bluuebunny/crossref_metadata_2025 huggingface dataset:
Primitive Optical Computing Model with Films: Boolean Conjunction of the Square Matrix-Arrayed Color Codes
Authors: Kawano Tomonori ,   The University of Kitakyushu, 1-1 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka 808-0135, Japan
Published: April 2016

Color is one of the most useful and attractive characteristics of light applicable to optical science and the related industries. In recent decades, a number of studies focusing on the use of light as a key component of computation have attracted considerable attention from researchers and engineers because these studies are potentially applicable to signal processing through optical interconnections between electronic devices. Such studies include the optical parallel logic gates proposed by a Japanese research group, allowing spontaneous and parallel computing with spatial coding using lights, simply by overlaying a pair of shadowgram images. For computational handling of the colors visible to human eyes,Commission Internationale de l’Eclairgehas defined CIE 1976 color space (CIELAB). The author has been engaged in the development of CIELAB-based printable and computable color codes possibly used for novel optical logic gate system as one of natural computing approaches. In the present study, by employing the pairs of CIELAB-coded-printed transparent films overlaid, a Boolean operation for the crossing (conjugation) of 2-by-2 color matrices based on the scanning of CIELAB values was demonstrated. This approach is still primitive but might be a significant step for manifesting the array-based processing of colors representing print-preserved and digitalized information.
Use of Colored Reflectors for Negation or Highlighting of Scanned Color Information on Film-Based CIELAB-Coded Optical Logic Gate Models
Authors: Moritaka Kiyoshi ,   The University of Kitakyushu, 1-1 Hibikino, Wakamatsu Kitakyushu, Fukuoka 808-0135, Japan, Kawano Tomonori
Published: April 2016

In the last two decades, a number of researchers have been engaged in the study of natural computing systems that employ physical, chemical, and biological properties as direct media for manifesting computations. Among such attempts, studies focusing on the use of lights as key computation components in particular have attracted the attention of researchers and engineers, since these studies are potentially applicable to signal processing through optical interconnections between electronic devices. Our research team has recently been engaged in the study of a novel color-based natural computing model. Our recent works included using CIELAB-coded colors on printed-paper to compute Boolean conjunctions (AND operations). In this study, we performed Boolean operations based on CIELAB-coded colors by placing color-printed films over aluminum-coated reflectors with and/or without color. The results of the operations were gathered by testing the color codes printed on the films for negation or highlighting. This type of CIELAB-based color computing has a wide range of potential applications, such as a method for security or access control to secured systems. Such applications could match paired color keys on which the arrays of color codes could be printed and optically computed.
Step Output Tracking Controller Design for Networked Control Systems
Authors: Pang Zhong-Hua ,   Department of Automation, Tsinghua University, Beijing 100084, China, Liu Guo-Ping , Zhou Donghua ,   School of Automation Engineering, Qingdao Technological University, Qingdao 266033, China,   School of Engineering, University of South Wales, Pontypridd CF37 1DL, United Kingdom,   CTGT Center, Harbin Institute of Technology, Harbin 150001, China
Published: April 2016

This paper is concerned with the step output tracking controller design problem for networked discretetime linear systems. The communication constraints such as network-induced delay, packet disorder, and packet dropout are considered, which are treated as the round-trip time (RTT) delay with an upper bound. An event-driven networked predictive control scheme is proposed to actively compensate for the RTT delay, which avoids the requirement of synchronization between the controller side and the plant side. The stability of the closed-loop system and the design procedure of the observer-based controller are discussed. A numerical example is employed to illustrate the effectiveness of the proposed methods.
On the Impact of Path Redundancy Awareness in Evolutionary P2P Networking
Authors: Pérez-Cortés Elizabeth ,   Electrical Engineering Department, Universidad Autónoma Metropolitana Iztapalapa, San Rafael Atlixco No. 186, Col. Vicentina, 09340, México D.F., Mexico, Sato Hiroyuki ,   Faculty of Informatics and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan
Published: April 2016

A P2P system is composed by autonomous nodes interconnected to share resources. The interconnections between the nodes define the P2P topology that is traversed to lookup resources. As nodes are autonomous, they are free to decide when to arrive and leave and what resources to share and download. To cope with this dynamism, the Evolutionary P2P Networking approach performs a periodical P2P topology reconfiguration applying evolutionary computation and using the amount of successful lookups as the evaluation function that drives the process. We extended this approach to also consider, as a part of the evaluation function, the creation of redundant paths in the topology and, additionally, we introduced elitism to improve the evolutionary process. In this work we present an extensive evaluation of both approaches. The results show that our approach scales better and produces more connected topologies. The improved connectivity ensures a higher rate of successful lookups under static and dynamic scenarios.
Influence of Field Structure on the Multi-Agent Coverage Algorithm on Unknown Fields
Authors: Yamachi Hidemi ,   Department of Computer and Information Engineering, Nippon Institute of Technology, 4-1 Gakuendai Miyashiro, Saitama 345-0826, Japan, Tsujimura Yasuhiro , Kambayashi Yasushi
Published: April 2016

