bluuebunny/crossref_metadata_2025 huggingface dataset:
3D Measurement of a Moving Object Using a Moving Camera Attached with a 6-Axis Sensor
Authors: Akamatsu Toshihiro ,   Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Dong Fangyan , Hirota Kaoru
Published: April 2016

Measurement using a moving camera and a 6-axis sensor under the camera is proposed to determine the distance from the camera to the surface of a moving object and the object’s position movement in two continuous frame images. This makes it possible to measure the 3D position of a moving object at half of the computational cost while keeping the same accuracy as using a stereo camera. 3D measurement experiments with several original images show that the computational time using the proposal is about twice as fast as that of a stereo camera. The proposed method is planning to be used to vehicles or mobile robots avoid obstacles, and its use as a depth meter is also investigated.
Solar-Powered Field Server and Aerator Development for Lake Palakpakin
Authors: Solpico Dominic B. ,   Ateneo Innovation Center, Ateneo de Manila University, Loyola Heights, Quezon City 1108, Philippines, Libatique Nathaniel J. C. , Tangonan Gregory L. , Cabacungan Paul M. , Girardot Guillaume , Macaraig Ramon M. , Perez Teresita R. , Teran Andrea ,   Electronics Computer and Communications Engineering Department, Ateneo de Manila University,   Institut Catholique d’Arts et Métiers, 6 rue Auber, Lille 59000, France,   Alsons Aquaculture Corporation, 2286 Chino Roces Ave., Makati City, 1200, Philippines,   Environmental Sciences Department, Ateneo de Manila University
Published: April 2016

We have designed, developed and deployed a robust system of sensors in a small and shallow – 1 km diameter and about 7 m deep – inland lake used for aquaculture. The sensor system currently measures and sends out telemetry data on dissolved oxygen, conductivity and temperature in the lake at two depths – 0.5 and 2.5 meters – every 30 minutes. The measurements are sent out via SMS to a central server 80 km away and displayed in near-real time on a website which can be accessed by local fishermen, researchers and other stakeholders. The system also features an aerator, which operates automatically during the evening and early morning 12 hours at a time, and can also be turned on outside this period via missed-call (dropped call) from a cellular phone. This system can aid in decision-making of local fishermen, making it a potentially powerful approach to lake management, and in conjunction with other measures and long term planning, for averting or mitigating fishkill events.
Selection of Logistic Web Services Based on Fuzzy Evaluation on Principal Component of Quality of Service
Authors: Li Dongmin ,   School of Control Science and Engineering, Shandong University, No.17923, JingShi Street, Ji’nan, Shandong 250061, China, Zhang Huanshui ,   Department of Mechanical and Electronic Engineering, Shandong University of Science and Technology, No.223, DaiZong Street, Tai’an, Shandong 271019, China
Published: April 2016

The current results on logistic Web services selection are not optimal due to some key quality indexes of logistic Web services excluded, in order to resolve the above problem, an evaluation system on quality of service is established by use of principal component analysis based on quality of logistic service, quality of Web service, and satisfaction of customers. The values of quality of service with subjective uncertainty in the evaluation system are given with trapezoidal fuzzy number according to the definition of logistic business and evaluation from domain experts and customers, besides, the weight on each quality of service is given by pairwise comparison, and an algorithm based on analytic hierarchy process for logistic Web service selection is established. The optimal service is got by adopting the algorithm in the logistic scenario on automotive transportation, which proves that the way on service selection in this paper is feasible and effective.
Estimation of Seaweed Twist Based on Diffusion Kernels in Physical Simulation
Authors: Ogawa Jun ,   Graduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido 060-0814, Japan, Yamamoto Masahito , Furukawa Masashi ,   Department of System and Informatics, Hokkaido Information University, 59-2 Nishi Nopporo, Ebetsu, Hokkaido 069-8585, Japan
Published: April 2016

