bluuebunny/crossref_metadata_2025 huggingface dataset:
Temporal Abstraction for Long-Term Test Changes in the Hepatitis Domain
Authors: Kawasaki Saori ,   Japan Advanced Institute of Science and Technology, Ishikawa, 923-1292 Japan, Nguyen Trong Dung , Ho Tu Bao
Published: April 2016

Temporal abstraction (TA) transforms temporal data into a symbolic interval-based representation of data. Most TA methods is applicable to data collected regularly over short periods. We proposed a TA method for temporal data irregularly collected over long periods. The core of our method is the notion of "change of states" and algorithms to detect them. We applied the method to analyze a hepatitis database with results evaluated by medical experts.
Generalized Associative Memory Models: Their Memory Capacities and Potential Application
Authors: Yap Teddy N. ,   Software Technology Department College of Computer Studies De La Salle University Professional Schools, Inc., 2401 Taft Avenue 1004 Manila, Philippines, Jr.  , Azcarraga Arnulfo P. ,   Program for Research into Intelligent Systems School of Computing
Published: April 2016

The Hopfield and bi-directional associative memory (BAM) models are well developed and carefully studied models for associative memory that are patterned after the memory structure of the animal brain. Their basic limitation is that they can only perform associations between at most two sets of patterns. Several different models for generalized associative memory are proposed. These models are all extensions or generalizations of the Hopfield and BAM models that can perform multiple associations. Extensive software simulations are conducted to evaluate the different models, using the memory capacity as basis for comparing their performance. Lastly, potential application of these models as data fusion systems is explored.
Hybrid Fuzzy Logic Strategy for Soccer Robot Game
Authors: Maravillas Elmer A. ,   Department of Mechanical Engineering, Reyes Napoleon H. , Dadios Elmer P. ,   Graduate Studies, College of Computer Studies,   Department of Manufacturing Engineering and Management, De La Salle University, 2401 Taft Avenue, Manila, 1004 Philippines
Published: April 2016

This paper presents a control strategy for the robot soccer game goalie using hybrid fuzzy logic systems. The strategy adopts the divide and conquer concept by decomposing the goalie’s task of defending the goal into four (4) categories. Consequently, each category is characterized by different goalie-ball situations and will be handled by a separate rule-base. The first fuzzy system takes the x-coordinates of the robot and the ball then outputs the category number that determines the rule-base to be used in the second fuzzy system. The second fuzzy system handles the goalie’s movements. It takes the current y-coordinate of the goalie-robot and the ball then outputs the y-coordinate of the goalie’s next position (destination) which is located along its line-of-action (a line with predefined x-coordinate where the goalie moves back and forth just in front of the goal it is defending). Experiment shows that this strategy is feasible, efficient, and robust.
Tool Operation Recognition Based on Robust Optical Flow and HMM from Short-Time Sequential Image Data
Authors: Sakaino Hidetomo ,   NTT Communications Corp., 3-20-2 Nishishinjuku, Shinjuku-ku, Tokyo, Japan, Yanagisawa Yutaka , Satoh Tetsuji ,   NTT Communication Science Labs., 2-4 Hikari-dai, Seika-cho, Soraku-gun, Kyoto, Japan
Published: April 2016

This paper discusses a method to precisely recognize which tool is to be used based on the optical flow and HMM from short-time sequential images that operate a variety of hand-operated carpenter tools in the real environment. Operation recognition from a single-eye camera includes problems on differences in the difficulty of fixing the shape of the tool and poor motion periodicity due to occlusion of the fingers, back of the hand, and arm of the operator. This paper models operation without separating the integrated motions of the hand and tool and recognizes it with four tools divided into different categories from these motions. The optical flow method via the nonlinear robust function is used to suppress possible error caused by discontinuous motion components, HMM with a flexible time axis is applied to implement learning and recognition. The average vector of the optical flow mapped into the conversion diagram was designed to output symbol numbers for the generation of symbol time series. The three subjects have been asked to operate given tools for conducting learning recognition experiments. The number of input and output symbol has been varied for comparison. This results in a maximum of 100% recognition on the average for learning and recognition by the same person and in a maximum of 88.6% for learning and recognition by different persons. This method has been proven robust and effective because an average of 79.4% or higher recognition rate has been obtained even for short data of input symbol 5 (equivalent to 0.2 seconds) difficult to recognize.
Extraction of Motion Characteristics Corresponding to Sensitivity Information Using Dance Movement
Authors: Kamisato Shihoko ,   University of Ryukyus, Senbaru 1, Nishihara, Okinawa 903-0213, Japan, Odo Satoru , Ishikawa Yoshino , Hoshino Kiyoshi ,   Japan Meteorological Agency, Otemachi 1-3-4, Chiyoda-ku, Tokyo 100-8122, Japan,   Institute of Engineering Mechanics and Systems, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

