Optimized Aircraft Electric Control System Based on Adaptive Tabu Search Algorithm and Fuzzy Logic Control

Directory of Open Access Journals (Sweden)

Saifullah Khalid

2016-09-01

Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.

A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem.

Science.gov (United States)

Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah

2016-01-01

The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.

A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem

Science.gov (United States)

Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah

2016-01-01

The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them. PMID:26819585

Tabu search, a versatile technique for the functions optimization; Busqueda Tabu, una tecnica versatil para la optimizacion de funciones

Energy Technology Data Exchange (ETDEWEB)

Castillo M, J.A. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)

2003-07-01

The basic elements of the Tabu search technique are presented, putting emphasis in the qualities that it has in comparison with the traditional methods of optimization known as in descending pass. Later on some modifications are sketched that have been implemented in the technique along the time, so that this it is but robust. Finally they are given to know some areas where this technique has been applied, obtaining successful results. (Author)

System identification using Nuclear Norm & Tabu Search optimization

Science.gov (United States)

Ahmed, Asif A.; Schoen, Marco P.; Bosworth, Ken W.

2018-01-01

In recent years, subspace System Identification (SI) algorithms have seen increased research, stemming from advanced minimization methods being applied to the Nuclear Norm (NN) approach in system identification. These minimization algorithms are based on hard computing methodologies. To the authors’ knowledge, as of now, there has been no work reported that utilizes soft computing algorithms to address the minimization problem within the nuclear norm SI framework. A linear, time-invariant, discrete time system is used in this work as the basic model for characterizing a dynamical system to be identified. The main objective is to extract a mathematical model from collected experimental input-output data. Hankel matrices are constructed from experimental data, and the extended observability matrix is employed to define an estimated output of the system. This estimated output and the actual - measured - output are utilized to construct a minimization problem. An embedded rank measure assures minimum state realization outcomes. Current NN-SI algorithms employ hard computing algorithms for minimization. In this work, we propose a simple Tabu Search (TS) algorithm for minimization. TS algorithm based SI is compared with the iterative Alternating Direction Method of Multipliers (ADMM) line search optimization based NN-SI. For comparison, several different benchmark system identification problems are solved by both approaches. Results show improved performance of the proposed SI-TS algorithm compared to the NN-SI ADMM algorithm.

Tabu search approaches for the multi-level warehouse layout problem with adjacency constraints

Science.gov (United States)

Zhang, G. Q.; Lai, K. K.

2010-08-01

A new multi-level warehouse layout problem, the multi-level warehouse layout problem with adjacency constraints (MLWLPAC), is investigated. The same item type is required to be located in adjacent cells, and horizontal and vertical unit travel costs are product dependent. An integer programming model is proposed to formulate the problem, which is NP hard. Along with a cube-per-order index policy based heuristic, the standard tabu search (TS), greedy TS, and dynamic neighbourhood based TS are presented to solve the problem. The computational results show that the proposed approaches can reduce the transportation cost significantly.

A practical optimization procedure for radial BWR fuel lattice design using tabu search with a multiobjective function

International Nuclear Information System (INIS)

Francois, J.L.; Martin-del-Campo, C.; Francois, R.; Morales, L.B.

2003-01-01

An optimization procedure based on the tabu search (TS) method was developed for the design of radial enrichment and gadolinia distributions for boiling water reactor (BWR) fuel lattices. The procedure was coded in a computing system in which the optimization code uses the tabu search method to select potential solutions and the HELIOS code to evaluate them. The goal of the procedure is to search for an optimal fuel utilization, looking for a lattice with minimum average enrichment, with minimum deviation of reactivity targets and with a local power peaking factor (PPF) lower than a limit value. Time-dependent-depletion (TDD) effects were considered in the optimization process. The additive utility function method was used to convert the multiobjective optimization problem into a single objective problem. A strategy to reduce the computing time employed by the optimization was developed and is explained in this paper. An example is presented for a 10x10 fuel lattice with 10 different fuel compositions. The main contribution of this study is the development of a practical TDD optimization procedure for BWR fuel lattice design, using TS with a multiobjective function, and a strategy to economize computing time

A tabu-search for minimising the carry-over effects value of a round ...

African Journals Online (AJOL)

the tournament occurs when a team plays two consecutive home games or two ...... The initial solution for the tabu-search algorithm was generated randomly by ... at random on each level of the tree. ..... f e g j 9 7 6 1 5 c 0 a i 2 l 3 k d 4 h b 8.

A Framing Link Based Tabu Search Algorithm for Large-Scale Multidepot Vehicle Routing Problems

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Xuhao Zhang

2014-01-01

Full Text Available A framing link (FL based tabu search algorithm is proposed in this paper for a large-scale multidepot vehicle routing problem (LSMDVRP. Framing links are generated during continuous great optimization of current solutions and then taken as skeletons so as to improve optimal seeking ability, speed up the process of optimization, and obtain better results. Based on the comparison between pre- and postmutation routes in the current solution, different parts are extracted. In the current optimization period, links involved in the optimal solution are regarded as candidates to the FL base. Multiple optimization periods exist in the whole algorithm, and there are several potential FLs in each period. If the update condition is satisfied, the FL base is updated, new FLs are added into the current route, and the next period starts. Through adjusting the borderline of multidepot sharing area with dynamic parameters, the authors define candidate selection principles for three kinds of customer connections, respectively. Link split and the roulette approach are employed to choose FLs. 18 LSMDVRP instances in three groups are studied and new optimal solution values for nine of them are obtained, with higher computation speed and reliability.

Automated Energy Calibration and Fitting of LaCl3(Ce y-Spectra Using Peak Likelihood and Tabu Search

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Timothy P. McClanahan

2008-10-01

Full Text Available An automated method for ?-emission spectrum calibration and deconvolution is presented for spaceflight applications for a Cerium doped Lanthanum Chloride, (LaCl3(Ce ?-ray detector system. This detector will be coupled with a pulsed neutron generator (PNG to induce and enhance nuclide signal quality and rates, yielding large volumes of spectral information. Automated analytical methods are required to deconvolve and quantify nuclide signals from spectra; this will both reduce human interactions in spectrum analysis and facilitate feedback to automated robotic and operations planning. Initial system tests indicate significant energy calibration drifts (>6%, that which must be mitigated for spectrum analysis. A linear energy calibration model is presently considered, with gain and zero factors. Deconvolution methods incorporate a tabu search heuristic to formulate and optimize searches using memory structures. Iterative use of a peak likelihood methodology identifies global calibration minima and peak areas. The method is compared to manual methods of calibration and indicates superior performance using tabu methods. Performance of the Tabu enhanced calibration method is superior to similar unoptimized local search. The techniques are also applicable to other emission spectroscopy, eg. X-ray and neutron.

A hybridised variable neighbourhood tabu search heuristic to increase security in a utility network

International Nuclear Information System (INIS)

Janssens, Jochen; Talarico, Luca; Sörensen, Kenneth

2016-01-01

We propose a decision model aimed at increasing security in a utility network (e.g., electricity, gas, water or communication network). The network is modelled as a graph, the edges of which are unreliable. We assume that all edges (e.g., pipes, cables) have a certain, not necessarily equal, probability of failure, which can be reduced by selecting edge-specific security strategies. We develop a mathematical programming model and a metaheuristic approach that uses a greedy random adaptive search procedure to find an initial solution and uses tabu search hybridised with iterated local search and a variable neighbourhood descend heuristic to improve this solution. The main goal is to reduce the risk of service failure between an origin and a destination node by selecting the right combination of security measures for each network edge given a limited security budget. - Highlights: • A decision model aimed at increasing security in a utility network is proposed. • The goal is to reduce the risk of service failure given a limited security budget. • An exact approach and a variable neighbourhood tabu search heuristic are developed. • A generator for realistic networks is built and used to test the solution methods. • The hybridised heuristic reduces the total risk on average with 32%.

Models and Tabu Search Metaheuristics for Service Network Design with Asset-Balance Requirements

DEFF Research Database (Denmark)

Pedersen, Michael Berliner; Crainic, T.G.; Madsen, Oli B.G.

2009-01-01

This paper focuses on a generic model for service network design, which includes asset positioning and utilization through constraints on asset availability at terminals. We denote these relations as "design-balance constraints" and focus on the design-balanced capacitated multicommodity network...... design model, a generalization of the capacitated multicommodity network design model generally used in service network design applications. Both arc-and cycle-based formulations for the new model are presented. The paper also proposes a tabu search metaheuristic framework for the arc-based formulation....... Results on a wide range of network design problem instances from the literature indicate the proposed method behaves very well in terms of computational efficiency and solution quality....

Obtention control bars patterns for a BWR using Tabo search; Obtencion de patrones de barras de control para un BWR usando busqueda Tabu

Energy Technology Data Exchange (ETDEWEB)

Castillo, A.; Ortiz, J.J.; Alonso, G. [Instituto Nacional de Investigaciones Nucleares, Km. 36.5 Carretera Mexico-Toluca, Ocoyoacac, Estado de Mexico 52045 (Mexico); Morales, L.B. [UNAM, IIMAS, Ciudad Universitaria, D. F. 04510 (Mexico); Valle, E. del [IPN, ESFM, Unidad Profesional ' Adolfo Lopez Mateos' , Col. Lindavista 07738, D. F. (Mexico)]. e-mail: jacm@nuclear.inin.mx

2004-07-01

The obtained results when implementing the technique of tabu search, for to optimize patterns of control bars in a BWR type reactor, using the CM-PRESTO code are presented. The patterns of control bars were obtained for the designs of fuel reloads obtained in a previous work, using the same technique. The obtained results correspond to a cycle of 18 months using 112 fresh fuels enriched at the 3.53 of U-235. The used technique of tabu search, prohibits recently visited movements, in the position that correspond to the axial positions of the control bars, additionally the tiempo{sub t}abu matrix is used for to manage a size of variable tabu list and the objective function is punished with the frequency of the forbidden movements. The obtained patterns of control bars improve the longitude of the cycle with regard to the reference values and they complete the restrictions of safety. (Author)

Tabu Search-based Synthesis of Digital Microfluidic Biochips with Dynamically Reconfigurable Non-rectangular Devices

DEFF Research Database (Denmark)

Maftei, Elena; Pop, Paul; Madsen, Jan

2010-01-01

they are highly reconfigurable and scalable. A digital biochip is composed of a two-dimensional array of cells, together with reservoirs for storing the samples and reagents. Several adjacent cells are dynamically grouped to form a virtual device, on which operations are performed. So far, researchers have...... assumed that throughout its execution, an operation is performed on a rectangular virtual device, whose position remains fixed. However, during the execution of an operation, the virtual device can be reconfigured to occupy a different group of cells on the array, forming any shape, not necessarily...... rectangular. In this paper, we present a Tabu Search metaheuristic for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determines the allocation, resource binding, scheduling and placement of the operations in the application...

A DSS based on GIS and Tabu search for solving the CVRP: The Tunisian case

Directory of Open Access Journals (Sweden)

Sami Faiz

2014-06-01

Full Text Available The Capacitated Vehicle Routing Problem (CVRP is a well known optimization problem applied in numerous applications. It consists of delivering items to some geographically dispersed customers using a set of vehicles operating from a single depot. As the CVRP is known to be NP-hard, approximate methods perform well when generating promising sub-optimal solutions in a reasonable computation time. In this paper, we develop a Decision Support System (DSS for solving the CVRP that integrates a Geographical Information System (GIS enriched by a Tabu search (TS module. In order to demonstrate the performance of the proposed DSS in terms of CPU runtime and minimized traveled distance, we apply it on a large-sized real case. The results are then highlighted in a cartographic format using Google Maps.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

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Lei Shi

2018-01-01

Full Text Available In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA and tabu search (TS is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

Science.gov (United States)

Shi, Lei; Wan, Youchuan; Gao, Xianjun

2018-01-01

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy. PMID:29581721

A HYBRID HOPFIELD NEURAL NETWORK AND TABU SEARCH ALGORITHM TO SOLVE ROUTING PROBLEM IN COMMUNICATION NETWORK

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MANAR Y. KASHMOLA

2012-06-01

Full Text Available The development of hybrid algorithms for solving complex optimization problems focuses on enhancing the strengths and compensating for the weakness of two or more complementary approaches. The goal is to intelligently combine the key elements of these approaches to find superior solutions to solve optimization problems. Optimal routing in communication network is considering a complex optimization problem. In this paper we propose a hybrid Hopfield Neural Network (HNN and Tabu Search (TS algorithm, this algorithm called hybrid HNN-TS algorithm. The paradigm of this hybridization is embedded. We embed the short-term memory and tabu restriction features from TS algorithm in the HNN model. The short-term memory and tabu restriction control the neuron selection process in the HNN model in order to get around the local minima problem and find an optimal solution using the HNN model to solve complex optimization problem. The proposed algorithm is intended to find the optimal path for packet transmission in the network which is fills in the field of routing problem. The optimal path that will be selected is depending on 4-tuples (delay, cost, reliability and capacity. Test results show that the propose algorithm can find path with optimal cost and a reasonable number of iterations. It also shows that the complexity of the network model won’t be a problem since the neuron selection is done heuristically.

An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

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Soumya Banerjee

2011-03-01

Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

TABU PEREMPUAN DALAM BUDAYA MASYARAKAT BANTEN

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Ayatullah Humaeni

2016-01-01

Full Text Available Artikel ini mengkaji fenomena tabu (tabu perempuan dan maknanya bagi perempuan Banten. Bagaimana perempuan Banten memahami dan memaknai tabu-tabu yang hadir di sekitar mereka dan masih ditradisikan dari generasi ke generasi menjadi salah satu fokus utama artikel ini. Di samping itu, artikel ini juga mencoba mengidentifikasi dan menganalisis berbagai jenis tabu yang berhubungan dengan perempuan Banten. Artikel ini merupakan hasil penelitian lapangan dengan menggunakan metode study kasus yang bersifat deskriptif kualitatif dengan pendekatan antropologis. Metode yang digunakan untuk mengumpulkan data adalah kajian pustaka, observasi, dan wawancara mendalam. Keberadaan tabu perempuan dalam budaya Banten, sedikit banyak, mempunyai pengaruh bagi kehidupan sosial keagamaan masyarakat Banten. Jika menganalisis isi dan makna tabu berdasarkan kontkes sosial kulturalnya, beragam tabu yang ada pada masyarakat Banten, khususnya yang berkaitan dengan tabu perempuan Banten, memiliki fungsi dan makna sebagai bentuk penjagaan moral dan perilaku, pemeliharaan identitas diri dan identitas sosial, memperkuat hubungan emosional, bentuk perlindungan, sampai simbol kasih sayang dan cinta.

A Tabu Search WSN Deployment Method for Monitoring Geographically Irregular Distributed Events

Directory of Open Access Journals (Sweden)

2009-03-01

Full Text Available In this paper, we address the Wireless Sensor Network (WSN deployment issue. We assume that the observed area is characterized by the geographical irregularity of the sensed events. Formally, we consider that each point in the deployment area is associated a differentiated detection probability threshold, which must be satisfied by our deployment method. Our resulting WSN deployment problem is formulated as a Multi-Objectives Optimization problem, which seeks to reduce the gap between the generated events detection probabilities and the required thresholds while minimizing the number of deployed sensors. To overcome the computational complexity of an exact resolution, we propose an original pseudo-random approach based on the Tabu Search heuristic. Simulations show that our proposal achieves better performances than several other approaches proposed in the literature. In the last part of this paper, we generalize the deployment problem by including the wireless communication network connectivity constraint. Thus, we extend our proposal to ensure that the resulting WSN topology is connected even if a sensor communication range takes small values.

A Tabu Search WSN Deployment Method for Monitoring Geographically Irregular Distributed Events.

Science.gov (United States)

Aitsaadi, Nadjib; Achir, Nadjib; Boussetta, Khaled; Pujolle, Guy

2009-01-01

In this paper, we address the Wireless Sensor Network (WSN) deployment issue. We assume that the observed area is characterized by the geographical irregularity of the sensed events. Formally, we consider that each point in the deployment area is associated a differentiated detection probability threshold, which must be satisfied by our deployment method. Our resulting WSN deployment problem is formulated as a Multi-Objectives Optimization problem, which seeks to reduce the gap between the generated events detection probabilities and the required thresholds while minimizing the number of deployed sensors. To overcome the computational complexity of an exact resolution, we propose an original pseudo-random approach based on the Tabu Search heuristic. Simulations show that our proposal achieves better performances than several other approaches proposed in the literature. In the last part of this paper, we generalize the deployment problem by including the wireless communication network connectivity constraint. Thus, we extend our proposal to ensure that the resulting WSN topology is connected even if a sensor communication range takes small values.

African Journal of Science and Technology (AJST) TABU SEARCH ...

African Journals Online (AJOL)

The timetable is essentially created manually, using a set of tools that can ... This is a long process and a semester timetable takes an average of three ... by the manual systems afterwards. ... No lecturer can teach more than one lecture at the ..... Tabu variations .... The aim of the project was to develop a heuristic algorithm.

Application of Hybrid HS and Tabu Search Algorithm for Optimal Location of FACTS Devices to Reduce Power Losses in Power Systems

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Z. Masomi Zohrabad

2016-12-01

Full Text Available Power networks continue to grow following the annual growth of energy demand. As constructing new energy generation facilities bears a high cost, minimizing power grid losses becomes essential to permit low cost energy transmission in larger distances and additional areas. This study aims to model an optimization problem for an IEEE 30-bus power grid using a Tabu search algorithm based on an improved hybrid Harmony Search (HS method to reduce overall grid losses. The proposed algorithm is applied to find the best location for the installation of a Unified Power Flow Controller (UPFC. The results obtained from installation of the UPFC in the grid are presented by displaying outputs.

System network planning expansion using mathematical programming, genetic algorithms and tabu search

International Nuclear Information System (INIS)

Sadegheih, A.; Drake, P.R.

2008-01-01

In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used

Theoretical Investigation of Combined Use of PSO, Tabu Search and Lagrangian Relaxation methods to solve the Unit Commitment Problem

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Sahbi Marrouchi

2018-02-01

Full Text Available Solving the Unit Commitment problem (UCP optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination three optimization methods: Tabu search, Particle swarm optimization and Lagrangian relaxation methods in order to develop a proper unit commitment scheduling of the production units while reducing the production cost during a definite period. The proposed strategy has been implemented on a the IEEE 9 bus test system containing 3 production unit and the results were promising compared to strategies based on meta-heuristic and deterministic methods.

A tabu-search heuristic for solving the multi-depot vehicle scheduling problem

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Gilmar D'Agostini Oliveira Casalinho

2014-08-01

Full Text Available Currently the logistical problems are relying quite significantly on Operational Research in order to achieve greater efficiency in their operations. Among the problems related to the vehicles scheduling in a logistics system, the Multiple Depot Vehicle Scheduling Problem (MDVSP has been addressed in several studies. The MDVSP presupposes the existence of depots that affect the planning of sequences to which travel must be performed. Often, exact methods cannot solve large instances encountered in practice and in order to take them into account, several heuristic approaches are being developed. The aim of this study was thus to solve the MDVSP using a meta-heuristic based on tabu-search method. The main motivation for this work came from the indication that only recently the use of meta-heuristics is being applied to MDVSP context (Pepin et al. 2008 and, also, the limitations listed by Rohde (2008 in his study, which used the branch-and-bound in one of the steps of the heuristic presented to solve the problem, which has increased the time resolution. The research method for solving this problem was based on adaptations of traditional techniques of Operational Research, and provided resolutions presenting very competitive results for the MDVSP such as the cost of the objective function, number of vehicles used and computational time.

A Hybrid Tabu Search Heuristic for a Bilevel Competitive Facility Location Model

Science.gov (United States)

Küçükaydın, Hande; Aras, Necati; Altınel, I. Kuban

We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff's gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.

A Novel Framework for Medical Web Information Foraging Using Hybrid ACO and Tabu Search.

Science.gov (United States)

Drias, Yassine; Kechid, Samir; Pasi, Gabriella

2016-01-01

We present in this paper a novel approach based on multi-agent technology for Web information foraging. We proposed for this purpose an architecture in which we distinguish two important phases. The first one is a learning process for localizing the most relevant pages that might interest the user. This is performed on a fixed instance of the Web. The second takes into account the openness and dynamicity of the Web. It consists on an incremental learning starting from the result of the first phase and reshaping the outcomes taking into account the changes that undergoes the Web. The system was implemented using a colony of artificial ants hybridized with tabu search in order to achieve more effectiveness and efficiency. To validate our proposal, experiments were conducted on MedlinePlus, a real website dedicated for research in the domain of Health in contrast to other previous works where experiments were performed on web logs datasets. The main results are promising either for those related to strong Web regularities and for the response time, which is very short and hence complies the real time constraint.

Fuel Management in Candu Reactors Using Tabu Search

International Nuclear Information System (INIS)

Chambon, R.; Varin, E.

2008-01-01

Meta-heuristic methods are perfectly suited to solve fuel management optimization problem in LWR. Indeed, they are originally designed for combinatorial or integer parameter problems which can represent the reloading pattern of the assemblies. For the Candu reactors the problem is however completely different. Indeed, this type of reactor is refueled online. Thus, for their design at fuel reloading equilibrium, the parameter to optimize is the average exit burnup of each fuel channel (which is related to the frequency at which each channel has to be reloaded). It is then a continuous variable that we have to deal with. Originally, this problem was solved using gradient methods. However, their major drawback is the potential local optimum into which they can be trapped. This makes the meta-heuristic methods interesting. In this paper, we have successfully implemented the Tabu Search (TS) method in the reactor diffusion code DONJON. The case of an ACR-700 using 7 burnup zones has been tested. The results have been compared to those we obtained previously with gradient methods. Both methods give equivalent results. This validates them both. The TS has however a major drawback concerning the computation time. A problem with the enrichment as an additional parameter has been tested. In this case, the feasible domain is very narrow, and the optimization process has encountered limitations. Actually, the TS method may not be suitable to find the exact solution of the fuel management problem, but it may be used in a hybrid method such as a TS to find the global optimum region coupled with a gradient method to converge faster on the exact solution. (authors)

Kombinasi Firefly Algorithm-Tabu Search untuk Penyelesaian Traveling Salesman Problem

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Riyan Naufal Hay's

2017-07-01

Full Text Available Traveling Salesman Problem (TSP adalah masalah optimasi kombinatorial klasik dan memiliki peran dalam perencanaan, penjadwalan, dan pencarian pada bidang rekayasa dan pengetahuan (Dong, 2012. TSP juga merupakan objek yang baik untuk menguji kinerja metode optimasi, beberapa metode seperti Cooperative Genetic Ant System (CGAS (Dong, 2012, Parallelized Genetic Ant Colony System (PGAS Particle Swarm Optimization and Ant Colony Optimization Algorithms (PSO–ACO (Elloumi, 2014, dan Ant Colony Hyper-Heuristics (ACO HH (Aziz, 2015 telah dikembangkan untuk memecahkan TSP. Sehingga, pada penelitian ini diimplementasikan kombinasi metode baru untuk meningkatkan akurasi penyelesaian TSP. Firefly Algorithm (FA merupakan salah satu algoritma yang dapat digunakan untuk memecahkan masalah optimasi kombinatorial (Layeb, 2014. FA merupakan algoritma yang berpotensi kuat dalam memecahkan kasus optimasi dibanding algoritma yang ada termasuk Particle Swarm Optimization (Yang, 2010. Namun, FA memiliki kekurangan dalam memecahkan masalah optimasi dengan skala besar (Baykasoğlu dan Ozsoy, 2014. Tabu Search (TS merupakan metode optimasi yang terbukti efektif untuk memecahkan masalah optimasi dengan skala besar (Pedro, 2013. Pada penelitian ini, TS akan diterapkan pada FA (FATS untuk memecahkan kasus TSP. Hasil FATS akan dibandingkan terhadap penelitian sebelumnya yaitu ACOHH. Perbandingan hasil menunjukan peningkatan akurasi sebesar 0.89% pada dataset Oliver30, 0.14% dataset Eil51, 3.81% dataset Eil76 dan 1.27% dataset KroA100.

Tabu search for the redundancy allocation problem of homogenous series-parallel multi-state systems

International Nuclear Information System (INIS)

Ouzineb, Mohamed; Nourelfath, Mustapha; Gendreau, Michel

2008-01-01

This paper develops an efficient tabu search (TS) heuristic to solve the redundancy allocation problem for multi-state series-parallel systems. The system has a range of performance levels from perfect functioning to complete failure. Identical redundant elements are included in order to achieve a desirable level of availability. The elements of the system are characterized by their cost, performance and availability. These elements are chosen from a list of products available in the market. System availability is defined as the ability to satisfy consumer demand, which is represented as a piecewise cumulative load curve. A universal generating function technique is applied to evaluate system availability. The proposed TS heuristic determines the minimal cost system configuration under availability constraints. An originality of our approach is that it proceeds by dividing the search space into a set of disjoint subsets, and then by applying TS to each subset. The design problem, solved in this study, has been previously analyzed using genetic algorithms (GAs). Numerical results for the test problems from previous research are reported, and larger test problems are randomly generated. Comparisons show that the proposed TS out-performs GA solutions, in terms of both the solution quality and the execution time

Hybrid Multistarting GA-Tabu Search Method for the Placement of BtB Converters for Korean Metropolitan Ring Grid

Directory of Open Access Journals (Sweden)

Remund J. Labios

2016-01-01

Full Text Available This paper presents a method to determine the optimal locations for installing back-to-back (BtB converters in a power grid as a countermeasure to reduce fault current levels. The installation of BtB converters can be regarded as network reconfiguration. For the purpose, a hybrid multistarting GA-tabu search method was used to determine the best locations from a preselected list of candidate locations. The constraints used in determining the best locations include circuit breaker fault current limits, proximity of proposed locations, and capability of the solution to reach power flow convergence. A simple power injection model after applying line-opening on selected branches was used as a means for power flows with BtB converters. Kron reduction was also applied as a method for network reduction for fast evaluation of fault currents with a given topology. Simulations of the search method were performed on the Korean power system, particularly the Seoul metropolitan area.

Fuel loading and control rod patterns optimization in a BWR using tabu search

International Nuclear Information System (INIS)

Castillo, Alejandro; Ortiz, Juan Jose; Montes, Jose Luis; Perusquia, Raul

2007-01-01

This paper presents the QuinalliBT system, a new approach to solve fuel loading and control rod patterns optimization problem in a coupled way. This system involves three different optimization stages; in the first one, a seed fuel loading using the Haling principle is designed. In the second stage, the corresponding control rod pattern for the previous fuel loading is obtained. Finally, in the last stage, a new fuel loading is created, starting from the previous fuel loading and using the corresponding set of optimized control rod patterns. For each stage, a different objective function is considered. In order to obtain the decision parameters used in those functions, the CM-PRESTO 3D steady-state reactor core simulator was used. Second and third stages are repeated until an appropriate fuel loading and its control rod pattern are obtained, or a stop criterion is achieved. In all stages, the tabu search optimization technique was used. The QuinalliBT system was tested and applied to a real BWR operation cycle. It was found that the value for k eff obtained by QuinalliBT was 0.0024 Δk/k greater than that of the reference cycle

Sustainable Scheduling of Cloth Production Processes by Multi-Objective Genetic Algorithm with Tabu-Enhanced Local Search

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Rui Zhang

2017-09-01

Full Text Available The dyeing of textile materials is the most critical process in cloth production because of the strict technological requirements. In addition to the technical aspect, there have been increasing concerns over how to minimize the negative environmental impact of the dyeing industry. The emissions of pollutants are mainly caused by frequent cleaning operations which are necessary for initializing the dyeing equipment, as well as idled production capacity which leads to discharge of unconsumed chemicals. Motivated by these facts, we propose a methodology to reduce the pollutant emissions by means of systematic production scheduling. Firstly, we build a three-objective scheduling model that incorporates both the traditional tardiness objective and the environmentally-related objectives. A mixed-integer programming formulation is also provided to accurately define the problem. Then, we present a novel solution method for the sustainable scheduling problem, namely, a multi-objective genetic algorithm with tabu-enhanced iterated greedy local search strategy (MOGA-TIG. Finally, we conduct extensive computational experiments to investigate the actual performance of the MOGA-TIG. Based on a fair comparison with two state-of-the-art multi-objective optimizers, it is concluded that the MOGA-TIG is able to achieve satisfactory solution quality within tight computational time budget for the studied scheduling problem.

Inverse modeling approach for evaluation of kinetic parameters of a biofilm reactor using tabu search.

Science.gov (United States)

Kumar, B Shiva; Venkateswarlu, Ch

2014-08-01

The complex nature of biological reactions in biofilm reactors often poses difficulties in analyzing such reactors experimentally. Mathematical models could be very useful for their design and analysis. However, application of biofilm reactor models to practical problems proves somewhat ineffective due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, we propose an inverse modeling approach based on tabu search (TS) to estimate the parameters of kinetic and film thickness models. TS is used to estimate these parameters as a consequence of the validation of the mathematical models of the process with the aid of measured data obtained from an experimental fixed-bed anaerobic biofilm reactor involving the treatment of pharmaceutical industry wastewater. The results evaluated for different modeling configurations of varying degrees of complexity illustrate the effectiveness of TS for accurate estimation of kinetic and film thickness model parameters of the biofilm process. The results show that the two-dimensional mathematical model with Edward kinetics (with its optimum parameters as mu(max)rho(s)/Y = 24.57, Ks = 1.352 and Ki = 102.36) and three-parameter film thickness expression (with its estimated parameters as a = 0.289 x 10(-5), b = 1.55 x 10(-4) and c = 15.2 x 10(-6)) better describes the biofilm reactor treating the industry wastewater.

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

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Anongrit Kangrang

2018-01-01

Full Text Available Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA and the conditional tabu search algorithm (CTSA technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. The Ubolrat Reservoir located in the northeast region of Thailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. The future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. The situations of water shortage and excess water were shown in terms of frequency magnitude and duration. The results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. The optimal future rule curves were more suitable for future situations than the other rule curves.

A Hybrid Tabu Search Algorithm for a Real-World Open Vehicle Routing Problem Involving Fuel Consumption Constraints

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Yunyun Niu

2018-01-01

Full Text Available Outsourcing logistics operation to third-party logistics has attracted more attention in the past several years. However, very few papers analyzed fuel consumption model in the context of outsourcing logistics. This problem involves more complexity than traditional open vehicle routing problem (OVRP, because the calculation of fuel emissions depends on many factors, such as the speed of vehicles, the road angle, the total load, the engine friction, and the engine displacement. Our paper proposed a green open vehicle routing problem (GOVRP model with fuel consumption constraints for outsourcing logistics operations. Moreover, a hybrid tabu search algorithm was presented to deal with this problem. Experiments were conducted on instances based on realistic road data of Beijing, China, considering that outsourcing logistics plays an increasingly important role in China’s freight transportation. Open routes were compared with closed routes through statistical analysis of the cost components. Compared with closed routes, open routes reduce the total cost by 18.5% with the fuel emissions cost down by nearly 29.1% and the diver cost down by 13.8%. The effect of different vehicle types was also studied. Over all the 60- and 120-node instances, the mean total cost by using the light-duty vehicles is the lowest.

Solving Large Clustering Problems with Meta-Heuristic Search

DEFF Research Database (Denmark)

Turkensteen, Marcel; Andersen, Kim Allan; Bang-Jensen, Jørgen

In Clustering Problems, groups of similar subjects are to be retrieved from data sets. In this paper, Clustering Problems with the frequently used Minimum Sum-of-Squares Criterion are solved using meta-heuristic search. Tabu search has proved to be a successful methodology for solving optimization...... problems, but applications to large clustering problems are rare. The simulated annealing heuristic has mainly been applied to relatively small instances. In this paper, we implement tabu search and simulated annealing approaches and compare them to the commonly used k-means approach. We find that the meta-heuristic...

Minimization of municipal solid waste transportation route in West Jakarta using Tabu Search method

Science.gov (United States)

Chaerul, M.; Mulananda, A. M.

2018-04-01

Indonesia still adopts the concept of collect-haul-dispose for municipal solid waste handling and it leads to the queue of the waste trucks at final disposal site (TPA). The study aims to minimize the total distance of waste transportation system by applying a Transshipment model. In this case, analogous of transshipment point is a compaction facility (SPA). Small capacity of trucks collects the waste from waste temporary collection points (TPS) to the compaction facility which located near the waste generator. After compacted, the waste is transported using big capacity of trucks to the final disposal site which is located far away from city. Problem related with the waste transportation can be solved using Vehicle Routing Problem (VRP). In this study, the shortest distance of route from truck pool to TPS, TPS to SPA, and SPA to TPA was determined by using meta-heuristic methods, namely Tabu Search 2 Phases. TPS studied is the container type with total 43 units throughout the West Jakarta City with 38 units of Armroll truck with capacity of 10 m3 each. The result determines the assignment of each truck from the pool to the selected TPS, SPA and TPA with the total minimum distance of 2,675.3 KM. The minimum distance causing the total cost for waste transportation to be spent by the government also becomes minimal.

Complete local search with memory

NARCIS (Netherlands)

Ghosh, D.; Sierksma, G.

2000-01-01

Neighborhood search heuristics like local search and its variants are some of the most popular approaches to solve discrete optimization problems of moderate to large size. Apart from tabu search, most of these heuristics are memoryless. In this paper we introduce a new neighborhood search heuristic

Solving the competitive facility location problem considering the reactions of competitor with a hybrid algorithm including Tabu Search and exact method

Science.gov (United States)

Bagherinejad, Jafar; Niknam, Azar

2018-03-01

In this paper, a leader-follower competitive facility location problem considering the reactions of the competitors is studied. A model for locating new facilities and determining levels of quality for the facilities of the leader firm is proposed. Moreover, changes in the location and quality of existing facilities in a competitive market where a competitor offers the same goods or services are taken into account. The competitor could react by opening new facilities, closing existing ones, and adjusting the quality levels of its existing facilities. The market share, captured by each facility, depends on its distance to customer and its quality that is calculated based on the probabilistic Huff's model. Each firm aims to maximize its profit subject to constraints on quality levels and budget of setting up new facilities. This problem is formulated as a bi-level mixed integer non-linear model. The model is solved using a combination of Tabu Search with an exact method. The performance of the proposed algorithm is compared with an upper bound that is achieved by applying Karush-Kuhn-Tucker conditions. Computational results show that our algorithm finds near the upper bound solutions in a reasonable time.

Solução de problemas de planejamento florestal com restrições de inteireza utilizando busca tabu Solving forest management problems with integer constraints using tabu search

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Flávio Lopes Rodrigues

2003-10-01

Full Text Available Este trabalho teve como objetivos desenvolver e testar um algoritmo com base na metaheurística busca tabu (BT, para a solução de problemas de gerenciamento florestal com restrições de inteireza. Os problemas avaliados tinham entre 93 e 423 variáveis de decisão, sujeitos às restrições de singularidade, produção mínima e produção máxima periódicas. Todos os problemas tiveram como objetivo a maximização do valor presente líquido. O algoritmo para implementação da BT foi codificado em ambiente delphi 5.0 e os testes foram efetuados em um microcomputador AMD K6II 500 MHZ, com memória RAM de 64 MB e disco rígido de 15GB. O desempenho da BT foi avaliado de acordo com as medidas de eficácia e eficiência. Os diferentes valores ou categorias dos parâmetros da BT foram testados e comparados quanto aos seus efeitos na eficácia do algoritmo. A seleção da melhor configuração de parâmetros foi feita com o teste L&O, a 1% de probabilidade, e as análises através de estatísticas descritivas. A melhor configuração de parâmetros propiciou à BT eficácia média de 95,97%, valor mínimo igual a 90,39% e valor máximo igual a 98,84%, com um coeficiente de variação de 2,48% do ótimo matemático. Para o problema de maior porte, a eficiência da BT foi duas vezes superior à eficiência do algoritmo exato branch and bound, apresentando-se como uma abordagem muito atrativa para solução de importantes problemas de gerenciamento florestal.This work aimed to develop and test an algorithm based on Tabu Search (TS metaheuristics; to solve problems of forest management with integer constraints. TS was tested in five problems containing between 12 and 423 decision variables subjected to singularity constraints, minimum and maximum periodic productions. All the problems aimed at maximizing the net present value. TS was codified into delphi 5.0 language and the tests were performed in a microcomputer AMD K6II 500 MHZ, RAM memory 64 MB

A tabu-search for minimising the carry-over effects value of a round-robin tournament

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MP Kidd

2010-12-01

Full Text Available A player b in a round-robin sports tournament receives a carry-over effect from another player a if some third player opposes a in round i and b in round i+1. Let γ(ab denote the number of times player b receives a carry-over effect from player a during a tournament. Then the carry-over effects value of the entire tournament T on n players is given by Γ(T=ΣΣγ(ij^2. Furthermore, let Γ(n denote the minimum carry-over effects value over all round-robin tournaments on n players. A strict lower bound on Γ(n is n(n-1 (in which case there exists a round-robin tournament of order n such that each player receives a carry-over effect from each other player exactly once, and it is known that this bound is attained for n=2^r or n=20,22. It is also known that round-robin tournaments can be constructed from so-called starters; round-robin tournaments constructed in this way are called cyclic. It has previously been shown that cyclic round-robin tournaments have the potential of admitting small values for Γ(T, and in this paper a tabu-search is used to find starters which produce cyclic tournaments with small carry-over effects values. The best solutions in the literature are matched for n<=22, and new upper bounds are established on Γ(n for 24<=n<=40.

Complex Sequencing Problems and Local Search Heuristics

NARCIS (Netherlands)

Brucker, P.; Hurink, Johann L.; Osman, I.H.; Kelly, J.P.

1996-01-01

Many problems can be formulated as complex sequencing problems. We will present problems in flexible manufacturing that have such a formulation and apply local search methods like iterative improvement, simulated annealing and tabu search to solve these problems. Computational results are reported.

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.

