Results and Error Estimates from GRACE Forward Modeling over Greenland, Canada, and Alaska

Science.gov (United States)

Bonin, J. A.; Chambers, D. P.

2012-12-01

Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Greenland and Antarctica. However, the accuracy of the forward model technique has not been determined, nor is it known how the distribution of the local basins affects the results. We use a "truth" model composed of hydrology and ice-melt slopes as an example case, to estimate the uncertainties of this forward modeling method and expose those design parameters which may result in an incorrect high-resolution mass distribution. We then apply these optimal parameters in a forward model estimate created from RL05 GRACE data. We compare the resulting mass slopes with the expected systematic errors from the simulation, as well as GIA and basic trend-fitting uncertainties. We also consider whether specific regions (such as Ellesmere Island and Baffin Island) can be estimated reliably using our optimal basin layout.

Geographical range and local abundance of tree species in China.

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Haibao Ren

Full Text Available Most studies on the geographical distribution of species have utilized a few well-known taxa in Europe and North America, with little research in China and its wide range of climate and forest types. We assembled large datasets to quantify the geographic ranges of tree species in China and to test several biogeographic hypotheses: 1 whether locally abundant species tend to be geographically widespread; 2 whether species are more abundant towards their range-centers; and 3 how abundances are correlated between sites. Local abundances of 651 species were derived from four tree plots of 20-25 ha where all individuals ≥1 cm in stem diameter were mapped and identified taxonomically. Range sizes of these species across China were then estimated from over 460,000 geo-referenced records; a Bayesian approach was used, allowing careful measures of error of each range estimate. The log-transformed range sizes had a bell-shaped distribution with a median of 703,000 km(2, and >90% of 651 species had ranges >10(5 km(2. There was no relationship between local abundance and range size, and no evidence for species being more abundant towards their range-centers. Finally, species' abundances were positively correlated between sites. The widespread nature of most tree species in China suggests few are vulnerable to global extinction, and there is no indication of the double-peril that would result if rare species also had narrow ranges.

An improved lattice hydrodynamic model considering the influence of optimal flux for forward looking sites

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Wang, Yunong; Ge, Hongxia; Cheng, Rongjun

2017-11-01

In this paper, a lattice hydrodynamic model is derived considering the delayed-feedback control influence of optimal flux for forward looking sites on a single-lane road which includes more comprehensive information. The control method is used to analyze the stability of the model. The critical condition for the linear steady traffic flow is deduced and the numerical simulation is carried out to investigate the advantage of the proposed model with and without the effect of optimal flux for forward looking sites. Moreover it indicates that the characteristic of the model can lead to a lower energy consumption in traffic system. The results are consistent with the theoretical analysis correspondingly.

GWO-LPWSN: Grey Wolf Optimization Algorithm for Node Localization Problem in Wireless Sensor Networks

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R. Rajakumar

2017-01-01

Full Text Available Seyedali Mirjalili et al. (2014 introduced a completely unique metaheuristic technique particularly grey wolf optimization (GWO. This algorithm mimics the social behavior of grey wolves whereas it follows the leadership hierarchy and attacking strategy. The rising issue in wireless sensor network (WSN is localization problem. The objective of this problem is to search out the geographical position of unknown nodes with the help of anchor nodes in WSN. In this work, GWO algorithm is incorporated to spot the correct position of unknown nodes, so as to handle the node localization problem. The proposed work is implemented using MATLAB 8.2 whereas nodes are deployed in a random location within the desired network area. The parameters like computation time, percentage of localized node, and minimum localization error measures are utilized to analyse the potency of GWO rule with other variants of metaheuristics algorithms such as particle swarm optimization (PSO and modified bat algorithm (MBA. The observed results convey that the GWO provides promising results compared to the PSO and MBA in terms of the quick convergence rate and success rate.

A study of optimization problem for amplify-and-forward relaying over weibull fading channels

KAUST Repository

Ikki, Salama Said; Aissa, Sonia

2010-01-01

This paper addresses the power allocation and relay positioning problems in amplify-and-forward cooperative networks operating in Weibull fading environments. We study adaptive power allocation (PA) with fixed relay location, optimal relay location

OGC Geographic Information Service Deductive Semantic Reasoning Based on Description Vocabularies Reduction

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MIAO Lizhi

2015-09-01

Full Text Available As geographic information interoperability and sharing developing, more and more interoperable OGC (open geospatial consortium Web services (OWS are generated and published through the internet. These services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with executive semantic retrieval. This is especially true when considering the weak semantic description of geographic information service data. Focusing on semantic retrieval and reasoning of the distributed OWS resources, a deductive and semantic reasoning method is proposed to describe and search relevant OWS resources. Specifically, ①description words are extracted from OWS metadata file to generate GISe ontology-database and instance-database based on geographic ontology according to basic geographic elements category, ②a description words reduction model is put forward to implement knowledge reduction on GISe instance-database based on rough set theory and generate optimized instances database, ③utilizing GISe ontology-database and optimized instance-database to implement semantic inference and reasoning of geographic searching objects is used as an example to demonstrate the efficiency, feasibility and recall ration of the proposed description-word-based reduction model.

Optimal Aerodynamic Design of Conventional and Coaxial Helicopter Rotors in Hover and Forward Flight

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Giovanetti, Eli B.

This dissertation investigates the optimal aerodynamic performance and design of conventional and coaxial helicopters in hover and forward flight using conventional and higher harmonic blade pitch control. First, we describe a method for determining the blade geometry, azimuthal blade pitch inputs, optimal shaft angle (rotor angle of attack), and division of propulsive and lifting forces among the components that minimize the total power for a given forward flight condition. The optimal design problem is cast as a variational statement that is discretized using a vortex lattice wake to model inviscid forces, combined with two-dimensional drag polars to model profile losses. The resulting nonlinear constrained optimization problem is solved via Newton iteration. We investigate the optimal design of a compound vehicle in forward flight comprised of a coaxial rotor system, a propeller, and optionally, a fixed wing. We show that higher harmonic control substantially reduces required power, and that both rotor and propeller efficiencies play an important role in determining the optimal shaft angle, which in turn affects the optimal design of each component. Second, we present a variational approach for determining the optimal (minimum power) torque-balanced coaxial hovering rotor using Blade Element Momentum Theory including swirl. We show that the optimal hovering coaxial rotor generates only a small percentage of its total thrust on the portion of the lower rotor operating in the upper rotor's contracted wake, resulting in an optimal design with very different upper and lower rotor twist and chord distributions. We also show that the swirl component of induced velocity has a relatively small effect on rotor performance at the disk loadings typical of helicopter rotors. Third, we describe a more refined model of the wake of a hovering conventional or coaxial rotor. We approximate the rotor or coaxial rotors as actuator disks (though not necessarily uniformly loaded

Embedding Local Places in Global Spaces: Geographical Indications as a Territorial Development Strategy

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Bowen, Sarah

2010-01-01

Geographical indications (GIs) are place-based names that convey the geographical origin, as well as the cultural and historical identity, of agricultural products. GIs are unique, in that they provide a means of ensuring that control over production and sales of a product stays within a local area, but at the same time they make use of extralocal…

Probabilistic forward model for electroencephalography source analysis

International Nuclear Information System (INIS)

Plis, Sergey M; George, John S; Jun, Sung C; Ranken, Doug M; Volegov, Petr L; Schmidt, David M

2007-01-01

Source localization by electroencephalography (EEG) requires an accurate model of head geometry and tissue conductivity. The estimation of source time courses from EEG or from EEG in conjunction with magnetoencephalography (MEG) requires a forward model consistent with true activity for the best outcome. Although MRI provides an excellent description of soft tissue anatomy, a high resolution model of the skull (the dominant resistive component of the head) requires CT, which is not justified for routine physiological studies. Although a number of techniques have been employed to estimate tissue conductivity, no present techniques provide the noninvasive 3D tomographic mapping of conductivity that would be desirable. We introduce a formalism for probabilistic forward modeling that allows the propagation of uncertainties in model parameters into possible errors in source localization. We consider uncertainties in the conductivity profile of the skull, but the approach is general and can be extended to other kinds of uncertainties in the forward model. We and others have previously suggested the possibility of extracting conductivity of the skull from measured electroencephalography data by simultaneously optimizing over dipole parameters and the conductivity values required by the forward model. Using Cramer-Rao bounds, we demonstrate that this approach does not improve localization results nor does it produce reliable conductivity estimates. We conclude that the conductivity of the skull has to be either accurately measured by an independent technique, or that the uncertainties in the conductivity values should be reflected in uncertainty in the source location estimates

Energy gradients and the geographic distribution of local ant diversity.

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Kaspari, Michael; Ward, Philip S; Yuan, May

2004-08-01

Geographical diversity gradients, even among local communities, can ultimately arise from geographical differences in speciation and extinction rates. We evaluated three models--energy-speciation, energy-abundance, and area--that predict how geographic trends in net diversification rates generate trends in diversity. We sampled 96 litter ant communities from four provinces: Australia, Madagascar, North America, and South America. The energy-speciation hypothesis best predicted ant species richness by accurately predicting the slope of the temperature diversity curve, and accounting for most of the variation in diversity. The communities showed a strong latitudinal gradient in species richness as well as inter-province differences in diversity. The former vanished in the temperature-diversity residuals, suggesting that the latitudinal gradient arises primarily from higher diversification rates in the tropics. However, inter-province differences in diversity persisted in those residuals--South American communities remained more diverse than those in North America and Australia even after the effects of temperature were removed.

Optimal linear detectors for nonorthogonal amplify-and-forward protocol

KAUST Repository

Ahmed, Qasim Zeeshan; Park, Kihong; Alouini, Mohamed-Slim; Aissa, Sonia

2013-01-01

In this paper, we propose optimal linear detectors for non-orthogonal amplify-and-forward cooperative protocol when considering a single-relay scenario. Two types of detectors are proposed based on the principles of minimum mean square error (MMSE) and minimum bit error rate (MBER). The MMSE detector minimizes the mean square error, while the MBER minimizes the system bit error rate (BER). Both detectors exhibit excellent BER performance with relatively low complexity as compared to the maximal likelihood (ML) detector. The BER performance of both detectors is superior to the channel inversion, the maximal ratio combining, and the biased ML detectors. © 2013 IEEE.

Optimal linear detectors for nonorthogonal amplify-and-forward protocol

KAUST Repository

Ahmed, Qasim Zeeshan

2013-06-01

In this paper, we propose optimal linear detectors for non-orthogonal amplify-and-forward cooperative protocol when considering a single-relay scenario. Two types of detectors are proposed based on the principles of minimum mean square error (MMSE) and minimum bit error rate (MBER). The MMSE detector minimizes the mean square error, while the MBER minimizes the system bit error rate (BER). Both detectors exhibit excellent BER performance with relatively low complexity as compared to the maximal likelihood (ML) detector. The BER performance of both detectors is superior to the channel inversion, the maximal ratio combining, and the biased ML detectors. © 2013 IEEE.

Efficient Vector-Based Forwarding for Underwater Sensor Networks

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Peng Xie

2010-01-01

Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

Prediction Schemes to Enhance the Routing Process in Geographical GPSR Ad Hoc Protocol

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Raed Saqour

2007-01-01

Full Text Available Geographical routing protocols have received a serious attention due to more advantages they have in comparison to the conventional routing protocols. They require information about the physical position of nodes needed to be available. Commonly, each node determines its own position through the use of Global Positioning System (GPS or some other type of positioning service. Greedy Perimeter Stateless Routing (GPSR protocol, which is one of geographical routing protocols, limits the forwarding decision of the packet based on the node's own position, the destination's position and the position of the forwarding node's neighbors. Location information has some inaccuracy depending on the localization system and the environment exists in. This paper aims to study the impact of mobility metrics (beacon interval, and node speed on introducing location information error in GPSR protocol using different mobility models. The effect of these metrics is identified in GPSR as Neighbor Break Link (NBL problem. Based on simulation analysis, mobility prediction schemes are proposed to migrate the observed problem.

Efficient Iris Localization via Optimization Model

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Qi Wang

2017-01-01

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

Integral sustainable development: The example of local geographic milieu

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Vujadinović Snežana

2010-01-01

Full Text Available The local geographic milieu plays a significant role in development of every man because of its orientation in space, a sense of security and belonging to the community and the place where he lives or who perform his activities. In other words, one needs to fall in a particular social group that inhabits an area or to perform some activities able in a space, because that is something that stands out from the rest of the world and marking his individuality. The main long-term goal of development of each local community is to increase the quality of life of all its members, job creation, integration of the local community in a wider social system through health, educational and cultural institutions, creating a network of relationships and connections and correlations of all the actors from the state and public sector up to private enterprise, local authorities and local associations. Of particular importance for Serbia, is a question of development of local rural communities, which is closely linked to issues of sustainable and balanced spatial, socio-economic and demographic development. This issue becomes more important in efforts to prevent existing urban-centric trends and highlighted the economic and demographic polarization of Serbia. .

Optimal resource states for local state discrimination

Science.gov (United States)

Bandyopadhyay, Somshubhro; Halder, Saronath; Nathanson, Michael

2018-02-01

We study the problem of locally distinguishing pure quantum states using shared entanglement as a resource. For a given set of locally indistinguishable states, we define a resource state to be useful if it can enhance local distinguishability and optimal if it can distinguish the states as well as global measurements and is also minimal with respect to a partial ordering defined by entanglement and dimension. We present examples of useful resources and show that an entangled state need not be useful for distinguishing a given set of states. We obtain optimal resources with explicit local protocols to distinguish multipartite Greenberger-Horne-Zeilinger and graph states and also show that a maximally entangled state is an optimal resource under one-way local operations and classical communication to distinguish any bipartite orthonormal basis which contains at least one entangled state of full Schmidt rank.

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

Science.gov (United States)

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-08-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

Crop Classification by Forward Neural Network with Adaptive Chaotic Particle Swarm Optimization

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Yudong Zhang

2011-05-01

Full Text Available This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM based texture features. Then, the features were reduced by principle component analysis (PCA. Finally, a two-hidden-layer forward neural network (NN was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO. K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP, adaptive BP (ABP, momentum BP (MBP, Particle Swarm Optimization (PSO, and Resilient back-propagation (RPROP methods. Moreover, the computation time for each pixel is only 1.08 × 10−7 s.

Optimal classical-communication-assisted local model of n-qubit Greenberger-Horne-Zeilinger correlations

International Nuclear Information System (INIS)

Tessier, Tracey E.; Caves, Carlton M.; Deutsch, Ivan H.; Eastin, Bryan; Bacon, Dave

2005-01-01

We present a model, motivated by the criterion of reality put forward by Einstein, Podolsky, and Rosen and supplemented by classical communication, which correctly reproduces the quantum-mechanical predictions for measurements of all products of Pauli operators on an n-qubit GHZ state (or 'cat state'). The n-2 bits employed by our model are shown to be optimal for the allowed set of measurements, demonstrating that the required communication overhead scales linearly with n. We formulate a connection between the generation of the local values utilized by our model and the stabilizer formalism, which leads us to conjecture that a generalization of this method will shed light on the content of the Gottesman-Knill theorem

A study of optimization problem for amplify-and-forward relaying over weibull fading channels

KAUST Repository

Ikki, Salama Said

2010-09-01

This paper addresses the power allocation and relay positioning problems in amplify-and-forward cooperative networks operating in Weibull fading environments. We study adaptive power allocation (PA) with fixed relay location, optimal relay location with fixed power allocation, and joint optimization of the PA and relay location under total transmit power constraint, in order to minimize the outage probability and average error probability at high signal-to-noise ratios (SNR). Analytical results are validated by numerical simulations and comparisons between the different optimization schemes and their performance are provided. Results show that optimum PA brings only coding gain, while optimum relay location yields, in addition to the latter, diversity gains as well. Also, joint optimization improves both, the diversity gain and coding gain. Furthermore, results illustrate that the analyzed adaptive algorithms outperform uniform schemes. ©2010 IEEE.

Hybrid Firefly Variants Algorithm for Localization Optimization in WSN

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P. SrideviPonmalar

2017-01-01

Full Text Available Localization is one of the key issues in wireless sensor networks. Several algorithms and techniques have been introduced for localization. Localization is a procedural technique of estimating the sensor node location. In this paper, a novel three hybrid algorithms based on firefly is proposed for localization problem. Hybrid Genetic Algorithm-Firefly Localization Algorithm (GA-FFLA, Hybrid Differential Evolution-Firefly Localization Algorithm (DE-FFLA and Hybrid Particle Swarm Optimization -Firefly Localization Algorithm (PSO-FFLA are analyzed, designed and implemented to optimize the localization error. The localization algorithms are compared based on accuracy of estimation of location, time complexity and iterations required to achieve the accuracy. All the algorithms have hundred percent estimation accuracy but with variations in the number of firefliesr requirements, variation in time complexity and number of iteration requirements. Keywords: Localization; Genetic Algorithm; Differential Evolution; Particle Swarm Optimization

Study on feed forward neural network convex optimization for LiFePO4 battery parameters

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Liu, Xuepeng; Zhao, Dongmei

2017-08-01

Based on the modern facility agriculture automatic walking equipment LiFePO4 Battery, the parameter identification of LiFePO4 Battery is analyzed. An improved method for the process model of li battery is proposed, and the on-line estimation algorithm is presented. The parameters of the battery are identified using feed forward network neural convex optimization algorithm.

Mapping the results of local statistics: Using geographically weighted regression

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Stephen A. Matthews

2012-03-01

Full Text Available BACKGROUND The application of geographically weighted regression (GWR - a local spatial statistical technique used to test for spatial nonstationarity - has grown rapidly in the social, health, and demographic sciences. GWR is a useful exploratory analytical tool that generates a set of location-specific parameter estimates which can be mapped and analysed to provide information on spatial nonstationarity in the relationships between predictors and the outcome variable. OBJECTIVE A major challenge to users of GWR methods is how best to present and synthesize the large number of mappable results, specifically the local parameter parameter estimates and local t-values, generated from local GWR models. We offer an elegant solution. METHODS This paper introduces a mapping technique to simultaneously display local parameter estimates and local t-values on one map based on the use of data selection and transparency techniques. We integrate GWR software and GIS software package (ArcGIS and adapt earlier work in cartography on bivariate mapping. We compare traditional mapping strategies (i.e., side-by-side comparison and isoline overlay maps with our method using an illustration focusing on US county infant mortality data. CONCLUSIONS The resultant map design is more elegant than methods used to date. This type of map presentation can facilitate the exploration and interpretation of nonstationarity, focusing map reader attention on the areas of primary interest.

Improved quantum-behaved particle swarm optimization with local search strategy

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Maolong Xi

2017-03-01

Full Text Available Quantum-behaved particle swarm optimization, which was motivated by analysis of particle swarm optimization and quantum system, has shown compared performance in finding the optimal solutions for many optimization problems to other evolutionary algorithms. To address the problem of premature, a local search strategy is proposed to improve the performance of quantum-behaved particle swarm optimization. In proposed local search strategy, a super particle is presented which is a collection body of randomly selected particles’ dimension information in the swarm. The selected probability of particles in swarm is different and determined by their fitness values. To minimization problems, the fitness value of one particle is smaller; the selected probability is more and will contribute more information in constructing the super particle. In addition, in order to investigate the influence on algorithm performance with different local search space, four methods of computing the local search radius are applied in local search strategy and propose four variants of local search quantum-behaved particle swarm optimization. Empirical studies on a suite of well-known benchmark functions are undertaken in order to make an overall performance comparison among the proposed methods and other quantum-behaved particle swarm optimization. The simulation results show that the proposed quantum-behaved particle swarm optimization variants have better advantages over the original quantum-behaved particle swarm optimization.

Efficacy of very fast simulated annealing global optimization method for interpretation of self-potential anomaly by different forward formulation over 2D inclined sheet type structure

Science.gov (United States)

Biswas, A.; Sharma, S. P.

2012-12-01

Self-Potential anomaly is an important geophysical technique that measures the electrical potential due natural source of current in the Earth's subsurface. An inclined sheet type model is a very familiar structure associated with mineralization, fault plane, groundwater flow and many other geological features which exhibits self potential anomaly. A number of linearized and global inversion approaches have been developed for the interpretation of SP anomaly over different structures for various purposes. Mathematical expression to compute the forward response over a two-dimensional dipping sheet type structures can be described in three different ways using five variables in each case. Complexities in the inversion using three different forward approaches are different. Interpretation of self-potential anomaly using very fast simulated annealing global optimization has been developed in the present study which yielded a new insight about the uncertainty and equivalence in model parameters. Interpretation of the measured data yields the location of the causative body, depth to the top, extension, dip and quality of the causative body. In the present study, a comparative performance of three different forward approaches in the interpretation of self-potential anomaly is performed to assess the efficacy of the each approach in resolving the possible ambiguity. Even though each forward formulation yields the same forward response but optimization of different sets of variable using different forward problems poses different kinds of ambiguity in the interpretation. Performance of the three approaches in optimization has been compared and it is observed that out of three methods, one approach is best and suitable for this kind of study. Our VFSA approach has been tested on synthetic, noisy and field data for three different methods to show the efficacy and suitability of the best method. It is important to use the forward problem in the optimization that yields the

Store and forward teledermatology

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Kanthraj Garehatty

2007-01-01

Full Text Available Store and forward and real time or videoconferences are the two types of teledermatology services practiced. Dermatology and radio-diagnosis are visual specialties suited for store-and-forward teledermatology (SAFT. Advances in information technology, electronic instruments and biotechnology have revolutionized and brought changes in SAFT. Cellular phone, digital camera, personal digital assistants, Wi-Fi, Wi-Max and computer- aided-design software are incorporated to deliver the quality health care to remote geographic regions. Complete SAFT care equivalent to face-to-face consultation (Gold standard is essential. Health care providers in rural areas are the ′eyes′ for the consultants. Consultants to guide them should have a rapid periodic audit of visual parameters and dimensions of lesions. Given this background, this article reviews advances in 1 capture, store and transfer of images. 2 Computer Aided measurements of generalized and localized lesions and 3 the integration model to meet all the above two requirements in a centralized location. This process enables diagnosis, management, periodic assessment and complete follow-up care to achieve patient and physician satisfaction. Preservation of privacy and confidentiality of digital images is important. Uniform rules and regulations are required. Indian space research organization (ISRO, Government of India has demonstrated telemedicine pilot projects utilizing the satellite communication and mobile telemedicine units to be useful in meeting the health care needs of remote and rural India. we have to join hands with them to meet dermatology problems in rural areas.

A new experimental method for determining local airloads on rotor blades in forward flight

Science.gov (United States)

Berton, E.; Maresca, C.; Favier, D.

This paper presents a new approach for determining local airloads on helicopter rotor blade sections in forward flight. The method is based on the momentum equation in which all the terms are expressed by means of the velocity field measured by a laser Doppler velocimeter. The relative magnitude of the different terms involved in the momentum and Bernoulli equations is estimated and the results are encouraging.

Forward-weighted CADIS method for variance reduction of Monte Carlo calculations of distributions and multiple localized quantities

International Nuclear Information System (INIS)

Wagner, J. C.; Blakeman, E. D.; Peplow, D. E.

2009-01-01

This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is a variation on the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for some time to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain approximately uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented in the ADVANTG/MCNP framework and has been fully automated within the MAVRIC sequence of SCALE 6. Results of the application of the method to enabling the calculation of dose rates throughout an entire full-scale pressurized-water reactor facility are presented and discussed. (authors)

Speciation on a local geographic scale: the evolution of a rare rock outcrop specialist in Mimulus.

Science.gov (United States)

Ferris, Kathleen G; Sexton, Jason P; Willis, John H

2014-08-05

Speciation can occur on both large and small geographical scales. In plants, local speciation, where small populations split off from a large-ranged progenitor species, is thought to be the dominant mode, yet there are still few examples to verify speciation has occurred in this manner. A recently described morphological species in the yellow monkey flowers, Mimulus filicifolius, is an excellent candidate for local speciation because of its highly restricted geographical range. Mimulus filicifolius was formerly identified as a population of M. laciniatus due to similar lobed leaf morphology and rocky outcrop habitat. To investigate whether M. filicifolius is genetically divergent and reproductively isolated from M. laciniatus, we examined patterns of genetic diversity in ten nuclear and eight microsatellite loci, and hybrid fertility in M. filicifolius and its purported close relatives: M. laciniatus, M. guttatus and M. nasutus. We found that M. filicifolius is genetically divergent from the other species and strongly reproductively isolated from M. laciniatus. We conclude that M. filicifolius is an independent rock outcrop specialist despite being morphologically and ecologically similar to M. laciniatus, and that its small geographical range nested within other wide-ranging members of the M. guttatus species complex is consistent with local speciation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

The optimization of the electrostatic field inside the ZEUS forward drift chambers: Calculations and measurements

International Nuclear Information System (INIS)

Dobberstein, M.P.; Krawczyk, F.; Schaefer-Jotter, M.

1990-11-01

The electrostatic field inside small drift cells shows in general edge effects which are not negligible. These are usually corrected by field shaping wires or strips. The operating voltages of the field shaping electrodes have to be adjusted to maximize the field homogeneity. We present the underlying ideas of such an optimization procedure for the cells of the ZEUS forward drift chambers. Using the finite difference code PROFI, the optimization can be performed automatically by a multiple solution of the Poisson equation. An experimental verification of the optimal voltages was carried out measuring the gas amplifications at the six sense wires. Modifications of the drift cell geometry were necessary for calibration measurements with a laser beam. This caused additional distortions of the electrostatic field. Their influence was calculated using the MAFIA code, which allows to include open boundary conditions. (orig.)

Optimizer convergence and local minima errors and their clinical importance

International Nuclear Information System (INIS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-01-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization

A STRONG OPTIMIZATION THEOREM IN LOCALLY CONVEX SPACES

Institute of Scientific and Technical Information of China (English)

程立新; 腾岩梅

2003-01-01

This paper presents a geometric characterization of convex sets in locally convex spaces onwhich a strong optimization theorem of the Stegall-type holds, and gives Collier's theorem ofw* Asplund spaces a localized setting.

Geographic variation in opinions on climate change at state and local scales in the USA

Science.gov (United States)

Howe, Peter D.; Mildenberger, Matto; Marlon, Jennifer R.; Leiserowitz, Anthony

2015-06-01

Addressing climate change in the United States requires enactment of national, state and local mitigation and adaptation policies. The success of these initiatives depends on public opinion, policy support and behaviours at appropriate scales. Public opinion, however, is typically measured with national surveys that obscure geographic variability across regions, states and localities. Here we present independently validated high-resolution opinion estimates using a multilevel regression and poststratification model. The model accurately predicts climate change beliefs, risk perceptions and policy preferences at the state, congressional district, metropolitan and county levels, using a concise set of demographic and geographic predictors. The analysis finds substantial variation in public opinion across the nation. Nationally, 63% of Americans believe global warming is happening, but county-level estimates range from 43 to 80%, leading to a diversity of political environments for climate policy. These estimates provide an important new source of information for policymakers, educators and scientists to more effectively address the challenges of climate change.

Optimizing Geographic Allotment of Photovoltaic Capacity in a Distributed Generation Setting: Preprint

Energy Technology Data Exchange (ETDEWEB)

Urquhart, B.; Sengupta, M.; Keller, J.

2012-09-01

A multi-objective optimization was performed to allocate 2MW of PV among four candidate sites on the island of Lanai such that energy was maximized and variability in the form of ramp rates was minimized. This resulted in an optimal solution set which provides a range of geographic allotment alternatives for the fixed PV capacity. Within the optimal set, a tradeoff between energy produced and variability experienced was found, whereby a decrease in variability always necessitates a simultaneous decrease in energy. A design point within the optimal set was selected for study which decreased extreme ramp rates by over 50% while only decreasing annual energy generation by 3% over the maximum generation allocation. To quantify the allotment mix selected, a metric was developed, called the ramp ratio, which compares ramping magnitude when all capacity is allotted to a single location to the aggregate ramping magnitude in a distributed scenario. The ramp ratio quantifies simultaneously how much smoothing a distributed scenario would experience over single site allotment and how much a single site is being under-utilized for its ability to reduce aggregate variability. This paper creates a framework for use by cities and municipal utilities to reduce variability impacts while planning for high penetration of PV on the distribution grid.

Geometrical optimization of a local ballistic magnetic sensor

Energy Technology Data Exchange (ETDEWEB)

Kanda, Yuhsuke; Hara, Masahiro [Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami, Kumamoto 860-8555 (Japan); Nomura, Tatsuya [Advanced Electronics Research Division, INAMORI Frontier Research Center, Kyushu University, 744 Motooka, Fukuoka 819-0395 (Japan); Kimura, Takashi [Advanced Electronics Research Division, INAMORI Frontier Research Center, Kyushu University, 744 Motooka, Fukuoka 819-0395 (Japan); Department of Physics, Kyushu University, 6-10-1 Hakozaki, Fukuoka 812-8581 (Japan)

2014-04-07

We have developed a highly sensitive local magnetic sensor by using a ballistic transport property in a two-dimensional conductor. A semiclassical simulation reveals that the sensitivity increases when the geometry of the sensor and the spatial distribution of the local field are optimized. We have also experimentally demonstrated a clear observation of a magnetization process in a permalloy dot whose size is much smaller than the size of an optimized ballistic magnetic sensor fabricated from a GaAs/AlGaAs two-dimensional electron gas.

Optimizing radiation exposure for CT localizer radiographs

Energy Technology Data Exchange (ETDEWEB)

Bohrer, Evelyn; Maeder, Ulf; Fiebich, Martin [Univ. of Applied Sciences, Giessen (Germany). Inst. of Medical Physics and Radiation Protection-IMPS; Schaefer, Stefan; Krombach, Gabriele A. [Univ. Hospital Giessen (Germany). Dept. of Radiology; Noel, Peter B. [Technische Univ. Muenchen (Germany). Dept. of Diagnostic and Interventional Radiology

2017-08-01

The trend towards submillisievert CT scans leads to a higher dose fraction of localizer radiographs in CT examinations. The already existing technical capabilities make dose optimization of localizer radiographs worthwhile. Modern CT scanners apply automatic exposure control (AEC) based on attenuation data in such a localizer. Therefore not only this aspect but also the detectability of anatomical landmarks in the localizer for the desired CT scan range adjustment needs to be considered. The effective dose of a head, chest, and abdomen-pelvis localizer radiograph with standard factory settings and user-optimized settings was determined using Monte Carlo simulations. CT examinations of an anthropomorphic phantom were performed using multiple sets of acquisition parameters for the localizer radiograph and the AEC for the subsequent helical CT scan. Anatomical landmarks were defined to assess the image quality of the localizer. CTDI{sub vol} and effective mAs per slice of the helical CT scan were recorded to examine the impact of localizer settings on a helical CT scan. The dose of the localizer radiograph could be decreased by more than 90% while the image quality remained sufficient when selecting the lowest available settings (80 kVp, 20 mA, pa tube position). The tube position during localizer acquisition had a greater impact on the AEC than the reduction of tube voltage and tube current. Except for the use of a pa tube position, all changes of acquisition parameters for the localizer resulted in a decreased total radiation exposure. A dose reduction of CT localizer radiograph is necessary and possible. In the examined CT system there was no negative impact on the modulated helical CT scan when the lowest tube voltage and tube current were used for the localizer.

BER and optimal power allocation for amplify-and-forward relaying using pilot-aided maximum likelihood estimation

KAUST Repository

Wang, Kezhi

2014-10-01

Bit error rate (BER) and outage probability for amplify-and-forward (AF) relaying systems with two different channel estimation methods, disintegrated channel estimation and cascaded channel estimation, using pilot-aided maximum likelihood method in slowly fading Rayleigh channels are derived. Based on the BERs, the optimal values of pilot power under the total transmitting power constraints at the source and the optimal values of pilot power under the total transmitting power constraints at the relay are obtained, separately. Moreover, the optimal power allocation between the pilot power at the source, the pilot power at the relay, the data power at the source and the data power at the relay are obtained when their total transmitting power is fixed. Numerical results show that the derived BER expressions match with the simulation results. They also show that the proposed systems with optimal power allocation outperform the conventional systems without power allocation under the same other conditions. In some cases, the gain could be as large as several dB\\'s in effective signal-to-noise ratio.

BER and optimal power allocation for amplify-and-forward relaying using pilot-aided maximum likelihood estimation

KAUST Repository

Wang, Kezhi; Chen, Yunfei; Alouini, Mohamed-Slim; Xu, Feng

2014-01-01

Bit error rate (BER) and outage probability for amplify-and-forward (AF) relaying systems with two different channel estimation methods, disintegrated channel estimation and cascaded channel estimation, using pilot-aided maximum likelihood method in slowly fading Rayleigh channels are derived. Based on the BERs, the optimal values of pilot power under the total transmitting power constraints at the source and the optimal values of pilot power under the total transmitting power constraints at the relay are obtained, separately. Moreover, the optimal power allocation between the pilot power at the source, the pilot power at the relay, the data power at the source and the data power at the relay are obtained when their total transmitting power is fixed. Numerical results show that the derived BER expressions match with the simulation results. They also show that the proposed systems with optimal power allocation outperform the conventional systems without power allocation under the same other conditions. In some cases, the gain could be as large as several dB's in effective signal-to-noise ratio.

Local Approximation and Hierarchical Methods for Stochastic Optimization

Science.gov (United States)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the

Optimal sharing of quantity risk for a coalition of wind power producers facing nodal prices

KAUST Repository

Bitar, E. Y.; Baeyens, E.; Khargonekar, P. P.; Poolla, K.; Varaiya, P.

2012-01-01

It is widely accepted that aggregation of geographically diverse wind energy resources offers compelling potential to mitigate wind power variability, as wind speed at different geographic locations tends to decorrelate with increasing spatial separation. In this paper, we explore the extent to which a coalition of wind power producers can exploit the statistical benefits of aggregation to mitigate the risk of quantity shortfall with respect to forward contract offerings for energy. We propose a simple augmentation of the existing two-settlement market system with nodal pricing to permit quantity risk sharing among wind power producers by affording the group a recourse opportunity to utilize improved forecasts of their ensuing wind energy production to collectively modify their forward contracted positions so as to utilize the projected surplus in generation at certain buses to balance the projected shortfall in generation at complementary buses. Working within this framework, we show that the problem of optimally sizing a set of forward contracts for a group of wind power producers reduces to convex programming and derive closed form expressions for the set of optimal recourse policies. We also asses the willingness of individual wind power producers to form a coalition to cooperatively offer contracts for energy. We first show that the expected profit derived from coalitional contract offerings with recourse is greater than that achievable through independent contract offerings. And, using tools from coalitional game theory, we show that the core for our game is non-empty.

Optimal sharing of quantity risk for a coalition of wind power producers facing nodal prices

KAUST Repository

Bitar, E. Y.

2012-06-01

It is widely accepted that aggregation of geographically diverse wind energy resources offers compelling potential to mitigate wind power variability, as wind speed at different geographic locations tends to decorrelate with increasing spatial separation. In this paper, we explore the extent to which a coalition of wind power producers can exploit the statistical benefits of aggregation to mitigate the risk of quantity shortfall with respect to forward contract offerings for energy. We propose a simple augmentation of the existing two-settlement market system with nodal pricing to permit quantity risk sharing among wind power producers by affording the group a recourse opportunity to utilize improved forecasts of their ensuing wind energy production to collectively modify their forward contracted positions so as to utilize the projected surplus in generation at certain buses to balance the projected shortfall in generation at complementary buses. Working within this framework, we show that the problem of optimally sizing a set of forward contracts for a group of wind power producers reduces to convex programming and derive closed form expressions for the set of optimal recourse policies. We also asses the willingness of individual wind power producers to form a coalition to cooperatively offer contracts for energy. We first show that the expected profit derived from coalitional contract offerings with recourse is greater than that achievable through independent contract offerings. And, using tools from coalitional game theory, we show that the core for our game is non-empty.

Geometry optimization of molecules within an LCGTO local-density functional approach

International Nuclear Information System (INIS)

Mintmire, J.W.

1990-01-01

We describe our implementation of geometry optimization techniques within the linear combination of Gaussian-type orbitals (LCGTO) approach to local-density functional theory. The algorithm for geometry optimization is based on the evaluation of the gradient of the total energy with respect to internal coordinates within the local-density functional scheme. We present optimization results for a range of small molecules which serve as test cases for our approach

Localization of multilayer networks by optimized single-layer rewiring.

Science.gov (United States)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Stochastic optimal control, forward-backward stochastic differential equations and the Schroedinger equation

Energy Technology Data Exchange (ETDEWEB)

Paul, Wolfgang; Koeppe, Jeanette [Institut fuer Physik, Martin Luther Universitaet, 06099 Halle (Germany); Grecksch, Wilfried [Institut fuer Mathematik, Martin Luther Universitaet, 06099 Halle (Germany)

2016-07-01

The standard approach to solve a non-relativistic quantum problem is through analytical or numerical solution of the Schroedinger equation. We show a way to go around it. This way is based on the derivation of the Schroedinger equation from conservative diffusion processes and the establishment of (several) stochastic variational principles leading to the Schroedinger equation under the assumption of a kinematics described by Nelson's diffusion processes. Mathematically, the variational principle can be considered as a stochastic optimal control problem linked to the forward-backward stochastic differential equations of Nelson's stochastic mechanics. The Hamilton-Jacobi-Bellmann equation of this control problem is the Schroedinger equation. We present the mathematical background and how to turn it into a numerical scheme for analyzing a quantum system without using the Schroedinger equation and exemplify the approach for a simple 1d problem.

Least median of squares filtering of locally optimal point matches for compressible flow image registration

International Nuclear Information System (INIS)

Castillo, Edward; Guerrero, Thomas; Castillo, Richard; White, Benjamin; Rojo, Javier

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. (paper)

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

Science.gov (United States)

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

Directory of Open Access Journals (Sweden)

Huanqing Cui

2017-03-01

Full Text Available Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Crowdsourcing sensor tasks to a socio-geographic network

NARCIS (Netherlands)

Lasnia, Damian; Broering, Arne; Jirka, Simon; Remke, Albert; Pianho, M.; Santos, M.Y.; Pundt, H.

2010-01-01

This work describes an approach of a socio-geographic network for crowdsourcing sensor tasks to a human sensor web. Users can register as human sensors at the system by defining their skills and impact area. Based on that information, submitted sensor tasks are forwarded to the most suitable human

Is local participation always optimal for sustainable action?

DEFF Research Database (Denmark)

Brandt, Urs Steiner; Svendsen, Gert Tinggaard

2013-01-01

Is local participation always optimal for sustainable action? Here, Local Agenda 21 is a relevant case as it broadly calls for consensus-building among stakeholders. Consensus-building is, however, costly. We show that the costs of making local decisions are likely to rapidly exceed the benefits......-solutions, or not making any choices at all. Even though the informational value of meetings may be helpful to policy makers, the model shows that it also decreases as the number of participants increase. Overall, the result is a thought provoking scenario for Local Agenda 21 as it highlights the risk of less sustainable...

Local beam angle optimization with linear programming and gradient search

International Nuclear Information System (INIS)

Craft, David

2007-01-01

The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)

Theory and Algorithms for Global/Local Design Optimization

National Research Council Canada - National Science Library

Watson, Layne T; Guerdal, Zafer; Haftka, Raphael T

2005-01-01

The motivating application for this research is the global/local optimal design of composite aircraft structures such as wings and fuselages, but the theory and algorithms are more widely applicable...

Phase-Field Relaxation of Topology Optimization with Local Stress Constraints

DEFF Research Database (Denmark)

Stainko, Roman; Burger, Martin

2006-01-01

inequality constraints. We discretize the problem by finite elements and solve the arising finite-dimensional programming problems by a primal-dual interior point method. Numerical experiments for problems with local stress constraints based on different criteria indicate the success and robustness......We introduce a new relaxation scheme for structural topology optimization problems with local stress constraints based on a phase-field method. In the basic formulation we have a PDE-constrained optimization problem, where the finite element and design analysis are solved simultaneously...

A dynamic global and local combined particle swarm optimization algorithm

International Nuclear Information System (INIS)

Jiao Bin; Lian Zhigang; Chen Qunxian

2009-01-01

Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problems, but it has a tendency to get stuck in a near optimal solution and one may find it difficult to improve solution accuracy by fine tuning. This paper presents a dynamic global and local combined particle swarm optimization (DGLCPSO) algorithm to improve the performance of original PSO, in which all particles dynamically share the best information of the local particle, global particle and group particles. It is tested with a set of eight benchmark functions with different dimensions and compared with original PSO. Experimental results indicate that the DGLCPSO algorithm improves the search performance on the benchmark functions significantly, and shows the effectiveness of the algorithm to solve optimization problems.

The impact of local public services and geographical cost of living differences on poverty estimates

OpenAIRE

Aaberge, Rolf; Langørgen, Audun; Mogstad, Magne; Østensen, Marit

2008-01-01

Abstract: Despite a broad consensus on the need to account for the value of public services and geographical cost of living differences on the measurement of poverty, there is little reliable evidence on how these factors actually affect poverty estimates. Unlike the standard approach in studies of the distribution of public services, this paper employs a method for valuing sector-specific local public services that accounts for differences between municipalities in the costs and capacity ...

Optimal JPWL Forward Error Correction Rate Allocation for Robust JPEG 2000 Images and Video Streaming over Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Benoit Macq

2008-07-01

Full Text Available Based on the analysis of real mobile ad hoc network (MANET traces, we derive in this paper an optimal wireless JPEG 2000 compliant forward error correction (FEC rate allocation scheme for a robust streaming of images and videos over MANET. The packet-based proposed scheme has a low complexity and is compliant to JPWL, the 11th part of the JPEG 2000 standard. The effectiveness of the proposed method is evaluated using a wireless Motion JPEG 2000 client/server application; and the ability of the optimal scheme to guarantee quality of service (QoS to wireless clients is demonstrated.

Grey Wolf Optimizer Based on Powell Local Optimization Method for Clustering Analysis

Directory of Open Access Journals (Sweden)

Sen Zhang

2015-01-01

Full Text Available One heuristic evolutionary algorithm recently proposed is the grey wolf optimizer (GWO, inspired by the leadership hierarchy and hunting mechanism of grey wolves in nature. This paper presents an extended GWO algorithm based on Powell local optimization method, and we call it PGWO. PGWO algorithm significantly improves the original GWO in solving complex optimization problems. Clustering is a popular data analysis and data mining technique. Hence, the PGWO could be applied in solving clustering problems. In this study, first the PGWO algorithm is tested on seven benchmark functions. Second, the PGWO algorithm is used for data clustering on nine data sets. Compared to other state-of-the-art evolutionary algorithms, the results of benchmark and data clustering demonstrate the superior performance of PGWO algorithm.

