel; Burton, Mike; Allan, Graham R; Chiarugi, Antonio

    2017-07-15

    A 24 kg, suitcase sized, CW laser remote sensing spectrometer (LARSS) with a ~2 km range has been developed. It has demonstrated its flexibility in measuring both atmospheric CO2 from an airborne platform and terrestrial emission of CO2 from a remote mud volcano, Bledug Kuwu, Indonesia, from a ground-based sight. This system scans the CO2 absorption line with 20 discrete wavelengths, as opposed to the typical two-wavelength online offline instrument. This multi-wavelength approach offers an effective quality control, bias control, and confidence estimate of measured CO2 concentrations via spectral fitting. The simplicity, ruggedness, and flexibility in the design allow for easy transportation and use on different platforms with a quick setup in some of the most challenging climatic conditions. While more refinement is needed, the results represent a stepping stone towards widespread use of active one-sided gas remote sensing in the earth sciences.

  15. The orthorectified technology for UAV aerial remote sensing image based on the Programmable GPU

    International Nuclear Information System (INIS)

    Jin, Liu; Ying-cheng, Li; De-long, Li; Chang-sheng, Teng; Wen-hao, Zhang

    2014-01-01

    Considering the time requirements of the disaster emergency aerial remote sensing data acquisition and processing, this paper introduced the GPU parallel processing in orthorectification algorithm. Meanwhile, our experiments verified the correctness and feasibility of CUDA parallel processing algorithm, and the algorithm can effectively solve the problem of calculation large, time-consuming for ortho rectification process, realized fast processing of UAV airborne remote sensing image orthorectification based on GPU. The experimental results indicate that using the assumption of same accuracy of proposed method with CPU, the processing time is reduced obviously, maximum acceleration can reach more than 12 times, which greatly enhances the emergency surveying and mapping processing of rapid reaction rate, and has a broad application

  16. Hierarchical oxide-based composite nanostructures for energy, environmental, and sensing applications

    Science.gov (United States)

    Gao, Pu-Xian; Shimpi, Paresh; Cai, Wenjie; Gao, Haiyong; Jian, Dunliang; Wrobel, Gregory

    2011-02-01

    Self-assembled composite nanostructures integrate various basic nano-elements such as nanoparticles, nanofilms and nanowires toward realizing multifunctional characteristics, which promises an important route with potentially high reward for the fast evolving nanoscience and nanotechnology. A broad array of hierarchical metal oxide based nanostructures have been designed and fabricated in our research group, involving semiconductor metal oxides, ternary functional oxides such as perovskites and spinels and quaternary dielectric hydroxyl metal oxides with diverse applications in efficient energy harvesting/saving/utilization, environmental protection/control, chemical sensing and thus impacting major grand challenges in the area of materials and nanotechnology. Two of our latest research activities have been highlighted specifically in semiconductor oxide alloy nanowires and metal oxide/perovskite composite nanowires, which could impact the application sectors in ultraviolet/blue lighting, visible solar absorption, vehicle and industry emission control, chemical sensing and control for vehicle combustors and power plants.

  17. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

    Science.gov (United States)

    Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

    2016-01-01

    The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. PMID:26861345

  18. Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics

    Directory of Open Access Journals (Sweden)

    Kai Tang

    2018-05-01

    Full Text Available Non-contact human-computer interactions (HCI based on hand gestures have been widely investigated. Here, we present a novel method to locate the real-time position of the hand using the electrostatics of the human body. This method has many advantages, including a delay of less than one millisecond, low cost, and does not require a camera or wearable devices. A formula is first created to sense array signals with five spherical electrodes. Next, a solving algorithm for the real-time measured hand position is introduced and solving equations for three-dimensional coordinates of hand position are obtained. A non-contact real-time hand position sensing system was established to perform verification experiments, and the principle error of the algorithm and the systematic noise were also analyzed. The results show that this novel technology can determine the dynamic parameters of hand movements with good robustness to meet the requirements of complicated HCI.

  19. Micro-Doppler Ambiguity Resolution Based on Short-Time Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Jing-bo Zhuang

    2015-01-01

    Full Text Available When using a long range radar (LRR to track a target with micromotion, the micro-Doppler embodied in the radar echoes may suffer from ambiguity problem. In this paper, we propose a novel method based on compressed sensing (CS to solve micro-Doppler ambiguity. According to the RIP requirement, a sparse probing pulse train with its transmitting time random is designed. After matched filtering, the slow-time echo signals of the micromotion target can be viewed as randomly sparse sampling of Doppler spectrum. Select several successive pulses to form a short-time window and the CS sensing matrix can be built according to the time stamps of these pulses. Then performing Orthogonal Matching Pursuit (OMP, the unambiguous micro-Doppler spectrum can be obtained. The proposed algorithm is verified using the echo signals generated according to the theoretical model and the signals with micro-Doppler signature produced using the commercial electromagnetic simulation software FEKO.

  20. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges.

    Science.gov (United States)

    Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

    2016-02-06

    The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

  1. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

    Directory of Open Access Journals (Sweden)

    Yuanfang Chen

    2016-02-01

    Full Text Available The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases is an important research issue in the industrial applications of the Internet of Things (IoT. An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

  2. A Remote Sensing Image Fusion Method based on adaptive dictionary learning

    Science.gov (United States)

    He, Tongdi; Che, Zongxi

    2018-01-01

    This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

  3. Effects of Surface and Morphological Properties of Zeolite on Impedance Spectroscopy-Based Sensing Performance

    Directory of Open Access Journals (Sweden)

    Prabir K. Dutta

    2012-10-01

    Full Text Available Measurement by impedance spectroscopy of the changes in intrazeolitic cation motion of pressed pellets of zeolite particles upon adsorption of dimethylmethylphosphonate (DMMP provides a strategy for sensing DMMP, a commonly used simulant for highly toxic organophosphate nerve agents. In this work, two strategies for improving the impedance spectroscopy based sensing of DMMP on zeolites were investigated. The first one is the use of cerium oxide (CeO2 coated on the zeolite surface to neutralize acidic groups that may cause the decomposition of DMMP, and results in better sensor recovery. The second strategy was to explore the use of zeolite Y membrane. Compared to pressed pellets, the membranes have connected supercages of much longer length scales. The zeolite membranes resulted in higher sensitivity to DMMP, but recovery of the device was significantly slower as compared to pressed zeolite pellets.

  4. Perylene Diimide Based Fluorescent Dyes for Selective Sensing of Nitroaromatic Compounds: Selective Sensing in Aqueous Medium Across Wide pH Range.

    Science.gov (United States)

    Hariharan, P S; Pitchaimani, J; Madhu, Vedichi; Anthony, Savarimuthu Philip

    2016-03-01

    Water soluble perylenediimide based fluorophore salt, N,N'-bis(ethelenetrimethyl ammoniumiodide)-perylene-3,4,9,10-tetracarboxylicbisimide (PDI-1), has been used for selective fluorescence sensing of picric acid (PA) and 4-nitroaniline (4-NA) in organic as well as aqueous medium across wide pH range (1.0 to 10.0). PDI-1 showed strong fluorescence in dimethylformamide (DMF) (Φf = 0.26 (DMF) and moderate fluorescence in water. Addition of picric acid (PA) and 4-nitroaniline (4-NA) into PDI-1 in DMF/aqueous solution selectively quenches the fluorescence. The concentration dependent studies showed decrease of fluorescence linearly with increase of PA and 4-NA concentration. The interference studies demonstrate high selectivity for PA and 4-NA. Interestingly, PDI-1 showed selective fluorescence sensing of PA and 4-NA across wide pH range (1.0 to 10.0). Selective fluorescence sensing of PA and 4-NA has also been observed with trifluoroacetate (PDI-2), sulfate (PDI-3) salt of PDI-1 as well as octyl chain substituted PDI (PDI-4) without amine functionality. These studies suggest that PA and 4-NA might be having preferential interaction with PDI aromatic core and quenches the fluorescence. Thus PDI based dyes have been used for selective fluorescent sensing of explosive NACs for the first time to the best our knowledge.

  5. Light-guiding hydrogels for cell-based sensing and optogenetic synthesis in vivo

    Science.gov (United States)

    Choi, Myunghwan; Choi, Jin Woo; Kim, Seonghoon; Nizamoglu, Sedat; Hahn, Sei Kwang; Yun, Seok Hyun

    2013-12-01

    Polymer hydrogels are widely used as cell scaffolds for biomedical applications. Although the biochemical and biophysical properties of hydrogels have been investigated extensively, little attention has been paid to their potential photonic functionalities. Here, we report cell-integrated polyethylene glycol-based hydrogels for in vivo optical-sensing and therapy applications. Hydrogel patches containing cells were implanted in awake, freely moving mice for several days and shown to offer long-term transparency, biocompatibility, cell viability and light-guiding properties (loss of nanotoxicity of cadmium-based bare and shelled quantum dots (CdTe; CdSe/ZnS) in vivo.

  6. Information Extraction of High-Resolution Remotely Sensed Image Based on Multiresolution Segmentation

    Directory of Open Access Journals (Sweden)

    Peng Shao

    2014-08-01

    Full Text Available The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.

  7. Laser Sensing of Vegetation Based on Dual Spectrum Measurements of Reflection Coefficients

    Directory of Open Access Journals (Sweden)

    M. L. Belov

    2017-01-01

    Full Text Available Currently, a promising trend in remote sensing of environment is to monitor the vegetative cover: evaluate the productivity of agricultural crops; evaluate the moisture content of soils and the state of ecosystems; provide mapping the sites of bogging, desertification, drought, etc.; control the phases of vegetation of crops, etc.Development of monitoring systems for remote detection of vegetation sites being under unfavorable conditions (low or high temperature, excess or lack of water, soil salinity, disease, etc. is of relevance. Optical methods are the most effective for this task. These methods are based on the physical features of reflection spectra in the visible and near infrared spectral range for vegetation under unfavorable conditions and vegetation under normal conditions.One of the options of optoelectronic equipment for monitoring vegetation condition is laser equipment that allows remote sensing of vegetation from the aircraft and mapping of vegetation sites with abnormal (inactive periods of vegetation reflection spectra with a high degree of spatial resolution.The paper deals with development of a promising dual-spectrum method for laser remote sensing of vegetation. Using the experimentally measured reflection spectra of different vegetation types, mathematical modeling of probability for appropriate detection and false alarms to solve a problem of detecting the vegetation under unfavorable conditions (with abnormal reflection spectra is performed based on the results of dual-spectrum measurements of the reflection coefficient.In mathematical modeling, the lidar system was supposed to provide sensing at wavelengths of 0.532 μm and 0.85 μm. The noise of the measurement was supposed to be normal with zero mean value and mean-square value of 1% -10%.It is shown that the method of laser sensing of vegetation condition based on the results of dual-spectrum measurement of the reflection coefficient at wavelengths of 0.532 μm and 0

  8. A component-based system for agricultural drought monitoring by remote sensing.

    Science.gov (United States)

    Dong, Heng; Li, Jun; Yuan, Yanbin; You, Lin; Chen, Chao

    2017-01-01

    In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM) to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

  9. Towards a framework for agent-based image analysis of remote-sensing data.

    Science.gov (United States)

    Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

    2015-04-03

    Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

  10. Research on compressive sensing reconstruction algorithm based on total variation model

    Science.gov (United States)

    Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

    2017-12-01

    Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

  11. A component-based system for agricultural drought monitoring by remote sensing.

    Directory of Open Access Journals (Sweden)

    Heng Dong

    Full Text Available In recent decades, various kinds of remote sensing-based drought indexes have been proposed and widely used in the field of drought monitoring. However, the drought-related software and platform development lag behind the theoretical research. The current drought monitoring systems focus mainly on information management and publishing, and cannot implement professional drought monitoring or parameter inversion modelling, especially the models based on multi-dimensional feature space. In view of the above problems, this paper aims at fixing this gap with a component-based system named RSDMS to facilitate the application of drought monitoring by remote sensing. The system is designed and developed based on Component Object Model (COM to ensure the flexibility and extendibility of modules. RSDMS realizes general image-related functions such as data management, image display, spatial reference management, image processing and analysis, and further provides drought monitoring and evaluation functions based on internal and external models. Finally, China's Ningxia region is selected as the study area to validate the performance of RSDMS. The experimental results show that RSDMS provide an efficient and scalable support to agricultural drought monitoring.

  12. Bicarbonate sensing in mouse cortical astrocytes during extracellular acid/base disturbances

    Science.gov (United States)

    Naoshin, Zinnia; Defren, Sabrina; Schmaelzle, Jana; Weber, Tobias; Schneider, Hans‐Peter

    2017-01-01

    Key points The present study suggests that the electrogenic sodium–bicarbonate cotransporter, NBCe1, supported by carbonic anhydrase II, CAII, provides an efficient mechanism of bicarbonate sensing in cortical astrocytes. This mechanism is proposed to play a major role in setting the pHi responses to extracellular acid/base challenges in astrocytes.A decrease in extracellular [HCO3 −] during isocapnic acidosis and isohydric hypocapnia, or an increase in intracellular [HCO3 −] during hypercapnic acidosis, was effectively sensed by NBCe1, which carried bicarbonate out of the cells under these conditions, and caused an acidification and sodium fall in WT astrocytes, but not in NBCe1‐knockout astrocytes.Isocapnic acidosis, hypercapnic acidosis and isohydric hypocapnia evoked inward currents in NBCe1‐ and CAII‐expressing Xenopus laevis oocytes, but not in native oocytes, suggesting that NBCe1 operates in the outwardly directed mode under these conditions consistent with our findings in astrocytes.We propose that bicarbonate sensing of astrocytes may have functional significance during extracellular acid/base disturbances in the brain, as it not only alters intracellular pH/[HCO3 −]‐dependent functions of astrocytes, but also modulates the extracellular pH/[HCO3 −] in brain tissue. Abstract Extracellular acid/base status of the mammalian brain undergoes dynamic changes during many physiological and pathological events. Although intracellular pH (pHi) of astrocytes responds to extracellular acid/base changes, the mechanisms mediating these changes have remained unresolved. We have previously shown that the electrogenic sodium–bicarbonate cotransporter, NBCe1, is a high‐affinity bicarbonate carrier in cortical astrocytes. In the present study, we investigated whether NBCe1 plays a role in bicarbonate sensing in astrocytes, and in determining the pHi responses to extracellular acid/base challenges. We measured changes in intracellular H+ and Na+ in

  13. Optical oxygen sensing materials based on a novel dirhenium(I) complex assembled in mesoporous silica

    International Nuclear Information System (INIS)

    Liu Yanhong; Li Bin; Cong Yan; Zhang Liming; Fan Di; Shi Linfang

    2011-01-01

    A new dirhenium(I) complex fac-[{Re(CO) 3 (4,7-dinonadecyl-1,10-phenanthro -line)} 2 (4,4'-bipyridyl)] (trifluoromethanesulfonate) 2 (denoted as D-Re(I) ) is assembled in MCM-41 and SBA-15 type mesoporous silica support. The emission peaks of D-Re(I) in D-Re(I)/MCM-41 and D-Re(I)/SBA-15 are observed at 522 and 517 nm, respectively. Their long excited lifetimes, which are of the order of microseconds, indicate the presence of phosphorescence emission arising from the metal to ligand charge-transfer (MLCT) transition. The luminescence intensities of D-Re(I)/MCM-41 and D-Re(I)/SBA-15 decrease remarkably with increase in the oxygen concentration, meaning that they can be used as optical oxygen sensing materials based on luminescence quenching. The ratios I 0 /I 100 of D-Re(I)/MCM-41 and D-Re(I)/SBA-15 are estimated to be 5.6 and 20.1, respectively. The obtained Stern-Volmer oxygen quenching plots of the mesoporous sensing materials could be fitted well to the two-site Demas model and Lehrer model. - Research highlights: → Dirhenium(I) complex assembled in mesoporous molecular sieves for oxygen sensor design. → Large α-diimine ligand L used to improve oxygen sensing properties. → High sensitivity (I 0 /I 100 ) up to 20.1.

  14. Novel Door-opening Method for Six-legged Robots Based on Only Force Sensing

    Science.gov (United States)

    Chen, Zhi-Jun; Gao, Feng; Pan, Yang

    2017-09-01

    Current door-opening methods are mainly developed on tracked, wheeled and biped robots by applying multi-DOF manipulators and vision systems. However, door-opening methods for six-legged robots are seldom studied, especially using 0-DOF tools to operate and only force sensing to detect. A novel door-opening method for six-legged robots is developed and implemented to the six-parallel-legged robot. The kinematic model of the six-parallel-legged robot is established and the model of measuring the positional relationship between the robot and the door is proposed. The measurement model is completely based on only force sensing. The real-time trajectory planning method and the control strategy are designed. The trajectory planning method allows the maximum angle between the sagittal axis of the robot body and the normal line of the door plane to be 45º. A 0-DOF tool mounted to the robot body is applied to operate. By integrating with the body, the tool has 6 DOFs and enough workspace to operate. The loose grasp achieved by the tool helps release the inner force in the tool. Experiments are carried out to validate the method. The results show that the method is effective and robust in opening doors wider than 1 m. This paper proposes a novel door-opening method for six-legged robots, which notably uses a 0-DOF tool and only force sensing to detect and open the door.

  15. Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

    Science.gov (United States)

    Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

    2016-09-01

    Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

  16. VEGETATION COVERAGE AND IMPERVIOUS SURFACE AREA ESTIMATED BASED ON THE ESTARFM MODEL AND REMOTE SENSING MONITORING

    Directory of Open Access Journals (Sweden)

    R. Hu

    2018-04-01

    Full Text Available Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM, the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC and impervious layer with high spatiotemporal resolution (30 m, 8 day were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1 ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2 The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

  17. Implantable electrolyte conductance-based pressure sensing catheter, II. Device construction and testing.

    Science.gov (United States)

    Tan, Robert; Benharash, Peyman; Schulam, Peter; Schmidt, Jacob J

    2013-12-01

    Direct measurements of arterial blood pressure most commonly use bulky external instrumentation containing a pressure transducer connected to an ex vivo fluid-filled arterial line, which is subject to several sensing artifacts. In situ blood pressure sensors, typically solid state piezoresistive, capacitive, and interferometric sensors, are unaffected by these artifacts, but can be expensive to produce and miniaturize. We have developed an alternative approach to blood pressure measurement based on deformation of an elastic tube filled with electrolyte solution. Simple measurement of the electrical conductance of this solution as the tube dimensions change allows determination of the external pressure. The sensor is made from inexpensive materials and its miniaturization is straightforward. In vitro static testing of initial sensor prototypes mounted on a catheter tip showed a linear response with applied pressure and a resolution of 1 mmHg. In vivo sensing followed catheterization of the sensor into the femoral artery of a porcine model through a 7F catheter port. The sensor performed comparably to a commercial pressure transducer also connected to the catheter port. Due to its scalability and cost, this sensor has the potential for use in a range of pressure sensing applications, such as measurement of intracranial, spinal, or interstitial pressures.

  18. Influence of Fabricating Process on Gas Sensing Properties of ZnO Nanofiber-Based Sensors

    International Nuclear Information System (INIS)

    Xu Lei; Wang Rui; Liu Yong; Dong Liang

    2011-01-01

    ZnO nanofibers are synthesized by an electrospinning method and characterized by x-ray diffraction (XRD) and scanning electron microscopy (SEM). Two types of gas sensors are fabricated by loading these nanofibers as the sensing materials and their performances are investigated in detail. Compared with the sensors based on traditional ceramic tubes with Au electrodes (traditional sensors), the sensors fabricated by spinning ZnO nanofibers on ceramic planes with Ag-Pd electrodes (plane sensors) exhibit much higher sensing properties. The sensitivity for the plane sensors is about 30 to 100 ppm ethanol at 300°C, while the value is only 13 for the traditional sensors. The response and recovery times are about 2 and 3s for the plane sensors and are 3 and 6s for the traditional sensors, respectively. Lower minimum-detection-limit is also found for the plane sensors. These improvements are explained by considering the morphological damage in the fabricating process for traditional sensors. The results suggest that the plane sensors are more suitable to sensing investigation for higher veracity. (general)

  19. Watermarking-based protection of remote sensing images: requirements and possible solutions

    Science.gov (United States)

    Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella

    2001-12-01

    Earth observation missions have recently attracted ag rowing interest form the scientific and industrial communities, mainly due to the large number of possible applications capable to exploit remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products from non-authorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred means of data exchange. A crucial issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: i) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection ii) analysis of the state-of-the-art, and performance evaluation of existing algorithms in terms of the requirements at the previous point.

  20. High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses.

    Science.gov (United States)

    Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei

    2016-11-28

    We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

  1. Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

    Science.gov (United States)

    Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

    2018-04-01

    Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

  2. Design and Verification of Remote Sensing Image Data Center Storage Architecture Based on Hadoop

    Science.gov (United States)

    Tang, D.; Zhou, X.; Jing, Y.; Cong, W.; Li, C.

    2018-04-01

    The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

  3. Study on Method of Geohazard Change Detection Based on Integrating Remote Sensing and GIS

    International Nuclear Information System (INIS)

    Zhao, Zhenzhen; Yan, Qin; Liu, Zhengjun; Luo, Chengfeng

    2014-01-01

    Following a comprehensive literature review, this paper looks at analysis of geohazard using remote sensing information. This paper compares the basic types and methods of change detection, explores the basic principle of common methods and makes an respective analysis of the characteristics and shortcomings of the commonly used methods in the application of geohazard. Using the earthquake in JieGu as a case study, this paper proposes a geohazard change detection method integrating RS and GIS. When detecting the pre-earthquake and post-earthquake remote sensing images at different phases, it is crucial to set an appropriate threshold. The method adopts a self-adapting determination algorithm for threshold. We select a training region which is obtained after pixel information comparison and set a threshold value. The threshold value separates the changed pixel maximum. Then we apply the threshold value to the entire image, which could also make change detection accuracy maximum. Finally, we output the result to the GIS system to make change analysis. The experimental results show that this method of geohazard change detection based on integrating remote sensing and GIS information has higher accuracy with obvious advantages compared with the traditional methods

  4. Analysis of flood inundation in ungauged basins based on multi-source remote sensing data.

    Science.gov (United States)

    Gao, Wei; Shen, Qiu; Zhou, Yuehua; Li, Xin

    2018-02-09

    Floods are among the most expensive natural hazards experienced in many places of the world and can result in heavy losses of life and economic damages. The objective of this study is to analyze flood inundation in ungauged basins by performing near-real-time detection with flood extent and depth based on multi-source remote sensing data. Via spatial distribution analysis of flood extent and depth in a time series, the inundation condition and the characteristics of flood disaster can be reflected. The results show that the multi-source remote sensing data can make up the lack of hydrological data in ungauged basins, which is helpful to reconstruct hydrological sequence; the combination of MODIS (moderate-resolution imaging spectroradiometer) surface reflectance productions and the DFO (Dartmouth Flood Observatory) flood database can achieve the macro-dynamic monitoring of the flood inundation in ungauged basins, and then the differential technique of high-resolution optical and microwave images before and after floods can be used to calculate flood extent to reflect spatial changes of inundation; the monitoring algorithm for the flood depth combining RS and GIS is simple and easy and can quickly calculate the depth with a known flood extent that is obtained from remote sensing images in ungauged basins. Relevant results can provide effective help for the disaster relief work performed by government departments.

  5. A single-walled carbon nanotube thin film-based pH-sensing microfluidic chip.

    Science.gov (United States)

    Li, Cheng Ai; Han, Kwi Nam; Pham, Xuan-Hung; Seong, Gi Hun

    2014-04-21

    A novel microfluidic pH-sensing chip was developed based on pH-sensitive single-walled carbon nanotubes (SWCNTs). In this study, the SWCNT thin film acted both as an electrode and a pH-sensitive membrane. The potentiometric pH response was observed by electronic structure changes in the semiconducting SWCNTs in response to the pH level. In a microfluidic chip consisting of a SWCNT pH-sensing working electrode and an Ag/AgCl reference electrode, the calibration plot exhibited promising pH-sensing performance with an ideal Nernstian response of 59.71 mV pH(-1) between pH 3 and 11 (standard deviation of the sensitivity is 1.5 mV pH(-1), R(2) = 0.985). Moreover, the SWCNT electrode in the microfluidic device showed no significant variation at any pH value in the range of the flow rate between 0.1 and 15 μl min(-1). The selectivity coefficients of the SWCNT electrode revealed good selectivity against common interfering ions.

  6. BSA-coated nanoparticles for improved SERS-based intracellular pH sensing.

    Science.gov (United States)

    Zheng, Xiao-Shan; Hu, Pei; Cui, Yan; Zong, Cheng; Feng, Jia-Min; Wang, Xin; Ren, Bin

    2014-12-16

    Local microenvironment pH sensing is one of the key parameters for the understanding of many biological processes. As a noninvasive and high sensitive technique, surface-enhanced Raman spectroscopy (SERS) has attracted considerable interest in the detection of the local pH of live cells. We herein develop a facile way to prepare Au-(4-MPy)-BSA (AMB) pH nanosensor. The 4-MPy (4-mercaptopyridine) was used as the pH sensing molecule. The modification of the nanoparticles with BSA not only provides a high sensitive response to pH changes ranging from pH 4.0 to 9.0 but also exhibits a high sensitivity and good biocompatibility, stability, and reliability in various solutions (including the solutions of high ionic strength or with complex composition such as the cell culture medium), both in the aggregation state or after long-term storage. The AMB pH nanosensor shows great advantages for reliable intracellular pH analysis and has been successfully used to monitor the pH distribution of live cells and can address the grand challenges in SERS-based pH sensing for practical biological applications.

