A local effect model-based interpolation framework for experimental nanoparticle radiosensitisation data

OpenAIRE

Brown, Jeremy M. C.; Currell, Fred J.

2017-01-01

A local effect model (LEM)-based framework capable of interpolating nanoparticle-enhanced photon-irradiated clonogenic cell survival fraction measurements as a function of nanoparticle concentration was developed and experimentally benchmarked for gold nanoparticle (AuNP)-doped bovine aortic endothelial cells (BAECs) under superficial kilovoltage X-ray irradiation. For three different superficial kilovoltage X-ray spectra, the BAEC survival fraction response was predicted for two different Au...

Tourism Village Model Based on Local Indigenous: Case Study of Nongkosawit Tourism Village, Gunungpati, Semarang

Science.gov (United States)

Kurniasih; Nihayah, Dyah Maya; Sudibyo, Syafitri Amalia; Winda, Fajri Nur

2018-02-01

Officially, Nongkosawit Village has become a tourism village since 2012. However, the economic impact has not been received by the society yet because of inappropriate tourism village model. Therefore, this study aims to find out the best model for the development of Nongkosawit Tourism Village. This research used Analytical Hierarchy Process method. The results of this research shows that the model of tourism village which was suitable to the local indigenous of Nongkosawit Tourism Village was the cultural based tourism village with the percentage of 58%. Therefore, it is necessary to do re-orientation from the natural-based village model into the cultural-based village model by raising and exploring the existing culture through unique and different tourism products.

Local models of astrophysical discs

Science.gov (United States)

Latter, Henrik N.; Papaloizou, John

2017-12-01

Local models of gaseous accretion discs have been successfully employed for decades to describe an assortment of small-scale phenomena, from instabilities and turbulence, to dust dynamics and planet formation. For the most part, they have been derived in a physically motivated but essentially ad hoc fashion, with some of the mathematical assumptions never made explicit nor checked for consistency. This approach is susceptible to error, and it is easy to derive local models that support spurious instabilities or fail to conserve key quantities. In this paper we present rigorous derivations, based on an asympototic ordering, and formulate a hierarchy of local models (incompressible, Boussinesq and compressible), making clear which is best suited for a particular flow or phenomenon, while spelling out explicitly the assumptions and approximations of each. We also discuss the merits of the anelastic approximation, emphasizing that anelastic systems struggle to conserve energy unless strong restrictions are imposed on the flow. The problems encountered by the anelastic approximation are exacerbated by the disc's differential rotation, but also attend non-rotating systems such as stellar interiors. We conclude with a defence of local models and their continued utility in astrophysical research.

Shape determinative slice localization for patient-specific masseter modeling using shape-based interpolation

Energy Technology Data Exchange (ETDEWEB)

Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering (Singapore); Biomedical Imaging Lab., Agency for Science Technology and Research (Singapore); Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering (Singapore); Dept. of Preventive Dentistry, National Univ. of Singapore (Singapore); Ong, S.H. [Dept. of Electrical and Computer Engineering, National Univ. of Singapore (Singapore); Div. of Bioengineering, National Univ. of Singapore (Singapore); Liu, J.; Nowinski, W.L. [Biomedical Imaging Lab., Agency for Science Technology and Research (Singapore); Goh, P.S. [Dept. of Diagnostic Radiology, National Univ. of Singapore (Singapore)

2007-06-15

The masseter plays a critical role in the mastication system. A hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets. The main contribution here is the localizing of determinative slices in the data sets where clinicians are required to perform manual segmentations in order for an accurate model to be built. Shape-based criteria were used to locate the candidates for determinative slices and fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Five masseter models were built in our work and the average overlap indices ({kappa}) achieved is 85.2%. This indicates that there is good agreement between the models and the manual contour tracings. In addition, the time taken, as compared to manually segmenting all the slices, is significantly lesser. (orig.)

Shape determinative slice localization for patient-specific masseter modeling using shape-based interpolation

International Nuclear Information System (INIS)

Ng, H.P.; Foong, K.W.C.; Ong, S.H.; Liu, J.; Nowinski, W.L.; Goh, P.S.

2007-01-01

The masseter plays a critical role in the mastication system. A hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets. The main contribution here is the localizing of determinative slices in the data sets where clinicians are required to perform manual segmentations in order for an accurate model to be built. Shape-based criteria were used to locate the candidates for determinative slices and fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Five masseter models were built in our work and the average overlap indices (κ) achieved is 85.2%. This indicates that there is good agreement between the models and the manual contour tracings. In addition, the time taken, as compared to manually segmenting all the slices, is significantly lesser. (orig.)

A Spalart-Allmaras local correlation-based transition model for Thermo-fuid dynamics

Science.gov (United States)

D'Alessandro, V.; Garbuglia, F.; Montelpare, S.; Zoppi, A.

2017-11-01

The study of innovative energy systems often involves complex fluid flows problems and the Computational Fluid-Dynamics (CFD) is one of the main tools of analysis. It is important to put in evidence that in several energy systems the flow field experiences the laminar-to-turbulent transition. Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) are able to predict the flow transition but they are still inapplicable to the study of real problems due to the significant computational resources requirements. Differently standard Reynolds Averaged Navier Stokes (RANS) approaches are not always reliable since they assume a fully turbulent regime. In order to overcome this drawback in the recent years some locally formulated transition RANS models have been developed. In this work, we present a local correlation-based transition approach adding two equations that control the laminar-toturbulent transition process -γ and \\[\\overset{}{\\mathop{{{\\operatorname{Re}}θ, \\text{t}}}} \\] - to the well-known Spalart-Allmaras (SA) turbulence model. The new model was implemented within OpenFOAM code. The energy equation is also implemented in order to evaluate the model performance in thermal-fluid dynamics applications. In all the considered cases a very good agreement between numerical and experimental data was observed.

A comparative study of the models dealing with localized and semi-localized transitions in thermally stimulated luminescence

International Nuclear Information System (INIS)

Kumar, Munish; Kher, R K; Bhatt, B C; Sunta, C M

2007-01-01

Different models dealing with localized and semi-localized transitions, namely Chen-Halperin, Mandowski and the model based on the Braunlich-Scharmann (BS) approach are compared. It has been found that for recombination dominant situations (r > 1, the three models differ. This implies that for localized transitions under recombination dominant situations, the Chen-Halperin model is the best representative of the thermally stimulated luminescence (TSL) process. It has also been found that for the TSL glow curves arising from delocalized recombination in Mandowski's semi-localized transitions model, the double peak structure of the TSL glow curve is a function of the radiation dose as well as of the heating rate. Further, the double peak structure of the TSL glow curves arising from delocalized recombination disappears at low doses as well as at higher heating rates. It has also been found that the TSL glow curves arising from delocalized recombination in the semi-localized transitions model based on the BS approach do not exhibit double peak structure as observed in the Mandowski semi-localized transitions model

Local business models for district heat production; Kaukolaemmoen paikalliset liiketoimintamallit

Energy Technology Data Exchange (ETDEWEB)

Hakala, L.; Pesola, A.; Vanhanen, J.

2012-12-15

Local district heating business, outside large urban centers, is a profitable business in Finland, which can be practiced with several different business models. In addition to the traditional, local district heating business, local district heat production can be also based on franchising business model, on integrated service model or on different types of cooperation models, either between a local district heat producer and industrial site providing surplus heat or between a local district heat producer and a larger district heating company. Locally available wood energy is currently utilized effectively in the traditional district heating business model, in which a local entrepreneur produces heat to consumers in the local area. The franchising model is a more advanced version of the traditional district heating entrepreneurship. In this model, franchisor funds part of the investments, as well as offers centralized maintenance and fuel supply, for example. In the integrated service model, the local district heat producer offers also energy efficiency services and other value-added services, which are based on either the local district heat suppliers or his partner's expertise. In the cooperation model with industrial site, the local district heating business is based on the utilization of the surplus heat from the industrial site. In some cases, profitable operating model approach may be a district heating company outsourcing operations of one or more heating plants to a local entrepreneur. It can be concluded that all business models for district heat production (traditional district heat business model, franchising, integrated service model, cooperative model) discussed in this report can be profitable in Finnish conditions, as well for the local heat producer as for the municipality - and, above all, they produce cost-competitive heat for the end-user. All the models were seen as viable and interesting and having possibilities for expansion Finland

Image contrast enhancement based on a local standard deviation model

International Nuclear Information System (INIS)

Chang, Dah-Chung; Wu, Wen-Rong

1996-01-01

The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt's Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm

A range-based predictive localization algorithm for WSID networks

Science.gov (United States)

Liu, Yuan; Chen, Junjie; Li, Gang

2017-11-01

Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

Science.gov (United States)

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

Three hybridization models based on local search scheme for job shop scheduling problem

Science.gov (United States)

Balbi Fraga, Tatiana

2015-05-01

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

Calculation of generalized Lorenz-Mie theory based on the localized beam models

International Nuclear Information System (INIS)

Jia, Xiaowei; Shen, Jianqi; Yu, Haitao

2017-01-01

It has been proved that localized approximation (LA) is the most efficient way to evaluate the beam shape coefficients (BSCs) in generalized Lorenz-Mie theory (GLMT). The numerical calculation of relevant physical quantities is a challenge for its practical applications due to the limit of computer resources. The study presents an improved algorithm of the GLMT calculation based on the localized beam models. The BSCs and the angular functions are calculated by multiplying them with pre-factors so as to keep their values in a reasonable range. The algorithm is primarily developed for the original localized approximation (OLA) and is further extended to the modified localized approximation (MLA). Numerical results show that the algorithm is efficient, reliable and robust. - Highlights: • In this work, we introduce the proper pre-factors to the Bessel functions, BSCs and the angular functions. With this improvement, all the quantities involved in the numerical calculation are scaled into a reasonable range of values so that the algorithm can be used for computing the physical quantities of the GLMT. • The algorithm is not only an improvement in numerical technique, it also implies that the set of basic functions involved in the electromagnetic scattering (and sonic scattering) can be reasonably chosen. • The algorithms of the GLMT computations introduced in previous references suggested that the order of the n and m sums is interchanged. In this work, the sum of azimuth modes is performed for each partial wave. This offers the possibility to speed up the computation, since the sum of partial waves can be optimized according to the illumination conditions and the sum of azimuth modes can be truncated by selecting a criterion discussed in . • Numerical results show that the algorithm is efficient, reliable and robust, even in very exotic cases. The algorithm presented in this paper is based on the original localized approximation and it can also be used for the

Developing Learning Model Based on Local Culture and Instrument for Mathematical Higher Order Thinking Ability

Science.gov (United States)

Saragih, Sahat; Napitupulu, E. Elvis; Fauzi, Amin

2017-01-01

This research aims to develop a student-centered learning model based on local culture and instrument of mathematical higher order thinking of junior high school students in the frame of the 2013-Curriculum in North Sumatra, Indonesia. The subjects of the research are seventh graders which are taken proportionally random consisted of three public…

Localization Algorithm Based on a Spring Model (LASM for Large Scale Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Shuai Li

2008-03-01

Full Text Available A navigation method for a lunar rover based on large scale wireless sensornetworks is proposed. To obtain high navigation accuracy and large exploration area, highnode localization accuracy and large network scale are required. However, thecomputational and communication complexity and time consumption are greatly increasedwith the increase of the network scales. A localization algorithm based on a spring model(LASM method is proposed to reduce the computational complexity, while maintainingthe localization accuracy in large scale sensor networks. The algorithm simulates thedynamics of physical spring system to estimate the positions of nodes. The sensor nodesare set as particles with masses and connected with neighbor nodes by virtual springs. Thevirtual springs will force the particles move to the original positions, the node positionscorrespondingly, from the randomly set positions. Therefore, a blind node position can bedetermined from the LASM algorithm by calculating the related forces with the neighbornodes. The computational and communication complexity are O(1 for each node, since thenumber of the neighbor nodes does not increase proportionally with the network scale size.Three patches are proposed to avoid local optimization, kick out bad nodes and deal withnode variation. Simulation results show that the computational and communicationcomplexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps arealmost unrelated with the network scale size.

A Local Composition Model for Paraffinic Solid Solutions

DEFF Research Database (Denmark)

Coutinho, A.P. João; Knudsen, Kim; Andersen, Simon Ivar

1996-01-01

The description of the solid-phase non-ideality remains the main obstacle in modelling the solid-liquid equilibrium of hydrocarbons. A theoretical model, based on the local composition concept, is developed for the orthorhombic phase of n-alkanes and tested against experimental data for binary sy...... systems. It is shown that it can adequately predict the experimental phase behaviour of paraffinic mixtures. This work extends the applicability of local composition models to the solid phase. Copyright (C) 1996 Elsevier Science Ltd....

Pengembangan Model Outdoor Learning melalui Project Berbasis Local Wisdom dalam Pembelajaran Fisika

Directory of Open Access Journals (Sweden)

Indah kurnia Putri Damayanti

2017-12-01

Full Text Available Abstrak Penelitian ini bertujuan untuk: (1 menghasilkan model outdoor learning melalui project berbasis local wisdom yang layak digunakan dalam pembelajaran fisika, (2 mengetahui keefektifan penggunaan model outdoor learning melalui project berbasis local wisdom. Penelitian pengembangan ini menggunakan metode pengembangan R & D (Research dan Development. Pada tahap Development, peneliti mengadopsi model 4D, yaitu Define, Design, Develop, dan Disseminate. Hasil penelitian menunjukkan bahwa model outdoor learning melalui project berbasis local wisdom yang dikembangkan layak digunakan dari segi produk pendukung pembelajaran yang memenuhi kriteria sangat tinggi menurut para ahli, praktis menurut guru dan peserta didik. Lembar observasi yang memenuhi kriteria valid dan reliabel berdasarkan hasil ICC dan tes hasil belajar yang memenuhi kriteria valid dan reliabel berdasarkan hasil Quest. Selain itu, model outdoor learning melalui project berbasis local wisdom lebih efektif digunakan dalam pembelajaran fisika dilihat dari hasil analisis multivariate dan GLMMDs yang memperoleh nilai signifikansi 0,000 dan MD yang tinggi.   AbstractThis research was aimed to: (1 produce outdoor learning via project based suitable local wisdom model used in physics learning, (2 know the effectiveness in using outdoor learning via project based local wisdom model. This developing research used a R & D method (Research and Development. On Development step, the researcher adopted 4D model, they were Define, Design, Develop, dan Dissemination. The results showed that the developed outdoor learning via project based local wisdom model was suitable to be used in terms of learning support product that was in very high category according expert, practical according teacher and students. In addition the observation sheet was in valid criteria and reliabel based on ICC and the learning outcome test was in valid criteria and reliabel based on Quest. Besides, outdoor learning via

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

Directory of Open Access Journals (Sweden)

Francesco Pizzitutti

Full Text Available Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

Science.gov (United States)

Pizzitutti, Francesco; Pan, William; Feingold, Beth; Zaitchik, Ben; Álvarez, Carlos A; Mena, Carlos F

2018-01-01

Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

A Bubble-Based Drag Model at the Local-Grid Level for Eulerian Simulation of Bubbling Fluidized Beds

Directory of Open Access Journals (Sweden)

Kun Hong

2016-01-01

Full Text Available A bubble-based drag model at the local-grid level is proposed to simulate gas-solid flows in bubbling fluidized beds of Geldart A particles. In this model, five balance equations are derived from the mass and the momentum conservation. This set of equations along with necessary correlations for bubble diameter and voidage of emulsion phase is solved to obtain seven local structural parameters (uge, upe, εe, δb, ub, db, and ab which describe heterogeneous flows of bubbling fluidized beds. The modified drag coefficient obtained from the above-mentioned structural parameters is then incorporated into the two-fluid model to simulate the hydrodynamics of Geldart A particles in a lab-scale bubbling fluidized bed. The comparison between experimental and simulation results for the axial and radial solids concentration profiles is promising.

A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

International Nuclear Information System (INIS)

Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

2013-01-01

Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

Simulation of delamination crack growth in composite laminates: application of local and non-local interface damage models

International Nuclear Information System (INIS)

Ijaz, H.; Asad, M.

2015-01-01

The use of composite laminates is increasing in these days due to higher strength and low density values in comparison of metals. Delamination is a major source of failure in composite laminates. Damage mechanics based theories are employed to simulate the delamination phenomena between composite laminates. These damage models are inherently local and can cause the concentration of stresses around the crack tip. In the present study integral type non-local damage formulation is proposed to avoid the localization problem associated to damage formulation. A comprehensive study is carried out for the models and classical local damage model are performed and results are compared with available experimental data for un IMS/924 Carbon/fiber epoxy composite laminate. (author)

Locally Simple Models Construction: Methodology and Practice

Directory of Open Access Journals (Sweden)

I. A. Kazakov

2017-12-01

Full Text Available One of the most notable trends associated with the Fourth industrial revolution is a significant strengthening of the role played by semantic methods. They are engaged in artificial intelligence means, knowledge mining in huge flows of big data, robotization, and in the internet of things. Smart contracts also can be mentioned here, although the ’intelligence’ of smart contracts still needs to be seriously elaborated. These trends should inevitably lead to an increased role of logical methods working with semantics, and significantly expand the scope of their application in practice. However, there are a number of problems that hinder this process. We are developing an approach, which makes the application of logical modeling efficient in some important areas. The approach is based on the concept of locally simple models and is primarily focused on solving tasks in the management of enterprises, organizations, governing bodies. The most important feature of locally simple models is their ability to replace software systems. Replacement of programming by modeling gives huge advantages, for instance, it dramatically reduces development and support costs. Modeling, unlike programming, preserves the explicit semantics of models allowing integration with artificial intelligence and robots. In addition, models are much more understandable to general people than programs. In this paper we propose the implementation of the concept of locally simple modeling on the basis of so-called document models, which has been developed by us earlier. It is shown that locally simple modeling is realized through document models with finite submodel coverages. In the second part of the paper an example of using document models for solving a management problem of real complexity is demonstrated.

Coevolution Based Adaptive Monte Carlo Localization (CEAMCL

Directory of Open Access Journals (Sweden)

Luo Ronghua

2008-11-01

Full Text Available An adaptive Monte Carlo localization algorithm based on coevolution mechanism of ecological species is proposed. Samples are clustered into species, each of which represents a hypothesis of the robot's pose. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence when using MCL in highly symmetric environments can be solved. And the sample size can be adjusted adaptively over time according to the uncertainty of the robot's pose by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small size of samples can represent the desired density well enough to make precise localization. The new algorithm is termed coevolution based adaptive Monte Carlo localization (CEAMCL. Experiments have been carried out to prove the efficiency of the new localization algorithm.

Localized Multi-Model Extremes Metrics for the Fourth National Climate Assessment

Science.gov (United States)

Thompson, T. R.; Kunkel, K.; Stevens, L. E.; Easterling, D. R.; Biard, J.; Sun, L.

2017-12-01

We have performed localized analysis of scenario-based datasets for the Fourth National Climate Assessment (NCA4). These datasets include CMIP5-based Localized Constructed Analogs (LOCA) downscaled simulations at daily temporal resolution and 1/16th-degree spatial resolution. Over 45 temperature and precipitation extremes metrics have been processed using LOCA data, including threshold, percentile, and degree-days calculations. The localized analysis calculates trends in the temperature and precipitation extremes metrics for relatively small regions such as counties, metropolitan areas, climate zones, administrative areas, or economic zones. For NCA4, we are currently addressing metropolitan areas as defined by U.S. Census Bureau Metropolitan Statistical Areas. Such localized analysis provides essential information for adaptation planning at scales relevant to local planning agencies and businesses. Nearly 30 such regions have been analyzed to date. Each locale is defined by a closed polygon that is used to extract LOCA-based extremes metrics specific to the area. For each metric, single-model data at each LOCA grid location are first averaged over several 30-year historical and future periods. Then, for each metric, the spatial average across the region is calculated using model weights based on both model independence and reproducibility of current climate conditions. The range of single-model results is also captured on the same localized basis, and then combined with the weighted ensemble average for each region and each metric. For example, Boston-area cooling degree days and maximum daily temperature is shown below for RCP8.5 (red) and RCP4.5 (blue) scenarios. We also discuss inter-regional comparison of these metrics, as well as their relevance to risk analysis for adaptation planning.

Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

Energy Technology Data Exchange (ETDEWEB)

Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira [Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Research and Clinical Collaborations, Siemens Healthcare, Erlangen 91052 (Germany); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ (United Kingdom); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy)

2010-04-15

Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

International Nuclear Information System (INIS)

Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

2010-01-01

Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term α and the dose per fraction. The estimated values of α and OER from data fitting were 0.396 Gy -1 and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

Development of a micro-depletion model to us WIMS properties in history-based local-parameter calculations in RFSP

International Nuclear Information System (INIS)

Shen, W.

2004-01-01

A micro-depletion model has been developed and implemented in the *SIMULATE module of RFSP to use WIMS-calculated lattice properties in history-based local-parameter calculations. A comparison between the micro-depletion and WIMS results for each type of lattice cross section and for the infinite-lattice multiplication factor was also performed for a fuel similar to that which may be used in the ACR fuel. The comparison shows that the micro-depletion calculation agrees well with the WIMS-IST calculation. The relative differences in k-infinity are within ±0.5 mk and ±0.9 mk for perturbation and depletion calculations, respectively. The micro-depletion model gives the *SIMULATE module of RFSP the capability to use WIMS-calculated lattice properties in history-based local-parameter calculations without resorting to the Simple-Cell-Methodology (SCM) surrogate for CANDU core-tracking simulations. (author)

Students' Critical Thinking Skills in Chemistry Learning Using Local Culture-Based 7E Learning Cycle Model

Science.gov (United States)

Suardana, I. Nyoman; Redhana, I. Wayan; Sudiatmika, A. A. Istri Agung Rai; Selamat, I. Nyoman

2018-01-01

This research aimed at describing the effectiveness of the local culture-based 7E learning cycle model in improving students' critical thinking skills in chemistry learning. It was an experimental research with post-test only control group design. The population was the eleventh-grade students of senior high schools in Singaraja, Indonesia. The…

A NEW COMBINED LOCAL AND NON-LOCAL PBL MODEL FOR METEOROLOGY AND AIR QUALITY MODELING

Science.gov (United States)

A new version of the Asymmetric Convective Model (ACM) has been developed to describe sub-grid vertical turbulent transport in both meteorology models and air quality models. The new version (ACM2) combines the non-local convective mixing of the original ACM with local eddy diff...

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

Science.gov (United States)

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

Non-local model analysis of heat pulse propagation

International Nuclear Information System (INIS)

Iwasaki, Takuya; Itoh, Sanae-I.; Yagi, Masatoshi

1998-01-01

A new theoretical model equation which includes the non-local effect in the heat flux is proposed to study the transient transport phenomena. A non-local heat flux, which is expressed in terms of the integral equation, is superimposed on the conventional form of the heat flux. This model is applied to describe the experimental results from the power switching [Stroth U, et al 1996 Plasma Phys. Control. Fusion 38 1087] and the power modulation experiments [Giannone L, et al 1992 Nucl. Fusion 32 1985] in the W7-AS stellarator. A small fraction of non-local component in the heat flux is found to be very effective in modifying the response against an external modulation. The transient feature of the transport property, which are observed in the response of heat pulse propagation, are qualitatively reproduced by the transport simulations based on this model. A possibility is discussed to determine the correlation length of the non-local effect experimentally by use of the results of transport simulations. (author)

Reputation-based secure sensor localization in wireless sensor networks.

Science.gov (United States)

He, Jingsha; Xu, Jing; Zhu, Xingye; Zhang, Yuqiang; Zhang, Ting; Fu, Wanqing

2014-01-01

Location information of sensor nodes in wireless sensor networks (WSNs) is very important, for it makes information that is collected and reported by the sensor nodes spatially meaningful for applications. Since most current sensor localization schemes rely on location information that is provided by beacon nodes for the regular sensor nodes to locate themselves, the accuracy of localization depends on the accuracy of location information from the beacon nodes. Therefore, the security and reliability of the beacon nodes become critical in the localization of regular sensor nodes. In this paper, we propose a reputation-based security scheme for sensor localization to improve the security and the accuracy of sensor localization in hostile or untrusted environments. In our proposed scheme, the reputation of each beacon node is evaluated based on a reputation evaluation model so that regular sensor nodes can get credible location information from highly reputable beacon nodes to accomplish localization. We also perform a set of simulation experiments to demonstrate the effectiveness of the proposed reputation-based security scheme. And our simulation results show that the proposed security scheme can enhance the security and, hence, improve the accuracy of sensor localization in hostile or untrusted environments.

A Local Search Modeling for Constrained Optimum Paths Problems (Extended Abstract

Directory of Open Access Journals (Sweden)

Quang Dung Pham

2009-10-01

Full Text Available Constrained Optimum Path (COP problems appear in many real-life applications, especially on communication networks. Some of these problems have been considered and solved by specific techniques which are usually difficult to extend. In this paper, we introduce a novel local search modeling for solving some COPs by local search. The modeling features the compositionality, modularity, reuse and strengthens the benefits of Constrained-Based Local Search. We also apply the modeling to the edge-disjoint paths problem (EDP. We show that side constraints can easily be added in the model. Computational results show the significance of the approach.

Random incidence absorption coefficients of porous absorbers based on local and extended reaction models

DEFF Research Database (Denmark)

Jeong, Cheol-Ho

2011-01-01

resistivity and the absorber thickness on the difference between the two surface reaction models are examined and discussed. For a porous absorber backed by a rigid surface, the local reaction models give errors of less than 10% if the thickness exceeds 120 mm for a flow resistivity of 5000 Nm-4s. As the flow...... incidence acoustical characteristics of typical building elements made of porous materials assuming extended and local reaction. For each surface reaction, five well-established wave propagation models, the Delany-Bazley, Miki, Beranek, Allard-Champoux, and Biot model, are employed. Effects of the flow...... resistivity doubles, a decrease in the required thickness by 25 mm is observed to achieve the same amount of error. For an absorber backed by an air gap, the thickness ratio between the material and air cavity is important. If the absorber thickness is approximately 40% of the cavity depth, the local reaction...

A rights-based approach to science literacy using local languages: Contextualising inquiry-based learning in Africa

Science.gov (United States)

Babaci-Wilhite, Zehlia

2017-06-01

This article addresses the importance of teaching and learning science in local languages. The author argues that acknowledging local knowledge and using local languages in science education while emphasising inquiry-based learning improve teaching and learning science. She frames her arguments with the theory of inquiry, which draws on perspectives of both dominant and non-dominant cultures with a focus on science literacy as a human right. She first examines key assumptions about knowledge which inform mainstream educational research and practice. She then argues for an emphasis on contextualised learning as a right in education. This means accounting for contextualised knowledge and resisting the current trend towards de-contextualisation of curricula. This trend is reflected in Zanzibar's recent curriculum reform, in which English replaced Kiswahili as the language of instruction (LOI) in the last two years of primary school. The author's own research during the initial stage of the change (2010-2015) revealed that the effect has in fact proven to be counterproductive, with educational quality deteriorating further rather than improving. Arguing that language is essential to inquiry-based learning, she introduces a new didactic model which integrates alternative assumptions about the value of local knowledge and local languages in the teaching and learning of science subjects. In practical terms, the model is designed to address key science concepts through multiple modalities - "do it, say it, read it, write it" - a "hands-on" experiential combination which, she posits, may form a new platform for innovation based on a unique mix of local and global knowledge, and facilitate genuine science literacy. She provides examples from cutting-edge educational research and practice that illustrate this new model of teaching and learning science. This model has the potential to improve learning while supporting local languages and culture, giving local languages their

PLACE-BASED GREEN BUILDING: INTEGRATING LOCAL ENVIRONMENTAL AND PLANNING ANALYSIS INTO GREEN BUILDING GUIDELINES

Science.gov (United States)

This project will develop a model for place-based green building guidelines based on an analysis of local environmental, social, and land use conditions. The ultimate goal of this project is to develop a methodology and model for placing green buildings within their local cont...

Local and Global Function Model of the Liver

Energy Technology Data Exchange (ETDEWEB)

Wang, Hesheng, E-mail: hesheng@umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Feng, Mary [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Jackson, Andrew [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Ten Haken, Randall K.; Lawrence, Theodore S. [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Cao, Yue [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan (United States)

2016-01-01

Purpose: To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). Methods and Materials: A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. Results: The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. Conclusions: The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.

Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

Directory of Open Access Journals (Sweden)

Liyun Su

2012-01-01

Full Text Available We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations.

A Bayesian network approach for modeling local failure in lung cancer

International Nuclear Information System (INIS)

Oh, Jung Hun; Craft, Jeffrey; Al Lozi, Rawan; Vaidya, Manushka; Meng, Yifan; Deasy, Joseph O; Bradley, Jeffrey D; El Naqa, Issam

2011-01-01

Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction. To test this hypothesis, we propose a graphical Bayesian network framework for predicting local failure in lung cancer. The proposed approach was tested using two different datasets of locally advanced NSCLC patients treated with radiotherapy. The first dataset was collected retrospectively, which comprises clinical and dosimetric variables only. The second dataset was collected prospectively in which in addition to clinical and dosimetric information, blood was drawn from the patients at various time points to extract candidate biomarkers as well. Our preliminary results show that the proposed method can be used as an efficient method to develop predictive models of local failure in these patients and to interpret relationships among the different variables in the models. We also demonstrate the potential use of heterogeneous physical and biological variables to improve the model prediction. With the first dataset, we achieved better performance compared with competing Bayesian-based classifiers. With the second dataset, the combined model had a slightly higher performance compared to individual physical and biological models, with the biological variables making the largest contribution. Our preliminary results highlight the potential of the proposed integrated approach for predicting post-radiotherapy local failure in NSCLC patients.

Gene ontology based transfer learning for protein subcellular localization

Directory of Open Access Journals (Sweden)

Zhou Shuigeng

2011-02-01

Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

Inference for local autocorrelations in locally stationary models.

Science.gov (United States)

Zhao, Zhibiao

2015-04-01

For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address important hypothesis testing problems, such as whether the local autocorrelation process is indeed time-varying and whether the local autocorrelation is zero. In particular, our result provides an important generalization of the R function acf() to locally stationary Gaussian processes. Simulation studies and two empirical applications are developed. For the global temperature series, we find that the local autocorrelations are time-varying and have a "V" shape during 1910-1960. For the S&P 500 index, we conclude that the returns satisfy the efficient-market hypothesis whereas the magnitudes of returns show significant local autocorrelations.

A probabilistic model for robust localization based on a binaural auditory front-end

NARCIS (Netherlands)

May, T.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.

2011-01-01

Although extensive research has been done in the field of machine-based localization, the degrading effect of reverberation and the presence of multiple sources on localization performance has remained a major problem. Motivated by the ability of the human auditory system to robustly analyze complex

A Unified Model for BDS Wide Area and Local Area Augmentation Positioning Based on Raw Observations

Directory of Open Access Journals (Sweden)

Rui Tu

2017-03-01

Full Text Available In this study, a unified model for BeiDou Navigation Satellite System (BDS wide area and local area augmentation positioning based on raw observations has been proposed. Applying this model, both the Real-Time Kinematic (RTK and Precise Point Positioning (PPP service can be realized by performing different corrections at the user end. This algorithm was assessed and validated with the BDS data collected at four regional stations from Day of Year (DOY 080 to 083 of 2016. When the users are located within the local reference network, the fast and high precision RTK service can be achieved using the regional observation corrections, revealing a convergence time of about several seconds and a precision of about 2–3 cm. For the users out of the regional reference network, the global broadcast State-Space Represented (SSR corrections can be utilized to realize the global PPP service which shows a convergence time of about 25 min for achieving an accuracy of 10 cm. With this unified model, it can not only integrate the Network RTK (NRTK and PPP into a seamless positioning service, but also recover the ionosphere Vertical Total Electronic Content (VTEC and Differential Code Bias (DCB values that are useful for the ionosphere monitoring and modeling.

A Least Square-Based Self-Adaptive Localization Method for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Baoguo Yu

2016-01-01

Full Text Available In the wireless sensor network (WSN localization methods based on Received Signal Strength Indicator (RSSI, it is usually required to determine the parameters of the radio signal propagation model before estimating the distance between the anchor node and an unknown node with reference to their communication RSSI value. And finally we use a localization algorithm to estimate the location of the unknown node. However, this localization method, though high in localization accuracy, has weaknesses such as complex working procedure and poor system versatility. Concerning these defects, a self-adaptive WSN localization method based on least square is proposed, which uses the least square criterion to estimate the parameters of radio signal propagation model, which positively reduces the computation amount in the estimation process. The experimental results show that the proposed self-adaptive localization method outputs a high processing efficiency while satisfying the high localization accuracy requirement. Conclusively, the proposed method is of definite practical value.

Locality and nonlocality in geomorphic transport laws: Implications of a particle-based model of hillslope evolution

Science.gov (United States)

Tucker, G. E.; Bradley, D. N.

2008-12-01

Many geomorphic transport laws assume that the transport process is local, meaning that the space and time scales of particle displacement are short relative to those of the system as a whole. This assumption allows one to express sediment flux in terms of at-a-point properties such as the local surface gradient. However, while this assumption is quite reasonable for some processes (for example, grain displacement by raindrop impact), it is questionable for others (such as landsliding). Moreover, particle displacement distance may also depend on slope angle, becoming longer as gradient increases. For example, the average motion distance during sediment ravel events on very steep slopes may approach the length of the entire hillslope. In such cases, the mass flux through a given point may depend not only on the local topography but also on topography some distance upslope, thus violating the locality assumption. Here we use a stochastic, particle- based model of hillslope evolution to gain insight into the potential for, and consequences of, nonlocality in sediment transport. The model is designed as a simple analogy for a host of different processes that displace sediment grains on hillslopes. The hillslope is represented as a two-dimensional pile of particles. These particles undergo quasi-random motion according to the following rules: (1) during each iteration, a particle and a direction are selected at random; (2) the particle hops in the direction of motion with a probability that depends on the its height relative to that of its immediate neighbor; (3) the particle continues making hops in the same direction and with the same probability dependence, until coming to rest or exiting the base of the slope. The topography and motion statistics that emerge from these rules show a range of behavior that depends on a dimensionless relief parameter. At low relief, hillslope shape is parabolic, mean displacement length is on the order of two particle widths, and the

Modelling of ductile and cleavage fracture by local approach

International Nuclear Information System (INIS)

Samal, M.K.; Dutta, B.K.; Kushwaha, H.S.