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

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

Science.gov (United States)

Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

2017-01-23

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS

Directory of Open Access Journals (Sweden)

Zhongyu Li

2017-01-01

Full Text Available Bistatic forward-looking SAR (BFSAR is a kind of bistatic synthetic aperture radar (SAR system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I large and unknown range cell migration (RCM (including range walk and high-order RCM; (II the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

FACTORS OF LOGISTICS AND FORWARDING SERVICE FORMATION AND DEVELOPMENT

Directory of Open Access Journals (Sweden)

Galina Kucheruk

2016-06-01

Full Text Available Purpose: Forwarding service is a key part of the system of goods movement and as such it provides realization of numerous services. Providing of new additional and unconventional services to cargo owners by haulers will extend the range of their clients, increase profits from sales, facilitate and accelerate the introduction of new transport technologies, increase stability and strength of relations in the transport market. Methods: We formulated requirements to be met by modern forwarding service. Carriage management should be based on logistics concept and its methods; comprehensive resource optimization of haulers and owners of cargo and other supply chain participants (insurance, financial ones, etc.. Optimization of the space-time chain, even involving freight forwarders (transport intermediaries, is a complex scientific and practical task. Results: We offer directions for development of forwarding additional and non-conventional service for forwarding system of cargo haulage service, which would also provide an opportunity to reduce transport time and increase service level. Discussion: A general scheme of products delivery to consumers contains a significant number of units-particular entities. It is important to analyze not only the position of economic entities in the market, but the features and capabilities of their interaction in major systemic tasks of forwarding service, quality and effective promotion of freight flows

Improved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems

Science.gov (United States)

Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka

2014-01-01

A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. In the proposed local search technique, a potential particle position in the solution search space is collectively constructed by a number of randomly selected particles in the swarm. The number of times the selection is made varies with the dimension of the optimization problem and each selected particle donates the value in the location of its randomly selected dimension from its personal best. After constructing the potential particle position, some local search is done around its neighbourhood in comparison with the current swarm global best position. It is then used to replace the global best particle position if it is found to be better; otherwise no replacement is made. Using some well-studied benchmark problems with low and high dimensions, numerical simulations were used to validate the performance of the improved algorithms. Comparisons were made with four different PSO variants, two of the variants implement different local search technique while the other two do not. Results show that the improved algorithms could obtain better quality solution while demonstrating better convergence velocity and precision, stability, robustness, and global-local search ability than the competing variants. PMID:24723827

Neural-Fuzzy Digital Strategy of Continuous-Time Nonlinear Systems Using Adaptive Prediction and Random-Local-Optimization Design

Directory of Open Access Journals (Sweden)

Zhi-Ren Tsai

2013-01-01

Full Text Available A tracking problem, time-delay, uncertainty and stability analysis of a predictive control system are considered. The predictive control design is based on the input and output of neural plant model (NPM, and a recursive fuzzy predictive tracker has scaling factors which limit the value zone of measured data and cause the tuned parameters to converge to obtain a robust control performance. To improve the further control performance, the proposed random-local-optimization design (RLO for a model/controller uses offline initialization to obtain a near global optimal model/controller. Other issues are the considerations of modeling error, input-delay, sampling distortion, cost, greater flexibility, and highly reliable digital products of the model-based controller for the continuous-time (CT nonlinear system. They are solved by a recommended two-stage control design with the first-stage (offline RLO and second-stage (online adaptive steps. A theorizing method is then put forward to replace the sensitivity calculation, which reduces the calculation of Jacobin matrices of the back-propagation (BP method. Finally, the feedforward input of reference signals helps the digital fuzzy controller improve the control performance, and the technique works to control the CT systems precisely.

Evolutionary multimodal optimization using the principle of locality

KAUST Repository

Wong, Kachun; Wu, Chunho; Mok, Ricky; Peng, Chengbin; Zhang, Zhaolei

2012-01-01

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.

Evolutionary multimodal optimization using the principle of locality

KAUST Repository

Wong, Kachun

2012-07-01

The principle of locality is one of the most widely used concepts in designing computing systems. To explore the principle in evolutionary computation, crowding differential evolution is incorporated with locality for multimodal optimization. Instead of generating trial vectors randomly, the first method proposed takes advantage of spatial locality to generate trial vectors. Temporal locality is also adopted to help generate offspring in the second method proposed. Temporal and spatial locality are then applied together in the third method proposed. Numerical experiments are conducted to compare the proposed methods with the state-of-the-art methods on benchmark functions. Experimental analysis is undertaken to observe the effect of locality and the synergy between temporal locality and spatial locality. Further experiments are also conducted on two application problems. One is the varied-line-spacing holographic grating design problem, while the other is the protein structure prediction problem. The numerical results demonstrate the effectiveness of the methods proposed. © 2012 Elsevier Inc. All rights reserved.

Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.

Science.gov (United States)

Han, Yina; Yang, Kunde; Ma, Yuanliang; Liu, Guizhong

2014-01-01

Our objective is to train support vector machines (SVM)-based localized multiple kernel learning (LMKL), using the alternating optimization between the standard SVM solvers with the local combination of base kernels and the sample-specific kernel weights. The advantage of alternating optimization developed from the state-of-the-art MKL is the SVM-tied overall complexity and the simultaneous optimization on both the kernel weights and the classifier. Unfortunately, in LMKL, the sample-specific character makes the updating of kernel weights a difficult quadratic nonconvex problem. In this paper, starting from a new primal-dual equivalence, the canonical objective on which state-of-the-art methods are based is first decomposed into an ensemble of objectives corresponding to each sample, namely, sample-wise objectives. Then, the associated sample-wise alternating optimization method is conducted, in which the localized kernel weights can be independently obtained by solving their exclusive sample-wise objectives, either linear programming (for l1-norm) or with closed-form solutions (for lp-norm). At test time, the learnt kernel weights for the training data are deployed based on the nearest-neighbor rule. Hence, to guarantee their generality among the test part, we introduce the neighborhood information and incorporate it into the empirical loss when deriving the sample-wise objectives. Extensive experiments on four benchmark machine learning datasets and two real-world computer vision datasets demonstrate the effectiveness and efficiency of the proposed algorithm.

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

International Nuclear Information System (INIS)

Sidiropoulos, Epaminondas

2014-01-01

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

Forward and backward dynamics in implicitly defined overlapping generations models

NARCIS (Netherlands)

Gardini, L.; Hommes, C.; Tramontana, F.; de Vilder, R.

2009-01-01

In dynamic economic models derived from optimization principles, the forward equilibrium dynamics may not be uniquely defined, while the backward dynamics is well defined. We derive properties of the global forward equilibrium paths based on properties of the backward dynamics. We propose the

Design of an integrated forward and reverse logistics network optimi-zation model for commercial goods management

Directory of Open Access Journals (Sweden)

Eva Ponce-Cueto

2015-01-01

Full Text Available In this study, an optimization model is formulated for designing an integrated forward and reverse logistics network in the consumer goods industry. The resultant model is a mixed-integer linear programming model (MILP. Its purpose is to minimize the total costs of the closed-loop supply chain network. It is important to note that the design of the logistics network may involve a trade-off between the total costs and the optimality in commercial goods management. The model comprises a discrete set as potential locations of unlimited capacity warehouses and fixed locations of customers’ zones. It provides decisions related to the facility location and customers’ requirements satisfaction, all of this related with the inventory and shipment decisions of the supply chain. Finally, an application of this model is illustrated by a real-life case in the food and drinks industry. We can conclude that this model can significantly help companies to make decisions about problems associated with logistics network design.

Interactive Cosegmentation Using Global and Local Energy Optimization

OpenAIRE

Xingping Dong,; Jianbing Shen,; Shao, Ling; Yang, Ming-Hsuan

2015-01-01

We propose a novel interactive cosegmentation method using global and local energy optimization. The global energy includes two terms: 1) the global scribbled energy and 2) the interimage energy. The first one utilizes the user scribbles to build the Gaussian mixture model and improve the cosegmentation performance. The second one is a global constraint, which attempts to match the histograms of common objects. To minimize the local energy, we apply the spline regression to learn the smoothne...

Model Optimization Identification Method Based on Closed-loop Operation Data and Process Characteristics Parameters

Directory of Open Access Journals (Sweden)

Zhiqiang GENG

2014-01-01

Full Text Available Output noise is strongly related to input in closed-loop control system, which makes model identification of closed-loop difficult, even unidentified in practice. The forward channel model is chosen to isolate disturbance from the output noise to input, and identified by optimization the dynamic characteristics of the process based on closed-loop operation data. The characteristics parameters of the process, such as dead time and time constant, are calculated and estimated based on the PI/PID controller parameters and closed-loop process input/output data. And those characteristics parameters are adopted to define the search space of the optimization identification algorithm. PSO-SQP optimization algorithm is applied to integrate the global search ability of PSO with the local search ability of SQP to identify the model parameters of forward channel. The validity of proposed method has been verified by the simulation. The practicability is checked with the PI/PID controller parameter turning based on identified forward channel model.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

Science.gov (United States)

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Island development: Local governance under globalization

Directory of Open Access Journals (Sweden)

Huei-Min Tsai

2014-12-01

Full Text Available Issues surrounding island development have generated a growing volume of research. What does it mean to develop? How can island communities maintain control over development processes to the benefit of the local economy, rather than seeing economic flows enter and exit the island with little or a primarily negative impact? And how important is local knowledge for edifying local governance and enhancing potentials for innovation in island development? Island histories have repeatedly been forwarded as exemplars and ‘lessons’ for global learning on (unsustainability. To consider these issues, we have selected a number of papers from among the presentations given at the International Geographical Union’s Commission on Islands Conference, Island Development: Local Economy, Culture, Innovation and Sustainability, which took place in the Penghu Archipelago, Taiwan, 1–5 October 2013. These papers serve as examples of how the processes of globalization have penetrated the borders and changed the political and economic structures of islands. They also explore how island-based innovations in science, technology, culture, and formal or informal governance might contribute to sustainable island development.

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

Science.gov (United States)

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

Data-driven forward model inference for EEG brain imaging

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

2016-01-01

Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

AN INVESTIGATION OF LOCAL EFFECTS ON SURFACE WARMING WITH GEOGRAPHICALLY WEIGHTED REGRESSION (GWR

Directory of Open Access Journals (Sweden)

Y. Xue

2012-07-01

Full Text Available Urban warming is sensitive to the nature (thermal properties, including albedo, water content, heat capacity and thermal conductivity and the placement (surface geometry or urban topography of urban surface. In the literature the spatial dependence and heterogeneity of urban thermal landscape is widely observed based on thermal infrared remote sensing within the urban environment. Urban surface warming is conceived as a big contribution to urban warming, the study of urban surface warming possesses significant meaning for probing into the problem of urban warming.The urban thermal landscape study takes advantage of the continuous surface derived from thermal infrared remote sensing at the landscape scale, the detailed variation of local surface temperature can be measured and analyzed through the systematic investigation. At the same time urban environmental factors can be quantified with remote sensing and GIS techniques. This enables a systematic investigation of urban thermal landscape with a link to be established between local environmental setting and surface temperature variation. The goal of this research is utilizing Geographically Weighted Regression (GWR to analyze the spatial relationship between urban form and surface temperature variation in order to clarify the local effects on surface warming, moreover to reveal the possible dynamics in the local influences of environmental indicators on the variation of local surface temperature across space and time. In this research, GWR analysis proved that the spatial variation in relationships between environmental setting and surface temperature was significant with Monte Carlo significance test and distinctive in day-night change. Comparatively, GWR facilitated the site specific investigation based on local statistical technique. The inference based on GWR model provided enriched information regarding the spatial variation of local environment effect on surface temperature variation which

Surveying and Mapping Geographical Information from the Perspective of Geography

Directory of Open Access Journals (Sweden)

LÜ Guonian

2017-10-01

Full Text Available It briefly reviewed the history of geographic information content development since the existence of geographic information system. It pointed out that the current definition of geographic information is always the extension from the "spatial+ attributes" basic mapping framework of geographic information. It is increasingly difficult to adapt to the analysis and application of spatial-temporal big data. From the perspective of geography research subject and content, it summarized systematically that the content and extension of the "geographic information" that geography needs. It put forward that a six-element expression model of geographic information, including spatial location, semantic description, attribute characteristics, geometric form, evolution process, and objects relationship.Under the guidance of the laws of geography, for geographical phenomenon of spatial distribution, temporal pattern and evolution process, the interaction mechanism of the integrated expression, system analysis and efficient management, it designed that a unified GIS data model which is expressed by six basic elements, a new GIS data structure driven by geographical rules and interaction, and key technologies of unstructured spatio-temporal data organization and storage. It provided that a theoretical basis and technical support for the shift from the surveying and mapping geographic information to the scientific geographic information, and it can help improving the organization, management, analysis and expression ability of the GIS of the geographical laws such as geographical pattern, evolution process, and interaction between elements.

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.

Context-Aware Local Optimization of Sensor Network Deployment

Directory of Open Access Journals (Sweden)

Meysam Argany

2015-07-01

Full Text Available Wireless sensor networks are increasingly used for tracking and monitoring dynamic phenomena in urban and natural areas. Spatial coverage is an important issue in sensor networks in order to fulfill the needs of sensing applications. Optimization methods are widely used to efficiently distribute sensor nodes in the network to achieve a desired level of coverage. Most of the existing algorithms do not consider the characteristics of the real environment in the optimization process. In this paper, we propose the integration of contextual information in optimization algorithms to improve sensor network coverage. First, we investigate the implication of contextual information in sensor networks. Then, a conceptual framework for local context-aware sensor network deployment optimization method is introduced and related algorithms are presented in detail. Finally, several experiments are carried out to evaluate the validity of the proposed method. The results obtained from these experiments show the effectiveness of our approach in different contextual situations.

Engineering local optimality in quantum Monte Carlo algorithms

Science.gov (United States)

Pollet, Lode; Van Houcke, Kris; Rombouts, Stefan M. A.

2007-08-01

Quantum Monte Carlo algorithms based on a world-line representation such as the worm algorithm and the directed loop algorithm are among the most powerful numerical techniques for the simulation of non-frustrated spin models and of bosonic models. Both algorithms work in the grand-canonical ensemble and can have a winding number larger than zero. However, they retain a lot of intrinsic degrees of freedom which can be used to optimize the algorithm. We let us guide by the rigorous statements on the globally optimal form of Markov chain Monte Carlo simulations in order to devise a locally optimal formulation of the worm algorithm while incorporating ideas from the directed loop algorithm. We provide numerical examples for the soft-core Bose-Hubbard model and various spin- S models.

Local knowledge, use pattern and geographical distribution of Moringa oleifera Lam. (Moringaceae) in Nigeria.

Science.gov (United States)

Popoola, Jacob O; Obembe, Olawole O

2013-11-25

All parts of Moringa oleifera are medicinally valuable with overlapping uses in treating myriads of ailments and diseases including body pains and weakness, fever, asthma, cough, blood pressure, arthritis, diabetes, epilepsy, wound, and skin infection. Moringa also has robust ability to challenge terminal diseases such as HIV/AIDs infections, chronic anemia, cancer, malaria and hemorrhage. The present study was to obtain ethnobotanical information on the use and local knowledge variation, geographical distribution, and to collect different landraces of Moringa oleifera from the different agro-ecological regions in Nigeria, for further studies. Ethnobotanical data were collected through face to face interviews, semi structured questionnaires and discussions with selected people who had knowledge about the plant. The fidelity level (FL %) and use value for different use categories of Moringa oleifera and its parts were estimated. The variation in ethnobotanical knowledge was evaluated by comparing the mean use value among ethnic, gender and age groups using sample T test. Garmi GPS was used to determine the locations (latitude and longitude) and height in different areas to assess the geographical spread of the species. Seven (7) categories of use (Food, medicine, fodder, fencing, firewood, gum and coagulant) were recorded for Moringa oleifera. Food and medicinal uses showed highest fidelity level while the leaves and the seeds were the plant parts most utilized for the same purposes. There were significant differences among the ethnic, gender and age groups regarding the ethno-botanical use value. The geographical distribution pattern shows that the Moringa oleifera is well distributed in all ecological zones of Nigeria, well adapted to the varied climatic conditions and gaining unprecedented awareness among the people. Though considered an introduced species, Moringa oleifera has found wide acceptance, recognition and usefulness among the various ethnicities in the

Genetic local search algorithm for optimization design of diffractive optical elements.

Science.gov (United States)

Zhou, G; Chen, Y; Wang, Z; Song, H

1999-07-10

We propose a genetic local search algorithm (GLSA) for the optimization design of diffractive optical elements (DOE's). This hybrid algorithm incorporates advantages of both genetic algorithm (GA) and local search techniques. It appears better able to locate the global minimum compared with a canonical GA. Sample cases investigated here include the optimization design of binary-phase Dammann gratings, continuous surface-relief grating array generators, and a uniform top-hat focal plane intensity profile generator. Two GLSA's whose incorporated local search techniques are the hill-climbing method and the simulated annealing algorithm are investigated. Numerical experimental results demonstrate that the proposed algorithm is highly efficient and robust. DOE's that have high diffraction efficiency and excellent uniformity can be achieved by use of the algorithm we propose.

Technoeconomic Optimization of Waste Heat Driven Forward Osmosis for Flue Gas Desulfurization Wastewater Treatment

Energy Technology Data Exchange (ETDEWEB)

Gingerich, Daniel B [Carnegie Mellon Univ., Pittsburgh, PA (United States); Bartholomew, Timothy V [Carnegie Mellon Univ., Pittsburgh, PA (United States); Mauter, Meagan S [Carnegie Mellon Univ., Pittsburgh, PA (United States)

2017-06-26

With the Environmental Protection Agency’s recent Effluent Limitation Guidelines for Steam Electric Generators, power plants are having to install and operate new wastewater technologies. Many plants are evaluating desalination technologies as possible compliance options. However, the desalination technologies under review that can reduce wastewater volume or treat to a zero-liquid discharges standard have a significant energy penalty to the plant. Waste heat, available from the exhaust gas or cooling water from coal-fired power plants, offers an opportunity to drive wastewater treatment using thermal desalination technologies. One such technology is forward osmosis (FO). Forward osmosis utilizes an osmotic pressure gradient to passively pull water from a saline or wastewater stream across a semi-permeable membrane and into a more concentrated draw solution. This diluted draw solution is then fed into a distillation column, where the addition of low temperature waste heat can drive the separation to produce a reconcentrated draw solution and treated water for internal plant reuse. The use of low-temperature waste heat decouples water treatment from electricity production and eliminates the link between reducing water pollution and increasing air emissions from auxiliary electricity generation. In order to evaluate the feasibility of waste heat driven FO, we first build a model of an FO system for flue gas desulfurization (FGD) wastewater treatment at coal-fired power plants. This model includes the FO membrane module, the distillation column for draw solution recovery, and waste heat recovery from the exhaust gas. We then add a costing model to account for capital and operating costs of the forward osmosis system. We use this techno-economic model to optimize waste heat driven FO for the treatment of FGD wastewater. We apply this model to three case studies: the National Energy Technology Laboratory (NETL) 550 MW model coal fired power plant without carbon

Global-local optimization of flapping kinematics in hovering flight

KAUST Repository

Ghommem, Mehdi; Hajj, M. R.; Mook, Dean T.; Stanford, Bret K.; Bé ran, Philip S.; Watson, Layne T.

2013-01-01

The kinematics of a hovering wing are optimized by combining the 2-d unsteady vortex lattice method with a hybrid of global and local optimization algorithms. The objective is to minimize the required aerodynamic power under a lift constraint. The hybrid optimization is used to efficiently navigate the complex design space due to wing-wake interference present in hovering aerodynamics. The flapping wing is chosen so that its chord length and flapping frequency match the morphological and flight properties of two insects with different masses. The results suggest that imposing a delay between the different oscillatory motions defining the flapping kinematics, and controlling the way through which the wing rotates at the end of each half stroke can improve aerodynamic power under a lift constraint. Furthermore, our optimization analysis identified optimal kinematics that agree fairly well with observed insect kinematics, as well as previously published numerical results.

Global-local optimization of flapping kinematics in hovering flight

KAUST Repository

Ghommem, Mehdi

2013-06-01

The kinematics of a hovering wing are optimized by combining the 2-d unsteady vortex lattice method with a hybrid of global and local optimization algorithms. The objective is to minimize the required aerodynamic power under a lift constraint. The hybrid optimization is used to efficiently navigate the complex design space due to wing-wake interference present in hovering aerodynamics. The flapping wing is chosen so that its chord length and flapping frequency match the morphological and flight properties of two insects with different masses. The results suggest that imposing a delay between the different oscillatory motions defining the flapping kinematics, and controlling the way through which the wing rotates at the end of each half stroke can improve aerodynamic power under a lift constraint. Furthermore, our optimization analysis identified optimal kinematics that agree fairly well with observed insect kinematics, as well as previously published numerical results.

First-principle optimal local pseudopotentials construction via optimized effective potential method

International Nuclear Information System (INIS)

Mi, Wenhui; Zhang, Shoutao; Wang, Yanchao; Ma, Yanming; Miao, Maosheng

2016-01-01

The local pseudopotential (LPP) is an important component of orbital-free density functional theory, a promising large-scale simulation method that can maintain information on a material’s electron state. The LPP is usually extracted from solid-state density functional theory calculations, thereby it is difficult to assess its transferability to cases involving very different chemical environments. Here, we reveal a fundamental relation between the first-principles norm-conserving pseudopotential (NCPP) and the LPP. On the basis of this relationship, we demonstrate that the LPP can be constructed optimally from the NCPP for a large number of elements using the optimized effective potential method. Specially, our method provides a unified scheme for constructing and assessing the LPP within the framework of first-principles pseudopotentials. Our practice reveals that the existence of a valid LPP with high transferability may strongly depend on the element.

Topology optimization of nanoparticles for localized electromagnetic field enhancement

DEFF Research Database (Denmark)

Christiansen, Rasmus Ellebæk; Vester-Petersen, Joakim; Madsen, Søren Peder

2017-01-01

We consider the design of individual and periodic arrangements of metal or semiconductor nanoparticles for localized electromagnetic field enhancement utilizing a topology optimization based numerical framework as the design tool. We aim at maximizing a function of the electromagnetic field...

Development and optimization of power plant concepts for local wet fuels

Energy Technology Data Exchange (ETDEWEB)

Raiko, M.O.; Gronfors, T.H.A. [Fortum Energy Solutions, Fortum (Finland); Haukka, P. [Tampere University of Technology (Finland)

2003-01-01

Many changes in business drivers are now affecting power-producing companies. The power market has been opened up and the number of locally operating companies has increased. At the same time the need to utilize locally produced biofuels is increasing because of environmental benefits and regulations. In this situation, power-producing companies have on focus their in-house skills for generating a competitive edge over their rivals, such as the skills needed for developing the most economical energy investments for the best-paying customer for the local biomass producers. This paper explores the role of optimization in the development of small-sized energy investments. The paper provides an overview on a new design process for power companies for improved use of in-house technical and business expertise. As an example, illustrative design and optimization of local wet peat-based power investment is presented. Three concept alternatives are generated. Only power plant production capacity and peat moisture content are optimized for all alternatives. Long commercial experience of using peat as a power plant fuel in Finland can be transferred to bioenergy investments. In this paper, it is shown that conventional technology can be feasible for bioenergy production even in quite small size (below 10 MW). It is important to optimize simultaneously both the technology and the two businesses, power production and fuel production. Further, such high moisture content biomass as sludge, seaweed, grass, etc. can be economical fuels, if advanced drying systems are adopted in a power plant. (author)

The role of local environment and geographical distance in determining community composition of arbuscular mycorrhizal fungi at the landscape scale.

Science.gov (United States)

Hazard, Christina; Gosling, Paul; van der Gast, Christopher J; Mitchell, Derek T; Doohan, Fiona M; Bending, Gary D

2013-03-01

Arbuscular fungi have a major role in directing the functioning of terrestrial ecosystems yet little is known about their biogeographical distribution. The Baas-Becking hypothesis ('everything is everywhere, but, the environment selects') was tested by investigating the distribution of arbuscular mycorrhizal fungi (AMF) at the landscape scale and the influence of environmental factors and geographical distance in determining community composition. AMF communities in Trifolium repens and Lolium perenne roots were assessed in 40 geographically dispersed sites in Ireland representing different land uses and soil types. Field sampling and laboratory bioassays were used, with AMF communities characterised using 18S rRNA terminal-restriction fragment length polymorphism. Landscape-scale distribution of AMF was driven by the local environment. AMF community composition was influenced by abiotic variables (pH, rainfall and soil type), but not land use or geographical distance. Trifolium repens and L. perenne supported contrasting communities of AMF, and the communities colonising each plant species were consistent across pasture habitats and over distance. Furthermore, L. perenne AMF communities grouped by soil type within pasture habitats. This is the largest and most comprehensive study that has investigated the landscape-scale distribution of AMF. Our findings support the Baas-Becking hypothesis at the landscape scale and demonstrate the strong influence the local environment has on determining AMF community composition.

Topology Optimization of Continuum Structures with Local Stress Constraints

DEFF Research Database (Denmark)

Duysinx, Pierre; Bendsøe, Martin P

1998-01-01

We introduce an extension of current technologies for topology optimization of continuum structures which allows for treating local stress criteria. We first consider relevant stress criteria for porous composite materials, initially by studying the stress states of the so-called rank 2 layered m...

Improved Genetic Algorithm Optimization for Forward Vehicle Detection Problems

Directory of Open Access Journals (Sweden)

Longhui Gang

2015-07-01

Full Text Available Automated forward vehicle detection is an integral component of many advanced driver-assistance systems. The method based on multi-visual information fusion, with its exclusive advantages, has become one of the important topics in this research field. During the whole detection process, there are two key points that should to be resolved. One is to find the robust features for identification and the other is to apply an efficient algorithm for training the model designed with multi-information. This paper presents an adaptive SVM (Support Vector Machine model to detect vehicle with range estimation using an on-board camera. Due to the extrinsic factors such as shadows and illumination, we pay more attention to enhancing the system with several robust features extracted from a real driving environment. Then, with the introduction of an improved genetic algorithm, the features are fused efficiently by the proposed SVM model. In order to apply the model in the forward collision warning system, longitudinal distance information is provided simultaneously. The proposed method is successfully implemented on a test car and evaluation experimental results show reliability in terms of both the detection rate and potential effectiveness in a real-driving environment.

Cross hedging and forward-contract pricing of electricity

International Nuclear Information System (INIS)

Woo, C.-K.; Hoang, K.; Horowitz, I.

2001-01-01

We consider the problem of an electric-power marketer offering a fixed-price forward contract to provide electricity that it purchases from a potentially volatile and unpredictable fledgling spot energy market. One option for the risk-averse marketer who wants to hedge against the spot-price volatility is to engage in cross hedging to reduce the contract's profit variance, and to determine the forward-contract price as a risk-adjusted price - the sum of a baseline price and a risk premium. We show how the marketer can estimate the spot-price relationship between two wholesale energy markets for the purpose of cross hedging, as well as the optimal hedge and the forward contract's baseline price and risk premium

Modeling global and local dependence in a pair of commodity forward curves with an application to the US natural gas and heating oil markets

International Nuclear Information System (INIS)

Ohana, Steve

2010-01-01

The goal of this paper is to present a model for the joint evolution of correlated commodity forward curves. Each forward curve is directed by two state variables, namely slope and level, and the model is meant to capture both the local and global dependence structures between slopes and levels. Our framework can be interpreted as an extension of the concept of cointegration to forward curves. The model is applied to a US database of heating oil and natural gas futures prices over the period February 2000-February 2009. We find the long-run slope and level relationships between natural gas and heating oil markets, analyze the lead and lag properties between the two energy commodities, the volatilities and correlations between their daily co-movements and evaluate the robustness of these observations to the turmoil experienced by energy markets since 2003. (author)

Optimal Control of a Surge-Mode WEC in Random Waves

Energy Technology Data Exchange (ETDEWEB)

Chertok, Allan [Resolute Marine Energy, Inc., Boston, MA (United States); Ceberio, Olivier [Resolute Marine Energy, Inc., Boston, MA (United States); Staby, Bill [Resolute Marine Energy, Inc., Boston, MA (United States); Previsic, Mirko [Re Vision Consulting, Sacramento, CA (United States); Scruggs, Jeffrey [Univ. of Michigan, Ann Arbor, MI (United States); Van de Ven, James [Univ. of Minnesota, Minneapolis, MN (United States)

2016-08-30

The objective of this project was to develop one or more real-time feedback and feed-forward (MPC) control algorithms for an Oscillating Surge Wave Converter (OSWC) developed by RME called SurgeWEC™ that leverages recent innovations in wave energy converter (WEC) control theory to maximize power production in random wave environments. The control algorithms synthesized innovations in dynamic programming and nonlinear wave dynamics using anticipatory wave sensors and localized sensor measurements; e.g. position and velocity of the WEC Power Take Off (PTO), with predictive wave forecasting data. The result was an advanced control system that uses feedback or feed-forward data from an array of sensor channels comprised of both localized and deployed sensors fused into a single decision process that optimally compensates for uncertainties in the system dynamics, wave forecasts, and sensor measurement errors.

Effect of Local Junction Losses in the Optimization of T-shaped Flow Channels

Science.gov (United States)

Kosaraju, Srinivas

2015-11-01

T-shaped channels are extensively used in flow distribution applications such as irrigation, chemical dispersion, gas pipelines and space heating and cooling. The geometry of T-shaped channels can be optimized to reduce the overall pressure drop in stem and branch sections. Results of such optimizations are in the form of geometric parameters such as the length and diameter ratios of the stem and branch sections. The traditional approach of this optimization accounts for the pressure drop across the stem and branch sections, however, ignores the pressure drop in the T-junction. In this paper, we conduct geometry optimization while including the effect of local junction losses in laminar flows. From the results, we are able to identify a non-dimensional parameter that can be used to predict the optimal geometric configurations. This parameter can also be used to identify the conditions in which the local junction losses can be ignored during the optimization.

Brain Imaging, Forward Inference, and Theories of Reasoning

Science.gov (United States)

Heit, Evan

2015-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities. PMID:25620926

Brain imaging, forward inference, and theories of reasoning.

Science.gov (United States)

Heit, Evan

2014-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

Directory of Open Access Journals (Sweden)

Xiaohua Nie

2017-01-01

Full Text Available Cat Swarm Optimization (CSO algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

Science.gov (United States)

Nie, Xiaohua; Wang, Wei; Nie, Haoyao

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

Science.gov (United States)

Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward

2017-03-01

Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.

Optimal dietary patterns designed from local foods to achieve maternal nutritional goals.

Science.gov (United States)

Raymond, Jofrey; Kassim, Neema; Rose, Jerman W; Agaba, Morris

2018-04-04

Achieving nutritional requirements for pregnant and lactating mothers in rural households while maintaining the intake of local and culture-specific foods can be a difficult task. Deploying a linear goal programming approach can effectively generate optimal dietary patterns that incorporate local and culturally acceptable diets. The primary objective of this study was to determine whether a realistic and affordable diet that achieves nutritional goals for rural pregnant and lactating women can be formulated from locally available foods in Tanzania. A cross sectional study was conducted to assess dietary intakes of 150 pregnant and lactating women using a weighed dietary record (WDR), 24 h dietary recalls and a 7-days food record. A market survey was also carried out to estimate the cost per 100 g of edible portion of foods that are frequently consumed in the study population. Dietary survey and market data were then used to define linear programming (LP) model parameters for diet optimisation. All LP analyses were done using linear program solver to generate optimal dietary patterns. Our findings showed that optimal dietary patterns designed from locally available foods would improve dietary adequacy for 15 and 19 selected nutrients in pregnant and lactating women, respectively, but inadequacies remained for iron, zinc, folate, pantothenic acid, and vitamin E, indicating that these are problem nutrients (nutrients that did not achieve 100% of their RNIs in optimised diets) in the study population. These findings suggest that optimal use of local foods can improve dietary adequacy for rural pregnant and lactating women aged 19-50 years. However, additional cost-effective interventions are needed to ensure adequate intakes for the identified problem nutrients.

Results and Error Estimates from GRACE Forward Modeling over Antarctica

Science.gov (United States)

Bonin, Jennifer; Chambers, Don

2013-04-01

Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Antarctica. However when tested previously, the least squares technique has required constraints in the form of added process noise in order to be reliable. Poor choice of local basin layout has also adversely affected results, as has the choice of spatial smoothing used with GRACE. To develop design parameters which will result in correct high-resolution mass detection and to estimate the systematic errors of the method over Antarctica, we use a "truth" simulation of the Antarctic signal. We apply the optimal parameters found from the simulation to RL05 GRACE data across Antarctica and the surrounding ocean. We particularly focus on separating the Antarctic peninsula's mass signal from that of the rest of western Antarctica. Additionally, we characterize how well the technique works for removing land leakage signal from the nearby ocean, particularly that near the Drake Passage.

Analysis of the interaction of participants freight forwarding system

Directory of Open Access Journals (Sweden)

Pavlo Popovych

2016-12-01

Full Text Available Main goal of this work is the analysis of the interaction of participants of freight forwarding activities. Research methods included analysis of scientific literature, theory of systems and systems analysis, methods of induction and deduction. As sources of information used and applied work of fundamental importance known foreign and local scientists and regulatory and legislative documents of Ukraine for the state transport policy. In the article the basic interactions of participants of freight forwarding activities. Classified components freight forwarding services. Assign the concept freight forwarding system and its aim. Established element and forms of cooperation in the freight forwarding system. The main task of forwarding companies are organizing, coordinating and ensuring the delivery from shipper to consignee. Freight forwarding company responsible for the timely delivery of the goods on the condition of preservation of the quantity and quality specified time conditions. Currently used methods are uneffective decision-making, leading to losses. These circumstances require improvement methodology management of freight forwarding companies. This is possible only using modern mathematical methods and information technologies that will improve the operation of freight forwarding companies. The article presents a theoretical exposition of the basic processes of interaction between participants in freight forwarding system. The article may be of interest to specialists of freight forwarding companies.

Geographic Information Systems In Strategic Decision Making In Logistics Companies

Directory of Open Access Journals (Sweden)

Dr. Filiz Gürder

2013-07-01

Geographic information systems can make important contributions to logistic companies in the following areas: Routing, Optimization and Scheduling, Asset Tracking, Dispatching/Mobile, Territory Optimization and Planning, Site Selection and Optimization, Supply Chain Management, and Selecting the Supplier.

a Geographic Analysis of Optimal Signage Location Selection in Scenic Area

Science.gov (United States)

Ruan, Ling; Long, Ying; Zhang, Ling; Wu, Xiao Ling

2016-06-01

As an important part of the scenic area infrastructure services, signage guiding system plays an indispensable role in guiding the way and improving the quality of tourism experience. This paper proposes an optimal method in signage location selection and direction content design in a scenic area based on geographic analysis. The object of the research is to provide a best solution to arrange limited guiding boards in a tourism area to show ways arriving at any scenic spot from any entrance. There are four steps to achieve the research object. First, the spatial distribution of the junction of the scenic road, the passageway and the scenic spots is analyzed. Then, the count of scenic roads intersection on the shortest path between all entrances and all scenic spots is calculated. Next, combing with the grade of the scenic road and scenic spots, the importance of each road intersection is estimated quantitatively. Finally, according to the importance of all road intersections, the most suitable layout locations of signage guiding boards can be provided. In addition, the method is applied in the Ming Tomb scenic area in China and the result is compared with the existing signage guiding space layout.

Reinforcement active learning in the vibrissae system: optimal object localization.

Science.gov (United States)

Gordon, Goren; Dorfman, Nimrod; Ahissar, Ehud

2013-01-01

Rats move their whiskers to acquire information about their environment. It has been observed that they palpate novel objects and objects they are required to localize in space. We analyze whisker-based object localization using two complementary paradigms, namely, active learning and intrinsic-reward reinforcement learning. Active learning algorithms select the next training samples according to the hypothesized solution in order to better discriminate between correct and incorrect labels. Intrinsic-reward reinforcement learning uses prediction errors as the reward to an actor-critic design, such that behavior converges to the one that optimizes the learning process. We show that in the context of object localization, the two paradigms result in palpation whisking as their respective optimal solution. These results suggest that rats may employ principles of active learning and/or intrinsic reward in tactile exploration and can guide future research to seek the underlying neuronal mechanisms that implement them. Furthermore, these paradigms are easily transferable to biomimetic whisker-based artificial sensors and can improve the active exploration of their environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimizing a magnetic resonance care pathway: A strategy for radiography managers

International Nuclear Information System (INIS)

Castillo, J.; Caruana, C.J.; Morgan, P.S.; Westbrook, C.

2015-01-01

Purpose: This study reports the optimization of a local MR care pathway. A search of the literature did not result in any studies regarding the optimization of MRI care pathways through a formal research process. Discussions with international MR radiographers indicated that such development is often carried out using informal methods that are highly dependent on local conditions, that are rarely reported in the public domain and the validities of which are therefore not open to scrutiny; in addition, care pathways need to be specific to local healthcare needs and culture. In this study, the authors propose a formal documented methodology for developing a local MRI care pathway based on the well-established nominal group technique. Methods and materials: A nominal group technique was conducted amongst a multi-professional panel. Results: 14 participants accepted the invitation to participate: an executive from the principal public general hospital, a manager from the national Ministry for Health, a service development manager from the allied healthcare professional sector, 2 senior physiotherapists, 3 nursing officers, 3 MRI radiographers, 2 medical physicists, 1 radiologist. Ten optimization related issues were identified and ranked in order of decreasing importance. Highest ranking scores were assigned to patient safety, education of referrers and use of quality criteria. The NGT method also brought forward novel themes in particular the need for a radiographer's technical report and the need for referrers to indicate pain levels of patients. Conclusion: The design of an MR care pathway was successfully optimized using a collaborative multi-stakeholder approach. - Highlights: • We optimized an MRI clinical pathway using a nominal group technique. • The NGT brought forward novel themes such as the introduction of radiographer technical report. • The MRI clinical pathway will help management to establish knowledge, skills and competences. �

Cross hedging and forward-contract pricing of electricity

Energy Technology Data Exchange (ETDEWEB)

Woo, C.-K.; Hoang, K. [Energy and Environmental Economics, Inc., 353 Sacramento Street, Suite 1700, 94111 San Francisco, CA (United States); Horowitz, I. [Decision and Information Sciences, Warrington College of Business Administration, University of Florida, 32611 Gainesville, FL (United States)

2001-01-01

We consider the problem of an electric-power marketer offering a fixed-price forward contract to provide electricity that it purchases from a potentially volatile and unpredictable fledgling spot energy market. One option for the risk-averse marketer who wants to hedge against the spot-price volatility is to engage in cross hedging to reduce the contract's profit variance, and to determine the forward-contract price as a risk-adjusted price - the sum of a baseline price and a risk premium. We show how the marketer can estimate the spot-price relationship between two wholesale energy markets for the purpose of cross hedging, as well as the optimal hedge and the forward contract's baseline price and risk premium.

Optimalization of Beacon Selection for Localization in Wireless AD-HOC Networks

Directory of Open Access Journals (Sweden)

Martin Matula

2008-01-01

Full Text Available In this paper we engage in optimalization of convenient beacons for localization position of a node in the ad-hoc network. An algorithm designed by us localizes position of moving or static node by RSS (Received Signal Strength method and trilateration. At first, localization of unknown node runs by combination of all beacons. Than optimalizating algorithmreduces the number of beacons (and repeats localization, while only three left. Its reduction is based on highest levels of received signal strength. It is only when signals are from the nearest beacons. Position localizating exactness is statistically interpreted from all localization by beacons combination and its repeating.

Globally-Optimized Local Pseudopotentials for (Orbital-Free) Density Functional Theory Simulations of Liquids and Solids.

Science.gov (United States)

Del Rio, Beatriz G; Dieterich, Johannes M; Carter, Emily A

2017-08-08

The accuracy of local pseudopotentials (LPSs) is one of two major determinants of the fidelity of orbital-free density functional theory (OFDFT) simulations. We present a global optimization strategy for LPSs that enables OFDFT to reproduce solid and liquid properties obtained from Kohn-Sham DFT. Our optimization strategy can fit arbitrary properties from both solid and liquid phases, so the resulting globally optimized local pseudopotentials (goLPSs) can be used in solid and/or liquid-phase simulations depending on the fitting process. We show three test cases proving that we can (1) improve solid properties compared to our previous bulk-derived local pseudopotential generation scheme; (2) refine predicted liquid and solid properties by adding force matching data; and (3) generate a from-scratch, accurate goLPS from the local channel of a non-local pseudopotential. The proposed scheme therefore serves as a full and improved LPS construction protocol.

Locally optimized separability enhancement indices for urban land cover mapping

DEFF Research Database (Denmark)

Feyisa, Gudina L.; Meilby, Henrik; Darrel Jenerette, G.

2016-01-01

data in LULC classification. To more accurately quantify landscape patterns and their changes, we applied new locally optimized separability enhancement indices and decision rules (SEI–DR approach) to address commonly observed classification accuracy problems in urban environments. We tested the SEI...

The application of particle swarm optimization to identify gamma spectrum with neural network

International Nuclear Information System (INIS)

Shi Dongsheng; Di Yuming; Zhou Chunlin

2006-01-01

Aiming at the shortcomings that BP algorithm is usually trapped to a local optimum and it has a low speed of convergence in the application of neural network to identify gamma spectrum, according to the advantage of the globe optimal searching of particle swarm optimization, this paper put forward a new algorithm for neural network training by combining BP algorithm and Particle Swarm Optimization-mixed PSO-BP algorithm. In the application to identify gamma spectrum, the new algorithm overcomes the shortcoming that BP algorithm is usually trapped to a local optimum and the neural network trained by it has a high ability of generalization with identification result of one hundred percent correct. Practical example shows that the mixed PSO-BP algorithm can effectively and reliably be used to identify gamma spectrum. (authors)

A GEOGRAPHIC ANALYSIS OF OPTIMAL SIGNAGE LOCATION SELECTION IN SCENIC AREA

Directory of Open Access Journals (Sweden)

L. Ruan

2016-06-01

Full Text Available As an important part of the scenic area infrastructure services, signage guiding system plays an indispensable role in guiding the way and improving the quality of tourism experience. This paper proposes an optimal method in signage location selection and direction content design in a scenic area based on geographic analysis. The object of the research is to provide a best solution to arrange limited guiding boards in a tourism area to show ways arriving at any scenic spot from any entrance. There are four steps to achieve the research object. First, the spatial distribution of the junction of the scenic road, the passageway and the scenic spots is analyzed. Then, the count of scenic roads intersection on the shortest path between all entrances and all scenic spots is calculated. Next, combing with the grade of the scenic road and scenic spots, the importance of each road intersection is estimated quantitatively. Finally, according to the importance of all road intersections, the most suitable layout locations of signage guiding boards can be provided. In addition, the method is applied in the Ming Tomb scenic area in China and the result is compared with the existing signage guiding space layout.

One-dimensional, forward-forward mean-field games with congestion

KAUST Repository

Gomes, Diogo A.; Sedjro, Marc

2017-01-01

forward-forward MFGs. Finally, we construct traveling-wave solutions, which settles in a negative way the convergence problem for forward-forward MFGs. A similar technique gives the existence of time-periodic solutions for non-monotonic MFGs.

Locally optimal extracellular stimulation for chaotic desynchronization of neural populations.

Science.gov (United States)

Wilson, Dan; Moehlis, Jeff

2014-10-01

We use optimal control theory to design a methodology to find locally optimal stimuli for desynchronization of a model of neurons with extracellular stimulation. This methodology yields stimuli which lead to positive Lyapunov exponents, and hence desynchronizes a neural population. We analyze this methodology in the presence of interneuron coupling to make predictions about the strength of stimulation required to overcome synchronizing effects of coupling. This methodology suggests a powerful alternative to pulsatile stimuli for deep brain stimulation as it uses less energy than pulsatile stimuli, and could eliminate the time consuming tuning process.

Optimally localized Wannier functions for quasi one-dimensional nonperiodic insulators

DEFF Research Database (Denmark)

Cornean, Horia; Nenciu, A.; Nenciu, Gheorghe

2008-01-01

It is proved that for general, not necessarily periodic, quasi one-dimensional systems the band position operator corresponding to an isolated part of the energy spectrum has discrete spectrum and its eigenfunctions have the same spatial localization as the corresponding spectral projection....... As a consequence, an eigenbasis of the band position operator provides a basis of optimally localized (generalized) Wannier functions for quasi one-dimensional systems, and this proves the strong Marzari-Vanderbilt conjecture. If the system has some translation symmetries (e.g. usual translations, screw...