In the optimization of seaweed cultivation now being extensively researched, a problem arises in avoiding twisting seaweed. Twisting is a complex phenomenon and difficult to formulate. Producing the optimal water flow, requires calculating the risk of twisting occurring. In this paper, we propose a method to calculate and estimate the twist state based on the results of physical simulation. We devise a seaweed model using multiple rigid bodies that mutually and physically interfere. One result of physical interference, is that the model has two internal state variables – contact time and the number of contact points between individual pieces of seaweed. We introduce an evaluation function to quantify twisting using these state variables in each time step, and propose a way to calculate twist risk based on the von Neumann and Laplacian diffusion kernels, in a dynamic network.
A Study on Computational Time Reduction of Road Obstacle Detection by Parallel Image Processor
Authors: Okamoto Yutaro ,   Department of Electrical Engineering, Graduate School of Engineering, Tokyo University of Science,, Premachandra Chinthaka , Kato Kiyotaka
Published: April 2016

Automatic road obstacle detection is one of the significant problem in Intelligent Transport Systems (ITS). Many studies have been conducted for this interesting problem by using on-vehicle cameras. However, those methods still needs a dozens ofmillisecondsfor image processing. To develop the quick obstacle avoidance devices for vehicles, further computational time reduction is expected. Furthermore, regarding the applications, compact hardware is also expected for implementation. Thus, we study on computational time reduction of the road obstacle detection by using a small-type parallel image processor. Here, computational time is reduced by developing an obstacle detection algorithm which is appropriated to parallel processing concept of that hardware. According to the experimental evaluation of the new proposal, we could limit computational time for eleven milliseconds with a good obstacle detection performance.
Quantitative Common Sense Estimation System and its Application for Membership Function Generation
Authors: Hayakawa Yuta ,   Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan, Hagiwara Masafumi
Published: April 2016

Systems capable of autonomous thinking are sometimes required to cope with unanticipated situations. An important issue in this context is knowledge – especially common sense – acquisition. In this paper, we propose novel quantitative common sense estimation methods and apply them to an automatic membership function generation system. Our proposed system estimates threshold values corresponding tolargeandsmallfor various kinds of objectattribute sets to form membership functions, where it attempts to relate each object to its corresponding impression. Two methods are proposed in this paper. The first, Method-1, obtains data from the top 1,000 snippets through a web search and estimates the global and local tendencies by clustering them. The second, Method-2, uses the number of hits from a web search together with parts of the results obtained through Method-1. In addition, we devise several techniques to eliminate unnecessary information in the retrieved web pages. We also carried out experiments that verified the effectiveness of our proposed methods and the method combining those two.
Implementation of High-Precision Magnetostrictive-Type Liquid Level Measurement System UsingWavelet Transform
Authors: Choi Woo-Jin ,   HANLA IMS Co., Ltd., 115 Hwajeonsandan 1(il)-ro, Gangseo-gu, Busan, Korea, Lee John-Tark ,   Department of Electrical Engineering, Dong-A University, 37 Nakdong-Daero 550beon-gil, Saha-gu, Busan, Korea
Published: April 2016

Precise measurement of levels of liquids stored in tanks is essential for monitoring and predicting disasters by detecting leakages or arbitrary discharge of toxic materials. Therefore, tanks are typically equipped with a series of liquid level sensors. A magnetostrictive-type level sensor is composed of a waveguide, a current pulse interrogator, and a sensing coil for detecting reflective torsional signals caused by Wiedemann effect, which is themain principle of operation of magnetostrictive-type liquid level sensors. In order to implement a high-precision magnetostrictivetype liquid level measurement system, we used time–frequency analysis techniques such as wavelet transform (WT) to precisely detect the reflected signals. By using time–frequency analysis techniques such as short-time Fourier transform (STFT) and WT, a robust and precise liquid level measurement system can be implemented even in noisy environments.
Visualizing Fuzzy Relationship in Bibliographic Big Data Using Hybrid Approach Combining Fuzzyc-Means and Newman-Girvan Algorithm
Authors: Zolkepli Maslina ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan, Dong Fangyan , Hirota Kaoru
Published: April 2016

