bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Contact Point of Parts Using a Force Sensor for Remote-Controlled Assembly Using a 1DOF Haptic Device
Authors: Niitsu Satoshi ,   Department of Precision Mechanics, Chuo University, Tamura Ryosuke , Hiraoka Hiroyuki
Published: April 2016

This paper describes the calculation of the point of contact between assembled parts for remotecontrolled assembly using a haptic device with a single degree of freedom (DOF). To achieve such remote-controlled assembly, it is necessary to judge the constraint state and change the movement direction of the part. It is difficult to detect the points of contact between parts around which the rotational movement should be performed. In this paper, we report a method developed for the purpose of determining the contact point using a six-axis force sensor without knowing the geometry of the parts. The proposed method is applicable to cases in which the theoretical contact point cannot be calculated because of errors and fluctuations in the sensory data. The effectiveness and precision of the method are evaluated through experiments and simulations.
Functional Texture Design and Texturing Processes
Authors: Moronuki Nobuyuki ,   Tokyo Metropolitan University
Published: April 2016

Various functions can be obtained by applying regular patterns or textures to surfaces. Depending on the function, the required dimensions of the texture, such as the pitch, vary over a wide range: from nanometers for optical function to millimeters for friction. In addition, the high aspect ratio of the cross sectional profile or the hierarchical structure of a micro- or nano-structure is required to control the wettability, for example. This paper reviews various texturing processes as well as the functionalities thus attained and their application.
Diamond Machining of Holograms Using Fine Rectangular Shaped Cutting Tools
Authors: Meier Axel ,   Laboratory for Precision Machining, Riemer Oltmann , Brinksmeier Ekkard
Published: April 2016

Diamond machining is a flexible process ensuring an excellent workpiece precision. In combination with fast tool servos, which dynamically modulate the depth of cut, diffractive microstructures and holograms can be machined. The complexity and functionality of the structure depends on the flexibility of the machining process. Novel diamond tool geometries with fine rectangular shaped cutting edges and a width below 20 μm extend the machinable structure geometries. This paper presents fundamental cutting experiments using these novel tools with widths of the cutting edge of 10 μm and 20 μm to machine diffractive microstructures with a rectangular shaped profile. Particularly, the influence of the feed on the uniformity of the structure width and on burr formation on the structure edges is investigated. Using these tools together with fast tool servo assisted diamond turning holograms for multiple wavelengths can be machined, forming different intensity patterns in dependence of the wavelength.
Basic Study on Electro-Adhesive Surface Applying 3-Dimensional Micro Structures
Authors: Yamada Soichiro ,   School of Integrated Design Engineering, Graduate School of Science and Technology, Keio University, Koike Ryo , Arano Shintaro , Kakinuma Yasuhiro , Aoyama Tojiro ,   Department of System Design Engineering, Faculty of Science and Technology, Keio University
Published: April 2016

Electro Adhesive Gel (EAG) has the unique characteristic of changing its surface adhesive property with the intensity of the electrical field applied. This property makes EAG useful in applications to fixing devices and mechanical brakes. Although its adhesion performance depends on the distribution of the electro-rheological particles in the EAG, it is difficult to arrange the particle distribution uniformly in a wide area from the perspective of production process. In this study, a novel functional elastomer that has the same function as EAG is developed, Electro Adhesive Surface (EAS). In EAS, micro photolithography is used to fabricate strut pyramids distributed uniformly on a substrate, and then silicone gel is poured into the structure. When an electrical field is applied, the silicone gel rises to the tops of the pyramids formed by the struts, and adhesion occurs to an object on EAS. To determine a micro structure design for EAS, the fixing force was measured with various struts diameter and gaps. Experimental result shows that the larger struts diameter and the narrower gaps enhance the fixing force of EAS.
On-Machine Surface Texture Measuring System Using Laser Speckle Pattern Analysis
Authors: Shimizu Motochika ,   Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Sawano Hiroshi , Yoshioka Hayato , Shinno Hidenori ,   Research Fellow of Japan Society for the Promotion of Science,   Precision and Intelligence Laboratory, Tokyo Institute of Technology
Published: April 2016

Functional surfaces are expected technologies in various industries. However, the efficient generation of microscale surface structures is difficult because the process relies on precision surface texture assessments, which require long measuring times. An on-machine measuring system may solve this issue. In this study, a new on-machine surface texture measuring system based on laser speckle pattern analysis is proposed. The proposed system efficiently assesses various qualities of the surface texture, such as surface roughness, undulation of microscale surface structures, and anisotropy, from a laser speckle pattern obtained from the precision-machined surface. For precise measurements, disturbances caused by the machining system itself and the environment must be avoided. The laser speckle detection unit in the proposed system is supported by non-contact active vibration-isolation units, which reduce the transmission of ground vibrations. From the experimental results, the system indicated high repeatability in measurements and robustness against disturbances.
Punchless Drawing of Magnesium Alloy Sheet Under Cold Condition and its Computation
Authors: Yamashita Minoru ,   Department of Mechanical Engineering, Gifu University, Kuwabara Koji
Published: April 2016

