Latest Articles from JUCS - Journal of Universal Computer Science Latest 75 Articles from JUCS - Journal of Universal Computer Science https://lib.jucs.org/ Fri, 29 Mar 2024 10:48:23 +0200 Pensoft FeedCreator https://lib.jucs.org/i/logo.jpg Latest Articles from JUCS - Journal of Universal Computer Science https://lib.jucs.org/ Towards a Traceable Data Model Accommodating Bounded Uncertainty for DST Based Computation of BRCA1/2 Mutation Probability With Age https://lib.jucs.org/article/112797/ JUCS - Journal of Universal Computer Science 29(11): 1361-1384

DOI: 10.3897/jucs.112797

Authors: Lorenz Gillner, Ekaterina Auer

Abstract: In this paper, we describe the requirements for traceable open-source data retrieval in the context of computation of BRCA1/2 mutation probabilities (mutations in two tumor-suppressor genes responsible for hereditary BReast or/and ovarian CAncer). We show how such data can be used to develop a Dempster-Shafer model for computing the probability of BRCA1/2 mutations enhanced by taking into account the actual age of a patient or a family member in an appropriate way even if it is not known exactly. The model is compared with PENN II and BOADICEA (based on undisclosed data), two established platforms for this purpose accessible online, as well as with our own previous models. A proof-of-concept implementation shows that set-based techniques are able to provide better information about mutation probabilities, simultaneously highlighting the necessity for ground truth data of high quality.

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Research Article Tue, 28 Nov 2023 18:00:07 +0200
When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting https://lib.jucs.org/article/69619/ JUCS - Journal of Universal Computer Science 28(2): 181-201

DOI: 10.3897/jucs.69619

Authors: Vít Novotný, Michal Štefánik, Eniafe Festus Ayetiran, Petr Sojka, Radim Řehůřek

Abstract: In 2018, Mikolov et al. introduced the positional language model, which has characteristics of attention-based neural machine translation models and which achieved state-of-the-art performance on the intrinsic word analogy task. However, the positional model is not practically fast and it has never been evaluated on qualitative criteria or extrinsic tasks. We propose a constrained positional model, which adapts the sparse attention mechanism from neural machine translation to improve the speed of the positional model. We evaluate the positional and constrained positional models on three novel qualitative criteria and on language modeling. We show that the positional and constrained positional models contain interpretable information about the grammatical properties of words and outperform other shallow models on language modeling. We also show that our constrained model outperforms the positional model on language modeling and trains twice as fast.

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Research Article Mon, 28 Feb 2022 11:00:00 +0200
BSO-MV: An Optimized Multiview Clustering Approach for Items Recommendation in Social Networks https://lib.jucs.org/article/70341/ JUCS - Journal of Universal Computer Science 27(7): 667-692

DOI: 10.3897/jucs.70341

Authors: Lamia Berkani, Lylia Betit, Louiza Belarif

Abstract: Clustering-based approaches have been demonstrated to be efficient and scalable to large-scale data sets. However, clustering-based recommender systems suffer from relatively low accuracy and coverage. To address these issues, we propose in this article an optimized multiview clustering approach for the recommendation of items in social networks. First, the selection of the initial medoids is optimized using the Bees Swarm optimization algorithm (BSO) in order to generate better partitions (i.e. refining the quality of medoids according to the objective function). Then, the multiview clustering (MV) is applied, where users are iteratively clustered from the views of both rating patterns and social information (i.e. friendships and trust). Finally, a framework is proposed for testing the different alternatives, namely: (1) the standard recommendation algorithms; (2) the clustering-based and the optimized clustering-based recommendation algorithms using BSO; and (3) the MV and the optimized MV (BSO-MV) algorithms. Experimental results conducted on two real-world datasets demonstrate the effectiveness of the proposed BSO-MV algorithm in terms of improving accuracy, as it outperforms the existing related approaches and baselines.

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Research Article Wed, 28 Jul 2021 10:00:00 +0300
Interval Methods for Fixed and Periodic Points: Development and Visualization https://lib.jucs.org/article/24126/ JUCS - Journal of Universal Computer Science 26(10): 1312-1330

DOI: 10.3897/jucs.2020.068

Authors: José Eduardo de Almeida Ayres, Luiz Henrique de Figueiredo

Abstract: We describe the development of rigorous numerical methods based on interval analysis for finding all fixed points of a map and all attracting periodic points of a complex polynomial. We also discuss their performance with instructive visualizations.

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Research Article Wed, 28 Oct 2020 00:00:00 +0200
Numerical Treatment of a Data Completion Problem in Heat Conduction Modelling https://lib.jucs.org/article/24112/ JUCS - Journal of Universal Computer Science 26(9): 1177-1188

DOI: 10.3897/jucs.2020.061

Authors: Augusto C. de Castro Barbosa, Carlos De Moura, Jhoab De Negreiros, J. Mesquita de Souza Aguiar

Abstract: This work deals with a question in the mathematical modelling for the temperature evolution in a bar, for a long time linked as an inverse problem. The onedimensional model is the parabolic partial differential equation ut = α uxx, known as the heat diffusion equation. The classic direct problem (DP) involves this equation coupled to a set of constraints: initial and boundary conditions, in such a way as to guarantee existence of a unique solution. The data completion (DC) problem hereby considered may be described as follows: the temperature at one of the bar extreme points is unknown but there is a fixed interior point where it may be measured, for all time. Finite difference algorithms (FDA) were tested to approximate the solution for such a problem. The important point to be emphasized is that FDA may show up distinct performances when applied to either DP or DC, which is due to the way the discrete variables follow up the mesh steps - advancing in time, for the first case, on the space direction, for the other.

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Research Article Mon, 28 Sep 2020 00:00:00 +0300
IoT Heating Solution for Smart Home with Fuzzy Control https://lib.jucs.org/article/24084/ JUCS - Journal of Universal Computer Science 26(6): 747-761

DOI: 10.3897/jucs.2020.040

Authors: Łukasz Apiecionek, Jacek Czerniak, Dawid Ewald, Mateusz Biedziak

Abstract: There is currently an era of Internet of Things in the computer systems, which consists in connecting all possible devices to the Internet in order to provide them with new functionalities and thus { to improve the user's life standard. One of such solutions could be Smart Home. The possibility of monitoring inner environment is required for such solutions. Such monitoring provides potential for e.g. better heating control. The authors of this paper propose some heating control method with Fuzzy Logic. The proposed method was tested in a special climate chamber. The authors provided conclusions at the end of the paper.

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Research Article Sun, 28 Jun 2020 00:00:00 +0300
Ant-Set: A Subset-Oriented Ant Colony Optimization Algorithm for the Set Covering Problem https://lib.jucs.org/article/24001/ JUCS - Journal of Universal Computer Science 26(2): 293-316

DOI: 10.3897/jucs.2020.016

Authors: Murilo Falleiros Lemos Schmitt, Mauro Mulati, Ademir Constantino, Fábio Hernandes, Tony Hild

Abstract: This paper proposes an algorithm for the set covering problem based on the metaheuristic Ant Colony Optimization (ACO) called Ant-Set, which uses a lineoriented approach and a novelty pheromone manipulation based on the connections between components of the construction graph, while also applying a local search. The algorithm is compared with other ACO-based approaches. The results obtained show the effectiveness of the algorithm and the impact of the pheromone manipulation.

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Research Article Fri, 28 Feb 2020 00:00:00 +0200
Trust Based Cluster Head Election of Secure Message Transmission in MANET Using Multi Secure Protocol with TDES https://lib.jucs.org/article/22655/ JUCS - Journal of Universal Computer Science 25(10): 1221-1239

DOI: 10.3217/jucs-025-10-1221

Authors: K. Shankar, Mohamed Elhoseny

Abstract: In wireless communication, Mobile Ad Hoc Network (MANET) consists of a number of mobile nodes which are communicated with each other without any base station. One of the security attacks in MANETs is Packet forwarding misbehaviour attack; this makes MANETs weak by showing message loss behavior. For securing message transmission in MANET, the work proposes Energy Efficient Clustering Protocol (EECP) with Radial Basis Function (RBF) based CH is elected for formed Clusters. Moreover, here some Network measures are considered to detect the malicious nodes and CH model that is speed, mobility, trust and so on. The trust value of the node is computed from the neighbor node which helps in further location to find a malicious node in the network to avail message drop and energy consumption (EC). After detecting malicious nodes, Multi secure Protocols that is Secure Efficient Distance Vector Routing (SEDV) and Secure Link State Routing Protocol (SLSP) with encryption technique used for message security. If the" HELLO" message sending by the sender, its encrypted and decrypted triples in receiver end to get the plain message, this technique is Triple Data Encryption Standard (TDES). Finally, the implementation results are evaluated to analyze the message security level of the proposed system in MANET in terms, of Packet to Delivery Ratio (PDR, Network Life Time (NLT) and some other important Measures.

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Research Article Mon, 28 Oct 2019 00:00:00 +0200
Ontology and Weighted D-S Evidence Theory-Based Vulnerability Data Fusion Method https://lib.jucs.org/article/22592/ JUCS - Journal of Universal Computer Science 25(3): 203-221

DOI: 10.3217/jucs-025-03-0203

Authors: Xiaoling Tao, Liyan Liu, Feng Zhao, Yan Huang, Saide Zhu

Abstract: With the rapid development of high-speed and large-scale complex network, network vulnerability data presents the characteristics of massive, multi-source and heterogeneous, which makes data fusion become more complex. Although existing data fusion methods can fuse multi-source data, they do not consider that the multisource data may affect the accuracy of fusion result. To solve this problem, we propose an ontology and weighted D-S evidence theory-based vulnerability data fusion method. In our method, we utilize ontology to describe the network vulnerability semantically and construct the network vulnerability ontology hierarchically. Then we use weighted D-S evidence theory to perform the operation of probability distribution and fusion processing. Besides, we simulate our method on MapReduce parallel computing platform. The experiment results show that our method is more effective and accurate compared with existing fusion approaches using single detection tool and traditional D-S evidence theory.

