Tag: Soft Computing – A Fusion of Foundations, Methodologies and Applications

Assimilating and integrating network signals for solving some complex problems with a multiscale neural architecture

Abstract  In nature, some phenomena are so complicated (complex) that they are difficult to understand or to analyze in a formal manner,
due to a great deal of uncertainties caused by inevitable noises. In this paper, we propose an open evol…

Abstract  

In nature, some phenomena are so complicated (complex) that they are difficult to understand or to analyze in a formal manner,
due to a great deal of uncertainties caused by inevitable noises. In this paper, we propose an open evolutionary architecture
that has a great flexibility in representing information, and that possesses a rich potential for the evolution of a variety
of behaviors that could significantly expand the problem domains to which neural computing is applicable. The proposed model
is a mockup (abstract) system that consists of ambient grids and living nodes, which may interact with each other via various
kinds of communication mechanisms. Experiment result shows that it takes advantages of system dynamics occurring in different
levels to accomplish assigned tasks. It also shows the system exhibits certain degrees of robustness in dealing with noises
generated in the environments.

  • Content Type Journal Article
  • Category Original Paper
  • Pages 1-10
  • DOI 10.1007/s00500-011-0729-9
  • Authors
    • Chao-Yi Huang, Department of Information Management, Chungchou Institute of Technology, Yuanlin, Changhua, Taiwan, ROC
    • Jong-Chen Chen, Department of Information Management, National Yunlin University of Science and Technology, Touliu, Yunlin, Taiwan, ROC

Performance analysis in soccer: a Cartesian coordinates based approach using RoboCup data

Abstract  In soccer, like in business, results are often the best indicator of a team’s performance in a certain competition but insufficient
to a coach to asses his team performance. As a consequence, measurement tools play an important r…

Abstract  

In soccer, like in business, results are often the best indicator of a team’s performance in a certain competition but insufficient
to a coach to asses his team performance. As a consequence, measurement tools play an important role in this particular field.
In this research work, a performance tool for soccer, based only in Cartesian coordinates is presented. Capable of calculating
final game statistics, suisber of shots, the calculus methodology analyzes the game in a sequential manner, starting with
the identification of the kick event (the basis for detecting all events), which is related with a positive variation in the ball’s velocity vector. The
achieved results were quite satisfactory, mainly due to the number of successfully detected events in the validation process
(based on manual annotation). For the majority of the statistics, these values are above 92% and only in the case of shots
do these values drop to numbers between 74 and 85%. In the future, this methodology could be improved, especially regarding
the shot statistics, integrated with a real-time localization system, or expanded for other collective sports games, such
as hockey or basketball.

  • Content Type Journal Article
  • Category Original Paper
  • Pages 1-15
  • DOI 10.1007/s00500-011-0733-0
  • Authors
    • Pedro Henriques Abreu, Laboratory of Artificial Intelligence and Computer Science, Department of Informatics Engineering, Faculty of Engineering of Porto University, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal
    • José Moura, Laboratory of Artificial Intelligence and Computer Science, Department of Informatics Engineering, Faculty of Engineering of Porto University, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal
    • Daniel Castro Silva, Laboratory of Artificial Intelligence and Computer Science, Department of Informatics Engineering, Faculty of Engineering of Porto University, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal
    • Luís Paulo Reis, Laboratory of Artificial Intelligence and Computer Science, Department of Informatics Engineering, Faculty of Engineering of Porto University, Rua Dr. Roberto Frias, s/n, 4200-465 Porto, Portugal
    • Júlio Garganta, Investigation Center of Investigation, Education, Innovation and Intervention in Sport, Faculty of Sport of Porto University, Rua Dr. Plácido Costa, 91, 4200-450 Porto, Portugal

Study on semiparametric Wilcoxon fuzzy neural networks

Abstract  Fuzzy neural network (FNN) has long been recognized as an efficient and powerful learning machine for general machine learning
problems. Recently, Wilcoxon fuzzy neural network (WFNN), which generalizes the rank-based Wilcoxon appr…

