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Sample records for local model based

  1. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

    Science.gov (United States)

    Tuta, Jure; Juric, Matjaz B

    2018-03-24

    This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  2. MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

    Directory of Open Access Journals (Sweden)

    Jure Tuta

    2018-03-01

    Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

  3. 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

  4. From Family Based to Industrial Based Production: Local Economic Development Initiatives and the HELIX Model

    Directory of Open Access Journals (Sweden)

    Bartjan W Pennink

    2013-01-01

    Full Text Available To build a strong local economy, good practice tells us that each community should undertake a collaborative, strategically planned process to understand and then act upon its own strengths, weaknesses, opportunities and threats. From this perspective we start with the local communities but how is this related to the perspective from the Helix model in which three actors are explicitly introduced: the Government, the Industry and the Universities? The purpose of local economic development (LED is to build up the economic capacity of a local area to improve its economic future and the quality of life for all. To support  the Local Economic Development in remote areas,   a program  has been developed based on the LED frame work of the world bank. This approach and  the experiences over  the past years with this program are  described in the first part.  In the second part of the paper, We analyse work done with that program with the help of the social capital concept and the triple helix model.  In all cases it is important to pay attention to who is taken the initiative after the first move (and it is not always the governance as actor and for the triple helix we suggest  that the concepts of (national Government, Industry and University need a translation to Local Governance Agency, Cooperation or other ways of cooperation of local communities and Local Universities. Although a push from outside might help  a local region in development the endogenous factors are  also needed. Keywords: Triple Helix model, Local Economic Development, Local Actors, Double Triangle within the Helix Model

  5. Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

    Science.gov (United States)

    Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

    2017-12-01

    Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

  6. Model-based leakage localization in drinking water distribution networks using structured residuals

    OpenAIRE

    Puig Cayuela, Vicenç; Rosich, Albert

    2013-01-01

    In this paper, a new model based approach to leakage localization in drinking water networks is proposed based on generating a set of structured residuals. The residual evaluation is based on a numerical method based on an enhanced Newton-Raphson algorithm. The proposed method is suitable for water network systems because the non-linearities of the model make impossible to derive analytical residuals. Furthermore, the computed residuals are designed so that leaks are decoupled, which impro...

  7. Event-based computer simulation model of aspect-type experiments strictly satisfying Einstein's locality conditions

    NARCIS (Netherlands)

    De Raedt, Hans; De Raedt, Koen; Michielsen, Kristel; Keimpema, Koenraad; Miyashita, Seiji

    2007-01-01

    Inspired by Einstein-Podolsky-Rosen-Bohtn experiments with photons, we construct an event-based simulation model in which every essential element in the ideal experiment has a counterpart. The model satisfies Einstein's criterion of local causality and does not rely on concepts of quantum and

  8. Model-based monitoring techniques for leakage localization in distribution water networks

    OpenAIRE

    Meseguer Amela, Jordi; Mirats Tur, Josep Maria; Cembrano Gennari, Gabriela; Puig Cayuela, Vicenç

    2015-01-01

    This is an open access article under the CC BY-NC-ND license This paper describes an integrated model-based monitoring framework for leakage localization in district-metered areas (DMA) of water distribution networks, which takes advantage of the availability of a hydraulic model of the network. The leakage localization methodology is based on the use of flow and pressure sensors at the DMA inlets and a limited number of pressure sensors deployed inside the DMA. The placement of these sens...

  9. Improving UWB-Based Localization in IoT Scenarios with Statistical Models of Distance Error.

    Science.gov (United States)

    Monica, Stefania; Ferrari, Gianluigi

    2018-05-17

    Interest in the Internet of Things (IoT) is rapidly increasing, as the number of connected devices is exponentially growing. One of the application scenarios envisaged for IoT technologies involves indoor localization and context awareness. In this paper, we focus on a localization approach that relies on a particular type of communication technology, namely Ultra Wide Band (UWB). UWB technology is an attractive choice for indoor localization, owing to its high accuracy. Since localization algorithms typically rely on estimated inter-node distances, the goal of this paper is to evaluate the improvement brought by a simple (linear) statistical model of the distance error. On the basis of an extensive experimental measurement campaign, we propose a general analytical framework, based on a Least Square (LS) method, to derive a novel statistical model for the range estimation error between a pair of UWB nodes. The proposed statistical model is then applied to improve the performance of a few illustrative localization algorithms in various realistic scenarios. The obtained experimental results show that the use of the proposed statistical model improves the accuracy of the considered localization algorithms with a reduction of the localization error up to 66%.

  10. The Integrated Model of Sustainability Perspective in Spermatophyta Learning Based on Local Wisdom

    Science.gov (United States)

    Hartadiyati, E.; Rizqiyah, K.; Wiyanto; Rusilowati, A.; Prasetia, A. P. B.

    2017-09-01

    In present condition, culture is diminished, the change of social order toward the generation that has no policy and pro-sustainability; As well as the advancement of science and technology are often treated unwisely so as to excite local wisdom. It is therefore necessary to explore intra-curricular local wisdom in schools. This study aims to produce an integration model of sustainability perspectives based on local wisdom on spermatophyta material that is feasible and effective. This research uses define, design and develop stages to an integration model of sustainability perspectives based on local wisdom on spermatophyta material. The resulting product is an integration model of socio-cultural, economic and environmental sustainability perspective and formulated with preventive, preserve and build action on spermatophyta material consisting of identification and classification, metagenesis and the role of spermatophyta for human life. The integration model of sustainability perspective in learning spermatophyta based on local wisdom is considered proven to be effective in raising sustainability’s awareness of high school students.

  11. 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…

  12. Power law-based local search in spider monkey optimisation for lower order system modelling

    Science.gov (United States)

    Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

    2017-01-01

    The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

  13. Model-based synthesis of locally contingent responses to global market signals

    Science.gov (United States)

    Magliocca, N. R.

    2015-12-01

    Rural livelihoods and the land systems on which they depend are increasingly influenced by distant markets through economic globalization. Place-based analyses of land and livelihood system sustainability must then consider both proximate and distant influences on local decision-making. Thus, advancing land change theory in the context of economic globalization calls for a systematic understanding of the general processes as well as local contingencies shaping local responses to global signals. Synthesis of insights from place-based case studies of land and livelihood change is a path forward for developing such systematic knowledge. This paper introduces a model-based synthesis approach to investigating the influence of local socio-environmental and agent-level factors in mediating land-use and livelihood responses to changing global market signals. A generalized agent-based modeling framework is applied to six case-study sites that differ in environmental conditions, market access and influence, and livelihood settings. The largest modeled land conversions and livelihood transitions to market-oriented production occurred in sties with relatively productive agricultural land and/or with limited livelihood options. Experimental shifts in the distributions of agents' risk tolerances generally acted to attenuate or amplify responses to changes in global market signals. Importantly, however, responses of agents at different points in the risk tolerance distribution varied widely, with the wealth gap growing wider between agents with higher or lower risk tolerance. These results demonstrate model-based synthesis is a promising approach to overcome many of the challenges of current synthesis methods in land change science, and to identify generalized as well as locally contingent responses to global market signals.

  14. Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

    Science.gov (United States)

    Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

    2008-12-01

    How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

  15. 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.

  16. Assessment of damage localization based on spatial filters using numerical crack propagation models

    International Nuclear Information System (INIS)

    Deraemaeker, Arnaud

    2011-01-01

    This paper is concerned with vibration based structural health monitoring with a focus on non-model based damage localization. The type of damage investigated is cracking of concrete structures due to the loss of prestress. In previous works, an automated method based on spatial filtering techniques applied to large dynamic strain sensor networks has been proposed and tested using data from numerical simulations. In the simulations, simplified representations of cracks (such as a reduced Young's modulus) have been used. While this gives the general trend for global properties such as eigen frequencies, the change of more local features, such as strains, is not adequately represented. Instead, crack propagation models should be used. In this study, a first attempt is made in this direction for concrete structures (quasi brittle material with softening laws) using crack-band models implemented in the commercial software DIANA. The strategy consists in performing a non-linear computation which leads to cracking of the concrete, followed by a dynamic analysis. The dynamic response is then used as the input to the previously designed damage localization system in order to assess its performances. The approach is illustrated on a simply supported beam modeled with 2D plane stress elements.

  17. Proposal of a Holistic Model to Support Local-Level Evidence-Based Practice

    Directory of Open Access Journals (Sweden)

    Said Shahtahmasebi

    2010-01-01

    Full Text Available In response to a central drive for evidence-based practice, there have been many research support schemes, setups, and other practices concentrating on facilitating access to external research, such as the Centre for Evidence Based Healthcare Aotearoa, the Cochrane Collaboration, and the York Centre for Reviews and Dissemination. Very little attention has been paid to supporting internal research in terms of local evidence and internal research capabilities. The whole evidence-based practice movement has alienated internal decision makers and, thus, very little progress has been made in the context of evidence informing local policy formation. Health and social policies are made centrally based on dubious claims and often evidence is sought after implementation. For example, on record, most health care practitioners appear to agree with the causal link between depression and mental illness (sometimes qualified with other social factors with suicide; off the record, even some psychiatrists doubt that such a link is applicable to the population as a whole. Therefore, be it through misplaced loyalty or a lack of support for internal researchers/decision makers, local evidence informing local decision making may have been ignored in favour of external evidence. In this paper, we present a practical holistic model to support local evidence-based decision making. This approach is more relevant in light of a new approach to primary health care of “local knowledge” complementing external evidence. One possible outcome would be to network with other regional programmes around the world to share information and identify “best” practices, such as the “Stop Youth Suicide Campaign”(www.stopyouthsuicide.com.

  18. 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...

  19. Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models.

    Science.gov (United States)

    Liu, Zhiguang; Zhou, Liuyang; Leung, Howard; Shum, Hubert P H

    2016-11-01

    Depth sensor based 3D human motion estimation hardware such as Kinect has made interactive applications more popular recently. However, it is still challenging to accurately recognize postures from a single depth camera due to the inherently noisy data derived from depth images and self-occluding action performed by the user. In this paper, we propose a new real-time probabilistic framework to enhance the accuracy of live captured postures that belong to one of the action classes in the database. We adopt the Gaussian Process model as a prior to leverage the position data obtained from Kinect and marker-based motion capture system. We also incorporate a temporal consistency term into the optimization framework to constrain the velocity variations between successive frames. To ensure that the reconstructed posture resembles the accurate parts of the observed posture, we embed a set of joint reliability measurements into the optimization framework. A major drawback of Gaussian Process is its cubic learning complexity when dealing with a large database due to the inverse of a covariance matrix. To solve the problem, we propose a new method based on a local mixture of Gaussian Processes, in which Gaussian Processes are defined in local regions of the state space. Due to the significantly decreased sample size in each local Gaussian Process, the learning time is greatly reduced. At the same time, the prediction speed is enhanced as the weighted mean prediction for a given sample is determined by the nearby local models only. Our system also allows incrementally updating a specific local Gaussian Process in real time, which enhances the likelihood of adapting to run-time postures that are different from those in the database. Experimental results demonstrate that our system can generate high quality postures even under severe self-occlusion situations, which is beneficial for real-time applications such as motion-based gaming and sport training.

  20. 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.)

  1. 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.)

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

    Science.gov (United States)

    Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

    Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object

  8. 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

  9. 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).

  10. 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.

  11. 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...

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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…

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

    Science.gov (United States)

    Hong, S-M; Jung, B-H; Ruan, D

    2011-03-21

    Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

  3. 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

  4. 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.

  5. Numerical Modeling of Edge-Localized-Mode Filaments on Divertor Plates Based on Thermoelectric Currents

    International Nuclear Information System (INIS)

    Wingen, A.; Spatschek, K. H.; Evans, T. E.; Lasnier, C. J.

    2010-01-01

    Edge localized modes (ELMs) are qualitatively and quantitatively modeled in tokamaks using current bursts which have been observed in the scrape-off-layer (SOL) during an ELM crash. During the initial phase of an ELM, a heat pulse causes thermoelectric currents. They first flow in short connection length flux tubes which are initially established by error fields or other nonaxisymmetric magnetic perturbations. The currents change the magnetic field topology in such a way that larger areas of short connection length flux tubes emerge. Then currents predominantly flow in short SOL-like flux tubes and scale with the area of the flux tube assuming a constant current density. Quantitative predictions of flux tube patterns for a given current are in excellent agreement with measurements of the heat load and current flow at the DIII-D target plates during an ELM cycle.

  6. Scaling up local energy infrastructure; An agent-based model of the emergence of district heating networks

    International Nuclear Information System (INIS)

    Busch, Jonathan; Roelich, Katy; Bale, Catherine S.E.; Knoeri, Christof

    2017-01-01

    The potential contribution of local energy infrastructure – such as heat networks – to the transition to a low carbon economy is increasingly recognised in international, national and municipal policy. Creating the policy environment to foster the scaling up of local energy infrastructure is, however, still challenging; despite national policy action and local authority interest the growth of heat networks in UK cities remains slow. Techno-economic energy system models commonly used to inform policy are not designed to address institutional and governance barriers. We present an agent-based model of heat network development in UK cities in which policy interventions aimed at the institutional and governance barriers faced by diverse actors can be explored. Three types of project instigators are included – municipal, commercial and community – which have distinct decision heuristics and capabilities and follow a multi-stage development process. Scenarios of policy interventions developed in a companion modelling approach indicate that the effect of interventions differs between actors depending on their capabilities. Successful interventions account for the specific motivations and capabilities of different actors, provide a portfolio of support along the development process and recognise the important strategic role of local authorities in supporting low carbon energy infrastructure. - Highlights: • Energy policy should account for diverse actor motivations and capabilities. • Project development is a multi-stage process, not a one-off event. • Participatory agent-based modelling can inform policy that accounts for complexity. • Policy should take a portfolio approach to providing support. • Local authorities have an important strategic role in local infrastructure.

  7. A local-community-level, physically-based model of end-use energy consumption by Australian housing stock

    International Nuclear Information System (INIS)

    Ren Zhengen; Paevere, Phillip; McNamara, Cheryl

    2012-01-01

    We developed a physics based bottom-up model to estimate annual housing stock energy consumption at a local community level (Census Collection District—CCD) with an hourly resolution. Total energy consumption, including space heating and cooling, water heating, lighting and other household appliances, was simulated by considering building construction and materials, equipment and appliances, local climates and occupancy patterns. The model was used to analyse energy use by private dwellings in more than five thousand CCDs in the state of New South Wales (NSW), Australia. The predicted results focus on electricity consumption (natural gas and other fuel sources were excluded as the data are not available) and track the actual electricity consumption at CCD level with an error of 9.2% when summed to state level. For NSW and Victoria 2006, the predicted state electricity consumption is close to the published model (within 6%) and statistical data (within 10%). A key feature of the model is that it can be used to predict hourly electricity consumption and peak demand at fine geographic scales, which is important for grid planning and designing local energy efficiency or demand response strategies. - Highlights: ► We developed a physics-based model to estimate housing stock energy consumption. ► House type and vintage, family type and occupancy time were considered. ► The model results are close to actual energy consumption at local community level. ► Its’ results agree well with the published model and statistical data at state level. ► It shows the model could provide from hourly to annual residential energy consumption.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Model-based flaw localization from perturbations in the dynamic response of complex mechanical structures

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, D H

    2009-02-24

    A new method of locating structural damage using measured differences in vibrational response and a numerical model of the undamaged structure has been presented. This method is particularly suited for complex structures with little or no symmetry. In a prior study the method successively located simulated damage from measurements of the vibrational response on two simple structures. Here we demonstrate that it can locate simulated damage in a complex structure. A numerical model of a complex structure was used to calculate the structural response before and after the introduction of a void. The method can now be considered for application to structures of programmatic interest. It could be used to monitor the structural integrity of complex mechanical structures and assemblies over their lifetimes. This would allow early detection of damage, when repair is relatively easy and inexpensive. It would also allow one to schedule maintenance based on actual damage instead of a time schedule.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Credit Risk Analysis of Local Government Financing Platform – An empirical study based on KMV model

    Directory of Open Access Journals (Sweden)

    Zhou Tingting

    2015-01-01

    Full Text Available The local government financing platform is set up by local government through state-owned assets, real estate and equity capital. The functions of these companies are financing, construction, operation, the repaying debts. The local government financing platform can broaden the financing channels of local government in a great extent; alleviate the pressure of capital requirement. But at the same time, with the gradual expansion of the scale of debt, a series of problems has arisen: the amount of financing platform companies is huge, debt repayment depends too much on real estate price, the integration of government administration with enterprise, capital injection, and accounts of these companies are not well exposed. Once these problems outbreak, it may cause a series of financial crises, thereby threaten the entire banking industry even the healthy development of the national economy.

  19. Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

    Science.gov (United States)

    Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

    2018-04-01

    Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

  20. 3D LOCAL SCALE SOLAR RADIATION MODEL BASED ON URBAN LIDAR DATA

    Directory of Open Access Journals (Sweden)

    P. M. Redweik

    2012-09-01

    Full Text Available The aim of the present study is to obtain the direct, diffuse and reflected solar energy that reaches a generic point of an urban landscape regardless of its location on a roof, on the ground or on a façade. The vertical façades embody a discontinuity in a digital elevation surface function and most models fail in the determination of solar radiation for points on façades. The presented algorithm solves the problem in an integrated way: starting with a georreferenced LIDAR data cloud covering a 400 × 400 m2 urban area resampled in a 1m × 1m mesh, applies a new shadow algorithm over roofs, terrain and façades for each time frame, applies the Kumar solar radiation model for the calculation of direct, diffuse and reflected irradiation for each 1x1m raster cell on non vertical surfaces of roof and terrain, and calculates total and mean irradiation of each 1 meter wide column of vertical façade based on the illuminated area at each time frame. The results for each time frame are integrated for the wished time period from one hour to one year, being the time steps also selectable, allowing several kinds of solar radiation and shadowing studies. GIS were used to evaluate monthly averages of solar radiation for a particular location as well as to map the photovoltaic potential of the building façades and their roofs according to determined classes of potential.

  1. Theoretical Bases of the Model of Interaction of the Government and Local Government Creation

    OpenAIRE

    Nikolay I. Churinov

    2015-01-01

    Article is devoted to questions of understanding of a theoretical component: systems of interaction of bodies of different levels of the government. Author researches historical basis of the studied subject by research of foreign and domestic scientific experience in area of the theory of the state and the law. Much attention is paid to the scientific aspect of the question. By empirical approach interpretation of the theory of interaction of public authorities and local government, and also ...

  2. 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.

  3. Model Based Beamforming and Bayesian Inversion Signal Processing Methods for Seismic Localization of Underground Source

    DEFF Research Database (Denmark)

    Oh, Geok Lian

    properties such as the elastic wave speeds and soil densities. One processing method is casting the estimation problem into an inverse problem to solve for the unknown material parameters. The forward model for the seismic signals used in the literatures include ray tracing methods that consider only...... density values of the discretized ground medium, which leads to time-consuming computations and instability behaviour of the inversion process. In addition, the geophysics inverse problem is generally ill-posed due to non-exact forward model that introduces errors. The Bayesian inversion method through...... the first arrivals of the reflected compressional P-waves from the subsurface structures, or 3D elastic wave models that model all the seismic wave components. The ray tracing forward model formulation is linear, whereas the full 3D elastic wave model leads to a nonlinear inversion problem. In this Ph...

  4. Theoretical Bases of the Model of Interaction of the Government and Local Government Creation

    Directory of Open Access Journals (Sweden)

    Nikolay I. Churinov

    2015-09-01

    Full Text Available Article is devoted to questions of understanding of a theoretical component: systems of interaction of bodies of different levels of the government. Author researches historical basis of the studied subject by research of foreign and domestic scientific experience in area of the theory of the state and the law. Much attention is paid to the scientific aspect of the question. By empirical approach interpretation of the theory of interaction of public authorities and local government, and also subjective estimated opinion of the author is given.

  5. 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....

  6. 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

  7. 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.

  8. Modeling and analyzing cascading dynamics of the Internet based on local congestion information

    Science.gov (United States)

    Zhu, Qian; Nie, Jianlong; Zhu, Zhiliang; Yu, Hai; Xue, Yang

    2018-06-01

    Cascading failure has already become one of the vital issues in network science. By considering realistic network operational settings, we propose the congestion function to represent the congested extent of node and construct a local congestion-aware routing strategy with a tunable parameter. We investigate the cascading failures on the Internet triggered by deliberate attacks. Simulation results show that the tunable parameter has an optimal value that makes the network achieve a maximum level of robustness. The robustness of the network has a positive correlation with tolerance parameter, but it has a negative correlation with the packets generation rate. In addition, there exists a threshold of the attacking proportion of nodes that makes the network achieve the lowest robustness. Moreover, by introducing the concept of time delay for information transmission on the Internet, we found that an increase of the time delay will decrease the robustness of the network rapidly. The findings of the paper will be useful for enhancing the robustness of the Internet in the future.

  9. Advanced numerical simulation based on a non-local micromorphic model for metal forming processes

    Directory of Open Access Journals (Sweden)

    Diamantopoulou Evangelia

    2016-01-01

    Full Text Available An advanced numerical methodology is developed for metal forming simulation based on thermodynamically-consistent nonlocal constitutive equations accounting for various fully coupled mechanical phenomena under finite strain in the framework of micromorphic continua. The numerical implementation into ABAQUS/Explicit is made for 2D quadrangular elements thanks to the VUEL users’ subroutine. Simple examples with presence of a damaged area are made in order to show the ability of the proposed methodology to describe the independence of the solution from the space discretization.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Model-based sphere localization (MBSL) in x-ray projections

    Science.gov (United States)

    Sawall, Stefan; Maier, Joscha; Leinweber, Carsten; Funck, Carsten; Kuntz, Jan; Kachelrieß, Marc

    2017-08-01

    The detection of spherical markers in x-ray projections is an important task in a variety of applications, e.g. geometric calibration and detector distortion correction. Therein, the projection of the sphere center on the detector is of particular interest as the used spherical beads are no ideal point-like objects. Only few methods have been proposed to estimate this respective position on the detector with sufficient accuracy and surrogate positions, e.g. the center of gravity, are used, impairing the results of subsequent algorithms. We propose to estimate the projection of the sphere center on the detector using a simulation-based method matching an artificial projection to the actual measurement. The proposed algorithm intrinsically corrects for all polychromatic effects included in the measurement and absent in the simulation by a polynomial which is estimated simultaneously. Furthermore, neither the acquisition geometry nor any object properties besides the fact that the object is of spherical shape need to be known to find the center of the bead. It is shown by simulations that the algorithm estimates the center projection with an error of less than 1% of the detector pixel size in case of realistic noise levels and that the method is robust to the sphere material, sphere size, and acquisition parameters. A comparison to three reference methods using simulations and measurements indicates that the proposed method is an order of magnitude more accurate compared to these algorithms. The proposed method is an accurate algorithm to estimate the center of spherical markers in CT projections in the presence of polychromatic effects and noise.