Shallow cup drawing of magnesium alloy AZ31-O sheet was performed under cold condition using the Maslennikov’s technique. A deformable rubber pad was used, instead of the “hard” punch, in this technique. A small die profile radius was adopted, which was twice or four-times the sheet thickness. A semisolid lubricant was used for lubrication of the blank-die interface. On the other hand, the rubber-blank interface was degreased to increase friction. A limiting drawing ratio of 1.31 was obtained in the circular cup drawing. A peculiar fracture mode appeared in which the material suddenly fractured with the crack evolution emanating from the flange periphery. In the square cup drawing, an adequate blank shape was found to be circular compared with the other ones. Numerical simulation was also conducted using dynamic explicit finite element method. Adequate setting including speed scaling enabled us to predict the accurate deformation pattern and the forming force.
Influence of Resin Flow State on Aluminum Flake Orientation in a Metallic-Like Resin Product Manufactured Through Injection Molding
Authors: Nikawa Makoto ,   Faculty of Engineering, Gifu University, Shirota Takahito , Yamagata Hiroshi ,   Graduate School of Engineering, Gifu University
Published: April 2016

A potential method for predicting the orientation of aluminum flakes in a metallic-like product without a coating was examined. To achieve this goal, injection molding test of a thin product was carried out with a metallic-like resin that contained aluminum flakes. Furthermore, the flow state of the base material (polypropylene) of the metallic-like resin during molding was calculated via computer simulations, and the results were compared to the experimental results. The reflectance and orientation of the product were measured as functions of the gate shape and injection speed. The reflectance of the product made with the metallic-like resin was measured with a spectrophotometer, and the orientation of the aluminum flakes was measured via X-ray computed tomography (CT). The reflectance changed according to differences in the gate shape and injection speed. In addition, the orientation of the aluminum flakes changed with the distance from the surface of the product. The shear rate of the base material was calculated immediately after the resin completely filled the mold, and the results correlated well with the orientation of the flakes. The results suggest that it is possible to predict the orientation of aluminum flakes within metallic-like resins.
Multi-Axis Control Ultraprecision Machining Based on Tool Setting Errors Compensation
Authors: Baba Shinnosuke ,   Tokyo University Agriculture and Technology, Nakamoto Keiichi , Takeuchi Yoshimi ,   Chubu University
Published: April 2016

Initial position errors generated while setting cutting tools can deteriorate machining accuracy. However, because of the manual setting process, it is difficult to prevent the tool setting errors, which can increase in accordance with the number of the control axes. These errors make it difficult to locate the tool accurately at the correct position in multi-axis control machining. Therefore, this study aims to achieve multi-axis control ultraprecision machining based on tool setting errors compensation. From the conducted experiments, it is found that the proposed method is effective for compensating the tool setting errors in multi-axis control ultraprecision machining.
Digital Shape Reconstruction of a Micro-Sized Machining Tool Using Light-Field Microscopy
Authors: Usuki Shin ,   Research Institute of Electronics, Shizuoka University, Uno Masaru , Miura Kenjiro T. ,   ,,   Graduate School of Engineering, Shizuoka University
Published: April 2016

In this paper, we propose a digital shape reconstruction method for micro-sized 3D (three-dimensional) objects based on the shape from silhouette (SFS) method that reconstructs the shape of a 3D model from silhouette images taken from multiple viewpoints. In the proposed method, images used in the SFS method are depth images acquired with a light-field microscope by digital refocusing (DR) of a stacked image along the axial direction. The DR can generate refocused images from an acquired image by an inverse ray tracing technique using a microlens array. Therefore, this technique provides fast image stacking with different focal planes. Our proposed method can reconstruct micro-sized object models including edges, convex shapes, and concave shapes on the surface of an object such as micro-sized defects so that damaged structures in the objects can be visualized. Firstly, we introduce the SFS method and the light-field microscope for 3D shape reconstruction that is required in the field of micro-sized manufacturing. Secondly, we show the developed experimental equipment for microscopic image acquisition. Depth calibration using a USAF1951 test target is carried out to convert relative value into actual length. Then 3D modeling techniques including image processing are implemented for digital shape reconstruction. Finally, 3D shape reconstruction results of micro-sized machining tools are shown and discussed.
An Application for 3D Grain Generation Based on t-FFD
Authors: Shimada Chiaki ,   Toyama Prefectural University, Kobayashi Kazuya G. , Ootsubo Katsutoshi ,   ,,   Gifu University
Published: April 2016

This study aims to generate grain forms on 3D models by applying Free Form Deformation (t-FFD). As the fully automated placement of grain patterns on curved surfaces tends to generate distorted grain patterns, we propose a method of semi-automatically placing grain patterns, based on simple inputs from the user, as well as of controlling the heights of grain patterns in real sizes in reference to the model sizes. The proposed method has proved to successful in placing the desired grain forms.
Dexterous Creation of Soccer-Ball Pattern by Using Urethane Rubber
Authors: Funatani Kosuke ,   Department of Mechanical Engineering, Chubu University, Nakamoto Keiichi , Beaucamp Anthony , Takeuchi Yoshimi ,   ,,   Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology,   Department of Micro-Engineering, Kyoto University
Published: April 2016

