bluuebunny/crossref_metadata_2025 huggingface dataset:
Process of Acquiring Musical Performance Skills for Enhanced “Awareness” Given by a Multimedia-Based Learning Approach
Authors: Nakahira Katsuko T. ,   Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka, Niigata 940-2188, Japan, Akahane Miki , Fukami Yukiko ,   Tokyo University of Music, 3-4-5 Minami-Ikebukuro, Toshima, Tokyo 171-8540, Japan,   Kyoto Women’s University, 35 Kitahiyoshi-cho, Imakumano, Higashiyama, Kyoto 605-8501, Japan
Published: April 2016

As e-learning gains popularity, ways are being studied to apply e-learning to the teaching of musical performance skills. These studies require learners to submit multimedia records of their learning status to instructors. This paper discusses how learners can enhance performance skills effectively from an “awareness” of performance status. We have used a multimediabased learning approach, which includes a mechanism to enhance awareness of current strengths and weaknesses. We have developed three models that are expected to be useful for learners in acquiring performance skills, and have analyzed differences in the level of skills achieved using the three models. This paper also shows that a learners can enhance their awareness of how to improve skills by submitting video performance records and by closely comparing them to the model performance.
Experimental Study of a Structured Differential Evolution with Mixed Strategies
Authors: Ishimizu Takashi ,   School of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka 577-8502, Japan, Tagawa Kiyoharu
Published: April 2016

In this paper, a new Differential Evolution (DE) that has multiple populations, or islands, is proposed. The proposed DE is called Structured Differential Evolution (StDE). In order to generate a new individual from the current population, various characteristic strategies have been proposed for DE. However, the performances of these strategies depend on the kind of the optimization problem. The proposed StDE uses different strategies in respective islands. Therefore, it can be expected that the proposed StDE is effective for a wide range of optimization problems. Although various networks topologies among islands are reported for island-based evolutionary algorithms, the most popular ones, namely the ring network and the torus network, are employed by StDE. Furthermore, in order to enhance the performance of proposed StDE, various migration policies are examined in two kinds of networks though a variety of benchmark problems.
An Extended Interactive Evolutionary Computation Using Heart Rate Variability as Fitness Value for Composing Music Chord Progression
Authors: Fukumoto Makoto ,   Faculty of Computer Science and Engineering, Fukuoka Institute of Technology, Nakashima Shuta , Ogawa Shintaro , Imai Jun-ichi ,   Graduate School of Engineering, Fukuoka Institute of Technology, 3-30-1 Wajirohigashi, Higashi-ku, Fukuoka-shi, Fukuoka 811-0295, Japan,   Faculty of Information and Computer Science, Chiba Institute of Technology, 2-17-1 Tsudanuma, Narashino-shi, Chiba 275-0016, Japan
Published: April 2016

Interactive Evolutionary Computation (IEC) is known as an efficient method to create media content suited to the individual user. To reduce user’s fatigue, which remains as a serious problem in IEC, extended IEC that uses physiological information as a fitness value have been proposed. As a new extended IEC, this study proposed extended IEC using Heart Rate Variability (HRV), which reflects autonomic nervous activity. A High Frequency (HF) component of HRV was used as the fitness value. Two listening experiments were conducted to determine the efficacy of the proposed method. In experiment 1, with a concrete system of the proposed method creating music chord progression, a change in the fitness value was observed. In experiment 2, representative created music chord progressions were evaluated subjectively. The change in the fitness value of the HF component showed no gradual increase. Subjective evaluation results showed that the lowest fitness value was observed in the 1st generation, and the fitness value in the 10th generation significantly increased from the 1st generation (P< 0.05). The result of the subjective evaluation showed the efficacy of the proposed method.
Similarity Retrieval of Motion Capture Data Based on Derivative Features
Authors: Choensawat Worawat ,   School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577, Japan, Choi Woong , Hachimura Kozaburo ,   Department of Information and Computer Engineering, Gunma National College of Technology, 580 Tobamachi, Maebashi, Gunma 371-8530, Japan
Published: April 2016

In this paper, we propose (1) a method of similarity retrieval of motion capture data in which a new feature extraction technique is introduced for the improvement of similarity search precision, as well as (2) a method to reduce the search time on a large database by using lower bound Dynamic Time Wrapping (DTW). For similarity search, joint speed has been mainly used as features of a particular motion. Our method differs from others in that we use not only the magnitude of speed but also the pattern of speed change. We measure the pattern of changing joint speed in a short period of time with the derivative of joint speed. In our experiments, we found that our proposed feature extraction can improve search precision and time. The average precision was greater than 90% and its computation time was 10 seconds on a dataset of 225 motion clips with a total of 81,851 frames from CMU’s database. The experiments showed that we can improve search precision using our proposed feature extraction technique compared to the retrieval method without using this method. For search time, our experiment shows that our retrieval method using the lower bound DTWcan efficiently reduce the amount of search data.
Hospital Navi – A New Database for Searching Medical Information –
Authors: Gohma Hiroshi ,   Studies of Medical System Management, Graduate School of Medicine, Nagoya University, 65 Tsuruma-cho, Showa-ku, Nagoya 466-8560, Japan, Asano Mika , Hamajima Nobuyuki , Sobue Gen , Sugiura Shin-ichi ,   Graduate School of Humanities, Kinjo Gakuin University, Japan,   Department of Preventive Medicine, Graduate School of Medicine, Nagoya University, Japan,   Department of Neurology, Graduate School of Medicine, Nagoya University, Japan
Published: April 2016