Abstract  

Fuzzy neural network (FNN) has long been recognized as an efficient and powerful learning machine for general machine learning
problems. Recently, Wilcoxon fuzzy neural network (WFNN), which generalizes the rank-based Wilcoxon approach for linear parametric
regression problems to nonparametric neural network, was proposed aiming at improving robustness against outliers. FNN and
WFNN are nonparametric models in the sense that they put no restrictions, except possibly smoothness, on the functional form
of the regression function. However, they may be difficult to interpret and, even worse, yield poor estimates with high computational
cost when the number of predictor variables is large. To overcome this drawback, semiparametric models have been proposed
in statistical regression theory. A semiparametric model keeps the easy interpretability of its parametric part and retains
the flexibility of its nonparametric part. Based on this, semiparametric FNN and semiparametric WFNN will be proposed in this
paper. The learning rules are based on the backfitting procedure frequently used in semiparametric regression. Simulation
results show that the semiparametric models perform better than their nonparametric counterparts.

  • Content Type Journal Article
  • Category Original Paper
  • Pages 1-11
  • DOI 10.1007/s00500-011-0730-3
  • Authors
    • Hsu-Kun Wu, Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424 Taiwan
    • Yih-Lon Lin, Department of Information Engineering, I-Shou University, Kaohsiung, 84001 Taiwan
    • Jer-Guang Hsieh, Department of Electrical Engineering, I-Shou University, Kaohsiung, 84001 Taiwan
    • Jyh-Horng Jeng, Department of Information Engineering, I-Shou University, Kaohsiung, 84001 Taiwan

Bio-inspired group mobility model for mobile ad hoc networks based on bird-flocking behavior

Abstract  In this paper, we propose a novel group mobility model for mobile ad hoc networks (MANETs), named as Bird-Flocking Behavior
Inspired Group Mobility Model (BFBIGM), which takes inspiration from the mobility of a flock of birds, flyi…

Abstract  

In this paper, we propose a novel group mobility model for mobile ad hoc networks (MANETs), named as Bird-Flocking Behavior
Inspired Group Mobility Model (BFBIGM), which takes inspiration from the mobility of a flock of birds, flying in a formation.
Most existing modeling techniques are deficient in successfully addressing many aspects in terms of the application of realistic
forces on the movement of mobile nodes (MNs), the interaction of MNs within a group, and collision avoidance within a group
and with environmental obstacles. The results obtained through experiments show that in terms of connectivity metrics, such
as link duration, BFBIGM performs around 50% better in comparison to the popular existing mobility models like Random Waypoint
(RWP) Model (Johnson et al. in Ad hoc networking, Addison-Wesley, Menlo Park, pp. 139–172,2001) and the Reference Point Group Mobility (RPGM) Model (Hong et al. in: Proceedings of the 2nd ACM international workshop on
modeling, analysis and simulation of wireless and mobile systems, Seattle, WA, pp. 53–60,1999).

  • Content Type Journal Article
  • Category Focus
  • Pages 1-14
  • DOI 10.1007/s00500-011-0728-x
  • Authors
    • Sudip Misra, School of Information Technology, Indian Institute of Technology, Kharagpur, West Bengal, India
    • Prateek Agarwal, School of Information Technology, Indian Institute of Technology, Kharagpur, West Bengal, India

On a generalization of the concept of state property system

Abstract  Based in the notions of topological system of S. Vickers and lattice-valued topological space of S.E. Rodabaugh, the paper
introduces a generalization of the concepts of state property system of D. Aerts and closure space (used by …

Abstract  

Based in the notions of topological system of S. Vickers and lattice-valued topological space of S.E. Rodabaugh, the paper
introduces a generalization of the concepts of state property system of D. Aerts and closure space (used by many authors in
the literature), showing that the categories of the new structures are equivalent.

