A locally adaptive normal distribution

DEFF Research Database (Denmark)

Arvanitidis, Georgios; Hansen, Lars Kai; Hauberg, Søren

2016-01-01

entropy distribution under the given metric. The underlying metric is, however, non-parametric. We develop a maximum likelihood algorithm to infer the distribution parameters that relies on a combination of gradient descent and Monte Carlo integration. We further extend the LAND to mixture models......The multivariate normal density is a monotonic function of the distance to the mean, and its ellipsoidal shape is due to the underlying Euclidean metric. We suggest to replace this metric with a locally adaptive, smoothly changing (Riemannian) metric that favors regions of high local density...

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.

Scalable and Fully Distributed Localization in Large-Scale Sensor Networks

Directory of Open Access Journals (Sweden)

Miao Jin

2017-06-01

Full Text Available This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of the measurement error at one sensor node is limited within a small area of the network around the node. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing the superior performance of the proposed algorithm.

Supervisor localization a top-down approach to distributed control of discrete-event systems

CERN Document Server

Cai, Kai

2016-01-01

This monograph presents a systematic top-down approach to distributed control synthesis of discrete-event systems (DES). The approach is called supervisor localization; its essence is the allocation of external supervisory control action to individual component agents as their internal control strategies. The procedure is: first synthesize a monolithic supervisor, to achieve globally optimal and nonblocking controlled behavior, then decompose the monolithic supervisor into local controllers, one for each agent. The collective behavior of the resulting local controllers is identical to that achieved by the monolithic supervisor. The basic localization theory is first presented in the Ramadge–Wonham language-based supervisory control framework, then demonstrated with distributed control examples of multi-robot formations, manufacturing systems, and distributed algorithms. An architectural approach is adopted to apply localization to large-scale DES; this yields a heterarchical localization procedure, which is...

Restructuring local distribution services: Possibilities and limitations

Energy Technology Data Exchange (ETDEWEB)

Duann, D.J.

1994-08-01

The restructuring of local distribution services is now the focus of the natural gas industry. It is the last major step in the ``reconstitution`` of the natural gas industry and a critical clement in realizing the full benefits of regulatory and market reforms that already have taken place in the wellhead and interstate markets. It could also be the most important regulatory initiative for most end-use customers because they are affected directly by the costs and reliability of distribution services. Several factors contribute to the current emphasis on distribution service restructuring. They include the unbundling and restructuring of upstream markets, a realization of the limitations of supply-side options (such as gas procurement oversight), and the increased diversity and volatility of gas demand facing local distribution companies. Local distribution service is not one but a series of activities that start with commodity gas procurement and extend to transportation, load balancing, storage, and metering and billing of services provided. There are also considerable differences in the economies of scale and scope associated with these various activities. Thus, a mixture of supply arrangements (such as a competitive market or a monopoly) is required for the most efficient delivery of local distribution services. A distinction must be made between the supply of commodity gas and the provision of a bundled distribution service. This distinction and identification of the best supply arrangements for various distribution service components are the most critical factors in developing appropriate restructuring policies. For most state public utility commissions the criteria for service restructuring should include pursuing the economies of scale and scope in gas distribution, differentiating and matching gas service reliability and quality with customer requirements, and controlling costs associated with the search, negotiation, and contracting of gas services.

Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.

Science.gov (United States)

Gangnon, Ronald E

2012-03-01

The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.

Agent-based distributed hierarchical control of dc microgrid systems

DEFF Research Database (Denmark)

Meng, Lexuan; Vasquez, Juan Carlos; Guerrero, Josep M.

2014-01-01

In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken as ....... Standard genetic algorithm is applied in each local control system in order to search for a global optimum. Hardware-in-Loop simulation results are shown to demonstrate the effectiveness of the method.......In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken...... as a case study. The objective is to enhance the system efficiency by finding the optimal sharing ratio of load current. Virtual resistances in local control systems are taken as decision variables. Consensus algorithms are applied for global information discovery and local control systems coordination...

Distribution costs -- the cost of local delivery

International Nuclear Information System (INIS)

Winger, N.; Zarnett, P.; Carr, J.

2000-01-01

Most of the power transmission system in the province of Ontario is owned and operated as a regulated monopoly by Ontario Hydro Services Company (OHSC). Local distribution systems deliver to end-users from bulk supply points within a service territory. OHSC distributes to approximately one million, mostly rural customers, while the approximately 250 municipal utilities together serve about two million, mostly urban customers. Under the Energy Competition Act of 1998 local distribution companies will face some new challenges, including unbundled billing systems, a broader range of distribution costs, increased costs, made up of corporate taxes or payments in lieu of taxes and added costs for regulatory affairs. The consultants provide a detailed discussion of the components of distribution costs, the three components of the typical budget process (capital expenditures, (CAPEX), operating and maintenance (O and M) and administration and corporate (GA and C), a summary of some typical distribution costs in Ontario, and the estimated impacts of the Energy Competition Act (ECA) compliance on charges and rates. Various mitigation strategies are also reviewed. Among these are joint ventures by local distribution companies to reduce ECA compliance costs, re-examination of controllable costs, temporary reduction of the allowable return on equity (ROE) by 50 per cent, and/or reducing the competitive transition charge (CTC). It is estimated that either one of these two reductions could eliminate the full amount of the five to seven per cent uplift in delivered energy service costs. The conclusion of the consultants is that local distribution delivery charges will make up a greater proportion of end-user cost in the future than it has in the past. An increase to customers of about five per cent is expected when the competitive electricity market opens and unbundled billing begins. The cost increase could be mitigated by a combination of actions that would be needed for about

Development of neural network for analysis of local power distributions in BWR fuel bundles

International Nuclear Information System (INIS)

Tanabe, Akira; Yamamoto, Toru; Shinfuku, Kimihiro; Nakamae, Takuji.

1993-01-01

A neural network model has been developed to learn the local power distributions in a BWR fuel bundle. A two layers neural network with total 128 elements is used for this model. The neural network learns 33 cases of local power peaking factors of fuel rods with given enrichment distribution as the teacher signals, which were calculated by a fuel bundle nuclear analysis code based on precise physical models. This neural network model studied well the teacher signals within 1 % error. It is also able to calculate the local power distributions within several % error for the different enrichment distributions from the teacher signals when the average enrichment is close to 2 %. This neural network is simple and the computing speed of this model is 300 times faster than that of the precise nuclear analysis code. This model was applied to survey the enrichment distribution to meet a target local power distribution in a fuel bundle, and the enrichment distribution with flat power shape are obtained within short computing time. (author)

An Event-Based Approach to Distributed Diagnosis of Continuous Systems

Science.gov (United States)

Daigle, Matthew; Roychoudhurry, Indranil; Biswas, Gautam; Koutsoukos, Xenofon

2010-01-01

Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems

Science.gov (United States)

Hu, Anzhong; Lv, Tiejun; Gao, Hui; Zhang, Zhang; Yang, Shaoshi

2014-10-01

In this paper, an approach of estimating signal parameters via rotational invariance technique (ESPRIT) is proposed for two-dimensional (2-D) localization of incoherently distributed (ID) sources in large-scale/massive multiple-input multiple-output (MIMO) systems. The traditional ESPRIT-based methods are valid only for one-dimensional (1-D) localization of the ID sources. By contrast, in the proposed approach the signal subspace is constructed for estimating the nominal azimuth and elevation direction-of-arrivals and the angular spreads. The proposed estimator enjoys closed-form expressions and hence it bypasses the searching over the entire feasible field. Therefore, it imposes significantly lower computational complexity than the conventional 2-D estimation approaches. Our analysis shows that the estimation performance of the proposed approach improves when the large-scale/massive MIMO systems are employed. The approximate Cram\\'{e}r-Rao bound of the proposed estimator for the 2-D localization is also derived. Numerical results demonstrate that albeit the proposed estimation method is comparable with the traditional 2-D estimators in terms of performance, it benefits from a remarkably lower computational complexity.

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach.

Science.gov (United States)

Ke, Mingxing; Li, Ding; Tian, Shiwei; Zhang, Yuli; Tong, Kaixiang; Xu, Yuhua

2018-05-08

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level

Directory of Open Access Journals (Sweden)

Pol Olivella-Rosell

2018-04-01

Full Text Available This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.

Uniform competency-based local feature extraction for remote sensing images

Science.gov (United States)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

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

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.

An Efficient Local Algorithm for Distributed Multivariate Regression

Data.gov (United States)

National Aeronautics and Space Administration — This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm is designed for distributed...

A Scalable Local Algorithm for Distributed Multivariate Regression

Data.gov (United States)

National Aeronautics and Space Administration — This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm can be used for distributed...

Binding-energy distribution and dephasing of localized biexcitons

DEFF Research Database (Denmark)

Langbein, Wolfgang Werner; Hvam, Jørn Märcher; Umlauff, M.

1997-01-01

We report on the binding energy and dephasing of localized biexciton states in narrow ZnSe multiple quantum wells. The measured binding-energy distribution of the localized biexcitons shows a width of 2.2 meV centered at 8.5 meV, and is fairly independent of the exciton localization energy. In fo...

Fire Source Localization Based on Distributed Temperature Sensing by a Dual-Line Optical Fiber System

Directory of Open Access Journals (Sweden)

Miao Sun

2016-06-01

Full Text Available We propose a method for localizing a fire source using an optical fiber distributed temperature sensor system. A section of two parallel optical fibers employed as the sensing element is installed near the ceiling of a closed room in which the fire source is located. By measuring the temperature of hot air flows, the problem of three-dimensional fire source localization is transformed to two dimensions. The method of the source location is verified with experiments using burning alcohol as fire source, and it is demonstrated that the method represents a robust and reliable technique for localizing a fire source also for long sensing ranges.

Fire Source Localization Based on Distributed Temperature Sensing by a Dual-Line Optical Fiber System.

Science.gov (United States)

Sun, Miao; Tang, Yuquan; Yang, Shuang; Li, Jun; Sigrist, Markus W; Dong, Fengzhong

2016-06-06

We propose a method for localizing a fire source using an optical fiber distributed temperature sensor system. A section of two parallel optical fibers employed as the sensing element is installed near the ceiling of a closed room in which the fire source is located. By measuring the temperature of hot air flows, the problem of three-dimensional fire source localization is transformed to two dimensions. The method of the source location is verified with experiments using burning alcohol as fire source, and it is demonstrated that the method represents a robust and reliable technique for localizing a fire source also for long sensing ranges.

Feature Extraction Method for High Impedance Ground Fault Localization in Radial Power Distribution Networks

DEFF Research Database (Denmark)

Jensen, Kåre Jean; Munk, Steen M.; Sørensen, John Aasted

1998-01-01

A new approach to the localization of high impedance ground faults in compensated radial power distribution networks is presented. The total size of such networks is often very large and a major part of the monitoring of these is carried out manually. The increasing complexity of industrial...... of three phase voltages and currents. The method consists of a feature extractor, based on a grid description of the feeder by impulse responses, and a neural network for ground fault localization. The emphasis of this paper is the feature extractor, and the detection of the time instance of a ground fault...... processes and communication systems lead to demands for improved monitoring of power distribution networks so that the quality of power delivery can be kept at a controlled level. The ground fault localization method for each feeder in a network is based on the centralized frequency broadband measurement...

Multiagent System-Based Distributed Coordinated Control for Radial DC Microgrid Considering Transmission Time Delays

DEFF Research Database (Denmark)

Dou, Chun-Xia; Yue, Dong; Guerrero, Josep M.

2017-01-01

This paper focuses on a multi-agent based distributed coordinated control for radial DC microgrid considering trans-mission time delays. Firstly, a two-level multi-agent system is constructed, where local control is formulated based on local states and executed by means of the first-level agent......, and dis-tributed coordinated control law is formulated based on wide-area information and executed by means of the secondary- level agent in order to improve the voltage control performances. Afterwards, the research mainly focuses on designing the local controller and the distributed coordinated...

Automated leak localization performance without detailed demand distribution data

NARCIS (Netherlands)

Moors, Janneke; Scholten, L.; van der Hoek, J.P.; den Besten, J.

2018-01-01

Automatic leak localization has been suggested to reduce the time and personnel efforts needed to localize
(small) leaks. Yet, the available methods require a detailed demand distribution model for successful
calibration and good leak localization performance. The main aim of this work was

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

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...

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.

Real-time Distributed Economic Dispatch forDistributed Generation Based on Multi-Agent System

DEFF Research Database (Denmark)

Luo, Kui; Wu, Qiuwei; Nielsen, Arne Hejde

2015-01-01

The distributed economic dispatch for distributed generation is formulated as a optimization problem with equality and inequality constraints. An effective distributed approach based on multi-agent system is proposed for solving the economic dispatch problem in this paper. The proposed approach...... consists of two stages. In the first stage, an adjacency average allocation algorithm is proposed to ensure the generation-demand equality. In the second stage, a local replicator dynamics algorithm is applied to achieve nash equilibrium for the power dispatch game. The approach is implemented in a fully...

A density distribution algorithm for bone incorporating local orthotropy, modal analysis and theories of cellular solids.

Science.gov (United States)

Impelluso, Thomas J

2003-06-01

An algorithm for bone remodeling is presented which allows for both a redistribution of density and a continuous change of principal material directions for the orthotropic material properties of bone. It employs a modal analysis to add density for growth and a local effective strain based analysis to redistribute density. General re-distribution functions are presented. The model utilizes theories of cellular solids to relate density and strength. The code predicts the same general density distributions and local orthotropy as observed in reality.

Locally Minimum Storage Regenerating Codes in Distributed Cloud Storage Systems

Institute of Scientific and Technical Information of China (English)

Jing Wang; Wei Luo; Wei Liang; Xiangyang Liu; Xiaodai Dong

2017-01-01

In distributed cloud storage sys-tems, inevitably there exist multiple node fail-ures at the same time. The existing methods of regenerating codes, including minimum storage regenerating (MSR) codes and mini-mum bandwidth regenerating (MBR) codes, are mainly to repair one single or several failed nodes, unable to meet the repair need of distributed cloud storage systems. In this paper, we present locally minimum storage re-generating (LMSR) codes to recover multiple failed nodes at the same time. Specifically, the nodes in distributed cloud storage systems are divided into multiple local groups, and in each local group (4, 2) or (5, 3) MSR codes are constructed. Moreover, the grouping method of storage nodes and the repairing process of failed nodes in local groups are studied. The-oretical analysis shows that LMSR codes can achieve the same storage overhead as MSR codes. Furthermore, we verify by means of simulation that, compared with MSR codes, LMSR codes can reduce the repair bandwidth and disk I/O overhead effectively.

Distributed data base systems with special emphasis toward POREL

Science.gov (United States)

Neuhold, E. J.

1984-01-01

In the last few years a number of research and advanced development projects have resulted in distributed data base management prototypes. POREL, developed at the University of Stuttgart, is a multiuser, distributed, relational system developed for wide and local area networks of minicomputers and advanced micros. The general objectives of such data base systems and the architecture of POREL are discussed. In addition a comparison of some of the the existing distributed DMBS is included to provide the reader with information about the current state of the art.

Local Voltage Control in Distribution Networks: A Game-Theoretic Perspective

Energy Technology Data Exchange (ETDEWEB)

Zhou, Xinyang; Tian, Jie; Chen, Lijun; Dall' Anese, Emiliano

2016-11-21

Inverter-based voltage regulation is gaining importance to alleviate emerging reliability and power-quality concerns related to distribution systems with high penetration of photovoltaic (PV) systems. This paper seeks contribution in the domain of reactive power compensation by establishing stability of local Volt/VAr controllers. In lieu of the approximate linear surrogate used in the existing work, the paper establishes existence and uniqueness of an equilibrium point using nonlinear AC power flow model. Key to this end is to consider a nonlinear dynamical system with non-incremental local Volt/VAr control, cast the Volt/VAr dynamics as a game, and leverage the fixed-point theorem as well as pertinent contraction mapping argument. Numerical examples are provided to complement the analytical results.

New power distribution challenges at the local scale

International Nuclear Information System (INIS)

Delage, Marion; Cadoux, Florent; Petit, Marc

2016-01-01

Distribution grids are facing the connection of both more and more variable distributed generation sources and new loads such as electric vehicles. Then distribution grid operators evolve to distribution system operators (DSOs) with new flexibilities (power control of distributed energy sources) to complete their traditional planning and operation tools. In the future, additional distributed resources could be used, such as demand response and storage. DSOs are becoming actors of a global electrical system where power balancing must be ensured at the European level with local constraints (congestion and voltage), and with power flows from transmission to distribution grids but also inside the distribution grid or from distribution to transmission. Sensors and data availability are key issues to enable these transformations. This paper defines some general concerns and present European issues with illustrations from the French electrical system. (authors)

Histopathological confirmation of similar intramucosal distribution of fluorescein in both intravenous administration and local mucosal application for probe-based confocal laser endomicroscopy of the normal stomach.

Science.gov (United States)

Nonaka, Kouichi; Ohata, Ken; Ban, Shinichi; Ichihara, Shin; Takasugi, Rumi; Minato, Yohei; Tashima, Tomoaki; Matsuyama, Yasushi; Takita, Maiko; Matsuhashi, Nobuyuki; Neumann, Helmut

2015-12-16

Probe-based confocal laser endomicroscopy (pCLE) is capable of acquiring in vivo magnified cross-section images of the gastric mucosa. Intravenous injection of fluorescein sodium is used for confocal imaging. However, it is still under debate if local administration of the dye to the mucosa is also effective for confocal imaging as it is not yet clear if topical application also reveals the intramucosal distribution of fluorescein. The objective of this study was to evaluate the intramucosal distribution of fluorescein sodium after topical application and to compare the distribution to the conventional intravenous injection used for confocal imaging. pCLE of the stomach uninfected with Helicobacter pylori was performed in a healthy male employing intravenous administration and local mucosal application of fluorescein. The mucosa of the lower gastric body was biopsied 1 min and 5 min after intravenous administration or local mucosal application of fluorescein, and the distribution of fluorescein in the biopsy samples was examined histologically. Green fluorescence was already observed in the cytoplasm of fundic glandular cells in the biopsied deep mucosa 1 min after local mucosal application of fluorescein. It was also observed in the foveolar lumen and inter-foveolar lamina propria, although it was noted at only a few sites. In the tissue biopsied 5 min after the local mucosal application of fluorescein, green fluorescence was more frequently noted in the cytoplasm of fundic glandular cells than in that 1 min after the local mucosal application of fluorescein, although obvious green fluorescence was not identified in the foveolar lumen or inter-foveolar lamina propria. The distribution of intravenously administered fluorescein in the cytoplasm of fundic glandular cells was also clearly observed similarly to that after local mucosal application of fluorescein. Green fluorescence in more cells was observed in many cells 5 min after intravenous administration compared

A distributed data base management system. [for Deep Space Network

Science.gov (United States)

Bryan, A. I.

1975-01-01

Major system design features of a distributed data management system for the NASA Deep Space Network (DSN) designed for continuous two-way deep space communications are described. The reasons for which the distributed data base utilizing third-generation minicomputers is selected as the optimum approach for the DSN are threefold: (1) with a distributed master data base, valid data is available in real-time to support DSN management activities at each location; (2) data base integrity is the responsibility of local management; and (3) the data acquisition/distribution and processing power of a third-generation computer enables the computer to function successfully as a data handler or as an on-line process controller. The concept of the distributed data base is discussed along with the software, data base integrity, and hardware used. The data analysis/update constraint is examined.

A revised geographical range for Liolaemus elongates Koslowsky, 1896 (Squamata: Liolaemini in Argentina: review of reported and new-data based distribution with new localities

Directory of Open Access Journals (Sweden)

Ignacio Minoli

2013-12-01

Full Text Available Estimating the effective geographical ranges of species is central to species-oriented conservation and management. In this paper, we review the geographical distribution of Liolaemus elongatus Koslowsky, 1896 with three new records for northern Chubut and southern Río Negro provinces, Argentina. Based on detailed locality records pooled from multiple data sources, including new records obtained for this study, we revise the range of L. elongatus sensu stricto and provide geographical distribution maps comparing the previously recognized range to that proposed herein. Our results show that L. elongatus possesses a much more limited geographic distribution than previously thought, being restricted to areas south of 38°S latitude; the newly proposed range is merely half the species formerly recognized geographical distribution.

Research on social communication network evolution based on topology potential distribution

Science.gov (United States)

Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

2011-12-01

Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

Distributed bearing fault diagnosis based on vibration analysis

Science.gov (United States)

Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

2016-01-01

Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

Distributed Fiber-Optic Sensor for Detection and Localization of Acoustic Vibrations

Directory of Open Access Journals (Sweden)

Sifta Radim

2015-03-01

Full Text Available A sensing system utilizing a standard optical fiber as a distributed sensor for the detection and localization of mechanical vibrations is presented. Vibrations can be caused by various external factors, like moving people, cars, trains, and other objects producing mechanical vibrations that are sensed by a fiber. In our laboratory we have designed a sensing system based on the Φ-OTDR (phase sensitive Optical Time Domain Reflectometry using an extremely narrow laser and EDFAs.

Supervisor Localization: A Top-Down Approach to Distributed Control of Discrete-Event Systems

International Nuclear Information System (INIS)

Cai, K.; Wonham, W. M.

2009-01-01

A purely distributed control paradigm is proposed for discrete-event systems (DES). In contrast to control by one or more external supervisors, distributed control aims to design built-in strategies for individual agents. First a distributed optimal nonblocking control problem is formulated. To solve it, a top-down localization procedure is developed which systematically decomposes an external supervisor into local controllers while preserving optimality and nonblockingness. An efficient localization algorithm is provided to carry out the computation, and an automated guided vehicles (AGV) example presented for illustration. Finally, the 'easiest' and 'hardest' boundary cases of localization are discussed.

Enhancing guideline-based decision support with distributed computation through local mobile application

NARCIS (Netherlands)

Shalom, Erez; Shahar, Yuval; Goldstein, Ayelet; Ariel, Elior; Quaglini, Silvana; Sacchi, Lucia; Fung, L.S.N.; Jones, Valerie M.; Broens, T.H.F.; García-Sáez, Gema; Hernando, Elena

2014-01-01

We introduce the need for a distributed guideline-based decision support (DSS) process, describe its characteristics, and explain how we implemented this process within the European Union’s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e.,

A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution

Directory of Open Access Journals (Sweden)

Shizhen Zhao

2018-06-01

Full Text Available Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great extent by varying users. This means that the performance of an activity recognition classifier trained by one user’s dataset will degenerate when transferred to others. In this study, we focus on building a personalized classifier to detect four categories of human activities: light intensity activity, moderate intensity activity, vigorous intensity activity, and fall. In order to solve the problem caused by different distributions of inertial sensor signals, a user-adaptive algorithm based on K-Means clustering, local outlier factor (LOF, and multivariate Gaussian distribution (MGD is proposed. To automatically cluster and annotate a specific user’s activity data, an improved K-Means algorithm with a novel initialization method is designed. By quantifying the samples’ informative degree in a labeled individual dataset, the most profitable samples can be selected for activity recognition model adaption. Through experiments, we conclude that our proposed models can adapt to new users with good recognition performance.

Inference for Local Distributions at High Sampling Frequencies: A Bootstrap Approach

DEFF Research Database (Denmark)

Hounyo, Ulrich; Varneskov, Rasmus T.

of "large" jumps. Our locally dependent wild bootstrap (LDWB) accommodate issues related to the stochastic scale and jumps as well as account for a special block-wise dependence structure induced by sampling errors. We show that the LDWB replicates first and second-order limit theory from the usual...... empirical process and the stochastic scale estimate, respectively, as well as an asymptotic bias. Moreover, we design the LDWB sufficiently general to establish asymptotic equivalence between it and and a nonparametric local block bootstrap, also introduced here, up to second-order distribution theory....... Finally, we introduce LDWB-aided Kolmogorov-Smirnov tests for local Gaussianity as well as local von-Mises statistics, with and without bootstrap inference, and establish their asymptotic validity using the second-order distribution theory. The finite sample performance of CLT and LDWB-aided local...

Local Voltage Control in Distribution Networks: A Game-Theoretic Perspective: Preprint

Energy Technology Data Exchange (ETDEWEB)

Zhou, Xinyang; Tian, Jie; Chen, Lijun; Dall' Anese, Emiliano

2016-09-01

Inverter-based voltage regulation is gaining importance to alleviate emerging reliability and power-quality concerns related to distribution systems with high penetration of photovoltaic (PV) systems. This paper seeks contribution in the domain of reactive power compensation by establishing stability of local Volt/VAr controllers. In lieu of the approximate linear surrogate used in the existing work, the paper establishes existence and uniqueness of an equilibrium point using nonlinear AC power flow model. Key to this end is to consider a nonlinear dynamical system with non-incremental local Volt/VAr control, cast the Volt/VAr dynamics as a game, and leverage the fixed-point theorem as well as pertinent contraction mapping argument. Numerical examples are provided to complement the analytical results.

Stabilization analysis of Euler-Bernoulli beam equation with locally distributed disturbance

Directory of Open Access Journals (Sweden)

Pengcheng HAN

2017-12-01

Full Text Available In order to enrich the system stability theory of the control theories, taking Euler-Bernoulli beam equation as the research subject, the stability of Euler-Bernoulli beam equation with locally distributed disturbance is studied. A feedback controller based on output is designed to reduce the effects of the disturbances. The well-posedness of the nonlinear closed-loop system is investigated by the theory of maximal monotone operator, namely the existence and uniqueness of solutions for the closed-loop system. An appropriate state space is established, an appropriate inner product is defined, and a non-linear operator satisfying this state space is defined. Then, the system is transformed into the form of evolution equation. Based on this, the existence and uniqueness of solutions for the closed-loop system are proved. The asymptotic stability of the system is studied by constructing an appropriate Lyapunov function, which proves the asymptotic stability of the closed-loop system. The result shows that designing proper anti-interference controller is the foundation of investigating the system stability, and the research of the stability of Euler-bernoulli beam equation with locally distributed disturbance can prove the asymptotic stability of the system. This method can be extended to study the other equations such as wave equation, Timoshenko beam equation, Schrodinger equation, etc.

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.

Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method

DEFF Research Database (Denmark)

Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua

2014-01-01

the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...

Spatial Distribution Of Local Markets In Ife North Local Government Area

Directory of Open Access Journals (Sweden)

OMOTOYE-OMISORE Oyelola

2015-08-01

Full Text Available Researches have been carried out in the past by several authors concerning agricultural marketing without the use of geospatial techniques. This research therefore is meant to show the efficacy of Geographical Information System GIS in local market distribution. The role of market place as a man-made feature where goods and services are exchanged for the purpose of satisfying human needs cannot be overemphasized especially in the general development of villages and towns. This study shows the effectiveness of GIS without the use of metrics method to determine the agricultural market locations and closeness of the markets in Ife North Local Government area. Different kinds of people bring their goods from far and near villages for sale and sustainability in this research both primary and secondary data were collected. Primary data includes the use of Global Positioning System GPS receiver to collect coordinate points of the existing markets. It also involves verbal interview with market women. While secondary data were sourced from administrative maps and satellite images of the area of study it was geo-referenced and digitized. Arc Map was used to run average nearest neighbor analysis. Base on the analysis performed the major constraint facing the market people is poor road network which affect majority of the farmers in transporting their goods from remote villages as indicated in this study. As a result new markets sites were proposed with the use of geospatial techniques for easy accessibility.

Distributed Pedestrian Detection Alerts Based on Data Fusion with Accurate Localization

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Arturo de la Escalera

2013-09-01

Full Text Available Among Advanced Driver Assistance Systems (ADAS pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

Distributed pedestrian detection alerts based on data fusion with accurate localization.

Science.gov (United States)

García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

2013-09-04

Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided.

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.

Measurement based scenario analysis of short-range distribution system planning

DEFF Research Database (Denmark)

Chen, Peiyuan; Bak-Jensen, Birgitte; Chen, Zhe

2009-01-01

This paper focuses on short-range distribution system planning using a probabilistic approach. Empirical probabilistic distributions of load demand and distributed generations are derived from the historical measurement data and incorporated into the system planning. Simulations with various...... feasible scenarios are performed based on a local distribution system at Støvring in Denmark. Simulation results provide more accurate and insightful information for the decision-maker when using the probabilistic analysis than using the worst-case analysis, so that a better planning can be achieved....

Local viscosity distribution in bifurcating microfluidic blood flows

Science.gov (United States)

Kaliviotis, E.; Sherwood, J. M.; Balabani, S.

2018-03-01

The red blood cell (RBC) aggregation phenomenon is majorly responsible for the non-Newtonian nature of blood, influencing the blood flow characteristics in the microvasculature. Of considerable interest is the behaviour of the fluid at the bifurcating regions. In vitro experiments, using microchannels, have shown that RBC aggregation, at certain flow conditions, affects the bluntness and skewness of the velocity profile, the local RBC concentration, and the cell-depleted layer at the channel walls. In addition, the developed RBC aggregates appear unevenly distributed in the outlets of these channels depending on their spatial distribution in the feeding branch, and on the flow conditions in the outlet branches. In the present work, constitutive equations of blood viscosity, from earlier work of the authors, are applied to flows in a T-type bifurcating microchannel to examine the local viscosity characteristics. Viscosity maps are derived for various flow distributions in the outlet branches of the channel, and the location of maximum viscosity magnitude is obtained. The viscosity does not appear significantly elevated in the branches of lower flow rate as would be expected on the basis of the low shear therein, and the maximum magnitude appears in the vicinity of the junction, and towards the side of the outlet branch with the higher flow rate. The study demonstrates that in the branches of lower flow rate, the local viscosity is also low, helping us to explain why the effects of physiological red blood cell aggregation have no adverse effects in terms of in vivo vascular resistance.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Locality-Aware Task Scheduling and Data Distribution for OpenMP Programs on NUMA Systems and Manycore Processors

Directory of Open Access Journals (Sweden)

Ananya Muddukrishna

2015-01-01

Full Text Available Performance degradation due to nonuniform data access latencies has worsened on NUMA systems and can now be felt on-chip in manycore processors. Distributing data across NUMA nodes and manycore processor caches is necessary to reduce the impact of nonuniform latencies. However, techniques for distributing data are error-prone and fragile and require low-level architectural knowledge. Existing task scheduling policies favor quick load-balancing at the expense of locality and ignore NUMA node/manycore cache access latencies while scheduling. Locality-aware scheduling, in conjunction with or as a replacement for existing scheduling, is necessary to minimize NUMA effects and sustain performance. We present a data distribution and locality-aware scheduling technique for task-based OpenMP programs executing on NUMA systems and manycore processors. Our technique relieves the programmer from thinking of NUMA system/manycore processor architecture details by delegating data distribution to the runtime system and uses task data dependence information to guide the scheduling of OpenMP tasks to reduce data stall times. We demonstrate our technique on a four-socket AMD Opteron machine with eight NUMA nodes and on the TILEPro64 processor and identify that data distribution and locality-aware task scheduling improve performance up to 69% for scientific benchmarks compared to default policies and yet provide an architecture-oblivious approach for programmers.

Gas source localization and gas distribution mapping with a micro-drone

International Nuclear Information System (INIS)

Neumann, Patrick P.

2013-01-01

The objective of this Ph.D. thesis is the development and validation of a VTOL-based (Vertical Take Off and Landing) micro-drone for the measurement of gas concentrations, to locate gas emission sources, and to build gas distribution maps. Gas distribution mapping and localization of a static gas source are complex tasks due to the turbulent nature of gas transport under natural conditions and becomes even more challenging when airborne. This is especially so, when using a VTOL-based micro-drone that induces disturbances through its rotors, which heavily affects gas distribution. Besides the adaptation of a micro-drone for gas concentration measurements, a novel method for the determination of the wind vector in real-time is presented. The on-board sensors for the flight control of the micro-drone provide a basis for the wind vector calculation. Furthermore, robot operating software for controlling the micro-drone autonomously is developed and used to validate the algorithms developed within this Ph.D. thesis in simulations and real-world experiments. Three biologically inspired algorithms for locating gas sources are adapted and developed for use with the micro-drone: the surge-cast algorithm (a variant of the silkworm moth algorithm), the zigzag / dung beetle algorithm, and a newly developed algorithm called ''pseudo gradient algorithm''. The latter extracts from two spatially separated measuring positions the information necessary (concentration gradient and mean wind direction) to follow a gas plume to its emission source. The performance of the algorithms is evaluated in simulations and real-world experiments. The distance overhead and the gas source localization success rate are used as main performance criteria for comparing the algorithms. Next, a new method for gas source localization (GSL) based on a particle filter (PF) is presented. Each particle represents a weighted hypothesis of the gas source position. As a first step, the PF-based GSL algorithm

Gas source localization and gas distribution mapping with a micro-drone

Energy Technology Data Exchange (ETDEWEB)

Neumann, Patrick P.

