bluuebunny/crossref_metadata_2025 huggingface dataset:
Error-Correcting Semi-Supervised Pattern Recognition with Mode Filter on Graphs
Authors: Du Weiwei ,   Department of Information Science, Kyoto Institute of Technology, Matsugasaki, Sakyo-ku, Kyoto 606-8585, Japan, Urahama Kiichi ,   Department of Communication Design Science, Kyushu University, 4-9-1 Shiobaru, Minamiku, Fukuoka 815-8540, Japan
Published: April 2016

A robust semi-supervisedmethod using the mode filter has been presented for learning with partially-labeled training data including label errors. The mode filter has been originally developed for smoothing images contaminated with impulsive noises. However it needs nonlinear optimization which is usually solved with iterative methods. In this paper, we propose a direct solution method with full search of solution spaces. This direct method outperforms the iterative algorithm in classification rates and computational speeds. Additional iterations of the mode filter raise up the classification rates. We extend the mode filter by introducing weights based on the isolation degree of data, and show the effectiveness of this extension.
Using Radio Frequency Identification for Indoor Location Identification Based on Power Level, Signal Strength and Fuzzy Method
Authors: Chen Rung-Ching ,   Chaoyang University of Technology, 168 Jifeng E. Rd., Wufeng District, Taichung 41349, Taiwan, R.O.C., Lin Yu-Cheng , Huang Sheng-Ling , Zhao Qiangfu
Published: April 2016

In recent years, there has been a dramatic proliferation of research concerned with Radio Frequency Identification (RFID). RFID technologies are getting considerable attention not only from academic research but also from the applications for enterprise. One of the most important application issues prevailing throughout the last few decades of RFID application research is the indoor position location. Many researchers have used varied technologies to perform the action of indoor position location tracking. In our research, we propose a new method using RFID tags to perform indoor position location tracking. This method uses Received Signal Strength (RSS) to collect signal strengths from reference tags beforehand, and then uses the signal strengths to set up Power Level areas of range by reference tags. Next, using the signal strengths from the reference tags we match signal strengths with track tags. Finally, when the track tags are set up in indoor environments, they can find the position of neighboring reference tags by using the fuzzy set theory and an arithmetic mean to calculate the position location values; with this method we are able to break figures down to track tag position locations. We conducted this experiment to prove that our methodology can provide better accuracy than the LANDMARC system.
A Study on Conversational Content Recognition Method Using JapaneseWordNet for Robot-Assisted Therapies
Authors: Izutsu Yuta ,   Graduate School of Engineering, Mie University, Tsu, Mie 514-8507, Japan, Kawanaka Hiroharu , Yamamoto Koji , Suzuki Kiyoshi , Takase Haruhiko , Tsuruoka Shinji ,   Faculty of Medical Engineering, Suzuka University of Medical Science, Suzuka, Mie 510-0293, Japan,   Social Welfare Corporation Taiyo No Sato, Matsusaka, Mie 515-0818, Japan,   Graduate School of Regional Innovation Studies, Mie University, Tsu, Mie 514-8507, Japan
Published: April 2016

This paper proposes a conversational content recognition method for robot-assisted therapies. In the proposed method, nouns in the conversation are first extracted by morphological analysis techniques. As the next step, the dominant conception of them, which is called “synset” in this paper, are obtained by using a concept dictionary. And finally the conversational topic is determined considering the number and kinds of obtained synsets. In this paper, Japanese Word-Net was employed as concept dictionary, and evaluation experiments using daily conversation voice data recorded in the welfare facility were conducted. The obtained results by the proposed method were quite similar to those by human and indicated that the proposed method had enough possibility to recognize conversation among some persons. This paper describes the detail of the proposed method, experimental results and also does some problems about the proposed method.
Algorithm for Estimation of Thyroid Gland Size in Ultrasonography Images for Extracting Abnormal Thyroid in Medical Practice
Authors: Hatakeyama Yutaka ,   Center of Medical Information Science, Kochi University, Oko-cho Kohasu, Nankoku-shi, Kochi 783-8505, Japan, Kataoka Hiromi , Nakajima Noriaki , Watabe Teruaki , Okuhara Yoshiyasu
Published: April 2016

Measurement algorithm for the size of the thyroid gland in ultrasonography (US) images has been proposed on the basis of the position of the neighboring regions in order to objectively evaluate target organs for medical screening and secondary use. The measurement algorithm extracts the operator’s notion about the setting information on the basis of a drawn mark in the US images for decreasing computational costs. The measurement experiments for real US images performed in Kochi Medical School Hospital showed that the proposed algorithm detects the neighboring regions for the all target US images and that the enlarged thyroid glands evaluated by the proposed algorithm have relation with other blood test results. The proposed algorithmcan assist the evaluation of US screening and medical data analysis on the basis of the quantitative value of the US images.
Mouse Operation Support for the Physically-Challenged Persons who have Progressive Intractable Diseases
Authors: Honda Hirohiko ,   Applied Computer Sciences, Shonan Institute of Technology, 1-1-25 Tsujido-Nishikaigan, Fujisawa, Kanagawa 251-8511, Japan
Published: April 2016

