bluuebunny/crossref_metadata_2025 huggingface dataset:
Selected Papers from HNICEM 2005
Authors: Dadios Elmer P. ,   Professor, Department of Manufacturing Engineering and Management
Published: April 2016

HNICEM is a biennial international conference of experts in the fields of Robotics, Nanotechnology, Information Technology, Control and Communication, Environment, and Management. This special issue presents 11 articles selected from HNICEM 2005 that will provide valuable references for researchers and practitioners. The first article presents new content-based image retrieval based on the visual keys concept. Visual keys are defined as representative regions extracted from an image database and are constructed using image feature clustering. The second article presents interactive video recording and playback technique originally developed for biomedical multimedia training. The third article proposes techniques for determining motion parameters based on complex number expression of the rotation matrix. The fourth article studies the learning behavior of Genetic Algorithm and its potential in real time non-linear control. The effects of different parameters used in the GA for its learning are analyzed. The fifth article presents a Coordinated Hybrid Agent (CHA) framework for the control of Multi-Agent Systems (MASs) applied to a heterogeneous multi-agent such as a mobile robot, an overhead crane, and a robot manipulator. The sixth article presents an algorithm that emulates human inference in deducing root causes, avoiding intermediary causes and anticipating subsequent moves. The seventh article proposes a technique to create Intelligent Distributed Robotic Systems (IDRS) that show smart behavior using a wrapper-components approach. The eighth article presents an autonomous mobile robot with neural network (NN) vision that searches for and collects golf balls in an open or indoor golf driving range. The ninth article demonstrates the technological benefits of miniaturizing machine tools in the context of machine stiffness and accuracy. It also presents the design philosophy and configuration of a 4-axis miniaturized vertical machining center with a positioning accuracy of 4 to 10nm. The tenth article investigates a new type of ion exchanger for high ion exchange capacity (IEC) and rapid ion exchange velocity. Experimental results demonstrate the performance of polystyrene nanofiber ion exchangers (PSNIE) and cation exchanger fiber (CEF). The eleventh and last article presents the architectural design of a Multiservice Provisioning Platform (MSPP) for WiMAX over SONET/SDH. It involves networking existing technologies to deliver a solution that caters to a unique situation favoring wireless access networks to a fully cabled system. We extend our warmest thanks and deepest gratitude to the distinguished authors and reviewers who have contributed to this special issue for their outstanding contributions and cooperation. We are also grateful to Prof. Toshio Fukuda and Prof. Kaoru Hirota, chief editors of JACIII, for inviting me to serve as Guest Editor of this Journal.
Designing Image Retrieval System with the Concept of Visual Keys
Authors: Serata Manabu ,   Hirota Laboratory, Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama-city 226-8502, Japan, Hatakeyama Yutaka , Hirota Kaoru
Published: April 2016

A concept of visual keys is proposed to provide efficient and useful content-based image retrieval systems to users. Visual keys are defined as representative sub-images which are extracted from an image database by using image feature clustering. The proposed system is implemented and is tested on 1,000 images, which are included in the COREL database. Although the system makes use of only 80 sub-images from 8,962 ones extracted from the image database, the performance is kept with 90%. The retrieval time is within 4ms on the proposed system, which has retrieval efficiency like that of text retrieval by being applied text retrieval techniques, and thus the system is expected to provide the services on the WWW.
Neural Network Vision-Guided Mobile Robot for Retrieving Driving-Range Golf Balls
Authors: Dadios Elmer P. ,   Department of Manufacturing Engineering and Management, De La Salle University, 2401 Taft Avenue, De La Salle University, Manila 1004, Philippines, Hirota Kaoru , Catigum Michelle L. , Gutierrez Albert C. , Rodrigo Danison R. , Juan Christopher Allan G. San , Tan Jeffrey T. ,   Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan,   ROHM LSI Design Philippines Inc.,   Accenture Philippines,   Intel Technology Philippines Inc.,   Lexmark R&D Corp. Philippines
Published: April 2016

We developed an autonomous mobile robot with neural network (NN) vision that searches for and collects golf balls on an open or an indoor golf driving range. The robot recognizes range borderlines by red stripes. Scattered golf balls are collected using mechanically designed rotating blades. The NN vision identifies objects that are not golf balls and prevents the robot from picking them. The vision system is robust enough to navigate an open field and pick up the golf balls any time of day. Results of the experiments showed that our proposal operates accurately and reliably.
Adaptive Fuzzy Control for a Class of Nonlinear Systems with State Observer
Authors: Han Hugang ,   Faculty of Management Information Sciences, Prefectural University of Hiroshima, 1-1-71 Ujina-higashi, Minami-ku, Hiroshima 734-8558, Japan
Published: April 2016