There are a lot of researches and applications for the coverage problem of unknown fields by a robot, for example, planet exploration, mine-clearing operation. Using multi-robots for this problem we can expect effective operation. In order to control multi-robots effectively, obtaining cooperative action among robots is essential. We have proposed an algorithm for the cooperative multi-agent coverage simulation. There are three possible coverage paths: the zigzag, spiral and random paths. We have compared the effectiveness of those three coverage paths for a field where complex obstacles are allocated. The experimental results show that there are no remarkable differences of effectiveness among those three coverage paths. It is still not clear that how the shape or the allocation of obstacles affect the effectiveness of the coverage paths. In this paper we evaluate the influence of the field structure on the effectiveness of the coverage paths.
Understanding Geographic Attentions of Crowd from Photographing Information
Authors: Kubo Yusuke ,   National Defense Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-0811, Japan, Kubo Masao , Sato Hiroshi , Hirano Munetaka , Namatame Akira
Published: April 2016

We propose a framework for sharing photographs that reduces a load on communication network. When interesting events occur, many people take photographs of the events. Collecting photographs of such events and quickly building image database would enable us to share information in real-time more concretely than when using text based methods. However, a simple approach sending all photographs to a server immediately may cause congestion of a network infrastructure. In this paper, we propose a digital photographs classification method based on a main object of a photograph without using pixel information. Our method uses photographing information, that includes information about location and azimuth of a camera. Photographing information is automatically embedded into the photographs when it was taken. Our method determines main objects of photographs (socalled subject) and classifies the photographs based on these subjects. We can suppress congestion because only the best photographs transmitted to a server. In addition, classification accuracy is high because of the effect of collective intelligence. In this paper, we confirmed the effectiveness of our method through a series of experiments using a commercially available digital camera.
Development of Ghost Controller for Ms Pac-Man Versus Ghost Team with Grammatical Evolution
Authors: Tamura Kenji ,   Chuo Gakuin University, 451 Kujike, Abiko, Chiba 270-1196, Japan, Torii Takashi ,   Sugiyama Jogakuen University, 17-3 Hoshigaoka-Motomachi, Chikusa-ku, Nagoya 464-8662, Japan
Published: April 2016

These days, artificial intelligence (AI) has been used in game AI. Additionally, video game AI is studied actively in late years, for example, application of commercial game or competition etc. In many video games of recent years, real-time action and non-player characters have been required to attract players. This paper describes how to develop a ghost team controller using evolutionary system to play the video game, Ms Pac-Man. Ms Pac-Man has been used as a testbed of AI, especially multi-agent system. We propose a method to generate the ghost team controller with Grammatical Evolution. In case of developingMs Pacman agent with Evolutionary Computation using fitness function, the criterion of the fitness is used its obtained high score in many cases. In contrast, ghost team has to prevent Ms Pac-man to get high score, namely hold score in check. However, if Ms Pacman is captured in low score by accident, its ghost strategy have a possibility to survive next generation, and if the ghosts pursue Ms Pac-man in a line, agent isn’t captured for all time. Therefore developing ghost team agent is required to avoid these issues, and we introduced a penalty to the fitness, grammar like instinct and to attack Ms Pac-Man on both sides. This paper introduces experimental data about the ghost team controller for Ms Pac-Man versus ghost team, we used ghost team agents and tested them Ms Pac-Man agents. The experimental results showed that proposed system could catchMs Pac-Man agent compare with simple hand-coded ghost teams, and the evolved controller we made worked effectively. These results are concluded that proposed method works effectively for generating ghost controller.
Mobile Transparent Computing to Enable Ubiquitous Operating Systems and Applications
Authors: Huang Su-Zhen ,   School of Information Science and Engineering, Central South University, Yuelu District, Changsha, Hunan 410083, China, Wu Min , Xiong Yong-Hua
Published: April 2016

Mobile devices have emerged as an indispensable part of our daily life, one that has resulted in an increased demand for mobile devices to be able to access the Internet and obtain a variety of network services. However, mobile devices are often constrained by limited storage, huge power consumption, and low processing capability. This paper presents a new computing mode, mobile transparent computing (MTC), which combines ubiquitous mobile networks with transparent computing, to address the above challenges and possibly to enable a new world of ubiquitous operating systems (OSes) and applications with the following characteristics: (1) Mobile devices with no OSes pre-installed are able to load and boot multiple OSes on demand through a transparent network; (2) All resources, including the operating system (OS), applications, and user data, are stored on a transparent server (TS) rather than a mobile terminal, and can be streamed to be executed on mobile devices in small execution blocks; (3) All the personalized services (applications and data) can be synchronized to any other devices with the same user credential. Specifically, we propose a Pre OS technique, which can achieve feature (1) in the MTC model by initializing the mobile device and driving a network interface card (NIC) prior to OS loading, thereby transferring the needed OS streaming block to the mobile device. Experimental results conducted on the tablet demo-board with the model OK6410 based on the ARM11 architecture demonstrate that the Pre OS is able to support remote boot and streaming execution for both Android and Linux OS with satisfactory performance.
Distributed Power Allocation for Multiuser Two-Way Relay Networks Using Stackelberg Game
Authors: Jiang Fu ,   School of Information Science and Engineering, Central South University, Hunan Engineering Laboratory for Advanced Control and Intelligent Automation, Changsha, Hunan, 410075, China, Zhu Chaoliang , Peng Jun , He Yong , Li Shuo , Liu Weirong
Published: April 2016