  13. Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

    2018-03-01

    Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p breast cancer detected in the next subsequent mammography screening.

  14. 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.

  15. 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.

  16. Covariances for neutron cross sections calculated using a regional model based on local-model fits to experimental data

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D.L.; Guenther, P.T.

    1983-11-01

    We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references.

  17. Covariances for neutron cross sections calculated using a regional model based on local-model fits to experimental data

    International Nuclear Information System (INIS)

    Smith, D.L.; Guenther, P.T.

    1983-11-01

    We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references

  18. 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

  19. 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).

  20. 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.

  1. Development of local TDC model in core thermal hydraulic analysis

    International Nuclear Information System (INIS)

    Kwon, H.S.; Park, J.R.; Hwang, D.H.; Lee, S.K.

    2004-01-01

    The local TDC model consisting of natural mixing and forced mixing part was developed to obtain more realistic local fluid properties in the core subchannel analysis. To evaluate the performance of local TDC model, the CHF prediction capability was tested with the various CHF correlations and local fluid properties at CHF location which are based on the local TDC model. The results show that the standard deviation of measured to predicted CHF ratio (M/P) based on local TDC model can be reduced by about 7% compared to those based on global TDC model when the CHF correlation has no term to account for distance from the spacer grid. (author)

  2. 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.

  3. 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.

  4. 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.

  5. 4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

    Science.gov (United States)

    Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

    2008-01-01

    Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

  6. GPU-based local interaction simulation approach for simplified temperature effect modelling in Lamb wave propagation used for damage detection

    International Nuclear Information System (INIS)

    Kijanka, P; Radecki, R; Packo, P; Staszewski, W J; Uhl, T

    2013-01-01

    Temperature has a significant effect on Lamb wave propagation. It is important to compensate for this effect when the method is considered for structural damage detection. The paper explores a newly proposed, very efficient numerical simulation tool for Lamb wave propagation modelling in aluminum plates exposed to temperature changes. A local interaction approach implemented with a parallel computing architecture and graphics cards is used for these numerical simulations. The numerical results are compared with the experimental data. The results demonstrate that the proposed approach could be used efficiently to produce a large database required for the development of various temperature compensation procedures in structural health monitoring applications. (paper)

  7. Development and validation of a local time stepping-based PaSR solver for combustion and radiation modeling

    DEFF Research Database (Denmark)

    Pang, Kar Mun; Ivarsson, Anders; Haider, Sajjad

    2013-01-01

    In the current work, a local time stepping (LTS) solver for the modeling of combustion, radiative heat transfer and soot formation is developed and validated. This is achieved using an open source computational fluid dynamics code, OpenFOAM. Akin to the solver provided in default assembly i...... library in the edcSimpleFoam solver which was introduced during the 6th OpenFOAM workshop is modified and coupled with the current solver. One of the main amendments made is the integration of soot radiation submodel since this is significant in rich flames where soot particles are formed. The new solver...

  8. 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)

  9. 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.

  10. A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

    Science.gov (United States)

    Unke, Oliver T.; Meuwly, Markus

    2018-06-01

    Despite the ever-increasing computer power, accurate ab initio calculations for large systems (thousands to millions of atoms) remain infeasible. Instead, approximate empirical energy functions are used. Most current approaches are either transferable between different chemical systems, but not particularly accurate, or they are fine-tuned to a specific application. In this work, a data-driven method to construct a potential energy surface based on neural networks is presented. Since the total energy is decomposed into local atomic contributions, the evaluation is easily parallelizable and scales linearly with system size. With prediction errors below 0.5 kcal mol-1 for both unknown molecules and configurations, the method is accurate across chemical and configurational space, which is demonstrated by applying it to datasets from nonreactive and reactive molecular dynamics simulations and a diverse database of equilibrium structures. The possibility to use small molecules as reference data to predict larger structures is also explored. Since the descriptor only uses local information, high-level ab initio methods, which are computationally too expensive for large molecules, become feasible for generating the necessary reference data used to train the neural network.

  11. 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...

  12. 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.

  13. 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)

  14. 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.

  15. 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.

  16. Microsphere-Based Rapamycin Delivery, Systemic Versus Local Administration in a Rat Model of Renal Ischemia/Reperfusion Injury

    NARCIS (Netherlands)

    Zandstra, Jurjen; van Beuge, Marike M.; Zuidema, Johan; Petersen, Arjen H.; Staal, Mark; Duque, Luisa F.; Rodriguez, Sergio; Lathuile, Audrey A. R.; Veldhuis, Gert J.; Steendam, Rob; Bank, Ruud A.; Popa, Eliane R.

    2015-01-01

    The increasing prevalence and treatment costs of kidney diseases call for innovative therapeutic strategies that prevent disease progression at an early stage. We studied a novel method of subcapsular injection of monodisperse microspheres, to use as a local delivery system of drugs to the kidney.

  17. 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

  18. 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...

  19. Business Models for Local Foods

    DEFF Research Database (Denmark)

    Esbjerg, Lars; Pedersen, Maja; Pederson, Robert

    2014-01-01

    sales of food products (and vice versa) and therefore have to develop alternative marketing channels. The purpose of this paper is to investigate the practices of different small and medium-sized Danish producers of locally grown and/or processed foods in relation to developing marketing channels...

  20. 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…

  1. 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

  2. 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.

  3. 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.

  4. Detecting P and S-wave of Mt. Rinjani seismic based on a locally stationary autoregressive (LSAR) model

    Science.gov (United States)

    Nurhaida, Subanar, Abdurakhman, Abadi, Agus Maman

    2017-08-01

    Seismic data is usually modelled using autoregressive processes. The aim of this paper is to find the arrival times of the seismic waves of Mt. Rinjani in Indonesia. Kitagawa algorithm's is used to detect the seismic P and S-wave. Householder transformation used in the algorithm made it effectively finding the number of change points and parameters of the autoregressive models. The results show that the use of Box-Cox transformation on the variable selection level makes the algorithm works well in detecting the change points. Furthermore, when the basic span of the subinterval is set 200 seconds and the maximum AR order is 20, there are 8 change points which occur at 1601, 2001, 7401, 7601,7801, 8001, 8201 and 9601. Finally, The P and S-wave arrival times are detected at time 1671 and 2045 respectively using a precise detection algorithm.

  5. 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

  6. The Development of Cooperative Learning Model Based on Local Wisdom of Bali for Physical Education, Sport and Health Subject in Junior High School

    Science.gov (United States)

    Yoda, I. K.

    2017-03-01

    The purpose of this research is to develop a cooperative learning model based on local wisdom (PKBKL) of Bali (Tri Pramana’s concept), for physical education, sport, and health learning in VII grade of Junior High School in Singaraja-Buleleng Bali. This research is the development research of the development design chosen refers to the development proposed by Dick and Carey. The development of model and learning devices was conducted through four stages, namely: (1) identification and needs analysis stage (2) the development of design and draft of PKBKL and RPP models, (3) testing stage (expert review, try out, and implementation). Small group try out was conducted on VII-3 grade of Undiksha Laboratory Junior High School in the academic year 2013/2014, large group try out was conducted on VIIb of Santo Paulus Junior High School Singaraja in the academic year 2014/2015, and the implementation of the model was conducted on three (3) schools namely SMPN 2 Singaraja, SMPN 3 Singaraja, and Undiksha laboratory Junior High School in the academic year 2014/2015. Data were collected using documentation, testing, non-testing, questionnaire, and observation. The data were analyzed descriptively. The findings of this research indicate that: (1) PKBKL model has met the criteria of the operation of a learning model namely: syntax, social system, principles of reaction, support system, as well as instructional and nurturing effects, (2) PKBKL model is a valid, practical, and effective model, (3) the practicality of the learning devices (RPP), is at the high category. Based on the research results, there are two things recommended: (1) in order that learning stages (syntax) of PKBKL model can be performed well, then teachers need to have an understanding of the cooperative learning model of Student Team Achievement Division (STAD) type and the concepts of scientifically approach well, (2) PKBKL model can be performed well on physical education, sport and health learning, if the

  7. 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

  8. Application of coating and base material living models to evaluate degradation and estimate the mean local operating temperature of two ex-service 1{sup st} stage blades

    Energy Technology Data Exchange (ETDEWEB)

    Mandelli, M. [Proing Italia, Torbole sul Garda, Trento (Italy); Rinaldi, C. [ERSE, Milan (Italy); Vacchieri, E. [Ansaldo Energia S.p.A., Genoa (Italy)

    2010-07-01

    In the frame of the collaborative program COST 538 a coating life prediction code was implemented by Proing and ERSE with an inverse problem solution routine able to calculate the local mean operating temperature from the operating conditions and the extension of the coating depleted regions. Moreover base material degradation models were developed by Ansaldo Energia on both equiaxed and single crystal superalloys. This paper describes the application of such methodologies to two ex-service 1st stage gas turbine blades delivered to COST 538 by AEN after operation in two different plants with different operating conditions. The objective of the study was the application and validation of an innovative NDT and the estimate of the mean operating temperature at different positions of the components. The destructive metallographic analysis of the blades let to validate the non destructive frequency scanning eddy current technique (F-SECT). Coating life modelling results are compared with those of the base material degradation models. An interesting correlation was found between the estimated temperatures with the two methods and also with the NDT findings at the most significant component positions. (orig.)

  9. 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

  10. 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.

  11. SU-E-J-244: Development and Validation of a Knowledge Based Planning Model for External Beam Radiation Therapy of Locally Advanced Non-Small Cell Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Z; Kennedy, A [Sarah Cannon, Nashville, TN (United States); Larsen, E; Hayes, C; Grow, A [North Florida Cancer Center, Gainesville, FL (United States); Bahamondes, S.; Zheng, Y; Wu, X [JFK Comprehensive Cancer Institute, Lake Worth, FL (United States); Choi, M; Pai, S [Good Samaritan Hospital, Los Gatos, CA (United States); Li, J [Doctors Hospital of Augusta, Augusta, GA (United States); Cranford, K [Trident Medical Center, Charleston, SC (United States)

    2015-06-15

    Purpose: The study aims to develop and validate a knowledge based planning (KBP) model for external beam radiation therapy of locally advanced non-small cell lung cancer (LA-NSCLC). Methods: RapidPlan™ technology was used to develop a lung KBP model. Plans from 65 patients with LA-NSCLC were used to train the model. 25 patients were treated with VMAT, and the other patients were treated with IMRT. Organs-at-risk (OARs) included right lung, left lung, heart, esophagus, and spinal cord. DVH and geometric distribution DVH were extracted from the treated plans. The model was trained using principal component analysis and step-wise multiple regression. Box plot and regression plot tools were used to identify geometric outliers and dosimetry outliers and help fine-tune the model. The validation was performed by (a) comparing predicted DVH boundaries to actual DVHs of 63 patients and (b) using an independent set of treatment planning data. Results: 63 out of 65 plans were included in the final KBP model with PTV volume ranging from 102.5cc to 1450.2cc. Total treatment dose prescription varied from 50Gy to 70Gy based on institutional guidelines. One patient was excluded due to geometric outlier where 2.18cc of spinal cord was included in PTV. The other patient was excluded due to dosimetric outlier where the dose sparing to spinal cord was heavily enforced in the clinical plan. Target volume, OAR volume, OAR overlap volume percentage to target, and OAR out-of-field volume were included in the trained model. Lungs and heart had two principal component scores of GEDVH, whereas spinal cord and esophagus had three in the final model. Predicted DVH band (mean ±1 standard deviation) represented 66.2±3.6% of all DVHs. Conclusion: A KBP model was developed and validated for radiotherapy of LA-NSCLC in a commercial treatment planning system. The clinical implementation may improve the consistency of IMRT/VMAT planning.

  12. 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.

  13. Closed-Loop Feedback Computation Model of Dynamical Reputation Based on the Local Trust Evaluation in Business-to-Consumer E-Commerce

    Directory of Open Access Journals (Sweden)

    Bo Tian

    2016-02-01

    Full Text Available Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.

  14. [Localization Establishment of an Interdisciplinary Intervention Model to Prevent Post-Operative Delirium in Older Patients Based on 'Hospital Elder Life Program'].

    Science.gov (United States)

    Wang, Yan-Yan; Liao, Yu-Lin; Gao, Lang-Li; Hu, Xiu-Ying; Yue, Ji-Rong

    2017-06-01

    Postoperative delirium is a significant complication in elderly patients. The occurrence of delirium may increase the related physical and psychological risks, delay the length of hospital stays, and even lead to death. According to the current evidence-based model, the application of interdisciplinary intervention may effectively prevent delirium, shorten the length of hospital stays, and save costs. To establish a culturally appropriate interdisciplinary intervention model for preventing postoperative delirium in older Chinese patients. The authors adapted the original version of the Hospital Elder Life Program (HELP©) from the Hebrew Senior Life Institute for Aging Research of Harvard University by localizing the content using additional medical resources and translating the modified instrument into Chinese. Furthermore, the final version of this interdisciplinary intervention model for postoperative delirium was developed in accordance with the "guideline of delirium: diagnosis, prevention and management produced by the National Institute for Health and Clinical Excellence in 2010" and the "clinical practice guideline for postoperative delirium in older adults" produced by American geriatrics society in 2014. Finally, the translated instrument was revised and improved using discussions, consultations, and pilot study. The abovementioned procedure generated an interdisciplinary intervention model for preventing postoperative delirium that is applicable to the Chinese medical environment. The content addresses personnel structure and assignment of responsibility; details of interdisciplinary intervention protocols and implementation procedures; and required personnel training. The revised model is expected to decrease the occurrence of post-operative delirium and other complications in elderly patients, to help them maintain and improve their function, to shorten the length of their hospital stays, and to facilitate recovery.

  15. 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...

  16. 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

  17. 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...

  18. Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate

    Science.gov (United States)

    Deng, Dongdong; Murphy, Michael J.; Hakim, Joe B.; Franceschi, William H.; Zahid, Sohail; Pashakhanloo, Farhad; Trayanova, Natalia A.; Boyle, Patrick M.

    2017-09-01

    Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.

  19. 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.

  20. 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.

  1. LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection

    DEFF Research Database (Denmark)

    Nikolov, Ivan Adriyanov; Madsen, Claus B.

    2017-01-01

    for on-site outdoor localization and mapping in low feature environment using the inexpensive RPLIDAR and an 9-DOF IMU. Our algorithm geometrically simplifies the wind turbine blade 2D cross-section to an elliptical model and uses it for distance and shape correction. We show that the proposed algorithm...

  2. Entropy based fingerprint for local crystalline order

    Science.gov (United States)

    Piaggi, Pablo M.; Parrinello, Michele

    2017-09-01

    We introduce a new fingerprint that allows distinguishing between liquid-like and solid-like atomic environments. This fingerprint is based on an approximate expression for the entropy projected on individual atoms. When combined with local enthalpy, this fingerprint acquires an even finer resolution and it is capable of discriminating between different crystal structures.

  3. 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.

  4. 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)

  5. 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

  6. 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.

  7. 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).

  8. 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.

  9. Churn classification model for local telecommunication company ...

    African Journals Online (AJOL)

    ... model based on the Rough Set Theory to classify customer churn. The results of the study show that the proposed Rough Set classification model outperforms the existing models and contributes to significant accuracy improvement. Keywords: customer churn; classification model; telecommunication industry; data mining;

  10. 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

  11. 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.)

  12. 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)

  13. 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....

  14. 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.

  15. Automated geographic atrophy segmentation for SD-OCT images using region-based C-V model via local similarity factor.

    Science.gov (United States)

    Niu, Sijie; de Sisternes, Luis; Chen, Qiang; Leng, Theodore; Rubin, Daniel L

    2016-02-01

    Age-related macular degeneration (AMD) is the leading cause of blindness among elderly individuals. Geographic atrophy (GA) is a phenotypic manifestation of the advanced stages of non-exudative AMD. Determination of GA extent in SD-OCT scans allows the quantification of GA-related features, such as radius or area, which could be of important value to monitor AMD progression and possibly identify regions of future GA involvement. The purpose of this work is to develop an automated algorithm to segment GA regions in SD-OCT images. An en face GA fundus image is generated by averaging the axial intensity within an automatically detected sub-volume of the three dimensional SD-OCT data, where an initial coarse GA region is estimated by an iterative threshold segmentation method and an intensity profile set, and subsequently refined by a region-based Chan-Vese model with a local similarity factor. Two image data sets, consisting on 55 SD-OCT scans from twelve eyes in eight patients with GA and 56 SD-OCT scans from 56 eyes in 56 patients with GA, respectively, were utilized to quantitatively evaluate the automated segmentation algorithm. We compared results obtained by the proposed algorithm, manual segmentation by graders, a previously proposed method, and experimental commercial software. When compared to a manually determined gold standard, our algorithm presented a mean overlap ratio (OR) of 81.86% and 70% for the first and second data sets, respectively, while the previously proposed method OR was 72.60% and 65.88% for the first and second data sets, respectively, and the experimental commercial software OR was 62.40% for the second data set.

  16. 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.

  17. 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.

  18. 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.

  19. On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

    Science.gov (United States)

    Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

    2013-11-07

    A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

  20. 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.

  1. Barcode based localization system in indoor environment

    Directory of Open Access Journals (Sweden)

    Ľubica Ilkovičová

    2014-12-01

    Full Text Available Nowadays, in the era of intelligent buildings, there is a need to create indoornavigation systems, what is steadily a challenge. QR (Quick Response codesprovide accurate localization also in indoor environment, where other navigationtechniques (e.g. GPS are not available. The paper deals with the issues of posi-tioning using QR codes, solved at the Department of Surveying, Faculty of CivilEngineering SUT in Bratislava. Operating principle of QR codes, description ofthe application for positioning in indoor environment based on OS Android forsmartphones are described.

  2. 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

  3. LOCAL TEXTURE DESCRIPTION FRAMEWORK FOR TEXTURE BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    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.

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure

    International Nuclear Information System (INIS)

    Chen, Wen Hao; Yang, Sam Y. S.; Xiao, Ti Qiao; Mayo, Sherry C.; Wang, Yu Dan; Wang, Hai Peng

    2014-01-01

    A quantitative local computed tomography combined with data-constrained modelling has been developed. The method could improve distinctly the spatial resolution and the composition resolution in a sample larger than the field of view, for quantitative characterization of three-dimensional distributions of material compositions and void. Quantifying three-dimensional spatial distributions of pores and material compositions in samples is a key materials characterization challenge, particularly in samples where compositions are distributed across a range of length scales, and where such compositions have similar X-ray absorption properties, such as in coal. Consequently, obtaining detailed information within sub-regions of a multi-length-scale sample by conventional approaches may not provide the resolution and level of detail one might desire. Herein, an approach for quantitative high-definition determination of material compositions from X-ray local computed tomography combined with a data-constrained modelling method is proposed. The approach is capable of dramatically improving the spatial resolution and enabling finer details within a region of interest of a sample larger than the field of view to be revealed than by using conventional techniques. A coal sample containing distributions of porosity and several mineral compositions is employed to demonstrate the approach. The optimal experimental parameters are pre-analyzed. The quantitative results demonstrated that the approach can reveal significantly finer details of compositional distributions in the sample region of interest. The elevated spatial resolution is crucial for coal-bed methane reservoir evaluation and understanding the transformation of the minerals during coal processing. The method is generic and can be applied for three-dimensional compositional characterization of other materials

  13. 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 ...

  14. 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.

  15. Quark model and equivalent local potential

    International Nuclear Information System (INIS)

    Takeuchi, Sachiko; Shimizu, Kiyotaka

    2002-01-01

    In this paper, we investigate the short-range repulsion given by the quark cluster model employing an inverse scattering problem. We find that the local potential which reproduces the same phase shifts as those given by the quark cluster model has a strong repulsion at short distances in the NN 1 S 0 channel. There, however, appears an attractive pocket at very short distances due to a rather weak repulsive behavior at very high energy. This repulsion-attractive-pocket structure becomes more manifest in the channel which has an almost forbidden state, ΣN(T=3/2) 3 S 1 . In order to see what kinds of effects are important to reproduce the short-range repulsion in the quark cluster model, we investigate the contribution coming from the one-gluon-exchange potential and the normalization separately. It is clarified that the gluon exchange constructs the short-range repulsion in the NN 1 S 0 while the quark Pauli-blocking effect governs the feature of the repulsive behavior in the ΣN(T=3/2) 3 S 1 channel

  16. Model reduction of systems with localized nonlinearities.

    Energy Technology Data Exchange (ETDEWEB)

    Segalman, Daniel Joseph

    2006-03-01

    An LDRD funded approach to development of reduced order models for systems with local nonlinearities is presented. This method is particularly useful for problems of structural dynamics, but has potential application in other fields. The key elements of this approach are (1) employment of eigen modes of a reference linear system, (2) incorporation of basis functions with an appropriate discontinuity at the location of the nonlinearity. Galerkin solution using the above combination of basis functions appears to capture the dynamics of the system with a small basis set. For problems involving small amplitude dynamics, the addition of discontinuous (joint) modes appears to capture the nonlinear mechanics correctly while preserving the modal form of the predictions. For problems involving large amplitude dynamics of realistic joint models (macro-slip), the use of appropriate joint modes along with sufficient basis eigen modes to capture the frequencies of the system greatly enhances convergence, though the modal nature the result is lost. Also observed is that when joint modes are used in conjunction with a small number of elastic eigen modes in problems of macro-slip of realistic joint models, the resulting predictions are very similar to those of the full solution when seen through a low pass filter. This has significance both in terms of greatly reducing the number of degrees of freedom of the problem and in terms of facilitating the use of much larger time steps.