Obtention control bars patterns for a BWR using Tabo search

International Nuclear Information System (INIS)

Castillo, A.; Ortiz, J.J.; Alonso, G.; Morales, L.B.; Valle, E. del

2004-01-01

The obtained results when implementing the technique of tabu search, for to optimize patterns of control bars in a BWR type reactor, using the CM-PRESTO code are presented. The patterns of control bars were obtained for the designs of fuel reloads obtained in a previous work, using the same technique. The obtained results correspond to a cycle of 18 months using 112 fresh fuels enriched at the 3.53 of U-235. The used technique of tabu search, prohibits recently visited movements, in the position that correspond to the axial positions of the control bars, additionally the tiempo t abu matrix is used for to manage a size of variable tabu list and the objective function is punished with the frequency of the forbidden movements. The obtained patterns of control bars improve the longitude of the cycle with regard to the reference values and they complete the restrictions of safety. (Author)

Local search heuristics for the probabilistic dial-a-ride problem

DEFF Research Database (Denmark)

Ho, Sin C.; Haugland, Dag

2011-01-01

evaluation procedure in a pure local search heuristic and in a tabu search heuristic. The quality of the solutions obtained by the two heuristics have been compared experimentally. Computational results confirm that our neighborhood evaluation technique is much faster than the straightforward one...

Stochastic search techniques for post-fault restoration of electrical ...

Indian Academy of Sciences (India)

Three stochastic search techniques have been used to find the optimal sequence of operations required to restore supply in an electrical distribution system on the occurrence of a fault. The three techniques are the genetic algorithm,simulated annealing and the tabu search. The performance of these techniques has been ...

Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

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Arpita Nagpal

2017-01-01

Full Text Available Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm based on the tabu search as local search procedures to a Greedy Randomized Adaptive Search Procedure (GRASP for high dimensional microarray data sets. The proposed Tabu based Greedy Randomized Adaptive Search Procedure algorithm is named as TGRASP. In TGRASP, a new parameter has been introduced named as Tabu Tenure and the existing parameters, NumIter and size have been modified. We observed that different parameter settings affect the quality of the optimum. The second proposed algorithm known as FFGRASP (Firefly Greedy Randomized Adaptive Search Procedure uses a firefly optimization algorithm in the local search optimzation phase of the greedy randomized adaptive search procedure (GRASP. Firefly algorithm is one of the powerful algorithms for optimization of multimodal applications. Experimental results show that the proposed TGRASP and FFGRASP algorithms are much better than existing algorithm with respect to three performance parameters viz. accuracy, run time, number of a selected subset of features. We have also compared both the approaches with a unified metric (Extended Adjusted Ratio of Ratios which has shown that TGRASP approach outperforms existing approach for six out of nine cancer microarray datasets and FFGRASP performs better on seven out of nine datasets.

Solving a chemical batch scheduling problem by local search

NARCIS (Netherlands)

Brucker, P.; Hurink, Johann L.

1999-01-01

A chemical batch scheduling problem is modelled in two different ways as a discrete optimization problem. Both models are used to solve the batch scheduling problem in a two-phase tabu search procedure. The method is tested on real-world data.

A Multi Time Scale Wind Power Forecasting Model of a Chaotic Echo State Network Based on a Hybrid Algorithm of Particle Swarm Optimization and Tabu Search

Directory of Open Access Journals (Sweden)

Xiaomin Xu

2015-11-01

Full Text Available The uncertainty and regularity of wind power generation are caused by wind resources’ intermittent and randomness. Such volatility brings severe challenges to the wind power grid. The requirements for ultrashort-term and short-term wind power forecasting with high prediction accuracy of the model used, have great significance for reducing the phenomenon of abandoned wind power , optimizing the conventional power generation plan, adjusting the maintenance schedule and developing real-time monitoring systems. Therefore, accurate forecasting of wind power generation is important in electric load forecasting. The echo state network (ESN is a new recurrent neural network composed of input, hidden layer and output layers. It can approximate well the nonlinear system and achieves great results in nonlinear chaotic time series forecasting. Besides, the ESN is simpler and less computationally demanding than the traditional neural network training, which provides more accurate training results. Aiming at addressing the disadvantages of standard ESN, this paper has made some improvements. Combined with the complementary advantages of particle swarm optimization and tabu search, the generalization of ESN is improved. To verify the validity and applicability of this method, case studies of multitime scale forecasting of wind power output are carried out to reconstruct the chaotic time series of the actual wind power generation data in a certain region to predict wind power generation. Meanwhile, the influence of seasonal factors on wind power is taken into consideration. Compared with the classical ESN and the conventional Back Propagation (BP neural network, the results verify the superiority of the proposed method.

Evaluating impact of market changes on increasing cell-load variation in dynamic cellular manufacturing systems using a hybrid Tabu search and simulated annealing algorithms

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Aidin Delgoshaei

2016-06-01

Full Text Available In this paper, a new method is proposed for scheduling dynamic cellular manufacturing systems (D-CMS in the presence of uncertain product demands. The aim of this method is to control the process of trading off between in-house manufacturing and outsourcing while product demands are uncertain and can be varied from period to period. To solve the proposed problem, a hybrid Tabu Search and Simulated Annealing are developed to overcome hardness of the proposed model and then results are compared with a Branch and Bound and Simulated Annealing algorithms. A Taguchi method (L_27 orthogonal optimization is used to estimate parameters of the proposed method in order to solve experiments derived from literature. An in-depth analysis is conducted on the results in consideration of various factors. For evaluating the system imbalance in dynamic market demands, a new measuring index is developed. Our findings indicate that the uncertain condition of market demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. The results showed that the proposed hybrid method can provide solutions with better quality.

Transmission network expansion planning based on hybridization model of neural networks and harmony search algorithm

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Mohammad Taghi Ameli

2012-01-01

Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.

Search and optimization by metaheuristics techniques and algorithms inspired by nature

CERN Document Server

Du, Ke-Lin

2016-01-01

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computin...

A capacitated vehicle routing problem with order available time in e-commerce industry

Science.gov (United States)

Liu, Ling; Li, Kunpeng; Liu, Zhixue

2017-03-01

In this article, a variant of the well-known capacitated vehicle routing problem (CVRP) called the capacitated vehicle routing problem with order available time (CVRPOAT) is considered, which is observed in the operations of the current e-commerce industry. In this problem, the orders are not available for delivery at the beginning of the planning period. CVRPOAT takes all the assumptions of CVRP, except the order available time, which is determined by the precedent order picking and packing stage in the warehouse of the online grocer. The objective is to minimize the sum of vehicle completion times. An efficient tabu search algorithm is presented to tackle the problem. Moreover, a Lagrangian relaxation algorithm is developed to obtain the lower bounds of reasonably sized problems. Based on the test instances derived from benchmark data, the proposed tabu search algorithm is compared with a published related genetic algorithm, as well as the derived lower bounds. Also, the tabu search algorithm is compared with the current operation strategy of the online grocer. Computational results indicate that the gap between the lower bounds and the results of the tabu search algorithm is small and the tabu search algorithm is superior to the genetic algorithm. Moreover, the CVRPOAT formulation together with the tabu search algorithm performs much better than the current operation strategy of the online grocer.

A Group Theoretic Approach to Metaheuristic Local Search for Partitioning Problems

Science.gov (United States)

2005-05-01

Tabu Search. Mathematical and Computer Modeling 39: 599-616. 107 Daskin , M.S., E. Stern. 1981. A Hierarchical Objective Set Covering Model for EMS... A Group Theoretic Approach to Metaheuristic Local Search for Partitioning Problems by Gary W. Kinney Jr., B.G.S., M.S. Dissertation Presented to the...DISTRIBUTION STATEMENT A Approved for Public Release Distribution Unlimited The University of Texas at Austin May, 2005 20050504 002 REPORT

Integrating Conflict Driven Clause Learning to Local Search

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Gilles Audenard

2009-10-01

Full Text Available This article introduces SatHyS (SAT HYbrid Solver, a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL scheme. Each time the local search part reaches a local minimum, the CDCL is launched. For SAT problems it behaves like a tabu list, whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable sub-formula (MUS. Experimental results show good performances on many classes of SAT instances from the last SAT competitions.

A granular tabu search algorithm for a real case study of a vehicle routing problem with a heterogeneous fleet and time windows

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Jose Bernal

2017-10-01

Full Text Available Purpose: We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase, a granular tabu search is applied during the improvement phase (second phase. Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.

Algorithm of axial fuel optimization based in progressive steps of turned search

International Nuclear Information System (INIS)

Martin del Campo, C.; Francois, J.L.

2003-01-01

The development of an algorithm for the axial optimization of fuel of boiling water reactors (BWR) is presented. The algorithm is based in a serial optimizations process in the one that the best solution in each stage is the starting point of the following stage. The objective function of each stage adapts to orient the search toward better values of one or two parameters leaving the rest like restrictions. Conform to it advances in those optimization stages, it is increased the fineness of the evaluation of the investigated designs. The algorithm is based on three stages, in the first one are used Genetic algorithms and in the two following Tabu Search. The objective function of the first stage it looks for to minimize the average enrichment of the one it assembles and to fulfill with the generation of specified energy for the operation cycle besides not violating none of the limits of the design base. In the following stages the objective function looks for to minimize the power factor peak (PPF) and to maximize the margin of shutdown (SDM), having as restrictions the one average enrichment obtained for the best design in the first stage and those other restrictions. The third stage, very similar to the previous one, it begins with the design of the previous stage but it carries out a search of the margin of shutdown to different exhibition steps with calculations in three dimensions (3D). An application to the case of the design of the fresh assemble for the fourth fuel reload of the Unit 1 reactor of the Laguna Verde power plant (U1-CLV) is presented. The obtained results show an advance in the handling of optimization methods and in the construction of the objective functions that should be used for the different design stages of the fuel assemblies. (Author)

A Comparison of Local Search Methods for the Multicriteria Police Districting Problem on Graph

Directory of Open Access Journals (Sweden)

F. Liberatore

2016-01-01

Full Text Available In the current economic climate, law enforcement agencies are facing resource shortages. The effective and efficient use of scarce resources is therefore of the utmost importance to provide a high standard public safety service. Optimization models specifically tailored to the necessity of police agencies can help to ameliorate their use. The Multicriteria Police Districting Problem (MC-PDP on a graph concerns the definition of sound patrolling sectors in a police district. The objective of this problem is to partition a graph into convex and continuous subsets, while ensuring efficiency and workload balance among the subsets. The model was originally formulated in collaboration with the Spanish National Police Corps. We propose for its solution three local search algorithms: a Simple Hill Climbing, a Steepest Descent Hill Climbing, and a Tabu Search. To improve their diversification capabilities, all the algorithms implement a multistart procedure, initialized by randomized greedy solutions. The algorithms are empirically tested on a case study on the Central District of Madrid. Our experiments show that the solutions identified by the novel Tabu Search outperform the other algorithms. Finally, research guidelines for future developments on the MC-PDP are given.

An improved version of Inverse Distance Weighting metamodel assisted Harmony Search algorithm for truss design optimization

Directory of Open Access Journals (Sweden)

Y. Gholipour

Full Text Available This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessary means to reduce the computational cost and convergence rate of the optimization through a surrogate. This algorithm is a combination of a high quality approximation technique called Inverse Distance Weighting and a meta-heuristic algorithm called Harmony Search. The outcome is then polished by a semi-tabu search algorithm. This algorithm adopts a filtering system and determines solution vectors where exact simulation should be applied. The performance of the algorithm is evaluated by standard truss design problems and there has been a significant decrease in the computational effort and improvement of convergence rate.

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

Science.gov (United States)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this

Multiobjective Optimization of Water Distribution Networks Using Fuzzy Theory and Harmony Search

Directory of Open Access Journals (Sweden)

Zong Woo Geem

2015-07-01

Full Text Available Thus far, various phenomenon-mimicking algorithms, such as genetic algorithm, simulated annealing, tabu search, shuffled frog-leaping, ant colony optimization, harmony search, cross entropy, scatter search, and honey-bee mating, have been proposed to optimally design the water distribution networks with respect to design cost. However, flow velocity constraint, which is critical for structural robustness against water hammer or flow circulation against substance sedimentation, was seldom considered in the optimization formulation because of computational complexity. Thus, this study proposes a novel fuzzy-based velocity reliability index, which is to be maximized while the design cost is simultaneously minimized. The velocity reliability index is included in the existing cost optimization formulation and this extended multiobjective formulation is applied to two bench-mark problems. Results show that the model successfully found a Pareto set of multiobjective design solutions in terms of cost minimization and reliability maximization.

Symbiotic Tabu Search

OpenAIRE

Halavati, Ramin; Shouraki, Saeed Bagheri

2008-01-01

Authors wish to give their sincerest thanks to Professor Caro Lucas for his valuable comments during this task, and Ms. Mojdeh Jalali Heravi & Ms. Bahareh Jafari Jashmi for their help through implementation and tests.

Pattern Nulling of Linear Antenna Arrays Using Backtracking Search Optimization Algorithm

Directory of Open Access Journals (Sweden)

Kerim Guney

2015-01-01

Full Text Available An evolutionary method based on backtracking search optimization algorithm (BSA is proposed for linear antenna array pattern synthesis with prescribed nulls at interference directions. Pattern nulling is obtained by controlling only the amplitude, position, and phase of the antenna array elements. BSA is an innovative metaheuristic technique based on an iterative process. Various numerical examples of linear array patterns with the prescribed single, multiple, and wide nulls are given to illustrate the performance and flexibility of BSA. The results obtained by BSA are compared with the results of the following seventeen algorithms: particle swarm optimization (PSO, genetic algorithm (GA, modified touring ant colony algorithm (MTACO, quadratic programming method (QPM, bacterial foraging algorithm (BFA, bees algorithm (BA, clonal selection algorithm (CLONALG, plant growth simulation algorithm (PGSA, tabu search algorithm (TSA, memetic algorithm (MA, nondominated sorting GA-2 (NSGA-2, multiobjective differential evolution (MODE, decomposition with differential evolution (MOEA/D-DE, comprehensive learning PSO (CLPSO, harmony search algorithm (HSA, seeker optimization algorithm (SOA, and mean variance mapping optimization (MVMO. The simulation results show that the linear antenna array synthesis using BSA provides low side-lobe levels and deep null levels.

Optimization of Partitioned Architectures to Support Soft Real-Time Applications

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2014-01-01

In this paper we propose a new Tabu Search-based design optimization strategy for mixed-criticality systems implementing hard and soft real-time applications on the same platform. Our proposed strategy determined an implementation such that all hard real-time applications are schedulable and the ......In this paper we propose a new Tabu Search-based design optimization strategy for mixed-criticality systems implementing hard and soft real-time applications on the same platform. Our proposed strategy determined an implementation such that all hard real-time applications are schedulable...... and the quality of service of the soft real-time tasks is maximized. We have evaluated our strategy using an aerospace case study....

Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems

OpenAIRE

Petrovic, Sanja; Qu, Rong

2002-01-01

This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are dis...

Modeling Multilevel Supplier Selection Problem Based on Weighted-Directed Network and Its Solution

Directory of Open Access Journals (Sweden)

Chia-Te Wei

2017-01-01

Full Text Available With the rapid development of economy, the supplier network is becoming more and more complicated. It is important to choose the right suppliers for improving the efficiency of the supply chain, so how to choose the right ones is one of the important research directions of supply chain management. This paper studies the partner selection problem from the perspective of supplier network global optimization. Firstly, this paper discusses and forms the evaluation system to estimate the supplier from the two indicators of risk and greenness and then applies the value as the weight of the network between two nodes to build a weighted-directed supplier network; secondly, the study establishes the optimal combination model of supplier selection based on the global network perspective and solves the model by the dynamic programming-tabu search algorithm and the improved ant colony algorithm, respectively; finally, different scale simulation examples are given to testify the efficiency of the two algorithms. The results show that the ant colony algorithm is superior to the tabu search one as a whole, but the latter is slightly better than the former when network scale is small.

Competitiveness based on logistic management: a real case study

OpenAIRE

García Márquez, Fausto Pedro; Peña García Pardo, Isidro; Ramos M. Nieto, Marta

2014-01-01

An efficient and effective logistic system is a strategic objective in any produc- tive business. This paper presents a real case study of a routing problem in a food industry firm. This problem is solved as a Vehicle Routing Problem (VRP) using the Neural Net- work (NN) and Tabu Search (TS) algorithms. A customer selection based on a profitability analysis was carried out. The aforementioned algorithms were then applied, leading to a considerable reduction in the total logistic costs. This r...

Emotion of Physiological Signals Classification Based on TS Feature Selection

Institute of Scientific and Technical Information of China (English)

Wang Yujing; Mo Jianlin

2015-01-01

This paper propose a method of TS-MLP about emotion recognition of physiological signal.It can recognize emotion successfully by Tabu search which selects features of emotion’s physiological signals and multilayer perceptron that is used to classify emotion.Simulation shows that it has achieved good emotion classification performance.

Development of a fuzzy logic method to build objective functions in optimization problems: application to BWR fuel lattice design

International Nuclear Information System (INIS)

Martin-del-Campo, C.; Francois, J.L.; Barragan, A.M.; Palomera, M.A.

2005-01-01

In this paper we develop a methodology based on the use of the Fuzzy Logic technique to build multi-objective functions to be used in optimization processes applied to in-core nuclear fuel management. As an example, we selected the problem of determining optimal radial fuel enrichment and gadolinia distributions in a typical 'Boiling Water Reactor (BWR)' fuel lattice. The methodology is based on the use of the mathematical capability of Fuzzy Logic to model nonlinear functions of arbitrary complexity. The utility of Fuzzy Logic is to map an input space into an output space, and the primary mechanism for doing this is a list of if-then statements called rules. The rules refer to variables and adjectives that describe those variables and, the Fuzzy Logic technique interprets the values in the input vectors and, based on the set of rules assigns values to the output vector. The methodology was developed for the radial optimization of a BWR lattice where the optimization algorithm employed is Tabu Search. The global objective is to find the optimal distribution of enrichments and burnable poison concentrations in a 10*10 BWR lattice. In order to do that, a fuzzy control inference system was developed using the Fuzzy Logic Toolbox of Matlab and it has been linked to the Tabu Search optimization process. Results show that Tabu Search combined with Fuzzy Logic performs very well, obtaining lattices with optimal fuel utilization. (authors)

An Algoritm for the Alocation Optimization of Trading Executions

Directory of Open Access Journals (Sweden)

Claudiu Vinte

2006-02-01

Full Text Available In this paper, I wish to propose the Integer Allocation employing Tabu Search in conjunction with Simulated Annealing Heuristics for optimizing the distribution of trading executions in investors’ accounts. There is no polynomial algorithm discovered for Integer Linear Programming (a problem which is NP-complete. Generally, the practical experience shows that large-scale integer linear programs seem as yet practically unsolvable or extremely time-consuming. The algorithm described herein proposes an alternative approach to the problem. The algorithm consists of three steps: allocate the total executed quantity proportionally on the accounts, based on the allocation instructions (pro-rata basis; construct an initial solution, distributing the executed prices; improve the solution iteratively, employing Tabu Search in conjunction with Simulated Annealing heuristics.

Using Artificial Intelligence to Retrieve the Optimal Parameters and Structures of Adaptive Network-Based Fuzzy Inference System for Typhoon Precipitation Forecast Modeling

Directory of Open Access Journals (Sweden)

Chien-Lin Huang

2015-01-01

Full Text Available This study aims to construct a typhoon precipitation forecast model providing forecasts one to six hours in advance using optimal model parameters and structures retrieved from a combination of the adaptive network-based fuzzy inference system (ANFIS and artificial intelligence. To enhance the accuracy of the precipitation forecast, two structures were then used to establish the precipitation forecast model for a specific lead-time: a single-model structure and a dual-model hybrid structure where the forecast models of higher and lower precipitation were integrated. In order to rapidly, automatically, and accurately retrieve the optimal parameters and structures of the ANFIS-based precipitation forecast model, a tabu search was applied to identify the adjacent radius in subtractive clustering when constructing the ANFIS structure. The coupled structure was also employed to establish a precipitation forecast model across short and long lead-times in order to improve the accuracy of long-term precipitation forecasts. The study area is the Shimen Reservoir, and the analyzed period is from 2001 to 2009. Results showed that the optimal initial ANFIS parameters selected by the tabu search, combined with the dual-model hybrid method and the coupled structure, provided the favors in computation efficiency and high-reliability predictions in typhoon precipitation forecasts regarding short to long lead-time forecasting horizons.

Evidence-based Medicine Search: a customizable federated search engine.

Science.gov (United States)

Bracke, Paul J; Howse, David K; Keim, Samuel M

2008-04-01

This paper reports on the development of a tool by the Arizona Health Sciences Library (AHSL) for searching clinical evidence that can be customized for different user groups. The AHSL provides services to the University of Arizona's (UA's) health sciences programs and to the University Medical Center. Librarians at AHSL collaborated with UA College of Medicine faculty to create an innovative search engine, Evidence-based Medicine (EBM) Search, that provides users with a simple search interface to EBM resources and presents results organized according to an evidence pyramid. EBM Search was developed with a web-based configuration component that allows the tool to be customized for different specialties. Informal and anecdotal feedback from physicians indicates that EBM Search is a useful tool with potential in teaching evidence-based decision making. While formal evaluation is still being planned, a tool such as EBM Search, which can be configured for specific user populations, may help lower barriers to information resources in an academic health sciences center.

Module-Based Synthesis of Digital Microfluidic Biochips with Droplet-Aware Operation Execution

DEFF Research Database (Denmark)

Maftei, Elena; Pop, Paul; Madsen, Jan

2013-01-01

operations are executed by moving the droplets. So far, researchers have ignored the locations of droplets inside devices, considering that all the electrodes forming the device are occupied throughout the operation execution. In this article, we consider a droplet-aware execution of microfluidic operations......, which means that we know the exact position of droplets inside the modules at each time-step. We propose a Tabu Search-based metaheuristic for the synthesis of digital biochips with droplet-aware operation execution. Experimental results show that our approach can significantly reduce the application...... completion time, allowing us to use smaller area biochips and thus reduce costs....

Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model

DEFF Research Database (Denmark)

Pedersen, Michael Berliner; Crainic, Teodor Gabriel

We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...

Algorithm of axial fuel optimization based in progressive steps of turned search; Algoritmo de optimizacion axial de combustible basado en etapas progresivas de busqueda de entorno

Energy Technology Data Exchange (ETDEWEB)

Martin del Campo, C.; Francois, J.L. [Laboratorio de Analisis en Ingenieria de Reactores Nucleares, FI-UNAM, Paseo Cuauhnahuac 8532, Jiutepec, Morelos (Mexico)

2003-07-01

The development of an algorithm for the axial optimization of fuel of boiling water reactors (BWR) is presented. The algorithm is based in a serial optimizations process in the one that the best solution in each stage is the starting point of the following stage. The objective function of each stage adapts to orient the search toward better values of one or two parameters leaving the rest like restrictions. Conform to it advances in those optimization stages, it is increased the fineness of the evaluation of the investigated designs. The algorithm is based on three stages, in the first one are used Genetic algorithms and in the two following Tabu Search. The objective function of the first stage it looks for to minimize the average enrichment of the one it assembles and to fulfill with the generation of specified energy for the operation cycle besides not violating none of the limits of the design base. In the following stages the objective function looks for to minimize the power factor peak (PPF) and to maximize the margin of shutdown (SDM), having as restrictions the one average enrichment obtained for the best design in the first stage and those other restrictions. The third stage, very similar to the previous one, it begins with the design of the previous stage but it carries out a search of the margin of shutdown to different exhibition steps with calculations in three dimensions (3D). An application to the case of the design of the fresh assemble for the fourth fuel reload of the Unit 1 reactor of the Laguna Verde power plant (U1-CLV) is presented. The obtained results show an advance in the handling of optimization methods and in the construction of the objective functions that should be used for the different design stages of the fuel assemblies. (Author)

Optimal fuzzy logic-based PID controller for load-frequency control including superconducting magnetic energy storage units

International Nuclear Information System (INIS)

Pothiya, Saravuth; Ngamroo, Issarachai

2008-01-01

This paper proposes a new optimal fuzzy logic-based-proportional-integral-derivative (FLPID) controller for load frequency control (LFC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the multiple tabu search (MTS) algorithm is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters

Busca tabu para a programação de tarefas em job shop com datas de entrega

OpenAIRE

Cintia Rigão Scrich

1997-01-01

Resumo: Este trabalho trata do problema de programação de tarefas nos ambientes job shop tradicional e job shop flexível com o objetivo de minimizar o atraso total das tarefas. A principal diferença do job shop flexível em relação ao job shop tradicional é que cada operação possui um conjunto de máquinas alternativas onde pode ser processada. Para cada um dos problemas é desenvolvida uma heurística guiada pela metaheurística Busca Tabu. Estratégias de diversificação e intensificação para a bu...

A Geographical Heuristic Routing Protocol for VANETs

Science.gov (United States)

Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica

2016-01-01

Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation). PMID:27669254

FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm.

Directory of Open Access Journals (Sweden)

Shouheng Tuo

Full Text Available Two-locus model is a typical significant disease model to be identified in genome-wide association study (GWAS. Due to intensive computational burden and diversity of disease models, existing methods have drawbacks on low detection power, high computation cost, and preference for some types of disease models.In this study, two scoring functions (Bayesian network based K2-score and Gini-score are used for characterizing two SNP locus as a candidate model, the two criteria are adopted simultaneously for improving identification power and tackling the preference problem to disease models. Harmony search algorithm (HSA is improved for quickly finding the most likely candidate models among all two-locus models, in which a local search algorithm with two-dimensional tabu table is presented to avoid repeatedly evaluating some disease models that have strong marginal effect. Finally G-test statistic is used to further test the candidate models.We investigate our method named FHSA-SED on 82 simulated datasets and a real AMD dataset, and compare it with two typical methods (MACOED and CSE which have been developed recently based on swarm intelligent search algorithm. The results of simulation experiments indicate that our method outperforms the two compared algorithms in terms of detection power, computation time, evaluation times, sensitivity (TPR, specificity (SPC, positive predictive value (PPV and accuracy (ACC. Our method has identified two SNPs (rs3775652 and rs10511467 that may be also associated with disease in AMD dataset.

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

Science.gov (United States)

Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled

2018-03-01

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.

Custom Topology Generation for Network-on-Chip

DEFF Research Database (Denmark)

Stuart, Matthias Bo; Sparsø, Jens

2007-01-01

This paper compares simulated annealing and tabu search for generating custom topologies for applications with periodic behaviour executing on a network-on-chip. The approach differs from previous work by starting from a fixed mapping of IP-cores to routers and performing design space exploration...... around an initial topology. The tabu search has been modified from its normally encountered form to allow easier escaping from local minima. A number of synthetic benchmarks are used for tuning the parameters of both heuristics and for testing the quality of the solutions each heuristic produces...

Content Based Searching for INIS

International Nuclear Information System (INIS)

Jain, V.; Jain, R.K.

2016-01-01

Full text: Whatever a user wants is available on the internet, but to retrieve the information efficiently, a multilingual and most-relevant document search engine is a must. Most current search engines are word based or pattern based. They do not consider the meaning of the query posed to them; purely based on the keywords of the query; no support of multilingual query and and dismissal of nonrelevant results. Current information-retrieval techniques either rely on an encoding process, using a certain perspective or classification scheme, to describe a given item, or perform a full-text analysis, searching for user-specified words. Neither case guarantees content matching because an encoded description might reflect only part of the content and the mere occurrence of a word does not necessarily reflect the document’s content. For general documents, there doesn’t yet seem to be a much better option than lazy full-text analysis, by manually going through those endless results pages. In contrast to this, new search engine should extract the meaning of the query and then perform the search based on this extracted meaning. New search engine should also employ Interlingua based machine translation technology to present information in the language of choice of the user. (author

Experiencias de utilización del método de búsqueda TABU en la resolución de problemas de organización universitaria

Directory of Open Access Journals (Sweden)

J.M. Tamarit

2000-01-01

Full Text Available A lo largo de los 10 últimos años hemos trabajado en problemas de organización académica de grandes dimensiones. En problemas universitarios hemos tratado la confección de calendarios de exámenes, la asignación de estudiantes a grupos vinculada al problema de la automatrícula y también la confección de horarios. Todos estos problemas son difíciles (NP-hard por lo que en todos los casos los algoritmos de resolución implementados han sido complejos y basados en procedimientos adaptados a cada problema. Sin embargo, en todos ellos el método de Búsqueda Tabú (Tabu Search ha constituído el elemento esencial en la obtención de buenas soluciones. En el presente trabajo exponemos algunas enseñanzas de estas experiencias. Tanto aquellos elementos que se han mostrado útiles en el conjunto de los problemas como los que han mostrado una validez diferente en los diversos casos planteados. Asimismo se examinan diferentes posibilidades de uso de los elementos del Tabú y se exponen conclusiones.

A Slicing Tree Representation and QCP-Model-Based Heuristic Algorithm for the Unequal-Area Block Facility Layout Problem

Directory of Open Access Journals (Sweden)

Mei-Shiang Chang

2013-01-01

Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.

Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm

International Nuclear Information System (INIS)

Liang, Y.-C.; Chen, Y.-C.

2007-01-01

This paper presents a meta-heuristic algorithm, variable neighborhood search (VNS), to the redundancy allocation problem (RAP). The RAP, an NP-hard problem, has attracted the attention of much prior research, generally in a restricted form where each subsystem must consist of identical components. The newer meta-heuristic methods overcome this limitation and offer a practical way to solve large instances of the relaxed RAP where different components can be used in parallel. Authors' previously published work has shown promise for the variable neighborhood descent (VND) method, the simplest version among VNS variations, on RAP. The variable neighborhood search method itself has not been used in reliability design, yet it is a method that fits those combinatorial problems with potential neighborhood structures, as in the case of the RAP. Therefore, authors further extended their work to develop a VNS algorithm for the RAP and tested a set of well-known benchmark problems from the literature. Results on 33 test instances ranging from less to severely constrained conditions show that the variable neighborhood search method improves the performance of VND and provides a competitive solution quality at economically computational expense in comparison with the best-known heuristics including ant colony optimization, genetic algorithm, and tabu search

Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm

Energy Technology Data Exchange (ETDEWEB)

Liang, Y.-C. [Department of Industrial Engineering and Management, Yuan Ze University, No 135 Yuan-Tung Road, Chung-Li, Taoyuan County, Taiwan 320 (China)]. E-mail: ycliang@saturn.yzu.edu.tw; Chen, Y.-C. [Department of Industrial Engineering and Management, Yuan Ze University, No 135 Yuan-Tung Road, Chung-Li, Taoyuan County, Taiwan 320 (China)]. E-mail: s927523@mail.yzu.edu.tw

2007-03-15

This paper presents a meta-heuristic algorithm, variable neighborhood search (VNS), to the redundancy allocation problem (RAP). The RAP, an NP-hard problem, has attracted the attention of much prior research, generally in a restricted form where each subsystem must consist of identical components. The newer meta-heuristic methods overcome this limitation and offer a practical way to solve large instances of the relaxed RAP where different components can be used in parallel. Authors' previously published work has shown promise for the variable neighborhood descent (VND) method, the simplest version among VNS variations, on RAP. The variable neighborhood search method itself has not been used in reliability design, yet it is a method that fits those combinatorial problems with potential neighborhood structures, as in the case of the RAP. Therefore, authors further extended their work to develop a VNS algorithm for the RAP and tested a set of well-known benchmark problems from the literature. Results on 33 test instances ranging from less to severely constrained conditions show that the variable neighborhood search method improves the performance of VND and provides a competitive solution quality at economically computational expense in comparison with the best-known heuristics including ant colony optimization, genetic algorithm, and tabu search.

Top-k Keyword Search Over Graphs Based On Backward Search

Directory of Open Access Journals (Sweden)

Zeng Jia-Hui

2017-01-01

Full Text Available Keyword search is one of the most friendly and intuitive information retrieval methods. Using the keyword search to get the connected subgraph has a lot of application in the graph-based cognitive computation, and it is a basic technology. This paper focuses on the top-k keyword searching over graphs. We implemented a keyword search algorithm which applies the backward search idea. The algorithm locates the keyword vertices firstly, and then applies backward search to find rooted trees that contain query keywords. The experiment shows that query time is affected by the iteration number of the algorithm.

Dyniqx: a novel meta-search engine for metadata based cross search

OpenAIRE

Zhu, Jianhan; Song, Dawei; Eisenstadt, Marc; Barladeanu, Cristi; Rüger, Stefan

2008-01-01

The effect of metadata in collection fusion has not been sufficiently studied. In response to this, we present a novel meta-search engine called Dyniqx for metadata based cross search. Dyniqx exploits the availability of metadata in academic search services such as PubMed and Google Scholar etc for fusing search results from heterogeneous search engines. In addition, metadata from these search engines are used for generating dynamic query controls such as sliders and tick boxes etc which are ...

First application of quantum annealing to IMRT beamlet intensity optimization

International Nuclear Information System (INIS)

Nazareth, Daryl P; Spaans, Jason D

2015-01-01

Optimization methods are critical to radiation therapy. A new technology, quantum annealing (QA), employs novel hardware and software techniques to address various discrete optimization problems in many fields. We report on the first application of quantum annealing to the process of beamlet intensity optimization for IMRT.We apply recently-developed hardware which natively exploits quantum mechanical effects for improved optimization. The new algorithm, called QA, is most similar to simulated annealing, but relies on natural processes to directly minimize a system’s free energy. A simple quantum system is slowly evolved into a classical system representing the objective function. If the evolution is sufficiently slow, there are probabilistic guarantees that a global minimum will be located.To apply QA to IMRT-type optimization, two prostate cases were considered. A reduced number of beamlets were employed, due to the current QA hardware limitations. The beamlet dose matrices were computed using CERR and an objective function was defined based on typical clinical constraints, including dose-volume objectives, which result in a complex non-convex search space. The objective function was discretized and the QA method was compared to two standard optimization methods, simulated annealing and Tabu search, run on a conventional computing cluster.Based on several runs, the average final objective function value achieved by the QA was 16.9 for the first patient, compared with 10.0 for Tabu and 6.7 for the simulated annealing (SA) method. For the second patient, the values were 70.7 for the QA, 120.0 for Tabu and 22.9 for the SA. The QA algorithm required 27–38% of the time required by the other two methods.In this first application of hardware-enabled QA to IMRT optimization, its performance is comparable to Tabu search, but less effective than the SA in terms of final objective function values. However, its speed was 3–4 times faster than the other two methods

A synergetic combination of small and large neighborhood schemes in developing an effective procedure for solving the job shop scheduling problem.

Science.gov (United States)

Amirghasemi, Mehrdad; Zamani, Reza

2014-01-01

This paper presents an effective procedure for solving the job shop problem. Synergistically combining small and large neighborhood schemes, the procedure consists of four components, namely (i) a construction method for generating semi-active schedules by a forward-backward mechanism, (ii) a local search for manipulating a small neighborhood structure guided by a tabu list, (iii) a feedback-based mechanism for perturbing the solutions generated, and (iv) a very large-neighborhood local search guided by a forward-backward shifting bottleneck method. The combination of shifting bottleneck mechanism and tabu list is used as a means of the manipulation of neighborhood structures, and the perturbation mechanism employed diversifies the search. A feedback mechanism, called repeat-check, detects consequent repeats and ignites a perturbation when the total number of consecutive repeats for two identical makespan values reaches a given threshold. The results of extensive computational experiments on the benchmark instances indicate that the combination of these four components is synergetic, in the sense that they collectively make the procedure fast and robust.

Querying archetype-based EHRs by search ontology-based XPath engineering.

Science.gov (United States)

Kropf, Stefan; Uciteli, Alexandr; Schierle, Katrin; Krücken, Peter; Denecke, Kerstin; Herre, Heinrich

2018-05-11

Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that lead to false positive results, the precision can be increased by constraining the search to certain parts of documents. A search ontology-based specification of queries on XML documents defines search concepts and relates them to parts in the XML document structure. Such query specification method is practically introduced and evaluated by applying concrete research questions formulated in natural language on a data collection for information retrieval purposes. The search is performed by search ontology-based XPath engineering that reuses ontologies and XML-related W3C standards. The key result is that the specification of research questions can be supported by the usage of search ontology-based XPath engineering. A deeper recognition of entities and a semantic understanding of the content is necessary for a further improvement of precision and recall. Key limitation is that the application of the introduced process requires skills in ontology and software development. In future, the time consuming ontology development could be overcome by implementing a new clinical role: the clinical ontologist. The introduced Search Ontology XML extension connects Search Terms to certain parts in XML documents and enables an ontology-based definition of queries. Search ontology-based XPath engineering can support research question answering by the specification of complex XPath expressions without deep syntax knowledge about XPaths.

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

International Nuclear Information System (INIS)

Guo, Chunxiang; Liu, Xiaoli; Jin, Maozhu; Lv, Zhihan

2016-01-01

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.

Analyse af problemstillinger i moderne produktionssystemer ved hjælp af operationsanalytiske metoder

DEFF Research Database (Denmark)

Paulli, Jan

This PhD thesis consists of 6 volumes, the first being the above-mentioned Resumé. Vol. 2: Some Aspects of Applying Simulated Annealing and Tabu Search to the Quadratic Assignment Problem. Vol. 3: A Hierarchical Approach for the FMS Scheduling Problem Vol. 4: Solving the General Multiprocessor Job-shop...... Scheduling Problem (co-author: S. Dauzèrérès) Vol. 5: A Global Tabu Search Procedure for the General Multiprocessor Job-shop Scheduling Problem (co-author: S. Dauzère-Pérès) Vol. 6: Makespan Estimations in Flexible Manufacturing Systems (co-author: J.C. Fransoo, T.G. de Kok)...

HTTP-based Search and Ordering Using ECHO's REST-based and OpenSearch APIs

Science.gov (United States)

Baynes, K.; Newman, D. J.; Pilone, D.

2012-12-01

Metadata is an important entity in the process of cataloging, discovering, and describing Earth science data. NASA's Earth Observing System (EOS) ClearingHOuse (ECHO) acts as the core metadata repository for EOSDIS data centers, providing a centralized mechanism for metadata and data discovery and retrieval. By supporting both the ESIP's Federated Search API and its own search and ordering interfaces, ECHO provides multiple capabilities that facilitate ease of discovery and access to its ever-increasing holdings. Users are able to search and export metadata in a variety of formats including ISO 19115, json, and ECHO10. This presentation aims to inform technically savvy clients interested in automating search and ordering of ECHO's metadata catalog. The audience will be introduced to practical and applicable examples of end-to-end workflows that demonstrate finding, sub-setting and ordering data that is bound by keyword, temporal and spatial constraints. Interaction with the ESIP OpenSearch Interface will be highlighted, as will ECHO's own REST-based API.