2013-07-01

The objective of this Ph.D. thesis is the development and validation of a VTOL-based (Vertical Take Off and Landing) micro-drone for the measurement of gas concentrations, to locate gas emission sources, and to build gas distribution maps. Gas distribution mapping and localization of a static gas source are complex tasks due to the turbulent nature of gas transport under natural conditions and becomes even more challenging when airborne. This is especially so, when using a VTOL-based micro-drone that induces disturbances through its rotors, which heavily affects gas distribution. Besides the adaptation of a micro-drone for gas concentration measurements, a novel method for the determination of the wind vector in real-time is presented. The on-board sensors for the flight control of the micro-drone provide a basis for the wind vector calculation. Furthermore, robot operating software for controlling the micro-drone autonomously is developed and used to validate the algorithms developed within this Ph.D. thesis in simulations and real-world experiments. Three biologically inspired algorithms for locating gas sources are adapted and developed for use with the micro-drone: the surge-cast algorithm (a variant of the silkworm moth algorithm), the zigzag / dung beetle algorithm, and a newly developed algorithm called ''pseudo gradient algorithm''. The latter extracts from two spatially separated measuring positions the information necessary (concentration gradient and mean wind direction) to follow a gas plume to its emission source. The performance of the algorithms is evaluated in simulations and real-world experiments. The distance overhead and the gas source localization success rate are used as main performance criteria for comparing the algorithms. Next, a new method for gas source localization (GSL) based on a particle filter (PF) is presented. Each particle represents a weighted hypothesis of the gas source position. As a first step, the PF-based

Gas source localization and gas distribution mapping with a micro-drone

Energy Technology Data Exchange (ETDEWEB)

Neumann, Patrick P.

2013-07-01

The objective of this Ph.D. thesis is the development and validation of a VTOL-based (Vertical Take Off and Landing) micro-drone for the measurement of gas concentrations, to locate gas emission sources, and to build gas distribution maps. Gas distribution mapping and localization of a static gas source are complex tasks due to the turbulent nature of gas transport under natural conditions and becomes even more challenging when airborne. This is especially so, when using a VTOL-based micro-drone that induces disturbances through its rotors, which heavily affects gas distribution. Besides the adaptation of a micro-drone for gas concentration measurements, a novel method for the determination of the wind vector in real-time is presented. The on-board sensors for the flight control of the micro-drone provide a basis for the wind vector calculation. Furthermore, robot operating software for controlling the micro-drone autonomously is developed and used to validate the algorithms developed within this Ph.D. thesis in simulations and real-world experiments. Three biologically inspired algorithms for locating gas sources are adapted and developed for use with the micro-drone: the surge-cast algorithm (a variant of the silkworm moth algorithm), the zigzag / dung beetle algorithm, and a newly developed algorithm called ''pseudo gradient algorithm''. The latter extracts from two spatially separated measuring positions the information necessary (concentration gradient and mean wind direction) to follow a gas plume to its emission source. The performance of the algorithms is evaluated in simulations and real-world experiments. The distance overhead and the gas source localization success rate are used as main performance criteria for comparing the algorithms. Next, a new method for gas source localization (GSL) based on a particle filter (PF) is presented. Each particle represents a weighted hypothesis of the gas source position. As a first step, the PF-based GSL algorithm

Experimental analysis of considering the sound pressure distribution pattern at the ear canal entrance as an unrevealed head-related localization clue

Institute of Scientific and Technical Information of China (English)

TONG Xin; QI Na; MENG Zihou

2018-01-01

By analyzing the differences between binaural recording and real listening,it was deduced that there were some unrevealed auditory localization clues,and the sound pressure distribution pattern at the entrance of ear canal was probably a clue.It was proved through the listening test that the unrevealed auditory localization clues really exist with the reduction to absurdity.And the effective frequency bands of the unrevealed localization clues were induced and summed.The result of finite element based simulations showed that the pressure distribution at the entrance of ear canal was non-uniform,and the pattern was related to the direction of sound source.And it was proved that the sound pressure distribution pattern at the entrance of the ear canal carried the sound source direction information and could be used as an unrevealed localization cluc.The frequency bands in which the sound pressure distribution patterns had significant differences between front and back sound source directions were roughly matched with the effective frequency bands of unrevealed localization clues obtained from the listening tests.To some extent,it supports the hypothesis that the sound pressure distribution pattern could be a kind of unrevealed auditory localization clues.

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

Agent-based Distributed Unbalance Compensation for Optimal Power Quality in Islanded Microgrids

DEFF Research Database (Denmark)

Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

2014-01-01

-based distributed hierarchical control method. Communication links are required between neighboring units. Consensus algorithm and optimization algorithm are implemented in tertiary control for global information discovery and local optimal decision-making respectively. The tertiary control gives lower level......In microgrids, the distributed generators (DG) can be used as distributed compensators so as to compensate the voltage unbalances in the critical bus. However, the power quality disturbance in generator sides and local buses may be affected and exceeds the limit. It can be more convenient...... to implement tertiary control so as to adjust the compensation efforts among DGs and ensure the acceptable power quality in local buses. Moreover, as centralized control methods have certain disadvantages, such as low flexibility, expandability and heavy computation burden, this paper proposes an agent...

Study of the localization of slaughterhouses and distribution center of broilers agroindustries in Distrito Federal

Directory of Open Access Journals (Sweden)

Eliane Almeida do Carmo

2011-02-01

Full Text Available The work investigated the localization of an avian industry and optimized its net, from the corporatives to the consumers, determining the amount of slaughterhouses and distribution centers that the concern should possess and their localization in order to minimize costs. From the collection of real data and by utilizing tools of Geographic Information Systems and binary linear programming, the optimum setting for the net as well the setting of several alternative scenarios were determined. The objective function utilized minimizes the sum of the costs of the slaughterhouse localization, the costs of the localization of the distribution center, the production costs and shipment of the living chickens from the corporatives to the slaughterhouse, the costs of slaughter and shipment as far as the distribution center and the storage costs in the distribution center and shipment to the end clients. The optimum scenario obtained takes into account only the establishment of a slaughterhouse and a distribution center of increased capacity, standing out scale gains. The results support the localization of slaughterhouses close to the coporatives and distribution centers close to the clients submitted to the several restrictions imposed by the local reality.

COM-LOC: A Distributed Range-Free Localization Algorithm in Wireless Networks

NARCIS (Netherlands)

Dil, B.J.; Havinga, Paul J.M.; Marusic, S; Palaniswami, M; Gubbi, J.; Law, Y.W.

2009-01-01

This paper investigates distributed range-free localization in wireless networks using a communication protocol called sum-dist which is commonly employed by localization algorithms. With this protocol, the reference nodes flood the network in order to estimate the shortest distance between the

Local, distributed topology control for large-scale wireless ad-hoc networks

NARCIS (Netherlands)

Nieberg, T.; Hurink, Johann L.

In this document, topology control of a large-scale, wireless network by a distributed algorithm that uses only locally available information is presented. Topology control algorithms adjust the transmission power of wireless nodes to create a desired topology. The algorithm, named local power

Climate Controls AM Fungal Distributions from Global to Local Scales

Science.gov (United States)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal

Localized probability of improvement for kriging based multi-objective optimization

Science.gov (United States)

Li, Yinjiang; Xiao, Song; Barba, Paolo Di; Rotaru, Mihai; Sykulski, Jan K.

2017-12-01

The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.

Enhancement in statistical and image analysis for in situ µSXRF studies of elemental distribution and co-localization, using Dioscorea balcanica

International Nuclear Information System (INIS)

Dučić, Tanja; Borchert, Manuela; Savić, Aleksandar; Kalauzi, Aleksandar; Mitrović, Aleksandra; Radotić, Ksenija

2013-01-01

Synchrotron-radiation-based X-ray microfluorescence has been used for in situ investigation of the distribution of micronutrient and macronutrient elements in an unstained cross section of a stem of monocotyledonous liana plant Dioscorea balcanica Košanin. The elemental allocation has been quantified and the grouping/co-localization in straight and twisted stem internodes has been analysed. Synchrotron-based X-ray microfluorescence (µSXRF) is an analytical method suitable for in situ investigation of the distribution of micronutrient and macronutrient elements in several-micrometres-thick unstained biological samples, e.g. single cells and tissues. Elements are mapped and quantified at sub-p.p.m. concentrations. In this study the quantity, distribution and grouping/co-localization of various elements have been identified in straight and twisted internodes of the stems of the monocotyledonous climber D. balcanica Košanin. Three different statistical methods were employed to analyse the macro-nutrient and micronutrient distributions and co-localization. Macronutrient elements (K, P, Ca, Cl) are distributed homogeneously in both straight and twisted internodes. Micronutrient elements are mostly grouped in the vasculature and in the sclerenchyma cell layer. In addition, co-localization of micronutrient elements is much more prominent in twisted than in straight internodes. These image analyses and statistical methods provided very similar outcomes and could be applied to various types of biological samples imaged by µSXRF

Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

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Kang Xie

2015-01-01

Full Text Available According to the problems of current distributed architecture intrusion detection systems (DIDS, a new online distributed intrusion detection model based on cellular neural network (CNN was proposed, in which discrete-time CNN (DTCNN was used as weak classifier in each local node and state-controlled CNN (SCCNN was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation which allows the distributed intrusion detection to be performed better.

Diffusion Strategy-Based Distributed Operation of Microgrids Using Multiagent System

Directory of Open Access Journals (Sweden)

Van-Hai Bui

2017-07-01

Full Text Available In distributed operation, each unit is operated by its local controller instead of using a centralized controller, which allows the action to be based on local information rather than global information. Most of the distributed solutions have implemented the consensus method, however, convergence time of the consensus method is quite long, while diffusion strategy includes a stochastic gradient term and can reach convergence much faster compared with consensus method. Therefore, in this paper, a diffusion strategy-based distributed operation of microgrids (MGs is proposed using multiagent system for both normal and emergency operation modes. In normal operation, the MG system is operated by a central controller instead of the distributed controller to minimize the operation cost. If any event (fault occurs in the system, MG system can be divided into two parts to isolate the faulty region. In this case, the MG system is changed to emergency operation mode. The normal part is rescheduled by the central controller while the isolated part schedules its resources in a distributed manner. The isolated part carries out distributed communication using diffusion between neighboring agents for optimal operation of this part. The proposed method enables peer-to-peer communication among the agents without the necessity of a centralized controller, and simultaneously performs resource optimization. Simulation results show that the system can be operated in an economic way in both normal operation and emergency operation modes.

Distributed embedded controller development with petri nets application to globally-asynchronous locally-synchronous systems

CERN Document Server

Moutinho, Filipe de Carvalho

2016-01-01

This book describes a model-based development approach for globally-asynchronous locally-synchronous distributed embedded controllers.  This approach uses Petri nets as modeling formalism to create platform and network independent models supporting the use of design automation tools.  To support this development approach, the Petri nets class in use is extended with time-domains and asynchronous-channels. The authors’ approach uses models not only providing a better understanding of the distributed controller and improving the communication among the stakeholders, but also to be ready to support the entire lifecycle, including the simulation, the verification (using model-checking tools), the implementation (relying on automatic code generators), and the deployment of the distributed controller into specific platforms. Uses a graphical and intuitive modeling formalism supported by design automation tools; Enables verification, ensuring that the distributed controller was correctly specified; Provides flex...

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST

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Oliver Melvin J

2005-04-01

Full Text Available Abstract Background BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST, which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. Results W.ND-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN. W.ND-BLAST provides intuitive Graphic User Interfaces (GUI for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of W.ND-BLAST. W.ND-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes (11 hours on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. Conclusion W.ND-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for W.ND-BLAST is

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.

Distributed, signal strength-based indoor localization algorithm for use in healthcare environments.

Science.gov (United States)

Wyffels, Jeroen; De Brabanter, Jos; Crombez, Pieter; Verhoeve, Piet; Nauwelaers, Bart; De Strycker, Lieven

2014-11-01

In current healthcare environments, a trend toward mobile and personalized interactions between people and nurse call systems is strongly noticeable. Therefore, it should be possible to locate patients at all times and in all places throughout the care facility. This paper aims at describing a method by which a mobile node can locate itself indoors, based on signal strength measurements and a minimal amount of yes/no decisions. The algorithm has been developed specifically for use in a healthcare environment. With extensive testing and statistical support, we prove that our algorithm can be used in a healthcare setting with an envisioned level of localization accuracy up to room revel (or region level in a corridor), while avoiding heavy investments since the hardware of an existing nurse call network can be reused. The approach opted for leads to very high scalability, since thousands of mobile nodes can locate themselves. Network timing issues and localization update delays are avoided, which ensures that a patient can receive the needed care in a time and resources efficient way.

Managing electricity procurement cost and risk by a local distribution company

International Nuclear Information System (INIS)

Woo, C.-K.; Karimov, R.I.; Horowitz, Ira

2004-01-01

A local electricity distribution company (LDC) can satisfy some of its future electricity requirements through self-generation and volatile spot markets, and the remainder through fixed-price forward contracts that will reduce its exposure to the inherent risk of spot-price volatility. A theoretical framework is developed for determining the forward-contract purchase that minimizes the LDCs expected procurement cost, subject to a cost-exposure constraint. The answers to the questions of 'What to buy?' and 'How to buy?' are illustrated using an example of a hypothetical LDC that is based on a municipal utility in Florida. It is shown that the LDCs procurement decision is consistent with least-cost procurement subject to a cost-exposure constraint, and that an internet-based multi-round auction can produce competitive price quotes for its desired forward purchase

OPTIMIZATION OF THE POSITION OF THE LOCAL DISTRIBUTION CENTRE OF THE REGIONAL POST LOGISTICS NETWORK

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Paweł DROŹDZIEL

2017-09-01

Full Text Available The phenomenon of the present postal services is the fact that, customers expect the lowest price while maintaining the availability, security and on time delivery of mail items. We can find that, the costs associated with transport of the postal substrate is one of the most important factors affecting the total cost of the postal services. These transport costs depend on various factors such as the investment in vehicles purchase, operational costs of the postal vehicles (costs of maintenance, repairs, fuel costs of the vehicle, etc. labour costs of the drivers and so on. For this reason, it is important to find such an operational - organizational solutions that can reduce the costs associated with the transportation of postal shipments, resulting in reducing the total cost of postal services. One option to do this is to minimize the length of postal transportation routes. This article presents the approach based on the application of graph theory to optimize existing connections of postal logistics network. Published results is oriented to revaluate existing position of local centre and find a location for the new local distribution centre potentially. New location of local distribution centre can to optimize (minimize the total transport costs of the local postal transportation network in area of the Lublin Province.

Highly localized distributed Brillouin scattering response in a photonic integrated circuit

Science.gov (United States)

Zarifi, Atiyeh; Stiller, Birgit; Merklein, Moritz; Li, Neuton; Vu, Khu; Choi, Duk-Yong; Ma, Pan; Madden, Stephen J.; Eggleton, Benjamin J.

2018-03-01

The interaction of optical and acoustic waves via stimulated Brillouin scattering (SBS) has recently reached on-chip platforms, which has opened new fields of applications ranging from integrated microwave photonics and on-chip narrow-linewidth lasers, to phonon-based optical delay and signal processing schemes. Since SBS is an effect that scales exponentially with interaction length, on-chip implementation on a short length scale is challenging, requiring carefully designed waveguides with optimized opto-acoustic overlap. In this work, we use the principle of Brillouin optical correlation domain analysis to locally measure the SBS spectrum with high spatial resolution of 800 μm and perform a distributed measurement of the Brillouin spectrum along a spiral waveguide in a photonic integrated circuit. This approach gives access to local opto-acoustic properties of the waveguides, including the Brillouin frequency shift and linewidth, essential information for the further development of high quality photonic-phononic waveguides for SBS applications.

Highly localized distributed Brillouin scattering response in a photonic integrated circuit

Directory of Open Access Journals (Sweden)

Atiyeh Zarifi

2018-03-01

Full Text Available The interaction of optical and acoustic waves via stimulated Brillouin scattering (SBS has recently reached on-chip platforms, which has opened new fields of applications ranging from integrated microwave photonics and on-chip narrow-linewidth lasers, to phonon-based optical delay and signal processing schemes. Since SBS is an effect that scales exponentially with interaction length, on-chip implementation on a short length scale is challenging, requiring carefully designed waveguides with optimized opto-acoustic overlap. In this work, we use the principle of Brillouin optical correlation domain analysis to locally measure the SBS spectrum with high spatial resolution of 800 μm and perform a distributed measurement of the Brillouin spectrum along a spiral waveguide in a photonic integrated circuit. This approach gives access to local opto-acoustic properties of the waveguides, including the Brillouin frequency shift and linewidth, essential information for the further development of high quality photonic-phononic waveguides for SBS applications.

An Information-Based Approach to Precision Analysis of Indoor WLAN Localization Using Location Fingerprint

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Mu Zhou

2015-12-01

Full Text Available In this paper, we proposed a novel information-based approach to precision analysis of indoor wireless local area network (WLAN localization using location fingerprint. First of all, by using the Fisher information matrix (FIM, we derive the fundamental limit of WLAN fingerprint-based localization precision considering different signal distributions in characterizing the variation of received signal strengths (RSSs in the target environment. After that, we explore the relationship between the localization precision and access point (AP placement, which can provide valuable suggestions for the design of the highly-precise localization system. Second, we adopt the heuristic simulated annealing (SA algorithm to optimize the AP locations for the sake of approaching the fundamental limit of localization precision. Finally, the extensive simulations and experiments are conducted in both regular line-of-sight (LOS and irregular non-line-of-sight (NLOS environments to demonstrate that the proposed approach can not only effectively improve the WLAN fingerprint-based localization precision, but also reduce the time overhead.

Food availability and accessibility in the local food distribution ...

African Journals Online (AJOL)

Objectives: The objective was to understand the local food distribution system in Avian Park, with a focus on food availability and accessibility. Study design: This was a quantitative food store survey that employed semi-structured interviews and focus group discussions. Setting: The study was conducted in Avian Park, ...

Local Information as a Resource in Distributed Quantum Systems

Science.gov (United States)

Horodecki, Michał; Horodecki, Karol; Horodecki, Paweł; Horodecki, Ryszard; Oppenheim, Jonathan; Sende, Aditi; Sen, Ujjwal

2003-03-01

A new paradigm for distributed quantum systems where information is a valuable resource is developed. After finding a unique measure for information, we construct a scheme for its manipulation in analogy with entanglement theory. In this scheme, instead of maximally entangled states, two parties distill local states. We show that, surprisingly, the main tools of entanglement theory are general enough to work in this opposite scheme. Up to plausible assumptions, we show that the amount of information that must be lost during the protocol of concentration of local information can be expressed as the relative entropy distance from some special set of states.

Distributed MIMO chaotic radar based on wavelength-division multiplexing technology.

Science.gov (United States)

Yao, Tingfeng; Zhu, Dan; Ben, De; Pan, Shilong

2015-04-15

A distributed multiple-input multiple-output chaotic radar based on wavelength-division multiplexing technology (WDM) is proposed and demonstrated. The wideband quasi-orthogonal chaotic signals generated by different optoelectronic oscillators (OEOs) are emitted by separated antennas to gain spatial diversity against the fluctuation of a target's radar cross section and enhance the detection capability. The received signals collected by the receive antennas and the reference signals from the OEOs are delivered to the central station for joint processing by exploiting WDM technology. The centralized signal processing avoids precise time synchronization of the distributed system and greatly simplifies the remote units, which improves the localization accuracy of the entire system. A proof-of-concept experiment for two-dimensional localization of a metal target is demonstrated. The maximum position error is less than 6.5 cm.

Managing electricity procurement cost and risk by a local distribution company

International Nuclear Information System (INIS)

Chikeung Woo; Karimov, R.I.; Horowitz, I.

2004-01-01

A local electricity distribution company (LDC) can satisfy some of its future electricity requirements through self-generation and volatile spot markets, and the remainder through fixed-price forward contracts that will reduce its exposure to the inherent risk of spot-price volatility. A theoretical framework is developed for determining the forward-contract purchase that minimizes the LDCs expected procurement cost, subject to a cost-exposure constraint. The answers to the questions of ''What to buy?'' and ''How to buy?'' are illustrated using an example of a hypothetical LDC that is based on a municipal utility in Florida. It is shown that the LDCs procurement decision is consistent with least-cost procurement subject to a cost-exposure constraint, and that an internet-based multi-round auction can produce competitive price quotes for its desired forward purchase. (author)

Risk analysis for a local gas distribution network

International Nuclear Information System (INIS)

Peters, J.W.

1991-01-01

Cost control and service reliability are popular topics when discussing strategic issues facing local distribution companies (LDCs) in the 1990s. The ability to provide secure and uninterrupted gas service is crucial for growth and company image, both with the public and regulatory agencies. At the same time, the industry is facing unprecedented competition from alternate fuels, and cost control is essential for maintaining a competitive edge in the market. On the surface, it would appear that cost control and service reliability are contradictory terms. Improvement in service reliability should cost something, or does it? Risk analysis can provide the answer from a distribution design perspective. From a gas distribution engineer's perspective, projects such as loops, backfeeds and even valve placement are designed to reduce, minimize and/or eliminate potential customer outages. These projects improve service reliability by acting as backups should a failure occur on a component of the distribution network. These contingency projects are cost-effective but their longterm benefit or true value is under question. Their purpose is to maintain supply to an area in the distribution network in the event of a failure somewhere else. Two phrases, potential customer outages and in the event of failure, identify uncertainty

Post- and interseismic deformation due to both localized and distributed creep at depth (Invited)

Science.gov (United States)

Hetland, E. A.; Zhang, G.; Hines, T.

2013-12-01

There are two end-member representations of the ductile lithosphere (i.e., the lower crust and uppermost mantle) commonly used in models of post- and interseismic deformation around strike-slip faults: either (1) laterally homogeneous ductile layers, with sharp contrasts in rheological properties between the layers, in which creep is distributed; or (2) discrete extensions of the fault at depth in which creep is fully localized. The most realistic representation of the ductile lithosphere on earthquake cycle time scales likely falls between these two end-members. Researchers have considered both distributed and localized creep when interpreting post- and interseismic deformation, although the two mechanisms are most commonly treated separately, with the localized creep often approximated by kinematic slip on planar faults. There are a few noteworthy models that considered the feedback between both distributed and localized creep, although those models were largely constrained to 2D geometries of infinite length faults. The thickness of shear zones in the ductile lithosphere may be comparable to the locking depth of the fault, and the existence of a deep shear zone does not preclude the possibility that some distributed creep occurs in the surrounding lithosphere. Furthermore, variations in rheology, including both rheological models and their parameters, may be more subtle than the discrete contrasts typically assumed. In this presentation, we consider models of postseismic deformation following a finite length, strike-slip fault, as well as models of interseismic deformation around an infinite length strike-slip fault. Both sets of models are capable of localized and distributed creep at depth, and use Maxwell viscoelasticity. We show that the horizontal surface velocities during the early postseismic period are most sensitive to the viscosity of the shear zone; however during much of the interseismic period the shear zone is not apparent from the surface

Global and local emission impact assessment of distributed cogeneration systems with partial-load models

International Nuclear Information System (INIS)

Mancarella, Pierluigi; Chicco, Gianfranco

2009-01-01

Small-scale distributed cogeneration technologies represent a key resource to increase generation efficiency and reduce greenhouse gas emissions with respect to conventional separate production means. However, the diffusion of distributed cogeneration within urban areas, where air quality standards are quite stringent, brings about environmental concerns on a local level. In addition, partial-load emission worsening is often overlooked, which could lead to biased evaluations of the energy system environmental performance. In this paper, a comprehensive emission assessment framework suitable for addressing distributed cogeneration systems is formulated. Local and global emission impact models are presented to identify upper and lower boundary values of the environmental pressure from pollutants that would be emitted from reference technologies, to be compared to the actual emissions from distributed cogeneration. This provides synthetic information on the relative environmental impact from small-scale CHP sources, useful for general indicative and non-site-specific studies. The emission models are formulated according to an electrical output-based emission factor approach, through which off-design operation and relevant performance are easily accounted for. In particular, in order to address the issues that could arise under off-design operation, an equivalent load model is incorporated within the proposed framework, by exploiting the duration curve of the cogenerator loading and the emissions associated to each loading level. In this way, it is possible to quantify the contribution to the emissions from cogeneration systems that might operate at partial loads for a significant portion of their operation time, as for instance in load-tracking applications. Suitability of the proposed methodology is discussed with respect to hazardous air pollutants such as NO x and CO, as well as to greenhouse gases such as CO 2 . Two case study applications based on the emission

Fiber optic distributed temperature sensing for fire source localization

Science.gov (United States)

Sun, Miao; Tang, Yuquan; Yang, Shuang; Sigrist, Markus W.; Li, Jun; Dong, Fengzhong

2017-08-01

A method for localizing a fire source based on a distributed temperature sensor system is proposed. Two sections of optical fibers were placed orthogonally to each other as the sensing elements. A tray of alcohol was lit to act as a fire outbreak in a cabinet with an uneven ceiling to simulate a real scene of fire. Experiments were carried out to demonstrate the feasibility of the method. Rather large fluctuations and systematic errors with respect to predicting the exact room coordinates of the fire source caused by the uneven ceiling were observed. Two mathematical methods (smoothing recorded temperature curves and finding temperature peak positions) to improve the prediction accuracy are presented, and the experimental results indicate that the fluctuation ranges and systematic errors are significantly reduced. The proposed scheme is simple and appears reliable enough to locate a fire source in large spaces.

Large developing receptive fields using a distributed and locally reprogrammable address-event receiver.

Science.gov (United States)

Bamford, Simeon A; Murray, Alan F; Willshaw, David J

2010-02-01

A distributed and locally reprogrammable address-event receiver has been designed, in which incoming address-events are monitored simultaneously by all synapses, allowing for arbitrarily large axonal fan-out without reducing channel capacity. Synapses can change the address of their presynaptic neuron, allowing the distributed implementation of a biologically realistic learning rule, with both synapse formation and elimination (synaptic rewiring). Probabilistic synapse formation leads to topographic map development, made possible by a cross-chip current-mode calculation of Euclidean distance. As well as synaptic plasticity in rewiring, synapses change weights using a competitive Hebbian learning rule (spike-timing-dependent plasticity). The weight plasticity allows receptive fields to be modified based on spatio-temporal correlations in the inputs, and the rewiring plasticity allows these modifications to become embedded in the network topology.

Procedure of non-contacting local mass density and mass density distribution measurements

International Nuclear Information System (INIS)

Menzel, M.; Winkler, K.

1985-01-01

The invention has been aimed at a procedure of non-contacting local mass density and/or mass density distribution measurements i.e. without the interfering influence of sensors or probes. It can be applied to installations, apparatuses and pipings of chemical engineering, to tank constructions and transportation on extreme temperature and/or pressure conditions and aggressive media influences respectively. The procedure has utilized an ionizing quantum radiation whereby its unknown weakening and scattering is compensated by a suitable combination of scattering and transmission counter rate measurements in such a way that the local mass densities and the mass density distribution respectively are determinable

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.

Regional Distribution Shifts Help Explain Local Changes in Wintering Raptor Abundance: Implications for Interpreting Population Trends

Science.gov (United States)

Paprocki, Neil; Heath, Julie A.; Novak, Stephen J.

2014-01-01

Studies of multiple taxa across broad-scales suggest that species distributions are shifting poleward in response to global climate change. Recognizing the influence of distribution shifts on population indices will be an important part of interpreting trends within management units because current practice often assumes that changes in local populations reflect local habitat conditions. However, the individual- and population-level processes that drive distribution shifts may occur across a large, regional scale and have little to do with the habitats within the management unit. We examined the latitudinal center of abundance for the winter distributions of six western North America raptor species using Christmas Bird Counts from 1975–2011. Also, we considered whether population indices within western North America Bird Conservation Regions (BCRs) were explained by distribution shifts. All six raptors had significant poleward shifts in their wintering distributions over time. Rough-legged Hawks (Buteo lagopus) and Golden Eagles (Aquila chrysaetos) showed the fastest rate of change, with 8.41 km yr−1 and 7.74 km yr−1 shifts, respectively. Raptors may be particularly responsive to warming winters because of variable migration tendencies, intraspecific competition for nesting sites that drives males to winter farther north, or both. Overall, 40% of BCR population trend models were improved by incorporating information about wintering distributions; however, support for the effect of distribution on BCR indices varied by species with Rough-legged Hawks showing the most evidence. These results emphasize the importance of understanding how regional distribution shifts influence local-scale population indices. If global climate change is altering distribution patterns, then trends within some management units may not reflect changes in local habitat conditions. The methods used to monitor and manage bird populations within local BCRs will fundamentally change as

Regional distribution shifts help explain local changes in wintering raptor abundance: implications for interpreting population trends.

Directory of Open Access Journals (Sweden)

Neil Paprocki

Full Text Available Studies of multiple taxa across broad-scales suggest that species distributions are shifting poleward in response to global climate change. Recognizing the influence of distribution shifts on population indices will be an important part of interpreting trends within management units because current practice often assumes that changes in local populations reflect local habitat conditions. However, the individual- and population-level processes that drive distribution shifts may occur across a large, regional scale and have little to do with the habitats within the management unit. We examined the latitudinal center of abundance for the winter distributions of six western North America raptor species using Christmas Bird Counts from 1975-2011. Also, we considered whether population indices within western North America Bird Conservation Regions (BCRs were explained by distribution shifts. All six raptors had significant poleward shifts in their wintering distributions over time. Rough-legged Hawks (Buteo lagopus and Golden Eagles (Aquila chrysaetos showed the fastest rate of change, with 8.41 km yr(-1 and 7.74 km yr(-1 shifts, respectively. Raptors may be particularly responsive to warming winters because of variable migration tendencies, intraspecific competition for nesting sites that drives males to winter farther north, or both. Overall, 40% of BCR population trend models were improved by incorporating information about wintering distributions; however, support for the effect of distribution on BCR indices varied by species with Rough-legged Hawks showing the most evidence. These results emphasize the importance of understanding how regional distribution shifts influence local-scale population indices. If global climate change is altering distribution patterns, then trends within some management units may not reflect changes in local habitat conditions. The methods used to monitor and manage bird populations within local BCRs will fundamentally

Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics.

Science.gov (United States)

Zhao, Meng; Ding, Baocang

2015-03-01

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Web based parallel/distributed medical data mining using software agents

Energy Technology Data Exchange (ETDEWEB)

Kargupta, H.; Stafford, B.; Hamzaoglu, I.

1997-12-31

This paper describes an experimental parallel/distributed data mining system PADMA (PArallel Data Mining Agents) that uses software agents for local data accessing and analysis and a web based interface for interactive data visualization. It also presents the results of applying PADMA for detecting patterns in unstructured texts of postmortem reports and laboratory test data for Hepatitis C patients.

Research on fully distributed optical fiber sensing security system localization algorithm

Science.gov (United States)

Wu, Xu; Hou, Jiacheng; Liu, Kun; Liu, Tiegen

2013-12-01

A new fully distributed optical fiber sensing and location technology based on the Mach-Zehnder interferometers is studied. In this security system, a new climbing point locating algorithm based on short-time average zero-crossing rate is presented. By calculating the zero-crossing rates of the multiple grouped data separately, it not only utilizes the advantages of the frequency analysis method to determine the most effective data group more accurately, but also meets the requirement of the real-time monitoring system. Supplemented with short-term energy calculation group signal, the most effective data group can be quickly picked out. Finally, the accurate location of the climbing point can be effectively achieved through the cross-correlation localization algorithm. The experimental results show that the proposed algorithm can realize the accurate location of the climbing point and meanwhile the outside interference noise of the non-climbing behavior can be effectively filtered out.

Time distributions of recurrences of immunogenic and nonimmunogenic tumors following local irradiation

International Nuclear Information System (INIS)

Suit, H.D.; Sedlacek, R.; Fagundes, L.; Goitein, M.; Rothman, K.J.

1978-01-01

Three hundred and fourteen mice received single-dose irradiation of the right leg and thigh as treatment of an 8-mm mammary carcinoma isotransplant, and were then observed until death, usually by 1000 days. The time distributions of death due to local recurrence, radiation-induced sarcoma, distant metastasis in the absence of local regrowth, second primary, intercurrent disease, and unknown causes have been evaluated. The times for the transplant tumor inoculum to grow to an 8-mm tumor and the times of death due to local regrowth, distant metastasis, or induced tumor were all approximately log-normally distributed. Of the 128 recurrences, the latest-appearing 3 were at 300, 323, and 436 days; no recurrences were noted during the time period from 436 to 1000 days. These findings have been interpreted to mean that in some cases absolute cure of mice of the tumor in the leg was achieved by radiation alone at the dose levels employed. Radiation-induced sarcomas began to appear after 300 days. The time of appearance of the radiation-induced tumors was inversely related to radiation dose. Similar data for an immunogenic fibrosarcoma show that recurrences appeared earlier and were more closely bunched with respect to time than the recurrences of mammary carcinoma. The time distribution of the development of radiation-induced tumors in non-tumor-bearing animals was also approximately long-normally distributed; the slope of the time distribution curve was the same as that for radiation-induced tumors in mice which had been treated for tumor

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.

