bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating Instantaneous Psychological Stress from Emotional Composition of a Facial Expression
Authors: Das Suvashis ,   Department of Management and Information Systems Science, Nagaoka University of Technology, 1603-1 Kamitomiokamachi, Nagaoka, Niigata 940-2137, Japan, Yamada Koichi
Published: April 2016

Human psychological stress is a vast and highly complicated topic of study and research. The types and kinds of stress observed in humans vary among researchers. Also, to identify stress, many methods exist. Most of these methods are non-intrusive and are based on self-reporting and questionnaires which reduces the real-time efficacy of the procedure. Intrusive methods are, on the other hand, time consuming and cumbersome. The total problem of non-intrusive psychological stress detection from facial images can be visualized in three incremental stages: instantaneous analysis of subject, historical analysis of subject, and the subject’s environmental analysis. In this paper, we deal with instantaneous analysis of a subject. This means that the stress behavior of a subject is predicted for one moment of time using an image of his/her facial expression. In order to do so, we have conducted two surveys to establish the relationship between emotional compositions of a facial expression with stress and also to establish the relationship of individual emotions with stress. The novelty of the paper is 1) to establish relationships between the seven basic emotions (anger, contempt, disgust, fear, happy, sad, and surprise) and stress, 2) to establish relationship between emotional composition of a facial expression and stress, and 3) to predict a formula for evaluating stress in terms of emotional percentage mixture of a facial expression. In order to achieve the three goals, we use Facial Action Unit (AU) [1] coded image data to predict the emotional mixture of the facial expression in terms of the seven basic emotion percentages. An AU represents one of the many basic muscle movements that make up the facial expression. Then we analyze the survey outcomes to establish the relationship between individual emotions and stress. Finally we correlate the survey outcomes with the emotional mixture data obtained from the facial expression using Hidden Markov Model (HMM) approach to both establish a relationship of emotional composition with stress and to predict a formula for stress in terms of the seven basic emotion percentages jointly.
Acquisition of Dispatching Rules for Job-Shop Scheduling Problem by Artificial Neural Networks Using PSO
Authors: Tamura Yasumasa ,   Graduate School of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo, Hokkaido 060-0814, Japan, Yamamoto Masahito , Suzuki Ikuo , Furukawa Masashi ,   Department of Computer Science, Kitami Institute of Technology,   Department of System and Informatics, Faculty of Business Administration and Information Science, Hokkaido Information University
Published: April 2016

A Job-shop Scheduling Problem (JSP) constitutes the basic scheduling problem that is observed in manufacturing systems. In conventional JSP, feature values of work and queue times are used to formulate dispatching rules for scheduling. In this paper, an Artificial Neural Network (ANN) is used to create an index for job priority. Furthermore, in order to optimize the output of the ANN, Particle Swarm Optimization (PSO) is used in unsupervised learning of the synaptic weights for the ANN. The functions of the proposed method are discussed in this paper.
Evaluation of Haptic Interaction in Intercultural Online Negotiation
Authors: Chen Meng ,   Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Okada Shogo , Nitta Katsumi
Published: April 2016

In this study, we bring haptic technology into an online negotiation system to improve the method of conveying nonverbal information. Our goal is to verify the effectiveness of haptic interaction in communication between Japanese and Chinese participants. We conducted online negotiation experiments with and without haptic interaction. We classified Chinese participants according to their Japanese levels, and analyzed characteristics of their haptic interaction. Results of the questionnaire we administered implied that in negotiations with haptic interaction, the expression of emotion and the sense of presence were improved compared to those without haptic interaction. Results of Japanese – Chinese pairs showed haptic interaction to be of higher importance to Chinese than the Japanese pairs. For participants who lacked linguistic ability, haptic interaction still showed usefulness in experiments. We concluded from these results that haptic interaction during intercultural online negotiation was effective for intercultural users.
LUT Controller Design with Piecewise Bilinear Systems Using Estimation of Bounds for Approximation Errors
Authors: Taniguchi Tadanari ,   Tokai University, 4-1-1 Kitakaname, Hiratsuka, Kanagawa 259-1292, Japan, Eciolaza Luka , Sugeno Michio ,   European Center for Soft Computing, c/ Gonzalo Gutierrez Quieros, s/n, 33600 Mieres, Asturias, Spain
Published: April 2016

We propose the stabilization of nonlinear control systems approximated by Piecewise Bilinear (PB) models. The approximated model is fully parametric and a Look-Up-Table (LUT) represents its controller. Input-Output (I/O) feedback linearization is applied to stabilize PB control systems. We further propose PB modeling combined with conventional feedback linearization as a very powerful tool for analyzing and synthesizing nonlinear control systems. We also propose a method for designing robust stabilization controllers taking modeling error into consideration. Examples confirm the feasibility of our proposals.
User-Friendly Simulator for Open Modeling by Hierarchically Management
Authors: Ikai Masato ,   Department of Informatics, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan, Itakura Naoaki
Published: April 2016