  17. 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.

  18. 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...

  19. 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

  20. 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.

  1. Iris Template Protection Based on Local Ranking

    Directory of Open Access Journals (Sweden)

    Dongdong Zhao

    2018-01-01

    Full Text Available Biometrics have been widely studied in recent years, and they are increasingly employed in real-world applications. Meanwhile, a number of potential threats to the privacy of biometric data arise. Iris template protection demands that the privacy of iris data should be protected when performing iris recognition. According to the international standard ISO/IEC 24745, iris template protection should satisfy the irreversibility, revocability, and unlinkability. However, existing works about iris template protection demonstrate that it is difficult to satisfy the three privacy requirements simultaneously while supporting effective iris recognition. In this paper, we propose an iris template protection method based on local ranking. Specifically, the iris data are first XORed (Exclusive OR operation with an application-specific string; next, we divide the results into blocks and then partition the blocks into groups. The blocks in each group are ranked according to their decimal values, and original blocks are transformed to their rank values for storage. We also extend the basic method to support the shifting strategy and masking strategy, which are two important strategies for iris recognition. We demonstrate that the proposed method satisfies the irreversibility, revocability, and unlinkability. Experimental results on typical iris datasets (i.e., CASIA-IrisV3-Interval, CASIA-IrisV4-Lamp, UBIRIS-V1-S1, and MMU-V1 show that the proposed method could maintain the recognition performance while protecting the privacy of iris data.

  2. Evaluation of local electric fields generated by transcranial direct current stimulation with an extracephalic reference electrode based on realistic 3D body modeling

    Science.gov (United States)

    Im, Chang-Hwan; Park, Ji-Hye; Shim, Miseon; Chang, Won Hyuk; Kim, Yun-Hee

    2012-04-01

    In this study, local electric field distributions generated by transcranial direct current stimulation (tDCS) with an extracephalic reference electrode were evaluated to address extracephalic tDCS safety issues. To this aim, we generated a numerical model of an adult male human upper body and applied the 3D finite element method to electric current conduction analysis. In our simulations, the active electrode was placed over the left primary motor cortex (M1) and the reference electrode was placed at six different locations: over the right temporal lobe, on the right supraorbital region, on the right deltoid, on the left deltoid, under the chin, and on the right buccinator muscle. The maximum current density and electric field intensity values in the brainstem generated by the extracephalic reference electrodes were comparable to, or even less than, those generated by the cephalic reference electrodes. These results suggest that extracephalic reference electrodes do not lead to unwanted modulation of the brainstem cardio-respiratory and autonomic centers, as indicated by recent experimental studies. The volume energy density was concentrated at the neck area by the use of deltoid reference electrodes, but was still smaller than that around the active electrode locations. In addition, the distributions of elicited cortical electric fields demonstrated that the use of extracephalic reference electrodes might allow for the robust prediction of cortical modulations with little dependence on the reference electrode locations.

  3. 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

  4. 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)

  5. 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.

  6. 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...

  7. Device-based local delivery of siRNA against mammalian target of rapamycin (mTOR) in a murine subcutaneous implant model to inhibit fibrous encapsulation.

    Science.gov (United States)

    Takahashi, Hironobu; Wang, Yuwei; Grainger, David W

    2010-11-01

    Fibrous encapsulation of surgically implanted devices is associated with elevated proliferation and activation of fibroblasts in tissues surrounding these implants, frequently causing foreign body complications. Here we test the hypothesis that inhibition of the expression of mammalian target of rapamycin (mTOR) in fibroblasts can mitigate the soft tissue implant foreign body response by suppressing fibrotic responses around implants. In this study, mTOR was knocked down using small interfering RNA (siRNA) conjugated with branched polyethylenimine (bPEI) in fibroblastic lineage cells in serum-based cell culture as shown by both gene and protein analysis. This mTOR knock-down led to an inhibition in fibroblast proliferation by 70% and simultaneous down-regulation in the expression of type I collagen in fibroblasts in vitro. These siRNA/bPEI complexes were released from poly(ethylene glycol) (PEG)-based hydrogel coatings surrounding model polymer implants in a subcutaneous rodent model in vivo. No significant reduction in fibrous capsule thickness and mTOR expression in the foreign body capsules were observed. The siRNA inefficacy in this in vivo implant model was attributed to siRNA dosing limitations in the gel delivery system, and lack of targeting ability of the siRNA complex specifically to fibroblasts. While in vitro data supported mTOR knock-down in fibroblast cultures, in vivo siRNA delivery must be further improved to produce clinically relevant effects on fibrotic encapsulation around implants. Copyright © 2010 Elsevier B.V. All rights reserved.

  8. 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...

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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

  15. Infrared Beacons based Localization of Mobile Robot

    Czech Academy of Sciences Publication Activity Database

    Krejsa, Jiří; Věchet, Stanislav

    2012-01-01

    Roč. 117, č. 1 (2012), s. 17-22 ISSN 1392-1215 Institutional research plan: CEZ:AV0Z20760514 Keywords : mobile robot localization * extended Kalman filter * autonomous mobile robot Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.411, year: 2012 http://www.eejournal.ktu.lt/index.php/elt/article/view/1046

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Modelling of plastic flow localization and damage development in friction stir welded 6005A aluminium alloy using physics based strain hardening law

    DEFF Research Database (Denmark)

    Nielsen, Kim Lau; Pardoen, Thomas; Tvergaard, Viggo

    2010-01-01

    of these zones was extracted from micro-tensile specimens cut parallel to the welding direction. The measured material properties and weld topology were introduced into a 3D finite element model, fully coupled with the damage model. A Voce law hardening model involving a constant stage IV is used within...

  1. 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.

  2. 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.

  3. 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)

  4. Jet-Based Local Image Descriptors

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Darkner, Sune; Dahl, Anders Lindbjerg

    2012-01-01

    We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on ...

  5. 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

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    Jiayin Liu

    2017-06-01

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

  8. 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.

  9. Telehealth-based model of care redesign to facilitate local fitting and management of patients with a spinal fracture requiring a thoracic lumbar sacral orthosis in rural hospitals in New South Wales.

    Science.gov (United States)

    Gallagher, Ryan; Giles, Michelle; Morison, Jane; Henderson, Judith

    2018-03-23

    To develop and implement a telehealth-based model of care for spinal fractures requiring management with thoracic lumbar sacral orthoses that eliminates the need for transfer to a metropolitan tertiary referral hospital. Pre-post design observational study evaluating model of care implementation. Rural referral hospitals in a large NSW region covering metropolitan, rural and remote hospitals. Patients presenting with a thoracic or lumbar spine fracture requiring thoracic lumbar sacral orthoses management and rural clinicians caring for them. Number of patients managed in rural hospitals without transfer to a metropolitan tertiary referral hospital; length of stay and related cost efficiencies; clinicians' perceived skills, knowledge and confidence levels. Model of care was implemented with clinical and system governance processes; and educational workshops across eight rural hospitals. A total of 81 patients managed in rural hospitals under this model between July 2013 and June 2016 without transfer were included in this study. Mean length of stay reduced from nine to four days. Hospital transfers were eliminated from the patient journey, totalling 24 324 km. Workshops were attended by 71 clinicians from nine rural hospitals and survey findings indicated a significant increase in staff knowledge, skill and confidence post education. Cost efficiencies were gained by eliminating 162 inter-hospital transfers and 405 patient bed days. This model has streamlined patient journeys and reduced transfers and travel, enabling rural clinicians to provide specialised services in local communities and facilitating timely evidence-based care in local communities without any adverse events. © 2018 National Rural Health Alliance Ltd.

  10. 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

  11. Non-local modeling of materials

    DEFF Research Database (Denmark)

    Niordson, Christian Frithiof

    2002-01-01

    Numerical studies of non-local plasticity effects on different materials and problems are carried out. Two different theories are used. One is of lower order in that it retains the structure of a conventional plasticity boundary value problem, while the other is of higher order and employs higher...... order stresses as work conjugates to higher order strains and uses higher order boundary conditions. The influence of internal material length parameters is studied, and the effects of higher order boundary conditions are analyzed. The focus of the thesis is on metal-matrix composites, and non...

  12. 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.

  13. In-cell protease assay systems based on trans-localizing molecular beacon proteins using HCV protease as a model system.

    Directory of Open Access Journals (Sweden)

    Jeong Hee Kim

    Full Text Available This study describes a sensitive in-cell protease detection system that enables direct fluorescence detection of a target protease and its inhibition inside living cells. This live-cell imaging system provides a fluorescent molecular beacon protein comprised of an intracellular translocation signal sequence, a protease-specific cleavage sequence, and a fluorescent tag sequence(s. The molecular beacon protein is designed to change its intracellular localization upon cleavage by a target protease, i.e., from the cytosol to a subcellular organelle or from a subcellular organelle to the cytosol. Protease activity can be monitored at the single cell level, and accordingly the entire cell population expressing the protease can be accurately enumerated. The clear cellular change in fluorescence pattern makes this system an ideal tool for various life science and drug discovery research, including high throughput and high content screening applications.

  14. 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...

  15. 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.

  16. 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).

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. Formulation of strongly non-local, non-isothermal dynamics for heterogeneous solids based on the GENERIC with application to phase-field modeling

    NARCIS (Netherlands)

    Hütter, M.; Svendsen, B.

    2017-01-01

    The purpose of the current work is the formulation of models for conservative and non-conservative dynamics in solid systems with the help of the General Equation for the Non-Equilibrium Reversible-Irreversible Coupling (GENERIC: e.g., Grmela and Öttinger, Phys. Rev. E 56(6), 6620 (1997); Öttinger

  2. 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.)

  3. 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)

  4. 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)

  5. 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...

  6. 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)

  7. A Novel Murine Candidiasis Model with Severe Colonization in the Stomach Induced by N-acetylglucosamine-treatment and Its Scoring System Based on Local Characteristic Stomach Symptoms.

    Science.gov (United States)

    Ishijima, Sanae A; Abe, Shigeru

    2015-01-01

    We developed a novel murine candidiasis model of the gastrointestinal tract using N-acetylglucosamine ( GlcNAc ) as a tool to aggravate symptoms. Forty-eight hours after intragastrically inoculating Candida albicans cells to immunosuppressed and GlcNAc-treated mice, vigorously accumulating patchy whitish plaques were observed on their inner stomach surface. Candida cells colonizing the plaques consisted of both yeast and mycelia, and were directly stained with Calcofluor White M2R. Aggravation of the candidiasis symptoms was dependent on GlcNAc concentration in drinking water, wherein administration of 50 mM GlcNAc not only severely worsened stomach symptoms, but also significantly increased Candida cell number in the stomach and small intestine. The aggravation effect of GlcNAc was enhanced by addition of sedative chemical chlorpromazine chloride after inoculation. In order to semi-quantitatively assess colonization by Candida in the stomach, we devised a new symptom scoring system that represents the extent of the patchy whitish plaques on the mucosal epithelium of the stomach. Histochemical analysis of Candida-infected tissues revealed not only a large amount of thick Candida mycelia invading mucosal epithelial stomach tissues but also infiltrating inflammatory cells. These results suggest that this murine gastrointestinal candidiasis model could serve as a useful tool for evaluating the protective activity of antifungal agents, probiotics, or functional foods against gastrointestinal candidiasis. Furthermore, from another point of view, this novel murine model could also be used to analyze the pathological mechanisms behind the translocation of C. albicans across intestinal barriers, which results in systemic Candida dissemination and infection.

  8. 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

  9. Modelling of Local Necking and Fracture in Aluminium Alloys

    International Nuclear Information System (INIS)

    Achani, D.; Eriksson, M.; Hopperstad, O. S.; Lademo, O.-G.

    2007-01-01

    Non-linear Finite Element simulations are extensively used in forming and crashworthiness studies of automotive components and structures in which fracture need to be controlled. For thin-walled ductile materials, the fracture-related phenomena that must be properly represented are thinning instability, ductile fracture and through-thickness shear instability. Proper representation of the fracture process relies on the accuracy of constitutive and fracture models and their parameters that need to be calibrated through well defined experiments. The present study focuses on local necking and fracture which is of high industrial importance, and uses a phenomenological criterion for modelling fracture in aluminium alloys. As an accurate description of plastic anisotropy is important, advanced phenomenological constitutive equations based on the yield criterion YLD2000/YLD2003 are used. Uniaxial tensile tests and disc compression tests are performed for identification of the constitutive model parameters. Ductile fracture is described by the Cockcroft-Latham fracture criterion and an in-plane shear tests is performed to identify the fracture parameter. The reason is that in a well designed in-plane shear test no thinning instability should occur and it thus gives more direct information about the phenomenon of ductile fracture. Numerical simulations have been performed using a user-defined material model implemented in the general-purpose non-linear FE code LS-DYNA. The applicability of the model is demonstrated by correlating the predicted and experimental response in the in-plane shear tests and additional plane strain tension tests

  10. An integrated tiered service delivery model (ITSDM based on local CD4 testing demands can improve turn-around times and save costs whilst ensuring accessible and scalable CD4 services across a national programme.

    Directory of Open Access Journals (Sweden)

    Deborah K Glencross

    Full Text Available The South African National Health Laboratory Service (NHLS responded to HIV treatment initiatives with two-tiered CD4 laboratory services in 2004. Increasing programmatic burden, as more patients access anti-retroviral therapy (ART, has demanded extending CD4 services to meet increasing clinical needs. The aim of this study was to review existing services and develop a service-model that integrated laboratory-based and point-of-care testing (POCT, to extend national coverage, improve local turn-around/(TAT and contain programmatic costs.NHLS Corporate Data Warehouse CD4 data, from 60-70 laboratories and 4756 referring health facilities was reviewed for referral laboratory workload, respective referring facility volumes and related TAT, from 2009-2012.An integrated tiered service delivery model (ITSDM is proposed. Tier-1/POCT delivers CD4 testing at single health-clinics providing ART in hard-to-reach areas (350-1500 tests/day, serving ≥ 200 health-clinics. Tier-6 provides national support for standardisation, harmonization and quality across the organization.The ITSDM offers improved local TAT by extending CD4 services into rural/remote areas with new Tier-3 or Tier-2/POC-Hub services installed in existing community laboratories, most with developed infrastructure. The advantage of lower laboratory CD4 costs and use of existing infrastructure enables subsidization of delivery of more expensive POC services, into hard-to-reach districts without reasonable access to a local CD4 laboratory. Full ITSDM implementation across 5 service tiers (as opposed to widespread implementation of POC testing to extend service can facilitate sustainable 'full service coverage' across South Africa, and save>than R125 million in HIV/AIDS programmatic costs. ITSDM hierarchical parental-support also assures laboratory/POC management, equipment maintenance, quality control and on-going training between tiers.

  11. 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.

  12. 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...

  13. Base Station Performance Model

    OpenAIRE

    Walsh, Barbara; Farrell, Ronan

    2005-01-01

    At present the testing of power amplifiers within base station transmitters is limited to testing at component level as opposed to testing at the system level. While the detection of catastrophic failure is possible, that of performance degradation is not. This paper proposes a base station model with respect to transmitter output power with the aim of introducing system level monitoring of the power amplifier behaviour within the base station. Our model reflects the expe...

  14. 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.

  15. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  16. Character Education Based On Local Wisdom For the Prisoners

    Directory of Open Access Journals (Sweden)

    Muh Sukemi Buchory

    2018-01-01

    Full Text Available This research aims at revealing the existence of character education based on the local wisdom for the prisoners. The subject of this research is the prisoner inhabitant in Wirogunan Prison and Narcotics pakem in Sleman Yogyakarta. The data were gained by interviewing, documenting and demonstrating. The data were analyzed qualitative and quantitative descriptively. The results of this research are: (1 The training of Tembang Maca Pat and Javanese MC are equivalently adapted, (2 The character values being shaped: believe in God, responsibility, respect, fairness, confidence, faithfulness, discipline, careness, spirituality, manners, intelligence, emotion control, character building, the increase of social participants; (3 The competence on Tembang Maca Pat and MC of Javanese can be used as professional earning in society and also can be used as educational model for the prisoners.

  17. 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

  18. 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

  19. Locally processed roasted-maize-based weaning foods fortified with ...

    African Journals Online (AJOL)

    Locally processed roasted-maize-based weaning foods fortified with legumes: factors ... African Journal of Food, Agriculture, Nutrition and Development ... Tom Brown (roasted-maize porridge) is one of the traditional weaning foods in Ghana.

  20. 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...

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. Transorbital target localization in the porcine model

    Science.gov (United States)

    DeLisi, Michael P.; Mawn, Louise A.; Galloway, Robert L.

    2013-03-01

    Current pharmacological therapies for the treatment of chronic optic neuropathies such as glaucoma are often inadequate due to their inability to directly affect the optic nerve and prevent neuron death. While drugs that target the neurons have been developed, existing methods of administration are not capable of delivering an effective dose of medication along the entire length of the nerve. We have developed an image-guided system that utilizes a magnetically tracked flexible endoscope to navigate to the back of the eye and administer therapy directly to the optic nerve. We demonstrate the capabilities of this system with a series of targeted surgical interventions in the orbits of live pigs. Target objects consisted of NMR microspherical bulbs with a volume of 18 μL filled with either water or diluted gadolinium-based contrast, and prepared with either the presence or absence of a visible coloring agent. A total of 6 pigs were placed under general anesthesia and two microspheres of differing color and contrast content were blindly implanted in the fat tissue of each orbit. The pigs were scanned with T1-weighted MRI, image volumes were registered, and the microsphere containing gadolinium contrast was designated as the target. The surgeon was required to navigate the flexible endoscope to the target and identify it by color. For the last three pigs, a 2D/3D registration was performed such that the target's coordinates in the image volume was noted and its location on the video stream was displayed with a crosshair to aid in navigation. The surgeon was able to correctly identify the target by color, with an average intervention time of 20 minutes for the first three pigs and 3 minutes for the last three.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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

  12. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Sarfraz, M.

    2004-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  13. 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.

  14. 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.

  15. 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.

  16. 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)

  17. Cluster-based localization and tracking in ubiquitous computing systems

    CERN Document Server

    Martínez-de Dios, José Ramiro; Torres-González, Arturo; Ollero, Anibal

    2017-01-01

    Localization and tracking are key functionalities in ubiquitous computing systems and techniques. In recent years a very high variety of approaches, sensors and techniques for indoor and GPS-denied environments have been developed. This book briefly summarizes the current state of the art in localization and tracking in ubiquitous computing systems focusing on cluster-based schemes. Additionally, existing techniques for measurement integration, node inclusion/exclusion and cluster head selection are also described in this book.

  18. Modeling of Local Magnetic Field Enhancements within Solar Flux Ropes

    OpenAIRE

    Romashets, E; Vandas, M; Poedts, Stefaan

    2010-01-01

    To model and study local magnetic-field enhancements in a solar flux rope we consider the magnetic field in its interior as a superposition of two linear (constant alpha) force-free magnetic-field distributions, viz. a global one, which is locally similar to a part of the cylinder, and a local torus-shaped magnetic distribution. The newly derived solution for a toroid with an aspect ratio close to unity is applied. The symmetry axis of the toroid and that of the cylinder may or may not coinci...

  19. 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.

  20. A Strong Self-adaptivity Localization Algorithm Based on Gray Prediction Model for Mobile Nodes%一种使用灰度预测模型的强自适应性移动节点定位算法

    Institute of Scientific and Technical Information of China (English)

    单志龙; 刘兰辉; 张迎胜; 黄广雄

    2014-01-01

    定位技术是无线传感器网络的关键技术,而关于移动节点的定位又是其中的技术难点。该文针对移动节点定位问题提出基于灰度预测模型的强自适应性移动节点定位算法(GPLA)。算法在基于蒙特卡罗定位思想的基础上,利用灰度预测模型进行运动预测,精确采样区域,用估计距离进行滤波,提高采样粒子的有效性,通过限制性的线性交叉操作来生成新粒子,从而加快样本生成,减少采样次数,提高算法效率。仿真实验中,该算法在通信半径、锚节点密度、样本大小等条件变化的情况下,表现出较好的性能与较强的自适应性。%Localization of sensor nodes is an important issue in Wireless Sensor Networks (WSNs), and positioning of the mobile nodes is one of the difficulties. To deal with this issue, a strong self-adaptive Localization Algorithm based on Gray Prediction model for mobile nodes (GPLA) is proposed. On the background of Monte Carlo Localization Algoritm, gray prediction model is used in GPLA, which can accurate sampling area is used to predict nodes motion situation. In filtering process, estimated distance is taken to improve the validity of the sample particles. Finally, restrictive linear crossover is used to generate new particles, which can accelerate the sampling process, reduce the times of sampling and heighten the efficiency of GPLA. Simulation results show that the algorithm has excellent performance and strong self-adaptivity in different communication radius, anchor node, sample size, and other conditions.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. 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.

  3. 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.

  4. Modelling the flow structure in local scour around bridge pier

    International Nuclear Information System (INIS)

    Ghani, U.

