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Sample records for tabu search based

  1. Permutation based decision making under fuzzy environment using Tabu search

    Directory of Open Access Journals (Sweden)

    Mahdi Bashiri

    2012-04-01

    Full Text Available One of the techniques, which are used for Multiple Criteria Decision Making (MCDM is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method.

  2. Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints

    Directory of Open Access Journals (Sweden)

    Rajan Asir Christober Gnanakkan Charles

    2009-01-01

    Full Text Available This paper presents a new approach to solve short-term unit commitment problem (UCP using Neural Based Tabu Search (NBTS with cooling and banking constraints. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units. Numerical results are shown to compare the superiority of the cost solutions obtained using the Tabu Search (TS method, Dynamic Programming (DP and Lagrangian Relaxation (LR methods in reaching proper unit commitment.

  3. Three-dimensional high-precision indoor positioning strategy using Tabu search based on visible light communication

    Science.gov (United States)

    Peng, Qi; Guan, Weipeng; Wu, Yuxiang; Cai, Ye; Xie, Canyu; Wang, Pengfei

    2018-01-01

    This paper proposes a three-dimensional (3-D) high-precision indoor positioning strategy using Tabu search based on visible light communication. Tabu search is a powerful global optimization algorithm, and the 3-D indoor positioning can be transformed into an optimal solution problem. Therefore, in the 3-D indoor positioning, the optimal receiver coordinate can be obtained by the Tabu search algorithm. For all we know, this is the first time the Tabu search algorithm is applied to visible light positioning. Each light-emitting diode (LED) in the system broadcasts a unique identity (ID) and transmits the ID information. When the receiver detects optical signals with ID information from different LEDs, using the global optimization of the Tabu search algorithm, the 3-D high-precision indoor positioning can be realized when the fitness value meets certain conditions. Simulation results show that the average positioning error is 0.79 cm, and the maximum error is 5.88 cm. The extended experiment of trajectory tracking also shows that 95.05% positioning errors are below 1.428 cm. It can be concluded from the data that the 3-D indoor positioning based on the Tabu search algorithm achieves the requirements of centimeter level indoor positioning. The algorithm used in indoor positioning is very effective and practical and is superior to other existing methods for visible light indoor positioning.

  4. Optimization of fuel cells for BWR based in Tabu modified search

    International Nuclear Information System (INIS)

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

    2004-01-01

    The advances in the development of a computational system for the design and optimization of cells for assemble of fuel of Boiling Water Reactors (BWR) are presented. The method of optimization is based on the technique of Tabu Search (Tabu Search, TS) implemented in progressive stages designed to accelerate the search and to reduce the time used in the process of optimization. It was programed an algorithm to create the first solution. Also for to diversify the generation of random numbers, required by the technical TS, it was used the Makoto Matsumoto function obtaining excellent results. The objective function has been coded in such a way that can adapt to optimize different parameters like they can be the enrichment average or the peak factor of radial power. The neutronic evaluation of the cells is carried out in a fine way by means of the HELIOS simulator. In the work the main characteristics of the system are described and an application example is presented to the design of a cell of 10x10 bars of fuel with 10 different enrichment compositions and gadolinium content. (Author)

  5. Optimization of fuel cells for BWR based in Tabu modified search; Optimizacion de celdas de combustible para BWR basada en busqueda Tabu modificada

    Energy Technology Data Exchange (ETDEWEB)

    Martin del Campo M, C.; Francois L, J.L. [Facultad de Ingenieria, UNAM, Laboratorio de Analisis en Ingenieria de Reactores Nucleares, Paseo Cuauhnahuac 8532, 62550 Jiutepec, Morelos (Mexico); Palomera P, M.A. [Facultad de Ingenieria, UNAM, Posgrado en Ingenieria en Computacion, Circuito exterior s/n, Ciudad Universitaria, Mexico, D.F. (Mexico)]. e-mail: cmcm@fi-b.unam.mx

    2004-07-01

    The advances in the development of a computational system for the design and optimization of cells for assemble of fuel of Boiling Water Reactors (BWR) are presented. The method of optimization is based on the technique of Tabu Search (Tabu Search, TS) implemented in progressive stages designed to accelerate the search and to reduce the time used in the process of optimization. It was programed an algorithm to create the first solution. Also for to diversify the generation of random numbers, required by the technical TS, it was used the Makoto Matsumoto function obtaining excellent results. The objective function has been coded in such a way that can adapt to optimize different parameters like they can be the enrichment average or the peak factor of radial power. The neutronic evaluation of the cells is carried out in a fine way by means of the HELIOS simulator. In the work the main characteristics of the system are described and an application example is presented to the design of a cell of 10x10 bars of fuel with 10 different enrichment compositions and gadolinium content. (Author)

  6. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  8. 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.

  9. 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

  10. 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...

  11. 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.

  12. Tabu search for target-radar assignment

    DEFF Research Database (Denmark)

    Hindsberger, Magnus; Vidal, Rene Victor Valqui

    2000-01-01

    In the paper the problem of assigning air-defense illumination radars to enemy targets is presented. A tabu search metaheuristic solution is described and the results achieved are compared to those of other heuristic approaches, implementation and experimental aspects are discussed. It is argued ...

  13. An Iterated Tabu Search Approach for the Clique Partitioning Problem

    Directory of Open Access Journals (Sweden)

    Gintaras Palubeckis

    2014-01-01

    all cliques induced by the subsets is as small as possible. We develop an iterated tabu search (ITS algorithm for solving this problem. The proposed algorithm incorporates tabu search, local search, and solution perturbation procedures. We report computational results on CPP instances of size up to 2000 vertices. Performance comparisons of ITS against state-of-the-art methods from the literature demonstrate the competitiveness of our approach.

  14. Application of Tabu Search Algorithm in Job Shop Scheduling

    Directory of Open Access Journals (Sweden)

    Betrianis Betrianis

    2010-10-01

    Full Text Available Tabu Search is one of local search methods which is used to solve the combinatorial optimization problem. This method aimed is to make the searching process of the best solution in a complex combinatorial optimization problem(np hard, ex : job shop scheduling problem, became more effective, in a less computational time but with no guarantee to optimum solution.In this paper, tabu search is used to solve the job shop scheduling problem consists of 3 (three cases, which is ordering package of September, October and November with objective of minimizing makespan (Cmax. For each ordering package, there is a combination for initial solution and tabu list length. These result then  compared with 4 (four other methods using basic dispatching rules such as Shortest Processing Time (SPT, Earliest Due Date (EDD, Most Work Remaining (MWKR dan First Come First Served (FCFS. Scheduling used Tabu Search Algorithm is sensitive for variables changes and gives makespan shorter than scheduling used by other four methods.

  15. Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR for Load Forecasting

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    Cheng-Wen Lee

    2016-10-01

    Full Text Available Hybridizing chaotic evolutionary algorithms with support vector regression (SVR to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives.

  16. 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.

  17. 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

  18. Tabu search, a versatile technique for the functions optimization

    International Nuclear Information System (INIS)

    Castillo M, J.A.

    2003-01-01

    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)

  19. 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.

  20. Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints

    International Nuclear Information System (INIS)

    Pothiya, Saravuth; Ngamroo, Issarachai; Kongprawechnon, Waree

    2008-01-01

    This paper presents a new optimization technique based on a multiple tabu search algorithm (MTS) to solve the dynamic economic dispatch (ED) problem with generator constraints. In the constrained dynamic ED problem, the load demand and spinning reserve capacity as well as some practical operation constraints of generators, such as ramp rate limits and prohibited operating zone are taken into consideration. The MTS algorithm introduces additional mechanisms such as initialization, adaptive searches, multiple searches, crossover and restarting process. To show its efficiency, the MTS algorithm is applied to solve constrained dynamic ED problems of power systems with 6 and 15 units. The results obtained from the MTS algorithm are compared to those achieved from the conventional approaches, such as simulated annealing (SA), genetic algorithm (GA), tabu search (TS) algorithm and particle swarm optimization (PSO). The experimental results show that the proposed MTS algorithm approaches is able to obtain higher quality solutions efficiently and with less computational time than the conventional approaches

  1. Pressurized water reactor in-core nuclear fuel management by tabu search

    International Nuclear Information System (INIS)

    Hill, Natasha J.; Parks, Geoffrey T.

    2015-01-01

    Highlights: • We develop a tabu search implementation for PWR reload core design. • We conduct computational experiments to find optimal parameter values. • We test the performance of the algorithm on two representative PWR geometries. • We compare this performance with that given by established optimization methods. • Our tabu search implementation outperforms these methods in all cases. - Abstract: Optimization of the arrangement of fuel assemblies and burnable poisons when reloading pressurized water reactors has, in the past, been performed with many different algorithms in an attempt to make reactors more economic and fuel efficient. The use of the tabu search algorithm in tackling reload core design problems is investigated further here after limited, but promising, previous investigations. The performance of the tabu search implementation developed was compared with established genetic algorithm and simulated annealing optimization routines. Tabu search outperformed these existing programs for a number of different objective functions on two different representative core geometries

  2. 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)

  3. 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.

  4. Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

    Directory of Open Access Journals (Sweden)

    Yuzhen Yang

    2014-01-01

    Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

  5. 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)

  6. A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles

    Directory of Open Access Journals (Sweden)

    Ricardo Soto

    2015-01-01

    Full Text Available The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling a n2 × n2 grid, composed of n columns, n rows, and n subgrids, each one containing distinct integers from 1 to n2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with the alldifferent global constraint from the constraint programming world. The alldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.

  7. 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.

  8. Cooperative mobile agents search using beehive partitioned structure and Tabu Random search algorithm

    Science.gov (United States)

    Ramazani, Saba; Jackson, Delvin L.; Selmic, Rastko R.

    2013-05-01

    In search and surveillance operations, deploying a team of mobile agents provides a robust solution that has multiple advantages over using a single agent in efficiency and minimizing exploration time. This paper addresses the challenge of identifying a target in a given environment when using a team of mobile agents by proposing a novel method of mapping and movement of agent teams in a cooperative manner. The approach consists of two parts. First, the region is partitioned into a hexagonal beehive structure in order to provide equidistant movements in every direction and to allow for more natural and flexible environment mapping. Additionally, in search environments that are partitioned into hexagons, mobile agents have an efficient travel path while performing searches due to this partitioning approach. Second, we use a team of mobile agents that move in a cooperative manner and utilize the Tabu Random algorithm to search for the target. Due to the ever-increasing use of robotics and Unmanned Aerial Vehicle (UAV) platforms, the field of cooperative multi-agent search has developed many applications recently that would benefit from the use of the approach presented in this work, including: search and rescue operations, surveillance, data collection, and border patrol. In this paper, the increased efficiency of the Tabu Random Search algorithm method in combination with hexagonal partitioning is simulated, analyzed, and advantages of this approach are presented and discussed.

  9. 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.

  10. Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

    DEFF Research Database (Denmark)

    Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

    2007-01-01

    exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....

  11. Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

    DEFF Research Database (Denmark)

    Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

    2007-01-01

    This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...

  12. An Elitist Multiobjective Tabu Search for Optimal Design of Groundwater Remediation Systems.

    Science.gov (United States)

    Yang, Yun; Wu, Jianfeng; Wang, Jinguo; Zhou, Zhifang

    2017-11-01

    This study presents a new multiobjective evolutionary algorithm (MOEA), the elitist multiobjective tabu search (EMOTS), and incorporates it with MODFLOW/MT3DMS to develop a groundwater simulation-optimization (SO) framework based on modular design for optimal design of groundwater remediation systems using pump-and-treat (PAT) technique. The most notable improvement of EMOTS over the original multiple objective tabu search (MOTS) lies in the elitist strategy, selection strategy, and neighborhood move rule. The elitist strategy is to maintain all nondominated solutions within later search process for better converging to the true Pareto front. The elitism-based selection operator is modified to choose two most remote solutions from current candidate list as seed solutions to increase the diversity of searching space. Moreover, neighborhood solutions are uniformly generated using the Latin hypercube sampling (LHS) in the bounded neighborhood space around each seed solution. To demonstrate the performance of the EMOTS, we consider a synthetic groundwater remediation example. Problem formulations consist of two objective functions with continuous decision variables of pumping rates while meeting water quality requirements. Especially, sensitivity analysis is evaluated through the synthetic case for determination of optimal combination of the heuristic parameters. Furthermore, the EMOTS is successfully applied to evaluate remediation options at the field site of the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. With both the hypothetical and the large-scale field remediation sites, the EMOTS-based SO framework is demonstrated to outperform the original MOTS in achieving the performance metrics of optimality and diversity of nondominated frontiers with desirable stability and robustness. © 2017, National Ground Water Association.

  13. 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....

  14. 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.

  15. The max–min ant system and tabu search for pressurized water reactor loading pattern design

    International Nuclear Information System (INIS)

    Lin, Chaung; Chen, Ying-Hsiu

    2014-01-01

    Highlights: • An automatic loading pattern design tool for a pressurized water reactor is developed. • The design method consists of max–min ant system and tabu search. • The heuristic rules are developed to generate the candidates for tabu search. • The initial solution of tabu search is provided by max–min ant system. • The new algorithm shows very satisfactory results compared to the old one. - Abstract: An automatic loading pattern (LP) design tool for a pressurized water reactor is developed. The design procedure consists of two steps: first, a LP is generated using max–min ant system (MMAS) and then tabu search (TS) is adopted to search the satisfactory LP. The MMAS is previously developed and the TS process is newly-developed. The heuristic rules are implemented to generate the candidate LP in TS process. The heuristic rules are comprised of two kinds of action, i.e., a single swap in the location of two fuel assemblies and rotation of fuel assembly. Since developed TS process is a local search algorithm, it is efficient for the minor change of LP. It means that a proper initial LP should be provided by the first step, i.e., by MMAS. The design requirements such as hot channel factor, the hot zero power moderator temperature coefficient, and cycle length are formulated in the objective function. The results show that the developed tool can obtain the satisfactory LP and dramatically reduce the computation time compared with previous tool using ant system alone

  16. ASIGNACIÓN DE SUPERVISORES FORESTALES: RESOLUCIÓN MEDIANTE UN ALGORITMO TABU SEARCH ASSIGNMENT OF FOREST SUPERVISORS: RESOLUTION BY MEANS OF A TABU SEARCH ALGORITHM

    Directory of Open Access Journals (Sweden)

    Lorena Pradenas Rojas

    2008-12-01

    Full Text Available En este estudio se presenta un modelo matemático para un problema genérico de asignación de personal. Se implementa y evalúa un procedimiento de solución mediante la metaheurística Tabu Search. El algoritmo propuesto es usado para resolver un caso real de asignación de supervisores forestales. Los resultados muestran que el algoritmo desarrollado es eficiente en la resolución de este tipo de problema y tiene un amplio rango de aplicación para otras situaciones reales.This study presents a mathematical model for a generic problem of staff allocation. A solution is implemented and evaluated by means of the Tabu Search metaheuristic. The proposed algorithm is used to solve a real case of forestry supervisors' allocation. The results show that the developed algorithm is efficient solving this kind of problems and that it has a wide range of application for other real situations.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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%.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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)

  13. 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

  14. Kombinasi Firefly Algorithm-Tabu Search untuk Penyelesaian Traveling Salesman Problem

    Directory of Open Access Journals (Sweden)

    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.

  15. 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.

  16. 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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. 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

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  8. TABU PEREMPUAN DALAM BUDAYA MASYARAKAT BANTEN

    Directory of Open Access Journals (Sweden)

    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.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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)

  16. 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.

  17. 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

  18. 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

  19. 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...

  20. Space based microlensing planet searches

    Directory of Open Access Journals (Sweden)

    Tisserand Patrick

    2013-04-01

    Full Text Available The discovery of extra-solar planets is arguably the most exciting development in astrophysics during the past 15 years, rivalled only by the detection of dark energy. Two projects unite the communities of exoplanet scientists and cosmologists: the proposed ESA M class mission EUCLID and the large space mission WFIRST, top ranked by the Astronomy 2010 Decadal Survey report. The later states that: “Space-based microlensing is the optimal approach to providing a true statistical census of planetary systems in the Galaxy, over a range of likely semi-major axes”. They also add: “This census, combined with that made by the Kepler mission, will determine how common Earth-like planets are over a wide range of orbital parameters”. We will present a status report of the results obtained by microlensing on exoplanets and the new objectives of the next generation of ground based wide field imager networks. We will finally discuss the fantastic prospect offered by space based microlensing at the horizon 2020–2025.

  1. 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...

  2. 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.

  3. 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 ...

  4. 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…

  5. 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...

  6. 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...

  7. 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...

  8. 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.

  9. 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 ...

  10. 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.

  11. 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)

  12. 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)

  13. 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....

  14. 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.

  15. Accelerator-based neutrino oscillation searches

    International Nuclear Information System (INIS)

    Whitehouse, D.A.; Rameika, R.; Stanton, N.

    1993-01-01

    This paper attempts to summarize the neutrino oscillation section of the Workshop on Future Directions in Particle and Nuclear Physics at Multi-GeV Hadron Beam Facilities. There were very lively discussions about the merits of the different oscillation channels, experiments, and facilities, but we believe a substantial consensus emerged. First, the next decade is one of great potential for discovery in neutrino physics, but it is also one of great peril. The possibility that neutrino oscillations explain the solar neutrino and atmospheric neutrino experiments, and the indirect evidence that Hot Dark Matter (HDM) in the form of light neutrinos might make up 30% of the mass of the universe, point to areas where accelerator-based experiments could play a crucial role in piecing together the puzzle. At the same time, the field faces a very uncertain future. The LSND experiment at LAMPF is the only funded neutrino oscillation experiment in the United States and it is threatened by the abrupt shutdown of LAMPF proposed for fiscal 1994. The future of neutrino physics at the Brookhaven National Laboratory AGS depends the continuation of High Energy Physics (HEP) funding after the RHIC startup. Most proposed neutrino oscillation searches at Fermilab depend on the completion of the Main Injector project and on the construction of a new neutrino beamline, which is uncertain at this point. The proposed KAON facility at TRIUMF would provide a neutrino beam similar to that at the AGS but with a much increase intensity. The future of KAON is also uncertain. Despite the difficult obstacles present, there is a real possibility that we are on the verge of understanding the masses and mixings of the neutrinos. The physics importance of such a discovery can not be overstated. The current experimental status and future possibilities are discussed below

  16. A grammar checker based on web searching

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. 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

  19. 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...

  20. Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

    Directory of Open Access Journals (Sweden)

    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.

  1. 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.

  2. 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.

  3. 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....

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.)

  9. 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

  10. 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...

  11. 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.

  12. 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)

  13. 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).

  14. 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...

  15. Neurophysiological Based Methods of Guided Image Search

    National Research Council Canada - National Science Library

    Marchak, Frank

    2003-01-01

    .... We developed a model of visual feature detection, the Neuronal Synchrony Model, based on neurophysiological models of temporal neuronal processing, to improve the accuracy of automatic detection...

  16. 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.

  17. In Search of...Brain-Based Education.

    Science.gov (United States)

    Bruer, John T.

    1999-01-01

    Debunks two ideas appearing in brain-based education articles: the educational significance of brain laterality (right brain versus left brain) and claims for a sensitive period of brain development in young children. Brain-based education literature provides a popular but misleading mix of fact, misinterpretation, and fantasy. (47 references (MLH)

  18. 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.

  19. 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)

  20. 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.

  1. 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...

  2. 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).

  3. 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...

  4. 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...

  5. 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...

  6. Learning Dispatching Rules for Scheduling: A Synergistic View Comprising Decision Trees, Tabu Search and Simulation

    Directory of Open Access Journals (Sweden)

    Atif Shahzad

    2016-02-01

    Full Text Available A promising approach for an effective shop scheduling that synergizes the benefits of the combinatorial optimization, supervised learning and discrete-event simulation is presented. Though dispatching rules are in widely used by shop scheduling practitioners, only ordinary performance rules are known; hence, dynamic generation of dispatching rules is desired to make them more effective in changing shop conditions. Meta-heuristics are able to perform quite well and carry more knowledge of the problem domain, however at the cost of prohibitive computational effort in real-time. The primary purpose of this research lies in an offline extraction of this domain knowledge using decision trees to generate simple if-then rules that subsequently act as dispatching rules for scheduling in an online manner. We used similarity index to identify parametric and structural similarity in problem instances in order to implicitly support the learning algorithm for effective rule generation and quality index for relative ranking of the dispatching decisions. Maximum lateness is used as the scheduling objective in a job shop scheduling environment.

