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.

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

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....

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)

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...

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.

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

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 .

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.

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.

Potential and Challenges of Low-Cost and High-Tech Crowd-sensing Approaches in Hydrometeorology for Better Water Resources Management - Insights and Learnings from the Global iMoMo Initiative

Science.gov (United States)

Siegfried, Tobias

2016-04-01

In developing and transition countries and despite significant global investments in hydrometeorology, data on water remain scarce/fragmented. One key reason is that traditional sensing in hydrology, hydro- and agro-meteorology does not scale because of high investment costs and difficult maintenance of traditional technology, esp. in remote and/or poor regions. Even where there are data, these are often difficult to access and interpret for local stakeholders due outdated data transmission and the lack of access to modern tools for data management/analysis/synthesis and exchange. In recent years, there have been substantial technology developments in environmental sensing and mobile communication technology that enable the application and deployment of affordable and scalable high-tech solutions for better water monitoring at different scales (local to transboundary levels). The WMO is acknowledging and promoting the potential for application of these technologies. One key aspect is to anchor these technologies in local communities that perform crowd-sensing tasks on a regular basis. The merits as well as challenges (including introduction of human factor, less accuracy as compared to traditional sensing, intermittency of data, …) of such approaches will be discussed in the context of the WMO-led Global iMoMo Initiative and its numerous activities on the ground in Eastern and Southern Africa as well as in Central Asia.

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.

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.

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...

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

[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.

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.

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.

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

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.

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.

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.

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

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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.

Knowledge-based biomedical word sense disambiguation: comparison of approaches

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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

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

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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.

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

Online decision support based on modeling with the aim of increased irrigation efficiency

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Dövényi-Nagy, Tamás; Bakó, Károly; Molnár, Krisztina; Rácz, Csaba; Vasvári, Gyula; Nagy, János; Dobos, Attila

2015-04-01

The significant changes in the structure of ownership and control of irrigation infrastructure in the past decades resultted in the decrease of total irrigable and irrigated area (Szilárd, 1999). In this paper, the development of a model-based online service is described whose aim is to aid reasonable irrigation practice and increase water use efficiency. In order to establish a scientific background for irrigation, an agrometeorological station network has been built up by the Agrometeorological and Agroecological Monitoring Centre. A website has been launched in order to provide direct access for local agricultural producers to both the measured weather parameters and results of model based calculations. The public site provides information for general use, registered partners get a handy model based toolkit for decision support at the plot level concerning irrigation, plant protection or frost forecast. The agrometeorological reference station network was established in the recent years by the Agrometeorological and Agroecological Monitoring Centre and is distributed to cover most of the irrigated cropland areas of Hungary. From the spatial aspect, the stations have been deployed mainly in Eastern Hungary with concentrated irrigation infrastructure. The meteorological stations' locations have been carefully chosen to represent their environment in terms of soil, climatic and topographic factors, thereby assuring relevant and up-to-date input data for the models. The measured parameters range from classic meteorological data (air temperature, relative humidity, solar irradiation, wind speed etc.) to specific data which are not available from other services in the region, such as soil temperature, soil water content in multiple depths and leaf wetness. In addition to the basic grid of reference stations, specific stations under irrigated conditions have been deployed to calibrate and validate the models. A specific modeling framework (MetAgro) has been developed

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.

Six-Port Based Interferometry for Precise Radar and Sensing Applications

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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.

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

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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

Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

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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.

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

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

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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.

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

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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.

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

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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.

Remote Sensing Image Classification Based on Stacked Denoising Autoencoder

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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.

Bridge SHM system based on fiber optical sensing technology

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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.

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.

Combining the Pixel-based and Object-based Methods for Building Change Detection Using High-resolution Remote Sensing Images

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ZHANG Zhiqiang

2018-01-01

Full Text Available Timely and accurate change detection of buildings provides important information for urban planning and management.Accompanying with the rapid development of satellite remote sensing technology,detecting building changes from high-resolution remote sensing images have received wide attention.Given that pixel-based methods of change detection often lead to low accuracy while object-based methods are complicated for uses,this research proposes a method that combines pixel-based and object-based methods for detecting building changes from high-resolution remote sensing images.First,based on the multiple features extracted from the high-resolution images,a random forest classifier is applied to detect changed building at the pixel level.Then,a segmentation method is applied to segement the post-phase remote sensing image and to get post-phase image objects.Finally,both changed building at the pixel level and post-phase image objects are fused to recognize the changed building objects.Multi-temporal QuickBird images are used as experiment data for building change detection with high-resolution remote sensing images,the results indicate that the proposed method could reduce the influence of environmental difference,such as light intensity and view angle,on building change detection,and effectively improve the accuracies of building change detection.

Aptamer-Based Electrochemical Sensing of Lysozyme

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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.

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)

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

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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.

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.

Intelligent Chiral Sensing Based on Supramolecular and Interfacial Concepts

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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.

Fabrication of Porous Silicon Based Humidity Sensing Elements on Paper

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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.

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...

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.

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 ...

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.

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

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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

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.

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

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

Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data.

Science.gov (United States)

Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen

2013-02-01

The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on MODIS land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.

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.

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

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.

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,...

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.

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

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.

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.

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

Identification of Coupled Map Lattice Based on Compressed Sensing

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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.

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...

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...

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.

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

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

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).

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.

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.

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

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.

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

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

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.

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.

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.

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

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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.

DrivingSense: Dangerous Driving Behavior Identification Based on Smartphone Autocalibration

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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.

Effect of channel-width and chirality on graphene field-effect transistor based real-time biomolecule sensing

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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.

Effect of channel-width and chirality on graphene field-effect transistor based real-time biomolecule sensing

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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.

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

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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.

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)

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.

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.

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.

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

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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

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

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

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.

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

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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.

Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data

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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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

[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.

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.

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.

SYMBIOTIC SENSING: Exploring and Exploiting Cooperative Sensing in Heterogeneous Sensor Networks

NARCIS (Netherlands)

Le Viet Duc, L Duc

2016-01-01

During the last several years we have witnessed the emergence of smartphone-based sensing applications that include activity recognition, urban sensing, social sensing, and health monitoring. In fact, most smartphones have various sensors, wireless communication interfaces, a large memory capacity,

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.

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.

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.

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.

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.

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.

Results of agriclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

International Nuclear Information System (INIS)

Choudhury, A.M.

1990-08-01

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. (author). 3 refs

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.

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.

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.

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.

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.

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.

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.

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…

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

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.

Energy-efficient sensing in wireless sensor networks using compressed sensing.

Science.gov (United States)

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

[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.

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.

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.

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...

Adapting a Natura 2000 field guideline for a remote sensing-based assessment of heathland conservation status

Science.gov (United States)

Schmidt, Johannes; Fassnacht, Fabian Ewald; Neff, Christophe; Lausch, Angela; Kleinschmit, Birgit; Förster, Michael; Schmidtlein, Sebastian

2017-08-01

Remote sensing can be a valuable tool for supporting nature conservation monitoring systems. However, for many areas of conservation interest, there is still a considerable gap between field-based operational monitoring guidelines and the current remote sensing-based approaches. This hampers application in practice of the latter. Here, we propose a remote sensing approach for mapping the conservation status of Calluna-dominated Natura 2000 dwarf shrub habitats that is closely related to field mapping schemes. We transferred the evaluation criteria of the field guidelines to three related variables that can be captured by remote sensing: (1) coverage of the key species, (2) stand structural diversity, and (3) co-occurring species. Continuous information on these variables was obtained by regressing ground reference data from field surveys and UAV flights against airborne hyperspectral imagery. Merging the three resulting quality layers in an RGB representation allowed for illustrating the habitat quality in a continuous way. User-defined thresholds can be applied to this stack of quality layers to derive an overall assessment of habitat quality in terms of nature conservation, i.e. the conservation status. In our study, we found good accordance of the remotely sensed data with field-based information for the three variables key species, stand structural diversity and co-occurring vegetation (R2 of 0.79, 0.69, and 0.71, respectively) and it was possible to derive meaningful habitat quality maps. The conservation status could be derived with an accuracy of 65%. In interpreting these results it should be considered that the remote sensing based layers are independent estimates of habitat quality in their own right and not a mere replacement of the criteria used in the field guidelines. The approach is thought to be transferable to similar regions with minor adaptions. Our results refer to Calluna heathland which we consider a comparably easy target for remote sensing

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.

All-soft, battery-free, and wireless chemical sensing platform based on liquid metal for liquid- and gas-phase VOC detection.

Science.gov (United States)

Kim, Min-Gu; Alrowais, Hommood; Kim, Choongsoon; Yeon, Pyungwoo; Ghovanloo, Maysam; Brand, Oliver

2017-06-27

Lightweight, flexible, stretchable, and wireless sensing platforms have gained significant attention for personal healthcare and environmental monitoring applications. This paper introduces an all-soft (flexible and stretchable), battery-free, and wireless chemical microsystem using gallium-based liquid metal (eutectic gallium-indium alloy, EGaIn) and poly(dimethylsiloxane) (PDMS), fabricated using an advanced liquid metal thin-line patterning technique based on soft lithography. Considering its flexible, stretchable, and lightweight characteristics, the proposed sensing platform is well suited for wearable sensing applications either on the skin or on clothing. Using the microfluidic sensing platform, detection of liquid-phase and gas-phase volatile organic compounds (VOC) is demonstrated using the same design, which gives an opportunity to have the sensor operate under different working conditions and environments. In the case of liquid-phase chemical sensing, the wireless sensing performance and microfluidic capacitance tunability for different dielectric liquids are evaluated using analytical, numerical, and experimental approaches. In the case of gas-phase chemical sensing, PDMS is used both as a substrate and a sensing material. The gas sensing performance is evaluated and compared to a silicon-based, solid-state gas sensor with a PDMS sensing film.

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

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.

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

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.

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)

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

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.

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...

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

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

Science.gov (United States)

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote

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.

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.

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…

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

COMPARISON OF UNCALIBRATED RGBVI WITH SPECTROMETER-BASED NDVI DERIVED FROM UAV SENSING SYSTEMS ON FIELD SCALE

Directory of Open Access Journals (Sweden)

G. Bareth

2016-06-01

Full Text Available 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 (< 5 kg is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers’ field in Western Germany. (i A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii NDVI is computed from a newly 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.

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.

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

[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.

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.

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.

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.

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.

Determining Regional Actual Evapotranspiration of Irrigated Crops and Natural Vegetation in the São Francisco River Basin (Brazil Using Remote Sensing and Penman-Monteith Equation

Directory of Open Access Journals (Sweden)

Antônio H. de C. Teixeira

2010-05-01

Full Text Available To achieve sustainable development and to ensure water availability in hydrological basins, water managers need tools to determine the actual evapotranspiration (ET on a large scale. Field energy balances from irrigated and natural ecosystems together with a net of agro-meteorological stations were used to develop two models for ET quantification at basin scale, based on the Penman-Monteith equation. The first model (PM1 uses the resistances to the latent heat fluxes estimated from satellite measurements, while the second one (PM2 is based on the ratio of ET to the reference evapotranspiration (ET0 and its relation to remote sensing parameters. The models were applied in the Low-Middle São Francisco river basin in Brazil and, after comparison against field results, showed good agreements with PM1 and PM2 explaining, respectively, 79% and 89% of the variances and mean square errors (RMSE of 0.44 and 0.34 mm d−1. Even though the PM1 model was not chosen for ET calculations, the equation for surface resistance (rs was applied to infer the soil moisture conditions in a simplified vegetation classification. The maximum values of rs were for natural vegetation—caatinga (average of 1,937 s m−1. Wine grape and mango orchard presented similar values around 130 s m−1, while table grape presented the lowest ones, averaging 74 s m−1. Petrolina and Juazeiro, in Pernambuco (PE and Bahia (BA states, respectively, were highlighted with the biggest irrigated areas. The highest increments are for vineyards and mango orchards. For the first crop the maximum increment was verified between 2003 and 2004 in Petrolina-PE, when the cultivated area increased 151%. In the case of mango orchards the most significant period was from 2005 to 2006 in Juazeiro-BA (129%. As the best performance was for PM2, it was selected and used to analyse the regional ET at daily and annual scales, making use of Landsat images and a geographic information system for different

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

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

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...