  7. A stereo remote sensing feature selection method based on artificial bee colony algorithm

    Science.gov (United States)

    Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

    2014-05-01

    To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

  8. A wavelet-based regularized reconstruction algorithm for SENSE parallel MRI with applications to neuroimaging

    International Nuclear Information System (INIS)

    Chaari, L.; Pesquet, J.Ch.; Chaari, L.; Ciuciu, Ph.; Benazza-Benyahia, A.

    2011-01-01

    To reduce scanning time and/or improve spatial/temporal resolution in some Magnetic Resonance Imaging (MRI) applications, parallel MRI acquisition techniques with multiple coils acquisition have emerged since the early 1990's as powerful imaging methods that allow a faster acquisition process. In these techniques, the full FOV image has to be reconstructed from the resulting acquired under sampled k-space data. To this end, several reconstruction techniques have been proposed such as the widely-used Sensitivity Encoding (SENSE) method. However, the reconstructed image generally presents artifacts when perturbations occur in both the measured data and the estimated coil sensitivity profiles. In this paper, we aim at achieving accurate image reconstruction under degraded experimental conditions (low magnetic field and high reduction factor), in which neither the SENSE method nor the Tikhonov regularization in the image domain give convincing results. To this end, we present a novel method for SENSE-based reconstruction which proceeds with regularization in the complex wavelet domain by promoting sparsity. The proposed approach relies on a fast algorithm that enables the minimization of regularized non-differentiable criteria including more general penalties than a classical l 1 term. To further enhance the reconstructed image quality, local convex constraints are added to the regularization process. In vivo human brain experiments carried out on Gradient-Echo (GRE) anatomical and Echo Planar Imaging (EPI) functional MRI data at 1.5 T indicate that our algorithm provides reconstructed images with reduced artifacts for high reduction factors. (authors)

  9. Catalysis-reduction strategy for sensing inorganic and organic mercury based on gold nanoparticles.

    Science.gov (United States)

    Li, Xiaokun; Zhang, Youlin; Chang, Yulei; Xue, Bin; Kong, Xianggui; Chen, Wei

    2017-06-15

    In view of the high biotoxicity and trace concentration of mercury (Hg) in environmental water, developing simple, ultra-sensitive and highly selective method capable of simultaneous determination of various Hg species has attracted wide attention. Here, we present a novel catalysis-reduction strategy for sensing inorganic and organic mercury in aqueous solution through the cooperative effect of AuNP-catalyzed properties and the formation of gold amalgam. For the first time, a new AuNP-catalyzed-organic reaction has been discovered and directly used for sensing Hg 2+ , Hg 2 2+ and CH 3 Hg + according to the change of the amount of the catalytic product induced by the deposition of Hg atoms on the surface of AuNPs. The detection limit of Hg species is 5.0pM (1 ppt), which is 3 orders of magnitude lower than the U.S. Environmental Protection Agency (EPA) limit value of Hg for drinking water (2 ppb). The high selectivity can be exceptionally achieved by the specific formation of gold amalgam. Moreover, the application for detecting tap water samples further demonstrates that this AuNP-based assay can be an excellent method used for sensing mercury at very low content in the environment. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

    Science.gov (United States)

    Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

    2018-01-01

    RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

  11. Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Hongyang Lu

    2016-06-01

    Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

  12. A Comparison of Novel Optical Remote Sensing-Based Technologies for Forest-Cover/Change Monitoring

    Directory of Open Access Journals (Sweden)

    Gillian V. Lui

    2015-03-01

    Full Text Available Remote sensing is gaining considerable traction in forest monitoring efforts, with the Carnegie Landsat Analysis System lite (CLASlite software package and the Global Forest Change dataset (GFCD being two of the most recently developed optical remote sensing-based tools for analysing forest cover and change. Due to the relatively nascent state of these technologies, their abilities to classify land cover and monitor forest dynamics have yet to be evaluated against more established approaches. Here, we compared maps of forest cover and change produced by the more traditional supervised classification approach with those produced by CLASlite and the GFCD, working with imagery collected over Sierra Leone, West Africa. CLASlite maps of forest change from 2001–2007 and 2007–2014 exhibited the highest overall accuracies (79.1% and 89.6%, respectively and, importantly, the greatest capacity to discriminate natural from planted mature forest growth. CLASlite’s comparative advantage likely derived from its more robust sub-pixel classification logic and numerous user-defined parameters, which resulted in classified products with greater site relevance than those of the two other classification approaches. In light of today’s continuously growing body of analytical toolsets for remotely sensed data, our study importantly elucidates the ways in which methodological processes and limitations inherent in certain classification tools can impact the maps they are capable of producing, and demonstrates the need to understand and weigh such factors before any one tool is selected for a given application.

  13. Remotely Sensed Based Lake/Reservoir Routing in Congo River Basin

    Science.gov (United States)

    Raoufi, R.; Beighley, E.; Lee, H.

    2017-12-01

    Lake and reservoir dynamics can influence local to regional water cycles but are often not well represented in hydrologic models. One challenge that limits their inclusion in models is the need for detailed storage-discharge behavior that can be further complicated in reservoirs where specific operation rules are employed. Here, the Hillslope River Routing (HRR) model is combined with a remotely sensed based Reservoir Routing (RR) method and applied to the Congo River Basin. Given that topographic data are often continuous over the entire terrestrial surface (i.e., does not differentiate between land and open water), the HRR-RR model integrates topographic derived river networks and catchment boundaries (e.g., HydroSHEDs) with water boundary extents (e.g., Global Lakes and Wetlands Database) to develop the computational framework. The catchments bordering lakes and reservoirs are partitioned into water and land portions, where representative flowpath characteristics are determined and vertical water balance and lateral routings is performed separately on each partition based on applicable process models (e.g., open water evaporation vs. evapotranspiration). To enable reservoir routing, remotely sensed water surface elevations and extents are combined to determine the storage change time series. Based on the available time series, representative storage change patterns are determined. Lake/reservoir routing is performed by combining inflows from the HRR-RR model and the representative storage change patterns to determine outflows. In this study, a suite of storage change patterns derived from remotely sensed measurements are determined representative patterns for wet, dry and average conditions. The HRR-RR model dynamically selects and uses the optimal storage change pattern for the routing process based on these hydrologic conditions. The HRR-RR model results are presented to highlight the importance of lake attenuation/routing in the Congo Basin.

  14. Chemiluminescence-based multivariate sensing of local equivalence ratios in premixed atmospheric methane-air flames

    Energy Technology Data Exchange (ETDEWEB)

    Tripathi, Markandey M.; Krishnan, Sundar R.; Srinivasan, Kalyan K.; Yueh, Fang-Yu; Singh, Jagdish P.

    2011-09-07

    Chemiluminescence emissions from OH*, CH*, C2, and CO2 formed within the reaction zone of premixed flames depend upon the fuel-air equivalence ratio in the burning mixture. In the present paper, a new partial least square regression (PLS-R) based multivariate sensing methodology is investigated and compared with an OH*/CH* intensity ratio-based calibration model for sensing equivalence ratio in atmospheric methane-air premixed flames. Five replications of spectral data at nine different equivalence ratios ranging from 0.73 to 1.48 were used in the calibration of both models. During model development, the PLS-R model was initially validated with the calibration data set using the leave-one-out cross validation technique. Since the PLS-R model used the entire raw spectral intensities, it did not need the nonlinear background subtraction of CO2 emission that is required for typical OH*/CH* intensity ratio calibrations. An unbiased spectral data set (not used in the PLS-R model development), for 28 different equivalence ratio conditions ranging from 0.71 to 1.67, was used to predict equivalence ratios using the PLS-R and the intensity ratio calibration models. It was found that the equivalence ratios predicted with the PLS-R based multivariate calibration model matched the experimentally measured equivalence ratios within 7%; whereas, the OH*/CH* intensity ratio calibration grossly underpredicted equivalence ratios in comparison to measured equivalence ratios, especially under rich conditions ( > 1.2). The practical implications of the chemiluminescence-based multivariate equivalence ratio sensing methodology are also discussed.

  15. A DNA-based semantic fusion model for remote sensing data.

    Directory of Open Access Journals (Sweden)

    Heng Sun

    Full Text Available Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  16. A DNA-based semantic fusion model for remote sensing data.

    Science.gov (United States)

    Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

    2013-01-01

    Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  17. METHOD OF GROUP OBJECTS FORMING FOR SPACE-BASED REMOTE SENSING OF THE EARTH

    Directory of Open Access Journals (Sweden)

    A. N. Grigoriev

    2015-07-01

    Full Text Available Subject of Research. Research findings of the specific application of space-based optical-electronic and radar means for the Earth remote sensing are considered. The subject matter of the study is the current planning of objects survey on the underlying surface in order to increase the effectiveness of sensing system due to the rational use of its resources. Method. New concept of a group object, stochastic swath and stochastic length of the route is introduced. The overview of models for single, group objects and their parameters is given. The criterion for the existence of the group object based on two single objects is formulated. The method for group objects formation while current survey planning has been developed and its description is presented. The method comprises several processing stages for data about objects with the calculation of new parameters, the stochastic characteristics of space means and validates the spatial size of the object value of the stochastic swath and stochastic length of the route. The strict mathematical description of techniques for model creation of a group object based on data about a single object and onboard special complex facilities in difficult conditions of registration of spatial data is given. Main Results. The developed method is implemented on the basis of modern geographic information system in the form of a software tool layout with advanced tools of processing and analysis of spatial data in vector format. Experimental studies of the forming method for the group of objects were carried out on a different real object environment using the parameters of modern national systems of the Earth remote sensing detailed observation Canopus-B and Resurs-P. Practical Relevance. The proposed models and method are focused on practical implementation using vector spatial data models and modern geoinformation technologies. Practical value lies in the reduction in the amount of consumable resources by means of

  18. Remote-sensing based approach to forecast habitat quality under climate change scenarios.

    Directory of Open Access Journals (Sweden)

    Juan M Requena-Mullor

    Full Text Available As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the

  19. [Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

    Science.gov (United States)

    Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

    2018-02-01

    Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

  20. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-01-01

    in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight

  1. Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

    Science.gov (United States)

    Nieland, Simon; Kleinschmit, Birgit; Förster, Michael

    2015-05-01

    Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, "bottom-up" engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

  2. Facile Preparation of Carbon-Nanotube-based 3-Dimensional Transparent Conducting Networks for Flexible Noncontact Sensing Device

    KAUST Repository

    Tai, Yanlong; Lubineau, Gilles

    2016-01-01

    Here, we report the controllable fabrication of transparent conductive films (TCFs) for moisture-sensing applications based on heating-rate-triggered, 3-dimensional porous conducting networks of single-walled carbon nanotube (SWCNT)/poly(3

  3. A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yongwei Zhang

    2017-01-01

    Full Text Available In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

  4. Glucose Sensing Using Capacitive Biosensor Based on Polyvinylidene Fluoride Thin Film

    Directory of Open Access Journals (Sweden)

    Ambran Hartono

    2018-01-01

    Full Text Available A polyvinylidene fluoride (PVDF film-based capacitive biosensor was developed for glucose sensing. This device consists of a PVDF film sandwiched between two electrodes. A capacitive biosensor measures the dielectric properties of the dielectric layers at the interface between the electrolyte and the electrode. A glucose oxidase (GOx enzyme was immobilized onto the electrode to oxidize glucose. In practice, the biochemical reaction of glucose with the GOx enzyme generates free electron carriers. Consequently, the potential difference between the electrodes is increased, resulting in a measurable voltage output of the biosensor. The device was tested for various glucose concentrations in the range of 0.013 to 5.85 M, and various GOx enzyme concentrations between 4882.8 and 2.5 million units/L. We found that the sensor output increased with increasing glucose concentration up to 5.85 M. These results indicate that the PVDF film-based capacitive biosensors can be properly applied to glucose sensing and provide opportunities for the low-cost fabrication of glucose-based biosensors based on PVDF materials.

  5. Fluorescent blood glucose monitor by hemin-functionalized graphene quantum dots based sensing system

    Energy Technology Data Exchange (ETDEWEB)

    He, Yuezhen; Wang, Xiaoxun; Sun, Jian; Jiao, Shoufeng; Chen, Hongqi; Gao, Feng; Wang, Lun, E-mail: wanglun@mail.ahnu.edu.cn

    2014-01-31

    Graphical abstract: -- Highlights: •Hemin is assembled onto the surfaces of graphene quantum dots (GQDs). •With the aid of hemin, H{sub 2}O{sub 2} could quench the FL signal of GQDs obviously. •Based on this effect, a fluorescent platform is proposed for the sensing of glucose. •The proposed method provides a new pathway to explore practical application of GQDs. -- Abstract: In the present work, a highly sensitive and specific fluorescent biosensor for blood glucose monitoring is developed based on hemin-functionalized graphene quantum dots (GQDs) and glucose oxidase (GOx) system. The GQDs which are simply prepared by pyrolyzing citric acid exhibit strong fluorescence and good water-solubility. Due to the noncovalent assembly between hemin and GQDs, the addition of hemin can make hydrogen peroxide (H{sub 2}O{sub 2}) to destroy the passivated surface of GQDs, leading to significant fluorescence quenching of GQDs. Based on this effect, a novel fluorescent platform is proposed for the sensing of glucose. Under the optimized conditions, the linear range of glucose is from 9 to 300 μM, and the limit of detection is 0.1 μM. As unique properties of GQDs, the proposed biosensor is green, simple, cost-efficient, and it is successfully applied to the determination of glucose in human serum. In addition, the proposed method provides a new pathway to further design the biosensors based on the assembly of GQDs with hemin for detection of biomolecules.

  6. Water Extraction in High Resolution Remote Sensing Image Based on Hierarchical Spectrum and Shape Features

    International Nuclear Information System (INIS)

    Li, Bangyu; Zhang, Hui; Xu, Fanjiang

    2014-01-01

    This paper addresses the problem of water extraction from high resolution remote sensing images (including R, G, B, and NIR channels), which draws considerable attention in recent years. Previous work on water extraction mainly faced two difficulties. 1) It is difficult to obtain accurate position of water boundary because of using low resolution images. 2) Like all other image based object classification problems, the phenomena of ''different objects same image'' or ''different images same object'' affects the water extraction. Shadow of elevated objects (e.g. buildings, bridges, towers and trees) scattered in the remote sensing image is a typical noise objects for water extraction. In many cases, it is difficult to discriminate between water and shadow in a remote sensing image, especially in the urban region. We propose a water extraction method with two hierarchies: the statistical feature of spectral characteristic based on image segmentation and the shape feature based on shadow removing. In the first hierarchy, the Statistical Region Merging (SRM) algorithm is adopted for image segmentation. The SRM includes two key steps: one is sorting adjacent regions according to a pre-ascertained sort function, and the other one is merging adjacent regions based on a pre-ascertained merging predicate. The sort step is done one time during the whole processing without considering changes caused by merging which may cause imprecise results. Therefore, we modify the SRM with dynamic sort processing, which conducts sorting step repetitively when there is large adjacent region changes after doing merging. To achieve robust segmentation, we apply the merging region with six features (four remote sensing image bands, Normalized Difference Water Index (NDWI), and Normalized Saturation-value Difference Index (NSVDI)). All these features contribute to segment image into region of object. NDWI and NSVDI are discriminate between water and

  7. Some technical notes on using UAV-based remote sensing for post disaster assessment

    Science.gov (United States)

    Rokhmana, Catur Aries; Andaru, Ruli

    2017-07-01

    Indonesia is located in an area prone to disasters, which are various kinds of natural disasters happen. In disaster management, the geoinformation data are needed to be able to evaluate the impact area. The UAV (Unmanned Aerial Vehicle)-Based remote sensing technology is a good choice to produce a high spatial resolution of less than 15 cm, while the current resolution of the satellite imagery is still greater than 50 cm. This paper shows some technical notes that should be considered when using UAV-Based remote sensing system in post disaster for rapid assessment. Some cases are Aceh Earthquake in years 2013 for seeing infrastructure damages, Banjarnegara landslide in year 2014 for seeing the impact; and Kelud volcano eruption in year 2014 for seeing the impact and volumetric material calculation. The UAV-Based remote sensing system should be able to produce the Orthophoto image that can provide capabilities for visual interpretation the individual damage objects, and the changes situation. Meanwhile the DEM (digital Elevation model) product can derive terrain topography, and volumetric calculation with accuracy 3-5 pixel or sub-meter also. The UAV platform should be able for working remotely and autonomously in dangerous area and limited infrastructures. In mountainous or volcano area, an unconventional flight plan should implemented. Unfortunately, not all impact can be seen from above such as wall crack, some parcel boundaries, and many objects that covered by others higher object. The previous existing geoinformation data are also needed to be able to evaluate the change detection automatically.

  8. Accurate Quantitative Sensing of Intracellular pH based on Self-ratiometric Upconversion Luminescent Nanoprobe.

    Science.gov (United States)

    Li, Cuixia; Zuo, Jing; Zhang, Li; Chang, Yulei; Zhang, Youlin; Tu, Langping; Liu, Xiaomin; Xue, Bin; Li, Qiqing; Zhao, Huiying; Zhang, Hong; Kong, Xianggui

    2016-12-09

    Accurate quantitation of intracellular pH (pH i ) is of great importance in revealing the cellular activities and early warning of diseases. A series of fluorescence-based nano-bioprobes composed of different nanoparticles or/and dye pairs have already been developed for pH i sensing. Till now, biological auto-fluorescence background upon UV-Vis excitation and severe photo-bleaching of dyes are the two main factors impeding the accurate quantitative detection of pH i . Herein, we have developed a self-ratiometric luminescence nanoprobe based on förster resonant energy transfer (FRET) for probing pH i , in which pH-sensitive fluorescein isothiocyanate (FITC) and upconversion nanoparticles (UCNPs) were served as energy acceptor and donor, respectively. Under 980 nm excitation, upconversion emission bands at 475 nm and 645 nm of NaYF 4 :Yb 3+ , Tm 3+ UCNPs were used as pH i response and self-ratiometric reference signal, respectively. This direct quantitative sensing approach has circumvented the traditional software-based subsequent processing of images which may lead to relatively large uncertainty of the results. Due to efficient FRET and fluorescence background free, a highly-sensitive and accurate sensing has been achieved, featured by 3.56 per unit change in pH i value 3.0-7.0 with deviation less than 0.43. This approach shall facilitate the researches in pH i related areas and development of the intracellular drug delivery systems.

  9. Graphitic design: prospects of graphene-based nanocomposites for solar energy conversion, storage, and sensing.

    Science.gov (United States)

    Lightcap, Ian V; Kamat, Prashant V

    2013-10-15

    Graphene not only possesses interesting electrochemical behavior but also has a remarkable surface area and mechanical strength and is naturally abundant, all advantageous properties for the design of tailored composite materials. Graphene-semiconductor or -metal nanoparticle composites have the potential to function as efficient, multifunctional materials for energy conversion and storage. These next-generation composite systems could possess the capability to integrate conversion and storage of solar energy, detection, and selective destruction of trace environmental contaminants or achieve single-substrate, multistep heterogeneous catalysis. These advanced materials may soon become a reality, based on encouraging results in the key areas of energy conversion and sensing using graphene oxide as a support structure. Through recent advances, chemists can now integrate such processes on a single substrate while using synthetic designs that combine simplicity with a high degree of structural and composition selectivity. This progress represents the beginning of a transformative movement leveraging the advancements of single-purpose chemistry toward the creation of composites designed to address whole-process applications. The promising field of graphene nanocomposites for sensing and energy applications is based on fundamental studies that explain the electronic interactions between semiconductor or metal nanoparticles and graphene. In particular, reduced graphene oxide is a suitable composite substrate because of its two-dimensional structure, outstanding surface area, and electrical conductivity. In this Account, we describe common assembly methods for graphene composite materials and examine key studies that characterize its excited state interactions. We also discuss strategies to develop graphene composites and control electron capture and transport through the 2D carbon network. In addition, we provide a brief overview of advances in sensing, energy conversion

  10. Extraction Method for Earthquake-Collapsed Building Information Based on High-Resolution Remote Sensing

    International Nuclear Information System (INIS)

    Chen, Peng; Wu, Jian; Liu, Yaolin; Wang, Jing

    2014-01-01

    At present, the extraction of earthquake disaster information from remote sensing data relies on visual interpretation. However, this technique cannot effectively and quickly obtain precise and efficient information for earthquake relief and emergency management. Collapsed buildings in the town of Zipingpu after the Wenchuan earthquake were used as a case study to validate two kinds of rapid extraction methods for earthquake-collapsed building information based on pixel-oriented and object-oriented theories. The pixel-oriented method is based on multi-layer regional segments that embody the core layers and segments of the object-oriented method. The key idea is to mask layer by layer all image information, including that on the collapsed buildings. Compared with traditional techniques, the pixel-oriented method is innovative because it allows considerably rapid computer processing. As for the object-oriented method, a multi-scale segment algorithm was applied to build a three-layer hierarchy. By analyzing the spectrum, texture, shape, location, and context of individual object classes in different layers, the fuzzy determined rule system was established for the extraction of earthquake-collapsed building information. We compared the two sets of results using three variables: precision assessment, visual effect, and principle. Both methods can extract earthquake-collapsed building information quickly and accurately. The object-oriented method successfully overcomes the pepper salt noise caused by the spectral diversity of high-resolution remote sensing data and solves the problem of same object, different spectrums and that of same spectrum, different objects. With an overall accuracy of 90.38%, the method achieves more scientific and accurate results compared with the pixel-oriented method (76.84%). The object-oriented image analysis method can be extensively applied in the extraction of earthquake disaster information based on high-resolution remote sensing

  11. Sodium tripolyphosphate cross-linked chitosan based sensor for enhacing sensing properties towards acetone

    Science.gov (United States)

    Nasution, T. I.; Asrosa, R.; Nainggolan, I.; Balyan, M.; Indah, R.; Wahyudi, A.

    2018-02-01

    In this report, sensing properties of sodium tripolyphosphate (TPP) cross-linked chitosan based sensor has been successfully enhanced towards acetone. Chitosan solutions were cross-linked with sodium TPP in variation of 0.1%, 0.5%, 1% and 1.5% w/v, respectively. The sensors were fabricated in film form using an electrochemical deposition method. The sensing properties of the sensors were observed by exposing the pure chitosan and sodium TPP cross-linked chitosan sensors towards acetone concentrations of 5, 10, 50, 100 and 200 ppm. The measurement results revealed that the maximum response in output voltage value of pure chitosan sensor was 0.35 V while sodium TPP crosslinked chitosan sensors were above 0.35 V towards 5 ppm acetone concentration. When the sensors were exposed towards acetone concentration of 200 ppm, the maximum response of pure chitosan was 0.45 V while sodium TPP crosslinked chitosan sensors were above 0.45 V. Amongst the variation of sodium TPP, the maximum response of 1% sodium TPP was the highest since the maximum response was 0.4 V and 0.6 V towards 5 ppm and 200 ppm acetone concentration, respectively. While the maximum responses of other sodium TPP concentrations were under 0.4 V and 0.6 V towards 5 ppm and 200 ppm acetone concentration. Moreover, 1% sodium TPP cross-linked chitosan based sensor showed good reproducibility and outstanding lifetime. Therefore, 1% sodium TPP cross-linked chitosan based sensor has exhibited remarkable sensing properties as a novel acetone sensor.

  12. Simultaneous multicopter-based air sampling and sensing of meteorological variables

    Science.gov (United States)

    Brosy, Caroline; Krampf, Karina; Zeeman, Matthias; Wolf, Benjamin; Junkermann, Wolfgang; Schäfer, Klaus; Emeis, Stefan; Kunstmann, Harald

    2017-08-01

    The state and composition of the lowest part of the planetary boundary layer (PBL), i.e., the atmospheric surface layer (SL), reflects the interactions of external forcing, land surface, vegetation, human influence and the atmosphere. Vertical profiles of atmospheric variables in the SL at high spatial (meters) and temporal (1 Hz and better) resolution increase our understanding of these interactions but are still challenging to measure appropriately. Traditional ground-based observations include towers that often cover only a few measurement heights at a fixed location. At the same time, most remote sensing techniques and aircraft measurements have limitations to achieve sufficient detail close to the ground (up to 50 m). Vertical and horizontal transects of the PBL can be complemented by unmanned aerial vehicles (UAV). Our aim in this case study is to assess the use of a multicopter-type UAV for the spatial sampling of air and simultaneously the sensing of meteorological variables for the study of the surface exchange processes. To this end, a UAV was equipped with onboard air temperature and humidity sensors, while wind conditions were determined from the UAV's flight control sensors. Further, the UAV was used to systematically change the location of a sample inlet connected to a sample tube, allowing the observation of methane abundance using a ground-based analyzer. Vertical methane gradients of about 0.3 ppm were found during stable atmospheric conditions. Our results showed that both methane and meteorological conditions were in agreement with other observations at the site during the ScaleX-2015 campaign. The multicopter-type UAV was capable of simultaneous in situ sensing of meteorological state variables and sampling of air up to 50 m above the surface, which extended the vertical profile height of existing tower-based infrastructure by a factor of 5.

  13. Effect of channel-width and chirality on graphene field-effect transistor based real-time biomolecule sensing

    Directory of Open Access Journals (Sweden)

    Letian Lyu

    2018-03-01

    Full Text Available Graphene field-effect transistors (GFET hold promise in biomolecule sensing due to the outstanding properties of graphene materials. Charges in biomolecules are transduced into a change in the GFET current, which allows real-time monitoring of the biomolecule concentrations. Here we theoretically evaluate the performance of GFET based real-time biomolecule sensing, aiming to better understand the width-scaling limit in GFET based biosensors. In particular, we study the effect of the channel-width and the chirality on FET sensitivity by taking the percentage change of the FET current per unit charge density as the sensing signal. Firstly, GFETs made of graphene nanoribbons (GNR and graphene sheets (GS show comparable sensing signals to each other when gated at 1011 – 1012 cm-2 carrier densities. Sensing signals in GNRs are enhanced when gated near the sub-band thresholds, and increase their values in wider GNRs due to the change in device conductance and quantum capacitance. Secondly, the GNR chirality is found to fine tune the sensing signals. Armchair GNRs with smaller energy bandgaps appear to have an enhanced sensing signal close to 1011 cm-2 carrier densities. These results may help understand the scaling limit in GFET based biosensors along the width direction, and shed light on forming all-electrical bio-arrays.