Bibliographic big data visualization method is proposed by incorporating a combination of fuzzyc-means clustering and the Newman-Girvan clustering algorithm, where clustered results are displayed in a network view by grouping objects with similar cluster memberships. As current bibliographic visualizations focus on the crisp relationship among data, fuzzy analysis and visualization may offer insights to bibliographic big data, enabling faster decision making by improving displayed information precision. The proposed method is applied to the DBLP citation network dataset. Results show that merging two clustering algorithms and visualization using fuzzy techniques enables the user to converge a few target papers within an average of 5 minutes from 1.5 million papers stored in the DBLP. Users targeted for the proposed method include researchers, educators, and students who hope to use real-world social and biological networks. The proposal is planned to be opened to the public through the Internet.
Discrete Sliding-Mode Control for a Class of T-S Fuzzy Models with Modeling Error
Authors: Han Hugang ,   Prefectural University of Hiroshima, 1-1-71 Ujina-Higashi, Minami-ku, Hiroshima 734-8558, Japan, Lam Hak-Keung ,   King’s College London, Strand, London, WC2R 2LS, UK
Published: April 2016

This paper proposes a discrete sliding-mode controller for a class of nonlinear systems described by a T-S fuzzy model subject to modeling error, which may influence the system performance and the overall system stability. While most of existing literature treats the modeling error under the so-called parallel distributed compensation framework by using some norm-bounded matrices, the proposed control scheme in this paper integrates a feedback component, which mainly consists of fuzzy approximators to deal with the modeling error and an auxiliary component of the variable structure control with a sector to guarantee the global stability of the closed-loop system when the system state travels outside the sector. With the consideration of system stability, adaptive laws adjusting the parameters in the system are developed based on the Lyapunov synthesis approach. Finally, simulation results will confirm the effectiveness of the approach proposed in this paper.
Crisp and Fuzzy Granular Hierarchical Structures Generated from a Free Monoid
Authors: Murai Tetsuya ,   Graduate School of Information Science and Technologies, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo, Hokkaido 060-0814, Japan, Miyamoto Sadaaki , Inuiguchi Masahiro , Kudo Yasuo , Akama Seiki ,   Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan,   Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan,   College of Information and Systems, Graduate School of Engineering, Muroran Institute of Technology,   1-20-1 Higashi-Yurigaoka, Asoh-ku, Kawasaki, Kanagawa 215-0012, Japan
Published: April 2016

The granular hierarchical structure that we propose has the limitation that the set of truth values is not described explicitly. By regarding “sets of putting” as a special class of direct sets, we introduce crisp and fuzzy granular hierarchical structures. We found that there are two kinds of different preextensions between Yager’s fuzzy multisets and Zadeh’s fuzzy sets.
Variable Neighborhood Model for Agent Control Introducing Accessibility Relations Between Agents with Linear Temporal Logic
Authors: Ubukata Seiki ,   Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan, Murai Tetsuya , Kudo Yasuo , Akama Seiki ,   Graduate School of Information Science and Technologies, Hokkaido University, Kita 14, Nishi 9, Kita-Ku, Sapporo 060-0814, Japan,   College of Information and Systems, Muroran Institute of Technology, 27-1 Mizumoto, Muroran 050-8585, Japan,   C-Republic, 1-20-1, Higashi-Yurigaoka, Asao-ku, Kawasaki-shi 215-0012, Japan
Published: April 2016

In general, there are two types of agents, reflex and deliberative. The former does not have the ability for deep planning that produces higher-level actions to attain goals cooperatively, which is the ability of the latter. Can we cause reflex agents to act as though they could plan their actions? In this paper, we propose a variable neighborhood model for reflex agent control, that allows such agents to create plans in order to attain their goals. The model consists of three layers: (1) topological space, (2) agent space, and (3) linear temporal logic. Agents with their neighborhoods move in a topological space, such as a plane, and in a cellular space. Then, a binary relation between agents is generated each time from the agents’ position and neighborhood. We call the pair composed of a set of agents and binary relations the agent space. In order to cause reflex agents to have the ability to attain goals superficially, we consider the local properties of the binary relation between agents. For example, if two agents have a symmetrical relation at the current time, they can struggle to maintain symmetry or they could abandon symmetry at the next time, depending on the context. Then, low-level behavior, that is, the maintenance or abandonment of the local properties of binary relations, grant reflex agents a method for selecting neighborhoods for the next time. As a result, such a sequence of low-level behavior generates seemingly higher-level actions, as though reflex agents could attain a goal with such actions. This low-level behavior is shown through simulation to generate the achievement of a given goal, such as cooperation and target pursuing.
Estimating Writing Neatness from Online Handwritten Data
Authors: Miura Motoki ,   Kyushu Institute of Technology, 1-1 Sensui, Tobata, Kitakyushu, Fukuoka 804-8550, Japan, Toda Takamichi
Published: April 2016