2000-08-01

This report describes the modelling of ductile and cleavage fracture processes by local approach. It is now well known that the conventional fracture mechanics method based on single parameter criteria is not adequate to model the fracture processes. It is because of the existence of effect of size and geometry of flaw, loading type and rate on the fracture resistance behaviour of any structure. Hence, it is questionable to use same fracture resistance curves as determined from standard tests in the analysis of real life components because of existence of all the above effects. So, there is need to have a method in which the parameters used for the analysis will be true material properties, i.e. independent of geometry and size. One of the solutions to the above problem is the use of local approaches. These approaches have been extensively studied and applied to different materials (including SA33 Gr.6) in this report. Each method has been studied and reported in a separate section. This report has been divided into five sections. Section-I gives a brief review of the fundamentals of fracture process. Section-II deals with modelling of ductile fracture by locally uncoupled type of models. In this section, the critical cavity growth parameters of the different models have been determined for the primary heat transport (PHT) piping material of Indian pressurised heavy water reactor (PHWR). A comparative study has been done among different models. The dependency of the critical parameters on stress triaxiality factor has also been studied. It is observed that Rice and Tracey's model is the most suitable one. But, its parameters are not fully independent of triaxiality factor. For this purpose, a modification to Rice and Tracery's model is suggested in Section-III. Section-IV deals with modelling of ductile fracture process by locally coupled type of models. Section-V deals with the modelling of cleavage fracture process by Beremins model, which is based on Weibulls

Integrated modeling and characterization of local crack chemistry

International Nuclear Information System (INIS)

Savchik, J.A.; Burke, M.S.

1996-01-01

The MULTEQ computer program has become an industry wide tool which can be used to calculate the chemical composition in a flow occluded region as the solution within concentrates due to a local boiling process. These results can be used to assess corrosion concerns in plant equipment such as steam generators. Corrosion modeling attempts to quantify corrosion assessments by accounting for the mass transport processes involved in the corrosion mechanism. MULTEQ has played an ever increasing role in defining the local chemistry for such corrosion models. This paper will outline how the integration of corrosion modeling with the analysis of corrosion films and deposits can lead to the development of a useful modeling tool, wherein MULTEQ is interactively linked to a diffusion and migration transport process. This would provide a capability to make detailed inferences of the local crack chemistry based on the analyses of the local corrosion films and deposits inside a crack and thus provide guidance for chemical fixes to avoid cracking. This methodology is demonstrated for a simple example of a cracked tube. This application points out the utility of coupling MULTEQ with a mass transport process and the feasibility of an option in a future version of MULTEQ that would permit relating film and deposit analyses to the local chemical environment. This would increase the amount of information obtained from removed tube analyses and laboratory testing that can contribute to an overall program for mitigating tubing and crevice corrosion

Integrated modeling and characterization of local crack chemistry

International Nuclear Information System (INIS)

Savchik, J.A.; Burke, M.S.

1995-01-01

The MULTEQ computer program has become an industry wide tool which can be used to calculate the chemical composition in a flow occluded region as the solution within concentrates due to a local boiling process. These results can be used to assess corrosion concerns in plant equipment such as steam generators. Corrosion modeling attempts to quantify corrosion assessments by accounting for the mass transport processes involved in the corrosion mechanism. MULTEQ has played an ever increasing role in defining the local chemistry for such corrosion models. This paper will outline how the integration of corrosion modeling with the analysis of corrosion films and deposits can lead to the development of a useful modeling tool, wherein MULTEQ is interactively linked to a diffusion and migration transport process. This would provide a capability to make detailed inferences of the local crack chemistry based on the analyses of the local corrosion films and deposits inside a crack and thus provide guidance for chemical fixes to avoid cracking. This methodology is demonstrated for a simple example of a cracked tube. This application points out the utility of coupling MULTEQ with a mass transport process and the feasibility of an option in a future version of MULTEQ that would permit relating film and deposit analyses to the local chemical environment. This would increase the amount of information obtained from removed tube analyses and laboratory testing that can contribute to an overall program for mitigating tubing and crevice corrosion

Efficient Iris Localization via Optimization Model

Directory of Open Access Journals (Sweden)

Qi Wang

2017-01-01

Full Text Available Iris localization is one of the most important processes in iris recognition. Because of different kinds of noises in iris image, the localization result may be wrong. Besides this, localization process is time-consuming. To solve these problems, this paper develops an efficient iris localization algorithm via optimization model. Firstly, the localization problem is modeled by an optimization model. Then SIFT feature is selected to represent the characteristic information of iris outer boundary and eyelid for localization. And SDM (Supervised Descent Method algorithm is employed to solve the final points of outer boundary and eyelids. Finally, IRLS (Iterative Reweighted Least-Square is used to obtain the parameters of outer boundary and upper and lower eyelids. Experimental result indicates that the proposed algorithm is efficient and effective.

Local void and slip model used in BODYFIT-2PE

International Nuclear Information System (INIS)

Chen, B.C.J.; Chien, T.H.; Kim, J.H.; Lellouche, G.S.

1983-01-01

A local void and slip model has been proposed for a two-phase flow without the need of fitting any empirical parameters. This model is based on the assumption that all bubbles have reached their terminal rise velocities in the two-phase region. This simple model seems to provide reasonable calculational results when compared with the experimental data and other void and slip models. It provides a means to account for the void and slip of a two-phase flow on a local basis. This is particularly suitable for a fine mesh thermal-hydraulic computer program such as BODYFIT-2PE

A model for cell type localization in the migrating slug of ...

Indian Academy of Sciences (India)

PRAKASH

. Localization of the three major cell types within the migrating slug stage is a dynamic process (Sternfeld 1992;. A model for cell type localization in the migrating slug of Dictyostelium discoideum based on differential chemotactic sensitivity to ...

Generating clustered scale-free networks using Poisson based localization of edges

Science.gov (United States)

Türker, İlker

2018-05-01

We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

Science.gov (United States)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Monocular Vision-Based Robot Localization and Target Tracking

Directory of Open Access Journals (Sweden)

Bing-Fei Wu

2011-01-01

Full Text Available This paper presents a vision-based technology for localizing targets in 3D environment. It is achieved by the combination of different types of sensors including optical wheel encoders, an electrical compass, and visual observations with a single camera. Based on the robot motion model and image sequences, extended Kalman filter is applied to estimate target locations and the robot pose simultaneously. The proposed localization system is applicable in practice because it is not necessary to have the initializing setting regarding starting the system from artificial landmarks of known size. The technique is especially suitable for navigation and target tracing for an indoor robot and has a high potential extension to surveillance and monitoring for Unmanned Aerial Vehicles with aerial odometry sensors. The experimental results present “cm” level accuracy of the localization of the targets in indoor environment under a high-speed robot movement.

A RSSI-based parameter tracking strategy for constrained position localization

Science.gov (United States)

Du, Jinze; Diouris, Jean-François; Wang, Yide

2017-12-01

In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.

Analytical model for local scour prediction around hydrokinetic turbine foundations

Science.gov (United States)

Musa, M.; Heisel, M.; Hill, C.; Guala, M.

2017-12-01

Marine and Hydrokinetic renewable energy is an emerging sustainable and secure technology which produces clean energy harnessing water currents from mostly tidal and fluvial waterways. Hydrokinetic turbines are typically anchored at the bottom of the channel, which can be erodible or non-erodible. Recent experiments demonstrated the interactions between operating turbines and an erodible surface with sediment transport, resulting in a remarkable localized erosion-deposition pattern significantly larger than those observed by static in-river construction such as bridge piers, etc. Predicting local scour geometry at the base of hydrokinetic devices is extremely important during foundation design, installation, operation, and maintenance (IO&M), and long-term structural integrity. An analytical modeling framework is proposed applying the phenomenological theory of turbulence to the flow structures that promote the scouring process at the base of a turbine. The evolution of scour is directly linked to device operating conditions through the turbine drag force, which is inferred to locally dictate the energy dissipation rate in the scour region. The predictive model is validated using experimental data obtained at the University of Minnesota's St. Anthony Falls Laboratory (SAFL), covering two sediment mobility regimes (clear water and live bed), different turbine designs, hydraulic parameters, grain size distribution and bedform types. The model is applied to a potential prototype scale deployment in the lower Mississippi River, demonstrating its practical relevance and endorsing the feasibility of hydrokinetic energy power plants in large sandy rivers. Multi-turbine deployments are further studied experimentally by monitoring both local and non-local geomorphic effects introduced by a twelve turbine staggered array model installed in a wide channel at SAFL. Local scour behind each turbine is well captured by the theoretical predictive model. However, multi

Formulation analysis and computation of an optimization-based local-to-nonlocal coupling method.

Energy Technology Data Exchange (ETDEWEB)

D' Elia, Marta [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research; Bochev, Pavel Blagoveston [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research

2017-01-01

In this paper, we present an optimization-based coupling method for local and nonlocal continuum models. Our approach couches the coupling of the models into a control problem where the states are the solutions of the nonlocal and local equations, the objective is to minimize their mismatch on the overlap of the local and nonlocal problem domains, and the virtual controls are the nonlocal volume constraint and the local boundary condition. We present the method in the context of Local-to-Nonlocal di usion coupling. Numerical examples illustrate the theoretical properties of the approach.

Quantification of localized vertebral deformities using a sparse wavelet-based shape model.

Science.gov (United States)

Zewail, R; Elsafi, A; Durdle, N

2008-01-01

Medical experts often examine hundreds of spine x-ray images to determine existence of various pathologies. Common pathologies of interest are anterior osteophites, disc space narrowing, and wedging. By careful inspection of the outline shapes of the vertebral bodies, experts are able to identify and assess vertebral abnormalities with respect to the pathology under investigation. In this paper, we present a novel method for quantification of vertebral deformation using a sparse shape model. Using wavelets and Independent component analysis (ICA), we construct a sparse shape model that benefits from the approximation power of wavelets and the capability of ICA to capture higher order statistics in wavelet space. The new model is able to capture localized pathology-related shape deformations, hence it allows for quantification of vertebral shape variations. We investigate the capability of the model to predict localized pathology related deformations. Next, using support-vector machines, we demonstrate the diagnostic capabilities of the method through the discrimination of anterior osteophites in lumbar vertebrae. Experiments were conducted using a set of 150 contours from digital x-ray images of lumbar spine. Each vertebra is labeled as normal or abnormal. Results reported in this work focus on anterior osteophites as the pathology of interest.

Modeling local chemistry in PWR steam generator crevices

International Nuclear Information System (INIS)

Millett, P.J.

1997-01-01

Over the past two decades steam generator corrosion damage has been a major cost impact to PWR owners. Crevices and occluded regions create thermal-hydraulic conditions where aggressive impurities can become highly concentrated, promoting localized corrosion of the tubing and support structure materials. The type of corrosion varies depending on the local conditions, with stress corrosion cracking being the phenomenon of most current concern. A major goal of the EPRI research in this area has been to develop models of the concentration process and resulting crevice chemistry conditions. These models may then be used to predict crevice chemistry based on knowledge of bulk chemistry, thereby allowing the operator to control corrosion damage. Rigorous deterministic models have not yet been developed; however, empirical approaches have shown promise and are reflected in current versions of the industry-developed secondary water chemistry guidelines

A knowledge representation of local pandemic influenza planning models.

Science.gov (United States)

Islam, Runa; Brandeau, Margaret L; Das, Amar K

2007-10-11

Planning for pandemic flu outbreak at the small-government level can be aided through the use of mathematical policy models. Formulating and analyzing policy models, however, can be a time- and expertise-expensive process. We believe that a knowledge-based system for facilitating the instantiation of locale- and problem-specific policy models can reduce some of these costs. In this work, we present the ontology we have developed for pandemic influenza policy models.

Business model innovation for Local Energy Management: a perspective from Swiss utilities

Directory of Open Access Journals (Sweden)

Emanuele Facchinetti

2016-08-01

Full Text Available The successful deployment of the energy transition relies on a deep reorganization of the energy market. Business model innovation is recognized as a key driver of this process. This work contributes to this topic by providing to potential Local Energy Management stakeholders and policy makers a conceptual framework guiding the Local Energy Management business model innovation. The main determinants characterizing Local Energy Management concepts and impacting its business model innovation are identified through literature reviews on distributed generation typologies and customer/investor preferences related to new business opportunities emerging with the energy transition. Afterwards, the relation between the identified determinants and the Local Energy Management business model solution space is analyzed based on semi-structured interviews with managers of Swiss utilities companies. The collected managers’ preferences serve as explorative indicators supporting the business model innovation process and provide insights to policy makers on challenges and opportunities related to Local Energy Management.

New model. Local financing for local energy

International Nuclear Information System (INIS)

Detroy, Florent

2015-01-01

While evoking the case of the VMH Energies company in the Poitou-Charentes region, and indicating the difference between France and Germany in terms of wind and photovoltaic energy production potential, of number of existing local companies, and of citizen-based funding, this article shows that renewable energies could put the energy production financing in France into question again, with a more important participation of local communities and of their inhabitants. The author describes how the law on energy transition makes this possible, notably with the strengthening of citizen participation. The author evokes some French local experiments and the case of Germany where this participation is already very much developed

Stochastic Wheel-Slip Compensation Based Robot Localization and Mapping

Directory of Open Access Journals (Sweden)

SIDHARTHAN, R. K.

2016-05-01

Full Text Available Wheel slip compensation is vital for building accurate and reliable dead reckoning based robot localization and mapping algorithms. This investigation presents stochastic slip compensation scheme for robot localization and mapping. Main idea of the slip compensation technique is to use wheel-slip data obtained from experiments to model the variations in slip velocity as Gaussian distributions. This leads to a family of models that are switched depending on the input command. To obtain the wheel-slip measurements, experiments are conducted on a wheeled mobile robot and the measurements thus obtained are used to build the Gaussian models. Then the localization and mapping algorithm is tested on an experimental terrain and a new metric called the map spread factor is used to evaluate the ability of the slip compensation technique. Our results clearly indicate that the proposed methodology improves the accuracy by 72.55% for rotation and 66.67% for translation motion as against an uncompensated mapping system. The proposed compensation technique eliminates the need for extro receptive sensors for slip compensation, complex feature extraction and association algorithms. As a result, we obtain a simple slip compensation scheme for localization and mapping.

Combined discriminative global and generative local models for visual tracking

Science.gov (United States)

Zhao, Liujun; Zhao, Qingjie; Chen, Yanming; Lv, Peng

2016-03-01

It is a challenging task to develop an effective visual tracking algorithm due to factors such as pose variation, rotation, and so on. Combined discriminative global and generative local appearance models are proposed to address this problem. Specifically, we develop a compact global object representation by extracting the low-frequency coefficients of the color and texture of the object based on two-dimensional discrete cosine transform. Then, with the global appearance representation, we learn a discriminative metric classifier in an online fashion to differentiate the target object from its background, which is very important to robustly indicate the changes in appearance. Second, we develop a new generative local model that exploits the scale invariant feature transform and its spatial geometric information. To make use of the advantages of the global discriminative model and the generative local model, we incorporate them into Bayesian inference framework. In this framework, the complementary models help the tracker locate the target more accurately. Furthermore, we use different mechanisms to update global and local templates to capture appearance changes. The experimental results demonstrate that the proposed approach performs favorably against state-of-the-art methods in terms of accuracy.

Modelling Danish local CHP on market conditions

DEFF Research Database (Denmark)

Ravn, Hans V.; Riisom, Jannik; Schaumburg-Müller, Camilla

2004-01-01

with the liberalisation process of the energy sectors of the EU countries, it is however anticipated that Danish local CHP are to begin operating on market conditions within the year 2005. This means that the income that the local CHPs previously gained from selling electricity at the feed-in tariff is replaced in part...... the consequences of acting in a liberalised market for a given CHP plant, based on the abovementioned bottom-up model. The key assumption determining the bottom line is the electricity spot price. The formation of the spot price in the Nordic area depends heavily upon the state of the water reservoirs in Norway...

A local-circulation model for Darrieus vertical-axis wind turbines

Science.gov (United States)

Masse, B.

1986-04-01

A new computational model for the aerodynamics of the vertical-axis wind turbine is presented. Based on the local-circulation method generalized for curved blades, combined with a wake model for the vertical-axis wind turbine, it differs markedly from current models based on variations in the streamtube momentum and vortex models using the lifting-line theory. A computer code has been developed to calculate the loads and performance of the Darrieus vertical-axis wind turbine. The results show good agreement with experimental data and compare well with other methods.

Source Localization with Acoustic Sensor Arrays Using Generative Model Based Fitting with Sparse Constraints

Directory of Open Access Journals (Sweden)

Javier Macias-Guarasa

2012-10-01

Full Text Available This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies.

Papaya Development Model As A Competitive Local Superior Commodity

Directory of Open Access Journals (Sweden)

Reny Sukmawani

2014-12-01

Full Text Available The aim of this research is to study the comparative advantage and papaya competitive and to design its development model by using the approach of local base agriculture development. This research uses survey method. The resulting research shows that papaya is a base commodity that has comparative advantage and competitive. The development papaya in the district of Sukabumi is quite good bases on eight superior creations. But in order to be the main sector in economic development and has a competition, the development of papaya must concern to its influence factors. In supporting papaya development as a competitive local superior commodity, it needs to be done some efforts are as follows: (1 increase a skillful worker; (2 improve business management; (3 increase papaya productivity by using technology and study papaya planted technology in specific local superior commodity; (4 develop the involvement of the business relation; (5 provide market information and information technology network; and (6 improve infrastructures.

Local models and hidden nonlocality in Quantum Theory

OpenAIRE

Guerini, Leonardo

2014-01-01

This Master's thesis has two central subjects: the simulation of correlations generated by local measurements on entangled quantum states by local hidden-variables models and the revelation of hidden nonlocality. We present and detail the Werner's local model and the hidden nonlocality of some Werner states of dimension $d\\geq5$, the Gisin-Degorre's local model for a Werner state of dimension $d=2$ and the local model of Hirsch et al. for mixtures of the singlet state and noise, all of them f...

Coupling of nonlocal and local continuum models by the Arlequinapproach

KAUST Repository

Han, Fei

2011-08-09

The objective of this work is to develop and apply the Arlequin framework to couple nonlocal and local continuum mechanical models. A mechanically-based model of nonlocal elasticity, which involves both contact and long-range forces, is used for the \\'fine scale\\' description in which nonlocal interactions are considered to have non-negligible effects. Classical continuum mechanics only involving local contact forces is introduced for the rest of the structure where these nonlocal effects can be neglected. Both models overlap in a coupling subdomain called the \\'gluing area\\' in which the total energy is separated into nonlocal and local contributions by complementary weight functions. A weak compatibility is ensured between kinematics of both models using Lagrange multipliers over the gluing area. The discrete formulation of this specific Arlequin coupling framework is derived and fully described. The validity and limits of the technique are demonstrated through two-dimensional numerical applications and results are compared against those of the fully nonlocal elasticity method. © 2011 John Wiley & Sons, Ltd.

Strong Local-Nonlocal Coupling for Integrated Fracture Modeling

Energy Technology Data Exchange (ETDEWEB)

Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Silling, Stewart A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mitchell, John A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Seleson, Pablo D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Parks, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Turner, Daniel Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Burnett, Damon J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ostien, Jakob [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Gunzburger, Max [Florida State Univ., Tallahassee, FL (United States)

2015-09-01

Peridynamics, a nonlocal extension of continuum mechanics, is unique in its ability to capture pervasive material failure. Its use in the majority of system-level analyses carried out at Sandia, however, is severely limited, due in large part to computational expense and the challenge posed by the imposition of nonlocal boundary conditions. Combined analyses in which peridynamics is em- ployed only in regions susceptible to material failure are therefore highly desirable, yet available coupling strategies have remained severely limited. This report is a summary of the Laboratory Directed Research and Development (LDRD) project "Strong Local-Nonlocal Coupling for Inte- grated Fracture Modeling," completed within the Computing and Information Sciences (CIS) In- vestment Area at Sandia National Laboratories. A number of challenges inherent to coupling local and nonlocal models are addressed. A primary result is the extension of peridynamics to facilitate a variable nonlocal length scale. This approach, termed the peridynamic partial stress, can greatly reduce the mathematical incompatibility between local and nonlocal equations through reduction of the peridynamic horizon in the vicinity of a model interface. A second result is the formulation of a blending-based coupling approach that may be applied either as the primary coupling strategy, or in combination with the peridynamic partial stress. This blending-based approach is distinct from general blending methods, such as the Arlequin approach, in that it is specific to the coupling of peridynamics and classical continuum mechanics. Facilitating the coupling of peridynamics and classical continuum mechanics has also required innovations aimed directly at peridynamic models. Specifically, the properties of peridynamic constitutive models near domain boundaries and shortcomings in available discretization strategies have been addressed. The results are a class of position-aware peridynamic constitutive laws for

Computer-Aided Evaluation of Screening Mammograms Based on Local Texture Models

Czech Academy of Sciences Publication Activity Database

Grim, Jiří; Somol, Petr; Haindl, Michal; Daneš, J.

2009-01-01

Roč. 18, č. 4 (2009), s. 765-773 ISSN 1057-7149 R&D Projects: GA ČR GA102/07/1594; GA ČR GA102/08/0593; GA MŠk 1M0572 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Screening mammography * texture information * local statistical model * Gaussian mixture Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.848, year: 2009

Assessment of Constraint Effects based on Local Approach

International Nuclear Information System (INIS)

Lee, Tae Rin; Chang, Yoon Suk; Choi, Jae Boong; Seok, Chang Sung; Kim, Young Jin

2005-01-01

Traditional fracture mechanics has been used to ensure a structural integrity, in which the geometry independence is assumed in crack tip deformation and fracture toughness. However, the assumption is applicable only within limited conditions. To address fracture covering a broad range of loading and crack geometries, two-parameter global approach and local approach have been proposed. The two-parameter global approach can quantify the load and crack geometry effects by adopting T-stress or Q-parameter but time-consuming and expensive since lots of experiments and finite element (FE) analyses are necessary. On the other hand, the local approach evaluates the load and crack geometry effects based on damage model. Once material specific fitting constants are determined from a few experiments and FE analyses, the fracture resistance characteristics can be obtained by numerical simulation. The purpose of this paper is to investigate constraint effects for compact tension (CT) specimens with different in-plane or out-of-plane size using local approach. Both modified GTN model and Rousselier model are adopted to examine the ductile fracture behavior of SA515 Gr.60 carbon steel at high temperature. The fracture resistance (J-R) curves are estimated through numerical analysis, compared with corresponding experimental results and, then, crack length, thickness and side-groove effects are evaluated

A statistical model to estimate the local vulnerability to severe weather

Science.gov (United States)

Pardowitz, Tobias

2018-06-01

We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

Bi-local holography in the SYK model: perturbations

Energy Technology Data Exchange (ETDEWEB)

Jevicki, Antal; Suzuki, Kenta [Department of Physics, Brown University,182 Hope Street, Providence, RI 02912 (United States)

2016-11-08

We continue the study of the Sachdev-Ye-Kitaev model in the Large N limit. Following our formulation in terms of bi-local collective fields with dynamical reparametrization symmetry, we perform perturbative calculations around the conformal IR point. These are based on an ε expansion which allows for analytical evaluation of correlators and finite temperature quantities.

Using a NIATx based local learning collaborative for performance improvement.

Science.gov (United States)

Roosa, Mathew; Scripa, Joseph S; Zastowny, Thomas R; Ford, James H

2011-11-01

Local governments play an important role in improving substance abuse and mental health services. The structure of the local learning collaborative requires careful attention to old relationships and challenges local governmental leaders to help move participants from a competitive to collaborative environment. This study describes one county's experience applying the NIATx process improvement model via a local learning collaborative. Local substance abuse and mental health agencies participated in two local learning collaboratives designed to improve client retention in substance abuse treatment and client access to mental health services. Results of changes implemented at the provider level on access and retention are outlined. The process of implementing evidence-based practices by using the Plan-Do-Study-Act rapid-cycle change is a powerful combination for change at the local level. Key lessons include: creating a clear plan and shared vision, recognizing that one size does not fit all, using data can help fuel participant engagement, a long collaborative may benefit from breaking it into smaller segments, and paying providers to offset costs of participation enhances their engagement. The experience gained in Onondaga County, New York, offers insights that serve as a foundation for using the local learning collaborative in other community-based organizations. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

Directory of Open Access Journals (Sweden)

Hyungjin Kim

2015-08-01

Full Text Available Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera.

Science.gov (United States)

Kim, Hyungjin; Lee, Donghwa; Oh, Taekjun; Choi, Hyun-Taek; Myung, Hyun

2015-08-31

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments.

Investigation of model based beamforming and Bayesian inversion signal processing methods for seismic localization of underground sources

DEFF Research Database (Denmark)

Oh, Geok Lian; Brunskog, Jonas

2014-01-01

Techniques have been studied for the localization of an underground source with seismic interrogation signals. Much of the work has involved defining either a P-wave acoustic model or a dispersive surface wave model to the received signal and applying the time-delay processing technique and frequ...... that for field data, inversion for localization is most advantageous when the forward model completely describe all the elastic wave components as is the case of the FDTD 3D elastic model....

The Environmental Virtual Observatory (EVO) local exemplar: A cloud based local landscape learning visualisation tool for communicating flood risk to catchment stakeholders

Science.gov (United States)

Wilkinson, Mark; Beven, Keith; Brewer, Paul; El-khatib, Yehia; Gemmell, Alastair; Haygarth, Phil; Mackay, Ellie; Macklin, Mark; Marshall, Keith; Quinn, Paul; Stutter, Marc; Thomas, Nicola; Vitolo, Claudia

2013-04-01

Today's world is dominated by a wide range of informatics tools that are readily available to a wide range of stakeholders. There is growing recognition that the appropriate involvement of local communities in land and water management decisions can result in multiple environmental, economic and social benefits. Therefore, local stakeholder groups are increasingly being asked to participate in decision making alongside policy makers, government agencies and scientists. As such, addressing flooding issues requires new ways of engaging with the catchment and its inhabitants at a local level. To support this, new tools and approaches are required. The growth of cloud based technologies offers new novel ways to facilitate this process of exchange of information in earth sciences. The Environmental Virtual Observatory Pilot project (EVOp) is a new initiative from the UK Natural Environment Research Council (NERC) designed to deliver proof of concept for new tools and approaches to support the challenges as outlined above (http://www.evo-uk.org/). The long term vision of the Environmental Virtual Observatory is to: • Make environmental data more visible and accessible to a wide range of potential users including public good applications; • Provide tools to facilitate the integrated analysis of data, greater access to added knowledge and expert analysis and visualisation of the results; • Develop new, added-value knowledge from public and private sector data assets to help tackle environmental challenges. As part of the EVO pilot, an interactive cloud based tool has been developed with local stakeholders. The Local Landscape Visualisation Tool attempts to communicate flood risk in local impacted communities. The tool has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. This tool (assessable via a web portal) combines numerous cloud based tools and services, local catchment datasets, hydrological models and

More about the comparison of local and non-local NN interaction models

International Nuclear Information System (INIS)

Amghar, A.; Desplanques, B.

2003-01-01

The effect of non-locality in the NN interaction with an off-energy shell character has been studied in the past in relation with the possibility that some models could be approximately phase-shifts equivalent. This work is extended to a non-locality implying terms that involve an anticommutator with the operator p 2 . It includes both scalar and tensor components. The most recent 'high accuracy' models are considered in the analysis. After studying the deuteron wave functions, electromagnetic properties of various models are compared with the idea that these ones differ by their non-locality but are equivalent up to a unitary transformation. It is found that the extra non-local tensor interaction considered in this work tends to re-enforce the role of the term considered in previous works, allowing one to explain almost completely the difference in the deuteron D-state probabilities evidenced by the comparison of the Bonn-QB and Paris models for instance. Conclusions for the effect of the non-local scalar interaction are not so clear. In many cases, it was found that these terms could explain part of the differences that the comparison of predictions for various models evidences but cases where they could not were also found. Some of these last ones have been analyzed in order to pointing out the origin of the failure

Dynamics Modeling and Analysis of Local Fault of Rolling Element Bearing

Directory of Open Access Journals (Sweden)

Lingli Cui

2015-01-01

Full Text Available This paper presents a nonlinear vibration model of rolling element bearings with 5 degrees of freedom based on Hertz contact theory and relevant bearing knowledge of kinematics and dynamics. The slipping of ball, oil film stiffness, and the nonlinear time-varying stiffness of the bearing are taken into consideration in the model proposed here. The single-point local fault model of rolling element bearing is introduced into the nonlinear model with 5 degrees of freedom according to the loss of the contact deformation of ball when it rolls into and out of the local fault location. The functions of spall depth corresponding to defects of different shapes are discussed separately in this paper. Then the ode solver in Matlab is adopted to perform a numerical solution on the nonlinear vibration model to simulate the vibration response of the rolling elements bearings with local fault. The simulation signals analysis results show a similar behavior and pattern to that observed in the processed experimental signals of rolling element bearings in both time domain and frequency domain which validated the nonlinear vibration model proposed here to generate typical rolling element bearings local fault signals for possible and effective fault diagnostic algorithms research.

Energy-Based Acoustic Source Localization Methods: A Survey

Directory of Open Access Journals (Sweden)

Wei Meng

2017-02-01

Full Text Available Energy-based source localization is an important problem in wireless sensor networks (WSNs, which has been studied actively in the literature. Numerous localization algorithms, e.g., maximum likelihood estimation (MLE and nonlinear-least-squares (NLS methods, have been reported. In the literature, there are relevant review papers for localization in WSNs, e.g., for distance-based localization. However, not much work related to energy-based source localization is covered in the existing review papers. Energy-based methods are proposed and specially designed for a WSN due to its limited sensor capabilities. This paper aims to give a comprehensive review of these different algorithms for energy-based single and multiple source localization problems, their merits and demerits and to point out possible future research directions.

SU-E-T-144: Bayesian Inference of Local Relapse Data Using a Poisson-Based Tumour Control Probability Model

Energy Technology Data Exchange (ETDEWEB)

La Russa, D [The Ottawa Hospital Cancer Centre, Ottawa, ON (Canada)

2015-06-15

Purpose: The purpose of this project is to develop a robust method of parameter estimation for a Poisson-based TCP model using Bayesian inference. Methods: Bayesian inference was performed using the PyMC3 probabilistic programming framework written in Python. A Poisson-based TCP regression model that accounts for clonogen proliferation was fit to observed rates of local relapse as a function of equivalent dose in 2 Gy fractions for a population of 623 stage-I non-small-cell lung cancer patients. The Slice Markov Chain Monte Carlo sampling algorithm was used to sample the posterior distributions, and was initiated using the maximum of the posterior distributions found by optimization. The calculation of TCP with each sample step required integration over the free parameter α, which was performed using an adaptive 24-point Gauss-Legendre quadrature. Convergence was verified via inspection of the trace plot and posterior distribution for each of the fit parameters, as well as with comparisons of the most probable parameter values with their respective maximum likelihood estimates. Results: Posterior distributions for α, the standard deviation of α (σ), the average tumour cell-doubling time (Td), and the repopulation delay time (Tk), were generated assuming α/β = 10 Gy, and a fixed clonogen density of 10{sup 7} cm−{sup 3}. Posterior predictive plots generated from samples from these posterior distributions are in excellent agreement with the observed rates of local relapse used in the Bayesian inference. The most probable values of the model parameters also agree well with maximum likelihood estimates. Conclusion: A robust method of performing Bayesian inference of TCP data using a complex TCP model has been established.

Visual-based simultaneous localization and mapping and global positioning system correction for geo-localization of a mobile robot

International Nuclear Information System (INIS)

Berrabah, Sid Ahmed; Baudoin, Yvan; Sahli, Hichem

2011-01-01

This paper introduces an approach combining visual-based simultaneous localization and mapping (V-SLAM) and global positioning system (GPS) correction for accurate multi-sensor localization of an outdoor mobile robot in geo-referenced maps. The proposed framework combines two extended Kalman filters (EKF); the first one, referred to as the integration filter, is dedicated to the improvement of the GPS localization based on data from an inertial navigation system and wheels' encoders. The second EKF implements the V-SLAM process. The linear and angular velocities in the dynamic model of the V-SLAM EKF filter are given by the GPS/INS/Encoders integration filter. On the other hand, the output of the V-SLAM EKF filter is used to update the dynamics estimation in the integration filter and therefore the geo-referenced localization. This solution increases the accuracy and the robustness of the positioning during GPS outage and allows SLAM in less featured environments

Local load-sharing fiber bundle model in higher dimensions.

Science.gov (United States)

Sinha, Santanu; Kjellstadli, Jonas T; Hansen, Alex

2015-08-01

We consider the local load-sharing fiber bundle model in one to five dimensions. Depending on the breaking threshold distribution of the fibers, there is a transition where the fracture process becomes localized. In the localized phase, the model behaves as the invasion percolation model. The difference between the local load-sharing fiber bundle model and the equal load-sharing fiber bundle model vanishes with increasing dimensionality with the characteristics of a power law.

Gauge threshold corrections for local string models

International Nuclear Information System (INIS)

Conlon, Joseph P.

2009-01-01

We study gauge threshold corrections for local brane models embedded in a large compact space. A large bulk volume gives important contributions to the Konishi and super-Weyl anomalies and the effective field theory analysis implies the unification scale should be enhanced in a model-independent way from M s to RM s . For local D3/D3 models this result is supported by the explicit string computations. In this case the scale RM s comes from the necessity of global cancellation of RR tadpoles sourced by the local model. We also study D3/D7 models and discuss discrepancies with the effective field theory analysis. We comment on phenomenological implications for gauge coupling unification and for the GUT scale.

A Non-local Model for Transient Moisture Flow in Unsaturated Soils Based on the Peridynamic Theory

Science.gov (United States)

Jabakhanji, R.; Mohtar, R. H.

2012-12-01

A non-local, gradient free, formulation of the porous media flow problem in unsaturated soils was derived. It parallels the peridynamic theory, a non-local reformulation of solid mechanics presented by Silling. In the proposed model, the evolution of the state of a material point is driven by pairwise interactions with other points across finite distances. Flow and changes in moisture are the result of these interactions. Instead of featuring local gradients, the proposed model expresses the flow as a functional integral of the hydraulic potential field. The absence of spatial gradients, undefined at or on discontinuities, makes the model a good candidate for flow simulations in fractured soils. It also lends itself to coupling with peridynamic mechanical models for simulating crack formation triggered by shrinkage and swelling, and assessing their potential impact on a wide range of processes, such as infiltration, contaminant transport, slope stability and integrity of clay barriers. A description of the concept and an outline of the derivation and numerical implementation are presented. Simulation results of infiltration and drainage for 1D, single and two-layers soil columns, for three different soil types are also presented. The same simulations are repeated using HYDRUS-1D, a computer model using the classic local flow equation. We show that the proposed non-local formulation successfully reproduces the results from HYDRUS-1D. S.A. Silling, "Reformulation of Elasticity Theory for Discontinuities and Long-range Forces," Journal of the Mechanics and Physics of Solids 48, no. 1 (January 2000): 175-209. J. Simunek, M. Sejna, and M.T. Van Genuchten, "The HYDRUS-1D Software Package for Simulating the One-dimensional Movement of Water, Heat, and Multiple Solutes in Variably-saturated Media," University of California, Riverside, Research Reports 240 (2005).

Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network

Directory of Open Access Journals (Sweden)

Zahid Farid

2016-01-01

Full Text Available In indoor environments, WiFi (RSS based localization is sensitive to various indoor fading effects and noise during transmission, which are the main causes of localization errors that affect its accuracy. Keeping in view those fading effects, positioning systems based on a single technology are ineffective in performing accurate localization. For this reason, the trend is toward the use of hybrid positioning systems (combination of two or more wireless technologies in indoor/outdoor localization scenarios for getting better position accuracy. This paper presents a hybrid technique to implement indoor localization that adopts fingerprinting approaches in both WiFi and Wireless Sensor Networks (WSNs. This model exploits machine learning, in particular Artificial Natural Network (ANN techniques, for position calculation. The experimental results show that the proposed hybrid system improved the accuracy, reducing the average distance error to 1.05 m by using ANN. Applying Genetic Algorithm (GA based optimization technique did not incur any further improvement to the accuracy. Compared to the performance of GA optimization, the nonoptimized ANN performed better in terms of accuracy, precision, stability, and computational time. The above results show that the proposed hybrid technique is promising for achieving better accuracy in real-world positioning applications.

Adaptation Method for Overall and Local Performances of Gas Turbine Engine Model

Science.gov (United States)

Kim, Sangjo; Kim, Kuisoon; Son, Changmin

2018-04-01

An adaptation method was proposed to improve the modeling accuracy of overall and local performances of gas turbine engine. The adaptation method was divided into two steps. First, the overall performance parameters such as engine thrust, thermal efficiency, and pressure ratio were adapted by calibrating compressor maps, and second, the local performance parameters such as temperature of component intersection and shaft speed were adjusted by additional adaptation factors. An optimization technique was used to find the correlation equation of adaptation factors for compressor performance maps. The multi-island genetic algorithm (MIGA) was employed in the present optimization. The correlations of local adaptation factors were generated based on the difference between the first adapted engine model and performance test data. The proposed adaptation method applied to a low-bypass ratio turbofan engine of 12,000 lb thrust. The gas turbine engine model was generated and validated based on the performance test data in the sea-level static condition. In flight condition at 20,000 ft and 0.9 Mach number, the result of adapted engine model showed improved prediction in engine thrust (overall performance parameter) by reducing the difference from 14.5 to 3.3%. Moreover, there was further improvement in the comparison of low-pressure turbine exit temperature (local performance parameter) as the difference is reduced from 3.2 to 0.4%.

Improved Application of Local Models to Steel Corrosion in Lead-Bismuth Loops

International Nuclear Information System (INIS)

Zhang Jinsuo; Li Ning

2003-01-01

The corrosion of steels exposed to flowing liquid metals is influenced by local and global conditions of flow systems. The present study improves the previous local models when applied to closed loops by incorporating some global condition effects. In particular the bulk corrosion product concentration is calculated based on balancing the dissolution and precipitation in the entire closed loop. Mass transfer expressions developed in aqueous medium and an analytical expression are tested in the liquid-metal environments. The improved model is applied to a pure lead loop and produces results closer to the experimental data than the previous local models do. The model is also applied to a lead-bismuth eutectic (LBE) test loop. Systematic studies illustrate the effects of the flow rate, the oxygen concentration in LBE, and the temperature profile on the corrosion rate

Fusion-based multi-target tracking and localization for intelligent surveillance systems

Science.gov (United States)

Rababaah, Haroun; Shirkhodaie, Amir

2008-04-01

In this paper, we have presented two approaches addressing visual target tracking and localization in complex urban environment. The two techniques presented in this paper are: fusion-based multi-target visual tracking, and multi-target localization via camera calibration. For multi-target tracking, the data fusion concepts of hypothesis generation/evaluation/selection, target-to-target registration, and association are employed. An association matrix is implemented using RGB histograms for associated tracking of multi-targets of interests. Motion segmentation of targets of interest (TOI) from the background was achieved by a Gaussian Mixture Model. Foreground segmentation, on other hand, was achieved by the Connected Components Analysis (CCA) technique. The tracking of individual targets was estimated by fusing two sources of information, the centroid with the spatial gating, and the RGB histogram association matrix. The localization problem is addressed through an effective camera calibration technique using edge modeling for grid mapping (EMGM). A two-stage image pixel to world coordinates mapping technique is introduced that performs coarse and fine location estimation of moving TOIs. In coarse estimation, an approximate neighborhood of the target position is estimated based on nearest 4-neighbor method, and in fine estimation, we use Euclidean interpolation to localize the position within the estimated four neighbors. Both techniques were tested and shown reliable results for tracking and localization of Targets of interests in complex urban environment.

Securing Localization With Hidden and Mobile Base Stations

DEFF Research Database (Denmark)

Capkun, Srdjan; Srivastava, Mani; Cagalj, Mario

2006-01-01

localization based on hidden and mobile base stations. Our approach enables secure localization with a broad spectrum of localization techniques: ultrasonic or radio, based on received signal strength or signal time of flight. Through several examples we show how this approach can be used to secure nodecentric...

Local-metrics error-based Shepard interpolation as surrogate for highly non-linear material models in high dimensions

Science.gov (United States)

Lorenzi, Juan M.; Stecher, Thomas; Reuter, Karsten; Matera, Sebastian

2017-10-01

Many problems in computational materials science and chemistry require the evaluation of expensive functions with locally rapid changes, such as the turn-over frequency of first principles kinetic Monte Carlo models for heterogeneous catalysis. Because of the high computational cost, it is often desirable to replace the original with a surrogate model, e.g., for use in coupled multiscale simulations. The construction of surrogates becomes particularly challenging in high-dimensions. Here, we present a novel version of the modified Shepard interpolation method which can overcome the curse of dimensionality for such functions to give faithful reconstructions even from very modest numbers of function evaluations. The introduction of local metrics allows us to take advantage of the fact that, on a local scale, rapid variation often occurs only across a small number of directions. Furthermore, we use local error estimates to weigh different local approximations, which helps avoid artificial oscillations. Finally, we test our approach on a number of challenging analytic functions as well as a realistic kinetic Monte Carlo model. Our method not only outperforms existing isotropic metric Shepard methods but also state-of-the-art Gaussian process regression.

Gauging Non-local Quark Models

International Nuclear Information System (INIS)

Broniowski, W.

1999-09-01

The gauge effective quark model with non-local interactions is considered. It is shown how this approach regularize the theory in such a way that the anomalies are preserved and charges are properly quantized. With non-local interactions the effective action is finite to all orders in the loop expansion and there is no need to introduce the quark momentum cut-off parameter

Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.

Science.gov (United States)

Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel

2017-07-28

New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.

Local Model Predictive Control for T-S Fuzzy Systems.

Science.gov (United States)

Lee, Donghwan; Hu, Jianghai

2017-09-01

In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem. The local stability analysis, the estimation of the domain of attraction, and feasibility of the proposed MPC are proved. Examples are given to demonstrate the advantages of the suggested MPC over existing approaches.

LOCAL TEXTURE DESCRIPTION FRAMEWORK FOR TEXTURE BASED FACE RECOGNITION

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R. Reena Rose

2014-02-01

Full Text Available Texture descriptors have an important role in recognizing face images. However, almost all the existing local texture descriptors use nearest neighbors to encode a texture pattern around a pixel. But in face images, most of the pixels have similar characteristics with that of its nearest neighbors because the skin covers large area in a face and the skin tone at neighboring regions are same. Therefore this paper presents a general framework called Local Texture Description Framework that uses only eight pixels which are at certain distance apart either circular or elliptical from the referenced pixel. Local texture description can be done using the foundation of any existing local texture descriptors. In this paper, the performance of the proposed framework is verified with three existing local texture descriptors Local Binary Pattern (LBP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs for the five issues viz. facial expression, partial occlusion, illumination variation, pose variation and general recognition. Five benchmark databases JAFFE, Essex, Indian faces, AT&T and Georgia Tech are used for the experiments. Experimental results demonstrate that even with less number of patterns, the proposed framework could achieve higher recognition accuracy than that of their base models.

A Local Poisson Graphical Model for inferring networks from sequencing data.

Science.gov (United States)

Allen, Genevera I; Liu, Zhandong

2013-09-01

Gaussian graphical models, a class of undirected graphs or Markov Networks, are often used to infer gene networks based on microarray expression data. Many scientists, however, have begun using high-throughput sequencing technologies such as RNA-sequencing or next generation sequencing to measure gene expression. As the resulting data consists of counts of sequencing reads for each gene, Gaussian graphical models are not optimal for this discrete data. In this paper, we propose a novel method for inferring gene networks from sequencing data: the Local Poisson Graphical Model. Our model assumes a Local Markov property where each variable conditional on all other variables is Poisson distributed. We develop a neighborhood selection algorithm to fit our model locally by performing a series of l1 penalized Poisson, or log-linear, regressions. This yields a fast parallel algorithm for estimating networks from next generation sequencing data. In simulations, we illustrate the effectiveness of our methods for recovering network structure from count data. A case study on breast cancer microRNAs (miRNAs), a novel application of graphical models, finds known regulators of breast cancer genes and discovers novel miRNA clusters and hubs that are targets for future research.

Mathematical programming solver based on local search

CERN Document Server

Gardi, Frédéric; Darlay, Julien; Estellon, Bertrand; Megel, Romain

2014-01-01

This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kind of mathematical programming solver, namely LocalSolver, based on neighborhood search. First, an iconoclast methodology is presented to design and engineer local search algorithms. The authors' concern about industrializing local search approaches is of particular interest for practitioners. This methodology is applied to solve two industrial problems with high economic stakes. Software based on local search induces ex...

Atomistic simulation of processes in Ni-base alloys with account for local relaxations

International Nuclear Information System (INIS)

Bursik, Jiri

2007-01-01

Ordering in Ni-base superalloys is the crucial process controlling the development of the characteristic two-phase microstructure and subsequently the mechanical properties. Systems containing up to six alloying elements typical of advanced Ni-based superalloys are modelled in this work using a Monte Carlo approach with phenomenological Lennard-Jones pair potentials and interactions up to the third coordination sphere. Three-dimensional crystal block is used with over 10 5 atoms. Molecular dynamics approach is used to relax local atomic positions in course of ordering processes under applied stress. The importance of taking into account both relaxation of modelled block dimensions and relaxation of local atomic positions is discussed

Global and local level density models

International Nuclear Information System (INIS)

Koning, A.J.; Hilaire, S.; Goriely, S.

2008-01-01

Four different level density models, three phenomenological and one microscopic, are consistently parameterized using the same set of experimental observables. For each of the phenomenological models, the Constant Temperature Model, the Back-shifted Fermi gas Model and the Generalized Superfluid Model, a version without and with explicit collective enhancement is considered. Moreover, a recently published microscopic combinatorial model is compared with the phenomenological approaches and with the same set of experimental data. For each nuclide for which sufficient experimental data exists, a local level density parameterization is constructed for each model. Next, these local models have helped to construct global level density prescriptions, to be used for cases for which no experimental data exists. Altogether, this yields a collection of level density formulae and parameters that can be used with confidence in nuclear model calculations. To demonstrate this, a large-scale validation with experimental discrete level schemes and experimental cross sections and neutron emission spectra for various different reaction channels has been performed

Local discrete symmetries from superstring derived models

International Nuclear Information System (INIS)

Faraggi, A.E.

1996-10-01

Discrete and global symmetries play an essential role in many extensions of the Standard Model, for example, to preserve the proton lifetime, to prevent flavor changing neutral currents, etc. An important question is how can such symmetries survive in a theory of quantum gravity, like superstring theory. In a specific string model the author illustrates how local discrete symmetries may arise in string models and play an important role in preventing fast proton decay and flavor changing neutral currents. The local discrete symmetry arises due to the breaking of the non-Abelian gauge symmetries by Wilson lines in the superstring models and forbids, for example dimension five operators which mediate rapid proton decay, to all orders of nonrenormalizable terms. In the context of models of unification of the gauge and gravitational interactions, it is precisely this type of local discrete symmetries that must be found in order to insure that a given model is not in conflict with experimental observations

Joint Testlet Cognitive Diagnosis Modeling for Paired Local Item Dependence in Response Times and Response Accuracy

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Peida Zhan

2018-04-01

Full Text Available In joint models for item response times (RTs and response accuracy (RA, local item dependence is composed of local RA dependence and local RT dependence. The two components are usually caused by the same common stimulus and emerge as pairs. Thus, the violation of local item independence in the joint models is called paired local item dependence. To address the issue of paired local item dependence while applying the joint cognitive diagnosis models (CDMs, this study proposed a joint testlet cognitive diagnosis modeling approach. The proposed approach is an extension of Zhan et al. (2017 and it incorporates two types of random testlet effect parameters (one for RA and the other for RTs to account for paired local item dependence. The model parameters were estimated using the full Bayesian Markov chain Monte Carlo (MCMC method. The 2015 PISA computer-based mathematics data were analyzed to demonstrate the application of the proposed model. Further, a brief simulation study was conducted to demonstrate the acceptable parameter recovery and the consequence of ignoring paired local item dependence.

Estimation and prediction under local volatility jump-diffusion model

Science.gov (United States)

Kim, Namhyoung; Lee, Younhee

2018-02-01

Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

A systematic study of ball passing frequencies based on dynamic modeling of rolling ball bearings with localized surface defects

Science.gov (United States)

Niu, Linkai; Cao, Hongrui; He, Zhengjia; Li, Yamin

2015-11-01

Ball passing frequencies (BPFs) are very important features for condition monitoring and fault diagnosis of rolling ball bearings. The ball passing frequency on outer raceway (BPFO) and the ball passing frequency on inner raceway (BPFI) are usually calculated by two well-known kinematics equations. In this paper, a systematic study of BPFs of rolling ball bearings is carried out. A novel method for accurately calculating BPFs based on a complete dynamic model of rolling ball bearings with localized surface defects is proposed. In the used dynamic model, three-dimensional motions, relative slippage, cage effects and localized surface defects are all considered. Moreover, localized surface defects are modeled accurately with consideration of the finite size of the ball, the additional clearance due to material absence, and changes of contact force directions. The reasonability of the proposed method for the prediction of dynamic behaviors of actual ball bearings with localized surface defects and for the calculation of BPFs is discussed by investigating the motion characteristics of a ball when it rolls through a defect. Parametric investigation shows that the shaft speed, external loads, the friction coefficient, raceway groove curvature factors, the initial contact angle, and defect sizes have great effects on BPFs. For a loaded ball bearing, the combination of rolling and sliding in contact region occurs, and the BPFs calculated by simple kinematical relationships are inaccurate, especially for high speed, low external load, and large initial contact angle conditions where severe skidding occurs. The hypothesis that the percentage variation of the spacing between impulses in a defective ball bearing was about 1-2% reported in previous investigations can be satisfied only for the conditions where the skidding effect in a bearing is slight. Finally, the proposed method is verified with two experiments.

Improved non-local electron thermal transport model for two-dimensional radiation hydrodynamics simulations

Science.gov (United States)

Cao, Duc; Moses, Gregory; Delettrez, Jacques

2015-08-01

An implicit, non-local thermal conduction algorithm based on the algorithm developed by Schurtz, Nicolai, and Busquet (SNB) [Schurtz et al., Phys. Plasmas 7, 4238 (2000)] for non-local electron transport is presented and has been implemented in the radiation-hydrodynamics code DRACO. To study the model's effect on DRACO's predictive capability, simulations of shot 60 303 from OMEGA are completed using the iSNB model, and the computed shock speed vs. time is compared to experiment. Temperature outputs from the iSNB model are compared with the non-local transport model of Goncharov et al. [Phys. Plasmas 13, 012702 (2006)]. Effects on adiabat are also examined in a polar drive surrogate simulation. Results show that the iSNB model is not only capable of flux-limitation but also preheat prediction while remaining numerically robust and sacrificing little computational speed. Additionally, the results provide strong incentive to further modify key parameters within the SNB theory, namely, the newly introduced non-local mean free path. This research was supported by the Laboratory for Laser Energetics of the University of Rochester.

A local-world evolving hypernetwork model

International Nuclear Information System (INIS)

Yang Guang-Yong; Liu Jian-Guo

2014-01-01

Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mechanisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is γ = 2 + 1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypernetwork model shares the scale-free and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems. (interdisciplinary physics and related areas of science and technology)

New Temperature-based Models for Predicting Global Solar Radiation

International Nuclear Information System (INIS)

Hassan, Gasser E.; Youssef, M. Elsayed; Mohamed, Zahraa E.; Ali, Mohamed A.; Hanafy, Ahmed A.

2016-01-01

Highlights: • New temperature-based models for estimating solar radiation are investigated. • The models are validated against 20-years measured data of global solar radiation. • The new temperature-based model shows the best performance for coastal sites. • The new temperature-based model is more accurate than the sunshine-based models. • The new model is highly applicable with weather temperature forecast techniques. - Abstract: This study presents new ambient-temperature-based models for estimating global solar radiation as alternatives to the widely used sunshine-based models owing to the unavailability of sunshine data at all locations around the world. Seventeen new temperature-based models are established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. These models are developed using a 20-year measured dataset of global solar radiation for the case study location (Lat. 30°51′N and long. 29°34′E), and then, the general formulae of the newly suggested models are examined for ten different locations around Egypt. Moreover, the local formulae for the models are established and validated for two coastal locations where the general formulae give inaccurate predictions. Mostly common statistical errors are utilized to evaluate the performance of these models and identify the most accurate model. The obtained results show that the local formula for the most accurate new model provides good predictions for global solar radiation at different locations, especially at coastal sites. Moreover, the local and general formulas of the most accurate temperature-based model also perform better than the two most accurate sunshine-based models from the literature. The quick and accurate estimations of the global solar radiation using this approach can be employed in the design and evaluation of performance for

Range-Based Localization in Mobile Sensor Networks

NARCIS (Netherlands)

Dil, B.J.; Dil, B.; Dulman, S.O.; Havinga, Paul J.M.; Romer, K.; Karl, H.; Mattern, F.

2006-01-01

Localization schemes for wireless sensor networks can be classified as range-based or range-free. They differ in the information used for localization. Range-based methods use range measurements, while range-free techniques only use the content of the messages. None of the existing algorithms

Operating cost model for local service airlines

Science.gov (United States)

Anderson, J. L.; Andrastek, D. A.

1976-01-01

Several mathematical models now exist which determine the operating economics for a United States trunk airline. These models are valuable in assessing the impact of new aircraft into an airline's fleet. The use of a trunk airline cost model for the local service airline does not result in representative operating costs. A new model is presented which is representative of the operating conditions and resultant costs for the local service airline. The calculated annual direct and indirect operating costs for two multiequipment airlines are compared with their actual operating experience.

Analysis of Local Financial Management Transparency Based on Websites on Local Government in Java

Directory of Open Access Journals (Sweden)

Anissa Adriana

2018-03-01

Full Text Available The aim of this research is to analyze financial management transparency of local governments in Java using scoring and rating. The financial management transparency of the local governments is scored based on presentation of local financial information uploaded on each local government’s official website in Jawa in the fiscal years 2016.This research is a qualitative research with the object of research is all local government in Java. Data analysis in two levels, namely the transparency of local government financial management and identification of local government characteristics based on transparency of financial management. Data analysis in two levels, namely the transparency of local government financial management and identification of local government characteristics based on transparency of financial management. The results show that the Special Capital Region of Jakarta obtained the highest transparency index, at 58, 02% whereas Madiun Regency received the lowest transparency index, at 3, 40%. The average transparency index in Jawa for the fiscal years 2016 was still low, at only 19, 59%.The conclusion of this research is that Java regional governments consider the transparency of local financial management using less important websites because it is considered as a better thing not delivered to the public.

Assessing Local Model Adequacy in Bayesian Hierarchical Models Using the Partitioned Deviance Information Criterion

Science.gov (United States)

Wheeler, David C.; Hickson, DeMarc A.; Waller, Lance A.

2010-01-01

Many diagnostic tools and goodness-of-fit measures, such as the Akaike information criterion (AIC) and the Bayesian deviance information criterion (DIC), are available to evaluate the overall adequacy of linear regression models. In addition, visually assessing adequacy in models has become an essential part of any regression analysis. In this paper, we focus on a spatial consideration of the local DIC measure for model selection and goodness-of-fit evaluation. We use a partitioning of the DIC into the local DIC, leverage, and deviance residuals to assess local model fit and influence for both individual observations and groups of observations in a Bayesian framework. We use visualization of the local DIC and differences in local DIC between models to assist in model selection and to visualize the global and local impacts of adding covariates or model parameters. We demonstrate the utility of the local DIC in assessing model adequacy using HIV prevalence data from pregnant women in the Butare province of Rwanda during 1989-1993 using a range of linear model specifications, from global effects only to spatially varying coefficient models, and a set of covariates related to sexual behavior. Results of applying the diagnostic visualization approach include more refined model selection and greater understanding of the models as applied to the data. PMID:21243121

A Local-Realistic Model of Quantum Mechanics Based on a Discrete Spacetime

Science.gov (United States)

Sciarretta, Antonio

2018-01-01

This paper presents a realistic, stochastic, and local model that reproduces nonrelativistic quantum mechanics (QM) results without using its mathematical formulation. The proposed model only uses integer-valued quantities and operations on probabilities, in particular assuming a discrete spacetime under the form of a Euclidean lattice. Individual (spinless) particle trajectories are described as random walks. Transition probabilities are simple functions of a few quantities that are either randomly associated to the particles during their preparation, or stored in the lattice nodes they visit during the walk. QM predictions are retrieved as probability distributions of similarly-prepared ensembles of particles. The scenarios considered to assess the model comprise of free particle, constant external force, harmonic oscillator, particle in a box, the Delta potential, particle on a ring, particle on a sphere and include quantization of energy levels and angular momentum, as well as momentum entanglement.

Coupling 3D groundwater modeling with CFC-based age dating to classify local groundwater circulation in an unconfined crystalline aquifer

Science.gov (United States)

Kolbe, Tamara; Marçais, Jean; Thomas, Zahra; Abbott, Benjamin W.; de Dreuzy, Jean-Raynald; Rousseau-Gueutin, Pauline; Aquilina, Luc; Labasque, Thierry; Pinay, Gilles

2016-12-01

Nitrogen pollution of freshwater and estuarine environments is one of the most urgent environmental crises. Shallow aquifers with predominantly local flow circulation are particularly vulnerable to agricultural contaminants. Water transit time and flow path are key controls on catchment nitrogen retention and removal capacity, but the relative importance of hydrogeological and topographical factors in determining these parameters is still uncertain. We used groundwater dating and numerical modeling techniques to assess transit time and flow path in an unconfined aquifer in Brittany, France. The 35.5 km2 study catchment has a crystalline basement underneath a ∼60 m thick weathered and fractured layer, and is separated into a distinct upland and lowland area by an 80 m-high butte. We used groundwater discharge and groundwater ages derived from chlorofluorocarbon (CFC) concentration to calibrate a free-surface flow model simulating groundwater flow circulation. We found that groundwater flow was highly local (mean travel distance = 350 m), substantially smaller than the typical distance between neighboring streams (∼1 km), while CFC-based ages were quite old (mean = 40 years). Sensitivity analysis revealed that groundwater travel distances were not sensitive to geological parameters (i.e. arrangement of geological layers and permeability profile) within the constraints of the CFC age data. However, circulation was sensitive to topography in the lowland area where the water table was near the land surface, and to recharge rate in the upland area where water input modulated the free surface of the aquifer. We quantified these differences with a local groundwater ratio (rGW-LOCAL), defined as the mean groundwater travel distance divided by the mean of the reference surface distances (the distance water would have to travel across the surface of the digital elevation model). Lowland, rGW-LOCAL was near 1, indicating primarily topographical controls. Upland, rGW-LOCAL

Cluster-based global firms' use of local capabilities

DEFF Research Database (Denmark)

Andersen, Poul Houman; Bøllingtoft, Anne

2011-01-01

Purpose – Despite growing interest in clusters role for the global competitiveness of firms, there has been little research into how globalization affects cluster-based firms’ (CBFs) use of local knowledge resources and the combination of local and global knowledge used. Using the cluster......’s knowledge base as a mediating variable, the purpose of this paper is to examine how globalization affected the studied firms’ use of local cluster-based knowledge, integration of local and global knowledge, and networking capabilities. Design/methodology/approach – Qualitative case studies of nine firms...... in three clusters strongly affected by increasing global division of labour. Findings – The paper suggests that globalization has affected how firms use local resources and combine local and global knowledge. Unexpectedly, clustered firms with explicit procedures and established global fora for exchanging...

Developing a Local Neurofuzzy Model for Short-Term Wind Power Forecasting

Directory of Open Access Journals (Sweden)

E. Faghihnia

2014-01-01

Full Text Available Large scale integration of wind generation capacity into power systems introduces operational challenges due to wind power uncertainty and variability. Therefore, accurate wind power forecast is important for reliable and economic operation of the power systems. Complexities and nonlinearities exhibited by wind power time series necessitate use of elaborative and sophisticated approaches for wind power forecasting. In this paper, a local neurofuzzy (LNF approach, trained by the polynomial model tree (POLYMOT learning algorithm, is proposed for short-term wind power forecasting. The LNF approach is constructed based on the contribution of local polynomial models which can efficiently model wind power generation. Data from Sotavento wind farm in Spain was used to validate the proposed LNF approach. Comparison between performance of the proposed approach and several recently published approaches illustrates capability of the LNF model for accurate wind power forecasting.

Analysis of Local Dependence and Multidimensionality in Graphical Loglinear Rasch Models

DEFF Research Database (Denmark)

Kreiner, Svend; Christensen, Karl Bang

2004-01-01

Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model......Local independence; Multidimensionality; Differential item functioning; Uniform local dependence and DIF; Graphical Rasch models; Loglinear Rasch model...

Strain Localization and Weakening Processes in Viscously Deforming Rocks: Numerical Modeling Based on Laboratory Torsion Experiments

Science.gov (United States)

Doehmann, M.; Brune, S.; Nardini, L.; Rybacki, E.; Dresen, G.

2017-12-01

Strain localization is an ubiquitous process in earth materials observed over a broad range of scales in space and time. Localized deformation and the formation of shear zones and faults typically involves material softening by various processes, like shear heating and grain size reduction. Numerical modeling enables us to study the complex physical and chemical weakening processes by separating the effect of individual parameters and boundary conditions. Using simple piece-wise linear functions for the parametrization of weakening processes allows studying a system at a chosen (lower) level of complexity (e.g. Cyprych et al., 2016). In this study, we utilize a finite element model to test two weakening laws that reduce the strength of the material depending on either the I) amount of accumulated strain or II) deformational work. Our 2D Cartesian models are benchmarked to single inclusion torsion experiments performed at elevated temperatures of 900 °C and pressures of up to 400 MPa (Rybacki et al., 2014). The experiments were performed on Carrara marble samples containing a weak Solnhofen limestone inclusion at a maximum strain rate of 2.0*10-4 s-1. Our models are designed to reproduce shear deformation of a hollow cylinder equivalent to the laboratory setup, such that material leaving one side of the model in shear direction enters again on the opposite side using periodic boundary conditions. Similar to the laboratory tests, we applied constant strain rate and constant stress boundary conditions.We use our model to investigate the time-dependent distribution of stress and strain and the effect of different parameters. For instance, inclusion rotation is shown to be strongly dependent on the viscosity ratio between matrix and inclusion and stronger ductile weakening increases the localization rate while decreasing shear zone width. The most suitable weakening law for representation of ductile rock is determined by combining the results of parameter tests with

Landmark based localization in urban environment

Science.gov (United States)

Qu, Xiaozhi; Soheilian, Bahman; Paparoditis, Nicolas

2018-06-01

A landmark based localization with uncertainty analysis based on cameras and geo-referenced landmarks is presented in this paper. The system is developed to adapt different camera configurations for six degree-of-freedom pose estimation. Local bundle adjustment is applied for optimization and the geo-referenced landmarks are integrated to reduce the drift. In particular, the uncertainty analysis is taken into account. On the one hand, we estimate the uncertainties of poses to predict the precision of localization. On the other hand, uncertainty propagation is considered for matching, tracking and landmark registering. The proposed method is evaluated on both KITTI benchmark and the data acquired by a mobile mapping system. In our experiments, decimeter level accuracy can be reached.

The effect of the PROSPER partnership model on cultivating local stakeholder knowledge of evidence-based programs: a five-year longitudinal study of 28 communities.

Science.gov (United States)

Crowley, D Max; Greenberg, Mark T; Feinberg, Mark E; Spoth, Richard L; Redmond, Cleve R

2012-02-01

A substantial challenge in improving public health is how to facilitate the local adoption of evidence-based interventions (EBIs). To do so, an important step is to build local stakeholders' knowledge and decision-making skills regarding the adoption and implementation of EBIs. One EBI delivery system, called PROSPER (PROmoting School-community-university Partnerships to Enhance Resilience), has effectively mobilized community prevention efforts, implemented prevention programming with quality, and consequently decreased youth substance abuse. While these results are encouraging, another objective is to increase local stakeholder knowledge of best practices for adoption, implementation and evaluation of EBIs. Using a mixed methods approach, we assessed local stakeholder knowledge of these best practices over 5 years, in 28 intervention and control communities. Results indicated that the PROSPER partnership model led to significant increases in expert knowledge regarding the selection, implementation, and evaluation of evidence-based interventions. Findings illustrate the limited programming knowledge possessed by members of local prevention efforts, the difficulty of complete knowledge transfer, and highlight one method for cultivating that knowledge.

Numerical analysis of strain localization for transversely isotropic model with non-coaxial flow rule

Science.gov (United States)

Wei, Ding; Cong-cong, Yu; Chen-hui, Wu; Zheng-yi, Shu

2018-03-01

To analyse the strain localization behavior of geomaterials, the forward Euler schemes and the tangent modulus matrix are formulated based on the transversely isotropic yield criterion with non-coaxial flow rule developed by Lade, the program code is implemented based on the user subroutine (UMAT) of ABAQUS. The influence of the material principal direction on the strain localization and the bearing capacity of the structure are investigated and analyzed. Numerical results show the validity and performance of the proposed model in simulating the strain localization behavior of geostructures.

Addressing potential local adaptation in species distribution models: implications for conservation under climate change

Science.gov (United States)

Hällfors, Maria Helena; Liao, Jishan; Dzurisin, Jason D. K.; Grundel, Ralph; Hyvärinen, Marko; Towle, Kevin; Wu, Grace C.; Hellmann, Jessica J.

2016-01-01

Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs to treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account, may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted, however. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate MaxEnt models, one considering the species as a single population and two of disjunct populations. PCA analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species versus population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered.

The utility of comparative models and the local model quality for protein crystal structure determination by Molecular Replacement

Directory of Open Access Journals (Sweden)

Pawlowski Marcin

2012-11-01

Full Text Available Abstract Background Computational models of protein structures were proved to be useful as search models in Molecular Replacement (MR, a common method to solve the phase problem faced by macromolecular crystallography. The success of MR depends on the accuracy of a search model. Unfortunately, this parameter remains unknown until the final structure of the target protein is determined. During the last few years, several Model Quality Assessment Programs (MQAPs that predict the local accuracy of theoretical models have been developed. In this article, we analyze whether the application of MQAPs improves the utility of theoretical models in MR. Results For our dataset of 615 search models, the real local accuracy of a model increases the MR success ratio by 101% compared to corresponding polyalanine templates. On the contrary, when local model quality is not utilized in MR, the computational models solved only 4.5% more MR searches than polyalanine templates. For the same dataset of the 615 models, a workflow combining MR with predicted local accuracy of a model found 45% more correct solution than polyalanine templates. To predict such accuracy MetaMQAPclust, a “clustering MQAP” was used. Conclusions Using comparative models only marginally increases the MR success ratio in comparison to polyalanine structures of templates. However, the situation changes dramatically once comparative models are used together with their predicted local accuracy. A new functionality was added to the GeneSilico Fold Prediction Metaserver in order to build models that are more useful for MR searches. Additionally, we have developed a simple method, AmIgoMR (Am I good for MR?, to predict if an MR search with a template-based model for a given template is likely to find the correct solution.

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform.

Science.gov (United States)

Bai, Guanbing; Liu, Jinghong; Song, Yueming; Zuo, Yujia

2017-01-06

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 - 4 ( ° ) , σ L = 1.35 × 10 - 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius.

Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

Science.gov (United States)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

2014-12-01

Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

The Optimization of the Local Public Policies’ Development Process Through Modeling And Simulation

Directory of Open Access Journals (Sweden)

Minodora URSĂCESCU

2012-06-01

Full Text Available The local public policies development in Romania represents an empirically realized measure, the strategic management practices in this domain not being based on a scientific instrument capable to anticipate and evaluate the results of implementing a local public policy in a logic of needs-policies-effects type. Beginning from this motivation, the purpose of the paper resides in the reconceptualization of the public policies process on functioning principles of the dynamic systems with inverse connection, by means of mathematical modeling and techniques simulation. Therefore, the research is oriented in the direction of developing an optimization method for the local public policies development process, using as instruments the mathematical modeling and the techniques simulation. The research’s main results are on the one side constituted by generating a new process concept of the local public policies, and on the other side by proposing the conceptual model of a complex software product which will permit the parameterized modeling in a virtual environment of these policies development process. The informatic product’s finality resides in modeling and simulating each local public policy type, taking into account the respective policy’s characteristics, but also the value of their appliance environment parameters in a certain moment.

Underwater Broadband Source Localization Based on Modal Filtering and Features Extraction

Directory of Open Access Journals (Sweden)

Dominique Fattaccioli

2010-01-01

Full Text Available Passive source localization is a crucial issue in underwater acoustics. In this paper, we focus on shallow water environment (0 to 400 m and broadband Ultra-Low Frequency acoustic sources (1 to 100 Hz. In this configuration and at a long range, the acoustic propagation can be described by normal mode theory. The propagating signal breaks up into a series of depth-dependent modes. These modes carry information about the source position. Mode excitation factors and mode phases analysis allow, respectively, localization in depth and distance. We propose two different approaches to achieve the localization: multidimensional approach (using a horizontal array of hydrophones based on frequency-wavenumber transform (F-K method and monodimensional approach (using a single hydrophone based on adapted spectral representation (FTa method. For both approaches, we propose first complete tools for modal filtering, and then depth and distance estimators. We show that adding mode sign and source spectrum informations improves considerably the localization performance in depth. The reference acoustic field needed for depth localization is simulated with the new realistic propagation modelMoctesuma. The feasibility of both approaches, F-K and FTa, are validated on data simulated in shallow water for different configurations. The performance of localization, in depth and distance, is very satisfactory.