It is important to establish new approaches to create value-added products, such as craftwork or artistic goods, that are different from traditional methods of realizing high-quality and low-cost products. Such a production technology is commonly called “dexterous machining.” This study addresses the creation of artistic products by using soft materials with complicated shapes by employing an aqueous solution of sodium acetate to fix a workpiece and to suppress the deformation. Experimental results show that the use of an aqueous solution of sodium acetate has the potential to realize the “dexterous machining” of soft objects.
Development of Cutting Force Prediction Method Using Motion Information from CNC Controller
Authors: Hida Tomoya ,   Aikoku Alpha Corporation, Asano Tetsuya , Higashino Chiharu , Kanamaru Masaaki , Kaneko Jun’ichi , Takeuchi Yoshimi ,   ,,   Graduate School of Science and Engineering, Saitama University,   Department of Mechanical Engineering, Chubu University
Published: April 2016

Five-axis machines and multi-tasking machines are widely used because they facilitate integration of work processes and simplification of jigs and set-ups. Along with effective machine use, development of optimum machining such as research on tools and cutting methods to achieve high-speed cutting and increase of material removal rate is being investigated. While these efforts have greatly contributed to furthering of automation and cost reduction at the manufacturing site, complex machine motions and increased demanding work processes can lead to unexpected collisions and tool breakages. To prevent tool breakage caused by unexpected overloading or to improve the inefficient feed rate on the basis of safety considerations, simulations based on numerical control (NC) data are usually performed in advance to evaluate the cutting force. In high-speed, high-efficiency machining, however, the machine does not always execute movements as instructed by the NC data and the predicted cutting force does not always agree with the actual cutting forces. In this study, therefore, we developed an off-line system in which the motion information of each axis of an actual machine is acquired from a computer numerical control (CNC) controller, and is then used to predict the cutting force. The effects of using the proposed method are described in this article.
Orientation Smoothing for 5-Axis Machining Using Quasi-Redundant Degrees of Freedom
Authors: Sellmann Florian ,   Institute for Machine Tools and Manufacturing, Haas Titus , Nguyen Hop , Weikert Sascha , Wegener Konrad ,   inspire AG,   ,
Published: April 2016

A new approach for set point generation in the field of 5-axis machining using quasi-redundant degrees of freedom is introduced in this study. In machine tools that possess both rotational and translational axes, no bijective correlation exists between the tool center point and the movement of the machine tool axes based on the manufacturing tolerances. Depending on the manufacturing process, as many as two additional degrees of freedom exist that allow the machine tool axes movement to be optimised within the given manufacturing tolerances with respect to the axes’ inertia. In this study to reduce the mechanical excitation of the machine tool, the jerk of the machine tool axes is minimised. To enhance robustness, the optimisation problem is formulated as a quadratic program with linear constraints. This problem can be solved by using an interior point method. An application example shows that when exploiting quasi-redundancy, the mechanical excitation of the machine tool can be reduced.
Toward Everyday Language Computing - Computing from a Viewpoint of Linguistic Theory -
Authors: Kobayashi Ichiro ,   Faculty of Economics, Hosei University, 4342 Aihara-cho, Machida-shi, Tokyo 194-02, Japan, Sugeno Michio ,   Dept. of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama-shi, Kanagawea 226 Japan
Published: April 2016

This paper describes our approach toward everyday language computing and shows some examples. The basic idea in the computing is that human intelligence reflects the linguistic system they use in their everyday lives, i.e., everyday language. Everyday language is, therefore, thought to be the main tool for reasoning and thinking in human intellectual activities. To find out how to apply everyday language to computing, we apply systemic functional linguistic theory that discusses the linguistic system from the viewpoint of social context. Following the ideas from this linguistic theory, we analyze the organization of human intelligence and then propose ideas for information processing using language.
Fuzzy Inference Based Connection Admission Control in ATM Networks
Authors: Uehara Kiyohiko ,   Communication and Information Systems Research Laboratorie Research and Development Center, Toshiba Corporation, 1 Komukai Toshiba-cho, Saiwai-ku, Kawasaki 210, Japan, Hirota Kaoru ,   Interdisciplinary Graduate School of Science and Technology, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226, Japan
Published: April 2016

A connection admission control (CAC) method is proposed for asynchronous transfer mode (ATM) networks by applying the fuzzy inference and learning algorithm of neural networks. In order to guarantee the allowed cell loss ratio (CLR) in CAC, the upper bound of CLR must be used as the criterion for judging whether an incoming call can be accepted or not. For estimating the upper bound of CLR from observed CLR data, fuzzy inference, based on a weighted mean of fuzzy sets, is adopted. This inference method can effectively estimate the possibility distribution of CLR by applying the error back-propagation algorithm with the proposed energy functions in learning and provide the upper bound of CLR efficiently from the distribution. A self-compensation mechanism for estimation errors is also provided, which is simple enough to work in real time by taking advantage of the fuzzy inference method adopted. Fuzzy rules in the area with no observed data are generated by extrapolation from adjacent fuzzy rules in the area with observed data. This increases the multiplex gain, thereby guaranteeing the allowed CLR as much as possible. The simulation results show the feasibility of the proposed CAC method.
Mission Planning and Flight Control: Meeting the Challenge with Intelligent Techniques
Authors: Vachtsevanos George ,   School of Electrical and Computer Engineering, Kim Wonoh , Al-Hasan Sami A. , Freeman Rufus Jr.  , Simon Miguel , Schrage Daniel P. , Prasad J. V. R. ,   School of Aerospace Engineering Georgia Institute of Technology Atlanta, GA 30332, U.S.A.
Published: April 2016