Hospital Navi, which has two portals, was developed in order to search medical information. Here, the database is always refreshed, unlike other medical information sites, since medical information updated to the server is obtained monthly from eight local governments throughout the country. Moreover, Hospital Navi can indicate hospitals/clinics that are open at the point in time in Nagoya or Ichinomiya city in Aichi prefecture. In this project, volunteer doctors who are registered can change their clinic hours daily, and the results are uploaded on the web automatically. It is suggested that Hospital Navi is available for such emergency as the outbreak of influenza in 2009.
System Replacement to a New HIS and Data Warehouse
Authors: Honda Masayuki ,   Department of Medical Informatics, Nagasaki University Hospital, 1-7-1 Sakamoto, Nagasaki 852-8501, Japan, Matsumoto Takehiro
Published: April 2016

Large-scale hospital information systems (HIS) generally consist of (i) online transaction processing (OLTP) and (ii) online analytical processing (OLAP) systems. Electronic medical records (EMR) are a major OLTP element. The data warehouse (DWH) assumes many important OLAP roles and maintains an institution’s medical care at a high level by providing EMR with the best practice cases available. This article focuses mainly on why OLTP and OLAP are needed and what roles the DWH plays, which means that the DWH has its own utilities and supplementary merits. The background of this discussion is closely related to the HIS at Nagasaki University Hospital introduced before the DWH is discussed.
Discrimination of Pneumoconiosis X-Ray Images Scanned with a CCD Scanner
Authors: Minami Masahide ,   Health Control Department, Awazu Plant, Komatsu Ltd., 23 Tsu, Futsu, Komatsu 923-0392, Japan, KojiAbe  , Nakamura Munehiro ,   Department of Informatics, School of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka 577-8502, Japan,   Faculty of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa University, Kakuma, Kanazawa 920-1192, Japan
Published: April 2016

This paper presents a discrimination of pneumoconiosis X-ray images obtained with a common CCD scanner. Since the current computer-aided diagnosis systems of pneumoconiosis are not practical due to high costs of usage, features for measuring abnormalities of pneumoconiosis are proposed as variables for the discrimination in this paper. In the images, abnormal levels of pneumoconiosis could depend on density distribution in each of intercostal and rib areas. Therefore, the proposed method measures the abnormalities by extracting characteristics of the distribution in the areas. Besides, using the abnormalities, the proposed method discriminates chest X-ray images into normal or abnormal cases of pneumoconiosis. Experimental results of the discriminations for 56 right-lung images have shown that the proposed abnormalities are well extracted for the discrimination.
Interest-Based Ordering for Fuzzy Morphology on White Blood Cell Image Segmentation
Authors: Fatichah Chastine ,   Dept. Computational Intelligence & Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Tangel Martin Leonard , Widyanto Muhammad Rahmat , Dong Fangyan , Hirota Kaoru ,   Informatics Department, Faculty of Technology Information, Institut Teknologi Sepuluh Nopember, Kampus ITS Surabaya 60111 Indonesia,   Faculty of Computer Science, University of Indonesia, Kampus UI Depok, Jawa Barat, Indonesia
Published: April 2016

An Interest-based Ordering Scheme (IOS) for fuzzy morphology on White-Blood-Cell (WBC) image segmentation is proposed to improve accuracy of segmentation. The proposed method shows a high accuracy in segmenting both high- and low-density nuclei. Further, its running time is low, so it can be used for real applications. To evaluate the performance of the proposed method, 100 WBC images and 10 leukemia images are used, and the experimental results show that the proposed IOS segments a nucleus in WBC images 3.99% more accurately on average than the Lexicographical Ordering Scheme (LOS) does and 5.29% more accurately on average than the combined Fuzzy Clustering and Binary Morphology (FCBM) method does. The proposal method segments a cytoplasm 20.72% more accurately on average than the FCBM method. The WBC image segmentation is a part of WBC classification in an automatic cancer-diagnosis application that is being developed. In addition, the proposed method can be used to segment any images that focus on the important color of an object of interest.
Subliminal Calibration for Machine Operation
Authors: Igarashi Hiroshi ,   Department of Electrical and Electronic Engineering, Tokyo Denki University, 2-2 Kanda-Nishiki-cho, Chiyoda-ku, Tokyo 101-8457, Japan
Published: April 2016