    2014-01-01

    Bridge pier scouring is an important issue of any bridge design work. If it is not taken into account properly, then results will be disastrous. A number of bridges have failed due to clear water local scouring of piers. This research paper presents a numerical model study in which an attempt has been made to explore the flow variables which exist in and around a scoured bridge pier. A finite volume based model of bridge pier was developed using 3D (Three Dimensional) numerical code FLUENT and GAMBIT. After validation process, different discharge values were considered and its impact on three dimensional characteristics of flow such as stream-wise velocities on longitudinal and transverse sections, turbulance circulation cells, and boundary shear stresses was investigated. It was observed that increasing the discharge results in more turbulance around the pier on its downstream side and turbulence properties are intensified in such a situation. However, the primary velocities on the downstream side remain almost unchanged. The results have been presented in the form of contours, vector of primary velocities and x-y plots of bed shear stresses. This study can be used for enhanced understanding of flow features and improvement of formulae for prediction of scour holes around piers. (author)

  5. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  6. 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...

  7. Alveolar bone-loss area localization in periodontitis radiographs based on threshold segmentation with a hybrid feature fused of intensity and the H-value of fractional Brownian motion model.

    Science.gov (United States)

    Lin, P L; Huang, P W; Huang, P Y; Hsu, H C

    2015-10-01

    Periodontitis involves progressive loss of alveolar bone around the teeth. Hence, automatic alveolar bone-loss (ABL) measurement in periapical radiographs can assist dentists in diagnosing such disease. In this paper, we propose an effective method for ABL area localization and denote it as ABLIfBm. ABLIfBm is a threshold segmentation method that uses a hybrid feature fused of both intensity and texture measured by the H-value of fractional Brownian motion (fBm) model, where the H-value is the Hurst coefficient in the expectation function of a fBm curve (intensity change) and is directly related to the value of fractal dimension. Adopting leave-one-out cross validation training and testing mechanism, ABLIfBm trains weights for both features using Bayesian classifier and transforms the radiograph image into a feature image obtained from a weighted average of both features. Finally, by Otsu's thresholding, it segments the feature image into normal and bone-loss regions. Experimental results on 31 periodontitis radiograph images in terms of mean true positive fraction and false positive fraction are about 92.5% and 14.0%, respectively, where the ground truth is provided by a dentist. The results also demonstrate that ABLIfBm outperforms (a) the threshold segmentation method using either feature alone or a weighted average of the same two features but with weights trained differently; (b) a level set segmentation method presented earlier in literature; and (c) segmentation methods based on Bayesian, K-NN, or SVM classifier using the same two features. Our results suggest that the proposed method can effectively localize alveolar bone-loss areas in periodontitis radiograph images and hence would be useful for dentists in evaluating degree of bone-loss for periodontitis patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. 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

  9. 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.

  10. 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.

  11. 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...

  12. Chemical analysis and base-promoted hydrolysis of locally ...

    African Journals Online (AJOL)

    Abstract. The study was on the chemical analysis and base- promoted hydrolysis of extracted shea nut fat. The local method of extraction of the shea nut oil was employed in comparison with literature report. A simple cold-process alkali hydrolysis of the shea nut oil was used in producing the soap. The chemical analysis of ...

  13. Novel Ethernet Based Optical Local Area Networks for Computer Interconnection

    NARCIS (Netherlands)

    Radovanovic, Igor; van Etten, Wim; Taniman, R.O.; Kleinkiskamp, Ronny

    2003-01-01

    In this paper we present new optical local area networks for fiber-to-the-desk application. Presented networks are expected to bring a solution for having optical fibers all the way to computers. To bring the overall implementation costs down we have based our networks on short-wavelength optical

  14. Constraint-based local search for container stowage slot planning

    DEFF Research Database (Denmark)

    Pacino, Dario; Jensen, Rune Møller; Bebbington, Tom

    2012-01-01

    -sea vessels. This paper describes the constrained-based local search algorithm used in the second phase of this approach where individual containers are assigned to slots in each bay section. The algorithm can solve this problem in an average of 0.18 seconds per bay, corresponding to a 20 seconds runtime...

  15. Algebraic models of local period maps and Yukawa algebras

    Science.gov (United States)

    Bandiera, Ruggero; Manetti, Marco

    2018-02-01

    We describe some L_{∞} model for the local period map of a compact Kähler manifold. Applications include the study of deformations with associated variation of Hodge structure constrained by certain closed strata of the Grassmannian of the de Rham cohomology. As a by-product, we obtain an interpretation in the framework of deformation theory of the Yukawa coupling.

  16. VCE Model of Community, Local, Regional Food Systems

    OpenAIRE

    Niewolny, Kim

    2016-01-01

    This document is a chart illustrating the Virginia Cooperative Extension model for food systems at the community, local and regional level. This chart shows an interrelationship between basic and applied research, leveraging of resources and opportunities, communication and marketing, assessment, evaluation and impact, knowledge, skills, and social change, facilitation of partnerships, and also teaching.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Skull base tumor model.

    Science.gov (United States)

    Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

    2010-11-01

    Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

  3. 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

  4. Local and Global Gestalt Laws: A Neurally Based Spectral Approach.

    Science.gov (United States)

    Favali, Marta; Citti, Giovanna; Sarti, Alessandro

    2017-02-01

    This letter presents a mathematical model of figure-ground articulation that takes into account both local and global gestalt laws and is compatible with the functional architecture of the primary visual cortex (V1). The local gestalt law of good continuation is described by means of suitable connectivity kernels that are derived from Lie group theory and quantitatively compared with long-range connectivity in V1. Global gestalt constraints are then introduced in terms of spectral analysis of a connectivity matrix derived from these kernels. This analysis performs grouping of local features and individuates perceptual units with the highest salience. Numerical simulations are performed, and results are obtained by applying the technique to a number of stimuli.

  5. Visual Appearance-Based Unmanned Vehicle Sequential Localization

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. 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....

  8. 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....

  9. Mathematical models and methods of localized interaction theory

    CERN Document Server

    Bunimovich, AI

    1995-01-01

    The interaction of the environment with a moving body is called "localized" if it has been found or assumed that the force or/and thermal influence of the environment on each body surface point is independent and can be determined by the local geometrical and kinematical characteristics of this point as well as by the parameters of the environment and body-environment interactions which are the same for the whole surface of contact.Such models are widespread in aerodynamics and gas dynamics, covering supersonic and hypersonic flows, and rarefied gas flows. They describe the influence of light

  10. Application of modeling to local chemistry in PWR steam generators

    International Nuclear Information System (INIS)

    Fauchon, C.; Millett, P.J.; Ollar, P.

    1998-01-01

    Localized corrosion of the SG tubes and other components is due to the presence of an aggressive environment in local crevices and occluded regions. In crevices and on vertical and horizontal tube surfaces, corrosion products and particulate matter can accumulate in the form of porous deposits. The SG water contains impurities at extremely low levels (ppb). Low levels of non-volatile impurities, however, can be efficiently concentrated in crevices and sludge piles by a thermal hydraulic mechanism. The temperature gradient across the SG tube coupled with local flow starvation, produces local boiling in the sludge and crevices. Since mass transfer processes are inhibited in these geometries, the residual liquid becomes enriched in many of the species present in the SG water. The resulting concentrated solutions have been shown to be aggressive and can corrode the SG materials. This corrosion may occur under various conditions which result in different types of attack such as pitting, stress corrosion cracking, wastage and denting. A major goal of EPRI's research program has been the development of models of the concentration process and the resulting chemistry. An improved understanding should eventually allow utilities to reduce or eliminate the corrosion by the appropriate manipulation of the steam generator water chemistry and or crevice conditions. The application of these models to experimental data obtained for prototypical SG tube support crevices is described in this paper. The models adequately describe the key features of the experimental data allowing extrapolations to be made to plant conditions. (author)

  11. 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

  12. 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)

  13. Simplified local density model for adsorption over large pressure ranges

    International Nuclear Information System (INIS)

    Rangarajan, B.; Lira, C.T.; Subramanian, R.

    1995-01-01

    Physical adsorption of high-pressure fluids onto solids is of interest in the transportation and storage of fuel and radioactive gases; the separation and purification of lower hydrocarbons; solid-phase extractions; adsorbent regenerations using supercritical fluids; supercritical fluid chromatography; and critical point drying. A mean-field model is developed that superimposes the fluid-solid potential on a fluid equation of state to predict adsorption on a flat wall from vapor, liquid, and supercritical phases. A van der Waals-type equation of state is used to represent the fluid phase, and is simplified with a local density approximation for calculating the configurational energy of the inhomogeneous fluid. The simplified local density approximation makes the model tractable for routine calculations over wide pressure ranges. The model is capable of prediction of Type 2 and 3 subcritical isotherms for adsorption on a flat wall, and shows the characteristic cusplike behavior and crossovers seen experimentally near the fluid critical point

  14. Using long-term ground-based HSRL and geostationary observations in combination with model re-analysis to help disentangle local and long-range transported aerosols in Seoul, South Korea

    Science.gov (United States)

    Phillips, C.; Holz, R.; Eloranta, E. W.; Reid, J. S.; Kim, S. W.; Kuehn, R.; Marais, W.

    2017-12-01

    The University of Wisconsin High Spectral Resolution Lidar (HSRL) has been continuously operating at Seoul National University as part of the Korea-United States Air Quality Study (KORUS-AQ). The instrument was installed in March of 2016 and continues to operate as of August 2017, providing a truly unique data set to monitor aerosol and cloud properties. With its capability to separate the molecular and particulate scattering, the HSRL is able to detect extremely thin aerosol layers with sub-molecular scattering sensitivity. The system deployed in Seoul has depolarization measurements at 532 nm as well as a near IR channel at 1064 nm providing discrimination between dust, smoke, pollution, water clouds, and ice clouds. As will be presented, these capabilities can be used to produce three channel combined RGB images that provide visualization of small changes in the aerosol properties. A primary motivation of KORUS-AQ was to determine the relative effects of transported pollution and local pollution on air quality in Seoul. We hypothesize that HSRL-based image analysis algorithms combined with satellite and model re-analysis has the potential to identify cases when remote sources of aerosols and pollution are advected into the boundary layer with impacts to the surface air quality. To facilitate this research we have developed the capability to combine ten-minute geostationary imagery from Himawari-8, nearby radiosondes, model output, surface PM measurements, and AERONET data over the HSRL site. On a case-by-case basis, it is possible to separate layers of aerosols with different scattering properties using these tools. Additionally, a preliminary year-long aerosol climatology with integrated geo-stationary retrievals and modeling data will be presented. The focus is on investigating correlations between the HSRL aerosol measurements (depolarization, color ratio, extinction, and lidar ratio) with the model output and aerosol sources. This analysis will use recently

  15. A non-local model analysis of heat pulse propagation

    International Nuclear Information System (INIS)

    Iwasaki, T.; Itoh, S.I.; Yagi, M.; Stroth, U.

    1998-01-01

    The anomalous transport in high temperature plasma has been studied for a long time, from the beginning of the fusion research. Since the electron channel in stellarators and tokamaks is clearly anomalous, it is of fundamental importance to investigate the electron heat diffusivity coefficient, χ e and to understand the physical mechanism. Recently, the experimental data for the transient transport of the heat pulse propagation in fusion plasma has been accumulated. An observation was reported on W7-AS which the heat flux changes faster than the change of the temperature profile, responding to the switching on off of the central heating power. The observation on the transient response has simulated the transport modeling, e.g., the critical marginality which implies the existence of a finite threshold in ∇T for the excitation of the turbulence, or the model in which the thermal conductivity is assumed to depend on the heating power. Extensive study is made by use of these models, and the critical marginally model seems to be insufficient to explain various transient transport. The rapid change of the plasma state and its hysteresis nature were successfully modeled by a heating-power-dependent model. The foundation of this model, however, is left for future work. The development of the transport modeling remains to be an urgent problem. In this paper, we investigate the role of the non-locality of the plasma transport in the study of the heat pulse propagation. For this purpose, a model equation is proposed, in which the non-local effect is taken into account in the heat flux. The properties of this model are investigated by performing a transport simulation. The organization of this paper is as follows: In Sec. II, the model equation is proposed and the properties of the model are explained. Using the model equation, the switching on off experiment is simulated in Sec. III. Summary and discussion are given in Sec. IV. (author)

  16. Search-free license plate localization based on saliency and local variance estimation

    Science.gov (United States)

    Safaei, Amin; Tang, H. L.; Sanei, S.

    2015-02-01

    In recent years, the performance and accuracy of automatic license plate number recognition (ALPR) systems have greatly improved, however the increasing number of applications for such systems have made ALPR research more challenging than ever. The inherent computational complexity of search dependent algorithms remains a major problem for current ALPR systems. This paper proposes a novel search-free method of localization based on the estimation of saliency and local variance. Gabor functions are then used to validate the choice of candidate license plate. The algorithm was applied to three image datasets with different levels of complexity and the results compared with a number of benchmark methods, particularly in terms of speed. The proposed method outperforms the state of the art methods and can be used for real time applications.

  17. The Toggle Local Planner for sampling-based motion planning

    KAUST Repository

    Denny, Jory

    2012-05-01

    Sampling-based solutions to the motion planning problem, such as the probabilistic roadmap method (PRM), have become commonplace in robotics applications. These solutions are the norm as the dimensionality of the planning space grows, i.e., d > 5. An important primitive of these methods is the local planner, which is used for validation of simple paths between two configurations. The most common is the straight-line local planner which interpolates along the straight line between the two configurations. In this paper, we introduce a new local planner, Toggle Local Planner (Toggle LP), which extends local planning to a two-dimensional subspace of the overall planning space. If no path exists between the two configurations in the subspace, then Toggle LP is guaranteed to correctly return false. Intuitively, more connections could be found by Toggle LP than by the straight-line planner, resulting in better connected roadmaps. As shown in our results, this is the case, and additionally, the extra cost, in terms of time or storage, for Toggle LP is minimal. Additionally, our experimental analysis of the planner shows the benefit for a wide array of robots, with DOF as high as 70. © 2012 IEEE.

  18. Face detection and facial feature localization using notch based templates

    International Nuclear Information System (INIS)

    Qayyum, U.

    2007-01-01

    We present a real time detection off aces from the video with facial feature localization as well as the algorithm capable of differentiating between the face/non-face patterns. The need of face detection and facial feature localization arises in various application of computer vision, so a lot of research is dedicated to come up with a real time solution. The algorithm should remain simple to perform real time whereas it should not compromise on the challenges encountered during the detection and localization phase, keeping simplicity and all challenges i.e. algorithm invariant to scale, translation, and (+-45) rotation transformations. The proposed system contains two parts. Visual guidance and face/non-face classification. The visual guidance phase uses the fusion of motion and color cues to classify skin color. Morphological operation with union-structure component labeling algorithm extracts contiguous regions. Scale normalization is applied by nearest neighbor interpolation method to avoid the effect of different scales. Using the aspect ratio of width and height size. Region of Interest (ROI) is obtained and then passed to face/non-face classifier. Notch (Gaussian) based templates/ filters are used to find circular darker regions in ROI. The classified face region is handed over to facial feature localization phase, which uses YCbCr eyes/lips mask for face feature localization. The empirical results show an accuracy of 90% for five different videos with 1000 face/non-face patterns and processing rate of proposed algorithm is 15 frames/sec. (author)

  19. 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

  20. A block matching-based registration algorithm for localization of locally advanced lung tumors

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D., E-mail: gdhugo@vcu.edu [Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, 23298 (United States)

    2014-04-15

    Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm{sup 3}), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0

  1. A block matching-based registration algorithm for localization of locally advanced lung tumors

    International Nuclear Information System (INIS)

    Robertson, Scott P.; Weiss, Elisabeth; Hugo, Geoffrey D.

    2014-01-01

    Purpose: To implement and evaluate a block matching-based registration (BMR) algorithm for locally advanced lung tumor localization during image-guided radiotherapy. Methods: Small (1 cm 3 ), nonoverlapping image subvolumes (“blocks”) were automatically identified on the planning image to cover the tumor surface using a measure of the local intensity gradient. Blocks were independently and automatically registered to the on-treatment image using a rigid transform. To improve speed and robustness, registrations were performed iteratively from coarse to fine image resolution. At each resolution, all block displacements having a near-maximum similarity score were stored. From this list, a single displacement vector for each block was iteratively selected which maximized the consistency of displacement vectors across immediately neighboring blocks. These selected displacements were regularized using a median filter before proceeding to registrations at finer image resolutions. After evaluating all image resolutions, the global rigid transform of the on-treatment image was computed using a Procrustes analysis, providing the couch shift for patient setup correction. This algorithm was evaluated for 18 locally advanced lung cancer patients, each with 4–7 weekly on-treatment computed tomography scans having physician-delineated gross tumor volumes. Volume overlap (VO) and border displacement errors (BDE) were calculated relative to the nominal physician-identified targets to establish residual error after registration. Results: Implementation of multiresolution registration improved block matching accuracy by 39% compared to registration using only the full resolution images. By also considering multiple potential displacements per block, initial errors were reduced by 65%. Using the final implementation of the BMR algorithm, VO was significantly improved from 77% ± 21% (range: 0%–100%) in the initial bony alignment to 91% ± 8% (range: 56%–100%;p < 0.001). Left

  2. Integrating Globality and Locality for Robust Representation Based Classification

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2014-01-01

    Full Text Available The representation based classification method (RBCM has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC method and collaborative representation classification (CRC method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation.” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.

  3. 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.

  4. 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.

  5. Local TEC Modelling and Forecasting using Neural Networks

    Science.gov (United States)

    Tebabal, A.; Radicella, S. M.; Nigussie, M.; Damtie, B.; Nava, B.; Yizengaw, E.

    2017-12-01

    Abstract Modelling the Earth's ionospheric characteristics is the focal task for the ionospheric community to mitigate its effect on the radio communication, satellite navigation and technologies. However, several aspects of modelling are still challenging, for example, the storm time characteristics. This paper presents modelling efforts of TEC taking into account solar and geomagnetic activity, time of the day and day of the year using neural networks (NNs) modelling technique. The NNs have been designed with GPS-TEC measured data from low and mid-latitude GPS stations. The training was conducted using the data obtained for the period from 2011 to 2014. The model prediction accuracy was evaluated using data of year 2015. The model results show that diurnal and seasonal trend of the GPS-TEC is well reproduced by the model for the two stations. The seasonal characteristics of GPS-TEC is compared with NN and NeQuick 2 models prediction when the latter one is driven by the monthly average value of solar flux. It is found that NN model performs better than the corresponding NeQuick 2 model for low latitude region. For the mid-latitude both NN and NeQuick 2 models reproduce the average characteristics of TEC variability quite successfully. An attempt of one day ahead forecast of TEC at the two locations has been made by introducing as driver previous day solar flux and geomagnetic index values. The results show that a reasonable day ahead forecast of local TEC can be achieved.

  6. Free locally convex spaces with a small base

    Czech Academy of Sciences Publication Activity Database

    Gabriyelyan, S.; Kąkol, Jerzy

    2017-01-01

    Roč. 111, č. 2 (2017), s. 575-585 ISSN 1578-7303 R&D Projects: GA ČR GF16-34860L Institutional support: RVO:67985840 Keywords : compact resolution * free locally convex space * G-base Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 0.690, year: 2016 http://link.springer.com/article/10.1007%2Fs13398-016-0315-1

  7. Biogas Filter Based on Local Natural Zeolite Materials

    OpenAIRE

    Krido Wahono, Satriyo; Anggo Rizal, Wahyu

    2014-01-01

    UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as ...

  8. 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.

  9. Smartphone-Based Cooperative Indoor Localization with RFID Technology

    Directory of Open Access Journals (Sweden)

    Fernando Seco

    2018-01-01

    Full Text Available In GPS-denied indoor environments, localization and tracking of people can be achieved with a mobile device such as a smartphone by processing the received signal strength (RSS of RF signals emitted from known location beacons (anchor nodes, combined with Pedestrian Dead Reckoning (PDR estimates of the user motion. An enhacement of this localization technique is feasible if the users themselves carry additional RF emitters (mobile nodes, and the cooperative position estimates of a group of persons incorporate the RSS measurements exchanged between users. We propose a centralized cooperative particle filter (PF formulation over the joint state of all users that permits to process RSS measurements from both anchor and mobile emitters, as well as PDR motion estimates and map information (if available to increase the overall positioning accuracy, particularly in regions with low density of anchor nodes. Smartphones are used as a convenient mobile platform for sensor measurements acquisition, low-level processing, and data transmission to a central unit, where cooperative localization processing takes place. The cooperative method is experimentally demonstrated with four users moving in an area of 1600 m 2 , with 7 anchor nodes comprised of active RFID (radio frequency identification tags, and additional mobile tags carried by each user. Due to the limited coverage provided by the anchor beacons, RSS-based individual localization is inaccurate (6.1 m median error, but this improves to 4.9 m median error with the cooperative PF. Further gains are produced if the PDR information is added to the filter: median error of 3.1 m (individual and 2.6 m (cooperative; and if map information is also considered, the results are 1.8 m (individual and 1.6 m (cooperative. Thus, for each version of the particle filter, cooperative localization outperforms individual localization in terms of positioning accuracy.

  10. Local models of Gauge Mediated Supersymmetry Breaking in String Theory

    CERN Document Server

    Garcia-Etxebarria, I; Uranga, Angel M; Garcia-Etxebarria, Inaki; Saad, Fouad; Uranga, Angel M.

    2006-01-01

    We describe local Calabi-Yau geometries with two isolated singularities at which systems of D3- and D7-branes are located, leading to chiral sectors corresponding to a semi-realistic visible sector and a hidden sector with dynamical supersymmetry breaking. We provide explicit models with a 3-family MSSM-like visible sector, and a hidden sector breaking supersymmetry at a meta-stable minimum. For singularities separated by a distance smaller than the string scale, this construction leads to a simple realization of gauge mediated supersymmetry breaking in string theory. The models are simple enough to allow the explicit computation of the massive messenger sector, using dimer techniques for branes at singularities. The local character of the configurations makes manifest the UV insensitivity of the supersymmetry breaking mediation.

  11. 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

  12. 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

  13. A realistic model for quantum theory with a locality property

    International Nuclear Information System (INIS)

    Eberhard, P.H.