Optimally localized Wannier functions for quasi one-dimensional nonperiodic insulators

DEFF Research Database (Denmark)

Cornean, Horia; Nenciu, A.; Nenciu, Gheorghe

It is proved that for general, not necessarily periodic quasi one dimensional systems, the band position operator corresponding to an isolated part of the energy spectrum has discrete spectrum and its eigenfunctions have the same spatial localization as the corresponding spectral projection....... As a consequence, an eigenbasis of the band position operator provides a basis of optimally localized (generalized) Wannier functions for quasi one dimensional systems. If the system has some translation symmetries (e.g. usual translations, screw transformations), they are "inherited" bythe Wannier basis....

A geographical analysis of the Swedish wood fuel market

International Nuclear Information System (INIS)

Roos, Anders; Bohlin, Folke; Hektor, Bo; Hillring, Bengt; Parikka, Matti

2000-01-01

The geographical variation in Swedish wood fuel market characteristics for the district heating sector has been studied using Geographical Information Systems (GIS) and cross-sectional Tobit analysis. The results indicate that local availability and competition for wood fuels influence the wood fuel consumption at inland heating plants. The factors affecting the decision to use wood fuel at heating plants close to seaports, however, were not captured by the model, suggesting that coastal location reduces dependency on the local wood fuel market. The effects of changes in local wood fuel availability on wood fuel use by an inland heating plant are presented and discussed

Health-related quality of life, optimism, and coping strategies in persons suffering from localized scleroderma.

Science.gov (United States)

Szramka-Pawlak, B; Dańczak-Pazdrowska, A; Rzepa, T; Szewczyk, A; Sadowska-Przytocka, A; Żaba, R

2013-01-01

The clinical course of localized scleroderma may consist of bodily deformations, and bodily functions may also be affected. Additionally, the secondary lesions, such as discoloration, contractures, and atrophy, are unlikely to regress. The aforementioned symptoms and functional disturbances may decrease one's quality of life (QoL). Although much has been mentioned in the medical literature regarding QoL in persons suffering from dermatologic diseases, no data specifically describing patients with localized scleroderma exist. The aim of the study was to explore QoL in localized scleroderma patients and to examine their coping strategies in regard to optimism and QoL. The study included 41 patients with localized scleroderma. QoL was evaluated using the SKINDEX questionnaire, and levels of dispositional optimism were assessed using the Life Orientation Test-Revised. In addition, individual coping strategy was determined using the Mini-MAC scale and physical condition was assessed using the Localized Scleroderma Severity Index. The mean QoL score amounted to 51.10 points, with mean scores for individual components as follows: symptoms = 13.49 points, emotions = 21.29 points, and functioning = 16.32 points. A relationship was detected between QoL and the level of dispositional optimism as well as with coping strategies known as anxious preoccupation and helplessness-hopelessness. Higher levels of optimism predicted a higher general QoL. In turn, greater intensity of anxious preoccupied and helpless-hopeless behaviors predicted a lower QoL. Based on these results, it may be stated that localized scleroderma patients have a relatively high QoL, which is accompanied by optimism as well as a lower frequency of behaviors typical of emotion-focused coping strategies.

Optimal matching for prostate brachytherapy seed localization with dimension reduction.

Science.gov (United States)

Lee, Junghoon; Labat, Christian; Jain, Ameet K; Song, Danny Y; Burdette, Everette C; Fichtinger, Gabor; Prince, Jerry L

2009-01-01

In prostate brachytherapy, x-ray fluoroscopy has been used for intra-operative dosimetry to provide qualitative assessment of implant quality. More recent developments have made possible 3D localization of the implanted radioactive seeds. This is usually modeled as an assignment problem and solved by resolving the correspondence of seeds. It is, however, NP-hard, and the problem is even harder in practice due to the significant number of hidden seeds. In this paper, we propose an algorithm that can find an optimal solution from multiple projection images with hidden seeds. It solves an equivalent problem with reduced dimensional complexity, thus allowing us to find an optimal solution in polynomial time. Simulation results show the robustness of the algorithm. It was validated on 5 phantom and 18 patient datasets, successfully localizing the seeds with detection rate of > or = 97.6% and reconstruction error of < or = 1.2 mm. This is considered to be clinically excellent performance.

Notions of local controllability and optimal feedforward control for quantum systems

International Nuclear Information System (INIS)

Chakrabarti, Raj

2011-01-01

Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

Notions of local controllability and optimal feedforward control for quantum systems

Energy Technology Data Exchange (ETDEWEB)

Chakrabarti, Raj, E-mail: rchakra@purdue.edu [School of Chemical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

2011-05-06

Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

A novel approach to find and optimize bin locations and collection routes using a geographic information system.

Science.gov (United States)

Erfani, Seyed Mohammad Hassan; Danesh, Shahnaz; Karrabi, Seyed Mohsen; Shad, Rouzbeh

2017-07-01

One of the major challenges in big cities is planning and implementation of an optimized, integrated solid waste management system. This optimization is crucial if environmental problems are to be prevented and the expenses to be reduced. A solid waste management system consists of many stages including collection, transfer and disposal. In this research, an integrated model was proposed and used to optimize two functional elements of municipal solid waste management (storage and collection systems) in the Ahmadabad neighbourhood located in the City of Mashhad - Iran. The integrated model was performed by modelling and solving the location allocation problem and capacitated vehicle routing problem (CVRP) through Geographic Information Systems (GIS). The results showed that the current collection system is not efficient owing to its incompatibility with the existing urban structure and population distribution. Application of the proposed model could significantly improve the storage and collection system. Based on the results of minimizing facilities analyses, scenarios with 100, 150 and 180 m walking distance were considered to find optimal bin locations for Alamdasht, C-metri and Koohsangi. The total number of daily collection tours was reduced to seven as compared to the eight tours carried out in the current system (12.50% reduction). In addition, the total number of required crews was minimized and reduced by 41.70% (24 crews in the current collection system vs 14 in the system provided by the model). The total collection vehicle routing was also optimized such that the total travelled distances during night and day working shifts was cut back by 53%.

Forward and backward inference in spatial cognition.

Directory of Open Access Journals (Sweden)

Will D Penny

Full Text Available This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

Energy network dispatch optimization under emergency of local energy shortage

International Nuclear Information System (INIS)

Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang

2012-01-01

The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.

Memory-efficient dynamic programming backtrace and pairwise local sequence alignment.

Science.gov (United States)

Newberg, Lee A

2008-08-15

A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward-backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis. Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10,000. Sample C++-code for optimal backtrace is available in the Supplementary Materials. Supplementary data is available at Bioinformatics online.

Optimization of Regional Geodynamic Models for Mantle Dynamics

Science.gov (United States)

Knepley, M.; Isaac, T.; Jadamec, M. A.

2016-12-01

The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.

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.

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

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.

One-dimensional, forward-forward mean-field games with congestion

KAUST Repository

Gomes, Diogo A.

2017-03-29

Here, we consider one-dimensional forward-forward mean-field games (MFGs) with congestion, which were introduced to approximate stationary MFGs. We use methods from the theory of conservation laws to examine the qualitative properties of these games. First, by computing Riemann invariants and corresponding invariant regions, we develop a method to prove lower bounds for the density. Next, by combining the lower bound with an entropy function, we prove the existence of global solutions for parabolic forward-forward MFGs. Finally, we construct traveling-wave solutions, which settles in a negative way the convergence problem for forward-forward MFGs. A similar technique gives the existence of time-periodic solutions for non-monotonic MFGs.

Geographic proximity to treatment for early stage breast cancer and likelihood of mastectomy.

Science.gov (United States)

Boscoe, Francis P; Johnson, Christopher J; Henry, Kevin A; Goldberg, Daniel W; Shahabi, Kaveh; Elkin, Elena B; Ballas, Leslie K; Cockburn, Myles

2011-08-01

Women with early stage breast cancer who live far from a radiation therapy facility may be more likely to opt for mastectomy over breast conserving surgery (BCS). The geographic dimensions of this relationship deserve further scrutiny. For over 100,000 breast cancer patients in 10 states who received either mastectomy or BCS, a newly-developed software tool was used to calculate the shortest travel distance to the location of surgery and to the nearest radiation treatment center. The likelihood of receipt of mastectomy was modeled as a function of these distance measures and other demographic variables using multilevel logistic regression. Women traveling over 75 km for treatment are about 1.4 times more likely to receive a mastectomy than those traveling under 15 km. Geographic barriers to optimal breast cancer treatment remain a valid concern, though most women traveling long distances to receive mastectomies are doing so after bypassing local options. Copyright © 2011 Elsevier Ltd. All rights reserved.

Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations & Implied Sharpe Ratio

OpenAIRE

Lorig, Matthew; Sircar, Ronnie

2015-01-01

We study the finite horizon Merton portfolio optimization problem in a general local-stochastic volatility setting. Using model coefficient expansion techniques, we derive approximations for the both the value function and the optimal investment strategy. We also analyze the `implied Sharpe ratio' and derive a series approximation for this quantity. The zeroth-order approximation of the value function and optimal investment strategy correspond to those obtained by Merton (1969) when the risky...

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-01

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

Design Optimization of Laminated Composite Structures with Many Local Strength Criteria

DEFF Research Database (Denmark)

Lund, Erik

2012-01-01

This paper presents different strategies for handling very many local strength criteria in structural optimization of laminated composites. Global strength measures using Kreisselmeier-Steinhauser or p-norm functions are introduced for patch-wise parameterizations, and the efficiency of the metho...

FuGeF: A Resource Bound Secure Forwarding Protocol for Wireless Sensor Networks.

Science.gov (United States)

Umar, Idris Abubakar; Mohd Hanapi, Zurina; Sali, A; Zulkarnain, Zuriati A

2016-06-22

Resource bound security solutions have facilitated the mitigation of spatio-temporal attacks by altering protocol semantics to provide minimal security while maintaining an acceptable level of performance. The Dynamic Window Secured Implicit Geographic Forwarding (DWSIGF) routing protocol for Wireless Sensor Network (WSN) has been proposed to achieve a minimal selection of malicious nodes by introducing a dynamic collection window period to the protocol's semantics. However, its selection scheme suffers substantial packet losses due to the utilization of a single distance based parameter for node selection. In this paper, we propose a Fuzzy-based Geographic Forwarding protocol (FuGeF) to minimize packet loss, while maintaining performance. The FuGeF utilizes a new form of dynamism and introduces three selection parameters: remaining energy, connectivity cost, and progressive distance, as well as a Fuzzy Logic System (FLS) for node selection. These introduced mechanisms ensure the appropriate selection of a non-malicious node. Extensive simulation experiments have been conducted to evaluate the performance of the proposed FuGeF protocol as compared to DWSIGF variants. The simulation results show that the proposed FuGeF outperforms the two DWSIGF variants (DWSIGF-P and DWSIGF-R) in terms of packet delivery.

Relationship between Air Pollution and Weather Conditions under Complicated Geographical conditions

Science.gov (United States)

Cheng, Q.; Jiang, P.; Li, M.

2017-12-01

Air pollution is one of the most serious issues all over the world, especially in megacities with constrained geographical conditions for air pollution diffusion. However, the dynamic mechanism of air pollution diffusion under complicated geographical conditions is still be confused. Researches to explore relationship between air pollution and weather conditions from the perspective of local atmospheric circulations can contribute more to solve such problem. We selected three megacities (Beijing, Shanghai and Guangzhou) under different geographical condition (mountain-plain transition region, coastal alluvial plain and coastal hilly terrain) to explore the relationship between air pollution and weather conditions. RDA (Redundancy analysis) model was used to analyze how the local atmospheric circulation acts on the air pollutant diffusion. The results show that there was a positive correlation between the concentration of air pollutants and air pressure, while temperature, precipitation and wind speed have negative correlations with the concentration of air pollutants. Furthermore, geographical conditions, such as topographic relief, have significant effects on the direction, path and intensity of local atmospheric circulation. As a consequence, air pollutants diffusion modes in different cities under various geographical conditions are diverse from each other.

Local-scaling density-functional method: Intraorbit and interorbit density optimizations

International Nuclear Information System (INIS)

Koga, T.; Yamamoto, Y.; Ludena, E.V.

1991-01-01

The recently proposed local-scaling density-functional theory provides us with a practical method for the direct variational determination of the electron density function ρ(r). The structure of ''orbits,'' which ensures the one-to-one correspondence between the electron density ρ(r) and the N-electron wave function Ψ({r k }), is studied in detail. For the realization of the local-scaling density-functional calculations, procedures for intraorbit and interorbit optimizations of the electron density function are proposed. These procedures are numerically illustrated for the helium atom in its ground state at the beyond-Hartree-Fock level

Parallel and Cooperative Particle Swarm Optimizer for Multimodal Problems

Directory of Open Access Journals (Sweden)

Geng Zhang

2015-01-01

Full Text Available Although the original particle swarm optimizer (PSO method and its related variant methods show some effectiveness for solving optimization problems, it may easily get trapped into local optimum especially when solving complex multimodal problems. Aiming to solve this issue, this paper puts forward a novel method called parallel and cooperative particle swarm optimizer (PCPSO. In case that the interacting of the elements in D-dimensional function vector X=[x1,x2,…,xd,…,xD] is independent, cooperative particle swarm optimizer (CPSO is used. Based on this, the PCPSO is presented to solve real problems. Since the dimension cannot be split into several lower dimensional search spaces in real problems because of the interacting of the elements, PCPSO exploits the cooperation of two parallel CPSO algorithms by orthogonal experimental design (OED learning. Firstly, the CPSO algorithm is used to generate two locally optimal vectors separately; then the OED is used to learn the merits of these two vectors and creates a better combination of them to generate further search. Experimental studies on a set of test functions show that PCPSO exhibits better robustness and converges much closer to the global optimum than several other peer algorithms.

Scalable algorithms for optimal control of stochastic PDEs

KAUST Repository

Ghattas, Omar

2016-01-07

We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.

Scalable algorithms for optimal control of stochastic PDEs

KAUST Repository

Ghattas, Omar; Alexanderian, Alen; Petra, Noemi; Stadler, Georg

2016-01-01

We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.

Asymptotically optimal data analysis for rejecting local realism

International Nuclear Information System (INIS)

Zhang, Yanbao; Glancy, Scott; Knill, Emanuel

2011-01-01

Reliable experimental demonstrations of violations of local realism are highly desirable for fundamental tests of quantum mechanics. One can quantify the violation witnessed by an experiment in terms of a statistical p value, which can be defined as the maximum probability according to local realism of a violation at least as high as that witnessed. Thus, high violation corresponds to small p value. We propose a prediction-based-ratio (PBR) analysis protocol whose p values are valid even if the prepared quantum state varies arbitrarily and local realistic models can depend on previous measurement settings and outcomes. It is therefore not subject to the memory loophole [J. Barrett et al., Phys. Rev. A 66, 042111 (2002)]. If the prepared state does not vary in time, the p values are asymptotically optimal. For comparison, we consider protocols derived from the number of standard deviations of violation of a Bell inequality and from martingale theory [R. Gill, e-print arXiv:quant-ph/0110137]. We find that the p values of the former can be too small and are therefore not statistically valid, while those derived from the latter are suboptimal. PBR p values do not require a predetermined Bell inequality and can be used to compare results from different tests of local realism independent of experimental details.

Hooke–Jeeves Method-used Local Search in a Hybrid Global Optimization Algorithm

Directory of Open Access Journals (Sweden)

V. D. Sulimov

2014-01-01

Full Text Available Modern methods for optimization investigation of complex systems are based on development and updating the mathematical models of systems because of solving the appropriate inverse problems. Input data desirable for solution are obtained from the analysis of experimentally defined consecutive characteristics for a system or a process. Causal characteristics are the sought ones to which equation coefficients of mathematical models of object, limit conditions, etc. belong. The optimization approach is one of the main ones to solve the inverse problems. In the main case it is necessary to find a global extremum of not everywhere differentiable criterion function. Global optimization methods are widely used in problems of identification and computation diagnosis system as well as in optimal control, computing to-mography, image restoration, teaching the neuron networks, other intelligence technologies. Increasingly complicated systems of optimization observed during last decades lead to more complicated mathematical models, thereby making solution of appropriate extreme problems significantly more difficult. A great deal of practical applications may have the problem con-ditions, which can restrict modeling. As a consequence, in inverse problems the criterion functions can be not everywhere differentiable and noisy. Available noise means that calculat-ing the derivatives is difficult and unreliable. It results in using the optimization methods without calculating the derivatives.An efficiency of deterministic algorithms of global optimization is significantly restrict-ed by their dependence on the extreme problem dimension. When the number of variables is large they use the stochastic global optimization algorithms. As stochastic algorithms yield too expensive solutions, so this drawback restricts their applications. Developing hybrid algo-rithms that combine a stochastic algorithm for scanning the variable space with deterministic local search

Sub-Optimal Management of Type 2 Diabetes Mellitus – A Local Audit

African Journals Online (AJOL)

Original Research: Sub-Optimal Management of Type 2 Diabetes Mellitus – A Local Audit ... despite clinical trial data documenting improved outcomes associated not ... were used to define the Metabolic Syndrome.9 Central obesity was.

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

Energy Technology Data Exchange (ETDEWEB)

Li, Dengwang; Wang, Jie [College of Physics and Electronics, Shandong Normal University, Jinan, Shandong (China); Kapp, Daniel S.; Xing, Lei [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA (United States)

2015-06-15

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

International Nuclear Information System (INIS)

Li, Dengwang; Wang, Jie; Kapp, Daniel S.; Xing, Lei

2015-01-01

Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

Impact of geographic variations of the convective and dehydration center on stratospheric water vapor over the Asian monsoon region

Directory of Open Access Journals (Sweden)

K. Zhang

2016-06-01

Full Text Available The Asian monsoon region is the most prominent moisture center of water vapor in the lower stratosphere (LS during boreal summer. Previous studies have suggested that the transport of water vapor to the Asian monsoon LS is controlled by dehydration temperatures and convection mainly over the Bay of Bengal and Southeast Asia. However, there is a clear geographic variation of convection associated with the seasonal and intra-seasonal variations of the Asian monsoon circulation, and the relative influence of such a geographic variation of convection vs. the variation of local dehydration temperatures on water vapor transport is still not clear. Using satellite observations from the Aura Microwave Limb Sounder (MLS and a domain-filling forward trajectory model, we show that almost half of the seasonal water vapor increase in the Asian monsoon LS are attributable to geographic variations of convection and resultant variations of the dehydration center, of which the influence is comparable to the influence of the local dehydration temperature increase. In particular, dehydration temperatures are coldest over the southeast and warmest over the northwest Asian monsoon region. Although the convective center is located over Southeast Asia, an anomalous increase of convection over the northwest Asia monsoon region increases local diabatic heating in the tropopause layer and air masses entering the LS are dehydrated at relatively warmer temperatures. Due to warmer dehydration temperatures, anomalously moist air enters the LS and moves eastward along the northern flank of the monsoon anticyclonic flow, leading to wet anomalies in the LS over the Asian monsoon region. Likewise, when convection increases over the Southeast Asia monsoon region, dry anomalies appear in the LS. On a seasonal scale, this feature is associated with the monsoon circulation, convection and diabatic heating marching towards the northwest Asia monsoon region from June to August. The

The National Geographic Names Data Base: Phase II instructions

Science.gov (United States)

Orth, Donald J.; Payne, Roger L.

1987-01-01

The Geographic Names Information System is a computer-based information system developed to meet major national needs by providing information for named entities in the United States, its territories, and outlying areas. The National Geographic Names Data Base, a component of the Geographic Names Information System, currently contains most names and associated information recorded on the 1:24,000-scale (or largest scale available) topographic maps of the U.S. Geological Survey. The work involved in this initial compilation of names shown on the topographic-map series, and the development and editing of the National Geographic Names Data Base, is referred to as Phase I. Optimal use and effectiveness of an automated names system require that the names of features

Moving Forward - Progress on Forward Detectors

CERN Multimedia

Grafstrom, P.

2006-01-01

You might have been sitting in some meeting hearing about the ATLAS forward detectors. Coming back to your office wanting to learn more you look in the ATLAS TDR’s and disappointingly you find nothing about forward detectors. The explanation is of course that the forward detectors are newcomers in the ATLAS detector arsenal. ATLAS is designed to measure high Pt particles with pseudo rapidities up to 5 which in terms of angles means angles bigger than one degree (0.8 degree to be more accurate). Particles produced with smaller angles close to the beam escape detection. The hole in the forward direction will now partly be filled. Several new detectors have recently been proposed. These detectors are designed for various luminosity measurements but they also have a physics potential in themselves. Closest to the IP there is LUCID (LUminosity measurement using Cerenkov Integrating Detector). LUCID comprises some 170 Cerenkov tubes sitting around the beam pipe at about 17 m away from the IP. The tubes are 1.5 ...

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

Science.gov (United States)

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Geographic body size variation in the periodical cicadas Magicicada: implications for life cycle divergence and local adaptation.

Science.gov (United States)

Koyama, T; Ito, H; Kakishima, S; Yoshimura, J; Cooley, J R; Simon, C; Sota, T

2015-06-01

Seven species in three species groups (Decim, Cassini and Decula) of periodical cicadas (Magicicada) occupy a wide latitudinal range in the eastern United States. To clarify how adult body size, a key trait affecting fitness, varies geographically with climate conditions and life cycle, we analysed the relationships of population mean head width to geographic variables (latitude, longitude, altitude), habitat annual mean temperature (AMT), life cycle and species differences. Within species, body size was larger in females than males and decreased with increasing latitude (and decreasing habitat AMT), following the converse Bergmann's rule. For the pair of recently diverged 13- and 17-year species in each group, 13-year cicadas were equal in size or slightly smaller on average than their 17-year counterparts despite their shorter developmental time. This fact suggests that, under the same climatic conditions, 17-year cicadas have lowered growth rates compared to their 13-years counterparts, allowing 13-year cicadas with faster growth rates to achieve body sizes equivalent to those of their 17-year counterparts at the same locations. However, in the Decim group, which includes two 13-year species, the more southerly, anciently diverged 13-year species (Magicicada tredecim) was characterized by a larger body size than the other, more northerly 13- and 17-year species, suggesting that local adaptation in warmer habitats may ultimately lead to evolution of larger body sizes. Our results demonstrate how geographic clines in body size may be maintained in sister species possessing different life cycles. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

RDEL: Restart Differential Evolution algorithm with Local Search Mutation for global numerical optimization

Directory of Open Access Journals (Sweden)

Ali Wagdy Mohamed

2014-11-01

Full Text Available In this paper, a novel version of Differential Evolution (DE algorithm based on a couple of local search mutation and a restart mechanism for solving global numerical optimization problems over continuous space is presented. The proposed algorithm is named as Restart Differential Evolution algorithm with Local Search Mutation (RDEL. In RDEL, inspired by Particle Swarm Optimization (PSO, a novel local mutation rule based on the position of the best and the worst individuals among the entire population of a particular generation is introduced. The novel local mutation scheme is joined with the basic mutation rule through a linear decreasing function. The proposed local mutation scheme is proven to enhance local search tendency of the basic DE and speed up the convergence. Furthermore, a restart mechanism based on random mutation scheme and a modified Breeder Genetic Algorithm (BGA mutation scheme is combined to avoid stagnation and/or premature convergence. Additionally, an exponent increased crossover probability rule and a uniform scaling factors of DE are introduced to promote the diversity of the population and to improve the search process, respectively. The performance of RDEL is investigated and compared with basic differential evolution, and state-of-the-art parameter adaptive differential evolution variants. It is discovered that the proposed modifications significantly improve the performance of DE in terms of quality of solution, efficiency and robustness.

A robust internet-based auction to procure electricity forwards

International Nuclear Information System (INIS)

Woo, C.K.; Lloyd, D.; Borden, M.; Warrington, R.; Baskette, C.

2004-01-01

Securing forward contracts to manage procurement-cost risk is an intuitively appealing and economically reasonable strategy for a load-serving local distribution company (LDC) in today's volatile electricity marketplace. However, knowing what to buy does not guarantee least-cost implementation. The forward-contract price quoted by a prospective seller may not be the 'best deal' that an LDC could have obtained, especially when the forward contract desired by the LDC is not actively traded. This paper reports the results from five internet-based auctions for electricity forward contracts with non-firm delivery and varying hourly quantities held monthly by a Florida municipal utility (MU) from September 2002 to January 2003. The results confirm that a multi-round auction design is robust in realizing competitive price offers made by credit-worthy sellers, time-efficient contracting, and consistent cost savings to the MU. Thus, the Anglo-Dutch auction described herein is a reasonable substitute for generation ownership by an LDC. (author)

A model of optimization for local energy infrastructure development

International Nuclear Information System (INIS)

Juroszek, Zbigniew; Kudelko, Mariusz

2016-01-01

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

Extending the Domain Name System (DNS) to Provide Geographical Addressing Towards Vehicular Ad-Hoc Networks (VANETs)

NARCIS (Netherlands)

Fioreze, Tiago; Heijenk, Geert

2011-01-01

Geographical addressing is a key communication paradigm in emerging Intelligent Transportation Systems (ITS). In this paper, we address the issue of how to direct messages to roadside units (RSUs) in order to have them forwarded by the RSUs to the on-board units (OBUs) of vehicles in a certain

Global-Local Analysis and Optimization of a Composite Civil Tilt-Rotor Wing

Science.gov (United States)

Rais-Rohani, Masound

1999-01-01

This report gives highlights of an investigation on the design and optimization of a thin composite wing box structure for a civil tilt-rotor aircraft. Two different concepts are considered for the cantilever wing: (a) a thin monolithic skin design, and (b) a thick sandwich skin design. Each concept is examined with three different skin ply patterns based on various combinations of 0, +/-45, and 90 degree plies. The global-local technique is used in the analysis and optimization of the six design models. The global analysis is based on a finite element model of the wing-pylon configuration while the local analysis uses a uniformly supported plate representing a wing panel. Design allowables include those on vibration frequencies, panel buckling, and material strength. The design optimization problem is formulated as one of minimizing the structural weight subject to strength, stiffness, and d,vnamic constraints. Six different loading conditions based on three different flight modes are considered in the design optimization. The results of this investigation reveal that of all the loading conditions the one corresponding to the rolling pull-out in the airplane mode is the most stringent. Also the frequency constraints are found to drive the skin thickness limits, rendering the buckling constraints inactive. The optimum skin ply pattern for the monolithic skin concept is found to be (((0/+/-45/90/(0/90)(sub 2))(sub s))(sub s), while for the sandwich skin concept the optimal ply pattern is found to be ((0/+/-45/90)(sub 2s))(sub s).

End-of-Life Care in Nunavik, Quebec: Inuit Experiences, Current Realities, and Ways Forward.

Science.gov (United States)

Hordyk, Shawn Renee; Macdonald, Mary Ellen; Brassard, Paul

2017-06-01

Increasing longevity for Inuit living in Nunavik, northern Quebec, has resulted in heightened rates of cancers and chronic diseases necessitating complex treatments. Consequently, end-of-life (EOL) care, once the domain of Inuit families and communities, has come to include professionalized healthcare providers with varying degrees of awareness of factors to consider in providing care to Inuit populations. To better understand the factors shaping EOL care in Nunavik to support the development of a sustainable model of care. Using focused ethnography, we conducted participant observations and informal and semistructured interviews with 103 participants (community members, healthcare practitioners, and administrators) across Nunavik and in Montreal, the affiliated tertiary care center. Data domains included the following: care trajectories; patient and family experiences receiving and providing EOL care; local and urban resources and challenges; and ways forward. Sociocultural, historical, and geographic factors shape EOL care in Nunavik, presenting a complex set of challenges for Inuit patients, families, and healthcare providers. A sustainable model of EOL care requires building on shared initiatives, capitalizing on the existing strengths in communities, and attending to the multiple bereavement needs in the region. Building a sustainable model of EOL care requires respectful collaboration among governing structures, healthcare institutions, and community members. It must centrally value local knowledge and initiatives. To ensure Inuit families and patients are supported throughout the dying process, future initiatives must centrally include local stakeholders in both the design and evaluation of any changes to the current healthcare system.

An Improved Chaos Genetic Algorithm for T-Shaped MIMO Radar Antenna Array Optimization

Directory of Open Access Journals (Sweden)

Xin Fu

2014-01-01

Full Text Available In view of the fact that the traditional genetic algorithm easily falls into local optimum in the late iterations, an improved chaos genetic algorithm employed chaos theory and genetic algorithm is presented to optimize the low side-lobe for T-shaped MIMO radar antenna array. The novel two-dimension Cat chaotic map has been put forward to produce its initial population, improving the diversity of individuals. The improved Tent map is presented for groups of individuals of a generation with chaos disturbance. Improved chaotic genetic algorithm optimization model is established. The algorithm presented in this paper not only improved the search precision, but also avoids effectively the problem of local convergence and prematurity. For MIMO radar, the improved chaos genetic algorithm proposed in this paper obtains lower side-lobe level through optimizing the exciting current amplitude. Simulation results show that the algorithm is feasible and effective. Its performance is superior to the traditional genetic algorithm.

The geographical distribution of tremellaceous fungi in Poland

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Władysław Wojewoda

2014-11-01

Full Text Available The geographical distribution of the Polish tremellaceous fungi is discussed in this paper. The list of localities and the maps of the distribution of 60 Polish species (45 of Tremellales, 13 of Auriculariales and 2 of Septobasidiales are given. The author distinguishes several geographical elements, and describes the vertical distribution of these fungi. This paper is a supplement to "Fungi (Mycota", vol. 8, Polish Flora (Wojewoda 1977.

Local Optimization Strategies in Urban Vehicular Mobility.

Directory of Open Access Journals (Sweden)

Pierpaolo Mastroianni

Full Text Available The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.

Is local participation always optimal for sustainable action? The costs of consensus-building in Local Agenda 21.

Science.gov (United States)

Brandt, Urs Steiner; Svendsen, Gert Tinggaard

2013-11-15

Is local participation always optimal for sustainable action? Here, Local Agenda 21 is a relevant case as it broadly calls for consensus-building among stakeholders. Consensus-building is, however, costly. We show that the costs of making local decisions are likely to rapidly exceed the benefits. Why? Because as the number of participants grows, the more likely it is that the group will include individuals who have an extreme position and are unwilling to make compromises. Thus, the net gain of self-organization should be compared with those of its alternatives, for example voting, market-solutions, or not making any choices at all. Even though the informational value of meetings may be helpful to policy makers, the model shows that it also decreases as the number of participants increase. Overall, the result is a thought provoking scenario for Local Agenda 21 as it highlights the risk of less sustainable action in the future. Copyright © 2013 Elsevier Ltd. All rights reserved.

Education Demographic and Geographic Estimates Program (EDGE): Locale Boundaries User's Manual. NCES 2016-012

Science.gov (United States)

Geverdt, Douglas E.

2015-01-01

The National Center for Education Statistics (NCES) Education Demographic and Geographic Estimates (EDGE) program develops geographic data to help policymakers, program administrators, and the public understand relationships between educational institutions and the communities they serve. One of the commonly used geographic data items is the NCES…

Modelling grid losses and the geographic distribution of electricity generation

DEFF Research Database (Denmark)

Østergaard, Poul Alberg

2005-01-01

In Denmark more than 40% of the electricity consumption is covered by geographically scattered electricity sources namely wind power and local CHP (cogeneration of heat and power) plants. This causes problems in regard to load balancing and possible grid overloads. The potential grid problems...... and methods for solving these are analysed in this article on the basis of energy systems analyses, geographic distribution of consumption and production and grid load-flow analyses. It is concluded that by introducing scattered load balancing using local CHP plants actively and using interruptible loads...

Localized-Surface-Plasmon Enhanced the 357 nm Forward Emission from ZnMgO Films Capped by Pt Nanoparticles

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Song XM

2009-01-01

Full Text Available Abstract The Pt nanoparticles (NPs, which posses the wider tunable localized-surface-plasmon (LSP energy varying from deep ultraviolet to visible region depending on their morphology, were prepared by annealing Pt thin films with different initial mass-thicknesses. A sixfold enhancement of the 357 nm forward emission of ZnMgO was observed after capping with Pt NPs, which is due to the resonance coupling between the LSP of Pt NPs and the band-gap emission of ZnMgO. The other factors affecting the ultraviolet emission of ZnMgO, such as emission from Pt itself and light multi-scattering at the interface, were also discussed. These results indicate that Pt NPs can be used to enhance the ultraviolet emission through the LSP coupling for various wide band-gap semiconductors.

Expected Forward Progress and Throughput of Multi-Hop Frequency-Hopped Spread-Spectrum Networks

National Research Council Canada - National Science Library

Gluck, Jeffrey W; Geraniotis, Evaggelos

1987-01-01

...). The optimal average number of neighbors and transmission radius are derived for these cases when Reed-Solomon forward-error-control coding with minimum distance decoding or binary convolutional...

An optimized ensemble local mean decomposition method for fault detection of mechanical components

International Nuclear Information System (INIS)

Zhang, Chao; Chen, Shuai; Wang, Jianguo; Li, Zhixiong; Hu, Chao; Zhang, Xiaogang

2017-01-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error ( Relative RMSE ) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE , corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions. (paper)

An optimized ensemble local mean decomposition method for fault detection of mechanical components

Science.gov (United States)

Zhang, Chao; Li, Zhixiong; Hu, Chao; Chen, Shuai; Wang, Jianguo; Zhang, Xiaogang

2017-03-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error (Relative RMSE) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE, corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions.

Cost-effective handoff scheme based on mobility-aware dual pointer forwarding in proxy mobile IPv6 networks.

Science.gov (United States)

Son, Seungsik; Jeong, Jongpil

2014-01-01

In this paper, a mobility-aware Dual Pointer Forwarding scheme (mDPF) is applied in Proxy Mobile IPv6 (PMIPv6) networks. The movement of a Mobile Node (MN) is classified as intra-domain and inter-domain handoff. When the MN moves, this scheme can reduce the high signaling overhead for intra-handoff/inter-handoff, because the Local Mobility Anchor (LMA) and Mobile Access Gateway (MAG) are connected by pointer chains. In other words, a handoff is aware of low mobility between the previously attached MAG (pMAG) and newly attached MAG (nMAG), and another handoff between the previously attached LMA (pLMA) and newly attached LMA (nLMA) is aware of high mobility. Based on these mobility-aware binding updates, the overhead of the packet delivery can be reduced. Also, we analyse the binding update cost and packet delivery cost for route optimization, based on the mathematical analytic model. Analytical results show that our mDPF outperforms the PMIPv6 and the other pointer forwarding schemes, in terms of reducing the total cost of signaling.

A multiple-location model for natural gas forward curves

International Nuclear Information System (INIS)

Buffington, J.C.

1999-06-01

This thesis presents an approach for financial modelling of natural gas in which connections between locations are incorporated and the complexities of forward curves in natural gas are considered. Apart from electricity, natural gas is the most volatile commodity traded. Its price is often dependent on the weather and price shocks can be felt across several geographic locations. This modelling approach incorporates multiple risk factors that correspond to various locations. One of the objectives was to determine if the model could be used for closed-form option prices. It was suggested that an adequate model for natural gas must consider 3 statistical properties: volatility term structure, backwardation and contango, and stochastic basis. Data from gas forward prices at Chicago, NYMEX and AECO were empirically tested to better understand these 3 statistical properties at each location and to verify if the proposed model truly incorporates these properties. In addition, this study examined the time series property of the difference of two locations (the basis) and determines that these empirical properties are consistent with the model properties. Closed-form option solutions were also developed for call options of forward contracts and call options on forward basis. The options were calibrated and compared to other models. The proposed model is capable of pricing options, but the prices derived did not pass the test of economic reasonableness. However, the model was able to capture the effect of transportation as well as aspects of seasonality which is a benefit over other existing models. It was determined that modifications will be needed regarding the estimation of the convenience yields. 57 refs., 2 tabs., 7 figs., 1 append

Physical-geographical landscape of the tourist circuit Chilpancingo-Azul, Guerrero State, Mexico

Directory of Open Access Journals (Sweden)

Julio C. Carbajal Monroy

2011-02-01

Full Text Available This work deals with the delimitation of physical-geographical landscapes of the territory of the Tourist Circuit Chilpancingo Azul, at Guerrero's State central region, from geo-ecological conception for the physical-geographical synthetic classification of territorial units. This approach obtained territorial units and its hierarchical classification using a taxonomic system of localities, neighborhoods and boroughs (smallest categories. Taking into account the 1:100 000 scale different geographical units were determined: 3 localities, 31 neighborhoods and 177 boroughs. The characterization of these territorial units include lithologic constitution, geomorphological conditions (morphogenesis and morphometrics and spatial distribution of major types of soils and vegetation and land uses in the territory.

Human-geographical concept of the regional geodemographic system

Directory of Open Access Journals (Sweden)

Kateryna Sehida

2017-10-01

Full Text Available The synergetic analysis of geodemographic researches indicates that they can be solved with use of modern technologies of management. according to the theory of a sotsioaktogenez, for this purpose it is necessary to define and formulate accurately the purpose of future phase transition, to construct consistent system of the purposes taking into account own and provided resources, to create executive system, effective from the point of view of optimum use of the available methods (technologies and means of activity, and to control and analyze obtaining result. The analysis of results of social management demands the quantitative description and comparison of real result with his expected model (purpose. The offered concept of geodemographic system of the region on the basis of dissipative structures which treats people, groups of people, society is aimed at the development and functioning of the studied system where the special role belongs to implementation of administrative decisions. In article it is covered the generalized structure of the concept, it is revealed her the purpose, an object subject area. It is defined public and spatial localization of a research, in particular within regional, region and local communities. It is identified geodemographic process as composite human and geographical process as sotsioaktogenez (with determination of stages of motivation, system of the purposes, executive system and result from a line item of society and a family as self-development and self-organization (with determination of the internal and external factors supporting and evolutionary resources, mechanisms as process (information exchange, external and internal adaptation. Methodological approaches (geographical, system, synergy, information, historical, research techniques (the analysis of system indices, simulation of a path of development, the component analysis and evaluation and prognostic simulation are opened. Technological procedures

Acquisition parameters optimization of a transmission electron forward scatter diffraction system in a cold-field emission scanning electron microscope for nanomaterials characterization.

Science.gov (United States)

Brodusch, Nicolas; Demers, Hendrix; Trudeau, Michel; Gauvin, Raynald

2013-01-01

Transmission electron forward scatter diffraction (t-EFSD) is a new technique providing crystallographic information with high resolution on thin specimens by using a conventional electron backscatter diffraction (EBSD) system in a scanning electron microscope. In this study, the impact of tilt angle, working distance, and detector distance on the Kikuchi pattern quality were investigated in a cold-field emission scanning electron microscope (CFE-SEM). We demonstrated that t-EFSD is applicable for tilt angles ranging from -20° to -40°. Working distance (WD) should be optimized for each material by choosing the WD for which the EBSD camera screen illumination is the highest, as the number of detected electrons on the screen is directly dependent on the scattering angle. To take advantage of the best performances of the CFE-SEM, the EBSD camera should be close to the sample and oriented towards the bottom to increase forward scattered electron collection efficiency. However, specimen chamber cluttering and beam/mechanical drift are important limitations in the CFE-SEM used in this work. Finally, the importance of t-EFSD in materials science characterization was illustrated through three examples of phase identification and orientation mapping. © Wiley Periodicals, Inc.

Damage approach: A new method for topology optimization with local stress constraints

DEFF Research Database (Denmark)

Verbart, Alexander; Langelaar, Matthijs; van Keulen, Fred

2016-01-01

In this paper, we propose a new method for topology optimization with local stress constraints. In this method, material in which a stress constraint is violated is considered as damaged. Since damaged material will contribute less to the overall performance of the structure, the optimizer...... will promote a design with a minimal amount of damaged material. We tested the method on several benchmark problems, and the results show that the method is a viable alternative for conventional stress-based approaches based on constraint relaxation followed by constraint aggregation....

Nonlinear Optimization-Based Device-Free Localization with Outlier Link Rejection

Directory of Open Access Journals (Sweden)

Wendong Xiao

2015-04-01

Full Text Available Device-free localization (DFL is an emerging wireless technique for estimating the location of target that does not have any attached electronic device. It has found extensive use in Smart City applications such as healthcare at home and hospitals, location-based services at smart spaces, city emergency response and infrastructure security. In DFL, wireless devices are used as sensors that can sense the target by transmitting and receiving wireless signals collaboratively. Many DFL systems are implemented based on received signal strength (RSS measurements and the location of the target is estimated by detecting the changes of the RSS measurements of the wireless links. Due to the uncertainty of the wireless channel, certain links may be seriously polluted and result in erroneous detection. In this paper, we propose a novel nonlinear optimization approach with outlier link rejection (NOOLR for RSS-based DFL. It consists of three key strategies, including: (1 affected link identification by differential RSS detection; (2 outlier link rejection via geometrical positional relationship among links; (3 target location estimation by formulating and solving a nonlinear optimization problem. Experimental results demonstrate that NOOLR is robust to the fluctuation of the wireless signals with superior localization accuracy compared with the existing Radio Tomographic Imaging (RTI approach.

Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem

Directory of Open Access Journals (Sweden)

A. K. M. Foysal Ahmed

2018-03-01

Full Text Available The classical capacitated vehicle routing problem (CVRP is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches.

Geographical constraints to range-based attacks on links in complex networks

International Nuclear Information System (INIS)

Gong Baihua; Liu Jun; Huang Liang; Yang Kongqing; Yang Lei

2008-01-01

In this paper, we studied range-based attacks on links in geographically constrained scale-free networks and found that there is a continuous switching of roles of short- and long-range attacks on links when tuning the geographical constraint strength. Our results demonstrate that the geography has a significant impact on the network efficiency and security; thus one can adjust the geographical structure to optimize the robustness and the efficiency of the networks. We introduce a measurement of the impact of links on the efficiency of the network, and an effective attacking strategy is suggested

USAID Forward

Data.gov (United States)

US Agency for International Development — The USAID Forward reform initiative ran from 2010-2016. USAID Forward improved the way that the Agency delivers foreign assistance by embracing new partnerships,...

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

Science.gov (United States)

Wang, Zhihao; Yi, Jing

2016-01-01

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

Modeling and analysis of strategic forward contracting in transmission constrained power markets

International Nuclear Information System (INIS)

Yu, C.W.; Chung, T.S.; Zhang, S.H.; Wang, X.

2010-01-01

Taking the effects of transmission network into account, strategic forward contracting induced by the interaction of generation firms' strategies in the spot and forward markets is investigated. A two-stage game model is proposed to describe generation firms' strategic forward contracting and spot market competition. In the spot market, generation firms behave strategically by submitting bids at their nodes in a form of linear supply function (LSF) and there are arbitrageurs who buy and resell power at different nodes where price differences exceed the costs of transmission. The owner of the grid is assumed to ration limited transmission line capacity to maximize the value of the transmission services in the spot market. The Cournot-type competition is assumed for the strategic forward contract market. This two-stage model is formulated as an equilibrium problem with equilibrium constraints (EPEC); in which each firm's optimization problem in the forward market is a mathematical program with equilibrium constraints (MPEC) and parameter-dependent spot market equilibrium as the inner problem. A nonlinear complementarity method is employed to solve this EPEC model. (author)

A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING

Directory of Open Access Journals (Sweden)

Parisa Bazmi

2016-11-01

Full Text Available Named Data Networking (NDN is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN Based Traffic-aware Forwarding strategy (NNTF is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively.

