Search results for: Search Algorithms

Authors: J. Cheeneebash, S. Jugee

Abstract:

In this paper, the Tabu search algorithm is used to solve a transportation problem which consists of determining the shortest routes with the appropriate vehicle capacity to facilitate the travel of the students attending the University of Mauritius. The aim of this work is to minimize the total cost of the distance travelled by the vehicles in serving all the customers. An initial solution is obtained by the TOUR algorithm which basically constructs a giant tour containing all the customers and partitions it in an optimal way so as to produce a set of feasible routes. The Tabu search algorithm then makes use of a search procedure, a swapping procedure and the intensification and diversification mechanism to find the best set of feasible routes.

Keywords: Tabu Search, Vehicle Routing, Transport.

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Authors: Robin Gremlich, Andreas Hamfelt, Héctor de Pereda, Vladislav Valkovsky

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By introducing the concept of Oracle we propose an approach for improving the performance of genetic algorithms for large-scale asymmetric Traveling Salesman Problems. The results have shown that the proposed approach allows overcoming some traditional problems for creating efficient genetic algorithms.

Keywords: Genetic algorithms, Traveling Salesman Problem, optimal decision distribution, oracle.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

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In this paper, we propose a novel fast search algorithm for short MPEG video clips from video database. This algorithm is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Instead of fully decompressed video frames, partially decoded data, namely DC images are utilized. Combined with active search [4], a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by 6 hours of video to search for given 200 MPEG video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and Equal Error Rate (ERR) of 3 % is achieved, which is more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, adjacent pixel intensity difference quantization (APIDQ), DC image, histogram feature.

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Authors: Mazhar B. Tayel, Amr H. Yassin

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A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.

Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.

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Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: Emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing.

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Authors: Hakim Akeb, Mhand Hifi

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In this paper, the use of beam search and look-ahead strategies for solving the strip packing problem (SPP) is investigated. Given a strip of fixed width W, unlimited length L, and a set of n circular pieces of known radii, the objective is to determine the minimum length of the initial strip that packs all the pieces. An augmented algorithm which combines beam search and a look-ahead strategies is proposed. The look-ahead is used in order to evaluate the nodes at each level of the tree search. The best nodes are then retained for branching. The computational investigation showed that the proposed augmented algorithm is able to improve the best known solutions of the literature on most instances used.

Keywords: Combinatorial optimization, cutting and packing, beam search, heuristic, look-ahead strategy.

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Authors: P.S.Prakash, S.Selvan

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QoS Routing aims to find paths between senders and receivers satisfying the QoS requirements of the application which efficiently using the network resources and underlying routing algorithm to be able to find low-cost paths that satisfy given QoS constraints. The problem of finding least-cost routing is known to be NP hard or complete and some algorithms have been proposed to find a near optimal solution. But these heuristics or algorithms either impose relationships among the link metrics to reduce the complexity of the problem which may limit the general applicability of the heuristic, or are too costly in terms of execution time to be applicable to large networks. In this paper, we analyzed two algorithms namely Characterized Delay Constrained Routing (CDCR) and Optimized Delay Constrained Routing (ODCR). The CDCR algorithm dealt an approach for delay constrained routing that captures the trade-off between cost minimization and risk level regarding the delay constraint. The ODCR which uses an adaptive path weight function together with an additional constraint imposed on the path cost, to restrict search space and hence ODCR finds near optimal solution in much quicker time.

Keywords: QoS, Delay, Routing, Optimization

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Authors: S. Dhahri, A. Zitouni, H. Chaouch, R. Tourki

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This paper presents an adaptive motion estimator that can be dynamically reconfigured by the best algorithm depending on the variation of the video nature during the lifetime of an application under running. The 4 Step Search (4SS) and the Gradient Search (GS) algorithms are integrated in the estimator in order to be used in the case of rapid and slow video sequences respectively. The Full Search Block Matching (FSBM) algorithm has been also integrated in order to be used in the case of the video sequences which are not real time oriented. In order to efficiently reduce the computational cost while achieving better visual quality with low cost power, the proposed motion estimator is based on a Variable Block Size (VBS) scheme that uses only the 16x16, 16x8, 8x16 and 8x8 modes. Experimental results show that the adaptive motion estimator allows better results in term of Peak Signal to Noise Ratio (PSNR), computational cost, FPGA occupied area, and dissipated power relatively to the most popular variable block size schemes presented in the literature.

Keywords: H264, Configurable Motion Estimator, VariableBlock Size, PSNR, Dissipated power.