We focused on the movement of the mouse and pointer to design a system that adjusts the speed of the pointer movement based on the user’s changing characteristics. This system automatically supplements the user interface of the personal computer with a mechanism to maintain work efficiency for the user. For test purposes, we asked a physically-challenged person to evaluate this system and were able to show significant results. This system will help physically-challenged users maintain their quality of life as this enables them to continue using a personal computer even as their state of mobility deteriorates.
On Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints
Authors: Hamasuna Yukihiro ,   Department of Informatics, School of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka, Osaka 577-8502, Japan, Endo Yasunori , Miyamoto Sadaaki ,   Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

This paper presents semi-supervised agglomerative hierarchical clustering algorithm using clusterwise tolerance based pairwise constraints. In semi-supervised clustering, pairwise constraints, that is, must-link and cannot-link, are frequently used in order to improve clustering properties. From that sense, we will propose another way named clusterwise tolerance based pairwise constraints to handle must-link and cannot-link constraints inL2-space. In addition, we will propose semi-supervised agglomerative hierarchical clustering algorithm based on it. We will, moreover, show the effectiveness of the proposed method through numerical examples.
Comparison of Keywords Freely Inputted by Users and the Compendium of “Keywords for Children,” Which is Programmed into the Book Searching System for Children
Authors: Kawaura Takayuki ,   Department of Mathematics, Kansai Medical University, 18-89 Uyamahigashi, Hirakata City, Osaka 573-1136, Japan, Endo Jun , YasukoDoi  ,   Reading Support Section, Osaka Prefectural Central Library, 1-2-1 Aramoto-kita, Higashi Osaka-shi 577-0011, Japan,   International Institute for Children’s Literature, Osaka, 1-2-1 Aramoto-kita, Higashi Osaka-shi 577-0011, Japan
Published: April 2016

When children look for a book to read, they usually ask an adult to recommend something suitable. In many of such cases, librarians or teachers play an important role. It could also be parents or adults close to the children. The objective of the OPAC system provided in libraries is to offer a tool to help users to find books by themselves but it is not an easy system for children to use. In this study, we aim to construct a book searching system that is easy for children to use. To this end, we studied cases in which children used the book search engine “Adventure in the Sea of Books” we developed in 2002 for “International Institute for Children’s Literature, Osaka.” This is installed with “Subject Heading Lists for Children,” a system we uniquely developed to enable users to search a book by the title, author, or any words they can think of. In this study we will make a comparison between the keywords installed in “Subject Heading Lists for Children” and the index items which the users themselves inputted. This comparison will show what kinds of keywords are most requested by children, and lead to the development of a more userfriendly book searching system.
Evaluation of Operetta Songs Generation System Based on Impressions of Story Scenes
Authors: Ishizuka Kenkichi ,   Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8573, Japan, Onisawa Takehisa ,   Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8573, Japan
Published: April 2016

This paper describes a system which composes operetta songs fitting to adjectives representing producer’s impressions of story scenes. Inputs to the system are original theme music, story texts and adjectives representing producer’s impressions of story scenes. The system composes variations on theme music and lyrics based on impressions of story scenes using Kansei information processing in order to convey producer’s impression of a story to audiences. Evolutionary computation is also applied to generations of variations and lyrics. Subjects experiments are performed to verify the usefulness of the system usingThe Ant and the Chrysalisin Aesop’s Fables as a story. In the experiments, two types of evaluations are considered. The one is the evaluation from the viewpoint that the system generates operetta songs fitting to story scenes appropriately or not. The other is the evaluation from the viewpoint that the system generates operetta songs giving producers and listeners the same impressions of generated operetta songs or not.
A Recommendation System with the Use of Comprehensive Trend Indication Based on Weighted Complete Graph
Authors: Sugimoto Takuya ,   Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tenodai, Tsukuba Science City, Ibaraki 305-8573, Japan, Toyota Tetsuya , Nobuhara Hajime ,   Japan Society for the Promotion of Science, Sumitomo Ichibancho FS Bldg., 8 Ichibancho, Chiyoda-ku, Tokyo 102-8472, Japan
Published: April 2016

Recently, Internet shopping has become widespread, websites of which are equipped with a recommendation system to help users easily find their target items from among vast product information. As a typical method to create recommendation information, collaborative filtering is used but it has a problem that recommendation results tend to be biased toward the same category. Since this study intends recommendation with a high discoverability from a large point of view of category, we define dissimilarity between products based on information on Browse Node ID held by some products in Amazon and use k-medoids to newly categorize the products. Moreover, we create a weighted complete graph with those categories as nodes and indicate the trend across different categories. The proposed system estimates and recommends a category strongly related to a category that is thought to be unknown to the user but the user will like based on information of the weighted complete graph. We evaluate the effectiveness of the proposed system through experiments with 9 undergraduate students, 12 graduate students, and 2 office workers as subjects and show that the proposed system is better in recommending unknown products to the user than existing recommendation systems.
Special Issue on Cognitive Infocommunications
Authors: Baranyi Péter , Hashimoto Hideki , Sallai Gyula
Published: April 2016