Underwater Broadband Source Localization Based on Modal Filtering and Features Extraction

Directory of Open Access Journals (Sweden)

Cristol Xavier

2010-01-01

Full Text Available Passive source localization is a crucial issue in underwater acoustics. In this paper, we focus on shallow water environment (0 to 400 m and broadband Ultra-Low Frequency acoustic sources (1 to 100 Hz. In this configuration and at a long range, the acoustic propagation can be described by normal mode theory. The propagating signal breaks up into a series of depth-dependent modes. These modes carry information about the source position. Mode excitation factors and mode phases analysis allow, respectively, localization in depth and distance. We propose two different approaches to achieve the localization: multidimensional approach (using a horizontal array of hydrophones based on frequency-wavenumber transform ( method and monodimensional approach (using a single hydrophone based on adapted spectral representation ( method. For both approaches, we propose first complete tools for modal filtering, and then depth and distance estimators. We show that adding mode sign and source spectrum informations improves considerably the localization performance in depth. The reference acoustic field needed for depth localization is simulated with the new realistic propagation modelMoctesuma. The feasibility of both approaches, and , are validated on data simulated in shallow water for different configurations. The performance of localization, in depth and distance, is very satisfactory.

Structural-change localization and monitoring through a perturbation-based inverse problem.

Science.gov (United States)

Roux, Philippe; Guéguen, Philippe; Baillet, Laurent; Hamze, Alaa

2014-11-01

Structural-change detection and characterization, or structural-health monitoring, is generally based on modal analysis, for detection, localization, and quantification of changes in structure. Classical methods combine both variations in frequencies and mode shapes, which require accurate and spatially distributed measurements. In this study, the detection and localization of a local perturbation are assessed by analysis of frequency changes (in the fundamental mode and overtones) that are combined with a perturbation-based linear inverse method and a deconvolution process. This perturbation method is applied first to a bending beam with the change considered as a local perturbation of the Young's modulus, using a one-dimensional finite-element model for modal analysis. Localization is successful, even for extended and multiple changes. In a second step, the method is numerically tested under ambient-noise vibration from the beam support with local changes that are shifted step by step along the beam. The frequency values are revealed using the random decrement technique that is applied to the time-evolving vibrations recorded by one sensor at the free extremity of the beam. Finally, the inversion method is experimentally demonstrated at the laboratory scale with data recorded at the free end of a Plexiglas beam attached to a metallic support.

A Morphing framework to couple non-local and local anisotropic continua

KAUST Repository

Azdoud, Yan

2013-05-01

In this article, we develop a method to couple anisotropic local continua with anisotropic non-local continua with central long-range forces. First, we describe anisotropic non-local models based on spherical harmonic descriptions. We then derive compatible classic continuum models. Finally, we apply the morphing method to these anisotropic non-local models and present three-dimensional numerical examples to validate the efficiency of the technique. © 2013 Elsevier Ltd. All rights reserved.

Fiducial-based registration with a touchable region model.

Science.gov (United States)

Kim, Sungmin; Kazanzides, Peter

2017-02-01

Image-guided surgery requires registration between an image coordinate system and an intraoperative coordinate system that is typically referenced to a tracking device. In fiducial-based registration methods, this is achieved by localizing points (fiducials) in each coordinate system. Often, both localizations are performed manually, first by picking a fiducial point in the image and then by using a hand-held tracked pointer to physically touch the corresponding fiducial on the patient. These manual procedures introduce localization error that is user-dependent and can significantly decrease registration accuracy. Thus, there is a need for a registration method that is tolerant of imprecise fiducial localization in the preoperative and intraoperative phases. We propose the iterative closest touchable point (ICTP) registration framework, which uses model-based localization and a touchable region model. This method consists of three stages: (1) fiducial marker localization in image space, using a fiducial marker model, (2) initial registration with paired-point registration, and (3) fine registration based on the iterative closest point method. We perform phantom experiments with a fiducial marker design that is commonly used in neurosurgery. The results demonstrate that ICTP can provide accuracy improvements compared to the standard paired-point registration method that is widely used for surgical navigation and surgical robot systems, especially in cases where the surgeon introduces large localization errors. The results demonstrate that the proposed method can reduce the effect of the surgeon's localization performance on the accuracy of registration, thereby producing more consistent and less user-dependent registration outcomes.

Spiking cortical model based non-local means method for despeckling multiframe optical coherence tomography data

Science.gov (United States)

Gu, Yameng; Zhang, Xuming

2017-05-01

Optical coherence tomography (OCT) images are severely degraded by speckle noise. Existing methods for despeckling multiframe OCT data cannot deliver sufficient speckle suppression while preserving image details well. To address this problem, the spiking cortical model (SCM) based non-local means (NLM) method has been proposed in this letter. In the proposed method, the considered frame and two neighboring frames are input into three SCMs to generate the temporal series of pulse outputs. The normalized moment of inertia (NMI) of the considered patches in the pulse outputs is extracted to represent the rotational and scaling invariant features of the corresponding patches in each frame. The pixel similarity is computed based on the Euclidean distance between the NMI features and used as the weight. Each pixel in the considered frame is restored by the weighted averaging of all pixels in the pre-defined search window in the three frames. Experiments on the real multiframe OCT data of the pig eye demonstrate the advantage of the proposed method over the frame averaging method, the multiscale sparsity based tomographic denoising method, the wavelet-based method and the traditional NLM method in terms of visual inspection and objective metrics such as signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), equivalent number of looks (ENL) and cross-correlation (XCOR).

Dual entanglement measures based on no local cloning and no local deleting

International Nuclear Information System (INIS)

Horodecki, Michal; Sen, Aditi; Sen, Ujjwal

2004-01-01

The impossibility of cloning and deleting of unknown states constitute important restrictions on processing of information in the quantum world. On the other hand, a known quantum state can always be cloned or deleted. However, if we restrict the class of allowed operations, there will arise restrictions on the ability of cloning and deleting machines. We have shown that cloning and deleting of known states is in general not possible by local operations. This impossibility hints at quantum correlation in the state. We propose dual measures of quantum correlation based on the dual restrictions of no local cloning and no local deleting. The measures are relative entropy distances of the desired states in a (generally impossible) perfect local cloning or local deleting process from the best approximate state that is actually obtained by imperfect local cloning or deleting machines. Just like the dual measures of entanglement cost and distillable entanglement, the proposed measures are based on important processes in quantum information. We discuss their properties. For the case of pure states, estimations of these two measures are also provided. Interestingly, the entanglement of cloning for a maximally entangled state of two two-level systems is not unity

Constraint-Based Local Search for Constrained Optimum Paths Problems

Science.gov (United States)

Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal

Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.

Economic Learning Media Development Based on Local Locality

Science.gov (United States)

Hadi, Rizali; Supriyanto; Hasanah, Mahmudah

2017-01-01

This study aims to describe the learning medium of economic education at senior High School in Banjarmasin with media based on local wisdom. This research uses qualitative method as developed by Miles & Huberman, starting from data collection, data reduction data display, and then made conclusion. Data were collected in the order of Basic…

The Development of Interactive Mathematics Learning Material Based on Local Wisdom with .swf Format

Science.gov (United States)

Abadi, M. K.; Asih, E. C. M.; Jupri, A.

2018-05-01

Learning materials used by students and schools in Serang district are lacking because they do not contain local wisdom content. The aim of this study is to improve the deficiencies in learning materials used by students by making interactive materials based on local wisdom content with format .swf. The method in this research is research and development (RnD) with ADDIE model. In making this interactive learning materials in accordance with the stages of the ADDIE study. The results of this study include interactive learning materials based on local wisdom. This learning material is suitable for digital students.

Improved non-local electron thermal transport model for two-dimensional radiation hydrodynamics simulations

International Nuclear Information System (INIS)

Cao, Duc; Moses, Gregory; Delettrez, Jacques

2015-01-01

An implicit, non-local thermal conduction algorithm based on the algorithm developed by Schurtz, Nicolai, and Busquet (SNB) [Schurtz et al., Phys. Plasmas 7, 4238 (2000)] for non-local electron transport is presented and has been implemented in the radiation-hydrodynamics code DRACO. To study the model's effect on DRACO's predictive capability, simulations of shot 60 303 from OMEGA are completed using the iSNB model, and the computed shock speed vs. time is compared to experiment. Temperature outputs from the iSNB model are compared with the non-local transport model of Goncharov et al. [Phys. Plasmas 13, 012702 (2006)]. Effects on adiabat are also examined in a polar drive surrogate simulation. Results show that the iSNB model is not only capable of flux-limitation but also preheat prediction while remaining numerically robust and sacrificing little computational speed. Additionally, the results provide strong incentive to further modify key parameters within the SNB theory, namely, the newly introduced non-local mean free path. This research was supported by the Laboratory for Laser Energetics of the University of Rochester

Improved non-local electron thermal transport model for two-dimensional radiation hydrodynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Cao, Duc; Moses, Gregory [University of Wisconsin—Madison, 1500 Engineering Drive, Madison, Wisconsin 53706 (United States); Delettrez, Jacques [Laboratory for Laser Energetics of the University of Rochester, 250 East River Road, Rochester, New York 14623 (United States)

2015-08-15

An implicit, non-local thermal conduction algorithm based on the algorithm developed by Schurtz, Nicolai, and Busquet (SNB) [Schurtz et al., Phys. Plasmas 7, 4238 (2000)] for non-local electron transport is presented and has been implemented in the radiation-hydrodynamics code DRACO. To study the model's effect on DRACO's predictive capability, simulations of shot 60 303 from OMEGA are completed using the iSNB model, and the computed shock speed vs. time is compared to experiment. Temperature outputs from the iSNB model are compared with the non-local transport model of Goncharov et al. [Phys. Plasmas 13, 012702 (2006)]. Effects on adiabat are also examined in a polar drive surrogate simulation. Results show that the iSNB model is not only capable of flux-limitation but also preheat prediction while remaining numerically robust and sacrificing little computational speed. Additionally, the results provide strong incentive to further modify key parameters within the SNB theory, namely, the newly introduced non-local mean free path. This research was supported by the Laboratory for Laser Energetics of the University of Rochester.

Robust 3D face landmark localization based on local coordinate coding.

Science.gov (United States)

Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Maybank, Stephen J

2014-12-01

In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.

A Practical, Robust and Fast Method for Location Localization in Range-Based Systems.

Science.gov (United States)

Huang, Shiping; Wu, Zhifeng; Misra, Anil

2017-12-11

Location localization technology is used in a number of industrial and civil applications. Real time location localization accuracy is highly dependent on the quality of the distance measurements and efficiency of solving the localization equations. In this paper, we provide a novel approach to solve the nonlinear localization equations efficiently and simultaneously eliminate the bad measurement data in range-based systems. A geometric intersection model was developed to narrow the target search area, where Newton's Method and the Direct Search Method are used to search for the unknown position. Not only does the geometric intersection model offer a small bounded search domain for Newton's Method and the Direct Search Method, but also it can self-correct bad measurement data. The Direct Search Method is useful for the coarse localization or small target search domain, while the Newton's Method can be used for accurate localization. For accurate localization, by utilizing the proposed Modified Newton's Method (MNM), challenges of avoiding the local extrema, singularities, and initial value choice are addressed. The applicability and robustness of the developed method has been demonstrated by experiments with an indoor system.

Enhancing Community Based Early Warning Systems in Nepal with Flood Forecasting Using Local and Global Models

Science.gov (United States)

Dugar, Sumit; Smith, Paul; Parajuli, Binod; Khanal, Sonu; Brown, Sarah; Gautam, Dilip; Bhandari, Dinanath; Gurung, Gehendra; Shakya, Puja; Kharbuja, RamGopal; Uprety, Madhab

2017-04-01

Operationalising effective Flood Early Warning Systems (EWS) in developing countries like Nepal poses numerous challenges, with complex topography and geology, sparse network of river and rainfall gauging stations and diverse socio-economic conditions. Despite these challenges, simple real-time monitoring based EWSs have been in place for the past decade. A key constraint of these simple systems is the very limited lead time for response - as little as 2-3 hours, especially for rivers originating from steep mountainous catchments. Efforts to increase lead time for early warning are focusing on imbedding forecasts into the existing early warning systems. In 2016, the Nepal Department of Hydrology and Meteorology (DHM) piloted an operational Probabilistic Flood Forecasting Model in major river basins across Nepal. This comprised a low data approach to forecast water levels, developed jointly through a research/practitioner partnership with Lancaster University and WaterNumbers (UK) and the International NGO Practical Action. Using Data-Based Mechanistic Modelling (DBM) techniques, the model assimilated rainfall and water levels to generate localised hourly flood predictions, which are presented as probabilistic forecasts, increasing lead times from 2-3 hours to 7-8 hours. The Nepal DHM has simultaneously started utilizing forecasts from the Global Flood Awareness System (GLoFAS) that provides streamflow predictions at the global scale based upon distributed hydrological simulations using numerical ensemble weather forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). The aforementioned global and local models have already affected the approach to early warning in Nepal, being operational during the 2016 monsoon in the West Rapti basin in Western Nepal. On 24 July 2016, GLoFAS hydrological forecasts for the West Rapti indicated a sharp rise in river discharge above 1500 m3/sec (equivalent to the river warning level at 5 meters) with 53

Local Exhaust Ventilation

DEFF Research Database (Denmark)

Madsen, Ulla; Breum, N. O.; Nielsen, Peter V.

Capture efficiency of a local exhaust system, e.g. a kitchen hood, should include only contaminants being direct captured. In this study basic concepts of local exhaust capture efficiency are given, based on the idea of a control box. A validated numerical model is used for estimation of the capt......Capture efficiency of a local exhaust system, e.g. a kitchen hood, should include only contaminants being direct captured. In this study basic concepts of local exhaust capture efficiency are given, based on the idea of a control box. A validated numerical model is used for estimation...

Multi-hop localization algorithm based on grid-scanning for wireless sensor networks.

Science.gov (United States)

Wan, Jiangwen; Guo, Xiaolei; Yu, Ning; Wu, Yinfeng; Feng, Renjian

2011-01-01

For large-scale wireless sensor networks (WSNs) with a minority of anchor nodes, multi-hop localization is a popular scheme for determining the geographical positions of the normal nodes. However, in practice existing multi-hop localization methods suffer from various kinds of problems, such as poor adaptability to irregular topology, high computational complexity, low positioning accuracy, etc. To address these issues in this paper, we propose a novel Multi-hop Localization algorithm based on Grid-Scanning (MLGS). First, the factors that influence the multi-hop distance estimation are studied and a more realistic multi-hop localization model is constructed. Then, the feasible regions of the normal nodes are determined according to the intersection of bounding square rings. Finally, a verifiably good approximation scheme based on grid-scanning is developed to estimate the coordinates of the normal nodes. Additionally, the positioning accuracy of the normal nodes can be improved through neighbors' collaboration. Extensive simulations are performed in isotropic and anisotropic networks. The comparisons with some typical algorithms of node localization confirm the effectiveness and efficiency of our algorithm.

Local and omnibus goodness-of-fit tests in classical measurement error models

KAUST Repository

Ma, Yanyuan

2010-09-14

We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.

Approach of simultaneous localization and mapping based on local maps for robot

Institute of Scientific and Technical Information of China (English)

CHEN Bai-fan; CAI Zi-xing; HU De-wen

2006-01-01

An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps.A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.

Finger Vein Recognition Based on Local Directional Code

Science.gov (United States)

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger Vein Recognition Based on Local Directional Code

Directory of Open Access Journals (Sweden)

Rongyang Xiao

2012-11-01

Full Text Available Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP, Local Derivative Pattern (LDP and Local Line Binary Pattern (LLBP. However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD, this paper represents a new direction based local descriptor called Local Directional Code (LDC and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

Science.gov (United States)

Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

2014-01-01

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based "local" methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative "bucket-style" hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

Local lattice-gas model for immiscible fluids

International Nuclear Information System (INIS)

Chen, S.; Doolen, G.D.; Eggert, K.; Grunau, D.; Loh, E.Y.

1991-01-01

We present a lattice-gas model for two-dimensional immiscible fluid flows with surface tension that uses strictly local collision rules. Instead of using a local total color flux as Somers and Rem [Physica D 47, 39 (1991)], we use local colored holes to be the memory of particles of the same color. Interactions between walls and fluids are included that produce arbitrary contact angles

Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization

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José R. Casar

2011-09-01

Full Text Available The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network. The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling.

Sub-OBB based object recognition and localization algorithm using range images

International Nuclear Information System (INIS)

Hoang, Dinh-Cuong; Chen, Liang-Chia; Nguyen, Thanh-Hung

2017-01-01

This paper presents a novel approach to recognize and estimate pose of the 3D objects in cluttered range images. The key technical breakthrough of the developed approach can enable robust object recognition and localization under undesirable condition such as environmental illumination variation as well as optical occlusion to viewing the object partially. First, the acquired point clouds are segmented into individual object point clouds based on the developed 3D object segmentation for randomly stacked objects. Second, an efficient shape-matching algorithm called Sub-OBB based object recognition by using the proposed oriented bounding box (OBB) regional area-based descriptor is performed to reliably recognize the object. Then, the 3D position and orientation of the object can be roughly estimated by aligning the OBB of segmented object point cloud with OBB of matched point cloud in a database generated from CAD model and 3D virtual camera. To detect accurate pose of the object, the iterative closest point (ICP) algorithm is used to match the object model with the segmented point clouds. From the feasibility test of several scenarios, the developed approach is verified to be feasible for object pose recognition and localization. (paper)

Adaptation of Mesoscale Weather Models to Local Forecasting

Science.gov (United States)

Manobianco, John T.; Taylor, Gregory E.; Case, Jonathan L.; Dianic, Allan V.; Wheeler, Mark W.; Zack, John W.; Nutter, Paul A.

2003-01-01

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes

Chironomid-based water depth reconstructions: an independent evaluation of site-specific and local inference models

NARCIS (Netherlands)

Engels, S.; Cwynar, L.C.; Rees, A.B.H.; Shuman, B.N.

2012-01-01

Water depth is an important environmental variable that explains a significant portion of the variation in the chironomid fauna of shallow lakes. We developed site-specific and local chironomid water-depth inference models using 26 and 104 surface-sediment samples, respectively, from seven

Simulation-Based Approach for Studying the Balancing of Local Smart Grids with Electric Vehicle Batteries

Directory of Open Access Journals (Sweden)

Juhani Latvakoski

2015-07-01

Full Text Available Modern society is facing great challenges due to pollution and increased carbon dioxide (CO2 emissions. As part of solving these challenges, the use of renewable energy sources and electric vehicles (EVs is rapidly increasing. However, increased dynamics have triggered problems in balancing energy supply and consumption demand in the power systems. The resulting uncertainty and unpredictability of energy production, consumption, and management of peak loads has caused an increase in costs for energy market actors. Therefore, the means for studying the balancing of local smart grids with EVs is a starting point for this paper. The main contribution is a simulation-based approach which was developed to enable the study of the balancing of local distribution grids with EV batteries in a cost-efficient manner. The simulation-based approach is applied to enable the execution of a distributed system with the simulation of a local distribution grid, including a number of charging stations and EVs. A simulation system has been constructed to support the simulation-based approach. The evaluation has been carried out by executing the scenario related to balancing local distribution grids with EV batteries in a step-by-step manner. The evaluation results indicate that the simulation-based approach is able to facilitate the evaluation of smart grid– and EV-related communication protocols, control algorithms for charging, and functionalities of local distribution grids as part of a complex, critical cyber-physical system. In addition, the simulation system is able to incorporate advanced methods for monitoring, controlling, tracking, and modeling behavior. The simulation model of the local distribution grid can be executed with the smart control of charging and discharging powers of the EVs according to the load situation in the local distribution grid. The resulting simulation system can be applied to the study of balancing local smart grids with EV

A Local Land Use Competition Cellular Automata Model and Its Application

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Jun Yang

2016-06-01

Full Text Available Cellular automaton (CA is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local Land Use Competition Cellular Automata (LLUC-CA model, based on local land use competition, land suitability evaluation, demand analysis of the different land use types, and multi-target land use competition allocation algorithm to simulate land use change at a micro level. The model is applied to simulate land use changes at Jinshitan National Tourist Holiday Resort from 1988 to 2012. The results show that the simulation accuracies were 64.46%, 77.21%, 85.30% and 99.14% for the agricultural land, construction land, forestland and water, respectively. In addition, comparing the simulation results of the LLUC-CA and CA-Markov model with the real land use data, their overall spatial accuracies were found to be 88.74% and 86.82%, respectively. In conclusion, the results from this study indicated that the model was an acceptable method for the simulation of large-scale land use changes, and the approach used here is applicable to analyzing the land use change driven forces and assist in decision-making.

Numerical modeling of local scour around hydraulic structure in sandy beds by dynamic mesh method

Science.gov (United States)

Fan, Fei; Liang, Bingchen; Bai, Yuchuan; Zhu, Zhixia; Zhu, Yanjun

2017-10-01

Local scour, a non-negligible factor in hydraulic engineering, endangers the safety of hydraulic structures. In this work, a numerical model for simulating local scour was constructed, based on the open source code computational fluid dynamics model OpenFOAM. We consider both the bedload and suspended load sediment transport in the scour model and adopt the dynamic mesh method to simulate the evolution of the bed elevation. We use the finite area method to project data between the three-dimensional flow model and the two-dimensional (2D) scour model. We also improved the 2D sand slide method and added it to the scour model to correct the bed bathymetry when the bed slope angle exceeds the angle of repose. Moreover, to validate our scour model, we conducted and compared the results of three experiments with those of the developed model. The validation results show that our developed model can reliably simulate local scour.

Observation Likelihood Model Design and Failure Recovery Scheme toward Reliable Localization of Mobile Robots

Directory of Open Access Journals (Sweden)

Chang-bae Moon

2011-01-01

Full Text Available Although there have been many researches on mobile robot localization, it is still difficult to obtain reliable localization performance in a human co-existing real environment. Reliability of localization is highly dependent upon developer's experiences because uncertainty is caused by a variety of reasons. We have developed a range sensor based integrated localization scheme for various indoor service robots. Through the experience, we found out that there are several significant experimental issues. In this paper, we provide useful solutions for following questions which are frequently faced with in practical applications: 1 How to design an observation likelihood model? 2 How to detect the localization failure? 3 How to recover from the localization failure? We present design guidelines of observation likelihood model. Localization failure detection and recovery schemes are presented by focusing on abrupt wheel slippage. Experiments were carried out in a typical office building environment. The proposed scheme to identify the localizer status is useful in practical environments. Moreover, the semi-global localization is a computationally efficient recovery scheme from localization failure. The results of experiments and analysis clearly present the usefulness of proposed solutions.

Observation Likelihood Model Design and Failure Recovery Scheme Toward Reliable Localization of Mobile Robots

Directory of Open Access Journals (Sweden)

Chang-bae Moon

2010-12-01

Full Text Available Although there have been many researches on mobile robot localization, it is still difficult to obtain reliable localization performance in a human co-existing real environment. Reliability of localization is highly dependent upon developer's experiences because uncertainty is caused by a variety of reasons. We have developed a range sensor based integrated localization scheme for various indoor service robots. Through the experience, we found out that there are several significant experimental issues. In this paper, we provide useful solutions for following questions which are frequently faced with in practical applications: 1 How to design an observation likelihood model? 2 How to detect the localization failure? 3 How to recover from the localization failure? We present design guidelines of observation likelihood model. Localization failure detection and recovery schemes are presented by focusing on abrupt wheel slippage. Experiments were carried out in a typical office building environment. The proposed scheme to identify the localizer status is useful in practical environments. Moreover, the semi-global localization is a computationally efficient recovery scheme from localization failure. The results of experiments and analysis clearly present the usefulness of proposed solutions.

A model of optimization for local energy infrastructure development

International Nuclear Information System (INIS)

Juroszek, Zbigniew; Kudelko, Mariusz

2016-01-01

The authors present a non-linear, optimization model supporting the planning of local energy systems development. The model considers two forms of final energy – heat and electricity. The model reflects both private and external costs and is designed to show the social perspective. It considers the variability of the marginal costs attributed to local renewable resources. In order to demonstrate the capacity of the model, the authors present a case study by modelling the development of the energy infrastructure in a municipality located in the south of Poland. The ensuing results show that a swift and significant shift in the local energy policy of typical central European municipalities is needed. The modelling is done in two scenarios – with and without the internalization of external environmental costs. The results confirm that the internalization of the external costs of energy production on a local scale leads to a significant improvement in the allocation of resources. - Highlights: • A model for municipal energy system development in Central European environment has been developed. • The variability of marginal costs of local, renewable fuels is considered. • External, environmental costs are considered. • The model reflects both network and individual energy infrastructure (e.g. individual housing boilers). • A swift change in Central European municipal energy infrastructure is necessary.

Local fit evaluation of structural equation models using graphical criteria.

Science.gov (United States)

Thoemmes, Felix; Rosseel, Yves; Textor, Johannes

2018-03-01

Evaluation of model fit is critically important for every structural equation model (SEM), and sophisticated methods have been developed for this task. Among them are the χ² goodness-of-fit test, decomposition of the χ², derived measures like the popular root mean square error of approximation (RMSEA) or comparative fit index (CFI), or inspection of residuals or modification indices. Many of these methods provide a global approach to model fit evaluation: A single index is computed that quantifies the fit of the entire SEM to the data. In contrast, graphical criteria like d-separation or trek-separation allow derivation of implications that can be used for local fit evaluation, an approach that is hardly ever applied. We provide an overview of local fit evaluation from the viewpoint of SEM practitioners. In the presence of model misfit, local fit evaluation can potentially help in pinpointing where the problem with the model lies. For models that do fit the data, local tests can identify the parts of the model that are corroborated by the data. Local tests can also be conducted before a model is fitted at all, and they can be used even for models that are globally underidentified. We discuss appropriate statistical local tests, and provide applied examples. We also present novel software in R that automates this type of local fit evaluation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The EPED pedestal model and edge localized mode-suppressed regimes: Studies of quiescent H-mode and development of a model for edge localized mode suppression via resonant magnetic perturbations

Energy Technology Data Exchange (ETDEWEB)

Snyder, P. B.; Osborne, T. H.; Burrell, K. H.; Groebner, R. J.; Leonard, A. W.; Wade, M. R. [General Atomics, P.O. Box 85608, San Diego, California 92186-5608 (United States); Nazikian, R. [Princeton Plasma Physics Laboratory, Princeton, New Jersey (United States); Orlov, D. M. [University of California-San Diego, San Diego, California 92093 (United States); Schmitz, O. [Institut fuer Plasmaphysik, Forschungszentrum Juelich GmbH, Association FZJ-EURATOM, Juelich (Germany); Wilson, H. R. [York Plasma Institute, Department of Physics, University of York, Heslington, York YO10 5DD (United Kingdom)

2012-05-15

The EPED model predicts the H-mode pedestal height and width based upon two fundamental and calculable constraints: (1) onset of non-local peeling-ballooning modes at low to intermediate mode number, (2) onset of nearly local kinetic ballooning modes at high mode number. We present detailed tests of the EPED model in discharges with edge localized modes (ELMs), employing new high resolution measurements, and finding good quantitative agreement across a range of parameters. The EPED model is then applied for the first time to quiescent H-mode (QH), finding a similar level of agreement between predicted and observed pedestal height and width, and suggesting that the model can be used to predict the critical density for QH-mode operation. Finally, the model is applied toward understanding the suppression of ELMs with 3D resonant magnetic perturbations (RMP). Combining EPED with plasma response physics, a new working model for RMP ELM suppression is developed. We propose that ELMs are suppressed when a 'wall' associated with the RMP blocks the inward penetration of the edge transport barrier. A calculation of the required location of this 'wall' with EPED is consistent with observed profile changes during RMP ELM suppression and offers an explanation for the observed dependence on safety factor (q{sub 95}).

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors.

Directory of Open Access Journals (Sweden)

Zirui Xu

Full Text Available This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel's global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point's plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel.

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors.

Science.gov (United States)

Xu, Zirui; Yang, Wei; You, Kaiming; Li, Wei; Kim, Young-Il

2017-01-01

This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel's global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point's plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel.

A 3D global-to-local deformable mesh model based registration and anatomy-constrained segmentation method for image guided prostate radiotherapy

International Nuclear Information System (INIS)

Zhou Jinghao; Kim, Sung; Jabbour, Salma; Goyal, Sharad; Haffty, Bruce; Chen, Ting; Levinson, Lydia; Metaxas, Dimitris; Yue, Ning J.

2010-01-01

Purpose: In the external beam radiation treatment of prostate cancers, successful implementation of adaptive radiotherapy and conformal radiation dose delivery is highly dependent on precise and expeditious segmentation and registration of the prostate volume between the simulation and the treatment images. The purpose of this study is to develop a novel, fast, and accurate segmentation and registration method to increase the computational efficiency to meet the restricted clinical treatment time requirement in image guided radiotherapy. Methods: The method developed in this study used soft tissues to capture the transformation between the 3D planning CT (pCT) images and 3D cone-beam CT (CBCT) treatment images. The method incorporated a global-to-local deformable mesh model based registration framework as well as an automatic anatomy-constrained robust active shape model (ACRASM) based segmentation algorithm in the 3D CBCT images. The global registration was based on the mutual information method, and the local registration was to minimize the Euclidian distance of the corresponding nodal points from the global transformation of deformable mesh models, which implicitly used the information of the segmented target volume. The method was applied on six data sets of prostate cancer patients. Target volumes delineated by the same radiation oncologist on the pCT and CBCT were chosen as the benchmarks and were compared to the segmented and registered results. The distance-based and the volume-based estimators were used to quantitatively evaluate the results of segmentation and registration. Results: The ACRASM segmentation algorithm was compared to the original active shape model (ASM) algorithm by evaluating the values of the distance-based estimators. With respect to the corresponding benchmarks, the mean distance ranged from -0.85 to 0.84 mm for ACRASM and from -1.44 to 1.17 mm for ASM. The mean absolute distance ranged from 1.77 to 3.07 mm for ACRASM and from 2.45 to

Experiment-based modelling of hardening and localized plasticity in metals irradiated under cascade damage conditions

International Nuclear Information System (INIS)

Singh, B.N.; Ghoniem, N.M.; Trinkaus, H.

2002-01-01

The analysis of the available experimental observations shows that the occurrence of a sudden yield drop and the associated plastic flow localization are the major concerns regarding the performance and lifetime of materials exposed to fission or fusion neutrons. In the light of the known mechanical properties and microstructures of the as-irradiated and irradiated and deformed materials, it has been argued that the increase in the upper yield stress, the sudden yield drop and the initiation of plastic flow localization, can be rationalized in terms of the cascade induced source hardening (CISH) model. Various aspects of the model (main assumptions and predictions) have been investigated using analytical calculations, 3-D dislocation dynamics and molecular dynamics simulations. The main results and conclusions are briefly summarized. Finally, it is pointed out that even though the formation of cleared channels may be rationalized in terms of climb-controlled glide of the source dislocation, a number of problems regarding the initiation and the evolution of these channels remain unsolved

Experiment-based modelling of hardening and localized plasticity in metals irradiated under cascade damage conditions

Energy Technology Data Exchange (ETDEWEB)

Singh, B.N. E-mail: bachu.singh@risoe.dk; Ghoniem, N.M.; Trinkaus, H

2002-12-01

The analysis of the available experimental observations shows that the occurrence of a sudden yield drop and the associated plastic flow localization are the major concerns regarding the performance and lifetime of materials exposed to fission or fusion neutrons. In the light of the known mechanical properties and microstructures of the as-irradiated and irradiated and deformed materials, it has been argued that the increase in the upper yield stress, the sudden yield drop and the initiation of plastic flow localization, can be rationalized in terms of the cascade induced source hardening (CISH) model. Various aspects of the model (main assumptions and predictions) have been investigated using analytical calculations, 3-D dislocation dynamics and molecular dynamics simulations. The main results and conclusions are briefly summarized. Finally, it is pointed out that even though the formation of cleared channels may be rationalized in terms of climb-controlled glide of the source dislocation, a number of problems regarding the initiation and the evolution of these channels remain unsolved.

A Fovea Localization Scheme Using Vessel Origin-Based Parabolic Model

Directory of Open Access Journals (Sweden)

Chun-Yuan Yu

2014-09-01

Full Text Available At the center of the macula, fovea plays an important role in computer-aided diagnosis. To locate the fovea, this paper proposes a vessel origin (VO-based parabolic model, which takes the VO as the vertex of the parabola-like vasculature. Image processing steps are applied to accurately locate the fovea on retinal images. Firstly, morphological gradient and the circular Hough transform are used to find the optic disc. The structure of the vessel is then segmented with the line detector. Based on the characteristics of the VO, four features of VO are extracted, following the Bayesian classification procedure. Once the VO is identified, the VO-based parabolic model will locate the fovea. To find the fittest parabola and the symmetry axis of the retinal vessel, an Shift and Rotation (SR-Hough transform that combines the Hough transform with the shift and rotation of coordinates is presented. Two public databases of retinal images, DRIVE and STARE, are used to evaluate the proposed method. The experiment results show that the average Euclidean distances between the located fovea and the fovea marked by experts in two databases are 9.8 pixels and 30.7 pixels, respectively. The results are stronger than other methods and thus provide a better macular detection for further disease discovery.

A space-jump derivation for non-local models of cell-cell adhesion and non-local chemotaxis.

Science.gov (United States)

Buttenschön, Andreas; Hillen, Thomas; Gerisch, Alf; Painter, Kevin J

2018-01-01

Cellular adhesion provides one of the fundamental forms of biological interaction between cells and their surroundings, yet the continuum modelling of cellular adhesion has remained mathematically challenging. In 2006, Armstrong et al. proposed a mathematical model in the form of an integro-partial differential equation. Although successful in applications, a derivation from an underlying stochastic random walk has remained elusive. In this work we develop a framework by which non-local models can be derived from a space-jump process. We show how the notions of motility and a cell polarization vector can be naturally included. With this derivation we are able to include microscopic biological properties into the model. We show that particular choices yield the original Armstrong model, while others lead to more general models, including a doubly non-local adhesion model and non-local chemotaxis models. Finally, we use random walk simulations to confirm that the corresponding continuum model represents the mean field behaviour of the stochastic random walk.

Three-body models of the 6ΛΛHe and 9ΛBe hypernuclei with non-local interactions

International Nuclear Information System (INIS)

Theeten, M.; Baye, D.; Descouvemont, P.

2005-01-01

A three-body model involving non-local interactions is developed in configuration space. It is based on a hyperspherical-harmonics expansion and the Lagrange-mesh method. The 6 ΛΛ He and 9 Λ Be hypernuclei are studied as three-body αΛΛ and ααΛ systems. Recently proposed quark-model based ΛN and ΛΛ interactions are used. A non-local Λα interaction is obtained by folding the ΛN interaction with a Gaussian α density. Various phenomenological αα interactions are employed. The results agree within 1 keV with recent Faddeev calculations in momentum space. Energies and radii of 6 ΛΛ He and 9 Λ Be are compared with a purely local model. The B(E2) between the 9 Λ Be bound states is also calculated. The role of non-locality is discussed

Globally COnstrained Local Function Approximation via Hierarchical Modelling, a Framework for System Modelling under Partial Information

DEFF Research Database (Denmark)

Øjelund, Henrik; Sadegh, Payman

2000-01-01

be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....