This paper presents a hybrid hardware/software platform that supports flight control and mission planning algorithms for an autonomous helicopter. The emphasis is on the use of intelligent fuzzy logic based techniques and an object-modeling approach to account for unmodeled dynamics to address uncertainty issues and to provide a flexible platform for development purposes and an operator interface. Fuzzy logic routines are implemented in such critical vehicle modules as the route planner the fuzzy navigator the fault-tolerant tools and the flight controller.
An Application of Fuzzy Theory to the Case-Based Reasoning of the CISG
Authors: Hirota Kaoru ,   Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology 4259 Nagatuta, Midori-ku, Yokohama 226, Japan, Yoshino Hajime , Xu Ming Qiang , Zhu Yan , Li Xiao Yi , Horie Daigo ,   Meiji Gakuin University, Legal Expert Laboratory 1-2-37 Shirokanedai, Minato-ku, Tokyo 108, Japan
Published: April 2016

In legal case-based reasoning (CBR), there exist problems concerning fuzziness, e.g., representation of precedents, their retrieval, and similarity measures. In our proposed fuzzy legal CBR system, the issues and features of precedent are characterized on the basis of the facts of precedent and statute rule. The case rule that is used for interpreting the court judgment, which cannot be obtained from the statute rule directly, is made by experts. Fuzziness is represented by membership functions. Features and case rules, written in terms of Compound Predicate Formula (CPF) and frame, are stored in a case base. Cases similar to a new case are retrieved by issues and features, and an inference is made by case rules. A user interface is devised for this system. The system proposed here will be used for law education, where the target law of the system is contract, especially as it relates to the United Nations Convention on Contracts for the International Sale of Goods (CISG).
Statutory Interpretation by Case-Based Reasoning through Abductive Logic Programming
Authors: Satoh Ken ,   Division of Electronics and Information Enginnering, Hokkaido University, N-13 W-8, Sapporo, 060, Japan
Published: April 2016

This paper presents a method for solving statutory interpretation problem in the legal domain by using abductive logic programming. To interpret a rule, we must make an interpretation for legal predicates and terms in the rule; this interpretation is subject to change according to context. In this paper, we solve this problem byomparing and contrasting cases such as the CABARET system. This is done by translating case-based reasoning into abductive logic programming so that similarity between cases with respect to every undefined proposition in the rule is regarded as a set of abducibles that can be changed according to context. Our method is sound and complete in the sense that every possible interpretation is computed exactly.
Legal Reasoning Using Abductive Logic Programming
Authors: Kanai Takashi ,   School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Tatsunokuchi, Noumi, Ishikawa, Japan, Kunifuji Susumu
Published: April 2016

In this paper, we propose a new legal reasoning system using abductive logic programming (ALP). The system can deal with ambiguities of described facts and exceptions which is not described in relevant articles. In addition, the goal, queried to a legal reasoning system, differs in compliance with whether the user is a plaintiff or defendant. In usual deductive legal reasoning systems, there are two major problems in treating legal arguments. One is that legal facts usually have ambiguities, and the other is that two conflicting conclusions must be derived from one knowledge base, depending on whether a plaintiff of defendant is involved. To overcome these difficulties, abductive logic programming is used in our legal reasoning system, which can deal with implicit exceptions and generate presumptions according to the user’s needs.
CPF as a Tool for Constructing a Legal Knowledge Base
Authors: Sakurai Seiichiro ,   Department of Social Engineering Tokyo Institute of Technology, 2-12-1 Okayama, Meguro-ku, Tokyo 121, Japan
Published: April 2016

To construct a legal knowledge base, knowledge engineers must incorporate implicit lawyer expertise. Knowledge acquisition problems still arise in legal domains. If a lawyer can construct a legal knowledge base, the problem may be solved. CPF, a logic programming language, is proposed for lawyers to express legal knowledge. Since CPF is still complicated for lawyers, however, knowledge base written by lawyers may not be executable. This paper describes a method to construct an executable knowledge base from an unexecutable knowledge base written by lawyers. Since the most expressions written by lawyers are retained, the constructed knowledge base is comprehensible to lawyers.
A Framework for Nonmonotonic Reasoning with Rule Priorities
Authors: Shibasaki Masato ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226, Japan, Nitta Katsumi
Published: April 2016