Cognitive infocommunications (CogInfoCom), is an emerging interdisciplinary research field that has recently started to appear in the context of theoretical, R&D, and industryoriented projects. CogInfoCom deals with novel approaches to extend the cognitive capabilities of human users through the artificial cognitive capabilities of infocommunications devices, enabling them to interact more flexibly with IT infrastructure. Two key points must be considered when asking why the emergence of CogInfoCom is not only timely but also necessary. First of all, the infocommunications industry is experiencing trends that are resulting in the gradual appearance of artificial cognitive capabilities ? capabilities directed towards a broadened scope covering the sensing and processing of unstructured data. Secondly, future users of infocommunications devices will expect both to be able to access these artificial cognitive capabilities in their everyday activities and to be able to merge them with their own cognitive capabilities. They will thus be able to apply them flexibly ? through their infocommunications devices ? in a wide range of applications in both physical and virtual contexts. This Special Issue on Cognitive Infocommunications contains extended versions of key ideas presented at CogInfoCom conferences. The table of contents alone will demonstrate to the reader the broad scope of theoretical considerations and practical applications that underlie current and emerging CogInfoCom research. It is our hope that this Special Issue ? along with the CogInfoCom conference series ? will contribute to providing a scientific forum for researchers from areas related to CogInfoCom and beyond, so that they may be able to develop stronger cooperation and create a more common language in order to produce useful synergies, and in order to fully meet the interdisciplinary challenges that underlie CogInfoCom.
Design of Mutual Interaction Between a User and Smart Electric Wheelchair
Authors: Niitsuma Mihoko ,   Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan, Ochi Terumichi , Yamaguchi Masahiro , Iwamot Koki
Published: April 2016

This paper presents interaction between a user and a smart electric wheelchair. We propose a personal mobility tool (PMT) that integrates autonomous mobile robot navigation technology with intuitive and cognitive interaction between a user and a smart wheelchair. An intuitive and noncontinuous input method is proposed to enable a user to specify the direction in which the wheelchair is to go. Using an acceleration sensor and pressure sensors, the user gives a direction to the PMT, then the PMT determines the goal on an environmental map based on the direction. An output interface is used to help the user interpret robot behavior through informative communication between the user and the PMT. In this paper, a vibrotactile seat interface is presented.
Optimizing HMM Speech Synthesis for Low-Resource Devices
Authors: Tóth Bálint ,   Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Magyar tudósok krt. 2, Budapest 1117, Hungary, Németh Géza
Published: April 2016

Speech synthesis can be an importantmodality in Cognitive Infocommunications (CogInfoCom). Speech output is beneficial when the visual output of a system is blocked or is difficult to reach. Extra information can be added to output by applying different voice characteristics and emotional speech. CogInfo-Com systems can use low-resource devices in many cases. This paper describes the application of Hidden Markov Model (HMM) based speech synthesis to such systems. Several optimization steps, e.g., changing HMM parameters, applying performance-specific programming methods, are analyzed on three different smartphones in terms of speed, footprint size, and subjective speech quality. The goal is to approach realtime functionality while keeping the speech quality as high as possible. Successful optimization steps and resource-dependent optimal settings are introduced.
OGDE3: Opposition-Based Third Generalized Differential Evolution
Authors: Bourennani Farid ,   University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, Ontario, Canada L1H 7K4, Rahnamayan Shahryar , Naterer Greg F.
Published: April 2016

Multi-Objective Optimization (MOO) metaheuristics are commonly used for solving complex MOO problems characterized by non-convexity, multimodality, mixed-types variables, non-linearity, and other complexities. However, often metaheuristics suffer from slow convergence. Opposition-Based Learning (OBL) has been successfully used in the past for acceleration of single-objective metaheuristics. The most successful example in this regard is Opposition-based Differential Evolution (ODE). However, OBL was not fully explored for MOO metaheuristics. Therefore, in this paper, to the best of our knowledge, for the first time OBL is successfully adapted for a MOO metaheuristic by using a single population (no coevolution). The proposed MOO metaheuristic is based on the GDE3 method and it is called Opposition-based GDE3 (OGDE3). OGDE3 utilizes OBL for opposition-based population initialization and self-adaptive oppositionbased generating jumping. Furthermore, the new algorithm is compared with seven state-of-the-artMOO metaheuristics using the ZDT test suite. OGDE3 outperformed the other algorithms; the results are explained and discussed in detail.
A Large-Scale Magnetostatic Analysis Using an Iterative Domain Decomposition Method Based on the Minimal Residual Method
Authors: Ogino Masao ,   Information Technology Center, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan, Sugimoto Shin-ichiro , Terada Seigo , Bao Yanqing , Kanayama Hiroshi ,   Department of Systems Innovation, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan,   Department of Mechanical Engineering, Graduate School of Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
Published: April 2016