  14. Effect of channel-width and chirality on graphene field-effect transistor based real-time biomolecule sensing

    Science.gov (United States)

    Lyu, Letian; Jaswal, Perveshwer; Xu, Guangyu

    2018-03-01

    Graphene field-effect transistors (GFET) hold promise in biomolecule sensing due to the outstanding properties of graphene materials. Charges in biomolecules are transduced into a change in the GFET current, which allows real-time monitoring of the biomolecule concentrations. Here we theoretically evaluate the performance of GFET based real-time biomolecule sensing, aiming to better understand the width-scaling limit in GFET based biosensors. In particular, we study the effect of the channel-width and the chirality on FET sensitivity by taking the percentage change of the FET current per unit charge density as the sensing signal. Firstly, GFETs made of graphene nanoribbons (GNR) and graphene sheets (GS) show comparable sensing signals to each other when gated at 1011 - 1012 cm-2 carrier densities. Sensing signals in GNRs are enhanced when gated near the sub-band thresholds, and increase their values in wider GNRs due to the change in device conductance and quantum capacitance. Secondly, the GNR chirality is found to fine tune the sensing signals. Armchair GNRs with smaller energy bandgaps appear to have an enhanced sensing signal close to 1011 cm-2 carrier densities. These results may help understand the scaling limit in GFET based biosensors along the width direction, and shed light on forming all-electrical bio-arrays.

  15. Emerging GaN-based HEMTs for mechanical sensing within harsh environments

    Science.gov (United States)

    Köck, Helmut; Chapin, Caitlin A.; Ostermaier, Clemens; Häberlen, Oliver; Senesky, Debbie G.

    2014-06-01

    Gallium nitride based high-electron-mobility transistors (HEMTs) have been investigated extensively as an alternative to Si-based power transistors by academia and industry over the last decade. It is well known that GaN-based HEMTs outperform Si-based technologies in terms of power density, area specific on-state resistance and switching speed. Recently, wide band-gap material systems have stirred interest regarding their use in various sensing fields ranging from chemical, mechanical, biological to optical applications due to their superior material properties. For harsh environments, wide bandgap sensor systems are deemed to be superior when compared to conventional Si-based systems. A new monolithic sensor platform based on the GaN HEMT electronic structure will enable engineers to design highly efficient propulsion systems widely applicable to the automotive, aeronautics and astronautics industrial sectors. In this paper, the advancements of GaN-based HEMTs for mechanical sensing applications are discussed. Of particular interest are multilayered heterogeneous structures where spontaneous and piezoelectric polarization between the interface results in the formation of a 2-dimensional electron gas (2DEG). Experimental results presented focus on the signal transduction under strained operating conditions in harsh environments. It is shown that a conventional AlGaN/GaN HEMT has a strong dependence of drain current under strained conditions, thus representing a promising future sensor platform. Ultimately, this work explores the sensor performance of conventional GaN HEMTs and leverages existing technological advances available in power electronics device research. The results presented have the potential to boost GaN-based sensor development through the integration of HEMT device and sensor design research.

  16. Exploring in teaching mode of Optical Fiber Sensing Technology outcomes-based education (OBE)

    Science.gov (United States)

    Fu, Guangwei; Fu, Xinghu; Zhang, Baojun; Bi, Weihong

    2017-08-01

    Combining with the characteristics of disciplines and OBE mode, also aiming at the phenomena of low learning enthusiasm for the major required courses for senior students, the course of optical fiber sensing was chosen as the demonstration for the teaching mode reform. In the light of "theory as the base, focus on the application, highlighting the practice" principle, we emphasis on the introduction of the latest scientific research achievements and current development trends, highlight the practicability and practicality. By observation learning and course project, enables students to carry out innovative project design and implementation means related to the practical problems in science and engineering of this course.

  17. Small-displacement sensing system based on multiple total internal reflections in heterodyne interferometry.

    Science.gov (United States)

    Wang, Shinn-Fwu; Chiu, Ming-Hung; Chen, Wei-Wu; Kao, Fu-Hsi; Chang, Rong-Seng

    2009-05-01

    A small-displacement sensing system based on multiple total internal reflections in heterodyne interferometry is proposed. In this paper, a small displacement can be obtained only by measuring the variation in phase difference between s- and p-polarization states for the total internal reflection effect. In order to improve the sensitivity, we increase the number of total internal reflections by using a parallelogram prism. The theoretical resolution of the method is better than 0.417 nm. The method has some merits, e.g., high resolution, high sensitivity, and real-time measurement. Also, its feasibility is demonstrated.

  18. Research of hydroelectric generating set low-frequency vibration monitoring system based on optical fiber sensing

    Science.gov (United States)

    Min, Li; Zhang, Xiaolei; Zhang, Faxiang; Sun, Zhihui; Li, ShuJuan; Wang, Meng; Wang, Chang

    2017-10-01

    In order to satisfy hydroelectric generating set low-frequency vibration monitoring, the design of Passive low-frequency vibration monitoring system based on Optical fiber sensing in this paper. The hardware of the system adopts the passive optical fiber grating sensor and unbalanced-Michelson interferometer. The software system is used to programming by Labview software and finishing the control of system. The experiment show that this system has good performance on the standard vibration testing-platform and it meets system requirements. The frequency of the monitoring system can be as low as 0.2Hz and the resolution is 0.01Hz.

  19. Data Collection Method for Mobile Control Sink Node in Wireless Sensor Network Based on Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Ling Yongfa

    2016-01-01

    Full Text Available The paper proposes a mobile control sink node data collection method in the wireless sensor network based on compressive sensing. This method, with regular track, selects the optimal data collection points in the monitoring area via the disc method, calcu-lates the shortest path by using the quantum genetic algorithm, and hence determines the data collection route. Simulation results show that this method has higher network throughput and better energy efficiency, capable of collecting a huge amount of data with balanced energy consumption in the network.

  20. Reconstruction algorithm in compressed sensing based on maximum a posteriori estimation

    International Nuclear Information System (INIS)

    Takeda, Koujin; Kabashima, Yoshiyuki

    2013-01-01

    We propose a systematic method for constructing a sparse data reconstruction algorithm in compressed sensing at a relatively low computational cost for general observation matrix. It is known that the cost of ℓ 1 -norm minimization using a standard linear programming algorithm is O(N 3 ). We show that this cost can be reduced to O(N 2 ) by applying the approach of posterior maximization. Furthermore, in principle, the algorithm from our approach is expected to achieve the widest successful reconstruction region, which is evaluated from theoretical argument. We also discuss the relation between the belief propagation-based reconstruction algorithm introduced in preceding works and our approach

  1. Boronate-Modified Interdigitated Electrode Array for Selective Impedance-Based Sensing of Glycated Hemoglobin

    DEFF Research Database (Denmark)

    Boonyasit, Yuwadee; Laiwattanapaisal, Wanida; Chailapakul, Orawon

    2016-01-01

    An impedance-based label-free affinity sensor was developed for the recognition of glycated hemoglobin (HbA1c). Interdigitated gold microelectrode arrays (IDA) were first modified with a self-assembled monolayer of cysteamine followed by cross-linking with glutaraldehyde and subsequent binding of 3......-aminophenylboronic acid (APBA), which selectively binds HbA1c via cis-diol interactions. Impedance sensing was demonstrated to be highly responsive to the clinically relevant HbA1c levels (0.1%-8.36%) with a detection limit of 0.024% (3σ). The specificity of the assay was evaluated with non-glycated hemoglobin (Hb...

  2. Active learning innovative for the study of climatic variations in Sicily (Italy) and micro-climates in confined environments. Digitized construction of agro-meteorological laboratory and entrepreneurial development of methodical home automation systems

    Science.gov (United States)

    Crimi, Pietro

    2017-04-01

    In education to issues of environmental sustainability and the use of renewable energy resources, there are the existing laboratory teaching methodologies in Superior School "A. Volta" in Palermo (Italy) for acquisition, processing and control network of agro-meteorological data on the local area. This station was planned to allow students practical multidisciplinary learning experiences in the field of agro-meteorological applications. The School started a few months ago a project of MIUR (Italian Ministry of Education) that updates the lab through the most innovative digital technologies in the field of mechatronics, domotic and sustainable energy, that are supported by the latest needs of scientific-educational multimedia. It is an educational training that intends to implement a data collection center agro-meteorological on "digital platforms," informational purposes and applications, on current issues of climate changes and their consequences in Sicily (Italy). This active learning will interconnect the data collected from the station weather and climate of the school with those locally and regionally, with "weather-climatic patterns" correlations that are implemented in the Mediterranean area (International Program "GAW-Global Atmosphere Watch"). For this reason were enabled synergies with two major public scientific research and acquisition services-data disclosure (ENEA and SIAS-Agrometeorological Information Service, Sicily Region), both to energy efficiency of the School Station, both to support data and digital applications in GIS, with agro-meteorological services to companies operating in the agricultural and environmental sustainability, high consideration themes in European Programming. A branch of this training course is the entrepreneurship education, carried out by a few years in School with the development of "experimental models" for the creation of "innovation clusters" to make entrepreneurial experience since school, creating/managing mini

  3. Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data †

    Science.gov (United States)

    Xie, Qingqing; Wang, Liangmin

    2016-01-01

    With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman) algorithm and ciphertext policy attribute-based encryption (CP-ABE) scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA) and efficient enough for practical applications in terms of user side computation overhead. PMID:27897984

  4. Fluorometric sensing of Triton X-100 based organized media in water by a MOF

    Energy Technology Data Exchange (ETDEWEB)

    Dey, Biswajit, E-mail: bdeychem@gmail.com [Department of Chemistry, Visva-Bharati University, Santiniketan 731235 (India); Mondal, Ranjan Kumar; Dhibar, Subhendu [Department of Chemistry, Visva-Bharati University, Santiniketan 731235 (India); Chattopadhyay, Asoke Prasun [Department of Chemistry, University of Kalyani, Kalyani 741235 (India); Bhattacharya, Subhash Chandra [Department of Chemistry, Jadavpur University, Kolkata 700032 (India)

    2016-04-15

    The fluorescent property of the aqueous solution of a metal organic framework (MOF) of Mn(II), having a sedimentary rocks like microstructure in solid-state, has been investigated. The luminescent feature of the the aqueous solution of MOF has been employed for studying the interactions of MOF with different surfactants including neutral, cationic, and anionic types in water medium. Interestingly, the MOF can very selective sense Triton X-100 based micelle in water medium. During the sensing process the fluorescent monomer of the MOF gets accommodated at the palisade layer of Triton X-100 in water medium and this has also been justified by simple fluorescence spectral and FE-SEM microstructural analysis. Thus, a MOF of Mn(II) can act as a selective fluorescent sensor for Triton X-100 based organized medium in water. - Highlights: • Microstructural and crystallographic studies of a water-soluble MOF are performed. • The luminescent property of MOF in water medium is explored. • The interaction between Triton X-100 and the MOF in water medium is studied by fluorometric and microstructural analysis. • The MOF acts as a selective fluorometric sensor for the Triton X-100 based organized media in water. • The monomer of MOF presents in the Triton X-100 micelle in water.

  5. Fluorometric sensing of Triton X-100 based organized media in water by a MOF

    International Nuclear Information System (INIS)

    Dey, Biswajit; Mondal, Ranjan Kumar; Dhibar, Subhendu; Chattopadhyay, Asoke Prasun; Bhattacharya, Subhash Chandra

    2016-01-01

    The fluorescent property of the aqueous solution of a metal organic framework (MOF) of Mn(II), having a sedimentary rocks like microstructure in solid-state, has been investigated. The luminescent feature of the the aqueous solution of MOF has been employed for studying the interactions of MOF with different surfactants including neutral, cationic, and anionic types in water medium. Interestingly, the MOF can very selective sense Triton X-100 based micelle in water medium. During the sensing process the fluorescent monomer of the MOF gets accommodated at the palisade layer of Triton X-100 in water medium and this has also been justified by simple fluorescence spectral and FE-SEM microstructural analysis. Thus, a MOF of Mn(II) can act as a selective fluorescent sensor for Triton X-100 based organized medium in water. - Highlights: • Microstructural and crystallographic studies of a water-soluble MOF are performed. • The luminescent property of MOF in water medium is explored. • The interaction between Triton X-100 and the MOF in water medium is studied by fluorometric and microstructural analysis. • The MOF acts as a selective fluorometric sensor for the Triton X-100 based organized media in water. • The monomer of MOF presents in the Triton X-100 micelle in water.

  6. Collaborative spectrum sensing based on the ratio between largest eigenvalue and Geometric mean of eigenvalues

    KAUST Repository

    Shakir, Muhammad

    2011-12-01

    In this paper, we introduce a new detector referred to as Geometric mean detector (GEMD) which is based on the ratio of the largest eigenvalue to the Geometric mean of the eigenvalues for collaborative spectrum sensing. The decision threshold has been derived by employing Gaussian approximation approach. In this approach, the two random variables, i.e. The largest eigenvalue and the Geometric mean of the eigenvalues are considered as independent Gaussian random variables such that their cumulative distribution functions (CDFs) are approximated by a univariate Gaussian distribution function for any number of cooperating secondary users and received samples. The approximation approach is based on the calculation of exact analytical moments of the largest eigenvalue and the Geometric mean of the eigenvalues of the received covariance matrix. The decision threshold has been calculated by exploiting the CDF of the ratio of two Gaussian distributed random variables. In this context, we exchange the analytical moments of the two random variables with the moments of the Gaussian distribution function. The performance of the detector is compared with the performance of the energy detector and eigenvalue ratio detector. Analytical and simulation results show that our newly proposed detector yields considerable performance advantage in realistic spectrum sensing scenarios. Moreover, our results based on proposed approximation approach are in perfect agreement with the empirical results. © 2011 IEEE.

  7. Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data

    Directory of Open Access Journals (Sweden)

    Qingqing Xie

    2016-11-01

    Full Text Available With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP can provide location-based service (LBS for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman algorithm and ciphertext policy attribute-based encryption (CP-ABE scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA and efficient enough for practical applications in terms of user side computation overhead.

  8. Orthogonality-breaking sensing model based on the instantaneous Stokes vector and the Mueller calculus

    Science.gov (United States)

    Ortega-Quijano, Noé; Fade, Julien; Roche, Muriel; Parnet, François; Alouini, Mehdi

    2016-04-01

    Polarimetric sensing by orthogonality breaking has been recently proposed as an alternative technique for performing direct and fast polarimetric measurements using a specific dual-frequency dual-polarization (DFDP) source. Based on the instantaneous Stokes-Mueller formalism to describe the high-frequency evolution of the DFDP beam intensity, we thoroughly analyze the interaction of such a beam with birefringent, dichroic and depolarizing samples. This allows us to confirm that orthogonality breaking is produced by the sample diattenuation, whereas this technique is immune to both birefringence and diagonal depolarization. We further analyze the robustness of this technique when polarimetric sensing is performed through a birefringent waveguide, and the optimal DFDP source configuration for fiber-based endoscopic measurements is subsequently identified. Finally, we consider a stochastic depolarization model based on an ensemble of random linear diattenuators, which makes it possible to understand the progressive vanishing of the detected orthogonality breaking signal as the spatial heterogeneity of the sample increases, thus confirming the insensitivity of this method to diagonal depolarization. The fact that the orthogonality breaking signal is exclusively due to the sample dichroism is an advantageous feature for the precise decoupled characterization of such an anisotropic parameter in samples showing several simultaneous effects.

  9. Design and Fabrication of Piezoresistive Based Encapsulated Poly-Si Cantilevers for Bio/chemical Sensing

    Science.gov (United States)

    Krishna, N. P. Vamsi; Murthy, T. R. Srinivasa; Reddy, K. Jayaprakash; Sangeeth, K.; Hegde, G. M.

    Cantilever-based sensing is a growing research field not only within micro regime but also in nano technology. The technology offers a method for rapid, on-line and in-situ monitoring of specific bio/chemical substances by detecting the nanomechanical responses of a cantilever sensor. Cantilever with piezoresistive based detection scheme is more attractive because of its electronics compatibility. Majority of commercially available micromachined piezoresistive sensors are bulk micromachined devices and are fabricated using single crystal silicon wafers. As substrate properties are not important in surface micromachining, the expensive silicon wafers can be replaced by cheaper substrates, such as poly-silicon, glass or plastic. Here we have designed SU-8 based bio/chemical compatible micro electro mechanical device that includes an encapsulated polysilicon piezoresistor for bio/chemical sensing. In this paper we report the design, fabrication and analysis of the encapsulated poly-Si cantilevers. Design and theoretical analysis are carried out using Finite Element Analysis software. For fabrication of poly-silicon piezoresistive cantilevers we followed the surface micromachining process steps. Preliminary characterization of the cantilevers is presented.

  10. Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data.

    Science.gov (United States)

    Xie, Qingqing; Wang, Liangmin

    2016-11-25

    With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman) algorithm and ciphertext policy attribute-based encryption (CP-ABE) scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA) and efficient enough for practical applications in terms of user side computation overhead.

  11. SenSafe: A Smartphone-Based Traffic Safety Framework by Sensing Vehicle and Pedestrian Behaviors

    Directory of Open Access Journals (Sweden)

    Zhenyu Liu

    2016-01-01

    Full Text Available Traffic accident involving vehicles is one of the most serious problems in the transportation system nowadays. How to detect dangerous steering and then alarm drivers in real time is a problem. What is more, walking while using smartphones makes pedestrian more susceptible to various risks. Although dedicated short range communication (DSRC provides the way for safety communications, most of vehicles have not been deployed with DSRC components. Even worse, DSRC is not supported by the smartphones for vehicle-to-pedestrian (V2P communication. In this paper, a smartphone-based framework named SenSafe is developed to improve the traffic safety. SenSafe is a framework which only utilizes the smartphone to sense the surrounding events and provides alerts to drivers. Smartphone-based driving behaviors detection mechanism is developed inside the framework to discover various steering behaviors. Besides, the Wi-Fi association and authentication overhead is reduced to broadcast the compressed sensing data using the Wi-Fi beacon to inform the drivers of the surroundings. Furthermore, a collision estimation algorithm is designed to issue appropriate warnings. Finally, an Android-based implementation of SenSafe framework has been achieved to demonstrate the application reliability in real environments.

  12. A Molecular Electronic Transducer based Low-Frequency Accelerometer with Electrolyte Droplet Sensing Body

    Science.gov (United States)

    Liang, Mengbing

    "Sensor Decade" has been labeled on the first decade of the 21st century. Similar to the revolution of micro-computer in 1980s, sensor R&D developed rapidly during the past 20 years. Hard workings were mainly made to minimize the size of devices with optimal the performance. Efforts to develop the small size devices are mainly concentrated around Micro-electro-mechanical-system (MEMS) technology. MEMS accelerometers are widely published and used in consumer electronics, such as smart phones, gaming consoles, anti-shake camera and vibration detectors. This study represents liquid-state low frequency micro-accelerometer based on molecular electronic transducer (MET), in which inertial mass is not the only but also the conversion of mechanical movement to electric current signal is the main utilization of the ionic liquid. With silicon-based planar micro-fabrication, the device uses a sub-micron liter electrolyte droplet sealed in oil as the sensing body and a MET electrode arrangement which is the anode-cathode-cathode-anode (ACCA) in parallel as the read-out sensing part. In order to sensing the movement of ionic liquid, an imposed electric potential was applied between the anode and the cathode. The electrode reaction, I3-- + 2e-- ↔ 3I --, occurs around the cathode which is reverse at the anodes. Obviously, the current magnitude varies with the concentration of ionic liquid, which will be effected by the movement of liquid droplet as the inertial mass. With such structure, the promising performance of the MET device design is to achieve 10.8 V/G (G=9.81 m/s2) sensitivity at 20 Hz with the bandwidth from 1 Hz to 50 Hz, and a low noise floor of 100 microg/sqrt(Hz) at 20 Hz.

  13. Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

    Energy Technology Data Exchange (ETDEWEB)

    AlAfeef, Ala, E-mail: a.al-afeef.1@research.gla.ac.uk [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); School of Computing Science, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Bobynko, Joanna [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Cockshott, W. Paul. [School of Computing Science, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Craven, Alan J. [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom); Zuazo, Ian; Barges, Patrick [ArcelorMittal Maizières Research, Maizières-lès-Metz 57283 (France); MacLaren, Ian, E-mail: ian.maclaren@glasgow.ac.uk [SUPA School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ (United Kingdom)

    2016-11-15

    We have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionally, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS. - Highlights: • DualEELS is essential for chemically sensitive electron tomography using EELS. • A new compressed sensing based algorithm (DLET) gives high fidelity reconstruction. • This combination of DualEELS and DLET will give reliable results from few projections.

  14. User-based motion sensing and fuzzy logic for automated fall detection in older adults

    DEFF Research Database (Denmark)

    Boissy, Patrice; Choquette, Stéphane; Hamel, Mathieu

    2007-01-01

    , and reduce complications from falls. The performance of a 2-stage fall detection algorithm using impact magnitudes and changes in trunk angles derived from user-based motion sensors was evaluated under laboratory conditions. Ten healthy participants were instrumented on the front and side of the trunk with 3...... fall conditions with a success rate of 93% and a false-positive rate of 29% during nonfall conditions. Despite a slightly superior identification performance for the accelerometer located on the front of the trunk, no significant differences were found between the two motion sensor locations. Automated...... detection of fall events based on user-based motion sensing and fuzzy logic shows promising results. Additional rules and optimization of the algorithm will be needed to decrease the false-positive rate....

  15. A Study on Integrated Community Based Flood Mitigation with Remote Sensing Technique in Kota Bharu, Kelantan

    International Nuclear Information System (INIS)

    Ainullotfi, A A; Ibrahim, A L; Masron, T

    2014-01-01

    This study is conducted to establish a community based flood management system that is integrated with remote sensing technique. To understand local knowledge, the demographic of the local society is obtained by using the survey approach. The local authorities are approached first to obtain information regarding the society in the study areas such as the population, the gender and the tabulation of settlement. The information about age, religion, ethnic, occupation, years of experience facing flood in the area, are recorded to understand more on how the local knowledge emerges. Then geographic data is obtained such as rainfall data, land use, land elevation, river discharge data. This information is used to establish a hydrological model of flood in the study area. Analysis were made from the survey approach to understand the pattern of society and how they react to floods while the analysis of geographic data is used to analyse the water extent and damage done by the flood. The final result of this research is to produce a flood mitigation method with a community based framework in the state of Kelantan. With the flood mitigation that involves the community's understanding towards flood also the techniques to forecast heavy rainfall and flood occurrence using remote sensing, it is hope that it could reduce the casualties and damage that might cause to the society and infrastructures in the study area

  16. An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection

    Directory of Open Access Journals (Sweden)

    Sen Zhang

    2015-01-01

    Full Text Available The concentration of alumina in the electrolyte is of great significance during the production of aluminum; it may affect the stability of aluminum reduction cell and the current efficiency. However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell. At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement. In this paper, a novel soft sensing method based on a modified extreme learning machine (MELM for online measurement of the alumina concentration is proposed. The modified ELM algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references. It randomly chooses the input weights and analytically determines the output weights without manual intervention. The simulation results show that the approach can give more accurate estimations of alumina concentration with faster learning speed compared with other methods such as BP and SVM.

  17. S-CNN-BASED SHIP DETECTION FROM HIGH-RESOLUTION REMOTE SENSING IMAGES

    Directory of Open Access Journals (Sweden)

    R. Zhang

    2016-06-01

    Full Text Available Reliable ship detection plays an important role in both military and civil fields. However, it makes the task difficult with high-resolution remote sensing images with complex background and various types of ships with different poses, shapes and scales. Related works mostly used gray and shape features to detect ships, which obtain results with poor robustness and efficiency. To detect ships more automatically and robustly, we propose a novel ship detection method based on the convolutional neural networks (CNNs, called SCNN, fed with specifically designed proposals extracted from the ship model combined with an improved saliency detection method. Firstly we creatively propose two ship models, the “V” ship head model and the “||” ship body one, to localize the ship proposals from the line segments extracted from a test image. Next, for offshore ships with relatively small sizes, which cannot be efficiently picked out by the ship models due to the lack of reliable line segments, we propose an improved saliency detection method to find these proposals. Therefore, these two kinds of ship proposals are fed to the trained CNN for robust and efficient detection. Experimental results on a large amount of representative remote sensing images with different kinds of ships with varied poses, shapes and scales demonstrate the efficiency and robustness of our proposed S-CNN-Based ship detector.

  18. Direction-of-Arrival Estimation for Coprime Array Using Compressive Sensing Based Array Interpolation

    Directory of Open Access Journals (Sweden)

    Aihua Liu

    2017-01-01

    Full Text Available A method of direction-of-arrival (DOA estimation using array interpolation is proposed in this paper to increase the number of resolvable sources and improve the DOA estimation performance for coprime array configuration with holes in its virtual array. The virtual symmetric nonuniform linear array (VSNLA of coprime array signal model is introduced, with the conventional MUSIC with spatial smoothing algorithm (SS-MUSIC applied on the continuous lags in the VSNLA; the degrees of freedom (DoFs for DOA estimation are obviously not fully exploited. To effectively utilize the extent of DoFs offered by the coarray configuration, a compressing sensing based array interpolation algorithm is proposed. The compressing sensing technique is used to obtain the coarse initial DOA estimation, and a modified iterative initial DOA estimation based interpolation algorithm (IMCA-AI is then utilized to obtain the final DOA estimation, which maps the sample covariance matrix of the VSNLA to the covariance matrix of a filled virtual symmetric uniform linear array (VSULA with the same aperture size. The proposed DOA estimation method can efficiently improve the DOA estimation performance. The numerical simulations are provided to demonstrate the effectiveness of the proposed method.