In the 1990, a number of studies was made on nonmonotonic reasoning with rule priorities. Little is known, however, about relationships among these semantics because there is no framework in which these semantics can be compared. In this paper, we give the basis of this framework, which is a special form of Dung’s argumentation framework, although not covering all semantics of past studies in this category. To be concrete, we provide rule-based framework (RF) for extended logic programs (ELPs), clarify semantics of default rules and rule priorities, and extend it to RF for prioritized extended default logic programs (EDLPs). By means of RF for prioritized EDLPs, we reformulate several semantics of past studies , indicate their improvements, and give new prioritized EDLPs semantics.
Flowgraph Editor for Legal Articles
Authors: Miyagi Koji ,   Institute of Information Sciences and Electronics, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba-shi, Ibaraki 305-8573, Japan, Miura Motoki , Tanaka Jiro
Published: April 2016

Description using legal flowgraphs is often employed by legal experts for explaining law articles or for improving the efficiency of building knowledge bases. However, it was difficult to handle a legal flowgraph. Hence, we developed a flowgraph editor for drawing legal flowgraphs. To aid legal editing, this editor is equipped with graph layout able to handle any node size and hierarchical structure and display capable of displaying a large diagram on a single screen by magnifying local areas.
The Mutate and Spread Metaheuristic
Authors: Abboud Nicolas ,   Department of Industrial and Systems Engineering, Faculty of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima-shi, Hiroshima 739-8527, Japan, Sakawa Masatoshi
Published: April 2016

Evolutionary and adaptive search is not limited to parameter optimization. More exciting, wide-ranging possibilities arise in the search for structures, operators, and algorithms. In this paper, we present a metaheuristic that maintains a diversified population in which only the building blocks of a good solution are permitted to spread.
Computing Higher Order Derivatives in Universal Learning Networks
Authors: Hirasawa Kotaro ,   Department of Electrical and Electronic Systems Engineering, Kyushu University. Hakozaki, Fukuoka 812-81, Japan, Hu Jinglu , Ohbayashi Masanao , Murata Junichi
Published: April 2016

This paper discusses higher order derivative computing for universal learning networks that form a super set of all kinds of neural networks. Two computing algorithms, backward and forward propagation, are proposed. Using a technique called "local description" expresses the proposed algorithms very simply. Numerical simulations demonstrate the usefulness of higher order derivatives in neural network training.
Improved Fuzzy and Neural Network Algorithms for Word Frequency Prediction in Document Filtering
Authors: Baranyi Peter ,   Computer and Automation Institute Hungarian Academy of Sciences and Dept. of Automation Technical University of Budapest, Budafoki u. 8, Budapest, H-1111, Hungary, Koczy Laszlo T. , Gedeon Tamas D. ,   Dept. of Telecommunication and Telematics, Technical University of Budapest, Sztoczek u.2, Budapest, H- 1111, Hungary,   Dept. of Information Engineering, School of Computer Science and Engineering, The University of New South Wales, Sydney 2052 Australia
Published: April 2016

With very large document collections or high-volume document streams of , finding relevant documents is a major information filtering problem. An aid to information retrieval systems produces a word frequency measure estimated from important parts of the document using neural network approaches. In this paper, a fuzzy logic technique and, as its simplified case, a neural network algorithm are proposed for this task. The comparison of these two and an alternative neural network algorithm are discussed.
Generation of Fuzzy Rules from Decision Trees
Authors: Hall Lawrence O. ,   Department of Computer Science and Engineering University of South Florida Tampa, Fl. 33620, Lande Petter
Published: April 2016

The paper introduces two ways to develop fuzzy rules, using decision trees, from data with continuous valued inputs and outputs. A key problem is dealing with continuous outputs. Output classes are created, then a crisp decision tree is created using a set of fuzzy output classes and letting each training example to partially belong to classes. Alternatively, a discrete set of fuzzy outputs classes is created that includes a selected group of overlaps, such as class A.75/class B.25. Training examples are then provided to a standard decision tree learning program, such as C4.5. In both cases, fuzzy rules are extracted from the resulting decision tree. Output classes must be created for a case in which examples belong to discrete but overlapping classes. We discuss tradeoffs of the two approaches to output class creation. An example of system performance uses a discrete set of overlapping classes on the Box-Jenkins gas furnace prediction problem and a function approximation problem. The learned rules provide effective control and function approximation.
RasID - Random Search for Neural Network Training
Authors: Hu Jinglu ,   Department of Electrical and Electronic Systems Engineering, Kyushu University. 6-10-1 Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan, Hirasawa Kotaro , Murata Junichi
Published: April 2016

This paper presents a novel random search, RasID, for neural network training, that introduces a sophisticated probability density function (PDF) in a random search for generating search vectors. The PDF provides two parameters to control local search ranges and directions efficiently. This realizes an intensified search where it is easy to find good solutions locally or a diversified search to escape local minima based on success-failure of past searches. Local gradients, if available, and trend information on the criterion function surface are used to improve search performance. The proposed scheme is applied to layered neural network training and is benchmarked against deterministic and nondeterministic methods.
Stable-Optimum Gain Tuning for Designing Mobile Robot Controllers Using Incest Prevented Evolution
Authors: Hashem M.M.A. ,   Faculty of Engineering Systems and Technology, Graduate School of Science and Engineering,, Watanabe Keigo , Izumi Kiyotaka ,   Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering,,   Department of Mechanical Engineering, Faculty of Science and Engineering, Saga University 1-Honjomachi, Saga 840-8502, Japan
Published: April 2016