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...

Ant colony system (ACS with hybrid local search to solve vehicle routing problems

Directory of Open Access Journals (Sweden)

Suphan Sodsoon

2016-02-01

Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.

IBRI-CASONTO: Ontology-based semantic search engine

Directory of Open Access Journals (Sweden)

Awny Sayed

2017-11-01

Full Text Available The vast availability of information, that added in a very fast pace, in the data repositories creates a challenge in extracting correct and accurate information. Which has increased the competition among developers in order to gain access to technology that seeks to understand the intent researcher and contextual meaning of terms. While the competition for developing an Arabic Semantic Search systems are still in their infancy, and the reason could be traced back to the complexity of Arabic Language. It has a complex morphological, grammatical and semantic aspects, as it is a highly inflectional and derivational language. In this paper, we try to highlight and present an Ontological Search Engine called IBRI-CASONTO for Colleges of Applied Sciences, Oman. Our proposed engine supports both Arabic and English language. It is also employed two types of search which are a keyword-based search and a semantics-based search. IBRI-CASONTO is based on different technologies such as Resource Description Framework (RDF data and Ontological graph. The experiments represent in two sections, first it shows a comparison among Entity-Search and the Classical-Search inside the IBRI-CASONTO itself, second it compares the Entity-Search of IBRI-CASONTO with currently used search engines, such as Kngine, Wolfram Alpha and the most popular engine nowadays Google, in order to measure their performance and efficiency.

Computer-based literature search in medical institutions in India

Directory of Open Access Journals (Sweden)

Kalita Jayantee

2007-01-01

Full Text Available Aim: To study the use of computer-based literature search and its application in clinical training and patient care as a surrogate marker of evidence-based medicine. Materials and Methods: A questionnaire comprising of questions on purpose (presentation, patient management, research, realm (site accessed, nature and frequency of search, effect, infrastructure, formal training in computer based literature search and suggestions for further improvement were sent to residents and faculty of a Postgraduate Medical Institute (PGI and a Medical College. The responses were compared amongst different subgroups of respondents. Results: Out of 300 subjects approached 194 responded; of whom 103 were from PGI and 91 from Medical College. There were 97 specialty residents, 58 super-specialty residents and 39 faculty members. Computer-based literature search was done at least once a month by 89% though there was marked variability in frequency and extent. The motivation for computer-based literature search was for presentation in 90%, research in 65% and patient management in 60.3%. The benefit of search was acknowledged in learning and teaching by 80%, research by 65% and patient care by 64.4% of respondents. Formal training in computer based literature search was received by 41% of whom 80% were residents. Residents from PGI did more frequent and more extensive computer-based literature search, which was attributed to better infrastructure and training. Conclusion: Training and infrastructure both are crucial for computer-based literature search, which may translate into evidence based medicine.

The Time-Dependent Multiple-Vehicle Prize-Collecting Arc Routing Problem

DEFF Research Database (Denmark)

Black, Daniel; Eglese, Richard; Wøhlk, Sanne

2015-01-01

-life traffic situations where the travel times change with the time of day are taken into account. Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time......In this paper, we introduce a multi vehicle version of the Time-Dependent Prize-Collecting Arc Routing Problem (TD-MPARP). It is inspired by a situation where a transport manager has to choose between a number of full truck load pick-ups and deliveries to be performed by a fleet of vehicles. Real...

The time-dependent prize-collecting arc routing problem

DEFF Research Database (Denmark)

Black, Dan; Eglese, Richard; Wøhlk, Sanne

2013-01-01

with the time of day. Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time information. Both algorithms are capable of finding good solutions, though......A new problem is introduced named the Time-Dependent Prize-Collecting Arc Routing Problem (TD-PARP). It is particularly relevant to situations where a transport manager has to choose between a number of full truck load pick-ups and deliveries on a road network where travel times change...

Multi-objective Search-based Mobile Testing

OpenAIRE

Mao, K.

2017-01-01

Despite the tremendous popularity of mobile applications, mobile testing still relies heavily on manual testing. This thesis presents mobile test automation approaches based on multi-objective search. We introduce three approaches: Sapienz (for native Android app testing), Octopuz (for hybrid/web JavaScript app testing) and Polariz (for using crowdsourcing to support search-based mobile testing). These three approaches represent the primary scientific and technical contributions of the thesis...

A hybrid GA-TS algorithm for open vehicle routing optimization of coal mines material

Energy Technology Data Exchange (ETDEWEB)

Yu, S.W.; Ding, C.; Zhu, K.J. [China University of Geoscience, Wuhan (China)

2011-08-15

In the open vehicle routing problem (OVRP), the objective is to minimize the number of vehicles and the total distance (or time) traveled. This study primarily focuses on solving an open vehicle routing problem (OVRP) by applying a novel hybrid genetic algorithm and the Tabu search (GA-TS), which combines the GA's parallel computing and global optimization with TS's Tabu search skill and fast local search. Firstly, the proposed algorithm uses natural number coding according to the customer demands and the captivity of the vehicle for globe optimization. Secondly, individuals of population do TS local search with a certain degree of probability, namely, do the local routing optimization of all customer sites belong to one vehicle. The mechanism not only improves the ability of global optimization, but also ensures the speed of operation. The algorithm was used in Zhengzhou Coal Mine and Power Supply Co., Ltd.'s transport vehicle routing optimization.

An optimization algorithm for a capacitated vehicle routing problem ...

Indian Academy of Sciences (India)

Pinar Kirci

PINAR KIRCI. Engineering Sciences Department, Istanbul University, Istanbul, Turkey .... In VRP solution methods, tabu search algorithm belongs to ..... systems which are considered in statistical mechanics is ..... Procedia-Social Behav. Sci.

Exact and heuristic solutions to the Double TSP with Multiple Stacks

DEFF Research Database (Denmark)

Petersen, Hanne Løhmann; Archetti, Claudia; Madsen, Oli B.G.

-pallet, which can be loaded in 3 stacks in a standard 40 foot container. Different exact and heuristic solution approaches to the DTSPMS have been implemented and tested. The exact approaches are based on different mathematical formulations of the problem which are solved using branch-and-cut. One formulation...... instances. The implemented heuristics include tabu search, simulated annealing and large neighbourhood search. Particularly the LNS approach shows promising results. It finds the known optimal solution of smaller instances (15 orders) within 10 seconds in most cases, and in 3 minutes it finds solutions...

Optimal Spatial Design of Capacity and Quantity of Rainwater Catchment Systems for Urban Flood Mitigation

Science.gov (United States)

Huang, C.; Hsu, N.

2013-12-01

This study imports Low-Impact Development (LID) technology of rainwater catchment systems into a Storm-Water runoff Management Model (SWMM) to design the spatial capacity and quantity of rain barrel for urban flood mitigation. This study proposes a simulation-optimization model for effectively searching the optimal design. In simulation method, we design a series of regular spatial distributions of capacity and quantity of rainwater catchment facilities, and thus the reduced flooding circumstances using a variety of design forms could be simulated by SWMM. Moreover, we further calculate the net benefit that is equal to subtract facility cost from decreasing inundation loss and the best solution of simulation method would be the initial searching solution of the optimization model. In optimizing method, first we apply the outcome of simulation method and Back-Propagation Neural Network (BPNN) for developing a water level simulation model of urban drainage system in order to replace SWMM which the operating is based on a graphical user interface and is hard to combine with optimization model and method. After that we embed the BPNN-based simulation model into the developed optimization model which the objective function is minimizing the negative net benefit. Finally, we establish a tabu search-based algorithm to optimize the planning solution. This study applies the developed method in Zhonghe Dist., Taiwan. Results showed that application of tabu search and BPNN-based simulation model into the optimization model not only can find better solutions than simulation method in 12.75%, but also can resolve the limitations of previous studies. Furthermore, the optimized spatial rain barrel design can reduce 72% of inundation loss according to historical flood events.

Attribute-based proxy re-encryption with keyword search.

Science.gov (United States)

Shi, Yanfeng; Liu, Jiqiang; Han, Zhen; Zheng, Qingji; Zhang, Rui; Qiu, Shuo

2014-01-01

Keyword search on encrypted data allows one to issue the search token and conduct search operations on encrypted data while still preserving keyword privacy. In the present paper, we consider the keyword search problem further and introduce a novel notion called attribute-based proxy re-encryption with keyword search (ABRKS), which introduces a promising feature: In addition to supporting keyword search on encrypted data, it enables data owners to delegate the keyword search capability to some other data users complying with the specific access control policy. To be specific, ABRKS allows (i) the data owner to outsource his encrypted data to the cloud and then ask the cloud to conduct keyword search on outsourced encrypted data with the given search token, and (ii) the data owner to delegate other data users keyword search capability in the fine-grained access control manner through allowing the cloud to re-encrypted stored encrypted data with a re-encrypted data (embedding with some form of access control policy). We formalize the syntax and security definitions for ABRKS, and propose two concrete constructions for ABRKS: key-policy ABRKS and ciphertext-policy ABRKS. In the nutshell, our constructions can be treated as the integration of technologies in the fields of attribute-based cryptography and proxy re-encryption cryptography.

Attribute-Based Proxy Re-Encryption with Keyword Search

Science.gov (United States)

Shi, Yanfeng; Liu, Jiqiang; Han, Zhen; Zheng, Qingji; Zhang, Rui; Qiu, Shuo

2014-01-01

Keyword search on encrypted data allows one to issue the search token and conduct search operations on encrypted data while still preserving keyword privacy. In the present paper, we consider the keyword search problem further and introduce a novel notion called attribute-based proxy re-encryption with keyword search (), which introduces a promising feature: In addition to supporting keyword search on encrypted data, it enables data owners to delegate the keyword search capability to some other data users complying with the specific access control policy. To be specific, allows (i) the data owner to outsource his encrypted data to the cloud and then ask the cloud to conduct keyword search on outsourced encrypted data with the given search token, and (ii) the data owner to delegate other data users keyword search capability in the fine-grained access control manner through allowing the cloud to re-encrypted stored encrypted data with a re-encrypted data (embedding with some form of access control policy). We formalize the syntax and security definitions for , and propose two concrete constructions for : key-policy and ciphertext-policy . In the nutshell, our constructions can be treated as the integration of technologies in the fields of attribute-based cryptography and proxy re-encryption cryptography. PMID:25549257

Improved hybrid optimization algorithm for 3D protein structure prediction.

Science.gov (United States)

Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

2014-07-01

A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

Assessment and Comparison of Search capabilities of Web-based Meta-Search Engines: A Checklist Approach

Directory of Open Access Journals (Sweden)

Alireza Isfandiyari Moghadam

2010-03-01

Full Text Available   The present investigation concerns evaluation, comparison and analysis of search options existing within web-based meta-search engines. 64 meta-search engines were identified. 19 meta-search engines that were free, accessible and compatible with the objectives of the present study were selected. An author’s constructed check list was used for data collection. Findings indicated that all meta-search engines studied used the AND operator, phrase search, number of results displayed setting, previous search query storage and help tutorials. Nevertheless, none of them demonstrated any search options for hypertext searching and displaying the size of the pages searched. 94.7% support features such as truncation, keywords in title and URL search and text summary display. The checklist used in the study could serve as a model for investigating search options in search engines, digital libraries and other internet search tools.

Metaheuristic approaches to order sequencing on a unidirectional ...

African Journals Online (AJOL)

is that tabu search (TS) incorporates “intelligence. ..... location that will benefit the solution quality by considering implications that may arise ..... [12] Glover F, 1986, Future paths for integer programming and links to artificial intelligence, ...

A Secured Cognitive Agent based Multi-strategic Intelligent Search System

Directory of Open Access Journals (Sweden)

Neha Gulati

2018-04-01

Full Text Available Search Engine (SE is the most preferred information retrieval tool ubiquitously used. In spite of vast scale involvement of users in SE’s, their limited capabilities to understand the user/searcher context and emotions places high cognitive, perceptual and learning load on the user to maintain the search momentum. In this regard, the present work discusses a Cognitive Agent (CA based approach to support the user in Web-based search process. The work suggests a framework called Secured Cognitive Agent based Multi-strategic Intelligent Search System (CAbMsISS to assist the user in search process. It helps to reduce the contextual and emotional mismatch between the SE’s and user. After implementation of the proposed framework, performance analysis shows that CAbMsISS framework improves Query Retrieval Time (QRT and effectiveness for retrieving relevant results as compared to Present Search Engine (PSE. Supplementary to this, it also provides search suggestions when user accesses a resource previously tagged with negative emotions. Overall, the goal of the system is to enhance the search experience for keeping the user motivated. The framework provides suggestions through the search log that tracks the queries searched, resources accessed and emotions experienced during the search. The implemented framework also considers user security. Keywords: BDI model, Cognitive Agent, Emotion, Information retrieval, Intelligent search, Search Engine

Considerations for the development of task-based search engines

DEFF Research Database (Denmark)

Petcu, Paula; Dragusin, Radu

2013-01-01

Based on previous experience from working on a task-based search engine, we present a list of suggestions and ideas for an Information Retrieval (IR) framework that could inform the development of next generation professional search systems. The specific task that we start from is the clinicians......' information need in finding rare disease diagnostic hypotheses at the time and place where medical decisions are made. Our experience from the development of a search engine focused on supporting clinicians in completing this task has provided us valuable insights in what aspects should be considered...... by the developers of vertical search engines....

Object-based target templates guide attention during visual search

OpenAIRE

Berggren, Nick; Eimer, Martin

2018-01-01

During visual search, attention is believed to be controlled in a strictly feature-based fashion, without any guidance by object-based target representations. To challenge this received view, we measured electrophysiological markers of attentional selection (N2pc component) and working memory (SPCN) in search tasks where two possible targets were defined by feature conjunctions (e.g., blue circles and green squares). Critically, some search displays also contained nontargets with two target f...

Metaheuristic approaches to order sequencing on a unidirectional picking line

Directory of Open Access Journals (Sweden)

AP de Villiers

2013-06-01

Full Text Available In this paper the sequencing of orders on a unidirectional picking line is considered. The aim of the order sequencing is to minimise the number of cycles travelled by a picker within the picking line to complete all orders. A tabu search, simulated annealing, genetic algorithm, generalised extremal optimisation and a random local search are presented as possible solution approaches. Computational results based on real life data instances are presented for these metaheuristics and compared to the performance of a lower bound and the solutions used in practise. The random local search exhibits the best overall solution quality, however, the generalised extremal optimisation approach delivers comparable results in considerably shorter computational times.

Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships.

Science.gov (United States)

Zong, Nansu; Lee, Sungin; Ahn, Jinhyun; Kim, Hong-Gee

2017-08-01

The keyword-based entity search restricts search space based on the preference of search. When given keywords and preferences are not related to the same biomedical topic, existing biomedical Linked Data search engines fail to deliver satisfactory results. This research aims to tackle this issue by supporting an inter-topic search-improving search with inputs, keywords and preferences, under different topics. This study developed an effective algorithm in which the relations between biomedical entities were used in tandem with a keyword-based entity search, Siren. The algorithm, PERank, which is an adaptation of Personalized PageRank (PPR), uses a pair of input: (1) search preferences, and (2) entities from a keyword-based entity search with a keyword query, to formalize the search results on-the-fly based on the index of the precomputed Individual Personalized PageRank Vectors (IPPVs). Our experiments were performed over ten linked life datasets for two query sets, one with keyword-preference topic correspondence (intra-topic search), and the other without (inter-topic search). The experiments showed that the proposed method achieved better search results, for example a 14% increase in precision for the inter-topic search than the baseline keyword-based search engine. The proposed method improved the keyword-based biomedical entity search by supporting the inter-topic search without affecting the intra-topic search based on the relations between different entities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Kinetic theory of nonequilibrium ensembles, irreversible thermodynamics, and generalized hydrodynamics

CERN Document Server

Eu, Byung Chan

2016-01-01

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computin...

Un Algoritmo Evolutivo para Resolver el Problema de Coloración Robusta

Directory of Open Access Journals (Sweden)

Pedro Lara Velázquez

2012-03-01

Full Text Available Let G and \\bar{G} be two complementary graphs. Given a penalty function defined over the edges of \\bar{G}, it is said that the rigidity of a k-coloring of G is the summation ofthe penalties of the edges of G that join vertices whose endpoint are equally colored. Based on this previous definition, the Robust Coloring Problem is set when searching the valid k-coloring of minimum rigidity. Yáñez and Ramírez proved that this is an NP-hard problem. In this work we present an evolutive algorithm based in the scatter search technique, which obtains optimal solutions for those instances for which an optimal solution is known, and obtains the best known solutions compared to other heuristics, such as: simulated annealing, tabu search and partial enumeration.

SU-F-BRD-13: Quantum Annealing Applied to IMRT Beamlet Intensity Optimization

Energy Technology Data Exchange (ETDEWEB)

Nazareth, D [Roswell Park Cancer Institute, Buffalo, NY (United States); Spaans, J [Hawarden, IA (United States)

2014-06-15

Purpose: We report on the first application of quantum annealing (QA) to the process of beamlet intensity optimization for IMRT. QA is a new technology, which employs novel hardware and software techniques to address various discrete optimization problems in many fields. Methods: We apply the D-Wave Inc. proprietary hardware, which natively exploits quantum mechanical effects for improved optimization. The new QA algorithm, running on this hardware, is most similar to simulated annealing, but relies on natural processes to directly minimize the free energy of a system. A simple quantum system is slowly evolved into a classical system, representing the objective function. To apply QA to IMRT-type optimization, two prostate cases were considered. A reduced number of beamlets were employed, due to the current QA hardware limitation of ∼500 binary variables. The beamlet dose matrices were computed using CERR, and an objective function was defined based on typical clinical constraints, including dose-volume objectives. The objective function was discretized, and the QA method was compared to two standard optimization Methods: simulated annealing and Tabu search, run on a conventional computing cluster. Results: Based on several runs, the average final objective function value achieved by the QA was 16.9 for the first patient, compared with 10.0 for Tabu and 6.7 for the SA. For the second patient, the values were 70.7 for the QA, 120.0 for Tabu, and 22.9 for the SA. The QA algorithm required 27–38% of the time required by the other two methods. Conclusion: In terms of objective function value, the QA performance was similar to Tabu but less effective than the SA. However, its speed was 3–4 times faster than the other two methods. This initial experiment suggests that QA-based heuristics may offer significant speedup over conventional clinical optimization methods, as quantum annealing hardware scales to larger sizes.

SU-F-BRD-13: Quantum Annealing Applied to IMRT Beamlet Intensity Optimization

International Nuclear Information System (INIS)

Nazareth, D; Spaans, J

2014-01-01

Purpose: We report on the first application of quantum annealing (QA) to the process of beamlet intensity optimization for IMRT. QA is a new technology, which employs novel hardware and software techniques to address various discrete optimization problems in many fields. Methods: We apply the D-Wave Inc. proprietary hardware, which natively exploits quantum mechanical effects for improved optimization. The new QA algorithm, running on this hardware, is most similar to simulated annealing, but relies on natural processes to directly minimize the free energy of a system. A simple quantum system is slowly evolved into a classical system, representing the objective function. To apply QA to IMRT-type optimization, two prostate cases were considered. A reduced number of beamlets were employed, due to the current QA hardware limitation of ∼500 binary variables. The beamlet dose matrices were computed using CERR, and an objective function was defined based on typical clinical constraints, including dose-volume objectives. The objective function was discretized, and the QA method was compared to two standard optimization Methods: simulated annealing and Tabu search, run on a conventional computing cluster. Results: Based on several runs, the average final objective function value achieved by the QA was 16.9 for the first patient, compared with 10.0 for Tabu and 6.7 for the SA. For the second patient, the values were 70.7 for the QA, 120.0 for Tabu, and 22.9 for the SA. The QA algorithm required 27–38% of the time required by the other two methods. Conclusion: In terms of objective function value, the QA performance was similar to Tabu but less effective than the SA. However, its speed was 3–4 times faster than the other two methods. This initial experiment suggests that QA-based heuristics may offer significant speedup over conventional clinical optimization methods, as quantum annealing hardware scales to larger sizes

Chemical Information in Scirus and BASE (Bielefeld Academic Search Engine)

Science.gov (United States)

Bendig, Regina B.

2009-01-01

The author sought to determine to what extent the two search engines, Scirus and BASE (Bielefeld Academic Search Engines), would be useful to first-year university students as the first point of searching for chemical information. Five topics were searched and the first ten records of each search result were evaluated with regard to the type of…

Content-based Music Search and Recommendation System

Science.gov (United States)

Takegawa, Kazuki; Hijikata, Yoshinori; Nishida, Shogo

Recently, the turn volume of music data on the Internet has increased rapidly. This has increased the user's cost to find music data suiting their preference from such a large data set. We propose a content-based music search and recommendation system. This system has an interface for searching and finding music data and an interface for editing a user profile which is necessary for music recommendation. By exploiting the visualization of the feature space of music and the visualization of the user profile, the user can search music data and edit the user profile. Furthermore, by exploiting the infomation which can be acquired from each visualized object in a mutually complementary manner, we make it easier for the user to search music data and edit the user profile. Concretely, the system gives to the user an information obtained from the user profile when searching music data and an information obtained from the feature space of music when editing the user profile.

GeoSearcher: Location-Based Ranking of Search Engine Results.

Science.gov (United States)

Watters, Carolyn; Amoudi, Ghada

2003-01-01

Discussion of Web queries with geospatial dimensions focuses on an algorithm that assigns location coordinates dynamically to Web sites based on the URL. Describes a prototype search system that uses the algorithm to re-rank search engine results for queries with a geospatial dimension, thus providing an alternative ranking order for search engine…

An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks

Science.gov (United States)

Lin, Geng; Guan, Jian; Feng, Huibin

2018-06-01

The positive influence dominating set problem is a variant of the minimum dominating set problem, and has lots of applications in social networks. It is NP-hard, and receives more and more attention. Various methods have been proposed to solve the positive influence dominating set problem. However, most of the existing work focused on greedy algorithms, and the solution quality needs to be improved. In this paper, we formulate the minimum positive influence dominating set problem as an integer linear programming (ILP), and propose an ILP based memetic algorithm (ILPMA) for solving the problem. The ILPMA integrates a greedy randomized adaptive construction procedure, a crossover operator, a repair operator, and a tabu search procedure. The performance of ILPMA is validated on nine real-world social networks with nodes up to 36,692. The results show that ILPMA significantly improves the solution quality, and is robust.

Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics.

Science.gov (United States)

Dao, Tien Tuan; Hoang, Tuan Nha; Ta, Xuan Hien; Tho, Marie Christine Ho Ba

2013-02-01

Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes. Copyright © 2012 Elsevier Inc. All rights reserved.

Three dimensional pattern recognition using feature-based indexing and rule-based search

Science.gov (United States)

Lee, Jae-Kyu

In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

Heuristic algorithms for joint optimization of unicast and anycast traffic in elastic optical network–based large–scale computing systems

Directory of Open Access Journals (Sweden)

Markowski Marcin

2017-09-01

Full Text Available In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.

MetaboSearch: tool for mass-based metabolite identification using multiple databases.

Directory of Open Access Journals (Sweden)

Bin Zhou

Full Text Available Searching metabolites against databases according to their masses is often the first step in metabolite identification for a mass spectrometry-based untargeted metabolomics study. Major metabolite databases include Human Metabolome DataBase (HMDB, Madison Metabolomics Consortium Database (MMCD, Metlin, and LIPID MAPS. Since each one of these databases covers only a fraction of the metabolome, integration of the search results from these databases is expected to yield a more comprehensive coverage. However, the manual combination of multiple search results is generally difficult when identification of hundreds of metabolites is desired. We have implemented a web-based software tool that enables simultaneous mass-based search against the four major databases, and the integration of the results. In addition, more complete chemical identifier information for the metabolites is retrieved by cross-referencing multiple databases. The search results are merged based on IUPAC International Chemical Identifier (InChI keys. Besides a simple list of m/z values, the software can accept the ion annotation information as input for enhanced metabolite identification. The performance of the software is demonstrated on mass spectrometry data acquired in both positive and negative ionization modes. Compared with search results from individual databases, MetaboSearch provides better coverage of the metabolome and more complete chemical identifier information.The software tool is available at http://omics.georgetown.edu/MetaboSearch.html.

The use of meta-heuristics for airport gate assignment

DEFF Research Database (Denmark)

Cheng, Chun-Hung; Ho, Sin C.; Kwan, Cheuk-Lam

2012-01-01

proposed to generate good solutions within a reasonable timeframe. In this work, we attempt to assess the performance of three meta-heuristics, namely, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and a hybrid approach based on SA and TS. Flight data from Incheon International Airport...... are collected to carry out the computational comparison. Although the literature has documented these algorithms, this work may be a first attempt to evaluate their performance using a set of realistic flight data....

Research on perturbation based Monte Carlo reactor criticality search

International Nuclear Information System (INIS)

Li Zeguang; Wang Kan; Li Yangliu; Deng Jingkang

2013-01-01

Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Traditional Monte Carlo criticality search method is suffered from large amount of individual criticality runs and uncertainty and fluctuation of Monte Carlo results. A new Monte Carlo criticality search method based on perturbation calculation is put forward in this paper to overcome the disadvantages of traditional method. By using only one criticality run to get initial k_e_f_f and differential coefficients of concerned parameter, the polynomial estimator of k_e_f_f changing function is solved to get the critical value of concerned parameter. The feasibility of this method was tested. The results show that the accuracy and efficiency of perturbation based criticality search method are quite inspiring and the method overcomes the disadvantages of traditional one. (authors)

Meta-Heuristics for Dynamic Lot Sizing: a review and comparison of solution approaches

NARCIS (Netherlands)

R.F. Jans (Raf); Z. Degraeve (Zeger)

2004-01-01

textabstractProofs from complexity theory as well as computational experiments indicate that most lot sizing problems are hard to solve. Because these problems are so difficult, various solution techniques have been proposed to solve them. In the past decade, meta-heuristics such as tabu search,

Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

Directory of Open Access Journals (Sweden)

Chien-Lin Huang

2015-09-01

Full Text Available This study adopts rainwater harvesting systems (RWHS into a stormwater runoff management model (SWMM for the spatial design of capacities and quantities of rain barrel for urban flood mitigation. A simulation-optimization model is proposed for effectively identifying the optimal design. First of all, we particularly classified the characteristic zonal subregions for spatial design by using fuzzy C-means clustering with the investigated data of urban roof, land use and drainage system. In the simulation method, a series of regular spatial arrangements specification are designed by using statistical quartiles analysis for rooftop area and rainfall frequency analysis; accordingly, the corresponding reduced flooding circumstances can be simulated by SWMM. Moreover, the most effective solution for the simulation method is identified from the calculated net benefit, which is equivalent to the subtraction of the facility cost from the decreased inundation loss. It serves as the initially identified solution for the optimization model. In the optimization method, backpropagation neural network (BPNN are first applied for developing a water level simulation model of urban drainage systems to substitute for SWMM to conform to newly considered interdisciplinary multi-objective optimization model, and a tabu search-based algorithm is used with the embedded BPNN-based SWMM to optimize the planning solution. The developed method is applied to the Zhong-He District, Taiwan. Results demonstrate that the application of tabu search and the BPNN-based simulation model into the optimization model can effectively, accurately and fast search optimal design considering economic net benefit. Furthermore, the optimized spatial rain barrel design could reduce 72% of inundation losses according to the simulated flood events.

Automated Search-Based Robustness Testing for Autonomous Vehicle Software

Directory of Open Access Journals (Sweden)

Kevin M. Betts

2016-01-01

Full Text Available Autonomous systems must successfully operate in complex time-varying spatial environments even when dealing with system faults that may occur during a mission. Consequently, evaluating the robustness, or ability to operate correctly under unexpected conditions, of autonomous vehicle control software is an increasingly important issue in software testing. New methods to automatically generate test cases for robustness testing of autonomous vehicle control software in closed-loop simulation are needed. Search-based testing techniques were used to automatically generate test cases, consisting of initial conditions and fault sequences, intended to challenge the control software more than test cases generated using current methods. Two different search-based testing methods, genetic algorithms and surrogate-based optimization, were used to generate test cases for a simulated unmanned aerial vehicle attempting to fly through an entryway. The effectiveness of the search-based methods in generating challenging test cases was compared to both a truth reference (full combinatorial testing and the method most commonly used today (Monte Carlo testing. The search-based testing techniques demonstrated better performance than Monte Carlo testing for both of the test case generation performance metrics: (1 finding the single most challenging test case and (2 finding the set of fifty test cases with the highest mean degree of challenge.

A Systematic Understanding of Successful Web Searches in Information-Based Tasks

Science.gov (United States)

Zhou, Mingming

2013-01-01

The purpose of this study is to research how Chinese university students solve information-based problems. With the Search Performance Index as the measure of search success, participants were divided into high, medium and low-performing groups. Based on their web search logs, these three groups were compared along five dimensions of the search…

Development of health information search engine based on metadata and ontology.

Science.gov (United States)

Song, Tae-Min; Park, Hyeoun-Ae; Jin, Dal-Lae

2014-04-01

The aim of the study was to develop a metadata and ontology-based health information search engine ensuring semantic interoperability to collect and provide health information using different application programs. Health information metadata ontology was developed using a distributed semantic Web content publishing model based on vocabularies used to index the contents generated by the information producers as well as those used to search the contents by the users. Vocabulary for health information ontology was mapped to the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), and a list of about 1,500 terms was proposed. The metadata schema used in this study was developed by adding an element describing the target audience to the Dublin Core Metadata Element Set. A metadata schema and an ontology ensuring interoperability of health information available on the internet were developed. The metadata and ontology-based health information search engine developed in this study produced a better search result compared to existing search engines. Health information search engine based on metadata and ontology will provide reliable health information to both information producer and information consumers.

Supervised learning of tools for content-based search of image databases

Science.gov (United States)

Delanoy, Richard L.

1996-03-01

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

Perturbation based Monte Carlo criticality search in density, enrichment and concentration

International Nuclear Information System (INIS)

Li, Zeguang; Wang, Kan; Deng, Jingkang

2015-01-01

Highlights: • A new perturbation based Monte Carlo criticality search method is proposed. • The method could get accurate results with only one individual criticality run. • The method is used to solve density, enrichment and concentration search problems. • Results show the feasibility and good performances of this method. • The relationship between results’ accuracy and perturbation order is discussed. - Abstract: Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Existing Monte Carlo criticality search methods need large amount of individual criticality runs and may have unstable results because of the uncertainties of criticality results. In this paper, a new perturbation based Monte Carlo criticality search method is proposed and discussed. This method only needs one individual criticality calculation with perturbation tallies to estimate k eff changing function using initial k eff and differential coefficients results, and solves polynomial equations to get the criticality search results. The new perturbation based Monte Carlo criticality search method is implemented in the Monte Carlo code RMC, and criticality search problems in density, enrichment and concentration are taken out. Results show that this method is quite inspiring in accuracy and efficiency, and has advantages compared with other criticality search methods

Impact of Glaucoma and Dry Eye on Text-Based Searching

Science.gov (United States)

Sun, Michelle J.; Rubin, Gary S.; Akpek, Esen K.; Ramulu, Pradeep Y.

2017-01-01

Purpose We determine if visual field loss from glaucoma and/or measures of dry eye severity are associated with difficulty searching, as judged by slower search times on a text-based search task. Methods Glaucoma patients with bilateral visual field (VF) loss, patients with clinically significant dry eye, and normally-sighted controls were enrolled from the Wilmer Eye Institute clinics. Subjects searched three Yellow Pages excerpts for a specific phone number, and search time was recorded. Results A total of 50 glaucoma subjects, 40 dry eye subjects, and 45 controls completed study procedures. On average, glaucoma patients exhibited 57% longer search times compared to controls (95% confidence interval [CI], 26%–96%, P Dry eye subjects demonstrated similar search times compared to controls, though worse Ocular Surface Disease Index (OSDI) vision-related subscores were associated with longer search times (P dry eye (P > 0.08 for Schirmer's testing without anesthesia, corneal fluorescein staining, and tear film breakup time). Conclusions Text-based visual search is slower for glaucoma patients with greater levels of VF loss and dry eye patients with greater self-reported visual difficulty, and these difficulties may contribute to decreased quality of life in these groups. Translational Relevance Visual search is impaired in glaucoma and dry eye groups compared to controls, highlighting the need for compensatory strategies and tools to assist individuals in overcoming their deficiencies. PMID:28670502

Evidence-based librarianship: searching for the needed EBL evidence.

Science.gov (United States)

Eldredge, J D

2000-01-01

This paper discusses the challenges of finding evidence needed to implement Evidence-Based Librarianship (EBL). Focusing first on database coverage for three health sciences librarianship journals, the article examines the information contents of different databases. Strategies are needed to search for relevant evidence in the library literature via these databases, and the problems associated with searching the grey literature of librarianship. Database coverage, plausible search strategies, and the grey literature of library science all pose challenges to finding the needed research evidence for practicing EBL. Health sciences librarians need to ensure that systems are designed that can track and provide access to needed research evidence to support Evidence-Based Librarianship (EBL).

Robust object tacking based on self-adaptive search area

Science.gov (United States)

Dong, Taihang; Zhong, Sheng

2018-02-01

Discriminative correlation filter (DCF) based trackers have recently achieved excellent performance with great computational efficiency. However, DCF based trackers suffer boundary effects, which result in the unstable performance in challenging situations exhibiting fast motion. In this paper, we propose a novel method to mitigate this side-effect in DCF based trackers. We change the search area according to the prediction of target motion. When the object moves fast, broad search area could alleviate boundary effects and reserve the probability of locating object. When the object moves slowly, narrow search area could prevent effect of useless background information and improve computational efficiency to attain real-time performance. This strategy can impressively soothe boundary effects in situations exhibiting fast motion and motion blur, and it can be used in almost all DCF based trackers. The experiments on OTB benchmark show that the proposed framework improves the performance compared with the baseline trackers.

Computer module for scheduling of transportation of composite beam bridge structures

Directory of Open Access Journals (Sweden)

Bożejko Wojciech

2016-01-01

Full Text Available The paper presents the theoretical basis, an algorithm and a computer module system supporting scheduling of transportation and assembly of structures of the composite beam bridge implemented in a Just In Time system (JIT. Tabu search method has been used in the optimization procedure.

A Comparison of Existing Optimisation Techniques with the ...

African Journals Online (AJOL)

Log in or Register to get access to full text downloads. ... The channel assignment problem has an important role to play in mobile telephone communication. ... annealing, graph colouring, neural networks, genetic algorithms and tabu search. ... We apply the univariate marginal distribution algorithm to a benchmark problem ...

Implementation of a Tabu Search Heuristic for the Examinations ...

African Journals Online (AJOL)

Log in or Register to get access to full text downloads. ... The Examinations Timetabling Problem is the problem of assigning examinations and candidates to ... Generally, timetabling problems are NP-Hard and therefore very difficult to solve.

The Process Synthesis Pyramid: Conceptual design of a Liquefied Energy Chain using Pinch Analysis,Exergy Analysis,Deterministic Optimization and Metaheuristic Searches

International Nuclear Information System (INIS)

Aspelund, Audun

2012-01-01

Process Synthesis (PS) is a term used to describe a class of general and systematic methods for the conceptual design of processing plants and energy systems. The term also refers to the development of the process flowsheet (structure or topology), the selection of unit operations and the determination of the most important operating conditions.In this thesis an attempt is made to characterize some of the most common methodologies in a PS pyramid and discuss their advantages and disadvantages as well as where in the design phase they could be used most efficiently. The thesis shows how design tools have been developed for subambient processes by combining and expanding PS methods such as Heuristic Rules, sequential modular Process Simulations, Pinch Analysis, Exergy Analysis, Mathematical Programming using Deterministic Optimization methods and optimization using Stochastic Optimization methods. The most important contributions to the process design community are three new methodologies that include the pressure as an important variable in heat exchanger network synthesis (HENS).The methodologies have been used to develop a novel and efficient energy chain based on stranded natural gas including power production with carbon capture and sequestration (CCS). This Liquefied Energy Chain consists of an offshore process a combined gas carrier and an onshore process. This energy chain is capable of efficiently exploiting resources that cannot be utilized economically today with minor Co2 emissions. Finally, a new Stochastic Optimization approach based on a Tabu Search (TS), the Nelder Mead method or Downhill Simplex Method (NMDS) and the sequential process simulator HYSYS is used to search for better solutions for the Liquefied Energy Chain with respect to minimum cost or maximum profit. (au)

The Process Synthesis Pyramid: Conceptual design of a Liquefied Energy Chain using Pinch Analysis,Exergy Analysis,Deterministic Optimization and Metaheuristic Searches

Energy Technology Data Exchange (ETDEWEB)

Aspelund, Audun

2012-07-01

Process Synthesis (PS) is a term used to describe a class of general and systematic methods for the conceptual design of processing plants and energy systems. The term also refers to the development of the process flowsheet (structure or topology), the selection of unit operations and the determination of the most important operating conditions.In this thesis an attempt is made to characterize some of the most common methodologies in a PS pyramid and discuss their advantages and disadvantages as well as where in the design phase they could be used most efficiently. The thesis shows how design tools have been developed for subambient processes by combining and expanding PS methods such as Heuristic Rules, sequential modular Process Simulations, Pinch Analysis, Exergy Analysis, Mathematical Programming using Deterministic Optimization methods and optimization using Stochastic Optimization methods. The most important contributions to the process design community are three new methodologies that include the pressure as an important variable in heat exchanger network synthesis (HENS).The methodologies have been used to develop a novel and efficient energy chain based on stranded natural gas including power production with carbon capture and sequestration (CCS). This Liquefied Energy Chain consists of an offshore process a combined gas carrier and an onshore process. This energy chain is capable of efficiently exploiting resources that cannot be utilized economically today with minor Co2 emissions. Finally, a new Stochastic Optimization approach based on a Tabu Search (TS), the Nelder Mead method or Downhill Simplex Method (NMDS) and the sequential process simulator HYSYS is used to search for better solutions for the Liquefied Energy Chain with respect to minimum cost or maximum profit. (au)

Knowledge base, information search and intention to adopt innovation

NARCIS (Netherlands)

Rijnsoever, van F.J.; Castaldi, C.