Optical chaos and hybrid WDM/TDM based large capacity quasi-distributed sensing network with real-time fiber fault monitoring.

Science.gov (United States)

Luo, Yiyang; Xia, Li; Xu, Zhilin; Yu, Can; Sun, Qizhen; Li, Wei; Huang, Di; Liu, Deming

2015-02-09

An optical chaos and hybrid wavelength division multiplexing/time division multiplexing (WDM/TDM) based large capacity quasi-distributed sensing network with real-time fiber fault monitoring is proposed. Chirped fiber Bragg grating (CFBG) intensity demodulation is adopted to improve the dynamic range of the measurements. Compared with the traditional sensing interrogation methods in time, radio frequency and optical wavelength domains, the measurand sensing and the precise locating of the proposed sensing network can be simultaneously interrogated by the relative amplitude change (RAC) and the time delay of the correlation peak in the cross-correlation spectrum. Assisted with the WDM/TDM technology, hundreds of sensing units could be potentially multiplexed in the multiple sensing fiber lines. Based on the proof-of-concept experiment for axial strain measurement with three sensing fiber lines, the strain sensitivity up to 0.14% RAC/με and the precise locating of the sensors are achieved. Significantly, real-time fiber fault monitoring in the three sensing fiber lines is also implemented with a spatial resolution of 2.8 cm.

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.

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...

Supporting Craft Sense in Early Education

Directory of Open Access Journals (Sweden)

Kalle Virta

2013-10-01

Full Text Available The research task was to describe and construct theoretical background for Craft Sense in early education. Craft Sense represents a learner’s skill for obtaining Sloyd (Craft, Design & Technology related knowledge, skills and understanding. The development of Craft Sense is based on producing artefacts and evaluating the production process. In this research, the concept of Craft Sense is based on the integration of Sloyd and meta-cognitive regulation of learning activities. Based on theoretical information, an empirical research question was formulated: “What kind of Craft Sense do children have in early education Sloyd?” The method of study was assessing picture supported learning on a Sloyd course for young children. The data was analyzed by qualitative content analysis and Child Behaviour Rating Scale (CBRS. Findings indicate that the development of children’s Craft Sense can be supported with pictures. Furthermore, the CBRS can be used to evaluate and understand children’s Craft Sense. Keywords: Craft Sense, Sloyd, Sloyd Education, Meta-cognition

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.

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.

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.

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.

Disposable, Paper-Based, Inkjet-Printed Humidity and H2S Gas Sensor for Passive Sensing Applications

Science.gov (United States)

Quddious, Abdul; Yang, Shuai; Khan, Munawar M.; Tahir, Farooq A.; Shamim, Atif; Salama, Khaled N.; Cheema, Hammad M.

2016-01-01

An inkjet-printed, fully passive sensor capable of either humidity or gas sensing is presented herein. The sensor is composed of an interdigitated electrode, a customized printable gas sensitive ink and a specialized dipole antenna for wireless sensing. The interdigitated electrode printed on a paper substrate provides the base conductivity that varies during the sensing process. Aided by the porous nature of the substrate, a change in relative humidity from 18% to 88% decreases the electrode resistance from a few Mega-ohms to the kilo-ohm range. For gas sensing, an additional copper acetate-based customized ink is printed on top of the electrode, which, upon reaction with hydrogen sulphide gas (H2S) changes, both the optical and the electrical properties of the electrode. A fast response time of 3 min is achieved at room temperature for a H2S concentration of 10 ppm at a relative humidity (RH) of 45%. The passive wireless sensing is enabled through an antenna in which the inner loop takes care of conductivity changes in the 4–5 GHz band, whereas the outer-dipole arm is used for chipless identification in the 2–3 GHz band. PMID:27929450

Disposable, Paper-Based, Inkjet-Printed Humidity and H2S Gas Sensor for Passive Sensing Applications

Directory of Open Access Journals (Sweden)

Abdul Quddious

2016-12-01

Full Text Available An inkjet-printed, fully passive sensor capable of either humidity or gas sensing is presented herein. The sensor is composed of an interdigitated electrode, a customized printable gas sensitive ink and a specialized dipole antenna for wireless sensing. The interdigitated electrode printed on a paper substrate provides the base conductivity that varies during the sensing process. Aided by the porous nature of the substrate, a change in relative humidity from 18% to 88% decreases the electrode resistance from a few Mega-ohms to the kilo-ohm range. For gas sensing, an additional copper acetate-based customized ink is printed on top of the electrode, which, upon reaction with hydrogen sulphide gas (H2S changes, both the optical and the electrical properties of the electrode. A fast response time of 3 min is achieved at room temperature for a H2S concentration of 10 ppm at a relative humidity (RH of 45%. The passive wireless sensing is enabled through an antenna in which the inner loop takes care of conductivity changes in the 4–5 GHz band, whereas the outer-dipole arm is used for chipless identification in the 2–3 GHz band.

Disposable, Paper-Based, Inkjet-Printed Humidity and H2S Gas Sensor for Passive Sensing Applications

KAUST Repository

Quddious, Abdul; Yang, Shuai; Khan, Munawar M.; Tahir, Farooq A.; Shamim, Atif; Salama, Khaled N.; Cheema, Hammad M.

2016-01-01

An inkjet-printed, fully passive sensor capable of either humidity or gas sensing is presented herein. The sensor is composed of an interdigitated electrode, a customized printable gas sensitive ink and a specialized dipole antenna for wireless sensing. The interdigitated electrode printed on a paper substrate provides the base conductivity that varies during the sensing process. Aided by the porous nature of the substrate, a change in relative humidity from 18% to 88% decreases the electrode resistance from a few Mega-ohms to the kilo-ohm range. For gas sensing, an additional copper acetate-based customized ink is printed on top of the electrode, which, upon reaction with hydrogen sulphide gas (HS) changes, both the optical and the electrical properties of the electrode. A fast response time of 3 min is achieved at room temperature for a HS concentration of 10 ppm at a relative humidity (RH) of 45%. The passive wireless sensing is enabled through an antenna in which the inner loop takes care of conductivity changes in the 4-5 GHz band, whereas the outer-dipole arm is used for chipless identification in the 2-3 GHz band.

Disposable, Paper-Based, Inkjet-Printed Humidity and H2S Gas Sensor for Passive Sensing Applications

KAUST Repository

Quddious, Abdul

2016-12-06

An inkjet-printed, fully passive sensor capable of either humidity or gas sensing is presented herein. The sensor is composed of an interdigitated electrode, a customized printable gas sensitive ink and a specialized dipole antenna for wireless sensing. The interdigitated electrode printed on a paper substrate provides the base conductivity that varies during the sensing process. Aided by the porous nature of the substrate, a change in relative humidity from 18% to 88% decreases the electrode resistance from a few Mega-ohms to the kilo-ohm range. For gas sensing, an additional copper acetate-based customized ink is printed on top of the electrode, which, upon reaction with hydrogen sulphide gas (HS) changes, both the optical and the electrical properties of the electrode. A fast response time of 3 min is achieved at room temperature for a HS concentration of 10 ppm at a relative humidity (RH) of 45%. The passive wireless sensing is enabled through an antenna in which the inner loop takes care of conductivity changes in the 4-5 GHz band, whereas the outer-dipole arm is used for chipless identification in the 2-3 GHz band.

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

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

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.

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.

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.

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

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

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...

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...

Advanced sensing techniques for cognitive radio

CERN Document Server

Zhao, Guodong; Li, Shaoqian

2017-01-01

This SpringerBrief investigates advanced sensing techniques to detect and estimate the primary receiver for cognitive radio systems. Along with a comprehensive overview of existing spectrum sensing techniques, this brief focuses on the design of new signal processing techniques, including the region-based sensing, jamming-based probing, and relay-based probing. The proposed sensing techniques aim to detect the nearby primary receiver and estimate the cross-channel gain between the cognitive transmitter and primary receiver. The performance of the proposed algorithms is evaluated by simulations in terms of several performance parameters, including detection probability, interference probability, and estimation error. The results show that the proposed sensing techniques can effectively sense the primary receiver and improve the cognitive transmission throughput. Researchers and postgraduate students in electrical engineering will find this an exceptional resource.

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.

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.

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

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.

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.

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.

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.

Ultra-short FBG based distributed sensing using shifted optical Gaussian filters and microwave-network analysis.

Science.gov (United States)

Cheng, Rui; Xia, Li; Sima, Chaotan; Ran, Yanli; Rohollahnejad, Jalal; Zhou, Jiaao; Wen, Yongqiang; Yu, Can

2016-02-08

Ultrashort fiber Bragg gratings (US-FBGs) have significant potential as weak grating sensors for distributed sensing, but the exploitation have been limited by their inherent broad spectra that are undesirable for most traditional wavelength measurements. To address this, we have recently introduced a new interrogation concept using shifted optical Gaussian filters (SOGF) which is well suitable for US-FBG measurements. Here, we apply it to demonstrate, for the first time, an US-FBG-based self-referencing distributed optical sensing technique, with the advantages of adjustable sensitivity and range, high-speed and wide-range (potentially >14000 με) intensity-based detection, and resistance to disturbance by nonuniform parameter distribution. The entire system is essentially based on a microwave network, which incorporates the SOGF with a fiber delay-line between the two arms. Differential detections of the cascaded US-FBGs are performed individually in the network time-domain response which can be obtained by analyzing its complex frequency response. Experimental results are presented and discussed using eight cascaded US-FBGs. A comprehensive numerical analysis is also conducted to assess the system performance, which shows that the use of US-FBGs instead of conventional weak FBGs could significantly improve the power budget and capacity of the distributed sensing system while maintaining the crosstalk level and intensity decay rate, providing a promising route for future sensing applications.

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.

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.

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.

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.

Study of key technology of ghost imaging via compressive sensing for a phase object based on phase-shifting digital holography

International Nuclear Information System (INIS)

Leihong, Zhang; Dong, Liang; Bei, Li; Zilan, Pan; Dawei, Zhang; Xiuhua, Ma

2015-01-01

In this article, the algorithm of compressing sensing is used to improve the imaging resolution and realize ghost imaging via compressive sensing for a phase object based on the theoretical analysis of the lensless Fourier imaging of the algorithm of ghost imaging based on phase-shifting digital holography. The algorithm of ghost imaging via compressive sensing based on phase-shifting digital holography uses the bucket detector to measure the total light intensity of the interference and the four-step phase-shifting method is used to obtain the total light intensity of differential interference light. The experimental platform is built based on the software simulation, and the experimental results show that the algorithm of ghost imaging via compressive sensing based on phase-shifting digital holography can obtain the high-resolution phase distribution figure of the phase object. With the same sampling times, the phase clarity of the phase distribution figure obtained by the algorithm of ghost imaging via compressive sensing based on phase-shifting digital holography is higher than that obtained by the algorithm of ghost imaging based on phase-shift digital holography. In this article, this study further extends the application range of ghost imaging and obtains the phase distribution of the phase object. (letter)

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

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

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.