  19. Comprehensive long distance and real-time pipeline monitoring system based on fiber optic sensing

    Energy Technology Data Exchange (ETDEWEB)

    Nikles, Marc; Ravet, Fabien; Briffod, Fabien [Omnisens S.A., Morges (Switzerland)

    2009-07-01

    An increasing number of pipelines are constructed in remote regions affected by harsh environmental conditions. These pipeline routes often cross mountain areas which are characterized by unstable grounds and where soil texture changes between winter and summer increase the probability of hazards. Due to the long distances to be monitored and the linear nature of pipelines, distributed fiber optic sensing techniques offer significant advantages and the capability to detect and localize pipeline disturbance with great precision. Furthermore pipeline owner/operators lay fiber optic cable parallel to transmission pipelines for telecommunication purposes and at minimum additional cost monitoring capabilities can be added to the communication system. The Brillouin-based Omnisens DITEST monitoring system has been used in several long distance pipeline projects. The technique is capable of measuring strain and temperature over 100's kilometers with meter spatial resolution. Dedicated fiber optic cables have been developed for continuous strain and temperature monitoring and their deployment along the pipeline has enabled permanent and continuous pipeline ground movement, intrusion and leak detection. This paper presents a description of the fiber optic Brillouin-based DITEST sensing technique, its measurement performance and limits, while addressing future perspectives for pipeline monitoring. (author)

  20. Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity

    Science.gov (United States)

    Xu, Li; Shan, Lin; Adachi, Fumiyuki

    2014-01-01

    In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting intersymbol interference (ISI) over data transmission. Broadband channel model is often described by very few dominant channel taps and they can be probed by compressive sensing based sparse channel estimation (SCE) methods, for example, orthogonal matching pursuit algorithm, which can take the advantage of sparse structure effectively in the channel as for prior information. However, these developed methods are vulnerable to both noise interference and column coherence of training signal matrix. In other words, the primary objective of these conventional methods is to catch the dominant channel taps without a report of posterior channel uncertainty. To improve the estimation performance, we proposed a compressive sensing based Bayesian sparse channel estimation (BSCE) method which cannot only exploit the channel sparsity but also mitigate the unexpected channel uncertainty without scarifying any computational complexity. The proposed method can reveal potential ambiguity among multiple channel estimators that are ambiguous due to observation noise or correlation interference among columns in the training matrix. Computer simulations show that proposed method can improve the estimation performance when comparing with conventional SCE methods. PMID:24983012

  1. Displacement sensing based on resonant frequency monitoring of electrostatically actuated curved micro beams

    International Nuclear Information System (INIS)

    Krakover, Naftaly; Krylov, Slava; Ilic, B Robert

    2016-01-01

    The ability to control nonlinear interactions of suspended mechanical structures offers a unique opportunity to engineer rich dynamical behavior that extends the dynamic range and ultimate device sensitivity. We demonstrate a displacement sensing technique based on resonant frequency monitoring of curved, doubly clamped, bistable micromechanical beams interacting with a movable electrode. In this configuration, the electrode displacement influences the nonlinear electrostatic interactions, effective stiffness and frequency of the curved beam. Increased sensitivity is made possible by dynamically operating the beam near the snap-through bistability onset. Various in-plane device architectures were fabricated from single crystal silicon and measured under ambient conditions using laser Doppler vibrometry. In agreement with the reduced order Galerkin-based model predictions, our experimental results show a significant resonant frequency reduction near critical snap-through, followed by a frequency increase within the post-buckling configuration. Interactions with a stationary electrode yield a voltage sensitivity up to  ≈560 Hz V −1 and results with a movable electrode allow motion sensitivity up to  ≈1.5 Hz nm −1 . Our theoretical and experimental results collectively reveal the potential of displacement sensing using nonlinear interactions of geometrically curved beams near instabilities, with possible applications ranging from highly sensitive resonant inertial detectors to complex optomechanical platforms providing an interface between the classical and quantum domains. (paper)

  2. Autonomous Micro-Air-Vehicle Control Based on Visual Sensing for Odor Source Localization

    Directory of Open Access Journals (Sweden)

    Kenzo Kurotsuchi

    2017-07-01

    Full Text Available In this paper, we propose a novel control method for autonomous-odor-source localization using visual and odor sensing by micro air vehicles (MAVs. Our method is based on biomimetics, which enable highly autonomous localization. Our method does not need any instruction signals, including even global positioning system (GPS signals. An experimenter simply blows a whistle, and the MAV will then start to hover, to seek an odor source, and to keep hovering near the source. The GPS-signal-free control based on visual sense enables indoor/underground use. Moreover, the MAV is light-weight (85 grams and does not cause harm to others even if it accidentally falls. Experiments conducted in the real world were successful in enabling odor source localization using the MAV with a bio-inspired searching method. The distance error of the localization was 63 cm, more accurate than the target distance of 120 cm for individual identification. Our odor source localization is the first step to a proof of concept for a danger warning system. These localization experiments were the first step to a proof of concept for a danger warning system to enable a safer and more secure society.

  3. Texture-based classification for characterizing regions on remote sensing images

    Science.gov (United States)

    Borne, Frédéric; Viennois, Gaëlle

    2017-07-01

    Remote sensing classification methods mostly use only the physical properties of pixels or complex texture indexes but do not lead to recommendation for practical applications. Our objective was to design a texture-based method, called the Paysages A PRIori method (PAPRI), which works both at pixel and neighborhood level and which can handle different spatial scales of analysis. The aim was to stay close to the logic of a human expert and to deal with co-occurrences in a more efficient way than other methods. The PAPRI method is pixelwise and based on a comparison of statistical and spatial reference properties provided by the expert with local properties computed in varying size windows centered on the pixel. A specific distance is computed for different windows around the pixel and a local minimum leads to choosing the class in which the pixel is to be placed. The PAPRI method brings a significant improvement in classification quality for different kinds of images, including aerial, lidar, high-resolution satellite images as well as texture images from the Brodatz and Vistex databases. This work shows the importance of texture analysis in understanding remote sensing images and for future developments.

  4. Corn and sorghum phenotyping using a fixed-wing UAV-based remote sensing system

    Science.gov (United States)

    Shi, Yeyin; Murray, Seth C.; Rooney, William L.; Valasek, John; Olsenholler, Jeff; Pugh, N. Ace; Henrickson, James; Bowden, Ezekiel; Zhang, Dongyan; Thomasson, J. Alex

    2016-05-01

    Recent development of unmanned aerial systems has created opportunities in automation of field-based high-throughput phenotyping by lowering flight operational cost and complexity and allowing flexible re-visit time and higher image resolution than satellite or manned airborne remote sensing. In this study, flights were conducted over corn and sorghum breeding trials in College Station, Texas, with a fixed-wing unmanned aerial vehicle (UAV) carrying two multispectral cameras and a high-resolution digital camera. The objectives were to establish the workflow and investigate the ability of UAV-based remote sensing for automating data collection of plant traits to develop genetic and physiological models. Most important among these traits were plant height and number of plants which are currently manually collected with high labor costs. Vegetation indices were calculated for each breeding cultivar from mosaicked and radiometrically calibrated multi-band imagery in order to be correlated with ground-measured plant heights, populations and yield across high genetic-diversity breeding cultivars. Growth curves were profiled with the aerial measured time-series height and vegetation index data. The next step of this study will be to investigate the correlations between aerial measurements and ground truth measured manually in field and from lab tests.

  5. Micro-resonators based on integrated polymer technology for optical sensing

    Science.gov (United States)

    Girault, Pauline; Lemaitre, Jonathan; Guendouz, Mohammed; Lorrain, Nathalie; Poffo, Luiz; Gadonna, Michel; Bosc, Dominique

    2014-05-01

    Research on sensors has experienced a noticeable development over the last decades especially in label free optical biosensors. However, compact sensors without markers for rapid, reliable and inexpensive detection of various substances induce a significant research of new technological solutions. The context of this work is the development of a sensor based on easily integrated and inexpensive micro-resonator (MR) component in integrated optics, highly sensitive and selective mainly in the areas of health and food. In this work, we take advantage of our previous studies on filters based on micro-resonators (MR) to experiment a new couple of polymers in the objective to use MR as a sensing function. MRs have been fabricated by processing SU8 polymer as core and PMATRIFE polymer as cladding layer of the waveguide. The refractive index contrast reaches 0.16 @ 1550 nm. Sub-micronic ring waveguides gaps from 0.5 to 1 μm have been successfully achieved with UV (i-line) photolithography. This work confirms our forecasts, published earlier, about the resolution that can be achieved. First results show a good extinction coefficient of ~17 dB, a quality factor around 104 and a finesse of 12. These results are in concordance with the theoretical study and they allow us to validate our technology with this couple of polymers. Work is going on with others lower cladding materials that will be used to further increase refractive index contrast for sensing applications.

  6. Distortion correction algorithm for UAV remote sensing image based on CUDA

    International Nuclear Information System (INIS)

    Wenhao, Zhang; Yingcheng, Li; Delong, Li; Changsheng, Teng; Jin, Liu

    2014-01-01

    In China, natural disasters are characterized by wide distribution, severe destruction and high impact range, and they cause significant property damage and casualties every year. Following a disaster, timely and accurate acquisition of geospatial information can provide an important basis for disaster assessment, emergency relief, and reconstruction. In recent years, Unmanned Aerial Vehicle (UAV) remote sensing systems have played an important role in major natural disasters, with UAVs becoming an important technique of obtaining disaster information. UAV is equipped with a non-metric digital camera with lens distortion, resulting in larger geometric deformation for acquired images, and affecting the accuracy of subsequent processing. The slow speed of the traditional CPU-based distortion correction algorithm cannot meet the requirements of disaster emergencies. Therefore, we propose a Compute Unified Device Architecture (CUDA)-based image distortion correction algorithm for UAV remote sensing, which takes advantage of the powerful parallel processing capability of the GPU, greatly improving the efficiency of distortion correction. Our experiments show that, compared with traditional CPU algorithms and regardless of image loading and saving times, the maximum acceleration ratio using our proposed algorithm reaches 58 times that using the traditional algorithm. Thus, data processing time can be reduced by one to two hours, thereby considerably improving disaster emergency response capability

  7. A GIS/Remote Sensing-based methodology for groundwater potentiality assessment in Tirnavos area, Greece

    Science.gov (United States)

    Oikonomidis, D.; Dimogianni, S.; Kazakis, N.; Voudouris, K.

    2015-06-01

    The aim of this paper is to assess the groundwater potentiality combining Geographic Information Systems and Remote Sensing with data obtained from the field, as an additional tool to the hydrogeological research. The present study was elaborated in the broader area of Tirnavos, covering 419.4 km2. The study area is located in Thessaly (central Greece) and is crossed by two rivers, Pinios and Titarisios. Agriculture is one of the main elements of Thessaly's economy resulting in intense agricultural activity and consequently increased exploitation of groundwater resources. Geographic Information Systems (GIS) and Remote Sensing (RS) were used in order to create a map that depicts the likelihood of existence of groundwater, consisting of five classes, showing the groundwater potentiality and ranging from very high to very low. The extraction of this map is based on the study of input data such as: rainfall, potential recharge, lithology, lineament density, slope, drainage density and depth to groundwater. Weights were assigned to all these factors according to their relevance to groundwater potential and eventually a map based on weighted spatial modeling system was created. Furthermore, a groundwater quality suitability map was illustrated by overlaying the groundwater potentiality map with the map showing the potential zones for drinking groundwater in the study area. The results provide significant information and the maps could be used from local authorities for groundwater exploitation and management.

  8. Secure biometric image sensor and authentication scheme based on compressed sensing.

    Science.gov (United States)

    Suzuki, Hiroyuki; Suzuki, Masamichi; Urabe, Takuya; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

    2013-11-20

    It is important to ensure the security of biometric authentication information, because its leakage causes serious risks, such as replay attacks using the stolen biometric data, and also because it is almost impossible to replace raw biometric information. In this paper, we propose a secure biometric authentication scheme that protects such information by employing an optical data ciphering technique based on compressed sensing. The proposed scheme is based on two-factor authentication, the biometric information being supplemented by secret information that is used as a random seed for a cipher key. In this scheme, a biometric image is optically encrypted at the time of image capture, and a pair of restored biometric images for enrollment and verification are verified in the authentication server. If any of the biometric information is exposed to risk, it can be reenrolled by changing the secret information. Through numerical experiments, we confirm that finger vein images can be restored from the compressed sensing measurement data. We also present results that verify the accuracy of the scheme.

  9. A Novel Object Tracking Algorithm Based on Compressed Sensing and Entropy of Information

    Directory of Open Access Journals (Sweden)

    Ding Ma

    2015-01-01

    Full Text Available Object tracking has always been a hot research topic in the field of computer vision; its purpose is to track objects with specific characteristics or representation and estimate the information of objects such as their locations, sizes, and rotation angles in the current frame. Object tracking in complex scenes will usually encounter various sorts of challenges, such as location change, dimension change, illumination change, perception change, and occlusion. This paper proposed a novel object tracking algorithm based on compressed sensing and information entropy to address these challenges. First, objects are characterized by the Haar (Haar-like and ORB features. Second, the dimensions of computation space of the Haar and ORB features are effectively reduced through compressed sensing. Then the above-mentioned features are fused based on information entropy. Finally, in the particle filter framework, an object location was obtained by selecting candidate object locations in the current frame from the local context neighboring the optimal locations in the last frame. Our extensive experimental results demonstrated that this method was able to effectively address the challenges of perception change, illumination change, and large area occlusion, which made it achieve better performance than existing approaches such as MIL and CT.

  10. A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features

    Directory of Open Access Journals (Sweden)

    LEI Xiaoqi

    2016-02-01

    Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.

  11. Empirical Determination of Efficient Sensing Frequencies for Magnetometer-Based Continuous Human Contact Monitoring

    Directory of Open Access Journals (Sweden)

    Seungho Kuk

    2018-04-01

    Full Text Available The high linear correlation between the smartphone magnetometer readings in close proximity can be exploited for physical human contact detection, which could be useful for such applications as infectious disease contact tracing or social behavior monitoring. Alternative approaches using other capabilities in smartphones have aspects that do not fit well with the human contact detection. Using Wi-Fi or cellular fingerprints have larger localization errors than close human contact distances. Bluetooth beacons could reveal the identity of the transmitter, threatening the privacy of the user. Also, using sensors such as GPS does not work for indoor contacts. However, the magnetometer correlation check works best in human contact distances that matter in infectious disease transmissions or social interactions. The omni-present geomagnetism makes it work both indoors and outdoors, and the measured magnetometer values do not easily reveal the identity and the location of the smartphone. One issue with the magnetometer-based contact detection, however, is the energy consumption. Since the contacts can take place anytime, the magnetometer sensing and recording should be running continuously. Therefore, how we address the energy requirement for the extended and continuous operation can decide the viability of the whole idea. However, then, we note that almost all existing magnetometer-based applications such as indoor location and navigation have used high sensing frequencies, ranging from 10 Hz to 200 Hz. At these frequencies, we measure that the time to complete battery drain in a typical smartphone is shortened by three to twelve hours. The heavy toll raises the question as to whether the magnetometer-based contact detection can avoid such high sensing rates while not losing the contact detection accuracy. In order to answer the question, we conduct a measurement-based study using independently produced magnetometer traces from three different

  12. Empirical Determination of Efficient Sensing Frequencies for Magnetometer-Based Continuous Human Contact Monitoring.

    Science.gov (United States)

    Kuk, Seungho; Kim, Junha; Park, Yongtae; Kim, Hyogon

    2018-04-27

    The high linear correlation between the smartphone magnetometer readings in close proximity can be exploited for physical human contact detection, which could be useful for such applications as infectious disease contact tracing or social behavior monitoring. Alternative approaches using other capabilities in smartphones have aspects that do not fit well with the human contact detection. Using Wi-Fi or cellular fingerprints have larger localization errors than close human contact distances. Bluetooth beacons could reveal the identity of the transmitter, threatening the privacy of the user. Also, using sensors such as GPS does not work for indoor contacts. However, the magnetometer correlation check works best in human contact distances that matter in infectious disease transmissions or social interactions. The omni-present geomagnetism makes it work both indoors and outdoors, and the measured magnetometer values do not easily reveal the identity and the location of the smartphone. One issue with the magnetometer-based contact detection, however, is the energy consumption. Since the contacts can take place anytime, the magnetometer sensing and recording should be running continuously. Therefore, how we address the energy requirement for the extended and continuous operation can decide the viability of the whole idea. However, then, we note that almost all existing magnetometer-based applications such as indoor location and navigation have used high sensing frequencies, ranging from 10 Hz to 200 Hz. At these frequencies, we measure that the time to complete battery drain in a typical smartphone is shortened by three to twelve hours. The heavy toll raises the question as to whether the magnetometer-based contact detection can avoid such high sensing rates while not losing the contact detection accuracy. In order to answer the question, we conduct a measurement-based study using independently produced magnetometer traces from three different countries. Specifically, we

  13. Chemical sensing and imaging based on photon upconverting nano- and microcrystals: a review

    International Nuclear Information System (INIS)

    Christ, Simon; Schäferling, Michael

    2015-01-01

    The demand for photostable luminescent reporters that absorb and emit light in the red to near-infrared (NIR) spectral region continues in biomedical research and bioanalysis. In recent years, classical organic fluorophores have increasingly been displaced by luminescent nanoparticles. These consist of either polymer or silica based beads that are loaded with luminescent dyes, conjugated polymers, or inorganic nanomaterials such as semiconductor nanocrystals (quantum dots), colloidal clusters of silver and gold, or carbon dots. Among the inorganic materials, photon upconversion nanocrystals exhibit a high potential for application to bioimaging or biomolecular assays. They offer an exceptionally high photostability, can be excited in the NIR, and their anti-Stokes emission enables luminescence detection free of background and perturbing scatter effects even in complex biological samples. These lanthanide doped inorganic crystals have multiple emission lines that can be tuned by the selection of the dopants.This review article is focused on the applications of functionalized photon upconversion nanoparticles (UCNPs) to chemical sensing. This is a comparatively new field of research activity and mainly directed at the sensing and imaging of ubiquitous chemical analytes in biological samples, particularly in living cells. For this purpose, the particles have to be functionalized with suitable indicator dyes or recognition elements, as they do not show an intrinsic or specific luminescence response to most of these analytes (e.g. pH, oxygen, metal ions). We describe the strategies for the design of such responsive nanocomposites utilizing either luminescence resonance energy transfer or emission–reabsorption (inner filter effect) mechanisms and also highlight examples for their use either immobilized in sensor layers or directly as nanoprobes for intracellular sensing and imaging. (review)

  14. Remote Sensing-Based Characterization of Settlement Structures for Assessing Local Potential of District Heat

    Directory of Open Access Journals (Sweden)

    Michael Nast

    2011-07-01

    Full Text Available In Europe, heating of houses and commercial areas is one of the major contributors to greenhouse gas emissions. When considering the drastic impact of an increasing emission of greenhouse gases as well as the finiteness of fossil resources, the usage of efficient and renewable energy generation technologies has to be increased. In this context, small-scale heating networks are an important technical component, which enable the efficient and sustainable usage of various heat generation technologies. This paper investigates how the potential of district heating for different settlement structures can be assessed. In particular, we analyze in which way remote sensing and GIS data can assist the planning of optimized heat allocation systems. In order to identify the best suited locations, a spatial model is defined to assess the potential for small district heating networks. Within the spatial model, the local heat demand and the economic costs of the necessary heat allocation infrastructure are compared. Therefore, a first and major step is the detailed characterization of the settlement structure by means of remote sensing data. The method is developed on the basis of a test area in the town of Oberhaching in the South of Germany. The results are validated through detailed in situ data sets and demonstrate that the model facilitates both the calculation of the required input parameters and an accurate assessment of the district heating potential. The described method can be transferred to other investigation areas with a larger spatial extent. The study underlines the range of applications for remote sensing-based analyses with respect to energy-related planning issues.

  15. Research on Remote Sensing Image Classification Based on Feature Level Fusion

    Science.gov (United States)

    Yuan, L.; Zhu, G.

    2018-04-01

    Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

  16. Cantilever-based sensing: the origin of surface stress and optimization strategies

    International Nuclear Information System (INIS)

    Godin, Michel; Tabard-Cossa, Vincent; Miyahara, Yoichi; Grutter, Peter; Monga, Tanya; Bruce Lennox, R; Williams, P J; Beaulieu, L Y

    2010-01-01

    Many interactions drive the adsorption of molecules on surfaces, all of which can result in a measurable change in surface stress. This article compares the contributions of various possible interactions to the overall induced surface stress for cantilever-based sensing applications. The surface stress resulting from adsorption-induced changes in the electronic density of the underlying surface is up to 2-4 orders of magnitude larger than that resulting from intermolecular electrostatic or Lennard-Jones interactions. We reveal that the surface stress associated with the formation of high quality alkanethiol self-assembled monolayers on gold surfaces is independent of the molecular chain length, supporting our theoretical findings. This provides a foundation for the development of new strategies for increasing the sensitivity of cantilever-based sensors for various applications.

  17. Image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing

    Science.gov (United States)

    Zhou, Nanrun; Pan, Shumin; Cheng, Shan; Zhou, Zhihong

    2016-08-01

    Most image encryption algorithms based on low-dimensional chaos systems bear security risks and suffer encryption data expansion when adopting nonlinear transformation directly. To overcome these weaknesses and reduce the possible transmission burden, an efficient image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing is proposed. The original image is measured by the measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the cycle shift operation controlled by a hyper-chaotic system. Cycle shift operation can change the values of the pixels efficiently. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys distribution simultaneously as a nonlinear encryption system. Simulation results verify the validity and the reliability of the proposed algorithm with acceptable compression and security performance.

  18. Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

    Science.gov (United States)

    Yao, Shoukui; Qin, Xiaojuan

    2018-02-01

    Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

  19. The ship edge feature detection based on high and low threshold for remote sensing image

    Science.gov (United States)

    Li, Xuan; Li, Shengyang

    2018-05-01

    In this paper, a method based on high and low threshold is proposed to detect the ship edge feature due to the low accuracy rate caused by the noise. Analyze the relationship between human vision system and the target features, and to determine the ship target by detecting the edge feature. Firstly, using the second-order differential method to enhance the quality of image; Secondly, to improvement the edge operator, we introduction of high and low threshold contrast to enhancement image edge and non-edge points, and the edge as the foreground image, non-edge as a background image using image segmentation to achieve edge detection, and remove the false edges; Finally, the edge features are described based on the result of edge features detection, and determine the ship target. The experimental results show that the proposed method can effectively reduce the number of false edges in edge detection, and has the high accuracy of remote sensing ship edge detection.

  20. Research on metallic material defect detection based on bionic sensing of human visual properties

    Science.gov (United States)

    Zhang, Pei Jiang; Cheng, Tao

    2018-05-01

    Due to the fact that human visual system can quickly lock the areas of interest in complex natural environment and focus on it, this paper proposes an eye-based visual attention mechanism by simulating human visual imaging features based on human visual attention mechanism Bionic Sensing Visual Inspection Model Method to Detect Defects of Metallic Materials in the Mechanical Field. First of all, according to the biologically visually significant low-level features, the mark of defect experience marking is used as the intermediate feature of simulated visual perception. Afterwards, SVM method was used to train the advanced features of visual defects of metal material. According to the weight of each party, the biometrics detection model of metal material defect, which simulates human visual characteristics, is obtained.

  1. [Ecosystem services evaluation based on geographic information system and remote sensing technology: a review].

    Science.gov (United States)

    Li, Wen-Jie; Zhang, Shi-Huang; Wang, Hui-Min

    2011-12-01

    Ecosystem services evaluation is a hot topic in current ecosystem management, and has a close link with human beings welfare. This paper summarized the research progress on the evaluation of ecosystem services based on geographic information system (GIS) and remote sensing (RS) technology, which could be reduced to the following three characters, i. e., ecological economics theory is widely applied as a key method in quantifying ecosystem services, GIS and RS technology play a key role in multi-source data acquisition, spatiotemporal analysis, and integrated platform, and ecosystem mechanism model becomes a powerful tool for understanding the relationships between natural phenomena and human activities. Aiming at the present research status and its inadequacies, this paper put forward an "Assembly Line" framework, which was a distributed one with scalable characteristics, and discussed the future development trend of the integration research on ecosystem services evaluation based on GIS and RS technologies.

  2. UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation

    Science.gov (United States)

    Qiu, Xiang; Dai, Ming; Yin, Chuan-li

    2017-09-01

    Unmanned aerial vehicle (UAV) remote imaging is affected by the bad weather, and the obtained images have the disadvantages of low contrast, complex texture and blurring. In this paper, we propose a blind deconvolution model based on multiple scattering atmosphere point spread function (APSF) estimation to recovery the remote sensing image. According to Narasimhan analytical theory, a new multiple scattering restoration model is established based on the improved dichromatic model. Then using the L0 norm sparse priors of gradient and dark channel to estimate APSF blur kernel, the fast Fourier transform is used to recover the original clear image by Wiener filtering. By comparing with other state-of-the-art methods, the proposed method can correctly estimate blur kernel, effectively remove the atmospheric degradation phenomena, preserve image detail information and increase the quality evaluation indexes.