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Research Article Thu, 28 Mar 2019 00:00:00 +0200
Machine Learning Optimization of Parameters for Noise Estimation https://lib.jucs.org/article/23537/ JUCS - Journal of Universal Computer Science 24(9): 1271-1281

DOI: 10.3217/jucs-024-09-1271

Authors: Yuyong Jeon, Ilkyeun Ra, Youngjin Park, Sangmin Lee

Abstract: In this paper, a fast and effective method of parameter optimization for noise estimation is proposed for various types of noise. The proposed method is based on gradient descent, which is one of the optimization methods used in machine learning. The learning rate of gradient descent was set to a negative value for optimizing parameters for a speech quality improvement problem. The speech quality was evaluated using a suite of measures. After parameter optimization by gradient descent, the values were re-checked using a wider range to prevent convergence to a local minimum. To optimize the problem's five parameters, the overall number of operations using the proposed method was 99.99958% smaller than that using the conventional method. The extracted optimal values increased the speech quality by 1.1307%, 3.097%, 3.742%, and 3.861% on average for signal-to-noise ratios of 0, 5, 10, and 15 dB, respectively.

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Research Article Fri, 28 Sep 2018 00:00:00 +0300
Cancer Classification by Gene Subset Selection from Microarray Dataset https://lib.jucs.org/article/23292/ JUCS - Journal of Universal Computer Science 24(6): 682-710

DOI: 10.3217/jucs-024-06-0682

Authors: Asit Das, Soumen Pati, Hsien-Hung Huang, Chi-Ken Chen

Abstract: Microarray dataset contains huge number of genes, many of which are irrelevant regarding cancer classification and as a result classification accuracy is reduced. Therefore, the dataset should be pre-processed to filter out these redundant genes. In this paper, initially a Pareto optimality based Multi-objective Genetic Algorithm has been proposed where non-linear cellular automata is employed to overcome the demerits of random initialization to generate initial population in high dimensional space. The fitness functions are defined based on both attribute dependency and boundary region exploration of rough set theory and Log-Likelihood ratio to select the informative genes. The chromosomes are hybridized by applying multi-point crossover; whereas proximity mutation builds on Flip-bit mutation with a little modification to produce fittest offspring. Finally, the gene subset with strong biological significance in cancer treatment is obtained from the Pareto dominant solutions. Performances are investigated on publicly available microarray cancer datasets and compared with the state-of-the-art methods to demonstrate the effectiveness of the proposed method.

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Research Article Thu, 28 Jun 2018 00:00:00 +0300
Solving a Large Real-world Bus Driver Scheduling Problem with a Multi-assignment based Heuristic Algorithm https://lib.jucs.org/article/23215/ JUCS - Journal of Universal Computer Science 23(5): 479-504

DOI: 10.3217/jucs-023-05-0479

Authors: Ademir Constantino, Candido Ferreira Xavier De Mendonca Neto, Silvio De Araujo, Dario Landa-Silva, Rogério Calvi, Allainclair Flausino dos Santos

Abstract: The bus driver scheduling problem (BDSP) under study consists in finding a set of duties that covers the bus schedule from a Brazilian public transportation bus company with the objective of minimizing the total cost. A deterministic 2-phase heuristic algorithm is proposed using multiple assignment problems that arise from a model based on a weighted multipartite graph. In the first phase, the algorithm constructs an initial feasible solution by solving a number of assignment problems. In the second phase, the algorithm attempts to improve the solution by two different procedures. One procedure takes the whole set of duties and divides them in a set of partial duties which are recombined. The other procedure seeks to improve single long duties by eliminating the overtime time and inserting it into another duty. Computational tests are performed using large-scale real-world data with more than 2,300 tasks and random instances extracted from real data. Three different objective functions are analyzed. The overall results indicate that the proposed approach is competitive to solve large BDSP.

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Research Article Sun, 28 May 2017 00:00:00 +0300
A Steady-State Evolutionary Algorithm for Building Collaborative Learning Teams in Educational Environments Considering the Understanding Levels and Interest Levels of the Students https://lib.jucs.org/article/23587/ JUCS - Journal of Universal Computer Science 22(10): 1298-1318

DOI: 10.3217/jucs-022-10-1298

Authors: Virginia Yannibelli, Marcelo Armentano, Franco Berdun, Anala Amandi

Abstract: Collaborative learning team building is a fundamental, difficult and time-consuming task in educational environments. In this paper, we address a collaborative learning team building problem that considers two valuable grouping criteria usually considered by teachers. One of these criteria considers the understanding levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the understanding levels of their members. The other criterion considers the interest levels of the students with respect of the topics of a given course, and is based on building well-balanced teams in terms of the interest levels of their members. The problem addressed has been recognised as an NP-Hard optimization problem. To solve the problem, we propose a steady-state evolutionary algorithm. This algorithm aims to organize the students taking a given course into teams in such a way that the two grouping criteria of the problem are optimized. The performance of the algorithm is evaluated on nine problem instances with different levels of complexity, and is compared with that of the only algorithm previously proposed for solving the addressed problem. The obtained results show that the steady-state evolutionary algorithm significantly outperforms the previous algorithm.

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Research Article Sat, 1 Oct 2016 00:00:00 +0300
Improving Performance of the Differential Evolution Algorithm Using Cyclic Decloning and Changeable Population Size https://lib.jucs.org/article/23281/ JUCS - Journal of Universal Computer Science 22(6): 874-893

DOI: 10.3217/jucs-022-06-0874

Authors: Piotr Jędrzejowicz, Aleksander Skakovski

Abstract: Differential evolution (DE) is a stochastic global optimization method, that has been under continuous development during the past two decades. It has been recognized that preserving the diversification of population can significantly improve the performance of DE. Although, several results and approaches to population diversification have been proposed, it seems that this issue still has a potential for development. In this paper we have studied experimentally the possibility of increasing the performance of DE. Our investigation aims at identifying how the performance of DE depends on such factors as population diversity, size and number of fitness function evaluations carried out by DE to yield a solution. In our experiments we diversified the population in an intensive manner using the proposed decloning procedure carried out in cycles, and also through increasing the population size. The choice of how to preserve the diversification may depend on restrictions imposed on the population size, response time, and the quality of solutions that should be met by a specific implementation of the algorithm. The obtained results allowed us to propose a performance improvement policy that might noteworthy improve both the efficacy and response time of the algorithm. The discrete-continuous scheduling with continuous resource discretisation was used as the test problem.

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Research Article Wed, 1 Jun 2016 00:00:00 +0300
Heuristic Algorithms for Manufacturing and Replacement Strategies of the Production System https://lib.jucs.org/article/23110/ JUCS - Journal of Universal Computer Science 21(4): 503-525

DOI: 10.3217/jucs-021-04-0503

Authors: Robert Bucki, Bronislav Chramcov, Petr Suchánek

Abstract: The paper highlights the problem of minimizing economic costs of making orders in the automated manufacturing system which consists of work centres arranged in a series. Each of them is equipped with tools which carry out defined manufacturing operations. Tools are replaced with new ones only when no manufacturing operation can be performed any more in order to minimize the residual pass. The equations of state of the production line are presented and heuristic control strategies are discussed in detail. The criterion is to minimize the number of replacement procedures which results in maximizing the use of tools in work centres. To prove the correctness of the presented approach the paper is supported with an extended simulation study based on implementing available combinations of either manufacturing or replacement strategies taking into account various configurations which come into being in the real manufacturing environment. The simulation results form the basis for the detailed analysis to meet the requirements of the applicable decision-making procedures.

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Research Article Wed, 1 Apr 2015 00:00:00 +0300
Maximum Capacity Overlapping Channel Assignment Based on Max-Cut in 802.11 Wireless Mesh Networks https://lib.jucs.org/article/23822/ JUCS - Journal of Universal Computer Science 20(13): 1855-1874

DOI: 10.3217/jucs-020-13-1855

Authors: Ming Yang, Bo Liu, Wei Wang, Junzhou Luo, Xiaojun Shen

Abstract: By exploiting multi-radio multi-channel technology, wireless mesh networks can effectively provide wireless broadband access to the Internet for mobile users. Due to the limited number of orthogonal channels, overlapping channel assignment is one of the main factors that greatly affect the network capacity. However, current results in this area are not so satisfying. In this paper, we first propose a model for measuring achieved network capacity in MR-WMNs. Then we prove that finding an optimal overlapping channel assignment in a given MR-WMN with odd number of channels, is equivalent to finding an optimal assignment by only using its orthogonal channels. This theory allows us to use fewer channels to solve complicated channel assignment problems. Third, we prove that in 802.11b/g MR-WMN the simplified optimization problem is a Max-3-Cut problem. Although this problem is NP-hard, it has an efficient approximation algorithm that achieves approximation ratio of 1.19616 probabilistically by using the algorithm for Max-Cut whose approximation ratio is 1.1383 probabilistically. Based on the algorithm for Max-Cut, this paper proposes Max-Cut based channel assignment (MCCA) which uses a heuristic method to adjust the result produced by the Max-Cut algorithm to achieve an even better result. Finally, we perform extensive simulations to compare the MCCA with a state-of-the-art Tabu-Search based algorithm. The results show that the Max-Cut based overlapping channel assignment algorithm effectively and efficiently improves on the network capacity compared with existing algorithms.

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Research Article Fri, 28 Nov 2014 00:00:00 +0200
Multiplication and Squaring with Shifting Primes on OpenRISC Processors with Hardware Multiplier https://lib.jucs.org/article/23923/ JUCS - Journal of Universal Computer Science 19(16): 2368-2384

DOI: 10.3217/jucs-019-16-2368

Authors: Leandro Marin, Antonio Jara, Antonio Skarmeta

Abstract: Cryptographic primitives are the key component in the security protocols to support the authentication, key management and secure communication establishment. For that reason, this work presents the optimization of the Elliptic Curve Cryptography through the usage of Shifting Primes for constrained devices. Specifically, this presents the optimization for the chipsets JN51XX from NXP/Jennic, which are based on OpenRISC architecture and offer a class-2 constrained device. In details, Shifting Primes features have allowed to optimize the multiplication and squaring through a double accumulator and shifting reduction. This work is ancillary to the previous works about optimization of Shifting Primes for class-1 constrained devices. The optimization of the Elliptic Curve Cryptography for the class-2 constrained devices brings several opportunities for realistic scenarios, where the security interoperability between a gateway (class-2 device) and end-nodes (class 1 devices) is a major requirement.