This paper addresses the fuzzy control problem using the Lyapunov synthesis approach. In order to deal with cases where the system state is unavailable, a state observer is proposed. Consequently, the whole system behavior can be attributed to a kind of standard singularly perturbed form. At the same time, to deal with the gap, if any, between the real state and its estimated value from the state observer, we view it as a part of system disturbance, and propose a unique way to deal with the disturbance, i.e., adopt a switching function with an alterable coefficient, which is tuned by adaptive law based on the tracking error between the output of the considered system and the desired value. Finally, it is shown that the fuzzy controller proposed guarantees the tracking error will shrink to zero, while maintaining the stability of all signals involved in the system.
Semantic Query Optimization: Correctness and Control
Authors: Chippimolchai Pongtawat ,   Computer Science and Information Management Program, Asian Institute of Technology, Km. 42, Paholyothin Highway, Klong Luang, Pathumthani 12120, Thailand, Akama Kiyoshi , Wuwongse Vilas ,   Division of Large-Scale Computational Systems Information Initiative Center, Hokkaido University, Kita 11 Nishi 5, Kita-ku, Sapporo, Hokkaido 060-0811, Japan
Published: April 2016

We developed a semantic query optimization framework for deductive databases based on equivalent transformation (ET) rules. ET rules, prepared from the semantic knowledge of databases, such as integrity constraints, transform given queries into syntactically different but semantically equivalent and more efficient forms. We formally prove the correctness of query transformations by ET rules. For efficiency, we propose a two-phase heuristic-based strategy to guide query transformations and introduce a condition-based control strategy to prevent unwanted, unnecessary transformations. We give examples demonstrating the possible optimization.
Discovering Both Positive and Negative Fuzzy Association Rules in Large Transaction Databases
Authors: Han Jianchao ,   Department of Computer Science, California State University, Dominguez Hills, 1000 E. Victoria St., Carson, CA 90747, USA, Beheshti Mohsen
Published: April 2016

Mining association rules is an important task of dara mining and knowledge discovery. Traditional association rules mining is built on transaction databases, which has some limitations. Two of these limitations are 1) each transaction merely contains binary items, meaning that an item either occurs in a transaction or not; 2) only positive association rules are discovered, while negative associations are ignored. Mining fuzzy association rules has been proposed to address the first limitation, while mining algorithms for negative association rules have been developed to resolve the second limitation. In this paper, we combine these two approaches to propose a novel approach for mining both positive and negative fuzzy association rules. The interestingness measure for both positive and negative fuzzy association rule is proposed, the algorithm for mining these rules is described, and an illustrative example is presented to demonstrate how the measure and the algorithm work.
Fast Placement Algorithm for Rectilinear Jigsaw Puzzles
Authors: Murai Yasuyuki ,   Department of Information and Computer Sciences, Kanagawa Institute of Technology, 1030 Shimo-ogino, Atsugi, Kanagawa 243-0292, Japan, Tsuji Hiroyuki , Tatsumi Hisayuki , Tokumasu Shinji ,   Department of Computer Science, Tsukuba University of Technology, 4-12-7 Kasuga, Tsukuba, Ibaraki 305-0821, Japan
Published: April 2016

In previous papers, rectilinear jigsaw puzzles have been described as a specialized placement problem such that this has at least one solution to placement, but generally not that many. Instead of adopting the well-known iterative method to solve this problem, a new game-theoretic algorithm is developed by translating the problem to one of checkmate in games analogous to chess or shogi. By extending the game-theoretic algorithm, a much faster algorithm for large puzzles is developed by introducing various heuristics on the placement of pieces. We also proved through numerical experiments that this worked efficiently.
Expert System-Type Approach to Voice Disorders: Scheduling Botulinum Toxin Treatment for Adductor Spasmodic Dysphonia
Authors: Salvatore Anthony P. ,   University of Texas at El Paso, 500 W. University, El Paso, TX 79968, USA, Biswas Amitava , Kreinovich Vladik , Manriquez Bertha , Cannito Michael P. , Sinard Robert J. ,   Speech and Hearing Center, School of Audiology and Speech-Language Pathology, The University of Memphis, Memphis, TN 38105, USA,   Department of Otolaryngology, University of Texas, Southwestern Medical Center at Dallas, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA
Published: April 2016

One of the most debilitating voice disorders is adductor spasmodic dysphonia (ADSD), a voice disorder caused by involuntary movements of the muscles of the larynx (voice box). For treating ADSD, botulinum toxin (BT) injections turned out to be very useful. However, the effects of BT are highly variable, so at present, there is no objective criterion of when such a BT treatment is necessary. It is therefore desirable to develop such a criterion. In this paper, we show that traditional statistical techniques are unable to generate such a criterion, while a natural expert system approach seems to be capable of generating reasonably simple rules that determine when a BT treatment is necessary.
Incremental Learning, Recognition, and Generation of Time-Series Patterns Based on Self-Organizing Segmentation
Authors: Okada Shogo ,   Tokyo Institute of Technology, R2-52, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan, Hasegawa Osamu
Published: April 2016