Effect of Local Strain Distribution of Cold-Rolled Alloy 690 on Primary Water Stress Corrosion Crack Growth Behavior

Directory of Open Access Journals (Sweden)

Kim S.-W.

2017-06-01

Full Text Available This work aims to study the stress corrosion crack growth behavior of cold-rolled Alloy 690 in the primary water of a pressurized water reactor. Compared with Alloy 600, which shows typical intergranular cracking along high angle grain boundaries, the cold-rolled Alloy 690, with its heterogeneous microstructure, revealed an abnormal crack growth behavior in mixed mode, that is, in transgranular cracking near a banded region, and in intergranular cracking in a matrix region. From local strain distribution analysis based on local mis-orientation, measured along the crack path using the electron back scattered diffraction method, it was suggested that the abnormal behavior was attributable to a heterogeneity of local strain distribution. In the cold-rolled Alloy 690, the stress corrosion crack grew through a highly strained area formed by a prior cold-rolling process in a direction perpendicular to the maximum principal stress applied during a subsequent stress corrosion cracking test.

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.

Higher-order momentum distributions and locally affine LDDMM registration

DEFF Research Database (Denmark)

Sommer, Stefan Horst; Nielsen, Mads; Darkner, Sune

2013-01-01

description of affine transformations and subsequent compact description of non-translational movement in a globally nonrigid deformation. The resulting representation contains directly interpretable information from both mathematical and modeling perspectives. We develop the mathematical construction......To achieve sparse parametrizations that allow intuitive analysis, we aim to represent deformation with a basis containing interpretable elements, and we wish to use elements that have the description capacity to represent the deformation compactly. To accomplish this, we introduce in this paper...... higher-order momentum distributions in the large deformation diffeomorphic metric mapping (LDDMM) registration framework. While the zeroth-order moments previously used in LDDMM only describe local displacement, the first-order momenta that are proposed here represent a basis that allows local...

Experimental validation of a distributed algorithm for dynamic spectrum access in local area networks

DEFF Research Database (Denmark)

Tonelli, Oscar; Berardinelli, Gilberto; Tavares, Fernando Menezes Leitão

2013-01-01

Next generation wireless networks aim at a significant improvement of the spectral efficiency in order to meet the dramatic increase in data service demand. In local area scenarios user-deployed base stations are expected to take place, thus making the centralized planning of frequency resources...... activities with the Autonomous Component Carrier Selection (ACCS) algorithm, a distributed solution for interference management among small neighboring cells. A preliminary evaluation of the algorithm performance is provided considering its live execution on a software defined radio network testbed...

Localizing Value of Pain Distribution Patterns in Cervical Spondylosis

OpenAIRE

Bunyaratavej, Krishnapundha; Montriwiwatnchai, Peerapong; Siwanuwatn, Rungsak; Khaoroptham, Surachai

2015-01-01

Study Design Prospective observational study. Purpose To investigate the value of pain distribution in localizing appropriate surgical levels in patients with cervical spondylosis. Overview of Literature Previous studies have investigated the value of pain drawings in its correlation with various features in degenerative spine diseases including surgical outcome, magnetic resonance imaging findings, discographic study, and psychogenic issues. However, there is no previous study on the value o...

Regional Distribution Shifts Help Explain Local Changes in Wintering Raptor Abundance: Implications for Interpreting Population Trends

OpenAIRE

Paprocki, Neil; Heath, Julie A.; Novak, Stephen J.

2014-01-01

Studies of multiple taxa across broad-scales suggest that species distributions are shifting poleward in response to global climate change. Recognizing the influence of distribution shifts on population indices will be an important part of interpreting trends within management units because current practice often assumes that changes in local populations reflect local habitat conditions. However, the individual- and population-level processes that drive distribution shifts may occur across a ...

Application of Learning Methods to Local Electric Field Distributions in Defected Dielectric Materials

Science.gov (United States)

Ferris, Kim; Jones, Dumont

2014-03-01

Local electric fields reflect the structural and dielectric fluctuations in a semiconductor, and affect the material performance both for electron transport and carrier lifetime properties. In this paper, we use the LOCALF methodology with periodic boundary conditions to examine the local electric field distributions and its perturbations for II-VI (CdTe, Cd(1-x)Zn(x)Te) semiconductors, containing Te inclusions and small fluctuations in the local dielectric susceptibility. With inclusion of the induced-field term, the electric field distribution shows enhancements and diminishments compared to the macroscopic applied field, reflecting the microstructure characteristics of the dielectric. Learning methods are applied to these distributions to assess the spatial extent of the perturbation, and determine an electric field defined defect size as compared to its physical dimension. Critical concentrations of defects are assessed in terms of defect formation energies. This work was supported by the US Department of Homeland Security, Domestic Nuclear Detection Office, under competitively awarded contract/IAA HSHQDC-08-X-00872-e. This support does not constitute an express or implied endorsement on the part of the Gov't.

Harmonic Differential Quadrature Analysis of Soft-Core Sandwich Panels under Locally Distributed Loads

Directory of Open Access Journals (Sweden)

Xinwei Wang

2016-11-01

Full Text Available Sandwich structures are widely used in practice and thus various engineering theories adopting simplifying assumptions are available. However, most engineering theories of beams, plates and shells cannot recover all stresses accurately through their constitutive equations. Therefore, the soft-core is directly modeled by two-dimensional (2D elasticity theory without any pre-assumption on the displacement field. The top and bottom faces act like the elastic supports on the top and bottom edges of the core. The differential equations of the 2D core are then solved by the harmonic differential quadrature method (HDQM. To circumvent the difficulties in dealing with the locally distributed load by point discrete methods such as the HDQM, a general and rigorous way is proposed to treat the locally distributed load. Detailed formulations are provided. The static behavior of sandwich panels under different locally distributed loads is investigated. For verification, results are compared with data obtained by ABAQUS with very fine meshes. A high degree of accuracy on both displacement and stress has been observed.

Experimental investigation of localized stress-induced leakage current distribution in gate dielectrics using array test circuit

Science.gov (United States)

Park, Hyeonwoo; Teramoto, Akinobu; Kuroda, Rihito; Suwa, Tomoyuki; Sugawa, Shigetoshi

2018-04-01

Localized stress-induced leakage current (SILC) has become a major problem in the reliability of flash memories. To reduce it, clarifying the SILC mechanism is important, and statistical measurement and analysis have to be carried out. In this study, we applied an array test circuit that can measure the SILC distribution of more than 80,000 nMOSFETs with various gate areas at a high speed (within 80 s) and a high accuracy (on the 10-17 A current order). The results clarified that the distributions of localized SILC in different gate areas follow a universal distribution assuming the same SILC defect density distribution per unit area, and the current of localized SILC defects does not scale down with the gate area. Moreover, the distribution of SILC defect density and its dependence on the oxide field for measurement (E OX-Measure) were experimentally determined for fabricated devices.

Study of Climate Change Impact to Local Rainfall Distribution in Lampung Provinces

Directory of Open Access Journals (Sweden)

Tumiar Katarina Manik

2016-08-01

Full Text Available Global warming which leads to climate change has potential affect to Indonesia agriculture activities and production. Analyzing rainfall pattern and distribution is important to investigate the impact of global climate change to local climate. This study using rainfall data from 1976-2010 from both lowland and upland area of Lampung Province. The results show that rainfall tends to decrease since the 1990s which related to the years with El Nino event. Monsoonal pattern- having rain and dry season- still excist in Lampung; however, since most rain fell below the average, it could not meet crops water need. Farmers conclude that dry seasons were longer and seasonal pattern has been changed. Global climate change might affect Lampung rainfall distribution through changes on sea surface temperature which could intensify the El Nino effect. Therefore, watching the El Nino phenomena and how global warming affects it, is important in predicting local climate especially the rainfall distribution in order to prevent significant loss in agriculture productivities.

Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

Science.gov (United States)

Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

2014-01-01

Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

Experimental and numerical study of impact of voltage fluctuate, flicker and power factor wave electric generator to local distribution

Science.gov (United States)

Hadi, Nik Azran Ab; Rashid, Wan Norhisyam Abd; Hashim, Nik Mohd Zarifie; Mohamad, Najmiah Radiah; Kadmin, Ahmad Fauzan

2017-10-01

Electricity is the most powerful energy source in the world. Engineer and technologist combined and cooperated to invent a new low-cost technology and free carbon emission where the carbon emission issue is a major concern now due to global warming. Renewable energy sources such as hydro, wind and wave are becoming widespread to reduce the carbon emissions, on the other hand, this effort needs several novel methods, techniques and technologies compared to coal-based power. Power quality of renewable sources needs in depth research and endless study to improve renewable energy technologies. The aim of this project is to investigate the impact of renewable electric generator on its local distribution system. The power farm was designed to connect to the local distribution system and it will be investigated and analyzed to make sure that energy which is supplied to customer is clean. The MATLAB tools are used to simulate the overall analysis. At the end of the project, a summary of identifying various voltage fluctuates data sources is presented in terms of voltage flicker. A suggestion of the analysis impact of wave power generation on its local distribution is also presented for the development of wave generator farms.

Distributed Economic Dispatch in Microgrids Based on Cooperative Reinforcement Learning.

Science.gov (United States)

Liu, Weirong; Zhuang, Peng; Liang, Hao; Peng, Jun; Huang, Zhiwu; Weirong Liu; Peng Zhuang; Hao Liang; Jun Peng; Zhiwu Huang; Liu, Weirong; Liang, Hao; Peng, Jun; Zhuang, Peng; Huang, Zhiwu

2018-06-01

Microgrids incorporated with distributed generation (DG) units and energy storage (ES) devices are expected to play more and more important roles in the future power systems. Yet, achieving efficient distributed economic dispatch in microgrids is a challenging issue due to the randomness and nonlinear characteristics of DG units and loads. This paper proposes a cooperative reinforcement learning algorithm for distributed economic dispatch in microgrids. Utilizing the learning algorithm can avoid the difficulty of stochastic modeling and high computational complexity. In the cooperative reinforcement learning algorithm, the function approximation is leveraged to deal with the large and continuous state spaces. And a diffusion strategy is incorporated to coordinate the actions of DG units and ES devices. Based on the proposed algorithm, each node in microgrids only needs to communicate with its local neighbors, without relying on any centralized controllers. Algorithm convergence is analyzed, and simulations based on real-world meteorological and load data are conducted to validate the performance of the proposed algorithm.

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.

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.

Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement

Science.gov (United States)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier

2018-06-01

Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.

Distributed push-pull estimation for node localization in wireless sensor networks

NARCIS (Netherlands)

Dang, Viet-Hung; Le Viet Duc, L Duc; Lee, Young-Koo; Lee, Sungyoung

A great deal of research achievements on localization in wireless sensor networks (WSNs) has been obtained in recent years. Nevertheless, its interesting challenges in terms of cost-reduction, accuracy improvement, scalability, and distributed ability design have led to the development of a new

Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane.

Directory of Open Access Journals (Sweden)

Laura Paparelli

2016-09-01

Full Text Available Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH. We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided.

Distributed and collaborative: Experiences of local leadership of a first-year experience program

Directory of Open Access Journals (Sweden)

Jo McKenzie

2017-07-01

Full Text Available Local level leadership of the first year experience (FYE is critical for engaging academic and professional staff in working collaboratively on a whole of institution focus on student transition and success. This paper describes ways in which local informal leadership is experienced at faculty level in an institutional FYE program, based on interviews with faculty coordinators and small grant recipients. Initial analysis using the distributed leadership tenets described by Jones, Hadgraft, Harvey, Lefoe, and Ryland (2014 revealed features that enabled success, such as collaborative communities, as well as faculty differences influenced by the strength of the external mandate for change in the FYE. More fine-grained analysis indicated further themes in engaging others, enabling and enacting the FYE program that fostered internal mandates for change: gaining buy-in; being opportunistic; making use of evidence of success and recognition; along with the need for collegial support for coordinators and self-perceptions of leadership being about making connections, collaboration, trust and expertise.

Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

Science.gov (United States)

Dussaillant, Francisca; Apablaza, Mauricio

2017-08-01

After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

Optimal distribution of temperature points in μSR measurement of local field

International Nuclear Information System (INIS)

Pełka, R.; Zieliński, P.M.; Konieczny, P.; Wasiutyński, T.

2013-01-01

Three possible distributions of temperature points in the μSR measurement of local field (order parameter) are discussed. The least square method is applied to estimate the scale of the deviations of the fitted parameters from the true values. It indicates that the distribution corresponding to a uniform section of the order parameter values (uniform-in-signal) incurs the smallest errors. The distribution constructed on the basis of the zeros of the Chebyshev polynomials yields comparable uncertainties, while the uniform-in-temperature distribution turns out to be least effective incurring considerably larger errors. These findings can be useful while planning an order parameter measurement in the μSR experiment

A Local Scalable Distributed EM Algorithm for Large P2P Networks

Data.gov (United States)

National Aeronautics and Space Administration — his paper describes a local and distributed expectation maximization algorithm for learning parameters of Gaussian mixture models (GMM) in large peer-to-peer (P2P)...

Carriers' localization and thermal redistribution in post growth voluntarily tuned quantum dashes' size/composition distribution

International Nuclear Information System (INIS)

Alouane, M.H. Hadj; Helali, A.; Morris, D.; Maaref, H.; Aimez, V.; Salem, B.; Gendry, M.

2014-01-01

This paper treats the impact of post growth tuned InAs/InP quantum dashes' (QDas) size/composition distribution on carriers' localization and thermal redistribution. The spread of this distribution depends on the experimental conditions used for the phosphorus ion implantation enhanced intermixing process. Atypical temperature-dependent luminescence properties have been observed and found to be strongly dependent on the amount of QDas size/composition dispersion. The experimental results have been reproduced by a model that takes into account the width of the QDas localized states distribution and consequent thermally induced carriers' redistribution. This model gives critical temperature values marking the beginning and the end of carriers delocalization and thermal transfer processes via an intermixing induced carrier's transfer channel located below the wetting layer states. -- Highlights: • We examine optical properties of post growth tuned QDas size/composition distribution. • Carriers' localization and thermal redistribution within inhomogeneously intermixed QDas are the origin of the atypical temperature-dependent luminescence properties. • Localized states ensemble's model is successively used to interpret the experimental results. • The carriers thermal transfer processes occur via an intermixing induced channel located below the wetting layer states. • Intermixing degree strongly influence the critical temperatures marking the beginning and the end of the carriers thermal transfer processes

Vision based persistent localization of a humanoid robot for locomotion tasks

Directory of Open Access Journals (Sweden)

Martínez Pablo A.

2016-09-01

Full Text Available Typical monocular localization schemes involve a search for matches between reprojected 3D world points and 2D image features in order to estimate the absolute scale transformation between the camera and the world. Successfully calculating such transformation implies the existence of a good number of 3D points uniformly distributed as reprojected pixels around the image plane. This paper presents a method to control the march of a humanoid robot towards directions that are favorable for visual based localization. To this end, orthogonal diagonalization is performed on the covariance matrices of both sets of 3D world points and their 2D image reprojections. Experiments with the NAO humanoid platform show that our method provides persistence of localization, as the robot tends to walk towards directions that are desirable for successful localization. Additional tests demonstrate how the proposed approach can be incorporated into a control scheme that considers reaching a target position.

Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

Science.gov (United States)

Xu, Xiao-Feng

2018-03-01

Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System.

Science.gov (United States)

Xiong, Lian; Yang, Liu; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-14

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay.

Myocardial distribution of I131-labeled hexadecenoic acid in relation to the dog local coronary flow

International Nuclear Information System (INIS)

Riche, F.; Busquet, G.; Pilichowski, P.; Wolf, J.E.; Mathieu, J.P.; Comet, M.; Pernin, C.; Vidal, M.; Vincens, M.; Godart, J.

1981-01-01

20 anesthetized and thoracotomized dogs are studied. The local myocardial blood flow is measured with sup(99m)Tc human albumin microspheres. The intramyocardial distribution of the 16-I(131)-9-hexadecenoic acid in relation to local blood flow is studied in basal conditions (7 dogs), after experimental infarction (6 dogs) and postischemic reactive hyperhemia (7 dogs). We conclude that during basal condition, after infarction but not during reactive hyperhemia, the distribution of the labeled fatty acid reflect the local variations of blood flow [fr

INEMO: Distributed RF-Based Indoor Location Determination with Confidence Indicator

Directory of Open Access Journals (Sweden)

Youxian Sun

2007-12-01

Full Text Available Using radio signal strength (RSS in sensor networks localization is an attractive method since it is a cost-efficient method to provide range indication. In this paper, we present a two-tier distributed approach for RF-based indoor location determination. Our approach, namely, INEMO, provides positioning accuracy of room granularity and office cube granularity. A target can first give a room granularity request and the background anchor nodes cooperate to accomplish the positioning process. Anchors in the same room can give cube granularity if the target requires further accuracy. Fixed anchor nodes keep monitoring status of nearby anchors and local reference matching is used to support room separation. Furthermore, we utilize the RSS difference to infer the positioning confidence. The simulation results demonstrate the efficiency of the proposed RF-based indoor location determination.

A Matrix-Based Proactive Data Relay Algorithm for Large Distributed Sensor Networks.

Science.gov (United States)

Xu, Yang; Hu, Xuemei; Hu, Haixiao; Liu, Ming

2016-08-16

In large-scale distributed sensor networks, sensed data is required to be relayed around the network so that one or few sensors can gather adequate relative data to produce high quality information for decision-making. In regards to very high energy-constraint sensor nodes, data transmission should be extremely economical. However, traditional data delivery protocols are potentially inefficient relaying unpredictable sensor readings for data fusion in large distributed networks for either overwhelming query transmissions or unnecessary data coverage. By building sensors' local model from their previously transmitted data in three matrixes, we have developed a novel energy-saving data relay algorithm, which allows sensors to proactively make broadcast decisions by using a neat matrix computation to provide balance between transmission and energy-saving. In addition, we designed a heuristic maintenance algorithm to efficiently update these three matrices. This can easily be deployed to large-scale mobile networks in which decisions of sensors are based on their local matrix models no matter how large the network is, and the local models of these sensors are updated constantly. Compared with some traditional approaches based on our simulations, the efficiency of this approach is manifested in uncertain environment. The results show that our approach is scalable and can effectively balance aggregating data with minimizing energy consumption.

Distributing Knight. Using Type-Based Publish/Subscribe for Building Distributed Collaboration Tools

DEFF Research Database (Denmark)

Damm, Christian Heide; Hansen, Klaus Marius

2002-01-01

more important. We present Distributed Knight, an extension to the Knight tool, for distributed, collaborative, and gesture-based object-oriented modelling. Distributed Knight was built using the type-based publish/subscribe paradigm. Based on this case, we argue that type-based publish......Distributed applications are hard to understand, build, and evolve. The need for decoupling, flexibility, and heterogeneity in distributed collaboration tools present particular problems; for such applications, having the right abstractions and primitives for distributed communication becomes even....../subscribe provides a natural and effective abstraction for developing distributed collaboration tools....

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.

RSS-based localization of isotropically decaying source with unknown power and pathloss factor

International Nuclear Information System (INIS)

Sun, Shunyuan; Sun, Li; Ding, Zhiguo

2016-01-01

This paper addresses the localization of an isotropically decaying source based on the received signal strength (RSS) measurements that are collected from nearby active sensors that are position-known and wirelessly connected, and it propose a novel iterative algorithm for RSS-based source localization in order to improve the location accuracy and realize real-time location and automatic monitoring for hospital patients and medical equipment in the smart hospital. In particular, we consider the general case where the source power and pathloss factor are both unknown. For such a source localization problem, we propose an iterative algorithm, in which the unknown source position and two other unknown parameters (i.e. the source power and pathloss factor) are estimated in an alternating way based on each other, with our proposed sub-optimum initial estimate on source position obtained based on the RSS measurements that are collected from a few (closest) active sensors with largest RSS values. Analysis and simulation study show that our proposed iterative algorithm guarantees globally convergence to the least-squares (LS) solution, where for our suitably assumed independent and identically distributed (i.i.d.) zero-mean Gaussian RSS measurement errors the converged localization performance achieves the optimum that corresponds to the Cramer–Rao lower bound (CRLB).

Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources

International Nuclear Information System (INIS)

Tabatabaee, Sajad; Mortazavi, Seyed Saeedallah; Niknam, Taher

2017-01-01

This paper investigates the optimal scheduling of electric power units in the renewable based local distribution systems considering plug-in electric vehicles (PEVs). The appearance of PEVs in the electric grid can create new challenges for the operation of distributed generations and power units inside the network. In order to deal with this issue, a new stochastic optimization method is devised to let the central controll manage the power units and charging behavior of PEVs. The problem formulation aims to minimize the total cost of the network including the cost of power supply for loads and PEVs as well as the cost of energy not supplied (ENS) as the reliability costs. In order to make PEVs as opportunity for the grid, the vehicle-2-grid (V2G) technology is employed to reduce the operational costs. To model the high uncertain behavior of wind turbine, photovoltaics and the charging and discharging pattern of PEVs, a new stochastic power flow based on unscented transform is proposed. Finally, a new optimization algorithm based on bat algorithm (BA) is proposed to solve the problem optimally. The satisfying performance of the proposed stochastic method is tested on a grid-connected local distribution system. - Highlights: • Introduction of stochastic method to assess Plug-in Electric Vehicles effects on the microgrid. • Assessing the role of V2G technology on battery aging and degradation costs. • Use of BA for solving the proposed problem. • Introduction of a new modification method for the BA.

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

Science.gov (United States)

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

Evaluation of secure capability-based access control in the M2M local cloud platform

DEFF Research Database (Denmark)

Anggorojati, Bayu; Prasad, Neeli R.; Prasad, Ramjee

2016-01-01

delegation. Recently, the capability based access control has been considered as method to manage access in the Internet of Things (IoT) or M2M domain. In this paper, the implementation and evaluation of a proposed secure capability based access control in the M2M local cloud platform is presented......Managing access to and protecting resources is one of the important aspect in managing security, especially in a distributed computing system such as Machine-to-Machine (M2M). One such platform known as the M2M local cloud platform, referring to BETaaS architecture [1], which conceptually consists...... of multiple distributed M2M gateways, creating new challenges in the access control. Some existing access control systems lack in scalability and flexibility to manage access from users or entity that belong to different authorization domains, or fails to provide fine grained and flexible access right...

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.

Combined local current distribution measurements and high resolution neutron radiography of operating direct methanol fuel cells

Energy Technology Data Exchange (ETDEWEB)

Schroeder, Alexander; Wippermann, Klaus [Forschungszentrum Juelich GmbH (Germany). Inst. of Energy Research, IEF-3: Fuel Cells; Sanders, Tilman [RWTH Aachen (DE). Inst. for Power Electronics and Electrical Drives (ISEA); Arlt, Tobias [Helmholtz Centre Berlin (Germany). Inst. for Applied Materials

2010-07-01

Neutron radiography allows the investigation of the local fluid distribution in direct methanol fuel cells (DMFCs) under operating conditions. Spatial resolutions in the order of some tens of micrometers at the full test cell area are achieved. This offers the possibility to study practice-oriented, large stack cells with an active area of several hundred cm{sup 2} as well as specially designed, small test cells with an area of some cm{sup 2}. Combined studies of high resolution neutron radiography and segmented cell measurements are especially valuable, because they enable a correlation of local fluid distribution and local performance [1, 2]. The knowledge of this interdependency is essential to optimise the water management and performance respecting a homogeneous fluid, current and temperature distribution and to achieve high performance and durability of DMFCs. (orig.)

Distribution of local critical current along sample length and its relation to overall current in a long Bi2223/Ag superconducting composite tape

International Nuclear Information System (INIS)

Ochiai, S; Doko, D; Okuda, H; Oh, S S; Ha, D W

2006-01-01

The distribution of the local critical current and the n-value along the sample length and its relation to the overall critical current were studied experimentally and analytically for the bent multifilamentary Bi2223/Ag/Ag-Mg alloy superconducting composite tape. Then, based on the results, it was attempted to simulate on a computer the dependence of the critical current on the sample length. The main results are summarized as follows. The experimentally observed relation of the distributed local critical current and n-value to the overall critical current was described comprehensively with a simple voltage summation model, in which the sample was regarded as a one-dimensional series circuit. The sample length dependence of the critical current was reproduced on the computer by a Monte Carlo simulation incorporating the voltage summation model and the regression analysis results for the local critical current distribution and the relation of the n-value to the critical current

Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms.

Science.gov (United States)

Grin-Yatsenko, Vera A; Ponomarev, Valery A; Pronina, Marina V; Poliakov, Yury I; Plotnikova, Irina V; Kropotov, Juri D

2017-09-01

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

Node-based analysis of species distributions

DEFF Research Database (Denmark)

Borregaard, Michael Krabbe; Rahbek, Carsten; Fjeldså, Jon

2014-01-01

overrepresentation score (SOS) and the geographic node divergence (GND) score, which together combine ecological and evolutionary patterns into a single framework and avoids many of the problems that characterize community phylogenetic methods in current use.This approach goes through each node in the phylogeny...... with case studies on two groups with well-described biogeographical histories: a local-scale community data set of hummingbirds in the North Andes, and a large-scale data set of the distribution of all species of New World flycatchers. The node-based analysis of these two groups generates a set...... of intuitively interpretable patterns that are consistent with current biogeographical knowledge.Importantly, the results are statistically tractable, opening many possibilities for their use in analyses of evolutionary, historical and spatial patterns of species diversity. The method is implemented...

Effect of local automatic control rods on three-dimensional calculations of the power distribution in an RBMK

International Nuclear Information System (INIS)

Pogosbekyan, L.R.; Lysov, D.A.; Bronitskii, L.L.

1993-01-01

Numerical simulators and information systems that support nuclear reactor operators must have fast models to estimate how fuel reloads and control rod displacement affect neutron and power distributions in the core. The consequences of reloads and control rod displacement cannot be evaluated correctly without considering local automatic control-rod operations in maintaining the radial power distribution. Fast three-dimensional models to estimate the effects of reloads and displacement of the control and safety rods have already been examined. I.V. Zonov et al. used the following assumptions in their calculational model: (1) the full-scale problem could be reduced a three-dimensional fragment of a locally perturbed core, and (2) the boundary conditions of the fragment and its total power were constant. The last assumption considers approximately how local automatic control rods stabilize the radial power distribution, but three dimensional calculations with these rods are not considered. These assumptions were introduced to obtain high computational speed. I.L. Bronitskii et al. considered in more detail how moving the local automatic control rods affect the power dimensional in the three-dimensional fragment, because, with on-line monitoring of the reload process, information on control rod positions is periodically renewed, and the calculations are done in real time. This model to predict the three-dimensional power distribution to (1) do a preliminary reload analysis, and (2) prepare the core for reloading did not consider the effect of perturbations from the local automatic control rods. Here we examine a model of a stationary neutron distribution. On one hand it gives results in an acceptable computation time; on the other it is a full-scale three-dimensional model and considers how local automatic control rods affect both the radial and axial power distribution

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

Science.gov (United States)

Xiong, Lian; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-01

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. PMID:29342897

Pilot-multiplexed continuous-variable quantum key distribution with a real local oscillator

Science.gov (United States)

Wang, Tao; Huang, Peng; Zhou, Yingming; Liu, Weiqi; Zeng, Guihua

2018-01-01

We propose a pilot-multiplexed continuous-variable quantum key distribution (CVQKD) scheme based on a local local oscillator (LLO). Our scheme utilizes time-multiplexing and polarization-multiplexing techniques to dramatically isolate the quantum signal from the pilot, employs two heterodyne detectors to separately detect the signal and the pilot, and adopts a phase compensation method to almost eliminate the multifrequency phase jitter. In order to analyze the performance of our scheme, a general LLO noise model is constructed. Besides the phase noise and the modulation noise, the photon-leakage noise from the reference path and the quantization noise due to the analog-to-digital converter (ADC) are also considered, which are first analyzed in the LLO regime. Under such general noise model, our scheme has a higher key rate and longer secure distance compared with the preexisting LLO schemes. Moreover, we also conduct an experiment to verify our pilot-multiplexed scheme. Results show that it maintains a low level of the phase noise and is expected to obtain a 554-Kbps secure key rate within a 15-km distance under the finite-size effect.

Effect of the irradiance distribution from light curing units on the local micro-hardness of the surface of dental resins.

Science.gov (United States)

Haenel, Thomas; Hausnerová, Berenika; Steinhaus, Johannes; Price, Richard B T; Sullivan, Braden; Moeginger, Bernhard

2015-02-01

An inhomogeneous irradiance distribution from a light-curing unit (LCU) can locally cause inhomogeneous curing with locally inadequately cured and/or over-cured areas causing e.g. monomer elution or internal shrinkage stresses, and thus reduce the lifetime of dental resin based composite (RBC) restorations. The aim of the study is to determine both the irradiance distribution of two light curing units (LCUs) and its influence on the local mechanical properties of a RBC. Specimens of Arabesk TOP OA2 were irradiated for 5, 20, and 80s using a Bluephase® 20i LCU in the Low mode (666mW/cm(2)), in the Turbo mode (2222mW/cm(2)) and a Celalux® 2 (1264mW/cm(2)). The degree of conversion (DC) was determined with an ATR-FTIR. The Knoop micro-hardness (average of five specimens) was measured on the specimen surface after 24h of dark and dry storage at room temperature. The irradiance distribution affected the hardness distribution across the surface of the specimens. The hardness distribution corresponded well to the inhomogeneous irradiance distributions of the LCU. The highest reaction rates occurred after approximately 2s light exposure. A DC of 40% was reached after 3.6 or 5.7s, depending on the LCU. The inhomogeneous hardness distribution was still evident after 80s of light exposure. The irradiance distribution from a LCU is reflected in the hardness distribution across the surface. Irradiance level of the LCU and light exposure time do not affect the pattern of the hardness distribution--only the hardness level. In areas of low irradiation this may result in inadequate resin polymerization, poor physical properties, and hence premature failure of the restorations as they are usually much smaller than the investigated specimens. It has to be stressed that inhomogeneous does not necessarily mean poor if in all areas of the restoration enough light intensity is introduced to achieve a high degree of cure. Copyright © 2014 Academy of Dental Materials. Published by

A Matrix-Based Proactive Data Relay Algorithm for Large Distributed Sensor Networks

Directory of Open Access Journals (Sweden)

Yang Xu

2016-08-01

Full Text Available In large-scale distributed sensor networks, sensed data is required to be relayed around the network so that one or few sensors can gather adequate relative data to produce high quality information for decision-making. In regards to very high energy-constraint sensor nodes, data transmission should be extremely economical. However, traditional data delivery protocols are potentially inefficient relaying unpredictable sensor readings for data fusion in large distributed networks for either overwhelming query transmissions or unnecessary data coverage. By building sensors’ local model from their previously transmitted data in three matrixes, we have developed a novel energy-saving data relay algorithm, which allows sensors to proactively make broadcast decisions by using a neat matrix computation to provide balance between transmission and energy-saving. In addition, we designed a heuristic maintenance algorithm to efficiently update these three matrices. This can easily be deployed to large-scale mobile networks in which decisions of sensors are based on their local matrix models no matter how large the network is, and the local models of these sensors are updated constantly. Compared with some traditional approaches based on our simulations, the efficiency of this approach is manifested in uncertain environment. The results show that our approach is scalable and can effectively balance aggregating data with minimizing energy consumption.

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...

Myocardial distribution of I/sup 131/-labeled hexadecenoic acid in relation to the dog local coronary flow

Energy Technology Data Exchange (ETDEWEB)

Riche, F.; Busquet, G.; Pilichowski, P.; Wolf, J.E.; Mathieu, J.P.; Comet, M.; Pernin, C. (Centre Hospitalier Regional, 38 - Grenoble (France)); Vidal, M.; Vincens, M.; Godart, J. (Grenoble-1 Univ., 38 (France). Inst. des Sciences Nucleaires)

1981-01-01

20 anesthetized and thoracotomized dogs are studied. The local myocardial blood flow is measured with sup(99m)Tc human albumin microspheres. The intramyocardial distribution of the 16-I(131)-9-hexadecenoic acid in relation to local blood flow is studied in basal conditions (7 dogs), after experimental infarction (6 dogs) and postischemic reactive hyperhemia (7 dogs). We conclude that during basal condition, after infarction but not during reactive hyperhemia, the distribution of the labeled fatty acid reflect the local variations of blood flow.