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Authors: Fuzhang Zhao

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Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: Diversification search, intensification search, optimal weighting, particle swarm optimization.

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Authors: Adam Roman

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Finding synchronizing sequences for the finite automata is a very important problem in many practical applications (part orienters in industry, reset problem in biocomputing theory, network issues etc). Problem of finding the shortest synchronizing sequence is NP-hard, so polynomial algorithms probably can work only as heuristic ones. In this paper we propose two versions of polynomial algorithms which work better than well-known Eppstein-s Greedy and Cycle algorithms.

Keywords: Synchronizing words, reset sequences, Černý Conjecture

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, Multiobjective optimization, ZDT test functions, performance metrics.

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Authors: Manpreet Singh, Parvinder Singh Sandhu, Manjinder Singh Kahlon

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There are many classical algorithms for finding routing in FPGA. But Using DNA computing we can solve the routes efficiently and fast. The run time complexity of DNA algorithms is much less than other classical algorithms which are used for solving routing in FPGA. The research in DNA computing is in a primary level. High information density of DNA molecules and massive parallelism involved in the DNA reactions make DNA computing a powerful tool. It has been proved by many research accomplishments that any procedure that can be programmed in a silicon computer can be realized as a DNA computing procedure. In this paper we have proposed two tier approaches for the FPGA routing solution. First, geometric FPGA detailed routing task is solved by transforming it into a Boolean satisfiability equation with the property that any assignment of input variables that satisfies the equation specifies a valid routing. Satisfying assignment for particular route will result in a valid routing and absence of a satisfying assignment implies that the layout is un-routable. In second step, DNA search algorithm is applied on this Boolean equation for solving routing alternatives utilizing the properties of DNA computation. The simulated results are satisfactory and give the indication of applicability of DNA computing for solving the FPGA Routing problem.

Keywords: FPGA, Routing, DNA Computing.

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Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

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In this paper, we propose an improved fast search algorithm using combined histogram features and temporal division method for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal feature which is robust to color distortion. Combined with active search [4], a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by 6 hours of video to search for given 200 MPEG video clips which each length is 30 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 120ms, and Equal Error Rate (ERR) of 1% is achieved, which is more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Adjacent pixel intensity differencequantization (APIDQ), DC image, Histogram feature.

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Authors: Meng-Hui Chen, Chiao-Wei Yu, Pei-Chann Chang

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Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist. The main idea in this paper is using the peculiarity of ICA to explore the search space to solve the kinds of combinational problems. Otherwise, we also study to use the greed search to increase the local search ability. To verify the proposed algorithm in this paper, the experimental results of traveling salesman problem (TSP) is according to the traveling salesman problem library (TSPLIB). The results show that the proposed algorithm has higher performance than the other known methods.

Keywords: Traveling Salesman Problem, Artificial Chromosomes, Greedy Search, Imperial Competitive Algorithm.

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Authors: Mohammad Reza Karami Nejad

Abstract:

A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.

Keywords: Routing, Quality of Service, Multicaset, Learning Automata, Genetic, Next Generation Networks.

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Authors: Samia Dardouri, Ridha Bouallegue

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Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, Multimedia flows, Scheduling algorithms.

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Authors: Jürgen Dorn, Tabbasum Naz

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In the area of Human Resource Management, the trend is towards online exchange of information about human resources. For example, online applications for employment become standard and job offerings are posted in many job portals. However, there are too many job portals to monitor all of them if someone is interested in a new job. We developed a prototype for integrating information of different job portals into one meta-search engine. First, existing job portals were investigated and XML schema documents were derived automated from these portals. Second, translation rules for transforming each schema to a central HR-XML-conform schema were determined. The HR-XML-schema is used to build a form for searching jobs. The data supplied by a user in this form is now translated into queries for the different job portals. Each result obtained by a job portal is sent to the meta-search engine that ranks the result of all received job offers according to user's preferences.

Keywords: Meta-search, Information extraction and integration, human resource management, job search.

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Authors: Y. Harold Robinson, E. Golden Julie, P. Joyce Beryl Princess

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Image segmentation is the concept of splitting the images into several images. Image Segmentation algorithm is used to manipulate the process of image segmentation. The advantage of ABC is that it conducts every worldwide exploration and inhabitant exploration for iteration. Particle Swarm Optimization (PSO) and Evolutionary Particle Swarm Optimization (EPSO) encompass a number of search problems. Cleverness Artificial Bee Colony algorithm has been imposed to increase the performance of a neighborhood search. The simulation results clearly show that the presented ABC methods outperform the existing methods. The result shows that the algorithms can be used to implement the manipulator for grasping of colored objects. The efficiency of the presented method is improved a lot by comparing to other methods.