2008-01-01

Innovation is a process that involves searching for new information. This paper builds upon theoretical insights on individual and organizational learning and proposes a knowledge based model of how actors search for information when confronted with innovation. The model takes into account different

Development and Evaluation of Thesauri-Based Bibliographic Biomedical Search Engine

Science.gov (United States)

Alghoson, Abdullah

2017-01-01

Due to the large volume and exponential growth of biomedical documents (e.g., books, journal articles), it has become increasingly challenging for biomedical search engines to retrieve relevant documents based on users' search queries. Part of the challenge is the matching mechanism of free-text indexing that performs matching based on…

Energy/Reliability Trade-offs in Fault-Tolerant Event-Triggered Distributed Embedded Systems

DEFF Research Database (Denmark)

Gan, Junhe; Gruian, Flavius; Pop, Paul

2011-01-01

task, such that transient faults are tolerated, the timing constraints of the application are satisfied, and the energy consumed is minimized. Tasks are scheduled using fixed-priority preemptive scheduling, while replication is used for recovery from multiple transient faults. Addressing energy...... and reliability simultaneously is especially challenging, since lowering the voltage to reduce the energy consumption has been shown to increase the transient fault rate. We presented a Tabu Search-based approach which uses an energy/reliability trade-off model to find reliable and schedulable implementations...

SciRide Finder: a citation-based paradigm in biomedical literature search.

Science.gov (United States)

Volanakis, Adam; Krawczyk, Konrad

2018-04-18

There are more than 26 million peer-reviewed biomedical research items according to Medline/PubMed. This breadth of information is indicative of the progress in biomedical sciences on one hand, but an overload for scientists performing literature searches on the other. A major portion of scientific literature search is to find statements, numbers and protocols that can be cited to build an evidence-based narrative for a new manuscript. Because science builds on prior knowledge, such information has likely been written out and cited in an older manuscript. Thus, Cited Statements, pieces of text from scientific literature supported by citing other peer-reviewed publications, carry significant amount of condensed information on prior art. Based on this principle, we propose a literature search service, SciRide Finder (finder.sciride.org), which constrains the search corpus to such Cited Statements only. We demonstrate that Cited Statements can carry different information to this found in titles/abstracts and full text, giving access to alternative literature search results than traditional search engines. We further show how presenting search results as a list of Cited Statements allows researchers to easily find information to build an evidence-based narrative for their own manuscripts.

Object-based target templates guide attention during visual search.

Science.gov (United States)

Berggren, Nick; Eimer, Martin

2018-05-03

During visual search, attention is believed to be controlled in a strictly feature-based fashion, without any guidance by object-based target representations. To challenge this received view, we measured electrophysiological markers of attentional selection (N2pc component) and working memory (sustained posterior contralateral negativity; SPCN) in search tasks where two possible targets were defined by feature conjunctions (e.g., blue circles and green squares). Critically, some search displays also contained nontargets with two target features (incorrect conjunction objects, e.g., blue squares). Because feature-based guidance cannot distinguish these objects from targets, any selective bias for targets will reflect object-based attentional control. In Experiment 1, where search displays always contained only one object with target-matching features, targets and incorrect conjunction objects elicited identical N2pc and SPCN components, demonstrating that attentional guidance was entirely feature-based. In Experiment 2, where targets and incorrect conjunction objects could appear in the same display, clear evidence for object-based attentional control was found. The target N2pc became larger than the N2pc to incorrect conjunction objects from 250 ms poststimulus, and only targets elicited SPCN components. This demonstrates that after an initial feature-based guidance phase, object-based templates are activated when they are required to distinguish target and nontarget objects. These templates modulate visual processing and control access to working memory, and their activation may coincide with the start of feature integration processes. Results also suggest that while multiple feature templates can be activated concurrently, only a single object-based target template can guide attention at any given time. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

An optimization algorithm for a capacitated vehicle routing problem ...

Indian Academy of Sciences (India)

In this paper, vehicle routing problem (VRP) with time windows and real world constraints are considered as a real-world application on google maps. Also, tabu search is used and Hopfield neural networks is utilized. Basic constraints consist of customer demands, time windows, vehicle speed, vehicle capacity andworking ...

Disruption management of the vehicle routing problem with vehicle breakdown

DEFF Research Database (Denmark)

Mu, Q; Fu, Z; Lysgaard, Jens

2011-01-01

solution needs to be quickly generated to minimise the costs. Two Tabu Search algorithms are developed to solve the problem and are assessed in relation to an exact algorithm. A set of test problems has been generated and computational results from experiments using the heuristic algorithms are presented....

Teaching AI Search Algorithms in a Web-Based Educational System

Science.gov (United States)

Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis

2013-01-01

In this paper, we present a way of teaching AI search algorithms in a web-based adaptive educational system. Teaching is based on interactive examples and exercises. Interactive examples, which use visualized animations to present AI search algorithms in a step-by-step way with explanations, are used to make learning more attractive. Practice…

GeNemo: a search engine for web-based functional genomic data.

Science.gov (United States)

Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng

2016-07-08

A set of new data types emerged from functional genomic assays, including ChIP-seq, DNase-seq, FAIRE-seq and others. The results are typically stored as genome-wide intensities (WIG/bigWig files) or functional genomic regions (peak/BED files). These data types present new challenges to big data science. Here, we present GeNemo, a web-based search engine for functional genomic data. GeNemo searches user-input data against online functional genomic datasets, including the entire collection of ENCODE and mouse ENCODE datasets. Unlike text-based search engines, GeNemo's searches are based on pattern matching of functional genomic regions. This distinguishes GeNemo from text or DNA sequence searches. The user can input any complete or partial functional genomic dataset, for example, a binding intensity file (bigWig) or a peak file. GeNemo reports any genomic regions, ranging from hundred bases to hundred thousand bases, from any of the online ENCODE datasets that share similar functional (binding, modification, accessibility) patterns. This is enabled by a Markov Chain Monte Carlo-based maximization process, executed on up to 24 parallel computing threads. By clicking on a search result, the user can visually compare her/his data with the found datasets and navigate the identified genomic regions. GeNemo is available at www.genemo.org. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Q-learning-based adjustable fixed-phase quantum Grover search algorithm

International Nuclear Information System (INIS)

Guo Ying; Shi Wensha; Wang Yijun; Hu, Jiankun

2017-01-01

We demonstrate that the rotation phase can be suitably chosen to increase the efficiency of the phase-based quantum search algorithm, leading to a dynamic balance between iterations and success probabilities of the fixed-phase quantum Grover search algorithm with Q-learning for a given number of solutions. In this search algorithm, the proposed Q-learning algorithm, which is a model-free reinforcement learning strategy in essence, is used for performing a matching algorithm based on the fraction of marked items λ and the rotation phase α. After establishing the policy function α = π(λ), we complete the fixed-phase Grover algorithm, where the phase parameter is selected via the learned policy. Simulation results show that the Q-learning-based Grover search algorithm (QLGA) enables fewer iterations and gives birth to higher success probabilities. Compared with the conventional Grover algorithms, it avoids the optimal local situations, thereby enabling success probabilities to approach one. (author)

Search-based model identification of smart-structure damage

Science.gov (United States)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Parallel content-based sub-image retrieval using hierarchical searching.

Science.gov (United States)

Yang, Lin; Qi, Xin; Xing, Fuyong; Kurc, Tahsin; Saltz, Joel; Foran, David J

2014-04-01

The capacity to systematically search through large image collections and ensembles and detect regions exhibiting similar morphological characteristics is central to pathology diagnosis. Unfortunately, the primary methods used to search digitized, whole-slide histopathology specimens are slow and prone to inter- and intra-observer variability. The central objective of this research was to design, develop, and evaluate a content-based image retrieval system to assist doctors for quick and reliable content-based comparative search of similar prostate image patches. Given a representative image patch (sub-image), the algorithm will return a ranked ensemble of image patches throughout the entire whole-slide histology section which exhibits the most similar morphologic characteristics. This is accomplished by first performing hierarchical searching based on a newly developed hierarchical annular histogram (HAH). The set of candidates is then further refined in the second stage of processing by computing a color histogram from eight equally divided segments within each square annular bin defined in the original HAH. A demand-driven master-worker parallelization approach is employed to speed up the searching procedure. Using this strategy, the query patch is broadcasted to all worker processes. Each worker process is dynamically assigned an image by the master process to search for and return a ranked list of similar patches in the image. The algorithm was tested using digitized hematoxylin and eosin (H&E) stained prostate cancer specimens. We have achieved an excellent image retrieval performance. The recall rate within the first 40 rank retrieved image patches is ∼90%. Both the testing data and source code can be downloaded from http://pleiad.umdnj.edu/CBII/Bioinformatics/.

A Hybrid Algorithm for Optimizing Multi- Modal Functions

Institute of Scientific and Technical Information of China (English)

Li Qinghua; Yang Shida; Ruan Youlin

2006-01-01

A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which increases the robustness of it greatly and gives a new meaning of it in the meantime, has been developed. Combining the advantages of the new genetic algorithm, simplex algorithm and tabu search, a hybrid algorithm is proposed. In order to verify the effectiveness of the hybrid algorithm, it is applied to solving some typical numerical function optimization problems which are poorly solved by traditional genetic algorithms. The experimental results show that the hybrid algorithm is fast and reliable.

The in-core fuel management code system for VVER reactors

International Nuclear Information System (INIS)

Cada, R.; Krysl, V.; Mikolas, P.; Sustek, J.; Svarny, J.

2004-01-01

The structure and methodology of a fuel management system for NPP VVER 1000 (NPP Temelin) and VVER 440 (NPP Dukovany) is described. It is under development in SKODA JS a.s. and is followed by practical applications. The general objectives of the system are maximization of end of cycle reactivity, the minimization of fresh fuel inventory for the minimization of fed enrichment and minimization of burnable poisons (BPs) inventory. They are also safety related constraints in witch minimization of power peaking plays a dominant role. General structure of the system consists in preparation of input data for macrocode calculation, algorithms (codes) for optimization of fuel loading, calculation of fuel enrichment and BPs assignment. At present core loading can be calculated (optimized) by Tabu search algorithm (code ATHENA), genetic algorithm (code Gen1) and hybrid algorithm - simplex procedure with application of Tabu search algorithm on binary shuffling (code OPAL B ). Enrichment search is realized by the application of simplex algorithm (OPAL B code) and BPs assignment by module BPASS and simplex algorithm in OPAL B code. Calculations of the real core loadings are presented and a comparison of different optimization methods is provided. (author)

Network-based Type-2 Fuzzy System with Water Flow Like Algorithm for System Identification and Signal Processing

Directory of Open Access Journals (Sweden)

Che-Ting Kuo

2015-02-01

Full Text Available This paper introduces a network-based interval type-2 fuzzy inference system (NT2FIS with a dynamic solution agent algorithm water flow like algorithm (WFA, for nonlinear system identification and blind source separation (BSS problem. The NT2FIS consists of interval type-2 asymmetric fuzzy membership functions and TSK-type consequent parts to enhance the performance. The proposed scheme is optimized by a new heuristic learning algorithm, WFA, with dynamic solution agents. The proposed WFA is inspired by the natural behavior of water flow. Splitting, moving, merging, evaporation, and precipitation have all been introduced for optimization. Some modifications, including new moving strategies, such as the application of tabu searching and gradient-descent techniques, are proposed to enhance the performance of the WFA in training the NT2FIS systems. Simulation and comparison results for nonlinear system identification and blind signal separation are presented to illustrate the performance and effectiveness of the proposed approach.

SOCIAL NETWORK OPTIMIZATION A NEW METHAHEURISTIC FOR GENERAL OPTIMIZATION PROBLEMS

Directory of Open Access Journals (Sweden)

Hassan Sherafat

2017-12-01

Full Text Available In the recent years metaheuristics were studied and developed as powerful technics for hard optimization problems. Some of well-known technics in this field are: Genetic Algorithms, Tabu Search, Simulated Annealing, Ant Colony Optimization, and Swarm Intelligence, which are applied successfully to many complex optimization problems. In this paper, we introduce a new metaheuristic for solving such problems based on social networks concept, named as Social Network Optimization – SNO. We show that a wide range of np-hard optimization problems may be solved by SNO.

AN OVERVIEW OF SEARCHING AND DISCOVERING WEB BASED INFORMATION RESOURCES

Directory of Open Access Journals (Sweden)

Cezar VASILESCU

2010-01-01

Full Text Available The Internet becomes for most of us a daily used instrument, for professional or personal reasons. We even do not remember the times when a computer and a broadband connection were luxury items. More and more people are relying on the complicated web network to find the needed information.This paper presents an overview of Internet search related issues, upon search engines and describes the parties and the basic mechanism that is embedded in a search for web based information resources. Also presents ways to increase the efficiency of web searches, through a better understanding of what search engines ignore at websites content.

Optimal Routing for Heterogeneous Fixed Fleets of Multicompartment Vehicles

OpenAIRE

Wang, Qian; Ji, Qingkai; Chiu, Chun-Hung

2014-01-01

We present a metaheuristic called the reactive guided tabu search (RGTS) to solve the heterogeneous fleet multicompartment vehicle routing problem (MCVRP), where a single vehicle is required for cotransporting multiple customer orders. MCVRP is commonly found in delivery of fashion apparel, petroleum distribution, food distribution, and waste collection. In searching the optimum solution of MCVRP, we need to handle a large amount of local optima in the solution spaces. To overcome this proble...

A GIS-based Quantitative Approach for the Search of Clandestine Graves, Italy.

Science.gov (United States)

Somma, Roberta; Cascio, Maria; Silvestro, Massimiliano; Torre, Eliana

2018-05-01

Previous research on the RAG color-coded prioritization systems for the discovery of clandestine graves has not considered all the factors influencing the burial site choice within a GIS project. The goal of this technical note was to discuss a GIS-based quantitative approach for the search of clandestine graves. The method is based on cross-referenced RAG maps with cumulative suitability factors to host a burial, leading to the editing of different search scenarios for ground searches showing high-(Red), medium-(Amber), and low-(Green) priority areas. The application of this procedure allowed several outcomes to be determined: If the concealment occurs at night, then the "search scenario without the visibility" will be the most effective one; if the concealment occurs in daylight, then the "search scenario with the DSM-based visibility" will be most appropriate; the different search scenarios may be cross-referenced with offender's confessions and eyewitnesses' testimonies to verify the veracity of their statements. © 2017 American Academy of Forensic Sciences.

Search for brown dwarfs in the IRAS data bases

International Nuclear Information System (INIS)

Low, F.J.

1986-01-01

A report is given on the initial searches for brown dwarf stars in the IRAS data bases. The paper was presented to the workshop on 'Astrophysics of brown dwarfs', Virginia, USA, 1985. To date no brown dwarfs have been discovered in the solar neighbourhood. Opportunities for future searches with greater sensitivity and different wavelengths are outlined. (U.K.)

Impact of discretization of the decision variables in the search of optimized solutions for history matching and injection rate optimization; Impacto do uso de variaveis discretas na busca de solucoes otimizadas para o ajuste de historico e distribuicao de vazoes de injecao

Energy Technology Data Exchange (ETDEWEB)

Sousa, Sergio H.G. de; Madeira, Marcelo G. [Halliburton Servicos Ltda., Rio de Janeiro, RJ (Brazil)

2008-07-01

In the classical operations research arena, there is the notion that the search for optimized solutions in continuous solution spaces is easier than on discrete solution spaces, even when the latter is a subset of the first. On the upstream oil industry, there is an additional complexity in the optimization problems because there usually are no analytical expressions for the objective function, which require some form of simulation in order to be evaluated. Thus, the use of meta heuristic optimizers like scatter search, tabu search and genetic algorithms is common. In this meta heuristic context, there are advantages in transforming continuous solution spaces in equivalent discrete ones; the goal to do so usually is to speed up the search for optimized solutions. However, these advantages can be masked when the problem has restrictions formed by linear combinations of its decision variables. In order to study these aspects of meta heuristic optimization, two optimization problems are proposed and solved with both continuous and discrete solution spaces: assisted history matching and injection rates optimization. Both cases operate on a model of the Wytch Farm onshore oil filed located in England. (author)

Pathfinder: multiresolution region-based searching of pathology images using IRM.

OpenAIRE

Wang, J. Z.

2000-01-01

The fast growth of digitized pathology slides has created great challenges in research on image database retrieval. The prevalent retrieval technique involves human-supplied text annotations to describe slide contents. These pathology images typically have very high resolution, making it difficult to search based on image content. In this paper, we present Pathfinder, an efficient multiresolution region-based searching system for high-resolution pathology image libraries. The system uses wave...

Multilevel Thresholding Segmentation Based on Harmony Search Optimization

Directory of Open Access Journals (Sweden)

Diego Oliva

2013-01-01

Full Text Available In this paper, a multilevel thresholding (MT algorithm based on the harmony search algorithm (HSA is introduced. HSA is an evolutionary method which is inspired in musicians improvising new harmonies while playing. Different to other evolutionary algorithms, HSA exhibits interesting search capabilities still keeping a low computational overhead. The proposed algorithm encodes random samples from a feasible search space inside the image histogram as candidate solutions, whereas their quality is evaluated considering the objective functions that are employed by the Otsu’s or Kapur’s methods. Guided by these objective values, the set of candidate solutions are evolved through the HSA operators until an optimal solution is found. Experimental results demonstrate the high performance of the proposed method for the segmentation of digital images.

Quantum signature scheme based on a quantum search algorithm

International Nuclear Information System (INIS)

Yoon, Chun Seok; Kang, Min Sung; Lim, Jong In; Yang, Hyung Jin

2015-01-01

We present a quantum signature scheme based on a two-qubit quantum search algorithm. For secure transmission of signatures, we use a quantum search algorithm that has not been used in previous quantum signature schemes. A two-step protocol secures the quantum channel, and a trusted center guarantees non-repudiation that is similar to other quantum signature schemes. We discuss the security of our protocol. (paper)

An efficient heuristic for the multi-compartment vehicle routing problem

OpenAIRE

Paulo Vitor Silvestrin

2016-01-01

We study a variant of the vehicle routing problem that allows vehicles with multiple compartments. The need for multiple compartments frequently arises in practical applications when there are several products of different quality or type, that must be kept or handled separately. The resulting problem is called the multi-compartment vehicle routing problem (MCVRP). We propose a tabu search heuristic and embed it into an iterated local search to solve the MCVRP. In several experiments we analy...

Novel citation-based search method for scientific literature: application to meta-analyses

NARCIS (Netherlands)

Janssens, A.C.J.W.; Gwinn, M.

2015-01-01

Background: Finding eligible studies for meta-analysis and systematic reviews relies on keyword-based searching as the gold standard, despite its inefficiency. Searching based on direct citations is not sufficiently comprehensive. We propose a novel strategy that ranks articles on their degree of

Order Tracking Based on Robust Peak Search Instantaneous Frequency Estimation

International Nuclear Information System (INIS)

Gao, Y; Guo, Y; Chi, Y L; Qin, S R

2006-01-01

Order tracking plays an important role in non-stationary vibration analysis of rotating machinery, especially to run-up or coast down. An instantaneous frequency estimation (IFE) based order tracking of rotating machinery is introduced. In which, a peak search algorithms of spectrogram of time-frequency analysis is employed to obtain IFE of vibrations. An improvement to peak search is proposed, which can avoid strong non-order components or noises disturbing to the peak search work. Compared with traditional methods of order tracking, IFE based order tracking is simplified in application and only software depended. Testing testify the validity of the method. This method is an effective supplement to traditional methods, and the application in condition monitoring and diagnosis of rotating machinery is imaginable

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.

Science.gov (United States)

Azman, Syafiq Kamarul; Anwar, Muhammad Zohaib; Henschel, Andreas

2017-07-24

Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database. Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.

Update on CERN Search based on SharePoint 2013

Science.gov (United States)

Alvarez, E.; Fernandez, S.; Lossent, A.; Posada, I.; Silva, B.; Wagner, A.

2017-10-01

CERN’s enterprise Search solution “CERN Search” provides a central search solution for users and CERN service providers. A total of about 20 million public and protected documents from a wide range of document collections is indexed, including Indico, TWiki, Drupal, SharePoint, JACOW, E-group archives, EDMS, and CERN Web pages. In spring 2015, CERN Search was migrated to a new infrastructure based on SharePoint 2013. In the context of this upgrade, the document pre-processing and indexing process was redesigned and generalised. The new data feeding framework allows to profit from new functionality and it facilitates the long term maintenance of the system.

Tales from the Field: Search Strategies Applied in Web Searching

Directory of Open Access Journals (Sweden)

Soohyung Joo

2010-08-01

Full Text Available In their web search processes users apply multiple types of search strategies, which consist of different search tactics. This paper identifies eight types of information search strategies with associated cases based on sequences of search tactics during the information search process. Thirty-one participants representing the general public were recruited for this study. Search logs and verbal protocols offered rich data for the identification of different types of search strategies. Based on the findings, the authors further discuss how to enhance web-based information retrieval (IR systems to support each type of search strategy.

Search Method Based on Figurative Indexation of Folksonomic Features of Graphic Files

Directory of Open Access Journals (Sweden)

Oleg V. Bisikalo

2013-11-01

Full Text Available In this paper the search method based on usage of figurative indexation of folksonomic characteristics of graphical files is described. The method takes into account extralinguistic information, is based on using a model of figurative thinking of humans. The paper displays the creation of a method of searching image files based on their formal, including folksonomical clues.

Clinician search behaviors may be influenced by search engine design.

Science.gov (United States)

Lau, Annie Y S; Coiera, Enrico; Zrimec, Tatjana; Compton, Paul

2010-06-30

Searching the Web for documents using information retrieval systems plays an important part in clinicians' practice of evidence-based medicine. While much research focuses on the design of methods to retrieve documents, there has been little examination of the way different search engine capabilities influence clinician search behaviors. Previous studies have shown that use of task-based search engines allows for faster searches with no loss of decision accuracy compared with resource-based engines. We hypothesized that changes in search behaviors may explain these differences. In all, 75 clinicians (44 doctors and 31 clinical nurse consultants) were randomized to use either a resource-based or a task-based version of a clinical information retrieval system to answer questions about 8 clinical scenarios in a controlled setting in a university computer laboratory. Clinicians using the resource-based system could select 1 of 6 resources, such as PubMed; clinicians using the task-based system could select 1 of 6 clinical tasks, such as diagnosis. Clinicians in both systems could reformulate search queries. System logs unobtrusively capturing clinicians' interactions with the systems were coded and analyzed for clinicians' search actions and query reformulation strategies. The most frequent search action of clinicians using the resource-based system was to explore a new resource with the same query, that is, these clinicians exhibited a "breadth-first" search behaviour. Of 1398 search actions, clinicians using the resource-based system conducted 401 (28.7%, 95% confidence interval [CI] 26.37-31.11) in this way. In contrast, the majority of clinicians using the task-based system exhibited a "depth-first" search behavior in which they reformulated query keywords while keeping to the same task profiles. Of 585 search actions conducted by clinicians using the task-based system, 379 (64.8%, 95% CI 60.83-68.55) were conducted in this way. This study provides evidence that

Two efficient heuristics to solve the integrated load distribution and production planning problem

International Nuclear Information System (INIS)

Gajpal, Yuvraj; Nourelfath, Mustapha

2015-01-01

This paper considers a multi-period production system where a set of machines are arranged in parallel. The machines are unreliable and the failure rate of machine depends on the load assigned to the machine. The expected production rate of the system is considered to be a non-monotonic function of its load. Because of the machine failure rate, the total production output depends on the combination of loads assigned to different machines. We consider the integration of load distribution decisions with production planning decision. The product demands are considered to be known in advance. The objective is to minimize the sum of holding costs, backorder costs, production costs, setup costs, capacity change costs and unused capacity costs while satisfying the demand over specified time horizon. The constraint is not to exceed available repair resources required to repair the machine breakdown. The paper develops two heuristics to solve the integrated load distribution and production planning problem. The first heuristic consists of a three-phase approach, while the second one is based on tabu search metaheuristic. The efficiency of the proposed heuristics is tested through the randomly generated problem instances. - Highlights: • The expected performance of the system is a non-monotonic function of its load. • We consider the integration of load distribution and production planning decisions. • The paper proposes three phase and tabu search based heuristics to solve the problem. • Lower bound has been developed for checking the effectiveness of the heuristics. • The efficiency of the heuristic is tested through randomly generated instances.

A Full-Text-Based Search Engine for Finding Highly Matched Documents Across Multiple Categories

Science.gov (United States)

Nguyen, Hung D.; Steele, Gynelle C.

2016-01-01

This report demonstrates the full-text-based search engine that works on any Web-based mobile application. The engine has the capability to search databases across multiple categories based on a user's queries and identify the most relevant or similar. The search results presented here were found using an Android (Google Co.) mobile device; however, it is also compatible with other mobile phones.

A product feature-based user-centric product search model

OpenAIRE

Ben Jabeur, Lamjed; Soulier, Laure; Tamine, Lynda; Mousset, Paul

2016-01-01

During the online shopping process, users would search for interesting products and quickly access those that fit with their needs among a long tail of similar or closely related products. Our contribution addresses head queries that are frequently submitted on e-commerce Web sites. Head queries usually target featured products with several variations, accessories, and complementary products. We present in this paper a product feature-based user-centric model for product search involving in a...

Metaheuristic algorithms for building Covering Arrays: A review

Directory of Open Access Journals (Sweden)

Jimena Adriana Timaná-Peña

2016-09-01

Full Text Available Covering Arrays (CA are mathematical objects used in the functional testing of software components. They enable the testing of all interactions of a given size of input parameters in a procedure, function, or logical unit in general, using the minimum number of test cases. Building CA is a complex task (NP-complete problem that involves lengthy execution times and high computational loads. The most effective methods for building CAs are algebraic, Greedy, and metaheuristic-based. The latter have reported the best results to date. This paper presents a description of the major contributions made by a selection of different metaheuristics, including simulated annealing, tabu search, genetic algorithms, ant colony algorithms, particle swarm algorithms, and harmony search algorithms. It is worth noting that simulated annealing-based algorithms have evolved as the most competitive, and currently form the state of the art.

Architecture for knowledge-based and federated search of online clinical evidence.

Science.gov (United States)

Coiera, Enrico; Walther, Martin; Nguyen, Ken; Lovell, Nigel H

2005-10-24

It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Clinicians performed 1662 searches over the trial. The average search duration was 4.9 +/- 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the

An Advanced Tabu Search Approach to the Airlift Loading Problem

Science.gov (United States)

2006-12-01

Problem Statement................................................................ 37 3.1.1 SALP -TS Inputs...41 3.2.1 SALP -TS Data Structures .......................................................... 41 3.2.2 SALP -TS Solution...3.2.4 SALP Lower Bound ................................................................... 46 3.2.5 Initial Solution Generator

A Tabu Search Algorithm for application placement in computer clustering

NARCIS (Netherlands)

van der Gaast, Jelmer; Rietveld, Cornelieus A.; Gabor, Adriana; Zhang, Yingqian

2014-01-01

This paper presents and analyzes a model for the problem of placing applications on computer clusters (APP). In this problem, organizations requesting a set of software applications have to be assigned to computer clusters such that the costs of opening clusters and installing the necessary

Optimizing Re-planning Operation for Smart House Applying Solar Radiation Forecasting

Directory of Open Access Journals (Sweden)

Atsushi Yona

2014-08-01

Full Text Available This paper proposes the re-planning operation method using Tabu Search for direct current (DC smart house with photovoltaic (PV, solar collector (SC, battery and heat pump system. The proposed method is based on solar radiation forecasting using reported weather data, Fuzzy theory and Recurrent Neural Network. Additionally, the re-planning operation method is proposed with consideration of solar radiation forecast error, battery and inverter losses. In this paper, it is assumed that the installation location for DC smart house is Okinawa, which is located in Southwest Japan. The validity of proposed method is confirmed by comparing the simulation results.

Proceedings of the ECIR 2012 Workshop on Task-Based and Aggregated Search (TBAS2012)

DEFF Research Database (Denmark)

2012-01-01

Task-based search aims to understand the user's current task and desired outcomes, and how this may provide useful context for the Information Retrieval (IR) process. An example of task-based search is situations where additional user information on e.g. the purpose of the search or what the user...

Global polar geospatial information service retrieval based on search engine and ontology reasoning

Science.gov (United States)

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

Inference-Based Similarity Search in Randomized Montgomery Domains for Privacy-Preserving Biometric Identification.

Science.gov (United States)

Wang, Yi; Wan, Jianwu; Guo, Jun; Cheung, Yiu-Ming; C Yuen, Pong

2017-07-14

Similarity search is essential to many important applications and often involves searching at scale on high-dimensional data based on their similarity to a query. In biometric applications, recent vulnerability studies have shown that adversarial machine learning can compromise biometric recognition systems by exploiting the biometric similarity information. Existing methods for biometric privacy protection are in general based on pairwise matching of secured biometric templates and have inherent limitations in search efficiency and scalability. In this paper, we propose an inference-based framework for privacy-preserving similarity search in Hamming space. Our approach builds on an obfuscated distance measure that can conceal Hamming distance in a dynamic interval. Such a mechanism enables us to systematically design statistically reliable methods for retrieving most likely candidates without knowing the exact distance values. We further propose to apply Montgomery multiplication for generating search indexes that can withstand adversarial similarity analysis, and show that information leakage in randomized Montgomery domains can be made negligibly small. Our experiments on public biometric datasets demonstrate that the inference-based approach can achieve a search accuracy close to the best performance possible with secure computation methods, but the associated cost is reduced by orders of magnitude compared to cryptographic primitives.

Optimization in optical systems revisited: Beyond genetic algorithms

Science.gov (United States)

Gagnon, Denis; Dumont, Joey; Dubé, Louis

2013-05-01

Designing integrated photonic devices such as waveguides, beam-splitters and beam-shapers often requires optimization of a cost function over a large solution space. Metaheuristics - algorithms based on empirical rules for exploring the solution space - are specifically tailored to those problems. One of the most widely used metaheuristics is the standard genetic algorithm (SGA), based on the evolution of a population of candidate solutions. However, the stochastic nature of the SGA sometimes prevents access to the optimal solution. Our goal is to show that a parallel tabu search (PTS) algorithm is more suited to optimization problems in general, and to photonics in particular. PTS is based on several search processes using a pool of diversified initial solutions. To assess the performance of both algorithms (SGA and PTS), we consider an integrated photonics design problem, the generation of arbitrary beam profiles using a two-dimensional waveguide-based dielectric structure. The authors acknowledge financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC).

TOWARDS A UNIFIED VIEW OF METAHEURISTICS

Directory of Open Access Journals (Sweden)

El-Ghazali Talbi

2013-02-01

Full Text Available This talk provides a complete background on metaheuristics and presents in a unified view the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. The key search components of metaheuristics are considered as a toolbox for: - Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems for optimization problems. - Designing efficient metaheuristics for multi-objective optimization problems. - Designing hybrid, parallel and distributed metaheuristics. - Implementing metaheuristics on sequential and parallel machines.

SearchResultFinder: federated search made easy

NARCIS (Netherlands)

Trieschnigg, Rudolf Berend; Tjin-Kam-Jet, Kien; Hiemstra, Djoerd

Building a federated search engine based on a large number existing web search engines is a challenge: implementing the programming interface (API) for each search engine is an exacting and time-consuming job. In this demonstration we present SearchResultFinder, a browser plugin which speeds up

Computer-Assisted Search Of Large Textual Data Bases

Science.gov (United States)

Driscoll, James R.

1995-01-01

"QA" denotes high-speed computer system for searching diverse collections of documents including (but not limited to) technical reference manuals, legal documents, medical documents, news releases, and patents. Incorporates previously available and emerging information-retrieval technology to help user intelligently and rapidly locate information found in large textual data bases. Technology includes provision for inquiries in natural language; statistical ranking of retrieved information; artificial-intelligence implementation of semantics, in which "surface level" knowledge found in text used to improve ranking of retrieved information; and relevance feedback, in which user's judgements of relevance of some retrieved documents used automatically to modify search for further information.

OS2: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain

Science.gov (United States)

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem

2017-01-01

Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search (OS2) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, OS2 ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables OS2 to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of OS2 is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations. PMID:28692697

Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

Science.gov (United States)

Rusu, Teodora; Gogan, Oana Marilena

2016-05-01

This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

Personalizing Web Search based on User Profile

OpenAIRE

Utage, Sharyu; Ahire, Vijaya

2016-01-01

Web Search engine is most widely used for information retrieval from World Wide Web. These Web Search engines help user to find most useful information. When different users Searches for same information, search engine provide same result without understanding who is submitted that query. Personalized web search it is search technique for proving useful result. This paper models preference of users as hierarchical user profiles. a framework is proposed called UPS. It generalizes profile and m...

Noesis: Ontology based Scoped Search Engine and Resource Aggregator for Atmospheric Science

Science.gov (United States)

Ramachandran, R.; Movva, S.; Li, X.; Cherukuri, P.; Graves, S.

2006-12-01

The goal for search engines is to return results that are both accurate and complete. The search engines should find only what you really want and find everything you really want. Search engines (even meta search engines) lack semantics. The basis for search is simply based on string matching between the user's query term and the resource database and the semantics associated with the search string is not captured. For example, if an atmospheric scientist is searching for "pressure" related web resources, most search engines return inaccurate results such as web resources related to blood pressure. In this presentation Noesis, which is a meta-search engine and a resource aggregator that uses domain ontologies to provide scoped search capabilities will be described. Noesis uses domain ontologies to help the user scope the search query to ensure that the search results are both accurate and complete. The domain ontologies guide the user to refine their search query and thereby reduce the user's burden of experimenting with different search strings. Semantics are captured by refining the query terms to cover synonyms, specializations, generalizations and related concepts. Noesis also serves as a resource aggregator. It categorizes the search results from different online resources such as education materials, publications, datasets, web search engines that might be of interest to the user.

The role of space and time in object-based visual search

NARCIS (Netherlands)

Schreij, D.B.B.; Olivers, C.N.L.

2013-01-01

Recently we have provided evidence that observers more readily select a target from a visual search display if the motion trajectory of the display object suggests that the observer has dealt with it before. Here we test the prediction that this object-based memory effect on search breaks down if

Differential Search Coils Based Magnetometers: Conditioning, Magnetic Sensitivity, Spatial Resolution

Directory of Open Access Journals (Sweden)

Timofeeva Maria

2012-03-01

Full Text Available A theoretical and experimental comparison of optimized search coils based magnetometers, operating either in the Flux mode or in the classical Lenz-Faraday mode, is presented. The improvements provided by the Flux mode in terms of bandwidth and measuring range of the sensor are detailed. Theory, SPICE model and measurements are in good agreement. The spatial resolution of the sensor is studied which is an important parameter for applications in non destructive evaluation. A general expression of the magnetic sensitivity of search coils sensors is derived. Solutions are proposed to design magnetometers with reduced weight and volume without degrading the magnetic sensitivity. An original differential search coil based magnetometer, made of coupled coils, operating in flux mode and connected to a differential transimpedance amplifier is proposed. It is shown that this structure is better in terms of volume occupancy than magnetometers using two separated coils without any degradation in magnetic sensitivity. Experimental results are in good agreement with calculations.

Optimal Search Strategy of Robotic Assembly Based on Neural Vibration Learning

Directory of Open Access Journals (Sweden)

Lejla Banjanovic-Mehmedovic

2011-01-01

Full Text Available This paper presents implementation of optimal search strategy (OSS in verification of assembly process based on neural vibration learning. The application problem is the complex robot assembly of miniature parts in the example of mating the gears of one multistage planetary speed reducer. Assembly of tube over the planetary gears was noticed as the most difficult problem of overall assembly. The favourable influence of vibration and rotation movement on compensation of tolerance was also observed. With the proposed neural-network-based learning algorithm, it is possible to find extended scope of vibration state parameter. Using optimal search strategy based on minimal distance path between vibration parameter stage sets (amplitude and frequencies of robots gripe vibration and recovery parameter algorithm, we can improve the robot assembly behaviour, that is, allow the fastest possible way of mating. We have verified by using simulation programs that search strategy is suitable for the situation of unexpected events due to uncertainties.

ONTOLOGY BASED MEANINGFUL SEARCH USING SEMANTIC WEB AND NATURAL LANGUAGE PROCESSING TECHNIQUES

Directory of Open Access Journals (Sweden)

K. Palaniammal

2013-10-01

Full Text Available The semantic web extends the current World Wide Web by adding facilities for the machine understood description of meaning. The ontology based search model is used to enhance efficiency and accuracy of information retrieval. Ontology is the core technology for the semantic web and this mechanism for representing formal and shared domain descriptions. In this paper, we proposed ontology based meaningful search using semantic web and Natural Language Processing (NLP techniques in the educational domain. First we build the educational ontology then we present the semantic search system. The search model consisting three parts which are embedding spell-check, finding synonyms using WordNet API and querying ontology using SPARQL language. The results are both sensitive to spell check and synonymous context. This paper provides more accurate results and the complete details for the selected field in a single page.

A semantics-based method for clustering of Chinese web search results

Science.gov (United States)

Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

2014-01-01

Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

XSemantic: An Extension of LCA Based XML Semantic Search

Science.gov (United States)

Supasitthimethee, Umaporn; Shimizu, Toshiyuki; Yoshikawa, Masatoshi; Porkaew, Kriengkrai

One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge of XML structure or learning a new user interface. However, the keyword search is ambiguous. The users may use different terms to search for the same information. Furthermore, it is difficult for a system to decide which node is likely to be chosen as a return node and how much information should be included in the result. To address these challenges, we propose an XML semantic search based on keywords called XSemantic. On the one hand, we give three definitions to complete in terms of semantics. Firstly, the semantic term expansion, our system is robust from the ambiguous keywords by using the domain ontology. Secondly, to return semantic meaningful answers, we automatically infer the return information from the user queries and take advantage of the shortest path to return meaningful connections between keywords. Thirdly, we present the semantic ranking that reflects the degree of similarity as well as the semantic relationship so that the search results with the higher relevance are presented to the users first. On the other hand, in the LCA and the proximity search approaches, we investigated the problem of information included in the search results. Therefore, we introduce the notion of the Lowest Common Element Ancestor (LCEA) and define our simple rule without any requirement on the schema information such as the DTD or XML Schema. The first experiment indicated that XSemantic not only properly infers the return information but also generates compact meaningful results. Additionally, the benefits of our proposed semantics are demonstrated by the second experiment.

