bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards Decentralized Production: A Novel Method to Identify Flexibility Potentials in Production Sequences Based on Flexibility Graphs
Authors: Bochmann Lennart ,   Volkswagen AG, Gehrke Lars , Böckenkamp Adrian , Weichert Frank , Albersmann Rainer , Prasse Christian , Mertens Christoph , Motta Marco , Wegener Konrad ,   Institute of Machine Tools and Manufacturing, ETH Zurich, Zurich, Switzerland,   Chair of Enterprise Logistics, Technical University of Dortmund, Dortmund, Germany,   Department of Computer Science VII, Technical University of Dortmund, Dortmund, Germany,   F/L/S Fuzzy Logik Systeme GmbH, Dortmund, Germany,   Fraunhofer Institute for Material Flow and Logistics, Dortmund, Germany
Published: April 2016

Due to higher degrees of individualization, shorter product life cycles, and volatile selling markets, fulfilling customer demands -- the main task of automotive companies -- has become very complex. In order to tackle this complexity, new concepts that enable the decentralization of decision-making within the production process have become promising solutions. The advancement towards self-organized production requires novel approaches in the field of production program planning. This work introduces the concept of thevolume cycleas a new design factor in program planning. Additionally, a novel method to identify flexibility potentials in production sequences based on ,flexibility graphsis proposed, and the method is validated through a case study considering a segment of the assembly process for an automobile. Suitable visualization techniques for flexibility graphs are also discussed. Furthermore, in order to allow automatic analysis and evaluation of the flexibility potentials, methods of graph mining are introduced and the application possibilities of these techniques in terms of analyzing flexibility graphs are clarified. The results obtained from the case study illustrate that routing flexibility is not leveraged in today’s production lines, thus revealing a potential optimization domain.
Performance of High-Speed Precision Air-Bearing Spindle with Active Aerodynamic Bearing
Authors: Mizumoto Hiroshi ,   Tottori University, Tazoe Yoichi , Hirose Tomohiro , Atoji Katsuhiko ,   Nachi-Fujikoshi Corp.
Published: April 2016

A high-speed precision air-bearing tool spindle with active aerodynamic bearing is proposed for improving the quality of machining using small-diameter cutting and grinding tools. The spindle is basically supported by aerostatic radial and thrust bearings. According to the spindle vibration detected by capacitance sensors, the wedge angle of the active aerodynamic bearing was controlled using piezoelectric actuators, thereby suppressing the spindle vibration. In the present paper, the performances of a prototype air-bearing spindle with single-row active aerodynamic bearing and an improved air-bearing spindle with double-row bearings are reported. Through experiments, it was demonstrated that the maximum rotational speed controlled by the active aerodynamic bearing is 800 Hz (48,000 min-1), and that the amplitude of spindle vibration can be suppressed to <50 nm at the rotational speed of 500 Hz (30,000 min-1).
Characterization Methods of Nano-Patterned Surfaces Generated by Induction Heating Assisted Injection Molding
Authors: Menotti Stefano ,   Department of Mechanical Engineering, Technical University of Denmark, Bissacco Giuliano , Hansen Hans Nørgaard , Tang Peter Torben , Ravn Christian ,   IPU, Kgs. Lyngby Denmark
Published: April 2016

An induction heating-assisted injection molding (IHAIM) process developed by the authors is used to replicate surfaces containing random nano-patterns. The injection molding setup is developed so that an induction heating system rapidly heats the cavity wall at rates of up to 10°C/s. In order to enable the optimization of the IHAIM process for nano-pattern replication, it is necessary to develop robust methods for quantitative characterization of the replicated nano-patterns. For this purpose, three different approaches for quantitative characterization of random nano-patterns are applied and compared. Results show that the use of IHAIM is an efficient way to improve replication quality. All three measurement methods are capable of detecting the trend of the replication quality of the surface changing the process condition.
Development of Online Real-Time Collision Free Machining Using Simulation with CNC Openness
Authors: Hida Tomoya ,   Aikoku Alpha Corporation, Asano Tetsuya , Nishita Kazuhiro , Sakai Norio , Goto Akinobu , Takeuchi Yoshimi ,   American Aikoku Alpha Inc.,   Department of Mechanical Engineering, Chubu University
Published: April 2016

In recent years, 5-axis machine and multi-tasking machine have seen wide spread use. These tools can contribute to the enhancement of machining efficiency and precision. Conversely, their complex motion can cause numerous collision accidents between machines, tools, materials, and other parts. To prevent such accidents, it is now common to verify numerical control (NC) data using a machine motion simulator before performing the actual machining. However, the actual machining process is not always conducted in the expected manner. In some cases, the machining process is manually defined or altered, possibly causing a collision accident. In the present study, an online real-time collision free system was developed for the prevention of unexpected collisions. The effects of using this system are described in this article.
A MOEMS Accelerometer Based on Diffraction Grating with Improved Mechanical Structure
Authors: Lu Qianbo ,   State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Lian Wenxiu , Lou Shuqi , Wang Chen , Bai Jian , Yang Guoguang
Published: April 2016

