bluuebunny/crossref_metadata_2025 huggingface dataset:
Integration of Syntactic Analysis and Semantic Interpretation Based on Equivalent Transformation
Authors: Mabuchi Hiroshi ,   Faculty of Software and Information Science, Iwate Prefectural University, 152-52 Sugo, Takizawa, Iwate 020-0193, Japan, Akama Kiyoshi , Ishikawa Takahiko , Koike Hidekatsu ,   Research Division of Large-Scale Computational Systems, Information Initiative Center, Hokkaido University, Kita 11, Nishi 5, Kita-ku, Sapporo 060-0811, Japan,   Division of System and Information Engineering, Hokkaido University, Kita 11, Nishi 5, Kita-ku, Sapporo 060-0811, Japan
Published: April 2016

Making an efficient algorithm for natural language understanding by means of flexible and cooperative interaction between syntactic analysis and semantic interpretation is very difficult. In order to overcome the difficulties, the present paper proposes a new method for designing knowledge processing systems, the computation of which is based on equivalent transformation of declarative descriptions. Basic procedures for syntactic analysis and semantic interpretation are formalized as mutually independent equivalent transformation rules. Rule selection is dynamically determined flexibly during execution by a general principle independent of the domain of sentences.
Phase Transitions in Fuzzy Clustering Based on Fuzzy Entropy
Authors: Yasuda Makoto ,   Dept. of Electrical and Computer Engineering, Gifu National College of Technology, Shinsei-cho, Motosu-gun, Gifu 501-0495, Japan, Furuhashi Takeshi , Okuma Shigeru ,   Dept. of Information Engineering, Mie University, 1515 Kamihama-cho, Tsu 514-8507, Japan,   Dept. of Electrical Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
Published: April 2016

We studied the statistical mechanical characteristics of fuzzy clustering regularized with fuzzy entropy. We obtained Fermi-Dirac distribution as a membership function by regularizing the fuzzy c-means with fuzzy entropy. We then formulated it as direct annealing clustering, and determined the meanings of the Fermi-Dirac function and fuzzy entropy from the statistical mechanical point of view, and showed that this fuzzy clustering is a part of Fermi-Dirac statistics. We also derived the critical temperature at which phase transition occurs in this fuzzy clustering. Then, with a combination of cluster divisions by phase transitions and an adequate division termination condition, we derived fuzzy clustering that automatically determined the number of clusters, as verified by numerical experiments.
Integration of Distributed Robotic Systems
Authors: Karray Fakhri ,   Systems Design Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Soto Rogelio , Guedea Federico , Song Insop ,   Centro de Sistemas Inteligentes, ITESM, Campus Monterrey 64920, Monterrey, N.L., Mexico
Published: April 2016

Creating a distributed and remote operated robotic system is a very challenging and time-consuming task. This paper contains the development issues taking into account when multiple robotic components are integrated to create a distributed robotic application using the standard middleware, Common Object Request Broker Architecture (CORBA) specification. The main idea is to define a set of generic interfaces using the Interface Definition Language (IDL) that can be used with common components in order to facilitate the integration of new components or the modification of them. The generic IDL interfaces are based on wrapper functions, which provide an abstract encapsulated behaviors of the low level components. The approach is shown using two types of arm manipulators and two different pan-tilt model units. Because of the modularity and the abstraction of this approach, this development can be seen as the first stage in constructing more autonomous and complex system.
Possibilistic Uncertainty Propagation and Compromise Programming in the Life Cycle Analysis of Alternative Motor Vehicle Fuels
Authors: Tan Raymond R. ,   Chemical Engineering Department De La Salle University, Manila, 2401 Taft Avenue, 1004 Manila, Philippines, Culaba Alvin B. , Purvis Michael R. I. ,   Mechanical Engineering Department of De La Salle University,   Department of Mechanical & Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK
Published: April 2016

Data noise often does not allow definitive results to be drawn from life cycle assessments (LCAs). The use of possibility theory to model data uncertainty led to the development of an LCA model that is able to derive useful conclusions to a specified level of confidence. The specific decision domain in this study involves the identification and selection of the best environmental option from ten different automotive fuels.
Humanoid Robot HanSaRam: Recent Progress and Developments
Authors: Kim Jong-Hwan ,   Robot Intelligent Technology Lab., Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Gusong-dong, Yusong-gu, Daejon, 305-701, Republic of Korea, Kim Dong-Han , Kim Yong-Jae , Park Kui-Hong , Park Jae-Ho , Moon Choon-Kyoung , Ryu Jee-Hwan , Seow Kiam Tian , Koh Kyoung-Chul ,   A postdoc at RIT Lab in 2002, now with Nanyang Technological University, Singapore,   Mechanical and Control Engineering, Sun moon University
Published: April 2016