Extended-Search, Bézier Curve-Based Lane Detection and Reconstruction System for an Intelligent Vehicle

Directory of Open Access Journals (Sweden)

Xiaoyun Huang

2015-09-01

Full Text Available To improve the real-time performance and detection rate of a Lane Detection and Reconstruction (LDR system, an extended-search-based lane detection method and a Bézier curve-based lane reconstruction algorithm are proposed in this paper. The extended-search-based lane detection method is designed to search boundary blocks from the initial position, in an upwards direction and along the lane, with small search areas including continuous search, discontinuous search and bending search in order to detect different lane boundaries. The Bézier curve-based lane reconstruction algorithm is employed to describe a wide range of lane boundary forms with comparatively simple expressions. In addition, two Bézier curves are adopted to reconstruct the lanes' outer boundaries with large curvature variation. The lane detection and reconstruction algorithm — including initial-blocks' determining, extended search, binarization processing and lane boundaries' fitting in different scenarios — is verified in road tests. The results show that this algorithm is robust against different shadows and illumination variations; the average processing time per frame is 13 ms. Significantly, it presents an 88.6% high-detection rate on curved lanes with large or variable curvatures, where the accident rate is higher than that of straight lanes.

CAST: a new program package for the accurate characterization of large and flexible molecular systems.

Science.gov (United States)

Grebner, Christoph; Becker, Johannes; Weber, Daniel; Bellinger, Daniel; Tafipolski, Maxim; Brückner, Charlotte; Engels, Bernd

2014-09-15

The presented program package, Conformational Analysis and Search Tool (CAST) allows the accurate treatment of large and flexible (macro) molecular systems. For the determination of thermally accessible minima CAST offers the newly developed TabuSearch algorithm, but algorithms such as Monte Carlo (MC), MC with minimization, and molecular dynamics are implemented as well. For the determination of reaction paths, CAST provides the PathOpt, the Nudge Elastic band, and the umbrella sampling approach. Access to free energies is possible through the free energy perturbation approach. Along with a number of standard force fields, a newly developed symmetry-adapted perturbation theory-based force field is included. Semiempirical computations are possible through DFTB+ and MOPAC interfaces. For calculations based on density functional theory, a Message Passing Interface (MPI) interface to the Graphics Processing Unit (GPU)-accelerated TeraChem program is available. The program is available on request. Copyright © 2014 Wiley Periodicals, Inc.

Tag-Based Social Image Search: Toward Relevant and Diverse Results

Science.gov (United States)

Yang, Kuiyuan; Wang, Meng; Hua, Xian-Sheng; Zhang, Hong-Jiang

Recent years have witnessed a great success of social media websites. Tag-based image search is an important approach to access the image content of interest on these websites. However, the existing ranking methods for tag-based image search frequently return results that are irrelevant or lack of diversity. This chapter presents a diverse relevance ranking scheme which simultaneously takes relevance and diversity into account by exploring the content of images and their associated tags. First, it estimates the relevance scores of images with respect to the query term based on both visual information of images and semantic information of associated tags. Then semantic similarities of social images are estimated based on their tags. Based on the relevance scores and the similarities, the ranking list is generated by a greedy ordering algorithm which optimizes Average Diverse Precision (ADP), a novel measure that is extended from the conventional Average Precision (AP). Comprehensive experiments and user studies demonstrate the effectiveness of the approach.

Snippet-based relevance predictions for federated web search

NARCIS (Netherlands)

Demeester, Thomas; Nguyen, Dong-Phuong; Trieschnigg, Rudolf Berend; Develder, Chris; Hiemstra, Djoerd

How well can the relevance of a page be predicted, purely based on snippets? This would be highly useful in a Federated Web Search setting where caching large amounts of result snippets is more feasible than caching entire pages. The experiments reported in this paper make use of result snippets and

Composition-based statistics and translated nucleotide searches: Improving the TBLASTN module of BLAST

Directory of Open Access Journals (Sweden)

Schäffer Alejandro A

2006-12-01

Full Text Available Abstract Background TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server. Results We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy. Conclusion TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms.

Particle Swarm Optimization and harmony search based clustering and routing in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Veena Anand

2017-01-01

Full Text Available Wireless Sensor Networks (WSN has the disadvantage of limited and non-rechargeable energy resource in WSN creates a challenge and led to development of various clustering and routing algorithms. The paper proposes an approach for improving network lifetime by using Particle swarm optimization based clustering and Harmony Search based routing in WSN. So in this paper, global optimal cluster head are selected and Gateway nodes are introduced to decrease the energy consumption of the CH while sending aggregated data to the Base station (BS. Next, the harmony search algorithm based Local Search strategy finds best routing path for gateway nodes to the Base Station. Finally, the proposed algorithm is presented.

Tree decomposition based fast search of RNA structures including pseudoknots in genomes.

Science.gov (United States)

Song, Yinglei; Liu, Chunmei; Malmberg, Russell; Pan, Fangfang; Cai, Liming

2005-01-01

Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time O(k(t)N(2)), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.

Category Theory Approach to Solution Searching Based on Photoexcitation Transfer Dynamics

Directory of Open Access Journals (Sweden)

Makoto Naruse

2017-07-01

Full Text Available Solution searching that accompanies combinatorial explosion is one of the most important issues in the age of artificial intelligence. Natural intelligence, which exploits natural processes for intelligent functions, is expected to help resolve or alleviate the difficulties of conventional computing paradigms and technologies. In fact, we have shown that a single-celled organism such as an amoeba can solve constraint satisfaction problems and related optimization problems as well as demonstrate experimental systems based on non-organic systems such as optical energy transfer involving near-field interactions. However, the fundamental mechanisms and limitations behind solution searching based on natural processes have not yet been understood. Herein, we present a theoretical background of solution searching based on optical excitation transfer from a category-theoretic standpoint. One important indication inspired by the category theory is that the satisfaction of short exact sequences is critical for an adequate computational operation that determines the flow of time for the system and is termed as “short-exact-sequence-based time.” In addition, the octahedral and braid structures known in triangulated categories provide a clear understanding of the underlying mechanisms, including a quantitative indication of the difficulties of obtaining solutions based on homology dimension. This study contributes to providing a fundamental background of natural intelligence.

A novel line segment detection algorithm based on graph search

Science.gov (United States)

Zhao, Hong-dan; Liu, Guo-ying; Song, Xu

2018-02-01

To overcome the problem of extracting line segment from an image, a method of line segment detection was proposed based on the graph search algorithm. After obtaining the edge detection result of the image, the candidate straight line segments are obtained in four directions. For the candidate straight line segments, their adjacency relationships are depicted by a graph model, based on which the depth-first search algorithm is employed to determine how many adjacent line segments need to be merged. Finally we use the least squares method to fit the detected straight lines. The comparative experimental results verify that the proposed algorithm has achieved better results than the line segment detector (LSD).

[Formula: see text]: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain.

Science.gov (United States)

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem; Khan, Wajahat Ali

2017-01-01

Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search ([Formula: see text]) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, [Formula: see text] ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables [Formula: see text] to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of [Formula: see text] is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations.

Effect of Reading Ability and Internet Experience on Keyword-Based Image Search

Science.gov (United States)

Lei, Pei-Lan; Lin, Sunny S. J.; Sun, Chuen-Tsai

2013-01-01

Image searches are now crucial for obtaining information, constructing knowledge, and building successful educational outcomes. We investigated how reading ability and Internet experience influence keyword-based image search behaviors and performance. We categorized 58 junior-high-school students into four groups of high/low reading ability and…

Design and axial optimization of nuclear fuel for BWR reactors

International Nuclear Information System (INIS)

Garcia V, M.A.

2006-01-01

In the present thesis, the modifications made to the axial optimization system based on Tabu Search (BT) for the axial design of BWR fuel type are presented, developed previously in the Nuclear Engineering Group of the UNAM Engineering Faculty. With the modifications what is mainly looked is to consider the particular characteristics of the mechanical design of the GE12 fuel type, used at the moment in the Laguna Verde Nucleo electric Central (CNLV) and that it considers the fuel bars of partial longitude. The information obtained in this thesis will allow to plan nuclear fuel reloads with the best conditions to operate in a certain cycle guaranteeing a better yield and use in the fuel burnt, additionally people in charge in the reload planning will be favored with the changes carried out to the system for the design and axial optimization of nuclear fuel, which facilitate their handling and it reduces their execution time. This thesis this developed in five chapters that are understood in the following way in general: Chapter 1: It approaches the basic concepts of the nuclear energy, it describes the physical and chemical composition of the atoms as well as that of the uranium isotopes, the handling of the uranium isotope by means of the nuclear fission until arriving to the operation of the nuclear reactors. Chapter 2: The nuclear fuel cycle is described, the methods for its extraction, its conversion and its enrichment to arrive to the stages of the nuclear fuel management used in the reactors are described. Beginning by the radial design, the axial design and the core design of the nuclear reactor related with the fuel assemblies design. Chapter 3: the optimization methods of nuclear fuel previously used are exposed among those that are: the genetic algorithms method, the search methods based on heuristic rules and the application of the tabu search method, which was used for the development of this thesis. Chapter 4: In this part the used methodology to the

Open meta-search with OpenSearch: a case study

OpenAIRE

O'Riordan, Adrian P.

2007-01-01

The goal of this project was to demonstrate the possibilities of open source search engine and aggregation technology in a Web environment by building a meta-search engine which employs free open search engines and open protocols. In contrast many meta-search engines on the Internet use proprietary search systems. The search engines employed in this case study are all based on the OpenSearch protocol. OpenSearch-compliant systems support XML technologies such as RSS and Atom for aggregation a...

Constraint-Based Local Search for Constrained Optimum Paths Problems

Science.gov (United States)

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

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

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

Science.gov (United States)

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

2016-12-01

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

Sound Search Engine Concept

DEFF Research Database (Denmark)

2006-01-01

Sound search is provided by the major search engines, however, indexing is text based, not sound based. We will establish a dedicated sound search services with based on sound feature indexing. The current demo shows the concept of the sound search engine. The first engine will be realased June...

Applying Cuckoo Search for analysis of LFSR based cryptosystem

Directory of Open Access Journals (Sweden)

Maiya Din

2016-09-01

Full Text Available Cryptographic techniques are employed for minimizing security hazards to sensitive information. To make the systems more robust, cyphers or crypts being used need to be analysed for which cryptanalysts require ways to automate the process, so that cryptographic systems can be tested more efficiently. Evolutionary algorithms provide one such resort as these are capable of searching global optimal solution very quickly. Cuckoo Search (CS Algorithm has been used effectively in cryptanalysis of conventional systems like Vigenere and Transposition cyphers. Linear Feedback Shift Register (LFSR is a crypto primitive used extensively in design of cryptosystems. In this paper, we analyse LFSR based cryptosystem using Cuckoo Search to find correct initial states of used LFSR. Primitive polynomials of degree 11, 13, 17 and 19 are considered to analyse text crypts of length 200, 300 and 400 characters. Optimal solutions were obtained for the following CS parameters: Levy distribution parameter (β = 1.5 and Alien eggs discovering probability (pa = 0.25.

A unified architecture for biomedical search engines based on semantic web technologies.

Science.gov (United States)

Jalali, Vahid; Matash Borujerdi, Mohammad Reza

2011-04-01

There is a huge growth in the volume of published biomedical research in recent years. Many medical search engines are designed and developed to address the over growing information needs of biomedical experts and curators. Significant progress has been made in utilizing the knowledge embedded in medical ontologies and controlled vocabularies to assist these engines. However, the lack of common architecture for utilized ontologies and overall retrieval process, hampers evaluating different search engines and interoperability between them under unified conditions. In this paper, a unified architecture for medical search engines is introduced. Proposed model contains standard schemas declared in semantic web languages for ontologies and documents used by search engines. Unified models for annotation and retrieval processes are other parts of introduced architecture. A sample search engine is also designed and implemented based on the proposed architecture in this paper. The search engine is evaluated using two test collections and results are reported in terms of precision vs. recall and mean average precision for different approaches used by this search engine.

Road Traffic Congestion Management Based on a Search-Allocation Approach

Directory of Open Access Journals (Sweden)

Raiyn Jamal

2017-03-01

Full Text Available This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA. An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT technologies.

Agent-oriented Architecture for Task-based Information Search System

NARCIS (Netherlands)

Aroyo, Lora; de Bra, Paul M.E.; De Bra, P.; Hardman, L.

1999-01-01

The topic of the reported research discusses an agent-oriented architecture of an educational information search system AIMS - a task-based learner support system. It is implemented within the context of 'Courseware Engineering' on-line course at the Faculty of Educational Science and Technology,

A novel heuristic algorithm for capacitated vehicle routing problem

Science.gov (United States)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

Can social tagged images aid concept-based video search?

NARCIS (Netherlands)

Setz, A.T.; Snoek, C.G.M.

2009-01-01

This paper seeks to unravel whether commonly available social tagged images can be exploited as a training resource for concept-based video search. Since social tags are known to be ambiguous, overly personalized, and often error prone, we place special emphasis on the role of disambiguation. We

A World Wide Web Region-Based Image Search Engine

DEFF Research Database (Denmark)

Kompatsiaris, Ioannis; Triantafyllou, Evangelia; Strintzis, Michael G.

2001-01-01

In this paper the development of an intelligent image content-based search engine for the World Wide Web is presented. This system will offer a new form of media representation and access of content available in WWW. Information Web Crawlers continuously traverse the Internet and collect images...

Developing a distributed HTML5-based search engine for geospatial resource discovery

Science.gov (United States)

ZHOU, N.; XIA, J.; Nebert, D.; Yang, C.; Gui, Z.; Liu, K.

2013-12-01

With explosive growth of data, Geospatial Cyberinfrastructure(GCI) components are developed to manage geospatial resources, such as data discovery and data publishing. However, the efficiency of geospatial resources discovery is still challenging in that: (1) existing GCIs are usually developed for users of specific domains. Users may have to visit a number of GCIs to find appropriate resources; (2) The complexity of decentralized network environment usually results in slow response and pool user experience; (3) Users who use different browsers and devices may have very different user experiences because of the diversity of front-end platforms (e.g. Silverlight, Flash or HTML). To address these issues, we developed a distributed and HTML5-based search engine. Specifically, (1)the search engine adopts a brokering approach to retrieve geospatial metadata from various and distributed GCIs; (2) the asynchronous record retrieval mode enhances the search performance and user interactivity; (3) the search engine based on HTML5 is able to provide unified access capabilities for users with different devices (e.g. tablet and smartphone).

Solving a manpower scheduling problem for airline catering using tabu search

DEFF Research Database (Denmark)

Ho, Sin C.; Leung, Janny M. Y.

We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take off. Jobs (flights) must...

Resolución del Response Time Variability Problem mediante tabu search

OpenAIRE

Corominas Subias, Albert; García Villoria, Alberto; Pastor Moreno, Rafael

2009-01-01

El Response Time Variability Problem (RTVP) es un problema combinatorio de scheduling publicado recientemente en la literatura. Dicho problema de optimización combinatoria es muy fácil de formular pero muy difícil de resolver de forma exacta (es NP-hard). El RTVP se presenta cuando productos, clientes o tareas se han de secuenciar minimizando la variabilidad entre los instantes de tiempo en los que reciben los recursos que ellos necesitan. Este problema tiene una gran cantidad de aplicaciones...

SHOP: scaffold hopping by GRID-based similarity searches

DEFF Research Database (Denmark)

Bergmann, Rikke; Linusson, Anna; Zamora, Ismael

2007-01-01

A new GRID-based method for scaffold hopping (SHOP) is presented. In a fully automatic manner, scaffolds were identified in a database based on three types of 3D-descriptors. SHOP's ability to recover scaffolds was assessed and validated by searching a database spiked with fragments of known...... scaffolds were in the 31 top-ranked scaffolds. SHOP also identified new scaffolds with substantially different chemotypes from the queries. Docking analysis indicated that the new scaffolds would have similar binding modes to those of the respective query scaffolds observed in X-ray structures...

A Study on Control System Design Based on ARM Sea Target Search System

Directory of Open Access Journals (Sweden)

Lin Xinwei

2015-01-01

Full Text Available The infrared detector is used for sea target search, which can assist humans in searching suspicious objects at night and under poor visibility conditions, and improving search efficiency. This paper applies for interrupt and stack technology to solve problems of data losses that may be caused by one-to-many multi-byte protocol communication. Meanwhile, this paper implements hardware and software design of the system based on industrial-grade ARM control chip and uC / OS-II embedded operating system. The control system in the sea target search system is an information exchange and control center of the whole system, which solves the problem of controlling over the shooting angle of the infrared detector in the process of target search. After testing, the control system operates stably and reliably, and realizes rotation and control functions of the pan/tilt platform during automatic search, manual search and track.

An Analysis of Literature Searching Anxiety in Evidence-Based Medicine Education

Directory of Open Access Journals (Sweden)

Hui-Chin Chang

2014-01-01

Full Text Available Introduction. Evidence-Based Medicine (EBM is hurtling towards a cornerstone in lifelong learning for healthcare personnel worldwide. This study aims to evaluate the literature searching anxiety in graduate students in practicing EBM. Method The study participants were 48 graduate students who enrolled the EBM course at aMedical Universityin central Taiwan. Student’s t-test, Pearson correlation and multivariate regression, interviewing are used to evaluate the students’ literature searching anxiety of EBM course. The questionnaire is Literature Searching Anxiety Rating Scale -LSARS. Results The sources of anxiety are uncertainty of database selection, literatures evaluation and selection, technical assistance request, computer programs use, English and EBM education programs were disclosed. The class performance is negatively related to LSARS score, however, the correlation is statistically insignificant with the adjustment of gender, degree program, age category and experience of publication. Conclusion This study helps in understanding the causes and the extent of anxiety in order to work on a better teaching program planning to improve user’s searching skills and the capability of utilization the information; At the same time, provide friendly-user facilities of evidence searching. In short, we need to upgrade the learner’s searching 45 skills and reduce theanxiety. We also need to stress on the auxiliary teaching program for those with the prevalent and profoundanxiety during literature searching.

Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

Directory of Open Access Journals (Sweden)

Danping Wang

2017-01-01

Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

OpenAIRE

Bożek Andrzej; Wysocki Marian

2016-01-01

A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also ...

Michigan/Air Force Research Laboratory (AFRL) Collaborative Center in Control Science (MACCCS)

Science.gov (United States)

2016-09-01

pp. 143-156, April 2014. 15. M. Faied and A. Girard. Game Formulation of Multi-Team Target Assignment and Suppression Mission. IEEE Transactions on...19. J. Jackson, M. Faied , P. Kabamba and A. Girard. Distributed Constrained Minimum-Time Schedules in Networks of Arbitrary Topology. IEEE...December 2012. 23. J. Jackson, M. Faied , A. Girard. Comparison of Tabu/2-opt Heuristic and Optimal Tree Search Method for Assignment Problems

MotionExplorer: exploratory search in human motion capture data based on hierarchical aggregation.

Science.gov (United States)

Bernard, Jürgen; Wilhelm, Nils; Krüger, Björn; May, Thorsten; Schreck, Tobias; Kohlhammer, Jörn

2013-12-01

We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work.

Web-based information search and retrieval: effects of strategy use and age on search success.

Science.gov (United States)

Stronge, Aideen J; Rogers, Wendy A; Fisk, Arthur D

2006-01-01

The purpose of this study was to investigate the relationship between strategy use and search success on the World Wide Web (i.e., the Web) for experienced Web users. An additional goal was to extend understanding of how the age of the searcher may influence strategy use. Current investigations of information search and retrieval on the Web have provided an incomplete picture of Web strategy use because participants have not been given the opportunity to demonstrate their knowledge of Web strategies while also searching for information on the Web. Using both behavioral and knowledge-engineering methods, we investigated searching behavior and system knowledge for 16 younger adults (M = 20.88 years of age) and 16 older adults (M = 67.88 years). Older adults were less successful than younger adults in finding correct answers to the search tasks. Knowledge engineering revealed that the age-related effect resulted from ineffective search strategies and amount of Web experience rather than age per se. Our analysis led to the development of a decision-action diagram representing search behavior for both age groups. Older adults had more difficulty than younger adults when searching for information on the Web. However, this difficulty was related to the selection of inefficient search strategies, which may have been attributable to a lack of knowledge about available Web search strategies. Actual or potential applications of this research include training Web users to search more effectively and suggestions to improve the design of search engines.

Constraint-based local search for container stowage slot planning

DEFF Research Database (Denmark)

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

2012-01-01

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

A DE-Based Scatter Search for Global Optimization Problems

Directory of Open Access Journals (Sweden)

Kun Li

2015-01-01

Full Text Available This paper proposes a hybrid scatter search (SS algorithm for continuous global optimization problems by incorporating the evolution mechanism of differential evolution (DE into the reference set updated procedure of SS to act as the new solution generation method. This hybrid algorithm is called a DE-based SS (SSDE algorithm. Since different kinds of mutation operators of DE have been proposed in the literature and they have shown different search abilities for different kinds of problems, four traditional mutation operators are adopted in the hybrid SSDE algorithm. To adaptively select the mutation operator that is most appropriate to the current problem, an adaptive mechanism for the candidate mutation operators is developed. In addition, to enhance the exploration ability of SSDE, a reinitialization method is adopted to create a new population and subsequently construct a new reference set whenever the search process of SSDE is trapped in local optimum. Computational experiments on benchmark problems show that the proposed SSDE is competitive or superior to some state-of-the-art algorithms in the literature.

Efficient Multi-keyword Ranked Search over Outsourced Cloud Data based on Homomorphic Encryption

Directory of Open Access Journals (Sweden)

Nie Mengxi

2016-01-01

Full Text Available With the development of cloud computing, more and more data owners are motivated to outsource their data to the cloud server for great flexibility and less saving expenditure. Because the security of outsourced data must be guaranteed, some encryption methods should be used which obsoletes traditional data utilization based on plaintext, e.g. keyword search. To solve the search of encrypted data, some schemes were proposed to solve the search of encrypted data, e.g. top-k single or multiple keywords retrieval. However, the efficiency of these proposed schemes is not high enough to be impractical in the cloud computing. In this paper, we propose a new scheme based on homomorphic encryption to solve this challenging problem of privacy-preserving efficient multi-keyword ranked search over outsourced cloud data. In our scheme, the inner product is adopted to measure the relevance scores and the technique of relevance feedback is used to reflect the search preference of the data users. Security analysis shows that the proposed scheme can meet strict privacy requirements for such a secure cloud data utilization system. Performance evaluation demonstrates that the proposed scheme can achieve low overhead on both computation and communication.

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

Science.gov (United States)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

Analysis of Search Engines and Meta Search Engines\\\\\\' Position by University of Isfahan Users Based on Rogers\\\\\\' Diffusion of Innovation Theory

Directory of Open Access Journals (Sweden)

Maryam Akbari

2012-10-01

Full Text Available The present study investigated the analysis of search engines and meta search engines adoption process by University of Isfahan users during 2009-2010 based on the Rogers' diffusion of innovation theory. The main aim of the research was to study the rate of adoption and recognizing the potentials and effective tools in search engines and meta search engines adoption among University of Isfahan users. The research method was descriptive survey study. The cases of the study were all of the post graduate students of the University of Isfahan. 351 students were selected as the sample and categorized by a stratified random sampling method. Questionnaire was used for collecting data. The collected data was analyzed using SPSS 16 in both descriptive and analytic statistic. For descriptive statistic frequency, percentage and mean were used, while for analytic statistic t-test and Kruskal-Wallis non parametric test (H-test were used. The finding of t-test and Kruscal-Wallis indicated that the mean of search engines and meta search engines adoption did not show statistical differences gender, level of education and the faculty. Special search engines adoption process was different in terms of gender but not in terms of the level of education and the faculty. Other results of the research indicated that among general search engines, Google had the most adoption rate. In addition, among the special search engines, Google Scholar and among the meta search engines Mamma had the most adopting rate. Findings also showed that friends played an important role on how students adopted general search engines while professors had important role on how students adopted special search engines and meta search engines. Moreover, results showed that the place where students got the most acquaintance with search engines and meta search engines was in the university. The finding showed that the curve of adoption rate was not normal and it was not also in S-shape. Morover

Is Internet search better than structured instruction for web-based health education?

Science.gov (United States)

Finkelstein, Joseph; Bedra, McKenzie

2013-01-01

Internet provides access to vast amounts of comprehensive information regarding any health-related subject. Patients increasingly use this information for health education using a search engine to identify education materials. An alternative approach of health education via Internet is based on utilizing a verified web site which provides structured interactive education guided by adult learning theories. Comparison of these two approaches in older patients was not performed systematically. The aim of this study was to compare the efficacy of a web-based computer-assisted education (CO-ED) system versus searching the Internet for learning about hypertension. Sixty hypertensive older adults (age 45+) were randomized into control or intervention groups. The control patients spent 30 to 40 minutes searching the Internet using a search engine for information about hypertension. The intervention patients spent 30 to 40 minutes using the CO-ED system, which provided computer-assisted instruction about major hypertension topics. Analysis of pre- and post- knowledge scores indicated a significant improvement among CO-ED users (14.6%) as opposed to Internet users (2%). Additionally, patients using the CO-ED program rated their learning experience more positively than those using the Internet.

Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

Science.gov (United States)

Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

Solving multi-product inventory ship routing with a heterogeneous fleet model using a hybrid cross entropy-genetic algorithm: a case study in Indonesia

Directory of Open Access Journals (Sweden)

Budi Santosa

2016-01-01

Full Text Available This paper presents a model and an algorithm for an inventory ship routing problem (ISRP. It consists of two main parts: a model development of the ship routing problem in a multi-product inventory with a heterogeneous fleet and an algorithm development to solve the problem. The problem is referred to as ISRP. ISRP considers several parameters including the deadweight tonnage (DWT, product compatibility, port setup, and compartment washing costs. Considering these parameters, the objective function is to minimize the total cost, which consists of traveling, port setup, ship charter, and compartment washing costs. From the resulting model, there are two major steps used to solve the problem. The first is to select the ships in order to satisfy the constraint that restricts the mooring rule. The second is to find the best route, product allocation, and shipped quantity. ISRP is an Non Polynomial-hard problem. Finding the solution of such problem needs a high computation time. A new hybrid metaheuristics, namely the cross entropy-genetic algorithm (CEGA, was proposed to solve ISRP. The results were then compared with those resulted from a hybrid Tabu Search to measure the hybrid CEGA performance. The results showed that CEGA provided better solutions than those produced by the hybrid Tabu Search.

Promoting evidence based medicine in preclinical medical students via a federated literature search tool.

Science.gov (United States)

Keim, Samuel Mark; Howse, David; Bracke, Paul; Mendoza, Kathryn

2008-01-01

Medical educators are increasingly faced with directives to teach Evidence Based Medicine (EBM) skills. Because of its nature, integrating fundamental EBM educational content is a challenge in the preclinical years. To analyse preclinical medical student user satisfaction and feedback regarding a clinical EBM search strategy. The authors introduced a custom EBM search option with a self-contained education structure to first-year medical students. The implementation took advantage of a major curricular change towards case-based instruction. Medical student views and experiences were studied regarding the tool's convenience, problems and the degree to which they used it to answer questions raised by case-based instruction. Surveys were completed by 70% of the available first-year students. Student satisfaction and experiences were strongly positive towards the EBM strategy, especially of the tool's convenience and utility for answering issues raised during case-based learning sessions. About 90% of the students responded that the tool was easy to use, productive and accessed for half or more of their search needs. This study provides evidence that the integration of an educational EBM search tool can be positively received by preclinical medical students.

Developing a Grid-based search and categorization tool

CERN Document Server

Haya, Glenn; Vigen, Jens

2003-01-01

Grid technology has the potential to improve the accessibility of digital libraries. The participants in Project GRACE (Grid Search And Categorization Engine) are in the process of developing a search engine that will allow users to search through heterogeneous resources stored in geographically distributed digital collections. What differentiates this project from current search tools is that GRACE will be run on the European Data Grid, a large distributed network, and will not have a single centralized index as current web search engines do. In some cases, the distributed approach offers advantages over the centralized approach since it is more scalable, can be used on otherwise inaccessible material, and can provide advanced search options customized for each data source.

SA-Search: a web tool for protein structure mining based on a Structural Alphabet.

Science.gov (United States)

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-07-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search.

The Search for Extension: 7 Steps to Help People Find Research-Based Information on the Internet

Science.gov (United States)

Hill, Paul; Rader, Heidi B.; Hino, Jeff

2012-01-01

For Extension's unbiased, research-based content to be found by people searching the Internet, it needs to be organized in a way conducive to the ranking criteria of a search engine. With proper web design and search engine optimization techniques, Extension's content can be found, recognized, and properly indexed by search engines and…

A Novel Quad Harmony Search Algorithm for Grid-Based Path Finding

Directory of Open Access Journals (Sweden)

Saso Koceski

2014-09-01

Full Text Available A novel approach to the problem of grid-based path finding has been introduced. The method is a block-based search algorithm, founded on the bases of two algorithms, namely the quad-tree algorithm, which offered a great opportunity for decreasing the time needed to compute the solution, and the harmony search (HS algorithm, a meta-heuristic algorithm used to obtain the optimal solution. This quad HS algorithm uses the quad-tree decomposition of free space in the grid to mark the free areas and treat them as a single node, which greatly improves the execution. The results of the quad HS algorithm have been compared to other meta-heuristic algorithms, i.e., ant colony, genetic algorithm, particle swarm optimization and simulated annealing, and it was proved to obtain the best results in terms of time and giving the optimal path.

Laser Cutting Tool Path Optimization

OpenAIRE

Dewil, Reginald; Cattrysse, Dirk; Vansteenwegen, Pieter

2011-01-01

Given a set of irregular parts nested on a metal sheet, minimize the total non- cutting time for the cutter head, cutting all the required elements and returning to the starting location. The problem is modeled as a generalized traveling sales- person problem with special precedence constraints. An initial feasible solution is generated and improved by local moves embedded in a tabu search framework. The proposed algorithm shows promising results in comparison with a commercial...

Web Search Engines

OpenAIRE

Rajashekar, TB

1998-01-01

The World Wide Web is emerging as an all-in-one information source. Tools for searching Web-based information include search engines, subject directories and meta search tools. We take a look at key features of these tools and suggest practical hints for effective Web searching.

A Semidefinite Programming Based Search Strategy for Feature Selection with Mutual Information Measure.

Science.gov (United States)

Naghibi, Tofigh; Hoffmann, Sarah; Pfister, Beat

2015-08-01

Feature subset selection, as a special case of the general subset selection problem, has been the topic of a considerable number of studies due to the growing importance of data-mining applications. In the feature subset selection problem there are two main issues that need to be addressed: (i) Finding an appropriate measure function than can be fairly fast and robustly computed for high-dimensional data. (ii) A search strategy to optimize the measure over the subset space in a reasonable amount of time. In this article mutual information between features and class labels is considered to be the measure function. Two series expansions for mutual information are proposed, and it is shown that most heuristic criteria suggested in the literature are truncated approximations of these expansions. It is well-known that searching the whole subset space is an NP-hard problem. Here, instead of the conventional sequential search algorithms, we suggest a parallel search strategy based on semidefinite programming (SDP) that can search through the subset space in polynomial time. By exploiting the similarities between the proposed algorithm and an instance of the maximum-cut problem in graph theory, the approximation ratio of this algorithm is derived and is compared with the approximation ratio of the backward elimination method. The experiments show that it can be misleading to judge the quality of a measure solely based on the classification accuracy, without taking the effect of the non-optimum search strategy into account.

An ontology-based search engine for protein-protein interactions.

Science.gov (United States)

Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

evaluating search effectiveness of some selected search engines

African Journals Online (AJOL)

Precision, relative recall and response time were considered for this ... a total of 24 search queries were sampled based on information queries, .... searching process and results, although there are other ... Q3.2 Software prototype model.

The Research and Test of Fast Radio Burst Real-time Search Algorithm Based on GPU Acceleration

Science.gov (United States)

Wang, J.; Chen, M. Z.; Pei, X.; Wang, Z. Q.

2017-03-01

In order to satisfy the research needs of Nanshan 25 m radio telescope of Xinjiang Astronomical Observatory (XAO) and study the key technology of the planned QiTai radio Telescope (QTT), the receiver group of XAO studied the GPU (Graphics Processing Unit) based real-time FRB searching algorithm which developed from the original FRB searching algorithm based on CPU (Central Processing Unit), and built the FRB real-time searching system. The comparison of the GPU system and the CPU system shows that: on the basis of ensuring the accuracy of the search, the speed of the GPU accelerated algorithm is improved by 35-45 times compared with the CPU algorithm.

Planning the expansion of electrical transmission networks with evolutionary programming; Planeacion de la expansion de redes de transmision electrica con programacion evolucionaria

Energy Technology Data Exchange (ETDEWEB)

Ceciliano Meza, Jose Luis

1997-12-31

In this work it is presented for the first time in the literature the solution of the problem of the planning the expansion of an electrical transmission network (PERTE) with the use of the Evolutionary Programming. The evolutionary programming is a stochastic method of optimization with similar characteristics to the generic algorithms, but different. During the development of this work it is shown what each one of these two heuristic methods of optimization consist of. Additionally, the main characteristics of other two heuristic methods known in the literature are described (Tabu Searching and Simulated Annealing). These two methods together with the genetic algorithms and decomposition of Benders have also been used to solve the problem of planning PERTE. The operation of the proposed algorithm of evolutionary programming was tested in two networks of electrical transmission. The first case of test is a system which is known in the literature. The second case is a representative system of the electrical transmission network of Central America. The results obtained improve all the results shown when applying different heuristic methods of optimization (genetic algorithms, simulated annealing and Tabu searching) to solve the same problem. [Espanol] En este trabajo se presenta por primera vez en la literatura, la solucion del problema de la planeacion de expansion de una red de transmision electrica (PERTE) con el uso de la Programacion Evolucionaria. La programacion evolucionaria es un metodo estocastico de optimizacion con caracteristicas similares a los algoritmos geneticos, pero diferente. Durante el desarrollo de este trabajo se muestra en que consiste cada uno de estos dos metodos heuristicos de optimizacion. Ademas, se describen las caracteristicas principales de otros dos metodos heuristicos conocidos en la literatura (busqueda Tabu y Recorrido Simulado). Estos dos metodos juntos con los algoritmos geneticos y descomposicion de Benders tambien han sido

An opposition-based harmony search algorithm for engineering optimization problems

Directory of Open Access Journals (Sweden)

Abhik Banerjee

2014-03-01

Full Text Available Harmony search (HS is a derivative-free real parameter optimization algorithm. It draws inspiration from the musical improvisation process of searching for a perfect state of harmony. The proposed opposition-based HS (OHS of the present work employs opposition-based learning for harmony memory initialization and also for generation jumping. The concept of opposite number is utilized in OHS to improve the convergence rate of the HS algorithm. The potential of the proposed algorithm is assessed by means of an extensive comparative study of the numerical results on sixteen benchmark test functions. Additionally, the effectiveness of the proposed algorithm is tested for reactive power compensation of an autonomous power system. For real-time reactive power compensation of the studied model, Takagi Sugeno fuzzy logic (TSFL is employed. Time-domain simulation reveals that the proposed OHS-TSFL yields on-line, off-nominal model parameters, resulting in real-time incremental change in terminal voltage response profile.

FPS-RAM: Fast Prefix Search RAM-Based Hardware for Forwarding Engine

Science.gov (United States)

Zaitsu, Kazuya; Yamamoto, Koji; Kuroda, Yasuto; Inoue, Kazunari; Ata, Shingo; Oka, Ikuo

Ternary content addressable memory (TCAM) is becoming very popular for designing high-throughput forwarding engines on routers. However, TCAM has potential problems in terms of hardware and power costs, which limits its ability to deploy large amounts of capacity in IP routers. In this paper, we propose new hardware architecture for fast forwarding engines, called fast prefix search RAM-based hardware (FPS-RAM). We designed FPS-RAM hardware with the intent of maintaining the same search performance and physical user interface as TCAM because our objective is to replace the TCAM in the market. Our RAM-based hardware architecture is completely different from that of TCAM and has dramatically reduced the costs and power consumption to 62% and 52%, respectively. We implemented FPS-RAM on an FPGA to examine its lookup operation.

Project Robust Scheduling Based on the Scattered Buffer Technology

Directory of Open Access Journals (Sweden)

Nansheng Pang

2018-04-01

Full Text Available The research object in this paper is the sub network formed by the predecessor’s affect on the solution activity. This paper is to study three types of influencing factors from the predecessors that lead to the delay of starting time of the solution activity on the longest path, and to analyze the influence degree on the delay of the solution activity’s starting time from different types of factors. On this basis, through the comprehensive analysis of various factors that influence the solution activity, this paper proposes a metric that is used to evaluate the solution robustness of the project scheduling, and this metric is taken as the optimization goal. This paper also adopts the iterative process to design a scattered buffer heuristics algorithm based on the robust scheduling of the time buffer. At the same time, the resource flow network is introduced in this algorithm, using the tabu search algorithm to solve baseline scheduling. For the generation of resource flow network in the baseline scheduling, this algorithm designs a resource allocation algorithm with the maximum use of the precedence relations. Finally, the algorithm proposed in this paper and some other algorithms in previous literature are taken into the simulation experiment; under the comparative analysis, the experimental results show that the algorithm proposed in this paper is reasonable and feasible.

An algorithm based on granular tabu search for the problem of balancing public bikes by using multiple vehicles

Directory of Open Access Journals (Sweden)

Rodrigo Linfati

2014-01-01

Full Text Available El uso de sistemas de bicicletas públicas ha cobrado gran importancia en países europeos y alrededor de todo el planeta; esto ha llevado a la necesidad de buscar técnicas avanzadas que ayuden a la toma de decisiones. Un sistema de bicicletas públicas consiste en un conjunto de puntos donde se pueden recoger y entregar bicicletas; un depósito central donde existe un conjunto de vehículos que toma las bicicletas sobrantes y las transportan a los puntos donde exista un déficit (es decir que la demanda supera la oferta. Una de las grandes problemáticas que se presentan en los sistemas de bicicletas públicas es el balanceo, que consiste en enviar bicicletas desde los puntos donde se produce una oferta (bicicletas que sobran hacia los puntos donde existe una demanda (bicicletas que faltan. La forma de modelar este problema es con una adaptación del problema de ruteo de vehículos con recolección y entrega de mercancías (VRPPD, permitiendo que cada ruta realice entregas parciales a los clientes y limitando el número de clientes a visitar por ruta. En este artículo se introduce un modelo de programación lineal entera mixta y una metaheurística basada en una búsqueda tabú granular para encontrar soluciones. Se usan instancias desde 15 a 500 clientes adaptadas de la literatura. Los resultados computacionales evidencian que el algoritmo propuesto encuentra soluciones en tiempos acotados de cómputo.