In this study, an improved MOEMS (micro-optical electronic mechanical system) accelerometer based on integrated grating with phase modulation is proposed. This device is composed of a laser diode, an optoelectronic processing circuit, a sensing chip (consisting of a piezoelectric translator), an integrated grating as a reflective mirror on a transparent substrate, and a mechanical part of a bulk silicon proof mass suspended by four cantilevers whose upper surface acted as another mirror. This device generates a series of interference fringes by two diffracted beams when illuminated with a coherent light source, whose intensities are modulated by the relative distance between the grating and the proof mass. The intensities of the interference fringes varied with alterations in the distance caused by external accelerations that are proportional to the acceleration. The magnitude of acceleration can be calculated by using a differential circuit detecting the distance. The modified structure introduced in this paper obtains high sensitivity and reduces cross-sensitivity between different sensitive axes. The experimental results before the simulation and theory analysis demonstrate that this modified MOEMS accelerometer has a good performance with higher static acceleration sensitivity of 3 x 310V/g and very low crosstalk.
Automatic Recording Absolute Length-Measuring System with Fast Optical-Comb Fiber Interferometer
Authors: Matsumoto Hirokazu ,   Department of Precision Engineering, The University of Tokyo, Takamasu Kiyoshi ,   Tokyo Seimitsu Co., Ltd.
Published: April 2016

The optical frequency comb has a short pulse, broad spectra, many spectral lines, and high temporal coherency. In this paper, a new absolute length-measuring technique with a high resolution of 0.05 μm is developed by using the temporal-coherence interferometry of the optical comb. A new fiber Fabry-Perot etalon (etalon) of a free spectral range with a frequency of 15 GHz is developed to improve fine positioning in space, so a short translation stage of up to a 10 mm movement is realized for various ranges of length. Moreover, the interference fringe peak is automatically detected by developing a new analog electrical circuit. The ambiguity of the interference-fringe orders is determined by using the etalon at a frequency 14.9 GHz within a time of 1 second for various length ranges.
Development of Dimensional X-Ray Computed Tomography
Authors: Fujimoto Hiroyuki ,   National Metrology Institute of Japan (NMIJ), National Institute of Advanced Industrial Science and Technology (AIST), Abe Makoto , Osawa Sonko , Sato Osamu , Takatsuji Toshiyuki
Published: April 2016

Recently, a strong need has arisen for a dimensional X-ray computed tomography system that is capable of dimensional measurements. This is because the speedy realization of dimensional measurements for outward forms and inward forms on dense spatial points remarkably simplifies and accelerates production loop. However, although the image obtained via XCT describes the structure clearly and in great detail, dimensional metrology by means of XCT is not simple. The National Metrology Institute of Japan has been carrying out performance tests using gauges that include the gauges proposed in ISO10360. In this work, the magnification variation correction is carefully presented, and a maximum deviation of less than 5 μm is shown to be possible by means of the measurement of the forest phantom of 27 ruby spheres, the locations of which are calibrated by the coordinate measuring machine.
Detection of Human Position and Motion by Thermopile Infrared Sensor
Authors: Zhang Xipeng ,   Graduate School of Natural Science and Technology, Kanazawa University, Seki Hiroaki , Hikizu Masatoshi
Published: April 2016

Devices such as pyroelectric infrared sensors, ultrasonic sensors, cameras can be used to detect the presence of human-beings, but their systems have some problems related to low detection ability, low resolution, privacy, and high cost. We propose the use of thermopile infrared sensors without focus lenses and with high-gain amplifiers to detect the position and movement of human subjects. The system can detect even people that are not moving. This paper presents an approach that uses two thermopile sensors mounted on the ceiling to detect in 2D the position and orientation of human bodies. After each sensor takes measurements, we can build an approximate equation set that takes into account the output voltage, distance, and orientation of the human presence. The equation set can be solved, using the steepest descent method for the outputs of the two sensors, to obtain in real-time the position of a human-being in 2D. Body orientation can also be basically obtained by detecting slight changes in some positions while the human subject is moving. Tests are carried out to confirm that the proposed system works.
Analysis of the Coupled Vibration Between Feed Drive Systems and Machine Tool Structure
Authors: Sato Ryuta ,   Department of Mechanical Engineering, Kobe University, Tashiro Gen , Shirase Keiichi ,   KUBOTA Corporation
Published: April 2016

In this study, we have constructed a mathematical model that can analyze the coupled vibration of machine tool structure and feed drive systems. The model is proposed on the basis of the modal analysis of the actual machine tool structure. It consists of three translational and three rotational displacements of the bed, relative angular deformations between the bed and column, relative translational and angular deformations between the bed and saddle, and relative translational and angular deformations between the column and spindle head. In addition, each feed drive system is modeled using a vibration model, which has two degrees of freedom. The servo controllers of each axis are also modeled. To confirm the validity of the proposed model, frequency responses, motion trajectories of the feedback positions, linear scale positions, and the relative displacement between the table and head are measured and simulated. The effect of coupled vibrations on the tracking errors is examined with the help of both experiments and simulations. To investigate the effect of the servo systems on the vibration, both experiments and simulations are carried out by using feed drive systems in the following three conditions: mechanically clamped, servo-on, and servo-off. The results of experiments and the simulations show that the proposed model can express the mode of vibration and the influence of the condition of feed drive systems on the mode of vibration.
Development of Heating and Cooling Injection Mold with Far-Infrared Radiation Heater
Authors: Murata Yasuhiko ,   Department of Mechanical Engineering, Nippon Institute of Technology, Kuramochi Masahiro
Published: April 2016