This paper proposes a skill assist technique without having the operator to be aware of it. Heretofore, many operation assists in a human-machine system has added artificial force in human operation input such as reactive force from obstacles. Such an approach is suitable in a particular task as simulated by the designer, because it can improve safety and efficiency, but is simultaneously hindering human learning ability. The proposed method will correct the machine dynamics of the operation subject subliminally, meaning that the operator will not be aware that it is being altered. Henceforth, it will be possible to enhance operability, without having to prevent the human learning ability. As a result of a verification experiment on 20 test subjects, it has been clarified that it is possible to enhance the operation performance without the operators knowing of the assist.
Adaptive Cooperation for Multi Agent Systems Based on Human Social Behavior
Authors: Igarashi Hiroshi ,   Department of Electrical and Electronic Engineering, Tokyo Denki University, 2-2 Kanda-Nishiki-cho, Chiyoda-ku, Tokyo 101-8457, Japan, Adachi Yoshinobu , Takahashi Kazunari ,   Intelligent Systems Laboratory, SECOM Co., Ltd., 8-10-16 Shimorenjaku, Mitaka, Tokyo 181-8528, Japan,   Department of Information and Computer Sciences, Saitama University, 255 Shimo-Okubo, Sakura, Saitama 338-8570, Japan
Published: April 2016

This paper addresses a new cooperation technique for multi-agent systems. This technique is based on human social behaviour. According to biological knowledge, the population contributes to the preservation of the species and adaptability to environmental variations. Multiple robot cooperation, therefore, has a potential to be flexible and adaptable to various tasks. Furthermore, sociality based on the performance evaluation of other humans is expected to enhance the whole task performance. Finally, adaptability and the total performance of proposed technique are verified by pursuit survey on the multi-agent system.
On Kernel Fuzzy c-Means for Data with Tolerance Using Explicit Mapping for Kernel Data Analysis
Authors: Kanzawa Yuchi ,   Shibaura Institute of Technology, 3-7-5 Toyosu, Koto, Tokyo 135-8548, Japan, Endo Yasunori , Miyamoto Sadaaki ,   University of Tsukuba
Published: April 2016

While explicit mapping is generally unknown for kernel data analysis, its inner product should be known. Although we proposed a kernel fuzzy c-means algorithm for data with tolerance, cluster centers and tolerance in higher dimensional space have not been seen. Contrary to this common assumption, explicit mapping has been introduced and the situation of kernel fuzzy c-means in higher dimensional space has been described via kernel principal component analysis using explicit mapping. In this paper, cluster centers and the tolerance of kernel fuzzy c-means for data with tolerance are described via kernel principal component analysis using explicit mapping.
Knowledge Expansion Support by Related Search Keyword Generation Based onWikipedia Category and Pointwise Mutual Information
Authors: Kawauchi Saori ,   Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tenoudai, 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

When users use search engines to acquire knowledge on certain subjects in unknown domains, they often refer to the related search keywords that are generated on the frequency of use as search keywords. However, such searches by reference to related search keywords may not always turn out to be useful for the expansion of knowledge on the research subjects. We, therefore, propose a new method to generate related search keywords by means of Wikipedia. In the proposed method, users first searchWikipedia pages of the same title with the queries input by users to extract information on the category of the pages. Next, obtain the sets of pages that fall into the category and extract related page groups from the pages contained in any plural product sets of pages. Then, calculate pointwise mutual information or tf-idf for the keywords extracted from each page to make either information of higher values associated with search keywords. We have confirmed effectiveness of the proposed method through comparison with related search keywords generated by Google as well as through subjective evaluation experiments.
Interactive Data Mining Tool for Microarray Data Analysis Using Formal Concept Analysis
Authors: Tanabata Takanari ,   National Institute of Agrobiological Sciences, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan, Hirose Fumiaki , Hashikami Hidenobu , Nobuhara Hajime ,   Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tenodai, Tsukuba Science City, Ibaraki 305-8573, Japan
Published: April 2016

The DNA microarray analysis can explain gene functions by measuring tens of thousands of gene expressions at once and analyzing gene expression profiles that are obtained from the measurement. However, gene expression profiles have such a vast amount of information and therefore most analyses work are done on the data narrowed down by statistical methods, there remains a possibility ofmissing out on genes that consist the factors of phenomena from their evaluations. This study propose a method based on a formal concept analysis to visualize all gene expression profiles and characteristic information that can be obtained from annotation information of each gene so that the user can overview them. In the formal concept analysis, a lattice structure that allows genes to be hierarchically classified and made viewable is built based on the inclusion relations of attributes from a context table in which gene is the object and the attributes are expression profiles and binarized characteristic information. With the proposed method, the user can change the overview state by adjusting the expression ratio and the binary state of characteristic information, understand the relational structure of gene expressions, and carry out analyses of gene functions. We develop software to practice the proposed method, and then ask a biologist to evaluate effectiveness of proposed method applied to a function analysis of genes related to blue light signaling of rice seedlings.
Augmented Reality Aspects of Object Recognition in Driver Support Systems
Authors: Paróczi Zsombor ,   U1 Research Ltd., 2 Gábor Dénes str., INFOPARK, H-1117 Budapest, Hungary, Nagy István , Gáspár-Papanek Csaba , Kardkovács Zsolt T. , Varga Endre , Siegler Ádám , Lucz Péter ,   Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 2 Magyar tudosok blvd., H-1117 Budapest, Hungary,   Top-Map Plc., 105-113 Bartók Béla str., H-1115 Budapest, Hungary
Published: April 2016