A comprehensive multi-local-world model for complex networks

International Nuclear Information System (INIS)

Fan Zhengping; Chen Guanrong; Zhang Yunong

2009-01-01

The nodes in a community within a network are much more connected to each other than to the others outside the community in the same network. This phenomenon has been commonly observed from many real-world networks, ranging from social to biological even to technical networks. Meanwhile, the number of communities in some real-world networks, such as the Internet and most social networks, are evolving with time. To model this kind of networks, the present Letter proposes a multi-local-world (MLW) model to capture and describe their essential topological properties. Based on the mean-field theory, the degree distribution of this model is obtained analytically, showing that the generated network has a novel topological feature as being not completely random nor completely scale-free but behaving somewhere between them. As a typical application, the MLW model is applied to characterize the Internet against some other models such as the BA, GBA, Fitness and HOT models, demonstrating the superiority of the new model.

Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree

Science.gov (United States)

Chen, Qiyu; Liu, Gang; Ma, Xiaogang; Mariethoz, Gregoire; He, Zhenwen; Tian, Yiping; Weng, Zhengping

2018-05-01

Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently.

Comparative analysis of elements and models of implementation in local-level spatial plans in Serbia

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Stefanović Nebojša

2017-01-01

Full Text Available Implementation of local-level spatial plans is of paramount importance to the development of the local community. This paper aims to demonstrate the importance of and offer further directions for research into the implementation of spatial plans by presenting the results of a study on models of implementation. The paper describes the basic theoretical postulates of a model for implementing spatial plans. A comparative analysis of the application of elements and models of implementation of plans in practice was conducted based on the spatial plans for the local municipalities of Arilje, Lazarevac and Sremska Mitrovica. The analysis includes four models of implementation: the strategy and policy of spatial development; spatial protection; the implementation of planning solutions of a technical nature; and the implementation of rules of use, arrangement and construction of spaces. The main results of the analysis are presented and used to give recommendations for improving the elements and models of implementation. Final deliberations show that models of implementation are generally used in practice and combined in spatial plans. Based on the analysis of how models of implementation are applied in practice, a general conclusion concerning the complex character of the local level of planning is presented and elaborated. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 36035: Spatial, Environmental, Energy and Social Aspects of Developing Settlements and Climate Change - Mutual Impacts and Grant no. III 47014: The Role and Implementation of the National Spatial Plan and Regional Development Documents in Renewal of Strategic Research, Thinking and Governance in Serbia

Semi-local invariance in Ising models with multi-spin interaction

International Nuclear Information System (INIS)

Lipowski, A.

1996-08-01

We examine implications of semi-local invariance in Ising models with multispin interaction. In ergodic models all spin-spin correlation functions vanish and the local symmetry is the same as in locally gauge-invariant models. The d = 3 model with four-spin interaction is nonergodic at low temperature but the magnetic symmetry remains unbroken. The d = 3 model with eight-spin interaction is ergodic but undergoes the phase transition and most likely its low-temperature phase is characterized by a nonlocal order parameter. (author). 7 refs, 1 fig

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.

Walking dynamics of the passive compass-gait model under OGY-based state-feedback control: Analysis of local bifurcations via the hybrid Poincaré map

International Nuclear Information System (INIS)

Gritli, Hassène; Belghith, Safya

2017-01-01

Highlights: • We study the passive walking dynamics of the compass-gait model under OGY-based state-feedback control. • We analyze local bifurcations via a hybrid Poincaré map. • We show exhibition of the super(sub)-critical flip bifurcation, the saddle-node(saddle) bifurcation and a saddle-flip bifurcation. • An analysis via a two-parameter bifurcation diagram is presented. • Some new hidden attractors in the controlled passive walking dynamics are displayed. - Abstract: In our previous work, we have analyzed the passive dynamic walking of the compass-gait biped model under the OGY-based state-feedback control using the impulsive hybrid nonlinear dynamics. Such study was carried out through bifurcation diagrams. It was shown that the controlled bipedal gait exhibits attractive nonlinear phenomena such as the cyclic-fold (saddle-node) bifurcation, the period-doubling (flip) bifurcation and chaos. Moreover, we revealed that, using the controlled continuous-time dynamics, we encountered a problem in finding, identifying and hence following branches of (un)stable solutions in order to characterize local bifurcations. The present paper solves such problem and then provides a further investigation of the controlled bipedal walking dynamics using the developed analytical expression of the controlled hybrid Poincaré map. Thus, we show that analysis via such Poincaré map allows to follow branches of both stable and unstable fixed points in bifurcation diagrams and hence to explore the complete dynamics of the controlled compass-gait biped model. We demonstrate the generation, other than the conventional local bifurcations in bipedal walking, i.e. the flip bifurcation and the saddle-node bifurcation, of a saddle-saddle bifurcation, a subcritical flip bifurcation and a new type of a local bifurcation, the saddle-flip bifurcation. In addition, to further understand the occurrence of the local bifurcations, we present an analysis with a two-parameter bifurcation

Adaptive local surface refinement based on LR NURBS and its application to contact

Science.gov (United States)

Zimmermann, Christopher; Sauer, Roger A.

2017-12-01

A novel adaptive local surface refinement technique based on Locally Refined Non-Uniform Rational B-Splines (LR NURBS) is presented. LR NURBS can model complex geometries exactly and are the rational extension of LR B-splines. The local representation of the parameter space overcomes the drawback of non-existent local refinement in standard NURBS-based isogeometric analysis. For a convenient embedding into general finite element codes, the Bézier extraction operator for LR NURBS is formulated. An automatic remeshing technique is presented that allows adaptive local refinement and coarsening of LR NURBS. In this work, LR NURBS are applied to contact computations of 3D solids and membranes. For solids, LR NURBS-enriched finite elements are used to discretize the contact surfaces with LR NURBS finite elements, while the rest of the body is discretized by linear Lagrange finite elements. For membranes, the entire surface is discretized by LR NURBS. Various numerical examples are shown, and they demonstrate the benefit of using LR NURBS: Compared to uniform refinement, LR NURBS can achieve high accuracy at lower computational cost.

Gradient-based model calibration with proxy-model assistance

Science.gov (United States)

Burrows, Wesley; Doherty, John

2016-02-01

Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

Local models violating Bell's inequality by time delays

International Nuclear Information System (INIS)

Scalera, G.C.

1984-01-01

The performance of ensemble averages is neither a sufficient nor a necessary condition to avoid Bell's inequality violations characteristic of nonergodic systems. Slight modifications of a local nonergodic logical model violating Bell's inequality produce a stochastic model exactly fitting the quantum-mechanical correlation function. From these considerations is appears evident that the last experiments on the existence of local hidden variables are not conclusive

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Science.gov (United States)

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.

Visual Appearance-Based Unmanned Vehicle Sequential Localization

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Wei Liu

2013-01-01

Full Text Available Localizationis of vital importance for an unmanned vehicle to drive on the road. Most of the existing algorithms are based on laser range finders, inertial equipment, artificial landmarks, distributing sensors or global positioning system(GPS information. Currently, the problem of localization with vision information is most concerned. However, vision-based localization techniquesare still unavailable for practical applications. In this paper, we present a vision-based sequential probability localization method. This method uses the surface information of the roadside to locate the vehicle, especially in the situation where GPS information is unavailable. It is composed of two step, first, in a recording stage, we construct a ground truthmap with the appearance of the roadside environment. Then in an on-line stage, we use a sequential matching approach to localize the vehicle. In the experiment, we use two independent cameras to observe the environment, one is left-orientated and the other is right. SIFT features and Daisy features are used to represent for the visual appearance of the environment. The experiment results show that the proposed method could locate the vehicle in a complicated, large environment with high reliability.

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

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Julie Behr

Full Text Available This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC and substrate adherent polymorphonuclear neutrophils (PMN is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the β-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

Science.gov (United States)

Behr, Julie; Gaskin, Byron; Fu, Changliang; Dong, Cheng; Kunz, Robert

2015-01-01

This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC) and substrate adherent polymorphonuclear neutrophils (PMN) is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD) framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the β-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

3D micro-particle image modeling and its application in measurement resolution investigation for visual sensing based axial localization in an optical microscope

International Nuclear Information System (INIS)

Wang, Yuliang; Li, Xiaolai; Bi, Shusheng; Zhu, Xiaofeng; Liu, Jinhua

2017-01-01

Visual sensing based three dimensional (3D) particle localization in an optical microscope is important for both fundamental studies and practical applications. Compared with the lateral ( X and Y ) localization, it is more challenging to achieve a high resolution measurement of axial particle location. In this study, we aim to investigate the effect of different factors on axial measurement resolution through an analytical approach. Analytical models were developed to simulate 3D particle imaging in an optical microscope. A radius vector projection method was applied to convert the simulated particle images into radius vectors. With the obtained radius vectors, a term of axial changing rate was proposed to evaluate the measurement resolution of axial particle localization. Experiments were also conducted for comparison with that obtained through simulation. Moreover, with the proposed method, the effects of particle size on measurement resolution were discussed. The results show that the method provides an efficient approach to investigate the resolution of axial particle localization. (paper)

A Local Texture-Based Superpixel Feature Coding for Saliency Detection Combined with Global Saliency

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Bingfei Nan

2015-12-01

Full Text Available Because saliency can be used as the prior knowledge of image content, saliency detection has been an active research area in image segmentation, object detection, image semantic understanding and other relevant image-based applications. In the case of saliency detection from cluster scenes, the salient object/region detected needs to not only be distinguished clearly from the background, but, preferably, to also be informative in terms of complete contour and local texture details to facilitate the successive processing. In this paper, a Local Texture-based Region Sparse Histogram (LTRSH model is proposed for saliency detection from cluster scenes. This model uses a combination of local texture patterns and color distribution as well as contour information to encode the superpixels to characterize the local feature of image for region contrast computing. Combining the region contrast as computed with the global saliency probability, a full-resolution salient map, in which the salient object/region detected adheres more closely to its inherent feature, is obtained on the bases of the corresponding high-level saliency spatial distribution as well as on the pixel-level saliency enhancement. Quantitative comparisons with five state-of-the-art saliency detection methods on benchmark datasets are carried out, and the comparative results show that the method we propose improves the detection performance in terms of corresponding measurements.

Multiple Signal Classification Algorithm Based Electric Dipole Source Localization Method in an Underwater Environment

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Yidong Xu

2017-10-01

Full Text Available A novel localization method based on multiple signal classification (MUSIC algorithm is proposed for positioning an electric dipole source in a confined underwater environment by using electric dipole-receiving antenna array. In this method, the boundary element method (BEM is introduced to analyze the boundary of the confined region by use of a matrix equation. The voltage of each dipole pair is used as spatial-temporal localization data, and it does not need to obtain the field component in each direction compared with the conventional fields based localization method, which can be easily implemented in practical engineering applications. Then, a global-multiple region-conjugate gradient (CG hybrid search method is used to reduce the computation burden and to improve the operation speed. Two localization simulation models and a physical experiment are conducted. Both the simulation results and physical experiment result provide accurate positioning performance, with the help to verify the effectiveness of the proposed localization method in underwater environments.

Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

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Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2015-10-01

In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.

Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks

KAUST Repository

Elsawy, Hesham

2017-10-04

This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks

KAUST Repository

Elsawy, Hesham; Dai, Wenhan; Alouini, Mohamed-Slim; Win, Moe Z.

2017-01-01

This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.

Ambient Sound-Based Collaborative Localization of Indeterministic Devices

NARCIS (Netherlands)

Kamminga, Jacob Wilhelm; Le Viet Duc, L Duc; Havinga, Paul J.M.

2016-01-01

Localization is essential in wireless sensor networks. To our knowledge, no prior work has utilized low-cost devices for collaborative localization based on only ambient sound, without the support of local infrastructure. The reason may be the fact that most low-cost devices are indeterministic and

Islands Climatology at Local Scale. Downscaling with CIELO model

Science.gov (United States)

Azevedo, Eduardo; Reis, Francisco; Tomé, Ricardo; Rodrigues, Conceição

2016-04-01

Islands with horizontal scales of the order of tens of km, as is the case of the Atlantic Islands of Macaronesia, are subscale orographic features for Global Climate Models (GCMs) since the horizontal scales of these models are too coarse to give a detailed representation of the islands' topography. Even the Regional Climate Models (RCMs) reveals limitations when they are forced to reproduce the climate of small islands mainly by the way they flat and lowers the elevation of the islands, reducing the capacity of the model to reproduce important local mechanisms that lead to a very deep local climate differentiation. Important local thermodynamics mechanisms like Foehn effect, or the influence of topography on radiation balance, have a prominent role in the climatic spatial differentiation. Advective transport of air - and the consequent induced adiabatic cooling due to orography - lead to transformations of the state parameters of the air that leads to the spatial configuration of the fields of pressure, temperature and humidity. The same mechanism is in the origin of the orographic clouds cover that, besides the direct role as water source by the reinforcement of precipitation, act like a filter to direct solar radiation and as a source of long-wave radiation that affect the local balance of energy. Also, the saturation (or near saturation) conditions that they provide constitute a barrier to water vapour diffusion in the mechanisms of evapotranspiration. Topographic factors like slope, aspect and orographic mask have also significant importance in the local energy balance. Therefore, the simulation of the local scale climate (past, present and future) in these archipelagos requires the use of downscaling techniques to adjust locally outputs obtained at upper scales. This presentation will discuss and analyse the evolution of the CIELO model (acronym for Clima Insular à Escala LOcal) a statistical/dynamical technique developed at the University of the Azores

Developing Writing Skill of Language Students by Applying Innovative Teaching Strategy Model Based on Social and Local Wisdom Contexts

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Syarifuddin Achmad

2017-12-01

Full Text Available The aim of this study is to build up students’ writing skills through Innovation Teaching Strategy Model (ITSM. This study was conducted in Letters and Culture Faculty of Universitas Negeri Gorontalo (UNG, with the students of English and Indonesian department as the participants. The current study is based on the social culture and local wisdom context utilizing Information Computer Technology (ICT. This model supports the students to have a high level of thinking and performance in writing skills in English and Indonesian language. This study utilized Research and Development (R &D approach using Focus Group Discussion (FGD and Reflection method with the strategy of one group pre-test and post-test design. This study reaches two target achievements; firstly creating the effective innovation teaching strategy model after statistic examining through one group pre-test and post-test design, and secondly improving the students’ competencies and writing skill through learning and teaching process treatment of writing course as an effect of applying Innovation teaching strategy model application.

Modeling Source Water TOC Using Hydroclimate Variables and Local Polynomial Regression.

Science.gov (United States)

Samson, Carleigh C; Rajagopalan, Balaji; Summers, R Scott

2016-04-19

To control disinfection byproduct (DBP) formation in drinking water, an understanding of the source water total organic carbon (TOC) concentration variability can be critical. Previously, TOC concentrations in water treatment plant source waters have been modeled using streamflow data. However, the lack of streamflow data or unimpaired flow scenarios makes it difficult to model TOC. In addition, TOC variability under climate change further exacerbates the problem. Here we proposed a modeling approach based on local polynomial regression that uses climate, e.g. temperature, and land surface, e.g., soil moisture, variables as predictors of TOC concentration, obviating the need for streamflow. The local polynomial approach has the ability to capture non-Gaussian and nonlinear features that might be present in the relationships. The utility of the methodology is demonstrated using source water quality and climate data in three case study locations with surface source waters including river and reservoir sources. The models show good predictive skill in general at these locations, with lower skills at locations with the most anthropogenic influences in their streams. Source water TOC predictive models can provide water treatment utilities important information for making treatment decisions for DBP regulation compliance under future climate scenarios.

Spatial planning via extremal optimization enhanced by cell-based local search

International Nuclear Information System (INIS)

Sidiropoulos, Epaminondas

2014-01-01

A new treatment is presented for land use planning problems by means of extremal optimization in conjunction to cell-based neighborhood local search. Extremal optimization, inspired by self-organized critical models of evolution has been applied mainly to the solution of classical combinatorial optimization problems. Cell-based local search has been employed by the author elsewhere in problems of spatial resource allocation in combination with genetic algorithms and simulated annealing. In this paper it complements extremal optimization in order to enhance its capacity for a spatial optimization problem. The hybrid method thus formed is compared to methods of the literature on a specific characteristic problem. It yields better results both in terms of objective function values and in terms of compactness. The latter is an important quantity for spatial planning. The present treatment yields significant compactness values as emergent results

Vortices, semi-local vortices in gauged linear sigma model

International Nuclear Information System (INIS)

Kim, Namkwon

1998-11-01

We consider the static (2+1)D gauged linear sigma model. By analyzing the governing system of partial differential equations, we investigate various aspects of the model. We show the existence of energy finite vortices under a partially broken symmetry on R 2 with the necessary condition suggested by Y. Yang. We also introduce generalized semi-local vortices and show the existence of energy finite semi-local vortices under a certain condition. The vacuum manifold for the semi-local vortices turns out to be graded. Besides, with a special choice of a representation, we show that the O(3) sigma model of which target space is nonlinear is a singular limit of the gauged linear sigma model of which target space is linear. (author)

Compressing Sensing Based Source Localization for Controlled Acoustic Signals Using Distributed Microphone Arrays

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Wei Ke

2017-01-01

Full Text Available In order to enhance the accuracy of sound source localization in noisy and reverberant environments, this paper proposes an adaptive sound source localization method based on distributed microphone arrays. Since sound sources lie at a few points in the discrete spatial domain, our method can exploit this inherent sparsity to convert the localization problem into a sparse recovery problem based on the compressive sensing (CS theory. In this method, a two-step discrete cosine transform- (DCT- based feature extraction approach is utilized to cover both short-time and long-time properties of acoustic signals and reduce the dimensions of the sparse model. In addition, an online dictionary learning (DL method is used to adjust the dictionary for matching the changes of audio signals, and then the sparse solution could better represent location estimations. Moreover, we propose an improved block-sparse reconstruction algorithm using approximate l0 norm minimization to enhance reconstruction performance for sparse signals in low signal-noise ratio (SNR conditions. The effectiveness of the proposed scheme is demonstrated by simulation results and experimental results where substantial improvement for localization performance can be obtained in the noisy and reverberant conditions.

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

Science.gov (United States)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property

Noise Localization Method for Model Tests in a Large Cavitation Tunnel Using a Hydrophone Array

Directory of Open Access Journals (Sweden)

Cheolsoo Park

2016-02-01

Full Text Available Model tests are performed in order to predict the noise level of a full ship and to control its noise signature. Localizing noise sources in the model test is therefore an important research subject along with measuring noise levels. In this paper, a noise localization method using a hydrophone array in a large cavitation tunnel is presented. The 45-channel hydrophone array was designed using a global optimization technique for noise measurement. A set of noise experiments was performed in the KRISO (Korea Research Institute of Ships & Ocean Engineering large cavitation tunnel using scaled models, including a ship with a single propeller, a ship with twin propellers and an underwater vehicle. The incoherent broadband processors defined based on the Bartlett and the minimum variance (MV processors were applied to the measured data. The results of data analysis and localization are presented in the paper. Finally, it is shown that the mechanical noise, as well as the propeller noise can be successfully localized using the proposed localization method.

Development and validation of deterioration models for concrete bridge decks - phase 2 : mechanics-based degradation models.

Science.gov (United States)

2013-06-01

This report summarizes a research project aimed at developing degradation models for bridge decks in the state of Michigan based on durability mechanics. A probabilistic framework to implement local-level mechanistic-based models for predicting the c...

EDF and local authorities: a historical model of compromise and control?

International Nuclear Information System (INIS)

Bouneau, Ch.

2008-01-01

The June 15, 1906 Distribution Act is central to the country's legal and energy heritage, and has retained, after 1946, its validity and relevance, in the era of EDF. By acknowledging the essential role of local authorities, mainly cities, it established the local public electricity agency (SPL) based on relationships between the licensor and the Licence Holder. After setting up the FNCCR (Federation Nationale des Collectivites Concedantes et Regies) in 1933, the April 8, 946 Nationalization Act had initiated a golden age for local electric economy control by public agencies, by confirming the privileges of local authorities. The end of rural electrification, the role of FACE (Fonds d'Amortissement des charges d'electrification rurale) and the increasing number of inter-city associations symbolize the French model of concession economy. Open competition under European energy liberalization directives since 1990 has led to increased authority, as well as responsibilities, for local authorities looking for a new SPL. Its key words are not only competitiveness, but also social and territorial solidarity and the new requirements of sustainable energy development, and its agenda. (author)

Full-wave modeling of ICRF waves: global and quasi-local descriptions

International Nuclear Information System (INIS)

Dumont, R. J.

2007-01-01

Waves in the Ion Cyclotron Range of Frequencies (ICRF) undergo significant space dispersion as they propagate in magnetic fusion plasmas, making it necessary to incorporate non-local effects in their physical description. Full-wave codes are routinely employed to simulate ICRF heating experiments in tokamaks. The vast majority of these codes rely on a description of the plasma based on a 'quasi-local' derivation of the dielectric tensor, i.e. assuming that the range of space dispersion remains small compared to the system dimensions. However, non-local effects caused by wide particle orbits are expected to play a significant role in current and future experiments featuring wave-driven fast ions, fusion-born alpha particles... Global formalisms have thus been proposed to include these effects in a more comprehensive fashion. Based on a description of the particle dynamics in terms of action-angle variables, a full-wave code, named EVE, is currently under development. Its first version, presented here, incorporates quasi-local expressions valid to second order in Larmor radius, derived from the more general Hamiltonian formalism. The obtained tool has the advantage of being compatible with the current requirements of integrated modeling, and lends itself to direct comparisons with existing codes

Local coding based matching kernel method for image classification.

Directory of Open Access Journals (Sweden)

Yan Song

Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

Dominant glint based prey localization in horseshoe bats: a possible strategy for noise rejection.

Science.gov (United States)

Vanderelst, Dieter; Reijniers, Jonas; Firzlaff, Uwe; Peremans, Herbert

2011-12-01

Rhinolophidae or Horseshoe bats emit long and narrowband calls. Fluttering insect prey generates echoes in which amplitude and frequency shifts are present, i.e. glints. These glints are reliable cues about the presence of prey and also encode certain properties of the prey. In this paper, we propose that these glints, i.e. the dominant glints, are also reliable signals upon which to base prey localization. In contrast to the spectral cues used by many other bats, the localization cues in Rhinolophidae are most likely provided by self-induced amplitude modulations generated by pinnae movement. Amplitude variations in the echo not introduced by the moving pinnae can be considered as noise interfering with the localization process. The amplitude of the dominant glints is very stable. Therefore, these parts of the echoes contain very little noise. However, using only the dominant glints potentially comes at a cost. Depending on the flutter rate of the insect, a limited number of dominant glints will be present in each echo giving the bat a limited number of sample points on which to base localization. We evaluate the feasibility of a strategy under which Rhinolophidae use only dominant glints. We use a computational model of the echolocation task faced by Rhinolophidae. Our model includes the spatial filtering of the echoes by the morphology of the sonar apparatus of Rhinolophus rouxii as well as the amplitude modulations introduced by pinnae movements. Using this model, we evaluate whether the dominant glints provide Rhinolophidae with enough information to perform localization. Our simulations show that Rhinolophidae can use dominant glints in the echoes as carriers for self-induced amplitude modulations serving as localization cues. In particular, it is shown that the reduction in noise achieved by using only the dominant glints outweighs the information loss that occurs by sampling the echo. © 2011 Vanderelst et al.

Dominant glint based prey localization in horseshoe bats: a possible strategy for noise rejection.

Directory of Open Access Journals (Sweden)

Dieter Vanderelst

2011-12-01

Full Text Available Rhinolophidae or Horseshoe bats emit long and narrowband calls. Fluttering insect prey generates echoes in which amplitude and frequency shifts are present, i.e. glints. These glints are reliable cues about the presence of prey and also encode certain properties of the prey. In this paper, we propose that these glints, i.e. the dominant glints, are also reliable signals upon which to base prey localization. In contrast to the spectral cues used by many other bats, the localization cues in Rhinolophidae are most likely provided by self-induced amplitude modulations generated by pinnae movement. Amplitude variations in the echo not introduced by the moving pinnae can be considered as noise interfering with the localization process. The amplitude of the dominant glints is very stable. Therefore, these parts of the echoes contain very little noise. However, using only the dominant glints potentially comes at a cost. Depending on the flutter rate of the insect, a limited number of dominant glints will be present in each echo giving the bat a limited number of sample points on which to base localization. We evaluate the feasibility of a strategy under which Rhinolophidae use only dominant glints. We use a computational model of the echolocation task faced by Rhinolophidae. Our model includes the spatial filtering of the echoes by the morphology of the sonar apparatus of Rhinolophus rouxii as well as the amplitude modulations introduced by pinnae movements. Using this model, we evaluate whether the dominant glints provide Rhinolophidae with enough information to perform localization. Our simulations show that Rhinolophidae can use dominant glints in the echoes as carriers for self-induced amplitude modulations serving as localization cues. In particular, it is shown that the reduction in noise achieved by using only the dominant glints outweighs the information loss that occurs by sampling the echo.

Fiber Bragg grating based arterial localization device

Science.gov (United States)

Ho, Siu Chun Michael; Li, Weijie; Razavi, Mehdi; Song, Gangbing

2017-06-01

A critical first step to many surgical procedures is locating and gaining access to a patients vascular system. Vascular access allows the deployment of other surgical instruments and also the monitoring of many physiological parameters. Current methods to locate blood vessels are predominantly based on the landmark technique coupled with ultrasound, fluoroscopy, or Doppler. However, even with experience and technological assistance, locating the required blood vessel is not always an easy task, especially with patients that present atypical anatomy or suffer from conditions such as weak pulsation or obesity that make vascular localization difficult. With recent advances in fiber optic sensors, there is an opportunity to develop a new tool that can make vascular localization safer and easier. In this work, the authors present a new fiber Bragg grating (FBG) based vascular access device that specializes in arterial localization. The device estimates the location towards a local artery based on the bending of a needle inserted near the tissue surrounding the artery. Experimental results obtained from an artificial circulatory loop and a mock artery show the device works best for lower angles of needle insertion and can provide an approximately 40° range of estimation towards the location of a pulsating source (e.g. an artery).

Local Competition-Based Superpixel Segmentation Algorithm in Remote Sensing

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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.

Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

KAUST Repository

Pan, Bing; Wang, B.; Lubineau, Gilles; Moussawi, Ali

2015-01-01

Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

Comparison of Subset-Based Local and Finite Element-Based Global Digital Image Correlation

KAUST Repository

Pan, Bing

2015-02-12

Digital image correlation (DIC) techniques require an image matching algorithm to register the same physical points represented in different images. Subset-based local DIC and finite element-based (FE-based) global DIC are the two primary image matching methods that have been extensively investigated and regularly used in the field of experimental mechanics. Due to its straightforward implementation and high efficiency, subset-based local DIC has been used in almost all commercial DIC packages. However, it is argued by some researchers that FE-based global DIC offers better accuracy because of the enforced continuity between element nodes. We propose a detailed performance comparison between these different DIC algorithms both in terms of measurement accuracy and computational efficiency. Then, by measuring displacements of the same calculation points using the same calculation algorithms (e.g., correlation criterion, initial guess estimation, subpixel interpolation, optimization algorithm and convergence conditions) and identical calculation parameters (e.g., subset or element size), the performances of subset-based local DIC and two FE-based global DIC approaches are carefully compared in terms of measurement error and computational efficiency using both numerical tests and real experiments. A detailed examination of the experimental results reveals that, when subset (element) size is not very small and the local deformation within a subset (element) can be well approximated by the shape function used, standard subset-based local DIC approach not only provides better results in measured displacements, but also demonstrates much higher computation efficiency. However, several special merits of FE-based global DIC approaches are indicated.

Correspondence model-based 4D VMAT dose simulation for analysis of local metastasis recurrence after extracranial SBRT

Science.gov (United States)

Sothmann, T.; Gauer, T.; Wilms, M.; Werner, R.

2017-12-01

The purpose of this study is to introduce a novel approach to incorporate patient-specific breathing variability information into 4D dose simulation of volumetric arc therapy (VMAT)-based stereotactic body radiotherapy (SBRT) of extracranial metastases. Feasibility of the approach is illustrated by application to treatment planning and motion data of lung and liver metastasis patients. The novel 4D dose simulation approach makes use of a regression-based correspondence model that allows representing patient motion variability by breathing signal-steered interpolation and extrapolation of deformable image registration motion fields. To predict the internal patient motion during treatment with only external breathing signal measurements being available, the patients’ internal motion information and external breathing signals acquired during 4D CT imaging were correlated. Combining the correspondence model, patient-specific breathing signal measurements during treatment and time-resolved information about dose delivery, reconstruction of a motion variability-affected dose becomes possible. As a proof of concept, the proposed approach is illustrated by a retrospective 4D simulation of VMAT-based SBRT treatment of ten patients with 15 treated lung and liver metastases and known clinical endpoints for the individual metastases (local metastasis recurrence yes/no). Resulting 4D-simulated dose distributions were compared to motion-affected dose distributions estimated by standard 4D CT-only dose accumulation and the originally (i.e. statically) planned dose distributions by means of GTV D98 indices (dose to 98% of the GTV volume). A potential linkage of metastasis-specific endpoints to differences between GTV D98 indices of planned and 4D-simulated dose distributions was analyzed.

A statistical-dynamical modeling approach for the simulation of local paleo proxy records using GCM output

Energy Technology Data Exchange (ETDEWEB)

Reichert, B.K.; Bengtsson, L. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Aakesson, O. [Sveriges Meteorologiska och Hydrologiska Inst., Norrkoeping (Sweden)

1998-08-01

Recent proxy data obtained from ice core measurements, dendrochronology and valley glaciers provide important information on the evolution of the regional or local climate. General circulation models integrated over a long period of time could help to understand the (external and internal) forcing mechanisms of natural climate variability. For a systematic interpretation of in situ paleo proxy records, a combined method of dynamical and statistical modeling is proposed. Local 'paleo records' can be simulated from GCM output by first undertaking a model-consistent statistical downscaling and then using a process-based forward modeling approach to obtain the behavior of valley glaciers and the growth of trees under specific conditions. The simulated records can be compared to actual proxy records in order to investigate whether e.g. the response of glaciers to climatic change can be reproduced by models and to what extent climate variability obtained from proxy records (with the main focus on the last millennium) can be represented. For statistical downscaling to local weather conditions, a multiple linear forward regression model is used. Daily sets of observed weather station data and various large-scale predictors at 7 pressure levels obtained from ECMWF reanalyses are used for development of the model. Daily data give the closest and most robust relationships due to the strong dependence on individual synoptic-scale patterns. For some local variables, the performance of the model can be further increased by developing seasonal specific statistical relationships. The model is validated using both independent and restricted predictor data sets. The model is applied to a long integration of a mixed layer GCM experiment simulating pre-industrial climate variability. The dynamical-statistical local GCM output within a region around Nigardsbreen glacier, Norway is compared to nearby observed station data for the period 1868-1993. Patterns of observed

Graph-Based Semi-Supervised Learning for Indoor Localization Using Crowdsourced Data

Directory of Open Access Journals (Sweden)

Liye Zhang

2017-04-01

Full Text Available Indoor positioning based on the received signal strength (RSS of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing have been proposed. However, compared to conventional methods, lots of different devices are used in crowdsourcing system and less RSS values are collected by each device. Therefore, the crowdsourced RSS values are more erroneous and can result in significant localization errors. In order to eliminate the signal strength variations across diverse devices, the Linear Regression (LR algorithm is proposed to solve the device diversity problem in crowdsourcing system. After obtaining the uniform RSS values, a graph-based semi-supervised learning (G-SSL method is used to exploit the correlation between the RSS values at nearby locations to estimate an optimal RSS value at each location. As a result, the negative effect of the erroneous measurements could be mitigated. Since the AP locations need to be known in G-SSL algorithm, the Compressed Sensing (CS method is applied to precisely estimate the location of the APs. Based on the location of the APs and a simple signal propagation model, the RSS difference between different locations is calculated and used as an additional constraint to improve the performance of G-SSL. Furthermore, to exploit the sparsity of the weights used in the G-SSL, we use the CS method to reconstruct these weights more accurately and make a further improvement on the performance of the G-SSL. Experimental results show improved results in terms of the smoothness of the radio map and the localization accuracy.

A novel local learning based approach with application to breast cancer diagnosis

Science.gov (United States)

Xu, Songhua; Tourassi, Georgia

2012-03-01

In this paper, we introduce a new local learning based approach and apply it for the well-studied problem of breast cancer diagnosis using BIRADS-based mammographic features. To learn from our clinical dataset the latent relationship between these features and the breast biopsy result, our method first dynamically partitions the whole sample population into multiple sub-population groups through stochastically searching the sample population clustering space. Each encountered clustering scheme in our online searching process is then used to create a certain sample population partition plan. For every resultant sub-population group identified according to a partition plan, our method then trains a dedicated local learner to capture the underlying data relationship. In our study, we adopt the linear logistic regression model as our local learning method's base learner. Such a choice is made both due to the well-understood linear nature of the problem, which is compellingly revealed by a rich body of prior studies, and the computational efficiency of linear logistic regression--the latter feature allows our local learning method to more effectively perform its search in the sample population clustering space. Using a database of 850 biopsy-proven cases, we compared the performance of our method with a large collection of publicly available state-of-the-art machine learning methods and successfully demonstrated its performance advantage with statistical significance.

The charge-asymmetric nonlocally determined local-electric (CANDLE) solvation model

Energy Technology Data Exchange (ETDEWEB)

Sundararaman, Ravishankar; Goddard, William A. [Joint Center for Artificial Photosynthesis, Pasadena, California 91125 (United States)

2015-02-14

Many important applications of electronic structure methods involve molecules or solid surfaces in a solvent medium. Since explicit treatment of the solvent in such methods is usually not practical, calculations often employ continuum solvation models to approximate the effect of the solvent. Previous solvation models either involve a parametrization based on atomic radii, which limits the class of applicable solutes, or based on solute electron density, which is more general but less accurate, especially for charged systems. We develop an accurate and general solvation model that includes a cavity that is a nonlocal functional of both solute electron density and potential, local dielectric response on this nonlocally determined cavity, and nonlocal approximations to the cavity-formation and dispersion energies. The dependence of the cavity on the solute potential enables an explicit treatment of the solvent charge asymmetry. With four parameters per solvent, this “CANDLE” model simultaneously reproduces solvation energies of large datasets of neutral molecules, cations, and anions with a mean absolute error of 1.8 kcal/mol in water and 3.0 kcal/mol in acetonitrile.

Locally supersymmetric D=3 non-linear sigma models

International Nuclear Information System (INIS)

Wit, B. de; Tollsten, A.K.; Nicolai, H.