We propose a user-friendly simulator in which the structure and modeling are open to any user. The proposed simulator can easily build a complicated model by using a hierarchicalmanagement system. To realize model constructions that are easier for users to understand, we introduce a cascaded binary relation function CBRF as a model unit. An editor that efficiently uses the structure is being developed. Application of this simulator to various targets allows approximate simulation results to be quickly and easily obtained.
Fractal-Based Analysis for the Energy Consumption Efficiency of Biological Networks
Authors: Furuki Hidekazu ,   Department of Computer Science, National Defense Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-8686, Japan, Sato Hiroshi , Shirakawa Tomohiro
Published: April 2016

Using a simulation model, we investigated the energy consumption efficiency of biological networks in terms of the fractal dimension of network morphology, the flow rate inside, and the resources needed for network construction. In themodel, we constructedmany types of tree networks and simulated the fluidic flow inside the networks. As a result, we clarified the precision of a preexisting equation and the efficiency of energy consumption for the networks.
Cooperative Transport by a Swarm Robotic System Based on CMA-NeuroES Approach
Authors: Yu Tian ,   Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan, Yasuda Toshiyuki , Ohkura Kazuhiro , Matsumura Yoshiyuki , Goka Masanori ,   Graduate School of Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda, Nagano 386-8567, Japan,   Graduate School of Engineering, Fukuyama University, 985-1 Fukuyama City, Hiroshima 729-0251, Japan
Published: April 2016

Swarm robotic systems consist of many homogeneous autonomous robots with no type of global controllers. It is difficult to design controllers for such behavioral systems, since the behavior of system level is the emergent results of the dynamical interaction between the systems and the environment. This paper uses a method that in which robot controllers are designed by a covariance matrix adaptation evolution strategy (CMA-ES) with artificial neural networks. This approach is referred to as CMA-NeuroES. Among the many evolutionary algorithms for evolving artificial neural networks, two conventionally representation approaches, fast evolution strategies and differential evolution, are used for comparison. The cooperative transport problem is used as a benchmark of swarm robotic systems to test their performance. Results show that CMA-NeuroES has the overall best performance of the three.
A Threat Assessment Method Based on Hierarchies and Modules
Authors: Deng Fang ,   School of Automation, Beijing Institute of Technology, Beijing, 100081, China, Liu Xinan , Peng Zhihong , Chen Jie
Published: April 2016

With the development of low-level data fusion technology, threat assessment, which is a part of high-level data fusion, is recognized by an increasing numbers of people. However, the method to solve the problem of threat assessment for various kinds of targets and attacks is unknown. Hence, a threat assessment method is proposed in this paper to solve this problem. This method includes tertiary assessments: information classification, reorganization, and summary. In the tertiary assessments model, various threats with multi-class targets and attacks can be comprehensively assessed. A case study with specific algorithms and scenarios is shown to prove the validity and rationality of this method.
Multi-Resolution Dijkstra Method Based on Multi-Agent Simulation and its Application to Genetic Algorithm for Classroom Optimization
Authors: Maekawa Kotaro ,   Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-0033, Japan, Sawase Kazuhito , Nobuhara Hajime
Published: April 2016

The combinatorial optimization problem of university classroom schedule assignments is formulated using multiagent simulation and genetic algorithms in the evaluation and optimization process. The method we propose consists of global and local multiagent planning. Conventional global planning requires setting subgoals manually, which became a bottleneck in optimization. To solve this problem, a multi-resolution Dijkstra method for selected autonomously, assuming eight classrooms as a real University of Tsukuba building and 250 agents, we confirmed the effectiveness of the proposed multi-resolution Dijkstra’s algorithm as for both global and local route selections, compared to the uniform Dijkstra’s method.
Stabilization of Optimal Dynamic Quantized System with Packet Loss
Authors: Li Mu ,   School of Automation, Beijing Institute of Technology, No.5 Yard, Zhong Guan Cun South Street, Haidian District, Beijing 100081, China, Dou Lihua , Chen Jie , Sun Jian
Published: April 2016

This paper is concerned with the stabilization problem of an optimal dynamic quantized system with packet loss. The optimal dynamic quantizer, which minimizes the quantized output error, is designed for a discretetime system with packet loss occurring in the forward channel. A sufficient condition for the system’s mean square stability is developed based on matrix inequality method. A state feedback controller design method is also proposed, and numerical simulation demonstrates the effectiveness of the proposed method.
Multi-Channel Information Operations on Quantum Images
Authors: Sun Bo ,   Hirota Lab., Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Iliyasu Abdullah M. , Yan Fei , Sanchez Jesus A. Garcia , Dong Fangyan , Al-Asmari Awad Kh. , Hirota Kaoru ,   College of Engineering, Salman Bin Abdulaziz University, Al Kharj 11942, Kingdom of Saudi Arabia
Published: April 2016