Biomolecule-assisted synthesis and gas-sensing properties of porous nanosheet-based corundum In2O3 microflowers

International Nuclear Information System (INIS)

Zhang Wenhui; Zhang Weide

2012-01-01

Porous nanosheet-based corundum In 2 O 3 microflowers were fabricated by one-pot hydrothermal treatment of D-fructose and In(NO 3 ) 3 mixture using urea as a precipitating agent followed by calcination. The products were characterized by X-ray diffraction, scanning and transmission electron microscopy. The effects of D-fructose and urea on the fabrication of nanosheet-based corundum In 2 O 3 microflowers were investigated and a possible mechanism is proposed to explain the formation of the hierarchical nanostructures. The gas sensor based on the In 2 O 3 microflowers exhibits excellent sensing properties for the detection of formaldehyde. - Graphical abstract: Nanosheets-based corundum In 2 O 3 microflowers were fabricated by one-pot hydrothermal treatment of D-fructose/In(NO 3 ) 3 mixture followed by calcination, which show high performance for formaldehyde sensing. Highlights: ► Preparation of porous nanosheet-based corundum In 2 O 3 microflowers. ► Morphology and phase control of In 2 O 3 . ► Gas sensor based on the In 2 O 3 microflowers exhibits excellent sensing properties for the detection of formaldehyde.

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.

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.

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

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

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...

Sensing in tissue bioreactors

Science.gov (United States)

Rolfe, P.

2006-03-01

Specialized sensing and measurement instruments are under development to aid the controlled culture of cells in bioreactors for the fabrication of biological tissues. Precisely defined physical and chemical conditions are needed for the correct culture of the many cell-tissue types now being studied, including chondrocytes (cartilage), vascular endothelial cells and smooth muscle cells (blood vessels), fibroblasts, hepatocytes (liver) and receptor neurones. Cell and tissue culture processes are dynamic and therefore, optimal control requires monitoring of the key process variables. Chemical and physical sensing is approached in this paper with the aim of enabling automatic optimal control, based on classical cell growth models, to be achieved. Non-invasive sensing is performed via the bioreactor wall, invasive sensing with probes placed inside the cell culture chamber and indirect monitoring using analysis within a shunt or a sampling chamber. Electroanalytical and photonics-based systems are described. Chemical sensing for gases, ions, metabolites, certain hormones and proteins, is under development. Spectroscopic analysis of the culture medium is used for measurement of glucose and for proteins that are markers of cell biosynthetic behaviour. Optical interrogation of cells and tissues is also investigated for structural analysis based on scatter.

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.

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.

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.

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.

Perception of Innovative Crop Insurance in Australia

NARCIS (Netherlands)

Meuwissen, M.P.M.; Molnar, T.A.

2010-01-01

Worldwide, extreme climate risks cause stakeholders in food supply chains to search for new risk management tools. In Australia, recently so-called crop yield simulation insurance has been introduced based on an integrated agrometeorological simulation model. Current uptake is relatively low,

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

Remote Sensing Terminology in a Global and Knowledge-Based World

Science.gov (United States)

Kancheva, Rumiana

The paper is devoted to terminology issues related to all aspects of remote sensing research and applications. Terminology is the basis for a better understanding among people. It is crucial to keep up with the latest developments and novelties of the terminology in advanced technology fields such as aerospace science and industry. This is especially true in remote sensing and geoinformatics which develop rapidly and have ever extending applications in various domains of science and human activities. Remote sensing terminology issues are directly relevant to the contemporary worldwide policies on information accessibility, dissemination and utilization of research results in support of solutions to global environmental challenges and sustainable development goals. Remote sensing and spatial information technologies are an integral part of the international strategies for cooperation in scientific, research and application areas with a particular accent on environmental monitoring, ecological problems natural resources management, climate modeling, weather forecasts, disaster mitigation and many others to which remote sensing data can be put. Remote sensing researchers, professionals, students and decision makers of different counties and nationalities should fully understand, interpret and translate into their native language any term, definition or acronym found in papers, books, proceedings, specifications, documentation, and etc. The importance of the correct use, precise definition and unification of remote sensing terms refers not only to people working in this field but also to experts in a variety of disciplines who handle remote sensing data and information products. In this paper, we draw the attention on the specifics, peculiarities and recent needs of compiling specialized dictionaries in the area of remote sensing focusing on Earth observations and the integration of remote sensing with other geoinformation technologies such as photogrammetry, geodesy

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.

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.

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.

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.

Highly Sensitive and Selective Sensing of Free Bilirubin Using Metal-Organic Frameworks-Based Energy Transfer Process.

Science.gov (United States)

Du, Yaran; Li, Xiqian; Lv, Xueju; Jia, Qiong

2017-09-13

Free bilirubin, a key biomarker for jaundice, was detected with a newly designed fluorescent postsynthetically modified metal organic framework (MOF) (UIO-66-PSM) sensor. UiO-66-PSM was prepared based on the aldimine condensation reaction of UiO-66-NH 2 with 2,3,4-trihydroxybenzaldehyde. The fluorescence of UIO-66-PSM could be effectively quenched by free bilirubin via a fluorescent resonant energy transfer process, thus achieving its recognition of free bilirubin. It was the first attempt to design a MOF-based fluorescent probe for sensing free bilirubin. The probe exhibited fast response time, low detection limit, wide linear range, and high selectivity toward free bilirubin. The sensing system enabled the monitor of free bilirubin in real human serum. Hence, the reported free bilirubin sensing platform has potential applications for clinical diagnosis of jaundice.

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).

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.

A ground temperature map of the North Atlantic permafrost region based on remote sensing and reanalysis data

DEFF Research Database (Denmark)

Westermann, S.; Østby, T. I.; Gisnås, K.

2015-01-01

Permafrost is a key element of the terrestrial cryosphere which makes mapping and monitoring of its state variables an imperative task. We present a modeling scheme based on remotely sensed land surface temperatures and reanalysis products from which mean annual ground temperatures (MAGT) can be ...... with gradually decreasing permafrost probabilities. The study exemplifies the unexploited potential of remotely sensed data sets in permafrost mapping if they are employed in multi-sensor multi-source data fusion approaches.......Permafrost is a key element of the terrestrial cryosphere which makes mapping and monitoring of its state variables an imperative task. We present a modeling scheme based on remotely sensed land surface temperatures and reanalysis products from which mean annual ground temperatures (MAGT) can...

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.

Single-Thread-Based Wearable and Highly Stretchable Triboelectric Nanogenerators and Their Applications in Cloth-Based Self-Powered Human-Interactive and Biomedical Sensing

KAUST Repository

Lai, Ying-Chih

2016-11-03

The development of wearable and large-area fabric energy harvester and sensor has received great attention due to their promising applications in next-generation autonomous and wearable healthcare technologies. Here, a new type of “single” thread-based triboelectric nanogenerator (TENG) and its uses in elastically textile-based energy harvesting and sensing have been demonstrated. The energy-harvesting thread composed by one silicone-rubber-coated stainless-steel thread can extract energy during contact with skin. With sewing the energy-harvesting thread into a serpentine shape on an elastic textile, a highly stretchable and scalable TENG textile is realized to scavenge various kinds of human-motion energy. The collected energy is capable to sustainably power a commercial smart watch. Moreover, the simplified single triboelectric thread can be applied in a wide range of thread-based self-powered and active sensing uses, including gesture sensing, human-interactive interfaces, and human physiological signal monitoring. After integration with microcontrollers, more complicated systems, such as wireless wearable keyboards and smart beds, are demonstrated. These results show that the newly designed single-thread-based TENG, with the advantage of interactive, responsive, sewable, and conformal features, can meet application needs of a vast variety of fields, ranging from wearable and stretchable energy harvesters to smart cloth-based articles.

Single-Thread-Based Wearable and Highly Stretchable Triboelectric Nanogenerators and Their Applications in Cloth-Based Self-Powered Human-Interactive and Biomedical Sensing

KAUST Repository

Lai, Ying-Chih; Deng, Jianan; Zhang, Steven L.; Niu, Simiao; Guo, Hengyu; Wang, Zhong Lin

2016-01-01

The development of wearable and large-area fabric energy harvester and sensor has received great attention due to their promising applications in next-generation autonomous and wearable healthcare technologies. Here, a new type of “single” thread-based triboelectric nanogenerator (TENG) and its uses in elastically textile-based energy harvesting and sensing have been demonstrated. The energy-harvesting thread composed by one silicone-rubber-coated stainless-steel thread can extract energy during contact with skin. With sewing the energy-harvesting thread into a serpentine shape on an elastic textile, a highly stretchable and scalable TENG textile is realized to scavenge various kinds of human-motion energy. The collected energy is capable to sustainably power a commercial smart watch. Moreover, the simplified single triboelectric thread can be applied in a wide range of thread-based self-powered and active sensing uses, including gesture sensing, human-interactive interfaces, and human physiological signal monitoring. After integration with microcontrollers, more complicated systems, such as wireless wearable keyboards and smart beds, are demonstrated. These results show that the newly designed single-thread-based TENG, with the advantage of interactive, responsive, sewable, and conformal features, can meet application needs of a vast variety of fields, ranging from wearable and stretchable energy harvesters to smart cloth-based articles.

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.

An Open Source Software and Web-GIS Based Platform for Airborne SAR Remote Sensing Data Management, Distribution and Sharing

Science.gov (United States)

Changyong, Dou; Huadong, Guo; Chunming, Han; Ming, Liu

2014-03-01

With more and more Earth observation data available to the community, how to manage and sharing these valuable remote sensing datasets is becoming an urgent issue to be solved. The web based Geographical Information Systems (GIS) technology provides a convenient way for the users in different locations to share and make use of the same dataset. In order to efficiently use the airborne Synthetic Aperture Radar (SAR) remote sensing data acquired in the Airborne Remote Sensing Center of the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), a Web-GIS based platform for airborne SAR data management, distribution and sharing was designed and developed. The major features of the system include map based navigation search interface, full resolution imagery shown overlaid the map, and all the software adopted in the platform are Open Source Software (OSS). The functions of the platform include browsing the imagery on the map navigation based interface, ordering and downloading data online, image dataset and user management, etc. At present, the system is under testing in RADI and will come to regular operation soon.

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.

Multi-signalling cation sensing behaviour of a bis(pyridin-2-yl methyl)aniline based hetarylazo dye

International Nuclear Information System (INIS)

Kaur, Paramjit; Sareen, Divya; Kaur, Mandeep; Singh, Kamaljit

2013-01-01

Graphical abstract: The chromogenic and electrochemical behaviour of bis(pyridine-2-yl methyl)aniline based hetarylazo dye gets perturbed in the presence of cations, most effective being Cu 2+ . The conversion of ICT to ICT/MLCT is witnessed by TD-DFT calculations. -- Highlights: •Cation sensing of hetarylazo dye based upon visual, absorption and electrochemical changes is described. •Sensing mechanism is based upon perturbation in intramolecular charge-transfer upon interaction with cations. •Sensing protocol is supported by 1 H NMR studies as well as theoretical calculations. •Hetarylazo dye acts as a multichannel sensor. •Response of the dye towards various cations has also been explored in acidic pH window. -- Abstract: We investigated the cation sensing behaviour of a bis(pyridin-2-yl methyl)aniline appended hetarylazo dye via chromogenic and electrochemical transduction channels. The binding pocket constituting both the pyridyl as well as aniline nitrogen atoms acts as recognition site for the cations and consequent perturbation in the intramolecular charge-transfer prevailing in the dye results in the chromogenic response manifested in the form of hypsochromic shift in the intramolecular charge-transfer band and the attendant naked-eye color changes. The dye exhibits significant changes in its electrochemical behaviour in the presence of cations. The experimental results are also rationalized by time-dependent density functional theory (TD-DFT) calculations

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".

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

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

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.