  7. 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

  8. 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

  9. 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

  10. 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

  11. Thermal Unit Commitment Scheduling Problem in Utility System by Tabu Search Embedded Genetic Algorithm Method

    Directory of Open Access Journals (Sweden)

    C. Christober Asir Rajan

    2008-06-01

    Full Text Available The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal unit commitment in the power system for the next H hours. A 66-bus utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 24, 57 and 175 buses. Numerical results are shown comparing the cost solutions and computation time obtained by different intelligence and conventional methods.

  12. 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...

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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...

  18. 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

  19. 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...

  20. 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.

  1. 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.

  2. 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....

  3. 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).

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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,…

  17. Gains Based Remedies: the misguided search for a doctrine

    Directory of Open Access Journals (Sweden)

    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.

  18. 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.

  19. 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)

  20. 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

  1. 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

  2. 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)

  3. 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...

  4. 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

  5. Biobotic insect swarm based sensor networks for search and rescue

    Science.gov (United States)

    Bozkurt, Alper; Lobaton, Edgar; Sichitiu, Mihail; Hedrick, Tyson; Latif, Tahmid; Dirafzoon, Alireza; Whitmire, Eric; Verderber, Alexander; Marin, Juan; Xiong, Hong

    2014-06-01

    The potential benefits of distributed robotics systems in applications requiring situational awareness, such as search-and-rescue in emergency situations, are indisputable. The efficiency of such systems requires robotic agents capable of coping with uncertain and dynamic environmental conditions. For example, after an earthquake, a tremendous effort is spent for days to reach to surviving victims where robotic swarms or other distributed robotic systems might play a great role in achieving this faster. However, current technology falls short of offering centimeter scale mobile agents that can function effectively under such conditions. Insects, the inspiration of many robotic swarms, exhibit an unmatched ability to navigate through such environments while successfully maintaining control and stability. We have benefitted from recent developments in neural engineering and neuromuscular stimulation research to fuse the locomotory advantages of insects with the latest developments in wireless networking technologies to enable biobotic insect agents to function as search-and-rescue agents. Our research efforts towards this goal include development of biobot electronic backpack technologies, establishment of biobot tracking testbeds to evaluate locomotion control efficiency, investigation of biobotic control strategies with Gromphadorhina portentosa cockroaches and Manduca sexta moths, establishment of a localization and communication infrastructure, modeling and controlling collective motion by learning deterministic and stochastic motion models, topological motion modeling based on these models, and the development of a swarm robotic platform to be used as a testbed for our algorithms.

  6. 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...

  7. 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…

  8. 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.

  9. 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.

  10. 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/.

  11. 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/.

  12. 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.

  13. 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.

  14. Harmony Search Based Parameter Ensemble Adaptation for Differential Evolution

    Directory of Open Access Journals (Sweden)

    Rammohan Mallipeddi

    2013-01-01

    Full Text Available In differential evolution (DE algorithm, depending on the characteristics of the problem at hand and the available computational resources, different strategies combined with a different set of parameters may be effective. In addition, a single, well-tuned combination of strategies and parameters may not guarantee optimal performance because different strategies combined with different parameter settings can be appropriate during different stages of the evolution. Therefore, various adaptive/self-adaptive techniques have been proposed to adapt the DE strategies and parameters during the course of evolution. In this paper, we propose a new parameter adaptation technique for DE based on ensemble approach and harmony search algorithm (HS. In the proposed method, an ensemble of parameters is randomly sampled which form the initial harmony memory. The parameter ensemble evolves during the course of the optimization process by HS algorithm. Each parameter combination in the harmony memory is evaluated by testing them on the DE population. The performance of the proposed adaptation method is evaluated using two recently proposed strategies (DE/current-to-pbest/bin and DE/current-to-gr_best/bin as basic DE frameworks. Numerical results demonstrate the effectiveness of the proposed adaptation technique compared to the state-of-the-art DE based algorithms on a set of challenging test problems (CEC 2005.

  15. 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

  16. 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

  17. 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)

  18. 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 ...

  19. 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

  20. 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

  1. 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.

  2. 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…

  3. 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.

  4. Topology optimization based on the harmony search method

    International Nuclear Information System (INIS)

    Lee, Seung-Min; Han, Seog-Young

    2017-01-01

    A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

  5. Topology optimization based on the harmony search method

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung-Min; Han, Seog-Young [Hanyang University, Seoul (Korea, Republic of)

    2017-06-15

    A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

  6. The Cellular Differential Evolution Based on Chaotic Local Search

    Directory of Open Access Journals (Sweden)

    Qingfeng Ding

    2015-01-01

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

  7. 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

  8. Alephweb: a search engine based on the federated structure ...

    African Journals Online (AJOL)

    Revue d'Information Scientifique et Technique. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 7, No 1 (1997) >. Log in or Register to get access to full text downloads.

  9. A modified harmony search based method for optimal rural radial ...

    African Journals Online (AJOL)

    International Journal of Engineering, Science and Technology. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 2, No 3 (2010) >. Log in or Register to get access to full text downloads.

  10. 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.

  11. 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.

  12. 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.

  13. Integrating Conflict Driven Clause Learning to Local Search

    Directory of Open Access Journals (Sweden)

    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.

  14. Enhancing Image Retrieval System Using Content Based Search ...

    African Journals Online (AJOL)

    The output shows more efficiency in retrieval because instead of performing the search on the entire image database, the image category option directs the retrieval engine to the specified category. Also, there is provision to update or modify the different image categories in the image database as need arise. Keywords: ...

  15. 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…

  16. 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…

  17. 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

  18. 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

  19. 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.

  20. IBRI-CASONTO: Ontology-based semantic search engine

    OpenAIRE

    Awny Sayed; Amal Al Muqrishi

    2017-01-01

    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 ...

  1. Semiconductor-based experiments for neutrinoless double beta decay search

    International Nuclear Information System (INIS)

    Barnabé Heider, Marik

    2012-01-01

    Three experiments are employing semiconductor detectors in the search for neutrinoless double beta (0νββ) decay: COBRA, Majorana and GERDA. COBRA is studying the prospects of using CdZnTe detectors in terms of achievable energy resolution and background suppression. These detectors contain several ββ emitters and the most promising for 0νββ-decay search is 116 Cd. Majorana and GERDA will use isotopically enriched high purity Ge detectors to search for 0νββ-decay of 76 Ge. Their aim is to achieve a background ⩽10 −3 counts/(kg⋅y⋅keV) at the Q improvement compared to the present state-of-art. Majorana will operate Ge detectors in electroformed-Cu vacuum cryostats. A first cryostat housing a natural-Ge detector array is currently under preparation. In contrast, GERDA is operating bare Ge detectors submerged in liquid argon. The construction of the GERDA experiment is completed and a commissioning run started in June 2010. A string of natural-Ge detectors is operated to test the complete experimental setup and to determine the background before submerging the detectors enriched in 76 Ge. An overview and a comparison of these three experiments will be presented together with the latest results and developments.

  2. 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

  3. 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...

  4. 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.

  5. [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.

  6. Graphics-based intelligent search and abstracting using Data Modeling

    Science.gov (United States)

    Jaenisch, Holger M.; Handley, James W.; Case, Carl T.; Songy, Claude G.

    2002-11-01

    This paper presents an autonomous text and context-mining algorithm that converts text documents into point clouds for visual search cues. This algorithm is applied to the task of data-mining a scriptural database comprised of the Old and New Testaments from the Bible and the Book of Mormon, Doctrine and Covenants, and the Pearl of Great Price. Results are generated which graphically show the scripture that represents the average concept of the database and the mining of the documents down to the verse level.

  7. 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.

  8. 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.

  9. 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.

  10. 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…

  11. 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

  12. 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…

  13. A Combined Adaptive Tabu Search and Set Partitioning Approach for the Crew Scheduling Problem with an Air Tanker Crew Application

    Science.gov (United States)

    2002-08-15

    Agency Name(s) and Address(es) Maj Juan Vasquez AFOSR/NM 801 N. Randolph St., Rm 732 Arlington, VA 22203-1977 Sponsor/Monitor’s Acronym(s) Sponsor... Gelman , E., Patty, B., and R. Tanga. 1991. Recent Advances in Crew-Pairing Optimization at American Airlines, Interfaces, 21(1):62-74. Baker, E.K...Operations Research, 25(11):887-894. Chu, H.D., Gelman , E., and E.L. Johnson. 1997. Solving Large Scale Crew Scheduling Problems, European

  14. 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.

  15. Keyword-based Ciphertext Search Algorithm under Cloud Storage

    Directory of Open Access Journals (Sweden)

    Ren Xunyi

    2016-01-01

    Full Text Available With the development of network storage services, cloud storage have the advantage of high scalability , inexpensive, without access limit and easy to manage. These advantages make more and more small or medium enterprises choose to outsource large quantities of data to a third party. This way can make lots of small and medium enterprises get rid of costs of construction and maintenance, so it has broad market prospects. But now lots of cloud storage service providers can not protect data security.This result leakage of user data, so many users have to use traditional storage method.This has become one of the important factors that hinder the development of cloud storage. In this article, establishing keyword index by extracting keywords from ciphertext data. After that, encrypted data and the encrypted index upload cloud server together.User get related ciphertext by searching encrypted index, so it can response data leakage problem.

  16. 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...

  17. 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.

  18. 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…

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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)

  5. 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.

  6. 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.

  7. Structure-Based Search for New Inhibitors of Cholinesterases

    Directory of Open Access Journals (Sweden)

    Barbara Malawska

    2013-03-01

    Full Text Available Cholinesterases are important biological targets responsible for regulation of cholinergic transmission, and their inhibitors are used for the treatment of Alzheimer’s disease. To design new cholinesterase inhibitors, of different structure-based design strategies was followed, including the modification of compounds from a previously developed library and a fragment-based design approach. This led to the selection of heterodimeric structures as potential inhibitors. Synthesis and biological evaluation of selected candidates confirmed that the designed compounds were acetylcholinesterase inhibitors with IC50 values in the mid-nanomolar to low micromolar range, and some of them were also butyrylcholinesterase inhibitors.

  8. 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.

  9. 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.

  10. Optimization of interactive visual-similarity-based search

    NARCIS (Netherlands)

    Nguyen, G.P.; Worring, M.

    2008-01-01

    At one end of the spectrum, research in interactive content-based retrieval concentrates on machine learning methods for effective use of relevance feedback. On the other end, the information visualization community focuses on effective methods for conveying information to the user. What is lacking

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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...

  16. 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.

  17. Ontology-based Semantic Search Engine for Healthcare Services

    OpenAIRE

    Jotsna Molly Rajan; M. Deepa Lakshmi

    2012-01-01

    With the development of Web Services, the retrieval of relevant services has become a challenge. The keyword-based discovery mechanism using UDDI and WSDL is insufficient due to the retrievalof a large amount of irrelevant information. Also, keywords are insufficient in expressing semantic concepts since a single concept can be referred using syntactically different terms. Hence, service capabilities need to be manually analyzed, which lead to the development of the Semantic Web for automatic...

  18. 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.

  19. Nearby Search Indekos Based Android Using A Star (A*) Algorithm

    Science.gov (United States)

    Siregar, B.; Nababan, EB; Rumahorbo, JA; Andayani, U.; Fahmi, F.

    2018-03-01

    Indekos or rented room is a temporary residence for months or years. Society of academicians who come from out of town need a temporary residence, such as Indekos or rented room during their education, teaching, or duties. They are often found difficulty in finding a Indekos because lack of information about the Indekos. Besides, new society of academicians don’t recognize the areas around the campus and desire the shortest path from Indekos to get to the campus. The problem can be solved by implementing A Star (A*) algorithm. This algorithm is one of the shortest path algorithm to a finding shortest path from campus to the Indekos application, where the faculties in the campus as the starting point of the finding. Determination of the starting point used in this study aims to allow students to determine the starting point in finding the Indekos. The mobile based application facilitates the finding anytime and anywhere. Based on the experimental results, A* algorithm can find the shortest path with 86,67% accuracy.

  20. Content-based video indexing and searching with wavelet transformation

    Science.gov (United States)

    Stumpf, Florian; Al-Jawad, Naseer; Du, Hongbo; Jassim, Sabah

    2006-05-01

    Biometric databases form an essential tool in the fight against international terrorism, organised crime and fraud. Various government and law enforcement agencies have their own biometric databases consisting of combination of fingerprints, Iris codes, face images/videos and speech records for an increasing number of persons. In many cases personal data linked to biometric records are incomplete and/or inaccurate. Besides, biometric data in different databases for the same individual may be recorded with different personal details. Following the recent terrorist atrocities, law enforcing agencies collaborate more than before and have greater reliance on database sharing. In such an environment, reliable biometric-based identification must not only determine who you are but also who else you are. In this paper we propose a compact content-based video signature and indexing scheme that can facilitate retrieval of multiple records in face biometric databases that belong to the same person even if their associated personal data are inconsistent. We shall assess the performance of our system using a benchmark audio visual face biometric database that has multiple videos for each subject but with different identity claims. We shall demonstrate that retrieval of relatively small number of videos that are nearest, in terms of the proposed index, to any video in the database results in significant proportion of that individual biometric data.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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)

  2. 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,

  3. 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...

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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/.

  10. 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.

  11. 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.

  12. 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...

  13. A hybrid firefly algorithm and pattern search technique for SSSC based power oscillation damping controller design

    Directory of Open Access Journals (Sweden)

    Srikanta Mahapatra

    2014-12-01

    Full Text Available In this paper, a novel hybrid Firefly Algorithm and Pattern Search (h-FAPS technique is proposed for a Static Synchronous Series Compensator (SSSC-based power oscillation damping controller design. The proposed h-FAPS technique takes the advantage of global search capability of FA and local search facility of PS. In order to tackle the drawback of using the remote signal that may impact reliability of the controller, a modified signal equivalent to the remote speed deviation signal is constructed from the local measurements. The performances of the proposed controllers are evaluated in SMIB and multi-machine power system subjected to various transient disturbances. To show the effectiveness and robustness of the proposed design approach, simulation results are presented and compared with some recently published approaches such as Differential Evolution (DE and Particle Swarm Optimization (PSO. It is observed that the proposed approach yield superior damping performance compared to some recently reported approaches.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

  13. 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.

  14. The possibilities of searching for new materials based on isocationic analogs of ZnBVI

    Science.gov (United States)

    Kirovskaya, I. A.; Mironova, E. V.; Kosarev, B. A.; Yureva, A. V.; Ekkert, R. V.

    2017-08-01

    Acid-base properties of chalcogenides - analogs of ZnBVI - were investigated in detail by modern techniques. The regularities of their composition-dependent changes were set, these regularities correlating with the dependencies "bulk physicochemical property - composition". The main reason for such correlations was found, facilitating the search for new materials of corresponding sensors. In this case, it was the sensors for basic gases impurities.

  15. A peak value searching method of the MCA based on digital logic devices

    International Nuclear Information System (INIS)

    Sang Ziru; Huang Shanshan; Chen Lian; Jin Ge

    2010-01-01

    Digital multi-channel analyzers play a more important role in multi-channel pulse height analysis technique. The direction of digitalization are characterized by powerful pulse processing ability, high throughput, improved stability and flexibility. This paper introduces a method of searching peak value of waveform based on digital logic with FPGA. This method reduce the dead time. Then data correction offline can improvement the non-linearity of MCA. It gives the α energy spectrum of 241 Am. (authors)

  16. 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 ...

  17. 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...

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

  1. 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.

  2. A Rule-Based Local Search Algorithm for General Shift Design Problems in Airport Ground Handling

    DEFF Research Database (Denmark)

    Clausen, Tommy

    We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework with mul......We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework...... with multiple neighborhoods and a loosely coupled rule engine based on simulated annealing is presented. Computational experiments on real-life data from various airport ground handling organization show the performance and flexibility of the proposed algorithm....

  3. 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.

  4. 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.

  5. The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design.

    Science.gov (United States)

    Schubert, Christian R; Stultz, Collin M

    2009-08-01

    Fragment-based ligand design approaches, such as the multi-copy simultaneous search (MCSS) methodology, have proven to be useful tools in the search for novel therapeutic compounds that bind pre-specified targets of known structure. MCSS offers a variety of advantages over more traditional high-throughput screening methods, and has been applied successfully to challenging targets. The methodology is quite general and can be used to construct functionality maps for proteins, DNA, and RNA. In this review, we describe the main aspects of the MCSS method and outline the general use of the methodology as a fundamental tool to guide the design of de novo lead compounds. We focus our discussion on the evaluation of MCSS results and the incorporation of protein flexibility into the methodology. In addition, we demonstrate on several specific examples how the information arising from the MCSS functionality maps has been successfully used to predict ligand binding to protein targets and RNA.

  6. 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.

  7. 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.

  8. 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…

  9. 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.

  10. New Internet search volume-based weighting method for integrating various environmental impacts

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Changyoon, E-mail: changyoon@yonsei.ac.kr; Hong, Taehoon, E-mail: hong7@yonsei.ac.kr

    2016-01-15

    Weighting is one of the steps in life cycle impact assessment that integrates various characterized environmental impacts as a single index. Weighting factors should be based on the society's preferences. However, most previous studies consider only the opinion of some people. Thus, this research proposes a new weighting method that determines the weighting factors of environmental impact categories by considering public opinion on environmental impacts using the Internet search volumes for relevant terms. To validate the new weighting method, the weighting factors for six environmental impacts calculated by the new weighting method were compared with the existing weighting factors. The resulting Pearson's correlation coefficient between the new and existing weighting factors was from 0.8743 to 0.9889. It turned out that the new weighting method presents reasonable weighting factors. It also requires less time and lower cost compared to existing methods and likewise meets the main requirements of weighting methods such as simplicity, transparency, and reproducibility. The new weighting method is expected to be a good alternative for determining the weighting factor. - Highlight: • A new weighting method using Internet search volume is proposed in this research. • The new weighting method reflects the public opinion using Internet search volume. • The correlation coefficient between new and existing weighting factors is over 0.87. • The new weighting method can present the reasonable weighting factors. • The proposed method can be a good alternative for determining the weighting factors.

  11. New Internet search volume-based weighting method for integrating various environmental impacts

    International Nuclear Information System (INIS)

    Ji, Changyoon; Hong, Taehoon

    2016-01-01

    Weighting is one of the steps in life cycle impact assessment that integrates various characterized environmental impacts as a single index. Weighting factors should be based on the society's preferences. However, most previous studies consider only the opinion of some people. Thus, this research proposes a new weighting method that determines the weighting factors of environmental impact categories by considering public opinion on environmental impacts using the Internet search volumes for relevant terms. To validate the new weighting method, the weighting factors for six environmental impacts calculated by the new weighting method were compared with the existing weighting factors. The resulting Pearson's correlation coefficient between the new and existing weighting factors was from 0.8743 to 0.9889. It turned out that the new weighting method presents reasonable weighting factors. It also requires less time and lower cost compared to existing methods and likewise meets the main requirements of weighting methods such as simplicity, transparency, and reproducibility. The new weighting method is expected to be a good alternative for determining the weighting factor. - Highlight: • A new weighting method using Internet search volume is proposed in this research. • The new weighting method reflects the public opinion using Internet search volume. • The correlation coefficient between new and existing weighting factors is over 0.87. • The new weighting method can present the reasonable weighting factors. • The proposed method can be a good alternative for determining the weighting factors.

  12. 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/.

  13. Pulsar Timing Array Based Search for Supermassive Black Hole Binaries in the Square Kilometer Array Era.

    Science.gov (United States)

    Wang, Yan; Mohanty, Soumya D

    2017-04-14

    The advent of next generation radio telescope facilities, such as the Square Kilometer Array (SKA), will usher in an era where a pulsar timing array (PTA) based search for gravitational waves (GWs) will be able to use hundreds of well timed millisecond pulsars rather than the few dozens in existing PTAs. A realistic assessment of the performance of such an extremely large PTA must take into account the data analysis challenge posed by an exponential increase in the parameter space volume due to the large number of so-called pulsar phase parameters. We address this problem and present such an assessment for isolated supermassive black hole binary (SMBHB) searches using a SKA era PTA containing 10^{3} pulsars. We find that an all-sky search will be able to confidently detect nonevolving sources with a redshifted chirp mass of 10^{10}  M_{⊙} out to a redshift of about 28 (corresponding to a rest-frame chirp mass of 3.4×10^{8}  M_{⊙}). We discuss the important implications that the large distance reach of a SKA era PTA has on GW observations from optically identified SMBHB candidates. If no SMBHB detections occur, a highly unlikely scenario in the light of our results, the sky-averaged upper limit on strain amplitude will be improved by about 3 orders of magnitude over existing limits.