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Research Article Tue, 1 Oct 2013 00:00:00 +0300
A Hybrid Metaheuristic Strategy for Covering with Wireless Devices https://lib.jucs.org/article/23842/ JUCS - Journal of Universal Computer Science 18(14): 1906-1932

DOI: 10.3217/jucs-018-14-1906

Authors: Antonio Bajuelos, Santiago Canales, Gregorio Hernández, Mafalda Martins

Abstract: In this paper we focus on approximate solutions to solve a new class of Art Gallery Problems inspired by wireless localization. Instead of the usual guards we consider wireless devices whose signal can cross a certain number, k, of walls. These devices are called k-transmitters. We propose an algorithm for constructing the visibility region of a k-transmitter located on a point of a simple polygon. Then we apply a hybrid metaheuristic strategy to tackle the problem of minimizing the number of k-transmitters, located at vertices, that cover a given simple polygon, and compare its performance with two pure metaheuristics. We conclude that the approximate solutions obtained with the hybrid strategy, for 2-transmitters and 4-transmitters, on simple polygons, monotone polygons, orthogonal polygons and monotone orthogonal polygons, are better than the solutions obtained with the pure strategies.

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Research Article Sat, 28 Jul 2012 00:00:00 +0300
Two Local Search Strategies for Differential Evolution https://lib.jucs.org/article/23799/ JUCS - Journal of Universal Computer Science 18(13): 1853-1870

DOI: 10.3217/jucs-018-13-1853

Authors: Musrrat Ali, Millie Pant, Atulya Nagar, Chang Ahn

Abstract: Insertion of a local search technique is often considered an effective mechanism to increase the efficiency of a global optimization algorithm. In this paper we propose and analyze the effect of two local searches namely; Trigonometric Local Search (TLS) and Interpolated Local Search (ILS) on the working of basic Differential Evolution (DE). The corresponding algorithms are named as DETLS and DEILS. The performances of proposed algorithms are investigated and compared with basic DE, modified versions of DE and some other evolutionary algorithms. It is found that the proposed schemes improve the performance of DE in terms of quality of solution without compromising with the convergence rate.

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Research Article Sun, 1 Jul 2012 00:00:00 +0300
Solving Economic Dispatch Problems with Valve-point Effects using Particle Swarm Optimization https://lib.jucs.org/article/23798/ JUCS - Journal of Universal Computer Science 18(13): 1842-1852

DOI: 10.3217/jucs-018-13-1842

Authors: Kusum Deep, Jagdish Bansal

Abstract: Particle Swarm Optimization (PSO) is a swarm intelligence optimization method inspired from birds' flocking or fish schooling. Many improved versions of PSO are reported in literature, including some by the authors. Original as well as improved versions of PSO have proven their applicability to various fields like science, engineering and industries. Economic dispatch (ED) problem is one of the fundamental issues in power system operations. This problem turns out to be a non linear continuous optimization problem. In this paper, economic dispatch problem is solved using original PSO and two of its improved variants, namely, Laplace Crossover PSO (LXPSO) and Quadratic Approximation PSO (qPSO), in order to find better results than reported in the literature. Results are also compared with the earlier published results.

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Research Article Sun, 1 Jul 2012 00:00:00 +0300
Modeling and Performance Evaluation of a Contract-based Electronic Signature Process https://lib.jucs.org/article/23168/ JUCS - Journal of Universal Computer Science 18(5): 676-703

DOI: 10.3217/jucs-018-05-0676

Authors: Ahmed Nait-Sidi-Moh, Mohamed Bakhouya, Wafaa Ait-Cheik-Bihi, Jaafar Gaber

Abstract: Distributed systems become ubiquitous by allowing users access to a wide range of services at any time, anywhere, and from a variety of devices. In these open environments where there are many opportunities for both fraudulent services and misbehaving clients, service discovery systems are subject to security challenges. Controlling services' access is one of the fundamental issues that must be faced in the context of service discovery in distributed and open environments. Therefore, secure accesses and utilization of available services must be ensured for users. In our previous work, a contract-based approach for controlling the service access in a distributed computing context was presented. In this paper, we address the purpose and the usage of digital signature on negotiated electronic queries between a server and clients in service discovery systems and web service composition. The paper discusses the combined use of Timed Event Graphs and (max, +)- algebra to model, evaluate and optimize the performance of the signature process and client requests validation by a service provider (server). Based on an optimization resource allocation algorithm, an improvement study of the quality of service offered to the clients, in terms of waiting times and validation of their requests, is proposed. The results are reported and show the efficiency of the use of the proposed formal tools for performance analysis, evaluation and tuning of the considered process.

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Research Article Thu, 1 Mar 2012 00:00:00 +0200
Optimization of Gateway Deployment with Load Balancing and Interference Minimization in Wireless Mesh Networks https://lib.jucs.org/article/30039/ JUCS - Journal of Universal Computer Science 17(14): 2064-2083

DOI: 10.3217/jucs-017-14-2064

Authors: Junzhou Luo, Wenjia Wu, Ming Yang

Abstract: In a wireless mesh network (WMN), gateways act as the bridges between the mesh backbone and the Internet, and significantly affect the performance of the whole network. Hence, how to determine the optimal number and positions of gateways, i.e., gateway deployment, is one of the most important and challenging topics in practical and theoretical research on designing a WMN. Although several approaches have been proposed to address this problem, few of them take load balancing and interference minimization into account. In this paper, we study the Load-balancing and Interference-minimization Gateway Deployment Problem (LIGDP), which aims to achieve four objectives, i.e. minimizing deployment cost, minimizing MR-GW path length, balancing gateway load and minimizing link interference. We formulate it as a multi-objective integer linear program (ILP) issue first, and then propose an efficient gateway deployment approach, called LIGDP Heuristic. The approach joints two heuristic algorithms, i.e., MSC-based location algorithm (MLA) and load-aware and interference-aware association algorithm (LIAA), to determine gateway positions and construct GW-rooted trees. Simulation results not only show that the trade-off between deployment cost and network performance can be achieved by adjusting R-hop, GW throughput and MR throughput constraints, but also demonstrate that, compared with other existing approaches, LIGDP Heuristic performs better on MR-GW path, load balancing and interference minimization without deploying more gateways.

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Research Article Sat, 1 Oct 2011 00:00:00 +0300
An Adaptive Genetic Algorithm and Application in a Luggage Design Center https://lib.jucs.org/article/30038/ JUCS - Journal of Universal Computer Science 17(14): 2048-2063

DOI: 10.3217/jucs-017-14-2048

Authors: Chen-Fang Tsai, Weidong Li, Anne James

Abstract: This paper presents a new methodology for improving the efficiency and generality of Genetic Algorithms (GA). The methodology provides the novel function of adaptive parameter adjustment during each evolution generation of GA. The important characteristics of the methodology are mainly from the following two aspects: (1) superior performance members in GA are preserved and inferior performance members are deteriorated to enhance search efficiency towards optimal solutions; (2) adaptive crossover and mutation management is applied in GA based on the transformation functions to explore wider spaces so as to improve search effectiveness and algorithm robustness. The research was successfully applied for a luggage design chain to generate optimal solutions (minimized lifecycle cost). Experiments were conducted to compare the work with the prior art to demonstrate the characteristics and advantages of the research.

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Research Article Sat, 1 Oct 2011 00:00:00 +0300
Coordinated System for Real Time Muscle Deformation during Locomotion https://lib.jucs.org/article/29899/ JUCS - Journal of Universal Computer Science 17(3): 349-376

DOI: 10.3217/jucs-017-03-0349

Authors: Sandra Baldassarri, Francisco Seron

Abstract: This paper presents a system that simulates, in real time, the volumetric deformation of muscles during human locomotion. We propose a two-layered motion model. The requirements of realism and real time computation lead to a hybrid locomotion system that uses a skeleton as first layer. The muscles, represented by an anatomical surface model, constitute the second layer, whose deformations are simulated with a finite element method (FEM). The FEM subsystem is fed by the torques and forces got from the locomotion system, through a line of action model, and takes into account the geometry and material properties of the muscles. High level parameters (like height, weight, physical constitution, step frequency, step length or speed) allow to customize the individuals and the locomotion and therefore, the deformation of the persons' muscles.

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Research Article Tue, 1 Feb 2011 00:00:00 +0200
Color Image Restoration Using Neural Network Model https://lib.jucs.org/article/29882/ JUCS - Journal of Universal Computer Science 17(1): 107-125

DOI: 10.3217/jucs-017-01-0107

Authors: Satyadhyan Chickerur, Aswatha M

Abstract: Neural network learning approach for color image restoration has been discussed in this paper and one of the possible solutions for restoring images has been presented. Here neural network weights are considered as regularization parameter values instead of explicitly specifying them. The weights are modified during the training through the supply of training set data. The desired response of the network is in the form of estimated value of the current pixel. This estimated value is used to modify the network weights such that the restored value produced by the network for a pixel is as close as to this desired response. One of the advantages of the proposed approach is that, once the neural network is trained, images can be restored without having prior information about the model of noise/blurring with which the image is corrupted.

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Research Article Sat, 1 Jan 2011 00:00:00 +0200
From Computing Sets of Optima, Pareto Sets, and Sets of Nash Equilibria to General Decision-Related Set Computations https://lib.jucs.org/article/29802/ JUCS - Journal of Universal Computer Science 16(18): 2657-2685

DOI: 10.3217/jucs-016-18-2657

Authors: Vladik Kreinovich, Bartlomiej Kubica

Abstract: Several algorithms have been proposed to compute sets of optima, Pareto sets, and sets of Nash equilibria. In this paper, we present a general algorithm for decision-related set computations that includes all these algorithms as particular cases. To make our algorithm understandable to people working in optimization and in game theory, we also provide motivations and explanations for our formalizations of the corresponding problems and for the related notions of computable mathematics.