1993-01-01

We study non-linear sigma models with N local supersymmetries in three space-time dimensions. For N=1 and 2 the target space of these models is riemannian or Kaehler, respectively. All N>2 theories are associated with Einstein spaces. For N=3 the target space is quaternionic, while for N=4 it generally decomposes, into two separate quaternionic spaces, associated with inequivalent supermultiplets. For N=5, 6, 8 there is a unique (symmetric) space for any given number of supermultiplets. Beyond that there are only theories based on a single supermultiplet for N=9, 10, 12 and 16, associated with coset spaces with the exceptional isometry groups F 4(-20) , E 6(-14) , E 7(-5) and E 8(+8) , respectively. For N=3 and N ≥ 5 the D=2 theories obtained by dimensional reduction are two-loop finite. (orig.)

A cloud based tool for knowledge exchange on local scale flood risk.

Science.gov (United States)

Wilkinson, M E; Mackay, E; Quinn, P F; Stutter, M; Beven, K J; MacLeod, C J A; Macklin, M G; Elkhatib, Y; Percy, B; Vitolo, C; Haygarth, P M

2015-09-15

There is an emerging and urgent need for new approaches for the management of environmental challenges such as flood hazard in the broad context of sustainability. This requires a new way of working which bridges disciplines and organisations, and that breaks down science-culture boundaries. With this, there is growing recognition that the appropriate involvement of local communities in catchment management decisions can result in multiple benefits. However, new tools are required to connect organisations and communities. The growth of cloud based technologies offers a novel way to facilitate this process of exchange of information in environmental science and management; however, stakeholders need to be engaged with as part of the development process from the beginning rather than being presented with a final product at the end. Here we present the development of a pilot Local Environmental Virtual Observatory Flooding Tool. The aim was to develop a cloud based learning platform for stakeholders, bringing together fragmented data, models and visualisation tools that will enable these stakeholders to make scientifically informed environmental management decisions at the local scale. It has been developed by engaging with different stakeholder groups in three catchment case studies in the UK and a panel of national experts in relevant topic areas. However, these case study catchments are typical of many northern latitude catchments. The tool was designed to communicate flood risk in locally impacted communities whilst engaging with landowners/farmers about the risk of runoff from the farmed landscape. It has been developed iteratively to reflect the needs, interests and capabilities of a wide range of stakeholders. The pilot tool combines cloud based services, local catchment datasets, a hydrological model and bespoke visualisation tools to explore real time hydrometric data and the impact of flood risk caused by future land use changes. The novel aspects of the

Hop-distance relationship analysis with quasi-UDG model for node localization in wireless sensor networks

Directory of Open Access Journals (Sweden)

Chen Ping

2011-01-01

Full Text Available Abstract In wireless sensor networks (WSNs, location information plays an important role in many fundamental services which includes geographic routing, target tracking, location-based coverage, topology control, and others. One promising approach in sensor network localization is the determination of location based on hop counts. A critical priori of this approach that directly influences the accuracy of location estimation is the hop-distance relationship. However, most of the related works on the hop-distance relationship assume the unit-disk graph (UDG model that is unrealistic in a practical scenario. In this paper, we formulate the hop-distance relationship for quasi-UDG model in WSNs where sensor nodes are randomly and independently deployed in a circular region based on a Poisson point process. Different from the UDG model, quasi-UDG model has the non-uniformity property for connectivity. We derive an approximated recursive expression for the probability of the hop count with a given geographic distance. The border effect and dependence problem are also taken into consideration. Furthermore, we give the expressions describing the distribution of distance with known hop counts for inner nodes and those suffered from the border effect where we discover the insignificance of the border effect. The analytical results are validated by simulations showing the accuracy of the employed approximation. Besides, we demonstrate the localization application of the formulated relationship and show the accuracy improvement in the WSN localization.

Modelling of local extinction and reignition of the flame

Energy Technology Data Exchange (ETDEWEB)

Brink, A.; Kilpinen, P.; Hupa, M. [Aabo Akademi, Turku (Finland); Kjaeldman, L. [VTT Energy, Espoo (Finland); Jaeaeskelaeinen, K. [Imatran Voima Oy, Helsinki (Finland)

1996-12-31

The influence of the relations between the chemical time scale and the turbulent time scale on local extinction in turbulent flames has been studied. The results from the numerical investigation of a non-swirling flame in a sudden-expansion combustor was compared with measurements and computations reported in the literature. The turbulence-chemistry interaction was modelled using the Eddy-Dissipation Concept (EDC). In the study, different turbulent time scales were used; the Kolmogorov related time scale proposed in the EDC model and two turbulent time scales related to k/{epsilon}. The chemical time scale has been obtained from a model based on calculations with a comprehensive chemical reaction scheme. The results indicate that the Kolmogorov related time scale of the EDC model is too short to be used as an extinction criterium. The two k/{epsilon} related time scales both resulted in a closer agreement between the numerically obtained and the measured results. The result indicates that the time scale used in the EDC model should be further investigated before confident results from modelling of flows with extinction effects can be obtained. (author)

Modelling of local extinction and reignition of the flame

Energy Technology Data Exchange (ETDEWEB)

Brink, A; Kilpinen, P; Hupa, M [Aabo Akademi, Turku (Finland); Kjaeldman, L [VTT Energy, Espoo (Finland); Jaeaeskelaeinen, K [Imatran Voima Oy, Helsinki (Finland)

1997-12-31

The influence of the relations between the chemical time scale and the turbulent time scale on local extinction in turbulent flames has been studied. The results from the numerical investigation of a non-swirling flame in a sudden-expansion combustor was compared with measurements and computations reported in the literature. The turbulence-chemistry interaction was modelled using the Eddy-Dissipation Concept (EDC). In the study, different turbulent time scales were used; the Kolmogorov related time scale proposed in the EDC model and two turbulent time scales related to k/{epsilon}. The chemical time scale has been obtained from a model based on calculations with a comprehensive chemical reaction scheme. The results indicate that the Kolmogorov related time scale of the EDC model is too short to be used as an extinction criterium. The two k/{epsilon} related time scales both resulted in a closer agreement between the numerically obtained and the measured results. The result indicates that the time scale used in the EDC model should be further investigated before confident results from modelling of flows with extinction effects can be obtained. (author)

Multi-fidelity wake modelling based on Co-Kriging method

DEFF Research Database (Denmark)

Wang, Y. M.; Réthoré, Pierre-Elouan; van der Laan, Paul

2016-01-01

models, respectively. Both the univariate and multivariate based surrogate models are established by taking the local wind speed and wind direction as variables of the wind farm power efficiency function. Various multi-fidelity surrogate models are compared and different sampling schemes are discussed...

Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons

Directory of Open Access Journals (Sweden)

Yuan Zhuang

2016-04-01

Full Text Available Indoor wireless localization using Bluetooth Low Energy (BLE beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM, channel-separate fingerprinting (FP, outlier detection and extended Kalman filtering (EKF for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target’s location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy. The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of <2.56 m at 90% of the time with dense deployment of BLE beacons (1 beacon per 9 m, which performs 35.82% better than <3.99 m from the Propagation Model (PM + EKF algorithm and 15.77% more accurate than <3.04 m from the FP + EKF algorithm. With sparse deployment (1 beacon per 18 m, the proposed algorithm achieves the accuracies of <3.88 m at

The morphing method as a flexible tool for adaptive local/non-local simulation of static fracture

KAUST Repository

Azdoud, Yan

2014-04-19

We introduce a framework that adapts local and non-local continuum models to simulate static fracture problems. Non-local models based on the peridynamic theory are promising for the simulation of fracture, as they allow discontinuities in the displacement field. However, they remain computationally expensive. As an alternative, we develop an adaptive coupling technique based on the morphing method to restrict the non-local model adaptively during the evolution of the fracture. The rest of the structure is described by local continuum mechanics. We conduct all simulations in three dimensions, using the relevant discretization scheme in each domain, i.e., the discontinuous Galerkin finite element method in the peridynamic domain and the continuous finite element method in the local continuum mechanics domain. © 2014 Springer-Verlag Berlin Heidelberg.

A non-local shell model of hydrodynamic and magnetohydrodynamic turbulence

Energy Technology Data Exchange (ETDEWEB)

Plunian, F [Laboratoire de Geophysique Interne et Tectonophysique, CNRS, Universite Joseph Fourier, Maison des Geosciences, BP 53, 38041 Grenoble Cedex 9 (France); Stepanov, R [Institute of Continuous Media Mechanics, Korolyov 1, 614013 Perm (Russian Federation)

2007-08-15

We derive a new shell model of magnetohydrodynamic (MHD) turbulence in which the energy transfers are not necessarily local. Like the original MHD equations, the model conserves the total energy, magnetic helicity, cross-helicity and volume in phase space (Liouville's theorem) apart from the effects of external forcing, viscous dissipation and magnetic diffusion. The model of hydrodynamic (HD) turbulence is derived from the MHD model setting the magnetic field to zero. In that case the conserved quantities are the kinetic energy and the kinetic helicity. In addition to a statistically stationary state with a Kolmogorov spectrum, the HD model exhibits multiscaling. The anomalous scaling exponents are found to depend on a free parameter {alpha} that measures the non-locality degree of the model. In freely decaying turbulence, the infra-red spectrum also depends on {alpha}. Comparison with theory suggests using {alpha} = -5/2. In MHD turbulence, we investigate the fully developed turbulent dynamo for a wide range of magnetic Prandtl numbers in both kinematic and dynamic cases. Both local and non-local energy transfers are clearly identified.

Online Adaptive Local-Global Model Reduction for Flows in Heterogeneous Porous Media

KAUST Repository

Efendiev, Yalchin R.; Gildin, Eduardo; Yang, Yanfang

2016-01-01

We propose an online adaptive local-global POD-DEIM model reduction method for flows in heterogeneous porous media. The main idea of the proposed method is to use local online indicators to decide on the global update, which is performed via reduced cost local multiscale basis functions. This unique local-global online combination allows (1) developing local indicators that are used for both local and global updates (2) computing global online modes via local multiscale basis functions. The multiscale basis functions consist of offline and some online local basis functions. The approach used for constructing a global reduced system is based on Proper Orthogonal Decomposition (POD) Galerkin projection. The nonlinearities are approximated by the Discrete Empirical Interpolation Method (DEIM). The online adaption is performed by incorporating new data, which become available at the online stage. Once the criterion for updates is satisfied, we adapt the reduced system online by changing the POD subspace and the DEIM approximation of the nonlinear functions. The main contribution of the paper is that the criterion for adaption and the construction of the global online modes are based on local error indicators and local multiscale basis function which can be cheaply computed. Since the adaption is performed infrequently, the new methodology does not add significant computational overhead associated with when and how to adapt the reduced basis. Our approach is particularly useful for situations where it is desired to solve the reduced system for inputs or controls that result in a solution outside the span of the snapshots generated in the offline stage. Our method also offers an alternative of constructing a robust reduced system even if a potential initial poor choice of snapshots is used. Applications to single-phase and two-phase flow problems demonstrate the efficiency of our method.

Online Adaptive Local-Global Model Reduction for Flows in Heterogeneous Porous Media

KAUST Repository

Efendiev, Yalchin R.

2016-06-07

We propose an online adaptive local-global POD-DEIM model reduction method for flows in heterogeneous porous media. The main idea of the proposed method is to use local online indicators to decide on the global update, which is performed via reduced cost local multiscale basis functions. This unique local-global online combination allows (1) developing local indicators that are used for both local and global updates (2) computing global online modes via local multiscale basis functions. The multiscale basis functions consist of offline and some online local basis functions. The approach used for constructing a global reduced system is based on Proper Orthogonal Decomposition (POD) Galerkin projection. The nonlinearities are approximated by the Discrete Empirical Interpolation Method (DEIM). The online adaption is performed by incorporating new data, which become available at the online stage. Once the criterion for updates is satisfied, we adapt the reduced system online by changing the POD subspace and the DEIM approximation of the nonlinear functions. The main contribution of the paper is that the criterion for adaption and the construction of the global online modes are based on local error indicators and local multiscale basis function which can be cheaply computed. Since the adaption is performed infrequently, the new methodology does not add significant computational overhead associated with when and how to adapt the reduced basis. Our approach is particularly useful for situations where it is desired to solve the reduced system for inputs or controls that result in a solution outside the span of the snapshots generated in the offline stage. Our method also offers an alternative of constructing a robust reduced system even if a potential initial poor choice of snapshots is used. Applications to single-phase and two-phase flow problems demonstrate the efficiency of our method.

Local understandings of conservation in southeastern Mexico and their implications for community-based conservation as an alternative paradigm.

Science.gov (United States)

Reyes-Garcia, Victoria; Ruiz-Mallen, Isabel; Porter-Bolland, Luciana; Garcia-Frapolli, Eduardo; Ellis, Edward A; Mendez, Maria-Elena; Pritchard, Diana J; Sanchez-Gonzalez, María-Consuelo

2013-08-01

Since the 1990s national and international programs have aimed to legitimize local conservation initiatives that might provide an alternative to the formal systems of state-managed or otherwise externally driven protected areas. We used discourse analysis (130 semistructured interviews with key informants) and descriptive statistics (679 surveys) to compare local perceptions of and experiences with state-driven versus community-driven conservation initiatives. We conducted our research in 6 communities in southeastern Mexico. Formalization of local conservation initiatives did not seem to be based on local knowledge and practices. Although interviewees thought community-based initiatives generated less conflict than state-managed conservation initiatives, the community-based initiatives conformed to the biodiversity conservation paradigm that emphasizes restricted use of and access to resources. This restrictive approach to community-based conservation in Mexico, promoted through state and international conservation organizations, increased the area of protected land and had local support but was not built on locally relevant and multifunctional landscapes, a model that community-based conservation is assumed to advance. © 2013 Society for Conservation Biology.

General Business Model Patterns for Local Energy Management Concepts

International Nuclear Information System (INIS)

Facchinetti, Emanuele; Sulzer, Sabine

2016-01-01

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

General Business Model Patterns for Local Energy Management Concepts

Energy Technology Data Exchange (ETDEWEB)

Facchinetti, Emanuele, E-mail: emanuele.facchinetti@hslu.ch; Sulzer, Sabine [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland)

2016-03-03

The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

Modeling of Mixing Behavior in a Combined Blowing Steelmaking Converter with a Filter-Based Euler-Lagrange Model

Science.gov (United States)

Li, Mingming; Li, Lin; Li, Qiang; Zou, Zongshu

2018-05-01

A filter-based Euler-Lagrange multiphase flow model is used to study the mixing behavior in a combined blowing steelmaking converter. The Euler-based volume of fluid approach is employed to simulate the top blowing, while the Lagrange-based discrete phase model that embeds the local volume change of rising bubbles for the bottom blowing. A filter-based turbulence method based on the local meshing resolution is proposed aiming to improve the modeling of turbulent eddy viscosities. The model validity is verified through comparison with physical experiments in terms of mixing curves and mixing times. The effects of the bottom gas flow rate on bath flow and mixing behavior are investigated and the inherent reasons for the mixing result are clarified in terms of the characteristics of bottom-blowing plumes, the interaction between plumes and top-blowing jets, and the change of bath flow structure.

A generative, probabilistic model of local protein structure

DEFF Research Database (Denmark)

Boomsma, Wouter; Mardia, Kanti V.; Taylor, Charles C.

2008-01-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative...... conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state...

Local yield stress statistics in model amorphous solids

Science.gov (United States)

Barbot, Armand; Lerbinger, Matthias; Hernandez-Garcia, Anier; García-García, Reinaldo; Falk, Michael L.; Vandembroucq, Damien; Patinet, Sylvain

2018-03-01

We develop and extend a method presented by Patinet, Vandembroucq, and Falk [Phys. Rev. Lett. 117, 045501 (2016), 10.1103/PhysRevLett.117.045501] to compute the local yield stresses at the atomic scale in model two-dimensional Lennard-Jones glasses produced via differing quench protocols. This technique allows us to sample the plastic rearrangements in a nonperturbative manner for different loading directions on a well-controlled length scale. Plastic activity upon shearing correlates strongly with the locations of low yield stresses in the quenched states. This correlation is higher in more structurally relaxed systems. The distribution of local yield stresses is also shown to strongly depend on the quench protocol: the more relaxed the glass, the higher the local plastic thresholds. Analysis of the magnitude of local plastic relaxations reveals that stress drops follow exponential distributions, justifying the hypothesis of an average characteristic amplitude often conjectured in mesoscopic or continuum models. The amplitude of the local plastic rearrangements increases on average with the yield stress, regardless of the system preparation. The local yield stress varies with the shear orientation tested and strongly correlates with the plastic rearrangement locations when the system is sheared correspondingly. It is thus argued that plastic rearrangements are the consequence of shear transformation zones encoded in the glass structure that possess weak slip planes along different orientations. Finally, we justify the length scale employed in this work and extract the yield threshold statistics as a function of the size of the probing zones. This method makes it possible to derive physically grounded models of plasticity for amorphous materials by directly revealing the relevant details of the shear transformation zones that mediate this process.

Mobile Device Passive Localization Based on IEEE 802.11 Probe Request Frames

Directory of Open Access Journals (Sweden)

Lin Sun

2017-01-01

Full Text Available This paper presents a novel passive mobile device localization mode based on IEEE 802.11 Probe Request frames. In this approach, the listener can discover mobile devices by receiving the Probe Request frames and localize them on his walking path. The unique location of the mobile device is estimated on a geometric diagram and right-angled walking path. In model equations, site-related parameter, that is, path loss exponent, is eliminated to make the approach site-independent. To implement unique localization, the right-angled walking path is designed and the optimal location is estimated from the optional points. The performance of our method has been evaluated inside the room, outside the room, and in outdoor scenarios. Three kinds of walking paths, for example, horizontal, vertical, and slanted, are also tested.

AGRICULTURAL DEVELOPMENT PLANNING BASED ON LOCAL RESOURCES IN DEPOK CITY, INDONESIA

Directory of Open Access Journals (Sweden)

Abdurahim A.

2018-01-01

Full Text Available The background of this study is that Dewa Starfruit as a local resource in Depok City is threatened with extinction. The absence of regulations that protect these local resources and high rate of land use conversion causes decreasing number of starfruit plants and production. Starfruit farmers tend to switch professions to non-agricultural occupations. In national level, the largest number of agricultural business households experienced the greatest decline in horticulture subsector by 37.4% (Agricultural Census 2013. The elected regional head has branded Depok City with the tagline "friendly city" replacing Dewa Starfruit. The government's orientation and support for Dewa starfruit is fading away. Therefore, Depok City Government, especially DKP3, need to develop local resource-based agriculture development plan in order to be able to maintain local resources while improving it for society welfare. This research uses qualitative approach. The research informants were DKP3 apparatus of Depok City, Bappeda (Regional Government apparatus of Depok City, field officer and farmer group. Data collection techniques used in-depth interviews and documentary studies. Data analysis utilized interactive model. Research results indicate that the development of local resource-based agricultural development plans has not gone well. Despite various supporting factors, there are existing inhibiting factors which are land use conversion had never been discussed; DKP3 Depok City efforts to safeguard agricultural issues in musrenbang has not been optimal; no field data update, either by couseling workers or farmers; DKP3 Depok City prioritized RPL activity; uneducated farmers; and absence of regional head support.

Local galactic kinematics: an isothermal model

International Nuclear Information System (INIS)

Nunez, J.

1983-01-01

The kinematical parameters of galactic rotation in the solar neighborhood and the corrections to the precession have been calculated. For this purpose, an isothermal model for the solar neighborhood has been used together with the high order momenta of the local stellar velocity distribution and the Ogorodnikov-Milne model. Both have been calculated using some samples of the ''512 Distant FK4/FK4 Sup. Stars'' of Fricke (1977) and of Gliese's Gatalogue. (author)

Smartphone-Based Indoor Localization with Bluetooth Low Energy Beacons.

Science.gov (United States)

Zhuang, Yuan; Yang, Jun; Li, You; Qi, Longning; El-Sheimy, Naser

2016-04-26

Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localization with BLE beacons. The proposed algorithm uses FP and PRM to estimate the target's location and the distances between the target and BLE beacons respectively. We compare the performance of distance estimation that uses separate PRM for three advertisement channels (i.e., the separate strategy) with that use an aggregate PRM generated through the combination of information from all channels (i.e., the aggregate strategy). The performance of FP-based location estimation results of the separate strategy and the aggregate strategy are also compared. It was found that the separate strategy can provide higher accuracy; thus, it is preferred to adopt PRM and FP for each BLE advertisement channel separately. Furthermore, to enhance the robustness of the algorithm, a two-level outlier detection mechanism is designed. Distance and location estimates obtained from PRM and FP are passed to the first outlier detection to generate improved distance estimates for the EKF. After the EKF process, the second outlier detection algorithm based on statistical testing is further performed to remove the outliers. The proposed algorithm was evaluated by various field experiments. Results show that the proposed algorithm achieved the accuracy of EKF algorithm and 15.77% more accurate than EKF algorithm. With sparse deployment (1 beacon per 18 m), the proposed algorithm achieves the accuracies of EKF algorithm and 21.41% better than EKF algorithm. Therefore, the proposed algorithm is especially useful to improve the localization accuracy in environments with sparse beacon deployment.

An ultrasonic-based localization system for underground mines

CSIR Research Space (South Africa)

Jordaan, JP

2017-07-01

Full Text Available -based localization system for underground mines 2017 IEEE 15th International Conference on Industrial Informatics (INDIN), 24-26 July 2017, Emden, Germany JP Jordaan, CP Kruger, BJ Silva and GP Hancke Abstract: Localization is important for a wide range...

Local participation in biodiversity conservation initiatives: a comparative analysis of different models in South East Mexico.

Science.gov (United States)

Méndez-López, María Elena; García-Frapolli, Eduardo; Pritchard, Diana J; Sánchez González, María Consuelo; Ruiz-Mallén, Isabel; Porter-Bolland, Luciana; Reyes-Garcia, Victoria

2014-12-01

In Mexico, biodiversity conservation is primarily implemented through three schemes: 1) protected areas, 2) payment-based schemes for environmental services, and 3) community-based conservation, officially recognized in some cases as Indigenous and Community Conserved Areas. In this paper we compare levels of local participation across conservation schemes. Through a survey applied to 670 households across six communities in Southeast Mexico, we document local participation during the creation, design, and implementation of the management plan of different conservation schemes. To analyze the data, we first calculated the frequency of participation at the three different stages mentioned, then created a participation index that characterizes the presence and relative intensity of local participation for each conservation scheme. Results showed that there is a low level of local participation across all the conservation schemes explored in this study. Nonetheless, the payment for environmental services had the highest local participation while the protected areas had the least. Our findings suggest that local participation in biodiversity conservation schemes is not a predictable outcome of a specific (community-based) model, thus implying that other factors might be important in determining local participation. This has implications on future strategies that seek to encourage local involvement in conservation. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Study on Water Pollution Source Localization in Sensor Networks

Directory of Open Access Journals (Sweden)

Jun Yang

2016-01-01

Full Text Available The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.

A fingerprint classification algorithm based on combination of local and global information

Science.gov (United States)

Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

2011-12-01

Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

Non-local model analysis of heat pulse propagation and simulation of experiments in W7-AS

International Nuclear Information System (INIS)

Iwasaki, Takuya; Itoh, Sanae-I.; Yagi, Masatoshi; Itoh, Kimitaka; Stroth, U.

1999-01-01

A new model equation which includes the non-local effect in the hear flux is introduced to study the transient transport phenomena. A non-local heat flux, which is expressed in terms of the integral equation, is superimposed on the conventional form of the heat flux. This model is applied to describe the experimental results from the power switching [U. Stroth et al.: Plasma Phys. Control. Fusion 38 (1996) 1087] and the power modulation experiments [L. Giannone et al.: Nucl. Fusion 32 (1992) 1985] in the W7-AS stellarator. A small fraction of non-local component in the heat flux is found to be very effective in modifying the response against an external modulation. The transient feature of the transport property, which are observed in the response of heat pulse propagation, are qualitatively reproduced by the transport simulations based on this model. A possibility is discussed to estimate the correlation length of the non-local effect experimentally by use of the results of transport simulations. (author)

Bayesian-based localization in inhomogeneous transmission media

DEFF Research Database (Denmark)

Nadimi, E. S.; Blanes-Vidal, V.; Johansen, P. M.

2013-01-01

In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network with heteroge......In this paper, we propose a novel robust probabilistic approach based on the Bayesian inference using received-signal-strength (RSS) measurements with varying path-loss exponent. We derived the probability density function (pdf) of the distance between any two sensors in the network...... with heterogeneous transmission medium as a function of the given RSS measurements and the characteristics of the heterogeneous medium. The results of this study show that the localization mean square error (MSE) of the Bayesian-based method outperformed all other existing localization approaches. © 2013 ACM....

The Effectiveness of Local Culture-Based Mathematical Heuristic-KR Learning towards Enhancing Student's Creative Thinking Skill

Science.gov (United States)

Tandiseru, Selvi Rajuaty

2015-01-01

The problem in this research is the lack of creative thinking skills of students. One of the learning models that is expected to enhance student's creative thinking skill is the local culture-based mathematical heuristic-KR learning model (LC-BMHLM). Heuristic-KR is a learning model which was introduced by Krulik and Rudnick (1995) that is the…

Strategy community development based on local resources

Science.gov (United States)

Meirinawati; Prabawati, I.; Pradana, G. W.

2018-01-01

The problem of progressing regions is not far from economic problems and is often caused by the inability of the regions in response to changes in economic conditions that occur, so the need for community development programs implemented to solve various problems. Improved community effort required with the real conditions and needs of each region. Community development based on local resources process is very important, because it is an increase in human resource capability in the optimal utilization of local resource potential. In this case a strategy is needed in community development based on local resources. The community development strategy are as follows:(1) “Eight Line Equalization Plus” which explains the urgency of rural industrialization, (2) the construction of the village will be more successful when combining strategies are tailored to regional conditions, (3) the escort are positioning themselves as the Planner, supervisor, information giver, motivator, facilitator, connecting at once evaluators.

Including local rainfall dynamics and uncertain boundary conditions into a 2-D regional-local flood modelling cascade

Science.gov (United States)

Bermúdez, María; Neal, Jeffrey C.; Bates, Paul D.; Coxon, Gemma; Freer, Jim E.; Cea, Luis; Puertas, Jerónimo

2016-04-01

Flood inundation models require appropriate boundary conditions to be specified at the limits of the domain, which commonly consist of upstream flow rate and downstream water level. These data are usually acquired from gauging stations on the river network where measured water levels are converted to discharge via a rating curve. Derived streamflow estimates are therefore subject to uncertainties in this rating curve, including extrapolating beyond the maximum observed ratings magnitude. In addition, the limited number of gauges in reach-scale studies often requires flow to be routed from the nearest upstream gauge to the boundary of the model domain. This introduces additional uncertainty, derived not only from the flow routing method used, but also from the additional lateral rainfall-runoff contributions downstream of the gauging point. Although generally assumed to have a minor impact on discharge in fluvial flood modeling, this local hydrological input may become important in a sparse gauge network or in events with significant local rainfall. In this study, a method to incorporate rating curve uncertainty and the local rainfall-runoff dynamics into the predictions of a reach-scale flood inundation model is proposed. Discharge uncertainty bounds are generated by applying a non-parametric local weighted regression approach to stage-discharge measurements for two gauging stations, while measured rainfall downstream from these locations is cascaded into a hydrological model to quantify additional inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these inputs and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Improvements in model performance when incorporating these processes are quantified using observed

Introducing local property tax for fiscal decentralization and local authority autonomy

Science.gov (United States)

Dimopoulos, Thomas; Labropoulos, Tassos; Hadjimitsis, Diafantos G.

2015-06-01

Charles Tiebout (1956), in his work "A Pure Theory of Local Expenditures", provides a vision of the workings of the local public sector, acknowledging many similarities to the features of a competitive market, however omitting any references to local taxation. Contrary to other researchers' claim that the Tiebout model and the theory of fiscal decentralization are by no means synonymous, this paper aims to expand Tiebout's theory, by adding the local property tax in the context, introducing a fair, ad valorem property taxation system based on the automated assessment of the value of real estate properties within the boundaries of local authorities. Computer Assisted Mass Appraisal methodology integrated with Remote Sensing technology and GIS analysis is applied to local authorities' property registries and cadastral data, building a spatial relational database and providing data to be statistically processed through Multiple Regression Analysis modeling. The proposed scheme accomplishes economy of scale using CAMA procedures on one hand, but also succeeds in making local authorities self-sufficient through a decentralized, fair, locally calibrated property taxation model, providing rational income administration.

Asset-Based Community Development as a Strategy for Developing Local Global Health Curricula.

Science.gov (United States)

Webber, Sarah; Butteris, Sabrina M; Houser, Laura; Coller, Karen; Coller, Ryan J

2018-02-07

A significant and growing proportion of US children have immigrant parents, an issue of increasing importance to pediatricians. Training globally minded pediatric residents to address health inequities related to globalization is an important reason to expand educational strategies around local global health (LGH). We developed a curriculum in the pediatric global health residency track at the University of Wisconsin in an effort to address gaps in LGH education and to increase resident knowledge about local health disparities for global community members. This curriculum was founded in asset-based community development (ABCD), a strategy used in advocacy training but not reported in global health education. The initial curriculum outputs have provided the foundation for a longitudinal LGH curriculum and a community-academic partnership. Supported by a community partnership grant, this partnership is focused on establishing a community-based postpartum support group for local Latinos, with an emphasis on building capacity in the Latino community. Aspects of this curriculum can serve other programs looking to develop LGH curricula rooted in building local partnerships and capacity using an ABCD model. Copyright © 2018 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

Science.gov (United States)

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Adaptive local backlight dimming algorithm based on local histogram and image characteristics

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Burini, Nino; Korhonen, Jari

2013-01-01

-off between power consumption and image quality preservation than the other algorithms representing the state of the art among feature based backlight algorithms. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.......Liquid Crystal Display (LCDs) with Light Emitting Diode (LED) backlight is a very popular display technology, used for instance in television sets, monitors and mobile phones. This paper presents a new backlight dimming algorithm that exploits the characteristics of the target image......, such as the local histograms and the average pixel intensity of each backlight segment, to reduce the power consumption of the backlight and enhance image quality. The local histogram of the pixels within each backlight segment is calculated and, based on this average, an adaptive quantile value is extracted...

Localization of viewpoint of a video camera in a partially modeled universe

International Nuclear Information System (INIS)

Awanzino, C.

2000-01-01

Interventions in reprocessing cells in nuclear plants are performed by tele-operated robots. These reprocessing cells are essentially constituted of repetitive structures of similar pipes. In addition, the pipes in the cell are metallic. Thus, the pipe illumination by a light source brings areas of high light intensity, called highlights. Highlights often cause image processing failures, which lead to image misinterpretation. Thus, it is very difficult for the operator to steer itself. Our work aims at providing a system able to localize the robot inside the cell at any time to help the operator. A database of the cell is provided, but this database may be incomplete or unprecise. At first, we proposed a polarization based system, which exploits highlights to extract the axes of the pipes, by discriminating the scene from the background. But, when highlights are missing, the process may fail. Then, in a second part, we proposed a localization method using a correlation based assignment process. The robot localization is performed by minimizing a double criteria. The first part of this criteria translates into a good projection of the textured model in the image. The second one translates into the fact that the system composed of the scene and two successive images have to satisfy the epi-polar constraint. The minimization criteria is symmetric in relation to time in order to not perturb the localization process by previous localization errors. Indeed, the method calls into question the previous localization, in relation to the new image, to localize at best the new camera attitude. In order to validate the method, some experiments have been presented, but more general ones have to be performed. (author) [fr

Implementation of Localized Corrosion in the Performance Assessment Model for Yucca Mountain

International Nuclear Information System (INIS)

Vivek Jain, S.; David Sevougian; Patrick D. Mattie; Kevin G. Mon; Robert J. Mackinnon

2006-01-01

A total system performance assessment (TSPA) model has been developed to analyze the ability of the natural and engineered barriers of the Yucca Mountain repository to isolate nuclear waste over the 10,000-year period following repository closure. The principal features of the engineered barrier system (EBS) are emplacement tunnels (or ''drifts'') containing a two-layer waste package (WP) for waste containment and a titanium drip shield to protect the waste package from seeping water and falling rock, The 20-mm-thick outer shell of the WP is composed of Alloy 22, a highly corrosion-resistant nickel-based alloy. The barrier function of the EBS is to isolate the waste from migrating water. The water and its associated chemical conditions eventually lead to degradation of the waste packages and mobilization of the radionuclides within the packages. There are five possible waste package degradation modes of the Alloy 22: general corrosion, microbially influenced corrosion, stress corrosion cracking, early failure due to manufacturing defects, and localized corrosion. This paper specifically examines the incorporation of the Alloy-22 localized corrosion model into the Yucca Mountain TSPA model, particularly the abstraction and modeling methodology, as well as issues dealing with scaling, spatial variability, uncertainty, and coupling to other sub-models that are part of the total system model

Local Stability of AIDS Epidemic Model Through Treatment and Vertical Transmission with Time Delay

Science.gov (United States)

Novi W, Cascarilla; Lestari, Dwi

2016-02-01

This study aims to explain stability of the spread of AIDS through treatment and vertical transmission model. Human with HIV need a time to positively suffer AIDS. The existence of a time, human with HIV until positively suffer AIDS can be delayed for a time so that the model acquired is the model with time delay. The model form is a nonlinear differential equation with time delay, SIPTA (susceptible-infected-pre AIDS-treatment-AIDS). Based on SIPTA model analysis results the disease free equilibrium point and the endemic equilibrium point. The disease free equilibrium point with and without time delay are local asymptotically stable if the basic reproduction number is less than one. The endemic equilibrium point will be local asymptotically stable if the time delay is less than the critical value of delay, unstable if the time delay is more than the critical value of delay, and bifurcation occurs if the time delay is equal to the critical value of delay.

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

Science.gov (United States)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

Science.gov (United States)

Saini, Harsh; Raicar, Gaurav; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

2015-12-07

Protein subcellular localization is an important topic in proteomics since it is related to a protein׳s overall function, helps in the understanding of metabolic pathways, and in drug design and discovery. In this paper, a basic approximation technique from natural language processing called the linear interpolation smoothing model is applied for predicting protein subcellular localizations. The proposed approach extracts features from syntactical information in protein sequences to build probabilistic profiles using dependency models, which are used in linear interpolation to determine how likely is a sequence to belong to a particular subcellular location. This technique builds a statistical model based on maximum likelihood. It is able to deal effectively with high dimensionality that hinders other traditional classifiers such as Support Vector Machines or k-Nearest Neighbours without sacrificing performance. This approach has been evaluated by predicting subcellular localizations of Gram positive and Gram negative bacterial proteins. Copyright © 2015 Elsevier Ltd. All rights reserved.

Coherent density fluctuation model as a local-scale limit to ATDHF

International Nuclear Information System (INIS)

Antonov, A.N.; Petkov, I.Zh.; Stoitsov, M.V.