We segments and symbolizes image information on a series of human behavior as an aggregate unit of motions in a self-organizing manner and proposes a system that recognizes the entire behavior as a symbol string. This system symbolizes the motion unit incrementally and also generates motion from a symbol. To implement the system, we used a mixture of experts with a non-monotonous recurrent neural network used as the expert and our own DP matching method. In addition, our proposal makes not only teacher-labeled patterns, but also teacher-unlabeled patterns available for learning. By using this function, we proposed semi-supervised learning using our proposal in this paper. We verified the evaluation of the effectiveness of our proposal and semi-supervised learning function by two experiments using moving images including seven gestures.
Q-SEE: Qualitative Simulation Support System in Economic Education
Authors: Matsuo Tokuro ,   Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555, Japan, Komatsu Masaki , Ito Takayuki , Shintani Toramatsu ,   Division of Engineering and Applied Science, Harvard University, 33 Oxford Street, Cambridge 02446, USA
Published: April 2016

In this paper, we present a support method of economic learning system based on qualitative simulation. We employ qualitative simulations because this lets the learners can understand the conceptual principles in economic dynamics. In existing learning system with qualitative simulation, users are not supported effectively in building qualitative simulation model. To solve the problem, we propose a support process and methods based on users condition. In our system, users conditions are classified into 4 phases. Based on the phases, our system helps users make qualitative simulation model step by step. Furthermore, our system supports users through making partial-adjacent relationships/graph model and supports users displaying errors about inconsistency and incorrect rule when there are inconsistency and mistaken relationship in the graph model made by users. The work focuses on interactively helping a learner to develop a qualitative model of an economic system as a teaching tool. The system has three key advantages. (1) Our system supports users’ learning based on condition and process in which users make simulation models. (2) Users can make qualitative simulation model without their confusion because it is easy for users to make the model with consistency, propriety and adequacy using our system. (3) Users can make qualitative simulation model effectively because users can understand the detail and all over the model using our support system. The contributions of this paper are mainly showing the support process and support method in building qualitative simulation model.
Extending Fuzzy Directional Relationship and Applying for Mobile Robot Collision Avoidance Behavior
Authors: Ngo Long Thanh ,   Center of Simulation Technology, Le Quy Don Technical University, 100-Hoang Quoc Viet Rd., Cau Giay Dist., Hanoi, Vietnam, Pham Long The , Nguyen Phuong Hoang , Hirota Kaoru ,   Center of Health Information Technology, Ministry of Health, 3-Phuong Mai St., Dong Da Dist., Hanoi, Vietnam,   Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Modori-ku, Yokohama 226-8502, Japan
Published: April 2016

Fuzzy directional relationship is extended from crisp spatial relationship and applied for many problems as image processing, scene description. This paper deals with fuzzy directional relationship and proposes an approach to extend fuzzy directional relation for robot navigation based on behavior. Fuzzy directional relation is used to model the unknown environment perceived by mobile robot. Collision avoidance behavior is built for mobile robot to avoid obstacles based on fuzzy logic controller whose inputs are fuzzy relationship and range to obstacle. The simulated results on graphic environment are showed to demonstrate our approach.
Max-Product Shepard Approximation Operators
Authors: Bede Barnabás ,   Department of Mechanical and System Engineering, Bánki Donát Faculty of Mechanical Engineering, Budapest Tech, Népszinház u. 8, H-1081 Budapest, Hungary, Nobuhara Hajime , Fodor János , Hirota Kaoru ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midoriku, Yokohama 226-8502, Japan,   Institute of Intelligent Engineering Systems, John von Neumann Faculty of Informatics, Budapest Tech, Bécsi út 96/b, H-1034 Budapest, Hungary
Published: April 2016

In crisp approximation theory the operations that are used are only the usual sum and product of reals. We propose the following problem: are sum and product the only operations that can be used in approximation theory? As an answer to this problem we propose max-product Shepard approximation operators and we prove that these operators have very similar properties to those provided by the crisp approximation theory. In this sense we obtain uniform approximation theorem of Weierstrass type, and Jackson-type error estimate in approximation by these operators.
Classification of Time Series Using Singular Values and Wavelet Subband Analysis with ANN and SVM Classifiers
Authors: Benyó Balázs ,   Department of Information Technology, Széchenyi István University, Egyetem tér 1., Győr H-9026, Hungary, Somogyi Péter , Paláncz Béla ,   Department of Control Engineering and Information Technology, Budapest University of Technology and Economics, Magyar tudósok krt. 2., Budapest H-1117, Hungary,   Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Műegyetem rakpart 3., Budapest H-1117, Hungary
Published: April 2016