Particle Swarm Optimization Based on Local Attractors of Ordinary Differential Equation System

Directory of Open Access Journals (Sweden)

Wenyu Yang

2014-01-01

Full Text Available Particle swarm optimization (PSO is inspired by sociological behavior. In this paper, we interpret PSO as a finite difference scheme for solving a system of stochastic ordinary differential equations (SODE. In this framework, the position points of the swarm converge to an equilibrium point of the SODE and the local attractors, which are easily defined by the present position points, also converge to the global attractor. Inspired by this observation, we propose a class of modified PSO iteration methods (MPSO based on local attractors of the SODE. The idea of MPSO is to choose the next update state near the present local attractor, rather than the present position point as in the original PSO, according to a given probability density function. In particular, the quantum-behaved particle swarm optimization method turns out to be a special case of MPSO by taking a special probability density function. The MPSO methods with six different probability density functions are tested on a few benchmark problems. These MPSO methods behave differently for different problems. Thus, our framework not only gives an interpretation for the ordinary PSO but also, more importantly, provides a warehouse of PSO-like methods to choose from for solving different practical problems.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

Directory of Open Access Journals (Sweden)

Xianyu Yu

2016-05-01

Full Text Available In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Extended forward sensitivity analysis of one-dimensional isothermal flow

International Nuclear Information System (INIS)

Johnson, M.; Zhao, H.

2013-01-01

Sensitivity analysis and uncertainty quantification is an important part of nuclear safety analysis. In this work, forward sensitivity analysis is used to compute solution sensitivities on 1-D fluid flow equations typical of those found in system level codes. Time step sensitivity analysis is included as a method for determining the accumulated error from time discretization. The ability to quantify numerical error arising from the time discretization is a unique and important feature of this method. By knowing the relative sensitivity of time step with other physical parameters, the simulation is allowed to run at optimized time steps without affecting the confidence of the physical parameter sensitivity results. The time step forward sensitivity analysis method can also replace the traditional time step convergence studies that are a key part of code verification with much less computational cost. One well-defined benchmark problem with manufactured solutions is utilized to verify the method; another test isothermal flow problem is used to demonstrate the extended forward sensitivity analysis process. Through these sample problems, the paper shows the feasibility and potential of using the forward sensitivity analysis method to quantify uncertainty in input parameters and time step size for a 1-D system-level thermal-hydraulic safety code. (authors)

The Geographic Extent of Global Supply Chains

DEFF Research Database (Denmark)

Machikita, Tomohiro; Ueki, Yasushi

2012-01-01

We study the extent to which inter-firm relationships are locally concentrated and what determines firm differences in geographic proximity to domestic or foreign suppliers and customers. From micro-data on selfreported customer and supplier data of firms in Indonesia, the Philippines, Thailand, ...

Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm

International Nuclear Information System (INIS)

Pokhrel, Damodar; Murphy, Martin J.; Todor, Dorin A.; Weiss, Elisabeth; Williamson, Jeffrey F.

2011-01-01

Purpose: To present a novel method for reconstructing the 3D pose (position and orientation) of radio-opaque applicators of known but arbitrary shape from a small set of 2D x-ray projections in support of intraoperative brachytherapy planning. Methods: The generalized iterative forward projection matching (gIFPM) algorithm finds the six degree-of-freedom pose of an arbitrary rigid object by minimizing the sum-of-squared-intensity differences (SSQD) between the computed and experimentally acquired autosegmented projection of the objects. Starting with an initial estimate of the object's pose, gIFPM iteratively refines the pose parameters (3D position and three Euler angles) until the SSQD converges. The object, here specialized to a Fletcher-Weeks intracavitary brachytherapy (ICB) applicator, is represented by a fine mesh of discrete points derived from complex combinatorial geometric models of the actual applicators. Three pairs of computed and measured projection images with known imaging geometry are used. Projection images of an intrauterine tandem and colpostats were acquired from an ACUITY cone-beam CT digital simulator. An image postprocessing step was performed to create blurred binary applicators only images. To quantify gIFPM accuracy, the reconstructed 3D pose of the applicator model was forward projected and overlaid with the measured images and empirically calculated the nearest-neighbor applicator positional difference for each image pair. Results: In the numerical simulations, the tandem and colpostats positions (x,y,z) and orientations (α,β,γ) were estimated with accuracies of 0.6 mm and 2 deg., respectively. For experimentally acquired images of actual applicators, the residual 2D registration error was less than 1.8 mm for each image pair, corresponding to about 1 mm positioning accuracy at isocenter, with a total computation time of less than 1.5 min on a 1 GHz processor. Conclusions: This work describes a novel, accurate, fast, and completely

Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm

Energy Technology Data Exchange (ETDEWEB)

Pokhrel, Damodar; Murphy, Martin J.; Todor, Dorin A.; Weiss, Elisabeth; Williamson, Jeffrey F. [Department of Radiation Oncology, School of Medicine, Virginia Commonwealth University, Richmond, Virginia 23298 (United States)

2011-02-15

Purpose: To present a novel method for reconstructing the 3D pose (position and orientation) of radio-opaque applicators of known but arbitrary shape from a small set of 2D x-ray projections in support of intraoperative brachytherapy planning. Methods: The generalized iterative forward projection matching (gIFPM) algorithm finds the six degree-of-freedom pose of an arbitrary rigid object by minimizing the sum-of-squared-intensity differences (SSQD) between the computed and experimentally acquired autosegmented projection of the objects. Starting with an initial estimate of the object's pose, gIFPM iteratively refines the pose parameters (3D position and three Euler angles) until the SSQD converges. The object, here specialized to a Fletcher-Weeks intracavitary brachytherapy (ICB) applicator, is represented by a fine mesh of discrete points derived from complex combinatorial geometric models of the actual applicators. Three pairs of computed and measured projection images with known imaging geometry are used. Projection images of an intrauterine tandem and colpostats were acquired from an ACUITY cone-beam CT digital simulator. An image postprocessing step was performed to create blurred binary applicators only images. To quantify gIFPM accuracy, the reconstructed 3D pose of the applicator model was forward projected and overlaid with the measured images and empirically calculated the nearest-neighbor applicator positional difference for each image pair. Results: In the numerical simulations, the tandem and colpostats positions (x,y,z) and orientations ({alpha},{beta},{gamma}) were estimated with accuracies of 0.6 mm and 2 deg., respectively. For experimentally acquired images of actual applicators, the residual 2D registration error was less than 1.8 mm for each image pair, corresponding to about 1 mm positioning accuracy at isocenter, with a total computation time of less than 1.5 min on a 1 GHz processor. Conclusions: This work describes a novel, accurate

Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm.

Science.gov (United States)

Pokhrel, Damodar; Murphy, Martin J; Todor, Dorin A; Weiss, Elisabeth; Williamson, Jeffrey F

2011-02-01

To present a novel method for reconstructing the 3D pose (position and orientation) of radio-opaque applicators of known but arbitrary shape from a small set of 2D x-ray projections in support of intraoperative brachytherapy planning. The generalized iterative forward projection matching (gIFPM) algorithm finds the six degree-of-freedom pose of an arbitrary rigid object by minimizing the sum-of-squared-intensity differences (SSQD) between the computed and experimentally acquired autosegmented projection of the objects. Starting with an initial estimate of the object's pose, gIFPM iteratively refines the pose parameters (3D position and three Euler angles) until the SSQD converges. The object, here specialized to a Fletcher-Weeks intracavitary brachytherapy (ICB) applicator, is represented by a fine mesh of discrete points derived from complex combinatorial geometric models of the actual applicators. Three pairs of computed and measured projection images with known imaging geometry are used. Projection images of an intrauterine tandem and colpostats were acquired from an ACUITY cone-beam CT digital simulator. An image postprocessing step was performed to create blurred binary applicators only images. To quantify gIFPM accuracy, the reconstructed 3D pose of the applicator model was forward projected and overlaid with the measured images and empirically calculated the nearest-neighbor applicator positional difference for each image pair. In the numerical simulations, the tandem and colpostats positions (x,y,z) and orientations (alpha, beta, gamma) were estimated with accuracies of 0.6 mm and 2 degrees, respectively. For experimentally acquired images of actual applicators, the residual 2D registration error was less than 1.8 mm for each image pair, corresponding to about 1 mm positioning accuracy at isocenter, with a total computation time of less than 1.5 min on a 1 GHz processor. This work describes a novel, accurate, fast, and completely automatic method to

A Local and Global Search Combined Particle Swarm Optimization Algorithm and Its Convergence Analysis

Directory of Open Access Journals (Sweden)

Weitian Lin

2014-01-01

Full Text Available Particle swarm optimization algorithm (PSOA is an advantage optimization tool. However, it has a tendency to get stuck in a near optimal solution especially for middle and large size problems and it is difficult to improve solution accuracy by fine-tuning parameters. According to the insufficiency, this paper researches the local and global search combine particle swarm algorithm (LGSCPSOA, and its convergence and obtains its convergence qualification. At the same time, it is tested with a set of 8 benchmark continuous functions and compared their optimization results with original particle swarm algorithm (OPSOA. Experimental results indicate that the LGSCPSOA improves the search performance especially on the middle and large size benchmark functions significantly.

Spatial modelling of assumption of tourism development with geographic IT using

Directory of Open Access Journals (Sweden)

Jitka Machalová

2010-01-01

Full Text Available The aim of this article is to show the possibilities of spatial modelling and analysing of assumptions of tourism development in the Czech Republic with the objective to make decision-making processes in tourism easier and more efficient (for companies, clients as well as destination managements. The development and placement of tourism depend on the factors (conditions that influence its application in specific areas. These factors are usually divided into three groups: selective, localization and realization. Tourism is inseparably connected with space – countryside. The countryside can be modelled and consecutively analysed by the means of geographical information technologies. With the help of spatial modelling and following analyses the localization and realization conditions in the regions of the Czech Republic have been evaluated. The best localization conditions have been found in the Liberecký region. The capital city of Prague has negligible natural conditions; however, those social ones are on a high level. Next, the spatial analyses have shown that the best realization conditions are provided by the capital city of Prague. Then the Central-Bohemian, South-Moravian, Moravian-Silesian and Karlovarský regions follow. The development of tourism destination is depended not only on the localization and realization factors but it is basically affected by the level of local destination management. Spatial modelling can help destination managers in decision-making processes in order to optimal use of destination potential and efficient targeting their marketing activities.

Forward optical glory

International Nuclear Information System (INIS)

Nussenzveig, H.M.

Forward optical glory effects in Mie scattering are displayed here for the first time. These effects include regular oscillations in Mie efficiency factors and characteristic deviations from zero polarization in near-forward scattering which are observable for real refractive indices near √2 and 2. Complex angular momentum theory predicts the period of oscillation correctly and shows the important role played by surface waves with shortcuts through the sphere. three possible types of experiments for detecting the forward glory are proposed, involving measurements of extinction, radiation pressure, and polarization in near-forward scattering. (Author) [pt

CYBERNETICS AND GEOGRAPHICAL EDUCATION: CYBERNETICS OF LEARNING AND LEARNING OF CYBERNETICS

Directory of Open Access Journals (Sweden)

M. R. Arpentieva

2017-01-01

Full Text Available Modern geographical education implies a broad implementation of innovative technologies, allowing students to fully and deeply understand the subject and methods of professional activity, and effectively and productively act upon this understanding. Therefore, in the work of modern geographer computer and media technologies occupy a significant place, and geographic education occupies an important place in learning cybernetic disciplines: computer technologies act as an important condition for obtaining high quality professional education, as well as an important tool of professional activity of modern specialist-geographer. The article is devoted to comparing three modern approaches to the study and optimization of training Cybernetics and programming in the framework of geographical education: an approach devoted to the study of “learning styles”; the metacognitive approach to learning computer science and programming; and intersubjective, evergetic or actually cybernetic, approach. It describes their advantages and limitations in the context of geographical education, as well as the internal unity as different forms of study of productivity and conditions of the dialogical interaction between teacher and student in the context of obtaining high-quality geographical education.

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

Science.gov (United States)

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

2017-10-01

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

U Plant Geographic Zone Cleanup Prototype

International Nuclear Information System (INIS)

Romine, L.D.; Leary, K.D.; Lackey, M.B.; Robertson, J.R.

2006-01-01

The U Plant geographic zone (UPZ) occupies 0.83 square kilometers on the Hanford Site Central Plateau (200 Area). It encompasses the U Plant canyon (221-U Facility), ancillary facilities that supported the canyon, soil waste sites, and underground pipelines. The UPZ cleanup initiative coordinates the cleanup of the major facilities, ancillary facilities, waste sites, and contaminated pipelines (collectively identified as 'cleanup items') within the geographic zone. The UPZ was selected as a geographic cleanup zone prototype for resolving regulatory, technical, and stakeholder issues and demonstrating cleanup methods for several reasons: most of the area is inactive, sufficient characterization information is available to support decisions, cleanup of the high-risk waste sites will help protect the groundwater, and the zone contains a representative cross-section of the types of cleanup actions that will be required in other geographic zones. The UPZ cleanup demonstrates the first of 22 integrated zone cleanup actions on the Hanford Site Central Plateau to address threats to groundwater, the environment, and human health. The UPZ contains more than 100 individual cleanup items. Cleanup actions in the zone will be undertaken using multiple regulatory processes and decision documents. Cleanup actions will include building demolition, waste site and pipeline excavation, and the construction of multiple, large engineered barriers. In some cases, different cleanup actions may be taken at item locations that are immediately adjacent to each other. The cleanup planning and field activities for each cleanup item must be undertaken in a coordinated and cohesive manner to ensure effective execution of the UPZ cleanup initiative. The UPZ zone cleanup implementation plan (ZCIP) [1] was developed to address the need for a fundamental integration tool for UPZ cleanup. As UPZ cleanup planning and implementation moves forward, the ZCIP is intended to be a living document that will

5 CFR 950.204 - Local eligibility.

Science.gov (United States)

2010-01-01

... electronic technology that allows removal of the need for geographic restrictions on giving as determined by... whose geographic border touches the geographic border of another local campaign. Participation in a... voluntary board of directors which serves without compensation and holds regular meetings. (4) Conduct its...

Reliability based topology optimization for continuum structures with local failure constraints

DEFF Research Database (Denmark)

Luo, Yangjun; Zhou, Mingdong; Wang, Michael Yu

2014-01-01

This paper presents an effective method for stress constrained topology optimization problems under load and material uncertainties. Based on the Performance Measure Approach (PMA), the optimization problem is formulated as to minimize the objective function under a large number of (stress......-related) target performance constraints. In order to overcome the stress singularity phenomenon caused by the combined stress and reliability constraints, a reduction strategy on target reliability index is proposed and utilized together with the ε-relaxation approach. Meanwhile, an enhanced aggregation method...... is employed to aggregate the selected active constraints using a general K–S function, which avoids expensive computational cost from the large-scale nature of local failure constraints. Several numerical examples are given to demonstrate the validity of the present method....

Optimal growth entails risky localization in population dynamics

Science.gov (United States)

Gueudré, Thomas; Martin, David G.

2018-03-01

Essential to each other, growth and exploration are jointly observed in alive and inanimate entities, such as animals, cells or goods. But how the environment's structural and temporal properties weights in this balance remains elusive. We analyze a model of stochastic growth with time correlations and diffusive dynamics that sheds light on the way populations grow and spread over general networks. This model suggests natural explanations of empirical facts in econo-physics or ecology, such as the risk-return trade-off and the Zipf law. We conclude that optimal growth leads to a localized population distribution, but such risky position can be mitigated through the space geometry. These results have broad applicability and are subsequently illustrated over an empirical study of financial data.

Optimal Audiovisual Integration in the Ventriloquism Effect But Pervasive Deficits in Unisensory Spatial Localization in Amblyopia.

Science.gov (United States)

Richards, Michael D; Goltz, Herbert C; Wong, Agnes M F

2018-01-01

Classically understood as a deficit in spatial vision, amblyopia is increasingly recognized to also impair audiovisual multisensory processing. Studies to date, however, have not determined whether the audiovisual abnormalities reflect a failure of multisensory integration, or an optimal strategy in the face of unisensory impairment. We use the ventriloquism effect and the maximum-likelihood estimation (MLE) model of optimal integration to investigate integration of audiovisual spatial information in amblyopia. Participants with unilateral amblyopia (n = 14; mean age 28.8 years; 7 anisometropic, 3 strabismic, 4 mixed mechanism) and visually normal controls (n = 16, mean age 29.2 years) localized brief unimodal auditory, unimodal visual, and bimodal (audiovisual) stimuli during binocular viewing using a location discrimination task. A subset of bimodal trials involved the ventriloquism effect, an illusion in which auditory and visual stimuli originating from different locations are perceived as originating from a single location. Localization precision and bias were determined by psychometric curve fitting, and the observed parameters were compared with predictions from the MLE model. Spatial localization precision was significantly reduced in the amblyopia group compared with the control group for unimodal visual, unimodal auditory, and bimodal stimuli. Analyses of localization precision and bias for bimodal stimuli showed no significant deviations from the MLE model in either the amblyopia group or the control group. Despite pervasive deficits in localization precision for visual, auditory, and audiovisual stimuli, audiovisual integration remains intact and optimal in unilateral amblyopia.

Balanites aegyptiaca (L. Delile: geographical distribution and ethnobotanical knowledge by local populations in the Ferlo (north Senegal

Directory of Open Access Journals (Sweden)

Sagna, MB.

2014-01-01

Full Text Available Balanites aegyptiaca (L. Delile is a species of tropical flora for which the variety aegyptiaca is adapted to Sahelian climate. The species is among those chosen for the restoration of Sahelian ecosystems in the context of the pan-African reforestation project, the Great Green Wall for the Sahara and Sahel Initiative (GGW. This study redefines the distribution range and its ecology and studies its uses in the Ferlo region in the north of Senegal using surveys carried out among the local population. The eco-geographical study shows that the species occupies several Sahel-Saharan regions of Africa and the Middle East. With broad ecological amplitude, it is very resistant to drought and relatively indifferent to the type of soil. Results of the ethno-botanical survey show that local people in the Ferlo region have a wealth of knowledge and expertise on B. aegyptiaca. These surveys also revealed the extent to which local populations rely on the tree for food, fodder, construction and medicine. The fruit and wood are the most highly prized parts of the tree, with the greatest use of the fruit in people's diets. In medicinal terms, B. aegyptiaca is used to treat several affections. Marketing the fruits could be of socio-economic interest for local people, and in particular, for women. This study is particularly opportune since B. aegyptiaca var. aegyptiaca is currently being planted in large numbers within the Great Green Wall for the Sahara and the Sahel Initiative (GGW. It also provides information that could help in better management of this natural resource, adapted both to the hostile Sahelian climate and of great use to Mankind.

Partner cooperation with decode-and-forward: Closed-form outage analysis and comparison

KAUST Repository

Benjillali, Mustapha

2013-01-01

In this paper, we investigate the outage performance of "partner cooperation" based on opportunistic Decodeand- Forward with constrained partial selection and reactive relaying strategies in dual-hop cooperative Nakagami-m fading links. The source/destination, which is based on the unique knowledge of local channel state information, selects the best relay to increase the chances of cooperation in both uplink and downlink communications when the direct link is also available. After deriving new expressions for the cumulative distribution functions of the variables of interest, the outage probability of the system is obtained in closed-form. We also derive the ε-outage capacity in different particular cases, and the obtained results - when the channel model is reduced to a Rayleigh fading - either are new or correspond to those previously obtained in other works. Simulation results confirm the accuracy of our analysis for a large selection of system and fading parameters and provide a new insight into the design and optimization of cooperative configurations. © 2012 IEEE.

Lambdastation: a forwarding and admission control service to interface production network facilities with advanced research network paths

Energy Technology Data Exchange (ETDEWEB)

DeMar, Philip; Petravick, Don; /Fermilab

2004-12-01

Over the past several years, there has been a great deal of research effort and funding put into the deployment of optical-based, advanced technology wide-area networks. Fermilab and CalTech have initiated a project to enable our production network facilities to exploit these advanced research network facilities. Our objective is to forward designated data transfers across these advanced wide area networks on a per-flow basis, making use our capacious production-use storage systems connected to the local campus network. To accomplish this, we intend to develop a dynamically provisioned forwarding service that would provide alternate path forwarding onto available wide area advanced research networks. The service would dynamically reconfigure forwarding of specific flows within our local production-use network facilities, as well as provide an interface to enable applications to utilize the service. We call this service LambdaStation. If one envisions wide area optical network paths as high bandwidth data railways, then LambdaStation would functionally be the railroad terminal that regulates which flows at the local site get directed onto the high bandwidth data railways. LambdaStation is a DOE-funded SciDac research project in its very early stage of development.

Theoretical Aspects of Optimizing the Allocation of Public Financial Resources at Local Level

OpenAIRE

Eugen DOGARIU

2010-01-01

The allocation of financial resources at local, but also at central level, is an issue especially since in times of crisis, finding the optimum way to spend public funds concerns all authorities. This paper aims to identify the ways in which, by leaving from the division of powers based on the allocation of resources and tools available, the local authorities can identify an optimal level of public expenditure so as to achieve a maximum level of using them. Also, the paper seeks to identify t...

The geographical mobility of recently graduated medical doctors

DEFF Research Database (Denmark)

Drejer, Ina; Holm, Jacob Rubæk; Petersen, Karin Dam

specialize to become general practitioners (GPs). Access to medical services is included among the services important for ensuring the basics in a welfare society. The analysis is limited to general practitioners (GPs), although access to other types of medical professionals is also an important aspect......University graduates are not evenly distributed geographically, and attraction and retention of university graduates is high on the agenda in many regional development strategies. In this paper we study the geographical mobility of a particular type of university graduates: medical doctors who...... of local access to medical services. We have chosen GPs because they – except in cases of emergency – are the main entrance to medical services in Denmark. We study how different factors may influence where GPs choose to set up medical practice. We pay particular attention to the importance of local...

Optimization of the fiber laser parameters for local high-temperature impact on metal

Science.gov (United States)

Yatsko, Dmitrii S.; Polonik, Marina V.; Dudko, Olga V.

2016-11-01

This paper presents the local laser heating process of surface layer of the metal sample. The aim is to create the molten pool with the required depth by laser thermal treatment. During the heating the metal temperature at any point of the molten zone should not reach the boiling point of the main material. The laser power, exposure time and the spot size of a laser beam are selected as the variable parameters. The mathematical model for heat transfer in a semi-infinite body, applicable to finite slab, is used for preliminary theoretical estimation of acceptable parameters values of the laser thermal treatment. The optimization problem is solved by using an algorithm based on the scanning method of the search space (the zero-order method of conditional optimization). The calculated values of the parameters (the optimal set of "laser radiation power - exposure time - spot radius") are used to conduct a series of natural experiments to obtain a molten pool with the required depth. A two-stage experiment consists of: a local laser treatment of metal plate (steel) and then the examination of the microsection of the laser irradiated region. According to the experimental results, we can judge the adequacy of the ongoing calculations within the selected models.

Introduction of Geographical Information Systems (GIS) in Technical University Education in Ghana: Challenges and the Way Forward

Science.gov (United States)

Acquah, Prince C.; Asamoah, Jack N.; Konadu, Daniel D.

2017-01-01

Geographic Information System (GIS) continue to play very important role in improving spatial thinking skills of graduates from higher educational institutions. However, teaching and learning of GIS at the technical university level in Ghana remains very limited due to some implementation challenges. This paper reviews the implementation of GIS in…

3-D inversion of airborne electromagnetic data parallelized and accelerated by local mesh and adaptive soundings

Science.gov (United States)

Yang, Dikun; Oldenburg, Douglas W.; Haber, Eldad

2014-03-01

Airborne electromagnetic (AEM) methods are highly efficient tools for assessing the Earth's conductivity structures in a large area at low cost. However, the configuration of AEM measurements, which typically have widely distributed transmitter-receiver pairs, makes the rigorous modelling and interpretation extremely time-consuming in 3-D. Excessive overcomputing can occur when working on a large mesh covering the entire survey area and inverting all soundings in the data set. We propose two improvements. The first is to use a locally optimized mesh for each AEM sounding for the forward modelling and calculation of sensitivity. This dedicated local mesh is small with fine cells near the sounding location and coarse cells far away in accordance with EM diffusion and the geometric decay of the signals. Once the forward problem is solved on the local meshes, the sensitivity for the inversion on the global mesh is available through quick interpolation. Using local meshes for AEM forward modelling avoids unnecessary computing on fine cells on a global mesh that are far away from the sounding location. Since local meshes are highly independent, the forward modelling can be efficiently parallelized over an array of processors. The second improvement is random and dynamic down-sampling of the soundings. Each inversion iteration only uses a random subset of the soundings, and the subset is reselected for every iteration. The number of soundings in the random subset, determined by an adaptive algorithm, is tied to the degree of model regularization. This minimizes the overcomputing caused by working with redundant soundings. Our methods are compared against conventional methods and tested with a synthetic example. We also invert a field data set that was previously considered to be too large to be practically inverted in 3-D. These examples show that our methodology can dramatically reduce the processing time of 3-D inversion to a practical level without losing resolution

Development and Optimization of Polymeric Self-Emulsifying Nanocapsules for Localized Drug Delivery: Design of Experiment Approach

Directory of Open Access Journals (Sweden)

Jyoti Wadhwa

2014-01-01

Full Text Available The purpose of the present study was to formulate polymeric self-emulsifying curcumin nanocapsules with high encapsulation efficiency, good emulsification ability, and optimal globule size for localized targeting in the colon. Formulations were prepared using modified quasiemulsion solvent diffusion method. Concentration of formulation variables, namely, X1 (oil, X2 (polymeric emulsifier, and X3 (adsorbent, was optimized by design of experiments using Box-Behnken design, for its impact on mean globule size (Y1 and encapsulation efficiency (Y2 of the formulation. Polymeric nanocapsules with an average diameter of 100–180 nm and an encapsulation efficiency of 64.85 ± 0.12% were obtained. In vitro studies revealed that formulations released the drug after 5 h lag time corresponding to the time to reach the colonic region. Pronounced localized action was inferred from the plasma concentration profile (Cmax 200 ng/mL that depicts limited systemic absorption. Roentgenography study confirms the localized presence of carrier (0–2 h in upper GIT; 2–4 h in small intestine; and 4–24 h in the lower intestine. Optimized formulation showed significantly higher cytotoxicity (IC50 value 20.32 μM in HT 29 colonic cancer cell line. The present study demonstrates systematic development of polymeric self-emulsifying nanocapsule formulation of curcumin for localized targeting in colon.

System automation for a bacterial colony detection and identification instrument via forward scattering

International Nuclear Information System (INIS)

Bae, Euiwon; Hirleman, E Daniel; Aroonnual, Amornrat; Bhunia, Arun K; Robinson, J Paul

2009-01-01

A system design and automation of a microbiological instrument that locates bacterial colonies and captures the forward-scattering signatures are presented. The proposed instrument integrates three major components: a colony locator, a forward scatterometer and a motion controller. The colony locator utilizes an off-axis light source to illuminate a Petri dish and an IEEE1394 camera to capture the diffusively scattered light to provide the number of bacterial colonies and two-dimensional coordinate information of the bacterial colonies with the help of a segmentation algorithm with region-growing. Then the Petri dish is automatically aligned with the respective centroid coordinate with a trajectory optimization method, such as the Traveling Salesman Algorithm. The forward scatterometer automatically computes the scattered laser beam from a monochromatic image sensor via quadrant intensity balancing and quantitatively determines the centeredness of the forward-scattering pattern. The final scattering signatures are stored to be analyzed to provide rapid identification and classification of the bacterial samples

Optimal reducibility of all W states equivalent under stochastic local operations and classical communication

Energy Technology Data Exchange (ETDEWEB)

Rana, Swapan; Parashar, Preeti [Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 BT Road, Kolkata (India)

2011-11-15

We show that all multipartite pure states that are stochastic local operation and classical communication (SLOCC) equivalent to the N-qubit W state can be uniquely determined (among arbitrary states) from their bipartite marginals. We also prove that only (N-1) of the bipartite marginals are sufficient and that this is also the optimal number. Thus, contrary to the Greenberger-Horne-Zeilinger (GHZ) class, W-type states preserve their reducibility under SLOCC. We also study the optimal reducibility of some larger classes of states. The generic Dicke states |GD{sub N}{sup l}> are shown to be optimally determined by their (l+1)-partite marginals. The class of ''G'' states (superposition of W and W) are shown to be optimally determined by just two (N-2)-partite marginals.

Gradient-based optimization with B-splines on sparse grids for solving forward-dynamics simulations of three-dimensional, continuum-mechanical musculoskeletal system models.

Science.gov (United States)

Valentin, J; Sprenger, M; Pflüger, D; Röhrle, O

2018-05-01

Investigating the interplay between muscular activity and motion is the basis to improve our understanding of healthy or diseased musculoskeletal systems. To be able to analyze the musculoskeletal systems, computational models are used. Albeit some severe modeling assumptions, almost all existing musculoskeletal system simulations appeal to multibody simulation frameworks. Although continuum-mechanical musculoskeletal system models can compensate for some of these limitations, they are essentially not considered because of their computational complexity and cost. The proposed framework is the first activation-driven musculoskeletal system model, in which the exerted skeletal muscle forces are computed using 3-dimensional, continuum-mechanical skeletal muscle models and in which muscle activations are determined based on a constraint optimization problem. Numerical feasibility is achieved by computing sparse grid surrogates with hierarchical B-splines, and adaptive sparse grid refinement further reduces the computational effort. The choice of B-splines allows the use of all existing gradient-based optimization techniques without further numerical approximation. This paper demonstrates that the resulting surrogates have low relative errors (less than 0.76%) and can be used within forward simulations that are subject to constraint optimization. To demonstrate this, we set up several different test scenarios in which an upper limb model consisting of the elbow joint, the biceps and triceps brachii, and an external load is subjected to different optimization criteria. Even though this novel method has only been demonstrated for a 2-muscle system, it can easily be extended to musculoskeletal systems with 3 or more muscles. Copyright © 2018 John Wiley & Sons, Ltd.

Tanzanian food origins and protected geographical indications

DEFF Research Database (Denmark)

John, Innocensia Festo; Egelyng, Henrik; Lokina, Azack

2016-01-01

As the world's population is constantly growing, food security will remain on the policy Agenda, particularly in Africa. At the same time, global food systems experience a new wave focusing on local foods and food sovereignty featuring high quality food products of verifiable geographical origin...... of food origin products in Tanzania that have potential for GI certification. The hypothesis was that there are origin products in Tanzania whose unique characteristics are linked to the area of production. Geographical indications can be useful policy instruments contributing to food security...... the diversity of supply of natural and unique quality products and so contribute to enhanced food security....

On the cost/delay tradeoff of wireless delay tolerant geographic routing

OpenAIRE

Tasiopoulos, Argyrios; Tsiaras, Christos; Toumpis, Stavros

2012-01-01

In Delay Tolerant Networks (DTNs), there is a fundamental tradeoff between the aggregate transport cost of a packet and the delay in its delivery. We study this tradeoff in the context of geographical routing in wireless DTNs.We ?rst specify the optimal cost/delay tradeoff, i.e., the tradeoff under optimal network operation, using a dynamic network construction termed the Cost/Delay Evolving Graph (C/DEG) and the Optimal Cost/Delay Curve (OC/DC), a function that gives the minimum possible agg...

Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

Science.gov (United States)

Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

2018-04-01

In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

QUALITY INSPECTION AND ANALYSIS OF THREE-DIMENSIONAL GEOGRAPHIC INFORMATION MODEL BASED ON OBLIQUE PHOTOGRAMMETRY

Directory of Open Access Journals (Sweden)

S. Dong

2018-04-01

Full Text Available In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

Amplify-and-forward relaying in wireless communications

CERN Document Server

Rodriguez, Leonardo Jimenez; Le-Ngoc, Tho

2015-01-01

This SpringerBrief explores the advantage of relaying techniques in addressing the increasing demand for high data rates and reliable services over the air. It demonstrates how to design cost-effective relay systems that provide high spectral efficiency and fully exploit the diversity of the relay channel. The brief covers advances in achievable rates, power allocation schemes, and error performance for half-duplex (HD) and full-duplex (FD) amplify-and-forward (AF) single-relay systems. The authors discuss the capacity and respective optimal power allocation for a wide range of HD protocols ov

Selection combining for noncoherent decode-and-forward relay networks

Directory of Open Access Journals (Sweden)

Nguyen Ha

2011-01-01

Full Text Available Abstract This paper studies a new decode-and-forward relaying scheme for a cooperative wireless network composed of one source, K relays, and one destination and with binary frequency-shift keying modulation. A single threshold is employed to select retransmitting relays as follows: a relay retransmits to the destination if its decision variable is larger than the threshold; otherwise, it remains silent. The destination then performs selection combining for the detection of transmitted information. The average end-to-end bit-error-rate (BER is analytically determined in a closed-form expression. Based on the derived BER, the problem of choosing an optimal threshold or jointly optimal threshold and power allocation to minimize the end-to-end BER is also investigated. Both analytical and simulation results reveal that the obtained optimal threshold scheme or jointly optimal threshold and power-allocation scheme can significantly improve the BER performance compared to a previously proposed scheme.

Exploration of the relationship between geographical environment and human diseases in ancient China.

Science.gov (United States)

Zhu, Jian-Ping

2011-12-01

The Yellow Emperor's Classic of Internal Medicine, created in the Warring States period (475 to 221 BC) described a phenomenon whereby the eastern, western, northern, southern, and central regions were liable to different diseases. It brought forward the principle of treatment in accordance with local conditions. Lv's Spring and Autumn Annals, Huai Nan Tzu (Huainanzi), and the Regiment of Health (Yangshenglun) in the Qin, Han, Wei, Jin, and Southern and Northern Dynasties all describe regional diseases such as goiter (endemic goiter) and yellowish teeth (dental fluorosis) as being caused by geologic and climatic factors. Zhang (miasma), first mentioned in the Han Dynasty, was considered related to the summer heat and dampness particular to the geographical environment of the south. Zhang was further associated with malaria in the Jin Dynasty. General Treatise on the Etiology and Symptomology of Diseases (Zhubingyuanhou Lun), in the Sui Dynasty, held that as a type of poisonous gas, Zhang was the predisposing cause of malaria, seasonal disease, and barbiers, among other conditions. General Guide (Zhinan Zonglun), in the Southern Song Dynasty, regarded Zhang malaria as a separate disease. Healthy Prescription in the Southern Wuling District (Lingnan Weisheng Fang), in the late Song and early Yuan Dynasties, explicitly put forward the concepts of cold Zhang, hot Zhang, and lockjaw Zhang. Guidelines for Treatment of Zhang Malaria (Zhangnue Zhinan), in the Ming Dynasty, maintained that cold Zhang was equivalent to malaria, while hot Zhang and lockjaw Zhang were equivalent to cold damage, the latter of which can be treated by prescriptions for cold damage. Records on Zhang gas and Zhang disease decreased during the Ming and Qing Dynasties.

Clinical application and validation of an iterative forward projection matching algorithm for permanent brachytherapy seed localization from conebeam-CT x-ray projections

Energy Technology Data Exchange (ETDEWEB)

Pokhrel, Damodar; Murphy, Martin J.; Todor, Dorin A.; Weiss, Elisabeth; Williamson, Jeffrey F. [Department of Radiation Oncology, School of Medicine, Virginia Commonwealth University, Richmond, Virginia 23298 (United States)

2010-09-15

Purpose: To experimentally validate a new algorithm for reconstructing the 3D positions of implanted brachytherapy seeds from postoperatively acquired 2D conebeam-CT (CBCT) projection images. Methods: The iterative forward projection matching (IFPM) algorithm finds the 3D seed geometry that minimizes the sum of the squared intensity differences between computed projections of an initial estimate of the seed configuration and radiographic projections of the implant. In-house machined phantoms, containing arrays of 12 and 72 seeds, respectively, are used to validate this method. Also, four {sup 103}Pd postimplant patients are scanned using an ACUITY digital simulator. Three to ten x-ray images are selected from the CBCT projection set and processed to create binary seed-only images. To quantify IFPM accuracy, the reconstructed seed positions are forward projected and overlaid on the measured seed images to find the nearest-neighbor distance between measured and computed seed positions for each image pair. Also, the estimated 3D seed coordinates are compared to known seed positions in the phantom and clinically obtained VariSeed planning coordinates for the patient data. Results: For the phantom study, seed localization error is (0.58{+-}0.33) mm. For all four patient cases, the mean registration error is better than 1 mm while compared against the measured seed projections. IFPM converges in 20-28 iterations, with a computation time of about 1.9-2.8 min/iteration on a 1 GHz processor. Conclusions: The IFPM algorithm avoids the need to match corresponding seeds in each projection as required by standard back-projection methods. The authors' results demonstrate {approx}1 mm accuracy in reconstructing the 3D positions of brachytherapy seeds from the measured 2D projections. This algorithm also successfully localizes overlapping clustered and highly migrated seeds in the implant.

Clinical application and validation of an iterative forward projection matching algorithm for permanent brachytherapy seed localization from conebeam-CT x-ray projections.

Science.gov (United States)

Pokhrel, Damodar; Murphy, Martin J; Todor, Dorin A; Weiss, Elisabeth; Williamson, Jeffrey F

2010-09-01

To experimentally validate a new algorithm for reconstructing the 3D positions of implanted brachytherapy seeds from postoperatively acquired 2D conebeam-CT (CBCT) projection images. The iterative forward projection matching (IFPM) algorithm finds the 3D seed geometry that minimizes the sum of the squared intensity differences between computed projections of an initial estimate of the seed configuration and radiographic projections of the implant. In-house machined phantoms, containing arrays of 12 and 72 seeds, respectively, are used to validate this method. Also, four 103Pd postimplant patients are scanned using an ACUITY digital simulator. Three to ten x-ray images are selected from the CBCT projection set and processed to create binary seed-only images. To quantify IFPM accuracy, the reconstructed seed positions are forward projected and overlaid on the measured seed images to find the nearest-neighbor distance between measured and computed seed positions for each image pair. Also, the estimated 3D seed coordinates are compared to known seed positions in the phantom and clinically obtained VariSeed planning coordinates for the patient data. For the phantom study, seed localization error is (0.58 +/- 0.33) mm. For all four patient cases, the mean registration error is better than 1 mm while compared against the measured seed projections. IFPM converges in 20-28 iterations, with a computation time of about 1.9-2.8 min/ iteration on a 1 GHz processor. The IFPM algorithm avoids the need to match corresponding seeds in each projection as required by standard back-projection methods. The authors' results demonstrate approximately 1 mm accuracy in reconstructing the 3D positions of brachytherapy seeds from the measured 2D projections. This algorithm also successfully localizes overlapping clustered and highly migrated seeds in the implant.

Inverse vs. forward breast IMRT planning

International Nuclear Information System (INIS)

Mihai, Alina; Rakovitch, Eileen; Sixel, Katharina; Woo, Tony; Cardoso, Marlene; Bell, Chris; Ruschin, Mark; Pignol, Jean-Philippe

2005-01-01

Breast intensity-modulated radiation therapy (IMRT) improves dose distribution homogeneity within the whole breast. Previous publications report the use of inverse or forward dose optimization algorithms. Because the inverse technique is not widely available in commercial treatment planning systems, it is important to compare the 2 algorithms. The goal of this work is to compare them on a prospective cohort of 30 patients. Dose distributions were evaluated on differential dose-volume histograms using the volumes receiving more than 105% (V 105 ) and 110% (V 110 ) of the prescribed dose, and on the maximum dose (D max ) or hot spot and the sagittal dose gradient (SDG) being the gradient between the dose on inframammary crease and the dose prescribed. The data were analyzed using Wilcoxon signed rank test. The inverse planning significantly improves the V 105 (mean value 9.7% vs. 14.5%, p = 0.002), and the V 110 (mean value 1.4% vs. 3.2%, p = 0.006). However, the SDG is not statistically significantly different for either algorithm. Looking at the potential impact on skin acute reaction, although there is a significant reduction of V 110 using an inverse algorithm, it is unlikely this 1.6% volume reduction will present a significant clinical advantage over a forward algorithm. Both algorithms are equivalent in removing the hot spots on the inframammary fold, where acute skin reactions occur more frequently using a conventional wedge technique. Based on these results, we recommend that both forward and inverse algorithms should be considered for breast IMRT planning

Forward tracking detectors

Indian Academy of Sciences (India)

Abstract. Forward tracking is an essential part of a detector at the international linear collider (ILC). The requirements for forward tracking are explained and the proposed solutions in the detector concepts are shown.

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

DEFF Research Database (Denmark)

Pedersen, Pauli; Pedersen, Niels Leergaard

2014-01-01

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

TEMPORALLY VARIABLE GEOGRAPHICAL DISTANCE EFFECTS CONTRIBUTE TO THE ASSEMBLY OF ROOT-ASSOCIATED FUNGAL COMMUNITIES

Directory of Open Access Journals (Sweden)

Christopher James Barnes

2016-02-01

Full Text Available Root-associated fungi are key contributors to ecosystem functioning, however the factors which determine community assembly are still relatively poorly understood. This study simultaneously quantified the roles of geographical distance, environmental heterogeneity and time in determining root-associated fungal community composition at the local scale within a short rotation coppice (SRC willow plantation. Culture independent molecular analyses of the root-associated fungal community suggested a strong but temporally variable effect of geographical distance between fungal communities on composition at the local geographical level. Whilst these distance effects were most prevalent on October communities, soil pH had an effect on structuring of the communities throughout the sampling period. Given the temporal variation in the effects of geographical distance and the environment for shaping root-associated fungal communities, there is clearly need for a temporal component to sampling strategies in future investigations of fungal biogeography.

Open-source CFD model for optimization of forward osmosis and reverse osmosis membrane modules

DEFF Research Database (Denmark)

Gruber, Mathias Felix; Aslak, Ulf; Hélix-Nielsen, Claus

2016-01-01

Osmotic membrane separation processes are based on using semi-permeable membranes to remove solutes from a given feed solution. This can happen either as Reverse Osmosis (RO) where a hydraulic pressure is applied to drive separation across the membrane, or as Forward Osmosis (FO) where osmotic...

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models

OpenAIRE

Aprasoff, Jonathan; Donchin, Opher

2011-01-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedb...

On the geographical distribution of induced time-varying crustal magnetic fields

DEFF Research Database (Denmark)

Thebault, E.; Hemant, K.; Hulot, G.

2009-01-01

A long standing question in geomagnetism is whether the time variation of the induced crustal field is a detectable quantity and, if so, at which spatial wavelengths. We tackle this problem with the help of a forward modeling approach using a vertically integrated susceptibility (VIS) grid...... of the Earth's crust. For spherical harmonic degrees 15-90, we estimate the root mean square of the crustal magnetic field secular variation to amount 0.06-0.12 nT/yr at the terrestrial surface between epochs 1960-2002.5. The geographical distribution of the signal shows absolute values reaching 0.65-1.30 n...

Forward Jets and Forward-Central Jets at CMS

CERN Document Server

INSPIRE-00176215

2012-01-01

We report on cross section measurements for inclusive forward jet production and for the simultaneous production of a forward and a central jet in sqrt{s} = 7 TeV pp-collisions. Data collected in 2010, corresponding to an integrated luminosity of 3.14 pb^{-1}, is used for the measurements. Jets in the transverse momentum range pT = 35 - 140 GeV/c are reconstructed with the anti-kT (R = 0.5) algorithm. The extended coverage of large pseudo-rapidities is provided by the Hadronic Forward calorimeter (3.2 < \\eta < 4.7), while central jets are limited to \\eta < 2.8, covered by the main detector components. The two differential cross sections are presented as a function of the jet transverse momentum. Comparisons to next-to-leading order perturbative calculations, and predictions from event generators based on different parton showering mechanisms (PYTHIA and HERWIG) and parton dynamics (CASCADE) are shown.