Robust Initial Wetness Condition Framework of an Event-Based Rainfall–Runoff Model Using Remotely Sensed Soil Moisture

Directory of Open Access Journals (Sweden)

Wooyeon Sunwoo

2017-01-01

Full Text Available Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generation, particularly event-based models, which offer a practical modeling scheme because of their simplicity. However, there is a need to reduce the uncertainties related to the estimation of the initial wetness condition (IWC prior to a rainfall event. Soil moisture is one of the most important variables in rainfall–runoff modeling, and remotely sensed soil moisture is recognized as an effective way to improve the accuracy of runoff prediction. In this study, the IWC was evaluated based on remotely sensed soil moisture by using the Soil Conservation Service-Curve Number (SCS-CN method, which is one of the representative event-based models used for reducing the uncertainty of runoff prediction. Four proxy variables for the IWC were determined from the measurements of total rainfall depth (API5, ground-based soil moisture (SSMinsitu, remotely sensed surface soil moisture (SSM, and soil water index (SWI provided by the advanced scatterometer (ASCAT. To obtain a robust IWC framework, this study consists of two main parts: the validation of remotely sensed soil moisture, and the evaluation of runoff prediction using four proxy variables with a set of rainfall–runoff events in the East Asian monsoon region. The results showed an acceptable agreement between remotely sensed soil moisture (SSM and SWI and ground based soil moisture data (SSMinsitu. In the proxy variable analysis, the SWI indicated the optimal value among the proposed proxy variables. In the runoff prediction analysis considering various infiltration conditions, the SSM and SWI proxy variables significantly reduced the runoff prediction error as compared with API5 by 60% and 66%, respectively. Moreover, the proposed IWC framework with

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)

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

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.

Simultaneous distributed strain and temperature sensing based on combined Raman–Brillouin scattering using Fabry–Perot lasers

International Nuclear Information System (INIS)

Bolognini, Gabriele; Soto, Marcelo A; Di Pasquale, Fabrizio

2010-01-01

An investigation is performed of the possibility of achieving simultaneous distributed strain and temperature sensing based on hybrid Raman–Brillouin scattering with the use of multi-wavelength optical sources such as common Fabry–Perot (FP) lasers. By employing a self-heterodyne detection scheme based on a multi-wavelength optical local oscillator, the benefits of FP lasers are fully exploited, allowing for high-power Raman intensity measurements and a simultaneous high-accuracy detection of the Brillouin frequency shift parameter for each FP longitudinal mode. Experimental results point out a significant reduction of coherent Rayleigh noise, and highlight the enhanced performance in hybrid Raman–Brillouin sensing when using FP lasers; in particular using standard FP lasers at 1550 nm results in about 12 dB (7 dB) temperature (strain) accuracy improvement at 25 km sensing distance with respect to the use of standard distributed feedback lasers

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.

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.

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

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)

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.

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.

Sensing our Environment: Remote sensing in a physics classroom

Science.gov (United States)

Isaacson, Sivan; Schüttler, Tobias; Cohen-Zada, Aviv L.; Blumberg, Dan G.; Girwidz, Raimund; Maman, Shimrit

2017-04-01

Remote sensing is defined as data acquisition of an object, deprived physical contact. Fundamentally, most remote sensing applications are referred to as the use of satellite- or aircraft-based sensor technologies to detect and classify objects mainly on Earth or other planets. In the last years there have been efforts to bring the important subject of remote sensing into schools, however, most of these attempts focused on geography disciplines - restricting to the applications of remote sensing and to a less extent the technique itself and the physics behind it. Optical remote sensing is based on physical principles and technical devices, which are very meaningful from a theoretical point of view as well as for "hands-on" teaching. Some main subjects are radiation, atom and molecular physics, spectroscopy, as well as optics and the semiconductor technology used in modern digital cameras. Thus two objectives were outlined for this project: 1) to investigate the possibilities of using remote sensing techniques in physics teaching, and 2) to identify its impact on pupil's interest in the field of natural sciences. This joint project of the DLR_School_Lab, Oberpfaffenhofen of the German Aerospace Center (DLR) and the Earth and Planetary Image Facility (EPIF) at BGU, was conducted in 2016. Thirty teenagers (ages 16-18) participated in the project and were exposed to the cutting edge methods of earth observation. The pupils on both sides participated in the project voluntarily, knowing that at least some of the project's work had to be done in their leisure time. The pupil's project started with a day at EPIF and DLR respectively, where the project task was explained to the participants and an introduction to remote sensing of vegetation was given. This was realized in lectures and in experimental workshops. During the following two months both groups took several measurements with modern optical remote sensing systems in their home region with a special focus on flora

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.

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

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.

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.

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...

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

Science.gov (United States)

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

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.

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.

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.

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.

Sense about Science--"Making Sense of Radiation" and Understanding Peer Review

Science.gov (United States)

Sierra, Leonor

2011-01-01

Sense About Science is a UK-based charitable trust that equips people to make sense of science and of evidence on issues that matter to society. It was set up in 2003 in response to newspaper front pages being full of headlines about mobile phones "frying your brain", genetically modified "Frankenstein foods", the MMR vaccine,…

Making sense with ePortfolios

DEFF Research Database (Denmark)

Poulsen, Bo Klindt; Dimsits, Miriam

2017-01-01

of the statements from the students concerning their understanding of ePortfolio processes are fundamentally questions of how to make sense of the ePortfolio tool, both in their professional and personal lives. This calls for a didactical stance with the teachers who use ePortfolios, based on empowerment through......This article discusses the question of making sense out of working with ePortfolio in adult education. The article presents the results of a small-scale survey among adults in continuing education who have worked with ePortfolio as the central didactic principle. It is argued that many...... meaning-making, in order for ePortfolios to make sense. It is suggested that two relevant didactic perspectives for making sense of the world can be found in theories of biographicity and metaphor work. Moreover, a strong didactic stance that supports sense-making must be based on a strong teacher role...

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.

Portable, universal, and visual ion sensing platform based on the light emitting diode-based self-referencing-ion selective field-effect transistor.

Science.gov (United States)

Zhang, Xiaowei; Han, Yanchao; Li, Jing; Zhang, Libing; Jia, Xiaofang; Wang, Erkang

2014-02-04

In this work, a novel and universal ion sensing platform was presented, which enables the visual detection of various ions with high sensitivity and selectivity. Coaxial potential signals (millivolt-scale) of the sample from the self-referencing (SR) ion selective chip can be transferred into the ad620-based amplifier with an output of volt-scale potentials. The amplified voltage is high enough to drive a light emitting diode (LED), which can be used as an amplifier and indicator to report the sample information. With this double amplification device (light emitting diode-based self-referencing-ion selective field-effect transistor, LED-SR-ISFET), a tiny change of the sample concentration can be observed with a distinguishable variation of LED brightness by visual inspection. This LED-based luminescent platform provided a facile, low-cost, and rapid sensing strategy without the need of additional expensive chemiluminescence reagent and instruments. Moreover, the SR mode also endows this device excellent stability and reliability. With this innovative design, sensitive determination of K(+), H(+), and Cl(-) by the naked eye was achieved. It should also be noticed that this sensing strategy can easily be extended to other ions (or molecules) by simply integrating the corresponding ion (or molecule) selective electrode.

A new capacitive long-range displacement nanometer sensor with differential sensing structure based on time-grating

Science.gov (United States)

Yu, Zhicheng; Peng, Kai; Liu, Xiaokang; Pu, Hongji; Chen, Ziran

2018-05-01

High-precision displacement sensors, which can measure large displacements with nanometer resolution, are key components in many ultra-precision fabrication machines. In this paper, a new capacitive nanometer displacement sensor with differential sensing structure is proposed for long-range linear displacement measurements based on an approach denoted time grating. Analytical models established using electric field coupling theory and an area integral method indicate that common-mode interference will result in a first-harmonic error in the measurement results. To reduce the common-mode interference, the proposed sensor design employs a differential sensing structure, which adopts a second group of induction electrodes spatially separated from the first group of induction electrodes by a half-pitch length. Experimental results based on a prototype sensor demonstrate that the measurement accuracy and the stability of the sensor are substantially improved after adopting the differential sensing structure. Finally, a prototype sensor achieves a measurement accuracy of  ±200 nm over the full 200 mm measurement range of the sensor.

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.

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

Institute of Scientific and Technical Information of China (English)

无

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.

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.

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

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.

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.

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.

Design and Development Computer-Based E-Learning Teaching Material for Improving Mathematical Understanding Ability and Spatial Sense of Junior High School Students

Science.gov (United States)

Nurjanah; Dahlan, J. A.; Wibisono, Y.

2017-02-01

This paper aims to make a design and development computer-based e-learning teaching material for improving mathematical understanding ability and spatial sense of junior high school students. Furthermore, the particular aims are (1) getting teaching material design, evaluation model, and intrument to measure mathematical understanding ability and spatial sense of junior high school students; (2) conducting trials computer-based e-learning teaching material model, asessment, and instrument to develop mathematical understanding ability and spatial sense of junior high school students; (3) completing teaching material models of computer-based e-learning, assessment, and develop mathematical understanding ability and spatial sense of junior high school students; (4) resulting research product is teaching materials of computer-based e-learning. Furthermore, the product is an interactive learning disc. The research method is used of this study is developmental research which is conducted by thought experiment and instruction experiment. The result showed that teaching materials could be used very well. This is based on the validation of computer-based e-learning teaching materials, which is validated by 5 multimedia experts. The judgement result of face and content validity of 5 validator shows that the same judgement result to the face and content validity of each item test of mathematical understanding ability and spatial sense. The reliability test of mathematical understanding ability and spatial sense are 0,929 and 0,939. This reliability test is very high. While the validity of both tests have a high and very high criteria.

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.

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.

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.

Sensing sense and mobility at the end of the life course

DEFF Research Database (Denmark)

Blaakilde, Anne Leonora

2015-01-01

is struggling with memory loss, which is impeding his life as a retired migrant. The method of embodied interaction is used in order to sense and understand his sensing of the process of mental decline. This is exemplified by three analytic perspectives: touch, embodied map, and materialised mind....... The methodology presented contributes with a focus on understanding based on sensouos theory which implies embodied interaction and an active co-construction of meaning by ethnographer as well as by reader. This chapter's discussion of a methodology that values the senses adds richness to research on the life...

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.

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.

Remote RemoteRemoteRemote sensing potential for sensing ...

African Journals Online (AJOL)

Remote RemoteRemoteRemote sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing p. A Ngie, F Ahmed, K Abutaleb ...

VCSEL-based gigabit IR-UWB link for converged communication and sensing applications in optical metro-access networks

DEFF Research Database (Denmark)

Pham, Tien Thang; Gibbon, Timothy Braidwood; Tafur Monroy, Idelfonso

2012-01-01

We report on experimental demonstration of an impulse radio ultrawideband (IR-UWB) based converged communication and sensing system. A 1550-nm VCSEL-generated IR-UWB signal is used for 2-Gbps wireless data distribution over 800-m and 50-km single mode fiber links which present short-range in-buil...... application, paving the way forward for the development and deployment of converged UWB VCSEL-based technologies in access and in-building networks of the future.......We report on experimental demonstration of an impulse radio ultrawideband (IR-UWB) based converged communication and sensing system. A 1550-nm VCSEL-generated IR-UWB signal is used for 2-Gbps wireless data distribution over 800-m and 50-km single mode fiber links which present short-range in......-building and long-reach access network applications. The IR-UWB signal is also used to simultaneously measure the rotational speed of a blade spinning between 18 and 30 Hz. To the best of our knowledge, this is the very first demonstration of a simultaneous gigabit UWB telecommunication and wireless UWB sensing...