1985-04-01

The local scale transformation method is used for the construction of an Adiabatic Time-Dependent Hartree-Fock approach in terms of the local density distribution. The coherent density fluctuation relations of the model result in a particular case when the ''flucton'' local density is connected with the plane wave determinant model function be means of the local-scale coordinate transformation. The collective potential energy expression is obtained and its relation to the nuclear matter energy saturation curve is revealed. (author)

Single event upset threshold estimation based on local laser irradiation

International Nuclear Information System (INIS)

Chumakov, A.I.; Egorov, A.N.; Mavritsky, O.B.; Yanenko, A.V.

1999-01-01

An approach for estimation of ion-induced SEU threshold based on local laser irradiation is presented. Comparative experiment and software simulation research were performed at various pulse duration and spot size. Correlation of single event threshold LET to upset threshold laser energy under local irradiation was found. The computer analysis of local laser irradiation of IC structures was developed for SEU threshold LET estimation. The correlation of local laser threshold energy with SEU threshold LET was shown. Two estimation techniques were suggested. The first one is based on the determination of local laser threshold dose taking into account the relation of sensitive area to local irradiated area. The second technique uses the photocurrent peak value instead of this relation. The agreement between the predicted and experimental results demonstrates the applicability of this approach. (authors)

Measuring and Modeling the Earth's Gravity - Introduction to Ground-Based Gravity Surveys and Analysis of Local Gravity Data

Energy Technology Data Exchange (ETDEWEB)

Rowe, Charlotte Anne [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-21

We can measure changes in gravity from place to place on the earth. These measurements require careful recording of location, elevation and time for each reading. These readings must be adjusted for known effects (such as elevation, latitude, tides) that can bias our data and mask the signal of interest. After making corrections to our data, we can remove regional trends to obtain local Bouguer anomalies. The Bouguer anomalies arise from variations in the subsurface density structure. We can build models to explain our observations, but these models must be consistent with what is known about the local geology. Combining gravity models with other information – geologic, seismic, electromagnetic, will improve confidence in the results.

Fault feature extraction method based on local mean decomposition Shannon entropy and improved kernel principal component analysis model

Directory of Open Access Journals (Sweden)

Jinlu Sheng

2016-07-01

Full Text Available To effectively extract the typical features of the bearing, a new method that related the local mean decomposition Shannon entropy and improved kernel principal component analysis model was proposed. First, the features are extracted by time–frequency domain method, local mean decomposition, and using the Shannon entropy to process the original separated product functions, so as to get the original features. However, the features been extracted still contain superfluous information; the nonlinear multi-features process technique, kernel principal component analysis, is introduced to fuse the characters. The kernel principal component analysis is improved by the weight factor. The extracted characteristic features were inputted in the Morlet wavelet kernel support vector machine to get the bearing running state classification model, bearing running state was thereby identified. Cases of test and actual were analyzed.

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

Science.gov (United States)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

A General Polygon-based Deformable Model for Object Recognition

DEFF Research Database (Denmark)

Jensen, Rune Fisker; Carstensen, Jens Michael

1999-01-01

We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distr...

EVALUATION OF SIFT AND SURF FOR VISION BASED LOCALIZATION

Directory of Open Access Journals (Sweden)

X. Qu

2016-06-01

Full Text Available Vision based localization is widely investigated for the autonomous navigation and robotics. One of the basic steps of vision based localization is the extraction of interest points in images that are captured by the embedded camera. In this paper, SIFT and SURF extractors were chosen to evaluate their performance in localization. Four street view image sequences captured by a mobile mapping system, were used for the evaluation and both SIFT and SURF were tested on different image scales. Besides, the impact of the interest point distribution was also studied. We evaluated the performances from for aspects: repeatability, precision, accuracy and runtime. The local bundle adjustment method was applied to refine the pose parameters and the 3D coordinates of tie points. According to the results of our experiments, SIFT was more reliable than SURF. Apart from this, both the accuracy and the efficiency of localization can be improved if the distribution of feature points are well constrained for SIFT.

Active Neural Localization

OpenAIRE

Chaplot, Devendra Singh; Parisotto, Emilio; Salakhutdinov, Ruslan

2018-01-01

Localization is the problem of estimating the location of an autonomous agent from an observation and a map of the environment. Traditional methods of localization, which filter the belief based on the observations, are sub-optimal in the number of steps required, as they do not decide the actions taken by the agent. We propose "Active Neural Localizer", a fully differentiable neural network that learns to localize accurately and efficiently. The proposed model incorporates ideas of tradition...

Comparison of subset-based local and FE-based global digital image correlation: Theoretical error analysis and validation

KAUST Repository

Pan, B.

2016-03-22

Subset-based local and finite-element-based (FE-based) global digital image correlation (DIC) approaches are the two primary image matching algorithms widely used for full-field displacement mapping. Very recently, the performances of these different DIC approaches have been experimentally investigated using numerical and real-world experimental tests. The results have shown that in typical cases, where the subset (element) size is no less than a few pixels and the local deformation within a subset (element) can be well approximated by the adopted shape functions, the subset-based local DIC outperforms FE-based global DIC approaches because the former provides slightly smaller root-mean-square errors and offers much higher computation efficiency. Here we investigate the theoretical origin and lay a solid theoretical basis for the previous comparison. We assume that systematic errors due to imperfect intensity interpolation and undermatched shape functions are negligibly small, and perform a theoretical analysis of the random errors or standard deviation (SD) errors in the displacements measured by two local DIC approaches (i.e., a subset-based local DIC and an element-based local DIC) and two FE-based global DIC approaches (i.e., Q4-DIC and Q8-DIC). The equations that govern the random errors in the displacements measured by these local and global DIC approaches are theoretically derived. The correctness of the theoretically predicted SD errors is validated through numerical translation tests under various noise levels. We demonstrate that the SD errors induced by the Q4-element-based local DIC, the global Q4-DIC and the global Q8-DIC are 4, 1.8-2.2 and 1.2-1.6 times greater, respectively, than that associated with the subset-based local DIC, which is consistent with our conclusions from previous work. © 2016 Elsevier Ltd. All rights reserved.

A local leaky-box model for the local stellar surface density-gas surface density-gas phase metallicity relation

Science.gov (United States)

Zhu, Guangtun Ben; Barrera-Ballesteros, Jorge K.; Heckman, Timothy M.; Zakamska, Nadia L.; Sánchez, Sebastian F.; Yan, Renbin; Brinkmann, Jonathan

2017-07-01

We revisit the relation between the stellar surface density, the gas surface density and the gas-phase metallicity of typical disc galaxies in the local Universe with the SDSS-IV/MaNGA survey, using the star formation rate surface density as an indicator for the gas surface density. We show that these three local parameters form a tight relationship, confirming previous works (e.g. by the PINGS and CALIFA surveys), but with a larger sample. We present a new local leaky-box model, assuming star-formation history and chemical evolution is localized except for outflowing materials. We derive closed-form solutions for the evolution of stellar surface density, gas surface density and gas-phase metallicity, and show that these parameters form a tight relation independent of initial gas density and time. We show that, with canonical values of model parameters, this predicted relation match the observed one well. In addition, we briefly describe a pathway to improving the current semi-analytic models of galaxy formation by incorporating the local leaky-box model in the cosmological context, which can potentially explain simultaneously multiple properties of Milky Way-type disc galaxies, such as the size growth and the global stellar mass-gas metallicity relation.

Dissipative Continuous Spontaneous Localization (CSL) model.

Science.gov (United States)

Smirne, Andrea; Bassi, Angelo

2015-08-05

Collapse models explain the absence of quantum superpositions at the macroscopic scale, while giving practically the same predictions as quantum mechanics for microscopic systems. The Continuous Spontaneous Localization (CSL) model is the most refined and studied among collapse models. A well-known problem of this model, and of similar ones, is the steady and unlimited increase of the energy induced by the collapse noise. Here we present the dissipative version of the CSL model, which guarantees a finite energy during the entire system's evolution, thus making a crucial step toward a realistic energy-conserving collapse model. This is achieved by introducing a non-linear stochastic modification of the Schrödinger equation, which represents the action of a dissipative finite-temperature collapse noise. The possibility to introduce dissipation within collapse models in a consistent way will have relevant impact on the experimental investigations of the CSL model, and therefore also on the testability of the quantum superposition principle.

A probabilistic model for robust acoustic localization based on an auditory front-end

NARCIS (Netherlands)

May, T.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.; Boone, M.

2009-01-01

Although extensive research has been done in the field of localization, the degrading effect of reverberation and the presence of multiple sources on localization performance has remained a major issue. The classical approach to localize an acoustic source in the horizontal space is to search for

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Impact of MAC Delay on AUV Localization: Underwater Localization Based on Hyperbolic Frequency Modulation Signal.

Science.gov (United States)

Kim, Sungryul; Yoo, Younghwan

2018-01-26

Medium Access Control (MAC) delay which occurs between the anchor node's transmissions is one of the error sources in underwater localization. In particular, in AUV localization, the MAC delay significantly degrades the ranging accuracy. The Cramer-Rao Low Bound (CRLB) definition theoretically proves that the MAC delay significantly degrades the localization performance. This paper proposes underwater localization combined with multiple access technology to decouple the localization performance from the MAC delay. Towards this goal, we adopt hyperbolic frequency modulation (HFM) signal that provides multiplexing based on its good property, high-temporal correlation. Owing to the multiplexing ability of the HFM signal, the anchor nodes can transmit packets without MAC delay, i.e., simultaneous transmission is possible. In addition, the simulation results show that the simultaneous transmission is not an optional communication scheme, but essential for the localization of mobile object in underwater.

Trust Index Based Fault Tolerant Multiple Event Localization Algorithm for WSNs

Science.gov (United States)

Xu, Xianghua; Gao, Xueyong; Wan, Jian; Xiong, Naixue

2011-01-01

This paper investigates the use of wireless sensor networks for multiple event source localization using binary information from the sensor nodes. The events could continually emit signals whose strength is attenuated inversely proportional to the distance from the source. In this context, faults occur due to various reasons and are manifested when a node reports a wrong decision. In order to reduce the impact of node faults on the accuracy of multiple event localization, we introduce a trust index model to evaluate the fidelity of information which the nodes report and use in the event detection process, and propose the Trust Index based Subtract on Negative Add on Positive (TISNAP) localization algorithm, which reduces the impact of faulty nodes on the event localization by decreasing their trust index, to improve the accuracy of event localization and performance of fault tolerance for multiple event source localization. The algorithm includes three phases: first, the sink identifies the cluster nodes to determine the number of events occurred in the entire region by analyzing the binary data reported by all nodes; then, it constructs the likelihood matrix related to the cluster nodes and estimates the location of all events according to the alarmed status and trust index of the nodes around the cluster nodes. Finally, the sink updates the trust index of all nodes according to the fidelity of their information in the previous reporting cycle. The algorithm improves the accuracy of localization and performance of fault tolerance in multiple event source localization. The experiment results show that when the probability of node fault is close to 50%, the algorithm can still accurately determine the number of the events and have better accuracy of localization compared with other algorithms. PMID:22163972

Trust Index Based Fault Tolerant Multiple Event Localization Algorithm for WSNs

Directory of Open Access Journals (Sweden)

Jian Wan

2011-06-01

Full Text Available This paper investigates the use of wireless sensor networks for multiple event source localization using binary information from the sensor nodes. The events could continually emit signals whose strength is attenuated inversely proportional to the distance from the source. In this context, faults occur due to various reasons and are manifested when a node reports a wrong decision. In order to reduce the impact of node faults on the accuracy of multiple event localization, we introduce a trust index model to evaluate the fidelity of information which the nodes report and use in the event detection process, and propose the Trust Index based Subtract on Negative Add on Positive (TISNAP localization algorithm, which reduces the impact of faulty nodes on the event localization by decreasing their trust index, to improve the accuracy of event localization and performance of fault tolerance for multiple event source localization. The algorithm includes three phases: first, the sink identifies the cluster nodes to determine the number of events occurred in the entire region by analyzing the binary data reported by all nodes; then, it constructs the likelihood matrix related to the cluster nodes and estimates the location of all events according to the alarmed status and trust index of the nodes around the cluster nodes. Finally, the sink updates the trust index of all nodes according to the fidelity of their information in the previous reporting cycle. The algorithm improves the accuracy of localization and performance of fault tolerance in multiple event source localization. The experiment results show that when the probability of node fault is close to 50%, the algorithm can still accurately determine the number of the events and have better accuracy of localization compared with other algorithms.

Local-scale high-resolution atmospheric dispersion model using large-eddy simulation. LOHDIM-LES

International Nuclear Information System (INIS)

Nakayama, Hiromasa; Nagai, Haruyasu

2016-03-01

We developed LOcal-scale High-resolution atmospheric DIspersion Model using Large-Eddy Simulation (LOHDIM-LES). This dispersion model is designed based on LES which is effective to reproduce unsteady behaviors of turbulent flows and plume dispersion. The basic equations are the continuity equation, the Navier-Stokes equation, and the scalar conservation equation. Buildings and local terrain variability are resolved by high-resolution grids with a few meters and these turbulent effects are represented by immersed boundary method. In simulating atmospheric turbulence, boundary layer flows are generated by a recycling turbulent inflow technique in a driver region set up at the upstream of the main analysis region. This turbulent inflow data are imposed at the inlet of the main analysis region. By this approach, the LOHDIM-LES can provide detailed information on wind velocities and plume concentration in the investigated area. (author)

Autonomous tracked robots in planar off-road conditions modelling, localization, and motion control

CERN Document Server

González, Ramón; Guzmán, José Luis

2014-01-01

This monograph is framed within the context of off-road mobile robotics. In particular, it discusses issues related to modelling, localization, and motion control of tracked mobile robots working in planar slippery conditions. Tracked locomotion constitutes a well-known solution for mobile platforms operating over diverse challenging terrains, for that reason, tracked robotics constitutes an important research field with many applications (e.g. agriculture, mining, search and rescue operations, military activities). The specific topics of this monograph are: historical perspective of tracked vehicles and tracked robots; trajectory-tracking model taking into account slip effect; visual-odometry-based localization strategies; and advanced slip-compensation motion controllers ensuring efficient real-time execution. Physical experiments with a real tracked robot are presented showing the better performance of the suggested novel approaches to known techniques.   Keywords: longitudinal slip, visual odometry, slip...

Integrated Modeling of the Human-Natural System to Improve Local Water Management and Planning

Science.gov (United States)

Gutowski, W. J., Jr.; Dziubanski, D.; Franz, K.; Goodwin, J.; Rehmann, C. R.; Simpkins, W. W.; Tesfastion, L.; Wanamaker, A. D.; Jie, Y.

2015-12-01

Communities across the world are experiencing the effects of unsustainable water management practices. Whether the problem is a lack of water, too much water, or water of degraded quality, finding acceptable solutions requires community-level efforts that integrate sound science with local needs and values. Our project develops both a software technology (agent-based hydrological modeling) and a social technology (a participatory approach to model development) that will allow communities to comprehensively address local water challenges. Using agent-based modeling (ABM), we are building a modeling system that includes a semi-distributed hydrologic process model coupled with agent (stakeholder) models. Information from the hydrologic model is conveyed to the agent models, which, along with economic information, determine appropriate agent actions that subsequently affect hydrology within the model. The iterative participatory modeling (IPM) process will assist with the continual development of the agent models. Further, IPM creates a learning environment in which all participants, including researchers, are co-exploring relevant data, possible scenarios and solutions, and viewpoints through continuous interactions. Our initial work focuses on the impact of flood mitigation and conservation efforts on reducing flooding in an urban area. We are applying all research elements above to the Squaw Creek watershed that flows through parts of four counties in central Iowa. The watershed offers many of the typical tensions encountered in Iowa, such as different perspectives on water management between upstream farmers and downstream urban areas, competition for various types of recreational services, and increasing absentee land ownership that may conflict with community values. Ultimately, climate change scenarios will be incorporated into the model to determine long term patterns that may develop within the social or natural system.

A model for particle and heat losses by type I edge localized modes

International Nuclear Information System (INIS)

Tokar, M Z; Gupta, A; Kalupin, D; Singh, R

2007-01-01

A model to estimate the particle and energy losses caused in tokamaks by type I edge localized modes (ELMs) is proposed. This model is based on the assumption that the increase in transport by ELM is due to flows along magnetic field lines perturbed by ballooning-peeling MHD modes. The model reproduces well the experimentally found variation of losses with the plasma collisionality ν*, namely, the weak dependence of the particle loss and significant reduction of the energy loss with increasing ν*. It is argued that the electron parallel heat conductivity is dominating in the energy loss at not very large ν*

Synthesis of industrial applications of local approach to fracture models

International Nuclear Information System (INIS)

Eripret, C.

1993-03-01

This report gathers different applications of local approach to fracture models to various industrial configurations, such as nuclear pressure vessel steel, cast duplex stainless steels, or primary circuit welds such as bimetallic welds. As soon as models are developed on the basis of microstructural observations, damage mechanisms analyses, and fracture process, the local approach to fracture proves to solve problems where classical fracture mechanics concepts fail. Therefore, local approach appears to be a powerful tool, which completes the standard fracture criteria used in nuclear industry by exhibiting where and why those classical concepts become unvalid. (author). 1 tab., 18 figs., 25 refs

Four-parameter analytical local model potential for atoms

International Nuclear Information System (INIS)

Fei, Yu; Jiu-Xun, Sun; Rong-Gang, Tian; Wei, Yang

2009-01-01

Analytical local model potential for modeling the interaction in an atom reduces the computational effort in electronic structure calculations significantly. A new four-parameter analytical local model potential is proposed for atoms Li through Lr, and the values of four parameters are shell-independent and obtained by fitting the results of X a method. At the same time, the energy eigenvalues, the radial wave functions and the total energies of electrons are obtained by solving the radial Schrödinger equation with a new form of potential function by Numerov's numerical method. The results show that our new form of potential function is suitable for high, medium and low Z atoms. A comparison among the new potential function and other analytical potential functions shows the greater flexibility and greater accuracy of the present new potential function. (atomic and molecular physics)

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

Science.gov (United States)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

Directory of Open Access Journals (Sweden)

Mauro Castelli

2015-01-01

Full Text Available Energy consumption forecasting (ECF is an important policy issue in today’s economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

A multi-tiered time-series modelling approach to forecasting respiratory syncytial virus incidence at the local level.

Science.gov (United States)

Spaeder, M C; Fackler, J C

2012-04-01

Respiratory syncytial virus (RSV) is the most common cause of documented viral respiratory infections, and the leading cause of hospitalization, in young children. We performed a retrospective time-series analysis of all patients aged Forecasting models of weekly RSV incidence for the local community, inpatient paediatric hospital and paediatric intensive-care unit (PICU) were created. Ninety-five percent confidence intervals calculated around our models' 2-week forecasts were accurate to ±9·3, ±7·5 and ±1·5 cases/week for the local community, inpatient hospital and PICU, respectively. Our results suggest that time-series models may be useful tools in forecasting the burden of RSV infection at the local and institutional levels, helping communities and institutions to optimize distribution of resources based on the changing burden and severity of illness in their respective communities.

Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Chunhui Zhao

2015-09-01

Full Text Available Node localization is the core in wireless sensor network. It can be solved by powerful beacons, which are equipped with global positioning system devices to know their location information. In this article, we present a novel sparse localization approach with a mobile beacon based on LU decomposition. Our scheme firstly translates node localization problem into a 1-sparse vector recovery problem by establishing sparse localization model. Then, LU decomposition pre-processing is adopted to solve the problem that measurement matrix does not meet the re¬stricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted Cen¬troid scheme is introduced to accurately locate the node. Simulation and analysis show that our scheme has better localization performance and lower requirement for the mobile beacon than MAP+GC, MAP-M, and MAP-MN schemes. In addition, the obstacles and DOI have little effect on the novel scheme, and it has great localization performance under low SNR, thus, the scheme proposed is robust.

Integration of anatomical and external response mappings explains crossing effects in tactile localization: A probabilistic modeling approach.

Science.gov (United States)

Badde, Stephanie; Heed, Tobias; Röder, Brigitte

2016-04-01

To act upon a tactile stimulus its original skin-based, anatomical spatial code has to be transformed into an external, posture-dependent reference frame, a process known as tactile remapping. When the limbs are crossed, anatomical and external location codes are in conflict, leading to a decline in tactile localization accuracy. It is unknown whether this impairment originates from the integration of the resulting external localization response with the original, anatomical one or from a failure of tactile remapping in crossed postures. We fitted probabilistic models based on these diverging accounts to the data from three tactile localization experiments. Hand crossing disturbed tactile left-right location choices in all experiments. Furthermore, the size of these crossing effects was modulated by stimulus configuration and task instructions. The best model accounted for these results by integration of the external response mapping with the original, anatomical one, while applying identical integration weights for uncrossed and crossed postures. Thus, the model explained the data without assuming failures of remapping. Moreover, performance differences across tasks were accounted for by non-individual parameter adjustments, indicating that individual participants' task adaptation results from one common functional mechanism. These results suggest that remapping is an automatic and accurate process, and that the observed localization impairments in touch result from a cognitively controlled integration process that combines anatomically and externally coded responses.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

Science.gov (United States)

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

Sharp Contradiction for Local-Hidden-State Model in Quantum Steering

Science.gov (United States)

Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

2016-08-01

In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox.

A Variational Level Set Approach Based on Local Entropy for Image Segmentation and Bias Field Correction.

Science.gov (United States)

Tang, Jian; Jiang, Xiaoliang

2017-01-01

Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.

Population genetics models of local ancestry.

Science.gov (United States)

Gravel, Simon

2012-06-01

Migrations have played an important role in shaping the genetic diversity of human populations. Understanding genomic data thus requires careful modeling of historical gene flow. Here we consider the effect of relatively recent population structure and gene flow and interpret genomes of individuals that have ancestry from multiple source populations as mosaics of segments originating from each population. This article describes general and tractable models for local ancestry patterns with a focus on the length distribution of continuous ancestry tracts and the variance in total ancestry proportions among individuals. The models offer improved agreement with Wright-Fisher simulation data when compared to the state-of-the art and can be used to infer time-dependent migration rates from multiple populations. Considering HapMap African-American (ASW) data, we find that a model with two distinct phases of "European" gene flow significantly improves the modeling of both tract lengths and ancestry variances.

Genuine tripartite entangled states with a local hidden-variable model

International Nuclear Information System (INIS)

Toth, Geza; Acin, Antonio

2006-01-01

We present a family of three-qubit quantum states with a basic local hidden-variable model. Any von Neumann measurement can be described by a local model for these states. We show that some of these states are genuine three-partite entangled and also distillable. The generalization for larger dimensions or higher number of parties is also discussed. As a by-product, we present symmetric extensions of two-qubit Werner states

Localization and traces in open-closed topological Landau-Ginzburg models

International Nuclear Information System (INIS)

Herbst, Manfred; Lazaroiu, Calin-Iuliu

2005-01-01

We reconsider the issue of localization in open-closed B-twisted Landau-Ginzburg models with arbitrary Calabi-Yau target. Through careful analysis of zero-mode reduction, we show that the closed model allows for a one-parameter family of localization pictures, which generalize the standard residue representation. The parameter λ which indexes these pictures measures the area of worldsheets with S 2 topology, with the residue representation obtained in the limit of small area. In the boundary sector, we find a double family of such pictures, depending on parameters λ and μ which measure the area and boundary length of worldsheets with disk topology. We show that setting μ = 0 and varying λ interpolates between the localization picture of the B-model with a noncompact target space and a certain residue representation proposed recently. This gives a complete derivation of the boundary residue formula, starting from the explicit construction of the boundary coupling. We also show that the various localization pictures are related by a semigroup of homotopy equivalences

Derivative pricing based on local utility maximization

OpenAIRE

Jan Kallsen

2002-01-01

This paper discusses a new approach to contingent claim valuation in general incomplete market models. We determine the neutral derivative price which occurs if investors maximize their local utility and if derivative demand and supply are balanced. We also introduce the sensitivity process of a contingent claim. This process quantifies the reliability of the neutral derivative price and it can be used to construct price bounds. Moreover, it allows to calibrate market models in order to be co...

Localized endomorphisms of the chiral Ising model

International Nuclear Information System (INIS)

Boeckenhauer, J.

1994-07-01

In the frame of the treatment of the chiral Ising model by Mack and Schomerus, examples of localized endomorphisms ρ 1 loc and ρ 1/2 loc are presented. It is shown that they lead to the same superselection sectors as the global ones in the sense that π 0 oρ 1 log ≅π 1 and π 0 pρ 1/2 loc ≅π 1/2 holds. For proving the latter unitary equivalence, Arakis formalism of the selfdual CAR algebra is used. Further it is shown that the localized endomorphisms obey the Ising fusion rules. (orig.)

Non-local charges in local quantum field theory

International Nuclear Information System (INIS)

Buchholz, D.; Lopuszanski, J.T.; Rabsztyn, S.

1985-05-01

Non-local charges are studied in the general setting of local quantum field theory. It is shown, that these charges can be represented as polynomials in the incoming respectively outgoing fields with coefficients (kernels) which are subject to specific constraints. For the restricted class of models of a scalar, massive, self interacting particle in four dimensions, a more detailed analysis shows that all non-local charges of the generic type (genus 2) are products of generators of the Poincare group. This analysis, which is based on the macroscopic causality properties of the S-matrix, seems to indicate that less trivial examples of non-local charges can only exist in two dimensions. (orig.)

Application of the predicted heat strain model in development of localized, threshold-based heat stress management guidelines for the construction industry.

Science.gov (United States)

Rowlinson, Steve; Jia, Yunyan Andrea

2014-04-01

Existing heat stress risk management guidelines recommended by international standards are not practical for the construction industry which needs site supervision staff to make instant managerial decisions to mitigate heat risks. The ability of the predicted heat strain (PHS) model [ISO 7933 (2004). Ergonomics of the thermal environment analytical determination and interpretation of heat stress using calculation of the predicted heat strain. Geneva: International Standard Organisation] to predict maximum allowable exposure time (D lim) has now enabled development of localized, action-triggering and threshold-based guidelines for implementation by lay frontline staff on construction sites. This article presents a protocol for development of two heat stress management tools by applying the PHS model to its full potential. One of the tools is developed to facilitate managerial decisions on an optimized work-rest regimen for paced work. The other tool is developed to enable workers' self-regulation during self-paced work.

Finite Element Analysis of the Amontons-Coulomb's Model using Local and Global Friction Tests

International Nuclear Information System (INIS)

Oliveira, M. C.; Menezes, L. F.; Ramalho, A.; Alves, J. L.

2011-01-01

In spite of the abundant number of experimental friction tests that have been reported, the contact with friction modeling persists to be one of the factors that determine the effectiveness of sheet metal forming simulation. This difficulty can be understood due to the nature of the friction phenomena, which comprises the interaction of different factors connected to both sheet and tools' surfaces. Although in finite element numerical simulations friction models are commonly applied at the local level, they normally rely on parameters identified based on global experimental tests results. The aim of this study is to analyze the applicability of the Amontons-Coulomb's friction coefficient identified using complementary tests: (i) load-scanning, at the local level and (ii) draw-bead, at the global level; to the numerical simulation of sheet metal forming processes.

Local Community Detection Algorithm Based on Minimal Cluster

Directory of Open Access Journals (Sweden)

Yong Zhou

2016-01-01

Full Text Available In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. Most of the local community detection algorithms begin from one node. The agglomeration ability of a single node must be less than multiple nodes, so the beginning of the community extension of the algorithm in this paper is no longer from the initial node only but from a node cluster containing this initial node and nodes in the cluster are relatively densely connected with each other. The algorithm mainly includes two phases. First it detects the minimal cluster and then finds the local community extended from the minimal cluster. Experimental results show that the quality of the local community detected by our algorithm is much better than other algorithms no matter in real networks or in simulated networks.

Exploring the effect of diffuse reflection on indoor localization systems based on RSSI-VLC.

Science.gov (United States)

Mohammed, Nazmi A; Elkarim, Mohammed Abd

2015-08-10

This work explores and evaluates the effect of diffuse light reflection on the accuracy of indoor localization systems based on visible light communication (VLC) in a high reflectivity environment using a received signal strength indication (RSSI) technique. The effect of the essential receiver (Rx) and transmitter (Tx) parameters on the localization error with different transmitted LED power and wall reflectivity factors is investigated at the worst Rx coordinates for a directed/overall link. Since this work assumes harsh operating conditions (i.e., a multipath model, high reflectivity surfaces, worst Rx position), an error of ≥ 1.46 m is found. To achieve a localization error in the range of 30 cm under these conditions with moderate LED power (i.e., P = 0.45 W), low reflectivity walls (i.e., ρ = 0.1) should be used, which would enable a localization error of approximately 7 mm at the room's center.

Quantifying regional changes in terrestrial carbon storage by extrapolation from local ecosystem models

Energy Technology Data Exchange (ETDEWEB)

King, A W

1991-12-31

A general procedure for quantifying regional carbon dynamics by spatial extrapolation of local ecosystem models is presented Monte Carlo simulation to calculate the expected value of one or more local models, explicitly integrating the spatial heterogeneity of variables that influence ecosystem carbon flux and storage. These variables are described by empirically derived probability distributions that are input to the Monte Carlo process. The procedure provides large-scale regional estimates based explicitly on information and understanding acquired at smaller and more accessible scales.Results are presented from an earlier application to seasonal atmosphere-biosphere CO{sub 2} exchange for circumpolar ``subarctic`` latitudes (64{degree}N-90{degree}N). Results suggest that, under certain climatic conditions, these high northern ecosystems could collectively release 0.2 Gt of carbon per year to the atmosphere. I interpret these results with respect to questions about global biospheric sinks for atmospheric CO{sub 2} .

Nonlinear aeroacoustic characterization of Helmholtz resonators with a local-linear neuro-fuzzy network model

Science.gov (United States)

Förner, K.; Polifke, W.

2017-10-01

The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.

Modelling and inversion of local magnetic anomalies

International Nuclear Information System (INIS)

Quesnel, Y; Langlais, B; Sotin, C; Galdéano, A

2008-01-01

We present a method—named as MILMA for modelling and inversion of local magnetic anomalies—that combines forward and inverse modelling of aeromagnetic data to characterize both magnetization properties and location of unconstrained local sources. Parameters of simple-shape magnetized bodies (cylinder, prism or sphere) are first adjusted by trial and error to predict the signal. Their parameters provide a priori information for inversion of the measurements. Here, a generalized nonlinear approach with a least-squares criterion is adopted to seek the best parameters of the sphere (dipole). This inversion step allows the model to be more objectively adjusted to fit the magnetic signal. The validity of the MILMA method is demonstrated through synthetic and real cases using aeromagnetic measurements. Tests with synthetic data reveal accurate results in terms of depth source, whatever be the number of sources. The MILMA method is then used with real measurements to constrain the properties of the magnetized units of the Champtoceaux complex (France). The resulting parameters correlate with the crustal structure and properties revealed by other geological and geophysical surveys in the same area. The MILMA method can therefore be used to investigate the properties of poorly constrained lithospheric magnetized sources

Color-weak compensation using local affine isometry based on discrimination threshold matching

OpenAIRE

Mochizuki, Rika; Kojima, Takanori; Lenz, Reiner; Chao, Jinhui

2015-01-01

We develop algorithms for color-weak compensation and color-weak simulation based on Riemannian geometry models of color spaces. The objective function introduced measures the match of color discrimination thresholds of average normal observers and a color-weak observer. The developed matching process makes use of local affine maps between color spaces of color-normal and color-weak observers. The method can be used to generate displays of images that provide color-normal and color-weak obser...

Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering

Directory of Open Access Journals (Sweden)

Li Guangxu

2015-01-01

Full Text Available A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot.

Analytical local electron-electron interaction model potentials for atoms

International Nuclear Information System (INIS)

Neugebauer, Johannes; Reiher, Markus; Hinze, Juergen

2002-01-01

Analytical local potentials for modeling the electron-electron interaction in an atom reduce significantly the computational effort in electronic structure calculations. The development of such potentials has a long history, but some promising ideas have not yet been taken into account for further improvements. We determine a local electron-electron interaction potential akin to those suggested by Green et al. [Phys. Rev. 184, 1 (1969)], which are widely used in atom-ion scattering calculations, electron-capture processes, and electronic structure calculations. Generalized Yukawa-type model potentials are introduced. This leads, however, to shell-dependent local potentials, because the origin behavior of such potentials is different for different shells as has been explicated analytically [J. Neugebauer, M. Reiher, and J. Hinze, Phys. Rev. A 65, 032518 (2002)]. It is found that the parameters that characterize these local potentials can be interpolated and extrapolated reliably for different nuclear charges and different numbers of electrons. The analytical behavior of the corresponding localized Hartree-Fock potentials at the origin and at long distances is utilized in order to reduce the number of fit parameters. It turns out that the shell-dependent form of Green's potential, which we also derive, yields results of comparable accuracy using only one shell-dependent parameter

Error analysis of marker-based object localization using a single-plane XRII

International Nuclear Information System (INIS)

Habets, Damiaan F.; Pollmann, Steven I.; Yuan, Xunhua; Peters, Terry M.; Holdsworth, David W.

2009-01-01

The role of imaging and image guidance is increasing in surgery and therapy, including treatment planning and follow-up. Fluoroscopy is used for two-dimensional (2D) guidance or localization; however, many procedures would benefit from three-dimensional (3D) guidance or localization. Three-dimensional computed tomography (CT) using a C-arm mounted x-ray image intensifier (XRII) can provide high-quality 3D images; however, patient dose and the required acquisition time restrict the number of 3D images that can be obtained. C-arm based 3D CT is therefore limited in applications for x-ray based image guidance or dynamic evaluations. 2D-3D model-based registration, using a single-plane 2D digital radiographic system, does allow for rapid 3D localization. It is our goal to investigate - over a clinically practical range - the impact of x-ray exposure on the resulting range of 3D localization precision. In this paper it is assumed that the tracked instrument incorporates a rigidly attached 3D object with a known configuration of markers. A 2D image is obtained by a digital fluoroscopic x-ray system and corrected for XRII distortions (±0.035 mm) and mechanical C-arm shift (±0.080 mm). A least-square projection-Procrustes analysis is then used to calculate the 3D position using the measured 2D marker locations. The effect of x-ray exposure on the precision of 2D marker localization and on 3D object localization was investigated using numerical simulations and x-ray experiments. The results show a nearly linear relationship between 2D marker localization precision and the 3D localization precision. However, a significant amplification of error, nonuniformly distributed among the three major axes, occurs, and that is demonstrated. To obtain a 3D localization error of less than ±1.0 mm for an object with 20 mm marker spacing, the 2D localization precision must be better than ±0.07 mm. This requirement was met for all investigated nominal x-ray exposures at 28 cm FOV, and

The physical and radiobiological basis of the Local Effect Model (LEM) A response to the commentary by R. Katz

CERN Document Server

Scholz, M; The Physics of Quantum Electronics

2004-01-01

The physical and biological basis of our model to calculate the biological effects of charged particles, termed local effect model (LEM), has been recently questioned in a commentary by R. Katz. Major objections were related to the definition of the target size and the use of the term cross section. Here we show that the objections raised against our approach are unjustified and largely based on serious misunderstandings of the conceptual basis of the local effect model. Furthermore, we show that the approach developed by Katz and coworkers itself suffers from exactly those deficiencies, for which Katz criticises our model. The essential conceptual differences between the two models are discussed by means of some illustrative examples, based on a comparison with experimental data. For these examples, the predictions of the LEM model are fully consistent with the experimental data. Contrarily, e.g. for very heavy ions there are significant discrepancies observed for the Katz approach. These discrepancies can b...