Location-based Services using Image Search

DEFF Research Database (Denmark)

Vertongen, Pieter-Paulus; Hansen, Dan Witzner

2008-01-01

Recent developments in image search has made them sufficiently efficient to be used in real-time applications. GPS has become a popular navigation tool. While GPS information provide reasonably good accuracy, they are not always present in all hand held devices nor are they accurate in all situat...... of the image search engine and database image location knowledge, the location is determined of the query image and associated data can be presented to the user....

Optimal Routing for Heterogeneous Fixed Fleets of Multicompartment Vehicles

Directory of Open Access Journals (Sweden)

Qian Wang

2014-01-01

Full Text Available We present a metaheuristic called the reactive guided tabu search (RGTS to solve the heterogeneous fleet multicompartment vehicle routing problem (MCVRP, where a single vehicle is required for cotransporting multiple customer orders. MCVRP is commonly found in delivery of fashion apparel, petroleum distribution, food distribution, and waste collection. In searching the optimum solution of MCVRP, we need to handle a large amount of local optima in the solution spaces. To overcome this problem, we design three guiding mechanisms in which the search history is used to guide the search. The three mechanisms are experimentally demonstrated to be more efficient than the ones which only apply the known distance information. Armed with the guiding mechanisms and the well-known reactive mechanism, the RGTS can produce remarkable solutions in a reasonable computation time.

Large Neighborhood Search

DEFF Research Database (Denmark)

Pisinger, David; Røpke, Stefan

2010-01-01

Heuristics based on large neighborhood search have recently shown outstanding results in solving various transportation and scheduling problems. Large neighborhood search methods explore a complex neighborhood by use of heuristics. Using large neighborhoods makes it possible to find better...... candidate solutions in each iteration and hence traverse a more promising search path. Starting from the large neighborhood search method,we give an overview of very large scale neighborhood search methods and discuss recent variants and extensions like variable depth search and adaptive large neighborhood...

Novel citation-based search method for scientific literature: application to meta-analyses.

Science.gov (United States)

Janssens, A Cecile J W; Gwinn, M

2015-10-13

Finding eligible studies for meta-analysis and systematic reviews relies on keyword-based searching as the gold standard, despite its inefficiency. Searching based on direct citations is not sufficiently comprehensive. We propose a novel strategy that ranks articles on their degree of co-citation with one or more "known" articles before reviewing their eligibility. In two independent studies, we aimed to reproduce the results of literature searches for sets of published meta-analyses (n = 10 and n = 42). For each meta-analysis, we extracted co-citations for the randomly selected 'known' articles from the Web of Science database, counted their frequencies and screened all articles with a score above a selection threshold. In the second study, we extended the method by retrieving direct citations for all selected articles. In the first study, we retrieved 82% of the studies included in the meta-analyses while screening only 11% as many articles as were screened for the original publications. Articles that we missed were published in non-English languages, published before 1975, published very recently, or available only as conference abstracts. In the second study, we retrieved 79% of included studies while screening half the original number of articles. Citation searching appears to be an efficient and reasonably accurate method for finding articles similar to one or more articles of interest for meta-analysis and reviews.

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

Prospects for SUSY discovery based on inclusive searches with the ATLAS detector

International Nuclear Information System (INIS)

Ventura, Andrea

2009-01-01

The search for Supersymmetry (SUSY) among the possible scenarios of new physics is one of the most relevant goals of the ATLAS experiment running at CERN's Large Hadron Collider. In the present work the expected prospects for discovering SUSY with the ATLAS detector are reviewed, in particular for the first fb -1 of collected integrated luminosity. All studies and results reported here are based on inclusive search analyses realized with Monte Carlo signal and background data simulated through the ATLAS apparatus.

Supporting ontology-based keyword search over medical databases.

Science.gov (United States)

Kementsietsidis, Anastasios; Lim, Lipyeow; Wang, Min

2008-11-06

The proliferation of medical terms poses a number of challenges in the sharing of medical information among different stakeholders. Ontologies are commonly used to establish relationships between different terms, yet their role in querying has not been investigated in detail. In this paper, we study the problem of supporting ontology-based keyword search queries on a database of electronic medical records. We present several approaches to support this type of queries, study the advantages and limitations of each approach, and summarize the lessons learned as best practices.

New Architectures for Presenting Search Results Based on Web Search Engines Users Experience

Science.gov (United States)

Martinez, F. J.; Pastor, J. A.; Rodriguez, J. V.; Lopez, Rosana; Rodriguez, J. V., Jr.

2011-01-01

Introduction: The Internet is a dynamic environment which is continuously being updated. Search engines have been, currently are and in all probability will continue to be the most popular systems in this information cosmos. Method: In this work, special attention has been paid to the series of changes made to search engines up to this point,…

Exploring personalized searches using tag-based user profiles and resource profiles in folksonomy.

Science.gov (United States)

Cai, Yi; Li, Qing; Xie, Haoran; Min, Huaqin

2014-10-01

With the increase in resource-sharing websites such as YouTube and Flickr, many shared resources have arisen on the Web. Personalized searches have become more important and challenging since users demand higher retrieval quality. To achieve this goal, personalized searches need to take users' personalized profiles and information needs into consideration. Collaborative tagging (also known as folksonomy) systems allow users to annotate resources with their own tags, which provides a simple but powerful way for organizing, retrieving and sharing different types of social resources. In this article, we examine the limitations of previous tag-based personalized searches. To handle these limitations, we propose a new method to model user profiles and resource profiles in collaborative tagging systems. We use a normalized term frequency to indicate the preference degree of a user on a tag. A novel search method using such profiles of users and resources is proposed to facilitate the desired personalization in resource searches. In our framework, instead of the keyword matching or similarity measurement used in previous works, the relevance measurement between a resource and a user query (termed the query relevance) is treated as a fuzzy satisfaction problem of a user's query requirements. We implement a prototype system called the Folksonomy-based Multimedia Retrieval System (FMRS). Experiments using the FMRS data set and the MovieLens data set show that our proposed method outperforms baseline methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hidden policy ciphertext-policy attribute-based encryption with keyword search against keyword guessing attack

Institute of Scientific and Technical Information of China (English)

Shuo; QIU; Jiqiang; LIU; Yanfeng; SHI; Rui; ZHANG

2017-01-01

Attribute-based encryption with keyword search(ABKS) enables data owners to grant their search capabilities to other users by enforcing an access control policy over the outsourced encrypted data. However,existing ABKS schemes cannot guarantee the privacy of the access structures, which may contain some sensitive private information. Furthermore, resulting from the exposure of the access structures, ABKS schemes are susceptible to an off-line keyword guessing attack if the keyword space has a polynomial size. To solve these problems, we propose a novel primitive named hidden policy ciphertext-policy attribute-based encryption with keyword search(HP-CPABKS). With our primitive, the data user is unable to search on encrypted data and learn any information about the access structure if his/her attribute credentials cannot satisfy the access control policy specified by the data owner. We present a rigorous selective security analysis of the proposed HP-CPABKS scheme, which simultaneously keeps the indistinguishability of the keywords and the access structures. Finally,the performance evaluation verifies that our proposed scheme is efficient and practical.

An image-based search for pulsars among Fermi unassociated LAT sources

Science.gov (United States)

Frail, D. A.; Ray, P. S.; Mooley, K. P.; Hancock, P.; Burnett, T. H.; Jagannathan, P.; Ferrara, E. C.; Intema, H. T.; de Gasperin, F.; Demorest, P. B.; Stovall, K.; McKinnon, M. M.

2018-03-01

We describe an image-based method that uses two radio criteria, compactness, and spectral index, to identify promising pulsar candidates among Fermi Large Area Telescope (LAT) unassociated sources. These criteria are applied to those radio sources from the Giant Metrewave Radio Telescope all-sky survey at 150 MHz (TGSS ADR1) found within the error ellipses of unassociated sources from the 3FGL catalogue and a preliminary source list based on 7 yr of LAT data. After follow-up interferometric observations to identify extended or variable sources, a list of 16 compact, steep-spectrum candidates is generated. An ongoing search for pulsations in these candidates, in gamma rays and radio, has found 6 ms pulsars and one normal pulsar. A comparison of this method with existing selection criteria based on gamma-ray spectral and variability properties suggests that the pulsar discovery space using Fermi may be larger than previously thought. Radio imaging is a hitherto underutilized source selection method that can be used, as with other multiwavelength techniques, in the search for Fermi pulsars.

Research on the optimization strategy of web search engine based on data mining

Science.gov (United States)

Chen, Ronghua

2018-04-01

With the wide application of search engines, web site information has become an important way for people to obtain information. People have found that they are growing in an increasingly explosive manner. Web site information is verydifficult to find the information they need, and now the search engine can not meet the need, so there is an urgent need for the network to provide website personalized information service, data mining technology for this new challenge is to find a breakthrough. In order to improve people's accuracy of finding information from websites, a website search engine optimization strategy based on data mining is proposed, and verified by website search engine optimization experiment. The results show that the proposed strategy improves the accuracy of the people to find information, and reduces the time for people to find information. It has an important practical value.

Using fuzzy rule-based knowledge model for optimum plating conditions search

Science.gov (United States)

Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

2018-03-01

The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

Development of a PubMed Based Search Tool for Identifying Sex and Gender Specific Health Literature.

Science.gov (United States)

Song, Michael M; Simonsen, Cheryl K; Wilson, Joanna D; Jenkins, Marjorie R

2016-02-01

An effective literature search strategy is critical to achieving the aims of Sex and Gender Specific Health (SGSH): to understand sex and gender differences through research and to effectively incorporate the new knowledge into the clinical decision making process to benefit both male and female patients. The goal of this project was to develop and validate an SGSH literature search tool that is readily and freely available to clinical researchers and practitioners. PubMed, a freely available search engine for the Medline database, was selected as the platform to build the SGSH literature search tool. Combinations of Medical Subject Heading terms, text words, and title words were evaluated for optimal specificity and sensitivity. The search tool was then validated against reference bases compiled for two disease states, diabetes and stroke. Key sex and gender terms and limits were bundled to create a search tool to facilitate PubMed SGSH literature searches. During validation, the search tool retrieved 50 of 94 (53.2%) stroke and 62 of 95 (65.3%) diabetes reference articles selected for validation. A general keyword search of stroke or diabetes combined with sex difference retrieved 33 of 94 (35.1%) stroke and 22 of 95 (23.2%) diabetes reference base articles, with lower sensitivity and specificity for SGSH content. The Texas Tech University Health Sciences Center SGSH PubMed Search Tool provides higher sensitivity and specificity to sex and gender specific health literature. The tool will facilitate research, clinical decision-making, and guideline development relevant to SGSH.

Similarity-based search of model organism, disease and drug effect phenotypes

KAUST Repository

Hoehndorf, Robert

2015-02-19

Background: Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions, druggable therapeutic targets, and determination of pathogenicity. Results: We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Conclusions: Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.

DSPSO-TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions

Energy Technology Data Exchange (ETDEWEB)

Khamsawang, S., E-mail: k_suwit999@yahoo.co [Electrical Engineering Department, Faculty of Engineering, King Mongkut' s Institute of Technology Ladkrabang, Ladkrabang District 10520, Bangkok (Thailand); Jiriwibhakorn, S., E-mail: kjsomcha@kmitl.ac.t [Electrical Engineering Department, Faculty of Engineering, King Mongkut' s Institute of Technology Ladkrabang, Ladkrabang District 10520, Bangkok (Thailand)

2010-02-15

This paper proposes a new approach based on particle swarm optimization (PSO) and tabu search algorithm (TSA). This proposed approach is called distributed Sobol PSO and TSA (DSPSO-TSA). In order to improve the convergence characteristic and solution quality of searching process, three mechanisms had been presented. Firstly, the Sobol sequence is applied to generate an inertia factor instead of the existing process. Secondly, a distributed process is used so as to reach the global solution rapidly. The search process is divided to multi-stages and used a short-term memory for recognition the best search history. Finally, to guarantee the global solution, TSA had been activated to adjust the obtained solution of DSPSO algorithm. To show its effectiveness, the proposed DSPSO-TSA is applied to test four case studies of economic dispatch (ED) problem considering nonsmooth and noncontinuous fuel cost functions of generating units. The simulation results obtained from DSPSO-TSA are compared with conventional approaches such as genetic algorithm (GA), TSA, PSO, and others in literatures. The comparison results show that the efficiency of proposed approach can reach higher quality solution and faster computational time than the conventional methods.

DSPSO-TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions

International Nuclear Information System (INIS)

Khamsawang, S.; Jiriwibhakorn, S.

2010-01-01

This paper proposes a new approach based on particle swarm optimization (PSO) and tabu search algorithm (TSA). This proposed approach is called distributed Sobol PSO and TSA (DSPSO-TSA). In order to improve the convergence characteristic and solution quality of searching process, three mechanisms had been presented. Firstly, the Sobol sequence is applied to generate an inertia factor instead of the existing process. Secondly, a distributed process is used so as to reach the global solution rapidly. The search process is divided to multi-stages and used a short-term memory for recognition the best search history. Finally, to guarantee the global solution, TSA had been activated to adjust the obtained solution of DSPSO algorithm. To show its effectiveness, the proposed DSPSO-TSA is applied to test four case studies of economic dispatch (ED) problem considering nonsmooth and noncontinuous fuel cost functions of generating units. The simulation results obtained from DSPSO-TSA are compared with conventional approaches such as genetic algorithm (GA), TSA, PSO, and others in literatures. The comparison results show that the efficiency of proposed approach can reach higher quality solution and faster computational time than the conventional methods.

Omicseq: a web-based search engine for exploring omics datasets

Science.gov (United States)

Sun, Xiaobo; Pittard, William S.; Xu, Tianlei; Chen, Li; Zwick, Michael E.; Jiang, Xiaoqian; Wang, Fusheng

2017-01-01

Abstract The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. PMID:28402462

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

Science.gov (United States)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

COORDINATE-BASED META-ANALYTIC SEARCH FOR THE SPM NEUROIMAGING PIPELINE

DEFF Research Database (Denmark)

Wilkowski, Bartlomiej; Szewczyk, Marcin; Rasmussen, Peter Mondrup

2009-01-01

. BredeQuery offers a direct link from SPM5 to the Brede Database coordinate-based search engine. BredeQuery is able to ‘grab’ brain location coordinates from the SPM windows and enter them as a query for the Brede Database. Moreover, results of the query can be displayed in an SPM window and/or exported...

Web-Based Search and Plot System for Nuclear Reaction Data

International Nuclear Information System (INIS)

Otuka, N.; Nakagawa, T.; Fukahori, T.; Katakura, J.; Aikawa, M.; Suda, T.; Naito, K.; Korennov, S.; Arai, K.; Noto, H.; Ohnishi, A.; Kato, K.

2005-01-01

A web-based search and plot system for nuclear reaction data has been developed, covering experimental data in EXFOR format and evaluated data in ENDF format. The system is implemented for Linux OS, with Perl and MySQL used for CGI scripts and the database manager, respectively. Two prototypes for experimental and evaluated data are presented

Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis.

Science.gov (United States)

Huang, Yan Xin; Bao, Yong Li; Guo, Shu Yan; Wang, Yan; Zhou, Chun Guang; Li, Yu Xin

2008-12-16

The prediction of conformational B-cell epitopes is one of the most important goals in immunoinformatics. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues of interaction between an antigen and an antibody. Consequently, this area of research has received considerable attention from immunologists, structural biologists and computational biologists. Phage-displayed random peptide libraries are powerful tools used to obtain mimotopes that are selected by binding to a given monoclonal antibody (mAb) in a similar way to the native epitope. These mimotopes can be considered as functional epitope mimics. Mimotope analysis based methods can predict not only linear but also conformational epitopes and this has been the focus of much research in recent years. Though some algorithms based on mimotope analysis have been proposed, the precise localization of the interaction site mimicked by the mimotopes is still a challenging task. In this study, we propose a method for B-cell epitope prediction based on mimotope analysis called Pep-3D-Search. Given the 3D structure of an antigen and a set of mimotopes (or a motif sequence derived from the set of mimotopes), Pep-3D-Search can be used in two modes: mimotope or motif. To evaluate the performance of Pep-3D-Search to predict epitopes from a set of mimotopes, 10 epitopes defined by crystallography were compared with the predicted results from a Pep-3D-Search: the average Matthews correlation coefficient (MCC), sensitivity and precision were 0.1758, 0.3642 and 0.6948. Compared with other available prediction algorithms, Pep-3D-Search showed comparable MCC, specificity and precision, and could provide novel, rational results. To verify the capability of Pep-3D-Search to align a motif sequence to a 3D structure for predicting epitopes, 6 test cases were used. The predictive performance of Pep-3D-Search was demonstrated to be superior to that of other similar programs

Search Advertising

OpenAIRE

Cornière (de), Alexandre

2016-01-01

Search engines enable advertisers to target consumers based on the query they have entered. In a framework with horizontal product differentiation, imperfect product information and in which consumers incur search costs, I study a game in which advertisers have to choose a price and a set of relevant keywords. The targeting mechanism brings about three kinds of efficiency gains, namely lower search costs, better matching, and more intense product market price-competition. A monopolistic searc...

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

Science.gov (United States)

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

2017-01-01

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

METAHEURISTICS EVALUATION: A PROPOSAL FOR A MULTICRITERIA METHODOLOGY

Directory of Open Access Journals (Sweden)

Valdir Agustinho de Melo

2015-12-01

Full Text Available ABSTRACT In this work we propose a multicriteria evaluation scheme for heuristic algorithms based on the classic Condorcet ranking technique. Weights are associated to the ranking of an algorithm among a set being object of comparison. We used five criteria and a function on the set of natural numbers to create a ranking. The discussed comparison involves three well-known problems of combinatorial optimization - Traveling Salesperson Problem (TSP, Capacitated Vehicle Routing Problem (CVRP and Quadratic Assignment Problem (QAP. The tested instances came from public libraries. Each algorithm was used with essentially the same structure, the same local search was applied and the initial solutions were similarly built. It is important to note that the work does not make proposals involving algorithms: the results for the three problems are shown only to illustrate the operation of the evaluation technique. Four metaheuristics - GRASP, Tabu Search, ILS and VNS - are therefore only used for the comparisons.

Algorithms for Protein Structure Prediction

DEFF Research Database (Denmark)

Paluszewski, Martin

-trace. Here we present three different approaches for reconstruction of C-traces from predictable measures. In our first approach [63, 62], the C-trace is positioned on a lattice and a tabu-search algorithm is applied to find minimum energy structures. The energy function is based on half-sphere-exposure (HSE......) is more robust than standard Monte Carlo search. In the second approach for reconstruction of C-traces, an exact branch and bound algorithm has been developed [67, 65]. The model is discrete and makes use of secondary structure predictions, HSE, CN and radius of gyration. We show how to compute good lower...... bounds for partial structures very fast. Using these lower bounds, we are able to find global minimum structures in a huge conformational space in reasonable time. We show that many of these global minimum structures are of good quality compared to the native structure. Our branch and bound algorithm...

Study on Multi-stage Logistics System Design Problem with Inventory Considering Demand Change by Hybrid Genetic Algorithm

Science.gov (United States)

Inoue, Hisaki; Gen, Mitsuo

The logistics model used in this study is 3-stage model employed by an automobile company, which aims to solve traffic problems at a total minimum cost. Recently, research on the metaheuristics method has advanced as an approximate means for solving optimization problems like this model. These problems can be solved using various methods such as the genetic algorithm (GA), simulated annealing, and tabu search. GA is superior in robustness and adjustability toward a change in the structure of these problems. However, GA has a disadvantage in that it has a slightly inefficient search performance because it carries out a multi-point search. A hybrid GA that combines another method is attracting considerable attention since it can compensate for a fault to a partial solution that early convergence gives a bad influence on a result. In this study, we propose a novel hybrid random key-based GA(h-rkGA) that combines local search and parameter tuning of crossover rate and mutation rate; h-rkGA is an improved version of the random key-based GA (rk-GA). We attempted comparative experiments with spanning tree-based GA, priority based GA and random key-based GA. Further, we attempted comparative experiments with “h-GA by only local search” and “h-GA by only parameter tuning”. We reported the effectiveness of the proposed method on the basis of the results of these experiments.

Searching and Archiving : Exploring Online Search Behaviors of Researchers

NARCIS (Netherlands)

Vyas, Dhaval; de Groot, S.; van der Veer, Gerrit C.; Dainoff, Marvin J.

2007-01-01

Searching for relevant peer-reviewed material is an integral part of corporate and academic researchers. Researchers collect huge amount of information over the years and sometimes struggle organizing it. Based on a study with 30 academic researchers, we explore, in combination, different searching

Content Based Retrieval Database Management System with Support for Similarity Searching and Query Refinement

National Research Council Canada - National Science Library

Ortega-Binderberger, Michael

2002-01-01

... as a critical area of research. This thesis explores how to enhance database systems with content based search over arbitrary abstract data types in a similarity based framework with query refinement...

Contextual Cueing in Multiconjunction Visual Search Is Dependent on Color- and Configuration-Based Intertrial Contingencies

Science.gov (United States)

Geyer, Thomas; Shi, Zhuanghua; Muller, Hermann J.

2010-01-01

Three experiments examined memory-based guidance of visual search using a modified version of the contextual-cueing paradigm (Jiang & Chun, 2001). The target, if present, was a conjunction of color and orientation, with target (and distractor) features randomly varying across trials (multiconjunction search). Under these conditions, reaction times…

Modelagem de sistemas de manufatura flexíveis considerando restrições temporais e a capacidade do magazine A flexible manufacturing system model which considers constraints of time and magazine capacity

Directory of Open Access Journals (Sweden)

Arthur Tórgo Gómez

1998-04-01

Full Text Available Neste trabalho é apresentado um modelo que gera o seqüenciamento de partes e carregamento de ferramentas em um ambiente de manufatura flexível formado por uma máquina. São consideradas datas de vencimento das partes a serem processadas, os períodos dos turnos de produção, e uma restrição física de capacidade do magazine que armazena as ferramentas necessárias ao processamento das partes. No desenvolvimento do modelo são abordados os problemas de seleção de partes, de carregamento de ferramentas e o problema de "scheduling" com restrições. Um seqüenciamento inicial das partes e carregamento de ferramentas é obtido usando um algoritmo para identificação de grupos que considera a capacidade do magazine. A solução inicial é então melhorada pelo uso de busca tabu, gerando seqüências de partes e carregamento de ferramentas que refletem políticas de otimização determinadas por pesos em uma função objetivo. Vários testes foram realizados para validação do modelo, sendo aqui apresentados alguns resultados obtidos considerando os problemas de minimização do número de trocas de ferramentas, do número de instantes de parada para a troca de ferramentas, do tempo de atraso e do tempo referente ao período ocioso dos turnos de produção.In this paper we propose a model for scheduling parts and tools in a flexible manufacturing system composed of one machine. We consider the due dates of the parts to be processed, production periods and the physical capacity constraints of the magazine which stores the tools required for processing the parts. The model considers the problems of part selection, tool loading and part scheduling using a tabu search approach. An initial algorithm is proposed to identify clusters of parts and tools taking into consideration the magazine capacity. The tabu search optimization function indicates some possible optimization policies determined by weighted objective functions. Several tests were

SemantGeo: Powering Ecological and Environment Data Discovery and Search with Standards-Based Geospatial Reasoning

Science.gov (United States)

Seyed, P.; Ashby, B.; Khan, I.; Patton, E. W.; McGuinness, D. L.

2013-12-01

Recent efforts to create and leverage standards for geospatial data specification and inference include the GeoSPARQL standard, Geospatial OWL ontologies (e.g., GAZ, Geonames), and RDF triple stores that support GeoSPARQL (e.g., AllegroGraph, Parliament) that use RDF instance data for geospatial features of interest. However, there remains a gap on how best to fuse software engineering best practices and GeoSPARQL within semantic web applications to enable flexible search driven by geospatial reasoning. In this abstract we introduce the SemantGeo module for the SemantEco framework that helps fill this gap, enabling scientists find data using geospatial semantics and reasoning. SemantGeo provides multiple types of geospatial reasoning for SemantEco modules. The server side implementation uses the Parliament SPARQL Endpoint accessed via a Tomcat servlet. SemantGeo uses the Google Maps API for user-specified polygon construction and JsTree for providing containment and categorical hierarchies for search. SemantGeo uses GeoSPARQL for spatial reasoning alone and in concert with RDFS/OWL reasoning capabilities to determine, e.g., what geofeatures are within, partially overlap with, or within a certain distance from, a given polygon. We also leverage qualitative relationships defined by the Gazetteer ontology that are composites of spatial relationships as well as administrative designations or geophysical phenomena. We provide multiple mechanisms for exploring data, such as polygon (map-based) and named-feature (hierarchy-based) selection, that enable flexible search constraints using boolean combination of selections. JsTree-based hierarchical search facets present named features and include a 'part of' hierarchy (e.g., measurement-site-01, Lake George, Adirondack Region, NY State) and type hierarchies (e.g., nodes in the hierarchy for WaterBody, Park, MeasurementSite), depending on the ';axis of choice' option selected. Using GeoSPARQL and aforementioned ontology

A Dynamic Neighborhood Learning-Based Gravitational Search Algorithm.

Science.gov (United States)

Zhang, Aizhu; Sun, Genyun; Ren, Jinchang; Li, Xiaodong; Wang, Zhenjie; Jia, Xiuping

2018-01-01

Balancing exploration and exploitation according to evolutionary states is crucial to meta-heuristic search (M-HS) algorithms. Owing to its simplicity in theory and effectiveness in global optimization, gravitational search algorithm (GSA) has attracted increasing attention in recent years. However, the tradeoff between exploration and exploitation in GSA is achieved mainly by adjusting the size of an archive, named , which stores those superior agents after fitness sorting in each iteration. Since the global property of remains unchanged in the whole evolutionary process, GSA emphasizes exploitation over exploration and suffers from rapid loss of diversity and premature convergence. To address these problems, in this paper, we propose a dynamic neighborhood learning (DNL) strategy to replace the model and thereby present a DNL-based GSA (DNLGSA). The method incorporates the local and global neighborhood topologies for enhancing the exploration and obtaining adaptive balance between exploration and exploitation. The local neighborhoods are dynamically formed based on evolutionary states. To delineate the evolutionary states, two convergence criteria named limit value and population diversity, are introduced. Moreover, a mutation operator is designed for escaping from the local optima on the basis of evolutionary states. The proposed algorithm was evaluated on 27 benchmark problems with different characteristic and various difficulties. The results reveal that DNLGSA exhibits competitive performances when compared with a variety of state-of-the-art M-HS algorithms. Moreover, the incorporation of local neighborhood topology reduces the numbers of calculations of gravitational force and thus alleviates the high computational cost of GSA.

Ontology-Driven Search and Triage: Design of a Web-Based Visual Interface for MEDLINE.

Science.gov (United States)

Demelo, Jonathan; Parsons, Paul; Sedig, Kamran

2017-02-02

Diverse users need to search health and medical literature to satisfy open-ended goals such as making evidence-based decisions and updating their knowledge. However, doing so is challenging due to at least two major difficulties: (1) articulating information needs using accurate vocabulary and (2) dealing with large document sets returned from searches. Common search interfaces such as PubMed do not provide adequate support for exploratory search tasks. Our objective was to improve support for exploratory search tasks by combining two strategies in the design of an interactive visual interface by (1) using a formal ontology to help users build domain-specific knowledge and vocabulary and (2) providing multi-stage triaging support to help mitigate the information overload problem. We developed a Web-based tool, Ontology-Driven Visual Search and Triage Interface for MEDLINE (OVERT-MED), to test our design ideas. We implemented a custom searchable index of MEDLINE, which comprises approximately 25 million document citations. We chose a popular biomedical ontology, the Human Phenotype Ontology (HPO), to test our solution to the vocabulary problem. We implemented multistage triaging support in OVERT-MED, with the aid of interactive visualization techniques, to help users deal with large document sets returned from searches. Formative evaluation suggests that the design features in OVERT-MED are helpful in addressing the two major difficulties described above. Using a formal ontology seems to help users articulate their information needs with more accurate vocabulary. In addition, multistage triaging combined with interactive visualizations shows promise in mitigating the information overload problem. Our strategies appear to be valuable in addressing the two major problems in exploratory search. Although we tested OVERT-MED with a particular ontology and document collection, we anticipate that our strategies can be transferred successfully to other contexts. �

An Improved Harmony Search Based on Teaching-Learning Strategy for Unconstrained Optimization Problems

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Shouheng Tuo

2013-01-01

Full Text Available Harmony search (HS algorithm is an emerging population-based metaheuristic algorithm, which is inspired by the music improvisation process. The HS method has been developed rapidly and applied widely during the past decade. In this paper, an improved global harmony search algorithm, named harmony search based on teaching-learning (HSTL, is presented for high dimension complex optimization problems. In HSTL algorithm, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation are employed to maintain the proper balance between convergence and population diversity, and dynamic strategy is adopted to change the parameters. The proposed HSTL algorithm is investigated and compared with three other state-of-the-art HS optimization algorithms. Furthermore, to demonstrate the robustness and convergence, the success rate and convergence analysis is also studied. The experimental results of 31 complex benchmark functions demonstrate that the HSTL method has strong convergence and robustness and has better balance capacity of space exploration and local exploitation on high dimension complex optimization problems.

Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks.

Science.gov (United States)

Xu, Zhezhuang; Liu, Guanglun; Yan, Haotian; Cheng, Bin; Lin, Feilong

2017-10-27

In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor's mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay.

Ecosystem-Based Management in Fiji: Successes and Challenges after Five Years of Implementation

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Stacy D. Jupiter

2011-01-01

Full Text Available In 2005, a network of 3 large, district-wide marine protected areas (MPAs and 17 village-managed closures (tabu was established in Kubulau District, Fiji. Underwater visual census (UVC data of fish biomass and benthic cover were collected between 2007 and 2009 and analysed with PERMANOVA and ANOSIM to assess differences between closed and open areas. High reef fish biomass (>1000 kg/ha within closures, significantly elevated over open areas, was consistently observed from: (1 tabu areas on naturally productive reefs within visual distance from villages; and (2 the large, long-term permanent closure located away from fishing pressure. Factors that may have contributed to low fish biomass within closures include small size of closures; noncompliance with management rules; and disclosure of management success to fishers from villages with high reliance on fisheries products. Future success of the network depends on improving awareness of management rules and ensuring implementation within a broader ecosystem framework.

Agent based simulation on the process of human flesh search-From perspective of knowledge and emotion

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Zhu, Hou; Hu, Bin

2017-03-01

Human flesh search as a new net crowed behavior, on the one hand can help us to find some special information, on the other hand may lead to privacy leaking and offending human right. In order to study the mechanism of human flesh search, this paper proposes a simulation model based on agent-based model and complex networks. The computational experiments show some useful results. Discovered information quantity and involved personal ratio are highly correlated, and most of net citizens will take part in the human flesh search or will not take part in the human flesh search. Knowledge quantity does not influence involved personal ratio, but influences whether HFS can find out the target human. When the knowledge concentrates on hub nodes, the discovered information quantity is either perfect or almost zero. Emotion of net citizens influences both discovered information quantity and involved personal ratio. Concretely, when net citizens are calm to face the search topic, it will be hardly to find out the target; But when net citizens are agitated, the target will be found out easily.

Signature-based global searches at CDF

International Nuclear Information System (INIS)

Hocker, James Andrew

2008-01-01

Data collected in Run II of the Fermilab Tevatron are searched for indications of new electroweak scale physics. Rather than focusing on particular new physics scenarios, CDF data are analyzed for discrepancies with respect to the Standard Model prediction. Gross features of the data, mass bumps, and significant excesses of events with large summed transverse momentum are examined in a model-independent and quasi-model-independent approach. This global search for new physics in over three hundred exclusive final states in 2 fb -1 of p(bar p) collisions at √s = 1.96 TeV reveals no significant indication of physics beyond the Standard Model

Gains Based Remedies: the misguided search for a doctrine

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Tom Stafford

2016-12-01

Full Text Available ADVANCE ACCESSIn this article Tom Stafford (Paralegal at Clyde & Co LLP examines the phenomenon of “Gains Based Remedies”. These are awards that, unlike classical damage awards which are calculated by reference to the loss suffered by the claimant, correlate to the gain made by the defendant. A couple of common examples include an account of profits for breach of trust claims, or the “disgorgement” damages that were awarded in AG v Blake. These awards are however available for a spectrum of varied wrongs. Their seeming lack of unity has often baffled commentators who have tried to search for an underpinning doctrine. One particularly renowned commentary is that of Professor Edelman’s, who suggests that these wrongs can be understood by being broken down into one of two categories: awards which seek to deter wrongdoing, and awards which reverse a wrongful transfer of value. The purpose of this article is to discuss the flaws of this view of the law, and to suggest that in fact, any search for a doctrinal underpinning to Gains Based Remedies is misguided. The cases in which these awards are granted have only one feature common to all: the claimant’s loss is, for whatever reason, difficult or impossible to assess. For that reason, the courts use the only other measure of the wrong available: the defendant’s gain.

Analysis and Optimization of Mixed-Criticality Applications on Partitioned Distributed Architectures

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Marinescu, S. O.; Pop, Paul

2012-01-01

Constrained (RC) messages, transmitted if there are no TT messages, and Best Effort (BE) messages. We assume that applications are scheduled using Static Cyclic Scheduling (SCS) or Fixed-Priority Preemptive Scheduling (FPS). We are interested in analysis and optimization methods and tools, which decide...... within predefined time slots, allocated on each processor. At the communication-level, TTEthernet uses the concepts of virtual links for the separation of mixed-criticality messages. TTEthernet integrates three types of traffic: Time-Triggered (TT) messages, transmitted based on schedule tables, Rate...... the mapping of tasks to PEs, the sequence and length of the time partitions on each PE and the schedule tables of the SCS tasks and TT messages, such that the applications are schedulable and the response times of FPS tasks and RC messages is minimized. We have proposed a Tabu Search-based meta...

Omicseq: a web-based search engine for exploring omics datasets.

Science.gov (United States)

Sun, Xiaobo; Pittard, William S; Xu, Tianlei; Chen, Li; Zwick, Michael E; Jiang, Xiaoqian; Wang, Fusheng; Qin, Zhaohui S

2017-07-03

The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve 'findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

Science.gov (United States)

Balbi Fraga, Tatiana

2015-05-01

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

Sagace: A web-based search engine for biomedical databases in Japan

Directory of Open Access Journals (Sweden)

Morita Mizuki

2012-10-01

Full Text Available Abstract Background In the big data era, biomedical research continues to generate a large amount of data, and the generated information is often stored in a database and made publicly available. Although combining data from multiple databases should accelerate further studies, the current number of life sciences databases is too large to grasp features and contents of each database. Findings We have developed Sagace, a web-based search engine that enables users to retrieve information from a range of biological databases (such as gene expression profiles and proteomics data and biological resource banks (such as mouse models of disease and cell lines. With Sagace, users can search more than 300 databases in Japan. Sagace offers features tailored to biomedical research, including manually tuned ranking, a faceted navigation to refine search results, and rich snippets constructed with retrieved metadata for each database entry. Conclusions Sagace will be valuable for experts who are involved in biomedical research and drug development in both academia and industry. Sagace is freely available at http://sagace.nibio.go.jp/en/.

Opuntia in Mexico: identifying priority areas for conserving biodiversity in a multi-use landscape.

Directory of Open Access Journals (Sweden)

Patricia Illoldi-Rangel

Full Text Available BACKGROUND: México is one of the world's centers of species diversity (richness for Opuntia cacti. Yet, in spite of their economic and ecological importance, Opuntia species remain poorly studied and protected in México. Many of the species are sparsely but widely distributed across the landscape and are subject to a variety of human uses, so devising implementable conservation plans for them presents formidable difficulties. Multi-criteria analysis can be used to design a spatially coherent conservation area network while permitting sustainable human usage. METHODS AND FINDINGS: Species distribution models were created for 60 Opuntia species using MaxEnt. Targets of representation within conservation area networks were assigned at 100% for the geographically rarest species and 10% for the most common ones. Three different conservation plans were developed to represent the species within these networks using total area, shape, and connectivity as relevant criteria. Multi-criteria analysis and a metaheuristic adaptive tabu search algorithm were used to search for optimal solutions. The plans were built on the existing protected areas of México and prioritized additional areas for management for the persistence of Opuntia species. All plans required around one-third of México's total area to be prioritized for attention for Opuntia conservation, underscoring the implausibility of Opuntia conservation through traditional land reservation. Tabu search turned out to be both computationally tractable and easily implementable for search problems of this kind. CONCLUSIONS: Opuntia conservation in México require the management of large areas of land for multiple uses. The multi-criteria analyses identified priority areas and organized them in large contiguous blocks that can be effectively managed. A high level of connectivity was established among the prioritized areas resulting in the enhancement of possible modes of plant dispersal as well as

Generating "fragment-based virtual library" using pocket similarity search of ligand-receptor complexes.

Science.gov (United States)

Khashan, Raed S

2015-01-01

As the number of available ligand-receptor complexes is increasing, researchers are becoming more dedicated to mine these complexes to aid in the drug design and development process. We present free software which is developed as a tool for performing similarity search across ligand-receptor complexes for identifying binding pockets which are similar to that of a target receptor. The search is based on 3D-geometric and chemical similarity of the atoms forming the binding pocket. For each match identified, the ligand's fragment(s) corresponding to that binding pocket are extracted, thus forming a virtual library of fragments (FragVLib) that is useful for structure-based drug design. The program provides a very useful tool to explore available databases.