Oscillation of cerebral blood flow (CBF) in physiological or pathophysiological brain states is common, therefore it is promising to identify cerebral circulation disorders based on CBF signal classification. To characterize temporal blood flow patterns, we applied two feature extractions, spectral matrix and wavelet subband analysis. To distinguish between different physiological states, two different classifications have been developed - the radial basis function-based neural network and a support vector classifier with a Gaussian kernel. Feature extraction and classification are evaluated and their efficiency compared. Calculation was done using Mathematica 5.1 and its Wavelet Application.
Implementation of Course Model Driven Virtual Classroom in Higher Education
Authors: Gáti József ,   Budapest Tech Polytechnical Institution, Bécsi út 96/B, H-1034 Budapest, Hungary, Kártyás Gyula
Published: April 2016

Advances in information technology stimulate development of applications to enhance Internet-based higher education. Reviewing a virtual classroom model, we studied the possibilities and problems of introducing model-based distance learning in everyday higher education. We survey important issues and methodological elements of virtual classrooms in relation to demands of teaching procedures, programs, and materials. Our main objective is to determine specific circumstances enabling objects to be defined for this special modeling. We begin by introducing application of features in models for virtual teaching, then discuss issues in local and global education, focusing on the advantages of virtual education. We detail application-related features of the cited course model and discuss the implementation of virtual classrooms in higher education.
Topological Structures of Rough Sets Induced by Equivalence Relations
Authors: Kondo Michiro ,   School of Information Environment, Tokyo Denki University, Inzai 270-1382, Japan, Dudek Wieslaw A. ,   Institute of Mathematics, Wroclaw University of Technology, Wroclaw 50-370, Poland
Published: April 2016

In this paper we consider some fundamental topological properties of rough sets induced by equivalence relations and show that 1. Every approximation space is retrieval. 2. For every approximation space X=(X,θ), X is strongly connected if and only if θ=X×X. Moreover we consider topological properties of generalized rough sets.
On Fuzzy c-Means for Data with Tolerance
Authors: Murata Ryuichi ,   University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Endo Yasunori , Haruyama Hideyuki , Miyamoto Sadaaki
Published: April 2016

This paper presents two new clustering algorithms which are based on the entropy regularized fuzzyc-means and can treat data with some errors. First, the tolerance is formulated and introduce into optimization problems of clustering. Next, the problems are solved using Kuhn-Tucker conditions. Last, the algorithms are constructed based on the results of solving the problems.
An Application of Binary Decision Trees to Pattern Recognition
Authors: Takagi Noboru ,   Department of Intelligent Systems Design Engineering, Toyama Prefectural University, 5180 Kurokawa, Imizu, Toyama 939-0398, Japan
Published: April 2016

Decision rules are a key technique in decision making, data mining and knowledge discovery in databases. We introduce an application of decision rules, handwriting pattern classification. When decision rules are applied to pattern recognition, one rule forms a hyperrectangle in feature space, i.e., each decision rule corresponds to one hyperrectangle. This means that a set of decision rules is considered a classification system, called the subclass method. We apply decision rules to handwritten Japanese character recognition, showing experimental results.
An Efficient Authorization Mechanism for Secure XML Sources on the Web
Authors: Jo Sun-Moon ,   Department of Computer Information Technology Education, Paichai University, 439-6 Doma-2Dong, Seo-Gu, Daejeon, Korea, Yoo Weon-Hee ,   Department of Computer Science and Information Engineering, Inha University, 253 Yonghyun-Dong, Nam-Gu, Incheon, Korea
Published: April 2016

XML-based access control technology aims at providing an authorization policy that can be consistently applied to various products for access control services on Internet and different kinds of environment for the products and thus providing interoperability to the existing access control products with diverse kinds of environment and types. The existing access control fails to consider information structure and semantics sufficiently due to the fundamental limitations of HTML. In addition, XML document access control supplies only action read and permits alterations of very limited value for action write. The existing access control has disadvantages that DOM tree should be loaded on memory while all XML documents are parsed to generate DOM tree; that a lot of memory is used in repetitive search for tree to authorize access to all nodes in DOM tree; and that the complex authorization evaluation process may lower system performance. In this paper, we present an authorization mechanism for secure XML sources on the Web.
Automatic Web Service Composition Based on Behavior Network
Authors: Jung Myung-Chul ,   Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-gu, Seoul 120-749, Korea, Cho Sung-Bae
Published: April 2016

As Web services become more widely disseminated, tools are needed to help users find and integrate these services. As these services become more available, users and service providers will want to obtain new and value-added services by combining and reconfiguring existing services. We propose novel Web service composition based on a behavior network that selects services automatically through internal and external links with environmental information from sensor and goals. Optimal services are selected at each step, resulting in a globally optimal service sequence for achieving a preset goal. We developed our prototype using Amazon Web services to verify its feasibility. Experimental results comparing rule-based system and user tests demonstrated the potential of the behavior network for Web services applications.
MDVM System Concept, Paging Latency and Round-2 Randomized Leader Election Algorithm in SG
Authors: Bagchi Susmit ,   Deptt. of Information Technology, Sikkim Manipal Inst. of Technology, Majitar, Sikkim, India, Rahaman Hafizur , Das Purnendu ,   Deptt. of Information Technology, Bengal Engineering and Science University, Shibpur, Howrah, India,   School of Information Technology, Bengal Engineering and Science University, Shibpur, Howrah, India
Published: April 2016