The purpose of this paper is to give an overview of recent progress and developments in humanoid robotics. Key research directions and major problems are pointed out and examined in the context of research work on HanSaRam, a humanoid robot undergoing continual design an development in the Robot Intelligence Technology (RIT) Laboratory at KAIST as a Brain Korea project supported by the BK21 School of Information Technology since 2000.
Image Compression and Reconstruction based on Fuzzy Relation and Soft Computing Technology
Authors: Hirota Kaoru ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Nobuhara Hajime , Kawamoto Kazuhiko , Yoshida Shin’ichi
Published: April 2016

A fast image reconstruction method for Image Compression method based on Fuzzy relational equation (ICF) and soft computing is proposed. In experiments using 20 images (Standard Image DataBAse), the decrease in image reconstruction time to 1/132.02 and 1/382.29 are obtained when the compression rate is 0.0156 and 0.0625, respectively, and the proposed method outperforms the conventional one in the Peak Signal to Noise Ratio (PSNR). ICF using nonuniform coders over YUV color space is proposed in order to achieve effective compression. Linear quantization of compressed image data is introduced in order to improve the compression rate. Through experiments using 100 typical images (Corel Gallery, Arizona Directory), PSNR increases at 7.9-14.1% compared with the conventional method under the condition that compression rates are 0.0234-0.0938.
Support Vector Machine and Generalization
Authors: Kurita Takio ,   Neurosceince Research Institute, National Institute of Advanced Indastrial Science and Technology, Umezono 1-1-1, Tsukuba, Ibaraki 305-8568, Japan
Published: April 2016

The support vector machine (SVM) has been extended to build up nonlinear classifiers using the kernel trick. As a learning model, it has the best recognition performance among the many methods currently known because it is devised to obtain high performance for unlearned data. This paper reviews how to enhance generalization in learning classifiers centering on the SVM.
Operation of Spatiotemporal Patterns Stored in Living Neuronal Networks Cultured on a Microelectrode Array
Authors: Kudoh Suguru N. ,   Neuronics Research Group, Special Division for Human Life Technology, National Institute of Advanced Industrial Science and Technology (AIST), 1-8-31 Midorigaoka, Ikeda, Osaka 563-8577, Japan, Taguchi Takahisa ,   Interactions and intelligence, PRESTO, JST, Tokyo, Japan
Published: April 2016

We provided further insights into "biological" pattern detection. In dissociated neurons, we induced synaptic potentiation, which corresponds to an increase in the weight of connection between neurons of an artificial neural network. We also performed a kind of primary "operation" for a spatiotemporal pattern stored in a cultured neural netwo/k. Results suggest that small-scaled living neuronal networks enable to carry out information processing such as pattern detection. Information processing during pattern manipulation is analyzed using living neuronal networks interacting with artificial electric devices. The goal is an artificial living system in which the neural network recognizes environmental patterns around it and controls its growth conditions. The system is useful both in the context of new applied bioelectro technology and basic neuroscience research.
Rapid Discriminative Learning
Authors: Rokui Jun ,   Department of the Interdisciplinary Faculty of Science and Engineering, Shimane University, 1060 Nishikawatsu-cho, Matsue-shi 690-8504, Japan
Published: April 2016

This paper presents MCE/GPD using GPD that is known as a highly effective discriminative learning method. MCE/GPD is an excellent recognition method that is applicable especially to speech recognition, since it excels in recognizing performance and can be used to deal with variable-length vectors. MCE/GPD involves a problem of calculation resulting from c omplicated algorithms making it impractical. In this paper, we propose a learning method to increase speed at learning based on a hierarchical model. We used a hierarchical neural network to evaluate the method’s performance.
Pointing Device Based on Estimation of Trajectory and Shape of a Human Hand in a Monocular Image Sequence
Authors: Odo Satoru ,   Faculty of Humanities, Okinawa University, 555 Kokuba, Naha, Okinawa 902-8521, Japan, Hoshino Kiyoshi ,   Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami-gun, Okinawa 903-0213, Japan,   Institute of Engineering Mechanics and Systems, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

Pointing devices are essential components of graphical user interfaces, and the mouse in particular is widely used because of its intuitive and easy operation. Since it must be directly touched by the user, however, the mouse is restricted in the locations where it can be used. A pointing device consists of a pointing mechanism and a switching mechanism, so the use of a noncontact device to carry out these actions should remove the restriction concerning location. In this study, we investigate the construction of a pointing device that does not impart a feeling of restraint or awkwardness, which estimates the user’s hand shape and position from images captured by a monocular camera, a noncontact device. In this system, the captured image is transformed from a Cartesian coordinate system to a log-polar system to reduce image data and computational cost, and achieve real-time operation without using special hardware other than a regular camera. Higher order local autocorrelation features of the log-polar coordinate space were used to achieve robustness against background change and hand rotation. In addition to direct pointing, the ability to recognize gestures from the hand’s motion trajectory was incorporated to achieve more comfortable user-computer interaction. In experiments using a system consisting of a regular computer and digital video camera, tracking of the hand and estimation of symbolic signs from extracted frames was stable at a practical average speed of 30 ms per frame.
Classification of Remotely Sensed Images Using Independent Component Analysis and Spatial Consistency
Authors: Zeng Xiang-Yan ,   Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa 903-0213, Japan, Chen Yen-Wei , Nakao Zensho ,   Institute of computational Science and Engineering, Ocean University of China
Published: April 2016