A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

Data.gov (United States)

National Aeronautics and Space Administration — This paper describes a local and distributed expectation maximization algorithm for learning parameters of Gaussian mixture models (GMM) in large peer-to-peer (P2P)...

Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

Science.gov (United States)

Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

2018-02-01

Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.

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.

Quasiparticle density of states, localization, and distributed disorder in the cuprate superconductors

Science.gov (United States)

Sulangi, Miguel Antonio; Zaanen, Jan

2018-04-01

We explore the effects of various kinds of random disorder on the quasiparticle density of states of two-dimensional d -wave superconductors using an exact real-space method, incorporating realistic details known about the cuprates. Random on-site energy and pointlike unitary impurity models are found to give rise to a vanishing DOS at the Fermi energy for narrow distributions and low concentrations, respectively, and lead to a finite, but suppressed, DOS at unrealistically large levels of disorder. Smooth disorder arising from impurities located away from the copper-oxide planes meanwhile gives rise to a finite DOS at realistic impurity concentrations. For the case of smooth disorder whose average potential is zero, a resonance is found at zero energy for the quasiparticle DOS at large impurity concentrations. We discuss the implications of these results on the computed low-temperature specific heat, the behavior of which we find is strongly affected by the amount of disorder present in the system. We also compute the localization length as a function of disorder strength for various types of disorder and find that intermediate- and high-energy states are quasiextended for low disorder, and that states near the Fermi energy are strongly localized and have a localization length that exhibits an unusual dependence on the amount of disorder. We comment on the origin of disorder in the cuprates and provide constraints on these based on known results from scanning tunneling spectroscopy and specific heat experiments.

New distributed fusion filtering algorithm based on covariances over sensor networks with random packet dropouts

Science.gov (United States)

Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

2017-07-01

This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.

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...

Localizing Play-Based Pedagogy: Nigerian Educators’ Appropriation of Sesame Classroom Materials

Directory of Open Access Journals (Sweden)

Naomi A. Moland

2017-09-01

Full Text Available This article examines how international organizations promote play-based pedagogical approaches in early childhood settings around the world, and how local educators respond. As a case study, I investigated Sesame Workshop’s efforts to introduce play-based approaches in Nigerian classrooms. In addition to producing a Nigerian version of Sesame Street (called Sesame Square, Sesame Workshop trains educators in play-based approaches and has distributed alphabet flashcards, puppet kits, and storytelling games to more than 2,700 early childhood classrooms across Nigeria. These materials were intended to support Sesame Square’s messages, and to foster interactive, child-centered learning experiences. However, teachers often used the materials in ways that reflected more rote-based, teacher centered approaches. Data was gathered through observations and interviews in 27 educational sites across Nigeria that use Sesame materials. Findings reveal that teachers’ resistance to play-based approaches was sometimes for structural reasons (e.g., large class sizes, and sometimes related to their knowledge and training (e.g., they were accustomed to drilling the alphabet. I argue that ideals about constructivist, play-based learning are being disseminated by international organizations—alongside contrasting formalistic pedagogical approaches—and that all approaches will shift as they are localized. I question if approaches that are considered universally developmentally appropriate are relevant in all settings, and explore how early childhood educators adapt global pedagogical trends to make sense in their classrooms. I call for international organizations to explore context-appropriate play-based approaches that develop educators’ capacities to help all children thrive, while also incorporating local cultural beliefs about childhood and teaching. 

Maximum likelihood estimation-based denoising of magnetic resonance images using restricted local neighborhoods

International Nuclear Information System (INIS)

Rajan, Jeny; Jeurissen, Ben; Sijbers, Jan; Verhoye, Marleen; Van Audekerke, Johan

2011-01-01

In this paper, we propose a method to denoise magnitude magnetic resonance (MR) images, which are Rician distributed. Conventionally, maximum likelihood methods incorporate the Rice distribution to estimate the true, underlying signal from a local neighborhood within which the signal is assumed to be constant. However, if this assumption is not met, such filtering will lead to blurred edges and loss of fine structures. As a solution to this problem, we put forward the concept of restricted local neighborhoods where the true intensity for each noisy pixel is estimated from a set of preselected neighboring pixels. To this end, a reference image is created from the noisy image using a recently proposed nonlocal means algorithm. This reference image is used as a prior for further noise reduction. A scheme is developed to locally select an appropriate subset of pixels from which the underlying signal is estimated. Experimental results based on the peak signal to noise ratio, structural similarity index matrix, Bhattacharyya coefficient and mean absolute difference from synthetic and real MR images demonstrate the superior performance of the proposed method over other state-of-the-art methods.

Web-Based Distributed XML Query Processing

NARCIS (Netherlands)

Smiljanic, M.; Feng, L.; Jonker, Willem; Blanken, Henk; Grabs, T.; Schek, H-J.; Schenkel, R.; Weikum, G.

2003-01-01

Web-based distributed XML query processing has gained in importance in recent years due to the widespread popularity of XML on the Web. Unlike centralized and tightly coupled distributed systems, Web-based distributed database systems are highly unpredictable and uncontrollable, with a rather

Normal mammogram detection based on local probability difference transforms and support vector machines

International Nuclear Information System (INIS)

Chiracharit, W.; Kumhom, P.; Chamnongthai, K.; Sun, Y.; Delp, E.J.; Babbs, C.F

2007-01-01

Automatic detection of normal mammograms, as a ''first look'' for breast cancer, is a new approach to computer-aided diagnosis. This approach may be limited, however, by two main causes. The first problem is the presence of poorly separable ''crossed-distributions'' in which the correct classification depends upon the value of each feature. The second problem is overlap of the feature distributions that are extracted from digitized mammograms of normal and abnormal patients. Here we introduce a new Support Vector Machine (SVM) based method utilizing with the proposed uncrossing mapping and Local Probability Difference (LPD). Crossed-distribution feature pairs are identified and mapped into a new features that can be separated by a zero-hyperplane of the new axis. The probability density functions of the features of normal and abnormal mammograms are then sampled and the local probability difference functions are estimated to enhance the features. From 1,000 ground-truth-known mammograms, 250 normal and 250 abnormal cases, including spiculated lesions, circumscribed masses or microcalcifications, are used for training a support vector machine. The classification results tested with another 250 normal and 250 abnormal sets show improved testing performances with 90% sensitivity and 89% specificity. (author)

Optimization of distribution piping network in district cooling system using genetic algorithm with local search

International Nuclear Information System (INIS)

Chan, Apple L.S.; Hanby, Vic I.; Chow, T.T.

2007-01-01

A district cooling system is a sustainable means of distribution of cooling energy through mass production. A cooling medium like chilled water is generated at a central refrigeration plant and supplied to serve a group of consumer buildings through a piping network. Because of the substantial capital investment involved, an optimal design of the distribution piping configuration is one of the crucial factors for successful implementation of the district cooling scheme. In the present study, genetic algorithm (GA) incorporated with local search techniques was developed to find the optimal/near optimal configuration of the piping network in a hypothetical site. The effect of local search, mutation rate and frequency of local search on the performance of the GA in terms of both solution quality and computation time were investigated and presented in this paper

Local and global stability for Lotka-Volterra systems with distributed delays and instantaneous negative feedbacks

Science.gov (United States)

Faria, Teresa; Oliveira, José J.

This paper addresses the local and global stability of n-dimensional Lotka-Volterra systems with distributed delays and instantaneous negative feedbacks. Necessary and sufficient conditions for local stability independent of the choice of the delay functions are given, by imposing a weak nondelayed diagonal dominance which cancels the delayed competition effect. The global asymptotic stability of positive equilibria is established under conditions slightly stronger than the ones required for the linear stability. For the case of monotone interactions, however, sharper conditions are presented. This paper generalizes known results for discrete delays to systems with distributed delays. Several applications illustrate the results.

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

Mesoscale characterization of local property distributions in heterogeneous electrodes

Science.gov (United States)

Hsu, Tim; Epting, William K.; Mahbub, Rubayyat; Nuhfer, Noel T.; Bhattacharya, Sudip; Lei, Yinkai; Miller, Herbert M.; Ohodnicki, Paul R.; Gerdes, Kirk R.; Abernathy, Harry W.; Hackett, Gregory A.; Rollett, Anthony D.; De Graef, Marc; Litster, Shawn; Salvador, Paul A.

2018-05-01

The performance of electrochemical devices depends on the three-dimensional (3D) distributions of microstructural features in their electrodes. Several mature methods exist to characterize 3D microstructures over the microscale (tens of microns), which are useful in understanding homogeneous electrodes. However, methods that capture mesoscale (hundreds of microns) volumes at appropriate resolution (tens of nm) are lacking, though they are needed to understand more common, less ideal electrodes. Using serial sectioning with a Xe plasma focused ion beam combined with scanning electron microscopy (Xe PFIB-SEM), two commercial solid oxide fuel cell (SOFC) electrodes are reconstructed over volumes of 126 × 73 × 12.5 and 124 × 110 × 8 μm3 with a resolution on the order of ≈ 503 nm3. The mesoscale distributions of microscale structural features are quantified and both microscale and mesoscale inhomogeneities are found. We analyze the origin of inhomogeneity over different length scales by comparing experimental and synthetic microstructures, generated with different particle size distributions, with such synthetic microstructures capturing well the high-frequency heterogeneity. Effective medium theory models indicate that significant mesoscale variations in local electrochemical activity are expected throughout such electrodes. These methods offer improved understanding of the performance of complex electrodes in energy conversion devices.

A hand-held sensor for analyses of local distributions of magnetic fields and losses

CERN Document Server

Krismanic, G; Baumgartinger, N

2000-01-01

The paper describes a novel sensor for non-destructive analyses of local field and loss distributions in laminated soft magnetic cores, such as transformer cores. It was designed for rapid information on comparative local degrees of inhomogeneity, e.g., for the estimation of local building factors. Similar to a magnifying glass with handle, the compact hand-held sensor contains extremely sharp needle electrodes for the detection of the induction vector B as well as double-field coils for the vector H. Losses P are derived from the Poynting law. Applied to inner -- or also outer -- core regions, the sensor yields instantaneous computer displays of local H, B, and P.

Retrospective analysis of 'gamma distribution' based IMRT QA criteria

International Nuclear Information System (INIS)

Wen, C.; Chappell, R.A.

2010-01-01

Full text: IMRT has been implemented into clinical practice at Royal Hobart Hospital (RHH) since mid 2006 for treating patients with Head and Neck (H and N) or prostate tumours. A local quality assurance (QA) acceptance criteria based on 'gamma distribution' for approving IMRT plan was developed and implemented in early 2007. A retrospective analysis of such criteria over 194 clinical cases will be presented. The RHH IMRT criteria was established with assumption that gamma distribution obtained through inter-comparison of 2 D dose maps between planned and delivered was governed by a positive-hail' normal distribution. A commercial system-MapCheck was used for 2 D dose map comparison with a built-in gamma analysis tool. Gamma distribution histogram was generated and recorded for all cases. By retrospectively analysing those distributions using curve fitting technique, a statistical gamma distribution can be obtained and evaluated. This analytical result can be used for future IMRT planing and treatment delivery. The analyses indicate that gamma distribution obtained through MapCheckTM is well under the normal distribution, particularly for prostate cases. The applied pass/fail criteria is not overly sensitive to identify 'false fails' but can be further tighten-up for smaller field while for larger field found in both H and N and prostate cases, the criteria was correctly applied. Non-uniform distribution of detectors in MapCheck and experience level of planners are two major factors to variation in gamma distribution among clinical cases. This criteria derived from clinical statistics is superior and more accurate than single-valued criteria for lMRT QA acceptance procedure. (author)

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.

A Virtual Private Local PCN Ring Network Based on ATM VP Cross—Connection

Institute of Scientific and Technical Information of China (English)

LinBin; MaYingjun; 等

1995-01-01

Avirtual private local PCNring network (VPLPR)is proposed .VPLPR is a virtual logic ring seuved for digital cordless telephone system and it works on ATM VP cross-connection mechanism.Full-distributed data bases are organized for visitor location registers(VLR)and home location register(HLR).The signaling protocols are compatible upward to B-ISDN. The architecture and some of the main characteristics of VPLPR are given.How to configure the ATM VP cross-connection ring is described.And then a protocol conversion between STM frames and ATMcells in base station controller(BSC)is presented.

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...

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

Directory of Open Access Journals (Sweden)

Brady J Mattsson

Full Text Available Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Fatigue Strength Estimation Based on Local Mechanical Properties for Aluminum Alloy FSW Joints

Directory of Open Access Journals (Sweden)

Kittima Sillapasa

2017-02-01

Full Text Available Overall fatigue strengths and hardness distributions of the aluminum alloy similar and dissimilar friction stir welding (FSW joints were determined. The local fatigue strengths as well as local tensile strengths were also obtained by using small round bar specimens extracted from specific locations, such as the stir zone, heat affected zone, and base metal. It was found from the results that fatigue fracture of the FSW joint plate specimen occurred at the location of the lowest local fatigue strength as well as the lowest hardness, regardless of microstructural evolution. To estimate the fatigue strengths of aluminum alloy FSW joints from the hardness measurements, the relationship between fatigue strength and hardness for aluminum alloys was investigated based on the present experimental results and the available wide range of data from the references. It was found as: σa (R = −1 = 1.68 HV (σa is in MPa and HV has no unit. It was also confirmed that the estimated fatigue strengths were in good agreement with the experimental results for aluminum alloy FSW joints.

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.

Local host specialization, host-switching, and dispersal shape the regional distributions of avian haemosporidian parasites.

Science.gov (United States)

Ellis, Vincenzo A; Collins, Michael D; Medeiros, Matthew C I; Sari, Eloisa H R; Coffey, Elyse D; Dickerson, Rebecca C; Lugarini, Camile; Stratford, Jeffrey A; Henry, Donata R; Merrill, Loren; Matthews, Alix E; Hanson, Alison A; Roberts, Jackson R; Joyce, Michael; Kunkel, Melanie R; Ricklefs, Robert E

2015-09-08

The drivers of regional parasite distributions are poorly understood, especially in comparison with those of free-living species. For vector-transmitted parasites, in particular, distributions might be influenced by host-switching and by parasite dispersal with primary hosts and vectors. We surveyed haemosporidian blood parasites (Plasmodium and Haemoproteus) of small land birds in eastern North America to characterize a regional parasite community. Distributions of parasite populations generally reflected distributions of their hosts across the region. However, when the interdependence between hosts and parasites was controlled statistically, local host assemblages were related to regional climatic gradients, but parasite assemblages were not. Moreover, because parasite assemblage similarity does not decrease with distance when controlling for host assemblages and climate, parasites evidently disperse readily within the distributions of their hosts. The degree of specialization on hosts varied in some parasite lineages over short periods and small geographic distances independently of the diversity of available hosts and potentially competing parasite lineages. Nonrandom spatial turnover was apparent in parasite lineages infecting one host species that was well-sampled within a single year across its range, plausibly reflecting localized adaptations of hosts and parasites. Overall, populations of avian hosts generally determine the geographic distributions of haemosporidian parasites. However, parasites are not dispersal-limited within their host distributions, and they may switch hosts readily.

Distributed illumination control with local sensing and actuation in networked lighting systems

NARCIS (Netherlands)

Caicedo Fernandez, D.R.; Pandharipande, A.

2013-01-01

We consider the problem of illumination control in a networked lighting system wherein luminaires have local sensing and actuation capabilities. Each luminaire (i) consists of a light emitting diode (LED) based light source dimmable by a local controller, (ii) is actuated based on sensing

Detection prospects for high energy neutrino sources from the anisotropic matter distribution in the local universe

DEFF Research Database (Denmark)

Mertsch, Philipp; Rameez, Mohamed; Tamborra, Irene

2017-01-01

Constraints on the number and luminosity of the sources of the cosmic neutrinos detected by IceCube have been set by targeted searches for point sources. We set complementary constraints by using the 2MASS Redshift Survey (2MRS) catalogue, which maps the matter distribution of the local Universe....... Assuming that the distribution of the neutrino sources follows that of matter we look for correlations between `warm' spots on the IceCube skymap and the 2MRS matter distribution. Through Monte Carlo simulations of the expected number of neutrino multiplets and careful modelling of the detector performance...... (including that of IceCube-Gen2) we demonstrate that sources with local density exceeding $10^{-6} \\, \\text{Mpc}^{-3}$ and neutrino luminosity $L_{\

Distributed Optimization based Dynamic Tariff for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Zhao, Haoran

2017-01-01

This paper proposes a distributed optimization based dynamic tariff (DDT) method for congestion management in distribution networks with high penetration of electric vehicles (EVs) and heat pumps (HPs). The DDT method employs a decomposition based optimization method to have aggregators explicitly...... is able to minimize the overall energy consumption cost and line loss cost, which is different from previous decomposition-based methods such as multiagent system methods. In addition, a reconditioning method and an integral controller are introduced to improve convergence of the distributed optimization...... where challenges arise due to multiple congestion points, multiple types of flexible demands and network constraints. The case studies demonstrate the efficacy of the DDT method for congestion management in distribution networks....

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

Science.gov (United States)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

Science.gov (United States)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

Localizing value of pain distribution patterns in cervical spondylosis.

Science.gov (United States)

Bunyaratavej, Krishnapundha; Montriwiwatnchai, Peerapong; Siwanuwatn, Rungsak; Khaoroptham, Surachai

2015-04-01

Prospective observational study. To investigate the value of pain distribution in localizing appropriate surgical levels in patients with cervical spondylosis. Previous studies have investigated the value of pain drawings in its correlation with various features in degenerative spine diseases including surgical outcome, magnetic resonance imaging findings, discographic study, and psychogenic issues. However, there is no previous study on the value of pain drawings in identifying symptomatic levels for the surgery in cervical spondylosis. The study collected data from patients with cervical spondylosis who underwent surgical treatment between August 2009 and July 2012. Pain diagrams drawn separately by each patient and physician were collected. Pain distribution patterns among various levels of surgery were analyzed by the chi-square test. Agreement between different pairs of data, including pain diagrams drawn by each patient and physician, intra-examiner agreement on interpretation of pain diagrams, inter-examiner agreement on interpretation of pain diagrams, interpretation of pain diagram by examiners and actual surgery, was analyzed by Kappa statistics. The study group consisted of 19 men and 28 women with an average age of 55.2 years. Average duration of symptoms was 16.8 months. There was no difference in the pain distribution pattern at any level of surgery. The agreement between pain diagram drawn by each patient and physician was moderate. Intra-examiner agreement was moderate. There was slight agreement of inter-examiners, examiners versus actual surgery. Pain distribution pattern by itself has limited value in identifying surgical levels in patients with cervical spondylosis.

Distributed Input and State Estimation Using Local Information in Heterogeneous Sensor Networks

Directory of Open Access Journals (Sweden)

Dzung Tran

2017-07-01

Full Text Available A new distributed input and state estimation architecture is introduced and analyzed for heterogeneous sensor networks. Specifically, nodes of a given sensor network are allowed to have heterogeneous information roles in the sense that a subset of nodes can be active (that is, subject to observations of a process of interest and the rest can be passive (that is, subject to no observation. Both fixed and varying active and passive roles of sensor nodes in the network are investigated. In addition, these nodes are allowed to have non-identical sensor modalities under the common underlying assumption that they have complimentary properties distributed over the sensor network to achieve collective observability. The key feature of our framework is that it utilizes local information not only during the execution of the proposed distributed input and state estimation architecture but also in its design in that global uniform ultimate boundedness of error dynamics is guaranteed once each node satisfies given local stability conditions independent from the graph topology and neighboring information of these nodes. As a special case (e.g., when all nodes are active and a positive real condition is satisfied, the asymptotic stability can be achieved with our algorithm. Several illustrative numerical examples are further provided to demonstrate the efficacy of the proposed architecture.

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

A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

Science.gov (United States)

Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

2014-01-01

Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

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…

Bluetooth-based distributed measurement system

International Nuclear Information System (INIS)

Tang Baoping; Chen Zhuo; Wei Yuguo; Qin Xiaofeng

2007-01-01

A novel distributed wireless measurement system, which is consisted of a base station, wireless intelligent sensors and relay nodes etc, is established by combining of Bluetooth-based wireless transmission, virtual instrument, intelligent sensor, and network. The intelligent sensors mounted on the equipments to be measured acquire various parameters and the Bluetooth relay nodes get the acquired data modulated and sent to the base station, where data analysis and processing are done so that the operational condition of the equipment can be evaluated. The establishment of the distributed measurement system is discussed with a measurement flow chart for the distributed measurement system based on Bluetooth technology, and the advantages and disadvantages of the system are analyzed at the end of the paper and the measurement system has successfully been used in Daqing oilfield, China for measurement of parameters, such as temperature, flow rate and oil pressure at an electromotor-pump unit

Bluetooth-based distributed measurement system

Science.gov (United States)

Tang, Baoping; Chen, Zhuo; Wei, Yuguo; Qin, Xiaofeng

2007-07-01

A novel distributed wireless measurement system, which is consisted of a base station, wireless intelligent sensors and relay nodes etc, is established by combining of Bluetooth-based wireless transmission, virtual instrument, intelligent sensor, and network. The intelligent sensors mounted on the equipments to be measured acquire various parameters and the Bluetooth relay nodes get the acquired data modulated and sent to the base station, where data analysis and processing are done so that the operational condition of the equipment can be evaluated. The establishment of the distributed measurement system is discussed with a measurement flow chart for the distributed measurement system based on Bluetooth technology, and the advantages and disadvantages of the system are analyzed at the end of the paper and the measurement system has successfully been used in Daqing oilfield, China for measurement of parameters, such as temperature, flow rate and oil pressure at an electromotor-pump unit.

Bluetooth-based distributed measurement system

Energy Technology Data Exchange (ETDEWEB)

Tang Baoping; Chen Zhuo; Wei Yuguo; Qin Xiaofeng [Department of Mechatronics, College of Mechanical Engineering, Chongqing University, Chongqing, 400030 (China)

2007-07-15

A novel distributed wireless measurement system, which is consisted of a base station, wireless intelligent sensors and relay nodes etc, is established by combining of Bluetooth-based wireless transmission, virtual instrument, intelligent sensor, and network. The intelligent sensors mounted on the equipments to be measured acquire various parameters and the Bluetooth relay nodes get the acquired data modulated and sent to the base station, where data analysis and processing are done so that the operational condition of the equipment can be evaluated. The establishment of the distributed measurement system is discussed with a measurement flow chart for the distributed measurement system based on Bluetooth technology, and the advantages and disadvantages of the system are analyzed at the end of the paper and the measurement system has successfully been used in Daqing oilfield, China for measurement of parameters, such as temperature, flow rate and oil pressure at an electromotor-pump unit.

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.

Multicrack Localization in Rotors Based on Proper Orthogonal Decomposition Using Fractal Dimension and Gapped Smoothing Method

Directory of Open Access Journals (Sweden)

Zhiwen Lu

2016-01-01

Full Text Available Multicrack localization in operating rotor systems is still a challenge today. Focusing on this challenge, a new approach based on proper orthogonal decomposition (POD is proposed for multicrack localization in rotors. A two-disc rotor-bearing system with breathing cracks is established by the finite element method and simulated sensors are distributed along the rotor to obtain the steady-state transverse responses required by POD. Based on the discontinuities introduced in the proper orthogonal modes (POMs at the locations of cracks, the characteristic POM (CPOM, which is sensitive to crack locations and robust to noise, is selected for cracks localization. Instead of using the CPOM directly, due to its difficulty to localize incipient cracks, damage indexes using fractal dimension (FD and gapped smoothing method (GSM are adopted, in order to extract the locations more efficiently. The method proposed in this work is validated to be effective for multicrack localization in rotors by numerical experiments on rotors in different crack configuration cases considering the effects of noise. In addition, the feasibility of using fewer sensors is also investigated.

Towards A Complete Census of the Compton-thick AGN population and the NH Distribution of AGN in the Local Universe.

Science.gov (United States)

Annuar, A.

2015-09-01

We present updated results from an ongoing project to establish the most unbiased census of the Compton- thick active galactic nucleus (CTAGN) population and the intrinsic column density (NH) distribution of the overall AGN population in the local universe, using a sample of mid-infrared (mid-IR) selected AGN within 15 Mpc. We find that 20% of the AGN in the sample are bona-fide CTAGN based upon hard X-ray studies (E > 10 keV). More candidates are then selected using multiwavelength techniques, i.e. mid-IR:X-ray and optical [OIII]5007:X-ray flux ratios. Based on these analyses along with evidence from previous literature, we initially find a further 25% of potential candidates. We then observed two of these candidates, NGC 5643 and NGC 3486, using NuSTAR and is able to confirm the former as a CTAGN and rule out the latter as an obscured AGN. This constrains the total CTAGN population in the sample to 25-40%, though it could potentially be as high as 65% accounting for those that still lack data. Finally, we use these results to estimate the intrinsic NH distribution of the local AGN population. Two more of our CTAGN candidates are scheduled to be observed by NuSTAR, bringing the completeness of hard X-ray energy data of the sample to 65%. This work provides a well-defined local benchmark for AGN unification studies.

Blind Separation of Nonstationary Sources Based on Spatial Time-Frequency Distributions

Directory of Open Access Journals (Sweden)

Zhang Yimin

2006-01-01

Full Text Available Blind source separation (BSS based on spatial time-frequency distributions (STFDs provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localized in the time-frequency (t-f domain. In this paper, we propose the use of STFD matrices for both whitening and recovery of the mixing matrix, which are two stages commonly required in many BSS methods, to provide robust BSS performance to noise. In addition, a simple method is proposed to select the auto- and cross-term regions of time-frequency distribution (TFD. To further improve the BSS performance, t-f grouping techniques are introduced to reduce the number of signals under consideration, and to allow the receiver array to separate more sources than the number of array sensors, provided that the sources have disjoint t-f signatures. With the use of one or more techniques proposed in this paper, improved performance of blind separation of nonstationary signals can be achieved.

Improving electrical power systems reliability through locally controlled distributed curtailable load

Science.gov (United States)

Dehbozorgi, Mohammad Reza

2000-10-01

Improvements in power system reliability have always been of interest to both power companies and customers. Since there are no sizable electrical energy storage elements in electrical power systems, the generated power should match the load demand at any given time. Failure to meet this balance may cause severe system problems, including loss of generation and system blackouts. This thesis proposes a methodology which can respond to either loss of generation or loss of load. It is based on switching of electric water heaters using power system frequency as the controlling signal. The proposed methodology encounters, and the thesis has addressed, the following associated problems. The controller must be interfaced with the existing thermostat control. When necessary to switch on loads, the water in the tank should not be overheated. Rapid switching of blocks of load, or chattering, has been considered. The contributions of the thesis are: (A) A system has been proposed which makes a significant portion of the distributed loads connected to a power system to behave in a predetermined manner to improve the power system response during disturbances. (B) The action of the proposed system is transparent to the customers. (C) The thesis proposes a simple analysis for determining the amount of such loads which might be switched and relates this amount to the size of the disturbances which can occur in the utility. (D) The proposed system acts without any formal communication links, solely using the embedded information present system-wide. (E) The methodology of the thesis proposes switching of water heater loads based on a simple, localized frequency set-point controller. The thesis has identified the consequent problem of rapid switching of distributed loads, which is referred to as chattering. (F) Two approaches have been proposed to reduce chattering to tolerable levels. (G) A frequency controller has been designed and built according to the specifications required to

Distributed open environment for data retrieval based on pattern recognition techniques

International Nuclear Information System (INIS)

Pereira, A.; Vega, J.; Castro, R.; Portas, A.

2010-01-01

Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.

Distributed Open Environment for Data Retrieval based on Pattern Recognition Techniques

Energy Technology Data Exchange (ETDEWEB)

Pereira, A.; Vega, J.; Castro, R.; Portas, A. [Association EuratomCIEMAT para Fusion, Madrid (Spain)

2009-07-01

Full text of publication follows: Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, inter-operability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE, which provides a mature standard framework and a modular architecture. It can handle transactions and competition of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows concealment of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests. (authors)

Distributed open environment for data retrieval based on pattern recognition techniques

Energy Technology Data Exchange (ETDEWEB)

Pereira, A., E-mail: augusto.pereira@ciemat.e [Asociacion EURATOM/CIEMAT para Fusion, CIEMAT, Edificio 66, Avda. Complutense, 22, 28040 Madrid (Spain); Vega, J.; Castro, R.; Portas, A. [Asociacion EURATOM/CIEMAT para Fusion, CIEMAT, Edificio 66, Avda. Complutense, 22, 28040 Madrid (Spain)

2010-07-15

Pattern recognition methods for data retrieval have been applied to fusion databases for the localization and extraction of similar waveforms within temporal evolution signals. In order to standardize the use of these methods, a distributed open environment has been designed. It is based on a client/server architecture that supports distribution, interoperability and portability between heterogeneous platforms. The server part is a single desktop application based on J2EE (Java 2 Enterprise Edition), which provides a mature standard framework and a modular architecture. It can handle transactions and concurrency of components that are deployed on JETTY, an embedded web container within the Java server application for providing HTTP services. The data management is based on Apache DERBY, a relational database engine also embedded on the same Java based solution. This encapsulation allows hiding of unnecessary details about the installation, distribution, and configuration of all these components but with the flexibility to create and allocate many databases on different servers. The DERBY network module increases the scope of the installed database engine by providing traditional Java database network connections (JDBC-TCP/IP). This avoids scattering several database engines (a unique embedded engine defines the rules for accessing the distributed data). Java thin clients (Java 5 or above is the unique requirement) can be executed in the same computer than the server program (for example a desktop computer) but also server and client software can be distributed in a remote participation environment (wide area networks). The thin client provides graphic user interface to look for patterns (entire waveforms or specific structural forms) and display the most similar ones. This is obtained with HTTP requests and by generating dynamic content (servlets) in response to these client requests.

Evaluation of local power distribution with fine-mesh core model for the HTTR

International Nuclear Information System (INIS)

Murata, Isao; Yamashita, Kiyonobu; Maruyama, So; Shindo, Ryuichi; Fujimoto, Nozomu; Sudo, Yukio; Nakata, Tetsuo.

1991-01-01

An evaluation method of the local power distribution was developed considering the radial and axial heterogeneity caused by fuel rods, BP rods and block end graphite for the High Temperature Engineering Test Reactor (HTTR) in Japan Atomic Energy Research Institute (JAERI). The evaluation method was verified through the analyses of critical assembly experiments. A good agreement was obtained between calculations and measurements and the difference was less than 3 % on the power distribution. This method was applied to the core design for the HTTR to evaluate the maximum fuel temperature. From these results, it was confirmed that this evaluation method has an enough accuracy and is able to predict the detailed power distribution of the HTTR. (author)

Distribution of local magnetic field of vortex lattice near anisotropic superconductor surface in inclined external fields

International Nuclear Information System (INIS)

Efremova, S.A.; Tsarevskij, S.L.

1997-01-01

Magnetic field distribution in a unit cell of the Abrikosov vortex lattice near the surface of monoaxial anisotropic type-ii superconductors in inclined external magnetic field has been found in the framework of London model for the cases when the symmetry axis is perpendicular and parallel to the superconductor surface interface. Distribution of local magnetic field as a function of the distance from the superconductor interface surface and external field inclination angle has been obtained. Using high-Tc superconductor Y-Ba-Cu-O by way of examples, it has been shown that the study of local magnetic field distribution function, depending on external magnetic field inclination angle towards the superconductor symmetry axis and towards the superconductor surface, can provide important data on anisotropic properties of the superconductor [ru

Research on suitable heating conditions during local PWHT. Pt. 1. Influence of heating conditions on temperature distribution

International Nuclear Information System (INIS)

Tanaka, Jinkichi; Horii, Yukihiko; Sato, Masanobu; Murakawa, Hidekazu; Wang Jianhua

1999-01-01

To improve weld joint properties a heat treatment so called post weld heat treatment (PWHT) is often implemented for steel weldment. Generally, the PWHT is conducted in a furnace at a factory. But in site welds such as the girth joint of pipe, a local PWHT is applied using electric heater and so on. In the local PWHT steep temperature gradient occurs depending on the heating condition and it leads to rise of the thermal stress in addition to the welding residual stress. However, heating condition is not always defined the same in some standards. Therefore, suitable heat conditions for the local PWHT were studied supposing the power plant and so on experimentally and theoretically. Temperature distribution and thermal strains under different heating conditions were measured during the local PWHT using carbon steel pipes of 340 mm in diameter and 53 mm in wall thickness. The temperature gradient, thermal strain were also analyzed using Finite Element Method (FEM) as axis-symmetric model. Further, the influences of pipe size and heat transfer coefficient on the temperature distribution were analyzed and suitable heating source widths for various pipe sizes were proposed from the viewpoint of temperature distribution. (orig.)