    1987-04-01

    A model reproducing the predictions of relativistic quantum theory to any desired degree of accuracy is described in this paper. It involves quantities that are independent of the observer's knowledge, and therefore can be called real, and which are defined at each point in space, and therefore can be called local in a rudimentary sense. It involves faster-than-light, but not instantaneous, action at distance

  14. 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.

  15. 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.

  16. A local-area-network based radiation oncology microcomputer system

    International Nuclear Information System (INIS)

    Chu, W.K.; Taylor, T.K.; Kumar, P.P.; Imray, T.J.

    1985-01-01

    The application of computerized technology in the medical specialty of radiation oncology has gained wide acceptance in the past decade. Recognizing that most radiation oncology department personnel are familiar with computer operations and terminology, it appears reasonable to attempt to expand the computer's applications to other departmental activities, such as scheduling, record keeping, billing, treatment regimen and status, etc. Instead of sharing the processing capability available on the existent treatment minicomputer, the radiation oncology computer system is based upon a microcomputer local area network (LAN). The system was conceptualized in 1984 and completed in March 1985. This article outlines the LAN-based radiation oncology computer system

  17. Local field effects and metamaterials based on colloidal quantum dots

    International Nuclear Information System (INIS)

    Porvatkina, O V; Tishchenko, A A; Strikhanov, M N

    2015-01-01

    Metamaterials are composite structures that exhibit interesting and unusual properties, e.g. negative refractive index. In this article we consider metamaterials based on colloidal quantum dots (CQDs). We investigate these structures taking into account the local field effects and theoretically analyze expressions for permittivity and permeability of metamaterials based on CdSe CQDs. We obtain inequality describing the conditions when material with definite concentration of CQDs is metamaterial. Also we investigate how the values of dielectric polarizability and magnetic polarizability of CQDs depend on the dots radius and properties the material the quantum dots are made of. (paper)

  18. Nanobiosensors Based on Localized Surface Plasmon Resonance for Biomarker Detection

    Directory of Open Access Journals (Sweden)

    Yoochan Hong

    2012-01-01

    Full Text Available Localized surface plasmon resonance (LSPR is induced by incident light when it interacts with noble metal nanoparticles that have smaller sizes than the wavelength of the incident light. Recently, LSPR-based nanobiosensors were developed as tools for highly sensitive, label-free, and flexible sensing techniques for the detection of biomolecular interactions. In this paper, we describe the basic principles of LSPR-based nanobiosensing techniques and LSPR sensor system for biomolecule sensing. We also discuss the challenges using LSPR nanobiosensors for detection of biomolecules as a biomarker.

  19. 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

  20. Community-Based Ecotourism: The Transformation of Local Community

    Directory of Open Access Journals (Sweden)

    Pookhao Nantira

    2014-01-01

    Full Text Available Community-based ecotourism (CBET is considered a sustainable form of tourism that improves the quality of life of hosts at the tourist destination. Scholars have yet to explore the long-term operation of CBET in relation to its effects on the local way of life. Consequently, the purpose of this paper is to examine the transformation of a local community due to the operation of CBET in relation to sociocultural, economic and environmental aspects. The findings reveal that the community encounters both positive and negative impacts of transformation. However, unintended impacts of the CBET operation lay embedded in the transformation of relationships among the community members. The study identifies that close relationships among the villagers has been initially transformed to loose relationships due to forgotten communal goals; CBET has transformed from being a conservation tool to being a business-oriented goal which causes conflicts of interest among local people and alters traditional social structure. The study also agrees with the notion of social exchange theory for villagers to enhance environmental sustainability, and proposes that slight inequalities of benefits received from CBET causes social transformation at the local level.

  1. Integration of Local Hydrology into Regional Hydrologic Simulation Model

    Science.gov (United States)

    Van Zee, R. J.; Lal, W. A.

    2002-05-01

    South Florida hydrology is dominated by the Central and South Florida (C&SF) Project that is managed to provide flood protection, water supply and environmental protection. A complex network of levees canals and structures provide these services to the individual drainage basins. The landscape varies widely across the C&SF system, with corresponding differences in the way water is managed within each basin. Agricultural areas are managed for optimal crop production. Urban areas maximize flood protection while maintaining minimum water levels to protect adjacent wetlands and local water supplies. "Natural" areas flood and dry out in response to the temporal distribution of rainfall. The evaluation of planning, regulation and operational issues require access to a simulation model that captures the effects of both regional and local hydrology. The Regional Simulation Model (RSM) uses a "pseudo-cell" approach to integrate local hydrology within the context of a regional hydrologic system. A 2-dimensional triangulated mesh is used to represent the regional surface and ground water systems and a 1-dimensional canal network is superimposed onto this mesh. The movement of water is simulated using a finite volume formulation with a diffusive wave approximation. Each cell in the triangulated mesh has a "pseudo-cell" counterpart, which represents the same area as the cell, but it is conceptualized such that it simulates the localized hydrologic conditions Protocols have been established to provide an interface between a cell and its pseudo-cell counterpart. . A number of pseudo-cell types have already been developed and tested in the simulation of Water Conservation Area 1 and several have been proposed to deal with specific local issues in the Southwest Florida Feasibility Study. This presentation will provide an overview of the overall RSM design, describe the relationship between cells and pseudo-cells, and illustrate how pseudo-cells are be used to simulate agriculture

  2. Asymptotically exact solution of a local copper-oxide model

    International Nuclear Information System (INIS)

    Zhang Guangming; Yu Lu.

    1994-03-01

    We present an asymptotically exact solution of a local copper-oxide model abstracted from the multi-band models. The phase diagram is obtained through the renormalization-group analysis of the partition function. In the strong coupling regime, we find an exactly solved line, which crosses the quantum critical point of the mixed valence regime separating two different Fermi-liquid (FL) phases. At this critical point, a many-particle resonance is formed near the chemical potential, and a marginal-FL spectrum can be derived for the spin and charge susceptibilities. (author). 15 refs, 1 fig

  3. 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.

  4. A local mixing model for deuterium replacement in solids

    International Nuclear Information System (INIS)

    Doyle, B.L.; Brice, D.K.; Wampler, W.R.

    1980-01-01

    A new model for hydrogen isotope exchange by ion implantation has been developed. The basic difference between the present approach and previous work is that the depth distribution of the implanted species is included. The outstanding feature of this local mixing model is that the only adjustable parameter is the saturation hydrogen concentration which is specific to the target material and dependent only on temperature. The model is shown to give excellent agreement both with new data on H/D exchange in the low Z coating materials VB 2 , TiC, TiB 2 , and B reported here and with previously reported data on stainless steel. The saturation hydrogen concentrations used to fit these data were 0.15, 0.25, 0.15, 0.45, and 1.00 times atomic density respectively. This model should be useful in predicting the recycling behavior of hydrogen isotopes in tokamak limiter and wall materials. (author)

  5. 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

  6. 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.

  7. 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.

  8. Conversion to biofuel based heating systems - local environmental effects

    International Nuclear Information System (INIS)

    Jonsson, Anna

    2003-01-01

    One of the most serious environmental problems today is the global warming, i.e.climate changes caused by emissions of greenhouse gases. The greenhouse gases originate from combustion of fossil fuels and changes the atmospheric composition. As a result of the climate change, the Swedish government has decided to make a changeover of the Swedish energy system. This involves an increase of the supply of electricity and heating from renewable energy sources and a decrease in the amount electricity used for heating, as well as a more efficient use of the existing electricity system. Today, a rather large amount electricity is used for heating in Sweden. Furthermore, nuclear power will be phased out by the year 2010 in Sweden. Bio fuels are a renewable energy source and a conceivable alternative to the use of fossil fuels. Therefore, an increase of bio fuels will be seen the coming years. Bio fuels have a lot of environmental advantages, mainly for the global environment, but might also cause negative impacts such as depletion of the soils where the biomass is grown and local deterioration of the air quality where the bio fuels are combusted. These negative impacts are a result of the use of wrong techniques and a lack of knowledge and these factors have to be improved if the increase of the use of bio fuels is to be made effectively. The aim of this master thesis is to evaluate the possibilities for heating with bio fuel based systems in housing areas in the municipalities of Trollhaettan, Ulricehamn and Goetene in Vaestra Goetalands County in the South West of Sweden and to investigate which environmental and health effects are caused by the conversion of heating systems. The objective is to use the case studies as examples on preferable bio fuel based heating systems in different areas, and to what environmental impact this conversion of heating systems might cause. The housing areas for this study have been chosen on the basis of present heating system, one area

  9. 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.

  10. 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.

  11. 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.

  12. Droplet localization in the random XXZ model and its manifestations

    Science.gov (United States)

    Elgart, A.; Klein, A.; Stolz, G.

    2018-01-01

    We examine many-body localization properties for the eigenstates that lie in the droplet sector of the random-field spin- \\frac 1 2 XXZ chain. These states satisfy a basic single cluster localization property (SCLP), derived in Elgart et al (2018 J. Funct. Anal. (in press)). This leads to many consequences, including dynamical exponential clustering, non-spreading of information under the time evolution, and a zero velocity Lieb-Robinson bound. Since SCLP is only applicable to the droplet sector, our definitions and proofs do not rely on knowledge of the spectral and dynamical characteristics of the model outside this regime. Rather, to allow for a possible mobility transition, we adapt the notion of restricting the Hamiltonian to an energy window from the single particle setting to the many body context.

  13. local

    Directory of Open Access Journals (Sweden)

    Abílio Amiguinho

    2005-01-01

    Full Text Available The process of socio-educational territorialisation in rural contexts is the topic of this text. The theme corresponds to a challenge to address it having as main axis of discussion either the problem of social exclusion or that of local development. The reasons to locate the discussion in this last field of analysis are discussed in the first part of the text. Theoretical and political reasons are there articulated because the question is about projects whose intentions and practices call for the political both in the theoretical debate and in the choices that anticipate intervention. From research conducted for several years, I use contributions that aim at discuss and enlighten how school can be a potential locus of local development. Its identification and recognition as local institution (either because of those that work and live in it or because of those that act in the surrounding context are crucial steps to progressively constitute school as a partner for development. The promotion of the local values and roots, the reconstruction of socio-personal and local identities, the production of sociabilities and the equation and solution of shared problems were the dimensions of a socio-educative intervention, markedly globalising. This scenario, as it is argued, was also, intentionally, one of transformation and of deliberate change of school and of the administration of the educative territoires.

  14. 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.

  15. Statistical lamb wave localization based on extreme value theory

    Science.gov (United States)

    Harley, Joel B.

    2018-04-01

    Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

  16. Finger image quality based on singular point localization

    DEFF Research Database (Denmark)

    Wang, Jinghua; Olsen, Martin A.; Busch, Christoph

    2014-01-01

    Singular points are important global features of fingerprints and singular point localization is a crucial step in biometric recognition. Moreover the presence and position of the core point in a captured fingerprint sample can reflect whether the finger is placed properly on the sensor. Therefore...... and analyze the importance of singular points on biometric accuracy. The experiment is based on large scale databases and conducted by relating the measured quality of a fingerprint sample, given by the positions of core points, to the biometric performance. The experimental results show the positions of core...

  17. Biogas Filter Based on Local Natural Zeolite Materials

    Directory of Open Access Journals (Sweden)

    Satriyo Krido Wahono

    2014-02-01

    Full Text Available UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as increasing methane contents, increasing heating value, reduction of odors, reduction of corrosion potential, increasing the efficiency and stability of the generator.

  18. Localization-based super-resolution imaging of cellular structures.

    Science.gov (United States)

    Kanchanawong, Pakorn; Waterman, Clare M

    2013-01-01

    Fluorescence microscopy allows direct visualization of fluorescently tagged proteins within cells. However, the spatial resolution of conventional fluorescence microscopes is limited by diffraction to ~250 nm, prompting the development of super-resolution microscopy which offers resolution approaching the scale of single proteins, i.e., ~20 nm. Here, we describe protocols for single molecule localization-based super-resolution imaging, using focal adhesion proteins as an example and employing either photoswitchable fluorophores or photoactivatable fluorescent proteins. These protocols should also be easily adaptable to imaging a broad array of macromolecular assemblies in cells whose components can be fluorescently tagged and assemble into high density structures.

  19. Infrared target recognition based on improved joint local ternary pattern

    Science.gov (United States)

    Sun, Junding; Wu, Xiaosheng

    2016-05-01

    This paper presents a simple, efficient, yet robust approach, named joint orthogonal combination of local ternary pattern, for automatic forward-looking infrared target recognition. It gives more advantages to describe the macroscopic textures and microscopic textures by fusing variety of scales than the traditional LBP-based methods. In addition, it can effectively reduce the feature dimensionality. Further, the rotation invariant and uniform scheme, the robust LTP, and soft concave-convex partition are introduced to enhance its discriminative power. Experimental results demonstrate that the proposed method can achieve competitive results compared with the state-of-the-art methods.

  20. 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.

  1. One-loop Yukawa Couplings in Local Models

    CERN Document Server

    Conlon, Joseph P; Palti, Eran; 10.1007

    2010-01-01

    We calculate the one-loop Yukawa couplings and threshold corrections for supersymmetric local models of branes at singularities in type IIB string theory. We compute the corrections coming both from wavefunction and vertex renormalisation. The former comes in the IR from conventional field theory running and in the UV from threshold corrections that cause it to run from the winding scale associated to the full Calabi-Yau volume. The vertex correction is naively absent as it appears to correspond to superpotential renormalisation. However, we find that while the Wilsonian superpotential is not renormalised there is a physical vertex correction in the 1PI action associated to light particle loops.

  2. One-loop Yukawa couplings in local models

    Energy Technology Data Exchange (ETDEWEB)

    Conlon, Joseph P. [Rudolf Peierls Center for Theoretical Physics, Oxford (United Kingdom); Balliol College, Oxford (United Kingdom); Goodsell, Mark [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Palti, Eran [Centre de Physique Theorique, Ecole Polytechnique, CNRS, Palaiseau (France)

    2010-07-15

    We calculate the one-loop Yukawa couplings and threshold corrections for supersymmetric local models of branes at singularities in type IIB string theory. We compute the corrections coming both from wavefunction and vertex renormalisation. The former comes in the IR from conventional field theory running and in the UV from threshold corrections that cause it to run from the winding scale associated to the full Calabi-Yau volume. The vertex correction is naively absent as it appears to correspond to superpotential renormalisation. However, we find that while the Wilsonian superpotential is not renormalised there is a physical vertex correction in the 1PI action associated to light particle loops. (orig.)

  3. One-loop Yukawa couplings in local models

    International Nuclear Information System (INIS)

    Conlon, Joseph P.; Goodsell, Mark; Palti, Eran

    2010-07-01

    We calculate the one-loop Yukawa couplings and threshold corrections for supersymmetric local models of branes at singularities in type IIB string theory. We compute the corrections coming both from wavefunction and vertex renormalisation. The former comes in the IR from conventional field theory running and in the UV from threshold corrections that cause it to run from the winding scale associated to the full Calabi-Yau volume. The vertex correction is naively absent as it appears to correspond to superpotential renormalisation. However, we find that while the Wilsonian superpotential is not renormalised there is a physical vertex correction in the 1PI action associated to light particle loops. (orig.)

  4. Composite PET and MRI for accurate localization and metabolic modeling

    International Nuclear Information System (INIS)

    Bidaut, L.

    1991-01-01

    This paper reports that in order to help in analyzing PET data and really take advantage of their metabolic content, a system was designed and implemented to align and process data from various medical imaging modalities, particularly (but not only) for brain studies. Although this system is for now mostly used for anatomical localization, multi-modality ROIs and pharmaco-kinetic modeling, more multi-modality protocols will be implemented in the future, not only to help in PET reconstruction data correction and semi-automated ROI definition, but also for helping in improving diagnostic accuracy along with surgery and therapy planning

  5. Local models of heterotic flux vacua: spacetime and worldsheet aspects

    International Nuclear Information System (INIS)

    Israel, D.; Carlevaro, L.

    2011-01-01

    We report on some recent progress in understanding heterotic flux compactifications, from a worldsheet perspective mainly. We consider local models consisting in torus fibration over warped Eguchi-Hanson space and non-Kaehler resolved conifold geometries. We analyze the supergravity solutions and define a double-scaling limit of the resolved singularities, defined such that the geometry is smooth and weakly coupled. We show that, remarkably, the heterotic solutions admit solvable worldsheet CFT descriptions in this limit. This allows in particular to understand the important role of worldsheet non-perturbative effects. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  6. 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.

  7. 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.

  8. Clustering of 18 Local Black Rice Base on Total Anthocyanin

    Directory of Open Access Journals (Sweden)

    Kristamtini Kristamtini

    2017-10-01

    Full Text Available Black rice has a high anthocyanin content in the pericarp layer, which provides a dark purple color. Anthocyanin serve as an antioxidant that control cholesterol level in the blood, prevent anemia, potentially improve the body's resistance to disease, improve damage to liver cells (hepatitis and chirrosis, prevent impaired kidney function, prevent cancer/tumors, slows down antiaging, and prevent atherosclerosis and cardiovascular disease. Exploration results at AIAT Yogyakarta, Indonesia from 2011 to 2014 obtained 18 cultivar of local black rice Indonesia. The names of the rice are related to the color (black, red or purple formed by anthocyanin deposits in the pericarp layer, seed coat or aleuron. The objective of the study was to classify several types of local black rice from explorations based on the total anthocyanin content. The study was conducted by clustering analyzing the total anthocyanin content of 18 local black rice cultivars in Indonesia. Cluster analysis of total anthocyanin content were done using SAS ver. 9.2. Clustering dendogram shows that there were 4 groups of black rice cultivars based on the total anthocyanin content. Group I consists of Melik black rice, Patalan black rice, Yunianto black rice, Muharjo black rice, Ngatijo black rice, short life of Tugiyo black rice, Andel hitam 1, Jlitheng, and Sragen black rice. Group II consists of Pari ireng, Magelang black hairy rice, Banjarnegara-Wonosobo black rice, and Banjarnegara black rice. Group III consists of NTT black rice, Magelang non hairy black rice, Sembada hitam, and longevity Tugiyo black rice. Group IV consist only one type of black rice namely Cempo ireng. The grouping result indicate the existence of duplicate names among the black rice namely Patalan with Yunianto black rice, and short life Tugiyo with Andel hitam 1 black rice.

  9. Improving mobile robot localization: grid-based approach

    Science.gov (United States)

    Yan, Junchi

    2012-02-01

    Autonomous mobile robots have been widely studied not only as advanced facilities for industrial and daily life automation, but also as a testbed in robotics competitions for extending the frontier of current artificial intelligence. In many of such contests, the robot is supposed to navigate on the ground with a grid layout. Based on this observation, we present a localization error correction method by exploring the geometric feature of the tile patterns. On top of the classical inertia-based positioning, our approach employs three fiber-optic sensors that are assembled under the bottom of the robot, presenting an equilateral triangle layout. The sensor apparatus, together with the proposed supporting algorithm, are designed to detect a line's direction (vertical or horizontal) by monitoring the grid crossing events. As a result, the line coordinate information can be fused to rectify the cumulative localization deviation from inertia positioning. The proposed method is analyzed theoretically in terms of its error bound and also has been implemented and tested on a customary developed two-wheel autonomous mobile robot.

  10. Testing of motor unit synchronization model for localized muscle fatigue.

    Science.gov (United States)

    Naik, Ganesh R; Kumar, Dinesh K; Yadav, Vivek; Wheeler, Katherine; Arjunan, Sridhar

    2009-01-01

    Spectral compression of surface electromyogram (sEMG) is associated with onset of localized muscle fatigue. The spectral compression has been explained based on motor unit synchronization theory. According to this theory, motor units are pseudo randomly excited during muscle contraction, and with the onset of muscle fatigue the recruitment pattern changes such that motor unit firings become more synchronized. While this is widely accepted, there is little experimental proof of this phenomenon. This paper has used source dependence measures developed in research related to independent component analysis (ICA) to test this theory.

  11. RANCANGAN MODEL PERFORMANSI RISIKO RANTAI PASOK AGROINDUSTRI SUSU DENGAN MENGGUNAKAN PENDEKATAN LOGIKA FUZZY (A Supply Chain Risk Performance Model for Local Raw Milk Agro-Industry Based on Fuzzy Logic Approach

    Directory of Open Access Journals (Sweden)

    Winnie Septiani

    2015-05-01

    risiko dalam ukuran waktu, biaya dan kualitas. Tahap pertama dimulai dengan menganalisis eksposur risiko yang tidak terhindarkan yang meliputi analisis karakteristik lingkungan dan konfigurasi serta karakteristik rantai pasok agroindustri susu. Tahap kedua adalah menganalisis eksposure risiko yang dapat dihindari. Tahap ketiga adalah mengubah eksposur risiko ke dalam ukuran performansi waktu, biaya dan kualitas. Pada tahap kedua dihasilkan magnitude risiko, yang merupakan fungsi dari nilai probabilitas dan severity yang dilakukan dengan menggunakan Fuzzy Assosiated Memories (FAMs.Dengan model ini diharapkan dampak kerusakan dari risiko yang muncul pada rantai pasok agroindustri susu dapat terukur dan dapat diminimasi sehingga dapat meningkatkan ketangguhan (robustnes dari rantai pasok. Kata kunci: Performansi, risiko, fuzzy, rantai pasok, agroindustri susu

  12. 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.

  13. 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.

  14. Developmental Local Government as a Model for Grassroots Socio ...

    African Journals Online (AJOL)

    In the past five decades of political independence in Nigeria, local ... governments places a strong limitation on local autonomy and governance at the local level. ... negatively affecting grassroots socio-economic development in the Country.

  15. 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.

  16. 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.

  17. Non-localization and localization ROC analyses using clinically based scoring

    Science.gov (United States)

    Paquerault, Sophie; Samuelson, Frank W.; Myers, Kyle J.; Smith, Robert C.