Augmented Reality (AR) is a technique that combines a live view in real-time with virtual computergenerated images, creating a real-time augmented experience of reality. In this paper we define connection between augmented reality and cognitive infocommunications and show a demonstration system for driver support which combines raw sensory with extracted visual data to provide extended information about the visual scene around the car. Traffic sign recognition system presented in this paper is an independent work of U1 Research and Top-Map Plc.
Recognition of Emotions on the Basis of Different Levels of Speech Segments
Authors: Vicsi Klára ,   Department of Telecommunication and Media Informatics, Budapest University of Technology and Economics, 2 Magyar tudósok körútja, Budapest 1117, Hungary, Sztahó Dávid
Published: April 2016

Emotions play a very important role in human-human and human-machine communication. They can be expressed by voice, bodily gestures, and facial movements. People’s acceptance of any kind of intelligent device depends, to a large extent, on how the device reflects emotions. This is the reason why automatic emotion recognition is a recent research topic. In this paper we deal with automatic emotion recognition from human voice. Numerous papers in this field deal with database creation and with the examination of acoustic features appropriate for such recognition, but only few attempts were made to compare different emotional segmentation units that are needed to recognize the emotions in spontaneous speech properly. In the Laboratory of Speech Acoustics experiments were ran to examine the effect of diverse speech segment lengths on recognition performance. An emotional database was prepared on the basis of three different segmentation levels: word, intonational phrase and sentence. Automatic recognition tests were conducted using support vector machines with four basic emotions: neutral, anger, sadness, and joy. The analysis of the results clearly shows that intonation phrase-sized speech units give the best performance in emotional recognition in continuous speech.
Robust Facial Expression Recognition Using Near Infrared Cameras
Authors: Jeni Laszlo A. ,   Department of Electrical Engineering, The University of Tokyo, ISAS Campus, 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252-5210, Japan, Hashimoto Hideki , Kubota Takashi ,   Department of Electrical, Electronics and Communication Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan
Published: April 2016

In human-human communication we use verbal, vocal and non-verbal signals to communicate with others. Facial expressions are a form of non-verbal communication, recognizing them helps to improve the human-machine interaction. This paper proposes a system for pose- and illumination-invariant recognition of facial expressions using near-infrared camera images and precise 3D shape registration. Precise 3D shape information of the human face can be computed by means of Constrained Local Models (CLM), which fits a dense model to an unseen image in an iterative manner. We used a multi-class SVM to classify the acquired 3D shape into different emotion categories. Results surpassed human performance and show poseinvariant performance. Varying lighting conditions can influence the fitting process and reduce the recognition precision. We built a near-infrared and visible light camera array to test the method with different illuminations. Results shows that the near-infrared camera configuration is suitable for robust and reliable facial expression recognition with changing lighting conditions.
A Neural Network Model of Students’ English Abilities Based on Their Affective Factors in Learning
Authors: Bachtiar Fitra A. ,   Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577, Japan, Kamei Katsuari , Cooper Eric W. ,   College of Information Science and Engineering, Ritsumeikan University, 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577, Japan
Published: April 2016

The gap between teaching perspectives and students’ differences may impact negatively on teaching and learning effectiveness, indicating the need for a new approach for bridging this gap. The potentials of artificial neural networks for approximating extremely complex problems encouraged us to develop an estimation model of student English ability. The model was trained using a back propagation algorithm and tested using 154 samples from two universities. The model estimation rate related to student English ability demonstrated a high level of estimation by 93.34% for listening, 94.38% for reading, 94.90% for speaking, and 93.58% for writing.
Fuzzy Hidden Markov Models for Indonesian Speech Classification
Authors: The Intan Nurma Yulita Houw Liong ,   Faculty of Informatics, Telkom Institute of Technology, Adiwijaya  ,   Graduate Faculty, Telkom Institute of Technology, Jalan Telekomunikasi No.1, DayeuhKolot, Jawa Barat 40257, Indonesia
Published: April 2016

Indonesia has many tribes, so that there are many dialects. Speech classification is difficult if the database uses speech signals from various people who have different characteristics because of gender and dialect. The different characteristics will influence frequency, intonation, amplitude, and period of the speech. It makes the system must be trained for the various templates reference of speech signal. Therefore, this study has been developed for Indonesian speech classification. The solution is a new combination of fuzzy on hidden Markov models. The result shows a new version of fuzzy hiddenMarkovmodels is better than hidden Markov model.
Multiscale Image Aggregation for Dental Radiograph Segmentation
Authors: Tangel Martin Leonard ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Fatichah Chastine , Widyanto Muhammad Rahmat , Dong Fangyan , Hirota Kaoru ,   Faculty of Computer Science, University of Indonesia, Depok Campus, Depok 16424, West Java, Indonesia
Published: April 2016