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Research Article Tue, 28 Sep 2010 00:00:00 +0300
Compositional Semantics of Dataflow Networks with Query-Driven Communication of Exact Values https://lib.jucs.org/article/29801/ JUCS - Journal of Universal Computer Science 16(18): 2629-2656

DOI: 10.3217/jucs-016-18-2629

Authors: Michal Konečný, Amin Farjudian

Abstract: We develop and study the concept of dataflow process networks as used for exampleby Kahn to suit exact computation over data types related to real numbers, such as continuous functions and geometrical solids. Furthermore, we consider communicating these exact objectsamong processes using protocols of a query-answer nature as introduced in our earlier work. This enables processes to provide valid approximations with certain accuracy and focusing on certainlocality as demanded by the receiving processes through queries. We define domain-theoretical denotational semantics of our networks in two ways: (1) directly, i. e. by viewing the whole network as a composite process and applying the process semantics introduced in our earlier work; and (2) compositionally, i. e. by a fixed-point construction similarto that used by Kahn from the denotational semantics of individual processes in the network. The direct semantics closely corresponds to the operational semantics of the network (i. e. it iscorrect) but very difficult to study for concrete networks. The compositional semantics enablescompositional analysis of concrete networks, assuming it is correct. We prove that the compositional semantics is a safe approximation of the direct semantics. Wealso provide a method that can be used in many cases to establish that the two semantics fully coincide, i. e. safety is not achieved through inactivity or meaningless answers. The results are extended to cover recursively-defined infinite networks as well as nested finitenetworks. A robust prototype implementation of our model is available.

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Research Article Tue, 28 Sep 2010 00:00:00 +0300
Semantics of Query-Driven Communication of Exact Values https://lib.jucs.org/article/29800/ JUCS - Journal of Universal Computer Science 16(18): 2597-2628

DOI: 10.3217/jucs-016-18-2597

Authors: Michal Konečný, Amin Farjudian

Abstract: We address the question of how to communicate among distributed processes valuessuch as real numbers, continuous functions and geometrical solids with arbitrary precision, yet efficiently. We extend the established concept of lazy communication using streams of approximants by introducing explicit queries. We formalise this approach using protocols of a query-answer nature. Such protocols enable processes to provide valid approximations with certain accuracy and focusing on certain locality as demanded by the receiving processes through queries. A lattice-theoretic denotational semantics of channel and process behaviour is developed. Thequery space is modelled as a continuous lattice in which the top element denotes the query demanding all the information, whereas other elements denote queries demanding partial and/or local information. Answers are interpreted as elements of lattices constructed over suitable domains of approximations to the exact objects. An unanswered query is treated as an error anddenoted using the top element. The major novel characteristic of our semantic model is that it reflects the dependency of answerson queries. This enables the definition and analysis of an appropriate concept of convergence rate, by assigning an effort indicator to each query and a measure of information content to eachanswer. Thus we capture not only what function a process computes, but also how a process transforms the convergence rates from its inputs to its outputs. In future work these indicatorscan be used to capture further computational complexity measures. A robust prototype implementation of our model is available.

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Research Article Tue, 28 Sep 2010 00:00:00 +0300
A Heuristic Approach to Positive Root Isolation for Multiple Power Sums https://lib.jucs.org/article/29741/ JUCS - Journal of Universal Computer Science 16(14): 1912-1926

DOI: 10.3217/jucs-016-14-1912

Authors: Ming Xu, Chuandong Mu, Zhenbing Zeng, Zhi-bin Li

Abstract: Given a multiple power sum (extending polynomial's exponents to real numbers), the positive root isolation problem is to find a list of disjoint intervals, satisfying that they contain all positive roots and each of them contains exactly distinct one. In this paper, we develop the pseudo-derivative sequences for multiple power sums, then generalize Fourier's theorem and Descartes' sign rule for them to overestimate the number of their positive roots. Furthermore we bring up some formulas of linear and quadratic complexity to compute complex root bounds and positive root bounds based on Descartes' sign rule and Cauchy's theorem. Besides, we advance a factorization method for multiple power sums with rational coefficients utilizing Q-linear independence, thus reduce the computational complexity in the isolation process. Finally we present an efficient algorithm to isolate all positive roots under any given minimum root separation.

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Research Article Wed, 28 Jul 2010 00:00:00 +0300
Applying RFD to Construct Optimal Quality-Investment Trees https://lib.jucs.org/article/29736/ JUCS - Journal of Universal Computer Science 16(14): 1882-1901

DOI: 10.3217/jucs-016-14-1882

Authors: Pablo Rabanal, Ismael Rodriguez, Fernando Rubio

Abstract: River Formation Dynamics (RFD) is an evolutionary computation methodbased on copying how drops form rivers by eroding the ground and depositing sediments. Given a cost-evaluated graph, we apply RFD to find a way to connect a givenset of origins with a given destination in such a way that distances from origins to the destination are minimized (thus improving the quality of service) but costs to build theconnecting infrastructure are minimized (thus reducing investment expenses). After we prove the NP-completeness of this problem, we apply both RFD and an Ant ColonyOptimization (ACO) approach to heuristically solve it, and some experimental results are reported.

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Research Article Wed, 28 Jul 2010 00:00:00 +0300
Entropy Optimization of Social Networks Using an Evolutionary Algorithm https://lib.jucs.org/article/29656/ JUCS - Journal of Universal Computer Science 16(6): 983-1003

DOI: 10.3217/jucs-016-06-0983

Authors: Maytham Safar, Nosayba El-Sayed, Khaled Mahdi, David Taniar

Abstract: Recent work on social networks has tackled the measurement and optimization of these networks’ robustness and resilience to both failures and attacks. Different metrics have been used to quantitatively measure the robustness of a social network. In this work, we design and apply a Genetic Algorithm that maximizes the cyclic entropy of a social network model, hence optimizing its robustness to failures. Our social network model is a scale-free network created using Barabási and Albert's generative model, since it has been demonstrated recently that many large complex networks display a scale-free structure. We compare the cycles distribution of the optimally robust network generated by our algorithm to that belonging to a fully connected network. Moreover, we optimize the robustness of a scale-free network based on the links-degree entropy, and compare the outcomes to that which is based on cycles-entropy. We show that both cyclic and degree entropy optimization are equivalent and provide the same final optimal distribution. Hence, cyclic entropy optimization is justified in the search for the optimal network distribution.

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Research Article Sun, 28 Mar 2010 00:00:00 +0200
Newton Method for Nonlinear Dynamic Systems with Adaptive Time Stepping https://lib.jucs.org/article/29650/ JUCS - Journal of Universal Computer Science 16(6): 891-902

DOI: 10.3217/jucs-016-06-0891

Authors: Wensheng Shen, Changjiang Zhang, Jun Zhang, Xiaoqian Ma

Abstract: This paper presents a nonlinear solver based on the Newton-Krylov methods, where the Newton equations are solved by Krylov-subspace type approaches. We focus on the solution of unsteady systems, in which the temporal terms are discretized by the backward Euler method using finite difference. To save computational cost, an adaptive time stepping is used to minimize the number of time steps. The developed program can be applied to solve any nonlinear equations, provided the users could supply the discrete form of the equations. In particular, the nonlinear solver is implemented to solve unsteady reacting flows.

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Research Article Sun, 28 Mar 2010 00:00:00 +0200
A Comparison Between a Geometrical and an ANN Based Method for Retinal Bifurcation Points Extraction https://lib.jucs.org/article/29504/ JUCS - Journal of Universal Computer Science 15(13): 2608-2621

DOI: 10.3217/jucs-015-13-2608

Authors: Vitoantonio Bevilacqua, Lucia Cariello, Marco Giannini, Giuseppe Mastronardi, Vito Santarcangelo, Rocco Scaramuzzi, Antonella Troccoli

Abstract: This paper describes a comparative study between an Artificial Neural Network (ANN) and a geometric technique to detect for biometric applications,the bifurcation points of blood vessels in the retinal fundus. The first step is an image preprocessing phase to extract retina blood vessels. The contrast of the blood vessels from the retinal image background is enhanced in order to extract the blood vessels skeleton. Successively, candidate points of bifurcation are individualized by approximating the skeleton lines in segments. The distinction between bifurcations and vessel bends is carried out through the employment of two methods: geometric (through the study of intersections within the region obtained thresholding the image portion inside a circle centered around the junctions point and the circumference of the same circle) and an ANN. The results obtained are compared and discussed.

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Research Article Wed, 1 Jul 2009 00:00:00 +0300
Interactive Genetic Algorithms with Individual Fitness Not Assigned by Human https://lib.jucs.org/article/29492/ JUCS - Journal of Universal Computer Science 15(13): 2446-2462

DOI: 10.3217/jucs-015-13-2446

Authors: Dunwei Gong, Xin Yao, Jie Yuan

Abstract: Interactive genetic algorithms (IGAs) are effective methods to solve optimization problems with implicit or fuzzy indices. But human fatigue problem, resulting from evaluation on individuals and assignment of their fitness, is very important and hard to solve in IGAs. Aiming at solving the above problem, an interactive genetic algorithm with an individual fitness not assigned by human is proposed in this paper. Instead of assigning an individual fitness directly, we record time to choose an individual from a population as a satisfactory or unsatisfactory one according to sensitiveness to it, and its fitness is automatically calculated by a transformation from time space to fitness space. Then subsequent genetic operation is performed based on this fitness, and offspring is generated. We apply this algorithm to fashion design, and the experimental results validate its efficiency.