The future trend in the computing paradigm is marked by mobile computing based on mobile-client/server architecture connected by wireless communication network. However, the mobile computing systems have limitations because of the resource-thin mobile clients operating on battery power. The MDVM system allows the mobile clients to utilize memory and CPU resources of Server-Groups (SG) to overcome the resource limitations of clients in order to support the high-end mobile applications such as, m-commerce and virtual organization (VO). In this paper the concept of MDVM system and the architecture of cellular network containing the SG are discussed. A round-2 randomized distributed algorithm is proposed to elect a unique leader and co-leader of the SG. The algorithm is free from any assumption about network topology, buffer space limitations and is based on dynamically elected coordinators eliminating single point of failure. The algorithm is implemented in distributed system setup and the network-paging latency values of wired and wireless networks are measured experimentally. The experimental results demonstrate that in most cases the algorithm successfully terminates in first round and the possibility of second round execution decreases significantly with the increase in the size of SG (|Na|). The overall message complexity of the algorithm is O(|Na|). The comparative study of network-paging latencies indicates that 3G/4G mobile communication systems would support the realization of MDVM system.
Smart Help for Novice Users Based on Application Software Manuals
Authors: Iwashita Shino ,   Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka 815-8540, Japan, Ito Noriko , Kobayashi Ichiro , Sugimoto Toru , Sugeno Michio ,   Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 610-0394, Japan,   Ochanomizu University, 2-1-1 Otsuka, Bunkyo-ku, Tokyo 112-8610, Japan,   RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
Published: April 2016

The smart help we propose based on application software manuals features four phases: (1) understanding the user’s input text, which is a question about software operation; (2) matching the result of understanding with software manual text; (3) planning a dialog with the user; and (4) paraphrasing matching manual text to output for the user. Manual text found during matching is paraphrased using the analysis result found during understanding. In planning, the rhetorical structure of the selected manual is used to determine which clauses in matching manual text are specifically relevant to the user’s question. Four paraphrases for a novice user are identified in a subject experiment, and rules for these are applied based on linguistic features extracted during the understanding. We evaluated an implemented prototype, and discuss its applications and problems.
Application of Paraphrasing to Programming with Linguistic Expressions
Authors: Kaneko Nozomu ,   Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Onisawa Takehisa
Published: April 2016

This paper describes an interactive programming system that generates computer programs with Japanese linguistic expressions. The system is based on the idea ofprogramming by paraphrasing, which enables users with little knowledge on computer programming to make computer programs with linguistic expressions since paraphrasing is usually done in human everyday language communication. The case-based reasoning method is used for paraphrasing so that the system can obtain the meanings of unknown linguistic expressions used by users. The usefulness of the present system is confirmed by subject experiments on two text editing tasks: a bibliography formatting task and a text-to-HTML conversion task.
Quantification of Multivariate Categorical Data Considering Typicality of Item
Authors: Oh Chi-Hyon ,   Faculty of Liberal Arts and Sciences, Osaka University of Economics and Law, 6-10 Gakuonji, Yao, Osaka 581-8511, Japan, Honda Katsuhiro , Ichihashi Hidetomo ,   Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Nakaku, Sakai, Osaka 599-8531, Japan
Published: April 2016

We propose simultaneously applying homogeneity analysis and fuzzy clustering that simultaneously partitions individuals and items in categorical multivariate datasets. This objective function includes two types of memberships. One is conventional membership representing the degree of membership of each individual in each cluster. The other is an additional parameter that represents typicality of item. A numerical experiment demonstrates that our proposal is useful in quantifying categorical data, taking the typicality of each item into account.
FzMail: Using FIS-CRM for E-mail Classification
Authors: Romero Francisco P. ,   SMILe-ORETO Research Group (Soft Management of Internet e-Laboratory), Olivas José A. , Garcés Pablo J. ,   Department of Information Systems and Technologies, Escuela Superior de Informática, Universidad de Castilla La Mancha, Paseo de la Universidad 4, 13071-Ciudad Real, Spain,   Department of Computer Science and Artificial Intelligence, Universidad de Alicante, Carretera San Vicente del Raspeig s/n, 03080 - Alicante, Spain
Published: April 2016