This study is intended to quantitatively clarify the relationship between the motion characteristics behind the human motion in complicated motions like dancing and the subjective impressions of the observer. It examines the impression structures related to the motion of a determined body part of dancing and considers the motion characteristics giving a specific impression. To compare and consider the impression structures related to the motion of a body part, the authors made a principal component analysis, one of the multi-variable analytic methods, to check the arm and leg motions for any differences in the impression structure. Similarly, they considered any differences in the impression structures due to the experience knowledge of dance. Next, to consider any differences in the physical features that have effect on the impressions, they quantified the motion characteristics and used a heavy regression analysis to estimate the common motion characteristics that give the same impressions. In addition, they used the characteristics of the legs that are parts of the motion presumed to have the relationship with the impressions to reproduce the motion with CG for the consideration of these impressions. As a result, when the impressions of the arm and leg motions were compared, four impression evaluation axes of "like-dislike," "dynamic-static," "individual-monotonous," and "collected-wide" were extracted as the axes that evaluated the same impressions, but the impressions of "hard-soft" and "heavy-light" were extracted only from those of each arm or leg motion. When the evaluation axes of the impressions were compared between groups with differences in the knowledge of dance, five similar evaluation axes were extracted for each of them and there was no big difference in the impression structures themselves, but significant differences were found for the evaluation of impressions between the words used for the sensitivity evaluation in difference in knowledge. Attention was paid to the characteristics of the motion generating each impression to show the relationship between motion characteristics and subjective impressions.
Joint Audio-Visual Tracking Based on Dynamically Weighted Linear Combination of Probability State Density
Authors: Tsuchida Masaru ,   NTT Communication Science Laboratories, NTT Corporation, 3-1, Morinosato-Wakamiya, Atsugi 243-0198, Japan, Kawanishi Takahito , Murase Hiroshi , Takagi Shigeru ,   Currently, NTT-DATA Corporation, Kayabacho Tower Bldg., 1-21-2 Shinkawa, Chuo-ku, Tokyo 104-0033, Japan,   Currently, Graduate School of Information Science, Nagoya University, Furo-cho, Chigusa-ku, Nagoya 464-8603, Japan
Published: April 2016

This paper proposes a method that can be applied to speaker tracking under stabilized, continuous conditions using visual and audio information even when input information is interrupted due to disturbance or occlusion caused by the effects of noise or varying illumination. Using this method, the position of a speaker is expressed based on a likelihood distribution that is obtained through integration of visual information and audio information. First, visual and audio information is integrated as as a weighted linear combination of probability density distribution, which is estimated as a result of the observation of the visual and audio information. In this case, the weight is taken as a variable, which varys in proportion to the maximum value of probability density distributions obtained for each type of information. Next, the result obtained as described above and the weighted linear combination of the distribution in the past are obtained, and the result thus obtained is taken as the likelihood distribution related to the position of the speaker. By changing the weight dynamically, it becomes possible to select the type of information freely or to add weight and, accordingly, to conduct stabilized, continuous tracking even when the speaker cannot be detected momentarily due to occlusion, voice interruption, or noise. We conducted a series of experiments on speaker tracking using circular microphone array and an omni-directional camera. In this way, we have succeeded in confirming it possible to perform stabilized tracking on speakers continuously in spite of occlusion or voice interruption.
Behavior Learning and Animation Synthesis of Falling Flat Objects
Authors: Aoki Kohta ,   Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Hasegawa Osamu , Nagahashi Hiroshi ,   Imaging Science and Engineering Laboratory, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8503, Japan,   PRESTO, Japan Science and Technology Corp. (JST)
Published: April 2016

In this paper, we describe an approach to learning patterns from sample data sequences and generating new data sequences through learned models. The target application of this work is the animation of natural phenomena, especially falling behavior of flat objects. The natural object or phenomenon to be animated is recorded using one camera, and its characteristic behavior is captured. Feature vectors are defined as the representation of behavior and are automatically extracted from captured videos. By learning the structure of a set of sample vector sequences, the learned model can generate a novel pattern through the underlying structure. These generated patterns could differ from every original vector sequence but preserve characteristics of subject behavior. We can use such patterns to synthesize natural-looking animation.
Co-Evolution of Fuzzy Controller for the Mobile Robot Control
Authors: Byun Kwang-Sub ,   School of Electrical and Electronics Engineering, Chung-Ang University, 221, Heukseok-Dong, Dongjak-Gu, Seoul 156-756, Korea, Park Chang-Hyun , Sim Kwee-Bo
Published: April 2016

In this paper, we design the fuzzy rules using a modified Nash Genetic Algorithm. Fuzzy rules consist of antecedents and consequents. Because this paper uses the simplified method of Sugeno for the fuzzy inference engine, consequents have not membership functions but constants. Therefore, each fuzzy rule in this paper consists of a membership function in the antecedent and a constant value in the consequent. The main problem in fuzzy systems is how to design the fuzzy rule base. Modified Nash GA coevolves membership functions and parameters in consequents of fuzzy rules. We demonstrate this co-evolutionary algorithm and apply to the design of the fuzzy controller for a mobile robot. From the result of simulation, we compare modified Nash GA with the other co-evolution algorithms and verify the efficacy of this algorithm.
Recognition of Car License Plates Using Morphological Information and SOM Algorithm
Authors: Kim Kwang-Baek ,   Department of Computer Engineering, Silla University, 1-1 San, Gwaebop-dong, Sasang-gu, Busan 617-736, Korea, Kim Dae-Su ,   Department of Computer Science, Hanshin University, Korea
Published: April 2016