  14. 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.

  15. 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).

  16. An Analysis of the Applicability of Federal Law Regarding Hash-Based Searches of Digital Media

    Science.gov (United States)

    2014-06-01

    similarity matching, Fourth Amend- ment, federal law, search and seizure, warrant search, consent search, border search. 15. NUMBER OF PAGES 107 16. PRICE ...containing a white powdery substance labeled flour [53]. 3.3.17 United States v Heckenkamp 482 F.3d 1142 (9th Circuit 2007) People have a reasonable

  17. 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.

  18. 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.

  19. 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.

  20. A searching and reporting system for relational databases using a graph-based metadata representation.

    Science.gov (United States)

    Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

    2005-01-01

    Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

  1. 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

  2. Development and evaluation of a biomedical search engine using a predicate-based vector space model.

    Science.gov (United States)

    Kwak, Myungjae; Leroy, Gondy; Martinez, Jesse D; Harwell, Jeffrey

    2013-10-01

    Although biomedical information available in articles and patents is increasing exponentially, we continue to rely on the same information retrieval methods and use very few keywords to search millions of documents. We are developing a fundamentally different approach for finding much more precise and complete information with a single query using predicates instead of keywords for both query and document representation. Predicates are triples that are more complex datastructures than keywords and contain more structured information. To make optimal use of them, we developed a new predicate-based vector space model and query-document similarity function with adjusted tf-idf and boost function. Using a test bed of 107,367 PubMed abstracts, we evaluated the first essential function: retrieving information. Cancer researchers provided 20 realistic queries, for which the top 15 abstracts were retrieved using a predicate-based (new) and keyword-based (baseline) approach. Each abstract was evaluated, double-blind, by cancer researchers on a 0-5 point scale to calculate precision (0 versus higher) and relevance (0-5 score). Precision was significantly higher (psearching than keywords, laying the foundation for rich and sophisticated information search. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. 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.

  4. An Experiment and Detection Scheme for Cavity-Based Light Cold Dark Matter Particle Searches

    Directory of Open Access Journals (Sweden)

    Masroor H. S. Bukhari

    2017-01-01

    Full Text Available A resonance detection scheme and some useful ideas for cavity-based searches of light cold dark matter particles (such as axions are presented, as an effort to aid in the on-going endeavors in this direction as well as for future experiments, especially in possibly developing a table-top experiment. The scheme is based on our idea of a resonant detector, incorporating an integrated tunnel diode (TD and GaAs HEMT/HFET (High-Electron Mobility Transistor/Heterogeneous FET transistor amplifier, weakly coupled to a cavity in a strong transverse magnetic field. The TD-amplifier combination is suggested as a sensitive and simple technique to facilitate resonance detection within the cavity while maintaining excellent noise performance, whereas our proposed Halbach magnet array could serve as a low-noise and permanent solution replacing the conventional electromagnets scheme. We present some preliminary test results which demonstrate resonance detection from simulated test signals in a small optimal axion mass range with superior signal-to-noise ratios (SNR. Our suggested design also contains an overview of a simpler on-resonance dc signal read-out scheme replacing the complicated heterodyne read-out. We believe that all these factors and our propositions could possibly improve or at least simplify the resonance detection and read-out in cavity-based DM particle detection searches (and other spectroscopy applications and reduce the complications (and associated costs, in addition to reducing the electromagnetic interference and background.

  5. 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.

  6. The ship-borne infrared searching and tracking system based on the inertial platform

    Science.gov (United States)

    Li, Yan; Zhang, Haibo

    2011-08-01

    As a result of the radar system got interferenced or in the state of half silent ,it can cause the guided precision drop badly In the modern electronic warfare, therefore it can lead to the equipment depended on electronic guidance cannot strike the incoming goals exactly. It will need to rely on optoelectronic devices to make up for its shortcomings, but when interference is in the process of radar leading ,especially the electro-optical equipment is influenced by the roll, pitch and yaw rotation ,it can affect the target appear outside of the field of optoelectronic devices for a long time, so the infrared optoelectronic equipment can not exert the superiority, and also it cannot get across weapon-control system "reverse bring" missile against incoming goals. So the conventional ship-borne infrared system unable to track the target of incoming quickly , the ability of optoelectronic rivalry declines heavily.Here we provide a brand new controlling algorithm for the semi-automatic searching and infrared tracking based on inertial navigation platform. Now it is applying well in our XX infrared optoelectronic searching and tracking system. The algorithm is mainly divided into two steps: The artificial mode turns into auto-searching when the deviation of guide exceeds the current scene under the course of leading for radar.When the threshold value of the image picked-up is satisfied by the contrast of the target in the searching scene, the speed computed by using the CA model Least Square Method feeds back to the speed loop. And then combine the infrared information to accomplish the closed-loop control of the infrared optoelectronic system tracking. The algorithm is verified via experiment. Target capturing distance is 22.3 kilometers on the great lead deviation by using the algorithm. But without using the algorithm the capturing distance declines 12 kilometers. The algorithm advances the ability of infrared optoelectronic rivalry and declines the target capturing

  7. 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.

  8. Forecasting Energy CO2 Emissions Using a Quantum Harmony Search Algorithm-Based DMSFE Combination Model

    Directory of Open Access Journals (Sweden)

    Xingsheng Gu

    2013-03-01

    Full Text Available he accurate forecasting of carbon dioxide (CO2 emissions from fossil fuel energy consumption is a key requirement for making energy policy and environmental strategy. In this paper, a novel quantum harmony search (QHS algorithm-based discounted mean square forecast error (DMSFE combination model is proposed. In the DMSFE combination forecasting model, almost all investigations assign the discounting factor (β arbitrarily since β varies between 0 and 1 and adopt one value for all individual models and forecasting periods. The original method doesn’t consider the influences of the individual model and the forecasting period. This work contributes by changing β from one value to a matrix taking the different model and the forecasting period into consideration and presenting a way of searching for the optimal β values by using the QHS algorithm through optimizing the mean absolute percent error (MAPE objective function. The QHS algorithm-based optimization DMSFE combination forecasting model is established and tested by forecasting CO2 emission of the World top‒5 CO2 emitters. The evaluation indexes such as MAPE, root mean squared error (RMSE and mean absolute error (MAE are employed to test the performance of the presented approach. The empirical analyses confirm the validity of the presented method and the forecasting accuracy can be increased in a certain degree.

  9. 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.

  10. 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...

  11. Analisis Kata Tabu dan Klasifikasinya di Lirik Lagu Eminem pada Album `The Marshal Mathers LP`

    Directory of Open Access Journals (Sweden)

    Laily Nur Affini

    2017-04-01

    Full Text Available This research is dedicated for readers in the field of linguistics and has a purpose to reveal taboo words based on a certain theory and the classifications. The analysed taboo words exist in Emeninems album,The Marshall Mathers LP. A theory employed in the analysis is using Timothy Jay theory where taboo words are differentiated in seven classifications; cursing, profanity, blasphemy, obscenity, sexual harassment, vulgar language, name-calling and insult.The data was taken into two parts, primary and secondary. The primary data is the lyric itself and the secondary data is taken from books, articles and dictionary. The result of the analysis shows a revelation of the taboo words classifications, shown up in a table.

  12. 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

  13. 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.

  14. World Wide Web-based system for the calculation of substituent parameters and substituent similarity searches.

    Science.gov (United States)

    Ertl, P

    1998-02-01

    Easy to use, interactive, and platform-independent WWW-based tools are ideal for development of chemical applications. By using the newly emerging Web technologies such as Java applets and sophisticated scripting, it is possible to deliver powerful molecular processing capabilities directly to the desk of synthetic organic chemists. In Novartis Crop Protection in Basel, a Web-based molecular modelling system has been in use since 1995. In this article two new modules of this system are presented: a program for interactive calculation of important hydrophobic, electronic, and steric properties of organic substituents, and a module for substituent similarity searches enabling the identification of bioisosteric functional groups. Various possible applications of calculated substituent parameters are also discussed, including automatic design of molecules with the desired properties and creation of targeted virtual combinatorial libraries.

  15. SASAgent: an agent based architecture for search, retrieval and composition of scientific models.

    Science.gov (United States)

    Felipe Mendes, Luiz; Silva, Laryssa; Matos, Ely; Braga, Regina; Campos, Fernanda

    2011-07-01

    Scientific computing is a multidisciplinary field that goes beyond the use of computer as machine where researchers write simple texts, presentations or store analysis and results of their experiments. Because of the huge hardware/software resources invested in experiments and simulations, this new approach to scientific computing currently adopted by research groups is well represented by e-Science. This work aims to propose a new architecture based on intelligent agents to search, recover and compose simulation models, generated in the context of research projects related to biological domain. The SASAgent architecture is described as a multi-tier, comprising three main modules, where CelO ontology satisfies requirements put by e-science projects mainly represented by the semantic knowledge base. Preliminary results suggest that the proposed architecture is promising to achieve requirements found in e-Science projects, considering mainly the biological domain. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    German Gramajo

    2017-01-01

    Full Text Available 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 flight. Comparisons of this formulation to a path planning algorithm based on those with time constraint show equivalent coverage performance but improvement in prediction of overall mission duration and accuracy of the terminal position of the vehicle.

  17. Infodemiology of status epilepticus: A systematic validation of the Google Trends-based search queries.

    Science.gov (United States)

    Bragazzi, Nicola Luigi; Bacigaluppi, Susanna; Robba, Chiara; Nardone, Raffaele; Trinka, Eugen; Brigo, Francesco

    2016-02-01

    People increasingly use Google looking for health-related information. We previously demonstrated that in English-speaking countries most people use this search engine to obtain information on status epilepticus (SE) definition, types/subtypes, and treatment. Now, we aimed at providing a quantitative analysis of SE-related web queries. This analysis represents an advancement, with respect to what was already previously discussed, in that the Google Trends (GT) algorithm has been further refined and correlational analyses have been carried out to validate the GT-based query volumes. Google Trends-based SE-related query volumes were well correlated with information concerning causes and pharmacological and nonpharmacological treatments. Google Trends can provide both researchers and clinicians with data on realities and contexts that are generally overlooked and underexplored by classic epidemiology. In this way, GT can foster new epidemiological studies in the field and can complement traditional epidemiological tools. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. An image segmentation method based on fuzzy C-means clustering and Cuckoo search algorithm

    Science.gov (United States)

    Wang, Mingwei; Wan, Youchuan; Gao, Xianjun; Ye, Zhiwei; Chen, Maolin

    2018-04-01

    Image segmentation is a significant step in image analysis and machine vision. Many approaches have been presented in this topic; among them, fuzzy C-means (FCM) clustering is one of the most widely used methods for its high efficiency and ambiguity of images. However, the success of FCM could not be guaranteed because it easily traps into local optimal solution. Cuckoo search (CS) is a novel evolutionary algorithm, which has been tested on some optimization problems and proved to be high-efficiency. Therefore, a new segmentation technique using FCM and blending of CS algorithm is put forward in the paper. Further, the proposed method has been measured on several images and compared with other existing FCM techniques such as genetic algorithm (GA) based FCM and particle swarm optimization (PSO) based FCM in terms of fitness value. Experimental results indicate that the proposed method is robust, adaptive and exhibits the better performance than other methods involved in the paper.

  19. The U.S. Online News Coverage of Mammography Based on a Google News Search.

    Science.gov (United States)

    Young Lin, Leng Leng; Rosenkrantz, Andrew B

    2017-12-01

    To characterize online news coverage relating to mammography, including articles' stance toward screening mammography. Google News was used to search U.S. news sites over a 9-year period (2006-2015) based on the search terms "mammography" and "mammogram." The top 100 search results were recorded. Identified articles were manually reviewed. The top 100 news articles were from the following sources: local news outlet (50%), national news outlet (24%), nonimaging medical source (13%), entertainment or culture news outlet (6%), business news outlet (4%), peer-reviewed journal (1%), and radiology news outlet (1%). Most common major themes were the screening mammography controversy (29%), description of a new breast imaging technology (23%), dense breasts (11%), and promotion of a public screening initiative (11%). For the most recent year, article stance toward screening mammography was 59%, favorable; 16%, unfavorable; and 25%, neutral. After 2010, there was an abrupt shift in articles' stances from neutral to both favorable and unfavorable. A wide range of online news sources addressed a range of issues related to mammography. National, rather than local, news sites were more likely to focus on the screening controversy and more likely to take an unfavorable view. The controversial United States Preventive Services Task Force guidelines may have influenced articles to take a stance on screening mammography. As such online news may impact public perception of the topic and thus potentially impact guideline adherence, radiologists are encouraged to maintain awareness of this online coverage and to support the online dissemination of reliable and accurate information. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  20. 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.

  1. A simple heuristic for Internet-based evidence search in primary care: a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Eberbach A

    2016-08-01

    Full Text Available Andreas Eberbach,1 Annette Becker,1 Justine Rochon,2 Holger Finkemeler,1Achim Wagner,3 Norbert Donner-Banzhoff1 1Department of Family and Community Medicine, Philipp University of Marburg, Marburg, Germany; 2Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany; 3Department of Sport Medicine, Justus-Liebig-University of Giessen, Giessen, Germany Background: General practitioners (GPs are confronted with a wide variety of clinical questions, many of which remain unanswered. Methods: In order to assist GPs in finding quick, evidence-based answers, we developed a learning program (LP with a short interactive workshop based on a simple ­three-step-heuristic to improve their search and appraisal competence (SAC. We evaluated the LP ­effectiveness with a randomized controlled trial (RCT. Participants (intervention group [IG] n=20; ­control group [CG] n=31 rated acceptance and satisfaction and also answered 39 ­knowledge ­questions to assess their SAC. We controlled for previous knowledge in content areas covered by the test. Results: Main outcome – SAC: within both groups, the pre–post test shows significant (P=0.00 improvements in correctness (IG 15% vs CG 11% and confidence (32% vs 26% to find evidence-based answers. However, the SAC difference was not significant in the RCT. Other measures: Most workshop participants rated “learning atmosphere” (90%, “skills acquired” (90%, and “relevancy to my practice” (86% as good or very good. The ­LP-recommendations were implemented by 67% of the IG, whereas 15% of the CG already conformed to LP recommendations spontaneously (odds ratio 9.6, P=0.00. After literature search, the IG showed a (not significantly higher satisfaction regarding “time spent” (IG 80% vs CG 65%, “quality of information” (65% vs 54%, and “amount of information” (53% vs 47%.Conclusion: Long-standing established GPs have a good SAC. Despite high acceptance, strong

  2. 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…

  3. Balancing Efficiency and Effectiveness for Fusion-Based Search Engines in the "Big Data" Environment

    Science.gov (United States)

    Li, Jieyu; Huang, Chunlan; Wang, Xiuhong; Wu, Shengli

    2016-01-01

    Introduction: In the big data age, we have to deal with a tremendous amount of information, which can be collected from various types of sources. For information search systems such as Web search engines or online digital libraries, the collection of documents becomes larger and larger. For some queries, an information search system needs to…

  4. Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2011-02-01

    Full Text Available Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN. Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability.

  5. A trust-based sensor allocation algorithm in cooperative space search problems

    Science.gov (United States)

    Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

    2011-06-01

    Sensor allocation is an important and challenging problem within the field of multi-agent systems. The sensor allocation problem involves deciding how to assign a number of targets or cells to a set of agents according to some allocation protocol. Generally, in order to make efficient allocations, we need to design mechanisms that consider both the task performers' costs for the service and the associated probability of success (POS). In our problem, the costs are the used sensor resource, and the POS is the target tracking performance. Usually, POS may be perceived differently by different agents because they typically have different standards or means of evaluating the performance of their counterparts (other sensors in the search and tracking problem). Given this, we turn to the notion of trust to capture such subjective perceptions. In our approach, we develop a trust model to construct a novel mechanism that motivates sensor agents to limit their greediness or selfishness. Then we model the sensor allocation optimization problem with trust-in-loop negotiation game and solve it using a sub-game perfect equilibrium. Numerical simulations are performed to demonstrate the trust-based sensor allocation algorithm in cooperative space situation awareness (SSA) search problems.

  6. FACC: A Novel Finite Automaton Based on Cloud Computing for the Multiple Longest Common Subsequences Search

    Directory of Open Access Journals (Sweden)

    Yanni Li

    2012-01-01

    Full Text Available Searching for the multiple longest common subsequences (MLCS has significant applications in the areas of bioinformatics, information processing, and data mining, and so forth, Although a few parallel MLCS algorithms have been proposed, the efficiency and effectiveness of the algorithms are not satisfactory with the increasing complexity and size of biologic data. To overcome the shortcomings of the existing MLCS algorithms, and considering that MapReduce parallel framework of cloud computing being a promising technology for cost-effective high performance parallel computing, a novel finite automaton (FA based on cloud computing called FACC is proposed under MapReduce parallel framework, so as to exploit a more efficient and effective general parallel MLCS algorithm. FACC adopts the ideas of matched pairs and finite automaton by preprocessing sequences, constructing successor tables, and common subsequences finite automaton to search for MLCS. Simulation experiments on a set of benchmarks from both real DNA and amino acid sequences have been conducted and the results show that the proposed FACC algorithm outperforms the current leading parallel MLCS algorithm FAST-MLCS.

  7. Stardust@home: An Interactive Internet-based Search for Interstellar Dust

    Science.gov (United States)

    Mendez, B. J.; Westphal, A. J.; Butterworth, A. L.; Craig, N.

    2006-12-01

    On January 15, 2006, NASA's Stardust mission returned to Earth after nearly seven years in interplanetary space. During its journey, Stardust encountered comet Wild 2, collecting dust particles from it in a special material called aerogel. At two other times in the mission, aerogel collectors were also opened to collect interstellar dust. The Stardust Interstellar Dust Collector is being scanned by an automated microscope at the Johnson Space Center. There are approximately 700,000 fields of view needed to cover the entire collector, but we expect only a few dozen total grains of interstellar dust were captured within it. Finding these particles is a daunting task. We have recruited many thousands of volunteers from the public to aid in the search for these precious pieces of space dust trapped in the collectors. We call the project Stardust@home. Through Stardust@home, volunteers from the public search fields of view from the Stardust aerogel collector using a web-based Virtual Microscope. Volunteers who discover interstellar dust particles have the privilege of naming them. The interest and response to this project has been extraordinary. Many people from all walks of life are very excited about space science and eager to volunteer their time to contribute to a real research project such as this. We will discuss the progress of the project and the education and outreach activities being carried out for it.

  8. Recurrent neural network-based modeling of gene regulatory network using elephant swarm water search algorithm.

    Science.gov (United States)

    Mandal, Sudip; Saha, Goutam; Pal, Rajat Kumar

    2017-08-01

    Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. Inspired by the behavior of social elephants, we propose a new metaheuristic namely Elephant Swarm Water Search Algorithm (ESWSA) to infer Gene Regulatory Network (GRN). This algorithm is mainly based on the water search strategy of intelligent and social elephants during drought, utilizing the different types of communication techniques. Initially, the algorithm is tested against benchmark small and medium scale artificial genetic networks without and with presence of different noise levels and the efficiency was observed in term of parametric error, minimum fitness value, execution time, accuracy of prediction of true regulation, etc. Next, the proposed algorithm is tested against the real time gene expression data of Escherichia Coli SOS Network and results were also compared with others state of the art optimization methods. The experimental results suggest that ESWSA is very efficient for GRN inference problem and performs better than other methods in many ways.

  9. Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search

    Science.gov (United States)

    Song, Kai; Liu, Qi; Wang, Qi

    2011-01-01

    Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE) and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN). Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability. PMID:22319401

  10. Reduction rules-based search algorithm for opportunistic replacement strategy of multiple life-limited parts

    Directory of Open Access Journals (Sweden)

    Xuyun FU

    2018-01-01

    Full Text Available The opportunistic replacement of multiple Life-Limited Parts (LLPs is a problem widely existing in industry. The replacement strategy of LLPs has a great impact on the total maintenance cost to a lot of equipment. This article focuses on finding a quick and effective algorithm for this problem. To improve the algorithm efficiency, six reduction rules are suggested from the perspectives of solution feasibility, determination of the replacement of LLPs, determination of the maintenance occasion and solution optimality. Based on these six reduction rules, a search algorithm is proposed. This search algorithm can identify one or several optimal solutions. A numerical experiment shows that these six reduction rules are effective, and the time consumed by the algorithm is less than 38 s if the total life of equipment is shorter than 55000 and the number of LLPs is less than 11. A specific case shows that the algorithm can obtain optimal solutions which are much better than the result of the traditional method in 10 s, and it can provide support for determining to-be-replaced LLPs when determining the maintenance workscope of an aircraft engine. Therefore, the algorithm is applicable to engineering applications concerning opportunistic replacement of multiple LLPs in aircraft engines.