Multiscale Image Aggregation (MIA) is proposed for dental radiograph segmentation, where a grayscale image segmentation method using neighborhood pixels evaluation and fuzzy inference is applied to its original image and three scaled-down images. The average segmentation result by employing the proposed method is more accurate than that obtained by employing the Otsu method, and it is robust against inconsistent contrast, uneven exposure, and pixel’s noise of the radiograph. An experiment is performed using 122 dental radiographs covering periapical and bitewing radiographs from the Faculty of Dentistry, University of Indonesia, which represent the real radiographs used in dentistry and forensics, and 77.7% average segmentation accuracy is obtained by comparing each automatic segmentation result with the corresponding manual segmentation result as a reference. This proposal is a crucial part in our automatic dental-based identification system that is under development. Since manual dental-based identification is widely used for personal identification, an accurate automatic dental-based identification system is helpful in assisting forensic experts in identifying a large number of victims. Thus it makes identification of victims of disasters such as the Indian Ocean Tsunami and Tohoku Earthquake manageable.
Substitute Target Learning Based Control System for Control Knowledge Acquisition Within Constrained Environment
Authors: Kamarulzaman Syafiq Fauzi ,   Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Shibuya Takeshi , Yasunobu Seiji
Published: April 2016

Real-time operations are usually conducted within a constrained environment. A human requires constantly updated knowledge to respond flexibly under different constraints to configure a control method around the constraints. In this research, a control system based on substitute target learning is proposed to enable control operations to configure their own control method around the constraints. This control system is applied to an inverted pendulum control system and its effectiveness is confirmed through a series of simulations and an experiment using a real machine.
The Effective Technology- and Resource-Management Strategy of Established Japanese Company: A Case Study of Toraya, a Traditional Japanese Confectioner
Authors: Sugimoto Kana ,   Graduate School of Commerce, Waseda University, 1-6-1 Nishi-Waseda, Shinjuku-ku, Tokyo 169-8050, Japan, Someya Takao , Nagasawa Shin’ya
Published: April 2016

The purpose of this paper is to ascertain the effectiveness of the management strategies of the traditional Japanese confectioner Toraya. Rapid technological development and the demands of knowledgeable customers have made growth more difficult for manufacturers. We assume that the practices of longestablished manufacturers are best for others to follow. Toraya has been a high-value-added confectioner for almost 500 years. The reasons for its sustained competitiveness are described in this paper. We use the 3Cs analysis to clarify the business circumstances of the Japanese confection industry, the 4Ps analysis to explore Toraya’s structure, the strategic experimental module analysis to show the reliable value that Toraya offers its customers, and the Value, Rarity, Inimitability, and Organization analysis to explain its long-term success. The results reveal that Toraya has employed a low-technology strategy utilizing artisanal skill instead of machines and provides an excellent consumer experience that attracts customers. This is a sustainable competitive advantage because it takes years to establish and is not easily imitated. However, Toraya’s simple and effective management practices could be adopted as industry best practices.
A Study on Fuzzy Control of Humanoid Soccer Robot EFuRIO for Vision Control System and Walking Movement
Authors: Sulistijono Indra Adji ,   Electronics Engineering Polytechnic Institute of Surabaya (EEPIS), PENS Campus, Jalan Raya ITS Sukolilo, Surabaya 60111, Indonesia, Kuswadi Son , Setiaji One , Salfikar Inzar , Kubota Naoyuki ,   Politeknik Aceh, Jalan Tanggul, Pango Raya, Banda Aceh 23119, Indonesia,   Faculty of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan
Published: April 2016

Instability is one of the major defects in humanoid robots. Recently, various methods on the stability and reliability of humanoid robots have been studied actively. We propose a new fuzzy-logic control scheme for vision systems that would enable a robot to search for and to kick a ball towards an opponent goal. In this paper, a stabilization algorithm is proposed using the balance condition of the robot, which is measured using accelerometer sensors during standing and walking, and turning movement are estimated from these data. From this information the robot selects the appropriate motion pattern effectively. In order to generate the appropriate reaction in various body of robot situations, a fuzzy algorithm is applied in finding the appropriate angle of the joint from the vision system. The performance of the proposed algorithm is verified by searching for a ball, walking, turning tap and ball kicking movement experiments using an 18-DOF humanoid robot, called EFuRIO.
Nonlinear Dynamic System Identification Using Volterra Series: Multi-Objective Optimization Approach
Authors: Loghmanian Sayed Mohammad Reza ,   Faculty of Engineering, Islamic Azad University, Mobarakeh Branch, Isfahan, Iran, Yusof Rubiyah , Khalid Marzuki ,   Centre for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, International Campus, Jalan Semarak, 54100 Kuala Lumpur, Malaysia
Published: April 2016