Handwriting is the most fundamental expressive activity in learning. To utilize the intuitiveness and the nature of handwriting, digital pen technology has emerged to capture and transfer notes. We developed AirTransNote, a student note-sharing system that facilitates collaborative and interactive learning in conventional classrooms. A teacher can use the AirTransNote system to share student notes with the class on a projected screen immediately to enhance the group learning experience. However, to improve the effectiveness of sharing notes, the teacher must be able to select an effective note for sharing. This can be difficult and time consuming during a lecture. Moreover, students should be encouraged to improve the presentation of their handwritten notes. Well-written notes are more accessible for other students and reduce irrelevant and careless mistakes. To facilitate learning improvements based on note sharing, we require a method to estimate the neatness of a note automatically. If a method is established, the teacher can easily select effective notes. Furthermore, this method can help provide feedback to the student to improve their writing. We examined 14 basic features from handwritten notes by considering correlation coefficients and found that the variance of pen speed, angular point average, and pen speed average were the significant features for evaluating the neatness of handwritten notes.
Application of Rough Set-Based Information Analysis to Questionnaire Data
Authors: Yamaguchi Naoto ,   Integrated System Engineering, Graduate School of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu 804-8550, Japan, Wu Mao , Nakata Michinori , Sakai Hiroshi ,   Faculty of Management and Information Science, Josai International University, Gumyo, Togane, Chiba 283-8555, Japan
Published: April 2016

This article reports an application ofRough Nondeterministic Information Analysis (RNIA)to two data sets. One is the Mushroom data set in the UCI machine leaning repository, and the other is a student questionnaire data set. Even though these data sets include many missing values, we obtained some interesting rules by using ourgetRNIAsoftware tool. This software is powered by theNIS-Apriorialgorithm, and we apply rule generation and question-answering functionalities to data sets with nondeterministic values.
Mixed Oligopoly: Analysis of Consistent Equilibria
Authors: Kalashnikov Vyacheslav V. ,   Tecnológico de Monterrey (ITESM), Campus Monterrey, 64849, Mexico, Bulavsky Vladimir A. , Kalashnykova Nataliya I. , Watada Junzo , Hernández-Rodríguez Diego de Jesús ,   Central Economics & Mathematics Institute (CEMI), Russian Academy of Sciences (RAS), Moscow 117418, Russia,   Sumy State University, Sumy 40007, Ukraine,   Department of Physics & Maths (FCFM), Universidad Autónoma de Nuevo León (UANL), San Nicolás de los Garza, 66450, Mexico,   Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsuku, Kitakyushu, Fukuoka 808-0135, Japan
Published: April 2016

In this paper, a model of mixed oligopoly with conjectured variations equilibrium (CVE) is examined, in which one of the agents maximizes a convex combination of its net profit with the domestic social surplus. The agents’ conjectures concern the price variations, which depend on the variations in their production outputs. Using the established existence and uniqueness results for the CVE (theexterior equilibrium) for any fixed set of feasible conjectures, the notion of the interior equilibrium is introduced by developing a conjecture consistency criterion. Then, the existence theoremfor the interior equilibrium (defined as a CVE state withconsistent conjectures) is proven. When the convex combination coefficient tends to 1 (thus transforming the model into the mixed oligopoly in its extreme form), two trends are apparent. First, for private companies, the equilibrium with consistent conjectures becomes more proficient than the Cournot-Nash equilibrium. Second, there exists a (unique) value of the convex combination coefficient such that the private agent’s aggregate profit is the same in both the above-mentioned equilibria, which makes subsidies to producers or consumers unnecessary.
Mutually Dependent Markov Decision Processes
Authors: Fujita Toshiharu ,   Graduate School of Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata, Kitakyushu 804-8550, Japan, Kira Akifumi ,   Graduate School of Economics and Management, Tohoku University, 27-1 Kawauchi, Aoba-ku, Sendai 980-8576, Japan
Published: April 2016