  3. Boronic Acid-Based Approach for Separation and Immobilization of Glycoproteins and Its Application in Sensing

    Directory of Open Access Journals (Sweden)

    Lin Liu

    2013-10-01

    Full Text Available Glycoproteins influence a broad spectrum of biological processes including cell-cell interaction, host-pathogen interaction, or protection of proteins against proteolytic degradation. The analysis of their glyco-structures and concentration levels are increasingly important in diagnosis and proteomics. Boronic acids can covalently react with cis-diols in the oligosaccharide chains of glycoproteins to form five- or six-membered cyclic esters. Based on this interaction, boronic acid-based ligands and materials have attracted much attention in both chemistry and biology as the recognition motif for enrichment and chemo/biosensing of glycoproteins in recent years. In this work, we reviewed the progress in the separation, immobilization and detection of glycoproteins with boronic acid-functionalized materials and addressed its application in sensing.

  4. Fusion of remote sensing images based on pyramid decomposition with Baldwinian Clonal Selection Optimization

    Science.gov (United States)

    Jin, Haiyan; Xing, Bei; Wang, Lei; Wang, Yanyan

    2015-11-01

    In this paper, we put forward a novel fusion method for remote sensing images based on the contrast pyramid (CP) using the Baldwinian Clonal Selection Algorithm (BCSA), referred to as CPBCSA. Compared with classical methods based on the transform domain, the method proposed in this paper adopts an improved heuristic evolutionary algorithm, wherein the clonal selection algorithm includes Baldwinian learning. In the process of image fusion, BCSA automatically adjusts the fusion coefficients of different sub-bands decomposed by CP according to the value of the fitness function. BCSA also adaptively controls the optimal search direction of the coefficients and accelerates the convergence rate of the algorithm. Finally, the fusion images are obtained via weighted integration of the optimal fusion coefficients and CP reconstruction. Our experiments show that the proposed method outperforms existing methods in terms of both visual effect and objective evaluation criteria, and the fused images are more suitable for human visual or machine perception.

  5. AUTOMATIC GLOBAL REGISTRATION BETWEEN AIRBORNE LIDAR DATA AND REMOTE SENSING IMAGE BASED ON STRAIGHT LINE FEATURES

    Directory of Open Access Journals (Sweden)

    Z. Q. Liu

    2018-04-01

    Full Text Available An automatic global registration approach for point clouds and remote sensing image based on straight line features is proposed which is insensitive to rotational and scale transformation. First, the building ridge lines and contour lines in point clouds are automatically detected as registration primitives by integrating region growth and topology identification. Second, the collinear condition equation is selected as registration transformation function which is based on rotation matrix described by unit quaternion. The similarity measure is established according to the distance between the corresponding straight line features from point clouds and the image in the same reference coordinate system. Finally, an iterative Hough transform is adopted to simultaneously estimate the parameters and obtain correspondence between registration primitives. Experimental results prove the proposed method is valid and the spectral information is useful for the following classification processing.

  6. Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

    Science.gov (United States)

    Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

    2017-01-01

    Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

  7. Remote sensing-based characterization of rainfall during atmospheric rivers over the central United States

    Science.gov (United States)

    Nayak, Munir A.; Villarini, Gabriele

    2018-01-01

    Atmospheric rivers (ARs) play a central role in the hydrology and hydroclimatology of the central United States. More than 25% of the annual rainfall is associated with ARs over much of this region, with many large flood events tied to their occurrence. Despite the relevance of these storms for flood hydrology and water budget, the characteristics of rainfall associated with ARs over the central United has not been investigated thus far. This study fills this major scientific gap by describing the rainfall during ARs over the central United States using five remote sensing-based precipitation products over a 12-year study period. The products we consider are: Stage IV, Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH). As part of the study, we evaluate these products against a rain gauge-based dataset using both graphical- and metrics-based diagnostics. Based on our analyses, Stage IV is found to better reproduce the reference data. Hence, we use it for the characterization of rainfall in ARs. Most of the AR-rainfall is located in a narrow region within ∼150 km on both sides of the AR major axis. In this region, rainfall has a pronounced positive relationship with the magnitude of the water vapor transport. Moreover, we have also identified a consistent increase in rainfall intensity with duration (or persistence) of AR conditions. However, there is not a strong indication of diurnal variability in AR rainfall. These results can be directly used in developing flood protection strategies during ARs. Further, weather prediction agencies can benefit from the results of this study to achieve higher skill of resolving precipitation processes in their models.

  8. Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

    Science.gov (United States)

    Elmasri, B.; Rahman, A. F.

    2010-12-01

    Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation

  9. Object-based vegetation classification with high resolution remote sensing imagery

    Science.gov (United States)

    Yu, Qian

    Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions

  10. Fiber sensing based on new structures and post-processing enhancement

    Science.gov (United States)

    Ferreira, Marta Sofia dos Anjos

    The work described in this PhD Thesis focuses on the post-processing of optical fibers and their enhancement as sensing element. Since the majority of sensors presented are based in Fabry-Perot interferometers, an historical overview of this category of optical fiber sensors is firstly presented. This review considers the works published since the early years, in the beginning of the 1980s, until the middle of 2015. The incorporation of microcavities at the tip of a single mode fiber was extensively studied, particularly for the measurement of nitrogen and methane gas pressure. These cavities were fabricated using hollow core silica tubes and a hollow core photonic crystal fiber. Following a different approach, the microcavities were incorporated between two sections of single mode fiber. In this case, the low sensitivity to temperature makes these microcavities highly desirable for the measurement of strain at high temperatures. Competences in post-processing techniques such as the chemical etching and the writing of periodical structures in the fiber core by means of an excimer or a femtosecond laser were also acquired in the course of the PhD programme. One of the works consisted in the design and manufacturing of a double clad optical fiber. The refractive index of the inner cladding was higher than the one of the outer cladding and the core. Thus, light was guided in the inner cladding instead of propagating in the core. This situation was overcome by applying chemical etching, thus removing the inner cladding. The core, surrounded by air, was then able to guide light. Two different applications were found for this fiber, as a temperature sensor and as an optical refractometer. In the last, the optical phase changes with the liquid refractive index. Two different types of fiber Bragg gratings were characterized in strain and temperature. Sensing structures obtained through the phase mask technique at the tip of an optical fiber were subjected to chemical

  11. Prioritization of catchments based on soil erosion using remote sensing and GIS.

    Science.gov (United States)

    Khadse, Gajanan K; Vijay, Ritesh; Labhasetwar, Pawan K

    2015-06-01

    Water and soil are the most essential natural resources for socioeconomic development and sustenance of life. A study of soil and water dynamics at a watershed level facilitates a scientific approach towards their conservation and management. Remote sensing and Geographic Information System are tools that help to plan and manage natural resources on watershed basis. Studies were conducted for the formulation of catchment area treatment plan based on watershed prioritization with soil erosion studies using remote sensing techniques, corroborated with Geographic Information System (GIS), secondary data and ground truth information. Estimation of runoff and sediment yield is necessary in prioritization of catchment for the design of soil conservation structures and for identifying the critical erosion-prone areas of a catchment for implementation of best management plan with limited resources. The Universal Soil Loss Equation, Sediment Yield Determination and silt yield index methods are used for runoff and soil loss estimation for prioritization of the catchments. On the basis of soil erosion classes, the watersheds were grouped into very high, high, moderate and low priorities. High-priority watersheds need immediate attention for soil and water conservation, whereas low-priority watershed having good vegetative cover and low silt yield index may not need immediate attention for such treatments.

  12. Developing upconversion nanoparticle-based smart substrates for remote temperature sensing

    Science.gov (United States)

    Coker, Zachary; Marble, Kassie; Alkahtani, Masfer; Hemmer, Philip; Yakovlev, Vladislav V.

    2018-02-01

    Recent developments in understanding of nanomaterial behaviors and synthesis have led to their application across a wide range of commercial and scientific applications. Recent investigations span from applications in nanomedicine and the development of novel drug delivery systems to nanoelectronics and biosensors. In this study, we propose the application of a newly engineered temperature sensitive water-based bio-compatible core/shell up-conversion nanoparticle (UCNP) in the development of a smart substrate for remote temperature sensing. We developed this smart substrate by dispersing functionalized nanoparticles into a polymer solution and then spin-coating the solution onto one side of a microscope slide to form a thin film substrate layer of evenly dispersed nanoparticles. By using spin-coating to deposit the particle solution we both create a uniform surface for the substrate while simultaneously avoid undesired particle agglomeration. Through this investigation, we have determined the sensitivity and capabilities of this smart substrate and conclude that further development can lead to a greater range of applications for this type smart substrate and use in remote temperature sensing in conjunction with other microscopy and spectroscopy investigations.

  13. Two-dimensional straightness measurement based on optical knife-edge sensing

    Science.gov (United States)

    Wang, Chen; Zhong, Fenghe; Ellis, Jonathan D.

    2017-09-01

    Straightness error is a parasitic translation along a perpendicular direction to the primary displacement axis of a linear stage. The parasitic translations could be coupled into other primary displacement directions of a multi-axis platform. Hence, its measurement and compensation are critical in precision multi-axis metrology, calibration, and manufacturing. This paper presents a two-dimensional (2D) straightness measurement configuration based on 2D optical knife-edge sensing, which is simple, light-weight, compact, and easy to align. It applies a 2D optical knife-edge to manipulate the diffraction pattern sensed by a quadrant photodetector, whose output voltages could derive 2D straightness errors after a calibration process. This paper analyzes the physical model of the configuration and performs simulations and experiments to study the system sensitivity, measurement nonlinearity, and error sources. The results demonstrate that the proposed configuration has higher sensitivity and insensitive to beam's vibration, compared with the conventional configurations without using the knife-edge, and could achieve ±0.25 μ m within a ±40 μ m measurement range along a 40 mm primary axial motion.

  14. Schemes of detecting nuclear spin correlations by dynamical decoupling based quantum sensing

    Science.gov (United States)

    Ma, Wen-Long Ma; Liu, Ren-Bao

    Single-molecule sensitivity of nuclear magnetic resonance (NMR) and angstrom resolution of magnetic resonance imaging (MRI) are the highest challenges in magnetic microscopy. Recent development in dynamical decoupling (DD) enhanced diamond quantum sensing has enabled NMR of single nuclear spins and nanoscale NMR. Similar to conventional NMR and MRI, current DD-based quantum sensing utilizes the frequency fingerprints of target nuclear spins. Such schemes, however, cannot resolve different nuclear spins that have the same noise frequency or differentiate different types of correlations in nuclear spin clusters. Here we show that the first limitation can be overcome by using wavefunction fingerprints of target nuclear spins, which is much more sensitive than the ''frequency fingerprints'' to weak hyperfine interaction between the targets and a sensor, while the second one can be overcome by a new design of two-dimensional DD sequences composed of two sets of periodic DD sequences with different periods, which can be independently set to match two different transition frequencies. Our schemes not only offer an approach to breaking the resolution limit set by ''frequency gradients'' in conventional MRI, but also provide a standard approach to correlation spectroscopy for single-molecule NMR.

  15. Nonenzymatic glucose sensing based on deposited palladium nanoparticles on epoxy-silver electrodes

    International Nuclear Information System (INIS)

    Gutes, Albert; Carraro, Carlo; Maboudian, Roya

    2011-01-01

    Highlights: → New nonenzymatic glucose sensor material. → Modified epoxy-silver electrodes with palladium nanoparticles. → Simple electroless surface modification. → Wide linear response range. → Easy implementation. - Abstract: A new approach for nonenzymatic glucose sensing, based on a simple modification of epoxy-silver surfaces deposited on the tip of commercial copper electric wires, is presented. Palladium was galvanically displaced on the surface of the epoxy-silver surface in order to obtain metal nanoparticles that act as catalyst for the direct oxidation of glucose. Scanning electron microscopy revealed the formation of the metal nanoparticles. X-ray photoelectron spectroscopy confirmed the metallic nature of the formed nanostructures on the surface. Electrochemical characterization and calibration of the palladium-modified epoxy-silver electrode is reported, obtaining a linear range of 1-20 mM for the detection of glucose with low interference of ascorbic acid and uric acid. A simple 3-step coulometry was used as the detection technique. The developed sensing material is believed to be a great candidate for integration in small devices for clinical essays, due to the simplicity and cost effectiveness of the presented approach, compared to the state-of-the-art devices reported recently in the literature. Simplicity in the coulometry determinations makes these Pd-modified epoxy-silver sensors a good candidate for easy glucose determinations.

  16. Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery

    Science.gov (United States)

    Vishnukumar, S.; Wilscy, M.

    2017-12-01

    In this paper, we propose a single image Super-Resolution (SR) method based on Compressive Sensing (CS) and Improved Total Variation (TV) Minimization Sparse Recovery. In the CS framework, low-resolution (LR) image is treated as the compressed version of high-resolution (HR) image. Dictionary Training and Sparse Recovery are the two phases of the method. K-Singular Value Decomposition (K-SVD) method is used for dictionary training and the dictionary represents HR image patches in a sparse manner. Here, only the interpolated version of the LR image is used for training purpose and thereby the structural self similarity inherent in the LR image is exploited. In the sparse recovery phase the sparse representation coefficients with respect to the trained dictionary for LR image patches are derived using Improved TV Minimization method. HR image can be reconstructed by the linear combination of the dictionary and the sparse coefficients. The experimental results show that the proposed method gives better results quantitatively as well as qualitatively on both natural and remote sensing images. The reconstructed images have better visual quality since edges and other sharp details are preserved.

  17. Advances in estimation methods of vegetation water content based on optical remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

  18. Optical scanning holography based on compressive sensing using a digital micro-mirror device

    Science.gov (United States)

    A-qian, Sun; Ding-fu, Zhou; Sheng, Yuan; You-jun, Hu; Peng, Zhang; Jian-ming, Yue; xin, Zhou

    2017-02-01

    Optical scanning holography (OSH) is a distinct digital holography technique, which uses a single two-dimensional (2D) scanning process to record the hologram of a three-dimensional (3D) object. Usually, these 2D scanning processes are in the form of mechanical scanning, and the quality of recorded hologram may be affected due to the limitation of mechanical scanning accuracy and unavoidable vibration of stepper motor's start-stop. In this paper, we propose a new framework, which replaces the 2D mechanical scanning mirrors with a Digital Micro-mirror Device (DMD) to modulate the scanning light field, and we call it OSH based on Compressive Sensing (CS) using a digital micro-mirror device (CS-OSH). CS-OSH can reconstruct the hologram of an object through the use of compressive sensing theory, and then restore the image of object itself. Numerical simulation results confirm this new type OSH can get a reconstructed image with favorable visual quality even under the condition of a low sample rate.

  19. Gadolinium(III) ion selective sensor using a new synthesized Schiff's base as a sensing material

    International Nuclear Information System (INIS)

    Zamani, Hassan Ali; Mohammadhosseini, Majid; Haji-Mohammadrezazadeh, Saeed; Faridbod, Farnoush; Ganjali, Mohammad Reza; Meghdadi, Soraia; Davoodnia, Abolghasem

    2012-01-01

    According to a solution study which showed a selective complexation between N,N′-bis(methylsalicylidene)-2-aminobenzylamine (MSAB) and gadolinium ions, MSAB was used as a sensing element in construction of a gadolinium(III) ion selective electrode. Acetophenon (AP) was used as solvent mediator and sodium tetraphenyl borate (NaTPB) as an anion excluder. The electrode showed a good selectivity towards Gd(III) ions over a wide variety of cations tested. The constructed sensor displayed a Nernstian behavior (19.7 ± 0.3 mV/decade) in the concentration range of 1.0 × 10 −6 to 1.0 × 10 −2 mol L −1 with detection limit of 5.0 × 10 −7 mol L −1 and a short response time ( 3+ –PVC membrane sensor based on an ion carrier as sensing material is introduced. ► This technique is very simple and it's not necessary to use sophisticated equipment. ► This sensor shows good selectivity against other metal ions.

  20. Exploration of genetically encoded voltage indicators based on a chimeric voltage sensing domain

    Directory of Open Access Journals (Sweden)

    Yukiko eMishina

    2014-09-01

    Full Text Available Deciphering how the brain generates cognitive function from patterns of electrical signals is one of the ultimate challenges in neuroscience. To this end, it would be highly desirable to monitor the activities of very large numbers of neurons while an animal engages in complex behaviours. Optical imaging of electrical activity using genetically encoded voltage indicators (GEVIs has the potential to meet this challenge. Currently prevalent GEVIs are based on the voltage-sensitive fluorescent protein (VSFP prototypical design or on the voltage dependent state transitions of microbial opsins.We recently introduced a new VSFP design in which the voltage-sensing domain (VSD is sandwiched between a FRET pair of fluorescent proteins (termed VSFP-Butterflies and also demonstrated a series of chimeric VSD in which portions of the VSD of Ciona intestinalis voltage-sensitive phosphatase (Ci-VSP are substituted by homologous portions of a voltage-gated potassium channel subunit. These chimeric VSD had faster sensing kinetics than that of the native Ci-VSD. Here, we describe a new set of VSFPs that combine chimeric VSD with the Butterfly structure. We show that these chimeric VSFP-Butterflies can report membrane voltage oscillations of up to 200 Hz in cultured cells and report sensory evoked cortical population responses in living mice. This class of GEVIs may be suitable for imaging of brain rhythms in behaving mammalians.

  1. Exploration of genetically encoded voltage indicators based on a chimeric voltage sensing domain.

    Science.gov (United States)

    Mishina, Yukiko; Mutoh, Hiroki; Song, Chenchen; Knöpfel, Thomas

    2014-01-01

    Deciphering how the brain generates cognitive function from patterns of electrical signals is one of the ultimate challenges in neuroscience. To this end, it would be highly desirable to monitor the activities of very large numbers of neurons while an animal engages in complex behaviors. Optical imaging of electrical activity using genetically encoded voltage indicators (GEVIs) has the potential to meet this challenge. Currently prevalent GEVIs are based on the voltage-sensitive fluorescent protein (VSFP) prototypical design or on the voltage-dependent state transitions of microbial opsins. We recently introduced a new VSFP design in which the voltage-sensing domain (VSD) is sandwiched between a fluorescence resonance energy transfer pair of fluorescent proteins (termed VSFP-Butterflies) and also demonstrated a series of chimeric VSD in which portions of the VSD of Ciona intestinalis voltage-sensitive phosphatase are substituted by homologous portions of a voltage-gated potassium channel subunit. These chimeric VSD had faster sensing kinetics than that of the native Ci-VSD. Here, we describe a new set of VSFPs that combine chimeric VSD with the Butterfly structure. We show that these chimeric VSFP-Butterflies can report membrane voltage oscillations of up to 200 Hz in cultured cells and report sensory evoked cortical population responses in living mice. This class of GEVIs may be suitable for imaging of brain rhythms in behaving mammalians.

  2. Graphene-based LbL deposited films: further study of electrical and gas sensing properties

    Directory of Open Access Journals (Sweden)

    Nabok A.

    2017-01-01

    Full Text Available Graphene-surfactant composite materials obtained by the ultrasonic exfoliation of graphite powder in the presence of ionic surfactants (either CTAB or SDS were utilised to construct thin films using layer-by-layer (LbL electrostatic deposition technique. A series of graphene-based thin films were made by alternating layers of either graphene-SDS with polycations (PEI or PAH or graphene-CTAB with polyanions (PSS. Also, graphene-phthalocyanine composite films were produced by alternating layers of graphene-CTAB with tetrasulfonated nickel phthalocyanine. Graphene-surfactant LbL films exhibited good electric conductivity (about 0.1 S/cm of semiconductor type with a band gap of about 20 meV. Judging from UV-vis spectra measurements, graphene-phthalocyanine LbL films appeared to form joint π-electron system. Gas sensing testing of such composite films combining high conductivity of graphene with the gas sensing abilities of phthalocyanines showed substantial changes (up to 10% in electrical conductivity upon exposure to electro-active gases such as HCl and NH3.

  3. Ground-based grasslands data to support remote sensing and ecosystem modeling of terrestrial primary production

    Science.gov (United States)

    Olson, R. J.; Scurlock, J. M. O.; Turner, R. S.; Jennings, S. V.

    1995-01-01

    Estimating terrestrial net primary production (NPP) using remote-sensing tools and ecosystem models requires adequate ground-based measurements for calibration, parameterization, and validation. These data needs were strongly endorsed at a recent meeting of ecosystem modelers organized by the International Geosphere-Biosphere Program's (IGBP's) Data and Information System (DIS) and its Global Analysis, Interpretation, and Modelling (GAIM) Task Force. To meet these needs, a multinational, multiagency project is being coordinated by the IGBP DIS to compile existing NPP data from field sites and to regionalize NPP point estimates to various-sized grid cells. Progress at Oak Ridge National Laboratory (ORNL) on compiling NPP data for grasslands as part of the IGBP DIS data initiative is described. Site data and associated documentation from diverse field studies are being acquired for selected grasslands and are being reviewed for completeness, consistency, and adequacy of documentation, including a description of sampling methods. Data are being compiled in a database with spatial, temporal, and thematic characteristics relevant to remote sensing and global modeling. NPP data are available from the ORNL Distributed Active Archive Center (DAAC) for biogeochemical dynamics. The ORNL DAAC is part of the Earth Observing System Data and Information System, of the US National Aeronautics and Space Administration.

  4. Design and Characterization of a Novel Bio-inspired Hair Flow Sensor Based on Resonant Sensing

    Science.gov (United States)

    Guo, X.; Yang, B.; Wang, Q. H.; Lu, C. F.; Hu, D.

    2018-03-01

    Flow sensors inspired by the natural hair sensing mechanism have great prospect in the research of micro-autonomous system and technology (MAST) for the three-dimensional structure characteristics with high spatial and quality utilization. A novel bio-inspired hair flow sensor (BHFS) based on resonant sensing with a unique asymmetric design is presented in this paper. A hair transducer and a signal detector which is constituted of a two-stage micro-leverage mechanism and two symmetrical resonators (double ended tuning fork, DETF) are adopted to realize the high sensitivity to air flow. The sensitivity of the proposed BHFS is improved significantly than the published ones due to the high sensitivity of resonators and the higher amplification factor possessed by the two-stage micro-leverage mechanism. The standard deep dry silicon on glass (DDSOG) process is chosen to fabricate the proposed BHFS. The experiment result demonstrates that the fabricated BHFS has a mechanical sensitivity of 5.26 Hz/(m/s)2 at a resonant frequency of 22 kHz with the hair height of 6 mm.

  5. Risk assessment of storm surge disaster based on numerical models and remote sensing

    Science.gov (United States)

    Liu, Qingrong; Ruan, Chengqing; Zhong, Shan; Li, Jian; Yin, Zhonghui; Lian, Xihu

    2018-06-01

    Storm surge is one of the most serious ocean disasters in the world. Risk assessment of storm surge disaster for coastal areas has important implications for planning economic development and reducing disaster losses. Based on risk assessment theory, this paper uses coastal hydrological observations, a numerical storm surge model and multi-source remote sensing data, proposes methods for valuing hazard and vulnerability for storm surge and builds a storm surge risk assessment model. Storm surges in different recurrence periods are simulated in numerical models and the flooding areas and depth are calculated, which are used for assessing the hazard of storm surge; remote sensing data and GIS technology are used for extraction of coastal key objects and classification of coastal land use are identified, which is used for vulnerability assessment of storm surge disaster. The storm surge risk assessment model is applied for a typical coastal city, and the result shows the reliability and validity of the risk assessment model. The building and application of storm surge risk assessment model provides some basis reference for the city development plan and strengthens disaster prevention and mitigation.

  6. Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay

    Directory of Open Access Journals (Sweden)

    S. Eman Mahmoodi

    2014-04-01

    Full Text Available In this paper, we investigate the joint spectrum sensing and resource allocation problem to maximize throughput capacity of an OFDM-based cognitive radio link with a cognitive relay. By applying a cognitive relay that uses decode and forward (D&F, we achieve more reliable communications, generating less interference (by needing less transmit power and more diversity gain. In order to account for imperfections in spectrum sensing, the proposed schemes jointly modify energy detector thresholds and allocates transmit powers to all cognitive radio (CR subcarriers, while simultaneously assigning subcarrier pairs for secondary users (SU and the cognitive relay. This problem is cast as a constrained optimization problem with constraints on (1 interference introduced by the SU and the cognitive relay to the PUs; (2 miss-detection and false alarm probabilities and (3 subcarrier pairing for transmission on the SU transmitter and the cognitive relay and (4 minimum Quality of Service (QoS for each CR subcarrier. We propose one optimal and two suboptimal schemes all of which are compared to other schemes in the literature. Simulation results show that the proposed schemes achieve significantly higher throughput than other schemes in the literature for different relay situations.

  7. A new multifunctional 1, 10-phenanthroline based fluorophore for anion and cation sensing

    Energy Technology Data Exchange (ETDEWEB)

    Alreja, Priya; Kaur, Navneet, E-mail: neet_chem@yahoo.co.in

    2015-12-15

    We report a new multi-ion responsive fluorophore 1 possessing an amide functionality featuring with 1, 10-phenanthroline unit with appropriately placed coordination sites for sensing Cu{sup 2+} and Zn{sup 2+} ions in 1:2 stoichiometry. Also, various functionalities of 1 organize to create an appropriate cavity to accommodate weakly basic and larger iodide ion generating 1:1 complex. The fluorescence intensity was greatly quenched on coordination of Cu{sup 2+}, Zn{sup 2+} and I{sup −} ions with appropriately placed multiple donor sites of 1 which was further supported by Density Functional Theory (DFT) computational studies. - Highlights: • A novel multifunctional 1, 10- Phenanthroline based fluorophore for sensing anion and cations. • First report on applicability of amides as multiple users for anion and cations. • Fluorescence quenching observed with Cu{sup 2+}, Zn{sup 2+} and I{sup -}. • Fluorescence titration experiments are well supported by DFT calculations.