In this work a brief summary of FIS-CRM (Fuzzy Interrelations and Synonymy Conceptual Representation Model) and its application to intelligent e-mail management are presented. FzMail tool is based on a soft computing methodology for automatic classification of the mailbox into a fuzzy and hierarchical structure of groups of “conceptually related” messages. FIS-CRM is used to conceptually represent messages and it is also used in the process carried out to deal with the incoming messages in order to keep the achieved conceptual organization. The aim is to make an optimum exploitation of the concepts contained in these messages possible. Therefore, we apply Fuzzy Deformable Prototypes for the document clusters representation. The effectiveness of the method has been proved by applying these techniques in an IR system. The documents considered are composed by a set of e-mail messages produced by some distribution lists about different subjects and languages.
Multilayered GMDH-Type Neural Network with Radial Basis Functions and its Application to 3-Dimensional Medical Image Recognition of the Liver
Authors: Kondo Tadashi ,   School of Health Sciences, The University of Tokushima, 3-18-15 Kuramoto-cho, Tokushima 770-8509, Japan, Ueno Junji , Pandya Abhijit S. ,   Computer Sciences & Engineering, Florida Atlantic University, Boca Raton, FL 33431, U.S.A.
Published: April 2016

In this paper, a Group Method of Data Handling (GMDH)-type neural network algorithm with radial basis functions (RBF) is proposed. The proposed algorithm generates optimum RBF network architectures fitting the complexity of nonlinear systems using heuristic self-organization. The number of hidden layers, the number of neurons in hidden layers and relevant input variables are selected by minimizing prediction error defined as Akaike’s Information Criterion (AIC). Various nonlinear combinations of variables are initially generated in each layer and only relevant combinations are selected based on AIC. Hence, the optimum RBF network architecture fitting the complexity of the nonlinear system is obtained. We apply the GMDH-type neural network algorithm with RBF to 3-dimensional medical image recognition of the liver, showing that this algorithm is very easy and useful in 3-dimensional medical image recognition of the liver because the neural network architecture is automatically organized to minimize prediction error based on AIC.
A Semantic Concept Operation Based on Fuzzy Document Ordering System and its Application to Reuter Database
Authors: Ohashi Tadashi ,   Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Nobuhara Hajime , Hirota Kaoru
Published: April 2016

A fuzzy document ordering system (FOCUS) with a shrink operation is proposed to classify vast unknown documents on the Worldwide Web by changing the user’s viewpoint in hierarchical semantic concept structures. The shrink operation, a FOCUS semantic concept, is defined based on the user’s preference vector space and its hierarchical semantic concept structures developed using the concept System Dictionary (CSD) of the Japan Electronic Dictionary Research Institute (EDR). We demonstrate the effectiveness of the shrink operation in document ordering experiments by 5 subjects a using 20 known and 40 unknown documents extracted from the Reuter-21578 Database, i.e., shrinkage of the user’s preference vector space. We confirmed that precision obtained by FOCUS with the shrink operation exceeds that obtained by the conventional method without the shrink operation by over 20%. Processing time by our proposal is just 1/18 that of the conventional method (Pentium III, 550 MHz, Memory 256 MB).
New Fast Principal Component Analysis for Face Detection
Authors: El-Bakry Hazem M. ,   Faculty of Computer Science & Information Systems, Mansoura University, Egypt
Published: April 2016

Principal component analysis (PCA) has different important applications, especially in pattern detection such as face detection and recognition. In real-time applications, response time must be as fast as possible. For this, we propose a new PCA implementation for fast face detection based on the cross-correlation in the frequency domain between the input image and eigenvectors (weights). Simulation results demonstrate that our proposal is faster than the conventional one, and experimental results for different images show good performance.
An Activity Monitor Design Based on Wavelet Analysis and Wireless Sensor Networks
Authors: Tian Qian ,   Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan, Xie Long , Yamauchi Noriyoshi
Published: April 2016

The activity monitor we designed based on wavelet analysis and wireless sensor networks for monitoring human physical condition consists of sensor nodes to sample and transfer data, an FPGA board as a processing center to process data, and a PC to display results. We connect wireless sensor module Ni3 and MEMS accelerometers to make a sensor node small enough to wear and not limited by space. We propose reducing signal noise based on wavelet analysis to ensure a robust data resource and develop a simple wavelet-lifting architecture to decrease the complexity of implementation in the FPGA board. Experimental results demonstrate that our system provides an efficient platform for human physical condition monitoring.
Real-Coded Genetic Algorithm for Solving Generalized Polynomial Programming Problems
Authors: Wu Jui-Yu ,   Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 320, Taiwan, Chung Yun-Kung
Published: April 2016

Generalized polynomial programming (GPP) is a nonlinear programming (NLP) method based on a nonconvex objective function, which is subject to nonconvex inequality constraints. Hence, a GPP problem has multiple local optima in its constrained solution space. General NLP techniques use local optimization, and therefore do not easily solve GPP problems. Some deterministic global optimization approaches have been developed to overcome this drawback of NLP methods. Although these approaches yield a global solution to a GPP problem, they can be mathematically tedious. Therefore, this study presents a real-coded genetic algorithm (RGA), which is a stochastic global optimization method, to find a global solution to a GPP problem. The proposed RGA is used to solve a set of GPP problems. The best solution obtained by the RGA is compared with the known global solution to each test problem. Numerical results show that the proposed RGA converges to a global solution to a GPP problem.
A Novel Neuro-Fuzzy Inference System with Multi-Level Membership Function for Classification Applications
Authors: Lin Cheng-Jian ,   Department of Computer Science and Information Engineering, Chaoyang University of Technology, Taichung, Taiwan 413, R.O.C., Lee Chi-Yung , Chen Cheng-Hung ,   Department of Computer Science and Information Engineering, Nankai Institute of Technology, Nantou, Taiwan 542, R.O.C.
Published: April 2016