We present an evolution strategy (ES) algorithm - incest prevented evolution strategy (IPES) enhancing our novel evolution strategy (NES) algorithm. Validity of NES and IPES algorithms is compared with other evolutionary algorithms (EAs) and relative performances and also compared with test function results. The IPES algorithm shows the highest balance between exploration and exploitation over the NES algorithm on these test functions by achieving high-precision global results. Both algorithms are applied to solve stabilizing optimum gain tuning problems in mobile robot controllers. Two optimal servocontrollers are considered for a mobile robot with two independent drive wheels. A bidirectional fitness (cost) function is constructed for these controllers so that stable but optimum gains are tuned automatically evolutionarily instead of using a traditional algebraic Riccati equation solution. Two trajectory tracking control examples (straight line and circular) are considered for controllers. The superiority of the IPES algorithm over the NES algorithm is repeated in the application domain and the effectiveness of evolutionary gain tuning demonstrated by simulation results.
Neuronal and Hemodynamic Events from fMRI Time-Series
Authors: Rajapakse Jagath C. ,   School of Applied Science, Nanyang Technological University Block N4, Nanyang Avenue, Singapore, 639798, Singapore  (He was formerly with the Max-Planck-Institute of Cognitive Neuroscience, Leipzig.), Kruggel Frithjof , Zysset Stefan , Cramon D. Yves von ,   Max-Planck-Institute of Cognitive Neuroscience Inselstrasse 22-26, D-04103, Leipzig, Germany
Published: April 2016

Time-series provided by high-resolution functional MR imaging (fMRI) bear rich information of underlying physiological processes and associated hemodynamic events of human brain activation during sensory and cognitive stimulation. A computational model to represent neuronal and hemodynamic events in fMRI time-series is presented where the transient neuronal activities are modeled with exponential functions and coupling between neuronal response and hemodynamic response is approximated by a linear convolution. The hemodynamic parameters, namely lag and dispersion, and neuronal parameters, namely rise time and fall time, quantitate some of the neuronal and hemodynamic events following a sensory, motor, or cognitive task. Methods to estimate neuronal responses with hemodynamic demodulation and parameters assuming exponential transient changes are presented. Experiments with simulated time-series demonstrate the robustness of the parameter estimation scheme and with fMRI data obtained in a memory retrieval task is used to illustrate how the model parameters can improve detection of relevant activation in fMRI. This paper highlights the potentials of fMRI to study neuronal populations and the use of the proposed model in identifying neurophysiological events of brain function.
An Adaptive Self-Organizing Algorithm with Virtual Connection
Authors: Kawahara Shingo ,   EEE Dept., HOSEI Univ. 3-7-2 Kajino-cho, Koganei-shi, Tokyo 184-8584, Japan, Saito Toshimichi
Published: April 2016

In this paper, we propose an unsupervised learning algorithm that uses the concept of virtual connection. Performing some numerical experiments, we have confirmed that the algorithm has important functions: classification of the input space, labeling of the classified input space, and flexible adaptation to time-variant input space. The algorithm is suited for hardware implementation. An application to vector quantization is also discussed.
Evolutionary and Heuristic Approaches for the Selection of Neural Network Architectures and Parameters1
Authors: Whitfort Tim ,   Division of Information Technology, La Trobe University P.O. Box 199, Bendigo, Victoria, 3552, Australia, Matthews Chris , Choi Belinda , McCullagh John
Published: April 2016

Genetic algorithms (GAs) and neural networks have been combined in various ways in an effort to develop powerful tools for problem solving. This work presents a two-stage process for the specification of high-performing backpropagation neural networks for four commonly used real-world databases. In the first stage, GAs are used to evolve a set of potential neural network architectures and operating parameters. The best networks are then used for further training and testing, to determine an optimum starting seed and number of training passes. We also compare the evolved network architectures and operating parameters from stage I with some of the backpropagation neural network (BPNN) design heuristics previously reported in the literature. In order to test and compare networks specified in this way, an exhaustive set of experiments using the machine learning induction algorithm, C4.5 were also carried out on the four databases. These results, together with some previously published benchmark data and BPNN results, were then compared with those obtained from the networks developed using our method. Our results compare more than favorably with the C4.5, benchmark, and previously published BPNN results across the four databases.
Fuzzy Clustering for Detecting Linear Structures with Different Dimensions
Authors: Umayahara Kazutaka ,   Institute of Information Sciences and Electronics University of Tsukuba Tsukuba, Ibaraki 305-8573, Japan, Nakamori Yoshiteru , Miyamoto Sadaaki ,   Graduate School of Knowledge Science Japan Advanced Institute of Science and Technology, Hokuriku Tatsunokuchi, Ishikawa 923-1292, Japan
Published: April 2016