In this paper, we propose car license plate recognition using morphological information and a self-organizing map (SOM) algorithm. Morphological information on horizontal and vertical edges was used to extract the license plate from a car image. A 4-directional contour tracking algorithm was applied to extract the specific area, including characters, from an extracted plate. Recognition of extracted character strings was studied using the SOM algorithm. We used 50 car images to evaluate performance. Extraction for character strings by the proposed method showed better results than that from conventional color information on RGB and HSI. License plate recognition using the SOM algorithm was very efficient.
Development of an Automatic Tunneling Algorithm Based on Fuzzy Logic for the Microtunneling System
Authors: Park Taedong ,   Network Infra Research Team, Technology Lab., Korea Telecom, 463-1 Jeonmin-Dong, Yuseong-Gu, Daejeon, 305-811, Korea, Nam Janghyun , Han Jeong-Su , Do Jun-Hyeong , Bien Zeungnam ,   Department of EECS, Korea Advanced Institute of Science and Technology, 373-1 Guseong-Dong, Yuseong-Gu, Daejeon, 305-701, Korea
Published: April 2016

Microtunneling techniques play a crucial role in pipeline construction. This paper proposes an automatic microtunneling algorithm using fuzzy logic to assist operators in ensuring microtunneling construction quality. To make fuzzy controller output effective, we slightly modified conventional defuzzification methods. The proposed algorithm shows tunneling results comparable to those of experts.
Reliability Optimization Problems Using Adaptive Hybrid Genetic Algorithms
Authors: Mukuda Minoru ,   Department of Information Engineering, Nippon Institute of Technology, Minami-Saitama 345-8501, Japan, Yun YoungSu , Gen Mitsuo ,   School of Automotive, Industrial & Mechanical Engineering, Daegu University, Gyeongbuk Gyeongsan 712-714, Korea (Corresponding Author),   Graduate School of Information, Production & Systems, Waseda University, Kitakyushu 808-0135, Japan
Published: April 2016

This paper proposes an adaptive hybrid genetic algorithm (aHGA) for effectively solving the complex reliability optimization problems. The proposed aHGA uses a local search technique and an adaptive scheme for respectively constructing hybrid algorithm and adaptive ability. For more various comparisons with the proposed adaptive algorithm, other aHGAs with conventional adaptive schemes are considered. These aHGAs are tested and analyzed using two complex reliability optimization problems. Numerical result shows that the proposed aHGA outperforms the other competing aHGAs.
Concept-Based Interactive Brainstorming in Engineering Design
Authors: Avigad Gideon ,   The Iby and Aladar Fleischman, Faculty of Engineering, Tel-Aviv University, Tel-Aviv, Israel, Moshaiov Amiram , Brauner Neima
Published: April 2016

In this paper we present a concept-based evolutionary method, which strengthens symbiosis between computers and humans in exploring engineering solutions to multi-objective design problems. The use of concepts improves the human-machine interface. Moreover, it serves not only as a communication means but also enables evaluating concepts rather then just specific solutions while taking into account teammates’ perceptions and preferences. A scenario-based example is given to demonstrate the way our concept-based method can be used for computer-assisted iterative team design.
Anytime System Scheduler for Insufficient Resource Availability
Authors: Várkonyi-Kóczy Annamária R. ,   Department of Measurement and Information Systems, Integrated Intelligent Systems Japanese-Hungarian Joint Laboratory, Budapest University of Technology and Economics, H-1521, Magyar Tudósok krt. 2., Hungary, Samu Gábor
Published: April 2016

Anytime systems are advantageous when resource and/or data availability changes during operation and some kind of intelligent reconfiguration of the system is needed to cope with temporal data and resource access conditions. Such systems may provide an optimal tradeoff between time/resource needs and computational complexity and the quality (accuracy) of results and are designed using special models, methods, and algorithms together with applying active monitoring for being able to supervise the operation of the system on-line and making intelligent decisions based on sensory information of so-called shortage indicators. Since the monitor operates under prescribed response time requirements and the number and complexity of the executable tasks may be very high, especially in complex systems, new considerations must constantly be made to achieve optimal or acceptable performance. In software terms, this requires the application of special compilation methods dealing also with timing considerations and constraints of the underlying operating system and even with the run-time characteristics of the monitor. This must also be supported by anytime development tools and special anytime description languages. In this paper a hierarchical compilation method is introduced together with theoretical considerations about a possible anytime development tool and the basics of the anytime description meta-language ATDL are presented.
Evolutionary Design of Combinational Logic Circuits
Authors: Reis Cecília ,   Institute of Engineering of Porto, Polytechnic Institute of Porto, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal, Machado J. A. Tenreiro , Cunha J. Boaventura ,   University of Trás-os-Montes and Alto Douro, Engineering Department Apt. 1013, 5000-911 Vila Real, Portugal
Published: April 2016