Quantum circuits to realize color operations of channel of interest, channel swapping, and alpha blending on images are proposed using five kinds of quantum gates, i.e., NOT, CNOT, Toffoli, Rotation, and Controlled Rotation gates. Complexities of the proposed circuits are for an N-sized image, whereas the color information must be transformed pixel by pixel in the case of operators on classical computers. Simulations on the proposed three quantum color operations using three human facial and one Japanese style house images demonstrate that at most 9, 3, and 5 basic quantum gates are requested, that shows the feasibility of quantum circuits. Based on proposed three operations, all invertible classical color information transformation on imagesmay be designed and many applications can be realized on quantum computer, and the channel of interest based watermarking is being researched which the experiment results show that from the point of PSNR, our proposal is about 10 dB better than the chosen method of quantum image watermarking.
Compensation of Stribeck-Type Nonlinear Friction in Positioning Control Using Equivalent-Input-Disturbance Approach
Authors: Shi Qi ,   Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan, Ouyang Liyu , She Jinhua , Xu Li , Imani Junya , Ohyama Yasuhiro ,   School of Information Science and Engineering, Central South University, Yuelu Mountain, Changsha, Hunan 410083, China,   School of Computer Science, Tokyo University of Technology, 1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan,   Department of Electronics and Information Systems, Akita Prefectural University, 84-4 Ebinokuchi, Tsuchiya, Yuri-Honjo, Akita 015-0055, Japan
Published: April 2016

A method of compensating for Stribeck-type nonlinear friction torque for a two-mass mechatronic system has been devised based on the equivalent-inputdisturbance (EID) approach. The nonlinearity in the system is treated as an input-dependent disturbance, and an EID estimator is designed that estimates it. The incorporation of the estimate into the control input compensates for the nonlinearity. Simulation results demonstrate the validity of the method and show that the compensation accuracy is closely related to the time constant of the low-pass filter.
Detection of Affectively Comparable Term Using Hierarchical Knowledge and Blog Snippets
Authors: Yamanishi Ryosuke ,   Department of Media Technology, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga 525-8577, Japan, Fukumoto Junichi , Masui Fumito ,   Department of Computer Science, Kitami Institute of Technology, 165 Kouen-cho, Kitami, Hokkaido 090-8577, Japan
Published: April 2016

This paper describes a method for detecting affectively comparable terms. Comparable terms are often handled as sample objects instance in order to enrich linguistic expression, and using such terms explains and describes descriptions well. Coordinate terms in hierarchical knowledge are potentially comparable terms. Hierarchical coordinate terms are however sometimes affectively inappropriate as comparable term, because hierarchical knowledge is constructed by using only semantics without affections. We obtained the affections of terms obtained from blog and innovated them into hierarchical knowledge in order to detect affectively comparable terms. We conduct experiments to detect affectively comparable terms and discuss results, from which, we confirmed that affectively comparable terms could be detected by our proposed method. We deem detected affectively comparable terms to be applicable to creating artificial intelligence realizing intuitive interaction.
Flexible Route Planning for Sightseeing with Fuzzy Random and Fatigue-Dependent Satisfactions
Authors: Hasuike Takashi ,   Graduate School of Information Science and Technology, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan, Katagiri Hideki , Tsubaki Hiroe , Tsuda Hiroshi ,   Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan,   Department of Data Science, The Institute of Statistical Mathematics, 10-3 Midorimachi, Tachikawa, Tokyo 190-8562, Japan,   Faculty of Science and Engineering, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 610-0321, Japan
Published: April 2016

This paper proposes a flexible route planning problem for sightseeing with fuzzy random variables for travel times and satisfaction with activities under general sightseeing constraints. Travel time between sightseeing sites and satisfactions with activities depend on weather and climate conditions, and on traveler fatigue, so both fuzzy random variables for travel times and satisfactions and traveler fatigue-dependence are introduced. Tourists are likely to plan favored without drastically changing from the optimal route under usual conditions such as fine weather that suddenly changes for the worse. A route planning problem is proposed to obtain a favorite route similar to the optimal route under usual conditions. Trapezoidal fuzzy numbers and order relations are introduced as a basic case of fuzzy numbers. From order relations, the proposed model is transformed into an extended model of network optimization problems. A numerical example is used to compare the proposed model to standard route planning problems in sightseeing.
Anisotropic Dynamic-Morphological-Diffusion for Segmentation of Noisy Color Images
Authors: Maeda Junji ,   Graduate School of Engineering, Muroran Institute of Technology, 27-1 Mizumoto-cho, Muroran, Hokkaido 050-8585, Japan, Harada Takehiro , Saga Sato , Suzuki Yukinori ,   Seiko Epson Corporation, 3-3-5 Owa, Suwa, Nagano 392-8502, Japan
Published: April 2016