In this paper, identification of the nonlinear dynamic systems based on an optimized Volterra model structure is presented. Model structure selection is an important step in system identification, which involves the selection of variables and terms of a model. The key task is choosing a compact model representation where only significant terms are selected from among all the possible ones while also taking good performance into account. An automated algorithm based on multi-objective optimization is proposed for this purpose. The developed model should fulfill two criteria or objectives, namely, high prediction accuracy and optimum model structure. A genetic algorithm is applied to search the significant Volterra kernels from among all possible candidate model combinations. The result shows that the proposed algorithm is able to correctly identify the simulated examples and adequately model the nonlinear discrete dynamic system.
New Approach for Antisense Oligonucleotide-Mediated Exon Skipping in Duchenne Muscular Dystrophy
Authors: Aoki Yoshitsugu ,   Department of Molecular Therapy, National Institute of Neuroscience, National Center of Neurology and Psychiatry (NCNP), 4-1-1 Ogawa-higashi, Kodaira, Tokyo 187-8502, Japan, Nagata Tetsuya , Takeda Shin’ichi
Published: April 2016

Duchenne Muscular Dystrophy (DMD) is a lethalmuscle disorder characterized by mutations in the DMD gene. These mutations primarily disrupt the reading frame, resulting in the absence of functional dystrophin protein. Exon skipping, which involves the use of antisense oligonucleotides is a promising therapeutic approach for DMD, and clinical trials on exon skipping are currently underway in DMD patients. Recently, stable and less-toxic antisense oligonucleotides with higher efficacy have been developed in mouse and dog models of DMD. This review highlights a new approach for antisense oligonucleotide-based therapeutics for DMD, particularly for exon skipping-based methods.
Strategic Management and Design Innovation in the Long-Standing CompanyKyogashiMaster “Suetomi”
Authors: Irisawa Yusuke ,   Graduate School of Commerce, Waseda University, 1-6-1 Nishi-Waseda, Shinjuku-ku Tokyo 169-8050, Japan, Nagasawa Shin’ya
Published: April 2016

Japanese Confectionary “Suetomi” is a high level brand among Kyoto’s long-standing companies. This always makes the Japanese sweets a high level in Kyoto, and gets the high appraisal from the parties concerned the master of the tea ceremony, such as “Urasenke.” In this study, we present an analysis of Suetomi’s management strategy and its strength and differentiation based on an interview with the president, Mr. Yamaguchi. Then, we analyze their innovation from the viewpoint of product innovation and affective value (i.e., sense value). Finally, we discuss the innovation of theKyogashidesign based on our research. In conclusion, Suetomi has a different strong point from the other company as a long-standing company of Kyoto confections and we have understood performing the management strategy which establishes a sustainable competitive advantage using it. Thus, they have performed the design innovation of Kyoto confections products in the management strategy which is compatible in tradition and innovation, and have created the value of a customer’s sensitivity.
Professor Ebrahim Mamdani Memorial Issue
Authors: Arai Yoshinori , Watanabe Toshihiko
Published: April 2016

On February 22, 2010, Prof. Ebrahim H. Mamdani who devised Mamdani fuzzy inference has passed away. His work in fuzzy inference, which rapidly paved the way to its practical use, helped disseminate Prof. Lotfi Zadehfs fuzzy logic and the development of fuzzy research. Prof. Mamdanifs two papers on fuzzy inference ? gApplication of fuzzy algorithms for control of simple dynamic planth (Proc. IEE, Vol.121, No. 12, pp. 1585-1588, 1974) and gAn experiment in linguistic synthesis with a fuzzy logic controllerh (Int. J. of Man-Machine Studies, Vol.7, No.1, pp. 1-13, 1975) with S. Assilian ? enabled fuzzy inference technology to develop dramatically both indicatively and indirectly to where it has been applied, including fuzzy control systems. This special issue honors Prof. Mamdani for his invaluable efforts in these and many other fields. We have asked for submissions by researchers influenced by Prof. Mamdanifs achievements, including his work in fuzzy inference, and have narrowed down to one review and seven full papers. The review by Hirosato Seki and Kai Meng Tay provides an incisive overview on the many aspects of fuzzy inference that Prof. Mamdani brought to light. Prof. Mamdanifs fuzzy inference has become a deterministic technology that can be chosen naturally and that will continue to be influential and survivable well into the future.
On the Monotonicity of Fuzzy Inference Models
Authors: Seki Hirosato ,   Department of Mathematical Sciences, Kwansei Gakuin University, 2-1 Gakuen, Sanda, Hyogo 669-1337, Japan, Tay Kai Meng ,   Faculty of Engineering, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia
Published: April 2016