In this paper, a novel neuro-fuzzy inference system with multi-level membership function (NFIS_MMF) for classification applications is proposed. The NFIS_MMF model is a five-layer structure, which combines the traditional Takagi-Sugeno-Kang (TSK). Layer 2 of the NFIS_MMF model contains multi-level membership functions, which are multilevel activation functions. A self-constructing learning algorithm, which consists of the self-clustering algorithm (SCA), fuzzy entropy, and the backpropagation algorithm, is also proposed to construct the NFIS_MMF model and perform parameter learning. Simulations were conducted to show the performance and applicability of the proposed model.
Generalized Net Model of Auditory Information Processing
Authors: Chakarov Vihren E. ,   Centre for Biomedical Engineering - Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, Sofia-1113, Bulgaria, Atanassov Krassimir T. , Shannon Anthony G. ,   KvB Institute of Technology, North Sydney, 2060, Australia,   Warrane College, University of New South Wales, Kensington, 1465, Australia
Published: April 2016

In a series of papers we have described the human body, its separate systems, and their behavior using Generalized Nets (GNs). Here we construct a GN-model that represents auditory information processing - the first on our research on the structure and behavior of the human nervous system.
Classifying 3D Real-World Texture Images by Combining Maximum Response 8, 4thOrder of Auto Correlation and Colortons
Authors: Kawewong Aram ,   Imaging Science and Engineering Laboratory, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan, Hasegawa Osamu
Published: April 2016

A novel three-dimensional (3D) texture classification approach is proposed. It combines the use of Maximum Response 8 Filters (MR8) and 4thorder of Auto Correlation Filters (Autocor). These features are combined using Between-Class Error (BCE) information that is learned in a Pre-Testing Stage. Variance (MR8) and invariance (Autocor) of rotation present advantages and disadvantages. Our approach is intended to eliminate those drawbacks and combine favorable features. Our approach performs two single classification methods individually and in parallel. It selects output from the method that obtains the fewest BCEs. Additionally, color from the texture images was considered as an effective additional feature for texture classification. The overall performance of our approach was drastically improved by the addition of that feature. The efficiency of our approach was evaluated by employing over 5500 texture images that correspond to 61 real-world surface samples from the Columbia-Utrecht Reflectance and Texture (CUReT) database [2]. A classification percentage of 97.77% for 61 classes was achieved when Autocor [12] and MR8 [13] were combined. Superior performance was achieved by adding new color feature data: Colortons. Using them, the classification rate was 98.94% for 61 classes.
Interpretable Fuzzy Rules Acquisition of Coupled System Using Interactive Genetic Algorithms
Authors: Lu Dun-Yong ,   School of Mechanical and Vehicular Engineering,          Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, P. R. China, Onisawa Takehisa ,   Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

This paper describes the use of the interactive genetic algorithms to acquire fuzzy control rules with good interpretability for a complex system having dependent variables and non-linear property. A chromosome is coded with integer to represent a fuzzy rule, and individuals composed of various numbers of chromosomes are evolved by GA operations. The acquired fuzzy rules are explained with the linguistic expressions for fuzzy sets. These linguistic expressions are determined through comparing with the standard fuzzy sets of linguistic variables designated in advance. To reduce human fatigue in the individual evaluation process, only quantitative evaluation with fitness functions is given at earlier stage. When a so-called better individual appears, not only quantitative evaluation but qualitative one is used to evaluate both the interpretability and control performance of the acquired fuzzy rules. The presented approach is applied to the control of the coupled system having two control objectives with multi-input/output variables. Simulation experiments show that the approach is feasible to acquire the satisfactory fuzzy rules with good interpretability and good control performance.
Constructing Cost-Sensitive Fuzzy-Rule-Based Systems for Pattern Classification Problems
Authors: Nakashima Tomoharu ,   Department of Computer Science and Intelligent Systems, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan, Yokota Yasuyuki , Ishibuchi Hisao , Schaefer Gerald , Drastich Aleš , Závišek Michal ,   School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham B4 7ET, U.K.,   Faculty of Electrical Engineering and Communication, Brno University of Technology, 61200 Brno, Královo Pole, Kolejní 4, Czech Republic
Published: April 2016