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Research Article Wed, 1 Jul 2009 00:00:00 +0300
Effective Computability of Solutions of Differential Inclusions The Ten Thousand Monkeys Approach https://lib.jucs.org/article/29379/ JUCS - Journal of Universal Computer Science 15(6): 1162-1185

DOI: 10.3217/jucs-015-06-1162

Authors: Pieter Collins, Daniel Graça

Abstract: In this paper we consider the computability of the solution of the initialvalue problem for differential equations and for differential inclusions with semicontinuous right-hand side. We present algorithms for the computation of the solution using the "ten thousand monkeys" approach, in which we generate all possible solution tubes, and then check which are valid. In this way, we show that the solution of a locally Lipschitz differential equation is computable even if the function is not effectively locally Lipschitz, and recover a result of Ruohonen, in which it is shown that if the solution is unique, then it is computable. We give an example of a computable locally Lipschitz function which is not effectively locally Lipschitz. We also show that the solutions of a convex-valued upper-semicontinuous differential inclusion are upper-semicomputable, and the solutions of a lower-semicontinuous one-sided Lipschitz differential inclusion are lower-semicomputable.

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Research Article Sat, 28 Mar 2009 00:00:00 +0200
Bayesian Gene Regulatory Network Inference Optimization by means of Genetic Algorithms https://lib.jucs.org/article/29344/ JUCS - Journal of Universal Computer Science 15(4): 826-839

DOI: 10.3217/jucs-015-04-0826

Authors: Vitoantonio Bevilacqua, Giuseppe Mastronardi, Filippo Menolascina, Paolo Pannarale, Giuseppe Romanazzi

Abstract: Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When time-course data is available, gene interactions may be modeled by a Bayesian Network (BN). Given a structure, that models the conditional independence between genes, we can tune the parameters in a way that maximize the likelihood of the observed data. The structure that best fit the observed data reflects the real gene network's connections. Well known learning algorithms (greedy search and simulated annealing) devoted to BN structure learning have been used in literature. We enhanced the fundamental step of structure learning by means of a classical evolutionary algorithm, named GA (Genetic algorithm), to evolve a set of candidate BN structures and found the model that best fits data, without prior knowledge of such structure. In the context of genetic algorithms, we proposed various initialization and evolutionary strategies suitable for the task. We tested our choices using simulated data drawn from a gene simulator, which has been used in the literature for benchmarking [Yu et al. (2002)]. We assessed the inferred models against this reference, calculating the performance indicators used for network reconstruction. The performances of the different evolutionary algorithms have been compared against the traditional search algorithms used so far (greedy search and simulated annealing). Finally we individuated as best candidate an evolutionary approach enhanced by Crossover-Two Point and Selection Roulette Wheel for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model of the simulated dataset. Finally we tested the GA approach on a real dataset where it reach 62% of recovered connections (sensitivity) and 64% of direct connections (precision), outperforming the other algorithms.

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Research Article Sat, 28 Feb 2009 00:00:00 +0200
PDE-PEDA: A New Pareto-Based Multi-objective Optimization Algorithm https://lib.jucs.org/article/29335/ JUCS - Journal of Universal Computer Science 15(4): 722-741

DOI: 10.3217/jucs-015-04-0722

Authors: Xuesong Wang, Minglin Hao, Yuhu Cheng, Ruhai Lei

Abstract: Differential evolution (DE) algorithm puts emphasis particularly on imitating the microscopic behavior of individuals, while estimation of distribution algorithm (EDA) tries to estimate the probabilistic distribution of the entire population. DE and EDA can be extended to multi-objective optimization problems by using a Pareto-based approach, called Pareto DE (PDE) and Pareto EDA (PEDA) respectively. In this study, we describe a novel combination of PDE and PEDA (PDE-PEDA) for multi-objective optimization problems by taking advantage of the global searching ability of PEDA and the local optimizing ability of PDE, which can, effectively, maintain the balance between exploration and exploitation. The basic idea is that the offspring population of PDE-PEDA is composed of two parts, one part of the trial solution generated originates from PDE and the other part is sampled in the search space from the constructed probabilistic distribution model of PEDA. A scaling factor Pr used to balance contributions of PDE and PEDA can be adjusted in an on-line manner using a simulated annealing method. At an early evolutionary stage, a larger Pr should be adopted to ensure PEDA is used more frequently, whereas at later stage, a smaller Pr should be adopted to ensure that offspring is generated more often using PDE. The hybrid algorithm is evaluated on a set of benchmark problems and the experimental results show that PDE-PEDA outperforms the NSGA-II and PDE algorithms.

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Research Article Sat, 28 Feb 2009 00:00:00 +0200
Linear and Quadratic Complexity Bounds on the Values of the Positive Roots of Polynomials https://lib.jucs.org/article/29322/ JUCS - Journal of Universal Computer Science 15(3): 523-537

DOI: 10.3217/jucs-015-03-0523

Authors: Alkiviadis Akritas

Abstract: In this paper we review the existing linear and quadratic complexity (upper) bounds on the values of the positive roots of polynomials and their impact on the performance of the Vincent-Akritas-Strzeboński (VAS) continued fractions method for the isolation of real roots of polynomials. We first present the following four linear complexity bounds (two "old" and two "new" ones, respectively): Cauchy's, (C), Kioustelidis', (K), First-Lambda, (FL) and Local-Max, (LM); we then state the quadratic complexity extensions of these four bounds, namely: CQ, KQ, FLQ, and LMQ — the second, (KQ), having being presented by Hong back in 1998. All eight bounds are derived from Theorem 5 below. The estimates computed by the quadratic complexity bounds are less than or equal to those computed by their linear complexity counterparts. Moreover, it turns out that VAS(lmq) — the VAS method implementing LMQ — is 40% faster than the original version VAS(cauchy).

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Research Article Sun, 1 Feb 2009 00:00:00 +0200
GADYM - A Novel Genetic Algorithm in Mechanical Design Problems https://lib.jucs.org/article/29169/ JUCS - Journal of Universal Computer Science 14(15): 2566-2581

DOI: 10.3217/jucs-014-15-2566

Authors: Khadiza Tahera, Raafat Ibrahim, Paul Lochert

Abstract: T his paper proposes a variant of genetic algorithm - GADYM, Genetic Algorithm with Gender-Age structure, DYnamic parameter tuning and Mandatory self perfection scheme. The motivation of this algorithm is to increase the diversity throughout the search procedure and to ease the difficulties associated with the tuning of GA parameters and operators. To promote diversity , GADYM combines the concept of gender and age in individuals of a traditional Genetic Algorithm and implements the self perfection scheme through sharing. To ease the parameter tuning process, the proposed algorithm uses dynamic environment in which heterogeneous crossover and selection techniques are used and parameters are updated based on deterministic rules. Thus, GADYM uses a combination of genetic operators and variable parameter values whereas a traditional GA uses fixed values of those. The experim ental results of the proposed algorithm based on a mechanical design problem show promising result.

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Research Article Fri, 1 Aug 2008 00:00:00 +0300
Optimal Sensor Network Layout Using Multi-Objective Metaheuristics https://lib.jucs.org/article/29168/ JUCS - Journal of Universal Computer Science 14(15): 2549-2565

DOI: 10.3217/jucs-014-15-2549

Authors: Guillermo Molina, Enrique Alba, El-Ghazali Talbi

Abstract: Wireless Sensor Networks (WSN) allow, thanks to the use of small wireless devices known as sensor nodes, the monitorization of wide and remote areas with precision and liveness unseen to the date without the intervention of a human operator. For many WSN applications it is fundamental to achieve full coverage of the terrain monitored, known as sensor field. The next major concerns are the energetic efficiency of the network, in order to increase its lifetime, and having the minimum possible number of sensor nodes, in order to reduce the network cost. The task of placing the sensor nodes while addressing these objectives is known as WSN layout problem. In this paper we address a WSN layout problem instance in which full coverage is treated as a constraint while the other two objectives are optimized using a multiobjective approach. We employ a set of multi-objective optimization algorithms for this problem where we define the energy efficiency and the number of nodes as the independent optimization objectives. Our results prove the efficiency of multi-objective metaheuristics to solve this kind of problem and encourage further research on more realistic instances and more constrained scenarios.

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Research Article Fri, 1 Aug 2008 00:00:00 +0300
A Novel Multi-Layer Level Set Method for Image Segmentation https://lib.jucs.org/article/29151/ JUCS - Journal of Universal Computer Science 14(14): 2428-2452

DOI: 10.3217/jucs-014-14-2427

Authors: Xiao-Feng Wang, De-Shuang Huang

Abstract: In this paper, a new multi-layer level set method is proposed for multi-phase image segmentation. The proposed method is based on the conception of image layer and improved numerical solution of bimodal Chan-Vese model. One level set function is employed for curve evolution with a hierarchical form in sequential image layers. In addition, new initialization method and more efficient computational method for signed distance function are introduced. Moreover, the evolving curve can automatically stop on true boundaries in single image layer according to a termination criterion which is based on the length change of evolving curve. Specially, an adaptive improvement scheme is designed to speed up curve evolution process in a queue of sequential image layers, and the detection of background image layer is used to confirm the termination of the whole multi-layer level set evolution procedure. Finally, numerical experiments on some synthetic and real images have demonstrated the efficiency and robustness of our method. And the comparisons with multi-phase Chan-Vese method also show that our method has a less time-consuming computation and much faster convergence.

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Research Article Mon, 28 Jul 2008 00:00:00 +0300
On the Relationship between Filter Spaces and Weak Limit Spaces https://lib.jucs.org/article/29018/ JUCS - Journal of Universal Computer Science 14(6): 996-1015

DOI: 10.3217/jucs-014-06-0996

Authors: Matthias Schröder

Abstract: Countably based filter spaces have been suggested in the 1970's as a model for recursion theory on higher types. Weak limit spaces with a countable base are known to be the class of spaces which can be handled by the Type-2 Model of Effectivity (TTE). We prove that the category of countably based proper filter spaces is equivalent to the category of countably based weak limit spaces. This result implies that filter spaces form yet another category from which the category of qcb-spaces inherits its cartesian closed structure. Moreover, we compare the aforementioned categories to other categories of spaces relevant to computability theory.