We apply independent component analysis (ICA) to learn efficient color representation of remotely sensed images. Among the three basis functions obtained from RGB color space, two are in an opposing-color model by which the responses of R, G and B cones are combined in opposing fashions. This is coincident with the idea of contrasting reflected in many color systems. The interesting point is that there is no summation component that corresponds to illumination in other transforms. Spectral independent components are then used to cluster pixels. After pixel-based classification, we segment an image on the basis of regions by spatial consistency. Experimental results show that this method considerably improves the classification performance of multispectral remotely sensed images.
Composite Fuzzy Measure and its Application to Decision-Making
Authors: Kaino Toshihiro ,   School of Business Administration, Aoyama Gakuin University, 4-4-25 Shibuya, Shibuya-ku, Tokyo 150-8366, Japan, Hirota Kaoru ,   Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
Published: April 2016

In applications using fuzzy measures (on real numbers), it becomes a problem how to evaluate in-between intervals each characterized by a fuzzy measure, especially when the Choquet integral is differentiated in real world problems. A composite fuzzy measure built from fuzzy measures defined on fuzzy measurable spaces has been proposed by Kaino and Hirota using composite fuzzy weights, where the measurable space of this composite fuzzy measure is the direct sum of measurable spaces. An associative, composite fuzzy measure built from a finite number of fuzzy measures is proposed and, in a constructive application, it is applied to the automobile plant capital investment decision-making problem. It is assumed that an automobile company plans to sell a new car. The current plant line has a capacity of 3,200 new cars in addition to current car lines. Using this composite fuzzy measure, differentiation of the Choquet integral becomes a quantitative index for decision-making, which is confirmed by this decision-making experiment.
Computational Intelligence for Modeling Human Sensations in Virtual Environments
Authors: Lee Ka Keung ,   Advanced Robotics Lab, Department of Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, Hong Kong, China, Xu Yangsheng
Published: April 2016

In this research, computational intelligence techniques are applied towards the modeling of human sensations in virtual environments. We specifically focus on the following important questions: (1) how to efficiently model the relationship between human sensations and the physical stimuli presented to humans, (2) how to validate the human sensation models, and (3) how to reduce the size of the input data when it gets large and how to select the information which is most important to human sensation modeling. In order to provide an experimental testbed for the implementation of the proposed learning and analysis techniques, a full-body motion virtual reality interface capable of recording human sensations is developed. We propose using cascade neural networks with node-decoupled extended Kalman filter training for modeling human sensation in virtual environments. For the purpose of sensation model validation, we propose using a stochastic similarity measure based on hidden Markov models to calculate the relative similarity between model-generated sensation and actual human sensation. Next, we investigate a number of feature extraction and input selection techniques for reducing the input data size in human sensation modeling. We propose and develop a new input selection method based on independent component analysis, which is capable of reducing the data size and selecting the stimuli information that is most important to the human sensation.
Intelligent Sensor Fusion in Robotic Prosthetic Eye System
Authors: Gu Jason J. ,   Department of Electrical and Computer Engineering Dalhousie University, Halifax, NS B3J 2X4, Canada, Meng Max , Cook Albert , Liu Peter Xiaoping ,   Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong,   Dean of Faculty of Rehabilitation Medicine University of Alberta, 3-48 Corbett Hall, Edmonton, AB T6G 2G4, Canada,   Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada K1S 5B6
Published: April 2016

This paper is concerned with the design, sensing and control of a robotic prosthetic eye that moves horizontally in synchronization with the movement of the natural eye. Two generations of robotic prosthetic eye models have been developed. Theoretical issues on sensor failure detection and recovery, and signal processing techniques used in sensor data fusion are studied using statistical methods and artificial neural network based techniques. In addition, practical control system design and implementation using micro controllers are studied and implemented to carry out the natural eye movement detection and artificial robotic eye control tasks. Simulation and experimental studies are performed and the results are included to demonstrate the effectiveness of the research project reported in this paper.
Novel Approach to Decision-Tree Construction
Authors: Jin-Mao Wei ,   Research Institute of Computational Intelligence, School of Physics, Northeast Normal University, Changchun, Jilin, P. R. China, 130024, Shu-Qin Wang , Ming-Yang Wang
Published: April 2016