In this paper, we propose a modified anisotropic diffusion algorithm using the dynamicmorphological filtering as a new precise edge-preserving smoothing technique for an accurate segmentation of color images with heavy noise. We incorporate a dynamic selection of multiple structuring elements for each pixel in the morphological filter before the anisotropic diffusion in order to improve the ability of edge-preserving smoothing. As a result, noise and unnecessary details of images are effectively smoothed while preserving small image structures before performing a segmentation algorithm. Several simulated examples are presented that demonstrate the effectiveness of the proposed technique.
An Assessment Tool for Effective Monitoring of Autonomic Nervous System Activity in Healthy People
Authors: Yanagida Takuto ,   Research Institute of Electronics, Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu 432-8011, Japan, Okita Yoshimitsu , Nakamura Harunobu , Sugiura Toshifumi , Mimura Hidenori ,   Graduate School of Science and Technology, Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu 432-8011, Japan,   Graduate School of Human Development and Environment, Kobe University, 3-11 Tsurukabuto, Nada-ku, Kobe 657-8501, Japan
Published: April 2016

This paper proposes an application that analyzes and displays electrocardiograms (ECG; electrical activity of the heart over time) and plethysmograms (PTG; pulse waves produced by the heart pumping blood to the periphery) measured simultaneously. Recently in developed countries, chronic conditions typified by lifestyle-related diseases have become the leading cause of death. Simplified monitoring of the condition can be an effective approach to disease prevention and health promotion. We have focused on autonomic nervous system activity (ANSA) because it responds to stress as well as to changes in dietary patterns, and is correlated with hypertension, the source of some diseases, such as coronary disease. In this paper, we deal with both ECGs and PTGs as part of the biological data that reflects ANSA. The proposed application enables doctors to seamlessly negotiate analyzed waveforms and index charts of ECGs and PTGs in sync with each other. It also helps them comprehend the transition of ANSA. It offers a user interface (UI) that enables doctors to observe the two measures and the relationship between them for a quick assessment of ANSA; the sonification function of the ECG indices is implemented for providing the multi-modality of the UI. An experiment was conducted to confirm the feasibility of the analysis method of the application.
The Analysis of Portals Considering Mobile Clients
Authors: Kocsis Gergely ,   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, Ekler Péter , Albert István
Published: April 2016

Web analytics are used to retrieve anonymous information about users. We focus here on websites that support mobile clients. This information is important from the perspective of business analysis as web analytics help in making appropriate design decisions. Popular web sites may handle several million page views a day, so poor system design – even that related only to collecting statistics on user behavior – may produce performance bottlenecks or even system failures. This paper presents measurements based on a userdata database for a large mobile supported website and a model used when designing such sites.
Applications of Modern HCIs in Adaptive Mobile Learning
Authors: Szegletes Luca ,   Department of Automation and Applied Informatics, Budapest University of Technology and Economics, Magyar Tudosok korutja 2., 1117 Budapest, Hungary, Forstner Bertalan
Published: April 2016

Our paper shows how the evolution of HCI devices progresses as a mobile learning tool. Mobile devices provide interesting applications for cognitive infocommunication. Our principal objective is to assist in developing educational games on these devices. Working with different educational institutes, we designed a flexible biofeedback-controlled self-rewarding framework. Several promising approaches and methods are proposed outside the box of educational games in this paper. The attention of players is regulated by changing rewards. We show both how educational games can be improved and how adaptive entertainment games may be developed in the near future.
Surrounding Robots – A Discrete Localized Solution for the Intruder Problem –
Authors: Blázovics László ,   Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Magyar Tudósok körútja 2., 1117 Budapest, Hungary, Lukovszki Tamás , Forstner Bertalan ,   Faculty of Informatics, Eötvös Lóránd University, Pázmány Péter sétány 1/C 1117 Budapest, Hungary
Published: April 2016

Decentralized algorithms are often used in the cooperative robotics field, especially by large swarm systems. We present a distributed algorithm for a problem in which a group of autonomous mobile robots must surround a given target. These robots are oblivious, i.e., they have no memory of the past. They use only local sensing and need no dedicated communication among themselves. We introduce, then solve the problem in which the group of autonomous mobile robots must surround a given target – we call it the “discrete multiorbit target surrounding problem” (DMTSP). We evaluate our solution using simulation and prove that our solution invariably ensures that robots enclose the target in finite time.
Automatic Keyword Annotation System Using Newspapers
Authors: Takada Tomoki ,   Department of Computer Science, Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki-shi, Kanagawa 214-8571, Japan, Arai Mizuki , Takagi Tomohiro
Published: April 2016

Nowadays, an increasingly large amount of information exists on the web. Therefore, a method is needed that enables us to find necessary information quickly because this is becoming increasingly difficult for users. To solve this problem, information retrieval systems like Google and recommendation systems like that on Amazon are used. In this paper, we focus on information retrieval systems. These retrieval systems require index terms, which affect the precision of retrieval. Two methods generally decide index terms. One is analyzing a text using natural language processing and deciding index terms using varying amounts of statistics. The other is someone choosing document keywords as index terms. However, the latter method requires too much time and effort and becomes more impractical as information grows. Therefore, we propose the Nikkei annotator system, which is based on the model of the human brain and learns patterns of past keyword annotation and automatically outputs keywords that users prefer. The purposes of the proposed method are automating manual keyword annotation and achieving high speed and high accuracy keyword annotation. Experimental results showed that the proposed method is more accurate than TFIDF and Naive Bayes in P@5 and P@10. Moreover, these results also showed that the proposed method could annotate about 19 times faster than Naive Bayes.
How Does High Frequency Risk Hedge Activity Have an Affect on Underlying Market?: Analysis by Artificial Market Model
Authors: Kawakubo Saki ,   School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan, Izumi Kiyoshi , Yoshimura Shinobu ,   CREST, Japan Science and Technology Agency (JST), 5-3 Yonbanchou, Chiyoda-ku, Tokyo 102-8666, Japan
Published: April 2016