Piezoelectric self-sensing actuator for active vibration control of motorized spindle based on adaptive signal separation

Science.gov (United States)

He, Ye; Chen, Xiaoan; Liu, Zhi; Qin, Yi

2018-06-01

The motorized spindle is the core component of CNC machine tools, and the vibration of it reduces the machining precision and service life of the machine tools. Owing to the fast response, large output force, and displacement of the piezoelectric stack, it is often used as the actuator in the active vibration control of the spindle. A piezoelectric self-sensing actuator (SSA) can reduce the cost of the active vibration control system and simplify the structure by eliminating the use of a sensor, because a SSA can have both actuating and sensing functions at the same time. The signal separation method of a SSA based on a bridge circuit is widely applied because of its simple principle and easy implementation. However, it is difficult to maintain dynamic balance of the circuit. Prior research has used adaptive algorithm to balance of the bridge circuit on the flexible beam dynamically, but those algorithms need no correlation between sensing and control voltage, which limit the applications of SSA in the vibration control of the rotor-bearing system. Here, the electromechanical coupling model of the piezoelectric stack is established, followed by establishment of the dynamic model of the spindle system. Next, a new adaptive signal separation method based on the bridge circuit is proposed, which can separate relative small sensing voltage from related mixed voltage adaptively. The experimental results show that when the self-sensing signal obtained from the proposed method is used as a displacement signal, the vibration of the motorized spindle can be suppressed effectively through a linear quadratic Gaussian (LQG) algorithm.

Real-time monitoring of luminescent lifetime changes of PtOEP oxygen sensing film with LED/photodiode-based time-domain lifetime device.

Science.gov (United States)

Ji, Shaomin; Wu, Wanhua; Wu, Yubo; Zhao, Taiyang; Zhou, Fuke; Yang, Yubin; Zhang, Xin; Liang, Xiaofen; Wu, Wenting; Chi, Lina; Wang, Zhonggang; Zhao, Jianzhang

2009-05-01

A cost-effective LED/photodiode(PD)-based time-domain luminescent lifetime measuring device with rugged electronics and simplified algorithms was assembled and successfully used to characterize oxygen sensing films, by continuously monitoring phosphorescence lifetime changes of phosphorescent platinum octaethylporphyrin (PtOEP) in cardo poly(aryl ether ketone) polymer (IMPEK-C) vs. variation of the oxygen partial pressure in a gas mixture (O(2)/N(2)). The results determined by both phosphorescence lifetime and intensity monitoring were compared and the lifetime mode gave results which are in good agreement with the intensity mode. The lifetime-based linear Stern-Volmer plot indicates that the PtOEP molecules are nearly homogeneously distributed in the sensing film. The phosphorescent lifetime of the PtOEP film changes from 75 micros in neat N(2) to less than 2 micros in neat O(2). The sensing system (by combination of the PtOEP sensing film with the home-assembled lifetime device) gives a high lifetime-based O(2) sensing resolution, e.g. about 2 micros Torr(-1) for low O(2) concentration (below 3.5% O(2), V/V). This feasible lifetime device configuration is affordable to most sensor laboratories and the device may facilitate the study of O(2) sensing material with the continuous lifetime monitoring method.

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...

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.

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.

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.

Three-dimensional sensing methodology combining stereo vision and phase-measuring profilometry based on dynamic programming

Science.gov (United States)

Lee, Hyunki; Kim, Min Young; Moon, Jeon Il

2017-12-01

Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.

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.

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.;

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.

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.

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.

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)

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.

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.

Digital methods and remote sensing in archaeology archaeology in the age of sensing

CERN Document Server

Campana, Stefano

2016-01-01

This volume debuts the new scope of Remote Sensing, which was first defined as the analysis of data collected by sensors that were not in physical contact with the objects under investigation (using cameras, scanners, and radar systems operating from spaceborne or airborne platforms). A wider characterization is now possible: Remote Sensing can be any non-destructive approach to viewing the buried and nominally invisible evidence of past activity. Spaceborne and airborne sensors, now supplemented by laser scanning, are united using ground-based geophysical instruments and undersea remote sensing, as well as other non-invasive techniques such as surface collection or field-walking survey. Now, any method that enables observation of evidence on or beneath the surface of the earth, without impact on the surviving stratigraphy, is legitimately within the realm of Remote Sensing. The new interfaces and senses engaged in Remote Sensing appear throughout the book. On a philosophical level, this is about the landscap...

Sense of Place in Environmental Education

Science.gov (United States)

Kudryavtsev, Alex; Stedman, Richard C.; Krasny, Marianne E.

2012-01-01

Although environmental education research has embraced the idea of sense of place, it has rarely taken into account environmental psychology-based sense of place literature whose theory and empirical studies can enhance related studies in the education context. This article contributes to research on sense of place in environmental education from…

Number sense or working memory? The effect of two computer-based trainings on mathematical skills in elementary school.

Science.gov (United States)

Kuhn, Jörg-Tobias; Holling, Heinz

2014-01-01

Research on the improvement of elementary school mathematics has shown that computer-based training of number sense (e.g., processing magnitudes or locating numbers on the number line) can lead to substantial achievement gains in arithmetic skills. Recent studies, however, have highlighted that training domain-general cognitive abilities (e.g., working memory [WM]) may also improve mathematical achievement. This study addressed the question of whether a training of domain-specific number sense skills or domain-general WM abilities is more appropriate for improving mathematical abilities in elementary school. Fifty-nine children (M age = 9 years, 32 girls and 27 boys) received either a computer-based, adaptive training of number sense (n = 20), WM skills (n = 19), or served as a control group (n = 20). The training duration was 20 min per day for 15 days. Before and after training, we measured mathematical ability using a curriculum-based math test, as well as spatial WM. For both training groups, we observed substantial increases in the math posttest compared to the control group (d = .54 for number sense skills training, d = .57 for WM training, respectively). Whereas the number sense group showed significant gains in arithmetical skills, the WM training group exhibited marginally significant gains in word problem solving. However, no training group showed significant posttest gains on the spatial WM task. Results indicate that a short training of either domain-specific or domain-general skills may result in reliable short-term training gains in math performance, although no stable training effects were found in the spatial WM task.

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

KAUST Repository

Tai, Yanlong

2016-04-12

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(3,4-ethylenedioxythiophene)-polystyrene sulfonate (PEDOT:PSS). How baking conditions influence the self-assembled microstructure of the TCFs is discussed. The sensor presents high-performance properties, including a reasonable sheet resistance (2.1 kohm/sq), a high visible-range transmittance (> 69 %, PET = 90 %), and good stability when subjected to cyclic loading (> 1000 cycles, better than indium tin oxide film) during processing. Moreover, the benefits of these kinds of TCFs were verified through a fully transparent, highly sensitive, rapid response, noncontact moisture-sensing device (5×5 sensing pixels).

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.

A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

Science.gov (United States)

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

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

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

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.

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.

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.

Knowledge-Based Detection and Assessment of Damaged Roads Using Post-Disaster High-Resolution Remote Sensing Image

OpenAIRE

Wang, Jianhua; Qin, Qiming; Zhao, Jianghua; Ye, Xin; Feng, Xiao; Qin, Xuebin; Yang, Xiucheng

2015-01-01

Road damage detection and assessment from high-resolution remote sensing image is critical for natural disaster investigation and disaster relief. In a disaster context, the pairing of pre-disaster and post-disaster road data for change detection and assessment is difficult to achieve due to the mismatch of different data sources, especially for rural areas where the pre-disaster data (i.e., remote sensing imagery or vector map) are hard to obtain. In this study, a knowledge-based method for ...

Space-Based CO2 Active Optical Remote Sensing using 2-μm Triple-Pulse IPDA Lidar

Science.gov (United States)

Singh, Upendra; Refaat, Tamer; Ismail, Syed; Petros, Mulugeta

2017-04-01

Sustained high-quality column CO2 measurements from space are required to improve estimates of regional and global scale sources and sinks to attribute them to specific biogeochemical processes for improving models of carbon-climate interactions and to reduce uncertainties in projecting future change. Several studies show that space-borne CO2 measurements offer many advantages particularly over high altitudes, tropics and southern oceans. Current satellite-based sensing provides rapid CO2 monitoring with global-scale coverage and high spatial resolution. However, these sensors are based on passive remote sensing, which involves limitations such as full seasonal and high latitude coverage, poor sensitivity to the lower atmosphere, retrieval complexities and radiation path length uncertainties. CO2 active optical remote sensing is an alternative technique that has the potential to overcome these limitations. The need for space-based CO2 active optical remote sensing using the Integrated Path Differential Absorption (IPDA) lidar has been advocated by the Advanced Space Carbon and Climate Observation of Planet Earth (A-Scope) and Active Sensing of CO2 Emission over Nights, Days, and Seasons (ASCENDS) studies in Europe and the USA. Space-based IPDA systems can provide sustained, high precision and low-bias column CO2 in presence of thin clouds and aerosols while covering critical regions such as high latitude ecosystems, tropical ecosystems, southern ocean, managed ecosystems, urban and industrial systems and coastal systems. At NASA Langley Research Center, technology developments are in progress to provide high pulse energy 2-μm IPDA that enables optimum, lower troposphere weighted column CO2 measurements from space. This system provides simultaneous ranging; information on aerosol and cloud distributions; measurements over region of broken clouds; and reduces influences of surface complexities. Through the continual support from NASA Earth Science Technology Office

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

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.

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

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.

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.

How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods

Science.gov (United States)

C. Alina Cansler; Donald. McKenzie

2012-01-01

Remotely sensed indices of burn severity are now commonly used by researchers and land managers to assess fire effects, but their relationship to field-based assessments of burn severity has been evaluated only in a few ecosystems. This analysis illustrates two cases in which methodological refinements to field-based and remotely sensed indices of burn severity...

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

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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

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.

Vertical Jump Height Estimation Algorithm Based on Takeoff and Landing Identification Via Foot-Worn Inertial Sensing.

Science.gov (United States)

Wang, Jianren; Xu, Junkai; Shull, Peter B

2018-03-01

Vertical jump height is widely used for assessing motor development, functional ability, and motor capacity. Traditional methods for estimating vertical jump height rely on force plates or optical marker-based motion capture systems limiting assessment to people with access to specialized laboratories. Current wearable designs need to be attached to the skin or strapped to an appendage which can potentially be uncomfortable and inconvenient to use. This paper presents a novel algorithm for estimating vertical jump height based on foot-worn inertial sensors. Twenty healthy subjects performed countermovement jumping trials and maximum jump height was determined via inertial sensors located above the toe and under the heel and was compared with the gold standard maximum jump height estimation via optical marker-based motion capture. Average vertical jump height estimation errors from inertial sensing at the toe and heel were -2.2±2.1 cm and -0.4±3.8 cm, respectively. Vertical jump height estimation with the presented algorithm via inertial sensing showed excellent reliability at the toe (ICC(2,1)=0.98) and heel (ICC(2,1)=0.97). There was no significant bias in the inertial sensing at the toe, but proportional bias (b=1.22) and fixed bias (a=-10.23cm) were detected in inertial sensing at the heel. These results indicate that the presented algorithm could be applied to foot-worn inertial sensors to estimate maximum jump height enabling assessment outside of traditional laboratory settings, and to avoid bias errors, the toe may be a more suitable location for inertial sensor placement than the heel.

Discrete Wigner Function Reconstruction and Compressed Sensing

OpenAIRE

Zhang, Jia-Ning; Fang, Lei; Ge, Mo-Lin

2011-01-01

A new reconstruction method for Wigner function is reported for quantum tomography based on compressed sensing. By analogy with computed tomography, Wigner functions for some quantum states can be reconstructed with less measurements utilizing this compressed sensing based method.

Metal-Organic Framework Thin Film Coated Optical Fiber Sensors: A Novel Waveguide-Based Chemical Sensing Platform.