A new approach is presented, in which rough set theory is applied to select attributes as nodes of a decision tree. Initially, dataset is partitioned into subsets based on different condition attributes, then an attribute is chosen as a node for branching when the size of its corresponding implicit region is smaller than that of all other attributes. This approach is compared to the entropy-based method on some datasets from the UCI Machine Learning Database Repository, which instantiates the performance of the rough set approach. Statistical experiments showed that the proposed approach is feasible for decision-tree construction.
Fuzzy Aggregation Method Using Fisherface and Wavelet Decomposition for Face Recognition
Authors: Kwak Keun-Chang ,   School of Electrical and Electronic Engineering, Chungbuk National University, 48 Gaeshin-dong Heungduk-gu Chongju 361-703, Korea, Pedrycz Witold , Go Hyoun-Joo , Chun Myung-Geun ,   Dept. of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada T6G 2G7,   Systems Research Institute, Polish Academy of Sciences, 01-447 Warsaw, Poland
Published: April 2016

In this paper, we propose the fuzzy aggregation method for face recognition based on subimage sets decomposed by wavelets. The proposed approach consists of four main stages. The first stage uses the wavelet decomposition that helps extract intrinsic features of face images. The second stage of the approach applies a fisherface method to these four subimages obtained by wavelet decomposition. The choice of the fisherface method in this setting is motivated by its insensitivity to large variation in light direction, face pose, and facial expression. The last two phases are concerned with the aggregation of the individual classifiers by means of the fuzzy integral. The experiments use an n-fold cross-validation to assure high consistency of the classification results. The experimental results obtained for the Yale face databases reveal that the approach presented in this paper yields better classification performance in comparison with the results obtained by other recognition methods.
Intelligent Logo Watermarking Based on Independent Component Analysis
Authors: Hien Thai Duy ,   Faculty of Engineering, University of the Ryukyus, Okinawa 903-0213, Japan, Nakao Zensho , Chen Yen-Wei ,   College of Information Science and Engineering, Ritsumeikan University, Shiga 525-8577, Japan,   Institute for Computational Science and Engineering, Ocean University of China, China
Published: April 2016

We present new intelligent logo watermarking based on independent component analysis (ICA) in which a binary logo watermark is embedded in a host image in a wavelet domain. To improve robustness, an image adaptive watermarking algorithm is applied by a stochastic approach based on a noise visibility function (NVF). The algorithm design, evaluation, and experimentation are described. Experimental results show that the logo watermark is perfectly extracted by ICA with excellent invisibility and with robustness against various image and digital processing operators and almost all compression algorithms such as Jpeg, jpeg 2000, SPIHT, EZW, and principal component analysis (PCA) based compression.
Simultaneous Application of Fuzzy Clustering and Quantification with Incomplete Categorical Data
Authors: Honda Katsuhiro ,   Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka, Japan, Nakamura Yoshihito , Ichihashi Hidetomo
Published: April 2016

This paper proposes the simultaneous application of homogeneity analysis and fuzzy clustering with incomplete data. Taking into account the similarity between the loss function for homogeneity analysis and the least squares criterion for principal component analysis, we define the new objective function in a formulation similar to linear fuzzy clustering with missing values. Numerical experiments demonstrate the feasibility of the proposed method.
A Study on Supplier Evaluation and Selection Method Based on Dependence
Authors: Ju Jong-Moon ,   Department of Industrial Engineering, Graduate School of Kyungnam University, Hwang Seung-Gook ,   Division of Techno-Management, Kyungnam University,
Published: April 2016

Development of information and technology and the Internet has provided a variety of expanded connections between manufacturers and consumers. Enabling customers to directly transfer voice to manufacturers, Research on how manufacturers respond to customer needs, however, remains inadequate. We present, a method in which the optimal supplier is chosen based on customer needs from the buyer’s viewpoint. We also designed a way to evaluate and choose the optimal supplier based on consumer requirements by analyzing customer needs and evaluated data.
A Proposal of GA Using Symbiotic Evolutionary Viruses and its Virus Evaluation Techniques
Authors: Sakakura Yoshiaki ,   Frontier Doctoral Program in Science and Engineering, Ritsumeikan University, Taniguchi Noriyuki , Hoshino Yukinobu , Kamei Katsuari ,   Graduate School of Science and Engineering, Ritsumeikan University,   Human and Computer Intelligence, College Information Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan
Published: April 2016

In this paper, we propose a Genetic Algorithm (GA) using symbiotic evolutionary viruses based on both the building block hypothesis and the virus theory of evolution. The proposed GA aims to control the destruction of building blocks by discovery, maintenance, and propagation of building blocks based on virus operation. We prepare a group of individuals and a group of viruses. The group of individuals searches for solutions and the group of viruses searches for building blocks. These searches are done based on the symbiotic relation of both groups. Also, our GA has two types of virus evaluation technique. In one type, each virus is evaluated by the difference of the fitness of an individual before and after virus infection. In the other type, all viruses are evaluated by the difference of the fitness of an individual before and after infection of all viruses. We applied the proposed GA to a minimum value search problem using a test function with some local minima far from the optimum. Finally, we also discuss the search behavior in the proposed GA based on each virus evaluation technique.
Computational Cybernetics
Authors: Elmenreich Wilfried ,   Vienna University of Technology, Institut für Technische Informatik, Treitlstrasse 1-3/182-1, A-1040 Vienna, Austria, Rudas Imre J. ,   Budapest Polytechnic, Doberdó út 6, H-1034 Budapest, Hungary
Published: April 2016