One recent interest in fuzzy clustering is the simultaneous determination of a fuzzy partition of a given dataset and parameters of assumed models having different shapes that explain partitioned datasets. We propose an objective function to detect linear varieties with different dimensionalities. The noise cluster suggested by Dave is introduced. Since this is not all-purpose method, some techniques are suggested using artificial examples to show how to implement clustering successfully.
On Dynamic Clustering Models for 3-way Data
Authors: Sato-Ilic Mika ,   University of Tsukuba Inst. of Policy and Planning Sciences Tenodai 1-1-1, Tsukuba 305-8573, Japan
Published: April 2016

This paper presents clustering models for 3-way data consisting of similarities of objects over several times. Conventional methods for such 3-way data yields results showing the latent structure of inheritance over times, but cannot show exact changes of clusters over times. The advantage of proposed techniques for classifying 3-way data is showing exact changes, therefore the results for several times are comparable on the same coordinate of the solution’s space. The validity of these models is demonstrated by several examples.
A Fuzzy Linear Regression Analysis for Fuzzy Input-Output Data Using the Least Squares Method under Linear Constraints and Its Application to Fuzzy Rating Data
Authors: Takemura Kazuhisa ,   Institute of Policy and Planning Sciences, University of Tsukuba 1-1-1 Tennoudai Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

Fuzzy linear regression analysis using the least squares method under linear constraint, where input data, output data, and coefficients are represented by triangular fuzzy numbers, was proposed and compared to possibilistic linear regression analysis proposed by Sakawa and Yano (1992) using fuzzy rating data in a psychological study. Major findings of the comparison were as follows: (1) Under the proposed analysis, the width between the maximum and minimum of the predicted model was nearer to the width of the dependent variable than that of possibilistic linear regression analysis, (2) the representative prediction by the proposed analysis was also nearer to that of the dependent variable, compared to that of possibilistic linear regression analysis.
Study on Intelligent Vehicle Control Considering Driver Perception of Driving Environment
Authors: Takahashi Hiroshi ,   Nissan Research Center, Nissan Motor Co., Ltd., Kuroda Kouichi
Published: April 2016

We propose an approach to designing an intelligent vehicle controller for partially supporting driver operation of a vehicle. Driving is thought of as a system formed by the interaction between the driving environment, vehicle action, and driver expectations of the vehicle. Driver expectations during driving receive great attention. Driver intent to accelerate or decelerate is mainly generated by the perception of the driving environment. The model we propose involves information on the driving environment affecting driver intent taking driver differences in perceiving the driving environment into account. The model is represented affordance implicitly. An engineering model for installing the vehicle controller is expressed by a multipurpose decision maker allowing explicit treatment of the driving environment, vehicle action, and driver intent. A reasoning engine deals with differences in individual driver traits for generating intent to decelerate by using fuzzy integrals and measures. For example, a control procedure designed with the proposed model is applied to power train control. Simulation and experimental results show good performance by the vehicle control system.
Determinism Measurement in Time Series by Chaotic Approach and Its Applications
Authors: Fujimoto Yasunari ,   Meidensha Corporation 36-2 Nihonbashi Hakozakicho, Chuo-ku, Tokyo 103-8515, Japan, Iokibe Tadashi
Published: April 2016

Frequently irregular-looking time series may have a deterministic cause, which is why it is called deterministic chaos. Even if a time series has a little noise, it is not always easy to recognize noise by looking at data. Fast Fourier transform (FFT) is used to extract characteristic frequencies. A chaotic time series consists of an infinite number of frequency elements, producing a broad continuous power spectrum but has few distinguishable characteristics. We propose a way, called trajectory parallel measurement (TPM), based on the chaotic approach to distinguish determinism and randomness in a time series, and apply this to a chaotic time series with random noise, summarizing the results of practical application in diagnosing automatic transmission.
Nonlinear Model Following Control via Takagi-Sugeno Fuzzy Model
Authors: Taniguchi Tadanari ,   Department of Mechanical and Control Engineering The University of Electro-Communications 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan, Tanaka Kazuo
Published: April 2016

This paper presents a unified approach toward regulation and servocontrol problems as special cases of a nonlinear model following control via the Takagi-Sugeno fuzzy model. New parallel distributed compensation (PDC) is presented for realizing a nonlinear model following control. The new PDC fuzzy controller mirrors the structures of two Takagi-Sugeno fuzzy models representing a nonlinear system and nonlinear reference model. First, we derive linear matrix inequality (LMI) conditions to linearize the error system between the feedback system and the nonlinear reference model. A controller is designed using LMI conditions. Design examples verify the usefulness of nonlinear model following control.
Hierarchical Control System with Fuzzy Supervisory System and PID Controller and Application to Large-Scale Hydrogen Gas Purity Control
Authors: Tani Tetsuji ,   Manufacturing Department, Idemitsu Kosan Co., Ltd., Kobayashi Takahiro , Miyamoto Sadaaki ,   Institute of Information Sciences and Electronics, University of Tsukuba 1-1-1 Tennoudai, Tsukuba-shi, Ibaraki 305-8573, Japan
Published: April 2016