    2009-02-01

    We are investigating the potential for differences in study conclusions when assessing the estimated impact of a computer-aided detection (CAD) system on readers' performance. The data utilized in this investigation were derived from a multi-reader multi-case observer study involving one hundred mammographic background images to which fixed-size and fixed-intensity Gaussian signals were added, generating a low- and high-intensity signal sets. The study setting allowed CAD assessment in two situations: when CAD sensitivity was 1) superior or 2) lower than the average reader. Seven readers were asked to review each set in the unaided and CAD-aided reading modes, mark and rate their findings. Using this data, we studied the effect on study conclusion of three clinically-based receiver operating characteristic (ROC) scoring definitions. These scoring definitions included both location-specific and non-location-specific rules. The results showed agreement in the estimated impact of CAD on the overall reader performance. In the study setting where CAD sensitivity is superior to the average reader, the mean difference in AUC between the CAD-aided read and unaided read was 0.049 (95%CIs: -0.027; 0.130) for the image scoring definition that is based on non-location-specific rules, and 0.104 (95%CIs: 0.036; 0.174) and 0.090 (95%CIs: 0.031; 0.155) for image scoring definitions that are based on location-specific rules. The increases in AUC were statistically significant for the location-specific scoring definitions. It was further observed that the variance on these estimates was reduced when using the location-specific scoring definitions compared to that using a non-location-specific scoring definition. In the study setting where CAD sensitivity is equivalent or lower than the average reader, the mean differences in AUC are slightly above 0.01 for all image scoring definitions. These increases in AUC were not statistical significant for any of the image scoring definitions

  18. Extension of local front reconstruction method with controlled coalescence model

    Science.gov (United States)

    Rajkotwala, A. H.; Mirsandi, H.; Peters, E. A. J. F.; Baltussen, M. W.; van der Geld, C. W. M.; Kuerten, J. G. M.; Kuipers, J. A. M.

    2018-02-01

    The physics of droplet collisions involves a wide range of length scales. This poses a challenge to accurately simulate such flows with standard fixed grid methods due to their inability to resolve all relevant scales with an affordable number of computational grid cells. A solution is to couple a fixed grid method with subgrid models that account for microscale effects. In this paper, we improved and extended the Local Front Reconstruction Method (LFRM) with a film drainage model of Zang and Law [Phys. Fluids 23, 042102 (2011)]. The new framework is first validated by (near) head-on collision of two equal tetradecane droplets using experimental film drainage times. When the experimental film drainage times are used, the LFRM method is better in predicting the droplet collisions, especially at high velocity in comparison with other fixed grid methods (i.e., the front tracking method and the coupled level set and volume of fluid method). When the film drainage model is invoked, the method shows a good qualitative match with experiments, but a quantitative correspondence of the predicted film drainage time with the experimental drainage time is not obtained indicating that further development of film drainage model is required. However, it can be safely concluded that the LFRM coupled with film drainage models is much better in predicting the collision dynamics than the traditional methods.

  19. Bang-bang Model for Regulation of Local Blood Flow

    Science.gov (United States)

    Golub, Aleksander S.; Pittman, Roland N.

    2013-01-01

    The classical model of metabolic regulation of blood flow in muscle tissue implies the maintenance of basal tone in arterioles of resting muscle and their dilation in response to exercise and/or tissue hypoxia via the evoked production of vasodilator metabolites by myocytes. A century-long effort to identify specific metabolites responsible for explaining active and reactive hyperemia has not been successful. Furthermore, the metabolic theory is not compatible with new knowledge on the role of physiological radicals (e.g., nitric oxide, NO, and superoxide anion, O2−) in the regulation of microvascular tone. We propose a model of regulation in which muscle contraction and active hyperemia are considered the physiologically normal state. We employ the “bang-bang” or “on/off” regulatory model which makes use of a threshold and hysteresis; a float valve to control the water level in a tank is a common example of this type of regulation. Active bang-bang regulation comes into effect when the supply of oxygen and glucose exceeds the demand, leading to activation of membrane NADPH oxidase, release of O2− into the interstitial space and subsequent neutralization of the interstitial NO. Switching arterioles on/off when local blood flow crosses the threshold is realized by a local cell circuit with the properties of a bang-bang controller, determined by its threshold, hysteresis and dead-band. This model provides a clear and unambiguous interpretation of the mechanism to balance tissue demand with a sufficient supply of nutrients and oxygen. PMID:23441827

  20. 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.

  1. 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

  2. Example-Based Image Colorization Using Locality Consistent Sparse Representation.

    Science.gov (United States)

    Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

    2017-11-01

    Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

  3. Embodying, calibrating and caring for a local model of obesity

    DEFF Research Database (Denmark)

    Winther, Jonas; Hillersdal, Line

    Interdisciplinary research collaborations are increasingly made a mandatory 'standard' within strategic research grants. Collaborations between the natural, social and humanistic sciences are conceptualized as uniquely suited to study pressing societal problems. The obesity epidemic has been...... highlighted as such a problem. Within research communities disparate explanatory models of obesity exist (Ulijaszek 2008) and some of these models of obesity are brought together in the Copenhagen-based interdisciplinary research initiative; Governing Obesity (GO) with the aim of addressing the causes...

  4. 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.

  5. 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.

  6. 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

  7. Impact localization in dispersive waveguides based on energy-attenuation of waves with the traveled distance

    Science.gov (United States)

    Alajlouni, Sa'ed; Albakri, Mohammad; Tarazaga, Pablo

    2018-05-01

    An algorithm is introduced to solve the general multilateration (source localization) problem in a dispersive waveguide. The algorithm is designed with the intention of localizing impact forces in a dispersive floor, and can potentially be used to localize and track occupants in a building using vibration sensors connected to the lower surface of the walking floor. The lower the wave frequencies generated by the impact force, the more accurate the localization is expected to be. An impact force acting on a floor, generates a seismic wave that gets distorted as it travels away from the source. This distortion is noticeable even over relatively short traveled distances, and is mainly caused by the dispersion phenomenon among other reasons, therefore using conventional localization/multilateration methods will produce localization error values that are highly variable and occasionally large. The proposed localization approach is based on the fact that the wave's energy, calculated over some time window, decays exponentially as the wave travels away from the source. Although localization methods that assume exponential decay exist in the literature (in the field of wireless communications), these methods have only been considered for wave propagation in non-dispersive media, in addition to the limiting assumption required by these methods that the source must not coincide with a sensor location. As a result, these methods cannot be applied to the indoor localization problem in their current form. We show how our proposed method is different from the other methods, and that it overcomes the source-sensor location coincidence limitation. Theoretical analysis and experimental data will be used to motivate and justify the pursuit of the proposed approach for localization in a dispersive medium. Additionally, hammer impacts on an instrumented floor section inside an operational building, as well as finite element model simulations, are used to evaluate the performance of

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Modeling amorphization of tetrahedral structures under local approaches

    International Nuclear Information System (INIS)

    Jesurum, C.E.; Pulim, V.; Berger, B.; Hobbs, L.W.

    1997-01-01

    Many crystalline ceramics can be topologically disordered (amorphized) by disordering radiation events involving high-energy collision cascades or (in some cases) successive single-atom displacements. The authors are interested in both the potential for disorder and the possible aperiodic structures adopted following the disordering event. The potential for disordering is related to connectivity, and among those structures of interest are tetrahedral networks (such as SiO 2 , SiC and Si 3 N 4 ) comprising corner-shared tetrahedral units whose connectivities are easily evaluated. In order to study the response of these networks to radiation, the authors have chosen to model their assembly according to the (simple) local rules that each corner obeys in connecting to another tetrahedron; in this way they easily erect large computer models of any crystalline polymorphic form. Amorphous structures can be similarly grown by application of altered rules. They have adopted a simple model of irradiation in which all bonds in the neighborhood of a designated tetrahedron are destroyed, and they reform the bonds in this region according to a set of (possibly different) local rules appropriate to the environmental conditions. When a tetrahedron approaches the boundary of this neighborhood, it undergoes an optimization step in which a spring is inserted between two corners of compatible tetrahedra when they are within a certain distance of one another; component forces are then applied that act to minimize the distance between these corners and minimize the deviation from the rules. The resulting structure is then analyzed for the complete adjacency matrix, irreducible ring statistics, and bond angle distributions

  16. 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%.

  17. 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.

  18. Machine Learning Based Localization and Classification with Atomic Magnetometers

    Science.gov (United States)

    Deans, Cameron; Griffin, Lewis D.; Marmugi, Luca; Renzoni, Ferruccio

    2018-01-01

    We demonstrate identification of position, material, orientation, and shape of objects imaged by a Rb 85 atomic magnetometer performing electromagnetic induction imaging supported by machine learning. Machine learning maximizes the information extracted from the images created by the magnetometer, demonstrating the use of hidden data. Localization 2.6 times better than the spatial resolution of the imaging system and successful classification up to 97% are obtained. This circumvents the need of solving the inverse problem and demonstrates the extension of machine learning to diffusive systems, such as low-frequency electrodynamics in media. Automated collection of task-relevant information from quantum-based electromagnetic imaging will have a relevant impact from biomedicine to security.

  19. Hyperspectral image classification based on local binary patterns and PCANet

    Science.gov (United States)

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

    2018-04-01

    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  20. Model-Based Reasoning

    Science.gov (United States)

    Ifenthaler, Dirk; Seel, Norbert M.

    2013-01-01

    In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…

  1. Anomalously suppressed localization in the two-channel Anderson model

    International Nuclear Information System (INIS)

    Nguyen, Ba Phi; Kim, Kihong

    2012-01-01

    We study numerically the localization properties of a two-channel quasi-one-dimensional Anderson model with uncorrelated diagonal disorder within the nearest-neighbor tight-binding approximation. We calculate and analyze the disorder-averaged transmittance and the Lyapunov exponent. We find that the localization of the entire system is enhanced by increasing the interchain hopping strength t-tilde. From the numerical investigation of the energy dependence of the Lyapunov exponent for many different interchain hopping strengths, we find that apart from the band center anomaly, which usually occurs in strictly one-dimensional disordered systems, additional anomalies appear at special spectral points. They are found to be associated with the interchain hopping strength and occur at E=± t-tilde/2 and ± t-tilde. We find that the anomalies at E=± t-tilde are associated with the π-coupling occurring within one energy band and those at E=± t-tilde/2 are associated with the π-coupling occurring between two different energy bands. Despite having a similar origin, these two anomalies have distinct characteristics in their dependence on the strength of disorder. We also show that for a suitable range of parameter values, effectively delocalized states are observed in finite-size systems. (paper)

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. Progress towards localization in the attractive Hubbard model

    Science.gov (United States)

    Morong, W.; Xu, W.; Demarco, B.

    2017-04-01

    The interplay between fermionic superfluidity and disorder is a topic of long-standing interest that has recently come within reach of ultracold gas experiments. Outstanding questions include the fate of Cooper pairs in a localized superfluid and the effect of disorder on the superfluid transition temperature. We report progress on tackling this problem using a realization of the Hubbard model with attractive interactions. Our system consists of two spin states of fermionic potassium-40 trapped in a cubic optical lattice. Disorder is introduced using an optical speckle potential, and interactions are controlled via a Feshbach resonance. We study the binding and unbinding of Cooper pairs in this system using rf spectroscopy, changes in Tc by measuring the condensate fraction, and transport properties by observing the response to an applied impulse. We will discuss progress towards these measurements.

  8. Electron localization in liquid hydrocarbons: The Anderson model

    International Nuclear Information System (INIS)

    Hug, Gordon L.; Mozumder, A.

    2008-01-01

    Anderson's model is applied for initial localization in liquid hydrocarbons (particularly n-alkanes) in conjunction with certain results of scaling theory. Medium connectivity is calculated using experimental X-ray data on liquid structure, from which critical disorder (W/V) c is computed, where W is diagonal disorder and V is the transfer energy. Actual W prevailing in the liquid is computed from anisotropic molecular polarizability. V is estimated by a heuristic procedure originating in scaling theory. These values are used to compute the percentage of initially delocalized states available for low-energy electrons in alkane liquids. This percentage decreases monotonically from methane (100%) to n-pentane and beyond (0%). In ethane and propane, the initial states are highly delocalized (97.6% and 83.9%, respectively). Subsequent trapping changes the situation as evidenced in mobility studies. Butane presents a partially, intermediate delocalized case (53.2%)

  9. Onset patterns in a simple model of localized parametric forcing.

    Science.gov (United States)

    Porter, J; Tinao, I; Laverón-Simavilla, A; Rodríguez, J

    2013-10-01

    We investigate pattern selection at onset in a parametrically and inhomogeneously forced partial differential equation obtained by generalizing Mathieu's equation to include spatial interactions. No separation of scales is assumed. The proposed model is directly relevant to the case of parametrically forced surface waves, such as cross-waves, excited by the horizontal vibration of a fluid, where the forcing is localized to a finite region near the endwall or wavemaker. The availability of analytical solutions in the limit of piecewise constant forcing allows us investigate in detail the dependence of selected eigenfunctions on spatial detuning, forcing width, damping, boundary conditions, and container size. A wide range of onset patterns are located and described, many of which are rotated, modulated, or both, and deviate far from simple crosswise oriented standing waves. The linear selection mechanisms governing this multiplicity of potential onset patterns are discussed.

  10. A note on local GUT models in F-theory

    International Nuclear Information System (INIS)

    Chen, C.-M.; Chung, Y.-C.

    2010-01-01

    We construct non-minimal GUT local models in the F-theory configuration. The gauge group on the bulk G S is one rank higher than the GUT gauge group. The line bundles on the curves are nontrivial to break G S down to the GUT gauge groups. We demonstrate examples of SU(5) GUT from G S =SU(6) and G S =SO(10), the flipped SU(5) from G S =SO(10), and the SO(10) GUT from G S =SO(12) and G S =E 6 . We obtain complete GUT matter spectra and couplings, with minimum exotic matter contents. GUT gauge group breaking to MSSM is achievable by instanton configurations.

  11. Model for the local spiral structure of the galaxy

    International Nuclear Information System (INIS)

    Humphreys, R.M.

    1976-01-01

    The spatial distribution of the most luminous stars, associations, clusters, and H II regions in the region l = 270 0 to 30 0 reveal a major spiral arm, Sagittarius-Carina, which can be observed to 9 or 10 kpc from the sun in the direction l = 290 0 to 305 0 . Evidence is also presented for a spur at l = 305 0 to 310 0 on the inner side of the Saggitarius-Carina arm. The noncircular motions observed in the Carina and Sagittarius spiral features agree in both magnitude and direction and support the suggestion that Sagittarius-Carina is a major spiral arm. A model is presented for the local spiral structure with wide, massive, spiral arms which show fragmentation in our region of the Galaxy. On the basis of the optical spiral structure, the Milky Way is an Sc type spiral galaxy, perhaps of the M 101 type

  12. A local non-parametric model for trade sign inference

    Science.gov (United States)

    Blazejewski, Adam; Coggins, Richard

    2005-03-01

    We investigate a regularity in market order submission strategies for 12 stocks with large market capitalization on the Australian Stock Exchange. The regularity is evidenced by a predictable relationship between the trade sign (trade initiator), size of the trade, and the contents of the limit order book before the trade. We demonstrate this predictability by developing an empirical inference model to classify trades into buyer-initiated and seller-initiated. The model employs a local non-parametric method, k-nearest neighbor, which in the past was used successfully for chaotic time series prediction. The k-nearest neighbor with three predictor variables achieves an average out-of-sample classification accuracy of 71.40%, compared to 63.32% for the linear logistic regression with seven predictor variables. The result suggests that a non-linear approach may produce a more parsimonious trade sign inference model with a higher out-of-sample classification accuracy. Furthermore, for most of our stocks the observed regularity in market order submissions seems to have a memory of at least 30 trading days.

  13. Local stem cell depletion model for normal tissue damage

    International Nuclear Information System (INIS)

    Yaes, R.J.; Keland, A.

    1987-01-01

    The hypothesis that radiation causes normal tissue damage by completely depleting local regions of tissue of viable stem cells leads to a simple mathematical model for such damage. In organs like skin and spinal cord where destruction of a small volume of tissue leads to a clinically apparent complication, the complication probability is expressed as a function of dose, volume and stem cell number by a simple triple negative exponential function analogous to the double exponential function of Munro and Gilbert for tumor control. The steep dose response curves for radiation myelitis that are obtained with our model are compared with the experimental data for radiation myelitis in laboratory rats. The model can be generalized to include other types or organs, high LET radiation, fractionated courses of radiation, and cases where an organ with a heterogeneous stem cell population receives an inhomogeneous dose of radiation. In principle it would thus be possible to determine the probability of tumor control and of damage to any organ within the radiation field if the dose distribution in three dimensional space within a patient is known

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

    Directory of Open Access Journals (Sweden)

    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.

  15. 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.

  16. Explosion localization and characterization via infrasound using numerical modeling

    Science.gov (United States)

    Fee, D.; Kim, K.; Iezzi, A. M.; Matoza, R. S.; Jolly, A. D.; De Angelis, S.; Diaz Moreno, A.; Szuberla, C.

    2017-12-01

    Numerous methods have been applied to locate, detect, and characterize volcanic and anthropogenic explosions using infrasound. Far-field localization techniques typically use back-azimuths from multiple arrays (triangulation) or Reverse Time Migration (RTM, or back-projection). At closer ranges, networks surrounding a source may use Time Difference of Arrival (TDOA), semblance, station-pair double difference, etc. However, at volcanoes and regions with topography or obstructions that block the direct path of sound, recent studies have shown that numerical modeling is necessary to provide an accurate source location. A heterogeneous and moving atmosphere (winds) may also affect the location. The time reversal mirror (TRM) application of Kim et al. (2015) back-propagates the wavefield using a Finite Difference Time Domain (FDTD) algorithm, with the source corresponding to the location of peak convergence. Although it provides high-resolution source localization and can account for complex wave propagation, TRM is computationally expensive and limited to individual events. Here we present a new technique, termed RTM-FDTD, which integrates TRM and FDTD. Travel time and transmission loss information is computed from each station to the entire potential source grid from 3-D Green's functions derived via FDTD. The wave energy is then back-projected and stacked at each grid point, with the maximum corresponding to the likely source. We apply our method to detect and characterize thousands of explosions from Yasur Volcano, Vanuatu and Etna Volcano, Italy, which both provide complex wave propagation and multiple source locations. We compare our results with those from more traditional methods (e.g. semblance), and suggest our method is preferred as it is computationally less expensive than TRM but still integrates numerical modeling. RTM-FDTD could be applied to volcanic other anthropogenic sources at a wide variety of ranges and scenarios. Kim, K., Lees, J.M., 2015. Imaging

  17. 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…

  18. Suitability of Local Resource Management Practices Based on Supernatural Enforcement Mechanisms in the Local Social-cultural Context

    Directory of Open Access Journals (Sweden)

    Masatoshi Sasaoka

    2012-12-01

    Full Text Available Environmental anthropological studies on natural resource management have widely demonstrated and thematized local resource management practices based on the interactions between local people and supernatural agencies and their role in maintaining natural resources. In Indonesia, even though the legal status of local people's right to the forest and forest resources is still weak, the recent transition toward decentralization presents a growing opportunity for local people to collaborate with outsiders such as governmental agencies and environmental nongovernmental organizations in natural resource management. In such situations, in-depth understanding of the value of local resource management practices is needed to promote self-directed and effective resource management. Here, we focus on local forest resource management and its suitability in the local social-cultural context in central Seram, east Indonesia. Local resource management appears to be embedded in the wider social-cultural context of the local communities. However, few intensive case studies in Indonesia have addressed the relationship between the Indigenous resource management practices closely related to a people's belief in supernatural agents and the social-cultural context. We illustrate how the well-structured use of forest resources is established and maintained through these interactions. We then investigate how local resource management practices relate to the social-cultural and natural resources context of an upland community in central Seram and discuss the possible future applications for achieving conservation.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Model-based Software Engineering

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2010-01-01

    The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

  4. 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

  5. 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

  6. 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.

  7. Principles of models based engineering

    Energy Technology Data Exchange (ETDEWEB)

    Dolin, R.M.; Hefele, J.

    1996-11-01

    This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

  8. Trajectory-Based Visual Localization in Underwater Surveying Missions

    Directory of Open Access Journals (Sweden)

    Antoni Burguera

    2015-01-01

    Full Text Available We present a new vision-based localization system applied to an autonomous underwater vehicle (AUV with limited sensing and computation capabilities. The traditional EKF-SLAM approaches are usually expensive in terms of execution time; the approach presented in this paper strengthens this method by adopting a trajectory-based schema that reduces the computational requirements. The pose of the vehicle is estimated using an extended Kalman filter (EKF, which predicts the vehicle motion by means of a visual odometer and corrects these predictions using the data associations (loop closures between the current frame and the previous ones. One of the most important steps in this procedure is the image registration method, as it reinforces the data association and, thus, makes it possible to close loops reliably. Since the use of standard EKFs entail linearization errors that can distort the vehicle pose estimations, the approach has also been tested using an iterated Kalman filter (IEKF. Experiments have been conducted using a real underwater vehicle in controlled scenarios and in shallow sea waters, showing an excellent performance with very small errors, both in the vehicle pose and in the overall trajectory estimates.

  9. Trajectory-Based Visual Localization in Underwater Surveying Missions

    Science.gov (United States)

    Burguera, Antoni; Bonin-Font, Francisco; Oliver, Gabriel

    2015-01-01

    We present a new vision-based localization system applied to an autonomous underwater vehicle (AUV) with limited sensing and computation capabilities. The traditional EKF-SLAM approaches are usually expensive in terms of execution time; the approach presented in this paper strengthens this method by adopting a trajectory-based schema that reduces the computational requirements. The pose of the vehicle is estimated using an extended Kalman filter (EKF), which predicts the vehicle motion by means of a visual odometer and corrects these predictions using the data associations (loop closures) between the current frame and the previous ones. One of the most important steps in this procedure is the image registration method, as it reinforces the data association and, thus, makes it possible to close loops reliably. Since the use of standard EKFs entail linearization errors that can distort the vehicle pose estimations, the approach has also been tested using an iterated Kalman filter (IEKF). Experiments have been conducted using a real underwater vehicle in controlled scenarios and in shallow sea waters, showing an excellent performance with very small errors, both in the vehicle pose and in the overall trajectory estimates. PMID:25594602

  10. Risk based modelling

    International Nuclear Information System (INIS)

    Chapman, O.J.V.; Baker, A.E.