A large-scale RF-based Indoor Localization System Using Low-complexity Gaussian filter and improved Bayesian inference

Directory of Open Access Journals (Sweden)

L. Xiao

2013-04-01

Full Text Available The growing convergence among mobile computing device and smart sensors boosts the development of ubiquitous computing and smart spaces, where localization is an essential part to realize the big vision. The general localization methods based on GPS and cellular techniques are not suitable for tracking numerous small size and limited power objects in the indoor case. In this paper, we propose and demonstrate a new localization method, this method is an easy-setup and cost-effective indoor localization system based on off-the-shelf active RFID technology. Our system is not only compatible with the future smart spaces and ubiquitous computing systems, but also suitable for large-scale indoor localization. The use of low-complexity Gaussian Filter (GF, Wheel Graph Model (WGM and Probabilistic Localization Algorithm (PLA make the proposed algorithm robust and suitable for large-scale indoor positioning from uncertainty, self-adjective to varying indoor environment. Using MATLAB simulation, we study the system performances, especially the dependence on a number of system and environment parameters, and their statistical properties. The simulation results prove that our proposed system is an accurate and cost-effective candidate for indoor localization.

Electrophysiological Data and the Biophysical Modelling of Local Cortical Circuits

Directory of Open Access Journals (Sweden)

Dimitris Pinotsis

2014-03-01

Full Text Available This paper shows how recordings of gamma oscillations – under different experimental conditions or from different subjects – can be combined with a class of population models called neural fields and dynamic causal modeling (DCM to distinguish among alternative hypotheses regarding cortical structure and function. This approach exploits inter-subject variability and trial-specific effects associated with modulations in the peak frequency of gamma oscillations. It draws on the computational power of Bayesian model inversion, when applied to neural field models of cortical dynamics. Bayesian model comparison allows one to adjudicate among different mechanistic hypotheses about cortical excitability, synaptic kinetics and the cardinal topographic features of local cortical circuits. It also provides optimal parameter estimates that quantify neuromodulation and the spatial dispersion of axonal connections or summation of receptive fields in the visual cortex. This paper provides an overview of a family of neural field models that have been recently implemented using the DCM toolbox of the academic freeware Statistical Parametric Mapping (SPM. The SPM software is a popular platform for analyzing neuroimaging data, used by several neuroscience communities worldwide. DCM allows for a formal (Bayesian statistical analysis of cortical network connectivity, based upon realistic biophysical models of brain responses. It is this particular feature of DCM – the unique combination of generative models with optimization techniques based upon (variational Bayesian principles – that furnishes a novel way to characterize functional brain architectures. In particular, it provides answers to questions about how the brain is wired and how it responds to different experimental manipulations. For a review of the general role of neural fields in SPM the reader can consult e.g. see [1]. Neural fields have a long and illustrious history in mathematical

Mental models of women with breast implants : local complications

NARCIS (Netherlands)

Byram, S.; Fischhoff, B.; Embrey, M.; Bruine de Bruin, W.J.A.; Thorne, S.

2001-01-01

Twenty-five women with breast implants participated in semistructured interviews designed to reveal their "mental models" of the processes potentially causing local (ie, nonsystemic) problems. The authors analyzed their responses in terms of an "expert model," circumscribing scientifically relevant

Assessment of managed aquifer recharge potential using ensembles of local models.

Science.gov (United States)

Smith, Anthony J; Pollock, Daniel W

2012-01-01

A simple quantitative approach for assessing the artificial recharge potential of large regions using spatial ensembles of local models is proposed. The method extends existing qualitative approaches and enables rapid assessments within a programmable environment. Spatial discretization of a water resource region into continuous local domains allows simple local models to be applied independently in each domain using lumped parameters. The ensemble results can be analyzed directly or combined with other quantitative and thematic information and visualized as regional suitability maps. A case study considers the hydraulic potential for surface infiltration across a large water resource region using a published analytic model for basin recharge. The model solution was implemented within a geographic information system and evaluated independently in >21,000 local domains using lumped parameters derived from existing regional datasets. Computer execution times to run the whole ensemble and process the results were in the order of a few minutes. Relevant aspects of the case study results and general conclusions concerning the utility and limitations of the method are discussed. © 2011, CSIRO. Ground Water © 2011, National Ground Water Association.

Local Medicaid home- and community-based services spending and nursing home admissions of younger adults.

Science.gov (United States)

Thomas, Kali S; Keohane, Laura; Mor, Vincent

2014-11-01

We used fixed-effect models to examine the relationship between local spending on home- and community-based services (HCBSs) for cash-assisted Medicaid-only disabled (CAMOD) adults and younger adult admissions to nursing homes in the United States during 2001 through 2008, with control for facility and market characteristics and secular trends. We found that increased CAMOD Medicaid HCBS spending at the local level is associated with decreased admissions of younger adults to nursing homes. Our findings suggest that states' efforts to expand HCBS for this population should continue.

MR-based source localization for MR-guided HDR brachytherapy

Science.gov (United States)

Beld, E.; Moerland, M. A.; Zijlstra, F.; Viergever, M. A.; Lagendijk, J. J. W.; Seevinck, P. R.

2018-04-01

For the purpose of MR-guided high-dose-rate (HDR) brachytherapy, a method for real-time localization of an HDR brachytherapy source was developed, which requires high spatial and temporal resolutions. MR-based localization of an HDR source serves two main aims. First, it enables real-time treatment verification by determination of the HDR source positions during treatment. Second, when using a dummy source, MR-based source localization provides an automatic detection of the source dwell positions after catheter insertion, allowing elimination of the catheter reconstruction procedure. Localization of the HDR source was conducted by simulation of the MR artifacts, followed by a phase correlation localization algorithm applied to the MR images and the simulated images, to determine the position of the HDR source in the MR images. To increase the temporal resolution of the MR acquisition, the spatial resolution was decreased, and a subpixel localization operation was introduced. Furthermore, parallel imaging (sensitivity encoding) was applied to further decrease the MR scan time. The localization method was validated by a comparison with CT, and the accuracy and precision were investigated. The results demonstrated that the described method could be used to determine the HDR source position with a high accuracy (0.4–0.6 mm) and a high precision (⩽0.1 mm), at high temporal resolutions (0.15–1.2 s per slice). This would enable real-time treatment verification as well as an automatic detection of the source dwell positions.

Accounting for model error in Bayesian solutions to hydrogeophysical inverse problems using a local basis approach

Science.gov (United States)

Irving, J.; Koepke, C.; Elsheikh, A. H.

2017-12-01

Bayesian solutions to geophysical and hydrological inverse problems are dependent upon a forward process model linking subsurface parameters to measured data, which is typically assumed to be known perfectly in the inversion procedure. However, in order to make the stochastic solution of the inverse problem computationally tractable using, for example, Markov-chain-Monte-Carlo (MCMC) methods, fast approximations of the forward model are commonly employed. This introduces model error into the problem, which has the potential to significantly bias posterior statistics and hamper data integration efforts if not properly accounted for. Here, we present a new methodology for addressing the issue of model error in Bayesian solutions to hydrogeophysical inverse problems that is geared towards the common case where these errors cannot be effectively characterized globally through some parametric statistical distribution or locally based on interpolation between a small number of computed realizations. Rather than focusing on the construction of a global or local error model, we instead work towards identification of the model-error component of the residual through a projection-based approach. In this regard, pairs of approximate and detailed model runs are stored in a dictionary that grows at a specified rate during the MCMC inversion procedure. At each iteration, a local model-error basis is constructed for the current test set of model parameters using the K-nearest neighbour entries in the dictionary, which is then used to separate the model error from the other error sources before computing the likelihood of the proposed set of model parameters. We demonstrate the performance of our technique on the inversion of synthetic crosshole ground-penetrating radar traveltime data for three different subsurface parameterizations of varying complexity. The synthetic data are generated using the eikonal equation, whereas a straight-ray forward model is assumed in the inversion

Fatigue Life Prediction of High Modulus Asphalt Concrete Based on the Local Stress-Strain Method

Directory of Open Access Journals (Sweden)

Mulian Zheng

2017-03-01

Full Text Available Previously published studies have proposed fatigue life prediction models for dense graded asphalt pavement based on flexural fatigue test. This study focused on the fatigue life prediction of High Modulus Asphalt Concrete (HMAC pavement using the local strain-stress method and direct tension fatigue test. First, the direct tension fatigue test at various strain levels was conducted on HMAC prism samples cut from plate specimens. Afterwards, their true stress-strain loop curves were obtained and modified to develop the strain-fatigue life equation. Then the nominal strain of HMAC course determined using finite element method was converted into local strain using the Neuber method. Finally, based on the established fatigue equation and converted local strain, a method to predict the pavement fatigue crack initiation life was proposed and the fatigue life of a typical HMAC overlay pavement which runs a risk of bottom-up cracking was predicted and validated. Results show that the proposed method was able to produce satisfactory crack initiation life.

Value-based benefit-cost of local DSM

International Nuclear Information System (INIS)

Stein, V.

1995-01-01

Value-based benefits and costs of demand-side management (DSM) were discussed in the context of local electricity resource planning in downtown Toronto. The analysis considered the effects on local customer interruption as a result of DSM, and the deferment in need for local transmission and distribution upgrades. The life cycle and cash flow benefits and costs of DSM were discussed from the perspectives of the electric utility, the DSM-participating and non-participating customers, and society as a whole. Cashflow and lifecycle analyses results were reconciled. The Toronto Integrated Electrical Service (TIES) study, the basis for this paper, was described. Two main conclusions were reached, i.e. since the savings in the generationg system as a whole were far greater than the local savings,the value of a specific DSM program would be similar across a utility's service area, and (2) while cashflow analysis illustrated the short and medium term benefits and costs in a way most people intuitively understand, in effect,the lifecycle-cost estimates produce a clearer indicator of long-run economics

An efficient implementation of maximum likelihood identification of LTI state-space models by local gradient search

NARCIS (Netherlands)

Bergboer, N.H.; Verdult, V.; Verhaegen, M.H.G.

2002-01-01

We present a numerically efficient implementation of the nonlinear least squares and maximum likelihood identification of multivariable linear time-invariant (LTI) state-space models. This implementation is based on a local parameterization of the system and a gradient search in the resulting

Bonissone CIDU Presentation: Design of Local Fuzzy Models

Data.gov (United States)

National Aeronautics and Space Administration — After reviewing key background concepts in fuzzy systems and evolutionary computing, we will focus on the use of local fuzzy models, which are related to both kernel...

Limits to ductility set by plastic flow localization

International Nuclear Information System (INIS)

Needleman, A.; Rice, J.R.

1977-11-01

The theory of strain localization is reviewed with reference both to local necking in sheet metal forming processes and to more general three dimensional shear band localizations that sometimes mark the onset of ductile rupture. Both bifurcation behavior and the growth of initial imperfections are considered. In addition to analyses based on classical Mises-like constitutive laws, approaches to localization based on constitutive models that may more accurately model processes of slip and progressive rupturing on the microscale in structural alloys are discussed. Among these non-classical constitutive features are the destabilizing roles of yield surface vertices and of non-normality effects, arising, for example, from slight pressure sensitivity of yield. Analyses based on a constitutive model of a progressively cavitating dilational plastic material which is intended to model the process of ductile void growth in metals are also discussed. A variety of numerical results are presented. In the context of the three dimensional theory of localization, it is shown that a simple vertex model predicts ratios of ductility in plane strain tension to ductility in axisymmetric tension qualitatively consistent with experiment, and the destabilizing influence of a hydrostatic stress dependent void nucleation criterion is illustrated. In the sheet necking context, and focussing on positive biaxial stretching, it is shown that forming limit curves based on a simple vertex model and those based on a simple void growth model are qualitatively in accord, although attributing instability to very different physical mechanisms. These forming limit curves are compared with those obtained from the Mises material model and employing various material and geometric imperfections

Tracer disposition kinetics in the determination of local cerebral blood flow by a venous equilibrium model, tube model, and distributed model

International Nuclear Information System (INIS)

Sawada, Y.; Sugiyama, Y.; Iga, T.; Hanano, M.

1987-01-01

Tracer distribution kinetics in the determination of local cerebral blood flow (LCBF) were examined by using three models, i.e., venous equilibrium, tube, and distributed models. The technique most commonly used for measuring LCBF is the tissue uptake method, which was first developed and applied by Kety. The measurement of LCBF with the 14 C-iodoantipyrine (IAP) method is calculated by using an equation derived by Kety based on the Fick's principle and a two-compartment model of blood-tissue exchange and tissue concentration at a single data point. The procedure, in which the tissue is to be in equilibrium with venous blood, will be referred to as the tissue equilibration model. In this article, effects of the concentration gradient of tracer along the length of the capillary (tube model) and the transverse heterogeneity in the capillary transit time (distributed model) on the determination of LCBF were theoretically analyzed for the tissue sampling method. Similarities and differences among these models are explored. The rank order of the LCBF calculated by using arterial blood concentration time courses and the tissue concentration of tracer based on each model were tube model (model II) less than distributed model (model III) less than venous equilibrium model (model I). Data on 14 C-IAP kinetics reported by Ohno et al. were employed. The LCBFs calculated based on model I were 45-260% larger than those in models II or III. To discriminate among three models, we propose to examine the effect of altering the venous infusion time of tracer on the apparent tissue-to-blood concentration ratio (lambda app). A range of the ratio of the predicted lambda app in models II or III to that in model I was from 0.6 to 1.3

Local Equating Using the Rasch Model, the OPLM, and the 2PL IRT Model--or--What Is It Anyway if the Model Captures Everything There Is to Know about the Test Takers?

Science.gov (United States)

von Davier, Matthias; González B., Jorge; von Davier, Alina A.

2013-01-01

Local equating (LE) is based on Lord's criterion of equity. It defines a family of true transformations that aim at the ideal of equitable equating. van der Linden (this issue) offers a detailed discussion of common issues in observed-score equating relative to this local approach. By assuming an underlying item response theory model, one of…

Local difference measures between complex networks for dynamical system model evaluation.

Science.gov (United States)

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node

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.

Modelling Local Attitudes to Protected Areas in Developing Countries

Directory of Open Access Journals (Sweden)

Chiara Bragagnolo

2016-01-01

Full Text Available During a time of intensifying competition for land, Protected Areas (PAs are coming under increasing pressure to justify their status. Positive local attitudes to a PA are a potentially important component of any such justification, especially in the developing world where human pressure on natural resources is often high. However, despite numerous studies our understanding of what drives positive attitudes to PAs is still exceedingly limited. Here, we review the literature on local attitudes towards PAs in developing countries. Our survey reveals a highly fragmented research area where studies typically lack an explicit conceptual basis, and where there is wide variation in choice of statistical approach, explanatory and response variables, and incorporation of contextual information. Nevertheless, there is a relatively high degree of concordance between studies, with certain variables showing strong associations with attitudes. We recommend that PA attitude researchers in developing countries adopt a more rigorous model building approach based on a clear conceptual framework and drawing on the extensive empirical literature. Such an approach would improve the quality of research, increase comparability, and provide a stronger basis to support conservation decision-making.

Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines

Directory of Open Access Journals (Sweden)

Boming Song

2017-01-01

Full Text Available Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non-line of sight (NLOS propagation error of the localization signal between the access point (AP and the target node (Tag. In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR method or received signal strength indication (RSSI based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.

Applying Four Different Risk Models in Local Ore Selection

International Nuclear Information System (INIS)

Richmond, Andrew

2002-01-01

Given the uncertainty in grade at a mine location, a financially risk-averse decision-maker may prefer to incorporate this uncertainty into the ore selection process. A FORTRAN program risksel is presented to calculate local risk-adjusted optimal ore selections using a negative exponential utility function and three dominance models: mean-variance, mean-downside risk, and stochastic dominance. All four methods are demonstrated in a grade control environment. In the case study, optimal selections range with the magnitude of financial risk that a decision-maker is prepared to accept. Except for the stochastic dominance method, the risk models reassign material from higher cost to lower cost processing options as the aversion to financial risk increases. The stochastic dominance model usually was unable to determine the optimal local selection

An integrated approach to model strain localization bands in magnesium alloys

Science.gov (United States)

Baxevanakis, K. P.; Mo, C.; Cabal, M.; Kontsos, A.

2018-02-01

Strain localization bands (SLBs) that appear at early stages of deformation of magnesium alloys have been recently associated with heterogeneous activation of deformation twinning. Experimental evidence has demonstrated that such "Lüders-type" band formations dominate the overall mechanical behavior of these alloys resulting in sigmoidal type stress-strain curves with a distinct plateau followed by pronounced anisotropic hardening. To evaluate the role of SLB formation on the local and global mechanical behavior of magnesium alloys, an integrated experimental/computational approach is presented. The computational part is developed based on custom subroutines implemented in a finite element method that combine a plasticity model with a stiffness degradation approach. Specific inputs from the characterization and testing measurements to the computational approach are discussed while the numerical results are validated against such available experimental information, confirming the existence of load drops and the intensification of strain accumulation at the time of SLB initiation.

FEM-based neural-network approach to nonlinear modeling with application to longitudinal vehicle dynamics control.

Science.gov (United States)

Kalkkuhl, J; Hunt, K J; Fritz, H

1999-01-01

An finite-element methods (FEM)-based neural-network approach to Nonlinear AutoRegressive with eXogenous input (NARX) modeling is presented. The method uses multilinear interpolation functions on C0 rectangular elements. The local and global structure of the resulting model is analyzed. It is shown that the model can be interpreted both as a local model network and a single layer feedforward neural network. The main aim is to use the model for nonlinear control design. The proposed FEM NARX description is easily accessible to feedback linearizing control techniques. Its use with a two-degrees of freedom nonlinear internal model controller is discussed. The approach is applied to modeling of the nonlinear longitudinal dynamics of an experimental lorry, using measured data. The modeling results are compared with local model network and multilayer perceptron approaches. A nonlinear speed controller was designed based on the identified FEM model. The controller was implemented in a test vehicle, and several experimental results are presented.

A non-local hidden-variable model that violates Leggett-type inequalities

Energy Technology Data Exchange (ETDEWEB)

Zela, F de [Departamento de Ciencias, Seccion Fisica, Pontificia Universidad Catolica del Peru, Apartado 1761, Lima (Peru)

2008-12-19

Recent experiments of Groeblacher et al proved the violation of a Leggett-type inequality that was claimed to be valid for a broad class of non-local hidden-variable theories. The impossibility of constructing a non-local and realistic theory, unless it entails highly counterintuitive features, seems thus to have been experimentally proved. This would bring us close to a definite refutation of realism. Indeed, realism was proved to be also incompatible with locality, according to a series of experiments testing Bell inequalities. The present paper addresses the said experiments of Groeblacher et al and presents an explicit, contextual and realistic, model that reproduces the predictions of quantum mechanics. It thus violates the Leggett-type inequality that was established with the aim of ruling out a supposedly broad class of non-local models. We can thus conclude that plausible contextual, realistic, models are still tenable. This restates the possibility of a future completion of quantum mechanics by a realistic and contextual theory which is not in a class containing only highly counterintuitive models. The class that was ruled out by the experiments of Groeblacher et al is thus proved to be a limited one, arbitrarily separating models that physically belong in the same class.

A non-local hidden-variable model that violates Leggett-type inequalities

International Nuclear Information System (INIS)

Zela, F de

2008-01-01

Recent experiments of Groeblacher et al proved the violation of a Leggett-type inequality that was claimed to be valid for a broad class of non-local hidden-variable theories. The impossibility of constructing a non-local and realistic theory, unless it entails highly counterintuitive features, seems thus to have been experimentally proved. This would bring us close to a definite refutation of realism. Indeed, realism was proved to be also incompatible with locality, according to a series of experiments testing Bell inequalities. The present paper addresses the said experiments of Groeblacher et al and presents an explicit, contextual and realistic, model that reproduces the predictions of quantum mechanics. It thus violates the Leggett-type inequality that was established with the aim of ruling out a supposedly broad class of non-local models. We can thus conclude that plausible contextual, realistic, models are still tenable. This restates the possibility of a future completion of quantum mechanics by a realistic and contextual theory which is not in a class containing only highly counterintuitive models. The class that was ruled out by the experiments of Groeblacher et al is thus proved to be a limited one, arbitrarily separating models that physically belong in the same class

Business Model Innovation for Local Energy Management: A Perspective from Swiss Utilities

Energy Technology Data Exchange (ETDEWEB)

Facchinetti, Emanuele, E-mail: emanuele.facchinetti@hslu.ch [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland); Eid, Cherrelle [Faculty of Technology, Policy and Management, Delft University of Technology, Delft (Netherlands); Bollinger, Andrew [Urban Energy Systems Laboratory, EMPA, Dübendorf (Switzerland); Sulzer, Sabine [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland)

2016-08-04

The successful deployment of the energy transition relies on a deep reorganization of the energy market. Business model innovation is recognized as a key driver of this process. This work contributes to this topic by providing to potential local energy management (LEM) stakeholders and policy makers a conceptual framework guiding the LEM business model innovation. The main determinants characterizing LEM concepts and impacting its business model innovation are identified through literature reviews on distributed generation typologies and customer/investor preferences related to new business opportunities emerging with the energy transition. Afterwards, the relation between the identified determinants and the LEM business model solution space is analyzed based on semi-structured interviews with managers of Swiss utilities companies. The collected managers’ preferences serve as explorative indicators supporting the business model innovation process and provide insights into policy makers on challenges and opportunities related to LEM.

Business Model Innovation for Local Energy Management: A Perspective from Swiss Utilities

International Nuclear Information System (INIS)

Facchinetti, Emanuele; Eid, Cherrelle; Bollinger, Andrew; Sulzer, Sabine

2016-01-01

The successful deployment of the energy transition relies on a deep reorganization of the energy market. Business model innovation is recognized as a key driver of this process. This work contributes to this topic by providing to potential local energy management (LEM) stakeholders and policy makers a conceptual framework guiding the LEM business model innovation. The main determinants characterizing LEM concepts and impacting its business model innovation are identified through literature reviews on distributed generation typologies and customer/investor preferences related to new business opportunities emerging with the energy transition. Afterwards, the relation between the identified determinants and the LEM business model solution space is analyzed based on semi-structured interviews with managers of Swiss utilities companies. The collected managers’ preferences serve as explorative indicators supporting the business model innovation process and provide insights into policy makers on challenges and opportunities related to LEM.

A three-dimensional model of residential energy consumer archetypes for local energy policy design in the UK

International Nuclear Information System (INIS)

Zhang Tao; Siebers, Peer-Olaf; Aickelin, Uwe

2012-01-01

This paper reviews major studies in three traditional lines of research in residential energy consumption in the UK, i.e., economic/infrastructure, behaviour, and load profiling. Based on the review the paper proposes a three-dimensional model for archetyping residential energy consumers in the UK by considering property energy efficiency levels, the greenness of household behaviour of using energy, and the duration of property daytime occupancy. With the proposed model, eight archetypes of residential energy consumers in the UK have been identified. They are: pioneer greens, follower greens, concerned greens, home stayers, unconscientious wasters, regular wasters, daytime wasters, and disengaged wasters. Using a case study, these archetypes of residential energy consumers demonstrate the robustness of the 3-D model in aiding local energy policy/intervention design in the UK. - Highlights: ► This paper reviews the three traditional lines of research in residential energy consumption in the UK. ► Based on the literature review, the paper proposes a 3-D conceptual model for archetyping UK residential energy consumers. ► The 3-D archetype model can aid local energy policy/intervention design in the UK.

A review of recent advances in numerical modelling of local scour problems

DEFF Research Database (Denmark)

Sumer, B. Mutlu

2014-01-01

A review is presented of recent advances in numerical modelling of local scour problems. The review is organized in five sections: Highlights of numerical modelling of local scour; Influence of turbulence on scour; Backfilling of scour holes; Scour around complex structures; and Scour protection ...

Environmental Communication Based on Local Wisdom In Anticipation of Citarum Flood

Directory of Open Access Journals (Sweden)

Iriana Bakti

2017-06-01

Full Text Available Management of watersheds becomes part of a government program. This was conducted to anticipate the floods that hit the settlement. But the program is hard to do without the active role of the community, therefore the communication activities were undertaken based on local wisdom. The purpose of this paper is to find out about the environmental communication based on local wisdom in the Citarum Watershed. The method used is in the form of interviews and participant observation. As for the results obtained are: local wisdom is utilized by the environment actuator in the Citarum watershed management in the form of the proverb, rituals, and the environment preservation. Local wisdom by the environment actuator is meant as a way in, and domain in conducting environmental communication. In addition, local wisdom considered by the environment actuator as the ethic to be met in interacts with the target communities. Implementation of environmental communication activities with local wisdom based on the Citarum is done through a personal approach to some of the social and religious figures by using the communication channels of the group in the forum -the farmers group, majelis ta’lim, and community empowerment, which proceeds in a dialogical way to reach mutual agreement based on mutual trust among the participants of the environmental communication

On the more accurate channel model and positioning based on time-of-arrival for visible light localization

Science.gov (United States)

Amini, Changeez; Taherpour, Abbas; Khattab, Tamer; Gazor, Saeed

2017-01-01

This paper presents an improved propagation channel model for the visible light in indoor environments. We employ this model to derive an enhanced positioning algorithm using on the relation between the time-of-arrivals (TOAs) and the distances for two cases either by assuming known or unknown transmitter and receiver vertical distances. We propose two estimators, namely the maximum likelihood estimator and an estimator by employing the method of moments. To have an evaluation basis for these methods, we calculate the Cramer-Rao lower bound (CRLB) for the performance of the estimations. We show that the proposed model and estimations result in a superior performance in positioning when the transmitter and receiver are perfectly synchronized in comparison to the existing state-of-the-art counterparts. Moreover, the corresponding CRLB of the proposed model represents almost about 20 dB reduction in the localization error bound in comparison with the previous model for some practical scenarios.

Local Refinement of the Super Element Model of Oil Reservoir

Directory of Open Access Journals (Sweden)

A.B. Mazo

2017-12-01

Full Text Available In this paper, we propose a two-stage method for petroleum reservoir simulation. The method uses two models with different degrees of detailing to describe hydrodynamic processes of different space-time scales. At the first stage, the global dynamics of the energy state of the deposit and reserves is modeled (characteristic scale of such changes is km / year. The two-phase flow equations in the model of global dynamics operate with smooth averaged pressure and saturation fields, and they are solved numerically on a large computational grid of super-elements with a characteristic cell size of 200-500 m. The tensor coefficients of the super-element model are calculated using special procedures of upscaling of absolute and relative phase permeabilities. At the second stage, a local refinement of the super-element model is constructed for calculating small-scale processes (with a scale of m / day, which take place, for example, during various geological and technical measures aimed at increasing the oil recovery of a reservoir. Then we solve the two-phase flow problem in the selected area of the measure exposure on a detailed three-dimensional grid, which resolves the geological structure of the reservoir, and with a time step sufficient for describing fast-flowing processes. The initial and boundary conditions of the local problem are formulated on the basis of the super-element solution. This approach allows us to reduce the computational costs in order to solve the problems of designing and monitoring the oil reservoir. To demonstrate the proposed approach, we give an example of the two-stage modeling of the development of a layered reservoir with a local refinement of the model during the isolation of a water-saturated high-permeability interlayer. We show a good compliance between the locally refined solution of the super-element model in the area of measure exposure and the results of numerical modeling of the whole history of reservoir

Least-squares reverse time migration with local Radon-based preconditioning

KAUST Repository

Dutta, Gaurav

2017-03-08

Least-squares migration (LSM) can produce images with better balanced amplitudes and fewer artifacts than standard migration. The conventional objective function used for LSM minimizes the L2-norm of the data residual between the predicted and the observed data. However, for field-data applications in which the recorded data are noisy and undersampled, the conventional formulation of LSM fails to provide the desired uplift in the quality of the inverted image. We have developed a leastsquares reverse time migration (LSRTM) method using local Radon-based preconditioning to overcome the low signal-tonoise ratio (S/N) problem of noisy or severely undersampled data. A high-resolution local Radon transform of the reflectivity is used, and sparseness constraints are imposed on the inverted reflectivity in the local Radon domain. The sparseness constraint is that the inverted reflectivity is sparse in the Radon domain and each location of the subsurface is represented by a limited number of geologic dips. The forward and the inverse mapping of the reflectivity to the local Radon domain and vice versa is done through 3D Fourier-based discrete Radon transform operators. The weights for the preconditioning are chosen to be varying locally based on the relative amplitudes of the local dips or assigned using quantile measures. Numerical tests on synthetic and field data validate the effectiveness of our approach in producing images with good S/N and fewer aliasing artifacts when compared with standard RTM or standard LSRTM.

Learning Global-Local Distance Metrics for Signature-Based Biometric Cryptosystems

Directory of Open Access Journals (Sweden)

George S. Eskander Ekladious

2017-11-01

Full Text Available Biometric traits, such as fingerprints, faces and signatures have been employed in bio-cryptosystems to secure cryptographic keys within digital security schemes. Reliable implementations of these systems employ error correction codes formulated as simple distance thresholds, although they may not effectively model the complex variability of behavioral biometrics like signatures. In this paper, a Global-Local Distance Metric (GLDM framework is proposed to learn cost-effective distance metrics, which reduce within-class variability and augment between-class variability, so that simple error correction thresholds of bio-cryptosystems provide high classification accuracy. First, a large number of samples from a development dataset are used to train a global distance metric that differentiates within-class from between-class samples of the population. Then, once user-specific samples are available for enrollment, the global metric is tuned to a local user-specific one. Proof-of-concept experiments on two reference offline signature databases confirm the viability of the proposed approach. Distance metrics are produced based on concise signature representations consisting of about 20 features and a single prototype. A signature-based bio-cryptosystem is designed using the produced metrics and has shown average classification error rates of about 7% and 17% for the PUCPR and the GPDS-300 databases, respectively. This level of performance is comparable to that obtained with complex state-of-the-art classifiers.

Experience of BESIII data production with local cluster and distributed computing model

International Nuclear Information System (INIS)

Deng, Z Y; Li, W D; Liu, H M; Sun, Y Z; Zhang, X M; Lin, L; Nicholson, C; Zhemchugov, A

2012-01-01

The BES III detector is a new spectrometer which works on the upgraded high-luminosity collider, BEPCII. The BES III experiment studies physics in the tau-charm energy region from 2 GeV to 4.6 GeV . From 2009 to 2011, BEPCII has produced 106M ψ(2S) events, 225M J/ψ events, 2.8 fb −1 ψ(3770) data, and 500 pb −1 data at 4.01 GeV. All the data samples were processed successfully and many important physics results have been achieved based on these samples. Doing data production correctly and efficiently with limited CPU and storage resources is a big challenge. This paper will describe the implementation of the experiment-specific data production for BESIII in detail, including data calibration with event-level parallel computing model, data reconstruction, inclusive Monte Carlo generation, random trigger background mixing and multi-stream data skimming. Now, with the data sample increasing rapidly, there is a growing demand to move from solely using a local cluster to a more distributed computing model. A distributed computing environment is being set up and expected to go into production use in 2012. The experience of BESIII data production, both with a local cluster and with a distributed computing model, is presented here.

Aerosol numerical modelling at local scale

International Nuclear Information System (INIS)

Albriet, Bastien

2007-01-01

At local scale and in urban areas, an important part of particulate pollution is due to traffic. It contributes largely to the high number concentrations observed. Two aerosol sources are mainly linked to traffic. Primary emission of soot particles and secondary nanoparticle formation by nucleation. The emissions and mechanisms leading to the formation of such bimodal distribution are still badly understood nowadays. In this thesis, we try to provide an answer to this problematic by numerical modelling. The Modal Aerosol Model MAM is used, coupled with two 3D-codes: a CFD (Mercure Saturne) and a CTM (Polair3D). A sensitivity analysis is performed, at the border of a road but also in the first meters of an exhaust plume, to identify the role of each process involved and the sensitivity of different parameters used in the modelling. (author) [fr

Mathematical Model of Synthesis Catalyst with Local Reaction Centers

Directory of Open Access Journals (Sweden)

I. V. Derevich

2017-01-01

Full Text Available The article considers a catalyst granule with a porous ceramic passive substrate and point active centers on which an exothermic synthesis reaction occurs. A rate of the chemical reaction depends on the temperature according to the Arrhenius law. Heat is removed from the pellet surface in products of synthesis due to heat transfer. In our work we first proposed a model for calculating the steady-state temperature of a catalyst pellet with local reaction centers. Calculation of active centers temperature is based on the idea of self-consistent field (mean-field theory. At first, it is considered that powers of the reaction heat release at the centers are known. On the basis of the found analytical solution, which describes temperature distribution inside the granule, the average temperature of the reaction centers is calculated, which then is inserted in the formula for heat release. The resulting system of transcendental algebraic equations is transformed into a system of ordinary differential equations of relaxation type and solved numerically to achieve a steady-state value. As a practical application, the article considers a Fischer-Tropsch synthesis catalyst granule with active cobalt metallic micro-particles. Cobalt micro-particles are the centers of the exothermic reaction of hydrocarbons macromolecular synthesis. Synthesis occurs as a result of absorption of the components of the synthesis gas on metallic cobalt. The temperature distribution inside the granule for a single local center and reaction centers located on the same granule diameter is found. It was found that there is a critical temperature of reactor exceeding of which leads to significant local overheating of the centers - thermal explosion. The temperature distribution with the local reaction centers is qualitatively different from the granule temperature, calculated in the homogeneous approximation. It is shown that, in contrast to the homogeneous approximation, the

A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space

Directory of Open Access Journals (Sweden)

Jinjun Li

2011-01-01

Full Text Available A stereo similarity function based on local multi-model monogenic image feature descriptors (LMFD is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color monogenic signal framework. The gray monogenic signal, which is the extension of analytic signal to gray level image using Dirac operator and Laplace equation, consists of local amplitude, local orientation, and instantaneous phase of 2D image signal. The color monogenic signal is the extension of monogenic signal to color image based on Clifford algebras. The local color phase can be estimated by computing geometric product between the color monogenic signal and a unit reference vector in RGB color space. Experiment results on the synthetic and natural stereo images show the performance of the proposed approach.

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

Science.gov (United States)

Case, Jonathan L.; LaFontaine, Frank J.; Molthan, Andrew L.; Carcione, Brian; Wood, Lance; Maloney, Joseph; Estupinan, Jeral; Medlin, Jeffrey M.; Blottman, Peter; Rozumalski, Robert A.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

Science.gov (United States)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.