In this paper, we introduce a basic framework for mutually dependent Markov decision processes (MDMDP) showing recursive mutual dependence. Our model is structured upon two types of finite-stage Markov decision processes. At each stage, the reward in one process is given by the optimal value of the alternative process problem, whose initial state is determined by the current state and decision in the original process. We formulate the MDMDP model and derive mutually dependent recursive equations by dynamic programming. Furthermore, MDMDP is illustrated in a numerical example. The model enables easier treatment of some classes of complex multi-stage decision processes.
UserKanseiClothing Image Retrieval System
Authors: Urai Takaki ,   Graduate School, Kansai University, 3-3-35 Yamate-cho, Suita-shi, Osaka 564-8680, Japan, Tokumaru Masataka ,   Kansai University, 3-3-35 Yamate-cho, Suita-shi, Osaka 564-8680, Japan
Published: April 2016

This study proposes a clothing-image retrieval system that considers a user’skansei, i.e., the user’s emotional, physical, and aesthetical preferences. The system gradually learns the user’skanseiby repeated interaction with the user, and can then search for corresponding clothing images. The practicality of the proposed system is confirmed in experiments with real users. It is found that the proposed system can retrieve clothing images that corresponded to the user’skansei.
On Objective-Based Roughc-Regression
Authors: Sugawara Akira ,   Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan, Endo Yasunori , Kinoshita Naohiko ,   Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
Published: April 2016

The pattern recognition method of clustering is a technique automatically classifying data into clusters. Among clustering methods,c-regression based on fuzzy set theory, called Fuzzyc-Regression (FCR), is proposed to get a linear dataset structure. The most recent clustering is based on rough set theory called rough clustering, which is less descriptive than fuzzy clustering. A typical rough clustering algorithm is Roughk-Regression (RKR). However, RKR has problems because it depends on initial values and has no optimum index, so we do not know whether a clustering result will be optimal. This paper proposes Roughc-Regression (RCR) based on the optimization of an objective function and demonstrates its effectiveness through numerical examples.
Comparison of Knowledge Acquisition Methods for Dynamic Scheduling of Wafer Test Processes with Unpredictable Testing Errors
Authors: Matsuo Tsubasa ,   Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan, Inuiguchi Masahiro , Masunaga Kenichiro ,   Renesas Electronics Co., 2-6-2 Otemachi, Chiyoda-ku, Tokyo 100-0004, Japan
Published: April 2016

The scheduling of semiconductor wafer testing processes may be seen as a resource constraint project scheduling problem (RCPSP), but it includes uncertainties caused by wafer error, human factors, etc. Because uncertainties are not simply quantitative, estimating the range of the parameters is not useful. Considering such uncertainties, finding a good situationdependent dispatching rule is more suitable than solving an RCPSP under uncertainties. In this paper we apply machine learning approaches to acquiring situation-dependent dispatching rule. We compare obtained rules and examine their effectiveness and usefulness in problems with unpredictable wafer testing errors.
A Study of Application Cosine Similarity and HOSVD for Questionnaire Data
Authors: YosukeWatanabe  ,   Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan, Yoshikawa Tomohiro , Furuhashi Takeshi
Published: April 2016