Recently, two-way relay networks have been regarded as a promising technique that can improve bandwidth utilization. In this paper, the power allocation problem for multiuser two-way relay networks with amplifyand-forward protocol is investigated. In order to describe the self-interestedness of nodes in two-way relay networks, a two-level Stackelberg game is introduced to jointly optimize the benefits of the source pair and the relay nodes, where the relay nodes are modeled as leaders and the source pair is modeled as a follower. To facilitate the power allocation process, a distributed game-theoretic power allocation algorithm is proposed. Then, the existence and optimization of the Stackelberg equilibrium for the proposed power allocation algorithm is proven. The convergence of the presented algorithm is also analyzed by proving that price update is a standard function. Simulation results indicate that the proposed power allocation algorithm can improve energy utilization by jointly optimizing the utilities of both source pair and relay nodes.
Construction of Kinect-Based Measuring and Monitoring System for the Degree of Employee’s Fatigue
Authors: She Jinhua ,   School of Computer Science, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan, Nakamura Hitoshi , Imani Junya , Ohyama Yasuhiro ,   Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan
Published: April 2016

In this study, we developed a new system for measuring and monitoring the degree of an employee’s fatigue. The system is comprised of an ergometer, a pulsometer, a Kinect sensor, and a computer. It records the heart rate and the 3D motion of a subject during a pedaling exercise. This system is simple, inexpensive, and easy to use. This paper explains the construction of the system, and reports the results of verification experiments with a special focus on the use of the Kinect sensor. The results show that the Kinect sensor is a useful tool for recording body movement and that the system may be used to measure and monitor the degree of fatigue.
An Improved Particle Swarm Optimization Deployment for Wireless Sensor Networks
Authors: Ding Shuxin ,   School of Automation, Beijing Institute of Technology, Key Laboratory of Intelligent Control and Decision of Complex Systems, 5 Zhong Guan Cun South Street, Haidian District, Beijing 100081, China, Chen Chen , Chen Jie , Xin Bin
Published: April 2016

This paper addresses the issues associated with deployment of sensors, which are critical in wireless sensor networks. This paper provides an improved particle swarm optimization (PSO) algorithm by changing the basic form of PSO and introducing disturbance (d-PSO). By comparing with other PSO-based algorithms, simulation results show that the d-PSO algorithm provides a good-coverage solution with a satisfying coverage rate in a short time. This feature is especially useful for the rapid deployment of sensors.
Fuzzy Autocorrelation Model with Confidence Intervals of Fuzzy Random Data
Authors: Yabuuchi Yoshiyuki ,   Faculty of Economics, Shimonoseki City University, 2-1-1 Daigaku-cho, Shimonoseki, Yamaguchi 751-8510, Japan, Watada Junzo ,   Graduate School of Information, Production and Systems, Waseda University, 2-4 Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0196, Japan
Published: April 2016

Economic analyses are typical methods based on timeseries data or cross-section data. Economic systems are complex because they involve human behaviors and are affected by many factors. When a system includes such uncertainty, as those concerning human behaviors, a fuzzy system approach plays a pivotal role in such analysis. In this paper, we propose a fuzzy autocorrelation model with confidence intervals of fuzzy random timeseries data. These confidence intervals play an essential role in dealing with fuzzy random data on the fuzzy autocorrelation model that we have presented. We analyze tick-by-tick data of stock transactions and compare two time-series models, a fuzzy autocorrelation model proposed by us, and a new fuzzy time-series model that we propose in this paper.
A Development of Force Distribution Measurement System with High Resolution for Total Knee Arthroplasty
Authors: Som Mohd Hanafi Mat ,   Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui-shi, Fukui 910-0017, Japan, Nagamune Kouki , Kamiya Takashi , Kawaguchi Shogo , Takayama Koji , Matsumoto Tomoyuki , Kuroda Ryosuke , Kurosaka Masahiro ,   School of Mechatronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, Arau, Perlis 02600, Malaysia,   Graduate School of Medicine, Kobe University, 7-5-1 Kusunokicho, Chuo-ku, Hyogo, Kobe 650-0017, Japan
Published: April 2016