This issue contains selected papers from the International IEEE Conference on Computational Cybernetics that took place in August 2003 in Hungary at the site of lake Balaton. Computational Cybernetics is the synergetic integration of Cybernetics and Computational Intelligence techniques. Cybernetics was defined by Wiener as "the science of control and communication, in the animal and the machine". The word "cybernetics" itself stems from the Greek "kybernetes" that means pilot or governor. Thus, the science of computational Cybernetics is especially concerned with the comparative study of automatic control systems. Furthermore, Computational Cybernetics covers not only mechanical, but biological (living), social and economical systems and for this uses computational intelligence based results of communication theory, signal processing, information technology, control theory, the theory of adaptive systems, the theory of complex systems (game theory, operational research), and computer science. We have selected 14 papers from the conference covering the fields of system design and modeling, neural networks, and fuzzy control, which resemble the great variety of computational cybernetics. While it is sometimes difficult to integrate over these differing fields, we expect the evolution of future intelligent systems at the service of mankind by the synergetic integration of these different areas. It is our hope that the papers in this issue will inspire and help our readers in the development of advanced intelligent systems.
Motion-Based Template Matching for Obstacle Detection
Authors: Kawamoto Kazuhiko ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Mail-Box G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Ohnishi Naoya , Imiya Atsushi , Klette Reinhard , Hirota Kaoru ,   Institute of Media and Information Technology, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan,   Software Research Division, National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan,   Centre for Image Technology and Robotics, University of Auckland, Tamaki Campus, Building 731, Auckland, New Zealand
Published: April 2016

A matching algorithm that evaluates the difference between model and calculated flows for obstacle detection in video sequences is presented. A stabilization method for obstacle detection by median filtering to overcome instability in the computation of optical flow is also presented. Since optical flow is a scene-independent measurement, the proposed algorithm can be applied to various situations, whereas most of existing color- and texture-based algorithms depend on specific scenes, such as roadway and indoor scenes. An experiment is conducted with three real image sequences, in which a static box or a moving toy car appears, to evaluate the performance in terms of accuracy under varying thresholds using a receiver operating characteristic (ROC) curve. For the three image sequences, the ROC curves show, in the best case, that the false positive fraction and the true positive fraction is 19.0% and 79.6%, 11.4% and 84.5%, 19.0% and 85.4%, respectively. The processing time per frame is 19.38msec. on 2.0GHz Pentium 4, which is less than the video-frame rate.
Development of Fuzzy Controllers with Dynamics Regarding Stability Conditions and Sensitivity Analysis
Authors: Precup Radu-Emil ,   "Politehnica" University of Timisoara, Department of Automation and Industrial Informatics, Bd. V. Parvan 2, RO-300223 Timisoara, Romania, Preitl Stefan , Korondi Péter ,   Budapest University of Technology and Economics, Integrated Intelligent Systems Laboratory, P.O.Box 91, H-1521 Budapest, Hungary
Published: April 2016

The paper presents development techniques for fuzzy controllers with dynamics and with predictive effect dedicated to some electrical drives with variable inertia. The development techniques are presented regarding the stability analysis based on programs developed in Matlab & Simulink. In addition, it presents points of view regarding the sensitivity analysis on the basis of some sensitivity models associated to the control system.
A Combined Solution of the Inverse Kinematic Task in the Vicinity of the Singularities
Authors: Rudas Imre J. ,   John von Neumann Faculty of Informatics, Budapest Polytechnic, Népszínház u. 8, H-1081 Budapest, Hungary, Tar József K. , Bitó János F. , Szeghegyi Ágnes , Kozlowski Krzysztof R. ,   Károly Keleti Faculty of Economics, Budapest Polytechnic, Népszínház u. 8, H-1081 Budapest, Hungary,   Chair of Control, Robotics, and Computer Science, Poznan University of Technology, Poznan, 60-965, Ul. Piotrowo 3a, Poland
Published: April 2016

In the case of the traditional differential approach of solving the inverse kinematic task, depending on the desired trajectory that may approach, reach, and cross the boundaries of non-singular domains or domains of different degree of singularity, certain joint velocities may take huge values. Within the singularity it may happen that the desired task cannot exactly be solved, and that this imprecise solution has one or more degree of freedom in its ambiguity. The motion planner provided with end-point position and orientation data with respect to the workshop’s Cartesian frame does not have satisfactory information for locally resolving ambiguity. The rather modern approaches follow global way of thinking and apply Genetic Algorithms or similar evolutionary methods requiring huge computational power. The here presented approach is a compromise between these essentially different cases. For non-singular points it applies a fast algorithm to the differential solution, while near and in the singularities the Complex Algorithm combining the primary (that is tracking the prescribed data as precisely as possible) and secondary (complementary aspects applied in ambiguity resolution) requirements in an efficient way. The method is illustrated by calculations for particular trajectories in the case of a 6 DOF robot arm.
A Test Model for Hardware and Software Systems
Authors: Sziray József ,   Department of Informatics, Széchenyi University, Egyetem tér 1, H-9026 Györ, Hungary
Published: April 2016