Companies often carry out questionnaires, in order to gain a better grasp of consumer trends for the design of marketing strategies. The proper definition of a set of questions presents some difficulties. For example, if respondents take the meaning of two or more questions in one questionnaire to have the same/similar meanings, these questions could be rendered redundant. However, it is difficult to know beforehand how a respondent will interpret the meaning of a question. On the other hand, it is possible to assess the meaning that respondents assumed for questions, and how appropriate the set of questions is, in retrospect. In this paper, we propose a method for visualizing groups of respondents who assumed distinct meanings for questions, by applying Higher Order Singular Value Decomposition (HOSVD) to a tensor consisting of cosine similarity matrices. The proposed method is applied to a Web questionnaire dataset, and it is shown that the new method can identify the respondents’ unique understanding of the meanings of questions, which are not found using the conventional method. We also show that the proposedmethod is the most effective for the visualization of relationships between questions, among the possible ways of applying HOSVD to cosine similarity matrices.
An Approach to Obtain Proper Time for Interruption with Self Initiated Intermission
Authors: Prajapati Shreejana ,   Graduate School of Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka-machi, Nagaoka, Niigata 940-2188, Japan, Yamada Koichi , Unehara Muneyuki
Published: April 2016

Notification delivered at an inappropriate time is usually considered an interruption. To ensure appropriate timing, we considered treating the self-initiated intermission as a period for interrupting users without causing distractions. This intermission is the time to report oneself as being available for an interaction or being ready for an interruption. This gives users the privilege of choosing a suitable time to handle interruptions without hampering any currently active task. Users’ interruptibility is compared at the time of self-initiated intermission with two alternative types of interruption presentation: application switching and regular intervals. An empirical study showed that the self-initiated intermission is the best approach for interrupting users because their interruptibility is high at this time. We also found that users report on their intermission approximately up to four times during an hour long time span.
Speed-Sensorless Vector Control Based on ANN MRAS for Induction Motor Drives
Authors: Xu Kai ,   College of Information Science and Engineering, University of Chongqing Jiaotong, No. 66, Xuefu Rd., Nan’an District, Chonqing 400074, China, Liu Shanchao
Published: April 2016

In the speed-sensorless induction motor drives system, Model Reference Adaptive System (MRAS) is the most common strategy. However, speed estimation using reactive power based MRAS has the problem of instability in the regenerating mode of operation. Such estimation technique is simple and has several notable advantages, but is not suitable for induction motor drives. To overcome these problems, a suitable Artificial Neural Networks (ANN) is presented to replace the adjustable model to make the system stable when working at low speed and zero crossing. Simultaneously, in order to enhance the ANN convergence speed and avoid the trap of local minimum value of algorithm, we used themodified Particle Swarm Optimization (PSO) to optimize the weights and threshold values of neural networks. Then the ANN-based MRAS was used to identify the speed of motor in the indirect vector control system. The results of the simulation show that, by this method, the speed of motor can be identified accurately in different situations, and the result is reliable.
Bloch Sphere-Based Representation for Quantum Emotion Space
Authors: Yan Fei ,   School of Computer Science and Technology, Changchun University of Science and Technology, No. 7089, Weixing Road, Changchun 130022, China, Iliyasu Abdullah M. , Liu Zhen-Tao , Salama Ahmed S. , Dong Fangyan , Hirota Kaoru ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan,   College of Engineering, Salman Bin Abdulaziz University, Al-Kharj 11942, Kingdom of Saudi Arabia,   School of Automation, China University of Geosciences, Wuhan 430074, China
Published: April 2016

A Bloch Sphere-based Emotion Space (BSES), where two angles φ and θ in the Bloch sphere represent the emotion (such as happiness, surprise, anger, sadness, expectation, or relaxation in [0, 2π)) and its intensity (from neutral to maximum in [0, π]), respectively, is proposed. It exploits the psychological interpretation of color to assign a basic color to each emotion subspace such that the BSES can be visualized, and by using quantum gates, changes in emotions can be tracked and recovered. In an experimental validation, two typical human emotions, happiness and sadness, are analyzed and visualized using the BSES according to a preset emotional transmission model. A transition matrix that tracks emotional change can be used to control robots allowing them to adapt and respond to human emotions.
Evaluation of Hand-Eye Coordination Based on Brain Activity
Authors: Miura Satoshi ,   Faculty of Science and Engineering, Waseda University, 59-309, 3-4-1 Okubo, Shinjuku, Tokyo 169-8555, Japan, Kobayashi Yo , Kawamura Kazuya , Seki Masatoshi , Nakashima Yasutaka , Noguchi Takehiko , Yokoo Yuki , Fujie Masakatsu G. ,   Graduate School and Faculty of Engineering, Chiba University, 1-33 Yayoi-cho, Inage Ward, Chiba-shi, Chiba 263-8522, Japan
Published: April 2016