Several rapid heating and cooling molding methods have been developed for practical use to improve the surface quality of plastic injection-molded products. These methods, however, need expensive equipment and complex molds that require vast know-how, and hence cannot be applied easily to actual production. In order to establish a molding method in which the mold’s cavity surfaces can easily be heated, we designed and manufactured a heating and cooling injection mold with a far-infrared radiation heater. Using this mold, we molded a high-impact polystyrene molded product, and found that the use of such a mold could lead to a decrease in the V-shaped groove depth of weld lines, as well as to an improvement in the transcription of the mold’s cavity surface quality onto the molded product. We also carried out tensile tests on the molded products to confirm whether the use of such a mold could increase the product’s elongation at break.
Structure Analysis with 2D Quadrilateral Meshes Generated by a Label-Driven Subdivision
Authors: Liu Bo ,   Shizuoka University, Miura Kenjiro T. , Usuki Shin ,   ,
Published: April 2016

For a structural analysis using the finite element method, a hexahedral element is preferable to a tetrahedral element from the viewpoint of accuracy. However, it is very difficult to subdivide a mesh consisting of hexahedral elements if the shape of the mesh is complicated. Hence, in this paper, as a preliminary research, we use a label-driven subdivision method for a two-dimensional mesh, and show that meshes subdivided nonuniformly can guarantee as much accuracy as meshes with uniform subdivision.
A Digital Grain Generation Method Suitable for Geometric Textures
Authors: Miyachi Ryoji ,   Shizuoka University, Usuki Shin , Miura Kenjiro T. ,   ,
Published: April 2016

The automated production of products using digital data has been realized in recent years through the development of manufacturing machines. Digital data are also used for automatic texturing. In a product texturing system using digital data, texture information needs to be incorporated in the generation of digital data. However, it is difficult to generate such data manually since it is not easy to fit the texture to the product or to prevent the texture pattern from being stretched or shortened. Therefore, what is needed is a method of automatically generating digital data that yields a seamless texture with little distortion and a method of fitting the texture to the product shape. In this paper, the application of the Angle Based Flattening (ABF) method by Sheffer and de Sturler to the generation of digital data of textures is proposed. Another method to extend the ABF technic to make it more suitable to geometric textures is also proposed.
SIRMs (Single Input Rule Modules) Connected Fuzzy Inference Model
Authors: Yubazaki Naoyoshi ,   Mycom, Inc., 12, S. Shimobano-cho, Saga Hirosawa, Ukyo, Kyoto 616, Japan, Yi Jianqiang , 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 new fuzzy inference model, SIRMs (Single Input Rule Modules) Connected Fuzzy Inference Model, is proposed for plural input fuzzy control. For each input item, an importance degree is defined and single input fuzzy rule module is constructed. The importance degrees control the roles of the input items in systems. The model output is obtained by the summation of the products of the importance degree and the fuzzy inference result of each SIRM. The proposed model needs both very few rules and parameters, and the rules can be designed much easier. The new model is first applied to typical secondorder lag systems. The simulation results show that the proposed model can largely improve the control performance compared with that of the conventional fuzzy inference model. The tuning algorithm is then given based on the gradient descent method and used to adjust the parameters of the proposed model for identifying 4-input 1-output nonlinear functions. The identification results indicate that the proposed model also has the ability to identify nonlinear systems.
Fuzzy Temporal Methods for Video Multimedia Information Systems
Authors: Yager Ronald R. ,   Machine Intelligence Institute, Iona College, New Rochelle, NY 10801
Published: April 2016

We consider here the issue of querying video multimedia information systems. Central to this problem is the ability to specify and represent various natural temporal concepts used in the formulation of queries posed by the users of these systems. It is suggested that fuzzy set technology provides a very useful formalism for representing these temporal concepts. We then investigate various aspects of the use of fuzzy set methods for the retrieval of information in annotated video multimedia systems.
Attacking Legal Argument by Pointing Out the Incoherence of Interpretation of Statute
Authors: Okubo Yoshiaki ,   Division of Electronics and Information Engineering, Hokkaido University, N-13 W-8, Sapporo 060, Japan, Haraguchi Makoto
Published: April 2016