Monotonicity property is very important in real systems. The monotonicity may need to be satisfied in a variety of application domains, e.g., control, medical diagnosis, educational evaluation, etc. A search in the literature reveals that the importance of the monotonicity in fuzzy inference system has been highlighted. Therefore, this paper surveys the works relating the monotonicity for various fuzzy inference systems. It firstly focuses on the monotonicity of the Mamdani inference model. Themonotonicity ofMamdani model is shown by using a defuzzification method in cases of three t-norms. Secondly, the monotonicity conditions and applications of the T–S inference model are stated. Finally, the monotonicity of the single input type fuzzy inference models is surveyed.
Latent Topic Estimation Based on Events in a Document
Authors: Kitajima Risa ,   Advanced Sciences, Graduate School of Humanities and Sciences, Ochanomizu University, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, Japan, Kobayashi Ichiro
Published: April 2016

Several latent topic model-based methods such as Latent Semantic Indexing (LSI), Probabilistic LSI (pLSI), and Latent Dirichlet Allocation (LDA) have been widely used for text analysis. These methods basically assign topics to words, however, and the relationship between words in a document is therefore not considered. Considering this, we propose a latent topic extraction method that assigns topics to events that represent the relation between words in a document. There are several ways to express events, and the accuracy of estimating latent topics differs depending on the definition of an event. We therefore propose five event types and examine which event type works well in estimating latent topics in a document with a common document retrieval task. As an application of our proposed method, we also show multidocument summarization based on latent topics. Through these experiments, we have confirmed that our proposed method results in higher accuracy than the conventional method.
Drawing Algorithm for Fuzzy Graphs Using the Partition Tree
Authors: Shiono Yasunori ,   Faculty of Information Sciences and Arts, Toyo University, 2100 Kujirai, Kawagoe-shi, Saitama 350-8585, Japan, Kirishima Tadaaki , Ueda Yoshinori , Tsuchida Kensei ,   University College of Cornerstone Education, J. F. Oberlin University, 3758 Tokiwa-machi, Machida-shi, Tokyo 194-0294, Japan
Published: April 2016

Fuzzy graphs have been used frequently and effectively as a method for sociogram analysis. A fuzzy graph has the fundamental characteristic of being able to express a variety of relationships between nodes. The drawing of fuzzy graphs has been studied in computer-aided analysis systems with human interfaces and methods using genetic algorithms. However, computer-aided analysis systems with human interfaces do not provide for automatic drawing, while methods using genetic algorithms have the defect of requiring too much execution time for finding a locally optimum solution. To overcome these defects, we propose an algorithm for drawing intelligible and comprehensive fuzzy graphs using a partition tree. This method automatically draws the fuzzy graphwith nodes arranged on the intersections of a latticed space. Since nodes are optimally arranged on the latticed intersections and put together at a nearby position in accordance with the transition of clusters according to cluster levels in the partition tree, drawing the algorithm makes fuzzy relations easier to understand through fuzzy graph representation. Moreover, fuzzy graphs can be drawn faster than by conventional methods. This paper describes the algorithm and its verification by introducing a system implementing the method for displaying fuzzy graphs. Moreover, we have carried out a case study in which a questionnaire has been administered to students, allowing us to analyze human relations quantitatively using a method based on fuzzy theory. Human relations are represented as fuzzy graphs by our algorithm and analyzed using the fuzzy graph.
Development of a System Incorporating a Multifunctional Actuator Using an Intelligent Multifunction Control Method
Authors: Kuribayashi Kazuki ,   Division of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Yasunobu Seiji
Published: April 2016

Next-generation robots, such as humanoid robots, require a multifunction control system. In the present study, a multifunctional actuator is considered in order to construct a multifunction control system more simply. The multifunctional actuator can easily set the parameters of target angle and stiffness, but determining the appropriate parameters is difficult. Therefore, in order to address this difficulty, we construct an intelligent controller based on iMIMOc. This iMIMOc is applied to a robot that incorporates multifunctional actuators, and an iMIMOc system is developed. The effectiveness of the developed system is verified through simulation and real-machine experiments.
Optimal Parameter Setting of Active-Contours Using Differential Evolution and Expert-Segmented Sample Image
Authors: Darvish Arman ,   Faculty of Engineering and Applied Science, University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, Ontario L1H 7K4, Canada, Rahnamayan Shahryar
Published: April 2016

Generally, tissue extraction (segmentation) is one of the most challenging tasks in medical image processing. Inaccurate segmentation propagates errors to the subsequent steps in the image processing chain. Thus, in any image processing chain, the role of segmentation is in fact critical because it has a significant impact on the accuracy of the final results, such as those of feature extraction. The appearance of variant noise types makes medical image segmentation a more complicated task. Thus far, many approaches for image segmentation have been proposed, including the well-known active contour (snake) model. This method minimizes the energy associated with the target’s contour, which is the sum of the internal and external energy. Although this model has strong characteristics, it suffers from sensitivity to its control parameters. Finding the optimal parameter values is not a trivial task, because the parameters are correlated and problem-dependent. To overcome this problem, this paper proposes a new approach for setting snake’s optimal parameters, which utilizes an expertsegmented gold (ground-truth) image and an optimization algorithm to determine the optimal values for snake’s seven control parameters. The proposed approach was tested on three different medical image test suites: prostate ultrasound (33 images), breast ultrasound (30 images), and lung X-Ray images (48 images). In the current approach, the DE algorithm is employed as a global optimizer. The scheme introduced in this paper is general enough to allow snake to be replaced by any other segmentation algorithm, such as the level set method. For experimental verification, 111 images were utilized. In a comparison with the prepared gold images, the overall error rate is shown to be less than 3%. We explain the proposed approach and the experiments in detail.
Proposal of Method “Motion Space” to Express Movement of Robot
Authors: Kurashige Kentarou ,   Muroran Institute of Technology, 27-1 Mizumoto-cho, Muroran city, Hokkaido 050-8585, Japan, Kitayama Naoki , Kiyohashi Masafumi ,   Sun Information & Service, Co, Ltd., 3-15-9 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
Published: April 2016