Surgical robots have improved considerably in recent years, but their intuitive operability, and thus their user interoperability, has yet to be quantitatively evaluated. Thus, we propose a method for measuring a user’s brain activity while operating such a robot, to better enable the design of a robot with intuitive operability. The objective of this study was to determine the angle and radius between an endoscope and manipulator that best allows the user to perceive the manipulator as being part of their own body. In the experiments, a subject operated a hand controller to position the tip of a virtual slave manipulator onto a target in a surgical simulator while his/her brain activity was measured using a brain imaging device. The experiment was carried out several times with the virtual slave manipulator configured in a variety of ways. The results show that the amount of brain activity is significantly greater with a particular slave manipulator configuration. We concluded that the hand-eye coordination between the body image and the robot should be closely matched in the design of a robot having intuitive operability.
Multi-Robot Behavior Adaptation to Humans’ Intention in Human-Robot Interaction Using Information-Driven Fuzzy Friend-Q Learning
Authors: Chen Lue-Feng ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Liu Zhen-Tao , Wu Min , Dong Fangyan , Hirota Kaoru ,   School of Automation, China University of Geosciences
Published: April 2016

A multi-robot behavior adaptation mechanism that adapts to human intention is proposed for human-robot interaction (HRI), where information-driven fuzzy friend-Q learning (IDFFQ) is used to generate an optimal behavior-selection policy, and intention is understood mainly based on human emotions. This mechanism aims to endow robots with human-oriented interaction capabilities to understand and adapt their behaviors to human intentions. It also decreases the response time (RT) of robots by embedding the human identification information such as religion for behavior selection, and increases the satisfaction of humans by considering their deep-level information, including intention and emotion, so as to make interactions run smoothly. Experiments is performed in a scenario of drinking at a bar. Results show that the learning steps of the proposal is 51 steps less than that of the fuzzy production rule based friend-Q learning (FPRFQ), and the robots’ RT is about 25% of the time consumed by FPRFQ. Additionally, emotion recognition and intention understanding achieved an accuracy of 80.36% and 85.71%, respectively. Moreover, a subjective evaluation of customers through a questionnaire obtains a reaction of “satisfied.” Based on these preliminary experiments, the proposal is being extended to service robots for behavior adaptation to customers’ intention to drink at a bar.
Distributed Cooperation Based Priority Coverage Control Strategy for Mobile Sensors
Authors: Zheng Zhi ,   School of Automation, Beijing Institute of Technology, Peng Zhihong ,   School of Mathematics and Computer Science, Fujian Normal University
Published: April 2016

Random deployment and inadequate numbers of sensor nodes may cause low coverage, so we propose a new priority coverage control strategy based on the distributed cooperation of mobile sensors. Sensor nodes are distributed randomly around the region of interest (ROI) and searched for independently. When nodes are found, an unbreakable group is formed under repulsion, attraction and speed consistency control, then searching is begun cooperatively. When some node finds a ROI, it guides the other nodes in the group following it to the ROI. While in the ROI, nodes choose the most important position within the sensing range, then move toward it independently while avoiding collision, eventually, reaching the most important area of the ROI. Under the premise of satisfying key area coverage, sensor nodes are adjusted based on the degree of coverage, maximizing coverage. Simulation results show that the proposed method quickly improves the coverage rate and achieves priority coverage of key areas strongly robustly without being adversely affected by sudden damage to nodes. Applications include coverage with limited amounts of nodes in unknown environments.
Basic Study on the Classification of Time Series Data Using a Frequency Integrated Spherical Hidden Markov Self Organizing Map
Authors: Niina Gen ,   Faculty of Science and Engineering, Saga University, Dozono Hiroshi , Muramatsu Kazuhiro
Published: April 2016