    1993-01-01

    Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

  11. Ionogenic adsorbents based on local raw materials for radiation protection

    International Nuclear Information System (INIS)

    Isobaev, M.D.; Davlatnazarova, M.; Turdialiev, M.Z.; Abdullayev, T.H.; Pulatov, E.H.

    2012-01-01

    The successful management of uranium wastes and creating the conditions for effective rehabilitation activities require special adsorbents capable of holding on the surface complexes, including radioactive elements. Currently tested and have shown promising synthetic adsorbents based pitted apricot fruits and other fruit plants. This report presents data for the establishment of ionic type available adsorbents based on Tajikistan coal. As the base for the creation of this type of adsorbent were taken the coal of the 'Ziddi' deposits. As follows from our data on the chemical composition, the studied coals contain more than 20% of the ash. According to the available literature theses ashes contains various minerals compositions that can form the adsorbent's active surface. Thus, the model for this type of activated carbon can serve as a mixture of zeolite, ion exchange resins and activated carbon itself.

  12. 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*

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

    Directory of Open Access Journals (Sweden)

    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

  14. 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.

  15. 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.

  16. 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.

  17. Modeling local extinction in turbulent combustion using an embedding method

    Science.gov (United States)

    Knaus, Robert; Pantano, Carlos

    2012-11-01

    Local regions of extinction in diffusion flames, called ``flame holes,'' can reduce the efficiency of combustion and increase the production of certain pollutants. At sufficiently high speeds, a flame may also be lifted from the rim of the burner to a downstream location that may be stable. These two phenomena share a common underlying mechanism of propagation related to edge-flame dynamics where chemistry and fluid mechanics are equally important. We present a formulation that describes the formation, propagation, and growth of flames holes on the stoichiometric surface using edge flame dynamics. The boundary separating the flame from the quenched region is modeled using a progress variable defined on the moving stoichiometric surface that is embedded in the three-dimensional space using an extension algorithm. This Cartesian problem is solved using a high-order finite-volume WENO method extended to this nonconservative problem. This algorithm can track the dynamics of flame holes in a turbulent reacting-shear layer and model flame liftoff without requiring full chemistry calculations.

  18. 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.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Model-based consensus

    NARCIS (Netherlands)

    Boumans, M.; Martini, C.; Boumans, M.

    2014-01-01

    The aim of the rational-consensus method is to produce "rational consensus", that is, "mathematical aggregation", by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  2. Model-based consensus

    NARCIS (Netherlands)

    Boumans, Marcel

    2014-01-01

    The aim of the rational-consensus method is to produce “rational consensus”, that is, “mathematical aggregation”, by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  3. 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.

  4. A hybrid plume model for local-scale dispersion

    Energy Technology Data Exchange (ETDEWEB)

    Nikmo, J.; Tuovinen, J.P.; Kukkonen, J.; Valkama, I.

    1997-12-31

    The report describes the contribution of the Finnish Meteorological Institute to the project `Dispersion from Strongly Buoyant Sources`, under the `Environment` programme of the European Union. The project addresses the atmospheric dispersion of gases and particles emitted from typical fires in warehouses and chemical stores. In the study only the `passive plume` regime, in which the influence of plume buoyancy is no longer important, is addressed. The mathematical model developed and its numerical testing is discussed. The model is based on atmospheric boundary-layer scaling theory. In the vicinity of the source, Gaussian equations are used in both the horizontal and vertical directions. After a specified transition distance, gradient transfer theory is applied in the vertical direction, while the horizontal dispersion is still assumed to be Gaussian. The dispersion parameters and eddy diffusivity are modelled in a form which facilitates the use of a meteorological pre-processor. Also a new model for the vertical eddy diffusivity (K{sub z}), which is a continuous function of height in the various atmospheric scaling regions is presented. The model includes a treatment of the dry deposition of gases and particulate matter, but wet deposition has been neglected. A numerical solver for the atmospheric diffusion equation (ADE) has been developed. The accuracy of the numerical model was analysed by comparing the model predictions with two analytical solutions of ADE. The numerical deviations of the model predictions from these analytic solutions were less than two per cent for the computational regime. The report gives numerical results for the vertical profiles of the eddy diffusivity and the dispersion parameters, and shows spatial concentration distributions in various atmospheric conditions 39 refs.

  5. 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.

  6. Document localization algorithms based on feature points and straight lines

    Science.gov (United States)

    Skoryukina, Natalya; Shemiakina, Julia; Arlazarov, Vladimir L.; Faradjev, Igor

    2018-04-01

    The important part of the system of a planar rectangular object analysis is the localization: the estimation of projective transform from template image of an object to its photograph. The system also includes such subsystems as the selection and recognition of text fields, the usage of contexts etc. In this paper three localization algorithms are described. All algorithms use feature points and two of them also analyze near-horizontal and near- vertical lines on the photograph. The algorithms and their combinations are tested on a dataset of real document photographs. Also the method of localization quality estimation is proposed that allows configuring the localization subsystem independently of the other subsystems quality.

  7. 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.

  8. Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization

    Directory of Open Access Journals (Sweden)

    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.

  9. The Cellular Differential Evolution Based on Chaotic Local Search

    Directory of Open Access Journals (Sweden)

    Qingfeng Ding

    2015-01-01

    Full Text Available To avoid immature convergence and tune the selection pressure in the differential evolution (DE algorithm, a new differential evolution algorithm based on cellular automata and chaotic local search (CLS or ccDE is proposed. To balance the exploration and exploitation tradeoff of differential evolution, the interaction among individuals is limited in cellular neighbors instead of controlling parameters in the canonical DE. To improve the optimizing performance of DE, the CLS helps by exploring a large region to avoid immature convergence in the early evolutionary stage and exploiting a small region to refine the final solutions in the later evolutionary stage. What is more, to improve the convergence characteristics and maintain the population diversity, the binomial crossover operator in the canonical DE may be instead by the orthogonal crossover operator without crossover rate. The performance of ccDE is widely evaluated on a set of 14 bound constrained numerical optimization problems compared with the canonical DE and several DE variants. The simulation results show that ccDE has better performances in terms of convergence rate and solution accuracy than other optimizers.

  10. Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.

    Science.gov (United States)

    Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

    2015-07-06

    Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches.

  11. Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation

    Science.gov (United States)

    Sun, Xiao; Zhang, Tongda; Chai, Yueting; Liu, Yi

    2015-01-01

    Most of popular clustering methods typically have some strong assumptions of the dataset. For example, the k-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it. PMID:26221133

  12. FIB-based measurement of local residual stresses on microsystems

    Science.gov (United States)

    Vogel, Dietmar; Sabate, Neus; Gollhardt, Astrid; Keller, Juergen; Auersperg, Juergen; Michel, Bernd

    2006-03-01

    The paper comprises research results obtained for stress determination on micro and nanotechnology components. It meets the concern of controlling stresses introduced to sensors, MEMS and electronics devices during different micromachining processes. The method bases on deformation measurement options made available inside focused ion beam equipment. Removing locally material by ion beam milling existing stresses / residual stresses lead to deformation fields around the milled feature. Digital image correlation techniques are used to extract deformation values from micrographs captured before and after milling. In the paper, two main milling features have been analyzed - through hole and through slit milling. Analytical solutions for stress release fields of in-plane stresses have been derived and compared to respective experimental findings. Their good agreement allows to settle a method for determination of residual stress values, which is demonstrated for thin membranes manufactured by silicon micro technology. Some emphasis is made on the elimination of main error sources for stress determination, like rigid body object displacements and rotations due to drifts of experimental conditions under FIB imaging. In order to illustrate potential application areas of the method residual stress suppression by ion implantation is evaluated by the method and reported here.

  13. Activity-based DEVS modeling

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2018-01-01

    architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number......Use of model-driven approaches has been increasing to significantly benefit the process of building complex systems. Recently, an approach for specifying model behavior using UML activities has been devised to support the creation of DEVS models in a disciplined manner based on the model driven...... of the artifacts of the UML 2.5 activities and actions, from the vantage point of DEVS behavioral modeling, is covered in details. Their semantics are discussed to the extent of time-accurate requirements for simulation. We characterize them in correspondence with the specification of the atomic model behavior. We...

  14. Local labor markets and taste-based discrimination

    Directory of Open Access Journals (Sweden)

    Clémence Berson

    2016-04-01

    Full Text Available Abstract This article appeals to heterogeneity in workers’ non-wage preferences to model taste-based discrimination. Firms hire both types of workers and pay lower wages to minority workers, whatever their taste for discrimination. A single prejudiced firm in the market produces a substantial wage gap in all firms. Consequently, discrimination allows unprejudiced firms to make non-zero profits, so that they have little incentive to drive out prejudiced firms. As the market does not eliminate discrimination, state intervention is required. Indirect policies do not affect the absolute wage gap between the two groups, but may be more likely to be used than direct policies.

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

    Directory of Open Access Journals (Sweden)

    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.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. 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.

  19. Local Knowledge and Community–Based Assessment of ...

    African Journals Online (AJOL)

    Agribotix GCS 077

    Rural Appraisal (PRA) methods were employed for data collection and ..... diversity and provide a foundation for locally-appropriate sustainable ..... vegetation was a good habitat for wildlife and one could find daily traces of .... indicators including fruiting of certain local trees, appearance of certain types of frogs and birds,.

  20. 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

  1. 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.

  2. 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.

  3. The pion form factor within the hidden local symmetry model

    International Nuclear Information System (INIS)

    Benayoun, M.; David, P.; DelBuono, L.; Leruste, P.; O'Connell, H.B.

    2003-01-01

    We analyze a pion form factor formulation which fulfills the Analyticity requirement within the Hidden Local Symmetry (HLS) Model. This implies an s-dependent dressing of the ρ-γ VMD coupling and an account of several coupled channels. The corresponding function F π (s) provides nice fits of the pion form factor data from s=-0.25 to s=1 GeV 2 . It is shown that the coupling to KK has little effect, while ωπ 0 improves significantly the fit probability below the φ mass. No need for additional states like ρ(1450) shows up in this invariant-mass range. All parameters, except for the subtraction polynomial coefficients, are fixed from the rest of the HLS phenomenology. The fits show consistency with the expected behaviour of F π (s) at s=0 up to O(s 2 ) and with the phase shift data on δ 1 1 (s) from threshold to somewhat above the φ mass. The ω sector is also examined in relation with recent data from CMD-2. (orig.)

  4. 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

  5. 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.

  6. 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.

  7. Local and regional energy companies offering energy services: Key activities and implications for the business model

    International Nuclear Information System (INIS)

    Kindström, Daniel; Ottosson, Mikael

    2016-01-01

    Highlights: • Many companies providing energy services are experiencing difficulties. • This research identifies key activities for the provision of energy services. • Findings are aggregated to the business-model level providing managerial insights. • This research identifies two different business model innovation paths. • Energy companies may need to renew parts of, or the entire, business model. - Abstract: Energy services play a key role in increasing energy efficiency in the industry. The key actors in these services are the local and regional energy companies that are increasingly implementing energy services as part of their market offering and developing service portfolios. Although expectations for energy services have been high, progress has so far been limited, and many companies offering energy services, including energy companies, are experiencing difficulties in implementing energy services and providing them to the market. Overall, this research examines what is needed for local and regional energy companies to successfully implement energy services (and consequently provide them to the market). In doing this, a two-stage process is used: first, we identify key activities for the successful implementation of energy services, and second, we aggregate the findings to the business model level. This research demonstrates that to succeed in implementing energy services, an energy company may need to renew parts or all of its existing product-based business model, formulate a new business model, or develop coexisting multiple business models. By discussing two distinct business model innovation processes, this research demonstrates that there can be different paths to success.

  8. Local Balancing System from the Business Model Canvas Perspective

    Directory of Open Access Journals (Sweden)

    Matusiak Bożena Ewa

    2016-01-01

    Full Text Available The paper presents an overall view of the business model (BM for the e-balance system for: balancing energy production and consumption in energy efficient, smart neighbourhoods (the e-balance project, FP7-SMARTCITIES-2013 along with its functionalities, based upon the Osterwalder’s canvas methodology. Additionally, this is the second, after two years of work, more incisive evaluation of the BM from the user’s and demo site’s perspective (Bronsbergen, the Netherlands. The aim of this paper is to present results and assess the above mentioned BM in the face its commercialisation and applicability to Europe.

  9. Resonance fluorescence based two- and three-dimensional atom localization

    Science.gov (United States)

    Wahab, Abdul; Rahmatullah; Qamar, Sajid

    2016-06-01

    Two- and three-dimensional atom localization in a two-level atom-field system via resonance fluorescence is suggested. For the two-dimensional localization, the atom interacts with two orthogonal standing-wave fields, whereas for the three-dimensional atom localization, the atom interacts with three orthogonal standing-wave fields. The effect of the detuning and phase shifts associated with the corresponding standing-wave fields is investigated. A precision enhancement in position measurement of the single atom can be noticed via the control of the detuning and phase shifts.

  10. 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

  11. A note on eigenfrequency sensitivities and structural eigenfrequency optimization based on local sub-domain frequencies

    DEFF Research Database (Denmark)

    Pedersen, Pauli; Pedersen, Niels Leergaard

    2014-01-01

    foundation. A numerical heuristic redesign procedure is proposed and illustrated with examples. For the ideal case, an optimality criterion is fulfilled if the design have the same sub-domain frequency (local Rayleigh quotient). Sensitivity analysis shows an important relation between squared system...... eigenfrequency and squared local sub-domain frequency for a given eigenmode. Higher order eigenfrequenciesmay also be controlled in this manner. The presented examples are based on 2D finite element models with the use of subspace iteration for analysis and a heuristic recursive design procedure based...... on the derived optimality condition. The design that maximize a frequency depend on the total amount of available material and on a necessary interpolation as illustrated by different design cases.In this note we have assumed a linear and conservative eigenvalue problem without multiple eigenvalues. The presence...

  12. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....

  13. A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

    Science.gov (United States)

    Hegermiller, Christie; Antolinez, Jose A A; Rueda, Ana C.; Camus, Paula; Perez, Jorge; Erikson, Li; Barnard, Patrick; Mendez, Fernando J.

    2017-01-01

    Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

  14. Impact Localization Method for Composite Plate Based on Low Sampling Rate Embedded Fiber Bragg Grating Sensors

    Directory of Open Access Journals (Sweden)

    Zhuo Pang

    2017-01-01

    Full Text Available Fiber Bragg Grating (FBG sensors have been increasingly used in the field of Structural Health Monitoring (SHM in recent years. In this paper, we proposed an impact localization algorithm based on the Empirical Mode Decomposition (EMD and Particle Swarm Optimization-Support Vector Machine (PSO-SVM to achieve better localization accuracy for the FBG-embedded plate. In our method, EMD is used to extract the features of FBG signals, and PSO-SVM is then applied to automatically train a classification model for the impact localization. Meanwhile, an impact monitoring system for the FBG-embedded composites has been established to actually validate our algorithm. Moreover, the relationship between the localization accuracy and the distance from impact to the nearest sensor has also been studied. Results suggest that the localization accuracy keeps increasing and is satisfactory, ranging from 93.89% to 97.14%, on our experimental conditions with the decrease of the distance. This article reports an effective and easy-implementing method for FBG signal processing on SHM systems of the composites.

  15. A Stochastic Unit Commitment Model for a Local CHP Plant

    DEFF Research Database (Denmark)

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

    2005-01-01

    Local CHP development in Denmark has during the 90’s been characterised by large growth primarily due to government subsidies in the form of feed-in tariffs. In line with the liberalisation process in the EU, Danish local CHPs of a certain size must operate on market terms from 2005. This paper...

  16. 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.

  17. Graph-Based Cooperative Localization Using Symmetric Measurement Equations.

    Science.gov (United States)

    Gulati, Dhiraj; Zhang, Feihu; Clarke, Daniel; Knoll, Alois

    2017-06-17

    Precise localization is a key requirement for the success of highly assisted or autonomous vehicles. The diminishing cost of hardware has resulted in a proliferation of the number of sensors in the environment. Cooperative localization (CL) presents itself as a feasible and effective solution for localizing the ego-vehicle and its neighboring vehicles. However, one of the major challenges to fully realize the effective use of infrastructure sensors for jointly estimating the state of a vehicle in cooperative vehicle-infrastructure localization is an effective data association. In this paper, we propose a method which implements symmetric measurement equations within factor graphs in order to overcome the data association challenge with a reduced bandwidth overhead. Simulated results demonstrate the benefits of the proposed approach in comparison with our previously proposed approach of topology factors.

  18. Local Knowledge and Community–Based Assessment of ...

    African Journals Online (AJOL)

    Although much scientific knowledge exists about global environmental ... to an understanding of local knowledge on environmental change through Community Risk ... Rural Appraisal (PRA) methods were employed for data collection and ...

  19. HMM-based Trust Model

    DEFF Research Database (Denmark)

    ElSalamouny, Ehab; Nielsen, Mogens; Sassone, Vladimiro

    2010-01-01

    Probabilistic trust has been adopted as an approach to taking security sensitive decisions in modern global computing environments. Existing probabilistic trust frameworks either assume fixed behaviour for the principals or incorporate the notion of ‘decay' as an ad hoc approach to cope...... with their dynamic behaviour. Using Hidden Markov Models (HMMs) for both modelling and approximating the behaviours of principals, we introduce the HMM-based trust model as a new approach to evaluating trust in systems exhibiting dynamic behaviour. This model avoids the fixed behaviour assumption which is considered...... the major limitation of existing Beta trust model. We show the consistency of the HMM-based trust model and contrast it against the well known Beta trust model with the decay principle in terms of the estimation precision....

  20. 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.

  1. 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.

  2. Inhibition of bcl-2 and cox-2 Protein Expression after Local Application of a New Carmustine-Loaded Clinoptilolite-Based Delivery System in a Chemically Induced Skin Cancer Model in Mice

    Directory of Open Access Journals (Sweden)

    Cristina Mihaela Ghiciuc

    2017-11-01

    Full Text Available Our research has focused on in vitro and in vivo evaluations of a new Carmustine (BCNU-loaded clinoptilolite-based delivery system. Two clinoptilolite ionic forms—hydrogen form (HCLI and sodium form (NaCLI—were prepared, allowing a loading degree of about 5–6 mg BCNU/g of zeolite matrix due to the dual porous feature of clinoptilolite. Clinoptilolite-based delivery systems released 35.23% of the load in 12 h for the BCNU@HCLI system and only 10.82% for the BCNU@NaCLI system. The BCNU@HCLI system was chosen to develop gel and cream semisolid dosage forms. The cream (C_BCNU@HCLI released 29.6% of the loaded BCNU after 12 h in the Nylon synthetic membrane test and 31.6% in the collagen membrane test, higher by comparison to the gel. The new cream was evaluated in vivo in a chemically induced model of skin cancer in mice. Quantitative immunohistochemistry analysis showed stronger inhibition of B-cell lymphoma-2 (bcl-2 and cyclooxygenase 2 (cox-2 protein expression, known markers for cancer survival and aggressiveness, after the treatment with C_BCNU@HCLI by comparison to all the control treatment types, including an off-label magistral formula commercially available Carmustine cream as reference, bringing evidence that a clinoptilolite-based delivery systems could be used as a cancer drug carriers and controlled release systems (skin-targeted topical delivery systems.

  3. 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.

  4. 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...

  5. 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} .

  6. 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.

  7. 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.

  8. 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.

  9. Local stem cell depletion model for radiation myelitis

    International Nuclear Information System (INIS)

    Yaes, R.J.; Kalend, A.

    1988-01-01

    We propose a model for normal tissue damage based on the assumption that adult mammalian stem cells have limited mobility and, consequently, for each organ, there is a maximum volume (the critical volume, Vc), that can be repopulated and repaired by a single surviving stem cell. This concept is applied to a simple, 1-dimensional model of the spinal cord, where the critical volume is a slice of thickness, t, assumed to be small compared to lengths of spinal cord usually irradiated clinically. The probability of myelitis is explicitly obtained as a function of the dose, dose per fraction, length of cord irradiated, slice thickness, number of stem cells per slice and parameters alpha and beta of the stem cell survival curve. The complication probability is expressed as a triple negative exponential function of dose analogous to the double negative exponential function for tumor control, resulting in a steep dose-response curve with short tails in both the high dose and low dose regions. We show that the model predictions are compatible with the experimental data for radiation myelitis in the rat. We discuss how this concept can be applied to other organs such as skin and to organs composed of structurally and functionally distinct subunits, such as the kidney

  10. Benchmark of the local drift-kinetic models for neoclassical transport simulation in helical plasmas

    Science.gov (United States)

    Huang, B.; Satake, S.; Kanno, R.; Sugama, H.; Matsuoka, S.

    2017-02-01

    The benchmarks of the neoclassical transport codes based on the several local drift-kinetic models are reported here. Here, the drift-kinetic models are zero orbit width (ZOW), zero magnetic drift, DKES-like, and global, as classified in Matsuoka et al. [Phys. Plasmas 22, 072511 (2015)]. The magnetic geometries of Helically Symmetric Experiment, Large Helical Device (LHD), and Wendelstein 7-X are employed in the benchmarks. It is found that the assumption of E ×B incompressibility causes discrepancy of neoclassical radial flux and parallel flow among the models when E ×B is sufficiently large compared to the magnetic drift velocities. For example, Mp≤0.4 where Mp is the poloidal Mach number. On the other hand, when E ×B and the magnetic drift velocities are comparable, the tangential magnetic drift, which is included in both the global and ZOW models, fills the role of suppressing unphysical peaking of neoclassical radial-fluxes found in the other local models at Er≃0 . In low collisionality plasmas, in particular, the tangential drift effect works well to suppress such unphysical behavior of the radial transport caused in the simulations. It is demonstrated that the ZOW model has the advantage of mitigating the unphysical behavior in the several magnetic geometries, and that it also implements the evaluation of bootstrap current in LHD with the low computation cost compared to the global model.