In recent years, the use of robots has been spreading to various fields. Further, requirements for the use of robots are increasing. A method is therefore necessary for allowing persons who are not experts in using robots to actually operate a robot. We intend to develop a method for robot operation whereby a user need not have technical knowledge. In this paper, we focus on methods whereby a user of a robot assigns movement to the robot and the robot reproduces movement. One of the most widely used techniques that is used nowadays involves teaching playback. Teaching playback is a method in which a teacher moves a robot using controllers and lets the robot record movement and then play it back. Robots functioning via teaching playback cannot however adapt to a changing environment. The environment in which human beings live generally change. Teaching playback is therefore not usable in variable environments. Methods for generating movement robustly in environments have been studied. Designing the movement of a robot by using these methods cannot be done, however without understanding complicated formulas. Only movement designers having technical knowledge can use these techniques. We propose new knowledge of movement to solve the problems present in these methods. Knowledge of movement is information involving the generation of movement in a robot. In conventional methods, knowledge ofmovement was a complicated formula. By using our method, a robot incorporates knowledge based on information obtained by moving a robot just like in the teaching playback method. We expect that by using our methods a user can move a robot in the desired manner.
A Time-Delay-Dependent Approach for a Class of T-S Fuzzy Models with Time Delays and Uncertainties
Authors: Han Hugang ,   Faculty of Management and Information Systems, Prefectural University of Hiroshima, 1-1-71 Ujina-Higashi, Minami-ku, Hiroshima, Hiroshima 734-8558, Japan, Tanaka Taku ,   Nikko Systems Solutions Ltd., 12-1 Daito-Chou, Tsurumi-ku, Yokohama, Kanagawa 230-0032, Japan
Published: April 2016

This paper deals with a class of T-S fuzzy models with time delays and uncertainties. On the basis of the socalled delay partitioning idea and a novel Lyapunov function candidate, a time-delay-dependent approach is provided in order to alleviate the conservatism of conditions for system stability. At the same time, the sliding-mode and adaptive control techniques are adopted to deal with the uncertainties, trying to remove some drawbacks in the existing results of fuzzy sliding-mode control systems.
Agglomerative Hierarchical Clustering Without Reversals on Dendrograms Using Asymmetric Similarity Measures
Authors: Takumi Satoshi ,   Department of Risk Engineering, School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan, Miyamoto Sadaaki
Published: April 2016

Algorithms of agglomerative hierarchical clustering using asymmetric similarity measures are studied. Two different measures between two clusters are proposed, one of which generalizes the average linkage for symmetric similarity measures. Asymmetric dendrogram representation is considered after foregoing studies. It is proved that the proposed linkage methods for asymmetric measures have no reversals in the dendrograms. Examples based on real data show how the methods work.
Sequential Regression Models with Pairwise Constraints Using Noise Clusters
Authors: Tang Hengjin ,   Department of Risk Engineering, School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba-shi, Ibaraki, 305-8573, Japan, Miyamoto Sadaaki
Published: April 2016

Switching regression models are useful in a variety of real applications. Semi-supervised clustering with pairwise constraints is also well-known to be important and many researchers recently study this subject. In spite of their usefulness, there is one drawback: the results have a strong dependency on the predefined number of clusters. To avoid this drawback, we use a method of sequentially extracting one cluster at a time using noise-detecting method, and propose constrained switching regressionmodels which enables an automatic determination of clusters. We show the effectiveness of the proposed method by using numerical examples.
Comparison of Semi-Supervised Hierarchical Clustering Using Clusterwise Tolerance
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 ,   Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

This paper presents a new semi-supervised agglomerative hierarchical clustering algorithm with the ward method using clusterwise tolerance. Semi-supervised clustering has recently been noted and studied in many research fields. Must-link and cannot-link, called pairwise constraints, are frequently used in order to improve clustering properties in semi-supervised clustering. First, clusterwise tolerance based pairwise constraints are introduced in order to handle mustlink and cannot-link constraints. Next, a new semisupervised hierarchical clustering algorithm with the ward method is constructed based on the above discussions. The effectiveness of the proposed algorithms is, moreover, verified through numerical examples.