This paper presents a computational model for attacking legal arguments. Assume that, for a case with which we are concerned, an opponent side has constructed a legal argument based on analogical interpretation of a statute. In our model, the argument is attacked by pointing out the incoherence of the analogical interpretation of the statute. To examine such incoherence, we create a hypothetical case C' that is similar to the case in question, with the help of a Goal-Dependent Abstraction framework. Intuitively speaking, we create C' based on a similarity that is consistent with the similarity based on which the opponent's analogical interpretation has been made. Therefore, we can reasonably consider from the viewpoint of legal stability that the statute should be analogically interpreted to apply it to C' if we accept the opponent's interpretation. The incoherence of the analogical interpretation can be examined by finding a precedent in which the statute has been applied to C' based on complete interpretation. It should be noted that a legal argument based on complete interpretation of the statute has a conclusion that is opposite to that of the argument based on analogical interpretation. Therefore, if we find such a precedent, we attack the opponent's argument by pointing out the incoherence of interpretation of the statute and presenting a counterargument having the opposite conclusion.
Towards the Systematization of the Japanese Maritime Traffic Law
Authors: Matsumoto Hiroyuki ,   Faculty of Traffic Safety Science, Maritime Safety Academy, 5-1 Wakaba-cho, Kure-shi, Hiroshima 737, Japan
Published: April 2016

The existing laws and regulations function as a social engineering system in the vertically-structured society. However it is difficult for nonprofessionals to understand the legal knowledge which has, abstract expressions for provisions, the hierarchy structures of legal systems, the richness of legal text, the deficiency of laws, and so on. In this paper, I discuss, through a jurimetrics approach, the possibility of the systematization of legal knowledge (maritime traffic laws and regulations in Japan; a kind of public law) which is complicated in its structures and nature. Also, I propose, for the purpose of legal norm sentences analysis, the model of legal thoughts and the method of logical formalization using first-order predicate logic.
Natural Language Generation for Legal Expert System and Visualization of Generation Process
Authors: Miyata Takashi ,   Graduate School of Information Science,, Matsumoto Yuji
Published: April 2016

An HPSG-based grammar and a sentence generation system for a small set of Japanese in legal expert domains are constructed. The system adopts its own general semantic system in which a domain-specific logical form is converted. This separation between domain-specific and linguistic semantics gives flexibility to both task processing and sentence generation. We also propose a visualization system which shows the generation process in a tabular form and operates as a graphical user interface for grammar debugging.
ViSe2 - An Agent-Based Expert Consulting System with Efficient Cooperation
Authors: Bian Cheng-Gang ,   Department of Computer Science Faculty of Science University of Tromso, Norway, Cao Wen , Hartvigsen Gunnar
Published: April 2016

ViSe2 l is an expert consulting system which employs software agents to manage distributed knowledge sources. These individual software agents solve users’ problems either by themselves or via cooperation. The efficiency of cooperation plays a serious role in Distributed Problem Solving (DPS) and Multi-Agent Systems (MAS). We have focused on the development of a twin-base approach for agents to model the capabilities of each other, and thus achieve efficient cooperation. The current version of the ViSe2 implementation is an experimental model of an agent-based expert system. Compared with other cooperation approaches in Distributed Artificial Intelligence (DAI) area, the results received so far indicate that the ViSe2 agents serve their users in an efficient cooperation manner.
Fuzzy Flexible-Flow Shops at Two Machine Centers
Authors: Hong Tzung-Pei ,   Department of Information Management, Chen Wei-Chou ,   Institute of Information Engineering, I-Shou University Kaohsiung, 84008, Taiwan, R.O.C.
Published: April 2016

In simple-flow shop problems, each machine operation center has one machine. If a machine center has more than one machine, scheduling becomes a flexible shop flow problem. Flexible shop flows are thus generalizations of simple shop flow. Processing time for each job was previously assumed to be known exactly, but in many real-world applications, processing times vary dynamically due to human or operating factors. We apply fuzzy concepts to represent uncertainty in processing times for flexible-flow shops with two machine centers, then propose a fuzzy heuristic algorithm for job scheduling. We first use a fuzzy LPT algorithm to allocate jobs, then use a fuzzy Johnson algorithm to deal with task sequencing. The proposed method lets jobs be scheduled more flexibly than conventionally.
Self-organization in Cortical Maps & EM-learning
Authors: Frisone Francesco ,   University of Genova, Dept. of Informatics, Systems, lecommunications Via Opera Pia 13, 16145 Genova (IT), Morasso Pietro G. , Perico Luca
Published: April 2016

Starting from the problem of density estimation, it is shown that Expectation Maximization (EM) learning can be considered a Hebbian mechanism. From this, it is possible to outline a theory of self-organization of cortical maps, which is based on a well-defined optimization process and preserves biologically desirable characteristics such as local computation and uniform treatment of input and lateral connections. A thalamocortical network is described that implements the theory in a fully distributed manner: it uses cortical dynamics for the E-step and Hebbian adaptation of cortico-cortical connections at steady state for the M-step.
A Semantic-Ambiguity-Free Relational Model for Handling Imperfect Information1
Authors: Nakata Michinori ,   Department of Information Science, Chiba-Keizai College
Published: April 2016