This paper proposes a genetic algorithm for designing combinational logic circuits and studies four different case examples: 2-to-1 multiplexer, one-bit full adder, four-bit parity checker and a two-bit multiplier. The objective of this work is to generate a functional circuit with the minimum number of gates.
Sliding Mode Robot Control with Friction and Payload Estimation
Authors: Márton Lörinc ,   Dept. of Electrical Engineering, Sapientia Hungarian University of Transylvania, 540053 Tg. Mures, P-ta. Trandafirilor 61, Romania, Lantos Béla ,   Dept. of Control Engineering and Information Technology, Budapest University of Technology and Economics, H-1117 Budapest, Magyar Tudósok körútja 2, Hungary
Published: April 2016

The paper deals with robust motion control of robotic systems with unknown friction parameters and payload mass. The parameters of the robot arm were considered known with a given precision. To solve the control of the robot with unknown payload mass and friction parameters, sliding mode control algorithm was proposed combined with robust parameter adaptation techniques. Using Lyapunov method it was shown that the resulting controller achieves a guaranteed final tracking accuracy. Simulation results are presented to illustrate the effectiveness and achievable control performance of the proposed scheme.
Single-Channel Noise Reduction for Multiple Background Noises Using Perceptual Wavelet Packet Transform and Fuzzy Logic
Authors: Phothisonothai Montri ,   Computer Vision Laboratory & VLSI Laboratory, Department of Electronics and Telecommunication Engineering, King Mongkut’s University of Technology Thonburi, 91 Pracha-Utith Road, Trungkru, Bangmod, Bangkok 10140, Thailand, Kumhom Pinit , Chamnongthai Kosin
Published: April 2016

Background noises interfere with communication devices such as mobile telephone, digital hearing aid, etc. Therefore noise reduction (NR) part for limiting the effect of these noises is important. The paper proposes a noise reduction method based on the soft decision-making by the fuzzy inference system (FIS). The different characteristics of noises frequently occurring are used for creating the fuzzy decision rule base of the FIS. The FIS have two input parameters: the average energy and the difference of the average energy. The analysis of the FIS is done in the domain of the perceptual wavelet packet transform (PWPT) that is the human’s psychoacoustic model. The output of the FIS is used to modify the PWPT coefficients in such a way that it is more likely that the noise components are reduced while the speech signal is enhanced. The enhanced speech signal is the result of the inverse perceptual wavelet packet transform (IPWPT) of the modified coefficients. The experiment results show that the proposed method gives lower distortion than do the conventional methods especially when the input signal-to-noise ratio (SNR) is low; e.g. at SRN at 0dB the proposed method improves the output SNR level up to 4.18dB.
Studies on Effects of Initialization on Structure Formationand Generalization of Structural Learning with Forgetting
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

In this paper, our proposed initialization for multilayer neural networks (NN) applies to the structural learning with forgetting. Initialization consists of two steps: weights of hidden units are initialized so that their hyperplanes pass through the center of gravity of an input pattern set, and weights of output units are initialized to zero. Several simulations were performed to study how the initialization effects the structure formation of the NN. From the simulation result, it was confirmed that the initialization gives better network structure and higher generalization ability.
Color Instance-Based Reasoning and its Application to Dynamic Image Restoration Under Low Luminance Conditions
Authors: Hatakeyama Yutaka ,   Department of Computational Intelligence and Systems Science,, Kawamoto Kazuhiko , Nobuhara Hajime , Yoshida Shin-ichi , Hirota Kaoru
Published: April 2016

Color instance-based reasoning is applied to dynamic image restoration under low luminance conditions is presented by introducing color change vectors. The color change vectors are constructed based on image measurement, i.e., no optical lighting models are required. This property enables us to deal with low luminance conditions, under which it is difficult to capture color information using traditional optics-based methods. The proposed algorithm restores color values by adaptively modifying the color change vectors in response to a given dynamic image. Experiments are done with still and dynamic images to compare the proposed algorithm with the conventional one in terms of color difference. The experimental results show that the proposed algorithm decreases the color-difference a maximum of 20% compared to the conventional algorithm. The proposed algorithm presents the foundation to identify a person by a low cost CCD camera in the practical security system.
Combining Local and Global Access to Ontologies in a Multiagent System
Authors: Brena Ramon ,   Center for Intelligent Systems, Tecnologico de Monterrey, Mexico, Ceballos Hector G.
Published: April 2016

As Ontologic knowledge gets more and more important in agent-based systems, its handling becomes crucial for successful applications. We propose a hybrid approach, in which part of the ontology is handled locally, using a "client component", and the rest of the ontological knowledge is handled by an "ontology agent", which is accessed by the other agents in the system through their client component. We propose specific methods for representing, storing, querying and translating ontologies for effective use in the context of the "JITIK" system, which is a multiagent system for knowledge and information distribution. We report as well a working prototype implementing our proposal.
Towards Context-Aware Knowledge Management in e-Enterprises
Authors: Huang Weihong ,   Centre for Internet Computing, The University of Hull, Scarborough Campus, Filey Road, Scarborough, YO11 3AZ, U.K.
Published: April 2016