Distributed generation solutions: changes and opportunities for distribution companies

International Nuclear Information System (INIS)

Chuddy, B.

2004-01-01

'Full text:' The rapid expansion of hydrogen based power alternatives and other significant distributed generation (DG) alternatives is changing the traditional role of the local electricity distributor. This presentation is about opportunities related to incorporating such facilities into LDC and client distribution systems. This ranges from support of large co-generation facilities, such as that under development at Mississauga's Pearson International, to the integration of output from varied new forms small-scale, wind, biomass, and fuel cell power production within local distribution networks. Mr. Chuddy will examine Enersource's present and anticipated role: (1) as a technologies company aiding in developing distribution systems that integrate and fully utilize DG technology into those models and; (2) as an LDC that continues to lead the conservation movement on several fronts, including advocacy of aggregated demand response mechanisms in Ontario's wholesale market design. (author)

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.

Mapping local and global variability in plant trait distributions

Energy Technology Data Exchange (ETDEWEB)

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; Chen, Ming; Wythers, Kirk R.; Fazayeli, Farideh; Banerjee, Arindam; Atkin, Owen K.; Kattge, Jens; Amiaud, Bernard; Blonder, Benjamin; Boenisch, Gerhard; Bond-Lamberty, Ben; Brown, Kerry A.; Byun, Chaeho; Campetella, Giandiego; Cerabolini, Bruno E. L.; Cornelissen, Johannes H. C.; Craine, Joseph M.; Craven, Dylan; de Vries, Franciska T.; Díaz, Sandra; Domingues, Tomas F.; Forey, Estelle; González-Melo, Andrés; Gross, Nicolas; Han, Wenxuan; Hattingh, Wesley N.; Hickler, Thomas; Jansen, Steven; Kramer, Koen; Kraft, Nathan J. B.; Kurokawa, Hiroko; Laughlin, Daniel C.; Meir, Patrick; Minden, Vanessa; Niinemets, Ülo; Onoda, Yusuke; Peñuelas, Josep; Read, Quentin; Sack, Lawren; Schamp, Brandon; Soudzilovskaia, Nadejda A.; Spasojevic, Marko J.; Sosinski, Enio; Thornton, Peter E.; Valladares, Fernando; van Bodegom, Peter M.; Williams, Mathew; Wirth, Christian; Reich, Peter B.

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrence ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.

Finger Vein Recognition Based on Local Directional Code

Science.gov (United States)

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

2012-01-01

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

Finger Vein Recognition Based on Local Directional Code

Directory of Open Access Journals (Sweden)

Rongyang Xiao

2012-11-01

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

Subspace Learning via Local Probability Distribution for Hyperspectral Image Classification

Directory of Open Access Journals (Sweden)

Huiwu Luo

2015-01-01

Full Text Available The computational procedure of hyperspectral image (HSI is extremely complex, not only due to the high dimensional information, but also due to the highly correlated data structure. The need of effective processing and analyzing of HSI has met many difficulties. It has been evidenced that dimensionality reduction has been found to be a powerful tool for high dimensional data analysis. Local Fisher’s liner discriminant analysis (LFDA is an effective method to treat HSI processing. In this paper, a novel approach, called PD-LFDA, is proposed to overcome the weakness of LFDA. PD-LFDA emphasizes the probability distribution (PD in LFDA, where the maximum distance is replaced with local variance for the construction of weight matrix and the class prior probability is applied to compute the affinity matrix. The proposed approach increases the discriminant ability of the transformed features in low dimensional space. Experimental results on Indian Pines 1992 data indicate that the proposed approach significantly outperforms the traditional alternatives.

Learning Based Approach for Optimal Clustering of Distributed Program's Call Flow Graph

Science.gov (United States)

Abofathi, Yousef; Zarei, Bager; Parsa, Saeed

Optimal clustering of call flow graph for reaching maximum concurrency in execution of distributable components is one of the NP-Complete problems. Learning automatas (LAs) are search tools which are used for solving many NP-Complete problems. In this paper a learning based algorithm is proposed to optimal clustering of call flow graph and appropriate distributing of programs in network level. The algorithm uses learning feature of LAs to search in state space. It has been shown that the speed of reaching to solution increases remarkably using LA in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of proposed algorithm over others.

Monitoring device for local power peaking coefficients

International Nuclear Information System (INIS)

Mihashi, Ishi

1987-01-01

Purpose: To determine and monitor the local power peaking coefficients by a method not depending on the combination of fuel types. Constitution: Representative values for the local power distribution can be obtained by determining corresponding burn-up degrees based on the burn-up degree of each of fuel assembly segments obtained in a power distribution monitor and by the interpolation and extrapolation of void coefficients. The typical values are multiplied with compensation coefficients for the control rod effect and coefficients for compensating the effect of adjacent fuel assemblies in a calculation device to obtain typical values for the present local power distribution compensated with all of the effects. Further, the calculation device compares them with typical values of the present local power distribution to obtain an aimed local power peaking coefficient as the maximum value thereof. According to the present invention, since the local power peaking coefficients can be determined not depending on the combination of the kind of fuels, if the combination of fuel assemblies is increased upon fuel change, the amount of operation therefor is not increased. (Kamimura, M.)

On the sufficient conditions of the localization of the Fourier-Laplace series of distributions from liouville classes

International Nuclear Information System (INIS)

Ahmedov, Anvarjon A; Nurullah bin Rasedee, Ahmad Fadly; Rakhimov, Abdumalik

2013-01-01

In this work we investigate the localization principle of the Fourier-Laplace series of the distribution. Here we prove the sufficient conditions of the localization of the Riesz means of the spectral expansions of the Laplace-Beltrami operator on the unit sphere.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

Directory of Open Access Journals (Sweden)

Johannes Bill

Full Text Available During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Science.gov (United States)

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

A distributed substation automation model based on the multi-agents technology; Um modelo distribuido de automacao de subestacoes baseado em tecnologia multiagentes

Energy Technology Data Exchange (ETDEWEB)

Geus, Klaus de; Milsztajn, Flavio; Kolb, Carlos Jose Johann; Dometerco, Jose Henrique; Souza, Alexandre Mendonca de; Braga, Ciro de Carvalho; Parolin, Emerson Luis; Frisch, Arlenio Carneiro; Fortunato Junior, Luiz Kiss; Erzinger Junior, Augusto; Jonack, Marco Antonio; Guiera, Anderson Juliano Azambuja [Companhia Paranaense de Energia (COPEL), Curitiba, PR (Brazil)]. E-mail: klaus@copel.com; flaviomil@copel.com; kolb@copel.com; dometerc@copel.com; alexandre.mendonca@copel.com; ciro@copel.com; parolin@copel.com; arlenio@copel.com; luiz.kiss@copel.com; aerzinger@copel.com; jonack@copel.com; guiera@copel.com

2006-10-15

The main purpose of this paper is to analyse distributed computing technology which can be used in substation automation systems. Based on performance comparative results obtained in laboratory, a specific model for distributed substation automation is proposed considering the current model employed at COPEL - Companhia Paranaense de Energia. The proposed model is based on the multi-agents technology, which has lately received special attention in the development of distributed systems with local intelligence. (author)

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

Science.gov (United States)

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms

Directory of Open Access Journals (Sweden)

Ying Zhang

2016-02-01

Full Text Available Due to their special environment, Underwater Wireless Sensor Networks (UWSNs are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field.

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms.

Science.gov (United States)

Zhang, Ying; Liang, Jixing; Jiang, Shengming; Chen, Wei

2016-02-06

Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object's mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

Science.gov (United States)

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

A Local Asynchronous Distributed Privacy Preserving Feature Selection Algorithm for Large Peer-to-Peer Networks

Data.gov (United States)

National Aeronautics and Space Administration — In this paper we develop a local distributed privacy preserving algorithm for feature selection in a large peer-to-peer environment. Feature selection is often used...

Performance analysis for IEEE 802.11 distributed coordination function in radio-over-fiber-based distributed antenna systems.

Science.gov (United States)

Fan, Yuting; Li, Jianqiang; Xu, Kun; Chen, Hao; Lu, Xun; Dai, Yitang; Yin, Feifei; Ji, Yuefeng; Lin, Jintong

2013-09-09

In this paper, we analyze the performance of IEEE 802.11 distributed coordination function in simulcast radio-over-fiber-based distributed antenna systems (RoF-DASs) where multiple remote antenna units (RAUs) are connected to one wireless local-area network (WLAN) access point (AP) with different-length fiber links. We also present an analytical model to evaluate the throughput of the systems in the presence of both the inter-RAU hidden-node problem and fiber-length difference effect. In the model, the unequal delay induced by different fiber length is involved both in the backoff stage and in the calculation of Ts and Tc, which are the period of time when the channel is sensed busy due to a successful transmission or a collision. The throughput performances of WLAN-RoF-DAS in both basic access and request to send/clear to send (RTS/CTS) exchange modes are evaluated with the help of the derived model.

Neutron distribution modeling based on integro-probabilistic approach of discrete ordinates method

International Nuclear Information System (INIS)

Khromov, V.V.; Kryuchkov, E.F.; Tikhomirov, G.V.

1992-01-01

In this paper is described the universal nodal method for the neutron distribution calculation in reactor and shielding problems, based on using of influence functions and factors of local-integrated volume and surface neutron sources in phase subregions. This method permits to avoid the limited capabilities of collision-probability method concerning with the detailed calculation of angular neutron flux dependence, scattering anisotropy and empty channels. The proposed method may be considered as modification of S n - method with advantage of ray-effects elimination. There are presented the description of method theory and algorithm following by the examples of method applications for calculation of neutron distribution in three-dimensional model of fusion reactor blanket and in highly heterogeneous reactor with empty channel

Power Consumption Evaluation of Distributed Computing Network Considering Traffic Locality

Science.gov (United States)

Ogawa, Yukio; Hasegawa, Go; Murata, Masayuki

When computing resources are consolidated in a few huge data centers, a massive amount of data is transferred to each data center over a wide area network (WAN). This results in increased power consumption in the WAN. A distributed computing network (DCN), such as a content delivery network, can reduce the traffic from/to the data center, thereby decreasing the power consumed in the WAN. In this paper, we focus on the energy-saving aspect of the DCN and evaluate its effectiveness, especially considering traffic locality, i.e., the amount of traffic related to the geographical vicinity. We first formulate the problem of optimizing the DCN power consumption and describe the DCN in detail. Then, numerical evaluations show that, when there is strong traffic locality and the router has ideal energy proportionality, the system's power consumption is reduced to about 50% of the power consumed in the case where a DCN is not used; moreover, this advantage becomes even larger (up to about 30%) when the data center is located farthest from the center of the network topology.

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

Science.gov (United States)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Jianzhong Wang

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

Impact of localized microwave hyperthermia on the pH-distribution in malignant tumors

International Nuclear Information System (INIS)

Vaupel, P.

1982-01-01

The impact of localized microwave hyperthermia (2.45 GHz) on the tissue pH-distribution was investigated in C3H mause mammary tumors. The measurements were performed in microareas of the tissue using pH-microelectrodes with tip diameters of approximately 1 μm. pH-readings during localized heating revealed that tissue temperatures exceeding 42 0 C were followed by a pronounced pH-drop in tumors with a negligible amount of necrosis. Tissue pH-values measured immediately after heating (43 0 C for 60 min) were lowered by an average of 0.54 +- 0.19 pH-units as compared with preheating data (2p [de

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

Science.gov (United States)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

Local search in physical distribution management

NARCIS (Netherlands)

G.A.P. Kindervater (Gerard); M.W.P. Savelsbergh (Martin)

1992-01-01

textabstractPhysical distribution management presents a variety of decision making problems at three levels of strategic, tactical and operational planning. The importance of effective and efficient distribution management is evident from its associated costs. Physical distribution management at the

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

A Geographic Information Systems (GIS)-based analysis of modern South African rodent distributions, habitat use, and environmental tolerances.

Science.gov (United States)

Campbell, Timothy L; Lewis, Patrick J; Thies, Monte L; Williams, Justin K

2012-11-01

GOALS OF THIS STUDY WERE TO: (1) develop distributional maps of modern rodent genera throughout the countries of South Africa, Lesotho, and Swaziland by georeferencing museum specimens; (2) assess habitat preferences for genera by cross-referencing locality position with South African vegetation; and (3) identify mean annual precipitation and temperature range where the genera are located. Conterminous South Africa including the countries of Lesotho and Swaziland Digital databases of rodent museum specimens housed in the Ditsong National Museum of Natural History, South Africa (DM), and the Division of Mammals, National Museum of Natural History, Smithsonian Institution, United States (NMNH), were acquired and then sorted into a subset of specimens with associated coordinate data. The coordinate data were then used to develop distributional maps for the rodent genera present within the study area. Percent habitat occupation and descriptive statistics for six climatic variables were then determined for each genus by cross-referencing locality positions with vegetation and climatic maps. This report presents a series of maps illustrating the distribution of 35 rodent genera based on 19,471 geo-referenced specimens obtained from two major collections. Inferred habitat use by taxon is provided for both locality and specimen percent occurrence at three hierarchical habitat levels: biome, bioregion, and vegetation unit. Descriptive statistics for six climatic variables are also provided for each genus based on locality and specimen percent incidence. As rodent faunas are commonly used in paleoenvironmental reconstructions, an accurate assessment of rodent environmental tolerance ranges is necessary before confidence can be placed in an actualistic model. While the data presented here represent only a subset of the modern geographic distributions for many of the taxa examined, a wide range of environmental regimes are observed, suggesting that more research is necessary

A Geographic Information Systems (GIS)-based analysis of modern South African rodent distributions, habitat use, and environmental tolerances

Science.gov (United States)

Campbell, Timothy L; Lewis, Patrick J; Thies, Monte L; Williams, Justin K

2012-01-01

Goals of this study were to: (1) develop distributional maps of modern rodent genera throughout the countries of South Africa, Lesotho, and Swaziland by georeferencing museum specimens; (2) assess habitat preferences for genera by cross-referencing locality position with South African vegetation; and (3) identify mean annual precipitation and temperature range where the genera are located. Conterminous South Africa including the countries of Lesotho and Swaziland Digital databases of rodent museum specimens housed in the Ditsong National Museum of Natural History, South Africa (DM), and the Division of Mammals, National Museum of Natural History, Smithsonian Institution, United States (NMNH), were acquired and then sorted into a subset of specimens with associated coordinate data. The coordinate data were then used to develop distributional maps for the rodent genera present within the study area. Percent habitat occupation and descriptive statistics for six climatic variables were then determined for each genus by cross-referencing locality positions with vegetation and climatic maps. This report presents a series of maps illustrating the distribution of 35 rodent genera based on 19,471 geo-referenced specimens obtained from two major collections. Inferred habitat use by taxon is provided for both locality and specimen percent occurrence at three hierarchical habitat levels: biome, bioregion, and vegetation unit. Descriptive statistics for six climatic variables are also provided for each genus based on locality and specimen percent incidence. As rodent faunas are commonly used in paleoenvironmental reconstructions, an accurate assessment of rodent environmental tolerance ranges is necessary before confidence can be placed in an actualistic model. While the data presented here represent only a subset of the modern geographic distributions for many of the taxa examined, a wide range of environmental regimes are observed, suggesting that more research is necessary

A Multi-Agent Traffic Control Model Based on Distributed System

Directory of Open Access Journals (Sweden)

Qian WU

2014-06-01

Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

Measures of Dependence for α-Stable Distributed Processes and Its Application to Diagnostics of Local Damage in Presence of Impulsive Noise

Directory of Open Access Journals (Sweden)

Grzegorz Żak

2017-01-01

Full Text Available Local damage detection in rotating machinery is simply searching for cyclic impulsive signal in noisy observation. Such raw signal is mixture of various components with specific properties (deterministic, random, cyclic, impulsive, etc.. The problem appears when the investigated process is based on one of the heavy-tailed distributions. In this case the classical measure can not be considered. Therefore, alternative measures of dependence adequate for such processes should be considered. In this paper we examine the structure of dependence of alpha-stable based systems expressed by means of two measures, namely, codifference and covariation. The reason for using alpha-stable distribution is simple and intuitive: signal of interest is impulsive so its distribution is heavy-tailed. The main goal is to introduce a new technique for estimation of covariation. Due to the complex nature of such vibration signals applying novel methods instead of classical ones is recommended. Classical algorithms usually are based on the assumption that theoretical second moment is finite, which is not true in case of the data acquired on the faulty components. Main advantage of our proposed algorithm is independence from second moment assumption.

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.

Multi-link faults localization and restoration based on fuzzy fault set for dynamic optical networks.

Science.gov (United States)

Zhao, Yongli; Li, Xin; Li, Huadong; Wang, Xinbo; Zhang, Jie; Huang, Shanguo

2013-01-28

Based on a distributed method of bit-error-rate (BER) monitoring, a novel multi-link faults restoration algorithm is proposed for dynamic optical networks. The concept of fuzzy fault set (FFS) is first introduced for multi-link faults localization, which includes all possible optical equipment or fiber links with a membership describing the possibility of faults. Such a set is characterized by a membership function which assigns each object a grade of membership ranging from zero to one. OSPF protocol extension is designed for the BER information flooding in the network. The BER information can be correlated to link faults through FFS. Based on the BER information and FFS, multi-link faults localization mechanism and restoration algorithm are implemented and experimentally demonstrated on a GMPLS enabled optical network testbed with 40 wavelengths in each fiber link. Experimental results show that the novel localization mechanism has better performance compared with the extended limited perimeter vector matching (LVM) protocol and the restoration algorithm can improve the restoration success rate under multi-link faults scenario.

Securing Metering Infrastructure of Smart Grid: A Machine Learning and Localization Based Key Management Approach

Directory of Open Access Journals (Sweden)

Imtiaz Parvez

2016-08-01

Full Text Available In smart cities, advanced metering infrastructure (AMI of the smart grid facilitates automated metering, control and monitoring of power distribution by employing a wireless network. Due to this wireless nature of communication, there exist potential threats to the data privacy in AMI. Decoding the energy consumption reading, injecting false data/command signals and jamming the networks are some hazardous measures against this technology. Since a smart meter possesses limited memory and computational capability, AMI demands a light, but robust security scheme. In this paper, we propose a localization-based key management system for meter data encryption. Data are encrypted by the key associated with the coordinate of the meter and a random key index. The encryption keys are managed and distributed by a trusted third party (TTP. Localization of the meter is proposed by a method based on received signal strength (RSS using the maximum likelihood estimator (MLE. The received packets are decrypted at the control center with the key mapped with the key index and the meter’s coordinates. Additionally, we propose the k-nearest neighbors (kNN algorithm for node/meter authentication, capitalizing further on data transmission security. Finally, we evaluate the security strength of a data packet numerically for our method.

Integrated Power Flow and Short Circuit Calculation Method for Distribution Network with Inverter Based Distributed Generation

Directory of Open Access Journals (Sweden)

Shan Yang

2016-01-01

Full Text Available Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverter based distributed generation is proposed. The proposed method let the inverter based distributed generation be equivalent to Iθ bus, which makes it suitable to calculate the power flow of distribution network with a current limited inverter based distributed generation. And the low voltage ride through capability of inverter based distributed generation can be considered as well in this paper. Finally, some tests of power flow and short circuit current calculation are performed on a 33-bus distribution network. The calculated results from the proposed method in this paper are contrasted with those by the traditional method and the simulation method, whose results have verified the effectiveness of the integrated method suggested in this paper.

Distributed Group-Based Mobility Management Scheme in Wireless Body Area Networks

Directory of Open Access Journals (Sweden)

Moneeb Gohar

2017-01-01

Full Text Available For group-based mobility management in 6LoWPAN-based wireless body area networks (WBAN, some schemes using the Proxy Mobile IPv6 (PMIP have been proposed. However, the existing PMIP-based mobility schemes tend to induce large registration delay and handover delay. To overcome such limitations, we propose a new distributed group-based mobility management scheme, in which the Local Mobility Anchor (LMA function is implemented by each Mobile Access Gateway (MAG and the handover operation is performed between two neighboring MAGs without the help of LMA. Besides, each MAG maintains the information of the group of mobile sensors and aggregates the Authentication-Authorization-Accounting (AAA query messages for a group of mobile sensors as a “single” message to decrease the control overhead. By numerical analysis, it is shown that the proposed scheme can reduce the registration and handover delays, compared to the existing PMIP-based mobility schemes.

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).

A cyclic distributed garbage collector for network objects

OpenAIRE

Rodrigues, Helena; Jones, Richard

1996-01-01

This paper presents an algorithm for distributed garbage collection and outlines its implementation within the Network Objects system. The algorithm is based on a reference listing scheme, which is augmented by partial tracing in order to collect distributed garbage cycles. Processes may be dynamically organised into groups, according to appropriate heuristics, to reclaim distributed garbage cycles. The algorithm places no overhead on local collectors and suspends local mutators only briefly....

Path Searching Based Fault Automated Recovery Scheme for Distribution Grid with DG

Science.gov (United States)

Xia, Lin; Qun, Wang; Hui, Xue; Simeng, Zhu

2016-12-01

Applying the method of path searching based on distribution network topology in setting software has a good effect, and the path searching method containing DG power source is also applicable to the automatic generation and division of planned islands after the fault. This paper applies path searching algorithm in the automatic division of planned islands after faults: starting from the switch of fault isolation, ending in each power source, and according to the line load that the searching path traverses and the load integrated by important optimized searching path, forming optimized division scheme of planned islands that uses each DG as power source and is balanced to local important load. Finally, COBASE software and distribution network automation software applied are used to illustrate the effectiveness of the realization of such automatic restoration program.

Correlation between local hemodynamics and lesion distribution in a novel aortic regurgitation murine model of atherosclerosis.

Science.gov (United States)

Hoi, Yiemeng; Zhou, Yu-Qing; Zhang, Xiaoli; Henkelman, R Mark; Steinman, David A

2011-05-01

Following surgical induction of aortic valve regurgitation (AR), extensive atherosclerotic plaque development along the descending thoracic and abdominal aorta of Ldlr⁻/⁻ mice has been reported, with distinct spatial distributions suggestive of a strong local hemodynamic influence. The objective of this study was to test, using image-based computational fluid dynamics (CFD), whether this is indeed the case. The lumen geometry was reconstructed from micro-CT scanning of a control Ldlr⁻/⁻ mouse, and CFD simulations were carried out for both AR and control flow conditions derived from Doppler ultrasound measurements and literature data. Maps of time-averaged wall shear stress magnitude (TAWSS), oscillatory shear index (OSI) and relative residence time (RRT) were compared against the spatial distributions of plaque stained with oil red O, previously acquired in a group of AR and control mice. Maps of OSI and RRT were found to be consistent with plaque distributions in the AR mice and the absence of plaque in the control mice. TAWSS was uniformly lower under control vs. AR flow conditions, suggesting that levels (> 100 dyn/cm²) exceeded those required to alone induce a pro-atherogenic response. Simulations of a straightened CFD model confirmed the importance of anatomical curvature for explaining the spatial distribution of lesions in the AR mice. In summary, oscillatory and retrograde flow induced in the AR mice, without concomitant low shear, may exacerbate or accelerate lesion formation, but the distinct anatomical curvature of the mouse aorta is responsible for the spatial distribution of lesions.

Spectral narrowing and spin echo for localized carriers with heavy-tailed L evy distribution of hopping times

Energy Technology Data Exchange (ETDEWEB)

Yue, Z. [Univ. of Utah, Salt Lake City, UT (United States); Mkhitaryan, Vagharsh [Ames Lab. and Iowa State Univ., Ames, IA (United States); Raikh, M. E. [Univ. of Utah, Salt Lake City, UT (United States)

2016-02-02

We study analytically the free induction decay and the spin echo decay originating from the localized carriers moving between the sites which host random magnetic fields. Due to disorder in the site positions and energies, the on-site residence times, , are widely spread according to the L evy distribution. The power-law tail ∝ τ^-1-∝ in the distribution of does not affect the conventional spectral narrowing for α > 2, but leads to a dramatic acceleration of the free induction decay in the domain 2 > α > 1. The next abrupt acceleration of the decay takes place as becomes smaller than 1. In the latter domain the decay does not follow a simple-exponent law. To capture the behavior of the average spin in this domain, we solve the evolution equation for the average spin using the approach different from the conventional approach based on the Laplace transform. Unlike the free induction decay, the tail in the distribution of the residence times leads to the slow decay of the spin echo. The echo is dominated by realizations of the carrier motion for which the number of sites, visited by the carrier, is minimal.

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

KAUST Repository

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

2015-01-01

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

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

KAUST Repository

Pan, Bing

2015-02-12

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

Distribution state estimation based voltage control for distribution networks; Koordinierte Spannungsregelung anhand einer Zustandsschaetzung im Verteilnetz

Energy Technology Data Exchange (ETDEWEB)

Diwold, Konrad; Yan, Wei [Fraunhofer IWES, Kassel (Germany); Braun, Martin [Fraunhofer IWES, Kassel (Germany); Stuttgart Univ. (Germany). Inst. fuer Energieuebertragung und Hochspannungstechnik (IEH)

2012-07-01

The increased integration of distributed energy units creates challenges for the operators of distribution systems. This is due to the fact that distribution systems that were initially designed for distributed consumption and central generation now face decentralized feed-in. One imminent problem associated with decentralised fee-in are local voltage violations in the distribution system, which are hard to handle via conventional voltage control strategies. This article proposes a new voltage control framework for distribution system operation. The framework utilizes reactive power of distributed energy units as well on-load tap changers to mitigate voltage problems in the network. Using an optimization-band the control strategy can be used in situations where network information is derived from distribution state estimators and thus holds some error. The control capabilities in combination with a distribution state estimator are tested using data from a real rural distribution network. The results are very promising, as voltage control is achieved fast and accurate, preventing a majority of the voltage violations during system operation under realistic system conditions. (orig.)

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.

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Functional brain networks develop from a "local to distributed" organization.

Directory of Open Access Journals (Sweden)

Damien A Fair

2009-05-01

Full Text Available The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI, graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength between regions close in anatomical space and 'integration' (an increased correlation strength between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults

Functional brain networks develop from a "local to distributed" organization.

Science.gov (United States)

Fair, Damien A; Cohen, Alexander L; Power, Jonathan D; Dosenbach, Nico U F; Church, Jessica A; Miezin, Francis M; Schlaggar, Bradley L; Petersen, Steven E

2009-05-01

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength) between regions close in anatomical space and 'integration' (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have

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

Study on distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database

Science.gov (United States)

WANG, Qingrong; ZHU, Changfeng

2017-06-01

Integration of distributed heterogeneous data sources is the key issues under the big data applications. In this paper the strategy of variable precision is introduced to the concept lattice, and the one-to-one mapping mode of variable precision concept lattice and ontology concept lattice is constructed to produce the local ontology by constructing the variable precision concept lattice for each subsystem, and the distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database is proposed to draw support from the special relationship between concept lattice and ontology construction. Finally, based on the standard of main concept lattice of the existing heterogeneous database generated, a case study has been carried out in order to testify the feasibility and validity of this algorithm, and the differences between the main concept lattice and the standard concept lattice are compared. Analysis results show that this algorithm above-mentioned can automatically process the construction process of distributed concept lattice under the heterogeneous data sources.

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

Science.gov (United States)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

2011-01-01

Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

Quantitative method to determine the regional drinking water odorant regulation goals based on odor sensitivity distribution: illustrated using 2-MIB.

Science.gov (United States)

Yu, Jianwei; An, Wei; Cao, Nan; Yang, Min; Gu, Junong; Zhang, Dong; Lu, Ning

2014-07-01

Taste and odor (T/O) in drinking water often cause consumer complaints and are thus regulated in many countries. However, people in different regions may exhibit different sensitivities toward T/O. This study proposed a method to determine the regional drinking water odorant regulation goals (ORGs) based on the odor sensitivity distribution of the local population. The distribution of odor sensitivity to 2-methylisoborneol (2-MIB) by the local population in Beijing, China was revealed by using a normal distribution function/model to describe the odor complaint response to a 2-MIB episode in 2005, and a 2-MIB concentration of 12.9 ng/L and FPA (flavor profile analysis) intensity of 2.5 was found to be the critical point to cause odor complaints. Thus the Beijing ORG for 2-MIB was determined to be 12.9 ng/L. Based on the assumption that the local FPA panel can represent the local population in terms of sensitivity to odor, and that the critical FPA intensity causing odor complaints was 2.5, this study tried to determine the ORGs for seven other cities of China by performing FPA tests using an FPA panel from the corresponding city. ORG values between 12.9 and 31.6 ng/L were determined, showing that a unified ORG may not be suitable for drinking water odor regulations. This study presents a novel approach for setting drinking water odor regulations. Copyright © 2014. Published by Elsevier B.V.

Community financing of local ivermectin distribution in Nigeria: potential payment and cost-recovery outlook.

Science.gov (United States)

Onwujekwe, O E; Shu, E N; Okonkwo, P O

2000-04-01

The preferred payment mechanism in a community financing scheme for local ivermectin distribution was elicited from randomly selected household heads from three communities in Nigeria using interviewer-administered structured questionnaires. The majority of the respondents in the three communities were prepared to pay for local ivermectin distribution. Additionally, the average amounts the respondents were prepared to pay per person treated ($0.28, $0.30 and $0.38 in Nike, Achi and Toro, respectively) were all more than the $0.20 ceiling recommended by the partners of the African Programme on Onchocerciasis Control (APOC). Thus, the cost-recovery outlook is bright in these communities. However, the preferred payment modality varied. Fee-for-service was the predominant payment modality in the Achi and Nike communities, while the Toro community preferred pre-payment. This study demonstrates that many communities have different payment preferences for endemic disease control efforts. This knowledge will help in developing acceptable and sustainable schemes. The imposition of unacceptable payment mechanisms will lead to an unwillingness to pay.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.

Science.gov (United States)

Mao, Keming; Deng, Zhuofu

2016-01-01

This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

Directory of Open Access Journals (Sweden)

Keming Mao

2016-01-01

Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

Distributed SLAM Using Improved Particle Filter for Mobile Robot Localization

Directory of Open Access Journals (Sweden)

Fujun Pei

2014-01-01

Full Text Available The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle filter use in distributed SLAM was improved in two aspects. First, we improved the important function of the local filters in particle filter. The adaptive values were used to replace a set of constants in the computational process of importance function, which improved the robustness of the particle filter. Second, an information fusion method was proposed by mixing the innovation method and the number of effective particles method, which combined the advantages of these two methods. And this paper extends the previously known convergence results for particle filter to prove that improved particle filter converges to the optimal filter in mean square as the number of particles goes to infinity. The experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system to have a better tolerance and robustness.

Functionalized multi-walled carbon nanotube based sensors for distributed methane leak detection

Science.gov (United States)

This paper presents a highly sensitive, energy efficient and low-cost distributed methane (CH4) sensor system (DMSS) for continuous monitoring, detection and localization of CH4 leaks in natural gas infrastructure such as transmission and distribution pipelines, wells, and produc...

Density-functional theory based on the electron distribution on the energy coordinate

Science.gov (United States)

Takahashi, Hideaki

2018-03-01

We developed an electronic density functional theory utilizing a novel electron distribution n(ɛ) as a basic variable to compute ground state energy of a system. n(ɛ) is obtained by projecting the electron density n({\\boldsymbol{r}}) defined on the space coordinate {\\boldsymbol{r}} onto the energy coordinate ɛ specified with the external potential {\\upsilon }ext}({\\boldsymbol{r}}) of interest. It was demonstrated that the Kohn-Sham equation can also be formulated with the exchange-correlation functional E xc[n(ɛ)] that employs the density n(ɛ) as an argument. It turned out an exchange functional proposed in our preliminary development suffices to describe properly the potential energies of several types of chemical bonds with comparable accuracies to the corresponding functional based on local density approximation. As a remarkable feature of the distribution n(ɛ) it inherently involves the spatially non-local information of the exchange hole at the bond dissociation limit in contrast to conventional approximate functionals. By taking advantage of this property we also developed a prototype of the static correlation functional E sc including no empirical parameters, which showed marked improvements in describing the dissociations of covalent bonds in {{{H}}}2,{{{C}}}2{{{H}}}4 and {CH}}4 molecules.