  • Content Type Journal Article
  • Category Original Paper
  • Pages 1-12
  • DOI 10.1007/s00500-011-0709-0
  • Authors
    • Sergey A. Solovyov, Department of Mathematics, University of Latvia, Zellu iela 8, Riga, 1002 Latvia

Lattice pseudoeffect algebras as double residuated structures

Abstract  Pseudoeffect algebras are partial algebraic structures which are non-commutative generalizations of effect algebras. The main
result of the paper is a characterization of lattice pseudoeffect algebras in terms of so-called pseudo S…

Abstract  

Pseudoeffect algebras are partial algebraic structures which are non-commutative generalizations of effect algebras. The main
result of the paper is a characterization of lattice pseudoeffect algebras in terms of so-called pseudo Sasaki algebras. In
contrast to pseudoeffect algebras, pseudo Sasaki algebras are total algebras. They are obtained as a generalization of Sasaki
algebras, which in turn characterize lattice effect algebras. Moreover, it is shown that lattice pseudoeffect algebras are
a special case of double CI-posets, which are algebraic structures with two pairs of residuated operations, and which can
be considered as generalizations of residuated posets. For instance, a lattice ordered pseudoeffect algebra, regarded as a
double CI-poset, becomes a residuated poset if and only if it is a pseudo MV-algebra. It is also shown that an arbitrary pseudoeffect
algebra can be described as a special case of conditional double CI-poset, in which case the two pairs of residuated operations
are only partially defined.

  • Content Type Journal Article
  • Category Original Paper
  • Pages 1-10
  • DOI 10.1007/s00500-011-0710-7
  • Authors
    • David J. Foulis, Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA, USA
    • Sylvia Pulmannová, Mathematical Institute, Slovak Academy of Sciences, Štefánikova 49, 814 73 Bratislava, Slovakia
    • Elena Vinceková, Mathematical Institute, Slovak Academy of Sciences, Štefánikova 49, 814 73 Bratislava, Slovakia

Termite tunneling feature extraction using genetic algorithm

Abstract  Path design uses information about termite reproduction and the termite environment necessary for tunneling. Features are
extracted by analyzing relevance of this information, and the fitness and relevance of these features are eva…

Abstract  

Path design uses information about termite reproduction and the termite environment necessary for tunneling. Features are
extracted by analyzing relevance of this information, and the fitness and relevance of these features are evaluated. The proposed
method is demonstrated and is capable of finding various optimal termite tunneling paths.

  • Content Type Journal Article
  • Category Focus
  • Pages 1-7
  • DOI 10.1007/s00500-011-0726-z
  • Authors
    • Malrey Lee, Center for Advanced Image and Information Technology, School of Electronics and Information Engineering, ChonBuk National University, 664-14, 1Ga, DeokJin-Dong, Jeonju, Chon Buk 561-756, South Korea
    • Eun-Kwan Kang, Department of Multimedia, JeonJu University, 45, Baengina-gil, Wansan-Gu, Jeonju, South Korea

SignatureClust: a tool for landmark gene-guided clustering

Abstract  Over the last several years, many clustering algorithms have been applied to gene expression data. However, most clustering
algorithms force the user into having one set of clusters, resulting in a restrictive biological interpreta…

Abstract  

Over the last several years, many clustering algorithms have been applied to gene expression data. However, most clustering
algorithms force the user into having one set of clusters, resulting in a restrictive biological interpretation of gene function.
It would be difficult to interpret the complex biological regulatory mechanisms and genetic interactions from this restrictive
interpretation of microarray expression data. The software package SignatureClust allows users to select a group of functionally
related genes (called ‘Landmark Genes’), and to project the gene expression data onto these genes. Compared to existing algorithms
and software in this domain, our software package offers two unique benefits. First, by selecting different sets of landmark
genes, it enables the user to cluster the microarray data from multiple biological perspectives. This encourages data exploration
and discovery of new gene associations. Second, most packages associated with clustering provide internal validation measures,
whereas our package validates the biological significance of the new clusters by retrieving significant ontology and pathway
terms associated with the new clusters. SignatureClust is a free software tool that enables biologists to get multiple views
of the microarray data. It highlights new gene associations that were not found using a traditional clustering algorithm.
The software package ‘SignatureClust’ and the user manual can be downloaded from http://infos.korea.ac.kr/sigclust.php.