Science.gov (United States)

Kim, Ki-Joong; Lu, Ping; Culp, Jeffrey T; Ohodnicki, Paul R

2018-02-23

Integration of optical fiber with sensitive thin films offers great potential for the realization of novel chemical sensing platforms. In this study, we present a simple design strategy and high performance of nanoporous metal-organic framework (MOF) based optical gas sensors, which enables detection of a wide range of concentrations of small molecules based upon extremely small differences in refractive indices as a function of analyte adsorption within the MOF framework. Thin and compact MOF films can be uniformly formed and tightly bound on the surface of etched optical fiber through a simple solution method which is critical for manufacturability of MOF-based sensor devices. The resulting sensors show high sensitivity/selectivity to CO 2 gas relative to other small gases (H 2 , N 2 , O 2 , and CO) with rapid (optical fiber platform which results in an amplification of inherent optical absorption present within the MOF-based sensing layer with increasing values of effective refractive index associated with adsorption of gases.

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,

Designing sparse sensing matrix for compressive sensing to reconstruct high resolution medical images

Directory of Open Access Journals (Sweden)

Vibha Tiwari

2015-12-01

Full Text Available Compressive sensing theory enables faithful reconstruction of signals, sparse in domain $ \\Psi $, at sampling rate lesser than Nyquist criterion, while using sampling or sensing matrix $ \\Phi $ which satisfies restricted isometric property. The role played by sensing matrix $ \\Phi $ and sparsity matrix $ \\Psi $ is vital in faithful reconstruction. If the sensing matrix is dense then it takes large storage space and leads to high computational cost. In this paper, effort is made to design sparse sensing matrix with least incurred computational cost while maintaining quality of reconstructed image. The design approach followed is based on sparse block circulant matrix (SBCM with few modifications. The other used sparse sensing matrix consists of 15 ones in each column. The medical images used are acquired from US, MRI and CT modalities. The image quality measurement parameters are used to compare the performance of reconstructed medical images using various sensing matrices. It is observed that, since Gram matrix of dictionary matrix ($ \\Phi \\Psi \\mathrm{} $ is closed to identity matrix in case of proposed modified SBCM, therefore, it helps to reconstruct the medical images of very good quality.

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

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 4 : web-based bridge information database--visualization analytics and distributed sensing.

Science.gov (United States)

2012-03-01

This report introduces the design and implementation of a Web-based bridge information visual analytics system. This : project integrates Internet, multiple databases, remote sensing, and other visualization technologies. The result : combines a GIS ...

Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

Directory of Open Access Journals (Sweden)

PENG Gang

2014-12-01

Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

Remote Sensing and Reflectance Profiling in Entomology.

Science.gov (United States)

Nansen, Christian; Elliott, Norman

2016-01-01

Remote sensing describes the characterization of the status of objects and/or the classification of their identity based on a combination of spectral features extracted from reflectance or transmission profiles of radiometric energy. Remote sensing can be benchtop based, and therefore acquired at a high spatial resolution, or airborne at lower spatial resolution to cover large areas. Despite important challenges, airborne remote sensing technologies will undoubtedly be of major importance in optimized management of agricultural systems in the twenty-first century. Benchtop remote sensing applications are becoming important in insect systematics and in phenomics studies of insect behavior and physiology. This review highlights how remote sensing influences entomological research by enabling scientists to nondestructively monitor how individual insects respond to treatments and ambient conditions. Furthermore, novel remote sensing technologies are creating intriguing interdisciplinary bridges between entomology and disciplines such as informatics and electrical engineering.

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.

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.

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)

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.

Divided Attention and Processes Underlying Sense of Agency

Directory of Open Access Journals (Sweden)

Wen eWen

2016-01-01

Full Text Available Sense of agency refers to the subjective feeling of controlling events through one’s behavior or will. Sense of agency results from matching predictions of one’s own actions with actual feedback regarding the action. Furthermore, when an action involves a cued goal, performance-based inference contributes to sense of agency. That is, if people achieve their goal, they would believe themselves to be in control. Previous studies have shown that both action-effect comparison and performance-based inference contribute to sense of agency; however, the dominance of one process over the other may shift based on task conditions such as the presence or absence of specific goals. In this study, we examined the influence of divided attention on these two processes underlying sense of agency in two conditions. In the experimental task, participants continuously controlled a moving dot for 10 s while maintaining a string of three or seven digits in working memory. We found that when there was no cued goal (no-cued-goal condition, sense of agency was impaired by high cognitive load. Contrastingly, when participants controlled the dot based on a cued goal (cued-goal-directed condition, their sense of agency was lower than in the no-cued-goal condition and was not affected by cognitive load. The results suggest that the action-effect comparison process underlying sense of agency requires attention. On the other hand, the weaker influence of divided attention in the cued-goal-directed condition could be attributed to the dominance of performance-based inference, which is probably automatic.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

Science.gov (United States)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Community Based Informatics: Geographical Information Systems, Remote Sensing and Ontology collaboration - A technical hands-on approach

Science.gov (United States)

Branch, B. D.; Raskin, R. G.; Rock, B.; Gagnon, M.; Lecompte, M. A.; Hayden, L. B.

2009-12-01

With the nation challenged to comply with Executive Order 12906 and its needs to augment the Science, Technology, Engineering and Mathematics (STEM) pipeline, applied focus on geosciences pipelines issue may be at risk. The Geosciences pipeline may require intentional K-12 standard course of study consideration in the form of project based, science based and evidenced based learning. Thus, the K-12 to geosciences to informatics pipeline may benefit from an earth science experience that utilizes a community based “learning by doing” approach. Terms such as Community GIS, Community Remotes Sensing, and Community Based Ontology development are termed Community Informatics. Here, approaches of interdisciplinary work to promote and earth science literacy are affordable, consisting of low cost equipment that renders GIS/remote sensing data processing skills necessary in the workforce. Hence, informal community ontology development may evolve or mature from a local community towards formal scientific community collaboration. Such consideration may become a means to engage educational policy towards earth science paradigms and needs, specifically linking synergy among Math, Computer Science, and Earth Science disciplines.

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

Best practices in Remote Sensing for REDD+

DEFF Research Database (Denmark)

Dons, Klaus; Grogan, Kenneth

2012-01-01

due to steep terrain, • phenological gradients across natural, agricultural and forestry ecosystems including plantations and • the need to serve the REDD-specific context of deforestation and forest degradation across spatial and temporal scales make remote sensing based approaches particularly...... be expected from remote sensing imagery and the provided information shall help to better anticipate problems that will be encountered when acquiring, analyzing and interpreting remote sensing data. Beyond remote sensing, it may be a good point of departure for a large group of scientists with a diverse...... and governance, and deforestation and forest degradation processes. The second part summarizes the available literature on remote sensing based good practices for REDD. It largely draws from the documents of the Intergovernmental Panel on Climate Change (IPCC), the United Nations Framework Convention on Climate...

Remote sensing observation used in offshore wind energy

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Pena Diaz, Alfredo; Christiansen, Merete Bruun

2008-01-01

Remote sensing observations used in offshore wind energy are described in three parts: ground-based techniques and applications, airborne techniques and applications, and satellite-based techniques and applications. Ground-based remote sensing of winds is relevant, in particular, for new large wind...

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.

A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

Directory of Open Access Journals (Sweden)

Jorge Sá Silva

2012-02-01

Full Text Available As the Internet evolved, social networks (such as Facebook have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype.

A Web Service-based framework model for people-centric sensing applications applied to social networking.

Science.gov (United States)

Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

2012-01-01

As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

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

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.

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

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

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

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.

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.

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.

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.

A Novel Physical Sensing Principle for Liquid Characterization Using Paper-Based Hygro-Mechanical Systems (PB-HMS).

Science.gov (United States)

Perez-Cruz, Angel; Stiharu, Ion; Dominguez-Gonzalez, Aurelio

2017-07-20

In recent years paper-based microfluidic systems have emerged as versatile tools for developing sensors in different areas. In this work; we report a novel physical sensing principle for the characterization of liquids using a paper-based hygro-mechanical system (PB-HMS). The PB-HMS is formed by the interaction of liquid droplets and paper-based mini-structures such as cantilever beams. The proposed principle takes advantage of the hygroscopic properties of paper to produce hygro-mechanical motion. The dynamic response of the PB-HMS reveals information about the tested liquid that can be applied to characterize certain properties of liquids. A suggested method to characterize liquids by means of the proposed principle is introduced. The experimental results show the feasibility of such a method. It is expected that the proposed principle may be applied to sense properties of liquids in different applications where both disposability and portability are of extreme importance.

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.

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

Science.gov (United States)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

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

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

Self-Sensing Control of Nafion-Based Ionic Polymer-Metal Composite (IPMC Actuator in the Extremely Low Humidity Environment

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Minoru Sasaki

2013-10-01

Full Text Available This paper presents feedforward, feedback and two-degree-of-freedom control applied to an Ionic Polymer-Metal Composite (IPMC actuator. It presents a high potential for development of miniature robots and biomedical devices and artificial muscles. We have reported in the last few years that dehydration treatment improves the electrical controllability of bending in Selemion CMV-based IPMCs. We tried to replicate this controllability in Nafion-based IPMC. We found that the displacement of a Nafion-based IPMC was proportional to the total charge imposed, just as in the Selemion-CMV case. This property is the basis of self-sensing controllers for Nafion-based IPMC bending behavior: we perform bending curvature experiments on Nafion-based IPMCs, obtaining the actuator's dynamics and transfer function. From these, we implemented self-sensing controllers using feedforward, feedback and two-degree-of-freedom techniques. All three controllers performed very well with the Nafion-based IPMC actuator.

Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler

Energy Technology Data Exchange (ETDEWEB)

Aditya Kumar

2010-12-30

This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

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Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

2017-09-08

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

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.

The Importance of Sensing Own's Movements in the World for the Sense of Personal Identity

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Mariana Broens

2012-01-01

Full Text Available Within philosophy and cognitive science, the focus in relation to the problem of personal identity has been almost exclusively on the brain. We submit that the resulting neglect of the body and of bodily movements in the world has been detrimental in understanding how organisms develop a sense of identity. We examine the importance of sensing one’s own movements for the development of a basic, nonconceptual sense of self. More specifically, we argue that the origin of the sense of self stems from the sensitivity to spontaneous movements. Based on this, the organism develops a sense of “I move” and, finally, a sense of “I can move”. Proprioception and kinesthesis are essential in this development. At the same time, we argue against the traditional dichotomy between so-called external and internal senses, agreeing with Gibson that perception of the self and of the environment invariably go together. We discuss a traditional distinction between two aspects of bodily self: the body sense and the body image. We suggest that they capture different aspects of the sense of self. We argue that especially the body sense is of great importance to our nonconceptual sense of self. Finally, we attempt to draw some consequences for research in cognitive science, specifically in the area of robotics, by examining a case of missing proprioception. We make a plea for robots to be equipped not just with external perceptual and motor abilities but also with a sense of proprioception. This, we submit, would constitute one further step towards understanding creatures acting in the world with a sense of themselves.

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

Bioinspired Infrared Sensing Materials and Systems.

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Shen, Qingchen; Luo, Zhen; Ma, Shuai; Tao, Peng; Song, Chengyi; Wu, Jianbo; Shang, Wen; Deng, Tao

2018-05-11

Bioinspired engineering offers a promising alternative approach in accelerating the development of many man-made systems. Next-generation infrared (IR) sensing systems can also benefit from such nature-inspired approach. The inherent compact and uncooled operation of biological IR sensing systems provides ample inspiration for the engineering of portable and high-performance artificial IR sensing systems. This review overviews the current understanding of the biological IR sensing systems, most of which are thermal-based IR sensors that rely on either bolometer-like or photomechanic sensing mechanism. The existing efforts inspired by the biological IR sensing systems and possible future bioinspired approaches in the development of new IR sensing systems are also discussed in the review. Besides these biological IR sensing systems, other biological systems that do not have IR sensing capabilities but can help advance the development of engineered IR sensing systems are also discussed, and the related engineering efforts are overviewed as well. Further efforts in understanding the biological IR sensing systems, the learning from the integration of multifunction in biological systems, and the reduction of barriers to maximize the multidiscipline collaborations are needed to move this research field forward. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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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.