Soft tissue or ligament balancing in total knee arthroplasty is important for ensuring knee joint stability. Correct balancing and appropriate alignment of ligaments extend prosthesis life by preventing unnecessary force fromacting on the prosthesis during routine activities. The current implementation of total knee arthroplasty relies heavily on the subjective “feel” of the surgeon for correct prosthesis implantation onto tibiofemoral components. We developed a force distribution sensing systemto provide quantitative information to surgeons during ligament balancing. The measurement system consists of two main components: two force sensors embedded in trial insert for each condyle and signal acquisition for data processing and force visualization. Sensors were designed and developed using pressure-sensitive conductive rubber that measures changes in resistance in the event of deformation caused by external force. Corresponding voltage measured by circuits is transmitted via an RF transceiver to a computer and visualized as color gradient. Current sensors could measure maximum force of 196.13 N (20 kgf). Results from calibration and experiments on a plastic trial prosthesis indicated that the device has good potential for providing appropriate force distribution information on the knee during total knee arthroplasty procedure.
Archive of Useful Solutions for Directed Mating in Evolutionary Constrained Multiobjective Optimization
Authors: Miyakawa Minami ,   The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan, Takadama Keiki , Sato Hiroyuki
Published: April 2016

As an evolutionary approach to solve multi-objective optimization problems involving several constraints, recently a multi-objective evolutionary algorithm (MOEA) using two-stage non-dominated sorting and directed mating (TNSDM) has been proposed. In TNSDM, directed mating utilizes infeasible solutions dominating feasible solutions in the objective space to generate offspring. In our previous studies, significant contribution of directed mating to the improvement of the search performancewas verified on several benchmark problems. However, in the conventional TNSDM, infeasible solutions utilized in directed mating are discarded in the selection process of parents (elites) population and cannot be utilized in the next generation. TNSDM has potential to further improve the search performance by archiving useful solutions for directed mating to the next generation and repeatedly utilizing them in directed mating. To further improve effects of directed mating in TNSDM, in this work, we propose an archiving strategy of useful solutions for directed mating. We verify the search performance of TNSDM using the proposed archive by varying the size of archive, and compare its search performance with the conventional CNSGA-II and RTS onmobjectiveskknapsacks problems. As results, we show that the search performance of TNSDM is improved by introducing the proposed archive in aspects of diversity of the obtained solutions in the objective space and convergence of solutions toward the optimal Pareto front.
Active Sampling for Constrained Clustering
Authors: Okabe Masayuki ,   Information and Media Center, Toyohashi University of Technology, 1-1 Tempaku, Toyohashi, Aichi 441-8580, Japan, Yamada Seiji ,   National Institute of Informatics, SOKENDAI, 2-1-2 Chiyoda, Tokyko 101-8430, Japan
Published: April 2016

Constrained clustering is a framework for improving clustering performance by using constraints about data pairs. Since performance of constrained clustering depends on the set of constraints used, a method is needed to select good constraints that promote clustering performance. In this paper, we propose an active sampling method working with a constrained cluster ensemble algorithm that aggregates clustering results that a modified COP-Kmeans iteratively produces by changing the priorities of constraints. Our method follows the approach of uncertainty sampling and measures uncertainty using variations of clustering results where data pairs are clustered together in some results but not in others. It selects the data pair to be labeled that has the most variable result during cluster ensemble process. Experimental results show that our method outperforms random sampling. We further investigate the effect of important parameters.
Performance Comparison of Collaborative Filtering withk-Anonymized Data by Fuzzyk-Member Clustering
Authors: Kawano Arina ,   Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Nakaku, Sakai, Osaka 599-8531, Japan, Honda Katsuhiro , Notsu Akira , Ichihashi Hidetomo ,   Department of Economics, Osaka University of Economics and Law, 6-10 Gakuonji, Yao, Osaka 581-8511, Japan
Published: April 2016

In order to perform collaborative filtering with published databases in a privacy preserving manner, databases must be anonymized beforehand. This paper studies the applicability of fuzzyk-member clustering in privacy preserving collaborative filtering withk-anonymized data, in which users’ historical data ofkor more users are suppressed considering soft data partitions. By allowing boundary samples to be shared by multiple clusters, data anonymization is performed without significant loss of information. Its performances are compared with several different types of fuzzy membership functions.
Dental Numbering for Periapical Radiograph Based on Multiple Fuzzy Attribute Approach
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 , Yan Fei , Betancourt Janet Pomares , Widyanto Muhammad Rahmat , Dong Fangyan , Hirota Kaoru ,   Department of Informatics, Institut Teknologi Sepuluh Nopember, Kampus ITS Keputih, Surabaya 60111, Indonesia,   Department of Computer Science, University of Indonesia, Depok Campus, Depok 16424, West Java, Indonesia
Published: April 2016