PERSPECTIVE TRANSPORT-POWER SYSTEM BASED ON THE INTEGRATION OF MAGLEV-TECHNOLOGY AND DISTRIBUTED PHOTO-ELECTRIC STATION

Directory of Open Access Journals (Sweden)

V. O. Dzenzerskiy

2018-02-01

Full Text Available Purpose. The research main purpose is the perfection of magnetolevitating technology on electrodynamic suspension and providing its functioning on the base of ecologically rational energy systems. It means creation of the MAGLEV transport-power system which uses renewable energy sources (in particular, photoelectric converters and is connected to national/local networks as an energy user and producer simultaneously. Methodology. Conducted research, analysis and summary conclusions are based both on the results of works on the given subject, and own works of authors. The methods of systems analysis and computer design of components of the large cyber-physical transport-power system were used during research conducting. Findings. The physical-technical foundations of conception of the perspective transport-power system, which includes high-speed ground vehicle on electrodynamic suspension and distributed photo-electric energy complex are developed. The adapt to the performance of the given transport type and guaranteeing its safe functioning in any weather terms. Originality. For the first time authors substantiated the possibility for creation of single transport complex uniting the speed magnetolevitating system and distributed power supply system on the base of sun energy. It is simultaneously the inalienable part of the precision fast-acting control system, working in the real-time mode. Practical value. The offered scientific-technical solution allows on the base of renewable energy source to solve the problems of power supply and a high-speed transport control. Due to the inclusion of the distributed power supply system into local intellectual networks on the SMART-grid technology it gives the possibility to optimize energy consumption of territories neighboring to high-speed way.

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.

Constraining particle dark matter using local galaxy distribution

International Nuclear Information System (INIS)

Ando, Shin’ichiro; Ishiwata, Koji

2016-01-01

It has been long discussed that cosmic rays may contain signals of dark matter. In the last couple of years an anomaly of cosmic-ray positrons has drawn a lot of attentions, and recently an excess in cosmic-ray anti-proton has been reported by AMS-02 collaboration. Both excesses may indicate towards decaying or annihilating dark matter with a mass of around 1–10 TeV. In this article we study the gamma rays from dark matter and constraints from cross correlations with distribution of galaxies, particularly in a local volume. We find that gamma rays due to inverse-Compton process have large intensity, and hence they give stringent constraints on dark matter scenarios in the TeV scale mass regime. Taking the recent developments in modeling astrophysical gamma-ray sources as well as comprehensive possibilities of the final state products of dark matter decay or annihilation into account, we show that the parameter regions of decaying dark matter that are suggested to explain the excesses are excluded. We also discuss the constrains on annihilating scenarios.

THE STRESS STATE OF THE RADIALLY INHOMOGENEOUS HEMISPHERICAL SHELL UNDER LOCALLY DISTRIBUTED VERTICAL LOAD

Directory of Open Access Journals (Sweden)

Andreev Vladimir Igorevich

2018-01-01

Full Text Available Subject: one of the promising trends in the development of structural mechanics is the development of methods for solving problems in the theory of elasticity for bodies with continuous inhomogeneity of any deformation characteristics: these methods make it possible to use the strength of the material most fully. In this paper, we consider the two-dimensional problem for the case when a vertical, locally distributed load acts on the hemisphere and the inhomogeneity is caused by the influence of the temperature field. Research objectives: derive governing system of equations in spherical coordinates for determination of the stress state of the radially inhomogeneous hemispherical shell under locally distributed vertical load. Materials and methods: as a mechanical model, we chose a thick-walled reinforced concrete shell (hemisphere with inner and outer radii a and b, respectively, b > a. The shell’s parameters are a = 3.3 m, b = 4.5 m, Poisson’s ratio ν = 0.16; the load parameters are f = 10MPa - vertical localized load distributed over the outer face, θ0 = 30°, temperature on the internal surface of the shell Ta = 500 °C, temperature on the external surface of the shell Tb = 0 °C. The resulting boundary-value problem (a system of differential equations with variable coefficients is solved using the Maple software package. Results: maximal compressive stresses σr with allowance for material inhomogeneity are reduced by 10 % compared with the case when the inhomogeneity is ignored. But it is not so important compared with a 3-fold decrease in the tensile stress σθ on the inner surface and a 2-fold reduction in the tensile stress σθ on the outer surface of the hemisphere as concretes generally have a tensile strength substantially smaller than the compressive strength. Conclusions: the method presented in this article makes it possible to reduce the deformation characteristics of the material, i.e. it leads to a reduction in stresses

Evolution of the distribution of baryons in a simulated Local Group Universe

Science.gov (United States)

Peirani, S.

2012-12-01

Using hydrodynamical zoom simulations in the standard ΛCDM cosmology, we have investigated the evolution of the distribution of baryons (gas and stars) in a local group-type universe. We found that physical mechanisms able to drive the gas out of the virial radius at high redshifts (such as AGN) will have a stronger impact on the deficit of baryons in the mass budget of Milky Way type-galaxies at present times than those that expel the gas in the longer, late phases of galaxy formation.

Interpreting dark matter direct detection independently of the local velocity and density distribution

International Nuclear Information System (INIS)

Fox, Patrick J.; Kribs, Graham D.; Tait, Tim M. P.

2011-01-01

We demonstrate precisely what particle physics information can be extracted from a single direct detection observation of dark matter while making absolutely no assumptions about the local velocity distribution and local density of dark matter. Our central conclusions follow from a very simple observation: the velocity distribution of dark matter is positive definite, f(v)≥0. We demonstrate the utility of this result in several ways. First, we show a falling deconvoluted recoil spectrum (deconvoluted of the nuclear form factor), such as from ordinary elastic scattering, can be 'mocked up' by any mass of dark matter above a kinematic minimum. As an example, we show that dark matter much heavier than previously considered can explain the CoGeNT excess. Specifically, m χ Ge can be in just as good agreement as light dark matter, while m χ >m Ge depends on understanding the sensitivity of xenon to dark matter at very low recoil energies, E R < or approx. 6 keVnr. Second, we show that any rise in the deconvoluted recoil spectrum represents distinct particle physics information that cannot be faked by an arbitrary f(v). As examples of resulting nontrivial particle physics, we show that inelastic dark matter and dark matter with a form factor can both yield such a rise.

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...

Active damage localization for plate-like structures using wireless sensors and a distributed algorithm

International Nuclear Information System (INIS)

Liu, L; Yuan, F G

2008-01-01

Wireless structural health monitoring (SHM) systems have emerged as a promising technology for robust and cost-effective structural monitoring. However, the applications of wireless sensors on active diagnosis for structural health monitoring (SHM) have not been extensively investigated. Due to limited energy sources, battery-powered wireless sensors can only perform limited functions and are expected to operate at a low duty cycle. Conventional designs are not suitable for sensing high frequency signals, e.g. in the ultrasonic frequency range. More importantly, algorithms to detect structural damage with a vast amount of data usually require considerable processing and communication time and result in unaffordable power consumption for wireless sensors. In this study, an energy-efficient wireless sensor for supporting high frequency signals and a distributed damage localization algorithm for plate-like structures are proposed, discussed and validated to supplement recent advances made for active sensing-based SHM. First, the power consumption of a wireless sensor is discussed and identified. Then the design of a wireless sensor for active diagnosis using piezoelectric sensors is introduced. The newly developed wireless sensor utilizes an optimized combination of field programmable gate array (FPGA) and conventional microcontroller to address the tradeoff between power consumption and speed requirement. The proposed damage localization algorithm, based on an energy decay model, enables wireless sensors to be practically used in active diagnosis. The power consumption for data communication can be minimized while the power budget for data processing can still be affordable for a battery-powered wireless sensor. The Levenberg–Marquardt method is employed in a mains-powered sensor node or PC to locate damage. Experimental results and discussion on the improvement of power efficiency are given

Distributed multi-agent based coordinated power management and control strategy for microgrids with distributed energy resources

International Nuclear Information System (INIS)

Rahman, M.S.; Oo, A.M.T.

2017-01-01

Highlights: • Agent-based energy management and control scheme is designed for power sharing. • Distributed agent communication topology is formed by the graph theory. • Proposed scheme is capable of dynamically adapt to the change in system conditions. • Multi-agent coordination is achieved through information exchange. • Proposed power sharing strategy ensures the reliability of energy supply. - Abstract: In this paper, a distributed peer-to-peer multi-agent framework is proposed for managing the power sharing in microgrids with power electronic inverter-interfaced distributed energy resources (DERs). Recently, the introduction of electric vehicles (EVs) has gained much popularity by offering vehicle-to-home (V2H) technologies to support the sustainable operation of microgrids. Since microgrids often exhibit volatile characteristics due to natural intermittency and uncertainty, it is necessary to maintain the balancing of generation and demand through the proper management of power sharing. Therefore, the main purpose of this paper is to design an agent-based control framework to ensure the coordinated power management within the microgrids through effective utilization of EVs. The required agent communication framework is adhered to the graph theory where the control agents interact with each other using local as well as neighboring information and their distributed coordination effectively steers the proportional sharing of real and reactive powers among the inverter-interfaced EVs to maintain the stability of microgrids. The well known Ziegler-Nichols method is used to tune the proportional-integral (PI) controller of the inner current control loop within each individual control agent to perform necessary shared control tasks. A microgrid with solar photovoltaic (PV) and V2H systems is chosen to illustrate the results and it is seen that the proposed scheme improves the system performance in a smarter way through information exchange. Furthermore

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.

Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.

Science.gov (United States)

Qiu, Huaxin; Duan, Haibin

2017-11-01

Unmanned aerial vehicle (UAV) flocking control is a serious and challenging problem due to local interactions and changing environments. In this paper, a pigeon flocking model and a pigeon coordinated obstacle-avoiding model are proposed based on a behavior that pigeon flocks will switch between hierarchical and egalitarian interaction mode at different flight phases. Owning to the similarity between bird flocks and UAV swarms in essence, a distributed flocking control algorithm based on the proposed pigeon flocking and coordinated obstacle-avoiding models is designed to coordinate a heterogeneous UAV swarm to fly though obstacle environments with few informed individuals. The comparative simulation results are elaborated to show the feasibility, validity and superiority of our proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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....

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.

Local sensor based on nanowire field effect transistor from inhomogeneously doped silicon on insulator

Science.gov (United States)

Presnov, Denis E.; Bozhev, Ivan V.; Miakonkikh, Andrew V.; Simakin, Sergey G.; Trifonov, Artem S.; Krupenin, Vladimir A.

2018-02-01

We present the original method for fabricating a sensitive field/charge sensor based on field effect transistor (FET) with a nanowire channel that uses CMOS-compatible processes only. A FET with a kink-like silicon nanowire channel was fabricated from the inhomogeneously doped silicon on insulator wafer very close (˜100 nm) to the extremely sharp corner of a silicon chip forming local probe. The single e-beam lithographic process with a shadow deposition technique, followed by separate two reactive ion etching processes, was used to define the narrow semiconductor nanowire channel. The sensors charge sensitivity was evaluated to be in the range of 0.1-0.2 e /√{Hz } from the analysis of their transport and noise characteristics. The proposed method provides a good opportunity for the relatively simple manufacture of a local field sensor for measuring the electrical field distribution, potential profiles, and charge dynamics for a wide range of mesoscopic objects. Diagnostic systems and devices based on such sensors can be used in various fields of physics, chemistry, material science, biology, electronics, medicine, etc.

Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data.

Science.gov (United States)

Detwiler, Landon T; Suciu, Dan; Franklin, Joshua D; Moore, Eider B; Poliakov, Andrew V; Lee, Eunjung S; Corina, David P; Ojemann, George A; Brinkley, James F

2009-01-01

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too "heavyweight" for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a "lightweight" distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts.

Distributed XQuery-based integration and visualization of multimodality brain mapping data

Directory of Open Access Journals (Sweden)

Landon T Detwiler

2009-01-01

Full Text Available This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts.

Local-Field Distribution of Two Dielectric Inclusions at Small Separation

Science.gov (United States)

Siu, Yuet-Lun; Yu, Kin-Wah

2001-03-01

When two dielectric inclusions approach to each other in a composite medium, significant mutual polarization effects must occur. These effects are multipolar in nature and are difficult to treat from first principles(J. D. Jackson, Classical Electrodynamics), 2nd edition, (Wiley, New York, 1975).. In this work, we employ the discrete-dipole theory(B. T. Draine and P. J. Flatau, J. Opt. Soc. Am. A 11) 1491 (1994). to account for the mutual polarization effects by dividing the inclusions into many small subparts. We begin the calculation at small inclusion sizes and large separation, where the point-dipole limit being valid, and proceed to larger inclusion sizes and small separation, for which the mutual polarization effect becomes important. Then, we apply the theory to determine the dipole moment of each subpart self-consistently. In this way, each dipole moment yields the local electric field, which in turn polarizes the neighboring dipoles. We also begin the calculation at small inclusion sizes and large separation, where the point-dipole limit being valid, and proceed to larger inclusion sizes and small separation. Our resluts indicate that convergence is achieved with moderate computational effects. The results produce valuable information about the local electric field distribution, which is relevant to optical absorption due to surface phonon-polaritons of ionic microcrystals.

Fractal-based exponential distribution of urban density and self-affine fractal forms of cities

International Nuclear Information System (INIS)

Chen Yanguang; Feng Jian

2012-01-01

Highlights: ► The model of urban population density differs from the common exponential function. ► Fractal landscape influences the exponential distribution of urban density. ► The exponential distribution of urban population suggests a self-affine fractal. ► Urban space can be divided into three layers with scaling and non-scaling regions. ► The dimension of urban form with characteristic scale can be treated as 2. - Abstract: Urban population density always follows the exponential distribution and can be described with Clark’s model. Because of this, the spatial distribution of urban population used to be regarded as non-fractal pattern. However, Clark’s model differs from the exponential function in mathematics because that urban population is distributed on the fractal support of landform and land-use form. By using mathematical transform and empirical evidence, we argue that there are self-affine scaling relations and local power laws behind the exponential distribution of urban density. The scale parameter of Clark’s model indicating the characteristic radius of cities is not a real constant, but depends on the urban field we defined. So the exponential model suggests local fractal structure with two kinds of fractal parameters. The parameters can be used to characterize urban space filling, spatial correlation, self-affine properties, and self-organized evolution. The case study of the city of Hangzhou, China, is employed to verify the theoretical inference. Based on the empirical analysis, a three-ring model of cities is presented and a city is conceptually divided into three layers from core to periphery. The scaling region and non-scaling region appear alternately in the city. This model may be helpful for future urban studies and city planning.

Locally distributed ground deformation in an area of potential phreatic eruption, Midagahara volcano, Japan, detected by single-look-based InSAR time series analysis

Science.gov (United States)

Kobayashi, Tomokazu

2018-05-01

Although it is difficult to monitor the spatial extent and temporal evolution of local and small-magnitude ground inflation, this information is vital to assess the potential for phreatic eruption. Herein, we demonstrate the detection of locally distributed ground deformation preceding the enhancement of geothermal activity in the Midagahara volcano, Japan, through the application of single-look-based interferometric synthetic aperture radar analysis. In the Jigoku-dani geothermal area, the ground deformation proceeded at a low speed of 4 cm/year at most with a spatial extent of 500 m in the east-west direction and 250 m in the north-south direction. The deformation can be recognized to progress from 2007, at the latest, to 2010, after which the geothermal activity increased, with the collapse of sulfur towers and the appearance of active fumaroles and boiling water on the ground surface. The most deformed area corresponds to the geothermal area with the highest activity observed on the ground surface. Assuming a sill opening model, the deformation source is estimated to be located at a depth of 50 m from the surface with a speed of 7 cm/year at most, which is consistent with the depth of the highly conductive medium inferred from magnetotelluric analyses. This may suggest that volcanic fluid and/or heat was injected into the fluid-rich medium from depth and caused the ground inflation. Our results demonstrate that high-spatial-resolution deformation data can be an effective tool to monitor subsurface pressure conditions with pinpoint spatial accuracy during the build-up to phreatic eruptions.

Hotspot detection using image pattern recognition based on higher-order local auto-correlation

Science.gov (United States)

Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

2011-04-01

Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

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

Science.gov (United States)

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

2017-12-20

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

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

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Burini, Nino; Korhonen, Jari

2013-01-01

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

Detection prospects for high energy neutrino sources from the anisotropic matter distribution in the local Universe

Energy Technology Data Exchange (ETDEWEB)

Mertsch, Philipp; Rameez, Mohamed; Tamborra, Irene, E-mail: mertsch@nbi.ku.dk, E-mail: mohamed.rameez@nbi.ku.dk, E-mail: tamborra@nbi.ku.dk [Niels Bohr International Academy, Niels Bohr Institute, Blegdamsvej 17, 2100 Copenhagen (Denmark)

2017-03-01

Constraints on the number and luminosity of the sources of the cosmic neutrinos detected by IceCube have been set by targeted searches for point sources. We set complementary constraints by using the 2MASS Redshift Survey (2MRS) catalogue, which maps the matter distribution of the local Universe. Assuming that the distribution of the neutrino sources follows that of matter, we look for correlations between ''warm'' spots on the IceCube skymap and the 2MRS matter distribution. Through Monte Carlo simulations of the expected number of neutrino multiplets and careful modelling of the detector performance (including that of IceCube-Gen2), we demonstrate that sources with local density exceeding 10{sup −6} Mpc{sup −3} and neutrino luminosity L {sub ν} ∼< 10{sup 42} erg s{sup −1} (10{sup 41} erg s{sup −1}) will be efficiently revealed by our method using IceCube (IceCube-Gen2). At low luminosities such as will be probed by IceCube-Gen2, the sensitivity of this analysis is superior to requiring statistically significant direct observation of a point source.

Sensor distributions for structural monitoring

DEFF Research Database (Denmark)

Ulriksen, Martin Dalgaard; Bernal, Dionisio

2017-01-01

Deciding on the spatial distribution of output sensors for vibration-based structural health monitoring (SHM) is a task that has been, and still is, studied extensively. Yet, when referring to the conventional damage characterization hierarchy, composed of detection, localization, and quantificat......Deciding on the spatial distribution of output sensors for vibration-based structural health monitoring (SHM) is a task that has been, and still is, studied extensively. Yet, when referring to the conventional damage characterization hierarchy, composed of detection, localization......, and quantification, it is primarily the first component that has been addressed with regard to optimal sensor placement. In this particular context, a common approach is to distribute sensors, of which the amount is determined a priori, such that some scalar function of the probability of detection for a pre......-defined set of damage patterns is maximized. Obviously, the optimal sensor distribution, in terms of damage detection, is algorithm-dependent, but studies have showed how correlation generally exists between the different strategies. However, it still remains a question how this “optimality” correlates...

Design and Irnplernentation of Distributed Relational DBMS

OpenAIRE

都司, 達夫; 丸山, 正理; 大木下, 俊也; 冨士, 竹仁; 田中, 仁士; 上坂, 利文; 加藤, 昌央; 木本, 茂; 林, 利治; 渡辺, 勝正; TSUJI, Tatsuo; MARUYAMA, Masari; OGINOSIDTA, Toshiya; FUJI, Takehito; TANAKA, Hitoshi

1992-01-01

This paper describes a distributed relational database management system with emphasis on design and implementation. We have designed and constructed the system on the UNIX local area network in our university. It is based upon the SQL standard, and distributed processings are implemented using RPC (Remote Procedure Calls). The main features of出esystem include: (1) Multi -client and multi -server system, (2) Client-based distribution management, (3) Deadlock free concurrency control scheme, (...

[Assessment of ecosystem in giant panda distribution area based on entropy method and coefficient of variation].

Science.gov (United States)

Yan, Zhi Gang; Li, Jun Qing

2017-12-01

The areas of the habitat and bamboo forest, and the size of the giant panda wild population have greatly increased, while habitat fragmentation and local population isolation have also intensified in recent years. Accurate evaluation of ecosystem status of the panda in the giant panda distribution area is important for giant panda conservation. The ecosystems of the distribution area and six mountain ranges were subdivided into habitat and population subsystems based on the hie-rarchical system theory. Using the panda distribution area as the study area and the three national surveys as the time node, the evolution laws of ecosystems were studied using the entropy method, coefficient of variation, and correlation analysis. We found that with continuous improvement, some differences existed in the evolution and present situation of the ecosystems of six mountain ranges could be divided into three groups. Ecosystems classified into the same group showed many commonalities, and difference between the groups was considerable. Problems of habitat fragmentation and local population isolation became more serious, resulting in ecosystem degradation. Individuali-zed ecological protection measures should be formulated and implemented in accordance with the conditions in each mountain system to achieve the best results.

Cell array-based intracellular localization screening reveals novel functional features of human chromosome 21 proteins

Directory of Open Access Journals (Sweden)

Kahlem Pascal

2006-06-01

Full Text Available Abstract Background Trisomy of human chromosome 21 (Chr21 results in Down's syndrome, a complex developmental and neurodegenerative disease. Molecular analysis of Down's syndrome, however, poses a particular challenge, because the aneuploid region of Chr21 contains many genes of unknown function. Subcellular localization of human Chr21 proteins may contribute to further understanding of the functions and regulatory mechanisms of the genes that code for these proteins. Following this idea, we used a transfected-cell array technique to perform a rapid and cost-effective analysis of the intracellular distribution of Chr 21 proteins. Results We chose 89 genes that were distributed over the majority of 21q, ranging from RBM11 (14.5 Mb to MCM3AP (46.6 Mb, with part of them expressed aberrantly in the Down's syndrome mouse model. Open reading frames of these genes were cloned into a mammalian expression vector with an amino-terminal His6 tag. All of the constructs were arrayed on glass slides and reverse transfected into HEK293T cells for protein expression. Co-localization detection using a set of organelle markers was carried out for each Chr21 protein. Here, we report the subcellular localization properties of 52 proteins. For 34 of these proteins, their localization is described for the first time. Furthermore, the alteration in cell morphology and growth as a result of protein over-expression for claudin-8 and claudin-14 genes has been characterized. Conclusion The cell array-based protein expression and detection approach is a cost-effective platform for large-scale functional analyses, including protein subcellular localization and cell phenotype screening. The results from this study reveal novel functional features of human Chr21 proteins, which should contribute to further understanding of the molecular pathology of Down's syndrome.

Multicriteria optimization of the spatial dose distribution

International Nuclear Information System (INIS)

Schlaefer, Alexander; Viulet, Tiberiu; Muacevic, Alexander; Fürweger, Christoph

2013-01-01

Purpose: Treatment planning for radiation therapy involves trade-offs with respect to different clinical goals. Typically, the dose distribution is evaluated based on few statistics and dose–volume histograms. Particularly for stereotactic treatments, the spatial dose distribution represents further criteria, e.g., when considering the gradient between subregions of volumes of interest. The authors have studied how to consider the spatial dose distribution using a multicriteria optimization approach.Methods: The authors have extended a stepwise multicriteria optimization approach to include criteria with respect to the local dose distribution. Based on a three-dimensional visualization of the dose the authors use a software tool allowing interaction with the dose distribution to map objectives with respect to its shape to a constrained optimization problem. Similarly, conflicting criteria are highlighted and the planner decides if and where to relax the shape of the dose distribution.Results: To demonstrate the potential of spatial multicriteria optimization, the tool was applied to a prostate and meningioma case. For the prostate case, local sparing of the rectal wall and shaping of a boost volume are achieved through local relaxations and while maintaining the remaining dose distribution. For the meningioma, target coverage is improved by compromising low dose conformality toward noncritical structures. A comparison of dose–volume histograms illustrates the importance of spatial information for achieving the trade-offs.Conclusions: The results show that it is possible to consider the location of conflicting criteria during treatment planning. Particularly, it is possible to conserve already achieved goals with respect to the dose distribution, to visualize potential trade-offs, and to relax constraints locally. Hence, the proposed approach facilitates a systematic exploration of the optimal shape of the dose distribution

Multiagent-based Distributed Control for Operation Cost Minimization of Droop Controlled DC Microgrid Using Incremental Cost Consensus

DEFF Research Database (Denmark)

Li, Chendan; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.

2015-01-01

In this paper, a multiagent based distributed control is proposed for DC microgrid to minimize the operation cost. The power of each distributed generator (DG) is dispatched in a distributed manner in a multiagent system by means of voltage scheduling. Every DG unit is taken as an agent......, and they share the load corresponding to the operation cost of all the units in the system with only communication with direct neighbors through incremental cost consensus. The power regulation according to the power reference generated by consensus is implemented through voltage scheduling in local primary...... controllers. Simulation verification shows that total operation cost of the DC microgrid is successfully reduced though the proposed method....

Integrated Power Flow and Short Circuit Calculation Method for Distribution Network with Inverter Based Distributed Generation

OpenAIRE

Yang, Shan; Tong, Xiangqian

2016-01-01

Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverte...

A Numerical Study of Water Loss Rate Distributions in MDCT-based Human Airway Models

Science.gov (United States)

Wu, Dan; Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Lin, Ching-Long

2015-01-01

Both three-dimensional (3D) and one-dimensional (1D) computational fluid dynamics (CFD) methods are applied to study regional water loss in three multi-detector row computed-tomography (MDCT)-based human airway models at the minute ventilations of 6, 15 and 30 L/min. The overall water losses predicted by both 3D and 1D models in the entire respiratory tract agree with available experimental measurements. However, 3D and 1D models reveal different regional water loss rate distributions due to the 3D secondary flows formed at bifurcations. The secondary flows cause local skewed temperature and humidity distributions on inspiration acting to elevate the local water loss rate; and the secondary flow at the carina tends to distribute more cold air to the lower lobes. As a result, the 3D model predicts that the water loss rate first increases with increasing airway generation, and then decreases as the air approaches saturation, while the 1D model predicts a monotonic decrease of water loss rate with increasing airway generation. Moreover, the 3D (or 1D) model predicts relatively higher water loss rates in lower (or upper) lobes. The regional water loss rate can be related to the non-dimensional wall shear stress (τ*) by the non-dimensional mass transfer coefficient (h0*) as h0* = 1.15 τ*0.272, R = 0.842. PMID:25869455

SPATIAL DISTRIBUTIONS OF ABSORPTION, LOCAL SUPPRESSION, AND EMISSIVITY REDUCTION OF SOLAR ACOUSTIC WAVES IN MAGNETIC REGIONS

International Nuclear Information System (INIS)

Chou, D.-Y.; Yang, M.-H.; Zhao Hui; Liang Zhichao; Sun, M.-T.

2009-01-01

Observed acoustic power in magnetic regions is lower than the quiet Sun because of absorption, emissivity reduction, and local suppression of solar acoustic waves in magnetic regions. In the previous studies, we have developed a method to measure the coefficients of absorption, emissivity reduction, and local suppression of sunspots. In this study, we go one step further to measure the spatial distributions of three coefficients in two active regions, NOAA 9055 and 9057. The maps of absorption, emissivity reduction, and local suppression coefficients correlate with the magnetic map, including plage regions, except the emissivity reduction coefficient of NOAA 9055 where the emissivity reduction coefficient is too weak and lost among the noise.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

Science.gov (United States)

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

KAUST Repository

Maadooliat, Mehdi; Gao, Xin; Huang, Jianhua Z.

2012-01-01

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence-structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu. edu/~madoliat/LagSVD) that can be used to produce informative animations. © The Author 2012. Published by Oxford University Press.

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

KAUST Repository

Maadooliat, Mehdi

2012-08-27

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence-structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu. edu/~madoliat/LagSVD) that can be used to produce informative animations. © The Author 2012. Published by Oxford University Press.

Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging

Directory of Open Access Journals (Sweden)

Geert Deconinck

2015-12-01

Full Text Available The charging of electric vehicles (EVs impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid (e.g., under-voltage, phase unbalances; for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with event-driven control at the operational level. Different case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.

African and local wind-blown dist contributions at three rural sites in SE Spain: the aerosol size distribution

International Nuclear Information System (INIS)

Orza, J. A. G.; Cabello, M.; Lidon, V.; Martinez, J.

2009-01-01

The entrainment of particulate material into the atmosphere by wind action on surface soils both disturbed and natural, as well as directly due to human activities like agricultural practices, mineral industry operations, construction works and traffic, is a significant contribution to the aerosol load in Mediterranean semi-arid areas. A further crustal contribution in the region comes from the frequent arrival of African mineral dust plumes. We summarize some of the results obtained after 4-6 month campaigns at three rural sites in SE Spain where the aerosol number size distribution (31 size bins between 0.25 and 32 μm) was continuously measured. The influence of both local wind speed and the arrival of air masses loaded with African dust on the airborne particulate distribution is assessed. Similarities and differences between the three locations give information that allows a better understanding of the influence of both local wind speed and African dust outbreaks (ADO), while highlight what is mostly related to local features. (Author)

Performance assessment of commercial relays for anti-islanding protection of rotating machine based distributed generation

Energy Technology Data Exchange (ETDEWEB)

Katiraei, F. [Quanta Technology, Houston, TX (United States); Abbey, C. [Natural Resources Canada, Ottawa, ON (Canada). CANMET Energy Technology Centre; Da Cunha, I. [LeapFrog Energy Technologies Inc., Mississauga, ON (Canada); Brisette, Y. [Hydro-Quebec, Montreal, PQ (Canada). Research Inst

2008-07-01

According to power industry standards, distributed generation must stop energizing the power grid upon loss of the main system. Either passive or active methods may be used to fulfill this requirement. Passive methods rely on locally measured signals to determine whether the main grid is present, while active methods inject a perturbation into the system that will manifest itself in locally measured signals if the main grid is not present. This paper compared simulation and experimental results for various commercially available relays for passive anti-islanding protection of small (below 500 kW) distributed generators using either synchronous or induction generators. A commercial multifunction relay and an application specific relay for rate-of-change-of-frequency and vector shift were modelled in simulation. Simulation results were compared with tests using a 25 kV induction generator. Results obtained for the induction machine based DG were in good agreement with trip times associated with under/overvoltage relays. The poor results with frequency based relays may be attributed to the method used for calculating frequency. Sensitivity analysis on the degree of capacitor compensation revealed a small non-detection zone, suggesting that this risk should be evaluated for induction machine based interconnections. These results showed that accurate relay modeling is challenging, particularly for frequency based techniques. Other methods for relay testing, such as hardware-in-the-loop, may be more appropriate than simulation, and are more practical in terms of cost effectiveness, than extensive field trials. 7 refs., 1 tab., 6 figs.

Accelerated Enveloping Distribution Sampling: Enabling Sampling of Multiple End States while Preserving Local Energy Minima.

Science.gov (United States)

Perthold, Jan Walther; Oostenbrink, Chris

2018-05-17

Enveloping distribution sampling (EDS) is an efficient approach to calculate multiple free-energy differences from a single molecular dynamics (MD) simulation. However, the construction of an appropriate reference-state Hamiltonian that samples all states efficiently is not straightforward. We propose a novel approach for the construction of the EDS reference-state Hamiltonian, related to a previously described procedure to smoothen energy landscapes. In contrast to previously suggested EDS approaches, our reference-state Hamiltonian preserves local energy minima of the combined end-states. Moreover, we propose an intuitive, robust and efficient parameter optimization scheme to tune EDS Hamiltonian parameters. We demonstrate the proposed method with established and novel test systems and conclude that our approach allows for the automated calculation of multiple free-energy differences from a single simulation. Accelerated EDS promises to be a robust and user-friendly method to compute free-energy differences based on solid statistical mechanics.

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)

Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (Oncorhynchus mykiss across a complex riverscape.

Directory of Open Access Journals (Sweden)

Jeffrey A Falke

Full Text Available Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (Oncorhynchus mykiss, a threatened salmonid fish, across ∼15,000 stream km in the John Day River basin, Oregon, USA. We used hurdle regression and a multi-model information theoretic approach to identify the relative importance of covariates representing key aspects of the steelhead life cycle (e.g., site access, spawning habitat quality, juvenile survival at two spatial scales: within 2-km long survey reaches (local sites and ecological neighborhoods (5 km surrounding the local sites. Based on Akaike's Information Criterion, models that included covariates describing ecological neighborhoods provided the best description of the distribution and abundance of steelhead spawning given the data. Among these covariates, our representation of offspring survival (growing-season-degree-days, °C had the strongest effect size (7x relative to other predictors. Predictive performances of model-averaged composite and neighborhood-only models were better than a site-only model based on both occurrence (percentage of sites correctly classified = 0.80±0.03 SD, 0.78±0.02 vs. 0.62±0.05, respectively and counts (root mean square error = 3.37, 3.93 vs. 5.57, respectively. The importance of both temperature and stream flow for steelhead spawning suggest this species may be highly sensitive to impacts of land and water uses, and to projected climate impacts in the region and that landscape context, complementation, and connectivity will drive how this species responds to future environments.