This paper describes a large-scale 3D magnetostatic analysis using the Domain Decomposition Method (DDM). To improve the convergence of the interface problem of DDM, a DDM approach based on the Conjugate Residual (CR) method or the MINimal RESidual (MINRES) method is proposed. The CR or MINRES method improved the convergence rate and showed more stable convergence behavior in solving the interface problem than the Conjugate Gradient (CG) method, and reduced computation time for a large-scale problem with about 10 million degrees of freedom.
Finite Element Analysis of Tsunami by Viscous Shallow-Water Equations
Authors: Dan Hiroshi ,   Department of Mechanical Engineering, Faculty of Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan, Kanayama Hiroshi
Published: April 2016

In this paper, viscous shallow-water equations are derived from three-dimensional Navier-Stokes equations under the hydrostatic assumption. The viscous shallow-water equations are approximated by the finite element method based on our numerical scheme developed in 1978. This approach is used to simulate a tsunami in Hakata Bay. Results show a reasonable estimate of the tsunami arrival time.
Representing Visual Complexity of Images Using a 3D Feature Space Based on Structure, Noise, and Diversity
Authors: Le Phuc Q. ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Iliyasu Abdullah M. , Sanchez Jesus A. Garcia , Dong Fangyan , Hirota Kaoru
Published: April 2016

A 3D feature space is proposed to represent visual complexity of images based on Structure, Noise, and Diversity (SND) features that are extracted from the images. By representing images using the proposed feature space, the human classification of visual complexity of images as being simple, medium, or complex can be implied from the structure of the space. The structure of the SND space as determined by a clustering algorithm and a fuzzy inference system are then used to assign visual complexity labels and values to the images respectively. Experiments on Corel 1000A dataset, Web-crawled, and Caltech 256 object category dataset with 1000, 9907, and 30607 images respectively using MATLAB demonstrate the capability of the 3D feature space to effectively represent the visual complexity. The proposal provides a richer understanding about the visual complexity of images which has applications in evaluations to determine the capacity and feasibility of the images to tolerate image processing tasks such as watermarking and compression.
Modeling Approach Based on Modular Fuzzy Model
Authors: Watanabe Toshihiko ,   Department of Electrical and Electronic Engineering, Faculty of Engineering, Osaka Electro-Communication University, 18-8 Hatsu-cho, Neyagawa, Osaka 572-8530, Japan, Seki Hirosato ,   Department of Mathematical Sciences, Kwansei Gakuin University, 2-1 Gakuen, Sanda, Hyogo 669-1337, Japan
Published: April 2016

Fuzzy modeling is one of the most important techniques for nonlinear modeling. SIRMs (Single Input Rule Modules) has been studied as a useful modeling method for real-life applications such as control and pattern recognition. Although the SIRMs is a practical modeling approach based on fuzzy reasoning, its performance is adversely affected by high-dimensional or complicated characteristics of the problems. The modular fuzzy model is an extension of the SIRMs for overcoming such a performance problem. In this paper, we study a modeling approach based on the modular fuzzy model by extending the SIRMs architecture. We show that the construction of error objective functions for modeling the modular fuzzy model and the SIRMs affects the prediction performance of the model. Through numerical experiments on modeling problems and reinforcement learning problems, we study the model construction based on the error objective functions. We find that the error objective function should be selected according to the number of dimensions of projection in the modular fuzzy model.
An Evaluation Strategy for Visual Key Image Retrieval on Mobile Devices
Authors: Okamoto Kazushi ,   Academic Link Center, Chiba University, Kawamoto Kazuhiko , Dong Fangyan , Yoshida Shinichi , Hirota Kaoru ,   Institute of Media and Information Technology, Chiba University, 1-33 Yayoicho, Inage-ku, Chiba 263-8522, Japan,   Dept. of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan,   School of Information, Kochi University of Technology, 185 Tosayamada-cho-Miyanokuchi, Kochi 782-8502, Japan
Published: April 2016

An evaluation strategy for visual key image retrieval systems is proposed in order to show the design criteria of a querying interface on mobile devices. Indexes (lists of visual keys) generated by different number of visual keys and visual features are validated using Art-Explosion 600,000, which contains about 300 semantic categories and over 100,000 natural photos. The result suggests that access to a collection with a visual key can provide a relevant image in rank 10 and 4 relevant images in rank 20 when the number of visual keys is 60, which is the lower limit. In portable devices, which display 16 visual keys per page, users can at least access a required image by browsing only 4 pages with 60 visual keys, and can use the image for related subsequent queries by using the other image retrieval functions.
Multi-Scale Bag-of-Features for Scalable Map Retrieval
Authors: Tanaka Kanji ,   Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan, Kondo Kensuke
Published: April 2016