The dental numbering for periapical radiograph based on multiple fuzzy attribute approach proposed here analyzes each individual tooth based on multiple criteria such as area/perimeter and width/height ratios. The classification and numbering in a special dental image called a periapical radiograph is studied without speculative classification in cases of ambiguous objects, so an accurate, assistive result is obtained due to the capability of handling ambiguous teeth. Experiment results in using periapical dental radiograph from the University of Indonesia indicate a total classification accuracy of 82.51%, an average classification rate per input radiograph of 84.29%, a maxilla-mandible identification accuracy from 78 radiographs of 82.05%, and a numbering accuracy from 15 radiographs of 90.47%. It is planned that the proposed classification and numbering be implemented as a submodule for dental-based personal identification now being developed.
Special Issue on CogInfoCom 2012
Authors: Charaf Hassan
Published: April 2016

Cognitive infocommunications (CogInfoCom) investigates connections between the cognitive sciences and different areas of infocommunications. CogInfoCom also focuses on engineering application fields integrating related scientific areas and results. Cognitive infocommunications systems involve hardware and software components that collect and store information and enable users to interact with this information. Besides communication security, considerations include the amount of stored information, which may be huge. This means that there is a need for algorithms and solutions that store and process data effectively. The CogInfoCom field presents a number of motivational challenges requiring active deep research, implementation, integration and measurement. This special issue focuses on the Cognitive Mobile Applications and Services track of the 3rd IEEE International Conference on Cognitive Infocommunications (CogInfoComf12). Mobile phones and tablets are now everyday tools that enable users to easily connect to the Internet, download social content, find interesting places, etc. Mobile technology has become one of the most important fields in the IT industry just as Web technology was 10-15 years ago. Mobile phones and tablets use sensors and interfaces like accelerometers, cameras, GPS, and thermometers that monitor and enable easier interaction with the real world. Agents hosted by mobile devices that learn from sensor-originated information also support individual applications and complex systems. This special issue focuses on the cognitive capabilities of mobile phones, the various agents that mobile devices host, and how they can be applied efficiently in applications and services including social aspects of mobile solutions. Papers from the conference cover mobile controlled environments, mobile-supported learning, augmented reality, energy efficiency and communication techniques. We thank the authors for submitting their papers to CogInfoCom as a venue for presenting their findings. We are also grateful to program committee members and reviewers for their efforts in making the conference and the special issue possible. We feel that these papers will provide readers with interesting and valuable results from the field of cognitive infocommunications.
The Usage and Behavior Patterns of Mobile BitTorrent Clients
Authors: Ekler Péter ,   Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Magyar Tudsok krtja 2., 1117 Budapest, Hungary, Csorba Kristóf
Published: April 2016

With the many changes in mobile phone use, it is now common for users to connect to the Internet and share social and multimedia data, and peer-to-peer technology remains one of the most efficient solutions to content sharing. We analysed the lifecycle of content shared using the BitTorrent network, focusing on torrents retrieved by mobile phone clients using our MobTorrent application. MobTorrent, a complete Bit-Torrent client for feature phones, enables anonymous usage statistics to be collected. Based on statistics collected over the last three years, we analyze how mobile BitTorrent clients are being used. We discuss the success of individual sessions by additionally measuring peer connection download and success ratio statistics. This research can be considered as a pioneer work in the field of mobile content sharing solutions.
Analysis of Parameters of Gait Cycle in Case of Reumathoid Arthritis (A Case Study)
Authors: Steiner Henriette ,   Department of Control Engineering and Information Technology, Budapest University of Technology and Economics, 1117 Magyar tudósok körútja 2, Budapest, Hungary, Kertész Zsolt
Published: April 2016

Rheumatoid arthritis (RA) is a chronic, systemic disorder that may affect many tissues and organs, but principally attacks flexible joints. We examined the effect of eurhythmy on the development of young adult female. 1 young adult female participated in eurhythmy. We analyze walking two times a (it means two full body analyses each time – with and without staff at the same time).
Identification of Season-Dependent Sightseeing Spots Based on Metadata-Derived Features and Image Processing
Authors: Chen Chia-Huang ,   Graduate School of System Design, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan, Takama Yasufumi
Published: April 2016

Sharing traveling experience and photos on Social Network Service or Web albums is more and more popular recently. Good sightseeing photos in specific situation such as sunset and spring season can impress tourists well, and be clues for them to consider where and when to visit for sightseeing. Regarding situations to be identified, this paper focuses on season. Compared with situations relating with weather and time of day (e.g., sunrise/sunset), whether or not different seasons have different scenery depends on sightseeing spots. Therefore, classifying sightseeing spots into season-dependent/independent is required as preprocessing for season-based classification of sightseeing photos. This paper proposes a hybrid approach for identifying season-dependent sightseeing spots, of which the first phase applies machine learning with statistical features of sightseeing photos obtained from metadata. In order to improve precision, the second phase applies color-based classification to spots identified as season-dependent in the first phase. The experimental results show the effectiveness of the proposed method.
Effects of Ecological Inheritance on Coevolution of Cooperative Behaviors and Physically Niche Constructing Behaviors
Authors: Kojima Takuro ,   Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan, Suzuki Reiji , Arita Takaya
Published: April 2016