We present hierarchical control that combines conventional PID controllers and their supervisory fuzzy control designed based on human knowledge. Hierarchical control consists of 2 control function blocks, where we use (1) a statistical model using multiregression with an updating factor for the function block to estimate parameters of plant operations and (2) fuzzy logic for the control function block to compensate for operating conditions. Hierarchical control has been applied to hydrogen gas purity control in large-scale petroleum-refining plants. It has been verified that this control shows better performance than conventional human supervisory control and (1) reduces operator interaction, (2) cuts energy consumption, and (3) lowers CO2 generation.
Fuzzy Set Based Neural Networks: Structure, Learning and Application
Authors: Caminhas Walmir ,   Federal University of Minas Gerais, Tavares Hermano , Gomide Fernando , Pedrycz Witold ,   State University of Campinas Faculty of Electrical & Computer Engineering 13083-970 Campinas, Sao Paulo, Brazil,   University of Alberta Dept. of Electrical & Computer Engineering Edmonton, Canada T6G 2G7
Published: April 2016

We introduce a class of neural network constructed from fuzzy set models of neurons. The network has a multilayer, feed-forward structure whose units are modeled through triangular norms and co-norms, and weights within the unit interval. The neuron models provide a wide spectrum of design choices - a desirable feature whenever real-world applications are of concern. We focus on pattern classification problems to introduce main concepts and algorithms. The learning procedure does not need any information about derivatives - a very convenient feature within fuzzy set theory that makes the procedure efficient and fast. We provide procedures to construct the network, initialize weights properly, and automatically generate classes of membership functions. Knowledge is easily extracted from the network as ifthen rules. Computational examples demonstrate neurofuzzy network performance and efficiency. We conclude with remarks on computational complexity analysis and a prospectus for further developments.
Solving Fuzzy Problems in Operations Research
Authors: Buckley James J. ,   Department of Mathematics, University of Alabama at Birmingham Birmingham, Alabama, 35294, USA, Feuring Thomas , Hayashi Yoichi ,   Department of Electrical Engineering and Computer Science, University of Siegen H61derlinstr. 3, 57068 Siegen, Germany,   Department of Computer Science, Meiji University 1-1-1 Higashimita, Tama-ku, Kawasaki, 214-8571, Japan
Published: April 2016

Fuzzy optimization problems to which traditional methods - calculus and crisp algorithms - are not directly applicable have not been completely solved. We used evolutionary algorithms to produce good approximate solutions to fuzzy optimization problems including fully fuzzified linear programming, nonlinear fuzzy regression, neural net training, and fuzzy hierarchical analysis. We applied our evolutionary algorithm package to generating good approximate solutions to fuzzy optimization problems in operations research including the fuzzy shortest route problem and the fuzzy min-cost capacitated flow problem.
Knowledge-Based Approach in Intelligent Handwritten Form Processing
Authors: Ding Liya ,   Institute of Systems Science National University of Singapore, Singapore 31 Science Park Road SNS hub, Singapore 117611, Lui Ho Chung ,   Kent Ridge Digital Labs, Singapore 21 Heng Mui Keng Terrace, Singapore 119613
Published: April 2016

In this paper, we introduce a knowledge-based approach applied in the postprocessing of intelligent hand-written fax-form processing. This approach significantly improves recognition in application systems. The main topics covered in this article include (a) hierarchical representation of knowledge, (b) description of domain knowledge, and (c) inference mechanisms on the knowledge hierarchy.
Professor Ernest Czogala Memorial Issue Part 2
Authors: Hayashi Yoichi ,   Guest Editor of Professor Ernest Czogala memorial issueDept. of Computer Science Meiji University1-1-1 Higashimita, Tama-ku Kawasaki 214-8571, Japan
Published: April 2016

After the publication of Professor Ernest Czogala Memorial Issue Part 1, I found 2 obituaries, one in the International Journal of Applied Mathematics and Computer Science, Vo1.9 No.1, published by the Technical University Press, Poland, by Maria Drelichowska and Lucjan Karwan of the Technical University, Silesia, Gliwice, Poland. The other was published"Fuzzy Systems in Medicine" (P.S. Szczepaniak eds.), Physica-Verlag, published in January 2000, which included my paper,"Fuzzy and Crisp Logical Rule Extraction Methods in Application to Medical Data," which I wrote in collaboration with W. Duch et al. This issue includes the final paper,"A Classifier Based on Neurofuzzy Inference," by Ernest Czogala, Jacek Leski, and Yoichi Hayashi, which is why this edition has been published later than planned. I would like include a comment by Samuel Ullman, written in Birmingham, Alabama, where Ernest's cousin and researcher James J. Buckley works: "Youth is not a time of life; it is a state of mind... Nobody grows old merely by years. We grow old by deserting our ideals." The Samuel Ullman Museum at the University of Alabama is at 2150 15th Avenue South, Birmingham, Alabama 35294-1150 (phone:001(205)934-5634), thanks to citizens of Japan and the United States. We thank Drs. Toshio Fukuda and Kaoru Hirota, Editors in Chief of the JACI, for accepting my proposal for this special issue. Special thanks also go to the referees for their cooperation, devotion, and review. We also thank Fuji Technology Press President Keiji Hayashi for his dedicated work.