An extended relational model without semantic ambiguity, called a semantic-ambiguity-free relational model, is proposed using fuzzy sets and the theory of possibility. The model features every attribute having a membership attribute whose value consists of a pair of values based on necessity and possibility measures. The membership attribute value of an attribute in a base relation is the degree to which the attribute value is compatible with integrity constraints imposed on the base relation. This clarifies the source of the membership attribute value. The model has no semantic ambiguity for interpreting membership attribute values, unlike models consisting of relations with membership attribute values attached to tuple values. We show the formulation of 8 operations - union, intersection, difference, Cartesian product, projection, join, selection, and quotient - consisting of relational algebra proposed by Codd for query processing. This approach shows how to prevent users from misinterpreting tuples in databases allowing imperfect information.
Simulated Evolution and Learning
Authors: Yao Xin ,   School of Computer Science The University of Birmingham Edgbaston, Birmingham B15 2TT, U. K.URL: http://www.cs.bham.ac.uk/˜xin
Published: April 2016

Evolution and learning are two fundamental forms of adaptationl,2). Simulated evolution and learning refers to the study of techniques and methods inspired by Nature for solving complex and difficult real-world problems. These techniques and methods include evolutionary algorithms3), fuzzy learning algorithms, neural learning algorithms, and various statistical learning methods such as nearest neighbor classifiers. In addition to various learning tasks, these techniques and methods have also been applied to various difficult optimization problems that cannot be solved effectively by classical methods (such as mathematical programming methods). This special issue contains six papers selected from those presented at the Second Asia-Pacific Conference on Simulated Evolution And Learning (SEAL'98), Canberra, Australia, 24-27 November 1998. However, all six papers have been rereviewed and substantially extended and revised. They represent significant improved work from their original SEA L'98 papers. The six papers can be grouped into three categories. The first two papers by He et al. and by Ishibuchi and Nakashima described novel applications of genetic algorithms to nearest neighbor classifiers. The next two papers by Kawakami et al. and by Tachibana and Furuhashi presented new fuzzy learning systems. The last two papers by Myung and Kim and by Yu and Wu discussed constrained optimization using the evolutionary approach. I would like to take this opportunity to thank Dr Bob McKay, the SEAL'98 Organizing Committee Chair, for playing a pivotal role in organizing the very successful SEAL'98, Professor Kaoru Hirota, the Editor-in-Chief of the Journal of Advanced Computational Intelligence, for encouraging me to edit this special issue, and all the authors for their high-quality work. References: 1)X. Yao, J-H. Kim, and T. Furuhashi, eds., Simulated Evolution and Learning, Vol. 1285 of Lecture Notes in Artificial Intelligence. Berlin, Germany: Springer-Verlag, 1997. 2)B. Mckay, X. Yao, C. S. Newton, J-H. kim, and T. Furuhashi, eds., Simulated Evolution and Learning, Vo1.1585 of Lecture Notes in Artificial Intelligence. Berlin, Germany: Springer-Verlag, 1999. 3)X. Yao, ed., Evolutionary Computation: Theory and Applications. Singapore: World Scientific Publishing Co., 1999.
Dynamic Multidimensional Wavelet Neural Network and Its Application
Authors: Yon Jung-Heum ,   Department of Electronic Engineering, Chung-Ang University 221 Huksuk-dong, Dongjak-gu, Seoul 156-756, Korea, Kim Yong-Taek , Seo Jae-Yong , Jeon Hong-Tae
Published: April 2016

We propose an efficient neural network called a dynamic multidimensional wavelet neural network (DMWNN). Since the resulting network based on wavelet theory can provide the efficient representation of a nonlinear function and has the capability to keep some previous information for later use, it can perform effective dynamic mapping with lower input signal dimensions. These features of the DMWNN show one way to compensate for the weakness of the diagonal recurrent neural network (DRNN) and feed-forward wavelet neural network (FWNN). Effectiveness in application of the proposed neural network is also demonstrated through simulation results.
Anytime Evaluation of Regression-Type Algorithms
Authors: Várkonyi-Kóczy Annamária R. ,   Department of Measurement and Information Systems, Kovácsházy Tamás , Takács Orsolya , Benedescik Csaba
Published: April 2016

Regression-type algorithms are widely used for system modeling and characterization. There are applications where such characterizations are to be performed online to support control mechanisms and other decisions. In embedded autonomous systems, robustness considerations ask for techniques that, in addition to reflecting the actual state of the system and its environment, can continuously provide immediate signal processing results even in case of abrupt changes and/or temporal shortage of computational power and/or loss of some data. In other words, in such situations, actual processing should be continued to ensure appropriate performance. Consequently there is a need for robust techniques called "anytime" algorithms, which can provide short response time and be very flexible with respect to the available input information and computational power. This paper presents some considerations concerning such flexibility in the case of regression-type algorithms.
Rank-Based Multiple Classifier Decision Combination: A Theoretical Study
Authors: Saranli Afsar ,   Speech Processing Laboratory, Department of Electrical and Electronics Engineering Middle East Technical University Ismet Inonu Bulv. 06531, Ankara, Turkiye, Demirekler Mubeccel
Published: April 2016