  8. Actin-based gravity-sensing mechanisms in unicellular plant model systems

    Science.gov (United States)

    Braun, Markus; Limbach, Christoph

    2005-08-01

    Considerable progress has been made in the understanding of the molecular and cellular mechanisms underlying gravity sensing and gravity-oriented polarized growth in single-celled rhizoids and protonemata of the characean algae. It is well known that the actin cytoskeleton plays a key role in these processes. Numerous actin-binding proteins control apical actin polymerization and the dynamic remodeling of the actin arrangement. An actomyosin-based system mediates the delivery and incorporation of secretory vesicles at the growing tip and coordinates the tip-high gradient of cytoplasmic free calcium which is required for local exocytosis. Additionally, the actomyosin system precisely controls the position of statoliths and, upon a change in orientation relative to the gravity vector, directs sedimenting statoliths to the confined graviperception sites of the plasma membrane where gravitropic signalling is initiated. The upward growth response of protonemata is preceded by an actin-dependent relocalization of the Ca2+-gradient to the upper flank. The downward growth response of rhizoids, however, is caused by differential growth of the opposite flankes due to a local reduction of cytoplasmic free calcium limited to the plasma membrane area where statoliths are sedimented. Thus, constant actin polymerization in the growing tip and the spatiotemporal control of actin remodeling are essential for gravity sensing and gravity-oriented polarized growth of characean rhizoids and protonemata.

  9. Ground-based grasslands data to support remote sensing and ecosystem modeling of terrestrial primary production

    Energy Technology Data Exchange (ETDEWEB)

    Olson, R.J.; Turner, R.S. [Oak Ridge National Lab., TN (United States); Scurlock, J.M.O. [King`s College London, (England); Jennings, S.V. [Tennessee Univ., Knoxville, TN (United States)

    1995-12-31

    Estimating terrestrial net primary production (NPP) using remote- sensing tools and ecosystem models requires adequate ground-based measurements for calibration, parameterization, and validation. These data needs were strongly endorsed at a recent meeting of ecosystem modelers organized by the International Geosphere-Biosphere Programme`s (IGBP`s) Data and Information System (DIS) and its Global Analysis, Interpretation, and Modelling (GAIM) Task Force. To meet these needs, a multinational, multiagency project is being coordinated by the IGBP DIS to compile existing NPP data from field sites and to regionalize NPP point estimates to various-sized grid cells. Progress at Oak Ridge National Laboratory (ORNL) on compiling NPP data for grasslands as part of the IGBP DIS data initiative is described. Site data and associated documentation from diverse field studies are being acquired for selected grasslands and are being reviewed for completeness, consistency, and adequacy of documentation, including a description of sampling methods. Data are being compiled in a database with spatial, temporal, and thematic characteristics relevant to remote sensing and global modeling. NPP data are available from the ORNL Distributed Active Archive Center (DAAC) for biogeochemical dynamics. The ORNL DAAC is part of the Earth Observing System Data and Information System, of the US National Aeronautics and Space Administration.

  10. Real time network traffic monitoring for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    A wireless local area network (WLAN) is an important type of wireless networks which connotes different wireless nodes in a local area network. WLANs suffer from important problems such as network load balancing, large amount of energy, and load of sampling. This paper presents a new networking traffic approach based on Compressed Sensing (CS) for improving the quality of WLANs. The proposed architecture allows reducing Data Delay Probability (DDP) to 15%, which is a good record for WLANs. The proposed architecture is increased Data Throughput (DT) to 22 % and Signal to Noise (S/N) ratio to 17 %, which provide a good background for establishing high qualified local area networks. This architecture enables continuous data acquisition and compression of WLAN's signals that are suitable for a variety of other wireless networking applications. At the transmitter side of each wireless node, an analog-CS framework is applied at the sensing step before analog to digital converter in order to generate the compressed version of the input signal. At the receiver side of wireless node, a reconstruction algorithm is applied in order to reconstruct the original signals from the compressed signals with high probability and enough accuracy. The proposed algorithm out-performs existing algorithms by achieving a good level of Quality of Service (QoS). This ability allows reducing 15 % of Bit Error Rate (BER) at each wireless node.

  11. Remote sensing and monitor system for a large poultry farm based on Internet

    Science.gov (United States)

    Bai, Hongwu; Teng, Guanghui; Ma, Liang; Li, Zhizhong; Yuan, Zhengdong; Li, Minzan; Yang, Xiuslayerg

    2005-09-01

    A remote sensing and monitor system for a large poultry layer farm is developed based on distributed data acquisition and internet control. The supervising system applied patent techniques known as arc orbit movable vidicon, wireless video transmission and telecommunications. It features supervising at all orientations, and digital video telecommunicating through internet. All measured and control information is sent to a central computer, which is in charge of storing, displaying, analyzing and serving to internet, where managers can monitor real time production scene anywhere and customers can also see the healthy layers through internet. This paper primarily discusses how to design the remote sensing and monitor system (RSMS), and its usage in a large poultry farm, Deqingyuan Healthy Breeding Ecological Garden, Yanqing County, Beijing, China. The system applied web service technology and the middleware using XML language and Java language. It preponderated in data management, data exchange, expansibility, security, and compatibility. As a part of poultry sustainable development management system, it has been applied in a large farm with 1,200,000 layers. Tests revealed that there was distinct decline in the death ratio of chicken with 2. 2%, as the surroundings of layers had been ameliorated. At the same time, there was definite increase in the laying ratio with 3. 5%.

  12. Who Benefits From Humor-Based Positive Psychology Interventions? The Moderating Effects of Personality Traits and Sense of Humor.

    Science.gov (United States)

    Wellenzohn, Sara; Proyer, René T; Ruch, Willibald

    2018-01-01

    The evidence for the effectiveness of humor-based positive psychology interventions (PPIs; i.e., interventions aimed at enhancing happiness and lowering depressive symptoms) is steadily increasing. However, little is known about who benefits most from them. We aim at narrowing this gap by examining whether personality traits and sense of humor moderate the long-term effects of humor-based interventions on happiness and depressive symptoms. We conducted two placebo-controlled online-intervention studies testing for moderation effects. In Study 1 ( N = 104) we tested for moderation effects of basic personality traits (i.e., psychoticism, extraversion, and neuroticism) in the three funny things intervention, a humor-based PPI. In Study 2 ( N = 632) we tested for moderation effects of the sense of humor in five different humor-based interventions. Happiness and depressive symptoms were assessed before and after the intervention, as well as after 1, 3, and 6 months. In Study 2, we assessed sense of humor before and 1 month after the intervention to investigate if changes in sense of humor go along with changes in happiness and depressive symptoms. We found moderating effects only for extraversion. Extraverts benefitted more from the three funny things intervention than introverts. For neuroticism and psychoticism no moderation effects were found. For sense of humor, no moderating effects were found for the effectiveness of the five humor-based interventions tested in Study 2. However, changes in sense of humor from pretest to the 1-month follow-up predicted changes in happiness and depressive symptoms. Taking a closer look, the playful attitude- and sense of humor-subscales predicted changes in happiness and depression for up to 6 months. Overall, moderating effects for personality (i.e., extraversion) were found, but none for sense of humor at baseline. However, increases in sense of humor during and after the intervention were associated with the interventions

  13. ELEMENTOS ESTRATÉGICOS DE LA GESTIÓN DEL CONOCIMIENTO ORGANIZACIONAL PARA LA INNOVACIÓN. CASO: RED DE AGROMETEOROLOGÍA / STRATEGIC ELEMENTS OF ORGANIZATIONAL KNOWLEDGE MANAGEMENT FOR IN-NOVATION CASE: AGROMETEOROLOGY NETWORK

    Directory of Open Access Journals (Sweden)

    Barlin Orlando Olivares

    2016-06-01

    Full Text Available RESUMEN: Esta experiencia docente tiene como objetivo proponer un modelo de gestión del conocimiento organizacional para el programa de capacitación desarrollado por el departamento de agrometeorología del Instituto Nacional de Investigaciones Agrícolas (INIA del estado Anzoátegui, Venezuela. Se utilizó el protocolo de solución de problemas, derivado de la aplicación de ciclos de aprendizaje, denominado TADIR (Traducción, Análisis, Diseño, Implementación y Revisión. Se estableció la diversificación de las formas de promover las actividades, tareas, resultados, productos generados por el proyecto, antes, durante y posterior a su ejecución, de manera fácil y completa, así como la conciencia en la población sobre las bondades de la agrometeorológica y su importancia para el desarrollo agrícola del país. Los resultados de esta investigación pueden estar al servicio de la misma organización de manera directa e indirecta y de otras que quieran asumir el reto de contribuir al proceso de transformación que vive la nación. ABSTRACT: This teaching experience seeks to propose an organizational knowledge management model for the training program developed by the Agrometeorology Department of the National Institute for Agricultural Research (INAI, in Spanish of the State of Anzoátegui, Venezuela. The problem solution protocol deriving from the application of learning cycles, TADIR (Translation, Analysis, Design, Implementation and Revision, was used. An array of different ways to promote activities, tasks, results, and products generated by the project was established before, during and after the execution in an easy and complete manner. The population was also made aware of the advantages of agrometeorology and its importance for the agricultural development of the country. The results of this research can be made directly or indirectly available to the same organization or any others who wish to take the challenge of contributing

  14. MetaSensing's FastGBSAR: ground based radar for deformation monitoring

    Science.gov (United States)

    Rödelsperger, Sabine; Meta, Adriano

    2014-10-01

    The continuous monitoring of ground deformation and structural movement has become an important task in engineering. MetaSensing introduces a novel sensor system, the Fast Ground Based Synthetic Aperture Radar (FastGBSAR), based on innovative technologies that have already been successfully applied to airborne SAR applications. The FastGBSAR allows the remote sensing of deformations of a slope or infrastructure from up to a distance of 4 km. The FastGBSAR can be setup in two different configurations: in Real Aperture Radar (RAR) mode it is capable of accurately measuring displacements along a linear range profile, ideal for monitoring vibrations of structures like bridges and towers (displacement accuracy up to 0.01 mm). Modal parameters can be determined within half an hour. Alternatively, in Synthetic Aperture Radar (SAR) configuration it produces two-dimensional displacement images with an acquisition time of less than 5 seconds, ideal for monitoring areal structures like dams, landslides and open pit mines (displacement accuracy up to 0.1 mm). The MetaSensing FastGBSAR is the first ground based SAR instrument on the market able to produce two-dimensional deformation maps with this high acquisition rate. By that, deformation time series with a high temporal and spatial resolution can be generated, giving detailed information useful to determine the deformation mechanisms involved and eventually to predict an incoming failure. The system is fully portable and can be quickly installed on bedrock or a basement. The data acquisition and processing can be fully automated leading to a low effort in instrument operation and maintenance. Due to the short acquisition time of FastGBSAR, the coherence between two acquisitions is very high and the phase unwrapping is simplified enormously. This yields a high density of resolution cells with good quality and high reliability of the acquired deformations. The deformation maps can directly be used as input into an Early

  15. GaSb-based single-mode distributed feedback lasers for sensing (Conference Presentation)

    Science.gov (United States)

    Gupta, James A.; Bezinger, Andrew; Lapointe, Jean; Poitras, Daniel; Aers, Geof C.

    2017-02-01

    GaSb-based tunable single-mode diode lasers can enable rapid, highly-selective and highly-sensitive absorption spectroscopy systems for gas sensing. In this work, single-mode distributed feedback (DFB) laser diodes were developed for the detection of various trace gases in the 2-3.3um range, including CO2, CO, HF, H2S, H2O and CH4. The lasers were fabricated using an index-coupled grating process without epitaxial regrowth, making the process significantly less expensive than conventional DFB fabrication. The devices are based on InGaAsSb/AlGaAsSb separate confinement heterostructures grown on GaSb by molecular beam epitaxy. DFB lasers were produced using a two step etch process. Narrow ridge waveguides were first defined by optical lithography and etched into the semiconductor. Lateral gratings were then defined on both sides of the ridge using electron-beam lithography and etched to produce the index-grating. Effective index modeling was used to optimize the ridge width, etch depths and the grating pitch to ensure single-lateral-mode operation and adequate coupling strength. The effective index method was further used to simulate the DFB laser emission spectrum, based on a transfer matrix model for light transmission through the periodic structure. The fabricated lasers exhibit single-mode operation which is tunable through the absorption features of the various target gases by adjustment of the drive current. In addition to the established open-path sensing applications, these devices have great potential for optoelectronic integrated gas sensors, making use of integrated photodetectors and possibly on-chip Si photonics waveguide structures.

  16. A comparision between satellite based and drone based remote sensing technology to achieve sustainable development: a review

    Directory of Open Access Journals (Sweden)

    Babankumar Bansod

    2017-12-01

    Full Text Available Precision agriculture is a way to manage the crop yield resources like water, fertilizers, soil, seeds in order to increase production, quality, gain and reduce squander products so that the existing system become eco-friendly. The main target of precision agriculture is to match resources and execution according to the crop and climate to ameliorate the effects of Praxis. Global Positioning System, Geographic Information System, Remote sensing technologies and various sensors are used in Precision farming for identifying the variability in field and using different methods to deal with them. Satellite based remote sensing is used to study the variability in crop and ground but suffer from various disadvantageous such as prohibited use, high price, less revisiting them, poor resolution due to great height, Unmanned Aerial Vehicle (UAV is other alternative option for application in precision farming. UAV overcomes the drawback of the ground based system, i.e. inaccessibility to muddy and very dense regions. Hovering at a peak of 500 meter - 1000 meter is good enough to offer various advantageous in image acquisition such as high spatial and temporal resolution, full flexibility, low cost. Recent studies of application of UAV in precision farming indicate advanced designing of UAV, enhancement in georeferencing and the mosaicking of image, analysis and extraction of information required for supplying a true end product to farmers. This paper also discusses the various platforms of UAV used in farming applications, its technical constraints, seclusion rites, reliability and safety.

  17. DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

    Directory of Open Access Journals (Sweden)

    J. Rhee

    2016-06-01

    Full Text Available The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6 and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6. An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

  18. Gas-sensing properties of SnO2-TiO2-based sensor for volatile organic compound gas and its sensing mechanism

    International Nuclear Information System (INIS)

    Zeng Wen; Liu Tianmo

    2010-01-01

    We report the microstructure and gas-sensing properties of the SnO 2 -TiO 2 composite oxide dope with Ag ion prepared by the sol-gel method. Of all various volatile organic compounds (VOCs) such as ethanol, methanol, acetone and formaldehyde were examined, the sensor exhibits remarkable selectivity to each VOCs at different operating temperature. Further investigations based on quantum chemistry calculation show that difference orbital energy of VOCs molecule may be a qualitative factor to affect the selectivity of the sensor.

  19. Ultrafast Capillary Electrophoresis Isolation of DNA Aptamer for the PCR Amplification-Based Small Analyte Sensing

    Directory of Open Access Journals (Sweden)

    Emmanuelle eFiore

    2015-08-01

    Full Text Available Here, we report a new homogeneous DNA amplification-based aptamer assay for small analyte sensing. The aptamer of adenosine chosen as the model analyte was split into two fragments able to assemble in the presence of target. Primers were introduced at extremities of one fragment in order to generate the amplifiable DNA component. The amount of amplifiable fragment was quantifiable by Real-Time Polymerase Chain Reaction (RT-PCR amplification and directly reliable on adenosine concentration. This approach combines the very high separation efficiency and the homogeneous format (without immobilization of capillary electrophoresis and the sensitivity of real time PCR amplification. An ultrafast isolation of target-bound split aptamer (60 s was developed by designing a capillary electrophoresis input/ouput scheme. Such method was successfully applied to the determination of adenosine with a LOD of 1 µM.

  20. Pressure distribution-based texture sensing by using a simple artificial mastication system.

    Science.gov (United States)

    Yamamoto, Takeshi; Higashimori, Mitsuru; Nakauma, Makoto; Nakao, Satomi; Ikegami, Akira; Ishihara, Sayaka

    2014-01-01

    This paper proposes a novel texture sensing method for nursing-care gel by using an artificial mastication system, in which not only mechanical characteristics but also geometrical ones are objectively and quantitatively evaluated. When human masticates gel food, she or he perceives the changes of the shape and contact force simultaneously. Based on the impressions, they evaluate the texture. For reproducing such a procedure, the pressure distribution of gel is measured in the simple artificial mastication, and the information associated to both the geometrical and mechanical characteristics is simultaneously acquired. The relationship between the value of sensory evaluation (i.e. impression human perceives), and the pressure distribution data is numerically modeled by applying the image texture analysis. Experimental results show that the proposed method succeeds in estimating the values of sensory evaluation of nine kinds of gel with the coefficient of determination greater than 0.93.

  1. Development of Laser Based Remote Sensing System for Inner-Concrete Defects

    Science.gov (United States)

    Shimada, Yoshinori; Kotyaev, Oleg

    Laser-based remote sensing using a vibration detection system has been developed using a photorefractive crystal to reduce the effect of concrete surface-roughness. An electric field was applied to the crystal and the reference beam was phase shifted to increase the detection efficiency (DE). The DE increased by factor of 8.5 times compared to that when no voltage and no phase shifting were applied. Vibration from concrete defects can be detected at a distance of 5 m from the system. A vibration-canceling system has also developed that appears to be promising for canceling vibrations between the laser system and the concrete. Finally, we have constructed a prototype system that can be transported in a small truck.

  2. Magnetic Field Sensors Based on Giant Magnetoresistance (GMR Technology: Applications in Electrical Current Sensing

    Directory of Open Access Journals (Sweden)

    Càndid Reig

    2009-10-01

    Full Text Available The 2007 Nobel Prize in Physics can be understood as a global recognition to the rapid development of the Giant Magnetoresistance (GMR, from both the physics and engineering points of view. Behind the utilization of GMR structures as read heads for massive storage magnetic hard disks, important applications as solid state magnetic sensors have emerged. Low cost, compatibility with standard CMOS technologies and high sensitivity are common advantages of these sensors. This way, they have been successfully applied in a lot different environments. In this work, we are trying to collect the Spanish contributions to the progress of the research related to the GMR based sensors covering, among other subjects, the applications, the sensor design, the modelling and the electronic interfaces, focusing on electrical current sensing applications.

  3. Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

    Science.gov (United States)

    Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

    2018-04-01

    In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

  4. Backtracking-Based Iterative Regularization Method for Image Compressive Sensing Recovery

    Directory of Open Access Journals (Sweden)

    Lingjun Liu

    2017-01-01

    Full Text Available This paper presents a variant of the iterative shrinkage-thresholding (IST algorithm, called backtracking-based adaptive IST (BAIST, for image compressive sensing (CS reconstruction. For increasing iterations, IST usually yields a smoothing of the solution and runs into prematurity. To add back more details, the BAIST method backtracks to the previous noisy image using L2 norm minimization, i.e., minimizing the Euclidean distance between the current solution and the previous ones. Through this modification, the BAIST method achieves superior performance while maintaining the low complexity of IST-type methods. Also, BAIST takes a nonlocal regularization with an adaptive regularizor to automatically detect the sparsity level of an image. Experimental results show that our algorithm outperforms the original IST method and several excellent CS techniques.

  5. Acridine-based fluorescence chemosensors for selective sensing of Fe3+ and Ni2+ ions

    Science.gov (United States)

    Wang, Chaoyu; Fu, Jiaxin; Yao, Kun; Xue, Kun; Xu, Kuoxi; Pang, Xiaobin

    2018-06-01

    Two novel acridine-based fluorescence chemosensors (L1 and L2) were prepared and their metal ions sensing properties were investigated. L1 (L2) exhibited an excellent selective fluorescence response toward Fe3+ (Ni2+) and the stoichiometry ratio of L1-Fe3+ and L2-Ni2+ were 1:1. The detection limits of L1 and L2 were calculated by the fluorescence titration to be 4.13 μM and 1.52 μM, respectively, which were below the maximum permissive level of Fe3+ and Ni2+ ions in drinking water set by the EPA. The possible mechanism of the fluorescence detection of Fe3+ and Ni2+ had been proposed according to the analysis of Job's plot, IR spectra and ESI-MS. The determination of Fe3+ and Ni2+ ions in living cells had been applied successfully.

  6. A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

    Energy Technology Data Exchange (ETDEWEB)

    Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch [University of Applied Sciences and Arts Northwestern Switzerland FHNW, 5210 Windisch (Switzerland)

    2017-11-01

    One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

  7. A Safety Enhancement Broadcasting Scheme Based on Context Sensing in VANETs

    Directory of Open Access Journals (Sweden)

    Chen Chen

    2016-01-01

    Full Text Available The broadcasting plays a vital role for context awareness in VANETs (Vehicular Ad Hoc Networks whose primary goal is to improve the driving safety depending on effective information exchanging. In this paper, based on the LQG (linear quadratic Gaussian optimal control theory, a broadcasting control scheme named LQG-CCA is proposed to improve the network throughput thus increasing the opportunities for the safety-related events to be successfully handled. By predicting the network throughput with the Kalman filter model, our LQG model is envisioned to minimize the difference between the predicted and expected throughput through the adjustment of CCA (Clear Channel Assessment sensing threshold. Numerical results show that our proposed model can significantly improve the network performance in terms of average throughput, average End-to-End delay, and average packets delivery ratio compared with a highly cited work D-FPAV and a latest published model APPR.

  8. A robust anomaly based change detection method for time-series remote sensing images

    Science.gov (United States)

    Shoujing, Yin; Qiao, Wang; Chuanqing, Wu; Xiaoling, Chen; Wandong, Ma; Huiqin, Mao

    2014-03-01

    Time-series remote sensing images record changes happening on the earth surface, which include not only abnormal changes like human activities and emergencies (e.g. fire, drought, insect pest etc.), but also changes caused by vegetation phenology and climate changes. Yet, challenges occur in analyzing global environment changes and even the internal forces. This paper proposes a robust Anomaly Based Change Detection method (ABCD) for time-series images analysis by detecting abnormal points in data sets, which do not need to follow a normal distribution. With ABCD we can detect when and where changes occur, which is the prerequisite condition of global change studies. ABCD was tested initially with 10-day SPOT VGT NDVI (Normalized Difference Vegetation Index) times series tracking land cover type changes, seasonality and noise, then validated to real data in a large area in Jiangxi, south of China. Initial results show that ABCD can precisely detect spatial and temporal changes from long time series images rapidly.

  9. Curcumin based optical sensing of fluoride in organo-aqueous media using irradiation technique

    Science.gov (United States)

    Venkataraj, Roopa; Radhakrishnan, P.; Kailasnath, M.

    2017-06-01

    The present work describes the degradation of natural dye Curcumin in organic-aqueous media upon irradiation by a multi-wavelength source of light like mercury lamp. The presence of anions in the solution leads to degradation of Curcumin and this degradation is especially enhanced in the case of fluoride ion. The degradation of Curcumin is investigated by studying the change in its absorption and fluorescence characteristics in organoaqueous solution upon irradiation. A broad detection range of fluoride ranging from 2.3×10-6-2.22×10-3 M points to the potential of the method of visible light irradiation enabling aqueous based sensing of fluoride using Curcumin.

  10. Numerical tilting compensation in microscopy based on wavefront sensing using transport of intensity equation method

    Science.gov (United States)

    Hu, Junbao; Meng, Xin; Wei, Qi; Kong, Yan; Jiang, Zhilong; Xue, Liang; Liu, Fei; Liu, Cheng; Wang, Shouyu

    2018-03-01

    Wide-field microscopy is commonly used for sample observations in biological research and medical diagnosis. However, the tilting error induced by the oblique location of the image recorder or the sample, as well as the inclination of the optical path often deteriorates the imaging quality. In order to eliminate the tilting in microscopy, a numerical tilting compensation technique based on wavefront sensing using transport of intensity equation method is proposed in this paper. Both the provided numerical simulations and practical experiments prove that the proposed technique not only accurately determines the tilting angle with simple setup and procedures, but also compensates the tilting error for imaging quality improvement even in the large tilting cases. Considering its simple systems and operations, as well as image quality improvement capability, it is believed the proposed method can be applied for tilting compensation in the optical microscopy.

  11. Surface plasmon resonance based sensing of different chemical and biological samples using admittance loci method

    Science.gov (United States)

    Brahmachari, Kaushik; Ghosh, Sharmila; Ray, Mina

    2013-06-01

    The admittance loci method plays an important role in the design of multilayer thin film structures. In this paper, admittance loci method has been explored theoretically for sensing of various chemical and biological samples based on surface plasmon resonance (SPR) phenomenon. A dielectric multilayer structure consisting of a Boro silicate glass (BSG) substrate, calcium fluoride (CaF2) and zirconium dioxide (ZrO2) along with different dielectric layers has been investigated. Moreover, admittance loci as well as SPR curves of metal-dielectric multilayer structure consisting of the BSG substrate, gold metal film and various dielectric samples has been simulated in MATLAB environment. To validate the proposed simulation results, calibration curves have also been provided.

  12. A DVD-ROM based high-throughput cantilever sensing platform

    DEFF Research Database (Denmark)

    Bosco, Filippo

    and October 2011. The project was part of the Xsense research network, funded by the Strategic Danish Research Council, and supervised by Prof. Anja Boisen. The goal of the Xsense project is to design and fabricate a compact and cheap device for explosive sensing in air and liquid. Four different technologies...... of a high-throughput label-free sensor platform utilizing cantilever based sensors. These sensors have often been acclaimed to facilitate highly parallelized operation. Unfortunately, so far no concept has been presented which offers large data sets as well as easy liquid sample handling. We use optics...... and mechanics from a DVD player to handle liquid samples and to read-out cantilever deflection and resonant frequency. In a few minutes, several liquid samples can be analyzed in parallel, measuring over several hundreds of individual cantilevers. Three generations of systems have been developed and tested...