  11. Global Optimization Based on the Hybridization of Harmony Search and Particle Swarm Optimization Methods

    Directory of Open Access Journals (Sweden)

    A. P. Karpenko

    2014-01-01

    Full Text Available We consider a class of stochastic search algorithms of global optimization which in various publications are called behavioural, intellectual, metaheuristic, inspired by the nature, swarm, multi-agent, population, etc. We use the last term.Experience in using the population algorithms to solve challenges of global optimization shows that application of one such algorithm may not always effective. Therefore now great attention is paid to hybridization of population algorithms of global optimization. Hybrid algorithms unite various algorithms or identical algorithms, but with various values of free parameters. Thus efficiency of one algorithm can compensate weakness of another.The purposes of the work are development of hybrid algorithm of global optimization based on known algorithms of harmony search (HS and swarm of particles (PSO, software implementation of algorithm, study of its efficiency using a number of known benchmark problems, and a problem of dimensional optimization of truss structure.We set a problem of global optimization, consider basic algorithms of HS and PSO, give a flow chart of the offered hybrid algorithm called PSO HS , present results of computing experiments with developed algorithm and software, formulate main results of work and prospects of its development.

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

    Directory of Open Access Journals (Sweden)

    Mauro Castelli

    2015-01-01

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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Reducing a Knowledge-Base Search Space When Data Are Missing

    Science.gov (United States)

    James, Mark

    2007-01-01

    This software addresses the problem of how to efficiently execute a knowledge base in the presence of missing data. Computationally, this is an exponentially expensive operation that without heuristics generates a search space of 1 + 2n possible scenarios, where n is the number of rules in the knowledge base. Even for a knowledge base of the most modest size, say 16 rules, it would produce 65,537 possible scenarios. The purpose of this software is to reduce the complexity of this operation to a more manageable size. The problem that this system solves is to develop an automated approach that can reason in the presence of missing data. This is a meta-reasoning capability that repeatedly calls a diagnostic engine/model to provide prognoses and prognosis tracking. In the big picture, the scenario generator takes as its input the current state of a system, including probabilistic information from Data Forecasting. Using model-based reasoning techniques, it returns an ordered list of fault scenarios that could be generated from the current state, i.e., the plausible future failure modes of the system as it presently stands. The scenario generator models a Potential Fault Scenario (PFS) as a black box, the input of which is a set of states tagged with priorities and the output of which is one or more potential fault scenarios tagged by a confidence factor. The results from the system are used by a model-based diagnostician to predict the future health of the monitored system.

  19. 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.

  20. TCSC based automatic generation control of deregulated power system using quasi-oppositional harmony search algorithm

    Directory of Open Access Journals (Sweden)

    Mahendra Nandi

    2017-08-01

    Full Text Available In present aspect, automatic generation control (AGC of deregulated power system with thyristor controlled series compensator (TCSC device is investigated. The objective is to discuss bilateral power transaction issue with the TCSC effect. A deregulated two-area power system model having two thermal units in each control area is considered for this act. A quasi-oppositional harmony search (QOHS algorithm is being applied for the constrained optimization problem. Three cases, commonly studied in deregulation, are discussed for the effectiveness of the proposed technique. Further, sensitivity analysis is studied by varying the test system parameters up to ±25% from their rated values. The obtained simulation plots are analytically discussed with the calculation of oscillatory modes, transient details and the studied performance indices. Sugeno fuzzy logic control technique is also investigated to the studied test system. The simulation results show that the proposed QOHS based TCSC controller is quite effective in deregulated environment.

  1. Orthogonal search-based rule extraction for modelling the decision to transfuse.

    Science.gov (United States)

    Etchells, T A; Harrison, M J

    2006-04-01

    Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search-based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100-mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on-going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb 13 mm and Hb 38 mm, Hb < 102 g x l(-1) and OGH; 4. Hb < 78 g x l(-1).

  2. Voltage stability index based optimal placement of static VAR compensator and sizing using Cuckoo search algorithm

    Science.gov (United States)

    Venkateswara Rao, B.; Kumar, G. V. Nagesh; Chowdary, D. Deepak; Bharathi, M. Aruna; Patra, Stutee

    2017-07-01

    This paper furnish the new Metaheuristic algorithm called Cuckoo Search Algorithm (CSA) for solving optimal power flow (OPF) problem with minimization of real power generation cost. The CSA is found to be the most efficient algorithm for solving single objective optimal power flow problems. The CSA performance is tested on IEEE 57 bus test system with real power generation cost minimization as objective function. Static VAR Compensator (SVC) is one of the best shunt connected device in the Flexible Alternating Current Transmission System (FACTS) family. It has capable of controlling the voltage magnitudes of buses by injecting the reactive power to system. In this paper SVC is integrated in CSA based Optimal Power Flow to optimize the real power generation cost. SVC is used to improve the voltage profile of the system. CSA gives better results as compared to genetic algorithm (GA) in both without and with SVC conditions.

  3. Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis.

    Science.gov (United States)

    Li, Chaoshun; Zhou, Jianzhong

    2014-09-01

    Supervised learning method, like support vector machine (SVM), has been widely applied in diagnosing known faults, however this kind of method fails to work correctly when new or unknown fault occurs. Traditional unsupervised kernel clustering can be used for unknown fault diagnosis, but it could not make use of the historical classification information to improve diagnosis accuracy. In this paper, a semi-supervised kernel clustering model is designed to diagnose known and unknown faults. At first, a novel semi-supervised weighted kernel clustering algorithm based on gravitational search (SWKC-GS) is proposed for clustering of dataset composed of labeled and unlabeled fault samples. The clustering model of SWKC-GS is defined based on wrong classification rate of labeled samples and fuzzy clustering index on the whole dataset. Gravitational search algorithm (GSA) is used to solve the clustering model, while centers of clusters, feature weights and parameter of kernel function are selected as optimization variables. And then, new fault samples are identified and diagnosed by calculating the weighted kernel distance between them and the fault cluster centers. If the fault samples are unknown, they will be added in historical dataset and the SWKC-GS is used to partition the mixed dataset and update the clustering results for diagnosing new fault. In experiments, the proposed method has been applied in fault diagnosis for rotatory bearing, while SWKC-GS has been compared not only with traditional clustering methods, but also with SVM and neural network, for known fault diagnosis. In addition, the proposed method has also been applied in unknown fault diagnosis. The results have shown effectiveness of the proposed method in achieving expected diagnosis accuracy for both known and unknown faults of rotatory bearing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Application of 3D Zernike descriptors to shape-based ligand similarity searching

    Directory of Open Access Journals (Sweden)

    Venkatraman Vishwesh

    2009-12-01

    Full Text Available Abstract Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

  5. Application of 3D Zernike descriptors to shape-based ligand similarity searching.

    Science.gov (United States)

    Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

    2009-12-17

    The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

  6. Object-based implicit learning in visual search: perceptual segmentation constrains contextual cueing.

    Science.gov (United States)

    Conci, Markus; Müller, Hermann J; von Mühlenen, Adrian

    2013-07-09

    In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

  7. Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System

    Directory of Open Access Journals (Sweden)

    Bin Guo

    2008-01-01

    Full Text Available A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certain conditions, smart objects become hidden ones. However, current systems provide no mechanism to detect and manage objects when this problem occurs. Second, there is no common context infrastructure for building smart artifact systems, which makes it difficult for separately developed applications to interact with each other and uneasy for them to share and reuse knowledge. Unlike previous systems, Home-Explorer builds on an ontology-based knowledge infrastructure named Sixth-Sense, which makes it easy for the system to interact with other applications or agents also based on this ontology. The hidden object problem is also reflected in our ontology, which enables Home-Explorer to deal with both smart objects and hidden objects. A set of rules for deducing an object's status or location information and for locating hidden objects are described and evaluated.

  8. 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

  9. 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...

  10. 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...

  11. Fine-grained Database Field Search Using Attribute-Based Encryption for E-Healthcare Clouds.

    Science.gov (United States)

    Guo, Cheng; Zhuang, Ruhan; Jie, Yingmo; Ren, Yizhi; Wu, Ting; Choo, Kim-Kwang Raymond

    2016-11-01

    An effectively designed e-healthcare system can significantly enhance the quality of access and experience of healthcare users, including facilitating medical and healthcare providers in ensuring a smooth delivery of services. Ensuring the security of patients' electronic health records (EHRs) in the e-healthcare system is an active research area. EHRs may be outsourced to a third-party, such as a community healthcare cloud service provider for storage due to cost-saving measures. Generally, encrypting the EHRs when they are stored in the system (i.e. data-at-rest) or prior to outsourcing the data is used to ensure data confidentiality. Searchable encryption (SE) scheme is a promising technique that can ensure the protection of private information without compromising on performance. In this paper, we propose a novel framework for controlling access to EHRs stored in semi-trusted cloud servers (e.g. a private cloud or a community cloud). To achieve fine-grained access control for EHRs, we leverage the ciphertext-policy attribute-based encryption (CP-ABE) technique to encrypt tables published by hospitals, including patients' EHRs, and the table is stored in the database with the primary key being the patient's unique identity. Our framework can enable different users with different privileges to search on different database fields. Differ from previous attempts to secure outsourcing of data, we emphasize the control of the searches of the fields within the database. We demonstrate the utility of the scheme by evaluating the scheme using datasets from the University of California, Irvine.

  12. 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…

  13. Support patient search on pathology reports with interactive online learning based data extraction.

    Science.gov (United States)

    Zheng, Shuai; Lu, James J; Appin, Christina; Brat, Daniel; Wang, Fusheng

    2015-01-01

    Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user's interaction with minimal human effort. We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system's data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users' corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of tests. Extracting data from pathology reports could enable

  14. Support patient search on pathology reports with interactive online learning based data extraction

    Directory of Open Access Journals (Sweden)

    Shuai Zheng

    2015-01-01

    Full Text Available Background: Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user′s interaction with minimal human effort. Methods : We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system′s data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users′ corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. Results: We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of

  15. Augmented Reality for Searching Potential Assets in Medan using GPS based Tracking

    Science.gov (United States)

    Muchtar, M. A.; Syahputra, M. F.; Syahputra, N.; Ashrafia, S.; Rahmat, R. F.

    2017-01-01

    Every city is required to introduce its variety of potential assets so that the people know how to utilize or to develop their area. Potential assets include infrastructure, facilities, people, communities, organizations, customs that affects the characteristics and the way of life in Medan. Due to lack of socialization and information, most of people in Medan only know a few parts of the assets. Recently, so many mobile apps provide search and mapping locations used to find the location of potential assets in user’s area. However, the available information, such as text and digital maps, sometimes do not much help the user clearly and dynamically. Therefore, Augmented Reality technology able to display information in real world vision is implemented in this research so that the information can be more interactive and easily understood by user. This technology will be implemented in mobile apps using GPS based tracking and define the coordinate of user’s smartphone as a marker so that it can help people dynamically and easily find the location of potential assets in the nearest area based on the direction of user’s view on camera.

  16. Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    Norlina Mohd Sabri

    2016-06-01

    Full Text Available This research is focusing on the radio frequency (RF magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of Particle Swarm Optimization (PSO, Genetic Algorithm (GA, Artificial Immune System (AIS and Ant Colony Optimization (ACO. Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process.

  17. A Sustainable City Planning Algorithm Based on TLBO and Local Search

    Science.gov (United States)

    Zhang, Ke; Lin, Li; Huang, Xuanxuan; Liu, Yiming; Zhang, Yonggang

    2017-09-01

    Nowadays, how to design a city with more sustainable features has become a center problem in the field of social development, meanwhile it has provided a broad stage for the application of artificial intelligence theories and methods. Because the design of sustainable city is essentially a constraint optimization problem, the swarm intelligence algorithm of extensive research has become a natural candidate for solving the problem. TLBO (Teaching-Learning-Based Optimization) algorithm is a new swarm intelligence algorithm. Its inspiration comes from the “teaching” and “learning” behavior of teaching class in the life. The evolution of the population is realized by simulating the “teaching” of the teacher and the student “learning” from each other, with features of less parameters, efficient, simple thinking, easy to achieve and so on. It has been successfully applied to scheduling, planning, configuration and other fields, which achieved a good effect and has been paid more and more attention by artificial intelligence researchers. Based on the classical TLBO algorithm, we propose a TLBO_LS algorithm combined with local search. We design and implement the random generation algorithm and evaluation model of urban planning problem. The experiments on the small and medium-sized random generation problem showed that our proposed algorithm has obvious advantages over DE algorithm and classical TLBO algorithm in terms of convergence speed and solution quality.

  18. Design of personalized search engine based on user-webpage dynamic model

    Science.gov (United States)

    Li, Jihan; Li, Shanglin; Zhu, Yingke; Xiao, Bo

    2013-12-01

    Personalized search engine focuses on establishing a user-webpage dynamic model. In this model, users' personalized factors are introduced so that the search engine is better able to provide the user with targeted feedback. This paper constructs user and webpage dynamic vector tables, introduces singular value decomposition analysis in the processes of topic categorization, and extends the traditional PageRank algorithm.

  19. 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.

  20. 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.

  1. Indexing data cubes for content-based searches in radio astronomy

    Science.gov (United States)

    Araya, M.; Candia, G.; Gregorio, R.; Mendoza, M.; Solar, M.

    2016-01-01

    Methods for observing space have changed profoundly in the past few decades. The methods needed to detect and record astronomical objects have shifted from conventional observations in the optical range to more sophisticated methods which permit the detection of not only the shape of an object but also the velocity and frequency of emissions in the millimeter-scale wavelength range and the chemical substances from which they originate. The consolidation of radio astronomy through a range of global-scale projects such as the Very Long Baseline Array (VLBA) and the Atacama Large Millimeter/submillimeter Array (ALMA) reinforces the need to develop better methods of data processing that can automatically detect regions of interest (ROIs) within data cubes (position-position-velocity), index them and facilitate subsequent searches via methods based on queries using spatial coordinates and/or velocity ranges. In this article, we present the development of an automatic system for indexing ROIs in data cubes that is capable of automatically detecting and recording ROIs while reducing the necessary storage space. The system is able to process data cubes containing megabytes of data in fractions of a second without human supervision, thus allowing it to be incorporated into a production line for displaying objects in a virtual observatory. We conducted a set of comprehensive experiments to illustrate how our system works. As a result, an index of 3% of the input size was stored in a spatial database, representing a compression ratio equal to 33:1 over an input of 20.875 GB, achieving an index of 773 MB approximately. On the other hand, a single query can be evaluated over our system in a fraction of second, showing that the indexing step works as a shock-absorber of the computational time involved in data cube processing. The system forms part of the Chilean Virtual Observatory (ChiVO), an initiative which belongs to the International Virtual Observatory Alliance (IVOA) that

  2. Searching for answers to clinical questions using google versus evidence-based summary resources: a randomized controlled crossover study.

    Science.gov (United States)

    Kim, Sarang; Noveck, Helaine; Galt, James; Hogshire, Lauren; Willett, Laura; O'Rourke, Kerry

    2014-06-01

    To compare the speed and accuracy of answering clinical questions using Google versus summary resources. In 2011 and 2012, 48 internal medicine interns from two classes at Rutgers University Robert Wood Johnson Medical School, who had been trained to use three evidence-based summary resources, performed four-minute computer searches to answer 10 clinical questions. Half were randomized to initiate searches for answers to questions 1 to 5 using Google; the other half initiated searches using a summary resource. They then crossed over and used the other resource for questions 6 to 10. They documented the time spent searching and the resource where the answer was found. Time to correct response and percentage of correct responses were compared between groups using t test and general estimating equations. Of 480 questions administered, interns found answers for 393 (82%). Interns initiating searches in Google used a wider variety of resources than those starting with summary resources. No significant difference was found in mean time to correct response (138.5 seconds for Google versus 136.1 seconds for summary resource; P = .72). Mean correct response rate was 58.4% for Google versus 61.5% for summary resource (mean difference -3.1%; 95% CI -10.3% to 4.2%; P = .40). The authors found no significant differences in speed or accuracy between searches initiated using Google versus summary resources. Although summary resources are considered to provide the highest quality of evidence, improvements to allow for better speed and accuracy are needed.

  3. An Adaptive Tabu Search Heuristic for the Location Routing Pickup and Delivery Problem with Time Windows with a Theater Distribution Application

    Science.gov (United States)

    2006-08-01

    including approximations of delivery costs. The solution of a sub-problem provides input for another sub-problem. Perl (1983) and Perl and Daskin (1985...developed in this section represents a modification and combination of both the three-layer location routing formulation of Perl and Daskin (1985) and the...1985) LRP formulation to create the LPDPTW. 4.2.1 Generalization of the LRP Perl and Daskin (1985) utilize a fixed charge location problem as the

  4. An Adaptive Tabu Search Heuristic for the Location Routing Pickup and Delivery Problem with Time Windows with a Theater Distribution Application

    National Research Council Canada - National Science Library

    Burks, Jr, Robert E

    2006-01-01

    .... The location routing problem (LRP) is an extension of the vehicle routing problem where the solution identifies the optimal location of the depots and provides the vehicle schedules and distribution routes...

  5. Algoritmo Tabú para un problema de distribución de espacios || Tabu search algorithm for a room allocation problem

    Directory of Open Access Journals (Sweden)

    Molina Luque, Julián

    2006-06-01

    Full Text Available La distribución de espacios es un problema que habitualmente se presenta en situaciones reales cuando se deben asignar simultáneamente diferentes conjuntos de espacios (despachos, habitaciones, salas, etc. distribuidos entre edificios y/o plantas entre varios grupos de personas de tal forma que se minimicen las distancias entre los espacios asignados a cada grupo y lasede de dicho grupo. Esta situación da lugar a un problema combinatorio con una función objetivo cuadrática, lo cual complica enormemente su resolución mediante un método exacto. Por este motivo, proponemos para su resolución un metaheurístico basado en Búsqueda Tabú con dos grupos de movimientos claramente diferenciados: intercambio de despachos y reasignación de sedes. Finalmente, aplicamos dicho algoritmo a un caso real en la Universidad Pablo de Olavide de Sevilla (España.

  6. 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

  7. Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.

    Science.gov (United States)

    Schreibmann, Eduard; Marcus, David M; Fox, Tim

    2014-07-08

    Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.

  8. Earthdata Search: How Usability Drives Innovation To Enable A Broad User Base

    Science.gov (United States)

    Reese, M.; Siarto, J.; Lynnes, C.; Shum, D.

    2017-12-01

    Earthdata Search (https://search.earthdata.nasa.gov) is a modern web application allowing users to search, discover, visualize, refine, and access NASA Earth Observation data using a wide array of service offerings. Its goal is to ease the technical burden on data users by providing a high-quality application that makes it simple to interact with NASA Earth observation data, freeing them to spend more effort on innovative endeavors. This talk would detail how we put end users first in our design and development process, focusing on usability and letting usability needs drive requirements for the underlying technology. Just a few examples of how this plays out practically, Earthdata Search teams with a lightning fast metadata repository, allowing it to be an extremely responsive UI that updates as the user changes criteria not only at the dataset level, but also at the file level. This results in a better exploration experience as the time penalty is greatly reduced. Also, since Earthdata Search uses metadata from over 35,000 datasets that are managed by different data providers, metadata standards, quality and consistency will vary. We found that this was negatively impacting users' search and exploration experience. We have resolved this problem with the introduction of "humanizers", which is a community-driven process to both "smooth out" metadata values and provide non-jargonistic representations of some content within the Earthdata Search UI. This is helpful for both the experience data scientist and our users that are brand new to the discipline.

  9. Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud.

    Science.gov (United States)

    Munisamy, Shyamala Devi; Chokkalingam, Arun

    2015-01-01

    Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

  10. Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud

    Directory of Open Access Journals (Sweden)

    Shyamala Devi Munisamy

    2015-01-01

    Full Text Available Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider’s premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

  11. The Scatter Search Based Algorithm to Revenue Management Problem in Broadcasting Companies

    Science.gov (United States)

    Pishdad, Arezoo; Sharifyazdi, Mehdi; Karimpour, Reza

    2009-09-01

    The problem under question in this paper which is faced by broadcasting companies is how to benefit from a limited advertising space. This problem is due to the stochastic behavior of customers (advertiser) in different fare classes. To address this issue we propose a mathematical constrained nonlinear multi period model which incorporates cancellation and overbooking. The objective function is to maximize the total expected revenue and our numerical method performs it by determining the sales limits for each class of customer to present the revenue management control policy. Scheduling the advertising spots in breaks is another area of concern and we consider it as a constraint in our model. In this paper an algorithm based on Scatter search is developed to acquire a good feasible solution. This method uses simulation over customer arrival and in a continuous finite time horizon [0, T]. Several sensitivity analyses are conducted in computational result for depicting the effectiveness of proposed method. It also provides insight into better results of considering revenue management (control policy) compared to "no sales limit" policy in which sooner demand will served first.