FRACTAL DIMENSION OF URBAN EXPANSION BASED ON REMOTE SENSING IMAGES

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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.

Actin-based gravity-sensing mechanisms in unicellular plant model systems

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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.

Multi-resource data-based research on remote sensing monitoring over the green tide in the Yellow Sea

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Gao, Zhiqiang; Xu, Fuxiang; Song, Debin; Zheng, Xiangyu; Chen, Maosi

2017-09-01

This paper conducted dynamic monitoring over the green tide (large green alga—Ulva prolifera) occurred in the Yellow Sea in 2014 to 2016 by the use of multi-source remote sensing data, including GF-1 WFV, HJ-1A/1B CCD, CBERS-04 WFI, Landsat-7 ETM+ and Landsta-8 OLI, and by the combination of VB-FAH (index of Virtual-Baseline Floating macroAlgae Height) with manual assisted interpretation based on remote sensing and geographic information system technologies. The result shows that unmanned aerial vehicle (UAV) and shipborne platform could accurately monitor the distribution of Ulva prolifera in small spaces, and therefore provide validation data for the result of remote sensing monitoring over Ulva prolifera. The result of this research can provide effective information support for the prevention and control of Ulva prolifera.

A flavone-based turn-on fluorescent probe for intracellular cysteine/homocysteine sensing with high selectivity.

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Zhang, Jian; Lv, Yanlin; Zhang, Wei; Ding, Hui; Liu, Rongji; Zhao, Yongsheng; Zhang, Guangjin; Tian, Zhiyuan

2016-01-01

A new type of flavone-based fluorescent probe (DMAF) capable of cysteine (Cys)/homocysteine (Hcy) sensing with high selectivity over other amino acids was developed. Such type of probe undergoes Cys/Hcy-mediated cyclization reaction with the involvement of its aldehyde group, which suppresses of the photoinduced electron transfer (PET) process of the probe molecule and consequently leads to the enhancement of fluorescence emission upon excitation using visible light. The formation of product of the Cys/Hcy-mediated cyclization reaction was confirmed and the preliminary fluorescence imaging experiments revealed the biocompatibility of the as-prepared probe and validated its practicability for intracellular Cys/Hcy sensing. Copyright © 2015 Elsevier B.V. All rights reserved.

Fluorometric sensing of Triton X-100 based organized media in water by a MOF

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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.

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.

Orthogonality-breaking sensing model based on the instantaneous Stokes vector and the Mueller calculus

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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.

A highly selective fluorescence sensing platform for nanomolar Hg(II) detection based on cytosine derived quantum dot

Science.gov (United States)

Luo, Liang; Song, Ting; Wang, Haoqiang; Yuan, Qunhui; Zhou, Shenghai

2018-03-01

Inspired by low toxicity and good biocompatibility of biomass derived quantum dot (QD), we herein developed a cytosine derived quantum dot, namely cyt-dot, via a one-step hydrothermal synthesis. The as-prepared cyt-dot emits blue fluorescence (FL) containing abundant oxygen (20.6 at.%) and nitrogen (24.1 at.%) contents. The cyt-dot based sensing platform shows exclusive selectivity for Hg(II) while being insensitive towards Fe(III) and Ag(I), which are important interference that usually cannot be ruled out. The detection limit for Hg(II) is of 11 nM, which is very close to the guideline value of 10 nM allowed by the U.S. Environmental Protection Agency in drinking water. In real water sample analyses, the present sensing platform can fulfil satisfied recoveries ranging from 100% to 108%. Besides, the acidity of solution has almost no effect on the sensing performance of the cyt-dot in a pH range of 5-8, suggesting its potential applications in sensing and bio-imaging.

Influence of Graphene Nanosheets on Rheology, Microstructure, Strength Development and Self-Sensing Properties of Cement Based Composites

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Sardar Kashif Ur Rehman

2018-03-01

Full Text Available In this research, Graphene oxide (GO, prepared by modified hammer method, is characterized using X-ray Diffraction (XRD, Fourier Transform Infrared (FT-IR Spectrometry and Raman spectra. The dispersion efficiency of GO in aqueous solution is examined by Ultraviolet–visible spectroscopy and it is found that GO sheets are well dispersed. Thereafter, rheological properties, flow diameter, hardened density, compressive strength and electrical properties of GO based cement composite are investigated by incorporating 0.03% GO in cement matrix. The reasons for improvement in strength are also discussed. Rheological results confirm that GO influenced the flow behavior and enhanced the viscosity of the cement based system. From XRD and Thermogravimetric Analysis (TGA results, it is found that more hydration occurred when GO was incorporated in cement based composite. The GO based cement composite improves the compressive strength and density of mortar by 27% and 1.43%, respectively. Electrical properties results showed that GO–cement based composite possesses self-sensing characteristics. Hence, GO is a potential nano-reinforcement candidate and can be used as self-sensing sustainable construction material.

IDENTIFICATION OF THE main HONEY CROPS BASED on remote sensing data

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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.

A Wireless Swing Angle Measurement Scheme Using Attitude Heading Reference System Sensing Units Based on Microelectromechanical Devices

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Bingtuan Gao

2014-11-01

Full Text Available Feasible real-time swing angle measurement is significant to improve the efficiency and safety of industrial crane systems. This paper presents a wireless microelectromechanical system (MEMS-based swing angle measurement system. The system consists of two attitude heading reference system (AHRS sensing units with a wireless communication function, which are mounted on the hook (or payload and the jib (or base of the crane, respectively. With a combination of a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, the standard extended Kalman filter (EKF is used to estimate the desired orientation of the payload and the base. Wireless ZigBee communication is employed to transmit the orientation of the payload to the sensing unit mounted on the base, which measures the orientation of the base. Because several physical parameters from the payload to the base can be acquired from the original crane control system, the swing angles of the payload can be calculated based on the two measured orientation parameters together with the known physical parameters. Experiments were performed to show the feasibility and effectiveness of the proposed swing angle measurement system.

Developing the remote sensing-based water environmental model for monitoring alpine river water environment over Plateau cold zone

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You, Y.; Wang, S.; Yang, Q.; Shen, M.; Chen, G.

2017-12-01

Alpine river water environment on the Plateau (such as Tibetan Plateau, China) is a key indicator for water security and environmental security in China. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. In this study some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a), water turbidity (WT) or water clarity (SD), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC)) over the china's southwest highland rivers, such as the Brahmaputra. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based on various types of satellite data, at first we developed the techniques of multi-sensor data correction, atmospheric correction. Second, we also built the inversion spectral database derived from long-term remote sensing data and field sampling data. Then we have studied and developed a high-precision inversion model over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration. Third, take the middle reaches of the Brahmaputra river as the study area, we validated the key

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.

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.

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.

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.

AIE-doped poly(ionic liquid) photonic spheres: a single sphere-based customizable sensing platform for the discrimination of multi-analytes.

Science.gov (United States)

Zhang, Wanlin; Gao, Ning; Cui, Jiecheng; Wang, Chen; Wang, Shiqiang; Zhang, Guanxin; Dong, Xiaobiao; Zhang, Deqing; Li, Guangtao

2017-09-01

By simultaneously exploiting the unique properties of ionic liquids and aggregation-induced emission (AIE) luminogens, as well as photonic structures, a novel customizable sensing system for multi-analytes was developed based on a single AIE-doped poly(ionic liquid) photonic sphere. It was found that due to the extraordinary multiple intermolecular interactions involved in the ionic liquid units, one single sphere could differentially interact with broader classes of analytes, thus generating response patterns with remarkable diversity. Moreover, the optical properties of both the AIE luminogen and photonic structure integrated in the poly(ionic liquid) sphere provide multidimensional signal channels for transducing the involved recognition process in a complementary manner and the acquisition of abundant and sufficient sensing information could be easily achieved on only one sphere sensor element. More importantly, the sensing performance of our poly(ionic liquid) photonic sphere is designable and customizable through a simple ion-exchange reaction and target-oriented multi-analyte sensing can be conveniently realized using a selective receptor species, such as counterions, showing great flexibility and extendibility. The power of our single sphere-based customizable sensing system was exemplified by the successful on-demand detection and discrimination of four multi-analyte challenge systems: all 20 natural amino acids, nine important phosphate derivatives, ten metal ions and three pairs of enantiomers. To further demonstrate the potential of our spheres for real-life application, 20 amino acids in human urine and their 26 unprecedented complex mixtures were also discriminated between by the single sphere-based array.

Commercial future: making remote sensing a media event

Science.gov (United States)

Lurie, Ian

1999-12-01

The rapid growth of commercial remote sensing has made high quality digital sensing data widely available -- now, remote sensing must become and remain a strong, commercially viable industry. However, this new industry cannot survive without an educated consumer base. To access markets, remote sensing providers must make their product more accessible, both literally and figuratively: Potential customers must be able to find the data they require, when they require it, and they must understand the utility of the information available to them. The Internet and the World Wide Web offer the perfect medium to educate potential customers and to sell remote sensing data to those customers. A well-designed web presence can provide both an information center and a market place for companies offering their data for sale. A very high potential web-based market for remote sensing lies in media. News agencies, web sites, and a host of other visual media services can use remote sensing data to provide current, relevant information regarding news around the world. This paper will provide a model for promotion and sale of remote sensing data via the Internet.

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

Science.gov (United States)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

Piezoelectric self sensing actuators for high voltage excitation

International Nuclear Information System (INIS)

Grasso, E; Totaro, N; Janocha, H; Naso, D

2013-01-01

Self sensing techniques allow the use of a piezoelectric transducer simultaneously as an actuator and as a sensor. Such techniques are based on knowledge of the transducer behaviour and on measurements of electrical quantities, in particular voltage and charge. Past research work has mainly considered the linear behaviour of piezoelectric transducers, consequently restricting the operating driving voltages to low values. In this work a new self sensing technique is proposed which is able to perform self sensing reconstruction both at low and at high driving voltages. This technique, in fact, makes use of a hysteretic model to describe the nonlinear piezoelectric capacitance necessary for self sensing reconstruction. The capacitance can be measured and identified at the antiresonances of a vibrating structure with a good approximation. After providing a mathematical background to deal with the main aspects of self sensing, this technique is compared theoretically and experimentally to a typical linear one by using an aluminum plate with one bonded self sensing transducer and a positive position feedback (PPF) controller to verify the performance in self sensing based vibration control. (paper)

Ground-Based Remote Sensing of Volcanic CO2 Fluxes at Solfatara (Italy—Direct Versus Inverse Bayesian Retrieval

Directory of Open Access Journals (Sweden)

Manuel Queißer

2018-01-01

Full Text Available CO2 is the second most abundant volatile species of degassing magma. CO2 fluxes carry information of incredible value, such as periods of volcanic unrest. Ground-based laser remote sensing is a powerful technique to measure CO2 fluxes in a spatially integrated manner, quickly and from a safe distance, but it needs accurate knowledge of the plume speed. The latter is often difficult to estimate, particularly for complex topographies. So, a supplementary or even alternative way of retrieving fluxes would be beneficial. Here, we assess Bayesian inversion as a potential technique for the case of the volcanic crater of Solfatara (Italy, a complex terrain hosting two major CO2 degassing fumarolic vents close to a steep slope. Direct integration of remotely sensed CO2 concentrations of these vents using plume speed derived from optical flow analysis yielded a flux of 717 ± 121 t day−1, in agreement with independent measurements. The flux from Bayesian inversion based on a simple Gaussian plume model was in excellent agreement under certain conditions. In conclusion, Bayesian inversion is a promising retrieval tool for CO2 fluxes, especially in situations where plume speed estimation methods fail, e.g., optical flow for transparent plumes. The results have implications beyond volcanology, including ground-based remote sensing of greenhouse gases and verification of satellite soundings.