  11. Modeling Guru: Knowledge Base for NASA Modelers

    Science.gov (United States)

    Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

    2009-05-01

    Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

  12. A Local Land Use Competition Cellular Automata Model and Its Application

    Directory of Open Access Journals (Sweden)

    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.

  13. 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)

  14. Structure-Based Turbulence Model

    National Research Council Canada - National Science Library

    Reynolds, W

    2000-01-01

    .... Maire carried out this work as part of his Phi) research. During the award period we began to explore ways to simplify the structure-based modeling so that it could be used in repetitive engineering calculations...

  15. 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)

  16. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  17. A local-world node deleting evolving network model

    International Nuclear Information System (INIS)

    Gu Yuying; Sun Jitao

    2008-01-01

    A new type network growth rule which comprises node addition with the concept of local-world connectivity and node deleting is studied. A series of theoretical analysis and numerical simulation to the LWD network are conducted in this Letter. Firstly, the degree distribution p(k) of this network changes no longer pure scale free but truncates by an exponential tail and the truncation in p(k) increases as p a decreases. Secondly, the connectivity is tighter, as the local-world size M increases. Thirdly, the average path length L increases and the clustering coefficient decreases as generally node deleting increases. Finally, trends up when the local-world size M increases, so as to k max . Hence, the expanding local-world can compensate the infection of the node deleting

  18. A local-world node deleting evolving network model

    Energy Technology Data Exchange (ETDEWEB)

    Gu Yuying [Department of Mathematics, Tongji University, Shanghai 200092 (China); Sun Jitao [Department of Mathematics, Tongji University, Shanghai 200092 (China)], E-mail: sunjt@sh163.net

    2008-06-16

    A new type network growth rule which comprises node addition with the concept of local-world connectivity and node deleting is studied. A series of theoretical analysis and numerical simulation to the LWD network are conducted in this Letter. Firstly, the degree distribution p(k) of this network changes no longer pure scale free but truncates by an exponential tail and the truncation in p(k) increases as p{sub a} decreases. Secondly, the connectivity is tighter, as the local-world size M increases. Thirdly, the average path length L increases and the clustering coefficient decreases as generally node deleting increases. Finally, trends up when the local-world size M increases, so as to k{sub max}. Hence, the expanding local-world can compensate the infection of the node deleting.

  19. Coupling of nonlocal and local continuum models by the Arlequinapproach

    KAUST Repository

    Han, Fei; Lubineau, Gilles

    2011-01-01

    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

  20. Connecting Global to Local Parameters in Barred Galaxy Models

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Key words. Galaxies: barred—orbits—global and local parameters. .... series near the stable Lagrange point L1, which coincides with the origin. Doing so, .... Toomre, A. 1981, In: The Structure and Evolution of Normal Galaxies, (eds) S. M. Fall,.

  1. 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...

  2. Computer Based Modelling and Simulation

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 6; Issue 3. Computer Based Modelling and Simulation - Modelling Deterministic Systems. N K Srinivasan. General Article Volume 6 Issue 3 March 2001 pp 46-54. Fulltext. Click here to view fulltext PDF. Permanent link:

  3. 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

  4. Tree detection in urban regions from aerial imagery and DSM based on local maxima points

    Science.gov (United States)

    Korkmaz, Özgür; Yardımcı ćetin, Yasemin; Yilmaz, Erdal

    2017-05-01

    In this study, we propose an automatic approach for tree detection and classification in registered 3-band aerial images and associated digital surface models (DSM). The tree detection results can be used in 3D city modelling and urban planning. This problem is magnified when trees are in close proximity to each other or other objects such as rooftops in the scenes. This study presents a method for locating individual trees and estimation of crown size based on local maxima from DSM accompanied by color and texture information. For this purpose, segment level classifier trained for 10 classes and classification results are improved by analyzing the class probabilities of neighbour segments. Later, the tree classes under a certain height were eliminated using the Digital Terrain Model (DTM). For the tree classes, local maxima points are obtained and the tree radius estimate is made from the vertical and horizontal height profiles passing through these points. The final tree list containing the centers and radius of the trees is obtained by selecting from the list of tree candidates according to the overlapping and selection parameters. Although the limited number of train sets are used in this study, tree classification and localization results are competitive.

  5. Comparison of Modeling Grassland Degradation with and without Considering Localized Spatial Associations in Vegetation Changing Patterns

    Directory of Open Access Journals (Sweden)

    Yuwei Wang

    2018-01-01

    Full Text Available Grassland ecosystems worldwide are confronted with degradation. It is of great importance to understand long-term trajectory patterns of grassland vegetation by advanced analytical models. This study proposes a new approach called a binary logistic regression model with neighborhood interactions, or BLR-NIs, which is based on binary logistic regression (BLR, but fully considers the spatio-temporally localized spatial associations or characterization of neighborhood interactions (NIs in the patterns of grassland vegetation. The BLR-NIs model was applied to a modeled vegetation degradation of grasslands in the Xilin river basin, Inner Mongolia, China. Residual trend analysis on the normalized difference vegetation index (RESTREND-NDVI, which excluded the climatic impact on vegetation dynamics, was adopted as a preprocessing step to derive three human-induced trajectory patterns (vegetation degradation, vegetation recovery, and no significant change in vegetation during two consecutive periods, T1 (2000–2008 and T2 (2007–2015. Human activities, including livestock grazing intensity and transportation accessibility measured by road network density, were included as explanatory variables for vegetation degradation, which was defined for locations if vegetation recovery or no significant change in vegetation in T1 and vegetation degradation in T2 were observed. Our work compared the results of BLR-NIs and the traditional BLR model that did not consider NIs. The study showed that: (1 both grazing intensity and road density had a positive correlation to vegetation degradation based on the traditional BLR model; (2 only road density was found to positively correlate to vegetation degradation by the BLR-NIs model; NIs appeared to be critical factors to predict vegetation degradation; and (3 including NIs in the BLR model improved the model performance substantially. The study provided evidence for the importance of including localized spatial

  6. 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

  7. 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

  8. 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.

  9. 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

  10. Localized electrochemical corrosion of nickel-based alloys. Final report

    International Nuclear Information System (INIS)

    Isaacs, H.S.; Oyeleye, O.; Davidson, M.; Dudek, D.; Hatton, T.A.; Tester, J.W.; Helling, R.K.; Erickson, J.C.

    1986-09-01

    The technique of monitoring open-circuit potential over time to study pitting corrosion of Alloy 600 was demonstrated at 95 0 C. Chloride ion and oxygen levels were varied to determine the conditions required for pit initiation and propagation at 25 0 C and 95 0 C. Without applied potential pitting was not observed at 25 0 C in solutions of up to 2.6 M NaCl. At 95 0 C pit initiation occurred above 0.22 M NaCl for a nitrogen sparged system, 0.042 M NaCl for a contaminated air sparged system and 0.059 M for an O 2 sparged system. At 95 0 C initiation followed by propagation was observed at 0.22 M, 0.12 M and 0.11 M NaCl for the N 2 , air and O 2 sparged systems, respectively. A theoretical model, using a hemispherical pit geometry and transport based on the Nernst-Einstein equation, was developed to predict changes in ion concentration, current and pit size. For a pit with an initial radius of 100 A, a fixed potential difference of 0.5 V and constant ionic diffusivities on the order of 10 -5 , cm 2 /sec, the model predicts that the solution within the pit will become saturated with metal chloride within 2 x 10 -7 seconds. The current density increases exponentially with time and reaches a maximum value of 7.2 x 10 4 A/cm 2 at the point of saturation

  11. Genetic diversity of Ghanaian local chicken populations based on ...

    African Journals Online (AJOL)

    In Ghana, local chickens are raised across distinct agro-ecological zones and constitute unique populations with variable phenotypes that need to be characterized to provide needed information for the conservation of useful genotypes against future needs. In particular, the Interior Savannah (GHIS) in the north, the Forest ...

  12. Measurement-based local quantum filters and their ability to ...

    Indian Academy of Sciences (India)

    Debmalya Das

    2017-05-30

    May 30, 2017 ... Entanglement; local filters; quantum measurement. PACS No. 03.65 ... ties [4,5], it also plays a key role in quantum computing where it is ... Furthermore, we pro- vide an ..... Corresponding to each of these vectors, we can con-.

  13. Measurement-based local quantum filters and their ability to ...

    Indian Academy of Sciences (India)

    Debmalya Das

    Berhampur (Transit Campus), National Highway 59, Berhampur 760 010, India. ∗. Corresponding author. E-mail: arvind@iisermohali.ac.in. MS received 29 July 2016; revised 21 October 2016; accepted 16 December 2016; published online 30 May 2017. Abstract. We introduce local filters as a means to detect the ...

  14. Spectrum-based Fault Localization in Embedded Software

    NARCIS (Netherlands)

    Abreu, R.

    2009-01-01

    Locating software components that are responsible for observed failures is a time-intensive and expensive phase in the software development cycle. Automatic fault localization techniques aid developers/testers in pinpointing the root cause of software failures, as such reducing the debugging effort.

  15. A special purpose knowledge-based face localization method

    Science.gov (United States)

    Hassanat, Ahmad; Jassim, Sabah

    2008-04-01

    This paper is concerned with face localization for visual speech recognition (VSR) system. Face detection and localization have got a great deal of attention in the last few years, because it is an essential pre-processing step in many techniques that handle or deal with faces, (e.g. age, face, gender, race and visual speech recognition). We shall present an efficient method for localization human's faces in video images captured on mobile constrained devices, under a wide variation in lighting conditions. We use a multiphase method that may include all or some of the following steps starting with image pre-processing, followed by a special purpose edge detection, then an image refinement step. The output image will be passed through a discrete wavelet decomposition procedure, and the computed LL sub-band at a certain level will be transformed into a binary image that will be scanned by using a special template to select a number of possible candidate locations. Finally, we fuse the scores from the wavelet step with scores determined by color information for the candidate location and employ a form of fuzzy logic to distinguish face from non-face locations. We shall present results of large number of experiments to demonstrate that the proposed face localization method is efficient and achieve high level of accuracy that outperforms existing general-purpose face detection methods.

  16. Local and global trust based on the concept of promises

    NARCIS (Netherlands)

    Bergstra, J.; Burgess, M.

    2009-01-01

    We use the notion of a promise to define local trust between agents possessing autonomous decision-making. An agent is trustworthy if it is expected that it will keep a promise. This definition satisfies most commonplace meanings of trust. Reputation is then an estimation of this expectation value

  17. Localization and Communication for UWB-based Wireless Sensor Networks

    NARCIS (Netherlands)

    Wang, Y.

    2011-01-01

    The great demand for location-aware wireless sensor networks (WSNs) motivates the research in this thesis. The unique characteristics of WSNs impose numerous challenges on localization and communication. In this thesis, we handle some key challenges and provide affordable solutions. Impulse radio

  18. High-resolution biosensor based on localized surface plasmons

    Czech Academy of Sciences Publication Activity Database

    Piliarik, Marek; Šípová, Hana; Kvasnička, Pavel; Galler, N.; Krenn, J. R.; Homola, Jiří

    2012-01-01

    Roč. 20, č. 1 (2012), s. 672-680 ISSN 1094-4087 R&D Projects: GA AV ČR KAN200670701; GA MŠk OC09058 Institutional research plan: CEZ:AV0Z20670512 Keywords : optical biosenzor * surface plasmon resonance * localized surface plasmon Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 3.546, year: 2012

  19. Local energy developments based on spatial and systemic approaches

    NARCIS (Netherlands)

    Manickam, Anu

    Local energy developments from a spatial and systemic approach are highlighted using examples from a Dutch case study. Developments in energy systems included interconnectedness of contextual factors and systems responses. The need to explore both the contextual factors and systemic aspects are

  20. Alteration of 'R7T7' type nuclear glasses: statistical approach, experimental validation, local evolution model

    International Nuclear Information System (INIS)

    Thierry, F.

    2003-02-01

    The aim of this work is to propose an evolution of nuclear (R7T7-type) glass alteration modeling. The first part of this thesis is about development and validation of the 'r(t)' model. This model which predicts the decrease of alteration rates in confined conditions is based upon a coupling between a first-order dissolution law and a diffusion barrier effect of the alteration gel layer. The values and the uncertainties regarding the main adjustable parameters of the model (α, Dg and C*) have been determined from a systematic study of the available experimental data. A program called INVERSION has been written for this purpose. This work lead to characterize the validity domain of the 'r(t)' model and to parametrize it. Validation experiments have been undertaken, confirming the validity of the parametrization over 200 days. A new model is proposed in the second part of this thesis. It is based on an inhibition of glass dissolution reaction by silicon coupled with a local description of silicon retention in the alteration gel layer. This model predicts the evolutions of boron and silicon concentrations in solution as well as the concentrations and retention profiles in the gel layer. These predictions have been compared to measurements of retention profiles by the secondary ion mass spectrometry (SIMS) method. The model has been validated on fractions of gel layer which reactivity present low or moderate disparities. (author)

  1. Fast subcellular localization by cascaded fusion of signal-based and homology-based methods

    Directory of Open Access Journals (Sweden)

    Wang Wei

    2011-10-01

    Full Text Available Abstract Background The functions of proteins are closely related to their subcellular locations. In the post-genomics era, the amount of gene and protein data grows exponentially, which necessitates the prediction of subcellular localization by computational means. Results This paper proposes mitigating the computation burden of alignment-based approaches to subcellular localization prediction by a cascaded fusion of cleavage site prediction and profile alignment. Specifically, the informative segments of protein sequences are identified by a cleavage site predictor using the information in their N-terminal shorting signals. Then, the sequences are truncated at the cleavage site positions, and the shortened sequences are passed to PSI-BLAST for computing their profiles. Subcellular localization are subsequently predicted by a profile-to-profile alignment support-vector-machine (SVM classifier. To further reduce the training and recognition time of the classifier, the SVM classifier is replaced by a new kernel method based on the perturbational discriminant analysis (PDA. Conclusions Experimental results on a new dataset based on Swiss-Prot Release 57.5 show that the method can make use of the best property of signal- and homology-based approaches and can attain an accuracy comparable to that achieved by using full-length sequences. Analysis of profile-alignment score matrices suggest that both profile creation time and profile alignment time can be reduced without significant reduction in subcellular localization accuracy. It was found that PDA enjoys a short training time as compared to the conventional SVM. We advocate that the method will be important for biologists to conduct large-scale protein annotation or for bioinformaticians to perform preliminary investigations on new algorithms that involve pairwise alignments.

  2. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  3. Local Politics and Portfolio Management Models: National Reform Ideas and Local Control

    Science.gov (United States)

    Bulkley, Katrina E.; Henig, Jeffrey R.

    2015-01-01

    Amid the growth of charter schools, autonomous schools, and private management organizations, an increasing number of urban districts are moving toward a portfolio management model (PMM). In a PMM, the district central office oversees schools that operate under a variety of governance models. The expansion of PMMs raises questions about local…

  4. 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.

  5. 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

  6. RANS modeling of scalar dispersion from localized sources within a simplified urban-area model

    Science.gov (United States)

    Rossi, Riccardo; Capra, Stefano; Iaccarino, Gianluca

    2011-11-01

    The dispersion of a passive scalar downstream a localized source within a simplified urban-like geometry is examined by means of RANS scalar flux models. The computations are conducted under conditions of neutral stability and for three different incoming wind directions (0°, 45°, 90°) at a roughness Reynolds number of Ret = 391. A Reynolds stress transport model is used to close the flow governing equations whereas both the standard eddy-diffusivity closure and algebraic flux models are employed to close the transport equation for the passive scalar. The comparison with a DNS database shows improved reliability from algebraic scalar flux models towards predicting both the mean concentration and the plume structure. Since algebraic flux models do not increase substantially the computational effort, the results indicate that the use of tensorial-diffusivity can be promising tool for dispersion simulations for the urban environment.

  7. Lumped Mass Modeling for Local-Mode-Suppressed Element Connectivity

    DEFF Research Database (Denmark)

    Joung, Young Soo; Yoon, Gil Ho; Kim, Yoon Young

    2005-01-01

    connectivity parameterization (ECP) is employed. On the way to the ultimate crashworthy structure optimization, we are now developing a local mode-free topology optimization formulation that can be implemented in the ECP method. In fact, the local mode-freeing strategy developed here can be also used directly...... experiencing large structural changes, appears to be still poor. In ECP, the nodes of the domain-discretizing elements are connected by zero-length one-dimensional elastic links having varying stiffness. For computational efficiency, every elastic link is now assumed to have two lumped masses at its ends....... Choosing appropriate penalization functions for lumped mass and link stiffness is important for local mode-free results. However, unless the objective and constraint functions are carefully selected, it is difficult to obtain clear black-and-white results. It is shown that the present formulation is also...

  8. 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

  9. 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.

  10. 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.

  11. Multiobjective Memetic Estimation of Distribution Algorithm Based on an Incremental Tournament Local Searcher

    Directory of Open Access Journals (Sweden)

    Kaifeng Yang

    2014-01-01

    Full Text Available A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

  12. Multiobjective memetic estimation of distribution algorithm based on an incremental tournament local searcher.

    Science.gov (United States)

    Yang, Kaifeng; Mu, Li; Yang, Dongdong; Zou, Feng; Wang, Lei; Jiang, Qiaoyong

    2014-01-01

    A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

  13. Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Pablo Marin-Plaza

    2018-01-01

    Full Text Available The aim of this work is to integrate and analyze the performance of a path planning method based on Time Elastic Bands (TEB in real research platform based on Ackermann model. Moreover, it will be proved that all modules related to the navigation can coexist and work together to achieve the goal point without any collision. The study is done by analyzing the trajectory generated from global and local planners. The software prototyping tool is Robot Operating System (ROS from Open Source Robotics Foundation and the research platform is the iCab (Intelligent Campus Automobile from University Carlos III. This work has been validated from a test inside the campus where the iCab has performed the navigation between the starting point and the goal point without any collision. During the experiment, we proved the low sensitivity of the TEB method to variations of the vehicle model configuration and constraints.

  14. 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...

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

    KAUST Repository

    Pan, B.; Wang, Bo; Lubineau, Gilles

    2016-01-01

    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

  16. Quantitative generalized ratiometric fluorescence spectroscopy for turbid media based on probe encapsulated by biologically localized embedding

    International Nuclear Information System (INIS)

    Yan, Xiu-Fang; Chen, Zeng-Ping; Cui, Yin-Yin; Hu, Yuan-Liang; Yu, Ru-Qin

    2016-01-01

    PEBBLE (probe encapsulated by biologically localized embedding) nanosensor encapsulating an intensity-based fluorescence indicator and an inert reference fluorescence dye inside the pores of stable matrix can be used as a generalized wavelength-ratiometric probe. However, the lack of an efficient quantitative model render the choices of inert reference dyes and intensity-based fluorescence indicators used in PEBBLEs based generalized wavelength-ratiometric probes rather limited. In this contribution, an extended quantitative fluorescence model was derived specifically for generalized wavelength-ratiometric probes based on PEBBLE technique (QFM GRP ) with a view to simplify the design of PEBBLEs and hence further extend their application potentials. The effectiveness of QFM GRP has been tested on the quantitative determination of free Ca 2+ in both simulated and real turbid media using a Ca 2+ sensitive PEBBLE nanosensor encapsulating Rhod-2 and eosin B inside the micropores of stable polyacrylamide matrix. Experimental results demonstrated that QFM GRP could realize precise and accurate quantification of free Ca 2+ in turbid samples, even though there is serious overlapping between the fluorescence excitation peaks of eosin B and Ca 2+ bound Rhod-2. The average relative predictive error value of QFM GRP for the test simulated turbid samples was 5.9%, about 2–4 times lower than the corresponding values of partial least squares calibration model and the empirical ratiometric model based on the ratio of fluorescence intensities at the excitation peaks of Ca 2+ bound Rhod-2 and eosin B. The recovery rates of QFM GRP for the real and spiked turbid samples varied from 93.1% to 101%, comparable to the corresponding results of atomic absorption spectrometry. - Highlights: • An advanced model was derived for generalized wavelength-ratiometric PEBBLEs. • The model can simplify the design of generalized wavelength-ratiometric PEBBLEs. • The model realized accurate

  17. Efficient modeling of photonic crystals with local Hermite polynomials

    International Nuclear Information System (INIS)

    Boucher, C. R.; Li, Zehao; Albrecht, J. D.; Ram-Mohan, L. R.

    2014-01-01

    Developing compact algorithms for accurate electrodynamic calculations with minimal computational cost is an active area of research given the increasing complexity in the design of electromagnetic composite structures such as photonic crystals, metamaterials, optical interconnects, and on-chip routing. We show that electric and magnetic (EM) fields can be calculated using scalar Hermite interpolation polynomials as the numerical basis functions without having to invoke edge-based vector finite elements to suppress spurious solutions or to satisfy boundary conditions. This approach offers several fundamental advantages as evidenced through band structure solutions for periodic systems and through waveguide analysis. Compared with reciprocal space (plane wave expansion) methods for periodic systems, advantages are shown in computational costs, the ability to capture spatial complexity in the dielectric distributions, the demonstration of numerical convergence with scaling, and variational eigenfunctions free of numerical artifacts that arise from mixed-order real space basis sets or the inherent aberrations from transforming reciprocal space solutions of finite expansions. The photonic band structure of a simple crystal is used as a benchmark comparison and the ability to capture the effects of spatially complex dielectric distributions is treated using a complex pattern with highly irregular features that would stress spatial transform limits. This general method is applicable to a broad class of physical systems, e.g