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Research Article Fri, 28 Mar 2008 00:00:00 +0200
The Bit-Complexity of Finding Nearly Optimal Quadrature Rules for Weighted Integration https://lib.jucs.org/article/29013/ JUCS - Journal of Universal Computer Science 14(6): 938-955

DOI: 10.3217/jucs-014-06-0938

Authors: Volker Bosserhoff

Abstract: Given a probability measure ν and a positive integer n. How to choose n knots and n weights such that the corresponding quadrature rule has the minimum worst-case error when applied to approximate the ν-integral of Lipschitz functions? This question has been considered by several authors. We study this question whithin the framework of Turing machine-based real computability and complexity theory as put forward by [Ko 1991] and others. After having defined the notion of a polynomialtime computable probability measure on the unit interval, we will show that there are measures of this type for which there is no computable optimal rule with two knots. We furthermore characterize - in terms of difficult open questions in discrete complexity theory - the complexity of computing rules whose worst-case error is arbitrarily close to optimal.

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Research Article Fri, 28 Mar 2008 00:00:00 +0200
Computability of Topological Pressure for Sofic Shifts with Applications in Statistical Physics https://lib.jucs.org/article/29009/ JUCS - Journal of Universal Computer Science 14(6): 876-895

DOI: 10.3217/jucs-014-06-0876

Authors: Christoph Spandl

Abstract: The topological pressure of dynamical systems theory is examined from a computability theoretic point of view. It is shown that for sofic shift dynamical systems, the topological pressure is a computable function. This result is applied to a certain class of one dimensional spin systems in statistical physics. As a consequence, the specific free energy of these spin systems is computable. Finally, phase transitions of these systems are considered. It turns out that the critical temperature is recursively approximable.

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Research Article Fri, 28 Mar 2008 00:00:00 +0200
On the Subrecursive Computability of Several Famous Constants https://lib.jucs.org/article/29008/ JUCS - Journal of Universal Computer Science 14(6): 861-875

DOI: 10.3217/jucs-014-06-0861

Authors: Dimiter Skordev

Abstract: For any class F of total functions in the set N of the natural numbers, we define the notion of F-computable real number. A real number α is called F-computable if there exist one-argument functions f, g and h in F such that for any n in N the distance between the rational number f(n) - g(n) over h(n) + 1 and the number α is not greater than the reciprocal of n + 1. Most concrete real numbers playing a role in analysis can be easily shown to be E3-computable (as usually, Em denotes the m-th Grzegorczyk class). Although (as it is proved in Section 5 of this paper) there exist E3-computable real numbers that are not E2-computable, we prove that π, e and other remarkable real numbers are E2-computable (the number π proves to be even L-computable, where L is the class of Skolem's lower elementary functions). However, only the rational numbers would turn out to be E2-computable according to a definition of F-computability using 2n instead of n + 1.

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Research Article Fri, 28 Mar 2008 00:00:00 +0200
Dynamic Bandwidth Pricing: Provision Cost, Market Size, Effective Bandwidths and Price Games https://lib.jucs.org/article/29003/ JUCS - Journal of Universal Computer Science 14(5): 766-785

DOI: 10.3217/jucs-014-05-0766

Authors: Sergios Soursos, Costas Courcoubetis, Richard Weber

Abstract: Nowadays, in the markets of broadband access services, traditional contracts are of "static" type. Customers buy the right to use a specific amount of resources for a specific period of time. On the other hand, modern services and applications render the demand for bandwidth highly variable and bursty. New types of contracts emerge ("dynamic contracts") which allow customers to dynamically adjust their bandwidth demand. In such an environment, we study the case of a price competition situation between two providers of static and dynamic contracts. We investigate the resulting reaction curves, search for the existence of an equilibrium point and examine if and how the market is segmented between the two providers. Our first model considers simple, constant provision costs. We then extend the model to include costs that depend on the multiplexing capabilities that the contracts offer to the providers, taking into consideration the size of the market. We base our analysis on the theory of effective bandwidths and investigate the new conditions that allow the provider of dynamic contracts to enter the market.

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Research Article Sat, 1 Mar 2008 00:00:00 +0200
Optimal Transit Price Negotiation: The Distributed Learning Perspective https://lib.jucs.org/article/29001/ JUCS - Journal of Universal Computer Science 14(5): 745-765

DOI: 10.3217/jucs-014-05-0745

Authors: Dominique Barth, Loubna Echabbi, Chahinez Hamlaoui

Abstract: We present a distributed learning algorithm for optimizing transit prices in the inter-domain routing framework. We present a combined game theoretical and distributed algorithmic analysis, where the notion of Nash equilibrium with the first approach meets the notion of stability in the second. We show that providers can learn how to strategically set their prices according to a Nash equilibrium; even when assuming incomplete information. We validate our theoretical model by simulations confirming the expected outcome. Moreover, we observe that some unilateral deviations from the proposed rule do not seem to affect the dynamic of the system.

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Research Article Sat, 1 Mar 2008 00:00:00 +0200
Rates of Asymptotic Regularity for Halpern Iterations of Nonexpansive Mappings https://lib.jucs.org/article/28893/ JUCS - Journal of Universal Computer Science 13(11): 1680-1691

DOI: 10.3217/jucs-013-11-1680

Authors: Laurentiu Leustean

Abstract: In this paper we obtain new effective results on the Halpern iterations of nonexpansive mappings using methods from mathematical logic or, more specifically, proof-theoretic techniques. We give effective rates of asymptotic regularity for the Halpern iterations of nonexpansive self-mappings of nonempty convex sets in normed spaces. The paper presents another case study in the project of proof mining, which is concerned with the extraction of effective uniform bounds from (prima-facie) ineffective proofs.

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Research Article Wed, 28 Nov 2007 00:00:00 +0200
A Comparison of Various Methods for Computing Bounds for Positive Roots of Polynomials https://lib.jucs.org/article/28764/ JUCS - Journal of Universal Computer Science 13(4): 455-467

DOI: 10.3217/jucs-013-04-0455

Authors: Alkiviadis Akritas, Panagiotis Vigklas

Abstract: The recent interest in isolating real roots of polynomials has revived interest in computing sharp upper bounds on the values of the positive roots of polynomials. Until now Cauchy's method was the only one widely used in this process. Ştefănescu's recently published theorem offers an alternative, but unfortunately is of limited applicability as it works only when there is an even number of sign variations (or changes) in the sequence of coefficients of the polynomial under consideration. In this paper we present a more general theorem that works for any number of sign variations provided a certain condition is met. We compare the method derived from our theorem with the corresponding methods by Cauchy and by Lagrange for computing bounds on the positive roots of polynomials. From the experimental results we conclude that it would be advantageous to extend our theorem so that it works without any restrictive conditions.

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Research Article Sat, 28 Apr 2007 00:00:00 +0300
Synthesis of Optimal Workflow Structure https://lib.jucs.org/article/28685/ JUCS - Journal of Universal Computer Science 12(9): 1385-1392

DOI: 10.3217/jucs-012-09-1385

Authors: József Tick, Zoltán Kovacs, Ferenc Friedler

Abstract: Optimal synthesis of workflow structures, the formerly undefined problem, has been introduced. Mathematical programming model is presented for determining the cost optimal workflow system of a given workflow problem. On the basis of a methodology developed for process network synthesis, effective solvers are available for the systematic synthesis of workflow systems.

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Research Article Thu, 28 Sep 2006 00:00:00 +0300
Construction of Wavelets and Applications https://lib.jucs.org/article/28677/ JUCS - Journal of Universal Computer Science 12(9): 1278-1291

DOI: 10.3217/jucs-012-09-1278

Authors: Ildikó László, Ferenc Schipp, Samuel Kozaitis

Abstract: A sequence of increasing translation invariant subspaces can be defined by the Haar-system (or generally by wavelets). The orthogonal projection to the subspaces generates a decomposition (multiresolution) of a signal. Regarding the rate of convergence and the number of operations, this kind of decomposition is much more favorable then the conventional Fourier expansion. In this paper, starting from Haar-like systems we will introduce a new type of multiresolution. The transition to higher levels in this case, instead of dilation will be realized by a two-fold map. Starting from a convenient scaling function and two-fold map, we will introduce a large class of Haar-like systems. Besides others, the original Haar system and Haar-like systems of trigonometric polynomials, and rational functions can be constructed in this way. We will show that the restriction of Haar-like systems to an appropriate set can be identified by the original Haar-system. Haar-like rational functions are used for the approximation of rational transfer functions which play an important role in signal processing [Bokor1 1998, Schipp01 2003, Bokor3 2003, Schipp 2002].

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Research Article Thu, 28 Sep 2006 00:00:00 +0300
Mathematical Models of Endocrine Systems https://lib.jucs.org/article/28676/ JUCS - Journal of Universal Computer Science 12(9): 1267-1277

DOI: 10.3217/jucs-012-09-1267

Authors: István Koós

Abstract: A mathematical model is proposed to allow expressive representation of endocrine systems by graphic means. The differential equations exactly describing the system can be formulated easily and automatically by the graphic model. Different kinds of software are supposed to solve these equations easily. Chaotic operational range can be found by fitting the parameters of equations. The results can account for some endocrine diseases and would be able to help the therapy.

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Research Article Thu, 28 Sep 2006 00:00:00 +0300
Sequential Data Assimilation: Information Fusion of a Numerical Simulation and Large Scale Observation Data https://lib.jucs.org/article/28619/ JUCS - Journal of Universal Computer Science 12(6): 608-626

DOI: 10.3217/jucs-012-06-0608

Authors: Kazuyuki Nakamura, Tomoyuki Higuchi, Naoki Hirose

Abstract: Data assimilation is a method of combining an imperfect simulation model and a number of incomplete observation data. Sequential data assimilation is a data assimilation in which simulation variables are corrected at every time step of observation. The ensemble Kalman filter is developed for a sequential data assimilation and frequently used in geophysics. On the other hand, the particle filter developed and used in statistics is similar in view of ensemble-based method, but it has different properties. In this paper, these two ensemble based filters are compared and characterized through matrix representation. An application of sequential data assimilation to tsunami simulation model with a numerical experiment is also shown. The particle filter is employed for this application. An erroneous bottom topography is corrected in the numerical experiment, which demonstrates that the particle filter is useful tool as the sequential data assimilation method.