A multi-variate discrimination technique based on range-searching

International Nuclear Information System (INIS)

Carli, T.; Koblitz, B.

2003-01-01

We present a fast and transparent multi-variate event classification technique, called PDE-RS, which is based on sampling the signal and background densities in a multi-dimensional phase space using range-searching. The employed algorithm is presented in detail and its behaviour is studied with simple toy examples representing basic patterns of problems often encountered in High Energy Physics data analyses. In addition an example relevant for the search for instanton-induced processes in deep-inelastic scattering at HERA is discussed. For all studied examples, the new presented method performs as good as artificial Neural Networks and has furthermore the advantage to need less computation time. This allows to carefully select the best combination of observables which optimally separate the signal and background and for which the simulations describe the data best. Moreover, the systematic and statistical uncertainties can be easily evaluated. The method is therefore a powerful tool to find a small number of signal events in the large data samples expected at future particle colliders

Beyond the search surface: visual search and attentional engagement.

Science.gov (United States)

Duncan, J; Humphreys, G

1992-05-01

Treisman (1991) described a series of visual search studies testing feature integration theory against an alternative (Duncan & Humphreys, 1989) in which feature and conjunction search are basically similar. Here the latter account is noted to have 2 distinct levels: (a) a summary of search findings in terms of stimulus similarities, and (b) a theory of how visual attention is brought to bear on relevant objects. Working at the 1st level, Treisman found that even when similarities were calibrated and controlled, conjunction search was much harder than feature search. The theory, however, can only really be tested at the 2nd level, because the 1st is an approximation. An account of the findings is developed at the 2nd level, based on the 2 processes of input-template matching and spreading suppression. New data show that, when both of these factors are controlled, feature and conjunction search are equally difficult. Possibilities for unification of the alternative views are considered.

Usability Testing of a Large, Multidisciplinary Library Database: Basic Search and Visual Search

Directory of Open Access Journals (Sweden)

Jody Condit Fagan

2006-09-01

Full Text Available Visual search interfaces have been shown by researchers to assist users with information search and retrieval. Recently, several major library vendors have added visual search interfaces or functions to their products. For public service librarians, perhaps the most critical area of interest is the extent to which visual search interfaces and text-based search interfaces support research. This study presents the results of eight full-scale usability tests of both the EBSCOhost Basic Search and Visual Search in the context of a large liberal arts university.

The Evolution of Web Searching.

Science.gov (United States)

Green, David

2000-01-01

Explores the interrelation between Web publishing and information retrieval technologies and lists new approaches to Web indexing and searching. Highlights include Web directories; search engines; portalisation; Internet service providers; browser providers; meta search engines; popularity based analysis; natural language searching; links-based…

Incremental Learning of Context Free Grammars by Parsing-Based Rule Generation and Rule Set Search

Science.gov (United States)

Nakamura, Katsuhiko; Hoshina, Akemi

This paper discusses recent improvements and extensions in Synapse system for inductive inference of context free grammars (CFGs) from sample strings. Synapse uses incremental learning, rule generation based on bottom-up parsing, and the search for rule sets. The form of production rules in the previous system is extended from Revised Chomsky Normal Form A→βγ to Extended Chomsky Normal Form, which also includes A→B, where each of β and γ is either a terminal or nonterminal symbol. From the result of bottom-up parsing, a rule generation mechanism synthesizes minimum production rules required for parsing positive samples. Instead of inductive CYK algorithm in the previous version of Synapse, the improved version uses a novel rule generation method, called ``bridging,'' which bridges the lacked part of the derivation tree for the positive string. The improved version also employs a novel search strategy, called serial search in addition to minimum rule set search. The synthesis of grammars by the serial search is faster than the minimum set search in most cases. On the other hand, the size of the generated CFGs is generally larger than that by the minimum set search, and the system can find no appropriate grammar for some CFL by the serial search. The paper shows experimental results of incremental learning of several fundamental CFGs and compares the methods of rule generation and search strategies.

A grammar checker based on web searching

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Joaquim Moré

2006-05-01

Full Text Available This paper presents an English grammar and style checker for non-native English speakers. The main characteristic of this checker is the use of an Internet search engine. As the number of web pages written in English is immense, the system hypothesises that a piece of text not found on the Web is probably badly written. The system also hypothesises that the Web will provide examples of how the content of the text segment can be expressed in a grammatically correct and idiomatic way. Thus, when the checker warns the user about the odd nature of a text segment, the Internet engine searches for contexts that can help the user decide whether he/she should correct the segment or not. By means of a search engine, the checker also suggests use of other expressions that appear on the Web more often than the expression he/she actually wrote.

Development of a Google-based search engine for data mining radiology reports.

Science.gov (United States)

Erinjeri, Joseph P; Picus, Daniel; Prior, Fred W; Rubin, David A; Koppel, Paul

2009-08-01

The aim of this study is to develop a secure, Google-based data-mining tool for radiology reports using free and open source technologies and to explore its use within an academic radiology department. A Health Insurance Portability and Accountability Act (HIPAA)-compliant data repository, search engine and user interface were created to facilitate treatment, operations, and reviews preparatory to research. The Institutional Review Board waived review of the project, and informed consent was not required. Comprising 7.9 GB of disk space, 2.9 million text reports were downloaded from our radiology information system to a fileserver. Extensible markup language (XML) representations of the reports were indexed using Google Desktop Enterprise search engine software. A hypertext markup language (HTML) form allowed users to submit queries to Google Desktop, and Google's XML response was interpreted by a practical extraction and report language (PERL) script, presenting ranked results in a web browser window. The query, reason for search, results, and documents visited were logged to maintain HIPAA compliance. Indexing averaged approximately 25,000 reports per hour. Keyword search of a common term like "pneumothorax" yielded the first ten most relevant results of 705,550 total results in 1.36 s. Keyword search of a rare term like "hemangioendothelioma" yielded the first ten most relevant results of 167 total results in 0.23 s; retrieval of all 167 results took 0.26 s. Data mining tools for radiology reports will improve the productivity of academic radiologists in clinical, educational, research, and administrative tasks. By leveraging existing knowledge of Google's interface, radiologists can quickly perform useful searches.

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

Science.gov (United States)

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

A Hybrid Optimization Algorithm for Low RCS Antenna Design

Directory of Open Access Journals (Sweden)

W. Shao

2012-12-01

Full Text Available In this article, a simple and efficient method is presented to design low radar cross section (RCS patch antennas. This method consists of a hybrid optimization algorithm, which combines a genetic algorithm (GA with tabu search algorithm (TSA, and electromagnetic field solver. The TSA, embedded into the GA frame, defines the acceptable neighborhood region of parameters and screens out the poor-scoring individuals. Thus, the repeats of search are avoided and the amount of time-consuming electromagnetic simulations is largely reduced. Moreover, the whole design procedure is auto-controlled by programming the VBScript language. A slot patch antenna example is provided to verify the accuracy and efficiency of the proposed method.

A heuristic algorithm for a multi-product four-layer capacitated location-routing problem

Directory of Open Access Journals (Sweden)

Mohsen Hamidi

2014-01-01

Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.

Project GRACE A grid based search tool for the global digital library

CERN Document Server

Scholze, Frank; Vigen, Jens; Prazak, Petra; The Seventh International Conference on Electronic Theses and Dissertations

2004-01-01

The paper will report on the progress of an ongoing EU project called GRACE - Grid Search and Categorization Engine (http://www.grace-ist.org). The project participants are CERN, Sheffield Hallam University, Stockholm University, Stuttgart University, GL 2006 and Telecom Italia. The project started in 2002 and will finish in 2005, resulting in a Grid based search engine that will search across a variety of content sources including a number of electronic thesis and dissertation repositories. The Open Archives Initiative (OAI) is expanding and is clearly an interesting movement for a community advocating open access to ETD. However, the OAI approach alone may not be sufficiently scalable to achieve a truly global ETD Digital Library. Many universities simply offer their collections to the world via their local web services without being part of any federated system for archiving and even those dissertations that are provided with OAI compliant metadata will not necessarily be picked up by a centralized OAI Ser...

Parallel Harmony Search Based Distributed Energy Resource Optimization

Energy Technology Data Exchange (ETDEWEB)

Ceylan, Oguzhan [ORNL; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2015-01-01

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electrical power distribution systems operation.

MinHash-Based Fuzzy Keyword Search of Encrypted Data across Multiple Cloud Servers

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Jingsha He

2018-05-01

Full Text Available To enhance the efficiency of data searching, most data owners store their data files in different cloud servers in the form of cipher-text. Thus, efficient search using fuzzy keywords becomes a critical issue in such a cloud computing environment. This paper proposes a method that aims at improving the efficiency of cipher-text retrieval and lowering storage overhead for fuzzy keyword search. In contrast to traditional approaches, the proposed method can reduce the complexity of Min-Hash-based fuzzy keyword search by using Min-Hash fingerprints to avoid the need to construct the fuzzy keyword set. The method will utilize Jaccard similarity to rank the results of retrieval, thus reducing the amount of calculation for similarity and saving a lot of time and space overhead. The method will also take consideration of multiple user queries through re-encryption technology and update user permissions dynamically. Security analysis demonstrates that the method can provide better privacy preservation and experimental results show that efficiency of cipher-text using the proposed method can improve the retrieval time and lower storage overhead as well.

Ice Cover Prediction of a Power Grid Transmission Line Based on Two-Stage Data Processing and Adaptive Support Vector Machine Optimized by Genetic Tabu Search

OpenAIRE

Xiaomin Xu; Dongxiao Niu; Lihui Zhang; Yongli Wang; Keke Wang

2017-01-01

With the increase in energy demand, extreme climates have gained increasing attention. Ice disasters on transmission lines can cause gap discharge and icing flashover electrical failures, which can lead to mechanical failure of the tower, conductor, and insulators, causing significant harm to people’s daily life and work. To address this challenge, an intelligent combinational model is proposed based on improved empirical mode decomposition and support vector machine for short-term forecastin...

Smart Images Search based on Visual Features Fusion

International Nuclear Information System (INIS)

Saad, M.H.

2013-01-01

Image search engines attempt to give fast and accurate access to the wide range of the huge amount images available on the Internet. There have been a number of efforts to build search engines based on the image content to enhance search results. Content-Based Image Retrieval (CBIR) systems have achieved a great interest since multimedia files, such as images and videos, have dramatically entered our lives throughout the last decade. CBIR allows automatically extracting target images according to objective visual contents of the image itself, for example its shapes, colors and textures to provide more accurate ranking of the results. The recent approaches of CBIR differ in terms of which image features are extracted to be used as image descriptors for matching process. This thesis proposes improvements of the efficiency and accuracy of CBIR systems by integrating different types of image features. This framework addresses efficient retrieval of images in large image collections. A comparative study between recent CBIR techniques is provided. According to this study; image features need to be integrated to provide more accurate description of image content and better image retrieval accuracy. In this context, this thesis presents new image retrieval approaches that provide more accurate retrieval accuracy than previous approaches. The first proposed image retrieval system uses color, texture and shape descriptors to form the global features vector. This approach integrates the yc b c r color histogram as a color descriptor, the modified Fourier descriptor as a shape descriptor and modified Edge Histogram as a texture descriptor in order to enhance the retrieval results. The second proposed approach integrates the global features vector, which is used in the first approach, with the SURF salient point technique as local feature. The nearest neighbor matching algorithm with a proposed similarity measure is applied to determine the final image rank. The second approach

Custom Search Engines: Tools & Tips

Science.gov (United States)

Notess, Greg R.

2008-01-01

Few have the resources to build a Google or Yahoo! from scratch. Yet anyone can build a search engine based on a subset of the large search engines' databases. Use Google Custom Search Engine or Yahoo! Search Builder or any of the other similar programs to create a vertical search engine targeting sites of interest to users. The basic steps to…

Knowing How Good Our Searches Are: An Approach Derived from Search Filter Development Methodology

Directory of Open Access Journals (Sweden)

Sarah Hayman

2015-12-01

Full Text Available Objective – Effective literature searching is of paramount importance in supporting evidence based practice, research, and policy. Missed references can have adverse effects on outcomes. This paper reports on the development and evaluation of an online learning resource, designed for librarians and other interested searchers, presenting an evidence based approach to enhancing and testing literature searches. Methods – We developed and evaluated the set of free online learning modules for librarians called Smart Searching, suggesting the use of techniques derived from search filter development undertaken by the CareSearch Palliative Care Knowledge Network and its associated project Flinders Filters. The searching module content has been informed by the processes and principles used in search filter development. The self-paced modules are intended to help librarians and other interested searchers test the effectiveness of their literature searches, provide evidence of search performance that can be used to improve searches, as well as to evaluate and promote searching expertise. Each module covers one of four techniques, or core principles, employed in search filter development: (1 collaboration with subject experts; (2 use of a reference sample set; (3 term identification through frequency analysis; and (4 iterative testing. Evaluation of the resource comprised ongoing monitoring of web analytics to determine factors such as numbers of users and geographic origin; a user survey conducted online elicited qualitative information about the usefulness of the resource. Results – The resource was launched in May 2014. Web analytics show over 6,000 unique users from 101 countries (at 9 August 2015. Responses to the survey (n=50 indicated that 80% would recommend the resource to a colleague. Conclusions – An evidence based approach to searching, derived from search filter development methodology, has been shown to have value as an online learning

SA-Search: a web tool for protein structure mining based on a Structural Alphabet

OpenAIRE

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-01-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of f...

Permission-based Index Clustering for Secure Multi-User Search

OpenAIRE

Eirini C. Micheli; Giorgos Margaritis; Stergios V. Anastasiadis

2015-01-01

Secure keyword search in shared infrastructures prevents stored documents from leaking sensitive information to unauthorized users. A shared index provides confidentiality if it is exclusively used by users authorized to search all the indexed documents. We introduce the Lethe indexing workflow to improve query and update efficiency in secure keyword search. The Lethe workflow clusters together documents with similar sets of authorized users, and creates shared indices for configurable docume...

Hybrid fuzzy charged system search algorithm based state estimation in distribution networks

Directory of Open Access Journals (Sweden)

Sachidananda Prasad

2017-06-01

Full Text Available This paper proposes a new hybrid charged system search (CSS algorithm based state estimation in radial distribution networks in fuzzy framework. The objective of the optimization problem is to minimize the weighted square of the difference between the measured and the estimated quantity. The proposed method of state estimation considers bus voltage magnitude and phase angle as state variable along with some equality and inequality constraints for state estimation in distribution networks. A rule based fuzzy inference system has been designed to control the parameters of the CSS algorithm to achieve better balance between the exploration and exploitation capability of the algorithm. The efficiency of the proposed fuzzy adaptive charged system search (FACSS algorithm has been tested on standard IEEE 33-bus system and Indian 85-bus practical radial distribution system. The obtained results have been compared with the conventional CSS algorithm, weighted least square (WLS algorithm and particle swarm optimization (PSO for feasibility of the algorithm.

Identification of Fuzzy Inference Systems by Means of a Multiobjective Opposition-Based Space Search Algorithm

Directory of Open Access Journals (Sweden)

Wei Huang

2013-01-01

Full Text Available We introduce a new category of fuzzy inference systems with the aid of a multiobjective opposition-based space search algorithm (MOSSA. The proposed MOSSA is essentially a multiobjective space search algorithm improved by using an opposition-based learning that employs a so-called opposite numbers mechanism to speed up the convergence of the optimization algorithm. In the identification of fuzzy inference system, the MOSSA is exploited to carry out the parametric identification of the fuzzy model as well as to realize its structural identification. Experimental results demonstrate the effectiveness of the proposed fuzzy models.

Expectation violations in sensorimotor sequences: shifting from LTM-based attentional selection to visual search.

Science.gov (United States)

Foerster, Rebecca M; Schneider, Werner X

2015-03-01

Long-term memory (LTM) delivers important control signals for attentional selection. LTM expectations have an important role in guiding the task-driven sequence of covert attention and gaze shifts, especially in well-practiced multistep sensorimotor actions. What happens when LTM expectations are disconfirmed? Does a sensory-based visual-search mode of attentional selection replace the LTM-based mode? What happens when prior LTM expectations become valid again? We investigated these questions in a computerized version of the number-connection test. Participants clicked on spatially distributed numbered shapes in ascending order while gaze was recorded. Sixty trials were performed with a constant spatial arrangement. In 20 consecutive trials, either numbers, shapes, both, or no features switched position. In 20 reversion trials, participants worked on the original arrangement. Only the sequence-affecting number switches elicited slower clicking, visual search-like scanning, and lower eye-hand synchrony. The effects were neither limited to the exchanged numbers nor to the corresponding actions. Thus, expectation violations in a well-learned sensorimotor sequence cause a regression from LTM-based attentional selection to visual search beyond deviant-related actions and locations. Effects lasted for several trials and reappeared during reversion. © 2015 New York Academy of Sciences.

Learning Bayesian Dependence Model for Student Modelling

Directory of Open Access Journals (Sweden)

Adina COCU

2008-12-01

Full Text Available Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.

Intelligence systems in environmental management theory and applications

CERN Document Server

Sari, İrem

2017-01-01

This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspec...

Design Optimization of Mixed-Criticality Real-Time Applications on Cost-Constrained Partitioned Architectures

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2011-01-01

In this paper we are interested to implement mixed-criticality hard real-time applications on a given heterogeneous distributed architecture. Applications have different criticality levels, captured by their Safety-Integrity Level (SIL), and are scheduled using static-cyclic scheduling. Mixed......-criticality tasks can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. We consider that the separation is provided by partitioning, such that applications run in separate partitions, and each partition is allocated several time slots on a processor. Tasks...... slots on each processor and (iv) the schedule tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real...

Systematizing Web Search through a Meta-Cognitive, Systems-Based, Information Structuring Model (McSIS)

Science.gov (United States)

Abuhamdieh, Ayman H.; Harder, Joseph T.

2015-01-01

This paper proposes a meta-cognitive, systems-based, information structuring model (McSIS) to systematize online information search behavior based on literature review of information-seeking models. The General Systems Theory's (GST) prepositions serve as its framework. Factors influencing information-seekers, such as the individual learning…

Addressing special structure in the relevance feedback learning problem through aspect-based image search

NARCIS (Netherlands)

M.J. Huiskes (Mark)

2004-01-01

textabstractIn this paper we focus on a number of issues regarding special structure in the relevance feedback learning problem, most notably the effects of image selection based on partial relevance on the clustering behavior of examples. We propose a simple scheme, aspect-based image search, which

EARS: An Online Bibliographic Search and Retrieval System Based on Ordered Explosion.

Science.gov (United States)

Ramesh, R.; Drury, Colin G.

1987-01-01

Provides overview of Ergonomics Abstracts Retrieval System (EARS), an online bibliographic search and retrieval system in the area of human factors engineering. Other online systems are described, the design of EARS based on inverted file organization is explained, and system expansions including a thesaurus are discussed. (Author/LRW)

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials

Science.gov (United States)

2012-01-01

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. PMID:22595088

Using Google Search Appliance (GSA) to search digital library collections: A Case Study of the INIS Collection Search

International Nuclear Information System (INIS)

Savic, Dobrica

2014-01-01

Google Search has established a new standard for information retrieval which did not exist with previous generations of library search facilities. The INIS hosts one of the world’s largest collections of published information on the peaceful uses of nuclear science and technology. It offers on-line access to a unique collection of 3.6 million bibliographic records and 483,000 full texts of non-conventional (grey) literature. This large digital library collection suffered from most of the well-known shortcomings of the classic library catalogue. Searching was complex and complicated, it required training in Boolean logic, full-text searching was not an option, and response time was slow. An opportune moment to improve the system came with the retirement of the previous catalogue software and the adoption of GSA as an organization-wide search engine standard. INIS was quick to realize the potential of using such a well-known application to replace its on-line catalogue. This paper presents the advantages and disadvantages encountered during three years of GSA use. Based on specific INIS-based practice and experience, this paper also offers some guidelines on ways to improve classic collections of millions of bibliographic and full-text documents, while reaping multiple benefits, such as increased use, accessibility, usability, expandability and improving user search and retrieval experiences. (author)

Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction

Science.gov (United States)

Jonsson, Ari K.; Frank, Jeremy

2000-01-01

Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.

Confirmation bias in web-based search: a randomized online study on the effects of expert information and social tags on information search and evaluation.

Science.gov (United States)

Schweiger, Stefan; Oeberst, Aileen; Cress, Ulrike

2014-03-26

The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective. The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts' evaluations. A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts' blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants' treatment recommendation after information search. Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t173=7.67, Pinformation search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F2,168=10.61, Pinformation as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (F1,168=4.32, P=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (Ps>.33). We conclude that the psychotherapy bias is most effectively

Human memory search

NARCIS (Netherlands)

Davelaar, E.J.; Raaijmakers, J.G.W.; Hills, T.T.; Robbins, T.W.; Todd, P.M.

2012-01-01

The importance of understanding human memory search is hard to exaggerate: we build and live our lives based on what whe remember. This chapter explores the characteristics of memory search, with special emphasis on the use of retrieval cues. We introduce the dependent measures that are obtained

A BLE-Based Pedestrian Navigation System for Car Searching in Indoor Parking Garages.

Science.gov (United States)

Wang, Sheng-Shih

2018-05-05

The continuous global increase in the number of cars has led to an increase in parking issues, particularly with respect to the search for available parking spaces and finding cars. In this paper, we propose a navigation system for car owners to find their cars in indoor parking garages. The proposed system comprises a car-searching mobile app and a positioning-assisting subsystem. The app guides car owners to their cars based on a “turn-by-turn” navigation strategy, and has the ability to correct the user’s heading orientation. The subsystem uses beacon technology for indoor positioning, supporting self-guidance of the car-searching mobile app. This study also designed a local coordinate system to support the identification of the locations of parking spaces and beacon devices. We used Android as the platform to implement the proposed car-searching mobile app, and used Bytereal HiBeacon devices to implement the proposed positioning-assisting subsystem. We also deployed the system in a parking lot in our campus for testing. The experimental results verified that the proposed system not only works well, but also provides the car owner with the correct route guidance information.

Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

Science.gov (United States)

O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin

2017-12-06

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks †

Science.gov (United States)

Xu, Zhezhuang; Liu, Guanglun; Yan, Haotian; Cheng, Bin; Lin, Feilong

2017-01-01

In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor’s mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay. PMID:29077017

Optimization of patterns of control bars using neural networks; Optimizacion de patrones de barras de control usando redes neuronales

Energy Technology Data Exchange (ETDEWEB)

Mejia S, D.M. [IPN, ESFM, Depto. de Ingenieria Nuclear, 07738 Mexico D.F. (Mexico); Ortiz S, J.J. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: dulcema6715@hotmail.com

2005-07-01

In this work the RENOPBC system that is based on a recurrent multi state neural network, for the optimization of patterns of control bars in a cycle of balance of a boiling water reactor (BWR for their initials in English) is presented. The design of patterns of bars is based on the execution of operation thermal limits, to maintain criticizes the reactor and that the axial profile of power is adjusted to one predetermined along several steps of burnt. The patterns of control bars proposed by the system are comparable to those proposed by human experts with many hour-man of experience. These results are compared with those proposed by other techniques as genetic algorithms, colonies of ants and tabu search for the same operation cycle. As consequence it is appreciated that the proposed patterns of control bars, have bigger operation easiness that those proposed by the other techniques. (Author)

Optimization of patterns of control bars using neural networks

International Nuclear Information System (INIS)

Mejia S, D.M.; Ortiz S, J.J.

2005-01-01

In this work the RENOPBC system that is based on a recurrent multi state neural network, for the optimization of patterns of control bars in a cycle of balance of a boiling water reactor (BWR for their initials in English) is presented. The design of patterns of bars is based on the execution of operation thermal limits, to maintain criticizes the reactor and that the axial profile of power is adjusted to one predetermined along several steps of burnt. The patterns of control bars proposed by the system are comparable to those proposed by human experts with many hour-man of experience. These results are compared with those proposed by other techniques as genetic algorithms, colonies of ants and tabu search for the same operation cycle. As consequence it is appreciated that the proposed patterns of control bars, have bigger operation easiness that those proposed by the other techniques. (Author)

Solving a static repositioning problem in bike-sharing systems using iterated tabu search

DEFF Research Database (Denmark)

Ho, Sin C.; Szeto, W. Y.

2014-01-01

In this paper, we study the static bike repositioning problem where the problem consists of selecting a subset of stations to visit, sequencing them, and determining the pick-up/drop-off quantities (associated with each of the visited stations) under the various operational constraints. The objec......In this paper, we study the static bike repositioning problem where the problem consists of selecting a subset of stations to visit, sequencing them, and determining the pick-up/drop-off quantities (associated with each of the visited stations) under the various operational constraints...

DESIGNING A SUPPLY CHAIN MODEL WITH CONSIDERATION DEMAND FORECASTING AND INFORMATION SHARING

Directory of Open Access Journals (Sweden)

S.M.T. Fatemi Ghomi

2012-01-01

Full Text Available

ENGLISH ABSTRACT: In traditional supply chain inventory management, orders are the only information firms exchange, but information technology now allows firms to share demand and inventory data quickly and inexpensively. To have an integrated plan, a manufacturer not only needs to know demand information from its customers but also supply information from its suppliers. In this paper, information flow is incorporated in a three-echelon supply chain model. Also to decrease the risk of the supply chain system, the customers’ demands are predicted first and this prediction is then used as an input to the supply chain model. In this paper a proposed evolving fuzzy predictor model will be used to predict the customers’ demands. For solving the supply chain model, a hybrid heuristic combining tabu search with simulated annealing sharing the same tabu list is developed.

AFRIKAANSE OPSOMMING: In tradisionele voorsieningskettingvoorraadbestuur verteenwoordig bestellings die enigste vorm van van inligting wat deur ondernemings uitgeruil word. Inligtingstegnologie laat ondernemings egter deesdae toe om vraag- en voorraadata vinnig en goedkoop uit te ruil. Om 'n geïntegreerde plan te hê, het 'n vervaardiger nie alleen aanvraaginligting nodig van sy klante nie, maar ook aanbodinligting van sy leweransiers. In hierdie artikel word inligtingvloei geinkorporeer in 'n drie-vlakvoorsieningskettingmodel. Voorts, om die risiko in die voorsieningskettingmodel te verminder, word die klante se aanvraag eers vooruitgeskat en die vooruitskatting word dan gebruik as 'n inset tot die model. Hierdie artikel gebruik 'n groeiende wasige vooruitskattingsmodel om die klantebehoeftes voor uit te skat. Om die model op te los, word 'n hibriede heuristiese metode gekombineer met 'n "tabu"-soektog gebruik.

Involuntary top-down control by search-irrelevant features: Visual working memory biases attention in an object-based manner.

Science.gov (United States)

Foerster, Rebecca M; Schneider, Werner X

2018-03-01

Many everyday tasks involve successive visual-search episodes with changing targets. Converging evidence suggests that these targets are retained in visual working memory (VWM) and bias attention from there. It is unknown whether all or only search-relevant features of a VWM template bias attention during search. Bias signals might be configured exclusively to task-relevant features so that only search-relevant features bias attention. Alternatively, VWM might maintain objects in the form of bound features. Then, all template features will bias attention in an object-based manner, so that biasing effects are ranked by feature relevance. Here, we investigated whether search-irrelevant VWM template features bias attention. Participants had to saccade to a target opposite a distractor. A colored cue depicted the target prior to each search trial. The target was predefined only by its identity, while its color was irrelevant. When target and cue matched not only in identity (search-relevant) but also in color (search-irrelevant), saccades went more often and faster directly to the target than without any color match (Experiment 1). When introducing a cue-distractor color match (Experiment 2), direct target saccades were most likely when target and cue matched in the search-irrelevant color and least likely in case of a cue-distractor color match. When cue and target were never colored the same (Experiment 3), cue-colored distractors still captured the eyes more often than different-colored distractors despite color being search-irrelevant. As participants were informed about the misleading color, the result argues against a strategical and voluntary usage of color. Instead, search-irrelevant features biased attention obligatorily arguing for involuntary top-down control by object-based VWM templates. Copyright © 2017 Elsevier B.V. All rights reserved.

m2-ABKS: Attribute-Based Multi-Keyword Search over Encrypted Personal Health Records in Multi-Owner Setting.

Science.gov (United States)

Miao, Yinbin; Ma, Jianfeng; Liu, Ximeng; Wei, Fushan; Liu, Zhiquan; Wang, Xu An

2016-11-01

Online personal health record (PHR) is more inclined to shift data storage and search operations to cloud server so as to enjoy the elastic resources and lessen computational burden in cloud storage. As multiple patients' data is always stored in the cloud server simultaneously, it is a challenge to guarantee the confidentiality of PHR data and allow data users to search encrypted data in an efficient and privacy-preserving way. To this end, we design a secure cryptographic primitive called as attribute-based multi-keyword search over encrypted personal health records in multi-owner setting to support both fine-grained access control and multi-keyword search via Ciphertext-Policy Attribute-Based Encryption. Formal security analysis proves our scheme is selectively secure against chosen-keyword attack. As a further contribution, we conduct empirical experiments over real-world dataset to show its feasibility and practicality in a broad range of actual scenarios without incurring additional computational burden.

A novel ternary content addressable memory design based on resistive random access memory with high intensity and low search energy

Science.gov (United States)

Han, Runze; Shen, Wensheng; Huang, Peng; Zhou, Zheng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2018-04-01

A novel ternary content addressable memory (TCAM) design based on resistive random access memory (RRAM) is presented. Each TCAM cell consists of two parallel RRAM to both store and search for ternary data. The cell size of the proposed design is 8F2, enable a ∼60× cell area reduction compared with the conventional static random access memory (SRAM) based implementation. Simulation results also show that the search delay and energy consumption of the proposed design at the 64-bit word search are 2 ps and 0.18 fJ/bit/search respectively at 22 nm technology node, where significant improvements are achieved compared to previous works. The desired characteristics of RRAM for implementation of the high performance TCAM search chip are also discussed.

SEARCHES FOR SUPERSYMMETRY IN ATLAS

CERN Document Server

Xu, Da; The ATLAS collaboration

2017-01-01

A wide range of supersymmetric searches are presented. All searches are based on the proton- proton collision dataset collected by the ATLAS experiment during the 2015 and 2016 (before summer) run with a center-of-mass energy of 13 TeV, corresponding to an integrated lumi- nosity of 36.1 (36.7) fb-1. The searches are categorized into inclusive gluino and squark search, third generation search, electroweak search, prompt RPV search and long-lived par- ticle search. No evidence of new physics is observed. The results are intepreted in various models and expressed in terms of limits on the masses of new particles.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

Science.gov (United States)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

BioCarian: search engine for exploratory searches in heterogeneous biological databases.

Science.gov (United States)

Zaki, Nazar; Tennakoon, Chandana

2017-10-02

There are a large number of biological databases publicly available for scientists in the web. Also, there are many private databases generated in the course of research projects. These databases are in a wide variety of formats. Web standards have evolved in the recent times and semantic web technologies are now available to interconnect diverse and heterogeneous sources of data. Therefore, integration and querying of biological databases can be facilitated by techniques used in semantic web. Heterogeneous databases can be converted into Resource Description Format (RDF) and queried using SPARQL language. Searching for exact queries in these databases is trivial. However, exploratory searches need customized solutions, especially when multiple databases are involved. This process is cumbersome and time consuming for those without a sufficient background in computer science. In this context, a search engine facilitating exploratory searches of databases would be of great help to the scientific community. We present BioCarian, an efficient and user-friendly search engine for performing exploratory searches on biological databases. The search engine is an interface for SPARQL queries over RDF databases. We note that many of the databases can be converted to tabular form. We first convert the tabular databases to RDF. The search engine provides a graphical interface based on facets to explore the converted databases. The facet interface is more advanced than conventional facets. It allows complex queries to be constructed, and have additional features like ranking of facet values based on several criteria, visually indicating the relevance of a facet value and presenting the most important facet values when a large number of choices are available. For the advanced users, SPARQL queries can be run directly on the databases. Using this feature, users will be able to incorporate federated searches of SPARQL endpoints. We used the search engine to do an exploratory search

SINGLE FIXED CRANE OPTIMISATION WITHIN A DISTRIBUTION CENTRE

Directory of Open Access Journals (Sweden)

J. Matthews

2012-01-01

Full Text Available

ENGLISH ABSTRACT: This paper considersthe optimisation of the movement of a fixed crane operating in a single aisle of a distribution centre. The crane must move pallets in inventory between docking bays, storage locations, and picking lines. Both a static and a dynamic approach to the problem are presented. The optimisation is performed by means of tabu search, ant colony metaheuristics,and hybrids of these two methods. All these solution approaches were tested on real life data obtained from an operational distribution centre. Results indicate that the hybrid methods outperform the other approaches.

AFRIKAANSE OPSOMMING: Die optimisering van die beweging van 'n vaste hyskraan in 'n enkele gang van 'n distribusiesentrum word in hierdie artikel beskou. Die hyskraan moet pallette vervoer tussen dokhokke, stoorposisies, en opmaaklyne. Beide 'n statiese en 'n dinamiese benadering tot die probleem word aangebied. Die optimisering word gedoen met behulp van tabu-soektogte, mierkolonieoptimisering,en hibriede van hierdie twee metodes. Al die oplossingsbenaderings is getoets met werklike data wat van 'n operasionele distribusiesentrum verkry is. Die resultate toon aan dat die hibriedmetodes die beste oplossings lewer.

Managing Online Search Statistics with dBASE III Plus.

Science.gov (United States)

Speer, Susan C.

1987-01-01

Describes a computer program designed to manage statistics about online searches which reports the number of searches by vendor, purpose, and librarian; calculates charges to departments and individuals; and prints monthly invoices to users with standing accounts. (CLB)

Vertical Search Engines

OpenAIRE

Curran, Kevin; Mc Glinchey, Jude

2017-01-01

This paper outlines the growth in popularity of vertical search engines, their origins, the differences between them and well-known broad based search engines such as Google and Yahoo. We also discuss their use in business-to-business, their marketing and advertising costs, what the revenue streams are and who uses them.

Joint redundancy and imperfect preventive maintenance optimization for series–parallel multi-state degraded systems

International Nuclear Information System (INIS)

Nourelfath, Mustapha; Châtelet, Eric; Nahas, Nabil

2012-01-01

This paper formulates a joint redundancy and imperfect preventive maintenance planning optimization model for series–parallel multi-state degraded systems. Non identical multi-state components can be used in parallel to improve the system availability by providing redundancy in subsystems. Multiple component choices are available in the market for each subsystem. The status of each component is considered to degrade with use. The objective is to determine jointly the maximal-availability series–parallel system structure and the appropriate preventive maintenance actions, subject to a budget constraint. System availability is defined as the ability to satisfy consumer demand that is represented as a piecewise cumulative load curve. A procedure is used, based on Markov processes and universal moment generating function, to evaluate the multi-state system availability and the cost function. A heuristic approach is also proposed to solve the formulated problem. This heuristic is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected sub-space.

Simulation Optimization of Search and Rescue in Disaster Relief Based on Distributed Auction Mechanism

Directory of Open Access Journals (Sweden)

Jian Tang

2017-11-01

Full Text Available In this paper, we optimize the search and rescue (SAR in disaster relief through agent-based simulation. We simulate rescue teams’ search behaviors with the improved Truncated Lévy walks. Then we propose a cooperative rescue plan based on a distributed auction mechanism, and illustrate it with the case of landslide disaster relief. The simulation is conducted in three scenarios, including “fatal”, “serious” and “normal”. Compared with the non-cooperative rescue plan, the proposed rescue plan in this paper would increase victims’ relative survival probability by 7–15%, increase the ratio of survivors getting rescued by 5.3–12.9%, and decrease the average elapsed time for one site getting rescued by 16.6–21.6%. The robustness analysis shows that search radius can affect the rescue efficiency significantly, while the scope of cooperation cannot. The sensitivity analysis shows that the two parameters, the time limit for completing rescue operations in one buried site and the maximum turning angle for next step, both have a great influence on rescue efficiency, and there exists optimal value for both of them in view of rescue efficiency.

A Statistical Ontology-Based Approach to Ranking for Multiword Search

Science.gov (United States)

Kim, Jinwoo

2013-01-01

Keyword search is a prominent data retrieval method for the Web, largely because the simple and efficient nature of keyword processing allows a large amount of information to be searched with fast response. However, keyword search approaches do not formally capture the clear meaning of a keyword query and fail to address the semantic relationships…

New generation of the multimedia search engines

Science.gov (United States)

Mijes Cruz, Mario Humberto; Soto Aldaco, Andrea; Maldonado Cano, Luis Alejandro; López Rodríguez, Mario; Rodríguez Vázqueza, Manuel Antonio; Amaya Reyes, Laura Mariel; Cano Martínez, Elizabeth; Pérez Rosas, Osvaldo Gerardo; Rodríguez Espejo, Luis; Flores Secundino, Jesús Abimelek; Rivera Martínez, José Luis; García Vázquez, Mireya Saraí; Zamudio Fuentes, Luis Miguel; Sánchez Valenzuela, Juan Carlos; Montoya Obeso, Abraham; Ramírez Acosta, Alejandro Álvaro

2016-09-01

Current search engines are based upon search methods that involve the combination of words (text-based search); which has been efficient until now. However, the Internet's growing demand indicates that there's more diversity on it with each passing day. Text-based searches are becoming limited, as most of the information on the Internet can be found in different types of content denominated multimedia content (images, audio files, video files). Indeed, what needs to be improved in current search engines is: search content, and precision; as well as an accurate display of expected search results by the user. Any search can be more precise if it uses more text parameters, but it doesn't help improve the content or speed of the search itself. One solution is to improve them through the characterization of the content for the search in multimedia files. In this article, an analysis of the new generation multimedia search engines is presented, focusing the needs according to new technologies. Multimedia content has become a central part of the flow of information in our daily life. This reflects the necessity of having multimedia search engines, as well as knowing the real tasks that it must comply. Through this analysis, it is shown that there are not many search engines that can perform content searches. The area of research of multimedia search engines of new generation is a multidisciplinary area that's in constant growth, generating tools that satisfy the different needs of new generation systems.