  13. A computationally efficient OMP-based compressed sensing reconstruction for dynamic MRI

    International Nuclear Information System (INIS)

    Usman, M; Prieto, C; Schaeffter, T; Batchelor, P G; Odille, F; Atkinson, D

    2011-01-01

    Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved. (note)

  14. A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

    Science.gov (United States)

    Felix, Simon; Bolzern, Roman; Battaglia, Marina

    2017-11-01

    One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

  15. A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus

    Science.gov (United States)

    Mohammadi, Jafar; Limmer, Steffen; Stańczak, Sławomir

    2016-07-01

    This paper considers eigenvalue estimation for the decentralized inference problem for spectrum sensing. We propose a decentralized eigenvalue computation algorithm based on the power method, which is referred to as generalized power method GPM; it is capable of estimating the eigenvalues of a given covariance matrix under certain conditions. Furthermore, we have developed a decentralized implementation of GPM by splitting the iterative operations into local and global computation tasks. The global tasks require data exchange to be performed among the nodes. For this task, we apply an average consensus algorithm to efficiently perform the global computations. As a special case, we consider a structured graph that is a tree with clusters of nodes at its leaves. For an accelerated distributed implementation, we propose to use computation over multiple access channel (CoMAC) as a building block of the algorithm. Numerical simulations are provided to illustrate the performance of the two algorithms.

  16. Block-Based Compressed Sensing for Neutron Radiation Image Using WDFB

    Directory of Open Access Journals (Sweden)

    Wei Jin

    2015-01-01

    Full Text Available An ideal compression method for neutron radiation image should have high compression ratio while keeping more details of the original image. Compressed sensing (CS, which can break through the restrictions of sampling theorem, is likely to offer an efficient compression scheme for the neutron radiation image. Combining wavelet transform with directional filter banks, a novel nonredundant multiscale geometry analysis transform named Wavelet Directional Filter Banks (WDFB is constructed and applied to represent neutron radiation image sparsely. Then, the block-based CS technique is introduced and a high performance CS scheme for neutron radiation image is proposed. By performing two-step iterative shrinkage algorithm the problem of L1 norm minimization is solved to reconstruct neutron radiation image from random measurements. The experiment results demonstrate that the scheme not only improves the quality of reconstructed image obviously but also retains more details of original image.

  17. Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

    Science.gov (United States)

    Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

    2012-12-01

    The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some

  18. Ultra-low power hydrogen sensing based on a palladium-coated nanomechanical beam resonator

    DEFF Research Database (Denmark)

    Henriksson, Jonas; Villanueva Torrijo, Luis Guillermo; Brugger, Juergen

    2012-01-01

    Hydrogen sensing is essential to ensure safety in near-future zero-emission fuel cell powered vehicles. Here, we present a novel hydrogen sensor based on the resonant frequency change of a nanoelectromechanical clamped-clamped beam. The beam is coated with a Pd layer, which expands in the presence...... of H 2, therefore generating a stress build-up that causes the frequency of the device to drop. The devices are able to detect H2 concentrations below 0.5% within 1 s of the onset of the exposure using only a few hundreds of pW of power, matching the industry requirements for H 2 safety sensors......, whereby the responsivity of the sensors is fully restored and the chemo-mechanical process is accelerated, significantly decreasing response times. The sensors are fabricated using standard processes, facilitating their eventual mass-production. © 2012 The Royal Society of Chemistry....

  19. Automatic registration of remote sensing images based on SIFT and fuzzy block matching for change detection

    Directory of Open Access Journals (Sweden)

    Cai Guo-Rong

    2011-10-01

    Full Text Available This paper presents an automated image registration approach to detecting changes in multi-temporal remote sensing images. The proposed algorithm is based on the scale invariant feature transform (SIFT and has two phases. The first phase focuses on SIFT feature extraction and on estimation of image transformation. In the second phase, Structured Local Binary Haar Pattern (SLBHP combined with a fuzzy similarity measure is then used to build a new and effective block similarity measure for change detection. Experimental results obtained on multi-temporal data sets show that compared with three mainstream block matching algorithms, the proposed algorithm is more effective in dealing with scale, rotation and illumination changes.

  20. Ship detection in optical remote sensing images based on deep convolutional neural networks

    Science.gov (United States)

    Yao, Yuan; Jiang, Zhiguo; Zhang, Haopeng; Zhao, Danpei; Cai, Bowen

    2017-10-01

    Automatic ship detection in optical remote sensing images has attracted wide attention for its broad applications. Major challenges for this task include the interference of cloud, wave, wake, and the high computational expenses. We propose a fast and robust ship detection algorithm to solve these issues. The framework for ship detection is designed based on deep convolutional neural networks (CNNs), which provide the accurate locations of ship targets in an efficient way. First, the deep CNN is designed to extract features. Then, a region proposal network (RPN) is applied to discriminate ship targets and regress the detection bounding boxes, in which the anchors are designed by intrinsic shape of ship targets. Experimental results on numerous panchromatic images demonstrate that, in comparison with other state-of-the-art ship detection methods, our method is more efficient and achieves higher detection accuracy and more precise bounding boxes in different complex backgrounds.

  1. Development of a Remote-Sensing Based Framework for Mapping Drought over North America

    Science.gov (United States)

    Hain, C.; Anderson, M. C.; Zhan, X.; Gao, F.; Svoboda, M.; Wardlow, B.; Mladenova, I. E.

    2012-12-01

    This presentation will address the development of a multi-scale drought monitoring tool for North America based on remotely sensed estimates of evapotranspiration. The North American continent represents a broad range in vegetation and climate conditions, from the boreal forests in Canada to the arid deserts in Mexico. This domain also encompasses a range in constraints limiting vegetation growth, with a gradient from radiation/energy limitation in the north to moisture limits in the south. This feasibility study over NA will provide a valuable test bed for future implementation world-wide in support of proposed global drought monitoring and early warning efforts. The Evaporative Stress Index (ESI) represents anomalies in the ratio of actual-to-potential ET (fPET), generated with the thermal remote sensing based Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance model and associated disaggregation algorithm, DisALEXI demonstrated that ESI maps over the continental US (CONUS) show good correspondence with standard drought metrics and with patterns of antecedent precipitation, but can be generated at significantly higher spatial resolution due to a limited reliance on ground observations. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall, for example in areas where drought impacts are being mitigated by intense irrigation or shallow water tables. As such, the ESI is a measure of actual stress rather than potential for stress, and has physical relevance to projected crop development. Because precipitation is not used in construction of the ESI, this index provides an independent assessment of drought conditions and will have particular utility for real-time monitoring in regions with sparse rainfall data or significant delays in meteorological reporting. The North American ESI product will be quantitatively compared with spatiotemporal patterns in the NADM, and with

  2. Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification

    Directory of Open Access Journals (Sweden)

    Xiaoyang Zhao

    2018-04-01

    Full Text Available In recent years, digital frame cameras have been increasingly used for remote sensing applications. However, it is always a challenge to align or register images captured with different cameras or different imaging sensor units. In this research, a novel registration method was proposed. Coarse registration was first applied to approximately align the sensed and reference images. Window selection was then used to reduce the search space and a histogram specification was applied to optimize the grayscale similarity between the images. After comparisons with other commonly-used detectors, the fast corner detector, FAST (Features from Accelerated Segment Test, was selected to extract the feature points. The matching point pairs were then detected between the images, the outliers were eliminated, and geometric transformation was performed. The appropriate window size was searched and set to one-tenth of the image width. The images that were acquired by a two-camera system, a camera with five imaging sensors, and a camera with replaceable filters mounted on a manned aircraft, an unmanned aerial vehicle, and a ground-based platform, respectively, were used to evaluate the performance of the proposed method. The image analysis results showed that, through the appropriate window selection and histogram specification, the number of correctly matched point pairs had increased by 11.30 times, and that the correct matching rate had increased by 36%, compared with the results based on FAST alone. The root mean square error (RMSE in the x and y directions was generally within 0.5 pixels. In comparison with the binary robust invariant scalable keypoints (BRISK, curvature scale space (CSS, Harris, speed up robust features (SURF, and commercial software ERDAS and ENVI, this method resulted in larger numbers of correct matching pairs and smaller, more consistent RMSE. Furthermore, it was not necessary to choose any tie control points manually before registration

  3. [Object-oriented stand type classification based on the combination of multi-source remote sen-sing data].

    Science.gov (United States)

    Mao, Xue Gang; Wei, Jing Yu

    2017-11-01

    The recognition of forest type is one of the key problems in forest resource monitoring. The Radarsat-2 data and QuickBird remote sensing image were used for object-based classification to study the object-based forest type classification and recognition based on the combination of multi-source remote sensing data. In the process of object-based classification, three segmentation schemes (segmentation with QuickBird remote sensing image only, segmentation with Radarsat-2 data only, segmentation with combination of QuickBird and Radarsat-2) were adopted. For the three segmentation schemes, ten segmentation scale parameters were adopted (25-250, step 25), and modified Euclidean distance 3 index was further used to evaluate the segmented results to determine the optimal segmentation scheme and segmentation scale. Based on the optimal segmented result, three forest types of Chinese fir, Masson pine and broad-leaved forest were classified and recognized using Support Vector Machine (SVM) classifier with Radial Basis Foundation (RBF) kernel according to different feature combinations of topography, height, spectrum and common features. The results showed that the combination of Radarsat-2 data and QuickBird remote sensing image had its advantages of object-based forest type classification over using Radarsat-2 data or QuickBird remote sensing image only. The optimal scale parameter for QuickBirdRadarsat-2 segmentation was 100, and at the optimal scale, the accuracy of object-based forest type classification was the highest (OA=86%, Kappa=0.86), when using all features which were extracted from two kinds of data resources. This study could not only provide a reference for forest type recognition using multi-source remote sensing data, but also had a practical significance for forest resource investigation and monitoring.

  4. Curvelet-based compressive sensing for InSAR raw data

    Science.gov (United States)

    Costa, Marcello G.; da Silva Pinho, Marcelo; Fernandes, David

    2015-10-01

    The aim of this work is to evaluate the compression performance of SAR raw data for interferometry applications collected by airborne from BRADAR (Brazilian SAR System operating in X and P bands) using the new approach based on compressive sensing (CS) to achieve an effective recovery with a good phase preserving. For this framework is desirable a real-time capability, where the collected data can be compressed to reduce onboard storage and bandwidth required for transmission. In the CS theory, a sparse unknown signals can be recovered from a small number of random or pseudo-random measurements by sparsity-promoting nonlinear recovery algorithms. Therefore, the original signal can be significantly reduced. To achieve the sparse representation of SAR signal, was done a curvelet transform. The curvelets constitute a directional frame, which allows an optimal sparse representation of objects with discontinuities along smooth curves as observed in raw data and provides an advanced denoising optimization. For the tests were made available a scene of 8192 x 2048 samples in range and azimuth in X-band with 2 m of resolution. The sparse representation was compressed using low dimension measurements matrices in each curvelet subband. Thus, an iterative CS reconstruction method based on IST (iterative soft/shrinkage threshold) was adjusted to recover the curvelets coefficients and then the original signal. To evaluate the compression performance were computed the compression ratio (CR), signal to noise ratio (SNR), and because the interferometry applications require more reconstruction accuracy the phase parameters like the standard deviation of the phase (PSD) and the mean phase error (MPE) were also computed. Moreover, in the image domain, a single-look complex image was generated to evaluate the compression effects. All results were computed in terms of sparsity analysis to provides an efficient compression and quality recovering appropriated for inSAR applications

  5. Estimating Evapotranspiration of an Apple Orchard Using a Remote Sensing-Based Soil Water Balance

    Directory of Open Access Journals (Sweden)

    Magali Odi-Lara

    2016-03-01

    Full Text Available The main goal of this research was to estimate the actual evapotranspiration (ETc of a drip-irrigated apple orchard located in the semi-arid region of Talca Valley (Chile using a remote sensing-based soil water balance model. The methodology to estimate ETc is a modified version of the Food and Agriculture Organization of the United Nations (FAO dual crop coefficient approach, in which the basal crop coefficient (Kcb was derived from the soil adjusted vegetation index (SAVI calculated from satellite images and incorporated into a daily soil water balance in the root zone. A linear relationship between the Kcb and SAVI was developed for the apple orchard Kcb = 1.82·SAVI − 0.07 (R2 = 0.95. The methodology was applied during two growing seasons (2010–2011 and 2012–2013, and ETc was evaluated using latent heat fluxes (LE from an eddy covariance system. The results indicate that the remote sensing-based soil water balance estimated ETc reasonably well over two growing seasons. The root mean square error (RMSE between the measured and simulated ETc values during 2010–2011 and 2012–2013 were, respectively, 0.78 and 0.74 mm·day−1, which mean a relative error of 25%. The index of agreement (d values were, respectively, 0.73 and 0.90. In addition, the weekly ETc showed better agreement. The proposed methodology could be considered as a useful tool for scheduling irrigation and driving the estimation of water requirements over large areas for apple orchards.

  6. Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

    Directory of Open Access Journals (Sweden)

    Guijun Yang

    2017-06-01

    Full Text Available Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI, chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

  7. IDENTIFICATION OF THE main HONEY CROPS BASED on remote sensing data

    Directory of Open Access Journals (Sweden)

    A. Moskalenko

    2017-05-01

    Full Text Available Possibilities of bee forage identification and mapping based on multispectral images Landsat 8 have been shown in the research. The satellite images can be used to determine areas of crops that are resource for nectar and pollen such as sunflower, buckwheat and corn. Identifying bee forages was based on methods of supervised classification such as minimum distance to means, the linear discriminant analysis, the maximum likelihood, the parallelepiped and the k-nearest neighbors. The accuracy of classification methods of remote sensing data for identification of pollen and nectars cultures was compared. The method of maximum likelihood showed the best results for buckwheat and good one for corn and sunflower fields by 13/07/2016. Also this method showed good result for corn and sunflower fields, and poor result for identification of buckwheat fields by 29/07/2016. The stage of flowering plants is the most important period of cropgrowth phase for beekeeping because it is the periodof formation of pollen and nectar. Therefore identification of bee forage has been analyzed vegetation period from germination to flowering. Images of Landsat 8 (sensor OLI by 26/05/2016, 27/06/2016, 13/07/2016 and 29/07/2016 have been used in the research. The optimum period of remote sensing data for identification agricultural crops of bee forage has been determined. Buckwheat fields can be identified more effective in mid-July. Corn fields can be determined at the end of July. Sunflowers can be identified well as before flowering as during flowering.

  8. Proposal for a remote sensing trophic state index based upon Thematic Mapper/Landsat images

    Directory of Open Access Journals (Sweden)

    Evlyn Márcia Leão de Moraes Novo

    2013-12-01

    Full Text Available This work proposes a trophic state index based on the remote sensing retrieval of chlorophyll-α concentration. For that, in situ Bidirectional Reflectance Factor (BRF data acquired in the Ibitinga reservoir were resampled to match Landsat/TM spectral simulated bands (TM_sim bands and used to run linear correlation with concurrent measurements of chlorophyll-α concentration. Monte Carlo simulation was then applied to select the most suitable model relating chlorophyll-α concentration and simulated TM/Landsat reflectance. TM4_sim/TM3_sim ratio provided the best model with a R2 value of 0.78. The model was then inverted to create a look-up-table (LUT relating TM4_sim/TM3_sim ratio intervals to chlorophyll-α concentration trophic state classes covering the entire range measured in the reservoir. Atmospheric corrected Landsat TM images converted to surface reflectance were then used to generate a TM4/TM3 ratio image. The ratio image frequency distribution encompassed the range of TM4_sim/TM3_sim ratio indicating agreement between in situ and satellite data and supporting the use of satellite data to map chlorophyll- concentration trophic state distribution in the reservoir. Based on that, the LUT was applied to a Landsat/TM ratio image to map the spatial distribution of chlorophyll- trophic state classes in Ibitinga reservoir. Despite the stochastic selection of TM4_sim/TM3_sim ratio as the best input variable for modeling the chlorophyll-α concentration, it has a physical basis: high concentration of phytoplankton increases the reflectance in the near-infrared (TM4 and decreases the reflectance in the red (TM3. The band ratio, therefore, enhances the relationship between chlorophyll- concentration and remotely sensed reflectance.

  9. Developing the remote sensing-based early warning system for monitoring TSS concentrations in Lake Mead.

    Science.gov (United States)

    Imen, Sanaz; Chang, Ni-Bin; Yang, Y Jeffrey

    2015-09-01

    Adjustment of the water treatment process to changes in water quality is a focus area for engineers and managers of water treatment plants. The desired and preferred capability depends on timely and quantitative knowledge of water quality monitoring in terms of total suspended solids (TSS) concentrations. This paper presents the development of a suite of nowcasting and forecasting methods by using high-resolution remote-sensing-based monitoring techniques on a daily basis. First, the integrated data fusion and mining (IDFM) technique was applied to develop a near real-time monitoring system for daily nowcasting of the TSS concentrations. Then a nonlinear autoregressive neural network with external input (NARXNET) model was selected and applied for forecasting analysis of the changes in TSS concentrations over time on a rolling basis onward using the IDFM technique. The implementation of such an integrated forecasting and nowcasting approach was assessed by a case study at Lake Mead hosting the water intake for Las Vegas, Nevada, in the water-stressed western U.S. Long-term monthly averaged results showed no simultaneous impact from forest fire events on accelerating the rise of TSS concentration. However, the results showed a probable impact of a decade of drought on increasing TSS concentration in the Colorado River Arm and Overton Arm. Results of the forecasting model highlight the reservoir water level as a significant parameter in predicting TSS in Lake Mead. In addition, the R-squared value of 0.98 and the root mean square error of 0.5 between the observed and predicted TSS values demonstrates the reliability and application potential of this remote sensing-based early warning system in terms of TSS projections at a drinking water intake. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. REMOTE-SENSING-BASED BIOPHYSICAL MODELS FOR ESTIMATING LAI OF IRRIGATED CROPS IN MURRY DARLING BASIN

    Directory of Open Access Journals (Sweden)

    I. Wittamperuma

    2012-07-01

    Full Text Available Remote sensing is a rapid and reliable method for estimating crop growth data from individual plant to crops in irrigated agriculture ecosystem. The LAI is one of the important biophysical parameter for determining vegetation health, biomass, photosynthesis and evapotranspiration (ET for the modelling of crop yield and water productivity. Ground measurement of this parameter is tedious and time-consuming due to heterogeneity across the landscape over time and space. This study deals with the development of remote-sensing based empirical relationships for the estimation of ground-based LAI (LAIG using NDVI, modelled with and without atmospheric correction models for three irrigated crops (corn, wheat and rice grown in irrigated farms within Coleambally Irrigation Area (CIA which is located in southern Murray Darling basin, NSW in Australia. Extensive ground truthing campaigns were carried out to measure crop growth and to collect field samples of LAI using LAI- 2000 Plant Canopy Analyser and reflectance using CROPSCAN Multi Spectral Radiometer at several farms within the CIA. A Set of 12 cloud free Landsat 5 TM satellite images for the period of 2010-11 were downloaded and regression analysis was carried out to analyse the co-relationships between satellite and ground measured reflectance and to check the reliability of data sets for the crops. Among all the developed regression relationships between LAI and NDVI, the atmospheric correction process has significantly improved the relationship between LAI and NDVI for Landsat 5 TM images. The regression analysis also shows strong correlations for corn and wheat but weak correlations for rice which is currently being investigated.

  11. Piezoresistive strain sensing of carbon nanotubes-based composite skin for aeronautical morphing structures

    Science.gov (United States)

    Viscardi, Massimo; Arena, Maurizio; Barra, Giuseppina; Vertuccio, Luigi; Ciminello, Monica; Guadagno, Liberata

    2018-03-01

    Nowadays, smart composites based on different nano-scale carbon fillers, such as carbon nanotubes (CNTs), are increasingly being thought of as a more possible alternative solution to conventional smart materials, mainly for their improved electrical properties. Great attention is being given by the research community in designing highly sensitive strain sensors for more and more ambitious challenges: in such context, interest fields related to carbon nanotubes have seen extraordinary development in recent years. The authors aim to provide the most contemporary overview possible of carbon nanotube-based strain sensors for aeronautical application. A smart structure as a morphing wing needs an embedded sensing system in order to measure the actual deformation state as well as to "monitor" the structural conditions. Looking at more innovative health monitoring tools for the next generation of composite structures, a resin strain sensor has been realized. The epoxy resin was first analysed by means of a micro-tension test, estimating the electrical resistance variations as function of the load, in order to demonstrate the feasibility of the sensor. The epoxy dogbone specimen has been equipped with a standard strain gauge to quantify its strain sensitivity. The voltamperometric tests highlight a good linearity of the electrical resistance value as the load increases at least in the region of elastic deformation of the material. Such intrinsic piezoresistive performance is essentially attributable to the re-arrangement of conductive percolating network formed by MWCNT, induced by the deformation of the material due to the applied loads. The specimen has been prepared within this investigation, to demonstrate its performance for a future composite laminate typical of aerospace structures. The future carbon-fiber sensor can replace conventional metal foil strain gauges in aerospace applications. Furthermore, dynamic tests will be carried out to detect any non

  12. Effective Sequential Classifier Training for SVM-Based Multitemporal Remote Sensing Image Classification

    Science.gov (United States)

    Guo, Yiqing; Jia, Xiuping; Paull, David

    2018-06-01

    The explosive availability of remote sensing images has challenged supervised classification algorithms such as Support Vector Machines (SVM), as training samples tend to be highly limited due to the expensive and laborious task of ground truthing. The temporal correlation and spectral similarity between multitemporal images have opened up an opportunity to alleviate this problem. In this study, a SVM-based Sequential Classifier Training (SCT-SVM) approach is proposed for multitemporal remote sensing image classification. The approach leverages the classifiers of previous images to reduce the required number of training samples for the classifier training of an incoming image. For each incoming image, a rough classifier is firstly predicted based on the temporal trend of a set of previous classifiers. The predicted classifier is then fine-tuned into a more accurate position with current training samples. This approach can be applied progressively to sequential image data, with only a small number of training samples being required from each image. Experiments were conducted with Sentinel-2A multitemporal data over an agricultural area in Australia. Results showed that the proposed SCT-SVM achieved better classification accuracies compared with two state-of-the-art model transfer algorithms. When training data are insufficient, the overall classification accuracy of the incoming image was improved from 76.18% to 94.02% with the proposed SCT-SVM, compared with those obtained without the assistance from previous images. These results demonstrate that the leverage of a priori information from previous images can provide advantageous assistance for later images in multitemporal image classification.

  13. UAV-Based Hyperspectral Remote Sensing for Precision Agriculture: Challenges and Opportunities

    Science.gov (United States)

    Angel, Y.; Parkes, S. D.; Turner, D.; Houborg, R.; Lucieer, A.; McCabe, M.

    2017-12-01

    Modern agricultural production relies on monitoring crop status by observing and measuring variables such as soil condition, plant health, fertilizer and pesticide effect, irrigation and crop yield. Managing all of these factors is a considerable challenge for crop producers. As such, providing integrated technological solutions that enable improved diagnostics of field condition to maximize profits, while minimizing environmental impacts, would be of much interest. Such challenges can be addressed by implementing remote sensing systems such as hyperspectral imaging to produce precise biophysical indicator maps across the various cycles of crop development. Recent progress in unmanned aerial vehicles (UAVs) have advanced traditional satellite-based capabilities, providing a capacity for high-spatial, spectral and temporal response. However, while some hyperspectral sensors have been developed for use onboard UAVs, significant investment is required to develop a system and data processing workflow that retrieves accurately georeferenced mosaics. Here we explore the use of a pushbroom hyperspectral camera that is integrated on-board a multi-rotor UAV system to measure the surface reflectance in 272 distinct spectral bands across a wavelengths range spanning 400-1000 nm, and outline the requirement for sensor calibration, integration onto a stable UAV platform enabling accurate positional data, flight planning, and development of data post-processing workflows for georeferenced mosaics. The provision of high-quality and geo-corrected imagery facilitates the development of metrics of vegetation health that can be used to identify potential problems such as production inefficiencies, diseases and nutrient deficiencies and other data-streams to enable improved crop management. Immense opportunities remain to be exploited in the implementation of UAV-based hyperspectral sensing (and its combination with other imaging systems) to provide a transferable and scalable

  14. All-polymeric sensing platform based on packaged self-assembled bottle microresonator (Conference Presentation)

    Science.gov (United States)

    Bernini, Romeo; Grimaldi, Immacolata A.; Persichetti, Gianluca; Testa, Genni

    2017-02-01

    In recent years, microbottle resonators that support non-degenerate whispering gallery modes (WGMs), propagating by successive total internal reflections close to the resonator surface and all along its axis, have been widely investigated due to their potential applications in optical sensing, microlasers and nonlinear optics. To overcome some drawbacks of the standard silica microbottle resonators, we focused our attention on polymers such as SU-8 resist and NOA resins. A drop of polymeric material is dispensed onto a fiber stem, providing a mechanical support for the bottle resonator, and is photo-polymerized by an UV lamp. The interrogation system, usually constituted by a tapered silica fiber evanescently coupled with the microresonator, is substituted by a more stable planar waveguide realized in SU-8 by means of standard photolithography technique. Moreover, for guarantying the stability to surrounding disturbance of the coupling between the microbottle resonator and the planar waveguide, the fiber stem is glued to substrate. Two drilled holes in the substrate allow the rise of the glue at the ends of the fiber stem and the fixing of sensor on PMMA substrate. In the present work, we presented an integrated full polymeric platform with self-assembled bottle microresonators packaged in a stable structure. SU-8 and NOA based microbottles are realized and morphologically characterized. The low autofluorescence emission and long term stability make the NOA based bottles suitable to be employed in a great variety of conditions. Bulk sensing measurements are performed by using water:ethanol solutions and a bulk sensitivity of 120 nm/RIU is estimated.

  15. Surface Plasmon Resonance based sensing of lysozyme in serum on Micrococcus lysodeikticus-modified graphene oxide surfaces.