This study presents a theoretical investigation of the rank-based multiple classifier decision problem for closed-set pattern identification. The problem of combining the decisions of more than one classifiers with raw outputs in the form of candidate class rankings is considered and formulated as a general discrete optimization problem with an objective function based on the total probability of correct decision. This formulation uses certain performance statistics about the joint behavior of the ensemble of classifiers, which need to be estimated from cross-validation data. An initial approach leads to an integer (binary) programming problem with a simple and global optimum solution but of prohibitive dimensionality. Therefore, we present a partitioning formalism under which this dimensionality can be reduced by incorporating our prior knowledge about the problem domain and the structure of the training data. It is also shown that formalism can effectively explain a number of successfully used combination approaches in the literature.
Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application
Authors: Kasabov Nikola ,   Department of Information Science, University of Otago, P.O.Box 56, Dunedin, New Zealand, Kim Jaesoo , Kozma Robert , Cohen Tico ,   Waste Solutions Ltd, P.O.Box 997, Dunedin, New Zealand
Published: April 2016

The paper presents a method for rule extraction from fuzzy neural networks FuNN. The method is applied to a real problem - adaptive control of a wastewater treatment reactor The method extracts from a trained FuNN fuzzy rules that have coefficients of importance and certainty factors attached to their condition and conclusion parts respectively. The rules can have different levels of abstraction depending on the chosen values of several parameters. General rules can be used for explanation and understanding purposes, while precise and specific rules can be used for inference over new data.
Semi-stratified Motion Planning of Multi-agent Manipulation
Authors: Harmati István ,   Department of Control Engineering and Information Technology Budapest University of Technology and Economics, H-1117 Pazmany Peter s6tany I /D, Budapest, Hungary, Lantos Ma , Payandeh Shahram ,   Experimental Robotics Laboratory School of Engineering Science, Simon Fraser University, 8888 University Drive Burnaby, British Columbia, Canada V5A IS6
Published: April 2016

The paper addresses a manipulation problem based on kinematic model where the equations of the motion of the system can change discontinuously depending on the actual state of the system. In this case, the configuration space is stratified. The stratified control theory using the smooth motion planning algorithm promises a powerful alternative for this manipulation problem, however, it meets also some significant difficulties. The paper presents the main steps of developing computational frame work and some improvements for stratified motion planning. The concept proposes a semi-stratified method which decomposes the manipulation problem into stratified motion planning and pure finger relocation through the special selection of the reference points. Because of the different type of computational tasks (symbolic, numerical), the realization steps are also investigated.
Approximate Data Querying in Fuzzy Relational Database
Authors: Intan Rolly ,   Department of Computer Science, Meiji University, Kawasaki-shi, Kanagawa-ken, Japan, Mukaidono Masao ,   Petra Christian University, Siwalankerto, 121-131, Surabaya, Indonesia 60236
Published: April 2016

Fuzzy relational database was proposed for dealing with imprecise data or fuzzy information in a relational database. In order to provide a more realistic relation in representing similarity between two imprecise data, we need to weaken fuzzy similarity relation to be weak fuzzy similarity relation in which fuzzy conditional probability relation (FCPR, for short) is regarded as a concrete example of the weak fuzzy similarity relation. In this paper, application of approximate data querying is discussed induced by FCPR in the presence of the fuzzy relational database. Application of approximate data querying in order to provide fuzzy query relation is presented into two frameworks, namely dependent inputs and independent inputs. Finally, related to join operator, approximate join of two or more fuzzy query relations is given for the purpose of extending query system.
Developing Case-based Reasoning System for Medical Consultation Using the Importance of Features
Authors: Phuong Nguyen Hoang ,   Institute of Information Technology, National Center for Natural Science and Technology, Hoang Quoc Viet Rd., Cau Giay Dist., Hanoi, Vietnam, Tu Nguyen Ba , Ohsato Ario ,   Department of Management and Information Systems Science, Nagaoka University of Technology, 1603-1, Kami-Tomioka-Machi, Nagaoka, Niigata 940-2188, Japan
Published: April 2016

Using the Importance of Features, we present an implementation of the knowledge system that realized the diagnosis of medical diseases using case-based reasoning. The methodology of this system uses the importance of features. In our method, the feature is a symptom. The symptom represents the different important degree vis-a-vis each type of disease. In one disease, different symptoms have different important degrees. The system consists of cases as Knowledge for Diagnosis of Lung pathologies according to Vietnamese Traditional Medicine. We developed this system in Visual C++, using Microsoft Access data-base engine and it runs under Windows 9X.
Sigma-Pi Cascade Extended Hybrid Neural Network
Authors: Iyoda Eduardo Masato ,   Department of Computational Intelligence and Systems Science Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama, 226-8502 Japan, Hirota Kaoru , Zuben Fernando J. Von ,   Department of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering, State University of Campinas, P.O. Box 6101, Campinas-SP, 13083-970 Brazil
Published: April 2016