Review on solving the forward problem in EEG source analysis

Directory of Open Access Journals (Sweden)

Vergult Anneleen

2007-11-01

Full Text Available Abstract Background The aim of electroencephalogram (EEG source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes. Methods While other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field. Results It starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter. In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM, the finite element method (FEM and the finite difference method (FDM. In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative

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

Directory of Open Access Journals (Sweden)

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.

ULTRA: Underwater Localization for Transit and Reconnaissance Autonomy

Science.gov (United States)

Huntsberger, Terrance L.

2013-01-01

This software addresses the issue of underwater localization of unmanned vehicles and the inherent drift in their onboard sensors. The software gives a 2 to 3 factor of improvement over the state-of-the-art underwater localization algorithms. The software determines the localization (position, heading) of an AUV (autonomous underwater vehicle) in environments where there is no GPS signal. It accomplishes this using only the commanded position, onboard gyros/accelerometers, and the bathymetry of the bottom provided by an onboard sonar system. The software does not rely on an onboard bathymetry dataset, but instead incrementally determines the position of the AUV while mapping the bottom. In order to enable long-distance underwater navigation by AUVs, a localization method called ULTRA uses registration of the bathymetry data products produced by the onboard forward-looking sonar system for hazard avoidance during a transit to derive the motion and pose of the AUV in order to correct the DR (dead reckoning) estimates. The registration algorithm uses iterative point matching (IPM) combined with surface interpolation of the Iterative Closest Point (ICP) algorithm. This method was used previously at JPL for onboard unmanned ground vehicle localization, and has been optimized for efficient computational and memory use.

PlayNCool: Opportunistic Network Coding for Local Optimization of Routing in Wireless Mesh Networks

DEFF Research Database (Denmark)

Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Pedersen, Morten Videbæk

2013-01-01

This paper introduces PlayNCool, an opportunistic protocol with local optimization based on network coding to increase the throughput of a wireless mesh network (WMN). PlayNCool aims to enhance current routing protocols by (i) allowing random linear network coding transmissions end-to-end, (ii) r...

Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT

Directory of Open Access Journals (Sweden)

Thu L. N. Nguyen

2016-05-01

Full Text Available Localization in wireless sensor networks (WSNs is one of the primary functions of the intelligent Internet of Things (IoT that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach.

Enhanced Performance of Thin Film Composite Forward Osmosis Membrane by Chemical Post-Treatment

Science.gov (United States)

Liu, Zheng; Chen, Jiangrong; Cao, Zhen; Wang, Jian; Guo, Chungang

2018-01-01

Forward osmosis is an attractive technique in water purification and desalination fields. Enhancement of the forward osmosis membrane performance is essential to the application of this technique. In this study, an optimized chemical post-treatment approach which was used to improve RO membrane performance was employed for enhancing water flux of thin film composite forward osmosis membrane. Home-made polysulfide-based forward osmosis membrane was prepared and nitric acid, sulfuric acid, ethanol, 2-propanol were employed as post-treatment solutions. After a short-term treatment, all the membrane samples manifested water flux enhancement compared with their untreated counterparts. Over 50% increase of water flux had been obtained by ethanol solution treatment. The swelling, changes of hydrophobicity and solvency in both active layer and substrate were verified as the major causes for the enhancement of the water flux. It is noted that the treatment time and solution concentration should be controlled to get both appropriate water flux and reverse salt flux. The results obtained in this study will be useful for further FO membrane development and application.

Contract portfolio optimization for a gasoline supply chain

Science.gov (United States)

Wang, Shanshan

this model, we characterize a simple and easily implementable dynamic contract portfolio policy that would enable the company to dynamically rebalance its supply contract portfolio over time in anticipation of the future market conditions in each individual channel while satisfying the contractual obligations. The optimal policy is a state-dependent base-share contract portfolio policy characterized by a branded base-share level and an unbranded contract commitment combination, given as a function of the initial information state. Using real-world market data, we estimate the model parameters. We also apply an efficient modified policy iteration method to compute the optimal contract portfolio strategies and corresponding profit value. We present computational results in order to obtain insights into the structure of optimal policies, capture the value of the dynamic contract portfolio policy by comparing it with static policies, and illustrate the sensitivity of the optimal contract portfolio and corresponding profit value in terms of the different parameters. Considering the geographic dispersion of different market areas and the pipeline network together with the dynamic contract portfolio optimization problem, we formulate a forward-looking operational model, which could be used by gasoline suppliers for lower-level planning. Finally, we discuss the generalization of the framework to other problems and applications, as well as further research.

Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System

Directory of Open Access Journals (Sweden)

Kulawiak Marcin

2017-12-01

Full Text Available Bluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in the vicinity significantly alters the expected signal range. The paper presents a novel mobile Geographic Information System for measurement, mapping and local as well as online storage of Bluetooth beacon signal strength in semireal time. For the purpose of on-site geovisual analysis of the signal, the application integrates a dedicated interpolation algorithm optimized for low-power devices. The paper discusses the performance and quality of the mapping algorithms in several different test environments.

Comparing the Selected Transfer Functions and Local Optimization Methods for Neural Network Flood Runoff Forecast

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Petr Maca

2014-01-01

Full Text Available The presented paper aims to analyze the influence of the selection of transfer function and training algorithms on neural network flood runoff forecast. Nine of the most significant flood events, caused by the extreme rainfall, were selected from 10 years of measurement on small headwater catchment in the Czech Republic, and flood runoff forecast was investigated using the extensive set of multilayer perceptrons with one hidden layer of neurons. The analyzed artificial neural network models with 11 different activation functions in hidden layer were trained using 7 local optimization algorithms. The results show that the Levenberg-Marquardt algorithm was superior compared to the remaining tested local optimization methods. When comparing the 11 nonlinear transfer functions, used in hidden layer neurons, the RootSig function was superior compared to the rest of analyzed activation functions.

Long Maturity Forward Rates

DEFF Research Database (Denmark)

Christiansen, Charlotte

2001-01-01

The paper aims to improve the knowledge of the empirical properties of the long maturity region of the forward rate curve. Firstly, the theoretical negative correlation between the slope at the long end of the forward rate curve and the term structure variance is recovered empirically and found...... to be statistically significant. Secondly, the expectations hypothesis is analyzed for the long maturity region of the forward rate curve using "forward rate" regressions. The expectations hypothesis is numerically close to being accepted but is statistically rejected. The findings provide mixed support...... for the affine term structure model....

A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments

Directory of Open Access Journals (Sweden)

Shen Shen

2018-02-01

Full Text Available Due to their strong immersion and real-time interactivity, helmet-mounted virtual reality (VR devices are becoming increasingly popular. Based on these devices, an immersive virtual geographic environment (VGE provides a promising method for research into crowd behavior in an emergency. However, the current cheaper helmet-mounted VR devices are not popular enough, and will continue to coexist with personal computer (PC-based systems for a long time. Therefore, a heterogeneous distributed virtual geographic environment (HDVGE could be a feasible solution to the heterogeneous problems caused by various types of clients, and support the implementation of spatiotemporal crowd behavior experiments with large numbers of concurrent participants. In this study, we developed an HDVGE framework, and put forward a set of design principles to define the similarities between the real world and the VGE. We discussed the HDVGE architecture, and proposed an abstract interaction layer, a protocol-based interaction algorithm, and an adjusted dead reckoning algorithm to solve the heterogeneous distributed problems. We then implemented an HDVGE prototype system focusing on subway fire evacuation experiments. Two types of clients are considered in the system: PC, and all-in-one VR. Finally, we evaluated the performances of the prototype system and the key algorithms. The results showed that in a low-latency local area network (LAN environment, the prototype system can smoothly support 90 concurrent users consisting of PC and all-in-one VR clients. HDVGE provides a feasible solution for studying not only spatiotemporal crowd behaviors in normal conditions, but also evacuation behaviors in emergency conditions such as fires and earthquakes. HDVGE could also serve as a new means of obtaining observational data about individual and group behavior in support of human geography research.

Multi objective genetic algorithm to optimize the local heat treatment of a hardenable aluminum alloy

Science.gov (United States)

Piccininni, A.; Palumbo, G.; Franco, A. Lo; Sorgente, D.; Tricarico, L.; Russello, G.

2018-05-01

The continuous research for lightweight components for transport applications to reduce the harmful emissions drives the attention to the light alloys as in the case of Aluminium (Al) alloys, capable to combine low density with high values of the strength-to-weight ratio. Such advantages are partially counterbalanced by the poor formability at room temperature. A viable solution is to adopt a localized heat treatment by laser of the blank before the forming process to obtain a tailored distribution of material properties so that the blank can be formed at room temperature by means of conventional press machines. Such an approach has been extensively investigated for age hardenable alloys, but in the present work the attention is focused on the 5000 series; in particular, the optimization of the deep drawing process of the alloy AA5754 H32 is proposed through a numerical/experimental approach. A preliminary investigation was necessary to correctly tune the laser parameters (focus length, spot dimension) to effectively obtain the annealed state. Optimal process parameters were then obtained coupling a 2D FE model with an optimization platform managed by a multi-objective genetic algorithm. The optimal solution (i.e. able to maximize the LDR) in terms of blankholder force and extent of the annealed region was thus evaluated and validated through experimental trials. A good matching between experimental and numerical results was found. The optimal solution allowed to obtain an LDR of the locally heat treated blank larger than the one of the material either in the wrought condition (H32) either in the annealed condition (H111).

Structured prediction for urban scene semantic segmentation with geographic contex

OpenAIRE

Volpi Michele; Ferrari Vittorio

2015-01-01

In this work we address the problem of semantic segmentation of urban remote sensing images into land cover maps. We propose to tackle this task by learning the geographic context of classes and use it to favor or discourage certain spatial configuration of label assignments. For this reason, we learn from training data two spatial priors enforcing different key aspects of the geographical space: local co-occurrence and relative location of land cover classes. We propose to embed these geogra...

An Improved Forwarding of Diverse Events with Mobile Sinks in Underwater Wireless Sensor Networks.

Science.gov (United States)

Raza, Waseem; Arshad, Farzana; Ahmed, Imran; Abdul, Wadood; Ghouzali, Sanaa; Niaz, Iftikhar Azim; Javaid, Nadeem

2016-11-04

In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput.

Multi-approaches analysis reveals local adaptation in the emmer wheat (Triticum dicoccoides) at macro- but not micro-geographical scale.

Science.gov (United States)

Volis, Sergei; Ormanbekova, Danara; Yermekbayev, Kanat; Song, Minshu; Shulgina, Irina

2015-01-01

Detecting local adaptation and its spatial scale is one of the most important questions of evolutionary biology. However, recognition of the effect of local selection can be challenging when there is considerable environmental variation across the distance at the whole species range. We analyzed patterns of local adaptation in emmer wheat, Triticum dicoccoides, at two spatial scales, small (inter-population distance less than one km) and large (inter-population distance more than 50 km) using several approaches. Plants originating from four distinct habitats at two geographic scales (cold edge, arid edge and two topographically dissimilar core locations) were reciprocally transplanted and their success over time was measured as 1) lifetime fitness in a year of planting, and 2) population growth four years after planting. In addition, we analyzed molecular (SSR) and quantitative trait variation and calculated the QST/FST ratio. No home advantage was detected at the small spatial scale. At the large spatial scale, home advantage was detected for the core population and the cold edge population in the year of introduction via measuring life-time plant performance. However, superior performance of the arid edge population in its own environment was evident only after several generations via measuring experimental population growth rate through genotyping with SSRs allowing counting the number of plants and seeds per introduced genotype per site. These results highlight the importance of multi-generation surveys of population growth rate in local adaptation testing. Despite predominant self-fertilization of T. dicoccoides and the associated high degree of structuring of genetic variation, the results of the QST - FST comparison were in general agreement with the pattern of local adaptation at the two spatial scales detected by reciprocal transplanting.

The methods and applications of optimization of radiation protection

International Nuclear Information System (INIS)

Liu Hua

2007-01-01

Optimization is the most important principle in radiation protection. The present article briefs the concept and up-to-date progress of optimization of protection, introduces some methods used in current optimization analysis, and presents various applications of optimization of protection. The author emphasizes that optimization of protection is a forward-looking iterative process aimed at preventing exposures before they occur. (author)

Layer-by-Layer Assembly for Preparation of High-Performance Forward Osmosis Membrane

Science.gov (United States)

Yang, Libin; Zhang, Jinglong; Song, Peng; Wang, Zhan

2018-01-01

Forward osmosis (FO) membrane with high separation performance is needed to promote its practical applications. Herein, layer-by-layer (LbL) approach was used to prepare a thin and highly cross-linked polyamide layer on a polyacrylonitrile substrate surface to prepare a thin-film composite forward osmosis (TFC-FO) membrane with enhanced FO performance. The effects of monomer concentrations and assembly cycles on the performance of the TFC-FO membranes were systematically investigated. Under the optimal preparation condition, TFC-FO membrane achieved the best performance, exhibiting the water flux of 14.4/6.9 LMH and reverse salt flux of 7.7/3.8 gMH under the pressure retarded osmosis/forward osmosis (PRO/FO) mode using 1M NaCl as the draw against a DI-water feed, and a rejection of 96.1% for 2000 mg/L NaCl aqueous solution. The result indicated that layer-by-layer method was a potential method to regulate the structure and performance of the TFC-FO membrane.

Felling-system and regeneration of pine forests on ecological-genetic-geographical basis

Directory of Open Access Journals (Sweden)

S. N. Sannikov

2015-12-01

Full Text Available A conception of the adaptation of Scots pine populations to the natural regeneration on open sites with the mosaic retained stand and mineralized soil surface on the basis of the ecological-genetic-geographical investigations in the forests of the Russia and the theory of petropsammofitness-pyrofitness (Sannikov S. N., 1983 has been substantiated. The methods of clear cuts with the seeding from surrounding forest, seed curtains and sufficiently extent of the substrate preparation for the pine selfsown have been selected and elaborated as a main organization principle of the system «felling-regeneration» in the plains pine forests of the forest zone. High regeneration efficiency of this system with the application of original aggregate for the optimal mineralization of the soil substrate (with its synchronous loosing has been shown on the example of dominating pine forest types in the subzone for-forest-steppe of the Western Siberia. The silvicultural-ecological and reproductive-genetic advantages of retaining seed curtains instead of separate seed trees have been substantiated. The basic parameters of the system «felling-regeneration», which guarantee a sufficient success of the following pine regeneration in the for-forest-steppe subzone, have been determined with the help of the methods of the mathematical imitation modeling of the pine selfsown density depending on the area and localization of seed curtains, surrounding forest and the extent of the substrate mineralization. The zonal differentiated system of the fellings and measures for the regeneration optimization in the climatically substituting pine forest types in the Western Siberia has been elaborated according to the parameters, studied earlier, on the ecological-genetic-geographical basis. The principles of this system in forest zone come to the clear strip-fellings with insemination of cuts from the seed curtains and forest walls, and to the hollow-fellings with the

Data Assimilation with Optimal Maps

Science.gov (United States)

El Moselhy, T.; Marzouk, Y.

2012-12-01

Tarek El Moselhy and Youssef Marzouk Massachusetts Institute of Technology We present a new approach to Bayesian inference that entirely avoids Markov chain simulation and sequential importance resampling, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. The map is written as a multivariate polynomial expansion and computed efficiently through the solution of a stochastic optimization problem. While our previous work [1] focused on static Bayesian inference problems, we now extend the map-based approach to sequential data assimilation, i.e., nonlinear filtering and smoothing. One scheme involves pushing forward a fixed reference measure to each filtered state distribution, while an alternative scheme computes maps that push forward the filtering distribution from one stage to the other. We compare the performance of these schemes and extend the former to problems of smoothing, using a map implementation of the forward-backward smoothing formula. Advantages of a map-based representation of the filtering and smoothing distributions include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent uniformly-weighted posterior samples without additional evaluations of the dynamical model. Perhaps the main advantage, however, is that the map approach inherently avoids issues of sample impoverishment, since it explicitly represents the posterior as the pushforward of a reference measure, rather than with a particular set of samples. The computational complexity of our algorithm is comparable to state-of-the-art particle filters. Moreover, the accuracy of the approach is controlled via the convergence criterion of the underlying optimization problem. We demonstrate the efficiency and accuracy of the map approach via data assimilation in

Locating food sovereignty: geographical and sectoral distance in the global food system

NARCIS (Netherlands)

M.J. Robbins (Martha Jane)

2013-01-01

textabstractThis paper seeks to problematize the role of local food systems within the food sovereignty movement and as a counter to the logic of the global industrial food system. It answers the question of how food sovereignty, via its tenet of local food systems, addresses the geographical and

Net charge fluctuations and local charge compensation

International Nuclear Information System (INIS)

Fu Jinghua

2006-01-01

We propose net charge fluctuation as a measure of local charge correlation length. It is demonstrated that, in terms of a schematic multiperipheral model, net charge fluctuation satisfies the same Quigg-Thomas relation as satisfied by charge transfer fluctuation. Net charge fluctuations measured in finite rapidity windows depend on both the local charge correlation length and the size of the observation window. When the observation window is larger than the local charge correlation length, the net charge fluctuation only depends on the local charge correlation length, while forward-backward charge fluctuations always have strong dependence on the observation window size. Net charge fluctuations and forward-backward charge fluctuations measured in the present heavy ion experiments show characteristic features similar to those from multiperipheral models. But the data cannot all be understood within this simple model

Geographical imbalances and divides in the scientific production of climate change knowledge

DEFF Research Database (Denmark)

Pasgaard, Maya; Dalsgaard, Bo; Maruyama, Pietro K.

2015-01-01

Studies on scientific production of climate change knowledge show a geographical bias against the developing and more vulnerable regions of the world. If there is limited knowledge exchange between regions, this may deepen global knowledge divides and, thus, potentially hamper adaptive capacities....... Consequently, there is a need to further understand this bias, and, particularly, link it with the exchange of knowledge across borders. We use a world-wide geographical distribution of author affiliations in > 15,000 scientific climate change publications to show that (1) research production mainly takes...... are determined mainly by geographical proximity, common climates, and similar political and economic characteristics. This indicates that political-economic, social and educational-scientific initiatives targeted to enhance local research production and collaborations across geographical-climate module borders...

Automatic Correction Algorithm of Hyfrology Feature Attribute in National Geographic Census

Science.gov (United States)

Li, C.; Guo, P.; Liu, X.

2017-09-01

A subset of the attributes of hydrologic features data in national geographic census are not clear, the current solution to this problem was through manual filling which is inefficient and liable to mistakes. So this paper proposes an automatic correction algorithm of hydrologic features attribute. Based on the analysis of the structure characteristics and topological relation, we put forward three basic principles of correction which include network proximity, structure robustness and topology ductility. Based on the WJ-III map workstation, we realize the automatic correction of hydrologic features. Finally, practical data is used to validate the method. The results show that our method is highly reasonable and efficient.

VECTOR THEORY AND OPTIMAL CHOICE OF ANTIMICROBIAL DRUG FOR LOCAL WOUND TREATMENT

Directory of Open Access Journals (Sweden)

Boyko N. N

2016-12-01

Full Text Available Introduction. One of important problems in the field of medicine and pharmacy is an optimal choice among several alternatives. For example, the choice of drugs for treatment among several analogs, selection of excipients among analogs for development of pharmaceutical forms with optimal pharmacological, technological and economical parameters, etc.The aim of the work is to show the possibility of vector theory use for optimal choice of antimicrobial drugs for local wound treatment among analogs taking into account several criteria at the same time. Materials and methods. For our investigation we have chosen ten drugs with antimicrobial properties for local wound treatment in different pharmaceutical forms (ointment, liniment, water and glycerin solution, tincture. We have determined antibacterial activity of drugs by agar well diffusion method on six test-stain microorganisms: Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, Proteus vulgaris ATCC 4636, Bacillus subtilis ATCC 6633, and Candida albicans ATCC 885-653. Well diameter was 10 mm, the volume of drug in the well was 0.27±0.02 ml, microbial burden of agar upper layer was 107 CFU/ml, and total layer height in Petri dish was 4.0±0.5 mm. In order to integrate various qualitative and quantitative parameters into one index (vector object in multidimensional factors’ space we modify these parameters to non-dimensional normalized values. For this purpose we use a desirability theory. We have chosen the following criteria for optimal choice of the drug: antimicrobial activity (integrated index of drug’s antimicrobial activity, drug’s price, pharmacological and technological index, spectrum of drug’s action on test strains of microorganisms studied. Results and their discussions. Using vector and desirability theory, we have obtained the following range of drugs in decreasing order: Laevomecol ointment, Ioddicerinum, Tincture of Sophora

Feed-Forward versus Feedback Inhibition in a Basic Olfactory Circuit.

Directory of Open Access Journals (Sweden)

Tiffany Kee

2015-10-01

Full Text Available Inhibitory interneurons play critical roles in shaping the firing patterns of principal neurons in many brain systems. Despite difference in the anatomy or functions of neuronal circuits containing inhibition, two basic motifs repeatedly emerge: feed-forward and feedback. In the locust, it was proposed that a subset of lateral horn interneurons (LHNs, provide feed-forward inhibition onto Kenyon cells (KCs to maintain their sparse firing--a property critical for olfactory learning and memory. But recently it was established that a single inhibitory cell, the giant GABAergic neuron (GGN, is the main and perhaps sole source of inhibition in the mushroom body, and that inhibition from this cell is mediated by a feedback (FB loop including KCs and the GGN. To clarify basic differences in the effects of feedback vs. feed-forward inhibition in circuit dynamics we here use a model of the locust olfactory system. We found both inhibitory motifs were able to maintain sparse KCs responses and provide optimal odor discrimination. However, we further found that only FB inhibition could create a phase response consistent with data recorded in vivo. These findings describe general rules for feed-forward versus feedback inhibition and suggest GGN is potentially capable of providing the primary source of inhibition to the KCs. A better understanding of how inhibitory motifs impact post-synaptic neuronal activity could be used to reveal unknown inhibitory structures within biological networks.

Online Robot Dead Reckoning Localization Using Maximum Relative Entropy Optimization With Model Constraints

International Nuclear Information System (INIS)

Urniezius, Renaldas

2011-01-01

The principle of Maximum relative Entropy optimization was analyzed for dead reckoning localization of a rigid body when observation data of two attached accelerometers was collected. Model constraints were derived from the relationships between the sensors. The experiment's results confirmed that accelerometers each axis' noise can be successfully filtered utilizing dependency between channels and the dependency between time series data. Dependency between channels was used for a priori calculation, and a posteriori distribution was derived utilizing dependency between time series data. There was revisited data of autocalibration experiment by removing the initial assumption that instantaneous rotation axis of a rigid body was known. Performance results confirmed that such an approach could be used for online dead reckoning localization.

Forward, Forward Option and No Hedging Which One is the Best for Managing Currency Risk?

Directory of Open Access Journals (Sweden)

Riko Hendrawan

2017-07-01

Full Text Available Bank Indonesia Regulation No.18/18/PBI/2016 concerning foreign exchange transactions against rupiah between banks and domestic parties, indicates that the importance of hedging for business actors in Indonesia. Based on the data of the rupiah exchange rate movement against the dollar from January 2006 to December 2016 shows that the fluctuation of the rupiah against the US dollar tends to weaken, although at some point the observation shows the strengthening of the rupiah against the US dollar. The purpose of this research is to assess impact of Forward, Forward Option and No Hedging Strategy for managing currency exposure between IDR to USD. Using data from January 2006–December 2016 taken from website of Bank Indonesia and Federal Reserve. Total 396 simulations,consists of 132 using Forward simulations, 132 using Forward Option simulations and 132 using No Hedging simulations. Findings from this research show that Forward Option was has no positive contribution in managing currency exposure, No Hedging Strategy has 36,36 percent positive contribution and forward contract has 72,73 percent positive contribution in managing currency exposure. Its means Forward Contract was better than Forward Option and No Hedging Strategies in managing currency exposure.

Geographical influence of heat stress on milk production of Holstein ...

African Journals Online (AJOL)

To model the influence of heat stress on milk production of Holstein dairy herds on pasture in South Africa, the maximum entropy (Maxent) modelling technique was used in a novel approach to model and map optimal milk-producing areas. Geographical locations of farms with top milk-producing Holstein herds on pasture ...

Assessing the Contribution of Sea Surface Temperature and Salinity to Coral δ18O using a Weighted Forward Model

Science.gov (United States)

Horlick, K. A.; Thompson, D. M.; Anderson, D. M.

2015-12-01

The isotopic ratio of 16O/18O (δ18O) in coral carbonate skeletons is a robust, high-resolution proxy for sea surface temperature (SST) and sea surface salinity (SSS) variability predating the instrumental record. Although SST and δ18O-water (correlated to SSS) variability both contribute to the δ18O signal in the coral carbonate archive, the paucity and limited temporal span of SST and SSS instrumental observations limit the ability to differentiate respective SST and SSS contribution to each δ18O record. From instrumental datasets such as HadISST v.3, ERSST, SODA, and Delcroix (2011), we forward model the δ18O ("pseudoproxy") signal using the linear bivariate forward model from Thompson 2011 ("pseudoproxy"= a1(SST)+a2(SSS)). By iteratively weighting (between 0 and 1 by 0.005) the relative contribution of SST and SSS terms to the δ18O "pseudoproxy" following Gorman et al. 2012 method, we derive the percent contributions of SST and SSS to δ18O at each site based on the weights that produce the optimal correlation to the observed coral δ18O signal. A Monte Carlo analysis of error propagation in the weighted and unweighted pseudoproxy time series was used to determine how well the weighted and unweighted forward models captured observed δ18O variance. Across the south-western Pacific (40 sites) we found that SST contributes from less than 8 to more than 78% of the variance. This work builds upon this simple forward model of coral δ18O and improves our understanding of potential sources of differences in the observed and forward modeled δ18O variability. These results may also improve SST and SSS reconstructions from corals by highlighting the reef areas whose coral δ18O signal is most heavily influenced by SST and SSS respectively. Using an inverse approach, creating a transfer function, local SST and SSS could also be reconstructed based on the site-specific weights and observed coral δ18O time series.

Application of nonlinear nodal diffusion generalized perturbation theory to nuclear fuel reload optimization

International Nuclear Information System (INIS)

Maldonado, G.I.; Turinsky, P.J.

1995-01-01

The determination of the family of optimum core loading patterns for pressurized water reactors (PWRs) involves the assessment of the core attributes for thousands of candidate loading patterns. For this reason, the computational capability to efficiently and accurately evaluate a reactor core's eigenvalue and power distribution versus burnup using a nodal diffusion generalized perturbation theory (GPT) model is developed. The GPT model is derived from the forward nonlinear iterative nodal expansion method (NEM) to explicitly enable the preservation of the finite difference matrix structure. This key feature considerably simplifies the mathematical formulation of NEM GPT and results in reduced memory storage and CPU time requirements versus the traditional response-matrix approach to NEM. In addition, a treatment within NEM GPT can account for localized nonlinear feedbacks, such as that due to fission product buildup and thermal-hydraulic effects. When compared with a standard nonlinear iterative NEM forward flux solve with feedbacks, the NEM GPT model can execute between 8 and 12 times faster. These developments are implemented within the PWR in-core nuclear fuel management optimization code FORMOSA-P, combining the robustness of its adaptive simulated annealing stochastic optimization algorithm with an NEM GPT neutronics model that efficiently and accurately evaluates core attributes associated with objective functions and constraints of candidate loading patterns

Forward tracking detectors

Indian Academy of Sciences (India)

At the ILC many of the most important physics reactions are central, so that the forward region, which is suppressed by the cos θ phase space factor often is a bit neglected. However, many processes at the ILC are peaked in the forward region like Bhabha scattering or W-pair production [1]. Fermion pair production has its.

Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

Science.gov (United States)

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

Random-growth urban model with geographical fitness

Science.gov (United States)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

Optimized curve design for image analysis using localized geodesic distance transformations

Science.gov (United States)

Braithwaite, Billy; Niska, Harri; Pöllänen, Irene; Ikonen, Tiia; Haataja, Keijo; Toivanen, Pekka; Tolonen, Teemu

2015-03-01

We consider geodesic distance transformations for digital images. Given a M × N digital image, a distance image is produced by evaluating local pixel distances. Distance Transformation on Curved Space (DTOCS) evaluates shortest geodesics of a given pixel neighborhood by evaluating the height displacements between pixels. In this paper, we propose an optimization framework for geodesic distance transformations in a pattern recognition scheme, yielding more accurate machine learning based image analysis, exemplifying initial experiments using complex breast cancer images. Furthermore, we will outline future research work, which will complete the research work done for this paper.

Local breast cancer spatial patterning: a tool for community health resource allocation to address local disparities in breast cancer mortality.

Directory of Open Access Journals (Sweden)

Dana M Brantley-Sieders

Full Text Available Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.

U.S.-Mexico Border Geographic Information System

Science.gov (United States)

Parcher, Jean W.

2008-01-01

Geographic Information Systems (GIS) and the development of extensive geodatabases have become invaluable tools for addressing a variety of contemporary societal issues and for making predictions about the future. The United States-Mexico Geographic Information System (USMX-GIS) is based on fundamental datasets that are produced and/or approved by the national geography agencies of each country, the U.S. Geological Survey (USGS) and the Instituto Nacional de Estadistica Y Geografia (INEGI) of Mexico, and the International Boundary and Water Commission (IBWC). The data are available at various scales to allow both regional and local analysis. The USGS and the INEGI have an extensive history of collaboration for transboundary mapping including exchanging digital technology and developing methods for harmonizing seamless national level geospatial datasets for binational environmental monitoring, urban growth analysis, and other scientific applications.

Geographic assistance of decontamination strategy elaboration

International Nuclear Information System (INIS)

Davydchuk, V.; Arapis, G.

1996-01-01

Those who elaborates the strategy of decontamination of vast territories is to take into consideration the heterogeneity of such elements of landscape as relief, lithology, humidity and types of soils and, vegetation, both on local and regional level. Geographic assistance includes evaluation of efficacy of decontamination technologies in different natural conditions, identification of areas of their effective application and definition of ecological damage, estimation of balances of the radionuclides in the landscapes to create background of the decontamination strategy

Geographically isolated wetlands: Rethinking a misnomer

Science.gov (United States)

Mushet, David M.; Calhoun, Aram J.K.; Alexander, Laurie C.; Cohen, Matthew J.; DeKeyser, Edward S.; Fowler, Laurie G.; Lane, Charles R.; Lang, Megan W.; Rains, Mark C.; Walls, Susan

2015-01-01

We explore the category “geographically isolated wetlands” (GIWs; i.e., wetlands completely surrounded by uplands at the local scale) as used in the wetland sciences. As currently used, the GIW category (1) hampers scientific efforts by obscuring important hydrological and ecological differences among multiple wetland functional types, (2) aggregates wetlands in a manner not reflective of regulatory and management information needs, (3) implies wetlands so described are in some way “isolated,” an often incorrect implication, (4) is inconsistent with more broadly used and accepted concepts of “geographic isolation,” and (5) has injected unnecessary confusion into scientific investigations and discussions. Instead, we suggest other wetland classification systems offer more informative alternatives. For example, hydrogeomorphic (HGM) classes based on well-established scientific definitions account for wetland functional diversity thereby facilitating explorations into questions of connectivity without an a priori designation of “isolation.” Additionally, an HGM-type approach could be used in combination with terms reflective of current regulatory or policymaking needs. For those rare cases in which the condition of being surrounded by uplands is the relevant distinguishing characteristic, use of terminology that does not unnecessarily imply isolation (e.g., “upland embedded wetlands”) would help alleviate much confusion caused by the “geographically isolated wetlands” misnomer.

Efficient power allocation for fixed-gain amplify-and-forward relaying in rayleigh fading

KAUST Repository

Zafar, Ammar

2013-06-01

In this paper, we study power allocation strategies for a fixed-gain amplify-and-forward relay network employing multiple relays. We consider two optimization problems for the relay network: 1) optimal power allocation to maximize the end-to-end signal-to-noise ratio (SNR) and 2) minimizing the total consumed power while maintaining the end-to-end SNR over a threshold value. We assume that the relays have knowledge of only the channel statistics of all the links. We show that the SNR maximization problem is concave and the power minimization problem is convex. Hence, we solve the problems through convex programming. Numerical results show the benefit of allocating power optimally rather than uniformly. © 2013 IEEE.

Power forward curves: a managerial perspective

International Nuclear Information System (INIS)

Nagarajan, Shankar

1999-01-01

This chapter concentrates on managerial application of power forward curves, and examines the determinants of electricity prices such as transmission constraints, its inability to be stored in a conventional way, its seasonality and weather dependence, the generation stack, and the swing risk. The electricity forward curve, classical arbitrage, constructing a forward curve, volatilities, and electricity forward curve models such as the jump-diffusion model, the mean-reverting heteroscedastic volatility model, and an econometric model of forward prices are examined. A managerial perspective of the applications of the forward curve is presented covering plant valuation, capital budgeting, performance measurement, product pricing and structuring, asset optimisation, valuation of transmission options, and risk management

Hydroclimate Forecasts in Ethiopia: Benefits, Impediments, and Ways Forward

Science.gov (United States)

Block, P. J.

2014-12-01

Numerous hydroclimate forecast models, tools, and guidance exist for application across Ethiopia and East Africa in the agricultural, water, energy, disasters, and economic sectors. This has resulted from concerted local and international interdisciplinary efforts, yet little evidence exists of rapid forecast uptake and use. We will review projected benefits and gains of seasonal forecast application, impediments, and options for the way forward. Specific case studies regarding floods, agricultural-economic links, and hydropower will be reviewed.

CFD-based optimization in plastics extrusion

Science.gov (United States)

Eusterholz, Sebastian; Elgeti, Stefanie

2018-05-01

This paper presents novel ideas in numerical design of mixing elements in single-screw extruders. The actual design process is reformulated as a shape optimization problem, given some functional, but possibly inefficient initial design. Thereby automatic optimization can be incorporated and the design process is advanced, beyond the simulation-supported, but still experience-based approach. This paper proposes concepts to extend a method which has been developed and validated for die design to the design of mixing-elements. For simplicity, it focuses on single-phase flows only. The developed method conducts forward-simulations to predict the quasi-steady melt behavior in the relevant part of the extruder. The result of each simulation is used in a black-box optimization procedure based on an efficient low-order parameterization of the geometry. To minimize user interaction, an objective function is formulated that quantifies the products' quality based on the forward simulation. This paper covers two aspects: (1) It reviews the set-up of the optimization framework as discussed in [1], and (2) it details the necessary extensions for the optimization of mixing elements in single-screw extruders. It concludes with a presentation of first advances in the unsteady flow simulation of a metering and mixing section with the SSMUM [2] using the Carreau material model.

URBAN TRAFFIC ACCIDENT ANALYSIS BY USING GEOGRAPHIC INFORMATION SYSTEM

Directory of Open Access Journals (Sweden)

Meltem SAPLIOĞLU

2006-03-01

Full Text Available In recent years, traffic accidents that cause more social and economic losses than that of natural disasters,have become a national problem in Turkey. To solve this problem and to reduce the casualties, road safety programs are tried to be developed. It is necessary to develop the most effective measures with low investment cost due to limited budgets allocated to such road safety programs. The most important program is to determine dangerous locations of traffic accidents and to improve these sections from the road safety view point. New Technologies are driving a cycle of continuous improvement that causes rapid changes in the traffic engineering and any engineering services within it. It is obvious that this developed services will be the potential for forward-thinking engineering studies to take a more influence role. In this study, Geographic Information System (GIS was used to identify the hazardous locations of traffic accidents in Isparta. Isparta city map was digitized by using Arcinfo 7.21. Traffic accident reports occurred between 1998-2002 were obtained from Directory of Isparta Traffic Region and had been used to form the database. Topology was set up by using Crash Diagrams and Geographic Position Reference Systems. Tables are formed according to the obtained results and interpreted.

Geographic Names

Data.gov (United States)

Minnesota Department of Natural Resources — The Geographic Names Information System (GNIS), developed by the United States Geological Survey in cooperation with the U.S. Board of Geographic Names, provides...

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

Directory of Open Access Journals (Sweden)

Minodora URSĂCESCU

2012-06-01

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

Single-hidden-layer feed-forward quantum neural network based on Grover learning.

Science.gov (United States)

Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

2013-09-01

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Optimal Design of a Push-Pull-Forward Half-Bridge (PPFHB) Bidirectional DC–DC Converter With Variable Input Voltage

DEFF Research Database (Denmark)

Zhang, Zhe; Thomsen, Ole Cornelius; Andersen, Michael A. E.

2012-01-01

This paper presents a low-cost bidirectional isolated dc–dc converte, derived from dual-active-bridge converter for the power sources with variable output voltage like supercapacitors. The proposed converter consists of push-pull-forward circuit half-bridge circuit (PPFHB) and a high-frequency tr......This paper presents a low-cost bidirectional isolated dc–dc converte, derived from dual-active-bridge converter for the power sources with variable output voltage like supercapacitors. The proposed converter consists of push-pull-forward circuit half-bridge circuit (PPFHB) and a high...

E-Learning in Malaysia: Moving forward in Open Distance Learning

Science.gov (United States)

Abas, Zoraini Wati

2009-01-01

Many higher education institutions have embarked on e-learning as a means to support their learning and teaching activities. In distance learning institutions, e-learning has enabled them to reach out to students dispersed over a wide geographical area, locally and internationally. In some countries, e-learning has also given students the…

A mixed incoherent feed-forward loop contributes to the regulation of bacterial photosynthesis genes.

Science.gov (United States)

Mank, Nils N; Berghoff, Bork A; Klug, Gabriele

2013-03-01

Living cells use a variety of regulatory network motifs for accurate gene expression in response to changes in their environment or during differentiation processes. In Rhodobacter sphaeroides, a complex regulatory network controls expression of photosynthesis genes to guarantee optimal energy supply on one hand and to avoid photooxidative stress on the other hand. Recently, we identified a mixed incoherent feed-forward loop comprising the transcription factor PrrA, the sRNA PcrZ and photosynthesis target genes as part of this regulatory network. This point-of-view provides a comparison to other described feed-forward loops and discusses the physiological relevance of PcrZ in more detail.

Do players reason by forward induction in dynamic perfect information games?

Directory of Open Access Journals (Sweden)

Sujata Ghosh

2016-06-01

Full Text Available We conducted an experiment where participants played a perfect-information game against a computer, which was programmed to deviate often from its backward induction strategy right at the beginning of the game. Participants knew that in each game, the computer was nevertheless optimizing against some belief about the participant's future strategy. It turned out that in the aggregate, participants were likely to respond in a way which is optimal with respect to their best-rationalization extensive form rationalizability conjecture - namely the conjecture that the computer is after a larger prize than the one it has foregone, even when this necessarily meant that the computer has attributed future irrationality to the participant when the computer made the first move in the game. Thus, it appeared that participants applied forward induction. However, there exist alternative explanations for the choices of most participants; for example, choices could be based on the extent of risk aversion that participants attributed to the computer in the remainder of the game, rather than to the sunk outside option that the computer has already foregone at the beginning of the game. For this reason, the results of the experiment do not yet provide conclusive evidence for Forward Induction reasoning on the part of the participants.

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

Science.gov (United States)

Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local

A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Directory of Open Access Journals (Sweden)

Zhigang Lian

2010-01-01

Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

The relationship between the bladder volume and optimal treatment planning in definitive radiotherapy for localized prostate cancer

International Nuclear Information System (INIS)

Nakamura, Naoki; Sekiguchi, Kenji; Akahane, Keiko; Shikama, Naoto; Takahashi, Osamu; Hama, Yukihiro; Nakagawa, Keiichi

2012-01-01

Background and purpose: There is no current consensus regarding the optimal bladder volumes in definitive radiotherapy for localized prostate cancer. The aim of this study was to clarify the relationship between the bladder volume and optimal treatment planning in radiotherapy for localized prostate cancer. Material and methods: Two hundred and forty-three patients underwent definitive radiotherapy with helical tomotherapy for intermediate- and high-risk localized prostate cancer. The prescribed dose defined as 95 % of the planning target volume (PTV) receiving 100 % of the prescription dose was 76 Gy in 38 fractions. The clinical target volume (CTV) was defined as the prostate with a 5-mm margin and 2 cm of the proximal seminal vesicle. The PTV was defined as the CTV with a 5-mm margin. Treatment plans were optimized to satisfy the dose constraints defined by in-house protocols for PTV and organs at risk (rectum wall, bladder wall, sigmoid colon and small intestine). If all dose constraints were satisfied, the plan was defined as an optimal plan (OP). Results: An OP was achieved with 203 patients (84%). Mean bladder volume (± 1 SD) was 266 ml (± 130 ml) among those with an OP and 214 ml (±130 ml) among those without an OP (p = 0.02). Logistic regression analysis also showed that bladder volumes below 150 ml decreased the possibility of achieving an OP. However, the percentage of patients with an OP showed a plateau effect at bladder volumes above 150 ml. Conclusions. Bladder volume is a significant factor affecting OP rates. However, our results suggest that bladder volumes exceeding 150 ml may not help meet planning dose constraints

A new and fast image feature selection method for developing an optimal mammographic mass detection scheme.

Science.gov (United States)

Tan, Maxine; Pu, Jiantao; Zheng, Bin

2014-08-01

Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Among these four methods, SFFS has highest efficacy, which takes 3%-5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC results of the ANNs optimized

LHC production of forward-center and forward-forward di-jets in the kt-factorization and transverse dependent unintegrated parton distribution frameworks

Science.gov (United States)

Modarres, M.; Masouminia, M. R.; Aminzadeh Nik, R.; Hosseinkhani, H.; Olanj, N.

2017-09-01

The present work is devoted to study the high-energy QCD events, such as the di-jet productions from proton-proton inelastic collisions at the LHC in the forward-center and the forward-forward configurations. This provides us with much valuable case study, since such phenomena can provide a direct glimpse into the partonic behavior of a hadron in a dominant gluonic region. We use the unintegrated parton distribution functions (UPDF) in the kt-factorization framework. The UPDF of Kimber et al. (KMR) and Martin et al. (MRW) are generated in the leading order (LO) and next-to-leading order (NLO), using the Harland-Lang et al. (MMHT2014) PDF libraries. While working in the forward-center and the forward-forward rapidity sectors, one can probe the parton densities at very low longitudinal momentum fractions (x). Such a model computation can provide simpler analytic description of data with respect to existing formalisms such as perturbative QCD. The differential cross-section calculations are performed at the center of mass energy of 7 TeV corresponding to CMS collaboration measurement. It is shown that the gluonic jet productions are dominant and a good description of data as well as other theoretical attempts (i.e. KS-linear, KS-nonlinear and rcBK) is obtained. The uncertainty of the calculations is derived by manipulating the hard scale of the processes by a factor of two. This conclusion is achieved, due to the particular visualization of the angular ordering constraint (AOC), that is incorporated in the definition of these UPDF.

Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

Directory of Open Access Journals (Sweden)

Kaijun Zhou

2017-09-01

Full Text Available The Jump Point Search (JPS algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS map, including Global Positioning System (GPS position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH, the Rapidly Exploring Random Tree (RRT, A*, and the Probabilistic Roadmaps (PRM algorithms. Furthermore, JPS is validated usefully in the structured urban environment.