Graphene/Gold Nano composites-Based Thin Films as an Enhanced Sensing Platform for Voltammetric Detection of Cr(VI) Ions

International Nuclear Information System (INIS)

Santhosh, Ch.; Saranya, M.; Ramachandran, R.; Felix, S.; Velmurugan, V.; Grace, A.N.

2014-01-01

A highly sensitive and selective Cr(VI) sensor with graphene-based nano composites film as an enhanced sensing platform is reported. The detection of chromium species is a challenging task because of the different possible oxidation states in which the element can occur. The sensing film was developed by homogeneously distributing Au nanoparticles (AuNPs) onto the two-dimensional (2D) graphene nano sheet matrix by electrochemical method. Such nano structured composite film platforms combine the advantages of AuNPs and graph ene nano sheets because of the synergistic effect between them. This effect greatly facilitates the electron-transfer processes and the sensing behavior for Cr(VI) detection, leading to a remarkably improved sensitivity and selectivity. The interference from other heavy metal ions is studied in detail. Such sensing elements are very promising for practical environmental monitoring applications.

[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.

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.

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.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

Science.gov (United States)

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

Science.gov (United States)

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform.

Science.gov (United States)

Dao, Nhu-Ngoc; Park, Minho; Kim, Joongheon; Cho, Sungrae

2017-01-01

As an important part of IoTization trends, wireless sensing technologies have been involved in many fields of human life. In cellular network evolution, the long term evolution advanced (LTE-A) networks including machine-type communication (MTC) features (named LTE-M) provide a promising infrastructure for a proliferation of Internet of things (IoT) sensing platform. However, LTE-M may not be optimally exploited for directly supporting such low-data-rate devices in terms of energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. Focusing on this circumstance, we propose a novel adaptive modulation and coding selection (AMCS) algorithm to address the energy consumption problem in the LTE-M based IoT-sensing platform. The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. In addition, a quantity-oriented resource planning (QORP) technique that utilizes these optimal MCS levels as main criteria for spectrum allocation has been proposed for better adapting to the sensing node requirements. The simulation results reveal that the proposed approach significantly reduces the energy consumption of IoT sensing nodes and #PRBs up to 23.09% and 25.98%, respectively.

Optical ph sensing material prepared from doped sol-gel film for use in acid-base titration

OpenAIRE

Musa Ahmad; T.W. Tan

2017-01-01

An optical pH sensing material has been prepared in this study by using sol-gel technique. Bromothymol blue, bromophenol blue and thymol blue were chosen in this study as acidbase indicators for strong acid-strong base, strong acid-weak base and weak acid-strong base titration, respectively. The results show that these indicators could be successfully entrapped inside the sol-gel film and still maintain its chemical behaviour as in solution. The entrapped acid-base indicators respond well to ...

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...

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.

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.

VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls

Science.gov (United States)

Kim, Byoungjip; Kang, Seungwoo; Ha, Jin-Young; Song, Junehwa

2015-01-01

In this paper, we introduce a novel smartphone framework called VisitSense that automatically detects and predicts a smartphone user’s place visits from ambient radio to enable behavioral targeting for mobile ads in large shopping malls. VisitSense enables mobile app developers to adopt visit-pattern-aware mobile advertising for shopping mall visitors in their apps. It also benefits mobile users by allowing them to receive highly relevant mobile ads that are aware of their place visit patterns in shopping malls. To achieve the goal, VisitSense employs accurate visit detection and prediction methods. For accurate visit detection, we develop a change-based detection method to take into consideration the stability change of ambient radio and the mobility change of users. It performs well in large shopping malls where ambient radio is quite noisy and causes existing algorithms to easily fail. In addition, we proposed a causality-based visit prediction model to capture the causality in the sequential visit patterns for effective prediction. We have developed a VisitSense prototype system, and a visit-pattern-aware mobile advertising application that is based on it. Furthermore, we deploy the system in the COEX Mall, one of the largest shopping malls in Korea, and conduct diverse experiments to show the effectiveness of VisitSense. PMID:26193275

VisitSense: Sensing Place Visit Patterns from Ambient Radio on Smartphones for Targeted Mobile Ads in Shopping Malls.

Science.gov (United States)

Kim, Byoungjip; Kang, Seungwoo; Ha, Jin-Young; Song, Junehwa

2015-07-16

In this paper, we introduce a novel smartphone framework called VisitSense that automatically detects and predicts a smartphone user's place visits from ambient radio to enable behavioral targeting for mobile ads in large shopping malls. VisitSense enables mobile app developers to adopt visit-pattern-aware mobile advertising for shopping mall visitors in their apps. It also benefits mobile users by allowing them to receive highly relevant mobile ads that are aware of their place visit patterns in shopping malls. To achieve the goal, VisitSense employs accurate visit detection and prediction methods. For accurate visit detection, we develop a change-based detection method to take into consideration the stability change of ambient radio and the mobility change of users. It performs well in large shopping malls where ambient radio is quite noisy and causes existing algorithms to easily fail. In addition, we proposed a causality-based visit prediction model to capture the causality in the sequential visit patterns for effective prediction. We have developed a VisitSense prototype system, and a visit-pattern-aware mobile advertising application that is based on it. Furthermore, we deploy the system in the COEX Mall, one of the largest shopping malls in Korea, and conduct diverse experiments to show the effectiveness of VisitSense.

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

Synthesis and Characterization of Highly Sensitive Hydrogen (H2 Sensing Device Based on Ag Doped SnO2 Nanospheres

Directory of Open Access Journals (Sweden)

Zhaorui Lu

2018-03-01

Full Text Available In this paper, pure and Ag-doped SnO2 nanospheres were synthesized by hydrothermal method and characterized via X-ray powder diffraction (XRD, field emission scanning electron microscopy (FESEM, energy dispersive spectroscopy (EDS, and X-ray photoelectron spectra (XPS, respectively. The gas sensing performance of the pure, 1 at.%, 3 at.%, and 5 at.% Ag-doped SnO2 sensing devices toward hydrogen (H2 were systematically evaluated. The results indicated that compared with pure SnO2 nanospheres, Ag-doped SnO2 nanospheres could not only decrease the optimum working temperature but also significantly improve H2 sensing such as higher gas response and faster response-recovery. Among all the samples, the 3 at.% Ag-doped SnO2 showed the highest response 39 to 100 μL/L H2 at 300 °C. Moreover, its gas sensing mechanism was discussed, and the results will provide reference and theoretical guidance for the development of high-performance SnO2-based H2 sensing devices.

Tracking Control of Shape-Memory-Alloy Actuators Based on Self-Sensing Feedback and Inverse Hysteresis Compensation

Directory of Open Access Journals (Sweden)

Shu-Hung Liu

2009-12-01

Full Text Available Shape memory alloys (SMAs offer a high power-to-weight ratio, large recovery strain, and low driving voltages, and have thus attracted considerable research attention. The difficulty of controlling SMA actuators arises from their highly nonlinear hysteresis and temperature dependence. This paper describes a combination of self-sensing and model-based control, where the model includes both the major and minor hysteresis loops as well as the thermodynamics effects. The self-sensing algorithm uses only the power width modulation (PWM signal and requires no heavy equipment. The method can achieve high-accuracy servo control and is especially suitable for miniaturized applications.

Throughput Maximization Using an SVM for Multi-Class Hypothesis-Based Spectrum Sensing in Cognitive Radio

Directory of Open Access Journals (Sweden)

Sana Ullah Jan

2018-03-01

Full Text Available A framework of spectrum sensing with a multi-class hypothesis is proposed to maximize the achievable throughput in cognitive radio networks. The energy range of a sensing signal under the hypothesis that the primary user is absent (in a conventional two-class hypothesis is further divided into quantized regions, whereas the hypothesis that the primary user is present is conserved. The non-radio frequency energy harvesting-equiped secondary user transmits, when the primary user is absent, with transmission power based on the hypothesis result (the energy level of the sensed signal and the residual energy in the battery: the lower the energy of the received signal, the higher the transmission power, and vice versa. Conversely, the lower is the residual energy in the node, the lower is the transmission power. This technique increases the throughput of a secondary link by providing a higher number of transmission events, compared to the conventional two-class hypothesis. Furthermore, transmission with low power for higher energy levels in the sensed signal reduces the probability of interference with primary users if, for instance, detection was missed. The familiar machine learning algorithm known as a support vector machine (SVM is used in a one-versus-rest approach to classify the input signal into predefined classes. The input signal to the SVM is composed of three statistical features extracted from the sensed signal and a number ranging from 0 to 100 representing the percentage of residual energy in the node’s battery. To increase the generalization of the classifier, k-fold cross-validation is utilized in the training phase. The experimental results show that an SVM with the given features performs satisfactorily for all kernels, but an SVM with a polynomial kernel outperforms linear and radial-basis function kernels in terms of accuracy. Furthermore, the proposed multi-class hypothesis achieves higher throughput compared to the

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.

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.

Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data

Directory of Open Access Journals (Sweden)

Wei Tu

2018-01-01

Full Text Available Portraying urban functional zones provides useful insights into understanding complex urban systems and establishing rational urban planning. Although several studies have confirmed the efficacy of remote sensing imagery in urban studies, coupling remote sensing and new human sensing data like mobile phone positioning data to identify urban functional zones has still not been investigated. In this study, a new framework integrating remote sensing imagery and mobile phone positioning data was developed to analyze urban functional zones with landscape and human activity metrics. Landscapes metrics were calculated based on land cover from remote sensing images. Human activities were extracted from massive mobile phone positioning data. By integrating them, urban functional zones (urban center, sub-center, suburbs, urban buffer, transit region and ecological area were identified by a hierarchical clustering. Finally, gradient analysis in three typical transects was conducted to investigate the pattern of landscapes and human activities. Taking Shenzhen, China, as an example, the conducted experiment shows that the pattern of landscapes and human activities in the urban functional zones in Shenzhen does not totally conform to the classical urban theories. It demonstrates that the fusion of remote sensing imagery and human sensing data can characterize the complex urban spatial structure in Shenzhen well. Urban functional zones have the potential to act as bridges between the urban structure, human activity and urban planning policy, providing scientific support for rational urban planning and sustainable urban development policymaking.

Remote sensing: best practice

Energy Technology Data Exchange (ETDEWEB)

Brown, Gareth [Sgurr Energy (Canada)

2011-07-01

This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.

Carbon for sensing devices

CERN Document Server

Tagliaferro, Alberto

2015-01-01

This book reveals why carbon is playing such an increasingly prominent role as a sensing material. The various steps that transform a raw material in a sensing device are thoroughly presented and critically discussed.  The authors deal with all aspects of carbon-based sensors, starting from the various hybridization and allotropes of carbon, with specific focus on micro and nanosized carbons (e.g., carbon nanotubes, graphene) and their growth processes. The discussion then moves to the role of functionalization and the different routes to achieve it. Finally, a number of sensing applications in various fields are presented, highlighting the connection with the basic properties of the various carbon allotropes.  Readers will benefit from this book’s bottom-up approach, which starts from the local bonding in carbon solids and ends with sensing applications, linking the local hybridization of carbon atoms and its modification by functionalization to specific device performance. This book is a must-have in th...

Metal nanostructures for non-enzymatic glucose sensing