The paper is concerned with the general aspects of testing complex hardware and software systems. First a mapping scheme as a test model is presented for an arbitrary given system. This scheme serves for describing the one-to-one correspondence between the input and output domains of the system, where the test inputs and fault classes are also involved. The presented test model incorporates both the verification and the validation schemes for hardware and software. The significance of the model is that it alleviates the clear differentiation between verification and validation tests, which is important and useful in the process of test design and evaluation. On the other hand, this model provides a clear overview on the various purpose test sets, which helps in organizing and applying these sets. The second part of the paper examines the case when the hardware and software are designed by using formal specification. Here the consequences and problems of formal methods, and their impacts on verification and validation are discussed.
Possibilities for Application of Associative Objects with Built-in Intelligence in Engineering Modeling
Authors: Horváth László ,   John von Neumann Faculty of Informatics, Budapest Tech Polytechnical Institute, N&eactue;pszínház u. 8, H-1081 Budapest, Hungary, Rudas Imre J.
Published: April 2016

An analysis is given in this paper for definition of features of environment adaptive model objects having the capability of description of mutual effects of engineering objects inside and associative engineering objects from the outside world. The final aim of the research is development of environment adaptive model objects for integration in or communication with product models. The model objects, targeted by the reported research, are able to carry and interpret all information and knowledge necessary for their processing. Creation and application of objects during engineering decision procedures as well as revision of earlier decisions during development of products are considered. This paper discusses concepts and features of intelligent model objects as they applied for environment-active modeling. It also reports an analysis of effects of changes in the model environment on model of intelligent engineering object. Following this, paper explains relationships within model objects for the purpose of engineering activities in mechanical systems. Finally, some considerations about implementation of the proposed modeling are concluded.
Special Issue on Selected Papers from InTech'03
Authors: Santiprabhob Pratit ,   Director, Intelligent Systems Research Laboratory, Faculty of Science and Technology, Assumption University, Bangkok 10240, Thailand, Theera-Umpon Nipon , Auephanwiriyakul Sansanee ,   Department of Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand,   Department of Computer Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand
Published: April 2016

On behalf of the Fuzzy systems and Intelligent technologies Research Society of Thailand (FIRST), Chiang Mai University, and Assumption University of Thailand, which have jointly organized the 4th International Conference on Intelligent Technology (InTech), we thank the editorial board of the Journal of Advanced Computational Intelligence and Intelligent Informatics for devoting part of this issue to selected papers from the Conference. The 4th InTech was held during December 17-19, 2003, in the lovely northern Thai city of Chiang Mai, becoming the most successful InTech ever, with over 110 papers accepted after stringent reviews for presentation at the Conference. Papers selected for publication in this special issue have been revised by their authors based on Journal guidelines. These papers detail a variety of applications of different intelligent technologies, ranging from data classification, system identification, and signal processing to full-text search and robotics. The technologies themselves are also varied, including fuzzy logic, genetic algorithms, regression, and data classification. We thank our reviewers, who have worked tirelessly in reviewing papers for the conference and selecting papers for this special issue. We also thank Professors Kaoru Hirota and Hung T. Nguyen for their ongoing support for InTech since its inception in 2000.
Comparison of Linguistic and Regular Hard C-Means in Postoperative Patient Data
Authors: Auephanwiriyakul Sansanee ,   Computer Engineering Department, Chiang Mai University, Chiang Mai 50200, Thailand, Theera-Umpon Nipon ,   Electrical Engineering Department, Chiang Mai University, Chiang Mai 50200, Thailand
Published: April 2016

Classification is one of the main topics in pattern recognition. Generally, classification problems deal with numeric data. However, there are uncertainties in the data frequently, such as data collected in management questionnaires, postoperative patient data, etc. Hence, classification problems on linguistic data are challenging. In this paper, we compare the performance of the linguistic Hard C-Means (LHCM) with the regular Hard C-Means (HCM) through the postoperative patient data. We found that the LHCM performs better than the regular HCM in terms of the classification rate. In addition, we are able to interpret each cluster attribute by the input linguistic label.
Leeway Prediction of Oceanic Disastrous Target via Support Vector Regression
Authors: Theera-Umpon Nipon ,   Department of Electrical Engineering, Faculty of Engineering, Chang Mai University, Chiang Mai 50200, Thailand, Boonprasert Udomsak ,   The Royal Thai Navy, Sattahip, Chonburi 20180, Thailand
Published: April 2016