Retrieving a large collection of environment maps built by mapper robots is a key problem in mobile robot self-localization. The map retrieval problem is studied from the novel perspective of the multi-scale Bag-Of-Features (BOF) approach in this paper. In general, the multi-scale approach is advantageous in capturing both the global structure and the local details of a given map. BOF map retrieval is advantageous in its compact map representation as well as the efficient map retrieval using an inverted file system. The main contribution of this paper is combining the advantages of both approaches. Our approach is based on multi cue BOF as well as packing BOF, and achieves the efficiency and compactness of the map retrieval system. Experiments evaluate the effectiveness of the techniques presented using a large collection of environment maps.
Hard c-Means Using Quadratic Penalty-Vector Regularization for Uncertain Data
Authors: Endo Yasunori ,   Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Taniguchi Arisa , Hamasuna Yukihiro ,   Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan,   Department of Informatics, Kinki University, 3-4-1 Kowakae, Higashiosaka, Osaka 577-8502, Japan
Published: April 2016

Clustering is an unsupervised classification technique for data analysis. In general, each datum in real space is transformed into a point in a pattern space to apply clustering methods. Data cannot often be represented by a point, however, because of its uncertainty, e.g., measurement error margin and missing values in data. In this paper, we will introduce quadratic penalty-vector regularization to handle such uncertain data using Hard c-Means (HCM), which is one of the most typical clustering algorithms. We first propose a new clustering algorithm called hard c-means using quadratic penalty-vector regularization for uncertain data (HCMP). Second, we propose sequential extraction hard c-means using quadratic penalty-vector regularization (SHCMP) to handle datasets whose cluster number is unknown. Furthermore, we verify the effectiveness of our proposed algorithms through numerical examples.
A Multi-Agent Personalized Query Refinement Approach for Academic Paper Retrieval in Big Data Environment
Authors: Gao Qian ,   School of information, Shandong Polytechnic University, 3501 University-ro, Changqing-gu, Jinan 250-353, China, Cho Young Im ,   College of Information Technology, University of Suwon, San 2-2, Bongdam-eup, Hwaseong-si 445-743, Korea
Published: April 2016

This paper proposes a multi-agent query refinement approach to realize personalized query expansion effective for academic paper retrieval in a Big Data environment. First, we use Hadoop as a platform to develop a formalized model to represent different types of large caches of data in order to analyze and process Big Data efficiently. Second, we use a client agent to verify user identities and monitor whether a device is ready to run a query-expanded task. We then use a query expansion agent to determine the domain that the initial query belongs to by applying a knowledgebased query expansion strategy and comprehensively considering users’ interests according to the intelligent devices they use by implementing a user-device-based query expansion strategy and a weighted query expansion strategy in order to obtain the optimized query expansion set. We compare our method with the conceptual retrieval method as well as other two lexical methods for query expansion, and we prove that our method has better average recall and average precision ratios.
Supervised Learning-Based Feature Selection for Mondrian Paintings Style Authentication
Authors: Lee Keon Myung ,   Department of Computer Science, Chungbuk National University, Cheongju, Chungbuk 361-763, Korea, Hwang Kyoung Soon , Lee Kyung Mi , Han Seung Kee , Jung Woo Hyun , Lee Seungbok ,   Department of Physics, Chungbuk National University, Cheongju, Chungbuk 361-763, Korea,   Department of Psychology, Chungbuk National University, Cheongju, Chungbuk 361-763, Korea
Published: April 2016

This paper concerns feature selection for computational analysis in authenticating works of art. The various features designed and extracted from art work in art forgery detection or the identification of the characteristics of art work style are valuable only when they have a meaningful influence on a given task such as classification. This paper presents features applicable to authenticating the painting style of Piet Mondrian and demonstrates meaningful features by using two supervised learning algorithms, a decision tree induction algorithm C4.5 and the Feature Generating Machine (FGM), both of which are used to select important features in the course of learning.
A Parameterization Based Correspondence Method for PDM Building
Authors: Li Guangxu ,   Department of Mechanical and Control Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka 804-8550, Japan, Kim Hyoungseop , Tan Joo Kooi , Ishikawa Seiji
Published: April 2016