The effect of option markets on their underlying markets has been studied intensively since the first option contract was listed. Despite considerable effort, including the development of theoretical and empirical approaches, we do not yet have conclusive evidence on this effect. We investigate the effect of option markets, especially that of dynamic hedging, on their underlying markets by using an artificial market. We propose a two-market model in which an option market and its underlying market interact. In our model, there are three types of agents, underlying local agents trading only on the underlying market, option local agents who trade only on the option market, and global agents who trade both on the underlying and the option market. In this simulation, we investigate the effect of hedgers, a global agent, to the underlying market. Hedgers who have option contracts trade the underlying asset to keep a delta neutral position. This hedge behavior is called dynamic hedging. We simulate two scenarios; one is the hedge with low frequency and the other is the hedge with high frequency that hedger can send hedge order anytime when hedge miss appears. We confirmed that dynamic hedging increases or decreases the volatility of the underlying market under certain conditions.
A Two-Phase Complete Algorithm for Multi-Objective Distributed Constraint Optimization
Authors: Medi Alexandre ,   University of Nantes, Direction des Relations Internationales, BP 13522, F-44 035, Nantes cedex 1, France, Okimoto Tenda , Inoue Katsumi ,   Faculty of Maritime Sciences, Kobe University, 5-1-1 Higashinadaku, Fukaeminamimachi, Kobe 658-0022, Japan,   National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyodaku, Tokyo 101-8430, Japan
Published: April 2016

A Distributed Constraint Optimization Problem (DCOP) is a fundamental problem that can formalize various applications related to multi-agent cooperation. Many application problems in multi-agent systems can be formalized as DCOPs. However, many real world optimization problems involve multiple criteria that should be considered separately and optimized simultaneously. A Multi-Objective Distributed Constraint Optimization Problem (MO-DCOP) is an extension of a mono-objective DCOP. Compared to DCOPs, there exists few works on MO-DCOPs. In this paper, we develop a novel complete algorithm for solving an MO-DCOP. This algorithm utilizes a widely used method called Pareto Local Search (PLS) to generate an approximation of the Pareto front. Then, the obtained information is used to guide the search thresholds in a Branch and Bound algorithm. In the evaluations, we evaluate the runtime of our algorithm and show empirically that using a Pareto front approximation obtained by a PLS algorithm allows to significantly speed-up the search in a Branch and Bound algorithm.
Efficient Deal Identification by Constraint Relaxation for Collaborative Decision Making Using Negotiation
Authors: Hailu Raiye ,   Nagoya Institute of Technology, Nagoya shi, Showa-ku, Gokiso-cho, Aichi 466-8555, Japan, Ito Takayuki
Published: April 2016

Negotiation is one means for making decision collaboratively. We propose efficient protocols for identifying deals in such negotiations. Specifically we focus on situations in which the negotiators must agree upon one option from among many. This work proposes solutions to problems faced when automating negotiations over multiple and interdependent issues. When negotiations are over issues that are interdependent, previous and future decisions concerning other issues affect how one decides the current issue. Therefore generally we must deal with all of the issues at the same time. To identify deals for negotiations over multiple and interdependent issues previous work has proposed a bidding based protocol that works well only when there is a high probability that agents in the negotiation have local maxima at similar positions in the contract space. This happens only when the contract space is small and the number of agents in the negotiation is low. Otherwise the protocol fails to identify deals. We propose a multi round bidding approach in which agents submit supersets of their bids from earlier rounds. A superset of a bid is created by relaxing the constraints that it satisfies. We will use the same concept of negotiation using relaxed constraints to extend a Hill Climbing (HC) protocol. HC has a linear execution time cost. Ordinarily it can not be used for complex negotiations. But we modify it so that it is used optimally and efficiently for such negotiations.
Influence of Payoff in Meta-Rewards Game
Authors: Toriumi Fujio ,   Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan, Yamamoto Hitoshi , Okada Isamu ,   Faculty of Business Administration, Rissho University, 3-2-16 Osaki, Shinagawa-ku, Tokyo 141-8602, Japan,   Faculty of Business Administration, Soka University, 1-236 Tangi, Hachioji, Tokyo 192-8577, Japan
Published: April 2016