This paper demonstrates an application of support vector machine (SVM) to the oceanic disasters search and rescue operation. The support vector regression (SVR) for system identification of a nonlinear black-box model is utilized in this research. The SVR-based ocean model helps the search and rescue unit by predicting the disastrous target’s position at any given time instant. The closer the predicted location to the actual location would shorten the searching time and minimize the loss. One of the most popular ocean models, namely the Princeton ocean model, is applied to provide the ground truth of the target leeway. From the experiments, the results on the simulated data show that the proposed SVR-based ocean model provides a good prediction compared to the Princeton ocean model. Moreover, the experimental results on the real data collected by the Royal Thai Navy also show that the proposed model can be used as an auxiliary tool in the search and rescue operation.
Separability Conditions for Multilayer Nets Having Solutions and Convergent Superiority of Bipolar Nets
Authors: Shiratsuchi Hiroshi ,   Faculty of Engineering, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan, Gotanda Hiromu , Inoue Katsuhiro , Kumamaru Kousuke ,   Kinki University School of Humanity-Oriented Science and Engineering,   Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology
Published: April 2016

Separability conditions are formulated for multilayer nets to have solutions by a set of normal vectors orthogonal to separation hyperplanes. Comparing separability conditions to distributions of normal vectors with weights and biases initialized ordinarily by random numbers with a zero mean, we found that bipolar nets are superior to unipolar nets in convergence of the back propagation learning initialized in such an ordinary manner.
Reinforcement Learning for Online Industrial Process Control
Authors: Govindhasamy James J. ,   Intelligent System and Control Research Group, Queen's University Belfast, Belfast BT9 5AH, Northern Ireland, United Kingdom, McLoone Seán F. , Irwin George W. , French John J. , Doyle Richard. P. ,   Department of Electronic Engineering, National University of Ireland Maynooth Maynooth, Co. Kildare, Ireland,   Seagate Technology Media Ltd., 99 Dowland Road, Aghanloo Industrial Estate Limavady BT49 OHR, Northern Ireland, United Kingdom
Published: April 2016

Reinforcement learning, in the form of Adaptive Critic Designs (ACDs), have the ability to analyse or evaluate a situation and respond to it accordingly. They offer an excellent alternative for adaptively controlling and optimising the highly nonlinear processes found in industry. Here, an enhanced implementation of the action dependent adaptive critic design (ADAC) of Si and Wang [9] is investigated for modelling and control of an industrial grinding process used in the manufacture of hard disk drive platters. This study, one of the first reported industrial applications of this emerging technology, shows that the proposed ADAC control scheme can achieve a 33% reduction in platter rejects compared to an existing proprietary controller.
Dynamic Visualization of Information: From Database to Dataspace
Authors: St-Jacques Claude ,   University of Ottawa, Ottawa, ON, KIN 6N5, Canada, Paquin Louis-Claude ,   Université du Québec à Montréal, Montréal, QC, H3C 3P8, Canada
Published: April 2016

This paper explores a generalization of the Teleweb project [1] through an XML protocol. The research aims to provide friendly online access to large multimedia databases where the "content or topic" of the media units of texts, sounds or video, is indexed with an arbitrary set of descriptors. Among others, the deliverables of Teleweb consist of a mapping algorithm for a dynamic broadcast and a visualization interface. To go beyond the cognitive limitations of listings as results of database requests, we design an original solution: a topological representation into a 3D image of the relationship among the respective units. Instead of browsing through lists of thousands of units, ten at a time, the user is engaged in a dynamically created immersive environment, where he can control his own navigation over the information. To model the relationship of proximity between units, we use the soft computing capability of the fuzzy logic. Converted into topological data, the degree of the relationship of one unit with another is used to generate a space by soliciting the user's cognitive skills of visual perception instead of by memorization. The database then becomes a data-space.
Combining Argumentation and Web Search Technology: Towards a Qualitative Approach for Ranking Results
Authors: Chesñevar Carlos Iván ,   Department of Computer Science, University of Lleida, 25001 Lleida, Spain, Maguitman Ana Gabriela ,   Computer Science Department, Indiana University, Bloomington, IN 47405-7104, USA
Published: April 2016

Several techniques for improving web search have been developed over the last years. Most existing approaches are still limited, mainly due to the absence of qualitative criteria for ranking results and insensitivity to user preferences for guiding the search. At the same time, defeasible argumentation evolved as a successful approach in AI to model commonsense qualitative reasoning with applications in many areas, such as agent theory, knowledge engineering and legal reasoning. This paper presents ARGUENET, a recommender system that classifies search results according to preference criteria declaratively specified by the user. The proposed approach integrates a traditional web search engine with a defeasible argumentation framework.
Automated 3D Surface Display for Evaluating Meniscal Tears Aided by Fuzzy Expert System
Authors: Hata Yutaka ,   Division of Computer Engineering, Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji 671-2201, Japan, Kobashi Syoji , Kondo Katsuya , Nakano Tomoharu ,   Chair of BISC Special Interest Group on Medical Imaging, BISC Group, Computer Science Division, University of California at Berkeley, Berkeley, CA 94720-1776, USA,   Cancer and Thoracic Surgery, Graduate School of Medicine, Okayama University, Japan
Published: April 2016