Place-march of corresponding landmarks is one of the major factors influencing 3D Points Distribution Model (PDM) quality. In this study, we propose a semi-automatic correspondence method based on surface parameterization theory. All the training sets are mapped into a spherical domain previously. The rotation transformation of training samples is regarded as spherical rotation of their maps. We solve it by comparing the density distribution of surface map of training sample with respect to the reference model. Simultaneously, the corresponding landmarks across the whole training set are marketed depending on the spherical coordinates on parameter domain. In this paper, we also compared the corresponding results with two constraint conditions of spherical conformal mapping: 3 datum points constrain and zero-mass constrain. Experimental results are given for left lung training sets of 3D shapes. The mean result with the 3 datum points constraint and the zero mass-center constraint was 21.65 mm and 20.19 mm respectively.
Special Issue on Advances in Fuzzy Inference and its Related Techniques
Authors: Uehara Kiyohiko
Published: April 2016

Fuzzy inference provides a way to describe system behavior using humanly understandable rules. Based on this advantage, fuzzy inference has been applied in a wide variety of fields, including control, prediction, and pattern recognition. It has also had a corresponding impact on industrial applications. The four articles included in this special issue cover the advances made in fuzzy inference and related techniques. The first paper proposes a method for fuzzy rule interpolation on the basis of the generalized mean. This method makes it possible to perform nonlinear mapping of convex fuzzy sets even with sparse fuzzy rules. The second paper proposes a fuzzy clustering algorithm, landmark fuzzy neighborhood DBSCAN (landmark FN-DBSCAN). This algorithm is quite efficient in the clustering of large data sets, particularly compared to conventional density-based algorithms. Fuzzy clustering can be used to construct fuzzy rule bases. The third paper applies fuzzy inference to ultrasonic human brain imaging based on YURAGI synthesis. In this method, the thickness of bones is calculated effectively from synthesized waves using fuzzy inference. The fourth paper applies adaptive neurofuzzy inference systems (ANFIS) to financial institution failure prediction. These systems function effectively in the handling of the finance data of Thai firms with high nonlinearity. As a guest editor, I really appreciate the efforts of the contributors and reviewers. I am very grateful to staffs in JACIII editorial office for their kind support.
Comparative Analysis of Relevance for SVM-Based Interactive Document Retrieval
Authors: Murata Hiroshi ,   Central Research Institute of Electric Power Industry (CRIEPI), 2-11-1 Iwado kita, Komae-shi, Tokyo 201-8511, Japan, Onoda Takashi , Yamada Seiji ,   National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
Published: April 2016

Support Vector Machines (SVMs) were applied to interactive document retrieval that uses active learning. In such a retrieval system, the degree of relevance is evaluated by using a signed distance from the optimal hyperplane. It is not clear, however, how the signed distance in SVMs has characteristics of vector space model. We therefore formulated the degree of relevance by using the signed distance in SVMs and comparatively analyzed it with a conventional Rocchio-based method. Although vector normalization has been utilized as preprocessing for document retrieval, few studies explained why vector normalization was effective. Based on our comparative analysis, we theoretically show the effectiveness of normalizing document vectors in SVM-based interactive document retrieval. We then propose a cosine kernel that is suitable for SVM-based interactive document retrieval. The effectiveness of the method was compared experimentally with conventional relevance feedback for Boolean, Term Frequency and Term Frequency-Inverse Document Frequency representations of document vectors. Experimental results for a Text REtrieval Conference data set showed that the cosine kernel is effective for all document representations, especially Term Frequency representation.
Cultivation of Synthetic Biology with the iGEM Competition
Authors: Thamamongood Thiprampai ,   Department of Biological Information, Tokyo Institute of Technology, J2-1707, 4259 Nagatsuta-cho, Midori-ku, Yokohama-shi, Kanagawa 226-8503, Japan, Lim Nathaniel Z. L. , Ho Trevor Y.H. , Ayukawa Shotaro , Kiga Daisuke , Chow King L. ,   Division of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong,   Education Academy of Computational Life Sciences, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama-shi, Kanagawa 226-8501, Japan,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, J2-1707, 4259 Nagatsuta-cho, Midori-ku, Yokohama-shi, Kanagawa 226-8503, Japan
Published: April 2016

The main goal of synthetic biology is to create new biological modules that augment or modify the behavior of living organisms in performing different tasks. These modules are useful in a wide range of applications, such as medicine, agriculture, energy and environmental remediation. The concept is simple, but a paradigm shift needs to be in place among future life scientists and engineers to embrace this new direction. The international Genetically Engineered Machine (iGEM) competition fits this purpose well as a synthetic biology competition mainly for undergraduate students. Participants design and construct biological devices using standardized and customized biological parts that are then characterized and submitted to an existing and ever expanding library. Overall, iGEM is an eye-opening learning experience for undergraduate students. It has made a strong educational impact on participating students and cultivated a future cohort of synthetic biology practitioners and ambassadors.
Chromatic Vision Support System with Color Conversion Constraints
Authors: Shirashige Yu ,   Faculty of Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kitakyushu-shi, Fukuoka 804-8550, Japan, Orii Hideaki , Kawano Hideaki , Maeda Hiroshi , Ikoma Norikazu
Published: April 2016