To reduce the negative impact of knowledge loss and to improve knowledge reuse effectiveness in knowledge management in e-Enterprises, this paper presents a context-aware approach to facilitate managing various types of static enterprise information and dynamic process information. Proposed approach features representing and integrating information at different conceptual levels to present contextual knowledge in an open environment. In this paper, we redefine the concept of context in intelligent systems and propose a set of meta-information elements for context description in business environments. In realising the context-awareness in knowledge management, we present a context knowledge structure model and look into the corresponding context knowledge storage and reuse solutions. To enhance context-aware knowledge management for e-Businesses over the global network, we introduce a new concept of Context Knowledge Grid with a layered knowledge interoperation reference model, which are supposed to leverage the contextual knowledge in e-Enterprises and enable interoperation with other knowledge frameworks such as the Semantic Web and the Semantic Grid.
Cascaded Fuzzy Congestion Controller for TCP/IP Traffic
Authors: Frantti Tapio ,   Kaitoväylä 1, P.O. Box 1100, 90571, Oulu, Finland
Published: April 2016

This paper presents a fuzzy congestion control solution for active queue management in wireline packet switched networks, that use TCP to solve end-to-end flow control. Queue management is a trade-off between link utilisation, delay and the loss of packets. The targets of it are to reduce the average queue length in routers, decrease the end-to-end delay and reduce the packet loss probability by preventing buffer overflows. In the presented solution, a fuzzy controller regulates the rejection probability of received packets in routers to prevent buffer overflow and the rejection of all packets during congestion. Using simulations a fuzzy controller is compared with the traditional random early discard (RED) algorithm. Pareto distributed traffic was used in the comparison for the evaluation of controllers. The results showed that the fuzzy controller decreased the packet loss rate with lower buffer occupation and increased the link utilisation and throughput. It also decreased control traffic between the transmitting nodes and routers via decreasing the number of ICMP (Internet Control Message Protocol) messages. In addition, by keeping the average queue size small, the developed algorithm had the ability to accommodate itself more effectively to very bursty traffic than the RED algorithm without dropping packets.
Self-Tuning Fuzzy Robust Control for Buildings with Sliding Bearing Isolation Under Seismic Excitation
Authors: Yeh Ken ,   Department of Civil Engineering, De-Lin Institute of Technology, Tu-Cheng, Taipei County 23646, Taiwan, R.O.C., Chien Chun-Chieh , Chen Cheng-Wu , Liang Han-Hsi ,   Department of Civil Engineering, National Central University, Chung-Li, Tao-Yuan 32054, Taiwan, R.O.C.,   Department of Architecture, National United University, Miao-Li 36003, Taiwan, R.O.C.
Published: April 2016

The purpose of this paper is to apply self-tuning fuzzy robust control for structurally controlling buildings with sliding bearing isolation. Combining fuzzy control and robust control such as sliding mode control reduces fuzzy rule bases complexity and ensures stability and robustness. Lyapunov theory is used to develop a self-tuning law. Stiffness uncertainty and time delay is utilized to demonstrate the robustness of this proposed algorithm. The effectiveness of this algorithm is demonstrated by simulation results for the Taiwan Chi Chi earthquake in 1999. Simulations show that self-tuning fuzzy robust control achieves satisfactory results in the application of structural control for buildings with sliding bearing isolators.
Forecasting Electric Load by Support Vector Machines with Genetic Algorithms
Authors: Pai Ping-Feng ,   Department of Information Management, National Chi Nan University, 1, University Rd. Puli, Nantou, 545, Taiwan, Hong Wei-Chiang , Lin Chih-Shen ,   School of Management, Da-Yeh University, 112 Shan-Jiau Road, Da-Tusen, Chang-Hua, 51505, Taiwan,   Department of Industrial Engineering and Enterprise Information, Tunghai University, Box 985, Taichung 407, Taiwan
Published: April 2016

Support vector machines (SVMs) have been successfully used in solving nonlinear regression and time series problems. However, the application of SVMs to load forecasting is very rare. Therefore, the purpose of this paper is to examine the feasibility of SVMs in forecasting electric load. In addition, the genetic algorithms are applied in the parameter selection of SVM model. Forecasting results compared with other two models, namely autoregressive integrated moving average (ARIMA) and general regression neural networks (GRNN), are provided. The experimental data are borrowed from the Taiwan Power Company. The numerical results indicate that the SVM model with genetic algorithms (SVMG) results in better predictive performance than the other two approaches.
A Proposal of Fuzzy Modeling on Fusion Axes
Authors: Yamamoto Kosuke ,   Department of Computational Science and Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan, Yoshikawa Tomohiro , Furuhashi Takeshi ,   Faculty of Engineering, Mie University, 1515 Kamihama-cho, Tsu-shi, Mie 514-8507, Japan
Published: April 2016