Niche construction is a process whereby organisms that modify their own or others’ niches through their ecological activities. Recent studies have revealed that changes in social structures of interactions caused by social niche construction of individuals can affect seriously the evolution of cooperation. However, such a social niche also could be changed indirectly by a modification of their physical environment. Our purpose is to clarify the coevolution of cooperative behavior and physically niche-constructing behavior that modifies social niche indirectly. For this purpose, we constructed an evolutionary model in which each individual has not only a strategy for a spatial Prisoner’s Dilemma but also has traits for a niche-constructing behavior for modifying its physical environment that can limit social interactions between neighboring individuals. By conducting evolutionary experiments, we show that a cyclic coevolution between cooperative behavior and niche-constructing behavior occurred in the situation with no or low degree of ecological inheritance, in which the constructed niche could not be inherited in succeeding generations at all. Conversely, when the degree of ecological inheritance was high, the evolution of cooperation was promoted by the emerged environmental structure constructed by the evolved niche-constructing behavior. We also show that the condition for each scenario to occur depends on the settings of the payoff parameters as well as the degree of ecological inheritance.
Learning of Glycan Motifs Using Genetic Programming and Various Fitness Functions
Authors: Miyahara Tetsuhiro ,   Graduate School of Information Sciences, Hiroshima City University, 3-4-1 Ozuka-higashi, Asaminami-ku, Hiroshima 731-3194, Japan, Kuboyama Tetsuji ,   Computer Centre, Gakushuin University, 1-7-1 Mejiro, Toshima-ku, Tokyo 151-8588, Japan
Published: April 2016

We apply a genetic programming approach to learning of glycan motifs by using tag tree patterns and various fitness functions. Tag tree patterns obtained from some glycan data show characteristic tree structures. We examine the effects of using various fitness functions on GP processes and obtained glycan motifs. We also show that our method is applicable to tree structured data other than glycan data.
Fuzzy VRIO and SWOT Analysis of Chery Automobile
Authors: Chen Faen ,   Graduate School of Management and Information Science, Osaka International University, 3-50-1 Sugi, Hirakata, Osaka 573-0192, Japan, Kodono Yukio ,   Faculty of Business Administration, Osaka International University, 3-50-1 Sugi, Hirakata, Osaka 573-0192, Japan
Published: April 2016

The Chinese market is indispensable for international automobile enterprises and they are expanding their investment in this market accordingly. To escalate their market share in China, automobile manufacturers and independent automotive enterprises have implemented a series of management strategies. Consequently, competition in China is becoming increasingly intense. Conversely, Chinese automobile enterprises have no international brand recognition. In this paper, an independent automobile enterprise, Chery Automobile Co. Ltd., is selected as a case study and examined using the SWOT (Strengths, Weaknesses, Opportunities and Threats) method. Moreover, we analyzed the strengths and weaknesses of the company’s internal environment using a fuzzy VRIO (Value, Rarity, Immutability and Organization) method. Applying the fuzzy theory to an analysis of the management environment can facilitate more effective strategy formulations. It is expected that the application of fuzzy theory to management methods will contribute to the future development of the Chinese automobile industry. The competitive advantages to Chery are illustrated by the fuzzy VRIO analysis.
Segmented Wavelet Decomposition for Capnogram Feature Extraction in Asthma Classification
Authors: Betancourt Janet Pomares ,   Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Tangel Martin Leonard , Yan Fei , Diaz Marianella Otaño , Otaño Alejandro Ernesto Portela , Dong Fangyan , Hirota Kaoru ,   Central Institute of Digital Research, 202, No.1704, Siboney, Playa, Havana, Cuba,   Polyclinic “Julian Grimau” 10 de Octubre Ave., No.1004, Arroyo Naranjo, Havana, Cuba
Published: April 2016

A feature extraction method from capnograms used for classifying asthma is proposed based on wavelet decomposition. Its computational cost is low and its performance is adequate for classifying asthma in real time. Experiments performed using 23 capnograms from an asthma camp in Cuba showed 97.39% best classification accuracy. The time required for a physiological multiparameter monitor to determine the suitable features of capnograms averaged 8 seconds. The proposal is to be used as part of a decision support system for asthma classification being developed by TITECH and TMDU research groups.
An Efficient Super Resolution Based on Image Dimensionality Reduction Using Accumulative Intensity Gradient
Authors: Haris Muhammad ,   Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Sawase Kazuhito , Widyanto Muhammad Rahmat , Nobuhara Hajime ,   Computer Science Faculty, University of Indonesia, Depok, West Java, Indonesia
Published: April 2016