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes

Energy Technology Data Exchange (ETDEWEB)

Zhou, Qianqian; Blohm, Andrew; Liu, Bo

2017-04-01

A planning framework is developed to optimize runoff control schemes at scales relevant for regional planning at an early stage. The framework employs less sophisticated modeling approaches to allow a practical application in developing regions with limited data sources and computing capability. The methodology contains three interrelated modules: (1)the geographic information system (GIS)-based hydrological module, which aims at assessing local hydrological constraints and potential for runoff control according to regional land-use descriptions; (2)the grading module, which is built upon the method of fuzzy comprehensive evaluation. It is used to establish a priority ranking system to assist the allocation of runoff control targets at the subdivision level; and (3)the genetic algorithm-based optimization module, which is included to derive Pareto-based optimal solutions for mesolevel allocation with multiple competing objectives. The optimization approach describes the trade-off between different allocation plans and simultaneously ensures that all allocation schemes satisfy the minimum requirement on runoff control. Our results highlight the importance of considering the mesolevel allocation strategy in addition to measures at macrolevels and microlevels in urban runoff management. (C) 2016 American Society of Civil Engineers.

Geographic Media Literacy

Science.gov (United States)

Lukinbeal, Chris

2014-01-01

While the use of media permeates geographic research and pedagogic practice, the underlying literacies that link geography and media remain uncharted. This article argues that geographic media literacy incorporates visual literacy, information technology literacy, information literacy, and media literacy. Geographic media literacy is the ability…

Experimental effects of climate messages vary geographically

Science.gov (United States)

Zhang, Baobao; van der Linden, Sander; Mildenberger, Matto; Marlon, Jennifer R.; Howe, Peter D.; Leiserowitz, Anthony

2018-05-01

Social science scholars routinely evaluate the efficacy of diverse climate frames using local convenience or nationally representative samples1-5. For example, previous research has focused on communicating the scientific consensus on climate change, which has been identified as a `gateway' cognition to other key beliefs about the issue6-9. Importantly, although these efforts reveal average public responsiveness to particular climate frames, they do not describe variation in message effectiveness at the spatial and political scales relevant for climate policymaking. Here we use a small-area estimation method to map geographical variation in public responsiveness to information about the scientific consensus as part of a large-scale randomized national experiment (n = 6,301). Our survey experiment finds that, on average, public perception of the consensus increases by 16 percentage points after message exposure. However, substantial spatial variation exists across the United States at state and local scales. Crucially, responsiveness is highest in more conservative parts of the country, leading to national convergence in perceptions of the climate science consensus across diverse political geographies. These findings not only advance a geographical understanding of how the public engages with information about scientific agreement, but will also prove useful for policymakers, practitioners and scientists engaged in climate change mitigation and adaptation.

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

Science.gov (United States)

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

2014-12-01

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

Conservation laws arising in the study of forward-forward Mean-Field Games

KAUST Repository

Gomes, Diogo A.; Nurbekyan, Levon; Sedjro, Marc

2017-01-01

We consider forward-forward Mean Field Game (MFG) models that arise in numerical approximations of stationary MFGs. First, we establish a link between these models and a class of hyperbolic conservation laws as well as certain nonlinear wave equations. Second, we investigate existence and long-time behavior of solutions for such models.

Conservation laws arising in the study of forward-forward Mean-Field Games

KAUST Repository

Gomes, Diogo A.

2017-04-24

We consider forward-forward Mean Field Game (MFG) models that arise in numerical approximations of stationary MFGs. First, we establish a link between these models and a class of hyperbolic conservation laws as well as certain nonlinear wave equations. Second, we investigate existence and long-time behavior of solutions for such models.

Geographic analysis of road accident severity index in Nigeria.

Science.gov (United States)

Iyanda, Ayodeji E

2018-05-28

Before 2030, deaths from road traffic accidents (RTAs) will surpass cerebrovascular disease, tuberculosis, and HIV/AIDS. Yet, there is little knowledge on the geographic distribution of RTA severity in Nigeria. Accident Severity Index is the proportion of deaths that result from a road accident. This study analysed the geographic pattern of RTA severity based on the data retrieved from Federal Road Safety Corps (FRSC). The study predicted a two-year data from a historic road accident data using exponential smoothing technique. To determine spatial autocorrelation, global and local indicators of spatial association were implemented in a geographic information system. Results show significant clusters of high RTA severity among states in the northeast and the northwest of Nigeria. Hence, the findings are discussed from two perspectives: Road traffic law compliance and poor emergency response. Conclusion, the severity of RTA is high in the northern states of Nigeria, hence, RTA remains a public health concern.

A framework for simultaneous aerodynamic design optimization in the presence of chaos

Energy Technology Data Exchange (ETDEWEB)

Günther, Stefanie, E-mail: stefanie.guenther@scicomp.uni-kl.de [TU Kaiserslautern, Chair for Scientific Computing, Paul-Ehrlich-Straße 34, 67663 Kaiserslautern (Germany); Gauger, Nicolas R. [TU Kaiserslautern, Chair for Scientific Computing, Paul-Ehrlich-Straße 34, 67663 Kaiserslautern (Germany); Wang, Qiqi [Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States)

2017-01-01

Integrating existing solvers for unsteady partial differential equations into a simultaneous optimization method is challenging due to the forward-in-time information propagation of classical time-stepping methods. This paper applies the simultaneous single-step one-shot optimization method to a reformulated unsteady constraint that allows for both forward- and backward-in-time information propagation. Especially in the presence of chaotic and turbulent flow, solving the initial value problem simultaneously with the optimization problem often scales poorly with the time domain length. The new formulation relaxes the initial condition and instead solves a least squares problem for the discrete partial differential equations. This enables efficient one-shot optimization that is independent of the time domain length, even in the presence of chaos.

Location based Network Optimizations for Mobile Wireless Networks

DEFF Research Database (Denmark)

Nielsen, Jimmy Jessen

selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...

Simulation Results of Double Forward Converter

Directory of Open Access Journals (Sweden)

P. Vijaya KUMAR

2009-12-01

Full Text Available This work aims to find a better forward converter for DC to DC conversion.Simulation of double forward converter in SMPS system is discussed in this paper. Aforward converter with RCD snubber to synchronous rectifier and/or to current doubleris also discussed. The evolution of the forward converter is first reviewed in a tutorialfashion. Performance parameters are discussed including operating principle, voltageconversion ratio, efficiency, device stress, small-signal dynamics, noise and EMI. Itscircuit operation and its performance characteristics of the forward converter with RCDsnubber and double forward converter are described and the simulation results arepresented.

DESTINATION MARKETING STRATEGY IN BALI THROUGH OPTIMIZING THE POTENTIAL OF LOCAL PRODUCTS

Directory of Open Access Journals (Sweden)

I Gusti Ayu Oka Suryawardani

2014-03-01

Full Text Available This study was designed to study destination marketing strategy in Bali through optimizing the potential of local products. Seventy nine of hotel managers were interviewed based on cluster sampling method to gain their point of view. The results show that destination must build their images around unique attributes that provide them sustainable competitive advantage including its attraction which should be designed to meet the needs of the target market and should be served by local products. The results also show that hotel managers thought that foreign tourists always preferred imported products, meanwhile previous statistical results indicate that foreign tourists significantly look for local products. There is a need to encourage hotel managers to change their perception and attitude about local and imported products. In fact, hoteliers expressed willingness to use local products as long as these meet the quality standard. As tourism involves four types of activities, namely something to see, something to do, something to buy, something to learn, destination product development could be focused in the above activities through offering foreign tourist, such as to stay in hotels, homestays or villas owned by Balinese; to eat in restaurants owned by Balinese by choosing the authentic local foods that are using local meat, seafood and vegetables, exotic local fruits and beverages; and to buy products that are produced by the Balinese. By promoting vacation on the real Balinese atmosphere such as stay in accommodations owned by the Balinese supported by the authenticity of local Balinese foods, fruits and beverages, these will strengthen the local economy, so the benefit of tourism development can be more beneficial to the local Balinese. The results suggests that destination management related to improvement of service and hospitality are really important through improvement of human resource by giving training to their employees, educate

Optimization of mining design of Hongwei uranium mine

International Nuclear Information System (INIS)

Wu Sanmao; Yuan Baixiang

2012-01-01

Combined with the mining conditions of Hongwei uranium mine, optimization schemes for hoisting cage, mine drainge,ore transport, mine wastewater treatment, power-supply system,etc are put forward in the mining design of the mine. Optimized effects are analyzed from the aspects of technique, economy, and energy saving and reducing emissions. (authors)

Modelling and Optimal Control of Typhoid Fever Disease with Cost-Effective Strategies.

Science.gov (United States)

Tilahun, Getachew Teshome; Makinde, Oluwole Daniel; Malonza, David

2017-01-01

We propose and analyze a compartmental nonlinear deterministic mathematical model for the typhoid fever outbreak and optimal control strategies in a community with varying population. The model is studied qualitatively using stability theory of differential equations and the basic reproductive number that represents the epidemic indicator is obtained from the largest eigenvalue of the next-generation matrix. Both local and global asymptotic stability conditions for disease-free and endemic equilibria are determined. The model exhibits a forward transcritical bifurcation and the sensitivity analysis is performed. The optimal control problem is designed by applying Pontryagin maximum principle with three control strategies, namely, the prevention strategy through sanitation, proper hygiene, and vaccination; the treatment strategy through application of appropriate medicine; and the screening of the carriers. The cost functional accounts for the cost involved in prevention, screening, and treatment together with the total number of the infected persons averted. Numerical results for the typhoid outbreak dynamics and its optimal control revealed that a combination of prevention and treatment is the best cost-effective strategy to eradicate the disease.

Forward energy measurement with CMS

CERN Document Server

Kheyn, Lev

2016-01-01

Energy flow is measured in the forward region of CMS at pseudorapidities up to 6.6 in pp interactions at 13 TeV with forward (HF) and very forward (CASTOR) calorimeters. The results are compared to model predictions. The CMS results at different center-of-mass energies are intercompared using pseudorapidity variable shifted by beam rapidity, thus studying applicability of hypothesis of limiting fragmentation.

Intelligent structural optimization: Concept, Model and Methods

International Nuclear Information System (INIS)

Lu, Dagang; Wang, Guangyuan; Peng, Zhang

2002-01-01

Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

A computational framework for the optimal design of morphing processes in locally activated smart material structures

International Nuclear Information System (INIS)

Wang, Shuang; Brigham, John C

2012-01-01

A proof-of-concept study is presented for a strategy to obtain maximally efficient and accurate morphing structures composed of active materials such as shape memory polymers (SMP) through synchronization of adaptable and localized activation and actuation. The work focuses on structures or structural components entirely composed of thermo-responsive SMP, and particularly utilizes the ability of such materials to display controllable variable stiffness. The study presents and employs a computational inverse mechanics approach that combines a computational representation of the SMP thermo-mechanical behavior with a nonlinear optimization algorithm to determine location, magnitude and sequencing of the activation and actuation to obtain a desired shape change subject to design objectives such as prevention of damage. Two numerical examples are presented in which the synchronization of the activation and actuation and the location of activation excitation were optimized with respect to the combined thermal and mechanical energy for design concepts in morphing skeletal structural components. In all cases the concept of localized activation along with the optimal design strategy were able to produce far more energy efficient morphing structures and more accurately reach the desired shape change in comparison to traditional methods that require complete structural activation prior to actuation. (paper)

Leading tip drives soma translocation via forward F-actin flow during neuronal migration.

Science.gov (United States)

He, Min; Zhang, Zheng-hong; Guan, Chen-bing; Xia, Di; Yuan, Xiao-bing

2010-08-11

Neuronal migration involves coordinated extension of the leading process and translocation of the soma, but the relative contribution of different subcellular regions, including the leading process and cell rear, in driving soma translocation remains unclear. By local manipulation of cytoskeletal components in restricted regions of cultured neurons, we examined the molecular machinery underlying the generation of traction force for soma translocation during neuronal migration. In actively migrating cerebellar granule cells in culture, a growth cone (GC)-like structure at the leading tip exhibits high dynamics, and severing the tip or disrupting its dynamics suppressed soma translocation within minutes. Soma translocation was also suppressed by local disruption of F-actin along the leading process but not at the soma, whereas disrupting microtubules along the leading process or at the soma accelerated soma translocation. Fluorescent speckle microscopy using GFP-alpha-actinin showed that a forward F-actin flow along the leading process correlated with and was required for soma translocation, and such F-actin flow depended on myosin II activity. In migrating neurons, myosin II activity was high at the leading tip but low at the soma, and increasing or decreasing this front-to-rear difference accelerated or impeded soma advance. Thus, the tip of the leading process actively pulls the soma forward during neuronal migration through a myosin II-dependent forward F-actin flow along the leading process.

Optimal Aerodynamic Design of Conventional and Coaxial Helicopter Rotors in Hover and Forward Flight

Science.gov (United States)

2015-12-28

graduate career a fun and (at times) productive pursuit. I owe a great deal to my parents , Kevin and Lisa, for their unconditional support. Finally...forward flight. Orchard and Newman [6] investigated fundamental design features of compound helicopters using a wing, a single rotor, and a propul- sor... style compound. For the case considered here, the coaxial rotors are unconstrained in lift offset. If a wing were used in a case that also included a lift

Contribution to the development of a food guide in Benin: linear programming for the optimization of local diets.

Science.gov (United States)

Levesque, Sarah; Delisle, Hélène; Agueh, Victoire

2015-03-01

Food guides are important tools for nutrition education. While developing a food guide in Benin, the objective was to determine the daily number of servings per food group and the portion sizes of common foods to be recommended. Linear programming (LP) was used to determine, for each predefined food group, the optimal number and size of servings of commonly consumed foods. Two types of constraints were introduced into the LP models: (i) WHO/FAO Recommended Nutrient Intakes and dietary guidelines for the prevention of chronic diseases; and (ii) dietary patterns based on local food consumption data recently collected in southern Benin in 541 adults. Dietary intakes of the upper tertile of participants for diet quality based on prevention and micronutrient adequacy scores were used in the LP algorithms. Southern area of the Republic of Benin. Local key-players in nutrition (n 30) from the government, academic institutions, international organizations and civil society were partners in the development of the food guide directed at the population. The number of servings per food group and the portion size for eight age-sex groups were determined. For four limiting micronutrients (Fe, Ca, folate and Zn), local diets could be optimized to meet only 70 % of the Recommended Nutrient Intakes, not 100 %. It was possible to determine the daily number of servings and the portion sizes of common foods that can be recommended in Benin with the help of LP to optimize local diets, although Recommended Nutrient Intakes were not fully met for a few critical micronutrients.

OPTIMIZING LOCAL BUDGET BALANCING IN ROMANIA

Directory of Open Access Journals (Sweden)

Gyorgy Adina Crsitina

2011-07-01

Full Text Available The importance of the local public finance is growing in accordance with the increasing proportion of the decentralization process. The mechanism of resource allocation, and especially the allocation criteria used, constitutes subjects of debate. Our objective pursued is to assess whether the avoidance of the first step for balancing the allocation of funds can provide enhanced fairness in balancing the local budgets across the country. Local budgets in Romania receive significant resources from the state budget in the form of amounts and quotas distributed from certain taxes, which are revenues for the state budget. Some of these amounts are designed to balance the local budgets. The distribution of funds from the state budget to the local budgets requires two steps. Firstly, the amounts are divided by county, secondly, these amounts are directed within the county especially towards localities which have a lower financial standing. Given the significant disparities between counties, we believe that this mechanism does not ensure fairness in the allocation because the funds distributed according to the first step may not use fair criteria to meet the requirements for balanced local budgets. Therefore, we intend to simulate a balanced allocation of national funds for eliminating the first step that produces the most significant inequities. Direct application of the second step of allocation, with its two phases, will provide more funds serving those local administrative units for the income tax per capita is lower than the national average. Comparing the values allocated for the year 2011 with those obtained in the simulation we will examine changes that occur after the application of this method which seems to be more equitable and appropriate. This work was supported by CNCSISUEFISCSU, project number PNII-IDEI 1780/2008

Optimal networks of future gravitational-wave telescopes

Science.gov (United States)

Raffai, Péter; Gondán, László; Heng, Ik Siong; Kelecsényi, Nándor; Logue, Josh; Márka, Zsuzsa; Márka, Szabolcs

2013-08-01

We aim to find the optimal site locations for a hypothetical network of 1-3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ˜58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms).

OPTIMAL LOCALIZATION OF SPECIAL TRANSPORT AND LOGISTIC FOODSTUFF CENTRE

Directory of Open Access Journals (Sweden)

A. M. Pasichnyk

2010-06-01

Full Text Available On the basis of research of statistic indices of custom-house, the population and geographic location of cities of Donetsk region, the method of calculation of optimum placing of the specialized transport-logistical centre of foodstuff is offered.

A Method of Dynamic Extended Reactive Power Optimization in Distribution Network Containing Photovoltaic-Storage System

Science.gov (United States)

Wang, Wu; Huang, Wei; Zhang, Yongjun

2018-03-01

The grid-integration of Photovoltaic-Storage System brings some undefined factors to the network. In order to make full use of the adjusting ability of Photovoltaic-Storage System (PSS), this paper puts forward a reactive power optimization model, which are used to construct the objective function based on power loss and the device adjusting cost, including energy storage adjusting cost. By using Cataclysmic Genetic Algorithm to solve this optimization problem, and comparing with other optimization method, the result proved that: the method of dynamic extended reactive power optimization this article puts forward, can enhance the effect of reactive power optimization, including reducing power loss and device adjusting cost, meanwhile, it gives consideration to the safety of voltage.

[Urban ecological land in Changsha City: its quantitative analysis and optimization].

Science.gov (United States)

Li, Xiao-Li; Zeng, Guang-Ming; Shi, Lin; Liang, Jie; Cai, Qing

2010-02-01

In this paper, a hierarchy index system suitable for catastrophe progression method was constructed to comprehensively analyze and evaluate the status of ecological land construction in Changsha City in 2007. Based on the evaluation results, the irrationalities of the distribution pattern of Changsha urban ecological land were discussed. With the support of geographic information system (GIS), the ecological corridors of the urban ecological land were constructed by using the 'least-cost' modeling, and, in combining with conflict analysis, the optimum project of the urban ecological land was put forward, forming an integrated evaluation system. The results indicated that the ecological efficiency of urban ecological land in Changsha in 2007 was at medium level, with an evaluation value being 0.9416, and the quantitative index being relatively high but the coordination index being relatively low. The analysis and verification with software Fragstats showed that the ecological efficiency of the urban ecological land after optimization was higher, with the evaluation value being 0.9618, and the SHDI, CONTAG, and other indices also enhanced.

Strategies for discovery and optimization of thermoelectric materials: Role of real objects and local fields

Science.gov (United States)

Zhu, Hao; Xiao, Chong

2018-06-01

Thermoelectric materials provide a renewable and eco-friendly solution to mitigate energy shortages and to reduce environmental pollution via direct heat-to-electricity conversion. Discovery of the novel thermoelectric materials and optimization of the state-of-the-art material systems lie at the core of the thermoelectric society, the basic concept behind these being comprehension and manipulation of the physical principles and transport properties regarding thermoelectric materials. In this mini-review, certain examples for designing high-performance bulk thermoelectric materials are presented from the perspectives of both real objects and local fields. The highlights of this topic involve the Rashba effect, Peierls distortion, local magnetic field, and local stress field, which cover several aspects in the field of thermoelectric research. We conclude with an overview of future developments in thermoelectricity.

Simultaneous Optimization of Tallies in Difficult Shielding Problems

International Nuclear Information System (INIS)

Peplow, Douglas E.; Evans, Thomas M.; Wagner, John C.

2008-01-01

Monte Carlo is quite useful for calculating specific quantities in complex transport problems. Many variance reduction strategies have been developed that accelerate Monte Carlo calculations for specific tallies. However, when trying to calculate multiple tallies or a mesh tally, users have had to accept different levels of relative uncertainty among the tallies or run separate calculations optimized for each individual tally. To address this limitation, an extension of the CADIS (Consistent Adjoint Driven Importance Sampling) method, which is used for difficult source/detector problems, has been developed to optimize several tallies or the cells of a mesh tally simultaneously. The basis for this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. This method utilizes the results of a forward discrete ordinates solution, which may be based on a quick, coarse-mesh calculation, to develop a forward-weighted source for the adjoint calculation. The importance map and the biased source computed from the adjoint flux are then used in the forward Monte Carlo calculation to obtain approximately uniform relative uncertainties for the desired tallies. This extension is called forward-weighted CADIS, or FW-CADIS

Validation of a new midway forward-adjoint coupling option in MCNP

Energy Technology Data Exchange (ETDEWEB)

Serov, I.V.; John, T.M.; Hoogenboom, J.E. [Technische Univ. Delft (Netherlands). Interfacultair Reactor Inst.

1996-09-01

The new midway Monte Carlo is based on the coupling of scores from a forward and an adjoint Monte Carlo calculation on a surface in between the source and the detector. The method is implemented in MCNP. The utilization of the method is fairly straight-forward and does not require any substantial expertise. The midway Monte Carlo method was tested against the gamma-ray skyshine MCNP benchmark problem. This problem involves deep penetration and streaming along complicated paths. The midway method supplied results, which agree with the results of the reference calculation within the limits of the estimated statistical uncertainties. The efficiency of the easy-to-implement midway calculation is higher than the efficiency of the reference calculation which is already optimized by use of an importance function. The midway method proves to be efficient in problems with complicated streaming paths towards small detectors. (author)

Validation of a new midway forward-adjoint coupling option in MCNP

International Nuclear Information System (INIS)

Serov, I.V.; John, T.M.; Hoogenboom, J.E.

1996-01-01

The new midway Monte Carlo is based on the coupling of scores from a forward and an adjoint Monte Carlo calculation on a surface in between the source and the detector. The method is implemented in MCNP. The utilization of the method is fairly straight-forward and does not require any substantial expertise. The midway Monte Carlo method was tested against the gamma-ray skyshine MCNP benchmark problem. This problem involves deep penetration and streaming along complicated paths. The midway method supplied results, which agree with the results of the reference calculation within the limits of the estimated statistical uncertainties. The efficiency of the easy-to-implement midway calculation is higher than the efficiency of the reference calculation which is already optimized by use of an importance function. The midway method proves to be efficient in problems with complicated streaming paths towards small detectors. (author)

A comparison of optimization algorithms for localized in vivo B0 shimming.

Science.gov (United States)

Nassirpour, Sahar; Chang, Paul; Fillmer, Ariane; Henning, Anke

2018-02-01

To compare several different optimization algorithms currently used for localized in vivo B 0 shimming, and to introduce a novel, fast, and robust constrained regularized algorithm (ConsTru) for this purpose. Ten different optimization algorithms (including samples from both generic and dedicated least-squares solvers, and a novel constrained regularized inversion method) were implemented and compared for shimming in five different shimming volumes on 66 in vivo data sets from both 7 T and 9.4 T. The best algorithm was chosen to perform single-voxel spectroscopy at 9.4 T in the frontal cortex of the brain on 10 volunteers. The results of the performance tests proved that the shimming algorithm is prone to unstable solutions if it depends on the value of a starting point, and is not regularized to handle ill-conditioned problems. The ConsTru algorithm proved to be the most robust, fast, and efficient algorithm among all of the chosen algorithms. It enabled acquisition of spectra of reproducible high quality in the frontal cortex at 9.4 T. For localized in vivo B 0 shimming, the use of a dedicated linear least-squares solver instead of a generic nonlinear one is highly recommended. Among all of the linear solvers, the constrained regularized method (ConsTru) was found to be both fast and most robust. Magn Reson Med 79:1145-1156, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Community structure informs species geographic distributions

KAUST Repository

Montesinos-Navarro, Alicia

2018-05-23

Understanding what determines species\\' geographic distributions is crucial for assessing global change threats to biodiversity. Measuring limits on distributions is usually, and necessarily, done with data at large geographic extents and coarse spatial resolution. However, survival of individuals is determined by processes that happen at small spatial scales. The relative abundance of coexisting species (i.e. \\'community structure\\') reflects assembly processes occurring at small scales, and are often available for relatively extensive areas, so could be useful for explaining species distributions. We demonstrate that Bayesian Network Inference (BNI) can overcome several challenges to including community structure into studies of species distributions, despite having been little used to date. We hypothesized that the relative abundance of coexisting species can improve predictions of species distributions. In 1570 assemblages of 68 Mediterranean woody plant species we used BNI to incorporate community structure into Species Distribution Models (SDMs), alongside environmental information. Information on species associations improved SDM predictions of community structure and species distributions moderately, though for some habitat specialists the deviance explained increased by up to 15%. We demonstrate that most species associations (95%) were positive and occurred between species with ecologically similar traits. This suggests that SDM improvement could be because species co-occurrences are a proxy for local ecological processes. Our study shows that Bayesian Networks, when interpreted carefully, can be used to include local conditions into measurements of species\\' large-scale distributions, and this information can improve the predictions of species distributions.

Advantages and application of forward osmosis

Science.gov (United States)

This month's Processing column explores the use of forward osmosis to dewater and concentrate. Forward osmosis is performed with specially designed membranes and requires very little energy. Where thermal evaporation and reverse osmosis may damage or alter products, forward osmosis preserves the s...

An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments

International Nuclear Information System (INIS)

Kucuksari, Sadik; Khaleghi, Amirreza M.; Hamidi, Maryam; Zhang, Ye; Szidarovszky, Ferenc; Bayraksan, Guzin; Son, Young-Jun

2014-01-01

Highlights: • The optimal size and locations for PV units for campus environments are achieved. • The GIS module finds the suitable rooftops and their panel capacity. • The optimization module maximizes the long-term profit of PV installations. • The simulation module evaluates the voltage profile of the distribution network. • The proposed work has been successfully demonstrated for a real university campus. - Abstract: Finding the optimal size and locations for Photovoltaic (PV) units has been a major challenge for distribution system planners and researchers. In this study, a framework is proposed to integrate Geographical Information Systems (GIS), mathematical optimization, and simulation modules to obtain the annual optimal placement and size of PV units for the next two decades in a campus area environment. First, a GIS module is developed to find the suitable rooftops and their panel capacity considering the amount of solar radiation, slope, elevation, and aspect. The optimization module is then used to maximize the long-term net profit of PV installations considering various costs of investment, inverter replacement, operation, and maintenance as well as savings from consuming less conventional energy. A voltage profile of the electricity distribution network is then investigated in the simulation module. In the case of voltage limit violation by intermittent PV generations or load fluctuations, two mitigation strategies, reallocation of the PV units or installation of a local storage unit, are suggested. The proposed framework has been implemented in a real campus area, and the results show that it can effectively be used for long-term installation planning of PV panels considering both the cost and power quality

Geographic variation in responses of European yellow dung flies to thermal stress.

Science.gov (United States)

Bauerfeind, Stephanie S; Sørensen, Jesper G; Loeschcke, Volker; Berger, David; Broder, E Dale; Geiger, Madeleine; Ferrari, Manuela; Blanckenhorn, Wolf U

2018-04-01

Climatic conditions can be very heterogeneous even over small geographic scales, and are believed to be major determinants of the abundance and distribution of species and populations. Organisms are expected to evolve in response to the frequency and magnitude of local thermal extremes, resulting in local adaptation. Using replicate yellow dung fly (Scathophaga stercoraria; Diptera: Scathophagidae) populations from cold (northern Europe) and warm climates (southern Europe), we compared 1) responses to short-term heat and cold shocks in both sexes, 2) heat shock protein (Hsp70) expression in adults and eggs, and 3) female reproductive traits when facing short-term heat stress during egg maturation. Contrary to expectations, thermal traits showed minor geographic differentiation, with weak evidence for greater heat resistance of southern flies but no differentiation in cold resistance. Hsp70 protein expression was little affected by heat stress, indicating systemic rather than induced regulation of the heat stress response, possibly related to this fly group's preference for cold climes. In contrast, sex differences were pronounced: males (which are larger) endured hot temperatures longer, while females featured higher Hsp70 expression. Heat stress negatively affected various female reproductive traits, reducing first clutch size, overall reproductive investment, egg lipid content, and subsequent larval hatching. These responses varied little across latitude but somewhat among populations in terms of egg size, protein content, and larval hatching success. Several reproductive parameters, but not Hsp70 expression, exhibited heritable variation among full-sib families. Rather than large-scale clinal geographic variation, our study suggests some local geographic population differentiation in the ability of yellow dung flies to buffer the impact of heat stress on reproductive performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Going forward with genetics: recent technological advances and forward genetics in mice.

Science.gov (United States)

Moresco, Eva Marie Y; Li, Xiaohong; Beutler, Bruce

2013-05-01

Forward genetic analysis is an unbiased approach for identifying genes essential to defined biological phenomena. When applied to mice, it is one of the most powerful methods to facilitate understanding of the genetic basis of human biology and disease. The speed at which disease-causing mutations can be identified in mutagenized mice has been markedly increased by recent advances in DNA sequencing technology. Creating and analyzing mutant phenotypes may therefore become rate-limiting in forward genetic experimentation. We review the forward genetic approach and its future in the context of recent technological advances, in particular massively parallel DNA sequencing, induced pluripotent stem cells, and haploid embryonic stem cells. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

NSGA-II Algorithm with a Local Search Strategy for Multiobjective Optimal Design of Dry-Type Air-Core Reactor

Directory of Open Access Journals (Sweden)

Chengfen Zhang

2015-01-01

Full Text Available Dry-type air-core reactor is now widely applied in electrical power distribution systems, for which the optimization design is a crucial issue. In the optimization design problem of dry-type air-core reactor, the objectives of minimizing the production cost and minimizing the operation cost are both important. In this paper, a multiobjective optimal model is established considering simultaneously the two objectives of minimizing the production cost and minimizing the operation cost. To solve the multi-objective optimization problem, a memetic evolutionary algorithm is proposed, which combines elitist nondominated sorting genetic algorithm version II (NSGA-II with a local search strategy based on the covariance matrix adaptation evolution strategy (CMA-ES. NSGA-II can provide decision maker with flexible choices among the different trade-off solutions, while the local-search strategy, which is applied to nondominated individuals randomly selected from the current population in a given generation and quantity, can accelerate the convergence speed. Furthermore, another modification is that an external archive is set in the proposed algorithm for increasing the evolutionary efficiency. The proposed algorithm is tested on a dry-type air-core reactor made of rectangular cross-section litz-wire. Simulation results show that the proposed algorithm has high efficiency and it converges to a better Pareto front.

Geographic Variation in Advertisement Calls in a Tree Frog Species: Gene Flow and Selection Hypotheses

Science.gov (United States)

Jang, Yikweon; Hahm, Eun Hye; Lee, Hyun-Jung; Park, Soyeon; Won, Yong-Jin; Choe, Jae C.

2011-01-01

Background In a species with a large distribution relative to its dispersal capacity, geographic variation in traits may be explained by gene flow, selection, or the combined effects of both. Studies of genetic diversity using neutral molecular markers show that patterns of isolation by distance (IBD) or barrier effect may be evident for geographic variation at the molecular level in amphibian species. However, selective factors such as habitat, predator, or interspecific interactions may be critical for geographic variation in sexual traits. We studied geographic variation in advertisement calls in the tree frog Hyla japonica to understand patterns of variation in these traits across Korea and provide clues about the underlying forces for variation. Methodology We recorded calls of H. japonica in three breeding seasons from 17 localities including localities in remote Jeju Island. Call characters analyzed were note repetition rate (NRR), note duration (ND), and dominant frequency (DF), along with snout-to-vent length. Results The findings of a barrier effect on DF and a longitudinal variation in NRR seemed to suggest that an open sea between the mainland and Jeju Island and mountain ranges dominated by the north-south Taebaek Mountains were related to geographic variation in call characters. Furthermore, there was a pattern of IBD in mitochondrial DNA sequences. However, no comparable pattern of IBD was found between geographic distance and call characters. We also failed to detect any effects of habitat or interspecific interaction on call characters. Conclusions Geographic variations in call characters as well as mitochondrial DNA sequences were largely stratified by geographic factors such as distance and barriers in Korean populations of H. japoinca. Although we did not detect effects of habitat or interspecific interaction, some other selective factors such as sexual selection might still be operating on call characters in conjunction with restricted gene

The ATLAS Forward Physics Program

OpenAIRE

Royon, C

2010-01-01

After a brief review of the approved ATLAS forward detector system we describe the main ATLAS forward physics program. This program currently includes such topics as soft and hard diffraction, double pomeron exchange, central exclusive production, rapidity gap survival, two photon physics, the determination of the total cross-section and the determination of the absolute luminosity A possible high luminosity upgrade program involving new forward proton detectors is also briefly reviewed. This...

A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

Science.gov (United States)

Zhang, Yongqin; Iman, Kory

2018-05-01

Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

Identification of spatially-localized initial conditions via sparse PCA

Science.gov (United States)

Dwivedi, Anubhav; Jovanovic, Mihailo

2017-11-01

Principal Component Analysis involves maximization of a quadratic form subject to a quadratic constraint on the initial flow perturbations and it is routinely used to identify the most energetic flow structures. For general flow configurations, principal components can be efficiently computed via power iteration of the forward and adjoint governing equations. However, the resulting flow structures typically have a large spatial support leading to a question of physical realizability. To obtain spatially-localized structures, we modify the quadratic constraint on the initial condition to include a convex combination with an additional regularization term which promotes sparsity in the physical domain. We formulate this constrained optimization problem as a nonlinear eigenvalue problem and employ an inverse power-iteration-based method to solve it. The resulting solution is guaranteed to converge to a nonlinear eigenvector which becomes increasingly localized as our emphasis on sparsity increases. We use several fluids examples to demonstrate that our method indeed identifies the most energetic initial perturbations that are spatially compact. This work was supported by Office of Naval Research through Grant Number N00014-15-1-2522.

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

Directory of Open Access Journals (Sweden)

Mauro Castelli

2015-01-01

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

Message Scheduling and Forwarding in Congested DTNs

KAUST Repository

Elwhishi, Ahmed; Ho, Pin-Han; Shihada, Basem

2012-01-01

Multi-copy utility-based routing has been considered as one of the most applicable approaches to effective message delivery in Delay Tolerant Networks (DTNs). By allowing multiple message replicas launched, the ratio of message delivery or delay can be significantly reduced compared with other counterparts. Such an advantage, nonetheless, is at the expense of taking more buffer space at each node and higher complexity in message forwarding decisions. This paper investigates an efficient message scheduling and dropping policy via analytical modeling approach, aiming to achieve optimal performance in terms of message delivery delay. Extensive simulation results, based on a synthetic mobility model and real mobility traces, show that the proposed scheduling framework can achieve superb performance against its counterparts in terms of delivery delay.

Message Scheduling and Forwarding in Congested DTNs

KAUST Repository

Elwhishi, Ahmed

2012-08-19

Multi-copy utility-based routing has been considered as one of the most applicable approaches to effective message delivery in Delay Tolerant Networks (DTNs). By allowing multiple message replicas launched, the ratio of message delivery or delay can be significantly reduced compared with other counterparts. Such an advantage, nonetheless, is at the expense of taking more buffer space at each node and higher complexity in message forwarding decisions. This paper investigates an efficient message scheduling and dropping policy via analytical modeling approach, aiming to achieve optimal performance in terms of message delivery delay. Extensive simulation results, based on a synthetic mobility model and real mobility traces, show that the proposed scheduling framework can achieve superb performance against its counterparts in terms of delivery delay.

Geographic Distribution of Teaching Talent in California. Consultant's Report Prepared for the State Committee on Public Education.

Science.gov (United States)

Guthrie, James; And Others

The central purpose of this study was to examine the relationship between distribution of teaching talent and geographic location of local school districts of California. School districts were assigned to one of four geographic categories (urban, suburban, rural, or small urban centers). Each category's teaching talent was assessed on six measures…

Scalable unit commitment by memory-bounded ant colony optimization with A{sup *} local search

Energy Technology Data Exchange (ETDEWEB)

Saber, Ahmed Yousuf; Alshareef, Abdulaziz Mohammed [Department of Electrical and Computer Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589 (Saudi Arabia)

2008-07-15

Ant colony optimization (ACO) is successfully applied in optimization problems. Performance of the basic ACO for small problems with moderate dimension and searching space is satisfactory. As the searching space grows exponentially in the large-scale unit commitment problem, the basic ACO is not applicable for the vast size of pheromone matrix of ACO in practical time and physical computer-memory limit. However, memory-bounded methods prune the least-promising nodes to fit the system in computer memory. Therefore, the authors propose memory-bounded ant colony optimization (MACO) in this paper for the scalable (no restriction for system size) unit commitment problem. This MACO intelligently solves the limitation of computer memory, and does not permit the system to grow beyond a bound on memory. In the memory-bounded ACO implementation, A{sup *} heuristic is introduced to increase local searching ability and probabilistic nearest neighbor method is applied to estimate pheromone intensity for the forgotten value. Finally, the benchmark data sets and existing methods are used to show the effectiveness of the proposed method. (author)

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

Generation of 3D Virtual Geographic Environment Based on Laser Scanning Technique

Institute of Scientific and Technical Information of China (English)

DU Jie; CHEN Xiaoyong; FumioYamazaki

2003-01-01

This paper demonstrates an experiment on the generation of 3D virtual geographic environment on the basis of experimental flight laser scanning data by a set of algorithms and methods that were developed to automatically interpret range images for extracting geo-spatial features and then to reconstruct geo-objects. The algorithms and methods for the interpretation and modeling of laser scanner data include triangulated-irregular-network (TIN)-based range image interpolation ; mathematical-morphology(MM)-based range image filtering,feature extraction and range image segmentation, feature generalization and optimization, 3D objects reconstruction and modeling; computergraphics (CG)-based visualization and animation of geographic virtual reality environment.

Papayas and Pedagogy: Geographically Dispersed Teams and Internet Self-Efficacy.

Science.gov (United States)

O'Malley, Michelle; Kelleher, Tom

2002-01-01

Describes how public relations (PR) students' Internet self-efficacy (e-mail, bulletin board system, real-time chat, and Web research) was measured before, immediately after, and 7 weeks after they worked in either geographically dispersed (Kansas and Hawaii) or local (Kansas only) teams to develop a PR issue statement. Finds Internet efficacy…

Local timber firm looking forward to develop on medium term

Directory of Open Access Journals (Sweden)

BUCS Lorant

2017-01-01

Full Text Available This article intends to outline the challenges faced by a local timber company in struggle to resist on medium-term on the market. There will be revealed the challenges the company is facing, and also the ways to adapt to the changing world of timber industry. There will be presented a short history of the founding and the evolution of the company on the local and international market, pointing out the relevant events which have marked the life of the company during the years. There will also be presented a short review of the competition on the market and the marketing strategy and policies which the company is using to be able to face the new challenges.

Adaptive Feed-Forward Control of Low Frequency Interior Noise

CERN Document Server

Kletschkowski, Thomas

2012-01-01

This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.

Forward-Looking Planning of Technology Development

Directory of Open Access Journals (Sweden)

Katarzyna Halicka

2015-12-01

Full Text Available The main aim of this article is to adapt the Future-Oriented Technology Analysis (FTA to prospective planning of technology development. Firstly, the article presents the assumptions, methods and idea, as well as the concept of the FTA method. Moreover, selected publications on the use of this method were analysed. Then, an original, base model of forward-looking planning of technology development was constructed and presented. The end result of this process will be the development of the localized in time, presented in graphic form, action plan referred to as the route of technology development. Basing on the literature review and the research projects a preliminary route of development of arbitrarily chosen technology was also built and presented.

Population Genetic Analysis of Theileria annulata from Six Geographical Regions in China, Determined on the Basis of Micro- and Mini-satellite Markers.

Science.gov (United States)

Yin, Fangyuan; Liu, Zhijie; Liu, Junlong; Liu, Aihong; Salih, Diaeldin A; Li, Youquan; Liu, Guangyuan; Luo, Jianxun; Guan, Guiquan; Yin, Hong

2018-01-01

Theileria annulata , a tick-borne apicomplexan protozoan, causes a lymphoproliferative disease of cattle with high prevalence in tropical and sub-tropical regions. Understanding the genetic diversity and structure of local populations will provide more fundamental knowledge for the population genetics and epidemics of protozoa. In this study, 78 samples of T. annulata collected from cattle/yaks representing 6 different geographic populations in China were genotyped using eight micro- and mini-satellite markers. High genetic variation within population, moderate genetic differentiation, and high level of diversity co-occurring with significant linkage disequilibrium were observed, which indicates there is gene flow between these populations in spite of the existence of reproductive and geographical barriers among populations. Furthermore, some degree of genetic differentiation was also found between samples from China and Oman. These findings provide a first glimpse of the genetic diversity of the T. annulata populations in China, and might contribute to the knowledge of distribution, dynamics, and epidemiology of T. annulata populations and optimize the management strategies for control.

Body size and geographic range do not explain long term variation in fish populations: a Bayesian phylogenetic approach to testing assembly processes in stream fish assemblages.

Directory of Open Access Journals (Sweden)

Stephen J Jacquemin

Full Text Available We combine evolutionary biology and community ecology to test whether two species traits, body size and geographic range, explain long term variation in local scale freshwater stream fish assemblages. Body size and geographic range are expected to influence several aspects of fish ecology, via relationships with niche breadth, dispersal, and abundance. These traits are expected to scale inversely with niche breadth or current abundance, and to scale directly with dispersal potential. However, their utility to explain long term temporal patterns in local scale abundance is not known. Comparative methods employing an existing molecular phylogeny were used to incorporate evolutionary relatedness in a test for covariation of body size and geographic range with long term (1983 - 2010 local scale population variation of fishes in West Fork White River (Indiana, USA. The Bayesian model incorporating phylogenetic uncertainty and correlated predictors indicated that neither body size nor geographic range explained significant variation in population fluctuations over a 28 year period. Phylogenetic signal data indicated that body size and geographic range were less similar among taxa than expected if trait evolution followed a purely random walk. We interpret this as evidence that local scale population variation may be influenced less by species-level traits such as body size or geographic range, and instead may be influenced more strongly by a taxon's local scale habitat and biotic assemblages.

Forward contract - minimize the exchange risk

OpenAIRE

Martin Maršík; František Vebr

1998-01-01

How can a Czech export (import) company hedge exchange risk? Some of the possibilities are these: 1/ use only CZK for foreign contracts; 2/ matching payments in the same or a parallel currency; 3/ use the products of the money markets; 4/ use the products of the forward market - FORWARD CONTRACT The forward market offers a forward contract to buy or sell a fixed amount of currency at a fixed price on a specific date in the future. The settlement of the contract is in more than two days. The e...

Geographical Information Systems (GIS); Sistemas de Informacion Geografica

Energy Technology Data Exchange (ETDEWEB)

Garcia Santiago, P.A. [Inisel Espacio, Madrid (Spain)

1994-12-31

Geographical Information Systems (GIS) have converted in a computer`s tool that due of its great versatility, exceeds of its usage as Basic Cartography Manager. The best GIS to use (vector or raster) will depend on the type of data we work with, we should keep in mind that the use of a specific GIS does not mean total incompatibility with others GIS. Future tendencies in this field aim to Data Storage Optimization and to Shared Operating System between Workstations and Personal computers. (Author)

Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation

NARCIS (Netherlands)

F. Cong (Fei); C.W. Oosterlee (Kees)

2016-01-01

htmlabstractWe propose a simulation-based approach for solving the constrained dynamic mean– variance portfolio managemen tproblem. For this dynamic optimization problem, we first consider a sub-optimal strategy, called the multi-stage strategy, which can be utilized in a forward fashion. Then,

Forward Jet Vertex Tagging: A new technique for the identification and rejection of forward pileup jets

CERN Document Server

The ATLAS collaboration

2015-01-01

The suppression of pileup forward jets is crucial for a variety of physics analyses at the LHC, ranging from VBF Higgs production to SUSY searches. A novel forward pileup tagging technique that exploits the correlation between central and forward jets originating from pileup interactions is presented. Tracking and vertex information in the central $\\eta$ region is used to indirectly tag and reject forward pileup jets that are back-to-back to central pileup jets. The pileup suppression power observed in Pythia8 simulated events increases with jet \\pt and ranges between a 30\\% and 60\\% pileup jet removal for 90\\% jet selection efficiency for jets between 20 and 50 GeV.