Transparency of fuzzy models has become one of the major topics in the field of fuzzy modeling. This paper discusses a methodology for constructing transparent models that have clear input-output relationships of unknown systems. Visualization of data in two/three dimensions is one of effective methods for obtaining the transparency. This paper proposes a visualization method of input-output relationships with a new dimensionality reduction method. This paper also presents a method that constructs fuzzy models in the visualized space for knowledge extraction. The proposed method is to obtain transparent models for understanding input-output relationships of unknown systems, and thus to show guidelines for constructing models with more appropriate structures. This paper defines "fusion axes" that are linear transformation of input variables for dimensionality reduction. The proposed method constructs a transparent model on the fusion axes using Fuzzy C-Means and Fuzzy Multiple Discriminant Analysis. This paper shows thorough a numerical experiment that the proposed method can identify an appropriate fusion axis to visualize the input-output relationships. This paper also applies the proposed method to gas furnaces data. This experiment shows that the proposed method finds a proper model structure by visualizing the input-output relationships.
Saliency-Driven Scene Learning and Recognition Based on Competitively Growing Neural Network Using Temporal Coding
Authors: Atsumi Masayasu ,   Department of Information Systems Science, Faculty of Engineering, Soka University, 1-236 Tangi-cho, Hachioji-shi, Tokyo 192-8577, Japan
Published: April 2016

This paper proposes a model of saliency-driven scene learning and recognition in which objects in saliency-driven attended spots are quickly learned and recognized based on the competitively growing neural network using temporal coding. In this model, objects in attended spots are sequentially encoded to be invariant with respect to position and size by this neural network and their positions and sizes are encoded simultaneously. This neural network represents objects using latency-based temporal coding and grows size and recognizability through self-organized learning with growth. Through simulation experiments of a robot equipped with a camera, it is shown that quick self-organized learning and glance recognition of objects in scenes are well performed by our model.
Intelligent Control of Autonomous Soccer Robots Compensating for Missing Information
Authors: Fujii Hikari ,   Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan, Kurihara Nobuyuki , Yoshida Kazuo ,   Keyence Corporation (Keio University), 1-3-14 Higashinakajima, Higashiyodogawa-ku, Osaka 533-8555, Japan
Published: April 2016

For autonomous mobile robots, visual information is used to recognize the environment. Although the acquisition of visual information is often disturbed in the real environment, it is necessary for a robot to act appropriately even if information is missing. We compensate for missing information for autonomous mobile robots by using short-term memory (STM) to make robots act appropriately. This method involves short-term memory and action selectors. Short-term memory is constructed based on the model of human memory and the forgetting curve used in cognitive science. These action selectors use compensated-for information and determine suitable action. One action selector consists of a neural network whose connection weights are learned by a genetic algorithm. Another selector is designed based on the designer's knowledge. These action selectors are switched based on reliability index of information. RoboCup Middle Size League soccer robots are used for demonstration. The experimental and simulation results show its effectiveness.
Constrained Optimization by the α Constrained Particle Swarm Optimizer
Authors: Takahama Tetsuyuki ,   Faculty of Information Sciences, Hiroshima City University, 3-4-1 Ozukahigashi, Asaminami-Ku, Hiroshima 731-3194, Japan, Sakai Setsuko ,   Faculty of Commercial Sciences, Hiroshima Shudo University, 1-1-1 Ozukahigashi, Asaminami-Ku, Hiroshima 731-3195, Japan
Published: April 2016

In this study, α constrained particle swarm optimizer αPSO, which is the combination of the α constrained method and particle swarm optimization, is proposed to solve constrained optimization problems. The α constrained methods can convert algorithms for unconstrained problems to algorithms for constrained problems using the α level comparison, which compares the search points based on the satisfaction level of constraints. In the αPSO, the agents who satisfy the constraints move to optimize the objective function and the agents who don't satisfy the constraints move to satisfy the constraints. The effectiveness of the αPSO is shown by comparing the αPSO with GENOCOP5.0, and other PSO-based methods on some nonlinear constrained problems.
Inductive Temporal Formula Specifications for System Verification
Authors: Yamada Chikatoshi ,   Takushoku University Hokkaido College, 4558 Memu, Fukagawa, Hokkaido 074-8585, Japan, Nagata Yasunori , Nakao Zensho ,   Department of Electrical and Electronics Engineering, University of the Ryukyus, 1 Senbaru, Nishihara, Nakagami, Okinawa 903-0213, Japan
Published: April 2016

Design verification has played an important role in the design of large scale and complex systems. In this article, we focus on model checking methods. Behaviors of modeled systems are in general specified by temporal formulas of computation tree logic, and users must know well about temporal specification because the specification might be complex. We propose a method temporal formulas are obtained inductively, and amounts of memory and time are reduced. We will show verification results using the proposed method.
On the Design and Structure of Artificial Eyes for Tracking Tasks
Authors: Vincze Markus ,   Automation and Control Institute, Vienna University of Technology, Gusshausstr. 27/376, 1040 Wien, Austria
Published: April 2016