Keywords: Color information, EPSO, ABC, image segmentation, particle swarm optimization, active contour, GMM.

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Authors: Sushma Satpute, Vaishali Katkar, Nilesh Sahare

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XML files contain data which is in well formatted manner. By studying the format or semantics of the grammar it will be helpful for fast retrieval of the data. There are many algorithms which describes about searching the data from XML files. There are no. of approaches which uses data structure or are related to the contents of the document. In these cases user must know about the structure of the document and information retrieval techniques using NLPs is related to content of the document. Hence the result may be irrelevant or not so successful and may take more time to search.. This paper presents fast XML retrieval techniques by using new indexing technique and the concept of RXML. When indexing an XML document, the system takes into account both the document content and the document structure and assigns the value to each tag from file. To query the system, a user is not constrained about fixed format of query.

Keywords: XML Retrieval, Indexed Search, Information Retrieval.

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Authors: J. Cheeneebash, K. B. Lallmamode, A. Gopaul

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Throughout this paper, a relatively new technique, the Tabu search variable selection model, is elaborated showing how it can be efficiently applied within the financial world whenever researchers come across the selection of a subset of variables from a whole set of descriptive variables under analysis. In the field of financial prediction, researchers often have to select a subset of variables from a larger set to solve different type of problems such as corporate bankruptcy prediction, personal bankruptcy prediction, mortgage, credit scoring and the Arbitrage Pricing Model (APM). Consequently, to demonstrate how the method operates and to illustrate its usefulness as well as its superiority compared to other commonly used methods, the Tabu search algorithm for variable selection is compared to two main alternative search procedures namely, the stepwise regression and the maximum R 2 improvement method. The Tabu search is then implemented in finance; where it attempts to predict corporate bankruptcy by selecting the most appropriate financial ratios and thus creating its own prediction score equation. In comparison to other methods, mostly the Altman Z-Score model, the Tabu search model produces a higher success rate in predicting correctly the failure of firms or the continuous running of existing entities.

Keywords: Predicting Bankruptcy, Tabu Search

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Authors: Tibor Kulcsar, Gabor Sarossy, Gabor Bereznai, Robert Auer, Janos Abonyi

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On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.

Keywords: indexing high dimensional databases, dimensional reduction, clustering, similarity, k-nn algorithm.

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Authors: H. B. Kekre, Tanuja K. Sarode

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This paper presents a very simple and efficient algorithm for codebook search, which reduces a great deal of computation as compared to the full codebook search. The algorithm is based on sorting and centroid technique for search. The results table shows the effectiveness of the proposed algorithm in terms of computational complexity. In this paper we also introduce a new performance parameter named as Average fractional change in pixel value as we feel that it gives better understanding of the closeness of the image since it is related to the perception. This new performance parameter takes into consideration the average fractional change in each pixel value.

Keywords: Vector Quantization, Data Compression, Encoding, Searching.

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Authors: Mohammad Shams Esfand Abadi, Nader Hadizadeh Kashani, Vahid Mehrdad

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In this paper we present a general formalism for the establishment of the family of selective regressor affine projection algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA), the SR partial rank algorithm (SR-PRA), the SR binormalized data reusing least mean squares (SR-BNDR-LMS), and the SR normalized LMS with orthogonal correction factors (SR-NLMS-OCF) algorithms are established by this general formalism. We demonstrate the performance of the presented algorithms through simulations in acoustic echo cancellation scenario.

Keywords: Adaptive filter, affine projection, selective regressor.

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Authors: Suguru Ochiai, Toru Yabuki, Yoshiki Yamaguchi, Yuetsu Kodama

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In this paper, we propose a Connect6 solver which adopts a hybrid approach based on a tree-search algorithm and image processing techniques. The solver must deal with the complicated computation and provide high performance in order to make real-time decisions. The proposed approach enables the solver to be implemented on a single Spartan-6 XC6SLX45 FPGA produced by XILINX without using any external devices. The compact implementation is achieved through image processing techniques to optimize a tree-search algorithm of the Connect6 game. The tree search is widely used in computer games and the optimal search brings the best move in every turn of a computer game. Thus, many tree-search algorithms such as Minimax algorithm and artificial intelligence approaches have been widely proposed in this field. However, there is one fundamental problem in this area; the computation time increases rapidly in response to the growth of the game tree. It means the larger the game tree is, the bigger the circuit size is because of their highly parallel computation characteristics. Here, this paper aims to reduce the size of a Connect6 game tree using image processing techniques and its position symmetric property. The proposed solver is composed of four computational modules: a two-dimensional checkmate strategy checker, a template matching module, a skilful-line predictor, and a next-move selector. These modules work well together in selecting next moves from some candidates and the total amount of their circuits is small. The details of the hardware design for an FPGA implementation are described and the performance of this design is also shown in this paper.