  12. Certificate-Based Encryption with Keyword Search: Enabling Secure Authorization in Electronic Health Record

    Directory of Open Access Journals (Sweden)

    Clémentine Gritti

    2016-11-01

    Full Text Available In an e-Health scenario, we study how the practitioners are authorized when they are requesting access to medical documents containing sensitive information. Consider the following scenario. A clinician wants to access and retrieve a patient’s Electronic Health Record (EHR, and this means that the clinician must acquire sufficient access right to access this document. As the EHR is within a collection of many other patients, the clinician would need to specify some requirements (such as a keyword which match the patient’s record, as well as having a valid access right. The complication begins when we do not want the server to learn anything from this query (as the server might be outsourced to other place. To encompass this situation, we define a new cryptographic primitive called Certificate-Based Encryption with Keyword Search (CBEKS, which will be suitable in this scenario. We also specify the corresponding security models, namely computational consistency, indistinguishability against chosen keyword and ciphertext attacks, indistinguishability against keyword-guessing attacks and collusion resistance. We provide a CBEKS construction that is proven secure in the standard model with respect to the aforementioned security models.

  13. Using infrared HOG-based pedestrian detection for outdoor autonomous searching UAV with embedded system

    Science.gov (United States)

    Shao, Yanhua; Mei, Yanying; Chu, Hongyu; Chang, Zhiyuan; He, Yuxuan; Zhan, Huayi

    2018-04-01

    Pedestrian detection (PD) is an important application domain in computer vision and pattern recognition. Unmanned Aerial Vehicles (UAVs) have become a major field of research in recent years. In this paper, an algorithm for a robust pedestrian detection method based on the combination of the infrared HOG (IR-HOG) feature and SVM is proposed for highly complex outdoor scenarios on the basis of airborne IR image sequences from UAV. The basic flow of our application operation is as follows. Firstly, the thermal infrared imager (TAU2-336), which was installed on our Outdoor Autonomous Searching (OAS) UAV, is used for taking pictures of the designated outdoor area. Secondly, image sequences collecting and processing were accomplished by using high-performance embedded system with Samsung ODROID-XU4 and Ubuntu as the core and operating system respectively, and IR-HOG features were extracted. Finally, the SVM is used to train the pedestrian classifier. Experiment show that, our method shows promising results under complex conditions including strong noise corruption, partial occlusion etc.

  14. State Recognition of High Voltage Isolation Switch Based on Background Difference and Iterative Search

    Science.gov (United States)

    Xu, Jiayuan; Yu, Chengtao; Bo, Bin; Xue, Yu; Xu, Changfu; Chaminda, P. R. Dushantha; Hu, Chengbo; Peng, Kai

    2018-03-01

    The automatic recognition of the high voltage isolation switch by remote video monitoring is an effective means to ensure the safety of the personnel and the equipment. The existing methods mainly include two ways: improving monitoring accuracy and adopting target detection technology through equipment transformation. Such a method is often applied to specific scenarios, with limited application scope and high cost. To solve this problem, a high voltage isolation switch state recognition method based on background difference and iterative search is proposed in this paper. The initial position of the switch is detected in real time through the background difference method. When the switch starts to open and close, the target tracking algorithm is used to track the motion trajectory of the switch. The opening and closing state of the switch is determined according to the angle variation of the switch tracking point and the center line. The effectiveness of the method is verified by experiments on different switched video frames of switching states. Compared with the traditional methods, this method is more robust and effective.

  15. A “Tuned” Mask Learnt Approach Based on Gravitational Search Algorithm

    Directory of Open Access Journals (Sweden)

    Youchuan Wan

    2016-01-01

    Full Text Available Texture image classification is an important topic in many applications in machine vision and image analysis. Texture feature extracted from the original texture image by using “Tuned” mask is one of the simplest and most effective methods. However, hill climbing based training methods could not acquire the satisfying mask at a time; on the other hand, some commonly used evolutionary algorithms like genetic algorithm (GA and particle swarm optimization (PSO easily fall into the local optimum. A novel approach for texture image classification exemplified with recognition of residential area is detailed in the paper. In the proposed approach, “Tuned” mask is viewed as a constrained optimization problem and the optimal “Tuned” mask is acquired by maximizing the texture energy via a newly proposed gravitational search algorithm (GSA. The optimal “Tuned” mask is achieved through the convergence of GSA. The proposed approach has been, respectively, tested on some public texture and remote sensing images. The results are then compared with that of GA, PSO, honey-bee mating optimization (HBMO, and artificial immune algorithm (AIA. Moreover, feature extracted by Gabor wavelet is also utilized to make a further comparison. Experimental results show that the proposed method is robust and adaptive and exhibits better performance than other methods involved in the paper in terms of fitness value and classification accuracy.

  16. Opportunities for Web-based Drug Repositioning: Searching for Potential Antihypertensive Agents with Hypotension Adverse Events.

    Science.gov (United States)

    Wang, Kejian; Wan, Mei; Wang, Rui-Sheng; Weng, Zuquan

    2016-04-01

    Drug repositioning refers to the process of developing new indications for existing drugs. As a phenotypic indicator of drug response in humans, clinical side effects may provide straightforward signals and unique opportunities for drug repositioning. We aimed to identify drugs frequently associated with hypotension adverse reactions (ie, the opposite condition of hypertension), which could be potential candidates as antihypertensive agents. We systematically searched the electronic records of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) through the openFDA platform to assess the association between hypotension incidence and antihypertensive therapeutic effect regarding a list of 683 drugs. Statistical analysis of FAERS data demonstrated that those drugs frequently co-occurring with hypotension events were more likely to have antihypertensive activity. Ranked by the statistical significance of frequent hypotension reporting, the well-known antihypertensive drugs were effectively distinguished from others (with an area under the receiver operating characteristic curve > 0.80 and a normalized discounted cumulative gain of 0.77). In addition, we found a series of antihypertensive agents (particularly drugs originally developed for treating nervous system diseases) among the drugs with top significant reporting, suggesting the good potential of Web-based and data-driven drug repositioning. We found several candidate agents among the hypotension-related drugs on our list that may be redirected for lowering blood pressure. More important, we showed that a pharmacovigilance system could alternatively be used to identify antihypertensive agents and sustainably create opportunities for drug repositioning.

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

    Science.gov (United States)

    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.

  18. Quantification of Parkinson Tremor Intensity Based On EMG Signal Analysis Using Fast Orthogonal Search Algorithm

    Directory of Open Access Journals (Sweden)

    H. Rezghian Moghadam

    2018-06-01

    Full Text Available The tremor injury is one of the common symptoms of Parkinson's disease. The patients suffering from Parkinson's disease have difficulty in controlling their movements owing to tremor. The intensity of the disease can be determined through specifying the range of intensity values of involuntary tremor in Parkinson patients. The level of disease in patients is determined through an empirical range of 0-5. In the early stages of Parkinson, resting tremor can be very mild and intermittent. So, diagnosing the levels of disease is difficult but important since it has only medication therapy. The aim of this study is to quantify the intensity of tremor by the analysis of electromyogram signal. The solution proposed in this paper is to employ a polynomial function model to estimate the Unified Parkinson's Disease Rating Scale (UPDRS value. The algorithm of Fast Orthogonal Search (FOS, which is based on identification of orthogonal basic functions, was utilized for model identification. In fact, some linear and nonlinear features extracted from wrist surface electromyogram signal were considered as the input of the model identified by FOS, and the model output was the UPDRS value. In this research, the proposed model was designed based on two different structures which have been called the single structure and parallel structure. The efficiency of designed models with different structures was evaluated. The evaluation results using K-fold cross validation approach showed that the proposed model with a parallel structure could determine the tremor severity of the Parkinson's disease with accuracy of 99.25% ±0.41, sensitivity of 97.17% ±1.9 and specificity of 99.72% ±0.18.

  19. Superinsulating Polyisocyanate Based Aerogels: A Targeted Search for the Optimum Solvent System.

    Science.gov (United States)

    Zhu, Zhiyuan; Snellings, Geert M B F; Koebel, Matthias M; Malfait, Wim J

    2017-05-31

    Polyisocyanate based aerogels combine ultralow thermal conductivities with better mechanical properties than silica aerogel, but these properties critically depend on the nature of the gelation solvent, perhaps more so than on any other parameter. Here, we present a systematic study of the relationship between the polyurethane-polyisocyanurate (PUR-PIR) aerogel microstructure, surface area, thermal conductivity, and density and the gelation solvent's Hansen solubility parameters for an industrially relevant PUR-PIR rigid foam formulation. We first investigated aerogels prepared in acetone-dimethyl sulfoxide (DMSO) blends and observed a minimum in thermal conductivity (λ) and maximum in specific surface area for an acetone:DMSO ratio of 85:15 v/v. We then prepared PUR-PIR aerogels in 32 different solvent blends, divided into three series with δ Dispersion , δ Polarity , and δ H-bonding fixed at 15.94, 11.30, and 7.48 MPa 1/2 , respectively, corresponding to the optimum parameters for the acetone:DMSO series. The aerogel properties display distinct dependencies on the various solubility parameters: aerogels with low thermal conductivity can be synthesized in solvents with a high δ H-bonding parameter (above 7.2) and δ Dispersion around 16.3 MPa 1/2 . In contrast, the δ Polarity parameter is of lesser importance. Our study highlights the importance of the gelation solvent, clarifies the influence of the different solvent properties, and provides a methodology for a targeted search across the solvent chemical space based on the Hansen solubility parameters.

  20. 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.

  1. Decentralized cooperative unmanned aerial vehicles conflict resolution by neural network-based tree search method

    Directory of Open Access Journals (Sweden)

    Jian Yang

    2016-09-01

    Full Text Available In this article, a tree search algorithm is proposed to find the near optimal conflict avoidance solutions for unmanned aerial vehicles. In the dynamic environment, the unmodeled elements, such as wind, would make UAVs deviate from nominal traces. It brings about difficulties for conflict detection and resolution. The back propagation neural networks are utilized to approximate the unmodeled dynamics of the environment. To satisfy the online planning requirement, the search length of the tree search algorithm would be limited. Therefore, the algorithm may not be able to reach the goal states in search process. The midterm reward function for assessing each node is devised, with consideration given to two factors, namely, the safe separation requirement and the mission of each unmanned aerial vehicle. The simulation examples and the comparisons with previous approaches are provided to illustrate the smooth and convincing behaviours of the proposed algorithm.

  2. 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

  3. BredeQuery: Coordinate-Based Meta-analytic Search of Neuroscientific Literature from the SPM Environment

    DEFF Research Database (Denmark)

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

    2010-01-01

    Query offers a direct link from SPM 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 a MATLAB window and/or exported directly...

  4. Exploration of the search space of the in-core fuel management problem by knowledge-based techniques

    International Nuclear Information System (INIS)

    Galperin, A.

    1995-01-01

    The process of generating reload configuration patterns is presented as a search procedure. The search space of the problem is found to contain ∼ 10 12 possible problem states. If computational resources and execution time necessary to evaluate a single solution are taken into account, this problem may be described as a ''large space search problem.'' Understanding of the structure of the search space, i.e., distribution of the optimal (or nearly optimal) solutions, is necessary to choose an appropriate search method and to utilize adequately domain heuristic knowledge. A worth function is developed based on two performance parameters: cycle length and power peaking factor. A series of numerical experiments was carried out; 300,000 patterns were generated in 40 sessions. All these patterns were analyzed by simulating the power production cycle and by evaluating the two performance parameters. The worth function was calculated and plotted. Analysis of the worth function reveals quite a complicated search space structure. The fine structure shows an extremely large number of local peaks: about one peak per hundred configurations. The direct implication of this discovery is that within a search space of 10 12 states, there are ∼10 10 local optima. Further consideration of the worth function shape shows that the distribution of the local optima forms a contour with much slower variations, where ''better'' or ''worse'' groups of patterns are spaced within a few thousand or tens of thousands of configurations, and finally very broad subregions of the whole space display variations of the worth function, where optimal regions include tens of thousands of patterns and are separated by hundreds of thousands and millions

  5. Search Help

    Science.gov (United States)

    Guidance and search help resource listing examples of common queries that can be used in the Google Search Appliance search request, including examples of special characters, or query term seperators that Google Search Appliance recognizes.

  6. 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)

  7. 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)

  8. A computer vision system for rapid search inspired by surface-based attention mechanisms from human perception.

    Science.gov (United States)

    Mohr, Johannes; Park, Jong-Han; Obermayer, Klaus

    2014-12-01

    Humans are highly efficient at visual search tasks by focusing selective attention on a small but relevant region of a visual scene. Recent results from biological vision suggest that surfaces of distinct physical objects form the basic units of this attentional process. The aim of this paper is to demonstrate how such surface-based attention mechanisms can speed up a computer vision system for visual search. The system uses fast perceptual grouping of depth cues to represent the visual world at the level of surfaces. This representation is stored in short-term memory and updated over time. A top-down guided attention mechanism sequentially selects one of the surfaces for detailed inspection by a recognition module. We show that the proposed attention framework requires little computational overhead (about 11 ms), but enables the system to operate in real-time and leads to a substantial increase in search efficiency. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. An approach involving dynamic group search optimization for allocating resources in OFDM-based cognitive radio system

    Directory of Open Access Journals (Sweden)

    Sameer Suresh Nanivadekar

    2018-03-01

    Full Text Available Allocation of channel resources in a cognitive radio system for achieving minimized transmission energy at an increased transmission rate is a challenging research. This paper proposes a resource allocation algorithm based on the meta-heuristic search principle. The proposed algorithm is an improved version of the Group Search Optimizer (GSO, which is a currently developed optimization algorithm that works through imitating the searching behaviour of the animals. The improvement is accomplished through introducing dynamics in the maximum pursuit angle of the GSO members. A cognitive radio system, relying on Orthogonal Frequency Division Multiplexing (OFDM for its operation, is simulated and the experimentations are carried out for sub-channel allocation. The proposed algorithm is experimentally compared with five renowned optimization algorithms, namely, conventional GSO, Particle Swarm Optimization, Genetic Algorithm, Firefly Algorithm and Artificial Bee Colony algorithm. The obtained results assert the competing performance of the proposed algorithm over the other algorithms. Keywords: Cognitive radio, OFDM, Resource, Allocation, Optimization, GSO

  10. 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.

  11. iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

    Science.gov (United States)

    Alor-Hernández, Giner; Pérez-Gallardo, Yuliana; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Rodríguez-González, Alejandro; Aguilar-Laserre, Alberto A

    2012-09-01

    Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

  12. Criticality and axial offset searches based on the integrated neutron balance approach

    International Nuclear Information System (INIS)

    Dall'Osso, A.; Van Geemert, R.

    2013-01-01

    Criticality and axial offset (AO) searches are key features in the simulation of plant operation procedures. Typically, the dedicated algorithms consist of either a Newton method or a secant method that features the successive computation of difference quotients to be used as derivatives. Within this context, computational robustness and efficiency are of paramount importance. This applies in particular to when the variations imposed during the search are spatially heterogeneous, such as in the case of tuning control rod positions for achieving target AO. In order to optimize this kind of search capability in AREVA NP's reactor code ARTEMIS in accordance with this design principle, a generalized approach has been implemented that harmonizes very well numerically with the overall multi-physics iterative solution process. As embedded in the latter, the new neutronic integral re-balancing approach is defined through periodic whole-core space-energy integrations of the principal terms in the core-integrated process-rate balance terms (i.e. neutron absorption, production and leakage). This procedure yields sequences of single zero-dimensional equations from which the chosen tuning parameters can be solved directly in dependence of the imposed (and systematically fixed) values for the response quantities k eff and/or AO. The converged result of the iteration sequence of successively obtained search parameter values is final in terms of being fully consistent with the entire set of multi-physics equations while enabling the accurate fulfillment of the target response value. The k etc and AO searches can be pursued simultaneously. Judging from the results of pursued verifications, the neutronic integral re-balancing approach fulfils the above-mentioned expectations convincingly. Specific verification examples are presented, such as the determination of the insertion depth of a critical control bank, a double search on target criticality and target AO by adjusting the boron

  13. Searching for Binary Systems Among Nearby Dwarfs Based on Pulkovo Observations and SDSS Data

    Science.gov (United States)

    Khovrichev, M. Yu.; Apetyan, A. A.; Roshchina, E. A.; Izmailov, I. S.; Bikulova, D. A.; Ershova, A. P.; Balyaev, I. A.; Kulikova, A. M.; Petyur, V. V.; Shumilov, A. A.; Os'kina, K. I.; Maksimova, L. A.

    2018-02-01

    Our goal is to find previously unknown binary systems among low-mass dwarfs in the solar neighborhood and to test the search technique. The basic ideas are to reveal the images of stars with significant ellipticities and/or asymmetries compared to the background stars on CCD frames and to subsequently determine the spatial parameters of the binary system and the magnitude difference between its components. For its realization we have developed a method based on an image shapelet decomposition. All of the comparatively faint stars with large proper motions ( V >13 m , μ > 300 mas yr-1) for which the "duplicate source" flag in the Gaia DR1 catalogue is equal to one have been included in the list of objects for our study. As a result, we have selected 702 stars. To verify our results, we have performed additional observations of 65 stars from this list with the Pulkovo 1-m "Saturn" telescope (2016-2017). We have revealed a total of 138 binary candidates (nine of them from the "Saturn" telescope and SDSS data). Six program stars are known binaries. The images of the primaries of the comparatively wide pairs WDS 14519+5147, WDS 11371+6022, and WDS 15404+2500 are shown to be resolved into components; therefore, we can talk about the detection of triple systems. The angular separation ρ, position angle, and component magnitude difference Δ m have been estimated for almost all of the revealed binary systems. For most stars 1.5'' < ρ < 2.5'', while Δ m <1.5m.

  14. Neurally and ocularly informed graph-based models for searching 3D environments

    Science.gov (United States)

    Jangraw, David C.; Wang, Jun; Lance, Brent J.; Chang, Shih-Fu; Sajda, Paul

    2014-08-01

    Objective. As we move through an environment, we are constantly making assessments, judgments and decisions about the things we encounter. Some are acted upon immediately, but many more become mental notes or fleeting impressions—our implicit ‘labeling’ of the world. In this paper, we use physiological correlates of this labeling to construct a hybrid brain-computer interface (hBCI) system for efficient navigation of a 3D environment. Approach. First, we record electroencephalographic (EEG), saccadic and pupillary data from subjects as they move through a small part of a 3D virtual city under free-viewing conditions. Using machine learning, we integrate the neural and ocular signals evoked by the objects they encounter to infer which ones are of subjective interest to them. These inferred labels are propagated through a large computer vision graph of objects in the city, using semi-supervised learning to identify other, unseen objects that are visually similar to the labeled ones. Finally, the system plots an efficient route to help the subjects visit the ‘similar’ objects it identifies. Main results. We show that by exploiting the subjects’ implicit labeling to find objects of interest instead of exploring naively, the median search precision is increased from 25% to 97%, and the median subject need only travel 40% of the distance to see 84% of the objects of interest. We also find that the neural and ocular signals contribute in a complementary fashion to the classifiers’ inference of subjects’ implicit labeling. Significance. In summary, we show that neural and ocular signals reflecting subjective assessment of objects in a 3D environment can be used to inform a graph-based learning model of that environment, resulting in an hBCI system that improves navigation and information delivery specific to the user’s interests.

  15. Search and selection hotel system in Surabaya based on geographic information system (GIS) with fuzzy logic

    Science.gov (United States)

    Purbandini, Taufik

    2016-03-01

    Surabaya is a metropolitan city in Indonesia. When the visitor has an interest in Surabaya for several days, then the visitor was looking for lodging that is closest to the interests of making it more efficient and practical. It was not a waste of time for the businessman because of congestion and so we need full information about the hotel as an inn during a stay in Surabaya began name, address of the hotel, the hotel's website, the distance from the hotel to the destination until the display of the map along the route with the help of Google Maps. This system was designed using fuzzy logic which aims to assist the user in making decisions. Design of hotel search and selection system was done through four stages. The first phase was the collection of data and as the factors that influence the decision-making along with the limit values of these factors. Factors that influence covers a distance of the hotel, the price of hotel rooms, and hotel reviews. The second stage was the processing of data and information by creating membership functions. The third stage was the analysis of systems with fuzzy logic. The steps were performed in systems analysis, namely fuzzification, inference using Mamdani, and defuzzification. The last stage was the design and construction of the system. Designing the system using use case diagrams and activity diagram to describe any process that occurs. Development system includes system implementation and evaluation systems. Implementation of mobile with Android-based system so that these applications were user friendly.