A nonparametric neural architecture called the Sigma-Pi Cascade extended Hybrid Neural Network σπ-(CHNN) is proposed to extend approximation capabilities in neural architectures such as Projection Pursuit Learning (PPL) and Hybrid Neural Networks (HNN). Like PPL and HNN, σπ-CHNN also uses distinct activation functions in its neurons but, unlike these previous neural architectures, it may consider multiplicative operators in its hidden neurons, enabling it to extract higher-order information from given data. σπ-CHNN uses arbitrary connectivity patterns among neurons. An evolutionary learning algorithm combined with a conjugate gradient algorithm is proposed to automatically design the topology and weights of σπ-CHNN. σπ-CHNN performance is evaluated in five benchmark regression problems. Results show that σπ-CHNN provides competitive performance compared to PPL and HNN in most problems, either in computational requirements to implement the proposed neural architecture or in approximation accuracy. In some problems, σπ-CHNN reduces the approximation error on the order of 10-1 compared to PPL and HNN, whereas in other cases it achieves the same approximation error as these neural architectures but uses a smaller number of hidden neurons (usually 1 hidden neuron less than PPL and HNN).
A Study on Deriving a Method for Chromosome Similarities Suitable for the Search Space
Authors: Banno Yoshifumi ,   Department of Electrical and Elecronic Engineering, Faculty of Engineering, Mie University, 1515, Kamihama-cho, Tsu, Mie, 514-8507 Japan, Yoshikawa Tomohiro , Kawanaka Hiroharu , Shinogi Tsuyoshi , Tsuruoka Shinji
Published: April 2016

Evolutionary Computations (ECs) are powerful search algorithms for nonlinear problems, and have been. widely studied. Generally, calculation of EC to acquire expected solutions takes much time because they need repeated calculation for search solutions. Hanaki et al. proposed the fitness inference to reduce evaluation time by simplifying calculation of the fitness of chromosomes. In fitness inference, how chromosome similarities is defined is very important corresponding to that of solutions. We studied chromosome similarities considering the solution similarities, and propose new chromosome similarities with the weight on each locus determined by the change of information on the locus using Sequential Difference Fitness Value Allocation. We used benchmark functions to study the feasibility of the proposed method and found that effective weights on loci suitable for the search space are automatically generated, and that the proposed method enables effective fitness inference.
GMP Based Fuzzy Reasoning: An Application to Sonar Based Navigation
Authors: Demirli Kudret ,   Fuzzy Systems Research Laboratory, Department of Mechanical & Industrial Engineering, Concordia University, Montreal, Quebec, Canada, H3G 1M8, Türksen Burhan , Molhim Mohammad ,   Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, Ontario, Canada M5S 3G8
Published: April 2016

Generalized Modus Ponens (GMP) type fuzzy reasoning is used for mobile robot navigation in this paper. However, GMP type reasoning suffers from different drawbacks that make it difficult to be used in real time applications. The objectives of this paper are to eliminate some of the drawbacks of GMP type fuzzy reasoning to make it favorable in control applications, and also demonstrate the effectiveness of the suggested improvements on a real-time application. The first drawback of GMP is its high computational requirements and the second problem is the lack of a systematic operator selection procedure. There are also other issues to be dealt with when the conclusions obtained from GMP are to be combined and defuzzified in order to be used in the control of an electro mechanical device. These drawbacks are tackled in appropriate ways and it is experimentally shown that GMP can be satisfactorily used for mobile robot navigation.
Obstacle Avoidance for Quadruped Robots Using a Neural Network
Authors: Yamaguchi Tomohiro ,   Department of Advanced Systems Control Engineering, Graduate School of Science and Engineering, Saga University, 1-Honjomachi, Saga 840-8502, Japan, Watanabe Keigo , Izumi Kiyotaka , Kiguchi Kazuo
Published: April 2016

Legged mobile robots, which differ from wheeled and crawler, need not avoid all obstacles by altering the path in the obstacle avoidance task. Because, legged mobile robots can get over or stride some obstacles, depending on the obstacle configuration and the current state of the robot. Legged mobile robots muse have suitable motion for each leg. We propose body motion control of a quadruped robot using a neural network (NN) for an obstacle avoidance task. Each leg motion is calculated by robot kinematics using body motion from the NN. NN design parameters are tuned off-line by a genetic algorithm (GA). Effectiveness of the present method is proved through an experiment.
Automatic Generation of Expressive Body Movement Based on Cohen-kestenberg Lifelike Motion Stereotypes
Authors: Nakata Toru ,   Digital Human Laboratory, National Institute for Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo 135-0064, Japan
Published: April 2016

Method of automatic choreography to generate lifelike body movements is proposed. This method is based on somatic theories that are conventionally used to evaluate human’s psychological and developmental states by analyzing body movement. This paper proposes the use of these theories in the inverse way to facilitate the generation of artificial body movements that are plausible in relation to the regarding evolutionary, developmental and emotional states of robots or other automata. This paper reviews somatic theories and describes a strategy for implementating automatic body movement generation. An additional psychological experiment is also conducted to evaluate expression ability of body movement rhythms.
Electricity Demand and Price Analysis in California Using Possibility Regression Model
Authors: Hirano Osamu ,   Graduate School of Social Sciences, Hosei University, 4342 Aihara-machi, Machida-shi, Tokyo 194-0298, Japan, Kanke Masayasu , Ozawa Kazuhiro ,   Meidensha Corporation, 127, Nishishin-machi, Ohta-shi, Gunma 373-0847, Japan,   Institute of Comparative Economic Studies, Hosei University, 4342 Aihara-machi, Machida-shi, Tokyo 194-0298, Japan
Published: April 2016