In this paper, we analyze a meta-rewards game which is part of a generalized metanorms game. We theoretically analyze the game and conduct computer simulations on it. We clarify the payoff structure as to the benefit and the cost of reward and meta-reward actions. Whereas the benefit of a meta-reward, which is a rewarding action for the other rewarding actions, should be greater than its cost, it should not be much greater than the benefit of a rewarding action for other cooperative actions. This insight can be applied to the actions of users of social media, and we propose a set of policies for managers of social media services.
Implementation of an Intelligent System for Identifying Vessels Exhibiting Abnormal Navigation Patterns
Authors: Kim Do-Yeon ,   Mokpo National Maritime University, 91 Haeyangdaehak-Ro, Mokpo City, Jeon-Nam, 530-729, Republic of Korea, Jeong Jung-Sik , Kim Geonung , Kim Hwa-Young , Hong Taeho ,   Korea Ship Safety Technology Authority, 12∼14 Floor, 7-50, Songdo-Dong, Yeonsu-Gu, Incheon City, 406-840, Republic of Korea
Published: April 2016

The recent rise in maritime traffic volume, resulted from an increase in international marine trading volumes and the growing popularity of marine leisure activities, has increased the frequency of marine accidents. Vessels exhibiting abnormal navigation patterns (e.g., weaving in and out of courses or rotating in the same position) may have a serious impact on other vessels staying on normal courses. For this reason, ground VTS centers are keeping track of criminal vessels or damaged vessels in tandem with marine police. However, the number of available studies aimed at assisting the identification of seemingly apparent risk factors resulting from human errors has been next to nothing to date. In this respect, this study intends to implement an intelligent system that can identify vessels exhibiting abnormal navigation patterns based on fuzzy inference, in order to assist controllers and mates alike.
Artificial Neural Networks for Earthquake Anomaly Detection
Authors: Sriram Aditya ,   University of Ontario Institute of Technology (UOIT), 2000 Simcoe Street North, Oshawa, Ontario L1H 7K4, Canada, Rahanamayan Shahryar , Bourennani Farid
Published: April 2016

Earthquakes are natural disasters caused by an unexpected release of seismic energy from extreme levels of stress within the earth’s crust. Over the years, earthquake prediction has been a controversial research subject that has challenged even the smartest ofminds. Because numerous seismic precursors and other factors exist that may indicate the potential of an earthquake occurring, it is extremely difficult to predict the exact time, location, and magnitude of an impending quake. Nevertheless, evaluating a combination of these precursors through advances in Artificial Intelligence (AI) can certainly increase the possibility of predicting an earthquake. The sole purpose for predicting a seismic event at a pre-determined locality is to provide substantial time for the citizens to take precautionary measures. With this in mind, Artificial Neural Networks (ANNs) have been promising techniques for the detection and prediction of locally impending earthquakes based on valid seismic information. To highlight the recent trends in earthquake abnormality detection, including various ideas and applications, in the field of Neural Networks, valid papers related to ANNs are reviewed and presented herein.
Swarming Algorithm for Unmanned Aerial Vehicle (UAV) Quadrotors – Swarm Behavior for Aggregation, Foraging, Formation, and Tracking –
Authors: Bandala Argel A. ,   De La Salle University, Manila, 2401 Taft Avenue, Manila 1004, Philippines, Dadios Elmer P. , Vicerra Ryan Rhay P. , Lim Laurence A. Gan
Published: April 2016

This paper presents the fusion of swarm behavior in multi robotic system specifically the quadrotors unmanned aerial vehicle (QUAV) operations. This study directed on using robot swarms because of its key feature of decentralized processing amongst its member. This characteristic leads to advantages of robot operations because an individual robot failure will not affect the group performance. The algorithm emulating the animal or insect swarm behaviors is presented in this paper and implemented into an artificial robotic agent (QUAV) in computer simulations. The simulation results concluded that for increasing number of QUAV the aggregation accuracy increases with an accuracy of 90.62%. The experiment for foraging revealed that the number of QUAV does not affect the accuracy of the swarm instead the iterations needed are greatly improved with an average of 160.53 iterations from 50 to 500 QUAV. For swarm tracking, the average accuracy is 89.23%. The accuracy of the swarm formation is 84.65%. These results clearly defined that the swarm system is accurate enough to perform the tasks and robust in any QUAV number.
Neuro-Fuzzy Control Techniques for Optimal Water Quality Index in a Small Scale Tiger Prawn Aquaculture Setup
Authors: Gustilo Reggie C. ,   ECE Department, De La Salle University, Manila, 2401 Taft Ave., Manila, Philippines, Dadios Elmer P. , Calilung Edwin , Lim Laurence A. Gan ,   MEM Department, De La Salle University, Manila, 2401 Taft Ave., Manila, Philippines,   ME Department, De La Salle University, Manila, 2401 Taft Ave., Manila, Philippines
Published: April 2016