We evaluate the performance of cost-sensitive fuzzy-rule-based systems for pattern classification problems. We assume that a misclassification cost is given a priori for each training pattern. The task of classification thus becomes to minimize both classification error and misclassification cost. We examine the performance of two types of fuzzy classification based on fuzzy if-then rules generated from training patterns. The difference is whether or not they consider misclassification costs in rule generation. In our computational experiments, we use several specifications of misclassification cost to evaluate the performance of the two classifiers. Experimental results show that both classification error and misclassification cost are reduced by considering the misclassification cost in fuzzy rule generation.
A Backward Feature Selection by Creating Compact Neural Network Using Coherence Learning and Pruning
Authors: Kabir Md. Monirul ,   Department of Human and Artificial Intelligence Systems, Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan, Shahjahan Md. , Murase Kazuyuki ,   Department of Electrical and Electronic Engineering, Khulna University of Engineering and Technology, Building no-13E, KUET Campus, Khulna-9203, Bangladesh,   Research and Education Program for Life Science, University of Fukui
Published: April 2016

In this paper we propose a new backward feature selection method that generates compact classifier of a three-layered feed-forward artificial neural network (ANN). In the algorithm, that is based on the wrapper model, two techniques, coherence and pruning, are integrated together in order to find relevant features with a network of minimal numbers of hidden units and connections. Firstly, a coherence learning and a pruning technique are applied during training for removing unnecessary hidden units from the network. After that, attribute distances are measured by a straightforward computation that is not computationally expensive. An attribute is then removed based on an error-based criterion. The network is retrained after the removal of the attribute. This unnecessary attribute selection process is continued until a stopping criterion is satisfied. We applied this method to several standard benchmark classification problems such as breast cancer, diabetes, glass identification and thyroid problems. Experimental results confirmed that the proposed method generates compact network structures that can select relevant features with good classification accuracies.
Edge Detection Model Based on Involuntary Tremors and Drifts of the Eye
Authors: Róka András ,   Computer and Automation Research Institute, Hungarian Academy of Sciences, H-1111 Budapest, Kende u. 13-17, Hungary, Csapó Ádám , Reskó Barna , Baranyi Péter
Published: April 2016

Recent results in retinal research have shown that ganglion cell receptive fields cover the mammalian retina in a mosaic arrangement, with insignificant amounts of overlap in the central fovea. This means that the biological relevance of traditional and widely adapted edge-detection algorithms with convolution-based overlapping operator architectures has been disproved. However, using traditional filters with non-overlapping operator architectures leads to considerable losses in contour information. This paper introduces a novel, tremor- and drift-based edge-detection algorithm that reconciles these differences between the physiology of the retina and the overlapping architectures used by today’s widely adapted algorithms. The algorithm takes into consideration data convergence, as well as the dynamic properties of the retina, by incorporating a model of involuntary eye tremors and drifts and the impulse responses of ganglion cells. Based on the evaluation of the model, two hypotheses are formulated on the highly debated role of involuntary eye tremors: 1) The role of involuntary eye movements has information theoretical implications 2) From an information processing point of view, the functional role of involuntary eye movements extends to more than just the maintenance of action potentials. Involuntary eye-movements may be responsible for the compensation of information losses caused by a non-overlapping receptive field architecture.
A Method to Estimate the Multimedia Communication Bands Based upon Multi-Order Markov Model
Authors: Kojima Tetsuya ,   Tokyo National College of Technology, 1220-2 Kunugidamachi, Hachioji-shi, Tokyo 193-0997, Japan, Enkhtur Lkhamsuren , Fujiwara Akiko , Aono Masahiro ,   University of Tsukuba, 1-1-1 Tennodai, Tsukuba-shi, Ibaraki 305-8577, Japan,   NTT Communications Corporation, NTT Otemachi Bldg. 6F, 3-5 Otemachi 2-Chome, Chiyoda-ku, Tokyo 100-0004, Japan
Published: April 2016

Surplus bands inevitably occur in the multimedia communication bands when VBR encoding is used for data streaming. These bands can be used efficiently by transmitting the other data such as a kind of additive static contents at the same time. However, there are some delays for adding the data, so that the transmission rates of the total data frequently exceed the maximum communication band. This is because each surplus bandwidth is calculated from the formerly observed data. We have proposed a method to estimate the surplus bandwidth by using the multi-order Markov model together with the quantization of the bandwidth. In this paper, we investigate the optimal quantization method for a given streaming video data. In addition, the effectiveness of the proposed method is evaluated under the optimal quantization settings. Discussions for some problems in future studies are also included.
Fuzzy Observable Markov Models for Pattern Recognition
Authors: Tran Dat ,   School of Information Sciences and Engineering, University of Canberra, ACT 2601, Australia, Ma Wanli , Sharma Dharmendra
Published: April 2016

This paper presents a mathematical framework for fuzzy discrete and continuous observable Markov models (OMMs) and their applications to written language, spam email and typist recognition. Experimental results show that the proposed OMMs are more effective than models such as vector quantization, Gaussian mixture model and hidden Markov model.