In this paper, the authors analyze the prices of electricity spot market in California. Firstly, we discuss the relation between annual demand of electricity and the temperature in California. We identify the electricity demand is related to temperature using possibility regression analysis. Then we show the fluctuation of electricity price is influenced by the demand. In the early summer season of 1998, the relationship between temperature and electricity price in California was simple. However, in the mid summer season in 1998, the price volatility of the electricity goes on increasing. Secondly we show that the expectation (speculative buying) of the market participant which is formed by temperature fluctuation induced the price volatility. We show that the price volatility is affected by temperature fluctuation for a previous few days.
High-quality Multi-level Error Diffusion Method Employing Fuzzy Inference
Authors: Suetake Noriaki ,   Institute of Engineering Mechanics and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Togashi Masanori ,   College of Engineering Systems, Third Cluster of Colleges, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

We propose a new multi-level error diffusion method employing the fuzzy inference, which realizes half toning with high quality. In the proposed method, dissimilar textures around quantization levels, which are the cause of the low image quality and obtained by a conventional method, are decreased by using fuzzy inference. In this paper, we apply the proposed method to various standard digital images. The image quality of the result using the proposed method is higher than those of other methods without noise-add filtering, and it is almost same as them with filtering in 2 or 3 times faster processing.
How to Make Programs from Problem Descriptions in the Equivalent Transformation Paradigm
Authors: Ishikawa Takahiko ,   Division of System and Information Engineering, Hokkaido University, Kita-11 Nishi-5 Kita-ku Sapporo, 060-0811 Japan, Akama Kiyoshi , Mabuchi Hiroshi ,   Information Instiative Center, Hokkaido University, Kita-11 Nishi-5 Kita-ku Sapporo, 060-0811 Japan,   Faculty of Software and Information Science, Iwate Prefectural University, 152-52 Sugo Takizawa, 020-0173 Japan
Published: April 2016

In the computation model of equivalent transformation (ET), problems are expressed by some declarative descriptions. Programs, which consist of equivalent transformation rules (ETRs), are made from the declarative descriptions, and applied to questions to solve them. The ET model can achieve various and efficient ways of problem-solving mainly due to the expressive power and priorities of ETRs. In this paper, we investigate and demonstrate, by solving a sample problem, how to make programs from problem descriptions in the ET paradigm. We introduce basic methods of generation and improvement of rules seeking for desirable ETRs. We can transform ETRs, preserving correctness of computation, through many manipulative techniques, i.e., changing from nondeterministic atoms into sequentially executable atoms, introducing multi-head rules, and adjusting priority of rules, by which we can effectively improve correct programs into both correct and more efficient programs.
Modeling and Analysis of Genetic Algorithms Based on the Viewpoint of Mixture Systems
Authors: Imai Jun-ichi ,   Muroran Institute of Technology, 27-1 Mizumoto-cho, Muroran, 050-8585, Japan, Shioya Hiroyuki , Kurihara Masahito ,   Graduate School of Engineering, Hokkaido University, Kita 13, Nishi 8, Sapporo, 060-8628, Japan
Published: April 2016

Some mathematical models have been proposed for theoretical analyses of genetic algorithms (GAs). However, these works have limited their objects to a few kinds of GAs in order to formulate them accurately. In this paper, we regard a GA as an information source that generates input-output data. That is, we regard a population and its next population generated by the GA as input and output respectively. Then we model the GA by learning from these data. Since this method uses only the input-output relations of data and ignores interior structures, we can describe a variety of GAs in a common form, and analyze them from a new point of view. We use some mixture models for a representation of these input-output relations in this paper. By using a mixture model for modeling a GA, we can represent the GA system as a combination of some partial systems. In this paper, we treat two types of mixture models, and investigate how these models are effective for analyzing GAs through some numerical experiments.
Fuzzy Modeling for Modifying Standard Prescriptions of Oriental Traditional Medicine
Authors: Phuong Nguyen Hoang ,   Institute of Information Technology, National Center of Natural Science and Technology, 18 Hoang Quoc Viet Rd, Cau Giay Dist., Hanoi, Vietnam, Santiprabhob Pratit , Hirota Kaoru ,   Department of Computer Science, University of Assumption University, Ramkhanghaeng Soi 24, Huamark, Bangkok 10240, Thailand,   Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8502, Japan
Published: April 2016

The aim of our research is to simulate a thinking of Traditional medical practitioners in forming a prescription of Oriental traditional medicine based on the observed symptoms of the patient. In this paper, we focus on modeling for modifying standard prescriptions of oriental Traditional medicine using the fuzzy sets theory when the standard prescription is given. Input data are symptoms and patient status which are represented as fuzzy sets and outputs are new ingredients of herbal plants of the given standard prescription and some new herbal plants constituting a advised prescription.