An efficient super resolution algorithm based on edge direction is proposed based on the dimensional reduction of color images and 3 types of edge direction. The basic idea is to reduce image – especially color image – dimensions and to interpolate pixels by using 3 simple edge directions – vertical, horizontal, and diagonal. The proposed algorithm conceivably eliminate more color artifacts than Bicubic. The results of experiments using 30 natural images confirm that PSNR of the proposed method achieve the same quality as Fast Curvature Based Interpolation (FCBI). We confirmed that computation time for the proposed method was 40% shorter for RGB and 20% shorter for grayscale images than the previous fastest method, i.e., FCBI. We show efficient panorama image generation based on the proposed super resolution method as one application of our proposal.
A Probabilistic WKL Rule for Incremental Feature Learning and Pattern Recognition
Authors: Léveillé Jasmin ,   Center of Excellence for Learning in Education, Science and Technology, Boston University, 677 Beacon Street, Boston, Massachusetts 02215, USA, Hayashi Isao , Fukushima Kunihiko ,   Faculty of Informatics, Kansai University, 2-1-1 Ryozenji-cho, Takatsuki, Osaka 569-1095, Japan,   Fuzzy Logic Systems Institute, 680-41 Kawazu, Iizuka, Fukuoka 820-0067, Japan
Published: April 2016

Recent advances in machine learning and computer vision have led to the development of several sophisticated learning schemes for object recognition by convolutional networks. One relatively simple learning rule, the Winner-Kill-Loser (WKL), was shown to be efficient at learning higher-order features in the neocognitron model when used in a written digit classification task. The WKL rule is one variant of incremental clustering procedures that adapt the number of cluster components to the input data. The WKL rule seeks to provide a complete, yet minimally redundant, covering of the input distribution. It is difficult to apply this approach directly to high-dimensional spaces since it leads to a dramatic explosion in the number of clustering components. In this work, a small generalization of the WKL rule is proposed to learn from high-dimensional data. We first show that the learning rule leads mostly to V1-like oriented cells when applied to natural images, suggesting that it captures second-order image statistics not unlike variants of Hebbian learning. We further embed the proposed learning rule into a convolutional network, specifically, the Neocognitron, and show its usefulness on a standard written digit recognition benchmark. Although the new learning rule leads to a small reduction in overall accuracy, this small reduction is accompanied by a major reduction in the number of coding nodes in the network. This in turn confirms that by learning statistical regularities rather than covering an entire input space, it may be possible to incrementally learn and retain most of the useful structure in the input distribution.
Preventing Large-Scale Emergencies in Modern Power Systems: AI Approach
Authors: Negnevitsky Michael ,   School of Engineering, University of Tasmania, Private Bag 65, Hobart, Australia, Tomin Nikita V. , Rehtanz Christian ,   Department of Electric Power System, Melentiev Energy Systems Institute, 130 Lermontov Str., Irkutsk 664033, Russia,   Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund University, Emil-Figge-Strasse 70, Dortmund 44221, Germany
Published: April 2016

In recent years, due to liberalization, power systems are being operated closer and closer to their limits. At the same time, they have increased in size and complexity. Both factors increase the risk of major power outages and blackouts. In emergency and abnormal conditions, a power system operator has to deal with large amounts of data. However, due to emotional and psychological stress, an operatormay not be able to respond to critical conditions adequately and make correct decisions promptly. Mistakes can damage very expensive power system equipment or worse lead to major emergencies and catastrophic situations. Intelligent systems can play an important role by alarming the operator and suggesting the necessary actions to be taken to deal with a given emergency. This paper outlines some experience obtained at the University of Tasmania, Australia, Energy Systems Institute, Russia and TU-Dortmund University, Germany in developing intelligent systems for preventing large-scale emergencies and blackouts in modern power systems.
Advanced Concept Offshore Wind Turbine Development
Authors: Afjeh Abdollah A. ,   Mechanical Industrial and Manufacturing Engineering Department, The University of Toledo, Toledo, OH 43606, USA, Andersen Brett , Lee Jin Woo , Norouzi Mahdi , Nikolaidis Efstratios ,   Department of Physics and Engineering, Frostburg State University, Frostburg, MD 21532, USA
Published: April 2016

Development of novel offshore wind turbine designs and technologies are necessary to reduce the cost of offshore wind energy since offshore wind turbines need to withstand ice and waves in addition to wind, a markedly different environment from their onshore counterparts. This paper focuses on major design challenges of offshore wind turbines and offers an advanced concept wind turbine that can significantly reduce the cost of offshore wind energy as an alternative to the current popular designs. The design consists of a two-blade, downwind rotor configuration fitted to a fixed bottom or floating foundation. Preliminary results indicate that cost savings of nearly 25% are possible compared with the conventional upwind wind turbine designs.
Optimizing Friction Stir Welding of Al 6061 Alloy Using Statistical Analysis
Authors: Kang Dae Min ,   Department of Mechanical Engineering, Pukyong National University, 100 Yongdang-Dong, Nam-Ku, Pusan 608-739, Korea, Park Kyoung Do , Lee Dai Yeal ,   Graduate School of Mechanical Engineering, Pukyong National University, 100 Yongdang-Dong, Nam-Ku, Pusan 608-739, Korea,   The Korea Chamber of Commerce & Industry Busan Human Resorce Development Institute, San 9, Yongdang-dong, Nam-gu, Pusan 608-080, Korea
Published: April 2016