    Science.gov (United States)

    Vasilescu, Alina; Gáspár, Szilveszter; Gheorghiu, Mihaela; David, Sorin; Dinca, Valentina; Peteu, Serban; Wang, Qian; Li, Musen; Boukherroub, Rabah; Szunerits, Sabine

    2017-03-15

    Lysozyme is an enzyme found in biological fluids, which is upregulated in leukemia, renal diseases as well as in a number of inflammatory gastrointestinal diseases. We present here the development of a novel lysozyme sensing concept based on the use of Micrococcus lysodeikticus whole cells adsorbed on graphene oxide (GO)-coated Surface Plasmon Resonance (SPR) interfaces. M. lysodeikticus is a typical enzymatic substrate for lysozyme. Unlike previously reported sensors which are based on the detection of lysozyme through bioaffinity interactions, the bioactivity of lysozyme will be used here for sensing purposes. Upon exposure to lysozyme containing serum, the integrity of the bacterial cell wall is affected and the cells detach from the GO based interfaces, causing a characteristic decrease in the SPR signal. This allows sensing the presence of clinically relevant concentrations of lysozyme in undiluted serum samples. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Improved drought monitoring in the Greater Horn of Africa by combining meteorological and remote sensing based indicators

    DEFF Research Database (Denmark)

    Horion, Stéphanie Marie Anne F; Kurnik, Blaz; Barbosa, Paulo

    2010-01-01

    , and therefore to better trigger timely and appropriate actions on the field. In this study, meteorological and remote sensing based drought indicators were compared over the Greater Horn of Africa in order to better understand: (i) how they depict historical drought events ; (ii) if they could be combined...... distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy...... of the amount and vigour of vegetation. For both indexes, anomalies were estimated using available satellite archives. Cross-correlations between remote sensing based anomalies and SPI were analysed for five land covers (forest, shrubland, grassland, sparse grassland, cropland and bare soil) over different...

  17. Smartphone-based sensing system using ZnO and graphene modified electrodes for VOCs detection.

    Science.gov (United States)

    Liu, Lei; Zhang, Diming; Zhang, Qian; Chen, Xing; Xu, Gang; Lu, Yanli; Liu, Qingjun

    2017-07-15

    Volatile organic compounds (VOCs) detection is in high demand for clinic treatment, environment monitoring, and food quality control. Especially, VOCs from human exhaled breath can serve as significant biomarkers of some diseases, such as lung cancer and diabetes. In this study, a smartphone-based sensing system was developed for real-time VOCs monitoring using alternative current (AC) impedance measurement. The interdigital electrodes modified with zinc oxide (ZnO), graphene, and nitrocellulose were used as sensors to produce impedance responses to VOCs. The responses could be detected by a hand-held device, sent out to a smartphone by Bluetooth, and reported with concentration on an android program of the smartphone. The smartphone-based system was demonstrated to detect acetone at concentrations as low as 1.56ppm, while AC impedance spectroscopy was used to distinguish acetone from other VOCs. Finally, measurements of the exhalations from human being were carried out to obtain the concentration of acetone in exhaled breath before and after exercise. The results proved that the smartphone-based system could be applied on the detection of VOCs in real settings for healthcare diagnosis. Thus, the smartphone-based system for VOCs detection provided a convenient, portable and efficient approach to monitor VOCs in exhaled breath and possibly allowed for early diagnosis of some diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks.

    Science.gov (United States)

    Liu, Xin

    2015-10-30

    In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF) energy of the primary node (PN) to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

  19. A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xin Liu

    2015-10-01

    Full Text Available In a cognitive sensor network (CSN, the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs becomes very large. In this paper, a novel wireless power transfer (WPT-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF energy of the primary node (PN to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability.

  20. Comparison of Uncalibrated Rgbvi with Spectrometer-Based Ndvi Derived from Uav Sensing Systems on Field Scale

    Science.gov (United States)

    Bareth, G.; Bolten, A.; Gnyp, M. L.; Reusch, S.; Jasper, J.

    2016-06-01

    The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1) to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2) investigate the UAV-based performance of the modified Yara N-Sensor, and (3) compare the results of the two different UAV-based sensing approaches for winter wheat.

  1. Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

    Directory of Open Access Journals (Sweden)

    TAO Feixiang

    2015-08-01

    Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

  2. A Region-Based GeneSIS Segmentation Algorithm for the Classification of Remotely Sensed Images

    Directory of Open Access Journals (Sweden)

    Stelios K. Mylonas

    2015-03-01

    Full Text Available This paper proposes an object-based segmentation/classification scheme for remotely sensed images, based on a novel variant of the recently proposed Genetic Sequential Image Segmentation (GeneSIS algorithm. GeneSIS segments the image in an iterative manner, whereby at each iteration a single object is extracted via a genetic-based object extraction algorithm. Contrary to the previous pixel-based GeneSIS where the candidate objects to be extracted were evaluated through the fuzzy content of their included pixels, in the newly developed region-based GeneSIS algorithm, a watershed-driven fine segmentation map is initially obtained from the original image, which serves as the basis for the forthcoming GeneSIS segmentation. Furthermore, in order to enhance the spatial search capabilities, we introduce a more descriptive encoding scheme in the object extraction algorithm, where the structural search modules are represented by polygonal shapes. Our objectives in the new framework are posed as follows: enhance the flexibility of the algorithm in extracting more flexible object shapes, assure high level classification accuracies, and reduce the execution time of the segmentation, while at the same time preserving all the inherent attributes of the GeneSIS approach. Finally, exploiting the inherent attribute of GeneSIS to produce multiple segmentations, we also propose two segmentation fusion schemes that operate on the ensemble of segmentations generated by GeneSIS. Our approaches are tested on an urban and two agricultural images. The results show that region-based GeneSIS has considerably lower computational demands compared to the pixel-based one. Furthermore, the suggested methods achieve higher classification accuracies and good segmentation maps compared to a series of existing algorithms.

  3. Mapping of leptospirosis risk factor based on remote sensing image in Tembalang, Semarang City, Central Java

    Directory of Open Access Journals (Sweden)

    Sunaryo Sunaryo

    2012-09-01

    of leptospirosis, physical environment of risk factor analysis.Methods: This cross sectional design consisted of 246 leptospirosis subjects mapped with GPS, and processed by using ArcGis 92 program. Leptospirosis case was overlaid with remote sensing (Quickbird image, then is done interpretation of spatial feature, and digitation on screen to visual identify of risk factor.Results: Based on digital visualization leptospirosis cases in 2009 were clustered in Tembalang with shortest distance index 0,009 km and is furthermost 18 km. More case distribution found at children and men adolescent. Temporally, case increased in the dry season, among of July and August. Result of visual interpretation and digitation can obtain land use map, water body, settlement, fl oods area, vegetation index and height.Conclusion: Spatial high resolution remote sensing image is very good for mapping of leptospirosis risk factor. Leptospirosis case distribution forms the cluster in Tembalang; case is predominated by children andmen adolescent. (Health Science Indones 2012;1:45-50 

  4. Matrix Factorisation-based Calibration For Air Quality Crowd-sensing

    Science.gov (United States)

    Dorffer, Clement; Puigt, Matthieu; Delmaire, Gilles; Roussel, Gilles; Rouvoy, Romain; Sagnier, Isabelle

    2017-04-01

    sensors share some information using the APISENSE® crowdsensing platform and we aim to calibrate the sensor responses from the data directly. For that purpose, we express the sensor readings as a low-rank matrix with missing entries and we revisit self-calibration as a Matrix Factorization (MF) problem. In our proposed framework, one factor matrix contains the calibration parameters while the other is structured by the calibration model and contains some values of the sensed phenomenon. The MF calibration approach also uses the precise measurements from ATMO—the French public institution—to drive the calibration of the mobile sensors. MF calibration can be improved using, e.g., the mean calibration parameters provided by the sensor manufacturers, or using sparse priors or a model of the physical phenomenon. All our approaches are shown to provide a better calibration accuracy than matrix-completion-based and robust-regression-based methods, even in difficult scenarios involving a lot of missing data and/or very few accurate references. When combined with a dictionary of air quality patterns, our experiments suggest that MF is not only able to perform sensor network calibration but also to provide detailed maps of air quality.

  5. Fiber Bragg gratings-based sensing for real-time needle tracking during MR-guided brachytherapy

    Energy Technology Data Exchange (ETDEWEB)

    Borot de Battisti, Maxence, E-mail: M.E.P.Borot@umcutrecht.nl; Maenhout, Metha; Lagendijk, Jan J. W.; Vulpen, Marco van; Moerland, Marinus A. [Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX (Netherlands); Denis de Senneville, Baudouin [Imaging Division, University Medical Center Utrecht, Heidelberglaan 100, Utrecht 3584 CX, The Netherlands and IMB, UMR 5251 CNRS/University of Bordeaux, Talence 33400 (France); Hautvast, Gilion; Binnekamp, Dirk [Philips Group Innovation Biomedical Systems, Eindhoven 5656 AE (Netherlands)

    2016-10-15

    Purpose: The development of MR-guided high dose rate (HDR) brachytherapy is under investigation due to the excellent tumor and organs at risk visualization of MRI. However, MR-based localization of needles (including catheters or tubes) has inherently a low update rate and the required image interpretation can be hampered by signal voids arising from blood vessels or calcifications limiting the precision of the needle guidance and reconstruction. In this paper, a new needle tracking prototype is investigated using fiber Bragg gratings (FBG)-based sensing: this prototype involves a MR-compatible stylet composed of three optic fibers with nine sets of embedded FBG sensors each. This stylet can be inserted into brachytherapy needles and allows a fast measurement of the needle deflection. This study aims to assess the potential of FBG-based sensing for real-time needle (including catheter or tube) tracking during MR-guided intervention. Methods: First, the MR compatibility of FBG-based sensing and its accuracy was evaluated. Different known needle deflections were measured using FBG-based sensing during simultaneous MR-imaging. Then, a needle tracking procedure using FBG-based sensing was proposed. This procedure involved a MR-based calibration of the FBG-based system performed prior to the interventional procedure. The needle tracking system was assessed in an experiment with a moving phantom during MR imaging. The FBG-based system was quantified by comparing the gold-standard shapes, the shape manually segmented on MRI and the FBG-based measurements. Results: The evaluation of the MR compatibility of FBG-based sensing and its accuracy shows that the needle deflection could be measured with an accuracy of 0.27 mm on average. Besides, the FBG-based measurements were comparable to the uncertainty of MR-based measurements estimated at half the voxel size in the MR image. Finally, the mean(standard deviation) Euclidean distance between MR- and FBG-based needle position

  6. Multiple kernel SVR based on the MRE for remote sensing water depth fusion detection

    Science.gov (United States)

    Wang, Jinjin; Ma, Yi; Zhang, Jingyu

    2018-03-01

    Remote sensing has an important means of water depth detection in coastal shallow waters and reefs. Support vector regression (SVR) is a machine learning method which is widely used in data regression. In this paper, SVR is used to remote sensing multispectral bathymetry. Aiming at the problem that the single-kernel SVR method has a large error in shallow water depth inversion, the mean relative error (MRE) of different water depth is retrieved as a decision fusion factor with single kernel SVR method, a multi kernel SVR fusion method based on the MRE is put forward. And taking the North Island of the Xisha Islands in China as an experimentation area, the comparison experiments with the single kernel SVR method and the traditional multi-bands bathymetric method are carried out. The results show that: 1) In range of 0 to 25 meters, the mean absolute error(MAE)of the multi kernel SVR fusion method is 1.5m,the MRE is 13.2%; 2) Compared to the 4 single kernel SVR method, the MRE of the fusion method reduced 1.2% (1.9%) 3.4% (1.8%), and compared to traditional multi-bands method, the MRE reduced 1.9%; 3) In 0-5m depth section, compared to the single kernel method and the multi-bands method, the MRE of fusion method reduced 13.5% to 44.4%, and the distribution of points is more concentrated relative to y=x.

  7. Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia

    Directory of Open Access Journals (Sweden)

    Midekisa Alemayehu

    2012-05-01

    Full Text Available Abstract Background Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. Methods In this study seasonal autoregressive integrated moving average (SARIMA models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST, vegetation indices (NDVI and EVI, and actual evapotranspiration (ETa with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. Results Malaria cases exhibited positive associations with LST at a lag of one month and positive associations with indicators of moisture (rainfall, EVI and ETa at lags from one to three months. SARIMA models that included these environmental covariates had better fits and more accurate predictions, as evidenced by lower AIC and RMSE values, than models without environmental covariates. Conclusions Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public

  8. Simulation of submillimetre atmospheric spectra for characterising potential ground-based remote sensing observations

    Directory of Open Access Journals (Sweden)

    E. C. Turner

    2016-11-01

    Full Text Available The submillimetre is an understudied region of the Earth's atmospheric electromagnetic spectrum. Prior technological gaps and relatively high opacity due to the prevalence of rotational water vapour lines at these wavelengths have slowed progress from a ground-based remote sensing perspective; however, emerging superconducting detector technologies in the fields of astronomy offer the potential to address key atmospheric science challenges with new instrumental methods. A site study, with a focus on the polar regions, is performed to assess theoretical feasibility by simulating the downwelling (zenith angle = 0° clear-sky submillimetre spectrum from 30 mm (10 GHz to 150 µm (2000 GHz at six locations under annual mean, summer, winter, daytime, night-time and low-humidity conditions. Vertical profiles of temperature, pressure and 28 atmospheric gases are constructed by combining radiosonde, meteorological reanalysis and atmospheric chemistry model data. The sensitivity of the simulated spectra to the choice of water vapour continuum model and spectroscopic line database is explored. For the atmospheric trace species hypobromous acid (HOBr, hydrogen bromide (HBr, perhydroxyl radical (HO2 and nitrous oxide (N2O the emission lines producing the largest change in brightness temperature are identified. Signal strengths, centre frequencies, bandwidths, estimated minimum integration times and maximum receiver noise temperatures are determined for all cases. HOBr, HBr and HO2 produce brightness temperature peaks in the mK to µK range, whereas the N2O peaks are in the K range. The optimal submillimetre remote sensing lines for the four species are shown to vary significantly between location and scenario, strengthening the case for future hyperspectral instruments that measure over a broad wavelength range. The techniques presented here provide a framework that can be applied to additional species of interest and taken forward to simulate

  9. Molybdenum disulfide nanoflower-chitosan-Au nanoparticles composites based electrochemical sensing platform for bisphenol A determination

    International Nuclear Information System (INIS)

    Huang, Ke-Jing; Liu, Yu-Jie; Liu, Yan-Ming; Wang, Ling-Ling

    2014-01-01

    Highlights: • This work constructs a novel electrochemical biosensor for bisphenol A detection. • Flower-like MoS 2 are prepared by a simple hydrothermal procedure. • AuNPs are assembled on MoS 2 nanoflowers modified electrode for signal amplification. • The developed sensor exhibits low detection limit and wide linear range. - Abstract: Two-dimensional transition metal dichalcogenide are attracting increasing attention in electrochemical sensing due to their unique electronic properties. In this work, flower-like molybdenum disulfide (MoS 2 ) was prepared by a simple hydrothermal method. The scanning electron microscopy and transmission electron microscopy images showed the MoS 2 nanoflower had sizes with diameter of about 200 nm and was constructed with many irregular sheets as a petal-like structure with thickness of several nanometers. A novel electrochemical sensor was constructed for the determination of bisphenol A (BPA) based on MoS 2 and chitosan-gold nanoparticles composites modified electrode. The sensor showed an efficient electrocatalytic role for the oxidation of BPA, and the oxidation overpotentials of BPA decreased significantly and the peak current increased greatly compared with bare GCE and other modified electrode. A good linear relationship between the oxidation peak current and BPA concentration was obtained in the range from 0.05 to 100 μM with a detection limit of 5.0 × 10 −9 M (S/N = 3). The developed sensor exhibited high sensitivity and long-term stability, and it was successfully applied for the determination of BPA in different samples. This work indicated MoS 2 nanoflowers were promising in electrochemical sensing and catalytic applications

  10. Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

    Science.gov (United States)

    Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

    2018-06-01

    Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

  11. Sensing lymphoma cells based on a cell-penetrating/apoptosis-inducing/electron-transfer peptide probe

    International Nuclear Information System (INIS)

    Sugawara, Kazuharu; Shinohara, Hiroki; Kadoya, Toshihiko; Kuramitz, Hideki

    2016-01-01

    To electrochemically sense lymphoma cells (U937), we fabricated a multifunctional peptide probe that consists of cell-penetrating/apoptosis-inducing/electron-transfer peptides. Electron-transfer peptides derive from cysteine residue combined with the C-terminals of four tyrosine residues (Y_4). A peptide whereby Y_4C is bound to the C-terminals of protegrin 1 (RGGRLCYCRRRFCVCVGR-NH_2) is known to be an apoptosis-inducing agent against U937 cells, and is referred to as a peptide-1 probe. An oxidation response of the peptide-1 probe has been observed due to a phenolic hydroxyl group, and this response is decreased by the uptake of the peptide probe into the cells. To improve the cell membrane permeability against U937 cells, the RGGR at the N-terminals of the peptide-1 probe was replaced by RRRR (peptide-2 probe). In contrast, RNRCKGTDVQAWY_4C (peptide-3 probe), which recognizes ovalbumin, was constructed as a control. Compared with the other probes, the change in the peak current of the peptide-2 probe was the greatest at low concentrations and occurred in a short amount of time. Therefore, the cell membrane permeability of the peptide-2 probe was increased based on the arginine residues and the apoptosis-inducing peptides. The peak current was linear and ranged from 100 to 1000 cells/ml. The relative standard deviation of 600 cells/ml was 5.0% (n = 5). Furthermore, the membrane permeability of the peptide probes was confirmed using fluorescent dye. - Highlights: • We constructed a multifunctional peptide probe for the electrochemical sensing of lymphoma cells. • The peptide probe consists of cell-penetrating/apoptosis-inducing/electron-transfer peptides. • The electrode response of the peptide probe changes due to selective uptake into the cells.

  12. Modelling population distribution using remote sensing imagery and location-based data

    Science.gov (United States)

    Song, J.; Prishchepov, A. V.

    2017-12-01

    Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models

  13. Remote Sensing-based Methodologies for Snow Model Adjustments in Operational Streamflow Prediction

    Science.gov (United States)

    Bender, S.; Miller, W. P.; Bernard, B.; Stokes, M.; Oaida, C. M.; Painter, T. H.

    2015-12-01

    Water management agencies rely on hydrologic forecasts issued by operational agencies such as NOAA's Colorado Basin River Forecast Center (CBRFC). The CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate research-oriented, remotely-sensed snow data into CBRFC operations and to improve the accuracy of CBRFC forecasts. The partnership has yielded valuable analysis of snow surface albedo as represented in JPL's MODIS Dust Radiative Forcing in Snow (MODDRFS) data, across the CBRFC's area of responsibility. When dust layers within a snowpack emerge, reducing the snow surface albedo, the snowmelt rate may accelerate. The CBRFC operational snow model (SNOW17) is a temperature-index model that lacks explicit representation of snowpack surface albedo. CBRFC forecasters monitor MODDRFS data for emerging dust layers and may manually adjust SNOW17 melt rates. A technique was needed for efficient and objective incorporation of the MODDRFS data into SNOW17. Initial development focused in Colorado, where dust-on-snow events frequently occur. CBRFC forecasters used retrospective JPL-CBRFC analysis and developed a quantitative relationship between MODDRFS data and mean areal temperature (MAT) data. The relationship was used to generate adjusted, MODDRFS-informed input for SNOW17. Impacts of the MODDRFS-SNOW17 MAT adjustment method on snowmelt-driven streamflow prediction varied spatially and with characteristics of the dust deposition events. The largest improvements occurred in southwestern Colorado, in years with intense dust deposition events. Application of the method in other regions of Colorado and in "low dust" years resulted in minimal impact. The MODDRFS-SNOW17 MAT technique will be implemented in CBRFC operations in late 2015, prior to spring 2016 runoff. Collaborative investigation of remote sensing-based adjustment methods for the CBRFC operational hydrologic forecasting environment will continue over the next several years.

  14. Confronting remote sensing product with ground base measurements across time and scale

    Science.gov (United States)

    Pourmokhtarian, A.; Dietze, M.

    2015-12-01

    Ecosystem models are essential tools in forecasting ecosystem responses to global climate change. One of the most challenging issues in ecosystem modeling is scaling while preserving landscape characteristics and minimizing loss of information, when moving from point observation to regional scale. There is a keen interest in providing accurate inputs for ecosystem models which represent ecosystem initial state conditions. Remote sensing land cover products, such as Landsat NLCD and MODIS MCD12Q1, provide extensive spatio-temporal coverage but do not capture forest composition and structure. Lidar and hyperspectral have the potential to meet this need but lack sufficient spatial and historical coverage. Forest inventory measurements provide detailed information on the landscape but in a very small footprint. Combining inventory and land cover could improve estimates of ecosystem state and characteristic across time and space. This study focuses on the challenges associated with fusing and scaling the US Forest Service FIA database and NLCD across regional scales to quantify ecosystem characteristics and reduce associated uncertainties. Across Southeast of U.S. 400 stratified random samples of 10x10 km2 landscapes were selected. Data on plant density, species, age, and DBH of trees in FIA plots within each site were extracted. Using allometry equations, the canopy cover of different plant functional types (PFTs) was estimated using a PPA-style canopy model and used to assign each inventory plot to a land cover class. Inventory and land cover were fused in a Bayesian model that adjusts the fractional coverage of inventory plots while accounting for multiple sources of uncertainty. Results were compared to estimates derived from inventory alone, land cover alone, and model spin-up alone. Our findings create a framework of data assimilation to better interpret remote sensing data using ground-based measurements.

  15. Study on the techniques of valuation of ecosystem services based on remote sensing in Anxin County

    Science.gov (United States)

    Wang, Hongyan; Li, Zengyuan; Gao, Zhihai; Wang, Bengyu; Bai, Lina; Wu, Junjun; Sun, Bin; Wang, Zhibo

    2014-05-01

    The farmland ecosystem is an important component of terrestrial ecosystems and has a fundamental role in the human life. The wetland is an unique and versatile ecological system. It is important for rational development and sustainable utilization of farmland and wetland resources to study on the measurement of valuation of farmland and wetland ecosystem services. It also has important significance for improving productivity. With the rapid development of remote sensing technology, it has become a powerful tool for evaluation of the value of ecosystem services. The land cover types in Anxin County mainly was farmland and wetland, the indicator system for ecosystem services valuation was brought up based on the remote sensing data of high spatial resolution ratio(Landsat-5 TM data and SPOT-5 data), the technology system for measurement of ecosystem services value was established. The study results show that the total ecosystem services value in 2009 in Anxin was 4.216 billion yuan, and the unit area value was between 8489 yuan/hm2 and 329535 yuan/hm2. The value of natural resources, water conservation value in farmland ecosystem and eco-tourism value in wetland ecosystem were higher than the other, total of the three values reached 2.858 billion yuan, and the percentage of the total ecosystem services values in Anxin was 67.79%. Through the statistics in the nine towns and three villages of Anxin County, the juantou town has the highest services value, reached 0.736 billion yuan. Scientific and comprehensive evaluation of the ecosystem services can conducive to promoting the understanding of the importance of the ecosystem. The research results had significance to ensure the sustainable use of wetland resources and the guidance of ecological construction in Anxin County.

  16. Sensing lymphoma cells based on a cell-penetrating/apoptosis-inducing/electron-transfer peptide probe

    Energy Technology Data Exchange (ETDEWEB)

    Sugawara, Kazuharu, E-mail: kzsuga@maebashi-it.ac.jp [Maebashi Institute of Technology, Gunma 371-0816 (Japan); Shinohara, Hiroki; Kadoya, Toshihiko [Maebashi Institute of Technology, Gunma 371-0816 (Japan); Kuramitz, Hideki [Department of Environmental Biology and Chemistry, Graduate School of Science and Engineering for Research, University of Toyama, Toyama 930-8555 (Japan)

    2016-06-14

    To electrochemically sense lymphoma cells (U937), we fabricated a multifunctional peptide probe that consists of cell-penetrating/apoptosis-inducing/electron-transfer peptides. Electron-transfer peptides derive from cysteine residue combined with the C-terminals of four tyrosine residues (Y{sub 4}). A peptide whereby Y{sub 4}C is bound to the C-terminals of protegrin 1 (RGGRLCYCRRRFCVCVGR-NH{sub 2}) is known to be an apoptosis-inducing agent against U937 cells, and is referred to as a peptide-1 probe. An oxidation response of the peptide-1 probe has been observed due to a phenolic hydroxyl group, and this response is decreased by the uptake of the peptide probe into the cells. To improve the cell membrane permeability against U937 cells, the RGGR at the N-terminals of the peptide-1 probe was replaced by RRRR (peptide-2 probe). In contrast, RNRCKGTDVQAWY{sub 4}C (peptide-3 probe), which recognizes ovalbumin, was constructed as a control. Compared with the other probes, the change in the peak current of the peptide-2 probe was the greatest at low concentrations and occurred in a short amount of time. Therefore, the cell membrane permeability of the peptide-2 probe was increased based on the arginine residues and the apoptosis-inducing peptides. The peak current was linear and ranged from 100 to 1000 cells/ml. The relative standard deviation of 600 cells/ml was 5.0% (n = 5). Furthermore, the membrane permeability of the peptide probes was confirmed using fluorescent dye. - Highlights: • We constructed a multifunctional peptide probe for the electrochemical sensing of lymphoma cells. • The peptide probe consists of cell-penetrating/apoptosis-inducing/electron-transfer peptides. • The electrode response of the peptide probe changes due to selective uptake into the cells.

  17. Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment.

    Science.gov (United States)

    Shahabi, Himan; Hashim, Mazlan

    2015-04-22

    This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.

  18. A study on software-based sensing technology for multiple object control in AR video.

    Science.gov (United States)

    Jung, Su