The symptoms of “color blindness” are due to an innate lack or deficit of “cone cells” that recognize colors. People with color blindness have difficulty discriminating combinations of specific colors. In this study, we developed a system to support color blindness. In this system, the brightness of colors is modified using a projector-camera system. Images that contain combinations of specific colors are difficult to discriminate using a camera, so this task is performed by a projector. We conducted experiments, to validate our proposed system using various color combinations.
Chaotic Music Generation System Using Music Conductor Gesture
Authors: Chen Shuai ,   Department of Human and Artificial Intelligent Systems, Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan, Maeda Yoichiro , Takahashi Yasutake
Published: April 2016

In research on interactive music generation, we propose a music generation method in which the computer generates music under the recognition of a humanmusic conductor’s gestures. In this research, generated music is tuned by parameters of a network of chaotic elements which are determined by the recognized gesture in real time. The music conductor’s hand motions are detected by Microsoft Kinect in this system. Music theories are embedded in the algorithm and, as a result, generated music is richer. Furthermore, we constructed the music generation system and performed experiments for generating music composed by human beings.
CHARM as Activity Model to Share Knowledge and Transmit Procedural Knowledge and its Application to Nursing Guidelines Integration
Authors: Nishimura Satoshi ,   The Institute of Scientific and Industrial Research (ISIR), Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan, Kitamura Yoshinobu , Sasajima Munehiko , Williamson Akiko , Kinoshita Chikako , Hirao Akemi , Hattori Kanetoshi , Mizoguchi Riichiro ,   Miki City Hospital, 58-1 Kasa, Miki, Hyogo 673-0402, Japan,   Kobe City College of Nursing, 3-4 Gakuen Nishi-machi, Nishi-ku, Kobe, Hyogo, Japan,   Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan
Published: April 2016

Japan is no exception among developed countries facing healthcare system problems due to aging and low birthrate as the number of possible patients increases and health care worker numbers shrink. The introduction of high tech medicine has increased the amount of knowledge to be learned by novice nurses. Although vast amounts of implicit knowledge have accumulated among nursing practitioners, this knowledge needs to be communicated when hospitals train younger generations of nurses and integrate nursing guidelines among multiple hospitals. In this paper, the authors have proposed an activity model called CHARM – the Convincing Human Action Rationalized Model. CHARM was developed to resolve the diverse needs of hospitals. CHARM explicates multidimensional purpose-oriented procedure relations often existing as implicit knowledge. For this reason, CHARM supports the training and education of novice nurses. CHARM also is used as a tool to integrate different knowledge and work procedures tacitly existing among different organizations. We developed CHARM models according to nursing guidelines of hospitals and applied them to the integration of nursing procedures at two hospitals. Based on these CHARMmodels, 12 differences were found among the two guidelines covering the same procedure for different hospitals. CHARM is being evaluated at these hospitals and positive responses are coming from nurses.
Bayesian Network Model that Infers Purchase Probability in an Online Shopping Site
Authors: Matsushita Yutaka ,   Department of Psychological Informatics, Kanazawa Institute of Technology, 3-1 Yatsukaho, Hakusan, Ishikawa 924-0838, Japan, Maeda Syunsuke ,   Asobimo Incorporated, 5-26-19 Nishiikebukuro, Toshima-ku, Tokyo 171-0021, Japan
Published: April 2016

In order to understand the properties of online shopping that contribute to visitors’ purchasing habits, we have developed a Bayesian network model that infers the probability of purchase from eye movement and web log data. The results obtained from this model imply that a short visit time on catalog pages and a high frequency of fixation on all pages are related to increased purchase probability. Furthermore, it is shown that websites conforming to Internet Usability Guidelines (IUG)make visitors feel little stress regardless of browsing patterns, and that websites not conforming to IUG require a very short visit time on catalog pages if low stress is to be maintained.
Fault Diagnosis of Power Distribution Feeders with PV System Using Equivalent-Input-Disturbance Approach
Authors: Hu Bo ,   Graduate School of Environment and Energy Engineering, Waseda University, 3-4-1 Okubo, Shinju-ku, Tokyo 169-8555, Japan, She Jinhua , Yokoyama Ryuichi ,   Department of Mechatronics School of Engineering, Tokyo University of Technology, 1401-1 Katakura, Hachioji, Tokyo 192-0982, Japan
Published: April 2016

This paper describes a fault diagnosis method based on the equivalent-input-disturbance (EID) approach to power distribution feeders connected to a photovoltaic (PV) system. Node faults are treated as a system disturbance and are estimated using an EID estimator. First, a dynamic model that contains both the PV system and a power supply utility for the feeder is built. Second, an EID estimator is constructed to estimate the disturbance to the system on the control input channel. Third, a method for abstracting the amount caused by the PV system in the EID is presented to estimate the effect caused by faults. Simulation results demonstrate the validity and superiority of the method.
Visualization of Non-Euclidean Relational Data by Robust Linear Fuzzy Clustering Based on FCMdd Framework
Authors: Honda Katsuhiro ,   Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan, Yamamoto Takeshi , Notsu Akira , Ichihashi Hidetomo
Published: April 2016