This paper proposes an automated procedure for segmenting menisci in MR images of a human knee aided by fuzzy expert system. A three-dimensional (3D) MR volumetric images composed of many slice images consists of several parts: bone marrow, meniscus, periarticular liquor, cartilage and others. We employ both T1-weighted and T2-weighted MR images to identify the menisci with high accuracy. After a registration between these images is manually done on a computer display, our procedure aided by fuzzy expert system can automatically segment meniscal regions from 3D MR images. Physicians can observe the 3D shapes of meniscal tears from any point of view on the display. We examined five subjects including a normal knee and three injured knees. The all meniscal regions were significantly identified, and these 3D shapes were displayed. The patterns of meniscal tears were identified on the display for all subjects. In a subject, since the preoperative and postoperative 3D meniscal shapes were clearly viewed, we easily recognized the operated meniscal regions. Thus, the system can provide useful information for diagnosing meniscal tears.
Taxonomy of Atomic Actions for Home-Service Robots
Authors: Kim Hyunseok ,   Digital Media Laboratory, Information and Communications University,  Dogok-dong, Gangnam-gu, Seoul 135-854, Korea, Jung Yuchul , Hwang Yong K.
Published: April 2016

In household environments, robots are expected to conduct many tasks. It is difficult, however, to write programs for all tasks beforehand ddue to task diversity and changing environmental conditions. One basic task of developing autonomous multifunctional robots is to define a set of basic robot actions that are executed unambiguously and checked for completion. A task planner then uses these actions to accomplish complex tasks that home-service robots are expected to do. This paper first proposes a set of tasks for first-generation home-service robots, then systematically decomposes them into sequences of smaller but meaningful actions called molecular actions. Molecular actions are then broken down into yet more primitive actions called atomic actions. Because vision, sound, range sensors, and force sensors are the main means of monitoring task progress and ompletion, atomic actions are classified based on the complexities and frequencies of the sensing algorithms used. The resulting taxonomy of atomic actions serves as a set of basic building blocks for a knowledge-based task planner. Its advantages are verified and demonstrated through experiments.
Using Attenuation Coefficient Generating Function in Parallel Execution of Neural Networks for Solving SAT
Authors: Zhang Kairong ,   Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan, Nagamatu Masahiro
Published: April 2016

The satisfiability problem (SAT) is one of the most basic and important problems in computer science. We have proposed a recurrent analog neural network called Lagrange Programming neural network with Polarized High-order connections (LPPH) for the SAT, together with a method of parallel execution of LPPH. Experimental results demonstrate a high speedup ratio. Furthermore this method is very easy to realize by hardware. LPPH dynamics has an important parameter, the attenuation coefficient, known to strongly affect LPPH execution speed, but determining a good value of attenuation coefficient is difficult. Experimental results show that the parallel execution reduces this difficulty. In this paper we propose a method to assign different values of attenuation coefficients to LPPHs used in the parallel execution. The values are generated uniformly randomly or randomly using a probability density function.
Evolutionary Pose Measurement by Stereo Model Matching
Authors: Song Wei ,   Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-0017, Japan, Mae Yasushi , Minami Mamoru ,   Dept. of Human and Artificial Intelligent System, University of Fukui, 3-9-1 Bunkyo, Fukui 910-0017, Japan
Published: April 2016

This paper presents a pose measurement method of a 3-D object. The proposed method utilizes an evolutionary search technique of the genetic algorithm (GA) and a fitness evaluation based on a matching stereo model, named as surface-strips model here. The unprocessed gray-scale image, called a raw image, is used in order to perform recognition of a target using known target object shape. Here, the problem to recognize the position/orientation of the target object is converted to an optimization problem of a fitness function that consists in the computation of the brightness difference between an internal surface and a contour-strips. In order to evaluate the proposed 3-D recognition method, experiments to detect position/orientation of a rectangular solid block have been conducted to show its effectiveness of recognizing objects in static image. Furthermore, experiments to recognize a ball on a turning table by a robot manipulator equipped with two hand-eye cameras have also been conducted to show the effectiveness of this method for Real-Time visual servoing.
Analysis and Simulation of Group Behavior Using a Dynamic Sphere of Influence
Authors: Taki Tsuyoshi ,   School of Life System Science and Technology, Chukyo University, 101 Tokodachi, Kaizu-cho, Toyota, Aichi 470-0393, Japan, Hasegawa Junichi
Published: April 2016

To evaluate or predict human behavior, extraction of characteristic patterns from actual crowd scenes and crowd simulation in different situations based on general human behavior model are needed. We use changes in a spatial feature formed by individual movement called a "dominant region", a type of dynamic personal space. In the paper, a basic concept and calculation of the dominant region and its applications are presented. Experiments show that the proposed feature is useful in evaluating and simulating human behavior.