Nature developed different types of eyes for different functions and creatures. In this work the design parameters to common eye types are analysed with respect to visual tracking abilities. The goal is to select optimal parameters for building artificial vision systems. The parameters investigated are different tessellations and resolutions of eye cells (pixels), the window size or field of view, the frequency to acquire visual input and the system latency or reaction time. The analysis shows that following a target is best achieved at high frequency with small target windows or with a space-variant tessellation. While the first case enables high resolution for smooth motions, the second case trades resolution for speed and jerky motions. An experimental set-up demonstrates the performance characteristics.
Fractional-Order Position/Force Robot Control
Authors: Ferreira N. M. Fonseca ,   Institute of Engineering of Coimbra, Polytechnic Institute of Coimbra, Rua Pedro Nunes -- Quinta da Nora, 3031-601 Coimbra, Portugal, Machado J. A. Tenreiro , Cunha J. Boaventura ,   Institute of Engineering of Porto, Polytechnic Institute of Porto, Rua Dr Ant. Bernardino de Almeida, 4200-072 Porto, Portugal,   University of Trás dos Montes e Alto Douro, Ap 1013, 5000-911 Vila Real, Portugal
Published: April 2016

This paper studies fractional-order (FO) position/force algorithms in the hybrid control (HC) and the cascade control (CC) of manipulators. The system performance is analyzed, in the time and frequency domains, and the effects of joint backlash and flexibility are investigated. The results show that the FO algorithms and the CC architecture have superior robustness and stability.
Maintenance of Building Blocks in GA Using Symbiotic Evolutionary Viruses
Authors: Sakakura Yoshiaki ,   Frontier Doctoral Program in Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan, Taniguchi Noriyuki , Hoshino Yukinobu , Kamei Katsuari ,   Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan,   Department of Human and Computer Intelligence, Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan
Published: April 2016

In this paper, we discuss about the solution search effectiveness, the solution search behaviors and the maintenance of building blocks in GA using symbiotic evolutionary viruses. The proposed GA is based on both the building block hypothesis and the virus theory of evolution. The proposed GA has the virus infecton. The virus infection directly deals with schemes. The proposed GA aims to control the destruction of building blocks by discovery, maintenance, and propagation of building blocks based on the virus infection. We will expect that a search efficiency of GA will be increased by them.
Feasibility Study on Marketing Research Using Eye Movement: An Investigation of Image Presentation Using an “Eye Camera” and Data Processing
Authors: Nagasawa Shin'ya ,   Waseda University, 1-21-1 Nishi-waseda, Shinjuku, Tokyo 169-0051, Japan, Yim Sora , Hongo Hitoshi ,   Dong-Eui University, 1394-9-23 Jwa-dong, Haeundae-gu, Busan, Korea,   SANYO Electric Co. Ltd., 1-18-13 Hashiridani, Hirakata, Osaka 573-8534, Japan
Published: April 2016

We studied the relationship between purchasing behavior and physiological measurement using an eye camera, including the correlation of physiological measurement based on an analysis of eye movement data at the behavioral level (close to intention) using conjoint analysis and with the attitude level using the analytic hierarchy process. Results showed poor correlation between data on eye movement, i.e., physiological reaction to stimulus, and the attitude level but a fairly good correlation between data on eye movement and the behavioral level.
Fuzzy Least Squares Regression Analysis for Social Judgment Study
Authors: Takemura Kazuhisa ,   Department of Psychology, Waseda University, 1-24-1 Toyama, Shinjuku-Ku, Tokyo 162-8644, Japan
Published: April 2016

Social judgment data was analyzed using fuzzy least squares regression analysis based on the extension principle. The proposed analysis is new fuzzy least squares regression analysis in which input data, output data, and coefficients are represented by L-R fuzzy numbers. To evaluate data fitness, we propose a fuzzy version of a squared multiple correlation (R2) and conducted an experiment to determine the effect of partial attribute information on the overall evaluation of desirability for a marital partner and personality of a person using fuzzy rating to measure vagueness in social judgment. Participants in the experiment were 90 university students. The result of marital partner judgment indicated that the fuzzy weight of consideration was higher than physical attraction on overall desirability evaluation for a marriage partner. The result of personality judgment indicated that the fuzzy weight of kindness was slightly higher than responsibility in overall desirability for a marriage candidate.
Identification of Fuzzy Measures with Distorted Probability Measures
Authors: Honda Aoi ,   Department of Systems Innovation and Informatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka 820-8502, Japan, Okazaki Yoshiaki ,   Department of Computer science and Mathematics, University of Paris I, Panthéon-Sorbonne 72, rue Regnault, 75013 Paris, France
Published: April 2016

We consider the identification of fuzzy measures using a class of distorted probabilities – a scale transformation of probabilities. A fuzzy measure, which is a nonadditive set function with a high degree of freedom, enables us to express complicated interactions among evaluative items. Because of the high degree of freedom, however, it is difficult to identify all of the values μ(A) for every event A from known data μ(B), B ∈ A, where A is generally a small subclass of events. In this paper, we classify fuzzy measures by introducing “type,” and propose an identifying fuzzy measures using a classified class of distorted probabilities.
Some Characterizations of k-Monotonicity Through the Bipolar Möbius Transform in Bi-Capacities
Authors: Fujimoto Katsushige ,   College of Symbiotic Systems Science, Fukushima University, 1 Kanayagawa, Fukushima 960-1296, Japan, Murofushi Toshiaki ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259-G3-47  Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
Published: April 2016