  16. Neurally and ocularly informed graph-based models for searching 3D environments.

    Science.gov (United States)

    Jangraw, David C; Wang, Jun; Lance, Brent J; Chang, Shih-Fu; Sajda, Paul

    2014-08-01

    As we move through an environment, we are constantly making assessments, judgments and decisions about the things we encounter. Some are acted upon immediately, but many more become mental notes or fleeting impressions-our implicit 'labeling' of the world. In this paper, we use physiological correlates of this labeling to construct a hybrid brain-computer interface (hBCI) system for efficient navigation of a 3D environment. First, we record electroencephalographic (EEG), saccadic and pupillary data from subjects as they move through a small part of a 3D virtual city under free-viewing conditions. Using machine learning, we integrate the neural and ocular signals evoked by the objects they encounter to infer which ones are of subjective interest to them. These inferred labels are propagated through a large computer vision graph of objects in the city, using semi-supervised learning to identify other, unseen objects that are visually similar to the labeled ones. Finally, the system plots an efficient route to help the subjects visit the 'similar' objects it identifies. We show that by exploiting the subjects' implicit labeling to find objects of interest instead of exploring naively, the median search precision is increased from 25% to 97%, and the median subject need only travel 40% of the distance to see 84% of the objects of interest. We also find that the neural and ocular signals contribute in a complementary fashion to the classifiers' inference of subjects' implicit labeling. In summary, we show that neural and ocular signals reflecting subjective assessment of objects in a 3D environment can be used to inform a graph-based learning model of that environment, resulting in an hBCI system that improves navigation and information delivery specific to the user's interests.

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

    Directory of Open Access Journals (Sweden)

    Kaijun Zhou

    2017-09-01

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

  18. Evaluation of the efficiency of computer-aided spectra search systems based on information theory

    International Nuclear Information System (INIS)

    Schaarschmidt, K.

    1979-01-01

    Application of information theory allows objective evaluation of the efficiency of computer-aided spectra search systems. For this purpose, a significant number of search processes must be analyzed. The amount of information gained by computer application is considered as the difference between the entropy of the data bank and a conditional entropy depending on the proportion of unsuccessful search processes and ballast. The influence of the following factors can be estimated: volume, structure, and quality of the spectra collection stored, efficiency of the encoding instruction and the comparing algorithm, and subjective errors involved in the encoding of spectra. The relations derived are applied to two published storage and retrieval systems for infared spectra. (Auth.)

  19. Planning Optimization of the Distributed Antenna System in High-Speed Railway Communication Network Based on Improved Cuckoo Search

    Directory of Open Access Journals (Sweden)

    Zhaoyu Chen

    2018-01-01

    Full Text Available The network planning is a key factor that directly affects the performance of the wireless networks. Distributed antenna system (DAS is an effective strategy for the network planning. This paper investigates the antenna deployment in a DAS for the high-speed railway communication networks and formulates an optimization problem which is NP-hard for achieving the optimal deployment of the antennas in the DAS. To solve this problem, a scheme based on an improved cuckoo search based on dimension cells (ICSDC algorithm is proposed. ICSDC introduces the dimension cell mechanism to avoid the internal dimension interferences in order to improve the performance of the algorithm. Simulation results show that the proposed ICSDC-based scheme obtains a lower network cost compared with the uniform network planning method. Moreover, ICSDC algorithm has better performance in terms of the convergence rate and accuracy compared with the conventional cuckoo search algorithm, the particle swarm optimization, and the firefly algorithm.

  20. 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.

  1. Cost Forecasting of Substation Projects Based on Cuckoo Search Algorithm and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Dongxiao Niu

    2018-01-01

    Full Text Available Accurate prediction of substation project cost is helpful to improve the investment management and sustainability. It is also directly related to the economy of substation project. Ensemble Empirical Mode Decomposition (EEMD can decompose variables with non-stationary sequence signals into significant regularity and periodicity, which is helpful in improving the accuracy of prediction model. Adding the Gauss perturbation to the traditional Cuckoo Search (CS algorithm can improve the searching vigor and precision of CS algorithm. Thus, the parameters and kernel functions of Support Vector Machines (SVM model are optimized. By comparing the prediction results with other models, this model has higher prediction accuracy.

  2. Designing the Search Service for Enterprise Portal based on Oracle Universal Content Management

    Science.gov (United States)

    Bauer, K. S.; Kuznetsov, D. Y.; Pominov, A. D.

    2017-01-01

    Enterprise Portal is an important part of an organization in informative and innovative space. The portal provides collaboration between employees and the organization. This article gives a valuable background of Enterprise Portal and technologies. The paper presents Oracle WebCenter Portal and UCM Server integration in detail. The focus is on tools for Enterprise Portal and on Search Service in particular. The paper also presents several UML diagrams to describe the use of cases for Search Service and main components of this application.

  3. Constraint Programming based Local Search for the Vehicle Routing Problem with Time Windows

    OpenAIRE

    Sala Reixach, Joan

    2012-01-01

    El projecte es centra en el "Vehicle Routing Problem with Time Windows". Explora i testeja un mètode basat en una formulació del problema en termes de programació de restriccions. Implementa un mètode de cerca local amb la capacitat de fer grans moviments anomenat "Large Neighbourhood Search".

  4. Aspiration Levels and R&D Search in Young Technology-Based Firms

    DEFF Research Database (Denmark)

    Candi, Marina; Saemundsson, Rognvaldur; Sigurjonsson, Olaf

    Decisions about allocation of resources to research and development (R&D), referred to here as R&D search, are critically important for competitive advantage. Using panel data collected yearly over a period of nine years, this paper re-visits existing theories of backward-looking and forward-look...

  5. Neural basis of feature-based contextual effects on visual search behavior

    Directory of Open Access Journals (Sweden)

    Kelly eShen

    2012-01-01

    Full Text Available Searching for a visual object is known to be adaptable to context, and it is thought to result from the selection of neural representations distributed on a visual salience map, wherein stimulus-driven and goal-directed signals are combined. Here we investigated the neural basis of this adaptability by recording superior colliculus (SC neurons while three female rhesus monkeys (Macaca mulatta searched with saccadic eye movements for a target presented in an array of visual stimuli whose feature composition varied from trial to trial. We found that sensory-motor activity associated with distracters was enhanced or suppressed depending on the search array composition and that it corresponded to the monkey's search strategy, as assessed by the distribution of the occasional errant saccades. This feature-related modulation occurred independently from the saccade goal and facilitated the process of saccade target selection. We also observed feature-related enhancement in the activity associated with distracters that had been the search target during the previous session. Consistent with recurrent processing, both feature-related neuronal modulations occurred more than 60 ms after the onset of the visually evoked responses, and their near coincidence with the time of saccade target selection suggests that they are integral to this process. These results suggest that SC neuronal activity is shaped by the visual context as dictated by both stimulus-driven and goal-directed signals. Given the close proximity of the SC to the motor circuit, our findings suggest a direct link between perception and action and no need for distinct salience and motor maps.

  6. High-Level Location Based Search Services That Improve Discoverability of Geophysical Data in the Virtual ITM Observatory

    Science.gov (United States)

    Schaefer, R. K.; Morrison, D.; Potter, M.; Barnes, R. J.; Nylund, S. R.; Patrone, D.; Aiello, J.; Talaat, E. R.; Sarris, T.

    2015-12-01

    The great promise of Virtual Observatories is the ability to perform complex search operations across the metadata of a large variety of different data sets. This allows the researcher to isolate and select the relevant measurements for their topic of study. The Virtual ITM Observatory (VITMO) has many diverse geophysical datasets that cover a large temporal and spatial range that present a unique search problem. VITMO provides many methods by which the user can search for and select data of interest including restricting selections based on geophysical conditions (solar wind speed, Kp, etc) as well as finding those datasets that overlap in time. One of the key challenges in improving discoverability is the ability to identify portions of datasets that overlap in time and in location. The difficulty is that location data is not contained in the metadata for datasets produced by satellites and would be extremely large in volume if it were available, making searching for overlapping data very time consuming. To solve this problem we have developed a series of light-weight web services that can provide a new data search capability for VITMO and others. The services consist of a database of spacecraft ephemerides and instrument fields of view; an overlap calculator to find times when the fields of view of different instruments intersect; and a magnetic field line tracing service that maps in situ and ground based measurements to the equatorial plane in magnetic coordinates for a number of field models and geophysical conditions. These services run in real-time when the user queries for data. These services will allow the non-specialist user to select data that they were previously unable to locate, opening up analysis opportunities beyond the instrument teams and specialists, making it easier for future students who come into the field.

  7. Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control Method, Software and Industrial Application

    CERN Document Server

    Kang, Shu Gang

    2013-01-01

    The Multi-Agent Based Beam Search (MABBS) method systematically integrates four major requirements of manufacturing production - representation capability, solution quality, computation efficiency, and implementation difficulty - within a unified framework to deal with the many challenges of complex real-world production planning and scheduling problems. Multi-agent Based Beam Search for Real-time Production Scheduling and Control introduces this method, together with its software implementation and industrial applications.  This book connects academic research with industrial practice, and develops a practical solution to production planning and scheduling problems. To simplify implementation, a reusable software platform is developed to build the MABBS method into a generic computation engine.  This engine is integrated with a script language, called the Embedded Extensible Application Script Language (EXASL), to provide a flexible and straightforward approach to representing complex real-world problems. ...

  8. An Improved Global Harmony Search Algorithm for the Identification of Nonlinear Discrete-Time Systems Based on Volterra Filter Modeling

    Directory of Open Access Journals (Sweden)

    Zongyan Li

    2016-01-01

    Full Text Available This paper describes an improved global harmony search (IGHS algorithm for identifying the nonlinear discrete-time systems based on second-order Volterra model. The IGHS is an improved version of the novel global harmony search (NGHS algorithm, and it makes two significant improvements on the NGHS. First, the genetic mutation operation is modified by combining normal distribution and Cauchy distribution, which enables the IGHS to fully explore and exploit the solution space. Second, an opposition-based learning (OBL is introduced and modified to improve the quality of harmony vectors. The IGHS algorithm is implemented on two numerical examples, and they are nonlinear discrete-time rational system and the real heat exchanger, respectively. The results of the IGHS are compared with those of the other three methods, and it has been verified to be more effective than the other three methods on solving the above two problems with different input signals and system memory sizes.

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

    Science.gov (United States)

    Yang, Dixiong; Liu, Zhenjun; Zhou, Jilei

    2014-04-01

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

  10. LiveWire interactive boundary extraction algorithm based on Haar wavelet transform and control point set direction search

    Science.gov (United States)

    Cheng, Jun; Zhang, Jun; Tian, Jinwen

    2015-12-01

    Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n2] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.

  11. 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...

  12. 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…

  13. Retrospective group fusion similarity search based on eROCE evaluation metric.

    Science.gov (United States)

    Avram, Sorin I; Crisan, Luminita; Bora, Alina; Pacureanu, Liliana M; Avram, Stefana; Kurunczi, Ludovic

    2013-03-01

    In this study, a simple evaluation metric, denoted as eROCE was proposed to measure the early enrichment of predictive methods. We demonstrated the superior robustness of eROCE compared to other known metrics throughout several active to inactive ratios ranging from 1:10 to 1:1000. Group fusion similarity search was investigated by varying 16 similarity coefficients, five molecular representations (binary and non-binary) and two group fusion rules using two reference structure set sizes. We used a dataset of 3478 actives and 43,938 inactive molecules and the enrichment was analyzed by means of eROCE. This retrospective study provides optimal similarity search parameters in the case of ALDH1A1 inhibitors. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Investigative change detection: identifying new topics using lexicon-based search

    Science.gov (United States)

    Hintz, Kenneth J.

    2002-08-01

    In law enforcement there is much textual data which needs to be searched in order to detect new threats. A new methodology which can be applied to this need is the automatic searching of the contents of documents from known sources to construct a lexicon of words used by that source. When analyzing future documents, the occurrence of words which have not been lexiconized are indicative of the introduction of a new topic into the source's lexicon which should be examined in its context by an analyst. A system analogous to this has been built and used to detect Fads and Categories on web sites. Fad refers to the first appearance of a word not in the lexicon; Category refers to the repeated appearance of a Fad word and the exceeding of some frequency or spatial occurrence metric indicating a permanence to the Category.

  15. 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

  16. A Web-based Tool for SDSS and 2MASS Database Searches

    Science.gov (United States)

    Hendrickson, M. A.; Uomoto, A.; Golimowski, D. A.

    We have developed a web site using HTML, Php, Python, and MySQL that extracts, processes, and displays data from the Sloan Digital Sky Survey (SDSS) and the Two-Micron All-Sky Survey (2MASS). The goal is to locate brown dwarf candidates in the SDSS database by looking at color cuts; however, this site could also be useful for targeted searches of other databases as well. MySQL databases are created from broad searches of SDSS and 2MASS data. Broad queries on the SDSS and 2MASS database servers are run weekly so that observers have the most up-to-date information from which to select candidates for observation. Observers can look at detailed information about specific objects including finding charts, images, and available spectra. In addition, updates from previous observations can be added by any collaborators; this format makes observational collaboration simple. Observers can also restrict the database search, just before or during an observing run, to select objects of special interest.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. GeoSearch: a new virtual globe application for the submission, storage, and sharing of point-based ecological data

    Science.gov (United States)

    Cardille, J. A.; Gonzales, R.; Parrott, L.; Bai, J.

    2009-12-01

    of ecological measurements in forests; we expect to extend the approach to a Quebec lake research network encompassing decades of lake measurements. In this session, we will describe and present four related components of the new system: GeoSearch’s globe-based searching and display of scientific data; prefuse-based visualization of social connections among members of a scientific research network; geolocation of research projects using Google Spreadsheets, KML, and Google Earth/Maps; and collaborative construction of a geolocated database of research articles. Each component is designed to have applications for scientists themselves as well as the general public. Although each implementation is in its infancy, we believe they could be useful to other researcher networks.

  2. Modified Three-Step Search Block Matching Motion Estimation and Weighted Finite Automata based Fractal Video Compression

    Directory of Open Access Journals (Sweden)

    Shailesh Kamble

    2017-08-01

    Full Text Available The major challenge with fractal image/video coding technique is that, it requires more encoding time. Therefore, how to reduce the encoding time is the research component remains in the fractal coding. Block matching motion estimation algorithms are used, to reduce the computations performed in the process of encoding. The objective of the proposed work is to develop an approach for video coding using modified three step search (MTSS block matching algorithm and weighted finite automata (WFA coding with a specific focus on reducing the encoding time. The MTSS block matching algorithm are used for computing motion vectors between the two frames i.e. displacement of pixels and WFA is used for the coding as it behaves like the Fractal Coding (FC. WFA represents an image (frame or motion compensated prediction error based on the idea of fractal that the image has self-similarity in itself. The self-similarity is sought from the symmetry of an image, so the encoding algorithm divides an image into multi-levels of quad-tree segmentations and creates an automaton from the sub-images. The proposed MTSS block matching algorithm is based on the combination of rectangular and hexagonal search pattern and compared with the existing New Three-Step Search (NTSS, Three-Step Search (TSS, and Efficient Three-Step Search (ETSS block matching estimation algorithm. The performance of the proposed MTSS block matching algorithm is evaluated on the basis of performance evaluation parameters i.e. mean absolute difference (MAD and average search points required per frame. Mean of absolute difference (MAD distortion function is used as the block distortion measure (BDM. Finally, developed approaches namely, MTSS and WFA, MTSS and FC, and Plane FC (applied on every frame are compared with each other. The experimentations are carried out on the standard uncompressed video databases, namely, akiyo, bus, mobile, suzie, traffic, football, soccer, ice etc. Developed

  3. CodeRAnts: A recommendation method based on collaborative searching and ant colonies, applied to reusing of open source code

    Directory of Open Access Journals (Sweden)

    Isaac Caicedo-Castro

    2014-01-01

    Full Text Available This paper presents CodeRAnts, a new recommendation method based on a collaborative searching technique and inspired on the ant colony metaphor. This method aims to fill the gap in the current state of the matter regarding recommender systems for software reuse, for which prior works present two problems. The first is that, recommender systems based on these works cannot learn from the collaboration of programmers and second, outcomes of assessments carried out on these systems present low precision measures and recall and in some of these systems, these metrics have not been evaluated. The work presented in this paper contributes a recommendation method, which solves these problems.

  4. PLC-based search and secure interlock system for the personnel safety in folded tandem ion accelerator

    International Nuclear Information System (INIS)

    Padmakumar, Sapna; Subramanyum, N.B.V.; Bhatt, Jignesh P.; Ware, Shailaja V.; Kansara, M.J.; Gupta, S.K.; Singh, P.

    2006-01-01

    Safety of the personnel is one of the key issues addressed in any accelerator project. The FOTIA facility at BARC is capable of operating under standard operation conditions without any radiation hazard. Even then for a safe and reliable operation of FOTIA a PLC (Programmable logic controller) based interlock system has been implemented. This interlocking system is compact, modular, flexible, robust and easy for troubleshooting. These advantages led to the popularity of PLC rather than using a relay-based system. This paper highlights the salient features of the search and secure interlock for the personal safety of FOTIA. (author)

  5. Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks

    Science.gov (United States)

    Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

    2014-01-01

    This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341

  6. The Rise of Market-Based Job Search Institutions and Job Niches for Low-Skilled Chinese Immigrants

    Directory of Open Access Journals (Sweden)

    Zai Liang

    2018-01-01

    Full Text Available Increasingly, market-based job search institutions, such as employment agencies and ethnic media, are playing a more important role than migrant networks for low-skilled Chinese immigrants searching for jobs. We argue that two major factors are driving this trend: the diversification of Chinese immigrants’ provinces of origin, and the spatial diffusion of businesses in the United States owned by Chinese immigrants. We also identify some new niche jobs for Chinese immigrants and assess the extent to which this development is driven by China’s growing prosperity. We use data from multiple sources, including a survey of employment agencies in Manhattan’s Chinatown, job advertisements in Chinese-language newspapers, and information on Chinese immigrant hometown associations in the United States.

  7. Statistical Pattern Recognition: Application to νμ→ντ Oscillation Searches Based on Kinematic Criteria

    Science.gov (United States)

    Bueno, A.; Martinez de la Ossa, A.; Navas, S.; Rubbia, A.

    2004-11-01

    Classic statistical techniques (like the multi-dimensional likelihood and the Fisher discriminant method) together with Multi-layer Perceptron and Learning Vector Quantization Neural Networks have been systematically used in order to find the best sensitivity when searching for νμ→ντ oscillations. We discovered that for a general direct ντ appearance search based on kinematic criteria: (a) An optimal discrimination power is obtained using only three variables (Evisible, PTmiss and ρl) and their correlations. Increasing the number of variables (or combinations of variables) only increases the complexity of the problem, but does not result in a sensible change of the expected sensitivity. (b) The multi-layer perceptron approach offers the best performance. As an example to assert numerically those points, we have considered the problem of ντ appearance at the CNGS beam using a Liquid Argon TPC detector.

  8. Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Wei Zhao

    2014-01-01

    Full Text Available This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes’ moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.

  9. An IRAS-Based Search for New Dusty Late-Type WC Wolf-Rayet Stars

    Science.gov (United States)

    Cohen, Martin

    1995-01-01

    I have examined all Infrared Astronomical Satellite (IRAS) data relevant to the 173 Galactic Wolf-Rayet (W-R) stars in an updated catalog, including the 13 stars newly discovered by Shara and coworkers. Using the W-R coordinates in these lists, I have examined the IRAS Point Source Catalog (PSC), the Faint Source Catalog, and the Faint Source Reject Catalog, and have generated one-dimensional spatial profiles, 'ADDSCANs', and two-dimensional full-resolution images, 'FRESCOS'. The goal was to assemble the best set of observed IRAS color indices for different W-R types, in particular for known dusty late-type WC Wolf-Rayet (WCL) objects. I have also unsuccessfully sought differences in IRAS colors and absolute magnitudes between single and binary W-R stars. The color indices for the entire ensemble of W-R stars define zones in the IRAS color-color ([12] - [25], [25] - [60])-plane. By searching the PSC for otherwise unassociated sources that satisfy these colors, I have identified potential new W-R candidates, perhaps too faint to have been recognized in previous optical searches. I have extracted these candidates' IRAS low-resolution spectrometer (LRS) data and compared the spectra with the highly characteristic LRS shape for known dusty WCL stars. The 13 surviving candidates must now be ex amined by optical spectroscopy. This work represents a much more rigorous and exhaustive version of the LRS study that identified IRAS 17380 - 3031 (WR98a) as the first new W-R (WC9) star discovered by IPAS. This search should have detected dusty WCL stars to a distance of 7.0 kpc from the Sun, for l is greater than 30 degrees, and to 2.9 kpc even in the innermost galaxy. For free-free-dominated W-R stars the corresponding distances are 2.5 and 1.0 kpc, respectively.