Geographic heterogeneity in cycling under various weather conditions: Evidence from Greater Rotterdam

NARCIS (Netherlands)

Helbich, M.; Böcker, L.; Dijst, M.J.

2014-01-01

With its sustainability, health and accessibility benefits, cycling has nowadays been established on research and policy agendas. Notwithstanding the decision to cycle is closely related to local weather conditions and interwoven with the geographical context, research dealing with both aspects is

Relating performance of thin-film composite forward osmosis membranes to support layer formation and structure

KAUST Repository

Tiraferri, Alberto

2011-02-01

Osmotically driven membrane processes have the potential to treat impaired water sources, desalinate sea/brackish waters, and sustainably produce energy. The development of a membrane tailored for these processes is essential to advance the technology to the point that it is commercially viable. Here, a systematic investigation of the influence of thin-film composite membrane support layer structure on forward osmosis performance is conducted. The membranes consist of a selective polyamide active layer formed by interfacial polymerization on top of a polysulfone support layer fabricated by phase separation. By systematically varying the conditions used during the casting of the polysulfone layer, an array of support layers with differing structures was produced. The role that solvent quality, dope polymer concentration, fabric layer wetting, and casting blade gate height play in the support layer structure formation was investigated. Using a 1M NaCl draw solution and a deionized water feed, water fluxes ranging from 4 to 25Lm-2h-1 with consistently high salt rejection (>95.5%) were produced. The relationship between membrane structure and performance was analyzed. This study confirms the hypothesis that the optimal forward osmosis membrane consists of a mixed-structure support layer, where a thin sponge-like layer sits on top of highly porous macrovoids. Both the active layer transport properties and the support layer structural characteristics need to be optimized in order to fabricate a high performance forward osmosis membrane. © 2010 Elsevier B.V.

New Communication Technologies, Local Journalism and the Perception of Locality

Directory of Open Access Journals (Sweden)

Ali ÖZCAN

2016-12-01

Full Text Available Studies on local journalism as an important element of participatory democracy generally focus on the history of the local press, the financial insufficiencies of local newspapers as well as technical/ technological incompetency that occurs as a result of these factors. This research analyzes local newspapers with a new scientific point of view by focusing on the perception of locality as a mental projection of geographical constraint. Perspectives regarding the transformations on perceptions of locality as a result of the disappearance of time and space constraints due to new communication technologies, and the opportunities that new communication environments offer to local newspapers will be provided. Moreover, the ways in which local newspapers reflect on locality with their printed versions under time and space constraints will be analyzed. The research scope of the study has been limited to 15 newspapers in Konya. Structured interviews and content analysis methods were used for data collection and analysis.

Exploring the Effect of Geographical Proximity and University Quality on University-Industry Collaboration in the United Kingdom

DEFF Research Database (Denmark)

Laursen, Keld; Reichstein, Toke; Salter, Ammon

2011-01-01

Exploring the effect of geographical proximity and university quality on university–industry collaboration in the United Kingdom, Regional Studies. This paper concerns the geographical distance between a firm and the universities in its local area. It is argued that firms' decisions to collaborat...... collaboration. However, it is also found that if faced with the choice, firms appear to give preference to the research quality of the university partner over geographical closeness. This is particularly true for high-research and development intensive firms....

Rapidly re-computable EEG (electroencephalography) forward models for realistic head shapes

International Nuclear Information System (INIS)

Ermer, J.J.; Mosher, J.C.; Baillet, S.; Leahy, R.M.

2001-01-01

Solution of the EEG source localization (inverse) problem utilizing model-based methods typically requires a significant number of forward model evaluations. For subspace based inverse methods like MUSIC (6), the total number of forward model evaluations can often approach an order of 10 3 or 10 4 . Techniques based on least-squares minimization may require significantly more evaluations. The observed set of measurements over an M-sensor array is often expressed as a linear forward spatio-temporal model of the form: F = GQ + N (1) where the observed forward field F (M-sensors x N-time samples) can be expressed in terms of the forward model G, a set of dipole moment(s) Q (3xP-dipoles x N-time samples) and additive noise N. Because of their simplicity, ease of computation, and relatively good accuracy, multi-layer spherical models (7) (or fast approximations described in (1), (7)) have traditionally been the 'forward model of choice' for approximating the human head. However, approximation of the human head via a spherical model does have several key drawbacks. By its very shape, the use of a spherical model distorts the true distribution of passive currents in the skull cavity. Spherical models also require that the sensor positions be projected onto the fitted sphere (Fig. 1), resulting in a distortion of the true sensor-dipole spatial geometry (and ultimately the computed surface potential). The use of a single 'best-fitted' sphere has the added drawback of incomplete coverage of the inner skull region, often ignoring areas such as the frontal cortex. In practice, this problem is typically countered by fitting additional sphere(s) to those region(s) not covered by the primary sphere. The use of these additional spheres results in added complication to the forward model. Using high-resolution spatial information obtained via X-ray CT or MR imaging, a realistic head model can be formed by tessellating the head into a set of contiguous regions (typically the scalp

AS Migration and Optimization of the Power Integrated Data Network

Science.gov (United States)

Zhou, Junjie; Ke, Yue

2018-03-01

In the transformation process of data integration network, the impact on the business has always been the most important reference factor to measure the quality of network transformation. With the importance of the data network carrying business, we must put forward specific design proposals during the transformation, and conduct a large number of demonstration and practice to ensure that the transformation program meets the requirements of the enterprise data network. This paper mainly demonstrates the scheme of over-migrating point-to-point access equipment in the reconstruction project of power data comprehensive network to migrate the BGP autonomous domain to the specified domain defined in the industrial standard, and to smooth the intranet OSPF protocol Migration into ISIS agreement. Through the optimization design, eventually making electric power data network performance was improved on traffic forwarding, traffic forwarding path optimized, extensibility, get larger, lower risk of potential loop, the network stability was improved, and operational cost savings, etc.

End-to-End Joint Antenna Selection Strategy and Distributed Compress and Forward Strategy for Relay Channels

Directory of Open Access Journals (Sweden)

Rahul Vaze

2009-01-01

Full Text Available Multihop relay channels use multiple relay stages, each with multiple relay nodes, to facilitate communication between a source and destination. Previously, distributed space-time codes were proposed to maximize the achievable diversity-multiplexing tradeoff; however, they fail to achieve all the points of the optimal diversity-multiplexing tradeoff. In the presence of a low-rate feedback link from the destination to each relay stage and the source, this paper proposes an end-to-end antenna selection (EEAS strategy as an alternative to distributed space-time codes. The EEAS strategy uses a subset of antennas of each relay stage for transmission of the source signal to the destination with amplifying and forwarding at each relay stage. The subsets are chosen such that they maximize the end-to-end mutual information at the destination. The EEAS strategy achieves the corner points of the optimal diversity-multiplexing tradeoff (corresponding to maximum diversity gain and maximum multiplexing gain and achieves better diversity gain at intermediate values of multiplexing gain, versus the best-known distributed space-time coding strategies. A distributed compress and forward (CF strategy is also proposed to achieve all points of the optimal diversity-multiplexing tradeoff for a two-hop relay channel with multiple relay nodes.

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

Science.gov (United States)

Huang, Shuqiang; Tao, Ming

2017-01-22

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K -center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems

Directory of Open Access Journals (Sweden)

Shuqiang Huang

2017-01-01

Full Text Available Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest and the population optimum (gbest; thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems

Science.gov (United States)

Huang, Shuqiang; Tao, Ming

2017-01-01

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms. PMID:28117735

Forward lunge: a training study of eccentric exercises of the lower limbs.

Science.gov (United States)

Jönhagen, Sven; Ackermann, Paul; Saartok, Tönu

2009-05-01

A few studies have shown that eccentric exercise is effective for prevention and treatment of muscle injuries. Most earlier studies on eccentric exercises have used training with advanced equipment. Forward lunges are considered eccentric exercises, and they may be performed without any equipment. These exercises are commonly used by sprint runners. We performed a prospective, randomized, 6-week training study comparing the effects of walking or jumping forward lunges on hamstring and quadriceps strength and function. Thirty-two soccer players were included in the study. The forward lunge training was done as an addition to ordinary soccer training twice a week for 6 weeks. The outcome was measured by the maximal hamstring and quadriceps strength tests and by functional tests with 1-leg hop tests and 30-m sprint runs. Overall muscle pain was evaluated using a visual analogue scale score, and local pain was estimated with an algometer. Whereas the walking lunge improved hamstring strength, the jumping lunge resulted in sprint running improvements. Algometer testing showed a general increase in the pain detection thresholds of all subjects, including the controls. Thus, precautions should be taken when algometers are used for temporal studies of pain. Walking and jumping forward lunges can be used for improving hamstring strength and running speed in young soccer player. The findings may have relevance when designing protocols for prevention and rehabilitation of muscle injuries.

5 CFR 950.103 - Establishing a local campaign.

Science.gov (United States)

2010-01-01

... 5 Administrative Personnel 2 2010-01-01 2010-01-01 false Establishing a local campaign. 950.103... PRIVATE VOLUNTARY ORGANIZATIONS General Provisions § 950.103 Establishing a local campaign. (a) The Director establishes and maintains the official list of local campaigns and the geographical area each...

LIDAR Wind Speed Measurement Analysis and Feed-Forward Blade Pitch Control for Load Mitigation in Wind Turbines: January 2010--January 2011

Energy Technology Data Exchange (ETDEWEB)

Dunne, F.; Simley, E.; Pao, L.Y.

2011-10-01

This report examines the accuracy of measurements that rely on Doppler LIDAR systems to determine their applicability to wind turbine feed-forward control systems and discusses feed-forward control system designs that use preview wind measurements. Light Detection and Ranging (LIDAR) systems are able to measure the speed of incoming wind before it interacts with a wind turbine rotor. These preview wind measurements can be used in feed-forward control systems designed to reduce turbine loads. However, the degree to which such preview-based control techniques can reduce loads by reacting to turbulence depends on how accurately the incoming wind field can be measured. The first half of this report examines the accuracy of different measurement scenarios that rely on coherent continuous-wave or pulsed Doppler LIDAR systems to determine their applicability to feed-forward control. In particular, the impacts of measurement range and angular offset from the wind direction are studied for various wind conditions. A realistic case involving a scanning LIDAR unit mounted in the spinner of a wind turbine is studied in depth with emphasis on choices for scan radius and preview distance. The effects of turbulence parameters on measurement accuracy are studied as well. Continuous-wave and pulsed LIDAR models based on typical commercially available units were used in the studies present in this report. The second half of this report discusses feed-forward control system designs that use preview wind measurements. Combined feedback/feed-forward blade pitch control is compared to industry standard feedback control when simulated in realistic turbulent above-rated winds. The feed-forward controllers are designed to reduce fatigue loads, increasing turbine lifetime and therefore reducing the cost of energy. Three feed-forward designs are studied: non-causal series expansion, Preview Control, and optimized FIR filter. The input to the feed-forward controller is a measurement of

Optimal networks of future gravitational-wave telescopes

International Nuclear Information System (INIS)

Raffai, Péter; Márka, Zsuzsa; Márka, Szabolcs; Gondán, László; Kelecsényi, Nándor; Heng, Ik Siong; Logue, Josh

2013-01-01

We aim to find the optimal site locations for a hypothetical network of 1–3 triangular gravitational-wave telescopes. We define the following N-telescope figures of merit (FoMs) and construct three corresponding metrics: (a) capability of reconstructing the signal polarization; (b) accuracy in source localization; and (c) accuracy in reconstructing the parameters of a standard binary source. We also define a combined metric that takes into account the three FoMs with practically equal weight. After constructing a geomap of possible telescope sites, we give the optimal 2-telescope networks for the four FoMs separately in example cases where the location of the first telescope has been predetermined. We found that based on the combined metric, placing the first telescope to Australia provides the most options for optimal site selection when extending the network with a second instrument. We suggest geographical regions where a potential second and third telescope could be placed to get optimal network performance in terms of our FoMs. Additionally, we use a similar approach to find the optimal location and orientation for the proposed LIGO-India detector within a five-detector network with Advanced LIGO (Hanford), Advanced LIGO (Livingston), Advanced Virgo, and KAGRA. We found that the FoMs do not change greatly in sites within India, though the network can suffer a significant loss in reconstructing signal polarizations if the orientation angle of an L-shaped LIGO-India is not set to the optimal value of ∼58.2°( + k × 90°) (measured counterclockwise from East to the bisector of the arms). (paper)

Multiple-copy state discrimination: Thinking globally, acting locally

International Nuclear Information System (INIS)

Higgins, B. L.; Pryde, G. J.; Wiseman, H. M.; Doherty, A. C.; Bartlett, S. D.

2011-01-01

We theoretically investigate schemes to discriminate between two nonorthogonal quantum states given multiple copies. We consider a number of state discrimination schemes as applied to nonorthogonal, mixed states of a qubit. In particular, we examine the difference that local and global optimization of local measurements makes to the probability of obtaining an erroneous result, in the regime of finite numbers of copies N, and in the asymptotic limit as N→∞. Five schemes are considered: optimal collective measurements over all copies, locally optimal local measurements in a fixed single-qubit measurement basis, globally optimal fixed local measurements, locally optimal adaptive local measurements, and globally optimal adaptive local measurements. Here an adaptive measurement is one in which the measurement basis can depend on prior measurement results. For each of these measurement schemes we determine the probability of error (for finite N) and the scaling of this error in the asymptotic limit. In the asymptotic limit, it is known analytically (and we verify numerically) that adaptive schemes have no advantage over the optimal fixed local scheme. Here we show moreover that, in this limit, the most naive scheme (locally optimal fixed local measurements) is as good as any noncollective scheme except for states with less than 2% mixture. For finite N, however, the most sophisticated local scheme (globally optimal adaptive local measurements) is better than any other noncollective scheme for any degree of mixture.

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

Science.gov (United States)

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Forward-backward rapidity correlations in a two-step scenario

International Nuclear Information System (INIS)

Brogueira, P.; Dias de Deus, J.

2007-01-01

We argue that two-step models, like String and Glasma models, with creation first of sources extended in rapidity that after locally decay into particles, lead to long range forward-backward correlations due to fluctuations in the number or the colour of the sources, and to a similar expression for the F-B correlation parameter b. In the simplest String percolation scenario, b increases with centrality or the number of participating nucleons. However, asymptotically it decreases with energy. This is different from the Glasma model where b increases with both, centrality and energy

Forward Scattering of Loaded and Unloaded Antennas

DEFF Research Database (Denmark)

Gustafsson, Mats; Andersen, Jørgen Bach; Kristensson, Gerhard

2012-01-01

Forward scattering of antennas is related to antenna performance via the forward-scattering sum rule. The forward-scattering sum rule is an integral identity that shows that a weighted integral of the extinction cross section over all spectrum is proportional to the static polarizability...... of the antenna structure. Here, the forward-scattering sum rule is experimentally verified for loaded, short-circuit, and open-circuit cylindrical dipole antennas. It is also shown that the absorption efficiency cannot be greater than 1/2 for reciprocal linearly polarized lossless matched antennas...... with a symmetric radiation pattern in the forward and backward directions....

Predicting local field potentials with recurrent neural networks.

Science.gov (United States)

Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

2016-08-01

We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

Automatic multi-cycle reload design of pressurized water reactor using particle swarm optimization algorithm and local search

International Nuclear Information System (INIS)

Lin, Chaung; Hung, Shao-Chun

2013-01-01

Highlights: • An automatic multi-cycle core reload design tool, which searches the fresh fuel assembly composition, is developed. • The search method adopts particle swarm optimization and local search. • The design objectives are to achieve required cycle energy, minimum fuel cost, and the satisfactory constraints. • The constraints include the hot zero power moderator temperature coefficient and the hot channel factor. - Abstract: An automatic multi-cycle core reload design tool, which searches the fresh fuel assembly composition, is developed using particle swarm optimization and local search. The local search uses heuristic rules to change the current search result a little so that the result can be improved. The composition of the fresh fuel assemblies should provide the required cycle energy and satisfy the constraints, such as the hot zero power moderator temperature coefficient and the hot channel factor. Instead of designing loading pattern for each FA composition during search process, two fixed loading patterns are used to calculate the core status and the better fitness function value is used in the search process. The fitness function contains terms which reflect the design objectives such as cycle energy, constraints, and fuel cost. The results show that the developed tool can achieve the desire objective

Code Differentiation for Hydrodynamic Model Optimization

Energy Technology Data Exchange (ETDEWEB)

Henninger, R.J.; Maudlin, P.J.

1999-06-27

Use of a hydrodynamics code for experimental data fitting purposes (an optimization problem) requires information about how a computed result changes when the model parameters change. These so-called sensitivities provide the gradient that determines the search direction for modifying the parameters to find an optimal result. Here, the authors apply code-based automatic differentiation (AD) techniques applied in the forward and adjoint modes to two problems with 12 parameters to obtain these gradients and compare the computational efficiency and accuracy of the various methods. They fit the pressure trace from a one-dimensional flyer-plate experiment and examine the accuracy for a two-dimensional jet-formation problem. For the flyer-plate experiment, the adjoint mode requires similar or less computer time than the forward methods. Additional parameters will not change the adjoint mode run time appreciably, which is a distinct advantage for this method. Obtaining ''accurate'' sensitivities for the j et problem parameters remains problematic.

A method to generate fully multi-scale optimal interpolation by combining efficient single process analyses, illustrated by a DINEOF analysis spiced with a local optimal interpolation

Directory of Open Access Journals (Sweden)

J.-M. Beckers

2014-10-01

Full Text Available We present a method in which the optimal interpolation of multi-scale processes can be expanded into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations, we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well-controlled test case. The clear guidelines deduced from this experiment are then applied to a real situation in which we combine large-scale analysis of hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI satellite images using data interpolating empirical orthogonal functions (DINEOF with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.

Single-Iteration Learning Algorithm for Feed-Forward Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Barhen, J.; Cogswell, R.; Protopopescu, V.

1999-07-31

A new methodology for neural learning is presented, whereby only a single iteration is required to train a feed-forward network with near-optimal results. To this aim, a virtual input layer is added to the multi-layer architecture. The virtual input layer is connected to the nominal input layer by a specird nonlinear transfer function, and to the fwst hidden layer by regular (linear) synapses. A sequence of alternating direction singular vrdue decompositions is then used to determine precisely the inter-layer synaptic weights. This algorithm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information &ansfer within a neural network.

Laser-induced forward transfer of single-walled carbon nanotubes

Science.gov (United States)

Palla-Papavlu, A.; Dinescu, M.; Wokaun, A.; Lippert, T.

2014-10-01

The objective of this work is the application of laser-induced forward transfer (LIFT) for the fabrication of chemiresistor sensors. The receiver substrate is an array with metal electrodes and the active materials placed by LIFT are single-walled carbon nanotubes (SWCNT). The functionality of such sensors depends on the geometry of the active material onto the metallic electrodes. First the best geometry for the sensing materials and electrodes was determined, including the optimization of the process parameters for printing uniform pixels of SWCNT onto the sensor electrodes. The sensors were characterized in terms of their sensing characteristics, i.e., upon exposure to ammonia, proving the feasibility of LIFT.

The Effect of Geographic Units of Analysis on Measuring Geographic Variation in Medical Services Utilization

Directory of Open Access Journals (Sweden)

Agnus M. Kim

2016-07-01

Full Text Available Objectives: We aimed to evaluate the effect of geographic units of analysis on measuring geographic variation in medical services utilization. For this purpose, we compared geographic variations in the rates of eight major procedures in administrative units (districts and new areal units organized based on the actual health care use of the population in Korea. Methods: To compare geographic variation in geographic units of analysis, we calculated the age–sex standardized rates of eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee-replacement surgery, caesarean section, hysterectomy, computed tomography scan, and magnetic resonance imaging scan from the National Health Insurance database in Korea for the 2013 period. Using the coefficient of variation, the extremal quotient, and the systematic component of variation, we measured geographic variation for these eight procedures in districts and new areal units. Results: Compared with districts, new areal units showed a reduction in geographic variation. Extremal quotients and inter-decile ratios for the eight procedures were lower in new areal units. While the coefficient of variation was lower for most procedures in new areal units, the pattern of change of the systematic component of variation between districts and new areal units differed among procedures. Conclusions: Geographic variation in medical service utilization could vary according to the geographic unit of analysis. To determine how geographic characteristics such as population size and number of geographic units affect geographic variation, further studies are needed.

Linear Processing Design of Amplify-and-Forward Relays for Maximizing the System Throughput

Directory of Open Access Journals (Sweden)

Qiang Wang

2018-01-01

Full Text Available In this paper, firstly, we study the linear processing of amplify-and-forward (AF relays for the multiple relays multiple users scenario. We regard all relays as one special “relay”, and then the subcarrier pairing, relay selection and channel assignment can be seen as a linear processing of the special “relay”. Under fixed power allocation, the linear processing of AF relays can be regarded as a permutation matrix. Employing the partitioned matrix, we propose an optimal linear processing design for AF relays to find the optimal permutation matrix based on the sorting of the received SNR over the subcarriers from BS to relays and from relays to users, respectively. Then, we prove the optimality of the proposed linear processing scheme. Through the proposed linear processing scheme, we can obtain the optimal subcarrier paring, relay selection and channel assignment under given power allocation in polynomial time. Finally, we propose an iterative algorithm based on the proposed linear processing scheme and Lagrange dual domain method to jointly optimize the joint optimization problem involving the subcarrier paring, relay selection, channel assignment and power allocation. Simulation results illustrate that the proposed algorithm can achieve a perfect performance.

Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

Science.gov (United States)

Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

2017-10-01

A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3

Geographic mosaic of plant evolution: extrafloral nectary variation mediated by ant and herbivore assemblages.

Directory of Open Access Journals (Sweden)

Anselmo Nogueira

Full Text Available Herbivory is an ecological process that is known to generate different patterns of selection on defensive plant traits across populations. Studies on this topic could greatly benefit from the general framework of the Geographic Mosaic Theory of Coevolution (GMT. Here, we hypothesize that herbivory represents a strong pressure for extrafloral nectary (EFN bearing plants, with differences in herbivore and ant visitor assemblages leading to different evolutionary pressures among localities and ultimately to differences in EFN abundance and function. In this study, we investigate this hypothesis by analyzing 10 populations of Anemopaegma album (30 individuals per population distributed through ca. 600 km of Neotropical savanna and covering most of the geographic range of this plant species. A common garden experiment revealed a phenotypic differentiation in EFN abundance, in which field and experimental plants showed a similar pattern of EFN variation among populations. We also did not find significant correlations between EFN traits and ant abundance, herbivory and plant performance across localities. Instead, a more complex pattern of ant-EFN variation, a geographic mosaic, emerged throughout the geographical range of A. album. We modeled the functional relationship between EFNs and ant traits across ant species and extended this phenotypic interface to characterize local situations of phenotypic matching and mismatching at the population level. Two distinct types of phenotypic matching emerged throughout populations: (1 a population with smaller ants (Crematogaster crinosa matched with low abundance of EFNs; and (2 seven populations with bigger ants (Camponotus species matched with higher EFN abundances. Three matched populations showed the highest plant performance and narrower variance of EFN abundance, representing potential plant evolutionary hotspots. Cases of mismatched and matched populations with the lowest performance were associated

Responses to The Way Forward

International Nuclear Information System (INIS)

1988-11-01

In November 1987 United Kingdom Nirex Limited launched a discussion document entitled The Way Forward. The stated aims of the document were to promote discussion and to seek constructive contributions to the task of ensuring that radioactive waste is managed safely. It further aimed to promote public understanding of the issues involved and to stimulate comment which would assist Nirex in developing acceptable proposals for the disposal of radioactive waste. From the 2,526 replies received the main findings are: there is a clear welcome for the consultation exercise among local authorities and the majority of responding organisations; there is no overall unanimity of view; there appears to be little support for the under sea-bed accessed off-shore repository; safety is judged to be the paramount factor for all consultees, though clearly views differ as to how best to achieve this. The safe transport of wastes is the next major area of concern; views differ as to whether areas of high amenity value should be excluded from consideration at the outset, though the majority view is probably that they should be; the monitoring and recoverability of wastes is generally deemed to be important; potential detrimental local economic impact and blight through social stigma associated with the public perception of radioactive waste disposal is also a key concern and there is opposition from local authorities and environmental groups to the use of the Special Development Order procedure for obtaining planning permission for either investigative drilling or subsequent development. (author)

Sex-specific differences of craniofacial traits in Croatia: the impact of environment in a small geographic area.

Science.gov (United States)

Buretic-Tomljanovic, Alena; Giacometti, Jasminka; Ostojic, Sasa; Kapovic, Miljenko

2007-01-01

Craniometric variation in humans reflects different genetic and environmental influences. Long-term climatic adaptation is less likely to show an impact on size and shape variation in a small local area than at the global level. The aim of this work was to assess the contribution of the particular environmental factors to body height and craniofacial variability in a small geographic area of Croatia. A total of 632 subjects, aged 18-21, participated in the survey. Body height, head length, head breadth, head height, head circumference, cephalic index, morphological face height, face breadth, and facial index were analysed regarding geographic, climatic and dietary conditions in different regions of the country, and correlated with the specific climatic variables (cumulative multiyear sunshine duration, cumulative multiyear average precipitation, multiyear average air temperatures) and calcium concentrations in drinking water. Significant differences between groups classified according to geographic, climatic or dietary affiliation, and the impact of the environmental predictors on the variation in the investigated traits were assessed using multiple forward stepwise regression analyses. Higher body height measures in both sexes were significantly correlated with Mediterranean diet type. Mediterranean diet type also contributed to higher head length and head circumference measures in females. Cephalic index values correlated to geographic regions in both sexes, showing an increase from southern to eastern Croatia. In the same direction, head length significantly decreased in males and head breadth increased in females. Mediterranean climate was associated with higher and narrower faces in females. The analysis of the particular climatic variables did not reveal a significant influence on body height in either sex. Concurrently, climatic features influenced all craniofacial traits in females and only head length and facial index in males. Mediterranean climate

Local language a medium of instruction : Challenges and way forward

NARCIS (Netherlands)

Akello, Lucy; Timmerman, Margaretha

2018-01-01

The paper reports on a participatory action research study conducted in six rural primary schools in Uganda in 2013 to establish why children taught in the local language had difficulties in reading and writing. Findings through interviews, focus group discussions, reviews of exercise books and

Orthogonal Bases used for Feed Forward Control of Wind Turbines

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2011-01-01

In optimizing wind turbines it can be of a large help to use information of wind speeds at upwind turbine for the control of downwind turbines, it is, however, problematic to use these measurements directly since they are highly influenced by turbulence behind the wind turbine rotor plane. In this....... In this paper an orthogonal basis is use to extract the general trends in the wind signal, which are forward to the down wind turbines. This concept controller is designed and simulated on a generic 4.8 MW wind turbine model, which shows the potential of this proposed scheme....

LHCf experiment: forward physics at LHC for cosmic rays study

Directory of Open Access Journals (Sweden)

Del Prete M.

2016-01-01

Full Text Available The LHCf experiment, optimized for the study of forward physics at LHC, completes its main physics program in this year 2015, with the proton-proton collisions at the energy of 13 TeV. LHCf gives important results on the study of neutral particles at extreme pseudo-rapidity, both for proton-proton and for proton-ion interactions. These results are an important reference for tuning the models of the hadronic interaction currently used for the simulation of the atmospheric showers induced by very high energy cosmic rays. The results of this analysis and the future perspective are presented in this paper.

What locals want: Jordanian employees' views on expatriate managers

OpenAIRE

Syed, Jawad; Hazboun, Nour George; Murray, Peter A.

2014-01-01

This paper sheds light on the expatriate–local relationship based on local employees' perspectives of expatriate managers. Drawing on a survey of local employees working in three Western multinational banks in Jordan, the study explores local employees' views on expatriate managers and their performance. The study reveals that local employees are generally indifferent to their manager's nationality as long as the manager has the capability to drive the subsidiary forward. However, one key con...

Forward Osmosis in Wastewater Treatment Processes.

Science.gov (United States)

Korenak, Jasmina; Basu, Subhankar; Balakrishnan, Malini; Hélix-Nielsen, Claus; Petrinic, Irena

2017-01-01

In recent years, membrane technology has been widely used in wastewater treatment and water purification. Membrane technology is simple to operate and produces very high quality water for human consumption and industrial purposes. One of the promising technologies for water and wastewater treatment is the application of forward osmosis. Essentially, forward osmosis is a process in which water is driven through a semipermeable membrane from a feed solution to a draw solution due to the osmotic pressure gradient across the membrane. The immediate advantage over existing pressure driven membrane technologies is that the forward osmosis process per se eliminates the need for operation with high hydraulic pressure and forward osmosis has low fouling tendency. Hence, it provides an opportunity for saving energy and membrane replacement cost. However, there are many limitations that still need to be addressed. Here we briefly review some of the applications within water purification and new developments in forward osmosis membrane fabrication.

Geographical information systems

DEFF Research Database (Denmark)

Möller, Bernd

2004-01-01

The chapter gives an introduction to Geographical Information Systems (GIS) with particular focus on their application within environmental management.......The chapter gives an introduction to Geographical Information Systems (GIS) with particular focus on their application within environmental management....

Optimization modeling of U.S. renewable electricity deployment using local input variables

Science.gov (United States)

Bernstein, Adam

For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar

2012-06-01

In this report, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR.

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar

2012-09-16

In this letter, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR. © 2012 IEEE.

Dispersal Kernel Determines Symmetry of Spread and Geographical Range for an Insect

International Nuclear Information System (INIS)

Holland, J.D.

2009-01-01

The distance from a source patch that dispersing insects reach depends on the number of dispersers, or random draws from a probability density function called a dispersal kernel, and the shape of that kernel. This can cause asymmetrical dispersal between habitat patches that produce different numbers of dispersers. Spatial distributions based on these dynamics can explain several ecological patterns including mega populations and geographic range boundaries. I hypothesized that a locally extirpated long horned beetle, the sugar maple borer, has a new geographical range shaped primarily by probabilistic dispersal distances. I used data on occurrence from Ontario, Canada to construct a model of geographical range in Indiana, USA based on maximum dispersal distance scaled by habitat area. This model predicted the new range boundary within 500 m very accurately. This beetle may be an ideal organism for exploring spatial dynamics driven by dispersal.

Forward physics with CMS

CERN Document Server

Grothe, Monika

2008-01-01

Forward physics with CMS at the LHC covers a wide range of physics subjects, including very low-x_Bj QCD, underlying event and multiple interactions characteristics, gamma-mediated processes, shower development at the energy scale of primary cosmic ray interactions with the atmosphere, diffraction in the presence of a hard scale and even MSSM Higgs discovery in central exclusive production. Selected feasibility studies to illustrate the forward physics potential of CMS are presented.

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.

Design of Multijunction Photovoltaic Cells Optimized for Varied Atmospheric Conditions

Directory of Open Access Journals (Sweden)

C. Zhang

2014-01-01

Full Text Available Band gap engineering provides an opportunity to not only provide higher overall conversion efficiencies of the reference AM1.5 spectra but also customize PV device design for specific geographic locations and microenvironments based on atmospheric conditions characteristic to that particular location. Indium gallium nitride and other PV materials offer the opportunity for limited bandgap engineering to match spectra. The effects of atmospheric conditions such as aerosols, cloud cover, water vapor, and air mass have been shown to cause variations in spectral radiance that alters PV system performance due to both overrating and underrating. Designing PV devices optimized for spectral radiance of a particular region can result in improved PV system performance. This paper presents a new method for designing geographically optimized PV cells with using a numerical model for bandgap optimization. The geographic microclimate spectrally resolved solar flux for twelve representative atmospheric conditions for the incident radiation angle (zenith angle of 48.1° and fixed array angle of 40° is used to iteratively optimize the band gap for tandem, triple, and quad-layer of InGaN-based multijunction cells. The results of this method are illustrated for the case study of solar farms in the New York region and discussed.

The Use of Lead Isotope and Rare Earth Element Geochemistry for Forensic Geographic Provenancing

Science.gov (United States)

Carey, A.; Darrah, T.; Harrold, Z.; Prutsman-Pfeiffer, J.; Poreda, R.

2008-12-01

Lead isotope and rare earth element composition of modern human bones are analyzed to explore their utility for geographical provenancing. DNA analysis is the standard for identification of individuals. DNA analysis requires a DNA match for comparison. Thus, DNA analysis is of limited use in cases involving unknown remains. Trace elements are incorporated into bones and teeth during biomineralization, recording the characteristics of an individual's geochemical environment. Teeth form during adolescence, recording the geochemical environment of an individual's youth. Bones remodel throughout an individual's lifetime. Bones consist of two types of bone tissue (cortical and trabecular) that remodel at different rates, recording the geochemical environment at the time of biomineralization. Cortical bone tissue, forming the outer surface of bones, is dense, hard tissue that remodels in 25-30 yrs. Conversely, trabecular bone tissue, the inner cavity of bones, is low density, porous and remodels in 2-5 years. Thus, analyzing teeth and both bone tissues allows for the development of a geographical time line capable of tracking immigration patterns through time instead of only an individual's youth. Geochemical isotopic techniques (Sr, O, C, N) have been used for geographical provenancing in physical anthropology. The isotopic values of Sr, C, O, N are predominantly a function of soil compositions in areas where food is grown or water is consumed. Application of these provenancing techniques has become difficult as an individual's diet may reflect the isotopic composition of foods obtained at the local grocer as opposed to local soil compositions. Thus, we explore the use of REEs and Pb isotopes for geographical provenancing. Pb and REEs are likely more reliable indicators of modern geographical location as their composition are high in bio-available sources such as local soils, atmospheric aerosols, and dust as opposed to Sr, C, O, N that are controlled by food and

Identifying Local Hotspots of Pediatric Chronic Diseases Using Emergency Department Surveillance

Science.gov (United States)

Lee, David C.; Yi, Stella S.; Fong, Hiu-Fai; Athens, Jessica K.; Ravenell, Joseph E.; Sevick, Mary Ann; Wall, Stephen P.; Elbel, Brian

2016-01-01

Objective To use novel geographic methods and large-scale claims data to identify the local distribution of pediatric chronic diseases in New York City. Methods Using a 2009 all-payer emergency claims database, we identified the proportion of unique children aged 0 to 17 with diagnosis codes for specific medical and psychiatric conditions. As a proof of concept, we compared these prevalence estimates to traditional health surveys and registry data using the most geographically granular data available. In addition, we used home addresses to map local variation in pediatric disease burden. Results We identified 549,547 New York City children who visited an emergency department at least once in 2009. Though our sample included more publicly insured and uninsured children, we found moderate to strong correlations of prevalence estimates when compared to health surveys and registry data at pre-specified geographic levels. Strongest correlations were found for asthma and mental health conditions by county among younger children (0.88, p=0.05 and 0.99, pdisease prevalence with higher geographic resolution. More studies are needed to investigate limitations of these methods and assess reliability of local disease estimates. What’s New This study demonstrated how emergency department surveillance may improve estimates of pediatric disease prevalence with higher geographic resolution. We identified 29% of New York City children with a single year of data and identified local hotspots of pediatric chronic diseases. PMID:28385326

The ALICE forward multiplicity detector

DEFF Research Database (Denmark)

Holm Christensen, Christian; Gulbrandsen, Kristjan; Sogaard, Carsten

2007-01-01

The ALICE Forward Multiplicity Detector (FMD) is a silicon strip detector with 51,200 strips arranged in 5 rings, covering the range $-3.4......The ALICE Forward Multiplicity Detector (FMD) is a silicon strip detector with 51,200 strips arranged in 5 rings, covering the range $-3.4...

Towards Optimal Event Detection and Localization in Acyclic Flow Networks

KAUST Repository

Agumbe Suresh, Mahima

2012-01-03

Acyclic flow networks, present in many infrastructures of national importance (e.g., oil & gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures, have been proven costly and imprecise, especially when dealing with large scale distribution systems. In this paper, to the best of our knowledge for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. Sensor nodes move along the edges of the network and detect events (i.e., attacks) and proximity to beacon nodes with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate their effectiveness with results obtained from a high fidelity simulator.

Review of the geographic distribution of Micrurus decoratus (Jan, 1858 (Serpentes: Elapidae

Directory of Open Access Journals (Sweden)

Rodrigo Castellari Gonzalez

2014-08-01

Full Text Available Micrurus decoratus (Jan, 1858 is a poorly known species of coral snake, with a controversial history concerning its geographical range. The lack of consensus among researchers, since its original description, is largely due to the reporting of erroneous localities in publications. Herein we present the geographical range for the species based on the review of 184 records from 67 different municipalities in Brazil, including two new records for the state of Espírito Santo, extending its distribution to ca. 300 km northward from the previous northernmost locality. We also comment on doubtful records for the states of Rio Grande do Sul and Bahia, which contain no accurate data. We restrict the occurrence of Micrurus decoratus to the Atlantic Rainforest, with elevation range from 400 up to 1,600 m in the Brazilian states of Santa Catarina, Paraná, São Paulo, Rio de Janeiro, Minas Gerais and Espírito Santo.

Intranet and village community: optimization of public service based on electronic government at the local level

Science.gov (United States)

Pradana, G. W.; Fanida, E. H.; Niswah, F.

2018-01-01

The demand for good governance is directed towards the realization of efficiency, effectiveness, and clean government. The move is demonstrated through national and regional levels to develop and implement electronic government concepts. Through the development of electronic government is done structuring management systems and work processes in the government environment by optimizing the utilization of information technology. One of the real forms of electronic government (e-Gov) implementation at the local level is the Intranet Sub-District program in Sukodono Sub-District, Sidoarjo. Intranet Sub-District is an innovation whose purpose is to realize the availability of information on the utilization of management, distribution, and storage of official scripts, and also the optimal delivery of information and communication in the implementation of guidance and supervision of local administration. The type of this paper is descriptive with a qualitative approach and focus on the implementation of the Intranet District Program in Sukodono District, Sidoarjo. The findings of the study are the limited number of human resources who have mastered ICT, the uneven network, the adequacy of institutional needs and the existence of budget support from the authorized institution and the information system has not accommodated all the service needs.

New Methods for Resilient Societies: The Geographical Analysis of Injury Data

Directory of Open Access Journals (Sweden)

Eric Vaz

2017-03-01

Full Text Available In this paper an empirical assessment of injury patterns is supplied as an example of social endurance - resilient societies can be built by means of geographical analysis of injury data, providing better support for decision makers regarding urban safety. Preventing road traffic collisions with vulnerable road users, such as pedestrians, could help mitigate significant loses and improve infrastructure planning. In this sense, the geographical aspects of injury prevention are of clear spatial analog, and should be tested regarding the carrying capacity of urban areas as well as vulnerability for growing urban regions. The application of open source development tool for spatial analysis research in health studies is addressed. The study aims to create a framework of available open source tools through Python that enable better decision making through a systematic review of existing tools for spatial analysis. Methodologically, spatial autocorrelation indices are tested as well as influential variables are brought forward to establish a better understanding of the incremental concern of injuries in rural areas, in general, and in the Greater Toronto Area, in particular. By using Python Library for Spatial Analysis (PySAL, an integrative vision of assessing a growing epidemiological concern of injuries in Toronto, one of North America’s fastest growing economic metropolises is offered. In this sense, this study promotes the use of PySAL and open source toolsets for integrating spatial analysis and geographical analysis for health practitioners. The novelty and capabilities of open source tools through methods such as PySAL allow for a cost efficiency as well as give planning an easier methodological toolbox for advances spatial modelling techniques.

Linear transceiver design for nonorthogonal amplify-and-forward protocol using a bit error rate criterion

KAUST Repository

Ahmed, Qasim Zeeshan

2014-04-01

The ever growing demand of higher data rates can now be addressed by exploiting cooperative diversity. This form of diversity has become a fundamental technique for achieving spatial diversity by exploiting the presence of idle users in the network. This has led to new challenges in terms of designing new protocols and detectors for cooperative communications. Among various amplify-and-forward (AF) protocols, the half duplex non-orthogonal amplify-and-forward (NAF) protocol is superior to other AF schemes in terms of error performance and capacity. However, this superiority is achieved at the cost of higher receiver complexity. Furthermore, in order to exploit the full diversity of the system an optimal precoder is required. In this paper, an optimal joint linear transceiver is proposed for the NAF protocol. This transceiver operates on the principles of minimum bit error rate (BER), and is referred as joint bit error rate (JBER) detector. The BER performance of JBER detector is superior to all the proposed linear detectors such as channel inversion, the maximal ratio combining, the biased maximum likelihood detectors, and the minimum mean square error. The proposed transceiver also outperforms previous precoders designed for the NAF protocol. © 2002-2012 IEEE.

Optimal HIV testing and earlier care: the way forward in Europe

DEFF Research Database (Denmark)

Coenen, T; Lundgren, J; Lazarus, Jeff

2008-01-01

The articles in this supplement were developed from a recent pan-European conference entitled 'HIV in Europe 2007: Working together for optimal testing and earlier care', which took place on 26-27 November in Brussels, Belgium. The conference, organized by a multidisciplinary group of experts rep...

Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models.

Science.gov (United States)

Yang, Chenguang; Li, Zhijun; Li, Jing

2013-02-01

In this paper, we investigate optimized adaptive control and trajectory generation for a class of wheeled inverted pendulum (WIP) models of vehicle systems. Aiming at shaping the controlled vehicle dynamics to be of minimized motion tracking errors as well as angular accelerations, we employ the linear quadratic regulation optimization technique to obtain an optimal reference model. Adaptive control has then been developed using variable structure method to ensure the reference model to be exactly matched in a finite-time horizon, even in the presence of various internal and external uncertainties. The minimized yaw and tilt angular accelerations help to enhance the vehicle rider's comfort. In addition, due to the underactuated mechanism of WIP, the vehicle forward velocity dynamics cannot be controlled separately from the pendulum tilt angle dynamics. Inspired by the control strategy of human drivers, who usually manipulate the tilt angle to control the forward velocity, we design a neural-network-based adaptive generator of implicit control trajectory (AGICT) of the tilt angle which indirectly "controls" the forward velocity such that it tracks the desired velocity asymptotically. The stability and optimal tracking performance have been rigorously established by theoretic analysis. In addition, simulation studies have been carried out to demonstrate the efficiency of the developed AGICT and optimized adaptive controller.

Optimal Allocation of Power-Electronic Interfaced Wind Turbines Using a Genetic Algorithm - Monte Carlo Hybrid Optimization Method

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe

2010-01-01

determined by the wind resource and geographic conditions, the location of wind turbines in a power system network may significantly affect the distribution of power flow, power losses, etc. Furthermore, modern WTs with power-electronic interface have the capability of controlling reactive power output...... limit requirements. The method combines the Genetic Algorithm (GA), gradient-based constrained nonlinear optimization algorithm and sequential Monte Carlo simulation (MCS). The GA searches for the optimal locations and capacities of WTs. The gradient-based optimization finds the optimal power factor...... setting of WTs. The sequential MCS takes into account the stochastic behaviour of wind power generation and load. The proposed hybrid optimization method is demonstrated on an 11 kV 69-bus distribution system....