This paper first proposes the bipolar Möbius transform as an extension of dividends of cooperative games to that of bi-cooperative games (bi-capacities) defined on 3N, which is different from the Möbius transform defined by Grabisch and Labreuche. The k-monotonicity of bi-capacities is characterized through each of the following notions: the bipolar and ordinary Möbius transforms, discrete derivatives, and partial derivatives of the piecewise multilinear extension of the ternary pseudo-Boolean function corresponding to the bi-capacities.
Level Sets as a Topological Base Applied to Subgroups of a Group of Moebius Transformations
Authors: Kukkurainen Paavo ,   Laboratory of Applied Mathematics, Lappeenranta University of Technology, P.O. Box 20, FIN-53851 Lappeenranta, Finland
Published: April 2016

We applied the theory of Moebius transformations, known in complex analysis, to fuzzy subgroups. We start using the two results presented by B. Seselja and A. Tepavcevic [4,5], taking a topological view point not in these papers. This leads to topological subgroups of a group of Moebius transformations. Although this is known in complex analysis, we approach it through of fuzzy concepts.
Fuzzy Logic and Differential Evolution Based Expert System for Defining Top Athlete's Aerobic and Anaerobic Thresholds
Authors: Saastamoinen Kalle ,   Laboratory of Applied Mathematics, Lappeenranta University of Technology, P.O. Box 20, FIN-53851 Lappeenranta, Finland, Ketola Jaakko
Published: April 2016

This article describes an expert system for defining an athlete's aerobic and anaerobic thresholds that successfully mimics the decision-making done by sport medicine professionals. The functionality of our system is based on the fuzzy comparison measure, generalized mean, fuzzy membership functions and differential evolution. Differential evolution is used to tune the parameters in our comparison measure. This measure is based on the use of fuzzy equivalences and a modification factor that tunes the shape of the membership function in hand. The measure presented is especially suitable for expert systems. We will test our system in order to show that our result does not show any statistically significant difference from the values estimated by experts.
Approximation by Growing Radial Basis Function Networks Using the Differential-Evolution-Based Algorithm
Authors: Liu Junhong ,   Department of Information Technology, Lappeenranta University of Technology, P.O. Box 20, FIN--53851 Lappeenranta, Finland, Lampinen Jouni
Published: April 2016

The differential evolution (DE) algorithm is a floating-point-encoded evolutionary algorithm for global optimization. We applied a DE-based method to training radial basis function (RBF) networks with variables including centers, weights, and widths. This algorithm consists of three steps – initial tuning focusing on finding the center of a one-node RBF network, local tuning, and global tuning both using cycling schemes to find RBF network parameters. The mean square error from desired output to actual network output is applied as the objective function to be minimized. Network training is shown by approximating a set of functions and reconstructing the spectra of oil samples and classification. Net performance is compared to approaches reported in the literature, and the resulting network generally performs better based on the tests performed. Results show that DE-based Gaussian RBF growth method improves approximation results reported.
Visual Perception for a Partner Robot Based on Computational Intelligence
Authors: Sulistijono Indra Adji ,   Dept. of Mechanical Engineering, Graduate School of Engineering, Tokyo Metropolitan University, 1-1 Minami-Osawa, Hachioji, Tokyo 192-0397, Japan, Kubota Naoyuki ,   Electronics Engineering Polytechnic Institute of Surabaya - ITS (EEPIS-ITS), Kampus ITS Sukolilo, Surabaya 60111, Indonesia,   Dept. of System Design, Tokyo Metropolitan University, 1-1 Minami-Osawa, Hachioji, Tokyo 192-0397, Japan,   PRESTO, Japan Science and Technology Agency (JST)
Published: April 2016

We propose computational intelligence for partner robot perception in which the robot requires the capability of visual perception to interact with human beings. Basically, robots should conduct moving object extraction, clustering, and classification for visual perception used in interactions with human beings. We propose total human visual tracking by long-term memory, k-means, self-organizing map, and a fuzzy controller is used for movement output. Experimental results show that the partner robot can conduct the human visual tracking.
Fuzzy Configuration Space for Moving Obstacle Avoidance of Autonomous Mobile Robots
Authors: Guerra Jorge ,   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, Nobuhara Hajime , Hirota Kaoru
Published: April 2016

A fuzzy configuration space description method that provides the path planning solution for autonomous mobile robots in dynamically changing environment is proposed based on a hybrid planning algorithm that combines total solutions and reactive control through fuzzy proximity measures. The system (made with C++) that monitors and controls mobile robots remotely is created using a multithreaded model while taking advantage of high performance OpenGL routines to counter the increase in computational cost generated by this approach. Experiments on a real Lego robot are performed using a personal computer with a 1.5GHz Pentium4 CPU and a CCD camera. The efficiency of the hybrid algorithm and the potential of this approach, as a distributed system, in greatly changing dynamic environments are shown. The system provides a starting point for further development of distributed robotic systems, for application in human support tasks where interaction with nonprecise human behaviors are better mentioned with fuzzy parameters.