  10. Quasi-steady State Reduction of Molecular Motor-Based Models of Directed Intermittent Search

    KAUST Repository

    Newby, Jay M.

    2010-02-19

    We present a quasi-steady state reduction of a linear reaction-hyperbolic master equation describing the directed intermittent search for a hidden target by a motor-driven particle moving on a one-dimensional filament track. The particle is injected at one end of the track and randomly switches between stationary search phases and mobile nonsearch phases that are biased in the anterograde direction. There is a finite possibility that the particle fails to find the target due to an absorbing boundary at the other end of the track. Such a scenario is exemplified by the motor-driven transport of vesicular cargo to synaptic targets located on the axon or dendrites of a neuron. The reduced model is described by a scalar Fokker-Planck (FP) equation, which has an additional inhomogeneous decay term that takes into account absorption by the target. The FP equation is used to compute the probability of finding the hidden target (hitting probability) and the corresponding conditional mean first passage time (MFPT) in terms of the effective drift velocity V, diffusivity D, and target absorption rate λ of the random search. The quasi-steady state reduction determines V, D, and λ in terms of the various biophysical parameters of the underlying motor transport model. We first apply our analysis to a simple 3-state model and show that our quasi-steady state reduction yields results that are in excellent agreement with Monte Carlo simulations of the full system under physiologically reasonable conditions. We then consider a more complex multiple motor model of bidirectional transport, in which opposing motors compete in a "tug-of-war", and use this to explore how ATP concentration might regulate the delivery of cargo to synaptic targets. © 2010 Society for Mathematical Biology.

  11. Study of Fuze Structure and Reliability Design Based on the Direct Search Method

    Science.gov (United States)

    Lin, Zhang; Ning, Wang

    2017-03-01

    Redundant design is one of the important methods to improve the reliability of the system, but mutual coupling of multiple factors is often involved in the design. In my study, Direct Search Method is introduced into the optimum redundancy configuration for design optimization, in which, the reliability, cost, structural weight and other factors can be taken into account simultaneously, and the redundant allocation and reliability design of aircraft critical system are computed. The results show that this method is convenient and workable, and applicable to the redundancy configurations and optimization of various designs upon appropriate modifications. And this method has a good practical value.

  12. A novel field search and rescue system based on SIM card location

    Science.gov (United States)

    Zhang, Huihui; Guo, Shutao; Cui, Dejing

    2017-06-01

    Nowadays, the rapid development of outdoor sports and adventure leads to the increase of the frequency of missing accidents. On the other hand, it becomes much more convenient and efficient for the criminals to escape with the help of new technologies. So we have developed a long-distance raids targeted field search and rescue system which utilizes RSSI ranging and Kalman filtering algorithm to realize remote positioning and dynamic supervision management only by a mobile phone with a SIM card, without any additional terminal equipment.

  13. PMSVM: An Optimized Support Vector Machine Classification Algorithm Based on PCA and Multilevel Grid Search Methods

    Directory of Open Access Journals (Sweden)

    Yukai Yao

    2015-01-01

    Full Text Available We propose an optimized Support Vector Machine classifier, named PMSVM, in which System Normalization, PCA, and Multilevel Grid Search methods are comprehensively considered for data preprocessing and parameters optimization, respectively. The main goals of this study are to improve the classification efficiency and accuracy of SVM. Sensitivity, Specificity, Precision, and ROC curve, and so forth, are adopted to appraise the performances of PMSVM. Experimental results show that PMSVM has relatively better accuracy and remarkable higher efficiency compared with traditional SVM algorithms.

  14. Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage.

    Science.gov (United States)

    Guo, Yeting; Liu, Fang; Cai, Zhiping; Xiao, Nong; Zhao, Ziming

    2018-04-13

    Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query.

  15. Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

    Directory of Open Access Journals (Sweden)

    Meiqin Liu

    2017-12-01

    Full Text Available Underwater wireless sensor networks (UWSNs can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme.

  16. A Method for Estimating View Transformations from Image Correspondences Based on the Harmony Search Algorithm

    Directory of Open Access Journals (Sweden)

    Erik Cuevas

    2015-01-01

    Full Text Available In this paper, a new method for robustly estimating multiple view relations from point correspondences is presented. The approach combines the popular random sampling consensus (RANSAC algorithm and the evolutionary method harmony search (HS. With this combination, the proposed method adopts a different sampling strategy than RANSAC to generate putative solutions. Under the new mechanism, at each iteration, new candidate solutions are built taking into account the quality of the models generated by previous candidate solutions, rather than purely random as it is the case of RANSAC. The rules for the generation of candidate solutions (samples are motivated by the improvisation process that occurs when a musician searches for a better state of harmony. As a result, the proposed approach can substantially reduce the number of iterations still preserving the robust capabilities of RANSAC. The method is generic and its use is illustrated by the estimation of homographies, considering synthetic and real images. Additionally, in order to demonstrate the performance of the proposed approach within a real engineering application, it is employed to solve the problem of position estimation in a humanoid robot. Experimental results validate the efficiency of the proposed method in terms of accuracy, speed, and robustness.

  17. Searches for the Higgs Boson at the LHC based on its couplings to Vector Bosons

    CERN Document Server

    Hackstein, C

    One of the primary goals of the Large Hadron Collider (LHC) is the sea rch for the Higgs Boson. All Higgs searches rely heavily on Monte Carlo predic tions of both the signal and background processes. These simulations n ecessarily include models and assumptions not derived from first principles. Esp ecially the process of hadronization and the underlying event are only par tially un- derstood and differ strongly between different generators. As a r esult, the predictions can be wrong for special regions of phase space. Ther efore, pre- dictions by several programs should be compared to gain an estimat e of the uncertainty of the observables considered. In this work, two different Monte Carlo generators were compared in their pre- dictions for a Higgs search in the Vector Boson Fusion (VBF) Higgs pr oduction channel with subsequent decay into W bosons that decay leptonica lly in turn. A significant difference in the description of both signal and backgro und was found between the two generators. As the Monte...

  18. Micro-seismic waveform matching inversion based on gravitational search algorithm and parallel computation

    Science.gov (United States)

    Jiang, Y.; Xing, H. L.

    2016-12-01

    Micro-seismic events induced by water injection, mining activity or oil/gas extraction are quite informative, the interpretation of which can be applied for the reconstruction of underground stress and monitoring of hydraulic fracturing progress in oil/gas reservoirs. The source characterises and locations are crucial parameters that required for these purposes, which can be obtained through the waveform matching inversion (WMI) method. Therefore it is imperative to develop a WMI algorithm with high accuracy and convergence speed. Heuristic algorithm, as a category of nonlinear method, possesses a very high convergence speed and good capacity to overcome local minimal values, and has been well applied for many areas (e.g. image processing, artificial intelligence). However, its effectiveness for micro-seismic WMI is still poorly investigated; very few literatures exits that addressing this subject. In this research an advanced heuristic algorithm, gravitational search algorithm (GSA) , is proposed to estimate the focal mechanism (angle of strike, dip and rake) and source locations in three dimension. Unlike traditional inversion methods, the heuristic algorithm inversion does not require the approximation of green function. The method directly interacts with a CPU parallelized finite difference forward modelling engine, and updating the model parameters under GSA criterions. The effectiveness of this method is tested with synthetic data form a multi-layered elastic model; the results indicate GSA can be well applied on WMI and has its unique advantages. Keywords: Micro-seismicity, Waveform matching inversion, gravitational search algorithm, parallel computation

  19. Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage

    Directory of Open Access Journals (Sweden)

    Yeting Guo

    2018-04-01

    Full Text Available Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE, an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query.

  20. Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage

    Science.gov (United States)

    Liu, Fang; Cai, Zhiping; Xiao, Nong; Zhao, Ziming

    2018-01-01

    Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query. PMID:29652810

  1. Random searching

    International Nuclear Information System (INIS)

    Shlesinger, Michael F

    2009-01-01

    There are a wide variety of searching problems from molecules seeking receptor sites to predators seeking prey. The optimal search strategy can depend on constraints on time, energy, supplies or other variables. We discuss a number of cases and especially remark on the usefulness of Levy walk search patterns when the targets of the search are scarce.

  2. Search Patterns

    CERN Document Server

    Morville, Peter

    2010-01-01

    What people are saying about Search Patterns "Search Patterns is a delight to read -- very thoughtful and thought provoking. It's the most comprehensive survey of designing effective search experiences I've seen." --Irene Au, Director of User Experience, Google "I love this book! Thanks to Peter and Jeffery, I now know that search (yes, boring old yucky who cares search) is one of the coolest ways around of looking at the world." --Dan Roam, author, The Back of the Napkin (Portfolio Hardcover) "Search Patterns is a playful guide to the practical concerns of search interface design. It cont

  3. Effect of eccentricity on searches for gravitational waves from coalescing compact binaries in ground-based detectors

    International Nuclear Information System (INIS)

    Brown, Duncan A.; Zimmerman, Peter J.

    2010-01-01

    Inspiralling compact binaries are expected to circularize before their gravitational-wave signals reach the sensitive frequency band of ground-based detectors. Current searches for gravitational waves from compact binaries using the LIGO and Virgo detectors therefore use circular templates to construct matched filters. Binary formation models have been proposed which suggest that some systems detectable by the LIGO-Virgo network may have non-negligible eccentricity. We investigate the ability of the restricted 3.5 post-Newtonian order TaylorF2 template bank, used by LIGO and Virgo to search for gravitational waves from compact binaries with masses M≤35M · , to detect binaries with nonzero eccentricity. We model the gravitational waves from eccentric binaries using the x-model post-Newtonian formalism proposed by Hinder et al.[I. Hinder, F. Hermann, P. Laguna, and D. Shoemaker, arXiv:0806.1037v1]. We find that small residual eccentricities (e 0 · · . For eccentricities e 0 > or approx. 0.1, the loss in matched filter signal-to-noise ratio due to eccentricity can be significant and so templates which include eccentric effects will be required to perform optimal searches for such systems.

  4. A Memory Hierarchy Model Based on Data Reuse for Full-Search Motion Estimation on High-Definition Digital Videos

    Directory of Open Access Journals (Sweden)

    Alba Sandyra Bezerra Lopes

    2012-01-01

    Full Text Available The motion estimation is the most complex module in a video encoder requiring a high processing throughput and high memory bandwidth, mainly when the focus is high-definition videos. The throughput problem can be solved increasing the parallelism in the internal operations. The external memory bandwidth may be reduced using a memory hierarchy. This work presents a memory hierarchy model for a full-search motion estimation core. The proposed memory hierarchy model is based on a data reuse scheme considering the full search algorithm features. The proposed memory hierarchy expressively reduces the external memory bandwidth required for the motion estimation process, and it provides a very high data throughput for the ME core. This throughput is necessary to achieve real time when processing high-definition videos. When considering the worst bandwidth scenario, this memory hierarchy is able to reduce the external memory bandwidth in 578 times. A case study for the proposed hierarchy, using 32×32 search window and 8×8 block size, was implemented and prototyped on a Virtex 4 FPGA. The results show that it is possible to reach 38 frames per second when processing full HD frames (1920×1080 pixels using nearly 299 Mbytes per second of external memory bandwidth.

  5. 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.

  6. MUSiC. A model unspecific search in CMS based on 2010 LHC data

    Energy Technology Data Exchange (ETDEWEB)

    Pieta, Holger

    2012-06-20

    A Model Unspecific Search in CMS (MUSiC) is presented in this work, along with its results on the data taken in 2010 by the Compact Muon Solenoid (CMS) at the Large Hadron Collider (LHC). This analysis shows a sensitivity to various models for new physics and provides a broad view at the data, due to its minimal theoretical bias. Events are classified with respect to their reconstructed objects: Muons, electrons, photons, jets and missing transverse energy. Up to three kinematic variables in each of these classes are systematically scanned for continuous bin regions deviating significantly from the predictions by the Standard Model of particle physics. No deviations beyond expected fluctuations are observed, when taking systematic uncertainties into account. The sensitivity of the analysis to certain models beyond the Standard Model is demonstrated.

  7. SPECTRa-T: machine-based data extraction and semantic searching of chemistry e-theses.

    Science.gov (United States)

    Downing, Jim; Harvey, Matt J; Morgan, Peter B; Murray-Rust, Peter; Rzepa, Henry S; Stewart, Diana C; Tonge, Alan P; Townsend, Joe A

    2010-02-22

    The SPECTRa-T project has developed text-mining tools to extract named chemical entities (NCEs), such as chemical names and terms, and chemical objects (COs), e.g., experimental spectral assignments and physical chemistry properties, from electronic theses (e-theses). Although NCEs were readily identified within the two major document formats studied, only the use of structured documents enabled identification of chemical objects and their association with the relevant chemical entity (e.g., systematic chemical name). A corpus of theses was analyzed and it is shown that a high degree of semantic information can be extracted from structured documents. This integrated information has been deposited in a persistent Resource Description Framework (RDF) triple-store that allows users to conduct semantic searches. The strength and weaknesses of several document formats are reviewed.

  8. Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction.

    Science.gov (United States)

    de Oliveira, Saulo H P; Law, Eleanor C; Shi, Jiye; Deane, Charlotte M

    2018-04-01

    Most current de novo structure prediction methods randomly sample protein conformations and thus require large amounts of computational resource. Here, we consider a sequential sampling strategy, building on ideas from recent experimental work which shows that many proteins fold cotranslationally. We have investigated whether a pseudo-greedy search approach, which begins sequentially from one of the termini, can improve the performance and accuracy of de novo protein structure prediction. We observed that our sequential approach converges when fewer than 20 000 decoys have been produced, fewer than commonly expected. Using our software, SAINT2, we also compared the run time and quality of models produced in a sequential fashion against a standard, non-sequential approach. Sequential prediction produces an individual decoy 1.5-2.5 times faster than non-sequential prediction. When considering the quality of the best model, sequential prediction led to a better model being produced for 31 out of 41 soluble protein validation cases and for 18 out of 24 transmembrane protein cases. Correct models (TM-Score > 0.5) were produced for 29 of these cases by the sequential mode and for only 22 by the non-sequential mode. Our comparison reveals that a sequential search strategy can be used to drastically reduce computational time of de novo protein structure prediction and improve accuracy. Data are available for download from: http://opig.stats.ox.ac.uk/resources. SAINT2 is available for download from: https://github.com/sauloho/SAINT2. saulo.deoliveira@dtc.ox.ac.uk. Supplementary data are available at Bioinformatics online.

  9. Hybrid Multiple Soft-Sensor Models of Grinding Granularity Based on Cuckoo Searching Algorithm and Hysteresis Switching Strategy

    Directory of Open Access Journals (Sweden)

    Jie-Sheng Wang

    2015-01-01

    Full Text Available According to the characteristics of grinding process and accuracy requirements of technical indicators, a hybrid multiple soft-sensor modeling method of grinding granularity is proposed based on cuckoo searching (CS algorithm and hysteresis switching (HS strategy. Firstly, a mechanism soft-sensor model of grinding granularity is deduced based on the technique characteristics and a lot of experimental data of grinding process. Meanwhile, the BP neural network soft-sensor model and wavelet neural network (WNN soft-sensor model are set up. Then, the hybrid multiple soft-sensor model based on the hysteresis switching strategy is realized. That is to say, the optimum model is selected as the current predictive model according to the switching performance index at each sampling instant. Finally the cuckoo searching algorithm is adopted to optimize the performance parameters of hysteresis switching strategy. Simulation results show that the proposed model has better generalization results and prediction precision, which can satisfy the real-time control requirements of grinding classification process.

  10. A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

    Science.gov (United States)

    Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie

    2014-12-01

    Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

  11. A class-based search for the in-core fuel management optimization of a pressurized water reactor

    International Nuclear Information System (INIS)

    Alvarenga de Moura Meneses, Anderson; Rancoita, Paola; Schirru, Roberto; Gambardella, Luca Maria

    2010-01-01

    The In-Core Fuel Management Optimization (ICFMO) is a prominent problem in nuclear engineering, with high complexity and studied for more than 40 years. Besides manual optimization and knowledge-based methods, optimization metaheuristics such as Genetic Algorithms, Ant Colony Optimization and Particle Swarm Optimization have yielded outstanding results for the ICFMO. In the present article, the Class-Based Search (CBS) is presented for application to the ICFMO. It is a novel metaheuristic approach that performs the search based on the main nuclear characteristics of the fuel assemblies, such as reactivity. The CBS is then compared to the one of the state-of-art algorithms applied to the ICFMO, the Particle Swarm Optimization. Experiments were performed for the optimization of Angra 1 Nuclear Power Plant, located at the Southeast of Brazil. The CBS presented noticeable performance, providing Loading Patterns that yield a higher average of Effective Full Power Days in the simulation of Angra 1 NPP operation, according to our methodology.

  12. A class-based search for the in-core fuel management optimization of a pressurized water reactor

    Energy Technology Data Exchange (ETDEWEB)

    Alvarenga de Moura Meneses, Anderson, E-mail: ameneses@lmp.ufrj.b [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); Rancoita, Paola [IDSIA (Dalle Molle Institute for Artificial Intelligence), Galleria 2, 6982 Manno-Lugano, TI (Switzerland); Mathematics Department, Universita degli Studi di Milano (Italy); Schirru, Roberto [Federal University of Rio de Janeiro, COPPE, Nuclear Engineering Program, CP 68509, CEP 21.941-972, Rio de Janeiro, RJ (Brazil); Gambardella, Luca Maria [IDSIA (Dalle Molle Institute for Artificial Intelligence), Galleria 2, 6982 Manno-Lugano, TI (Switzerland)

    2010-11-15

    The In-Core Fuel Management Optimization (ICFMO) is a prominent problem in nuclear engineering, with high complexity and studied for more than 40 years. Besides manual optimization and knowledge-based methods, optimization metaheuristics such as Genetic Algorithms, Ant Colony Optimization and Particle Swarm Optimization have yielded outstanding results for the ICFMO. In the present article, the Class-Based Search (CBS) is presented for application to the ICFMO. It is a novel metaheuristic approach that performs the search based on the main nuclear characteristics of the fuel assemblies, such as reactivity. The CBS is then compared to the one of the state-of-art algorithms applied to the ICFMO, the Particle Swarm Optimization. Experiments were performed for the optimization of Angra 1 Nuclear Power Plant, located at the Southeast of Brazil. The CBS presented noticeable performance, providing Loading Patterns that yield a higher average of Effective Full Power Days in the simulation of Angra 1 NPP operation, according to our methodology.

  13. 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.

  14. OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

    Science.gov (United States)

    Huang, Jingshan; Gutierrez, Fernando; Strachan, Harrison J; Dou, Dejing; Huang, Weili; Smith, Barry; Blake, Judith A; Eilbeck, Karen; Natale, Darren A; Lin, Yu; Wu, Bin; Silva, Nisansa de; Wang, Xiaowei; Liu, Zixing; Borchert, Glen M; Tan, Ming; Ruttenberg, Alan

    2016-01-01

    As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software.

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

    Directory of Open Access Journals (Sweden)

    Soonjoo Park, RN, PhD

    2015-09-01

    Conclusions: 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.

  16. Developing a Data Discovery Tool for Interdisciplinary Science: Leveraging a Web-based Mapping Application and Geosemantic Searching

    Science.gov (United States)

    Albeke, S. E.; Perkins, D. G.; Ewers, S. L.; Ewers, B. E.; Holbrook, W. S.; Miller, S. N.