The Osseus platform: a prototype for advanced web-based distributed simulation

Science.gov (United States)

Franceschini, Derrick; Riecken, Mark

2016-05-01

Recent technological advances in web-based distributed computing and database technology have made possible a deeper and more transparent integration of some modeling and simulation applications. Despite these advances towards true integration of capabilities, disparate systems, architectures, and protocols will remain in the inventory for some time to come. These disparities present interoperability challenges for distributed modeling and simulation whether the application is training, experimentation, or analysis. Traditional approaches call for building gateways to bridge between disparate protocols and retaining interoperability specialists. Challenges in reconciling data models also persist. These challenges and their traditional mitigation approaches directly contribute to higher costs, schedule delays, and frustration for the end users. Osseus is a prototype software platform originally funded as a research project by the Defense Modeling & Simulation Coordination Office (DMSCO) to examine interoperability alternatives using modern, web-based technology and taking inspiration from the commercial sector. Osseus provides tools and services for nonexpert users to connect simulations, targeting the time and skillset needed to successfully connect disparate systems. The Osseus platform presents a web services interface to allow simulation applications to exchange data using modern techniques efficiently over Local or Wide Area Networks. Further, it provides Service Oriented Architecture capabilities such that finer granularity components such as individual models can contribute to simulation with minimal effort.

Place Based STEM: Leveraging Local Resources to Engage K-12 Teachers in Teaching Integrated STEM and for Addressing the Local STEM Pipeline

Energy Technology Data Exchange (ETDEWEB)

Dr. Louis Nadelson; Anne Louise Seifert; Meagan McKinney

2014-06-01

Business, industry, parks, nature settings, government infrastructure, and people, can be invaluable resources for connecting STEM curriculum within context which results in conditions ideal for promoting purposeful learning of authentic STEM content. Thus, community-based STEM resources offer ideal context for teaching STEM content. A benefit of focusing teacher attention on these contextual, content aligned resources is that they are in every community; making place-based STEM education a possibility, regardless of the location of STEM teaching and learning. Further, associating STEM teaching and learning with local resources addresses workforce development and the STEM pipeline by exposing students to STEM careers and applications in their local communities. The desire to align STEM teaching and learning with local STEM related resources guided the design of our week-long integrated STEM K-12 teacher professional development (PD) program, i-STEM. We have completed four years of our i-STEM PD program and have made place-based STEM a major emphasis of our curriculum. This report focuses on the data collected in the fourth year of our program. Our week-long i-STEM PD served over 425 educators last summer (2013), providing them with in depth theme-based integrated STEM short courses which were limited to an average of 15 participants and whole group plenary sessions focused around placed based integrated STEM, inquiry, engineering design, standards and practices of Common Core and 21st Century skills. This state wide PD was distributed in five Idaho community colleges and took place over two weeks. The STEM short courses included topics on engineering for sustainability, using engineering to spark interest in STEM, municipal water systems, health, agriculture, food safety, mining, forestry, energy, and others. Integral to these short courses were field trips designed to connect the K-12 educators to the resources in their local communities that could be leveraged

Optimal Output of Distributed Generation Based On Complex Power Increment

Science.gov (United States)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Distributed Fair Auto Rate Medium Access Control for IEEE 802.11 Based WLANs

Science.gov (United States)

Zhu, Yanfeng; Niu, Zhisheng

Much research has shown that a carefully designed auto rate medium access control can utilize the underlying physical multi-rate capability to exploit the time-variation of the channel. In this paper, we develop a simple analytical model to elucidate the rule that maximizes the throughput of RTS/CTS based multi-rate wireless local area networks. Based on the discovered rule, we propose two distributed fair auto rate medium access control schemes called FARM and FARM+ from the view-point of throughput fairness and time-share fairness, respectively. With the proposed schemes, after receiving a RTS frame, the receiver selectively returns the CTS frame to inform the transmitter the maximum feasible rate probed by the signal-to-noise ratio of the received RTS frame. The key feature of the proposed schemes is that they are capable of maintaining throughput/time-share fairness in asymmetric situation where the distribution of SNR varies with stations. Extensive simulation results show that the proposed schemes outperform the existing throughput/time-share fair auto rate schemes in time-varying channel conditions.

HERUS: the far-IR/submm spectral energy distributions of local ULIRGs and photometric atlas

Science.gov (United States)

Clements, D. L.; Pearson, C.; Farrah, D.; Greenslade, J.; Bernard-Salas, Jeronimo; González-Alfonso, E.; Afonso, J.; Efstathiou, A.; Rigopoulou, D.; Lebouteiller, V.; Hurley, P. D.; Spoon, H.

2018-04-01

We present the Herschel-SPIRE photometric atlas for a complete flux limited sample of 43 local ultraluminous infrared galaxies (ULIRGs), selected at 60 μm by IRAS, as part of the HERschel ULIRG Survey (HERUS). Photometry observations were obtained using the SPIRE instrument at 250, 350, and 500 μm. We describe these observations, present the results, and combine the new observations with data from IRAS to examine the far-infrared spectral energy distributions (SEDs) of these sources. We fit the observed SEDs of HERUS objects with a simple parametrized modified blackbody model, where temperature and emissivity β are free parameters. We compare the fitted values to those of non-ULIRG local galaxies, and find, in agreement with earlier results, that HERUS ULIRGs have warmer dust (median temperature T = 37.9 ± 4.7 K compared to 21.3 ± 3.4 K) but a similar β distribution (median β = 1.7 compared to 1.8) to the Herschel reference sample (HRS, Cortese et al. 2014) galaxies. Dust masses are found to be in the range of 107.5-109 M⊙, significantly higher than that of HRS sources. We compare our results for local ULIRGs with higher redshift samples selected at 250 and 850 μm. These latter sources generally have cooler dust and/or redder 100-to-250 μm colours than our 60 μm-selected ULIRGs. We show that this difference may in part be the result of the sources being selected at different wavelengths rather than being a simple indication of rapid evolution in the properties of the population.

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

KAUST Repository

Pan, B.

2016-03-22

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

Options for a National Framework for Benefit Distribution and Their Relation to Community-Based and National REDD+ Monitoring

Directory of Open Access Journals (Sweden)

Margaret Skutsch

2014-07-01

Full Text Available Monitoring is a central element in the implementation of national REDD+ and may be essential in providing the data needed to support benefit distribution. We discuss the options for benefit sharing systems in terms of technical feasibility and political acceptability in respect of equity considerations, and the kind of data that would be needed for the different options. We contrast output-based distribution systems, in which rewards are distributed according to performance measured in terms of carbon impacts, with input-based systems in which performance is measured in term of compliance with prescribed REDD+ activities. Output-based systems, which would require regular community carbon inventories to produce Tier 3 data locally, face various challenges particularly for the case of assessing avoided deforestation, and they may not be perceived as equitable. Input-based systems would require data on activities undertaken rather than change in stocks; this information could come from community-acquired data. We also consider how community monitored data could support national forest monitoring systems and the further development of national REDD+.

Self-Intersection Local Times of Generalized Mixed Fractional Brownian Motion as White Noise Distributions

International Nuclear Information System (INIS)

Suryawan, Herry P.; Gunarso, Boby

2017-01-01

The generalized mixed fractional Brownian motion is defined by taking linear combinations of a finite number of independent fractional Brownian motions with different Hurst parameters. It is a Gaussian process with stationary increments, posseses self-similarity property, and, in general, is neither a Markov process nor a martingale. In this paper we study the generalized mixed fractional Brownian motion within white noise analysis framework. As a main result, we prove that for any spatial dimension and for arbitrary Hurst parameter the self-intersection local times of the generalized mixed fractional Brownian motions, after a suitable renormalization, are well-defined as Hida white noise distributions. The chaos expansions of the self-intersection local times in the terms of Wick powers of white noises are also presented. (paper)

Security Assessment of Web Based Distributed Applications

Directory of Open Access Journals (Sweden)

Catalin BOJA

2010-01-01

Full Text Available This paper presents an overview about the evaluation of risks and vulnerabilities in a web based distributed application by emphasizing aspects concerning the process of security assessment with regards to the audit field. In the audit process, an important activity is dedicated to the measurement of the characteristics taken into consideration for evaluation. From this point of view, the quality of the audit process depends on the quality of assessment methods and techniques. By doing a review of the fields involved in the research process, the approach wants to reflect the main concerns that address the web based distributed applications using exploratory research techniques. The results show that many are the aspects which must carefully be worked with, across a distributed system and they can be revealed by doing a depth introspective analyze upon the information flow and internal processes that are part of the system. This paper reveals the limitations of a non-existing unified security risk assessment model that could prevent such risks and vulnerabilities debated. Based on such standardize models, secure web based distributed applications can be easily audited and many vulnerabilities which can appear due to the lack of access to information can be avoided.

A local energy management of a hybrid PV-storage based distributed generation for microgrids

International Nuclear Information System (INIS)

Choudar, Adel; Boukhetala, Djamel; Barkat, Said; Brucker, Jean-Michel

2015-01-01

Highlights: • The proposed system is based on photovoltaic system, batteries and ultra-capacitors. • Batteries are used as an energy source, ultra-capacitors are used as a fast power regulator. • An energy management strategy, to operate a grid connected active PV system (APS). • Different levels of the control system are studied and organized in a hierarchical control structure. • Different operating modes are explained (island, limited PV power, normal, fast recovering). - Abstract: The presented work focuses on energy management strategy, to operate a grid connected active PV system (APS) in a microgrid. A microgrid is a smart grid in a small scale which can be stand-alone or grid-tied. The proposed system is based on photovoltaic system, batteries and ultra-capacitors. Three converters are used to interface the elements of the APS to a common DC-link capacitor. The presented control strategy manages the power flow between the converters and the grid through the DC-link in order to maintain the grid power demand coming from the grid operator. Batteries are used as an energy source, to stabilize and permit the APS units to run at a constant and stable output power, damping peak surges in electricity demand and to store the excess of energy from the PV array. Ultra-capacitors are used as a fast power regulator to: limit the battery’s current, regulate the DC-link voltage when the disconnection mode occurs and to deliver a smooth power to the grid, despite primary source and load fluctuations. Several operating modes are presented to manage locally the power flows between the various sources, taking into account the state of charge of batteries (SOC), the energy level of ultra-capacitors (Lev), the available PV power and the power demand from the grid operator

Building flexible, distributed collaboration tools using type-based publish/subscribe - The Distributed Knight case

DEFF Research Database (Denmark)

Hansen, Klaus Marius; Damm, Christian Heide

2004-01-01

Distributed collaboration is becoming increasingly impor tant also in software development. Combined with an in creasing interest in experimental and agile approaches to software development, this poses challenges to tool sup port for software development. Specifically, tool support is needed...... for flexible, distributed collaboration. We intro duce the Distributed Knight tool that provides flexible and lightweight support for distributed collaboration in object oriented modelling. The Distributed Knight implementa tion builds crucially on the type-based publish/subscribe distributed communication...... paradigm, which provides an effective and natural abstraction for developing distributed collaboration tools....

Opportunities for Local for Local Food Production: A Case in the Dutch Fruit and Vegetables

Directory of Open Access Journals (Sweden)

Jurriaan Visser

2013-03-01

Full Text Available This paper investigates the opportunities for farmers to produce for local consumers, based on a case study in the Dutch horticulture sector. Main requirements for the set-up of a local chain of supply chain actors are investigated. Producer requirements are added value, availability of time, infrastructure and training. Retailer requirements are quality of food, purchasing volumes, food safety, communication to consumers and traceability of products. For consumers taste/freshness, sustainability, health benefits and authenticity are important attributes of local foods. Based on literature review and interviews with stakeholders four possible strategies for local food chains are defined. The ‘keep it local’ strategy means that the local food supply chains will not make use of the current infrastructure of the marketing coop that acts as chain coordinator. Deliveries are directly between farmer and retail outlet. The local products - conventional supply chain strategy implies that current (non-local supply chains are used to distribute local products. The supply chain planning will be more complex since products need to be separated per grower and distributed to several local supermarkets. In the ‘enabling producers’ strategy the marketing coop/chain coordinator is going to enable its member producers to sell their products locally. The marketing coop can support producers in for instance, billing and payments, marketing, logistics. The fourth strategy aims at strengthening current consumer communication strategies. It is argued that connecting producers and consumers, regardless of where they live is advantageous.Conclusion is that strategy 3; ‘Enabling producers’, in combination with strategy 4; ‘Strengthening current consumer communication strategies’ are the most promising options in setting up local food supply chains. Strategies 1 and 2, where the marketing coop/chain coordinator itself takes on the challenge of setting up

A numerically research on energy loss evaluation in a centrifugal pump system based on local entropy production method

Directory of Open Access Journals (Sweden)

Hou Hucan

2017-01-01

Full Text Available Inspired by wide application of the second law of thermodynamics to flow and heat transfer devices, local entropy production analysis method was creatively introduced into energy assessment system of centrifugal water pump. Based on Reynolds stress turbulent model and energy equation model, the steady numerical simulation of the whole flow passage of one IS centrifugal pump was carried out. The local entropy production terms were calculated by user defined functions, mainly including wall entropy production, turbulent entropy production, and viscous entropy production. The numerical results indicated that the irreversible energy loss calculated by the local entropy production method agreed well with that calculated by the traditional method but with some deviations which were probably caused by high rotatability and high curvature of impeller and volute. The wall entropy production and turbulent entropy production took up large part of the whole entropy production about 48.61% and 47.91%, respectively, which indicated that wall friction and turbulent fluctuation were the major factors in affecting irreversible energy loss. Meanwhile, the entropy production rate distribution was discussed and compared with turbulent kinetic energy dissipation rate distribution, it showed that turbulent entropy production rate increased sharply at the near wall regions and both distributed more uniformly. The blade region in leading edge near suction side, trailing edge and volute tongue were the main regions to generate irreversible exergy loss. This research broadens a completely new view in evaluating energy loss and further optimizes pump using entropy production minimization.

Distribution patterns of wintering sea ducks in relation to the North Atlantic Oscillation and local environmental characteristics

Science.gov (United States)

Zipkin, Elise F.; Gardner, Beth; Gilbert, Andrew T.; O'Connell, Allan F.; Royle, J. Andrew; Silverman, Emily D.

2010-01-01

Twelve species of North American sea ducks (Tribe Mergini) winter off the eastern coast of the United States and Canada. Yet, despite their seasonal proximity to urbanized areas in this region, there is limited information on patterns of wintering sea duck habitat use. It is difficult to gather information on sea ducks because of the relative inaccessibility of their offshore locations, their high degree of mobility, and their aggregated distributions. To characterize environmental conditions that affect wintering distributions, as well as their geographic ranges, we analyzed count data on five species of sea ducks (black scoters Melanitta nigra americana, surf scoters M. perspicillata, white-winged scoters M. fusca, common eiders Somateria mollissima, and long-tailed ducks Clangula hyemalis) that were collected during the Atlantic Flyway Sea Duck Survey for ten years starting in the early 1990s. We modeled count data for each species within ten-nautical-mile linear survey segments using a zero-inflated negative binomial model that included four local-scale habitat covariates (sea surface temperature, mean bottom depth, maximum bottom slope, and a variable to indicate if the segment was in a bay or not), one broad-scale covariate (the North Atlantic Oscillation), and a temporal correlation component. Our results indicate that species distributions have strong latitudinal gradients and consistency in local habitat use. The North Atlantic Oscillation was the only environmental covariate that had a significant (but variable) effect on the expected count for all five species, suggesting that broad-scale climatic conditions may be directly or indirectly important to the distributions of wintering sea ducks. Our results provide critical information on species-habitat associations, elucidate the complicated relationship between the North Atlantic Oscillation, sea surface temperature, and local sea duck abundances, and should be useful in assessing the impacts of climate

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.

Distributed Supervisory Protection Interlock System

International Nuclear Information System (INIS)

Walz, H.V.; Agostini, R.C.; Barker, L.; Cherkassky, R.; Constant, T.; Matheson, R.

1989-03-01

The Distributed Supervisory Protection Interlock System, DSPI, is under development at the Stanford Linear Accelerator Center for requirements in the areas of personnel protection, beam containment and equipment protection interlocks. The DSPI system, distributed over the application site, consists of segments with microprocessor-based controller and I/O modules, local area networks for communication, and a global supervisor computer. Segments are implemented with commercially available controller and I/O modules arranged in local interlock clusters, and associated software. Segments provide local interlock data acquisition, processing and control. Local area networks provide the communication backbone between segments and a global supervisor processor. The supervisor processor monitors the overall system, reports detail status and provides human interfaces. Details of an R and D test system, which will implement the requirements for personnel protection of 4 typical linear accelerator sectors, will be described. 4 refs., 2 figs

A distributed clinical decision support system architecture

Directory of Open Access Journals (Sweden)

Shaker H. El-Sappagh

2014-01-01

Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.

Effect of LED-LCU light irradiance distribution on mechanical properties of resin based materials

International Nuclear Information System (INIS)

Magalhães Filho, T.R.; Weig, K.M.; Costa, M.F.; Werneck, M.M.; Barthem, R.B.; Costa Neto, C.A.

2016-01-01

The objective of this study is to analyze the light power distribution along the tip end of the light guide of three LED-LCUs (Light Curing Units) and to evaluate its effect on the mechanical properties of a polymer based dental composite. Firstly, the light power distribution over the whole area of LED-LCU light guide surface was analyzed by three methods: visual projection observation, spectral measurement and optical spectral analysis (OSA). The light power distribution and the total irradiance were different for the three LEDs used, but the wavelength was within the camphorquinone absorption spectrum. The use of a blank sheet was quite on hand to make a qualitative analysis of a beam, and it is costless. Secondly, specimens of a hybrid composite with approximately 8 mm diameter and 2 mm thickness were produced and polymerized by 20 s exposition time to each LED-LCU. Thirdly, the elastic modulus (E) and hardness (HV) were measured throughout the irradiated area by instrumented micro-indentation test (IIT), allowing to correlate localized power and mechanical properties. Both E and HV showed to be very sensitive to local power and wavelength dependent, but they followed the beam power profile. It was also shown that the mechanical properties could be directly correlated to the curing process. Very steep differences in mechanical properties over very short distances may impair the material performance, since residual stresses can easily be built over it. - Highlights: • A resin based composite (RBC) was polymerized by three different Light Emitting Diodes. • Each LED had its beam profile visually, wavelength and power analyzed. • The effective polymerization power (EPP) varied from 28% to 52% of the total beam power. • Wavelength seems to be as relevant as power in the light curing process. • Mechanical properties depend on the simultaneous effect of wavelength and power.

Effect of LED-LCU light irradiance distribution on mechanical properties of resin based materials

Energy Technology Data Exchange (ETDEWEB)

Magalhães Filho, T.R.; Weig, K.M. [Faculdade de Odontologia, Universidade Federal Fluminense, Rua São Paulo 28, CEP 24020-150 Niterói (Brazil); Engenharia Metalúrgica e de Materiais (COPPE), Universidade Federal do Rio de Janeiro, CP 68505, CEP: 21941-972 Rio de Janeiro (Brazil); Costa, M.F. [Engenharia Metalúrgica e de Materiais (COPPE), Universidade Federal do Rio de Janeiro, CP 68505, CEP: 21941-972 Rio de Janeiro (Brazil); Werneck, M.M. [Engenharia Elétrica (COPPE), Universidade Federal do Rio de Janeiro, CP 68504, CEP: 21941-972 Rio de Janeiro (Brazil); Barthem, R.B. [Instituto de Física, Universidade Federal do Rio de Janeiro, CP 68528, CEP: 21941-972 Rio de Janeiro (Brazil); Costa Neto, C.A., E-mail: celio@metalmat.ufrj.br [Engenharia Metalúrgica e de Materiais (COPPE), Universidade Federal do Rio de Janeiro, CP 68505, CEP: 21941-972 Rio de Janeiro (Brazil)

2016-06-01

The objective of this study is to analyze the light power distribution along the tip end of the light guide of three LED-LCUs (Light Curing Units) and to evaluate its effect on the mechanical properties of a polymer based dental composite. Firstly, the light power distribution over the whole area of LED-LCU light guide surface was analyzed by three methods: visual projection observation, spectral measurement and optical spectral analysis (OSA). The light power distribution and the total irradiance were different for the three LEDs used, but the wavelength was within the camphorquinone absorption spectrum. The use of a blank sheet was quite on hand to make a qualitative analysis of a beam, and it is costless. Secondly, specimens of a hybrid composite with approximately 8 mm diameter and 2 mm thickness were produced and polymerized by 20 s exposition time to each LED-LCU. Thirdly, the elastic modulus (E) and hardness (HV) were measured throughout the irradiated area by instrumented micro-indentation test (IIT), allowing to correlate localized power and mechanical properties. Both E and HV showed to be very sensitive to local power and wavelength dependent, but they followed the beam power profile. It was also shown that the mechanical properties could be directly correlated to the curing process. Very steep differences in mechanical properties over very short distances may impair the material performance, since residual stresses can easily be built over it. - Highlights: • A resin based composite (RBC) was polymerized by three different Light Emitting Diodes. • Each LED had its beam profile visually, wavelength and power analyzed. • The effective polymerization power (EPP) varied from 28% to 52% of the total beam power. • Wavelength seems to be as relevant as power in the light curing process. • Mechanical properties depend on the simultaneous effect of wavelength and power.

Programming a Distributed System Using Shared Objects

NARCIS (Netherlands)

Tanenbaum, A.S.; Bal, H.E.; Kaashoek, M.F.

1993-01-01

Building the hardware for a high-performance distributed computer system is a lot easier than building its software. The authors describe a model for programming distributed systems based on abstract data types that can be replicated on all machines that need them. Read operations are done locally,

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Junjie Ma

2018-02-01

Full Text Available Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

Science.gov (United States)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical

Distributed collaborative processing in wireless sensor networks with application to target localization and beamforming

OpenAIRE

Béjar Haro, Benjamín

2013-01-01

Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of es...

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.

Recovering Sample Diversity in Rao-Blackwellized Particle Filters for Simultaneous Localization and Mapping

National Research Council Canada - National Science Library

Anderson, Andrew D

2006-01-01

...) in simultaneous localization and mapping (SLAM) situations that arises when precise feature measurements yield a limited perceptual distribution relative to a motion-based proposal distribution...

Fault-Tolerant Consensus of Multi-Agent System With Distributed Adaptive Protocol.

Science.gov (United States)

Chen, Shun; Ho, Daniel W C; Li, Lulu; Liu, Ming

2015-10-01

In this paper, fault-tolerant consensus in multi-agent system using distributed adaptive protocol is investigated. Firstly, distributed adaptive online updating strategies for some parameters are proposed based on local information of the network structure. Then, under the online updating parameters, a distributed adaptive protocol is developed to compensate the fault effects and the uncertainty effects in the leaderless multi-agent system. Based on the local state information of neighboring agents, a distributed updating protocol gain is developed which leads to a fully distributed continuous adaptive fault-tolerant consensus protocol design for the leaderless multi-agent system. Furthermore, a distributed fault-tolerant leader-follower consensus protocol for multi-agent system is constructed by the proposed adaptive method. Finally, a simulation example is given to illustrate the effectiveness of the theoretical analysis.

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems.

Science.gov (United States)

Wan, Liangtian; Han, Guangjie; Wang, Hao; Shu, Lei; Feng, Nanxing; Peng, Bao

2016-03-12

In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm.

Derivation of the probability distribution function for the local density of states of a disordered quantum wire via the replica trick and supersymmetry

International Nuclear Information System (INIS)

Bunder, J.E.J.E.; McKenzie, R.H.Ross H.

2001-01-01

We consider the statistical properties of the local density of states of a one-dimensional Dirac equation in the presence of various types of disorder with Gaussian white-noise distribution. It is shown how either the replica trick or supersymmetry can be used to calculate exactly all the moments of the local density of states. Careful attention is paid to how the results change if the local density of states is averaged over atomic length scales. For both the replica trick and supersymmetry the problem is reduced to finding the ground state of a zero-dimensional Hamiltonian which is written solely in terms of a pair of coupled 'spins' which are elements of u(1,1). This ground state is explicitly found for the particular case of the Dirac equation corresponding to an infinite metallic quantum wire with a single conduction channel. The calculated moments of the local density of states agree with those found previously by Al'tshuler and Prigodin [Sov. Phys. JETP 68 (1989) 198] using a technique based on recursion relations for Feynman diagrams

Distributed Reactive Power Control based Conservation Voltage Reduction in Active Distribution Systems

Directory of Open Access Journals (Sweden)

EMIROGLU, S.

2017-11-01

Full Text Available This paper proposes a distributed reactive power control based approach to deploy Volt/VAr optimization (VVO / Conservation Voltage Reduction (CVR algorithm in a distribution network with distributed generations (DG units and distribution static synchronous compensators (D-STATCOM. A three-phase VVO/CVR problem is formulated and the reactive power references of D-STATCOMs and DGs are determined in a distributed way by decomposing the VVO/CVR problem into voltage and reactive power control. The main purpose is to determine the coordination between voltage regulator (VR and reactive power sources (Capacitors, D-STATCOMs and DGs based on VVO/CVR. The study shows that the reactive power injection capability of DG units may play an important role in VVO/CVR. In addition, it is shown that the coordination of VR and reactive power sources does not only save more energy and power but also reduces the power losses. Moreover, the proposed VVO/CVR algorithm reduces the computational burden and finds fast solutions. To illustrate the effectiveness of the proposed method, the VVO/CVR is performed on the IEEE 13-node test system feeder considering unbalanced loading and line configurations. The tests are performed taking the practical voltage-dependent load modeling and different customer types into consideration to improve accuracy.

Synchrotron radiation-based Fourier-transform infrared spectromicroscopy for characterization of the protein/peptide distribution in single microspheres

Directory of Open Access Journals (Sweden)

Manli Wang

2015-05-01

Full Text Available The present study establishes a visualization method for the measurement of the distribution and localization of protein/peptide constituents within a single poly-lactide-co-glycolide (PLGA microsphere using synchrotron radiation–based Fourier-transform infrared spectromicroscopy (SR-FTIR. The representative infrared wavenumbers specific for protein/peptide (Exenatide and excipient (PLGA were identified and chemical maps at the single microsphere level were generated by measuring and plotting the intensity of these specific bands. For quantitative analysis of the distribution within microspheres, Matlab software was used to transform the map file into a 3D matrix and the matrix values specific for the drug and excipient were extracted. Comparison of the normalized SR-FTIR maps of PLGA and Exenatide indicated that PLGA was uniformly distributed, while Exenatide was relatively non-uniformly distributed in the microspheres. In conclusion, SR-FTIR is a rapid, nondestructive and sensitive detection technology to provide the distribution of chemical constituents and functional groups in microparticles and microspheres.

The Reviewing of Distributed Power Sources Impact on Fallout’s Localization in 22 kV Network

Directory of Open Access Journals (Sweden)

Peter Bracinik

2008-01-01

Full Text Available The aim of this paper is to point out some facts that will occur by fault localization in 22 kV networks after the implementation of distributed power sources, especially wind power plants. This paper describes possible connection of these sources into power system in regard to their rated output. It also presents short theoretical background for short circuit calculation in 22 kV network. Then several examples explaining how the point of wind power plant connection can influence network’s operation during short-circuits and consequential fault’s localization are described in the second part of this paper

Two-dimensional atom localization based on coherent field controlling in a five-level M-type atomic system.

Science.gov (United States)

Jiang, Xiangqian; Li, Jinjiang; Sun, Xiudong

2017-12-11

We study two-dimensional sub-wavelength atom localization based on the microwave coupling field controlling and spontaneously generated coherence (SGC) effect. For a five-level M-type atom, introducing a microwave coupling field between two upper levels and considering the quantum interference between two transitions from two upper levels to lower levels, the analytical expression of conditional position probability (CPP) distribution is obtained using the iterative method. The influence of the detuning of a spontaneously emitted photon, Rabi frequency of the microwave field, and the SGC effect on the CPP are discussed. The two-dimensional sub-half-wavelength atom localization with high-precision and high spatial resolution is achieved by adjusting the detuning and the Rabi frequency, where the atom can be localized in a region smaller thanλ/10×λ/10. The spatial resolution is improved significantly compared with the case without the microwave field.

Spatial distribution of nanoparticles in PWR nanofluid coolant subjected to local nucleate boiling

Energy Technology Data Exchange (ETDEWEB)

Mirghaffari, Reza; Jahanfarnia, Gholamreza [Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Dept. of Nuclear Engineering

2016-12-15

Nanofluids have shown to be promising as an alternative for a PWR reactor coolant or as a safety system coolant to cover the core in the event of a loss of coolant accident. The nanoparticles distribution and neutronic parameters are intensively affected by the local boiling of nanofluid coolant. The main goal of this study was the physical-mathematical modeling of the nanoparticles distribution in the nucleate boiling of nanofluids within the viscous sublayer. Nanoparticles concentration, especially near the heat transfer surfaces, plays a significant role in the enhancement of thermal conductivity of nanofluids and prediction of CHF, Hide Out and Return phenomena. By solving the equation of convection-diffusion for the liquid phase near the heating surface and the bulk stream, the effect of heat flux on the distribution of nanoparticles was studied. The steady state mass conservation equations for liquids, vapors and nanoparticles were written for the flow boiling within the viscous sublayer adjacent the fuel cladding surface. The derived differential equations were discretized by the finite difference method and were solved numerically. It was found out that by increasing the surface heat flux, the concentration of nanoparticles increased.

A new distributed systems scheduling algorithm: a swarm intelligence approach

Science.gov (United States)

Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

2011-12-01

The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.

Micromechanical analysis of martensite distribution on strain localization in dual phase steels by scanning electron microscopy and crystal plasticity simulation

Energy Technology Data Exchange (ETDEWEB)

Jafari, M. [Department of Mechanical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Ziaei-Rad, S., E-mail: szrad@cc.iut.ac.ir [Department of Mechanical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Saeidi, N. [Department of Materials Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Jamshidian, M. [Department of Mechanical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of)

2016-07-18

The morphology and distribution of the dispersed martensite islands in the ferrite matrix plays a key role in the formation of shear bands in dual phase steels. In this study, we investigate the relationship between the martensite dispersion and the strain localization regions due to the formation of shear bands in fine-grained DP 780 steel, employing experimental observations as well as numerical simulations. SEM studies of the deformed microstructure showed that voids nucleated at ferrite-martensite interface within larger ferrite grains and regions with low local martensite fraction. The experimental results were precisely analyzed by finite element simulations based on the theory of crystal plasticity. A parametric study was then performed to obtain a deeper insight in to the effect of martensite dispersion on the strain localization of the neighboring ferrite. Crystal plasticity simulation results revealed that in a more regular structure compared to a random structure, a greater region of the ferrite phase contributes to accommodate plasticity. In addition, these regions limit the formation of main shear bands by creating barriers against stress concentration regions, results in lower growth and interaction of stress concentration regions with each others.

Taxonomic Challenges and Distribution of Gracilarioid Algae ...

African Journals Online (AJOL)

This paper reviews the taxonomical literature of the gracilarioid algae from Tanzania, and provides information about their ecology and distribution based on an intensive regime of local collection. Its aim was to provide names, even if on a preliminary basis, for local gracilarioid taxa. Our revision shows that species ...

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.

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.

Damage identification method for continuous girder bridges based on spatially-distributed long-gauge strain sensing under moving loads

Science.gov (United States)

Wu, Bitao; Wu, Gang; Yang, Caiqian; He, Yi

2018-05-01

A novel damage identification method for concrete continuous girder bridges based on spatially-distributed long-gauge strain sensing is presented in this paper. First, the variation regularity of the long-gauge strain influence line of continuous girder bridges which changes with the location of vehicles on the bridge is studied. According to this variation regularity, a calculation method for the distribution regularity of the area of long-gauge strain history is investigated. Second, a numerical simulation of damage identification based on the distribution regularity of the area of long-gauge strain history is conducted, and the results indicate that this method is effective for identifying damage and is not affected by the speed, axle number and weight of vehicles. Finally, a real bridge test on a highway is conducted, and the experimental results also show that this method is very effective for identifying damage in continuous girder bridges, and the local element stiffness distribution regularity can be revealed at the same time. This identified information is useful for maintaining of continuous girder bridges on highways.

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.