  • Content Type Journal Article
  • Category Focus
  • Pages 1-8
  • DOI 10.1007/s00500-011-0725-0
  • Authors
    • Pankaj Chopra, Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA, USA
    • Hanjun Shin, Department of Computer Science, College of Information and Communication, Korea University, Seoul, South Korea
    • Jaewoo Kang, Department of Computer Science, College of Information and Communication, Korea University, Seoul, South Korea
    • Sunwon Lee, Department of Computer Science, College of Information and Communication, Korea University, Seoul, South Korea

Distributed quantum entanglement sharing model for high-performance real-time system

Abstract  Two processors jointly provide a real-time service which can be completed by exactly one processor. Assuming each processor
is allowed to announce only a one-bit information in a distributed way to decide which one should process t…

Abstract  

Two processors jointly provide a real-time service which can be completed by exactly one processor. Assuming each processor
is allowed to announce only a one-bit information in a distributed way to decide which one should process the job, inevitably
some of the jobs will get lost if only classical resources are used. In this paper, we proposed the distributed quantum entanglement
sharing (DQES) model to share quantum entanglement with processors. Assisted with DQES model, not only the system dependability
can be enhanced, but the faulty processor can also be identified. We also presented some possible applications such like database
consistency, job scheduling, system dependability, and reliable communication protocols.

  • Content Type Journal Article
  • Category Focus
  • Pages 1-9
  • DOI 10.1007/s00500-011-0727-y
  • Authors
    • Chi-Yuan Chen, Department of Electrical Engineering, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Rd, Shoufeng, 97401 Hualien, Taiwan, ROC
    • Yao-Hsin Chou, Department of Computer Science and Information Engineering, National Chi Nan University, No. 1, University Rd, Puli, 54561 Nantou, Taiwan, ROC
    • Han-Chieh Chao, Department of Electrical Engineering, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Rd, Shoufeng, 97401 Hualien, Taiwan, ROC

High performance memetic algorithm particle filter for multiple object tracking on modern GPUs

Abstract  This work presents an effective approach to visual tracking using a graphics processing unit (GPU) for computation purposes.
In order to get a performance improvement against other platforms it is convenient to select proper algori…

Abstract  

This work presents an effective approach to visual tracking using a graphics processing unit (GPU) for computation purposes.
In order to get a performance improvement against other platforms it is convenient to select proper algorithms such as population-based
ones. They expose a parallel-friendly nature needing from many independent evaluations that map well to the parallel architecture
of the GPU. To this end we propose a particle filter (PF) hybridized with a memetic algorithm (MA) to produce a MAPF tracking
algorithm for single and multiple object tracking problems. Previous experimental results demonstrated that the MAPF algorithm
showed more accurate tracking results than the standard PF, and now we extend those results with the first complete adaptation
of the PF and the MAPF for visual tracking to the NVIDIA CUDA architecture. Results show a GPU speedup between 5×–16× for
different configurations.

  • Content Type Journal Article
  • Category Focus
  • Pages 1-14
  • DOI 10.1007/s00500-011-0715-2
  • Authors
    • Raúl Cabido, Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, c/ Tulipán s/n, 28933 Móstoles, Madrid, Spain
    • Antonio S. Montemayor, Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, c/ Tulipán s/n, 28933 Móstoles, Madrid, Spain
    • Juan J. Pantrigo, Departamento de Ciencias de la Computación, Universidad Rey Juan Carlos, c/ Tulipán s/n, 28933 Móstoles, Madrid, Spain