In this study, a three-way factorial design is used to optimize the friction stir welding (FSW) process of Al 6061 alloy. Control factors are shoulder diameter, travel speed, and rotation speed of tool, and each factor has three levels. Tensile strength tests are also carried out to measure the mechanical properties under various FSW conditions. In this work, travel speed, shoulder diameter, and tool speed are shown to individually be meaningful factors in the tensile strength of the alloy, but interactions among the weld factors are not detected. The result of the study is that the optimum process condition for maximum tensile strength is estimated to be A3B3C3. In addition, the presumed range of tensile strength under the optimal conditions is estimated to be 257±23 (Mpa) with 95% reliability.
Femtosecond Pulsed Laser Deposition of Graphite on Silicon and Copper Foil
Authors: Calleja Mary Ann ,   Photonics Research Laboratory, National Institute of Physics, University of the Philippines, Diliman 1101, Quezon City, Philippines, Amo Annaliza , Miranda Jessa Jayne , Patricio Floyd Willis , Garcia Wilson
Published: April 2016

We deposited graphite on silicon (111) and copper foil substrate through femtosecond pulsed laser deposition (fs-PLD). A high purity graphite target was placed inside a vacuum chamber at a base pressure of 10-2mbar. The deposition time was varied for 3 hours, 4 hours and 5 hours. XRD spectra showed a (110) peak indicating an oriented growth for samples deposited on silicon (111) and copper foil substrates. AFM topographical images of the samples deposited on silicon (111) showed flake-like structures. However, samples deposited on copper foil showed the presence of defects and lack of deposited particles.
Swarm Robot System for Underwater Communication Network
Authors: Vicerra Ryan Rhay P. ,   De La Salle University, 2401 Taft Ave., Manila, 1004 Philippines, Dadios Elmer P. , Bandala Argel A. , Lim Laurence A. Gan
Published: April 2016

This paper presents a swarm robot simulator for implementing underwater wireless communication network. Swarm intelligence is based on the collective behavior of social insects and animals such as ants, bees and others. In this paper, swarm was applied to overcome the challenges of transmitting data in a large underwater environment. A robot considered to be a member of the swarm acts as a simple “physical” carrier of the data, it moves until they converge and manage to form a link connecting the data transmitter and receiver. The system is developed, simulated and tested using a coded simulator.
Synchronized Dual Camera Vision System for Locating and Identify Highly Dynamic Objects
Authors: Gunay Noel S. ,   De La Salle University, 2401 Taft Ave., Manila, 1004 Philippines, Dadios Elmer P. , Vicerra Ryan Rhay P. , Bandala Argel A. , Lim Laurence A. Gan
Published: April 2016

This paper presents machine vision for locating and identifying 23 highly dynamic objects on 4.4 meters by 2.8 meters micro robot soccer playing field. The approach is based from the idea that the two camera vision subsystems should be synchronized and well informed in real time of the combined vision data and a selection of objects to track under each other’s camera view. A measure of effectiveness on using incremental tracking for two-camera operation is developed and is used to evaluate the introduced approach through experimentation. A real-time visualization of the whole playfield containing the 22 micro robots and a golf ball is also provided for the system operator to validate the objects’ actual poses with the vision system’s measurements. Results show that the proposed technique is very fast, accurate, reliable, and robust to external disturbances.
Bag-of-Bounding-Boxes: An Unsupervised Approach for Object-Level View Image Retrieval
Authors: Tanaka Kanji ,   University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan, Ando Masatoshi , Inagaki Yousuke
Published: April 2016

We propose a novel bag-of-words (BoW) framework for building and retrieving a compact database of view images for use in robotic localization, mapping, and SLAM applications. Unlike most previous methods, our method does not describe an image based on its many small local features (e.g., bag-of-SIFT-features). Instead, the proposed bag-of-bounding-boxes (BoBB) approach attempts to describe an image based on fewer larger object patterns, which leads to a semantic and compact image descriptor. To make the view retrieval systemmore practical and autonomous, the object pattern discovery process is unsupervised through a common pattern discovery (CPD) between the input and known reference images without requiring the use of a pre-trained object detector. Moreover, our CPD subtask does not rely on good image segmentation techniques and is able to handle scale variations by exploiting the recently developed CPD technique, i.e., a spatial randompartition. Following a traditional bounding-box based object annotation and knowledge transfer, we compactly describe an image in a BoBB form. Using a slightly modified inverted file system, we efficiently index and/or search for the BoBB descriptors. Experiments using the publicly available “Robot-Car” dataset show that the proposed method achieves accurate object-level view image retrieval using significantly compact image descriptors, e.g., 20 words per image.