A small scale real time tiger prawn aquaculture setup was built and tested in the laboratory using ordinary aquariums to test the controllability and control of the four most important parameters in culturing tiger prawns, the temperature, salinity, pH and dissolved oxygen. These parameters were monitored using Vernier sensors via Labview program. The water quality index of the artificial habitat was monitored and computed using fuzzy logic. New values for the safe parameter conditions of the tiger prawns were observed and used in the computation of the water quality index. Lastly, electronic valves and actuators are used to automatically control the four said water parameters and set them to their optimal values. The control needed by each parameter to force them to stay within their optimal values was done using neural network. This control system is used to activate the electronic valves that will dispense correction fluids for each of the four monitored water parameter.
Collision Avoidance in Multiple-Ship Situations by Distributed Local Search
Authors: Kim Dong-Gyun ,   Department of Maritime Sciences, Kobe University, 5-1-1 Fukaeminami-machi, Higashinada-ku, Kobe 658-0022, Japan, Hirayama Katsutoshi , Park Gyei-Kark ,   Department of Maritime Transportation Science, Mokpo Maritime University, 571 Chukkyo-dong, Mokpo City 530-729, Korea
Published: April 2016

As vital transportation carriers in trade, ships have the advantage of stability, economy, and bulk capacity over airplanes, trucks, and trains. Even so, their loss and cost due to collisions and other accidents exceed those of any other mode of transportation. To prevent ship collisions many ways have been suggested, e.g., the 1972 COLREGs which is the regulation for preventing collision between ships. Technologically speaking, many related studies have been conducted. The term “Ship domain” involves that area surrounding a ship that the navigator wants to keep other ships clear of. Ship domain alone is not sufficient, however, for enabling one or more ships to simultaneously determine the collision risk for all of the ships concerned. Fuzzy theory is useful in helping ships avoid collision in that fuzzy theory may define whether collision risk is based on distance to closest point of approach, time to closest point of approach, or relative bearing – algorithms that are difficult to apply to more than one ships at one time. The main purpose of this study is thus to reduce collision risk among multiple ships using a distributed local search algorithm (DLSA). By exchanging information on, for example, next-intended courses within a certain area among ships, ships having the maximum reduction in collision risk change courses simultaneously until all ships approach a destination without collision. In this paper, we introduce distributed local search and explain how it works using examples. We conducted experiments to test distributed local search performance for certain instances of ship collision avoidance. Experiments results showed that in most cases, our proposal applies well in ship collision avoidance amongmultiple ships.
Rule Representation for Nursing-Care Process Evaluation Using Decision Tree Techniques
Authors: Nii Manabu ,   Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji, Hyogo 671-2201, Japan, Takahama Kazunobu , Miyake Shota , Uchinuno Atsuko , Sakashita Reiko ,   WPI Immunology Frontier Research Center, Osaka University, Suita, Osaka, Japan,   College of Nursing Art and Science, University of Hyogo, 13-71 Kitaoji-cho, Akashi, Hyogo 673-8588, Japan
Published: April 2016

Improving the quality of nursing care is crucial to maintaining the quality of life. Our objective is to develop a computer-aided evaluation system that enables nursing experts to improve the quality of nursing care. In our previous works, some classification systems based on fuzzy logic, neural networks, and SVMs were developed. Although a classification system with high performance for all nursing-care datasets is desirable, we focus on how to visualize the classification results in this paper. It is important to visualize the results for our nursing-care text classification system because the computer-aided system has to explain the reasons for obtaining such results to human experts. In this paper, a tree-type expression is considered for visualizing the classification results. To visualize classification results with the tree-type expression, we consider a decision tree technique. Word existence, dependency relations, and phrase-based feature vector definitions have been proposed in our previous works. In the present study, these three types of feature vector definitions are compared with one another from the viewpoint of understandability.
Hierarchical Bayesian Model for Diffuse Optical Tomography of the Human Brain: Human Experimental Study
Authors: Yamashita Okito ,   Neural Information Analysis Laboratories, ATR, Soraku-gun, Kyoto 619-0288, Japan, Shimokawa Takeaki , Kosaka Takashi , Amita Takashi , Inoue Yoshihiro , Sato Masa-aki ,   Brain Functional Imaging Technologies Group, CiNet, 1-4 Yamadaoka, Suita City, Osaka 565-0871, Japan,   Medical Systems Division Research and Development Department, Shimadzu Corporation, Nakagyo-ku, Kyoto 604-8511, Japan
Published: April 2016