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Research Article Wed, 28 Jun 2006 00:00:00 +0300
The Berlin Brain-Computer Interface:Machine Learning Based Detection of User Specific Brain States https://lib.jucs.org/article/28618/ JUCS - Journal of Universal Computer Science 12(6): 581-607

DOI: 10.3217/jucs-012-06-0581

Authors: Benjamin Blankertz, Guido Dornhege, Steven Lemm, Matthias Krauledat, Gabriel Curio, Klaus-Robert Müller

Abstract: We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main contribution of the BBCI, which is a non-invasive EEG-based BCI system, is the use of advanced machine learning techniques that allow to adapt to the specific brain signatures of each user with literally no training. In BBCI a calibration session of about 20min is necessary to provide a data basis from which the individualized brain signatures are inferred. This is very much in contrast to conventional BCI approaches that rely on operand conditioning and need extensive subject training of the order 50-100 hours. Our machine learning concept thus allows to achieve high quality feedback already after the very first session. This work reviews a broad range of investigations and experiments that have been performed within the BBCI project. In addition to these general paradigmatic BCI results, this work provides a condensed outline of the underlying machine learning and signal processing techniques that make the BBCI succeed. In the first experimental paradgm we analyze the predictability of limb movement long before the actual movement takes place using only the movement intention measured from the pre-movement (readiness) EEG potentials. The experiments include both off-line studies and an online feedback paradigm. The limits with respect to the spatial resolution of the somatotopy are explored by contrasting brain patterns of movements of left vs. right hand rsp. foot. In a second conplementary paradigm voluntary modulations of sensorimotor rhythms caused by motor imagery (left hand vs. right hand vs. foot) are translated into a continuous feedback signal. Here we report results of a recent feedback study with 6 healthy subjects with no or very little experience with BCI control: half of the subjects achieved an information transfer rate above 35 bits per minute (bmp). Furthermore one subject used the BBCI to operate a mental typewriter in free spelling mode. The overall spelling speed was 4.5-8 letters per minute including the time needed for the correction errors.

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Research Article Wed, 28 Jun 2006 00:00:00 +0300
A Multi-objective Genetic Approach to Mapping Problem on Network-on-Chip https://lib.jucs.org/article/28599/ JUCS - Journal of Universal Computer Science 12(4): 370-394

DOI: 10.3217/jucs-012-04-0370

Authors: Giuseppe Ascia, Vincenzo Catania, Maurizio Palesi

Abstract: Advances in technology now make it possible to integrate hundreds of cores (e.g. general or special purpose processors, embedded memories, application specific components, mixed-signal I/O cores) in a single silicon die. The large number of resources that have to communicate makes the use of interconnection systems based on shared buses inefficient. One way to solve the problem of on-chip communications is to use a Network-on-Chip (NoC)-based communication infrastructure. Such interconnection systems offer new degrees of freedom, exploration of which may reveal significant optimization possibilities: the possibility of arranging the computing and storage resources in an NoC, for example, has a great impact on various performance indexes. The paper addresses the problem of topological mapping of intellectual properties (IPs) on the tiles of a mesh-based NoC architecture. The aim is to obtain the Pareto mappings that maximize performance and minimize power dissipation. We propose a heuristic technique based on evolutionary computing to obtain an optimal approximation of the Pareto-optimal front in an efficient and accurate way. At the same time, two of the most widely-known approaches to mapping in mesh­based NoC architectures are extended in order to explore the mapping space in a multi-criteria mode. The approaches are then evaluated and compared, in terms of both accuracy and efficiency, on a platform based on an event-driven trace-based simulator which makes it possible to take account of important dynamic effects that have a great impact on mapping. The evaluation performed on both synthesized traffic and real applications (an MPEG-4 codec) confirms the efficiency, accuracy and scalability of the proposed approach.

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Research Article Fri, 28 Apr 2006 00:00:00 +0300
How the Mathematical Objects Determine the Mathematical Principles https://lib.jucs.org/article/28547/ JUCS - Journal of Universal Computer Science 11(12): 2132-2141

DOI: 10.3217/jucs-011-12-2132

Authors: Dirk Van Dalen

Abstract: In our description of Brouwer's universe we have discussed a few basic principles which have unusual consequences in practical mathematics.

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Research Article Wed, 28 Dec 2005 00:00:00 +0200
New Bounds for Positive Roots of Polynomials https://lib.jucs.org/article/28545/ JUCS - Journal of Universal Computer Science 11(12): 2125-2131

DOI: 10.3217/jucs-011-12-2125

Authors: Doru Ştefănescu

Abstract: We consider a nonconstant polynomial P with real coeţients that has at least one negative coeţient and derive new upper bounds for the real roots of P . We compare our bounds with those obtained by other methods.

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Research Article Wed, 28 Dec 2005 00:00:00 +0200
Formal Topology and Constructive Mathematics: the Gelfand and Stone-Yosida Representation Theorems https://lib.jucs.org/article/28520/ JUCS - Journal of Universal Computer Science 11(12): 1932-1944

DOI: 10.3217/jucs-011-12-1932

Authors: Thierry Coquand, Bas Spitters

Abstract: We present a constructive proof of the Stone-Yosida representation theorem for Riesz spaces motivated by considerations from formal topology. This theorem is used to derive a representation theorem for f-algebras. In turn, this theorem implies the Gelfand representation theorem for C*-algebras of operators on Hilbert spaces as formulated by Bishop and Bridges. Our proof is shorter, clearer, and we avoid the use of approximate eigenvalues.

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Research Article Wed, 28 Dec 2005 00:00:00 +0200
Constructive Analysis of Iterated Rational Functions https://lib.jucs.org/article/28518/ JUCS - Journal of Universal Computer Science 11(12): 1904-1931

DOI: 10.3217/jucs-011-12-1904

Authors: Jeremy Clark

Abstract: We develop the elementary theory of iterated rational functions over the Riemann sphere in a constructive setting. We use Bishop style constructive proof methods throughout. Starting from the development of constructive complex analysis presented in [Bishop and Bridges 1985], we give constructive proofs of Montel's Theorem along with necessary generalisations, and use them to prove elementary facts concerning the Julia set of a general continuous rational function with complex coefficients. We finish with a construction of repelling cycles for these maps, thereby showing that Julia sets are always inhabited.

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Research Article Wed, 28 Dec 2005 00:00:00 +0200
Computability of the Spectrum of Self-Adjoint Operators https://lib.jucs.org/article/28515/ JUCS - Journal of Universal Computer Science 11(12): 1884-1900

DOI: 10.3217/jucs-011-12-1884

Authors: Vasco Brattka, Ruth Dillhage

Abstract: Self-adjoint operators and their spectra play a crucial role in analysis and physics. For instance, in quantum physics self-adjoint operators are used to describe measurements and the spectrum represents the set of possible measurement results. Therefore, it is a natural question whether the spectrum of a self-adjoint operator can be computed from a description of the operator. We prove that given a "program" of the operator one can obtain positive information on the spectrum as a compact set in the sense that a dense subset of the spectrum can be enumerated (or equivalently: its distance function can be computed from above) and a bound on the set can be computed. This generalizes some non-uniform results obtained by Pour-El and Richards, which imply that the spectrum of any computable self-adjoint operator is a recursively enumerable compact set. Additionally, we show that the spectrum of compact self-adjoint operators can even be computed in the sense that also negative information is available (i.e. the distance function can be fully computed). Finally, we also discuss computability properties of the resolvent map.

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Research Article Wed, 28 Dec 2005 00:00:00 +0200
Constructive Equivalents of the Uniform Continuity Theorem https://lib.jucs.org/article/28513/ JUCS - Journal of Universal Computer Science 11(12): 1878-1883

DOI: 10.3217/jucs-011-12-1878

Authors: Josef Berger

Abstract: For the purpose of constructive reverse mathematics, we show the equivalence of the uniform continuity theorem to a series of propositions; this illuminates the relationship between Brouwer's fan theorem and the uniform continuity theorem

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Research Article Wed, 28 Dec 2005 00:00:00 +0200
A Message-Optimal Distributed Graph Algorithm: Partial Precedence Constrained Scheduling https://lib.jucs.org/article/28181/ JUCS - Journal of Universal Computer Science 10(2): 106-119

DOI: 10.3217/jucs-010-02-0106

Authors: Pranay Chaudhuri, Hussein Thompson

Abstract: This paper presents a distributed algorithm for the partial precedence constrained scheduling problem. In the classical precedence constrained scheduling problem all the dependent tasks must be scheduled before the task itself can be scheduled. The partial precedence constrained scheduling problem is a generalized version of the original precedence constrained problem in the sense that the number of dependent tasks to be scheduled before the task itself can be scheduled is considered a variable. Using a directed graph to model the partial precedence constrained scheduling problem in which n nodes represent the tasks and e edges represent the precedence constraints, it is shown that the distributed algorithm requires O(e) messages and O(n) units of time and is optimal in communication complexity to within a constant factor.

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Research Article Sat, 28 Feb 2004 00:00:00 +0200
Extentions of Affine Arithmetic: Application to Unconstrained Global Optimization https://lib.jucs.org/article/27919/ JUCS - Journal of Universal Computer Science 8(11): 992-1015

DOI: 10.3217/jucs-008-11-0992

Authors: Frédéric Messine

Abstract: Global optimization methods in connection with interval arithmetic permit to determine an accurate enclosure of the global optimum, and of all the corresponding optimizers. One of the main features of these algorithms consists in the construction of an interval function which produces an enclosure of the range of the studied function over a box (right parallelepiped). We use here affine arithmetic in global optimization algorithms, in order to elaborate new inclusion functions. These techniques are implemented and then discussed. Three new affine and quadratic forms are introduced. On some polynomial examples, we show that these new tools often yield more efficient lower bounds (and upper bounds) compared to several well-known classical inclusion functions. The three new methods, presented in this paper, are integrated into various Branch and Bound algorithms. This leads to improve the convergence of these algorithms by attenuating some negative effects due to the use of interval analysis and standard affne arithmetic.