Keywords: Connect6, pattern matching, game-tree reduction, hardware direct computation

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Authors: Hassan Zarei, Ali Vahidian Kamyad, Sohrab Effati

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In this paper, a mathematical model of human immunodeficiency virus (HIV) is utilized and an optimization problem is proposed, with the final goal of implementing an optimal 900-day structured treatment interruption (STI) protocol. Two type of commonly used drugs in highly active antiretroviral therapy (HAART), reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are considered. In order to solving the proposed optimization problem an adaptive memetic algorithm with population management (AMAPM) is proposed. The AMAPM uses a distance measure to control the diversity of population in genotype space and thus preventing the stagnation and premature convergence. Moreover, the AMAPM uses diversity parameter in phenotype space to dynamically set the population size and the number of crossovers during the search process. Three crossover operators diversify the population, simultaneously. The progresses of crossover operators are utilized to set the number of each crossover per generation. In order to escaping the local optima and introducing the new search directions toward the global optima, two local searchers assist the evolutionary process. In contrast to traditional memetic algorithms, the activation of these local searchers is not random and depends on both the diversity parameters in genotype space and phenotype space. The capability of AMAPM in finding optimal solutions compared with three popular metaheurestics is introduced.

Keywords: HIV therapy design, memetic algorithms, adaptivealgorithms, nonlinear integer programming.

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Authors: Muhammad Naeem, Syed Ismail Shah, Habibullah Jamal

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In this paper, a simple heuristic genetic algorithm is used for Multistage Multiuser detection in fast fading environments. Multipath channels, multiple access interference (MAI) and near far effect cause the performance of the conventional detector to degrade. Heuristic Genetic algorithms, a rapidly growing area of artificial intelligence, uses evolutionary programming for initial search, which not only helps to converge the solution towards near optimal performance efficiently but also at a very low complexity as compared with optimal detector. This holds true for Additive White Gaussian Noise (AWGN) and multipath fading channels. Experimental results are presented to show the superior performance of the proposed techque over the existing methods.

Keywords: Genetic Algorithm (GA), Multiple AccessInterference (MAI), Multistage Detectors (MSD), SuccessiveInterference Cancellation.

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Authors: H. Megherbi, A. C. Megherbi, N. Megherbi, K. Benmahamed

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This paper presents three-phase evolution search methodology to automatically design fuzzy logic controllers (FLCs) that can work in a wide range of operating conditions. These include varying load, parameter variations, and unknown external disturbances. The three-phase scheme consists of an exploration phase, an exploitation phase and a robustness phase. The first two phases search for FLC with high accuracy performances while the last phase aims at obtaining FLC providing the best compromise between the accuracy and robustness performances. Simulations were performed for direct-drive two-axis robot arm. The evolved FLC with the proposed design technique found to provide a very satisfactory performance under the wide range of operation conditions and to overcome problem associated with coupling and nonlinearities characteristics inherent to robot arms.

Keywords: Fuzzy logic control, evolutionary algorithms, robustness, exploration/exploitation phase.

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Authors: Seongsoo Lee

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Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: Motion estimation, test zone search, high efficiency video coding, processing element, optimization.

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Authors: Farshad Ghassemi Toosi, Nikola S. Nikolov

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We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Keywords: Radial Tree Drawing, Real-Time Visualization, Angular Coordinates, Large Trees.

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Authors: V. K. Banga, R. Kumar, Y. Singh

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In this paper, we present optimal control for movement and trajectory planning for four degrees-of-freedom robot using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs) for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like; Movement, Friction and Settling Time in robotic arm movement have been compensated using Fuzzy logic and Genetic Algorithms. The development of a fuzzy genetic optimization algorithm is presented and discussed. The result are compared only GA and Fuzzy GA. This paper describes genetic algorithms, which is designed to optimize robot movement and trajectory. Though the model represents is a general model for redundant structures and could represent any n-link structures. The result is a complete trajectory planning with Fuzzy logic and Genetic algorithms demonstrating the flexibility of this technique of artificial intelligence.

Keywords: Inverse kinematics, Genetic algorithms (GAs), Fuzzy logic (FL), Trajectory planning.

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