    2015-12-01

    The sharing of data and results is paramount for advancing scientific research. The Wyoming Center for Environmental Hydrology and Geophysics (WyCEHG) is a multidisciplinary group that is driving scientific breakthroughs to help manage water resources in the Western United States. WyCEHG is mandated by the National Science Foundation (NSF) to share their data. However, the infrastructure from which to share such diverse, complex and massive amounts of data did not exist within the University of Wyoming. We developed an innovative framework to meet the data organization, sharing, and discovery requirements of WyCEHG by integrating both open and closed source software, embedded metadata tags, semantic web technologies, and a web-mapping application. The infrastructure uses a Relational Database Management System as the foundation, providing a versatile platform to store, organize, and query myriad datasets, taking advantage of both structured and unstructured formats. Detailed metadata are fundamental to the utility of datasets. We tag data with Uniform Resource Identifiers (URI's) to specify concepts with formal descriptions (i.e. semantic ontologies), thus allowing users the ability to search metadata based on the intended context rather than conventional keyword searches. Additionally, WyCEHG data are geographically referenced. Using the ArcGIS API for Javascript, we developed a web mapping application leveraging database-linked spatial data services, providing a means to visualize and spatially query available data in an intuitive map environment. Using server-side scripting (PHP), the mapping application, in conjunction with semantic search modules, dynamically communicates with the database and file system, providing access to available datasets. Our approach provides a flexible, comprehensive infrastructure from which to store and serve WyCEHG's highly diverse research-based data. This framework has not only allowed WyCEHG to meet its data stewardship

  17. 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.

  18. 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.

  19. Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

    Science.gov (United States)

    Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

    2018-05-01

    Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

  20. A CCD-based search for very low mass members of the Pleiades cluster

    Science.gov (United States)

    Stauffer, John R.; Hamilton, Donald; Probst, Ronald G.

    1994-01-01

    We have obtained deep charge coupled device (CCD)V and I images of a number of fields near the center of the Pleiades open cluster. We have also obtained imaging data for Praesepe, a very similar cluster in terms of distance and richness but nearly 10 times older than the Pleiades. Because brown dwarfs are predicted to become much fainter and cooler between Pleiades and Praesepe ages, this provides a powerful differential technique for placing constraints on the brown dwarf population in open clusters. Combined with our previously reported observations, we now have data for about 0.4 sq deg in the Pleiades, corresponding roughly to 5% of the area of that cluster. We have searched the new CCD frames for additional Pleiades brown dwarf candidates. Two possible candidates are present, the faintest of which has V approximately equal to 22.5, (V-I)(sub K) approximately equal to 4.6. Because we do not have proper motion data and the colors of these objects are not redder than the reddest known field stars, it is possible that some or all of our candidates are somewhat higher mass field stars rather than Pleiades-age brown dwarfs. Even if all six of the proposed brown dwarf candidates in our 0.4 sq deg field are Pleiades members, the relatively small number found suggests that low mass stars or brown dwarfs do not contribute significantly to the total mass of the cluster.

  1. 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

  2. Construction of web-based nutrition education contents and searching engine for usage of healthy menu of children

    Science.gov (United States)

    Lee, Tae-Kyong; Chung, Hea-Jung; Park, Hye-Kyung; Lee, Eun-Ju; Nam, Hye-Seon; Jung, Soon-Im; Cho, Jee-Ye; Lee, Jin-Hee; Kim, Gon; Kim, Min-Chan

    2008-01-01

    A diet habit, which is developed in childhood, lasts for a life time. In this sense, nutrition education and early exposure to healthy menus in childhood is important. Children these days have easy access to the internet. Thus, a web-based nutrition education program for children is an effective tool for nutrition education of children. This site provides the material of the nutrition education for children with characters which are personified nutrients. The 151 menus are stored in the site together with video script of the cooking process. The menus are classified by the criteria based on age, menu type and the ethnic origin of the menu. The site provides a search function. There are three kinds of search conditions which are key words, menu type and "between" expression of nutrients such as calorie and other nutrients. The site is developed with the operating system Windows 2003 Server, the web server ZEUS 5, development language JSP, and database management system Oracle 10 g. PMID:20126375

  3. A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles.

    Science.gov (United States)

    Omar, Hani; Hoang, Van Hai; Liu, Duen-Ren

    2016-01-01

    Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, since popular article titles and headlines can attract readers to buy magazines. In this paper, information retrieval techniques are adopted to extract words from article titles. The popularity measures of article titles are then analyzed by using the search indexes obtained from Google search engine. Backpropagation Neural Networks (BPNNs) have successfully been used to develop prediction models for sales forecasting. In this study, we propose a novel hybrid neural network model for sales forecasting based on the prediction result of time series forecasting and the popularity of article titles. The proposed model uses the historical sales data, popularity of article titles, and the prediction result of a time series, Autoregressive Integrated Moving Average (ARIMA) forecasting method to learn a BPNN-based forecasting model. Our proposed forecasting model is experimentally evaluated by comparing with conventional sales prediction techniques. The experimental result shows that our proposed forecasting method outperforms conventional techniques which do not consider the popularity of title words.

  4. A Hybrid Neural Network Model for Sales Forecasting Based on ARIMA and Search Popularity of Article Titles

    Science.gov (United States)

    Omar, Hani; Hoang, Van Hai; Liu, Duen-Ren

    2016-01-01

    Enhancing sales and operations planning through forecasting analysis and business intelligence is demanded in many industries and enterprises. Publishing industries usually pick attractive titles and headlines for their stories to increase sales, since popular article titles and headlines can attract readers to buy magazines. In this paper, information retrieval techniques are adopted to extract words from article titles. The popularity measures of article titles are then analyzed by using the search indexes obtained from Google search engine. Backpropagation Neural Networks (BPNNs) have successfully been used to develop prediction models for sales forecasting. In this study, we propose a novel hybrid neural network model for sales forecasting based on the prediction result of time series forecasting and the popularity of article titles. The proposed model uses the historical sales data, popularity of article titles, and the prediction result of a time series, Autoregressive Integrated Moving Average (ARIMA) forecasting method to learn a BPNN-based forecasting model. Our proposed forecasting model is experimentally evaluated by comparing with conventional sales prediction techniques. The experimental result shows that our proposed forecasting method outperforms conventional techniques which do not consider the popularity of title words. PMID:27313605

  5. Classical algorithms for automated parameter-search methods in compartmental neural models - A critical survey based on simulations using neuron

    International Nuclear Information System (INIS)

    Mutihac, R.; Mutihac, R.C.; Cicuttin, A.

    2001-09-01

    Parameter-search methods are problem-sensitive. All methods depend on some meta-parameters of their own, which must be determined experimentally in advance. A better choice of these intrinsic parameters for a certain parameter-search method may improve its performance. Moreover, there are various implementations of the same method, which may also affect its performance. The choice of the matching (error) function has a great impact on the search process in terms of finding the optimal parameter set and minimizing the computational cost. An initial assessment of the matching function ability to distinguish between good and bad models is recommended, before launching exhaustive computations. However, different runs of a parameter search method may result in the same optimal parameter set or in different parameter sets (the model is insufficiently constrained to accurately characterize the real system). Robustness of the parameter set is expressed by the extent to which small perturbations in the parameter values are not affecting the best solution. A parameter set that is not robust is unlikely to be physiologically relevant. Robustness can also be defined as the stability of the optimal parameter set to small variations of the inputs. When trying to estimate things like the minimum, or the least-squares optimal parameters of a nonlinear system, the existence of multiple local minima can cause problems with the determination of the global optimum. Techniques such as Newton's method, the Simplex method and Least-squares Linear Taylor Differential correction technique can be useful provided that one is lucky enough to start sufficiently close to the global minimum. All these methods suffer from the inability to distinguish a local minimum from a global one because they follow the local gradients towards the minimum, even if some methods are resetting the search direction when it is likely to get stuck in presumably a local minimum. Deterministic methods based on

  6. Mindfulness-Based Symptom and Stress Management Apps for Adults With Chronic Lung Disease: Systematic Search in App Stores.

    Science.gov (United States)

    Owens, Otis L; Beer, Jenay M; Reyes, Ligia I; Gallerani, David G; Myhren-Bennett, Amanda R; McDonnell, Karen K

    2018-05-15

    Up to 70% of lung cancer survivors are affected by chronic obstructive pulmonary disease (COPD), a common, debilitating, comorbid disease. Lung cancer and COPD are both characterized by symptoms such as breathlessness, fatigue, and psychological distress. These distressing chronic symptoms are exacerbated by stress and detract from an individual's quality of life. The aim of this study was to identify and evaluate evidence-based, commercially available apps for promoting mindfulness-based strategies among adults with a COPD or lung cancer history (ie, chronic lung disease). For this review, an interdisciplinary research team used 19 keyword combinations in the search engines of Google and iOS app stores in May 2017. Evaluations were conducted on the apps' (1) content, (2) usability heuristics, (3) grade-level readability, and (4) cultural sensitivity. The search resulted in 768 apps (508 in iOS and 260 in Google stores). A total of 9 apps met the inclusion criteria and received further evaluation. Only 1 app had below an eighth-grade reading level; the ninth one did not have enough text to calculate a readability score. None of the 9 apps met the cultural sensitivity evaluation criteria. This systematic review identified critical design flaws that may affect the ease of using the apps in this study. Few mobile apps promote mindfulness-based strategies among adults with chronic lung disease (ie, COPD or lung cancer or both), but those that exist, overall, do not meet the latest scientific evidence. Recommendations include more stringent regulation of health-related apps, use of evidence-based frameworks and participatory design processes, following evidence-based usability practices, use of culturally sensitive language and images, and ensuring that content is written in plain language. ©Otis L Owens, Jenay M Beer, Ligia I Reyes, David G Gallerani, Amanda R Myhren-Bennett, Karen K McDonnell. Originally published in JMIR Mhealth and Uhealth (http

  7. Personalized Search

    CERN Document Server

    AUTHOR|(SzGeCERN)749939

    2015-01-01

    As the volume of electronically available information grows, relevant items become harder to find. This work presents an approach to personalizing search results in scientific publication databases. This work focuses on re-ranking search results from existing search engines like Solr or ElasticSearch. This work also includes the development of Obelix, a new recommendation system used to re-rank search results. The project was proposed and performed at CERN, using the scientific publications available on the CERN Document Server (CDS). This work experiments with re-ranking using offline and online evaluation of users and documents in CDS. The experiments conclude that the personalized search result outperform both latest first and word similarity in terms of click position in the search result for global search in CDS.

  8. 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.

  9. 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…

  10. Evaluation of diffusion-tensor imaging-based global search and tractography for tumor surgery close to the language system.

    Directory of Open Access Journals (Sweden)

    Mirco Richter

    Full Text Available Pre-operative planning and intra-operative guidance in neurosurgery require detailed information about the location of functional areas and their anatomo-functional connectivity. In particular, regarding the language system, post-operative deficits such as aphasia can be avoided. By combining functional magnetic resonance imaging and diffusion tensor imaging, the connectivity between functional areas can be reconstructed by tractography techniques that need to cope with limitations such as limited resolution and low anisotropic diffusion close to functional areas. Tumors pose particular challenges because of edema, displacement effects on brain tissue and infiltration of white matter. Under these conditions, standard fiber tracking methods reconstruct pathways of insufficient quality. Therefore, robust global or probabilistic approaches are required. In this study, two commonly used standard fiber tracking algorithms, streamline propagation and tensor deflection, were compared with a previously published global search, Gibbs tracking and a connection-oriented probabilistic tractography approach. All methods were applied to reconstruct neuronal pathways of the language system of patients undergoing brain tumor surgery, and control subjects. Connections between Broca and Wernicke areas via the arcuate fasciculus (AF and the inferior fronto-occipital fasciculus (IFOF were validated by a clinical expert to ensure anatomical feasibility, and compared using distance- and diffusion-based similarity metrics to evaluate their agreement on pathway locations. For both patients and controls, a strong agreement between all methods was observed regarding the location of the AF. In case of the IFOF however, standard fiber tracking and Gibbs tracking predominantly identified the inferior longitudinal fasciculus that plays a secondary role in semantic language processing. In contrast, global search resolved connections in almost every case via the IFOF which

  11. Improving performance of content-based image retrieval schemes in searching for similar breast mass regions: an assessment

    International Nuclear Information System (INIS)

    Wang Xiaohui; Park, Sang Cheol; Zheng Bin

    2009-01-01

    This study aims to assess three methods commonly used in content-based image retrieval (CBIR) schemes and investigate the approaches to improve scheme performance. A reference database involving 3000 regions of interest (ROIs) was established. Among them, 400 ROIs were randomly selected to form a testing dataset. Three methods, namely mutual information, Pearson's correlation and a multi-feature-based k-nearest neighbor (KNN) algorithm, were applied to search for the 15 'the most similar' reference ROIs to each testing ROI. The clinical relevance and visual similarity of searching results were evaluated using the areas under receiver operating characteristic (ROC) curves (A Z ) and average mean square difference (MSD) of the mass boundary spiculation level ratings between testing and selected ROIs, respectively. The results showed that the A Z values were 0.893 ± 0.009, 0.606 ± 0.021 and 0.699 ± 0.026 for the use of KNN, mutual information and Pearson's correlation, respectively. The A Z values increased to 0.724 ± 0.017 and 0.787 ± 0.016 for mutual information and Pearson's correlation when using ROIs with the size adaptively adjusted based on actual mass size. The corresponding MSD values were 2.107 ± 0.718, 2.301 ± 0.733 and 2.298 ± 0.743. The study demonstrates that due to the diversity of medical images, CBIR schemes using multiple image features and mass size-based ROIs can achieve significantly improved performance.

  12. Prognostic significance of gastrointestinal symptoms and diagnosis in relation to the acute radiation syndrome. A retrospective analysis based on the data base SEARCH

    International Nuclear Information System (INIS)

    Hoebbel, Mathias Niklaus Johannes

    2016-01-01

    The following thesis explores the prognostic significance of gastrointestinal symptoms and diagnoses in relation to acute radiation syndrome. This is a retrospective analysis based on the SEARCH (System of Evaluation and Archiving of Radiation Accidents based on Case Histories) database, which was created by a team of researchers in Ulm in 1998. The SEARCH database compiled health status data of individuals involved in a total of 78 ionized radiation accidents between 1945 and 2003. In the past changes in bloodbuilding systems were considered the defining factor in determining a prognosis regarding survival times. Treatment decisions were made in line with these findings, including stem-cell transplants. In recent history, especially after the nuclear disaster in Chernobyl in 1986, the focus shifted onto other organ systems. As a result it has been proven that significant cutaneous damages present an important influence on survival regardless of haematopoiesis. Several researchers have looked at changes in the gastrointestinal tract and possible correlations with radiation induced multiple organ failure. In this paper, all of the data recorded in SEARCH in regards to gastrointestinal symptoms have been analyzed. These include symptoms such as nausea, vomiting and changes in bowel movement as well as their onset and severity. Radiation-induced oral mucositis was also further investigated. Despite the occasional gaps in data in SEARCH, results from the analysis proved that the occurrence of certain symptoms, their severity and their onset were directly correlated to life expectancy, regardless of the dose estimation, and the pending blood test results. An immediate triage of these patients by skilled medical professionals is imperative to accurate categorization.

  13. Installation Restoration Program, Phase 1. Records Search, Wheeler Air Force Base, Oahu, Hawaii

    Science.gov (United States)

    1983-07-01

    the 3vegetation was already exotic, consisting of trees such as guava , koa haole, eucalyptus and silver oak, and shrubs and 3 grasses including lantana...Alkalioo Soap 5 gal GrounOd S~r Of f Base Fire Pit fir.Pit Of f Base PmecI" CoCAClo 20$ P 680 1S Sa.L Cro-..d tAint 10-20 gal 8w L..dt±u Off km. Thinmar

  14. In search of synergies between policy-based systems management and economic models for autonomic computing

    OpenAIRE

    Anthony, Richard

    2011-01-01

    Policy-based systems management (PBM) and economics-based systems management (EBM) are two of the many techniques available for implementing autonomic systems, each having specific benefits and limitations, and thus different applicability; choosing the most appropriate technique is\\ud the first of many challenges faced by the developer. This talk begins with a critical discussion of the general design goals of autonomic systems and the main issues involved with their development and deployme...

  15. Education and Public Outreach for Stardust@home: An Interactive Internet-based Search for Interstellar Dust

    Science.gov (United States)

    Mendez, Bryan J.; Westphal, A. J.; Butterworth, A. L.; Craig, N.

    2006-12-01

    On January 15, 2006, NASA’s Stardust mission returned to Earth after nearly seven years in interplanetary space. During its journey, Stardust encountered comet Wild 2, collecting dust particles from it in a special material called aerogel. At two other times in the mission, aerogel collectors were also opened to collect interstellar dust. The Stardust Interstellar Dust Collector is being scanned by an automated microscope at the Johnson Space Center. There are approximately 700,000 fields of view needed to cover the entire collector, but we expect only a few dozen total grains of interstellar dust were captured within it. Finding these particles is a daunting task. We have recruited many thousands of volunteers from the public to aid in the search for these precious pieces of space dust trapped in the collectors. We call the project Stardust@home. Through Stardust@home, volunteers from the public search fields of view from the Stardust aerogel collector using a web-based Virtual Microscope. Volunteers who discover interstellar dust particles have the privilege of naming them. The interest and response to this project has been extraordinary. Many people from all walks of life are very excited about space science and eager to volunteer their time to contribute to a real research project such as this. We will discuss the progress of the project and the education and outreach activities being carried out for it.

  16. Maximize Minimum Utility Function of Fractional Cloud Computing System Based on Search Algorithm Utilizing the Mittag-Leffler Sum

    Directory of Open Access Journals (Sweden)

    Rabha W. Ibrahim

    2018-01-01

    Full Text Available The maximum min utility function (MMUF problem is an important representative of a large class of cloud computing systems (CCS. Having numerous applications in practice, especially in economy and industry. This paper introduces an effective solution-based search (SBS algorithm for solving the problem MMUF. First, we suggest a new formula of the utility function in term of the capacity of the cloud. We formulate the capacity in CCS, by using a fractional diffeo-integral equation. This equation usually describes the flow of CCS. The new formula of the utility function is modified recent active utility functions. The suggested technique first creates a high-quality initial solution by eliminating the less promising components, and then develops the quality of the achieved solution by the summation search solution (SSS. This method is considered by the Mittag-Leffler sum as hash functions to determine the position of the agent. Experimental results commonly utilized in the literature demonstrate that the proposed algorithm competes approvingly with the state-of-the-art algorithms both in terms of solution quality and computational efficiency.

  17. Duplex Interrogation by a Direct DNA Repair Protein in Search of Base Damage

    Science.gov (United States)

    Yi, Chengqi; Chen, Baoen; Qi, Bo; Zhang, Wen; Jia, Guifang; Zhang, Liang; Li, Charles J.; Dinner, Aaron R.; Yang, Cai-Guang; He, Chuan

    2012-01-01

    ALKBH2 is a direct DNA repair dioxygenase guarding mammalian genome against N1-methyladenine, N3-methylcytosine, and 1,N6-ethenoadenine damage. A prerequisite for repair is to identify these lesions in the genome. Here we present crystal structures of ALKBH2 bound to different duplex DNAs. Together with computational and biochemical analyses, our results suggest that DNA interrogation by ALKBH2 displays two novel features: i) ALKBH2 probes base-pair stability and detects base pairs with reduced stability; ii) ALKBH2 does not have nor need a “damage-checking site”, which is critical for preventing spurious base-cleavage for several glycosylases. The demethylation mechanism of ALKBH2 insures that only cognate lesions are oxidized and reversed to normal bases, and that a flipped, non-substrate base remains intact in the active site. Overall, the combination of duplex interrogation and oxidation chemistry allows ALKBH2 to detect and process diverse lesions efficiently and correctly. PMID:22659876

  18. Object recognition based on Google's reverse image search and image similarity

    Science.gov (United States)

    Horváth, András.

    2015-12-01

    Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

  19. Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection

    NARCIS (Netherlands)

    Hudelist, M.A.; Cobârzan, C.; Beecks, C.; van de Werken, Rob; Kletz, S.; Hürst, W.O.; Schoeffmann, K.

    2016-01-01

    We propose a novel video browsing approach that aims at optimally integrating traditional, machine-based retrieval methods with an interface design optimized for human browsing performance. Advanced video retrieval and filtering (e.g., via color and motion signatures, and visual concepts) on a

  20. In Search of Museum Professional Knowledge Base: Mapping the Professional Knowledge Debate onto Museum Work

    Science.gov (United States)

    Tlili, Anwar

    2016-01-01

    Museum professionalism remains an unexplored area in museum studies, particularly with regard to what is arguably the core generic question of a "sui generis" professional knowledge base, and its necessary and sufficient conditions. The need to examine this question becomes all the more important with the increasing expansion of the…