Diffuse optical tomography (DOT) is an emerging technology for improving the spatial resolution of conventional multi-channel near infrared spectroscopy (NIRS). The hemodynamics changes in two distinct anatomical layers, the scalp and the cortex, are known as the main contributor of NIRS measurement. Although any DOT algorithm has the ability to reconstruct scalp and cortical hemodynamics changes in their respective layers, no DOT algorithm has used a model characterizing the distinct nature of scalp and cortical hemodynamics changes to achieve accurate separation. Previously, we have proposed a hierarchical Bayesian model for DOT in which distinct prior distributions for the scalp and the cortical hemodynamics changes are assumed and then verified the reconstruction performance with a phantom experiment and a computer simulation of a real human head model (Shimokawa et al. 2013, Biomedical Optical Express). Here, we investigate the reconstruction accuracy of the proposed algorithm using human experimental data for the first time. We measured the brain activities of a single subject during a finger extension task with NIRS and fMRI. Our DOT reconstruction was compared with the fMRI localization results. Consequently, a remarkable consistency between fMRI and our DOT reconstruction was observed both in the spatial and temporal patterns. By extending the advantages of NIRS such as low running cost and portability with our DOT method, it might be possible to advance brain research in a real environment, which cannot be done with fMRI.
Sequential Cluster Extraction Using Power-Regularized Possibilistic c-Means
Authors: Kanzawa Yuchi ,   Shibaura Institute of Technology, 3-7-5 Toyosu, Koto, Tokyo 135-8548, Japan
Published: April 2016

The present study proposes an algorithm for sequential cluster extraction using power-regularized possibilistic c-means (pPCM). First, pPCM is derived in a similar manner to two types of entropy-regularized possibilistic c-means (ePCM) derivations, where a power function is utilized instead of the negative entropy in ePCM. The cluster fusion with pPCM is identical to the mean-shift with a generalized Epanichnikov kernel, whereas the proposed method employs sequential cluster extraction with pPCM. Numerical examples show that the cluster number produced by the proposed algorithm did not match with the true class number in real datasets, but the extracted clustering results were partially successful in terms of capturing dense regions of objects.
Inference with Fuzzy Rule Interpolation at an Infinite Number of Activating Points
Authors: Uehara Kiyohiko ,   Ibaraki University, 4-12-1 Nakanarusawa-cho, Hitachi 316-8511, Japan, Hirota Kaoru ,   Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan
Published: April 2016

An inference method for sparse fuzzy rules is proposed which interpolates fuzzy rules at an infinite number of activating points and deduces consequences based on α-GEMII (α-level-set and generalized-mean-based inference). The activating points, proposed in this paper, are determined so as to activate interpolated fuzzy rules by each given fact. The proposed method is named α-GEMINAS (α-GEMII-based inference with fuzzy rule interpolation at an infinite number of activating points). α-GEMINAS solves the problem in infinite-level interpolation where fuzzy rules are interpolated at the least upper and greatest lower bounds of an infinite number of α-cuts of each given fact. The infinite-level interpolation can nonlinearly transform the shapes of given membership functions to those of deduced ones in accordance even with sparse fuzzy rules under some conditions. These conditions are, however, strict from a practical viewpoint. α-GEMINAS can deduce consequences without these conditions and provide nonlinear mapping comparable with infinite-level interpolation. Simulation results demonstrate these properties of α-GEMINAS. Thereby, it is found that α-GEMINAS is practical and applicable to a wide variety of fields.
Deep Level Emotion Understanding Using Customized Knowledge for Human-Robot Communication
Authors: Sanchez Jesus Adrian Garcia ,   Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Ohnishi Kazuhiro , Shibata Atsushi , Dong Fangyan , Hirota Kaoru ,   Education Academy of Computational Life Sciences (ACLS), Tokyo Institute of Technology, J3-141, 4259 Nagatsuta-cho, Midori-ku, Yokohama 226-8501, Japan
Published: April 2016

In this study, a method for acquiring deep level emotion understanding is proposed to facilitate better human-robot communication, where customized learning knowledge of an observed agent (human or robot) is used with the observed input information from a Kinect sensor device. It aims to obtain agentdependent emotion understanding by utilizing special customized knowledge of the agent rather than ordinary surface level emotion understanding that uses visual/acoustic/distance information without any customized knowledge. In the experiment employing special demonstration scenarios where a company employee’s emotion is understood by a secretary eye robot equipped with a Kinect sensor device, it is confirmed that the proposed method provides deep level emotion understanding that is different from ordinary surface level emotion understanding. The proposal is being planned to be applied to a part of the emotion understanding module in the demonstration experiments of an ongoing robotics research project titled “Multi-Agent Fuzzy Atmosfield.”
Joint Spectrum Sensing and Data Transmission Optimization for Energy Efficiency in Cognitive Radio Sensor Networks: A Dynamic Cooperative Method
Authors: Li Yi ,   School of Information Science and Engineering, Central South University, Peng Jun , Jiang Fu , Liu Kaiyang , Zhang Xiaoyong
Published: April 2016

To address the inherent energy constraint in cognitive radio sensor networks, a novel joint optimization method of spectrum sensing and data transmission for energy efficiency is investigated in this paper. To begin with, a cooperative spectrum sensing scheme based on dynamic censoring is employed to shorten sensing time and save unnecessary spectrum sensing energy. Then to jointly optimize the energy efficiency, the distortion constrained probabilistic transmission scheme is utilized. Afterwards the sensing threshold solving issue can be formulated as a nonlinear minmax optimization problem with the detection probability and false alarm probability constraints. Solving by the Matlab software with the free OPTI toolbox, simulation results demonstrate that significant energy can be saved via the the proposed joint optimization method in various mobile cloud scenarios.