Geographic Ontologies, Gazetteers and Multilingualism

Directory of Open Access Journals (Sweden)

Robert Laurini

2015-01-01

Full Text Available Different languages imply different visions of space, so that terminologies are different in geographic ontologies. In addition to their geometric shapes, geographic features have names, sometimes different in diverse languages. In addition, the role of gazetteers, as dictionaries of place names (toponyms, is to maintain relations between place names and location. The scope of geographic information retrieval is to search for geographic information not against a database, but against the whole Internet: but the Internet stores information in different languages, and it is of paramount importance not to remain stuck to a unique language. In this paper, our first step is to clarify the links between geographic objects as computer representations of geographic features, ontologies and gazetteers designed in various languages. Then, we propose some inference rules for matching not only types, but also relations in geographic ontologies with the assistance of gazetteers.

RHIC forward experiment to study √s dependence of forward particle production

Directory of Open Access Journals (Sweden)

Sako T.

2017-01-01

Full Text Available The Relativistic Heavy Ion Collider forward experiment is ready to take data in the RHIC Run2017 √s = 510 GeV p-p collisions using the LHCf Arm1 detector. New accelerator data are valuable to verify the Feynman scaling of FX1 production and to study the evolution of the break of scaling in neutron production. Using the transversely polarized proton beam, asymmetric production of forward neutrons is precisely measured. That is useful to understand the fundamental meson exchange in the proton-proton collisions.

Robust Transceiver with Tomlinson-Harashima Precoding for Amplify-and-Forward MIMO Relaying Systems

KAUST Repository

Xing, Chengwen; Xia, Minghua; Gao, Feifei; Wu, Yik-Chung

2012-01-01

forwarding matrices at relays and linear equalizer at destination is proposed. With novel applications of elegant characteristics of multiplicative convexity and matrix-monotone functions, the optimal structure of the nonlinear transceiver is first derived. Based on the derived structure, the transceiver design problem reduces to a much simpler one with only scalar variables which can be efficiently solved. Finally, the performance advantage of the proposed robust design over non-robust design is demonstrated by simulation results.

Very forward measurements at the LHC

CERN Document Server

Berretti, Mirko

2017-01-01

In this talk we present a selection of forward physics results recently obtained with the run-1 and run-2 LHC data by the CMS, LHCf and TOTEM experiments. The status of the very forward LHC proton spectrometer, CT-PPS, is discussed: emphasis is given to the physics potential of CT-PPS and to the analyses that are currently ongoing with the data collected in 2016. Very recent forward measurements obtained with the LHCf and the CMS-CASTOR calorimeter are then addressed. In particular, CMS measured the inclusive energy spectrum in the very forward direction for proton-proton collisions at a center-of-mass energy of 13 TeV and the jet cross sections for p+Pb collisions at 5.02 TeV. The LHCf experiment has instead recently published the inclusive energy spectra of forward photons for pp collisions at 13 TeV. Finally, the new measurements of the total, elastic and inelastic cross sections obtained by the TOTEM collaboration at 2.76 and 13 TeV center of mass energy are presented.

New spatial clustering-based models for optimal urban facility location considering geographical obstacles

Science.gov (United States)

Javadi, Maryam; Shahrabi, Jamal

2014-03-01

The problems of facility location and the allocation of demand points to facilities are crucial research issues in spatial data analysis and urban planning. It is very important for an organization or governments to best locate its resources and facilities and efficiently manage resources to ensure that all demand points are covered and all the needs are met. Most of the recent studies, which focused on solving facility location problems by performing spatial clustering, have used the Euclidean distance between two points as the dissimilarity function. Natural obstacles, such as mountains and rivers, can have drastic impacts on the distance that needs to be traveled between two geographical locations. While calculating the distance between various supply chain entities (including facilities and demand points), it is necessary to take such obstacles into account to obtain better and more realistic results regarding location-allocation. In this article, new models were presented for location of urban facilities while considering geographical obstacles at the same time. In these models, three new distance functions were proposed. The first function was based on the analysis of shortest path in linear network, which was called SPD function. The other two functions, namely PD and P2D, were based on the algorithms that deal with robot geometry and route-based robot navigation in the presence of obstacles. The models were implemented in ArcGIS Desktop 9.2 software using the visual basic programming language. These models were evaluated using synthetic and real data sets. The overall performance was evaluated based on the sum of distance from demand points to their corresponding facilities. Because of the distance between the demand points and facilities becoming more realistic in the proposed functions, results indicated desired quality of the proposed models in terms of quality of allocating points to centers and logistic cost. Obtained results show promising

Influence of Geographic Factors on the Life Cycle Climate Change Impacts of Renewable Energy Systems

Science.gov (United States)

Fortier, M. O. P.

2017-12-01

Life cycle assessment (LCA) is a valuable tool to measure the cradle-to-grave climate change impacts of the sustainable energy systems that are planned to replace conventional fossil energy-based systems. The recent inclusion of geographic specificity in bioenergy LCAs has shown that the relative sustainability of these energy sources is often dependent on geographic factors, such as the climate change impact of changing the land cover and local resource availability. However, this development has not yet been implemented to most LCAs of energy systems that do not have biological feedstocks, such as wind, water, and solar-based energy systems. For example, the tidal velocity where tidal rotors are installed can significantly alter the life cycle climate change impacts of electricity generated using the same technology in different locations. For LCAs of solar updraft towers, the albedo change impacts arising from changing the reflectivity of the land that would be converted can be of the same magnitude as other life cycle process climate change impacts. Improvements to determining the life cycle climate change impacts of renewable energy technologies can be made by utilizing GIS and satellite data and by conducting site-specific analyses. This practice can enhance our understanding of the life cycle environmental impacts of technologies that are aimed to reduce the impacts of our current energy systems, and it can improve the siting of new systems to optimize a reduction in climate change impacts.

Robust Transceiver with Tomlinson-Harashima Precoding for Amplify-and-Forward MIMO Relaying Systems

KAUST Repository

Xing, Chengwen

2012-09-01

In this paper, robust transceiver design with Tomlinson-Harashima precoding (THP) for multi-hop amplifyand-forward (AF) multiple-input multiple-output (MIMO) relaying systems is investigated. At source node, THP is adopted to mitigate the spatial intersymbol interference. However, due to its nonlinear nature, THP is very sensitive to channel estimationerrors. In order to reduce the effects of channel estimation errors, a joint Bayesian robust design of THP at source, linear forwarding matrices at relays and linear equalizer at destination is proposed. With novel applications of elegant characteristics of multiplicative convexity and matrix-monotone functions, the optimal structure of the nonlinear transceiver is first derived. Based on the derived structure, the transceiver design problem reduces to a much simpler one with only scalar variables which can be efficiently solved. Finally, the performance advantage of the proposed robust design over non-robust design is demonstrated by simulation results.

Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution.

Science.gov (United States)

Bangera, Nitin B; Schomer, Donald L; Dehghani, Nima; Ulbert, Istvan; Cash, Sydney; Papavasiliou, Steve; Eisenberg, Solomon R; Dale, Anders M; Halgren, Eric

2010-12-01

Forward solutions with different levels of complexity are employed for localization of current generators, which are responsible for the electric and magnetic fields measured from the human brain. The influence of brain anisotropy on the forward solution is poorly understood. The goal of this study is to validate an anisotropic model for the intracranial electric forward solution by comparing with the directly measured 'gold standard'. Dipolar sources are created at known locations in the brain and intracranial electroencephalogram (EEG) is recorded simultaneously. Isotropic models with increasing level of complexity are generated along with anisotropic models based on Diffusion tensor imaging (DTI). A Finite Element Method based forward solution is calculated and validated using the measured data. Major findings are (1) An anisotropic model with a linear scaling between the eigenvalues of the electrical conductivity tensor and water self-diffusion tensor in brain tissue is validated. The greatest improvement was obtained when the stimulation site is close to a region of high anisotropy. The model with a global anisotropic ratio of 10:1 between the eigenvalues (parallel: tangential to the fiber direction) has the worst performance of all the anisotropic models. (2) Inclusion of cerebrospinal fluid as well as brain anisotropy in the forward model is necessary for an accurate description of the electric field inside the skull. The results indicate that an anisotropic model based on the DTI can be constructed non-invasively and shows an improved performance when compared to the isotropic models for the calculation of the intracranial EEG forward solution.

Constructing forward price curves in electricity markets

DEFF Research Database (Denmark)

Fleten, S.-E.; Lemming, Jørgen Kjærgaard

2003-01-01

We present and analyze a method for constructing approximated high-resolution forward price curves in electricity markets. Because a limited number of forward or futures contracts are traded in the market, only a limited picture of the theoretical continuous forward price curve is available...... to the analyst. Our method combines the information contained in observed bid and ask prices with information from the forecasts generated by bottom-up models. As an example, we use information concerning the shape of the seasonal variation from a bottom-up model to improve the forward price curve quoted...

Combining or Separating Forward and Reverse Logistics

DEFF Research Database (Denmark)

Herbert-Hansen, Zaza Nadja Lee; Larsen, Samuel; Nielsen, Anders

2018-01-01

Purpose – While forward logistics handles and manages the flow of goods downstream in the supply chain from suppliers to customers, reverse logistics (RL) manages the flow of returned goods upstream. A firm can combine reverse logistics with forward logistics, keep the flows separated, or choose......-research addresses intra-RL issues while the relationship between forward and reverse logistics is under-researched. This paper contributes to RL-theory by identifying the contextual factors that determine the most advantageous relationship between forward and reverse logistics, and proposes a novel decision making...

A mathematical model for optimization of an integrated network logistic design

Directory of Open Access Journals (Sweden)

Lida Tafaghodi

2011-10-01

Full Text Available In this study, the integrated forward/reverse logistics network is investigated, and a capacitated multi-stage, multi-product logistics network design is proposed by formulating a generalized logistics network problem into a mixed-integer nonlinear programming model (MINLP for minimizing the total cost of the closed-loop supply chain network. Moreover, the proposed model is solved by using optimization solver, which provides the decisions related to the facility location problem, optimum quantity of shipped product, and facility capacity. Numerical results show the power of the proposed MINLP model to avoid th sub-optimality caused by separate design of forward and reverse logistics networks and to handle various transportation modes and periodic demand.

The forwarding indices of graphs - a survey

Directory of Open Access Journals (Sweden)

Jun-Ming Xu

2013-01-01

Full Text Available A routing \\(R\\ of a connected graph \\(G\\ of order \\(n\\ is a collection of \\(n(n-1\\ simple paths connecting every ordered pair of vertices of \\(G\\. The vertex-forwarding index \\(\\xi(G,R\\ of \\(G\\ with respect to a routing \\(R\\ is defined as the maximum number of paths in \\(R\\ passing through any vertex of \\(G\\. The vertex-forwarding index \\(\\xi(G\\ of \\(G\\ is defined as the minimum \\(\\xi(G,R\\ over all routings \\(R\\ of \\(G\\. Similarly, the edge-forwarding index \\(\\pi(G,R\\ of \\(G\\ with respect to a routing \\(R\\ is the maximum number of paths in \\(R\\ passing through any edge of \\(G\\. The edge-forwarding index \\(\\pi(G\\ of \\(G\\ is the minimum \\(\\pi(G,R\\ over all routings \\(R\\ of \\(G\\. The vertex-forwarding index or the edge-forwarding index corresponds to the maximum load of the graph. Therefore, it is important to find routings minimizing these indices and thus has received much research attention for over twenty years. This paper surveys some known results on these forwarding indices, further research problems and several conjectures, also states some difficulty and relations to other topics in graph theory.

Immigrants Equilibrate Local Labor Markets: Evidence from the Great Recession*

Science.gov (United States)

Cadena, Brian C.; Kovak, Brian K.

2016-01-01

This paper demonstrates that low-skilled Mexican-born immigrants’ location choices in the U.S. respond strongly to changes in local labor demand, and that this geographic elasticity helps equalize spatial differences in labor market outcomes for low-skilled native workers, who are much less responsive. We leverage the substantial geographic variation in employment losses that occurred during Great Recession, and our results confirm the standard finding that high-skilled populations are quite geographically responsive to employment opportunities while low-skilled populations are much less so. However, low-skilled immigrants, especially those from Mexico, respond even more strongly than high-skilled native-born workers. Moreover, we show that natives living in metro areas with a substantial Mexican-born population are insulated from the effects of local labor demand shocks compared to those in places with few Mexicans. The reallocation of the Mexican-born workforce reduced the incidence of local demand shocks on low-skilled natives’ employment outcomes by more than 50 percent. PMID:27551329

Forward Osmosis Process

KAUST Repository

Duan, Jintang

2013-12-05

A process that can alleviate the internal concentration polarization and can enhance membrane performance of a forward osmosis system includes the steps of passing a fluid in a forward osmosis system from a feed solution with a first osmotic pressure, through a membrane into a draw solution comprising a draw solute with a second osmotic pressure, where the first osmotic pressure is lower than the second osmotic pressure, the membrane includes an active layer and a support layer, and the membrane is oriented such that the active layer of the membrane faces a draw side, and the support layer faces a feed side; and applying an external force to the fluid on the feed side of the membrane.

Forward Osmosis Process

KAUST Repository

Duan, Jintang; Pinnau, Ingo; Litwiller, Eric

2013-01-01

A process that can alleviate the internal concentration polarization and can enhance membrane performance of a forward osmosis system includes the steps of passing a fluid in a forward osmosis system from a feed solution with a first osmotic pressure, through a membrane into a draw solution comprising a draw solute with a second osmotic pressure, where the first osmotic pressure is lower than the second osmotic pressure, the membrane includes an active layer and a support layer, and the membrane is oriented such that the active layer of the membrane faces a draw side, and the support layer faces a feed side; and applying an external force to the fluid on the feed side of the membrane.

Bistatic Forward Scattering Radar Detection and Imaging

Directory of Open Access Journals (Sweden)

Hu Cheng

2016-06-01

Full Text Available Forward Scattering Radar (FSR is a special type of bistatic radar that can implement image detection, imaging, and identification using the forward scattering signals provided by the moving targets that cross the baseline between the transmitter and receiver. Because the forward scattering effect has a vital significance in increasing the targets’ Radar Cross Section (RCS, FSR is quite advantageous for use in counter stealth detection. This paper first introduces the front line technology used in forward scattering RCS, FSR detection, and Shadow Inverse Synthetic Aperture Radar (SISAR imaging and key problems such as the statistical characteristics of forward scattering clutter, accurate parameter estimation, and multitarget discrimination are then analyzed. Subsequently, the current research progress in FSR detection and SISAR imaging are described in detail, including the theories and experiments. In addition, with reference to the BeiDou navigation satellite, the results of forward scattering experiments in civil aircraft detection are shown. Finally, this paper considers future developments in FSR target detection and imaging and presents a new, promising technique for stealth target detection.

A localized navigation algorithm for Radiation Evasion for nuclear facilities. Part II: Optimizing the “Nearest Exit” Criterion

Energy Technology Data Exchange (ETDEWEB)

Khasawneh, Mohammed A., E-mail: mkha@ieee.org [Department of Electrical Engineering, Jordan University of Science and Technology (Jordan); Al-Shboul, Zeina Aman M., E-mail: xeinaaman@gmail.com [Department of Electrical Engineering, Jordan University of Science and Technology (Jordan); Jaradat, Mohammad A., E-mail: majaradat@just.edu.jo [Department of Mechanical Engineering, Jordan University of Science and Technology (Jordan); Malkawi, Mohammad I., E-mail: mmalkawi@aimws.com [College of Engineering, Jadara University, Irbid 221 10 (Jordan)

2013-06-15

Highlights: ► A new navigation algorithm for Radiation Evasion around nuclear facilities. ► An optimization criteria minimized under algorithm operation. ► A man-borne device guiding the occupational worker towards paths that warrant least radiation × time products. ► Benefits of using localized navigation as opposed to global navigation schemas. ► A path discrimination function for finding the navigational paths exhibiting the least amounts of radiation. -- Abstract: In this extension from part I (Khasawneh et al., in press), we modify the navigation algorithm which was presented with the objective of optimizing the “Radiation Evasion” Criterion so that navigation would optimize the criterion of “Nearest Exit”. Under this modification, algorithm would yield navigation paths that would guide occupational workers towards Nearest Exit points. Again, under this optimization criterion, algorithm leverages the use of localized information acquired through a well designed and distributed wireless sensor network, as it averts the need for any long-haul communication links or centralized decision and monitoring facility thereby achieving a more reliable performance under dynamic environments. As was done in part I, the proposed algorithm under the “Nearest Exit” Criterion is designed to leverage nearest neighbor information coming in through the sensory network overhead, in computing successful navigational paths from one point to another. For comparison purposes, the proposed algorithm is tested under the two optimization criteria: “Radiation Evasion” and “Nearest Exit”, for different numbers of step look-ahead. We verify the performance of the algorithm by means of simulations, whereby navigational paths are calculated for different radiation fields. We, via simulations, also, verify the performance of the algorithm in comparison with a well-known global navigation algorithm upon which we draw our conclusions.

A localized navigation algorithm for Radiation Evasion for nuclear facilities. Part II: Optimizing the “Nearest Exit” Criterion

International Nuclear Information System (INIS)

Khasawneh, Mohammed A.; Al-Shboul, Zeina Aman M.; Jaradat, Mohammad A.; Malkawi, Mohammad I.

2013-01-01

Highlights: ► A new navigation algorithm for Radiation Evasion around nuclear facilities. ► An optimization criteria minimized under algorithm operation. ► A man-borne device guiding the occupational worker towards paths that warrant least radiation × time products. ► Benefits of using localized navigation as opposed to global navigation schemas. ► A path discrimination function for finding the navigational paths exhibiting the least amounts of radiation. -- Abstract: In this extension from part I (Khasawneh et al., in press), we modify the navigation algorithm which was presented with the objective of optimizing the “Radiation Evasion” Criterion so that navigation would optimize the criterion of “Nearest Exit”. Under this modification, algorithm would yield navigation paths that would guide occupational workers towards Nearest Exit points. Again, under this optimization criterion, algorithm leverages the use of localized information acquired through a well designed and distributed wireless sensor network, as it averts the need for any long-haul communication links or centralized decision and monitoring facility thereby achieving a more reliable performance under dynamic environments. As was done in part I, the proposed algorithm under the “Nearest Exit” Criterion is designed to leverage nearest neighbor information coming in through the sensory network overhead, in computing successful navigational paths from one point to another. For comparison purposes, the proposed algorithm is tested under the two optimization criteria: “Radiation Evasion” and “Nearest Exit”, for different numbers of step look-ahead. We verify the performance of the algorithm by means of simulations, whereby navigational paths are calculated for different radiation fields. We, via simulations, also, verify the performance of the algorithm in comparison with a well-known global navigation algorithm upon which we draw our conclusions

Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

OpenAIRE

Yumin, Dong; Li, Zhao

2014-01-01

Quantum behaved particle swarm algorithm is a new intelligent optimization algorithm; the algorithm has less parameters and is easily implemented. In view of the existing quantum behaved particle swarm optimization algorithm for the premature convergence problem, put forward a quantum particle swarm optimization algorithm based on artificial fish swarm. The new algorithm based on quantum behaved particle swarm algorithm, introducing the swarm and following activities, meanwhile using the a...

Forward planning

International Nuclear Information System (INIS)

Fontenla, D.P.

2008-01-01

By definition, forward planning is a process where input consists of conditions on beam configurations and parameters and output consists of dose distributions on target and critical structures, in contrast to inverse planning, where the opposite is true. For forward planning IMRT, criteria are as follows: (i) Plans created as an extension of standard 3D conformational planning; (ii) No significant increase in the complexity of the treatment planning or treatment delivery process; (3) Treatment verification using standard QA procedures; and process consists of the following steps: (i) Create a standard 3D conformational treatment plan; (ii) Copy one of the existing beams; (iii) Create control points: design new beam segments, blocking high dose areas; (iv) Repeat for all beams; (v) Re-compute dose; and (vi) Adjust control points weights to achieve desired dose distribution. A detailed exposition, with many clinical examples, is given for the breast, lung, and brain (P.A.)

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.

Hanford spent nuclear fuel project recommended path forward, volume III: Alternatives and path forward evaluation supporting documentation

International Nuclear Information System (INIS)

Fulton, J.C.

1994-10-01

Volume I of the Hanford Spent Nuclear Fuel Project - Recommended Path Forward constitutes an aggressive series of projects to construct and operate systems and facilities to safely retrieve, package, transport, process, and store K Basins fuel and sludge. Volume II provided a comparative evaluation of four Alternatives for the Path Forward and an evaluation for the Recommended Path Forward. Although Volume II contained extensive appendices, six supporting documents have been compiled in Volume III to provide additional background for Volume II

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...

Constructing forward price curves in electricity markets

International Nuclear Information System (INIS)

Fleten, Stein-Erik; Lemming, Jacob

2003-01-01

We present and analyze a method for constructing approximated high-resolution forward price curves in electricity markets. Because a limited number of forward or futures contracts are traded in the market, only a limited picture of the theoretical continuous forward price curve is available to the analyst. Our method combines the information contained in observed bid and ask prices with information from the forecasts generated by bottom-up models. As an example, we use information concerning the shape of the seasonal variation from a bottom-up model to improve the forward price curve quoted on the Nordic power exchange

Optimized Neural Network for Fault Diagnosis and Classification

International Nuclear Information System (INIS)

Elaraby, S.M.

2005-01-01

This paper presents a developed and implemented toolbox for optimizing neural network structure of fault diagnosis and classification. Evolutionary algorithm based on hierarchical genetic algorithm structure is used for optimization. The simplest feed-forward neural network architecture is selected. Developed toolbox has friendly user interface. Multiple solutions are generated. The performance and applicability of the proposed toolbox is verified with benchmark data patterns and accident diagnosis of Egyptian Second research reactor (ETRR-2)

Salers Protected Designation of Origin cheese, France. The diversity and paradox of local knowledge in geographical indications

Directory of Open Access Journals (Sweden)

Bérard, Laurence

2016-06-01

Full Text Available Our case study of Salers cheese production in south-central France highlights how place-specific knowledge grounds the various networks shaping the rise of geographical indications (GI in food production. In 1961, Salers cheese producers created a “Protected Designation of Origin” (PDO. To preserve the distinctive character of their product, they opted to require use of the gerle, a traditional wooden vat, and an on-farm cheese making process. The gerle came recently under scrutiny from French governmental hygiene regulation enforcement, and the subsequent public controversy jeopardized the entire supply chain and destabilized Salers cheese-making methods. Prevailing in their efforts to protect Salers, producers established the gerle as mandatory and have since set up a governance board to ensure PDO brand integrity. Our analysis suggests that the diversity of technical choices and associated set of knowledge in Salers cheese production has paradoxically been both its strength and weakness. Local agricultural know-how forges links among participants in Salers networks, connecting cheese producers and consumers, to cattle, microbes, landscapes, wooden tools, and cheeses. Yet, diversity of local expertise creates a tension among producers who must collaborate to achieve unified standards within a PDO while resisting homogeneity. Such results contribute to discussing on PDO governance: an arena to share, compare, and unite local knowledge is critical for GI and thus for sustainable agricultural systems.Nuestro caso de estudio sobre producción de queso de Salers, en el centro-sur de Francia, ilustra cómo los saberes específicos locales explican el origen de la formación de una indicación geográfica (IG. En 1961, los productores del queso de Salers crearon una denominación de origen protegida (DOP. Para preservar el carácter distintivo de sus productos, optaron por requerir como condiciones necesarias tanto el uso de la «gerle», una

A Study on the Defensive Stance and Position of Handball Goalkeepers: Facing a Forward Jump Shot Made from 9 Meters.

Science.gov (United States)

Yang, Jong Hyun; Lee, Young Suk

2016-10-01

The purpose of this study was to find the defensive stance and calculate an optimal defense position for goalkeepers while blocking forward jump shots made from a distance of 9 m. Nine men's handball matches were recorded and 78 video clips were selected for analysis. These are the top class goalkeepers, which included players from the national team and reserve team of Korea. The goalkeeper's actual defensive position was significantly different from instructional suggestions; the width of both feet of the goalkeeper was approximately 2.5 times the width of the shoulders, and the hands were at waist height. The goalkeeper's actual defense position was about 1.10 (± 0.3) m from the goal line and also significantly different than instructional material (0.75 m). The optimal defense position, which was calculated from the goalkeeper's actual movement, was 1.44 m from the goal line, because the ratio of goalkeeper's defensive area in relation to the total area to be defended is highest at this point. In summary, we recommended that handball goalkeepers move forward, about a half step (0.34 m), when defending a forward jump shot made from 9 m, and instructional material should be modified according to the findings from this study.

Laser-induced forward transfer (LIFT) of congruent voxels

Energy Technology Data Exchange (ETDEWEB)

Piqué, Alberto, E-mail: pique@nrl.navy.mil [Materials Science and Technology Division, Code 6364, Naval Research Laboratory, Washington, DC 20375 (United States); Kim, Heungsoo; Auyeung, Raymond C.Y.; Beniam, Iyoel [Materials Science and Technology Division, Code 6364, Naval Research Laboratory, Washington, DC 20375 (United States); Breckenfeld, Eric [National Research Council Fellow at the Naval Research Laboratory, Washington, DC 20375 (United States)

2016-06-30

Highlights: • Laser-induced forward transfer (LIFT) is demonstrated with high viscosity Ag nanopaste. • Under the right conditions (viscosity and fluence) the transfer of congruent voxels was achieved. • For viscosities under 100 Pa s, congruent voxel transfer of silver nano-suspensions is only possible under a very narrow range of conditions. • For viscosities over 100 Pa s, congruent voxel transfer of silver nano-pastes works over a wider range of fluences, donor substrate thickness, gap distances and voxel areas. • The laser transfer of congruent voxels can be used for printing electronic patterns in particular interconnects. - Abstract: Laser-induced forward transfer (LIFT) of functional materials offers unique advantages and capabilities for the rapid prototyping of electronic, optical and sensor elements. The use of LIFT for printing high viscosity metallic nano-inks and nano-pastes can be optimized for the transfer of voxels congruent with the shape of the laser pulse, forming thin film-like structures non-lithographically. These processes are capable of printing patterns with excellent lateral resolution and thickness uniformity typically found in 3-dimensional stacked assemblies, MEMS-like structures and free-standing interconnects. However, in order to achieve congruent voxel transfer with LIFT, the particle size and viscosity of the ink or paste suspensions must be adjusted to minimize variations due to wetting and drying effects. When LIFT is carried out with high-viscosity nano-suspensions, the printed voxel size and shape become controllable parameters, allowing the printing of thin-film like structures whose shape is determined by the spatial distribution of the laser pulse. The result is a new level of parallelization beyond current serial direct-write processes whereby the geometry of each printed voxel can be optimized according to the pattern design. This work shows how LIFT of congruent voxels can be applied to the fabrication of 2D

Laser-induced forward transfer (LIFT) of congruent voxels

International Nuclear Information System (INIS)

Piqué, Alberto; Kim, Heungsoo; Auyeung, Raymond C.Y.; Beniam, Iyoel; Breckenfeld, Eric

2016-01-01

Highlights: • Laser-induced forward transfer (LIFT) is demonstrated with high viscosity Ag nanopaste. • Under the right conditions (viscosity and fluence) the transfer of congruent voxels was achieved. • For viscosities under 100 Pa s, congruent voxel transfer of silver nano-suspensions is only possible under a very narrow range of conditions. • For viscosities over 100 Pa s, congruent voxel transfer of silver nano-pastes works over a wider range of fluences, donor substrate thickness, gap distances and voxel areas. • The laser transfer of congruent voxels can be used for printing electronic patterns in particular interconnects. - Abstract: Laser-induced forward transfer (LIFT) of functional materials offers unique advantages and capabilities for the rapid prototyping of electronic, optical and sensor elements. The use of LIFT for printing high viscosity metallic nano-inks and nano-pastes can be optimized for the transfer of voxels congruent with the shape of the laser pulse, forming thin film-like structures non-lithographically. These processes are capable of printing patterns with excellent lateral resolution and thickness uniformity typically found in 3-dimensional stacked assemblies, MEMS-like structures and free-standing interconnects. However, in order to achieve congruent voxel transfer with LIFT, the particle size and viscosity of the ink or paste suspensions must be adjusted to minimize variations due to wetting and drying effects. When LIFT is carried out with high-viscosity nano-suspensions, the printed voxel size and shape become controllable parameters, allowing the printing of thin-film like structures whose shape is determined by the spatial distribution of the laser pulse. The result is a new level of parallelization beyond current serial direct-write processes whereby the geometry of each printed voxel can be optimized according to the pattern design. This work shows how LIFT of congruent voxels can be applied to the fabrication of 2D

Algorithmic Optimal Management of a Potable Water Distribution System: Application to the Primary Network of Bonaberi (Douala, Cameroon

Directory of Open Access Journals (Sweden)

Zineb Simeu-Abazi

2009-11-01

Full Text Available The optimal management of a potable water distribution system requires the control of the reference (standard data, the control points, control of the drainage parameters (pressure, flow, etc. and maintenance parameters. The control of the mentioned data defines the network learning process [1]. Besides classic IT functions of acquisition, storage and data processing, a geographical information system (GIS can be used as the basis for an alarm system, allowing one to identify and to localize the presence of water leaks in the network [2]. In this article we propose an algorithm coupling the various drainage parameters for the management of the network. The algorithm leads to an optimal management of leaks. An application is in progress on the primary network in the region of Bonaberi in Douala, the largest city of Cameroon.

Backward- and forward-looking responsibility for obesity: policies from WHO, the EU and England.

Science.gov (United States)

Vallgårda, Signild; Nielsen, Morten Ebbe Juul; Hartlev, Mette; Sandøe, Peter

2015-10-01

In assigning responsibility for obesity prevention a distinction may be drawn between who is responsible for the rise in obesity prevalence ('backward-looking responsibility'), and who is responsible for reducing it ('forward-looking responsibility'). We study how the two aspects of responsibility figure in the obesity policies of WHO (European Region), the EU and the Department of Health (England). Responsibility for the emergence and reduction of obesity is assigned to both individuals and other actors to different degrees in the policies, combining an individual and a systemic view. The policies assign backward-looking responsibility to individuals, the social environment, the authorities and businesses. When it comes to forward-looking responsibility, individuals are expected to play a central role in reducing and preventing obesity, but other actors are also urged to act. WHO assigns to individuals the lowest degree of backward- and forward-looking responsibility, and the Department of Health (England) assigns them the highest degree of responsibility. Differences in the assignment of backward- and above all forward-looking responsibility could be explained to some extent by the different roles of the three authorities making the plans. WHO is a UN agency with health as its goal, the EU is a liberal economic union with optimization of the internal European market as an important task, and England, as an independent sovereign country, has its own economic responsibilities. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

SU-F-J-11: Radiobiologically Optimized Patient Localization During Prostate External Beam Localization

Energy Technology Data Exchange (ETDEWEB)

Huang, Y; Gardner, S; Liu, C; Zhao, B; Wen, N; Brown, S; Chetty, I [Henry Ford Health System, Detroit, MI (United States)

2016-06-15

Purpose: To present a novel positioning strategy which optimizes radiation delivery with radiobiological response knowledge, and to evaluate its application during prostate external beam radiotherapy. Methods: Ten patients with low or intermediate risk prostate cancer were evaluated retrospectively in this IRB-approved study. For each patient, a VMAT plan was generated on the planning CT (PCT) to deliver 78 Gy in 39 fractions with PTV = prostate + 7 mm margin, except for 5mm in the posterior direction. Five representative pretreatment CBCT images were selected for each patient, and prostate, rectum, and bladder were delineated on all CBCT images. Each CBCT was auto-registered to the corresponding PCT. Starting from this auto-matched position (AM-position), a search for optimal treatment position was performed utilizing a score function based on radiobiological and dosimetric indices (D98-DTV, NTCP-rectum, and NTCP-bladder) for the daily target volume (DTV), rectum, and bladder. DTV was defined as prostate + 4 mm margin to account for intra-fraction motion as well as contouring variability on CBCT. We termed the optimal treatment position the radiobiologically optimized couch shift position (ROCS-position). Results: The indices, averaged over the 10 patients’ treatment plans, were (mean±SD): 77.7±0.2 Gy (D98-PTV), 12.3±2.7% (NTCP-rectum), and 53.2±11.2% (NTCP-bladder). The corresponding values calculated on all 50 CBCT images at the AM-positions were 72.9±11.3 Gy (D98-DTV), 15.8±6.4% (NTCP-rectum), and 53.0±21.1% (NTCP-bladder), respectively. In comparison, calculated on CBCT at the ROCS-positions, the indices were 77.0±2.1 Gy (D98-DTV), 12.1±5.7% (NTCP-rectum), and 60.7±16.4% (NTCP-bladder). Compared to autoregistration, ROCS-optimization recovered dose coverage to target volume and lowered the risk to rectum. Moreover, NTCPrectum for one patient remained high after ROCS-optimization and therefore could potentially benefit from adaptive planning

Adaptive local routing strategy on a scale-free network

International Nuclear Information System (INIS)

Feng, Liu; Han, Zhao; Ming, Li; Yan-Bo, Zhu; Feng-Yuan, Ren

2010-01-01

Due to the heterogeneity of the structure on a scale-free network, making the betweennesses of all nodes become homogeneous by reassigning the weights of nodes or edges is very difficult. In order to take advantage of the important effect of high degree nodes on the shortest path communication and preferentially deliver packets by them to increase the probability to destination, an adaptive local routing strategy on a scale-free network is proposed, in which the node adjusts the forwarding probability with the dynamical traffic load (packet queue length) and the degree distribution of neighbouring nodes. The critical queue length of a node is set to be proportional to its degree, and the node with high degree has a larger critical queue length to store and forward more packets. When the queue length of a high degree node is shorter than its critical queue length, it has a higher probability to forward packets. After higher degree nodes are saturated (whose queue lengths are longer than their critical queue lengths), more packets will be delivered by the lower degree nodes around them. The adaptive local routing strategy increases the probability of a packet finding its destination quickly, and improves the transmission capacity on the scale-free network by reducing routing hops. The simulation results show that the transmission capacity of the adaptive local routing strategy is larger than that of three previous local routing strategies. (general)

Management Accounting in freight-forwarding companies

DEFF Research Database (Denmark)

Jensen, Jens Ocksen; Lynggaard, Peter

2002-01-01

The article describes the internal business management processes in a freight forwarding compagny on the operative/tactical level. This is done as an explorative study of how these processes are organized in two medium-sized Danish freight-forwarding compagnies....

Geographical variation in egg mass and egg content in a passerine bird.

Directory of Open Access Journals (Sweden)

Suvi Ruuskanen

Full Text Available Reproductive, phenotypic and life-history traits in many animal and plant taxa show geographic variation, indicating spatial variation in selection regimes. Maternal deposition to avian eggs, such as hormones, antibodies and antioxidants, critically affect development of the offspring, with long-lasting effects on the phenotype and fitness. Little is however known about large-scale geographical patterns of variation in maternal deposition to eggs. We studied geographical variation in egg components of a passerine bird, the pied flycatcher (Ficedula hypoleuca, by collecting samples from 16 populations and measuring egg and yolk mass, albumen lysozyme activity, yolk immunoglobulins, yolk androgens and yolk total carotenoids. We found significant variation among populations in most egg components, but ca. 90% of the variation was among individuals within populations. Population however explained 40% of the variation in carotenoid levels. In contrast to our hypothesis, we found geographical trends only in carotenoids, but not in any of the other egg components. Our results thus suggest high within-population variation and leave little scope for local adaptation and genetic differentiation in deposition of different egg components. The role of these maternally-derived resources in evolutionary change should be further investigated.

Optimal frequency of rabies vaccination campaigns in Sub-Saharan Africa.

Science.gov (United States)

Bilinski, Alyssa M; Fitzpatrick, Meagan C; Rupprecht, Charles E; Paltiel, A David; Galvani, Alison P

2016-11-16

Rabies causes more than 24 000 human deaths annually in Sub-Saharan Africa. The World Health Organization recommends annual canine vaccination campaigns with at least 70% coverage to control the disease. While previous studies have considered optimal coverage of animal rabies vaccination, variation in the frequency of vaccination campaigns has not been explored. To evaluate the cost-effectiveness of rabies canine vaccination campaigns at varying coverage and frequency, we parametrized a rabies virus transmission model to two districts of northwest Tanzania, Ngorongoro (pastoral) and Serengeti (agro-pastoral). We found that optimal vaccination strategies were every 2 years, at 80% coverage in Ngorongoro and annually at 70% coverage in Serengeti. We further found that the optimality of these strategies was sensitive to the rate of rabies reintroduction from outside the district. Specifically, if a geographically coordinated campaign could reduce reintroduction, vaccination campaigns every 2 years could effectively manage rabies in both districts. Thus, coordinated campaigns may provide monetary savings in addition to public health benefits. Our results indicate that frequency and coverage of canine vaccination campaigns should be evaluated simultaneously and tailored to local canine ecology as well as to the risk of disease reintroduction from surrounding regions. © 2016 The Author(s).

Geographical and temporal changes of anthropometric traits in historical Yemen.

Science.gov (United States)

Danubio, Maria Enrica; Milia, Nicola; Coppa, Alfredo; Rufo, Fabrizio; Sanna, Emanuele

2016-02-01

This study investigates secular changes of anthropometric variables among four geographic groups in historical Yemen, to evaluate possible regional differences in the evolution of living standards. Nineteen somatic and cephalic measures collected by Coon in 1939, and 8 anthropometric indices in 1244 Yemenite adult males were analyzed. The individuals were divided into 10-year age groups. Within-group variations were tested by One-way ANCOVA (age as covariate). ANCOVA (controlling for age), and Forward stepwise discriminant analysis were used to evaluate and represent regional differences. ANCOVA and discriminant analysis confirmed and enhanced previous findings. At the time, the Yemenite population presented high intergroup heterogeneity. The highest mean values of height at all ages were found in the "mountain" region, which is characterized by very fertile soils and where, nowadays, most of the cereals and pulses are grown and where most livestock is raised. Within-group variations were limited and generally inconsistent in all geographic regions and concern vertical dimensions, but mean values of height never differed. The prolonged internal isolation of these groups resulted in significant regional morphometric differentiation. The main evidence comes from height which suggests that socioeconomic factors have played a role. Nevertheless, the possible better living conditions experienced by the "mountain" group, with the highest mean values of stature in all periods, did not allow the secular trend to take place in that region, too. Copyright © 2015. Published by Elsevier GmbH.

GEOGRAPHIC NAMES INFORMATION SYSTEM (GNIS) ...

Science.gov (United States)

The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.

Why do firms engage in forward-looking search?

DEFF Research Database (Denmark)

Jissink, Tymen; Rohrbeck, René; Huizingh, Eelko K.R.E.

firms with a low level of slack resources engage to a much lower extent into forward-looking search, if they operate in high-competitive-intensity environments. Our findings not only carry important implications for predicting a firm’s engagement in forward-looking search, but also potentially...... performed below aspirations are less likely to engage in forward-looking search, suggesting that forward-looking search is not a form of problemistic search. In contrast, firms that have abundant uncommitted (slack) resources as well as firms expecting to outperform in the near future are engaging more...... into forward-looking search. We also find interaction effect between performance feedback and environmental characteristics. Interestingly firms with a high level of slack resources are only surpassing their less rich peers in forward-looking search, if they are in technologically turbulent environments. Also...

Optimal urban networks via mass transportation

CERN Document Server

Buttazzo, Giuseppe; Stepanov, Eugene; Solimini, Sergio

2009-01-01

Recently much attention has been devoted to the optimization of transportation networks in a given geographic area. One assumes the distributions of population and of services/workplaces (i.e. the network's sources and sinks) are known, as well as the costs of movement with/without the network, and the cost of constructing/maintaining it. Both the long-term optimization and the short-term, "who goes where" optimization are considered. These models can also be adapted for the optimization of other types of networks, such as telecommunications, pipeline or drainage networks. In the monograph we study the most general problem settings, namely, when neither the shape nor even the topology of the network to be constructed is known a priori.

Indicator 1.07. Number and geographic distribution of forest-associated species at risk of losing genetic variation and locally adapted genotypes

Science.gov (United States)

C. H. Flather; M. S Knowles; C. H. Sieg

2011-01-01

This indicator provides information on the number and distribution of forest-associated species at risk of losing genetic variation across their geographic range. Comparing a species' current geographic distribution with its historic distribution is the basis for identifying those species whose range has contracted significantly. Human activities are accelerating...

Geographic divergence and colour change in response to visual backgrounds and illumination intensity in bearded dragons.

Science.gov (United States)

Cadena, Viviana; Smith, Kathleen R; Endler, John A; Stuart-Fox, Devi

2017-03-15

Animals may improve camouflage by both dynamic colour change and local evolutionary adaptation of colour but we have little understanding of their relative importance in colour-changing species. We tested for differences in colour change in response to background colour and light intensity in two populations of central bearded dragon lizards ( Pogona vitticeps ) representing the extremes in body coloration and geographical range. We found that bearded dragons change colour in response to various backgrounds and that colour change is affected by illumination intensity. Within-individual colour change was similar in magnitude in the two populations but varied between backgrounds. However, at the endpoints of colour change, each population showed greater similarity to backgrounds that were representative of the local habitat compared with the other population, indicating local adaptation to visual backgrounds. Our results suggest that even in species that change colour, both phenotypic plasticity and geographic divergence of coloration may contribute to improved camouflage. © 2017. Published by The Company of Biologists Ltd.

Poverty concentration in an affluent city: Geographic variation and correlates of neighborhood poverty rates in Hong Kong

Science.gov (United States)

Guo, Yingqi; Chang, Shu-Sen; Sha, Feng

2018-01-01

Previous investigations of geographic concentration of urban poverty indicate the contribution of a variety of factors, such as economic restructuring and class-based segregation, racial segregation, demographic structure, and public policy. However, the models used by most past research do not consider the possibility that poverty concentration may take different forms in different locations across a city, and most studies have been conducted in Western settings. We investigated the spatial patterning of neighborhood poverty and its correlates in Hong Kong, which is amongst cities with the highest GDP in the region, using the city-wide ordinary least square (OLS) regression model and the local-specific geographically weighted regression (GWR) model. We found substantial geographic variations in small-area poverty rates and identified several poverty clusters in the territory. Factors found to contribute to urban poverty in Western cities, such as socioeconomic factors, ethnicity, and public housing, were also mostly associated with local poverty rates in Hong Kong. Our results also suggest some heterogeneity in the associations of poverty with specific correlates (e.g. access to hospitals) that would be masked in the city-wide OLS model. Policy aimed to alleviate poverty should consider both city-wide and local-specific factors. PMID:29474393

Poverty concentration in an affluent city: Geographic variation and correlates of neighborhood poverty rates in Hong Kong.

Science.gov (United States)

Guo, Yingqi; Chang, Shu-Sen; Sha, Feng; Yip, Paul S F

2018-01-01

Previous investigations of geographic concentration of urban poverty indicate the contribution of a variety of factors, such as economic restructuring and class-based segregation, racial segregation, demographic structure, and public policy. However, the models used by most past research do not consider the possibility that poverty concentration may take different forms in different locations across a city, and most studies have been conducted in Western settings. We investigated the spatial patterning of neighborhood poverty and its correlates in Hong Kong, which is amongst cities with the highest GDP in the region, using the city-wide ordinary least square (OLS) regression model and the local-specific geographically weighted regression (GWR) model. We found substantial geographic variations in small-area poverty rates and identified several poverty clusters in the territory. Factors found to contribute to urban poverty in Western cities, such as socioeconomic factors, ethnicity, and public housing, were also mostly associated with local poverty rates in Hong Kong. Our results also suggest some heterogeneity in the associations of poverty with specific correlates (e.g. access to hospitals) that would be masked in the city-wide OLS model. Policy aimed to alleviate poverty should consider both city-wide and local-specific factors.