Pattern recognition in spaces of probability distributions for the analysis of edge-localized modes in tokamak plasmas

Energy Technology Data Exchange (ETDEWEB)

Shabbir, Aqsa

2016-07-07

In this doctoral work, pattern recognition techniques are developed and applied to data from tokamak plasmas, in order to contribute to a systematic analysis of edge-localized modes (ELMs). We employ probabilistic models for a quantitative data description geared towards an enhanced systematization of ELM phenomenology. Hence, we start from the point of view that the fundamental object resulting from the observation of a system is a probability distribution, with every single measurement providing a sample from this distribution. In exploring the patterns emerging from the various ELM regimes and relations, we need methods that can handle the intrinsic probabilistic nature of the data. The original contributions of this work are twofold. First, several novel pattern recognition methods in non-Euclidean spaces of probability distribution functions (PDFs) are developed and validated. The second main contribution lies in the application of these and other techniques to a systematic analysis of ELMs in tokamak plasmas. In regard to the methodological aims of the work, we employ the framework of information geometry to develop pattern visualization and classification methods in spaces of probability distributions. In information geometry, a family of probability distributions is considered as a Riemannian manifold. Every point on the manifold represents a single PDF and the distribution parameters provide local coordinates on the manifold. The Fisher information plays the role of a Riemannian metric tensor, enabling calculation of geodesic curves on the surface. The length of such curves yields the geodesic distance (GD) on probabilistic manifolds, which is a natural similarity (distance) measure between PDFs. Equipped with a suitable distance measure, we extrapolate several distance-based pattern recognition methods to the manifold setting. This includes k-nearest neighbor (kNN) and conformal predictor (CP) methods for classification, as well as multidimensional

Pattern recognition in spaces of probability distributions for the analysis of edge-localized modes in tokamak plasmas

International Nuclear Information System (INIS)

Shabbir, Aqsa

2016-01-01

In this doctoral work, pattern recognition techniques are developed and applied to data from tokamak plasmas, in order to contribute to a systematic analysis of edge-localized modes (ELMs). We employ probabilistic models for a quantitative data description geared towards an enhanced systematization of ELM phenomenology. Hence, we start from the point of view that the fundamental object resulting from the observation of a system is a probability distribution, with every single measurement providing a sample from this distribution. In exploring the patterns emerging from the various ELM regimes and relations, we need methods that can handle the intrinsic probabilistic nature of the data. The original contributions of this work are twofold. First, several novel pattern recognition methods in non-Euclidean spaces of probability distribution functions (PDFs) are developed and validated. The second main contribution lies in the application of these and other techniques to a systematic analysis of ELMs in tokamak plasmas. In regard to the methodological aims of the work, we employ the framework of information geometry to develop pattern visualization and classification methods in spaces of probability distributions. In information geometry, a family of probability distributions is considered as a Riemannian manifold. Every point on the manifold represents a single PDF and the distribution parameters provide local coordinates on the manifold. The Fisher information plays the role of a Riemannian metric tensor, enabling calculation of geodesic curves on the surface. The length of such curves yields the geodesic distance (GD) on probabilistic manifolds, which is a natural similarity (distance) measure between PDFs. Equipped with a suitable distance measure, we extrapolate several distance-based pattern recognition methods to the manifold setting. This includes k-nearest neighbor (kNN) and conformal predictor (CP) methods for classification, as well as multidimensional

Local environment effects in disordered alloys

International Nuclear Information System (INIS)

Cable, J.W.

1978-01-01

The magnetic moment of an atom in a ferromagnetic disordered alloy depends on the local environment of that atom. This is particularly true for Ni and Pd based alloys for which neutron diffuse scattering measurements of the range and magnitude of the moment disturbances indicate that both magnetic and chemical environment are important in determining the moment distribution. In this paper we review recent neutron studies of local environment effects in Ni based alloys. These are discussed in terms of a phenomenological model that allows a separation of the total moment disturbance at a Ni site into its chemical and magnetic components

A Story-Based Simulation for Teaching Sampling Distributions

Science.gov (United States)

Turner, Stephen; Dabney, Alan R.

2015-01-01

Statistical inference relies heavily on the concept of sampling distributions. However, sampling distributions are difficult to teach. We present a series of short animations that are story-based, with associated assessments. We hope that our contribution can be useful as a tool to teach sampling distributions in the introductory statistics…

Coordinated Voltage Control of Distributed PV Inverters for Voltage Regulation in Low Voltage Distribution Networks

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

This paper reviews and analyzes the existing voltage control methods of distributed solar PV inverters to improve the voltage regulation and thereby the hosting capacity of a low-voltage distribution network. A novel coordinated voltage control method is proposed based on voltage sensitivity...... optimization. The proposed method is used to calculate the voltage bands and droop settings of PV inverters at each node by the supervisory controller. The local controller of each PV inverter implements the volt/var control and if necessary, the active power curtailment as per the received settings and based...... on measured local voltages. The advantage of the proposed method is that the calculated reactive power and active power droop settings enable fair contribution of the PV inverters at each node to the voltage regulation. Simulation studies are conducted using DigSilent Power factory software on a simplified...

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Local atomic order in nanocrystalline Fe-based alloys obtained by mechanical alloying

International Nuclear Information System (INIS)

Jartych, E.

2003-01-01

Using the 57 Fe Moessbauer spectroscopy, a local atomic order in nanocrystalline alloys of iron with Al, Ni, W and Mo has been determined. Alloys were prepared by mechanical alloying method. Analysis of Moessbauer spectra was performed on the basis of the local environment model in terms of Warren-Cowley parameters. It was shown that impurity atoms are not randomly distributed in the volume of the first and the second co-ordination spheres of 57 Fe nuclei and they form clusters

Small Distributed Renewable Energy Generation for Low Voltage Distribution Networks

Directory of Open Access Journals (Sweden)

Chindris M.

2016-08-01

Full Text Available Driven by the existing energy policies, the use of renewable energy has increased considerably all over the world in order to respond to the increasing energy consumption and to reduce the environmental impact of the electricity generation. Although most policy makers and companies are focusing on large applications, the use of cheap small generation units, based on local renewable resources, has become increasingly attractive for the general public, small farms and remote communities. The paper presents several results of a research project aiming to identify the power quality issues and the impact of RES based distributed generation (DG or other non-linear loads on low voltage (LV distribution networks in Romania; the final goal is to develop a Universal Power Quality Conditioner (UPQC able to diminish the existing disturbances. Basically, the work analyses the existing DG technologies and identifies possible solutions for their integration in Romania; taking into account the existent state of the art, the attention was paid on small systems, using wind and solar energy, and on possibility to integrate them into suburban and rural LV distribution networks. The presence of DG units at distribution voltage level means the transition from traditional passive to active distribution networks. In general, the relatively low penetration levels of DG does not produce problems; however, the nowadays massive increase of local power generation have led to new integration challenges in order to ensure the reliability and quality of the power supply. Power quality issues are identified and their assessment is the key element in the design of measures aiming to diminish all existing disturbances.

An Applet-based Anonymous Distributed Computing System.

Science.gov (United States)

Finkel, David; Wills, Craig E.; Ciaraldi, Michael J.; Amorin, Kevin; Covati, Adam; Lee, Michael

2001-01-01

Defines anonymous distributed computing systems and focuses on the specifics of a Java, applet-based approach for large-scale, anonymous, distributed computing on the Internet. Explains the possibility of a large number of computers participating in a single computation and describes a test of the functionality of the system. (Author/LRW)

MR-based source localization for MR-guided HDR brachytherapy

Science.gov (United States)

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

2018-04-01

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

Agent-based reactive power management of power distribution networks with distributed energy generation

International Nuclear Information System (INIS)

Rahman, M.S.; Mahmud, M.A.; Oo, A.M.T.; Pota, H.R.; Hossain, M.J.

2016-01-01

Highlights: • A coordinated multi-agent system is proposed for reactive power management. • A linear quadratic regulator with a proportional integral controller is designed. • Proposed multi-agent scheme provides accurate estimation and control of the system. • Voltage stability is improved with proper power management for different scenarios. • Results obtained from the proposed scheme is compared to the traditional approach. - Abstract: In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

Multi-isocenter stereotactic radiotherapy: implications for target dose distributions of systematic and random localization errors

International Nuclear Information System (INIS)

Ebert, M.A.; Zavgorodni, S.F.; Kendrick, L.A.; Weston, S.; Harper, C.S.

2001-01-01

Purpose: This investigation examined the effect of alignment and localization errors on dose distributions in stereotactic radiotherapy (SRT) with arced circular fields. In particular, it was desired to determine the effect of systematic and random localization errors on multi-isocenter treatments. Methods and Materials: A research version of the FastPlan system from Surgical Navigation Technologies was used to generate a series of SRT plans of varying complexity. These plans were used to examine the influence of random setup errors by recalculating dose distributions with successive setup errors convolved into the off-axis ratio data tables used in the dose calculation. The influence of systematic errors was investigated by displacing isocenters from their planned positions. Results: For single-isocenter plans, it is found that the influences of setup error are strongly dependent on the size of the target volume, with minimum doses decreasing most significantly with increasing random and systematic alignment error. For multi-isocenter plans, similar variations in target dose are encountered, with this result benefiting from the conventional method of prescribing to a lower isodose value for multi-isocenter treatments relative to single-isocenter treatments. Conclusions: It is recommended that the systematic errors associated with target localization in SRT be tracked via a thorough quality assurance program, and that random setup errors be minimized by use of a sufficiently robust relocation system. These errors should also be accounted for by incorporating corrections into the treatment planning algorithm or, alternatively, by inclusion of sufficient margins in target definition

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.

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

Science.gov (United States)

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

2016-09-15

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

Evolutionary Agent-based Models to design distributed water management strategies

Science.gov (United States)

Giuliani, M.; Castelletti, A.; Reed, P. M.

2012-12-01

There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a

Non--Local Approach to the Analysis of the Stress Distribution in Granular Systems.

Science.gov (United States)

Scott, J. E.; Kenkre, V. M.; Hurd, A. J.

1998-03-01

A continuum mechanical theory of the stress distribution in granular materials is presented, where the transformation of the vertical spatial coordinate into a formal time variable converts the study of the static stress distribution into a generally non--Markoffian, i.e., memory-possessing (non-local) propagation analysis. Previous treatments (J. -P). Bouchaud, M. E. Cates, and P. Claudin, J. Phys. I France 5, 639 (1995). (C. -h). Liu, S. R. Nagel, D. A. Schecter, S. N. Coppersmith, S. Majumdar, O. Narayan, and T. A. Witten, Science 269, 513 (1995). are shown to be particular cases of our theory corresponding to, respectively, wave-like and dif fusive limits of the general evolution. Calculations are presented for the example of ceramic or metal powder compaction in dies, with emphasis on the understanding of previously unexplained features as seen in experimental data found in the literature o ver the past 50 years. Specific proposals for new experimental investigations are presented.

Multiple local minima in IMRT optimization based on dose-volume criteria

International Nuclear Information System (INIS)

Wu Qiuwen; Mohan, Radhe

2002-01-01

Multiple local minima traps are known to exist in dose-volume and dose-response objective functions. Nevertheless, their presence and consequences are not considered impediments in finding satisfactory solutions in routine optimization of IMRT plans using gradient methods. However, there is often a concern that a significantly superior solution may exist unbeknownst to the planner and that the optimization process may not be able to reach it. We have investigated the soundness of the assumption that the presence of multiple minima traps can be ignored. To find local minima, we start the optimization process a large number of times with random initial intensities. We investigated whether the occurrence of local minima depends upon the choice of the objective function parameters and the number of variables and whether their existence is an impediment in finding a satisfactory solution. To learn about the behavior of multiple minima, we first used a symmetric cubic phantom containing a cubic target and an organ-at-risk surrounding it to optimize the beam weights of two pairs of parallel-opposed beams using a gradient technique. The phantom studies also served to test our software. Objective function parameters were chosen to ensure that multiple minima would exist. Data for 500 plans, optimized with random initial beam weights, were analyzed. The search process did succeed in finding the local minima and showed that the number of minima depends on the parameters of the objective functions. It was also found that the consequences of local minima depended on the number of beams. We further searched for the multiple minima in intensity-modulated treatment plans for a head-and-neck case and a lung case. In addition to the treatment plan scores and the dose-volume histograms, we examined the dose distributions and intensity patterns. We did not find any evidence that multiple local minima affect the outcome of optimization using gradient techniques in any clinically

Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution

Directory of Open Access Journals (Sweden)

Qingwu Gong

2017-03-01

Full Text Available The intermittency and variability of permeated distributed generators (DGs could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices—EENS (expected energy not supplied, PLC (probability of load curtailment, EFLC (expected frequency of load curtailment, and SI (severity index—were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs’ output power, an improved PEM (point estimate method-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

Light-sheet fluorescence imaging to localize cardiac lineage and protein distribution

Science.gov (United States)

Ding, Yichen; Lee, Juhyun; Ma, Jianguo; Sung, Kevin; Yokota, Tomohiro; Singh, Neha; Dooraghi, Mojdeh; Abiri, Parinaz; Wang, Yibin; Kulkarni, Rajan P.; Nakano, Atsushi; Nguyen, Thao P.; Fei, Peng; Hsiai, Tzung K.

2017-02-01

Light-sheet fluorescence microscopy (LSFM) serves to advance developmental research and regenerative medicine. Coupled with the paralleled advances in fluorescence-friendly tissue clearing technique, our cardiac LSFM enables dual-sided illumination to rapidly uncover the architecture of murine hearts over 10 by 10 by 10 mm3 in volume; thereby allowing for localizing progenitor differentiation to the cardiomyocyte lineage and AAV9-mediated expression of exogenous transmembrane potassium channels with high contrast and resolution. Without the steps of stitching image columns, pivoting the light-sheet and sectioning the heart mechanically, we establish a holistic strategy for 3-dimentional reconstruction of the “digital murine heart” to assess aberrant cardiac structures as well as the spatial distribution of the cardiac lineages in neonates and ion-channels in adults.

Distribution and localization of the harmonic magnon modes in a one-dimensional Heisenberg spin glass

Science.gov (United States)

Boukahil, A.; Huber, D. L.

1989-09-01

The harmonic magnon modes in a one-dimensional Heisenberg spin glass having nearest-neighbor exchange interactions of fixed magnitude and random sign are investigated. The Lyapounov exponent is calculated for chains of 107-108 spins over the interval 0Stinchcombe and Pimentel using transfer-matrix techniques; at higher frequencies, gaps appear in the spectrum. At low frequencies, the localization length diverges as ω-2/3. A formal connection is established between the spin glass and the one-dimensional discretized Schrödinger equation. By making use of the connection, it is shown that the theory of Derrida and Gardner, which was developed for weak potential disorder, can account quantitatively for the distribution and localization of the low-frequency magnon modes in the spin-glass model.

We are not the 99 percent: quantifying asphericity in the distribution of Local Group satellites

Science.gov (United States)

Forero-Romero, Jaime E.; Arias, Verónica

2018-05-01

We use simulations to build an analytic probability distribution for the asphericity in the satellite distribution around Local Group (LG) type galaxies in the Lambda Cold Dark Matter (LCDM) paradigm. We use this distribution to estimate the atypicality of the satellite distributions in the LG even when the underlying simulations do not have enough systems fully resembling the LG in terms of its typical masses, separation and kinematics. We demonstrate the method using three different simulations (Illustris-1, Illustris-1-Dark and ELVIS) and a number of satellites ranging from 11 to 15. Detailed results differ greatly among the simulations suggesting a strong influence of the typical DM halo mass, the number of satellites and the simulated baryonic effects. However, there are three common trends. First, at most 2% of the pairs are expected to have satellite distributions with the same asphericity as the LG; second, at most 80% of the pairs have a halo with a satellite distribution as aspherical as in M31; and third, at most 4% of the pairs have a halo with satellite distribution as planar as in the MW. These quantitative results place the LG at the level of a 3σ outlier in the LCDM paradigm. We suggest that understanding the reasons for this atypicality requires quantifying the asphericity probability distribution as a function of halo mass and large scale environment. The approach presented here can facilitate that kind of study and other comparisons between different numerical setups and choices to study satellites around LG pairs in simulations.

Analytic and Unambiguous Phase-Based Algorithm for 3-D Localization of a Single Source with Uniform Circular Array

Directory of Open Access Journals (Sweden)

Le Zuo

2018-02-01

Full Text Available This paper presents an analytic algorithm for estimating three-dimensional (3-D localization of a single source with uniform circular array (UCA interferometers. Fourier transforms are exploited to expand the phase distribution of a single source and the localization problem is reformulated as an equivalent spectrum manipulation problem. The 3-D parameters are decoupled to different spectrums in the Fourier domain. Algebraic relations are established between the 3-D localization parameters and the Fourier spectrums. Fourier sampling theorem ensures that the minimum element number for 3-D localization of a single source with a UCA is five. Accuracy analysis provides mathematical insights into the 3-D localization algorithm that larger number of elements gives higher estimation accuracy. In addition, the phase-based high-order difference invariance (HODI property of a UCA is found and exploited to realize phase range compression. Following phase range compression, ambiguity resolution is addressed by the HODI of a UCA. A major advantage of the algorithm is that the ambiguity resolution and 3-D localization estimation are both analytic and are processed simultaneously, hence computationally efficient. Numerical simulations and experimental results are provided to verify the effectiveness of the proposed 3-D localization algorithm.

UOBPRM: A uniformly distributed obstacle-based PRM

KAUST Repository

Yeh, Hsin-Yi

2012-10-01

This paper presents a new sampling method for motion planning that can generate configurations more uniformly distributed on C-obstacle surfaces than prior approaches. Here, roadmap nodes are generated from the intersections between C-obstacles and a set of uniformly distributed fixed-length segments in C-space. The results show that this new sampling method yields samples that are more uniformly distributed than previous obstacle-based methods such as OBPRM, Gaussian sampling, and Bridge test sampling. UOBPRM is shown to have nodes more uniformly distributed near C-obstacle surfaces and also requires the fewest nodes and edges to solve challenging motion planning problems with varying narrow passages. © 2012 IEEE.

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

Directory of Open Access Journals (Sweden)

Ryu Miura

2013-06-01

Full Text Available An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner.

Development of An On-Line, Core Power Distribution Monitoring System

International Nuclear Information System (INIS)

Tunc ALdemir; Don Miller; Peng Wang

2007-01-01

The objective of the proposed work was to develop a software package that can construct in three-dimensional core power distributions using the signals from constant temperature power sensors distributed in the reactor core. The software developed uses a mode-based state/parameter estimation technique that is particularly attractive when there are model uncertainties and/or large signal noise. The software yields the expected value of local power at the detector locations and points in between, as well as the probability distribution of the local power density

Development of An On-Line, Core Power Distribution Monitoring System

Energy Technology Data Exchange (ETDEWEB)

Tunc ALdemir; Don Miller; Peng Wang

2007-10-02

The objective of the proposed work was to develop a software package that can construct in three-dimensional core power distributions using the signals from constant temperature power sensors distributed in the reactor core. The software developed uses a mode-based state/parameter estmation technique that is particularly attractive when there are model uncertainties and/or large signal noise. The software yields the expected value of local power at the detector locations and points in between, as well as the probability distribution of the local power density

Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

Directory of Open Access Journals (Sweden)

Deepthi Chander

2009-01-01

Full Text Available Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN. DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

Report on a field-portable VME-based distributed data acquisition system

International Nuclear Information System (INIS)

Drigert, M.W.; Cole, J.D.; Reber, E.L.; Young, J.M.

1996-01-01

A development effort was started two years ago to develop a portable data acquisition system which could be used for performing arms control verification and environmental monitoring measurements with complex multi-detector systems in the field. A field portable data acquisition system has been developed around a VMEbus based micro-processor and standard TCP/IP network protocols. The hardware consists of a compact VME crate and a single CAMAC crate containing the signal processing electronics. The component processes of the data acquisition system transfer control and event data over a set of TCP/IP socket connections. The use of network sockets for the interprocess communications allows the data acquisition system to be operated transparently on one workstation or on a number of workstations distributed around a local network

Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines

Directory of Open Access Journals (Sweden)

Boming Song

2017-01-01

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

Chaos optimization algorithms based on chaotic maps with different probability distribution and search speed for global optimization

Science.gov (United States)

Yang, Dixiong; Liu, Zhenjun; Zhou, Jilei

2014-04-01

Chaos optimization algorithms (COAs) usually utilize the chaotic map like Logistic map to generate the pseudo-random numbers mapped as the design variables for global optimization. Many existing researches indicated that COA can more easily escape from the local minima than classical stochastic optimization algorithms. This paper reveals the inherent mechanism of high efficiency and superior performance of COA, from a new perspective of both the probability distribution property and search speed of chaotic sequences generated by different chaotic maps. The statistical property and search speed of chaotic sequences are represented by the probability density function (PDF) and the Lyapunov exponent, respectively. Meanwhile, the computational performances of hybrid chaos-BFGS algorithms based on eight one-dimensional chaotic maps with different PDF and Lyapunov exponents are compared, in which BFGS is a quasi-Newton method for local optimization. Moreover, several multimodal benchmark examples illustrate that, the probability distribution property and search speed of chaotic sequences from different chaotic maps significantly affect the global searching capability and optimization efficiency of COA. To achieve the high efficiency of COA, it is recommended to adopt the appropriate chaotic map generating the desired chaotic sequences with uniform or nearly uniform probability distribution and large Lyapunov exponent.

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

Directory of Open Access Journals (Sweden)

Hyungjin Kim

2015-08-01

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

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

Science.gov (United States)

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

2015-08-31

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

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

Science.gov (United States)

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

Primal Recovery from Consensus-Based Dual Decomposition for Distributed Convex Optimization

NARCIS (Netherlands)

Simonetto, A.; Jamali-Rad, H.

2015-01-01

Dual decomposition has been successfully employed in a variety of distributed convex optimization problems solved by a network of computing and communicating nodes. Often, when the cost function is separable but the constraints are coupled, the dual decomposition scheme involves local parallel

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

International Nuclear Information System (INIS)

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

1987-01-01

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

Environmental Communication Based on Local Wisdom In Anticipation of Citarum Flood

Directory of Open Access Journals (Sweden)

Iriana Bakti

2017-06-01

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

Local orientation measurements in 3D

DEFF Research Database (Denmark)

Juul Jensen, D.

2005-01-01

The 3 Dimensional X-Ray Diffraction (3DXRD) method is presented and its potentials illustrated by examples. The 3DXRD method is based on diffraction of high energy X-rays and allows fast and nondestructive 3D characterization of the local distribution of crystallographic orientations in the bulk....

Data Locality via Coordinated Caching for Distributed Processing

Science.gov (United States)

Fischer, M.; Kuehn, E.; Giffels, M.; Jung, C.

2016-10-01

To enable data locality, we have developed an approach of adding coordinated caches to existing compute clusters. Since the data stored locally is volatile and selected dynamically, only a fraction of local storage space is required. Our approach allows to freely select the degree at which data locality is provided. It may be used to work in conjunction with large network bandwidths, providing only highly used data to reduce peak loads. Alternatively, local storage may be scaled up to perform data analysis even with low network bandwidth. To prove the applicability of our approach, we have developed a prototype implementing all required functionality. It integrates seamlessly into batch systems, requiring practically no adjustments by users. We have now been actively using this prototype on a test cluster for HEP analyses. Specifically, it has been integral to our jet energy calibration analyses for CMS during run 2. The system has proven to be easily usable, while providing substantial performance improvements. Since confirming the applicability for our use case, we have investigated the design in a more general way. Simulations show that many infrastructure setups can benefit from our approach. For example, it may enable us to dynamically provide data locality in opportunistic cloud resources. The experience we have gained from our prototype enables us to realistically assess the feasibility for general production use.

Statistical distribution of the local purity in a large quantum system

International Nuclear Information System (INIS)

De Pasquale, A; Pascazio, S; Facchi, P; Giovannetti, V; Parisi, G; Scardicchio, A

2012-01-01

The local purity of large many-body quantum systems can be studied by following a statistical mechanical approach based on a random matrix model. Restricting the analysis to the case of global pure states, this method proved to be successful, and a full characterization of the statistical properties of the local purity was obtained by computing the partition function of the problem. Here we generalize these techniques to the case of global mixed states. In this context, by uniformly sampling the phase space of states with assigned global mixedness, we determine the exact expression of the first two moments of the local purity and a general expression for the moments of higher order. This generalizes previous results obtained for globally pure configurations. Furthermore, through the introduction of a partition function for a suitable canonical ensemble, we compute the approximate expression of the first moment of the marginal purity in the high-temperature regime. In the process, we establish a formal connection with the theory of quantum twirling maps that provides an alternative, possibly fruitful, way of performing the calculation. (paper)

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

KAUST Repository

Dutta, Gaurav

2017-03-08

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

Multi-agent based controller for islanding operation of active distribution networks with distributed generation

DEFF Research Database (Denmark)

Cha, Seung-Tae; Wu, Qiuwei; Østergaard, Jacob

2011-01-01

-bus system was used to investigate the dynamic and steady state performance of the active distribution system during islanding operation. Case studies have been carried out using the Real-Time Digital Simulator (RTDS) based simulation platform. Case study results show that the proposed multi......The increasing amount of distributed generation (DG) in today’s highly complex restructured power networks gives more options for distribution system operators (DSOs) under contingency conditions. A low voltage distribution network with a large amount of DG can be operated as an islanded system...... if the distribution system is disconnected from the main grid due to the contingency. In order to successfully operate distribution systems under islanding mode, the possibility of small power islands within the distribution system needs to be considered. The control and management of these small power islands...

Simulating the effects of climate change on the distribution of an invasive plant, using a high resolution, local scale, mechanistic approach: challenges and insights.

Science.gov (United States)

Fennell, Mark; Murphy, James E; Gallagher, Tommy; Osborne, Bruce

2013-04-01

The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (Gunnera tinctoria) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate-induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread-rate and intensity of G. tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters. © 2012 Blackwell Publishing Ltd.

Distribution Analysis of the Local Critical Temperature and Current Density in YBCO Coated Conductors using Low-temperature Scanning Laser and Hall Probe Microscopy

International Nuclear Information System (INIS)

Park, S. K.; Cho, B. R.; Park, H. Y.; Ri, H. C.

2011-01-01

Distribution of the local critical temperature and current density in YBCO coated conductors were analyzed using Low-temperature Scanning Laser and Hall Probe Microscopy (LTSLHPM). We prepared YBCO coated conductors of various bridge types to study the spatial distribution of the critical temperature and the current density in single and multi bridges. LTSLHPM system was modified for detailed linescan or two-dimensional scan both scanning laser and scanning Hall probe method simultaneously. We analyzed the local critical temperature of single and multi bridges from series of several linescans of scanning laser microscopy. We also investigated local current density and hysteresis curve of single bridge from experimental results of scanning Hall probe microscopy.

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.

Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy.

Science.gov (United States)

Heers, Marcel; Chowdhury, Rasheda A; Hedrich, Tanguy; Dubeau, François; Hall, Jeffery A; Lina, Jean-Marc; Grova, Christophe; Kobayashi, Eliane

2016-01-01

Distributed inverse solutions aim to realistically reconstruct the origin of interictal epileptic discharges (IEDs) from noninvasively recorded electroencephalography (EEG) and magnetoencephalography (MEG) signals. Our aim was to compare the performance of different distributed inverse solutions in localizing IEDs: coherent maximum entropy on the mean (cMEM), hierarchical Bayesian implementations of independent identically distributed sources (IID, minimum norm prior) and spatially coherent sources (COH, spatial smoothness prior). Source maxima (i.e., the vertex with the maximum source amplitude) of IEDs in 14 EEG and 19 MEG studies from 15 patients with focal epilepsy were analyzed. We visually compared their concordance with intracranial EEG (iEEG) based on 17 cortical regions of interest and their spatial dispersion around source maxima. Magnetic source imaging (MSI) maxima from cMEM were most often confirmed by iEEG (cMEM: 14/19, COH: 9/19, IID: 8/19 studies). COH electric source imaging (ESI) maxima co-localized best with iEEG (cMEM: 8/14, COH: 11/14, IID: 10/14 studies). In addition, cMEM was less spatially spread than COH and IID for ESI and MSI (p < 0.001 Bonferroni-corrected post hoc t test). Highest positive predictive values for cortical regions with IEDs in iEEG could be obtained with cMEM for MSI and with COH for ESI. Additional realistic EEG/MEG simulations confirmed our findings. Accurate spatially extended sources, as found in cMEM (ESI and MSI) and COH (ESI) are desirable for source imaging of IEDs because this might influence surgical decision. Our simulations suggest that COH and IID overestimate the spatial extent of the generators compared to cMEM.

Contributing to the Food Sovereignty Debate: Re-Linking Local Production and Consumption

NARCIS (Netherlands)

Quaye, W.; Ruivenkamp, G.T.P.; Frempong, G.; Jongerden, J.P.

2013-01-01

Agri-based economies especially those in developing countries are becoming increasingly dependent on foreign markets and losing their autonomy in food production and distribution. However, there are possibilities to re-link local production and consumption. That is reconnecting local productive

IBS for non-gaussian distributions

International Nuclear Information System (INIS)

Fedotov, A.; Sidorin, A.O.; Smirnov, A.V.

2010-01-01

In many situations distribution can significantly deviate from Gaussian which requires accurate treatment of IBS. Our original interest in this problem was motivated by the need to have an accurate description of beam evolution due to IBS while distribution is strongly affected by the external electron cooling force. A variety of models with various degrees of approximation were developed and implemented in BETACOOL in the past to address this topic. A more complete treatment based on the friction coefficient and full 3-D diffusion tensor was introduced in BETACOOL at the end of 2007 under the name 'local IBS model'. Such a model allowed us calculation of IBS for an arbitrary beam distribution. The numerical benchmarking of this local IBS algorithm and its comparison with other models was reported before. In this paper, after briefly describing the model and its limitations, they present its comparison with available experimental data.

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.

Inference for exponentiated general class of distributions based on record values

Directory of Open Access Journals (Sweden)

Samah N. Sindi

2017-09-01

Full Text Available The main objective of this paper is to suggest and study a new exponentiated general class (EGC of distributions. Maximum likelihood, Bayesian and empirical Bayesian estimators of the parameter of the EGC of distributions based on lower record values are obtained. Furthermore, Bayesian prediction of future records is considered. Based on lower record values, the exponentiated Weibull distribution, its special cases of distributions and exponentiated Gompertz distribution are applied to the EGC of distributions.  

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.

Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

Directory of Open Access Journals (Sweden)

Jagyasi Bhushan

2009-01-01

Full Text Available Abstract Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN. DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

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

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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.

Efficient routing on scale-free networks based on local information

International Nuclear Information System (INIS)

Yin Chuanyang; Wang Binghong; Wang Wenxu; Zhou Tao; Yang Huijie

2006-01-01

In this Letter, we propose a new routing strategy with a single tunable parameter α only based on local information of network topology. The probability that a given node i with degree k i receives packets from its neighbors is proportional to k i α . In order to maximize the packets handling capacity of underlying structure that can be measured by the critical point of continuous phase transition from free flow to congestion, the optimal value of α is sought out. Through investigating the distributions of queue length on each node in free state, we give an explanation why the delivering capacity of the network can be enhanced by choosing the optimal α. Furthermore, dynamic properties right after the critical point are also studied. Interestingly, it is found that although the system enters the congestion state, it still possesses partial delivering capability which does not depend on α. This phenomenon suggests that the capacity of the scale-free network can be enhanced by increasing the forwarding ability of small important nodes which bear severe congestion

An extended continuous estimation of distribution algorithm for solving the permutation flow-shop scheduling problem

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Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2017-11-01

This article proposes an extended continuous estimation of distribution algorithm (ECEDA) to solve the permutation flow-shop scheduling problem (PFSP). In ECEDA, to make a continuous estimation of distribution algorithm (EDA) suitable for the PFSP, the largest order value rule is applied to convert continuous vectors to discrete job permutations. A probabilistic model based on a mixed Gaussian and Cauchy distribution is built to maintain the exploration ability of the EDA. Two effective local search methods, i.e. revolver-based variable neighbourhood search and Hénon chaotic-based local search, are designed and incorporated into the EDA to enhance the local exploitation. The parameters of the proposed ECEDA are calibrated by means of a design of experiments approach. Simulation results and comparisons based on some benchmark instances show the efficiency of the proposed algorithm for solving the PFSP.

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

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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.

Fast Reliability Assessing Method for Distribution Network with Distributed Renewable Energy Generation

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Chen, Fan; Huang, Shaoxiong; Ding, Jinjin; Ding, Jinjin; Gao, Bo; Xie, Yuguang; Wang, Xiaoming

2018-01-01

This paper proposes a fast reliability assessing method for distribution grid with distributed renewable energy generation. First, the Weibull distribution and the Beta distribution are used to describe the probability distribution characteristics of wind speed and solar irradiance respectively, and the models of wind farm, solar park and local load are built for reliability assessment. Then based on power system production cost simulation probability discretization and linearization power flow, a optimal power flow objected with minimum cost of conventional power generation is to be resolved. Thus a reliability assessment for distribution grid is implemented fast and accurately. The Loss Of Load Probability (LOLP) and Expected Energy Not Supplied (EENS) are selected as the reliability index, a simulation for IEEE RBTS BUS6 system in MATLAB indicates that the fast reliability assessing method calculates the reliability index much faster with the accuracy ensured when compared with Monte Carlo method.

Three-dimensional ultrastructural analyses of anterior pituitary gland expose spatial relationships between endocrine cell secretory granule localization and capillary distribution.