Visualization is a fundamental approach for revealing intrinsic structures in multidimensional observation. This paper considers visualization of non-Euclidean relational data by extracting local linear substructures. In order to extract robust linear clusters, an FCMdd-based linear fuzzy clustering model is applied in conjunction with a robust measure of alternativec-means. Non-Euclidean data matrices are handled with β-spread transformation in a manner similar to that of NERFc-Means. In several experiments, robust feature maps derived by the robust clustering model are compared with feature maps given by the conventional clustering model and Multi-Dimensional Scaling (MDS).
A Parallel Computation Method for Heuristic Attribute Reduction Using Reduced Decision Tables
Authors: Kudo Yasuo ,   College of Information and Systems, Muroran Institute of Technology, 27-1 Mizumoto, Muroran 050-8585, Japan, Murai Tetsuya ,   Graduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo 060-0814, Japan
Published: April 2016

In this paper, we propose a parallel computation framework for a heuristic attribute reduction method. Attribute reduction is a key technique to use rough set theory as a tool in data mining. The authors have previously proposed a heuristic attribute reduction method to compute as many relative reducts as possible from a given dataset with numerous attributes. We parallelize our method by using open multiprocessing. We also evaluate the performance of a parallelized attribute reduction method by experiments.
Spatiotemporal Human Brain Activities on Recalling Names of Body Parts
Authors: Yamanoi Takahiro ,   Department of Life Science and Technology, Hokkai-Gakuen University, W11, S26, Center ward, Sapporo, Hokkaido 064-0926, Japan, Tanaka Yoshinori , Otsuki Mika , Ohnishi Shin-ichi , Yamazaki Toshimasa , Sugeno Michio ,   Graduate School of Engineering, Hokkai-Gakuen University, W11, S26, Center ward, Sapporo, Hokkaido 064-0926, Japan,   Faculty of Health Sciences, Hokkaido University, W5, N12, North ward, Sapporo, Hokkaido 060-0812, Japan,   Faculty of Engineering, Hokkai-Gakuen University, W11, S26, Center ward, Sapporo, Hokkaido 064-0926, Japan,   Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan,   European Center for Soft Computing, Edificio Cientifico Technologico, c/ Gonzalo Guterrez Quiros, s/n 33600 Mieres-Asutrias, Spain
Published: April 2016

The authors measure electroencephalograms (EEGs) from a subject looking at line drawings of body parts and recalling their names silently. The equivalent current dipole source localization (ECDL) method is applied to the event related potentials (ERPs): summed EEGs. As the dominant language area of the subject is considered to be in the right hemisphere in the previous research study, ECDs are localized to the right middle temporal gyrus: the angular gyrus. Then ECDs are localized to the right fusiform gyrus, the right middle temporal pole (TEP), and the right inferior temporal white matter (TWM). ECDs are located in the ventral pathway. The areas are related to the integrated process of visual recognition of pictures and the recalling of words. Some of these areas are also related to image recognition and word generation.
Real-Time Face Decorations of Enlarging Eyes and Whitening Skin in Video Based on Face Posture Estimation by Particle Filter
Authors: Ikoma Norikazu ,   Faculty of Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kita-kyushu, Fukuoka 804-8550, Japan, Zhang Gefan
Published: April 2016

Decorations of face such as enlarging eyes, whitening skin, rendering face slim, and so on are commercially successful in amusement arcades especially in Japan for still image and off-line processing. This paper proposes to decorate human face in video on-line and in real-time processing. Face posture estimation using particle filter plays a key role to decorate the face by precisely determining position of the eyes as well as determining regional position of face. Our proposed method conducts two decorations, enlarging eyes and whitening skin, based on the estimation result of face posture. Real-time implementation of the proposed method has been demonstrated for real scenes of indoor situation.
An RGB Multi-Channel Representation for Images on Quantum Computers
Authors: Sun Bo ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Iliyasu Abdullah M. , Yan Fei , Dong Fangyan , Hirota Kaoru
Published: April 2016

RGB multi channel representation is proposed for images on quantum computers (MCQI) that captures information about colors (RGB channels) and their corresponding positions in an image in a normalized quantum state. The proposed representation makes it possible to store the RGB information about an image simultaneously by using 2n+3 qubits for encoding 2n× 2npixel images, whereas pixel-wise processing is necessary in many other quantum image representations, e.g., qubit lattice, grid qubit, and quantum lattice. Simulation of storage and retrieval of MCQI images using human facial images demonstrated that 15 qubits are required for encoding 64 × 64 colored images, and encoded information is retrieved by measurement. Perspectives of designing quantum image operators are also discussed based onMCQI representation, e.g., channel of interest, channel swapping, and restrict version of color transformation.