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Research Article Thu, 28 Nov 2002 00:00:00 +0200
Using Genetic Algorithms to Solve the Motion Planning Problem https://lib.jucs.org/article/27670/ JUCS - Journal of Universal Computer Science 6(4): 422-432

DOI: 10.3217/jucs-006-04-0422

Authors: Craig Eldershaw, Stephen Cameron

Abstract: Motion planning is a field of growing importance as more and more computer controlled devices are being used. Many different approaches exist to motion planning|none of them ideal in all situations. This paper considers how to convert a general motion planning problem into one of global optimisation. We regard the general problem as being the classical configuration space findpath problem, but assume that the configurations of the device can be bounded by a hierarchy of hyper-spheres rather than being explicitly computed. A program to solve this problem has been written employing Genetic Algorithms. This paper describes how this was done, and some preliminary results of using it.

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Research Article Fri, 28 Apr 2000 00:00:00 +0300
Perturbation Simulations of Rounding Errors in the Evaluation of Chebyshev Series https://lib.jucs.org/article/27499/ JUCS - Journal of Universal Computer Science 4(6): 561-573

DOI: 10.3217/jucs-004-06-0561

Authors: Roberto Barrio, Jean-Claude Berges

Abstract: This paper presents some numerical simulations of rounding errors produced during evaluation of Chebyshev series. The simulations are based on perturbation theory and use recent software called AQUARELS. They give more precise results than the theoretical bounds (the difference is of some orders of magnitude). The paper concludes by confirming theoretical results on the increment of the error at the end of the interval [-1; 1] and the increased performance achieved by some modifications to Clenshaw's algorithm near those points.

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Research Article Sun, 28 Jun 1998 00:00:00 +0300
A Hybrid Subdivision Strategy for Adaptive Integration Routines https://lib.jucs.org/article/27493/ JUCS - Journal of Universal Computer Science 4(5): 486-500

DOI: 10.3217/jucs-004-05-0486

Authors: Ronald Cools, Bart Maerten

Abstract: In this paper we propose a modification of a part of the global adaptive integration algorithm that is usually taken for granted: the subdivision strategy. We introduce a subdivision strategy where the routine decides whether it is best to divide a hyper-rectangular region or a n-simplex in 2 or 2n parts or something in between.

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Research Article Thu, 28 May 1998 00:00:00 +0300
Algebraic Solutions to a Class of Interval Equations https://lib.jucs.org/article/27460/ JUCS - Journal of Universal Computer Science 4(1): 48-67

DOI: 10.3217/jucs-004-01-0048

Authors: Evgenija Popova

Abstract: The arithmetic on the extended set of proper and improper intervals is an algebraic completion of the conventional interval arithmetic and thus facilitates the explicit solution of certain interval algebraic problems. Due to the existence of inverse elements with respect to addition and multiplication operations certain interval algebraic equations can be solved by elementary algebraic transformations. The conditionally distributive relations between extended intervals allow that complicated interval algebraic equations, multi-incident on the unknown variable, be reduced to simpler ones. In this paper we give the general type of "pseudo-linear" interval equations in the extended interval arithmetic. The algebraic solutions to a pseudo-linear interval equation in one variable are studied. All numeric and parametric algebraic solutions, as well as the conditions for nonexistence of the algebraic solution to some basic types pseudo-linear interval equations in one variable are found. Some examples leading to algebraic solution of the equations under consideration and the extra func- tionalities for performing true symbolic-algebraic manipulations on interval formulae in a Mathematica package are discussed.

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Research Article Wed, 28 Jan 1998 00:00:00 +0200
On the Algebra of Intervals and Convex Bodies https://lib.jucs.org/article/27457/ JUCS - Journal of Universal Computer Science 4(1): 34-47

DOI: 10.3217/jucs-004-01-0034

Authors: Svetoslav Markov

Abstract: We introduce and study abstract algebraic systems generalizing the arithmetic systems of intervals and convex bodies involving Minkowski operations such as quasimodules and quasilinear systems. Embedding theorems are proved and computational rules for algebraic transformations are given.

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Research Article Wed, 28 Jan 1998 00:00:00 +0200
Stack Filter Design Using a Distributed Parallel Implementation of Genetic Algorithms https://lib.jucs.org/article/27387/ JUCS - Journal of Universal Computer Science 3(7): 821-834

DOI: 10.3217/jucs-003-07-0821

Authors: Peter Undrill, Kostas Delibasis, George Cameron

Abstract: Stack filters are a class of non-linear spatial operators used for suppression of noise in signals. In this work their design is formulated as an optimisation problem and a method that uses Genetic Algorithms (GAs) to perform the configuration is explained. Because of its computational complexity the process has been implemented as a distributed parallel GA using the Parallel Virtual Machine (PVM) software. We present the results of applying our stack filters to the restoration of magnetic resonance (MR) images corrupted with uniform, uncorellated, noise showing improved statistical performance compared with the median filter and indicating better retention of image details. The efficiency of the parallel implementation is examined, addressing both algorithmic and data decomposition, showing that execution times can be significantly reduced by distributing the task across a network of heterogeneous processors.

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Research Article Mon, 28 Jul 1997 00:00:00 +0300
Curve Fitting and Interpolation of Biological Data Under Uncertainties https://lib.jucs.org/article/27210/ JUCS - Journal of Universal Computer Science 2(2): 59-69

DOI: 10.3217/jucs-002-02-0058

Authors: Svetoslav Markov, Y. Akyildiz

Abstract: This paper is devoted to the software implementation of two mathematical methods which are often used in biological applications: interpolation and curve fitting in the presence of uncertainties in the input data given in the form of intervals. The methods involve model functions linear in their parameters and are formulated by means of simple expressions in terms of interval arithmetic allowing the computation of verified bounds for the interpolating/approximating functions. The methods are demonstrated for certain classes of nonlinear modelling functions finding applications in biology. A case study involving enzyme-catalysed reaction is considered. The numerical results are performed in the computer algebra system Mathematica, which supports interval-arithmetic computations.

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Research Article Wed, 28 Feb 1996 00:00:00 +0200
On a Formally Correct Implementation of IEEE Computer Arithmetic https://lib.jucs.org/article/27148/ JUCS - Journal of Universal Computer Science 1(7): 560-569

DOI: 10.3217/jucs-001-07-0560

Authors: Evgenija Popova

Abstract: IEEE floating-point arithmetic standards 754 and 854 reflect the present state of the art in designing and implementing floating-point arithmetic units. A formalism applied to a standard non-trapping mode floating-point system shows incorrectness of some numeric and non-numeric results. A software emulation of decimal floating-point computer arithmetic supporting an enhanced set of exception symbols is reported. Some implementation details, discussion of some open questions about utility and consistency of the implemented arithmetic with the IEEE Standards are provided. The potential benefit for computations with infinite symbolic elements is outlined.

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Research Article Fri, 28 Jul 1995 00:00:00 +0300
On Directed Interval Arithmetic and its Applications https://lib.jucs.org/article/27145/ JUCS - Journal of Universal Computer Science 1(7): 514-526

DOI: 10.3217/jucs-001-07-0514

Authors: Svetoslav Markov

Abstract: We discuss two closely related interval arithmetic systems: i) the of directed (generalized) intervals studied by E. Kaucher, and ii) the syste intervals together with the outer and inner interval operations. A relation two systems becomes feasible due to introduction of special notations and a normal form of directed intervals. As an application, it has been shown that interval systems can be used for the computation of tight inner and outer in of ranges of functions and consequently for the development of software for computation of ranges of functions.

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Research Article Fri, 28 Jul 1995 00:00:00 +0300
LCF: A Lexicographic Binary Representation of the Rationals https://lib.jucs.org/article/27141/ JUCS - Journal of Universal Computer Science 1(7): 484-503

DOI: 10.3217/jucs-001-07-0484

Authors: Peter Kornerup, David Matula

Abstract: A binary representation of the rationals derived from their continued fraction expansions is described and analysed. The concepts "adjacency", "mediant" and "convergent" from the literature on Farey fractions and continued fractions are suitably extended to provide a foundation for this new binary representation system. Worst case representation-induced precision loss for any real number by a fixed length representable number of the system is shown to be at most 19% of bit word length, with no precision loss whatsoever induced in the representation of any reasonably sized rational number. The representation is supported by a computer arithmetic system implementing exact rational and approximate real computations in an on-line fashion.

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Research Article Fri, 28 Jul 1995 00:00:00 +0300
Round-off Error Propagation in the Solution of the Heat Equation by finite Differences https://lib.jucs.org/article/27140/ JUCS - Journal of Universal Computer Science 1(7): 469-483

DOI: 10.3217/jucs-001-07-0469

Authors: Fabienne Jézéquel

Abstract: The effect of round-off errors on the numerical solution of the heat equation by finite differences can be theoretically determined by computing the mean error at each time step. The floating point error propagation is then theoretically time linear. The experimental simulations agree with this result for the towards zero rounding arithmetic. However the results are not so good for the rounding to the nearest artihmetic. The theoretical formulas provide an approximation of the experimental round-off errors. In these formulas the mean value of the assignment operator is used, and consequently, their reliability depends on the arithmetic used.

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Research Article Fri, 28 Jul 1995 00:00:00 +0300
Modular Range Reduction https://lib.jucs.org/article/27105/ JUCS - Journal of Universal Computer Science 1(3): 162-175

DOI: 10.3217/jucs-001-03-0162

Authors: Marc Daumas, Christophe Mazenc, Xavier Merrheim, Jean-Michel Muller

Abstract: A new range reduction algorithm, called ModularRange Reduction (MRR), briefly introduced by the authors in [Daumas et al. 1994] is deeply analyzed. It is used to reduce the arguments to exponential and trigonometric function algorithms to be within the small range for which the algorithms are valid. MRR reduces the arguments quickly and accurately. A fast hardwired implementation of MRR operates in time (log(n)), where n is the number of bits of the binary input value. For example, with MRR it becomes possible to compute the sine and cosine of a very large number accurately. Web propose two possible architectures implementing this algorithm.

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Research Article Tue, 28 Mar 1995 00:00:00 +0300