Web-Based Undergraduate Chemistry Problem-Solving: The Interplay of Task Performance, Domain Knowledge and Web-Searching Strategies

Science.gov (United States)

She, Hsiao-Ching; Cheng, Meng-Tzu; Li, Ta-Wei; Wang, Chia-Yu; Chiu, Hsin-Tien; Lee, Pei-Zon; Chou, Wen-Chi; Chuang, Ming-Hua

2012-01-01

This study investigates the effect of Web-based Chemistry Problem-Solving, with the attributes of Web-searching and problem-solving scaffolds, on undergraduate students' problem-solving task performance. In addition, the nature and extent of Web-searching strategies students used and its correlation with task performance and domain knowledge also…

Does linear separability really matter? Complex visual search is explained by simple search

Science.gov (United States)

Vighneshvel, T.; Arun, S. P.

2013-01-01

Visual search in real life involves complex displays with a target among multiple types of distracters, but in the laboratory, it is often tested using simple displays with identical distracters. Can complex search be understood in terms of simple searches? This link may not be straightforward if complex search has emergent properties. One such property is linear separability, whereby search is hard when a target cannot be separated from its distracters using a single linear boundary. However, evidence in favor of linear separability is based on testing stimulus configurations in an external parametric space that need not be related to their true perceptual representation. We therefore set out to assess whether linear separability influences complex search at all. Our null hypothesis was that complex search performance depends only on classical factors such as target-distracter similarity and distracter homogeneity, which we measured using simple searches. Across three experiments involving a variety of artificial and natural objects, differences between linearly separable and nonseparable searches were explained using target-distracter similarity and distracter heterogeneity. Further, simple searches accurately predicted complex search regardless of linear separability (r = 0.91). Our results show that complex search is explained by simple search, refuting the widely held belief that linear separability influences visual search. PMID:24029822

Visualization of Pulsar Search Data

Science.gov (United States)

Foster, R. S.; Wolszczan, A.

1993-05-01

The search for periodic signals from rotating neutron stars or pulsars has been a computationally taxing problem to astronomers for more than twenty-five years. Over this time interval, increases in computational capability have allowed ever more sensitive searches, covering a larger parameter space. The volume of input data and the general presence of radio frequency interference typically produce numerous spurious signals. Visualization of the search output and enhanced real-time processing of significant candidate events allow the pulsar searcher to optimally processes and search for new radio pulsars. The pulsar search algorithm and visualization system presented in this paper currently runs on serial RISC based workstations, a traditional vector based super computer, and a massively parallel computer. A description of the serial software algorithm and its modifications for massively parallel computing are describe. The results of four successive searches for millisecond period radio pulsars using the Arecibo telescope at 430 MHz have resulted in the successful detection of new long-period and millisecond period radio pulsars.

On the network-based emulation of human visual search

NARCIS (Netherlands)

Gerrissen, J.F.

1991-01-01

We describe the design of a computer emulator of human visual search. The emulator mechanism is eventually meant to support ergonomic assessment of the effect of display structure and protocol on search performance. As regards target identification and localization, it mimics a number of

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Directory of Open Access Journals (Sweden)

Yudong Zhang

2015-01-01

Full Text Available Particle swarm optimization (PSO is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO, population topology (as fully connected, von Neumann, ring, star, random, etc., hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization, extensions (to multiobjective, constrained, discrete, and binary optimization, theoretical analysis (parameter selection and tuning, and convergence analysis, and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms. On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

Turn-Based War Chess Model and Its Search Algorithm per Turn

Directory of Open Access Journals (Sweden)

Hai Nan

2016-01-01

Full Text Available War chess gaming has so far received insufficient attention but is a significant component of turn-based strategy games (TBS and is studied in this paper. First, a common game model is proposed through various existing war chess types. Based on the model, we propose a theory frame involving combinational optimization on the one hand and game tree search on the other hand. We also discuss a key problem, namely, that the number of the branching factors of each turn in the game tree is huge. Then, we propose two algorithms for searching in one turn to solve the problem: (1 enumeration by order; (2 enumeration by recursion. The main difference between these two is the permutation method used: the former uses the dictionary sequence method, while the latter uses the recursive permutation method. Finally, we prove that both of these algorithms are optimal, and we analyze the difference between their efficiencies. An important factor is the total time taken for the unit to expand until it achieves its reachable position. The factor, which is the total number of expansions that each unit makes in its reachable position, is set. The conclusion proposed is in terms of this factor: Enumeration by recursion is better than enumeration by order in all situations.

Group search optimiser-based optimal bidding strategies with no Karush-Kuhn-Tucker optimality conditions

Science.gov (United States)

Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.

2017-03-01

General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.

Using a Google Search Appliance (GSA to search digital library collections: a case study of the INIS Collection Search

Directory of Open Access Journals (Sweden)

Dobrica Savic

2014-05-01

The International Nuclear Information System (INIS hosts one of the world’s largest collections of published information on the peaceful uses of nuclear science and technology. It offers online access to a unique collection of 3.6 million bibliographic records and 320,000 full-texts of non-conventional (grey literature. This large digital library collection suffered from most of the well-known shortcomings of the classic library catalogue. Searching was complex and complicated, required some training in using Boolean logic, full-text searching was not an option, and the response time was slow. An opportune moment came with the retirement of the previous catalogue software and with the adoption of Google Search Appliance (GSA as an organization-wide search engine standard. INIS was quick to realize a great potential in using such a well-known application as a replacement for its online catalogue and this paper presents the advantages and disadvantages encountered during three years of GSA use. Based on specific INIS-based practice and experience, this paper also offers some guidelines on ways to improve classic collections of millions of bibliographic and full-text documents, while achieving multiple benefits such as increased use, accessibility, usability, expandability and improving the user search and retrieval experience.

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

Science.gov (United States)

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

2015-02-01

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

Is searching full text more effective than searching abstracts?

Science.gov (United States)

Lin, Jimmy

2009-02-03

With the growing availability of full-text articles online, scientists and other consumers of the life sciences literature now have the ability to go beyond searching bibliographic records (title, abstract, metadata) to directly access full-text content. Motivated by this emerging trend, I posed the following question: is searching full text more effective than searching abstracts? This question is answered by comparing text retrieval algorithms on MEDLINE abstracts, full-text articles, and spans (paragraphs) within full-text articles using data from the TREC 2007 genomics track evaluation. Two retrieval models are examined: bm25 and the ranking algorithm implemented in the open-source Lucene search engine. Experiments show that treating an entire article as an indexing unit does not consistently yield higher effectiveness compared to abstract-only search. However, retrieval based on spans, or paragraphs-sized segments of full-text articles, consistently outperforms abstract-only search. Results suggest that highest overall effectiveness may be achieved by combining evidence from spans and full articles. Users searching full text are more likely to find relevant articles than searching only abstracts. This finding affirms the value of full text collections for text retrieval and provides a starting point for future work in exploring algorithms that take advantage of rapidly-growing digital archives. Experimental results also highlight the need to develop distributed text retrieval algorithms, since full-text articles are significantly longer than abstracts and may require the computational resources of multiple machines in a cluster. The MapReduce programming model provides a convenient framework for organizing such computations.

Is searching full text more effective than searching abstracts?

Directory of Open Access Journals (Sweden)

Lin Jimmy

2009-02-01

Full Text Available Abstract Background With the growing availability of full-text articles online, scientists and other consumers of the life sciences literature now have the ability to go beyond searching bibliographic records (title, abstract, metadata to directly access full-text content. Motivated by this emerging trend, I posed the following question: is searching full text more effective than searching abstracts? This question is answered by comparing text retrieval algorithms on MEDLINE® abstracts, full-text articles, and spans (paragraphs within full-text articles using data from the TREC 2007 genomics track evaluation. Two retrieval models are examined: bm25 and the ranking algorithm implemented in the open-source Lucene search engine. Results Experiments show that treating an entire article as an indexing unit does not consistently yield higher effectiveness compared to abstract-only search. However, retrieval based on spans, or paragraphs-sized segments of full-text articles, consistently outperforms abstract-only search. Results suggest that highest overall effectiveness may be achieved by combining evidence from spans and full articles. Conclusion Users searching full text are more likely to find relevant articles than searching only abstracts. This finding affirms the value of full text collections for text retrieval and provides a starting point for future work in exploring algorithms that take advantage of rapidly-growing digital archives. Experimental results also highlight the need to develop distributed text retrieval algorithms, since full-text articles are significantly longer than abstracts and may require the computational resources of multiple machines in a cluster. The MapReduce programming model provides a convenient framework for organizing such computations.

Learning Search Algorithms: An Educational View

Directory of Open Access Journals (Sweden)

Ales Janota

2014-12-01

Full Text Available Artificial intelligence methods find their practical usage in many applications including maritime industry. The paper concentrates on the methods of uninformed and informed search, potentially usable in solving of complex problems based on the state space representation. The problem of introducing the search algorithms to newcomers has its technical and psychological dimensions. The authors show how it is possible to cope with both of them through design and use of specialized authoring systems. A typical example of searching a path through the maze is used to demonstrate how to test, observe and compare properties of various search strategies. Performance of search methods is evaluated based on the common criteria.

Part-based deep representation for product tagging and search

Science.gov (United States)

Chen, Keqing

2017-06-01

Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

Effects of Discipline-based Career Course on Nursing Students' Career Search Self-efficacy, Career Preparation Behavior, and Perceptions of Career Barriers.

Science.gov (United States)

Park, Soonjoo

2015-09-01

The purpose of this study was to investigate the effectiveness of a discipline-based career course on perceptions of career barriers, career search self-efficacy, and career preparation behavior of nursing students. Differences in career search self-efficacy and career preparation behavior by the students' levels of career barriers were also examined. The study used a modified one-group, pretest-posttest design. The convenience sample consisted of 154 undergraduate nursing students in a university. The discipline-based career course consisted of eight sessions, and was implemented for 2 hours per session over 8 weeks. The data were collected from May to June in 2012 and 2013 using the following instruments: the Korean Career Indecision Inventory, the Career Search Efficacy Scale, and the Career Preparation Behavior Scale. Descriptive statistics, paired t test, and analysis of covariance were used to analyze the data. Upon the completion of the discipline-based career course, students' perceptions of career barriers decreased and career search self-efficacy and career preparation behavior increased. Career search self-efficacy and career preparation behavior increased in students with both low and high levels of career barriers. The difference between the low and high groups was significant for career search self-efficacy but not for career preparation behavior. The discipline-based career course was effective in decreasing perceptions of career barriers and increasing career search self-efficacy and career preparation behavior among nursing students. Copyright © 2015. Published by Elsevier B.V.

Optimizing Online Suicide Prevention: A Search Engine-Based Tailored Approach.

Science.gov (United States)

Arendt, Florian; Scherr, Sebastian

2017-11-01

Search engines are increasingly used to seek suicide-related information online, which can serve both harmful and helpful purposes. Google acknowledges this fact and presents a suicide-prevention result for particular search terms. Unfortunately, the result is only presented to a limited number of visitors. Hence, Google is missing the opportunity to provide help to vulnerable people. We propose a two-step approach to a tailored optimization: First, research will identify the risk factors. Second, search engines will reweight algorithms according to the risk factors. In this study, we show that the query share of the search term "poisoning" on Google shows substantial peaks corresponding to peaks in actual suicidal behavior. Accordingly, thresholds for showing the suicide-prevention result should be set to the lowest levels during the spring, on Sundays and Mondays, on New Year's Day, and on Saturdays following Thanksgiving. Search engines can help to save lives globally by utilizing a more tailored approach to suicide prevention.

CYCLOSA: Decentralizing Private Web Search Through SGX-Based Browser Extensions

OpenAIRE

Pires, Rafael; Goltzsche, David; Mokhtar, Sonia Ben; Bouchenak, Sara; Boutet, Antoine; Felber, Pascal; Kapitza, Rüdiger; Pasin, Marcelo; Schiavoni, Valerio

2018-01-01

By regularly querying Web search engines, users (unconsciously) disclose large amounts of their personal data as part of their search queries, among which some might reveal sensitive information (e.g. health issues, sexual, political or religious preferences). Several solutions exist to allow users querying search engines while improving privacy protection. However, these solutions suffer from a number of limitations: some are subject to user re-identification attacks, while others lack scala...

BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

Directory of Open Access Journals (Sweden)

Jiang Hualiang

2010-01-01

Full Text Available Abstract Background Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology. Results Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function, which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins. Conclusions This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.

A novel approach towards skill-based search and services of Open Educational Resources

NARCIS (Netherlands)

Ha, Kyung-Hun; Niemann, Katja; Schwertel, Uta; Holtkamp, Philipp; Pirkkalainen, Henri; Börner, Dirk; Kalz, Marco; Pitsilis, Vassilis; Vidalis, Ares; Pappa, Dimitra; Bick, Markus; Pawlowski, Jan; Wolpers, Martin

2011-01-01

Ha, K.-H., Niemann, K., Schwertel, U., Holtkamp, P., Pirkkalainen, H., Börner, D. et al (2011). A novel approach towards skill-based search and services of Open Educational Resources. In E. Garcia-Barriocanal, A. Öztürk, & M. C. Okur (Eds.), Metadata and Semantics Research: 5th International

Huitzoctli: A system to design Control Rod Pattern for BWR's using a hybrid method

International Nuclear Information System (INIS)

Castillo, Alejandro; Ortiz-Servin, Juan Jose; Perusquia, Raul; Morales, Luis B.

2011-01-01

Highlights: → The system was developed to design Control Rod Patterns for Boiling Water Reactors. → The critical reactor core and the thermal limits were fulfilled in all tested cases. → The Fuel Loading Pattern remains without changes during the iterative process. → The system uses the heuristics techniques: Scatter Search and Tabu Search. → The effective multiplication factor k eff at the EOC was improved in all tested cases. - Abstract: Huitzoctli system was developed to design Control Rod Patterns for Boiling Water Reactors (BWR). The main idea is to obtain a Control Rod Pattern under the following considerations: (a) the critical reactor core state is satisfied, (b) the axial power distribution must be adjusted to a target axial power distribution proposal, and (c) the maximum Fraction of Critical Power Ratio (MFLCPR), the maximum Fraction of Linear Power Density (FLPD) and the maximum Fraction of Average Planar Power Density (MPGR) must be fulfilled. Those parameters were obtained using the 3D CM-PRESTO code. In order to decrease the problem complexity, Control Cell Core load strategy was implemented; in the same way, intermediate axial positions and core eighth symmetry were took into account. In this work, the cycle length was divided in 12 burnup steps. The Fuel Loading Pattern is an input data and it remains without changes during the iterative process. The Huitzoctli system was developed to use the combinatorial heuristics techniques Scatter Search and Tabu Search. The first one was used as a global search method and the second one as a local search method. The Control Rod Patterns obtained with the Huitzoctli system were compared to other Control Rod Patterns designs obtained with other optimization techniques, under the same operating conditions. The results show a good performance of the system. In all cases the thermal limits were satisfied, and the axial power distribution was adjusted to the target axial power distribution almost

Category-based guidance of spatial attention during visual search for feature conjunctions.

Science.gov (United States)

Nako, Rebecca; Grubert, Anna; Eimer, Martin

2016-10-01

The question whether alphanumerical category is involved in the control of attentional target selection during visual search remains a contentious issue. We tested whether category-based attentional mechanisms would guide the allocation of attention under conditions where targets were defined by a combination of alphanumerical category and a basic visual feature, and search displays could contain both targets and partially matching distractor objects. The N2pc component was used as an electrophysiological marker of attentional object selection in tasks where target objects were defined by a conjunction of color and category (Experiment 1) or shape and category (Experiment 2). Some search displays contained the target or a nontarget object that matched either the target color/shape or its category among 3 nonmatching distractors. In other displays, the target and a partially matching nontarget object appeared together. N2pc components were elicited not only by targets and by color- or shape-matching nontargets, but also by category-matching nontarget objects, even on trials where a target was present in the same display. On these trials, the summed N2pc components to the 2 types of partially matching nontargets were initially equal in size to the target N2pc, suggesting that attention was allocated simultaneously and independently to all objects with target-matching features during the early phase of attentional processing. Results demonstrate that alphanumerical category is a genuine guiding feature that can operate in parallel with color or shape information to control the deployment of attention during visual search. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

Directory of Open Access Journals (Sweden)

Bożek Andrzej

2016-03-01

Full Text Available A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.

Design Optimization of Mixed-Criticality Real-Time Embedded Systems

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2015-01-01

is allocated several time slots on a processor. Tasks of different SILs can share a partition only if they are all elevated to the highest SIL among them. Such elevation leads to increased development costs, which increase dramatically with each SIL. Tasks of higher SILs can be decomposed into redundant...... structures of lower SIL tasks. We are interested to determine (i) the mapping of tasks to processors, (ii) the assignment of tasks to partitions, (iii) the decomposition of tasks into redundant lower SIL tasks, (iv) the sequence and size of the partition time slots on each processor, and (v) the schedule...... tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real-life benchmarks....

Job Search Methods: Consequences for Gender-based Earnings Inequality.

Science.gov (United States)

Huffman, Matt L.; Torres, Lisa

2001-01-01

Data from adults in Atlanta, Boston, and Los Angeles (n=1,942) who searched for work using formal (ads, agencies) or informal (networks) methods indicated that type of method used did not contribute to the gender gap in earnings. Results do not support formal job search as a way to reduce gender inequality. (Contains 55 references.) (SK)

'Alive' searches as complementing death searches in the epidemiological follow-up of Ontario miners

International Nuclear Information System (INIS)

Fair, M.E.; Newcombe, H.B.; Lalonde, P.; Poliquin, C.

1988-02-01

'Alive' searches have been used to complement the 'death' searches, in a study of the mortality experience of a cohort of Ontario miners. The purpose has been to develop a way of distinguishing between those cohort members who are 'confirmed' alive at a given time, and those who are 'lost to follow-up'. A total of 30,000 Workers' Compensation Board (WCB) records with valid Social Insurance Numbers (SIN) were used to search the income tax files by computer over two consecutive years (1977 and 1978) representing nearly 27 million tax returns. These tax file searches using SIN numbers have provided information on the procedures to be used in, and likely success of, the corresponding searches of the tax files that could be carried out where the SIN number is not available on the work records. The latter kind of search would have to be based on names, birth dates and such, and would be probabilistic in nature. The results of the study were as follows: After the initial death search, it was found that 7.5% of the cohort had died in Canada and their records were found on the Mortality Data Base. The remaining 92.5% has been 'assumed alive' in the earlier analysis. After the 'alive' follow-up using the income tax file, one was able to confirm that 89.1% of the 'assumed alive' had filed an income tax after the study period. Thus only 3.4% of the cohort remained untraced. Among those there could be an admixture of deaths outside of Canada, persons who have moved outside of Canada and are still alive, and/or persons alive within Canada, but who have not filed an income tax return. This study has indicated that the procedures developed are useful for purposes of 'alive' follow-up, for evaluation of the quality of the Mortality Data Base-cohort death file searches, for improving the accuracy of analytical results of epidemiological studies, and for reducing the cost and labour of resolving doubtful death searches

Personalized Profile Based Search Interface With Ranked and Clustered Display

National Research Council Canada - National Science Library

Kumar, Sachin; Oztekin, B. U; Ertoz, Levent; Singhal, Saurabh; Han, Euihong; Kumar, Vipin

2001-01-01

We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list...

Generalised Adaptive Harmony Search: A Comparative Analysis of Modern Harmony Search

Directory of Open Access Journals (Sweden)

Jaco Fourie

2013-01-01

Full Text Available Harmony search (HS was introduced in 2001 as a heuristic population-based optimisation algorithm. Since then HS has become a popular alternative to other heuristic algorithms like simulated annealing and particle swarm optimisation. However, some flaws, like the need for parameter tuning, were identified and have been a topic of study for much research over the last 10 years. Many variants of HS were developed to address some of these flaws, and most of them have made substantial improvements. In this paper we compare the performance of three recent HS variants: exploratory harmony search, self-adaptive harmony search, and dynamic local-best harmony search. We compare the accuracy of these algorithms, using a set of well-known optimisation benchmark functions that include both unimodal and multimodal problems. Observations from this comparison led us to design a novel hybrid that combines the best attributes of these modern variants into a single optimiser called generalised adaptive harmony search.

The Surface Extraction from TIN based Search-space Minimization (SETSM) algorithm

Science.gov (United States)

Noh, Myoung-Jong; Howat, Ian M.

2017-07-01

Digital Elevation Models (DEMs) provide critical information for a wide range of scientific, navigational and engineering activities. Submeter resolution, stereoscopic satellite imagery with high geometric and radiometric quality, and wide spatial coverage are becoming increasingly accessible for generating stereo-photogrammetric DEMs. However, low contrast and repeatedly-textured surfaces, such as snow and glacial ice at high latitudes, and mountainous terrains challenge existing stereo-photogrammetric DEM generation techniques, particularly without a-priori information such as existing seed DEMs or the manual setting of terrain-specific parameters. To utilize these data for fully-automatic DEM extraction at a large scale, we developed the Surface Extraction from TIN-based Search-space Minimization (SETSM) algorithm. SETSM is fully automatic (i.e. no search parameter settings are needed) and uses only the sensor model Rational Polynomial Coefficients (RPCs). SETSM adopts a hierarchical, combined image- and object-space matching strategy utilizing weighted normalized cross-correlation with both original distorted and geometrically corrected images for overcoming ambiguities caused by foreshortening and occlusions. In addition, SETSM optimally minimizes search-spaces to extract optimal matches over problematic terrains by iteratively updating object surfaces within a Triangulated Irregular Network, and utilizes a geometric-constrained blunder and outlier detection in object space. We prove the ability of SETSM to mitigate typical stereo-photogrammetric matching problems over a range of challenging terrains. SETSM is the primary DEM generation software for the US National Science Foundation's ArcticDEM project.

Evidence-based medicine - searching the medical literature. Part 1.

African Journals Online (AJOL)

Ann Burgess

password for access via HINARIa2 use that to log in. Then you can retrieve articles from the 6000 journals that will be available to you. You cannot retrieve the full text from journals that do not allow free access or HINARI access. How to search the literature on the internet. Before you start your search take a moment to think ...

A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

Science.gov (United States)

Guo, Shengwen; Fei, Baowei

2009-02-01

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.

Science.gov (United States)

Guo, Shengwen; Fei, Baowei

2009-03-27

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

Theoretical and Empirical Analyses of an Improved Harmony Search Algorithm Based on Differential Mutation Operator

Directory of Open Access Journals (Sweden)

Longquan Yong

2012-01-01

Full Text Available Harmony search (HS method is an emerging metaheuristic optimization algorithm. In this paper, an improved harmony search method based on differential mutation operator (IHSDE is proposed to deal with the optimization problems. Since the population diversity plays an important role in the behavior of evolution algorithm, the aim of this paper is to calculate the expected population mean and variance of IHSDE from theoretical viewpoint. Numerical results, compared with the HSDE, NGHS, show that the IHSDE method has good convergence property over a test-suite of well-known benchmark functions.

A Privacy-Preserving Intelligent Medical Diagnosis System Based on Oblivious Keyword Search

Directory of Open Access Journals (Sweden)

Zhaowen Lin

2017-01-01

Full Text Available One of the concerns people have is how to get the diagnosis online without privacy being jeopardized. In this paper, we propose a privacy-preserving intelligent medical diagnosis system (IMDS, which can efficiently solve the problem. In IMDS, users submit their health examination parameters to the server in a protected form; this submitting process is based on Paillier cryptosystem and will not reveal any information about their data. And then the server retrieves the most likely disease (or multiple diseases from the database and returns it to the users. In the above search process, we use the oblivious keyword search (OKS as a basic framework, which makes the server maintain the computational ability but cannot learn any personal information over the data of users. Besides, this paper also provides a preprocessing method for data stored in the server, to make our protocol more efficient.

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding.

Science.gov (United States)

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

The Linehaul-Feeder Vehicle Routing Problem with Virtual Depots and Time Windows

Directory of Open Access Journals (Sweden)

Huey-Kuo Chen

2011-01-01

Full Text Available This paper addresses the linehaul-feeder vehicle routing problem with virtual depots and time windows (LFVRPTW. Small and large vehicles deliver services to customers within time constraints; small vehicles en route may reload commodities from either the physical depot or from the larger vehicle at a virtual depot before continuing onward. A two-stage solution heuristic involving Tabu search is proposed to solve this problem. The test results show that the LFVRPTW performs better than the vehicle routing problem with time windows in terms of both objective value and the number of small vehicles dispatched.

Reliable Rescue Routing Optimization for Urban Emergency Logistics under Travel Time Uncertainty

Directory of Open Access Journals (Sweden)

Qiuping Li

2018-02-01

Full Text Available The reliability of rescue routes is critical for urban emergency logistics during disasters. However, studies on reliable rescue routing under stochastic networks are still rare. This paper proposes a multiobjective rescue routing model for urban emergency logistics under travel time reliability. A hybrid metaheuristic integrating ant colony optimization (ACO and tabu search (TS was designed to solve the model. An experiment optimizing rescue routing plans under a real urban storm event, was carried out to validate the proposed model. The experimental results showed how our approach can improve rescue efficiency with high travel time reliability.

Information retrieval for children based on the aggregated search paradigm

NARCIS (Netherlands)

Duarte Torres, Sergio

This report presents research to develop information services for children by expanding and adapting current Information retrieval technologies according to the search characteristics and needs of children. Concretely, we will employ the aggregated search paradigm as theoretical framework. The

A hybrid approach for integrated healthcare cooperative purchasing and supply chain configuration.

Science.gov (United States)

Rego, Nazaré; Claro, João; Pinho de Sousa, Jorge

2014-12-01

This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.

Memoryless cooperative graph search based on the simulated annealing algorithm

International Nuclear Information System (INIS)

Hou Jian; Yan Gang-Feng; Fan Zhen

2011-01-01

We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter—radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment. (interdisciplinary physics and related areas of science and technology)

Study of Search Engine Transaction Logs Shows Little Change in How Users use Search Engines. A review of: Jansen, Bernard J., and Amanda Spink. “How Are We Searching the World Wide Web? A Comparison of Nine Search Engine Transaction Logs.” Information Processing & Management 42.1 (2006: 248‐263.

Directory of Open Access Journals (Sweden)

David Hook

2006-09-01

Full Text Available Objective – To examine the interactions between users and search engines, and how they have changed over time. Design – Comparative analysis of search engine transaction logs. Setting – Nine major analyses of search engine transaction logs. Subjects – Nine web search engine studies (4 European, 5 American over a seven‐year period, covering the search engines Excite, Fireball, AltaVista, BWIE and AllTheWeb. Methods – The results from individual studies are compared by year of study for percentages of single query sessions, one term queries, operator (and, or, not, etc. usage and single result page viewing. As well, the authors group the search queries into eleven different topical categories and compare how the breakdown has changed over time. Main Results – Based on the percentage of single query sessions, it does not appear that the complexity of interactions has changed significantly for either the U.S.‐based or the European‐based search engines. As well, there was little change observed in the percentage of one‐term queries over the years of study for either the U.S.‐based or the European‐based search engines. Few users (generally less than 20% use Boolean or other operators in their queries, and these percentages have remained relatively stable. One area of noticeable change is in the percentage of users viewing only one results page, which has increased over the years of study. Based on the studies of the U.S.‐based search engines, the topical categories of ‘People, Place or Things’ and ‘Commerce, Travel, Employment or Economy’ are becoming more popular, while the categories of ‘Sex and Pornography’ and ‘Entertainment or Recreation’ are declining. Conclusions – The percentage of users viewing only one results page increased during the years of the study, while the percentages of single query sessions, oneterm sessions and operator usage remained stable. The increase in single result page viewing

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic

Science.gov (United States)

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals. PMID:27413364

A Fast Framework for Abrupt Change Detection Based on Binary Search Trees and Kolmogorov Statistic.

Science.gov (United States)

Qi, Jin-Peng; Qi, Jie; Zhang, Qing

2016-01-01

Change-Point (CP) detection has attracted considerable attention in the fields of data mining and statistics; it is very meaningful to discuss how to quickly and efficiently detect abrupt change from large-scale bioelectric signals. Currently, most of the existing methods, like Kolmogorov-Smirnov (KS) statistic and so forth, are time-consuming, especially for large-scale datasets. In this paper, we propose a fast framework for abrupt change detection based on binary search trees (BSTs) and a modified KS statistic, named BSTKS (binary search trees and Kolmogorov statistic). In this method, first, two binary search trees, termed as BSTcA and BSTcD, are constructed by multilevel Haar Wavelet Transform (HWT); second, three search criteria are introduced in terms of the statistic and variance fluctuations in the diagnosed time series; last, an optimal search path is detected from the root to leaf nodes of two BSTs. The studies on both the synthetic time series samples and the real electroencephalograph (EEG) recordings indicate that the proposed BSTKS can detect abrupt change more quickly and efficiently than KS, t-statistic (t), and Singular-Spectrum Analyses (SSA) methods, with the shortest computation time, the highest hit rate, the smallest error, and the highest accuracy out of four methods. This study suggests that the proposed BSTKS is very helpful for useful information inspection on all kinds of bioelectric time series signals.

Searching Trajectories by Regions of Interest

KAUST Repository

Shang, Shuo

2017-03-22

With the increasing availability of moving-object tracking data, trajectory search is increasingly important. We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in many popular applications such as trip planning and recommendation, and location based services in general. TSR query processing faces three challenges: how to model the spatial-density correlation between query regions and data trajectories, how to effectively prune the search space, and how to effectively schedule multiple so-called query sources. To tackle these challenges, a series of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.

Searching Trajectories by Regions of Interest

KAUST Repository

Shang, Shuo; chen, Lisi; Jensen, Christian S.; Wen, Ji-Rong; Kalnis, Panos

2017-01-01

With the increasing availability of moving-object tracking data, trajectory search is increasingly important. We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in many popular applications such as trip planning and recommendation, and location based services in general. TSR query processing faces three challenges: how to model the spatial-density correlation between query regions and data trajectories, how to effectively prune the search space, and how to effectively schedule multiple so-called query sources. To tackle these challenges, a series of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.

Health literacy and usability of clinical trial search engines.

Science.gov (United States)

Utami, Dina; Bickmore, Timothy W; Barry, Barbara; Paasche-Orlow, Michael K

2014-01-01

Several web-based search engines have been developed to assist individuals to find clinical trials for which they may be interested in volunteering. However, these search engines may be difficult for individuals with low health and computer literacy to navigate. The authors present findings from a usability evaluation of clinical trial search tools with 41 participants across the health and computer literacy spectrum. The study consisted of 3 parts: (a) a usability study of an existing web-based clinical trial search tool; (b) a usability study of a keyword-based clinical trial search tool; and (c) an exploratory study investigating users' information needs when deciding among 2 or more candidate clinical trials. From the first 2 studies, the authors found that users with low health literacy have difficulty forming queries using keywords and have significantly more difficulty using a standard web-based clinical trial search tool compared with users with adequate health literacy. From the third study, the authors identified the search factors most important to individuals searching for clinical trials and how these varied by health literacy level.

An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

OpenAIRE

Gramajo, German; Shankar, Praveen

2017-01-01

A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of ...

Use of Tabu Search in a Solver to Map Complex Networks onto Emulab Testbeds

National Research Council Canada - National Science Library

MacDonald, Jason E

2007-01-01

The University of Utah's solver for the testbed mapping problem uses a simulated annealing metaheuristic algorithm to map a researcher's experimental network topology onto available testbed resources...

An Advanced Tabu Search Approach to Solving the Mixed Payload Airlift Load Planning Problem

Science.gov (United States)

2009-03-01

cargo, and the problem therefore becomes trivial. 3. Shoring: Some cargo requires shoring which is small planks of plywood stacked on top of each...Integer Programming Method In 1989, Kevin Ng examined the bin-packing MPALP for Canada’s C-130 aircraft (Ng 1992). His goal was to move a set of... leadership & ethics [ ] warfighting [ ] international security [ ] doctrine [X] other (specify): Military Airlift

Use of Tabu Search in a Solver to Map Complex Networks onto Emulab Testbeds

Science.gov (United States)

2007-03-01

for. Our PF Chang dinners and Starbuck coffee breaks were pivotal in reconstituting me to take on another day at AFIT. I don’t know how I would’ve done...performance of assign. Option Description Value -s <seed> Random Number Generator Seed varies -P Prune Unsuable Pclasses n/a -H <float> Branching

A tabu search algorithm for scheduling a single robot in a job-shop environment

NARCIS (Netherlands)

Hurink, Johann L.; Knust, S.

1999-01-01

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time

A tabu search algorithm for scheduling a single robot in a job-shop environment

NARCIS (Netherlands)

Hurink, Johann L.; Knust, Sigrid

2002-01-01

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time

When is a search not a search? A comparison of searching the AMED complementary health database via EBSCOhost, OVID and DIALOG.

Science.gov (United States)

Younger, Paula; Boddy, Kate

2009-06-01

The researchers involved in this study work at Exeter Health library and at the Complementary Medicine Unit, Peninsula School of Medicine and Dentistry (PCMD). Within this collaborative environment it is possible to access the electronic resources of three institutions. This includes access to AMED and other databases using different interfaces. The aim of this study was to investigate whether searching different interfaces to the AMED allied health and complementary medicine database produced the same results when using identical search terms. The following Internet-based AMED interfaces were searched: DIALOG DataStar; EBSCOhost and OVID SP_UI01.00.02. Search results from all three databases were saved in an endnote database to facilitate analysis. A checklist was also compiled comparing interface features. In our initial search, DIALOG returned 29 hits, OVID 14 and Ebsco 8. If we assume that DIALOG returned 100% of potential hits, OVID initially returned only 48% of hits and EBSCOhost only 28%. In our search, a researcher using the Ebsco interface to carry out a simple search on AMED would miss over 70% of possible search hits. Subsequent EBSCOhost searches on different subjects failed to find between 21 and 86% of the hits retrieved using the same keywords via DIALOG DataStar. In two cases, the simple EBSCOhost search failed to find any of the results found via DIALOG DataStar. Depending on the interface, the number of hits retrieved from the same database with the same simple search can vary dramatically. Some simple searches fail to retrieve a substantial percentage of citations. This may result in an uninformed literature review, research funding application or treatment intervention. In addition to ensuring that keywords, spelling and medical subject headings (MeSH) accurately reflect the nature of the search, database users should include wildcards and truncation and adapt their search strategy substantially to retrieve the maximum number of appropriate

Real-Time Search in Clouds

OpenAIRE

Uddin, Misbah; Skinner, Amy; Stadler, Rolf; Clemm, Alexander

2013-01-01

We developed a novel approach for management of networks/networked systems based on network search [4]. Network search provides a simple, uniform interface, through which human administrators and management applications can obtain network information, configuration or operational, without knowing its schema and location. We believe that the capability of network search will spur the development of new tools for human administrators and enable the rapid development of new classes of network co...

Exploration Opportunity Search of Near-earth Objects Based on Analytical Gradients

Science.gov (United States)

Ren, Yuan; Cui, Ping-Yuan; Luan, En-Jie

2008-07-01

The problem of search of opportunity for the exploration of near-earth minor objects is investigated. For rendezvous missions, the analytical gradients of the performance index with respect to the free parameters are derived using the variational calculus and the theory of state-transition matrix. After generating randomly some initial guesses in the search space, the performance index is optimized, guided by the analytical gradients, leading to the local minimum points representing the potential launch opportunities. This method not only keeps the global-search property of the traditional method, but also avoids the blindness in the latter, thereby increasing greatly the computing speed. Furthermore, with this method, the searching precision could be controlled effectively.

A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

Directory of Open Access Journals (Sweden)

Huixin Tian

2016-01-01

Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

Directory of Open Access Journals (Sweden)

Yong-Bi Fu

2017-07-01

Full Text Available Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

Science.gov (United States)

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

Spatial search by quantum walk

International Nuclear Information System (INIS)

Childs, Andrew M.; Goldstone, Jeffrey

2004-01-01

Grover's quantum search algorithm provides a way to speed up combinatorial search, but is not directly applicable to searching a physical database. Nevertheless, Aaronson and Ambainis showed that a database of N items laid out in d spatial dimensions can be searched in time of order √(N) for d>2, and in time of order √(N) poly(log N) for d=2. We consider an alternative search algorithm based on a continuous-time quantum walk on a graph. The case of the complete graph gives the continuous-time search algorithm of Farhi and Gutmann, and other previously known results can be used to show that √(N) speedup can also be achieved on the hypercube. We show that full √(N) speedup can be achieved on a d-dimensional periodic lattice for d>4. In d=4, the quantum walk search algorithm takes time of order √(N) poly(log N), and in d<4, the algorithm does not provide substantial speedup

Design considerations for a large-scale image-based text search engine in historical manuscript collections

NARCIS (Netherlands)

Schomaker, Lambertus

2016-01-01

This article gives an overview of design considerations for a handwriting search engine based on pattern recognition and high-performance computing, “Monk”. In order to satisfy multiple and often conflicting technological requirements, an architecture is used which heavily relies on high-performance

PTree: pattern-based, stochastic search for maximum parsimony phylogenies

Directory of Open Access Journals (Sweden)

Ivan Gregor

2013-06-01

Full Text Available Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000–8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.

PTree: pattern-based, stochastic search for maximum parsimony phylogenies.

Science.gov (United States)

Gregor, Ivan; Steinbrück, Lars; McHardy, Alice C

2013-01-01

Phylogenetic reconstruction is vital to analyzing the evolutionary relationship of genes within and across populations of different species. Nowadays, with next generation sequencing technologies producing sets comprising thousands of sequences, robust identification of the tree topology, which is optimal according to standard criteria such as maximum parsimony, maximum likelihood or posterior probability, with phylogenetic inference methods is a computationally very demanding task. Here, we describe a stochastic search method for a maximum parsimony tree, implemented in a software package we named PTree. Our method is based on a new pattern-based technique that enables us to infer intermediate sequences efficiently where the incorporation of these sequences in the current tree topology yields a phylogenetic tree with a lower cost. Evaluation across multiple datasets showed that our method is comparable to the algorithms implemented in PAUP* or TNT, which are widely used by the bioinformatics community, in terms of topological accuracy and runtime. We show that our method can process large-scale datasets of 1,000-8,000 sequences. We believe that our novel pattern-based method enriches the current set of tools and methods for phylogenetic tree inference. The software is available under: http://algbio.cs.uni-duesseldorf.de/webapps/wa-download/.