The rapid progress in and the expanding complexity of information and technology systems have made data analysis increasingly relevant. Data having a variety of elements are complex, and making very difficult to evaluate a state of a model from observed data generated probabilistically by the model. To evaluate these hidden states, we propose Spherical-Self Organizing Map (S-SOM) with a Hidden Markov Model (HMM) that infers such hidden states.
Fuzzy Association Rule Mining Based Myocardial Ischemia Diagnosis on ECG Signal
Authors: Li Tianyu ,   Department of Computational Intelligence & Systems Science, Tokyo  Institute of Technology, Dong Fangyan , Hirota Kaoru ,   Education Academy of Computational Life Sciences, Tokyo  Institute of Technology
Published: April 2016

A fuzzy association rule mining based method is proposed for myocardial ischemia diagnosis on ECG signals. The proposal provides interpretable and understandable information to doctors as an assistant reference, while rule mining on fuzzy itemsets guarantees that the feature segmentation before rule extraction is feasible and effective. A set of fuzzy association rules is mined through experiments on data from the European ST-T Database, and classification results of myocardial ischemia and normal heartbeats on the test dataset using the extracted rules obtained values of 83.4%, 80.7%, and 81.4% for sensitivity, specificity, and accuracy, respectively. The proposed method aims to become a helpful tool to accelerate the diagnosis of myocardial ischemia on ECG signal, and to be expanded to other heart disease diagnosis areas such as hypertensive heart disease and arrhythmia.
Design and Implementation of Intelligent Event-Driven Human-Computer Interface on Vehicles
Authors: Zhang Jia ,   School of Automation, Beijing Institute of Technology, Xu Sheng-Li , Deng Fang ,   Key Laboratory of Intelligent Control and Decision of Complex Systems
Published: April 2016

An event-driven on-vehicle intelligent human-computer interface has been proposed to solve the problem of complex on-vehicle human-computer interaction. After need analysis of human-computer interaction under the vehicle platform, the framework of intelligent human-computer interface is established, various modules and workflows in the system are designed, and the reasoning feature based on fuzzy cognitive map (FCM) is implemented. The on-vehicle intelligent human-computer interface could help users to complete the interactive operation which is unrelated to the driving operations. Furthermore, the system could analyze the whole information and predict the information required by the user. At last, it could display the information on the interface. So, the on-vehicle intelligent human-computer interface could not only meet the user’s demand for secondary interactive tasks, but also could ensure the driving performance and safety.
Modeling of High Temperature Gas Flow 3D Distribution in BF Throat Based on the Computational Fluid Dynamics
Authors: An Jian Qi ,   School of Automation, China University of Geosciences, Peng Kai , Cao Wei Hua , Wu Min ,   School of Information Science and Engineering, Central South University
Published: April 2016

This paper aims at building a Computational Fluid Dynamics (CFD) model which can describe the gas flow three dimensions (3D) distribution in blast furnace (BF) throat. Firstly, the boundary conditions are obtained by rebuilding central gas flow shape in BF based on computer graphics. Secondly, the CFD model is built based on turbulent model by analyzing the features of gas flow. Finally, a method which can get the numerical solutions of the model is proposed by using CFD software ANSYS/FLUENT. The proposed model can reflect the changes of the gas flow distribution, and can help to guide the operation of furnace burdening and to ensure the BF stable and smooth production.
Fuzzy Set Representation of Kansei Texture and its Visualization for Online Shopping
Authors: Sakaniwa Hidenori ,   Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Dong Fangyan , Hirota Kaoru ,   Yokohama Research Laboratory, Hitachi Ltd.,,   Education Academy of Computational Life Sciences, Tokyo Institute of  Technology
Published: April 2016

A fuzzy set representation method of Kansei Texture is proposed to express individual difference of Kansei Texture feelings for the purpose of online shopping. The method provides buyers with criteria whether a request to send samples is necessary according to the variance degree of individual differences, and it also offers sellers with information regarding the possibility of returned goods in case of significant individual differences with regard to expensive prices. The correlation coefficient of the degree of individual difference and sample demand is 0.78 (P<0.05, t-test), i.e., a directly proportional relationship is observed between the two degrees. There is a tendency for expensive goods, e.g., those with price greater than $50, to be returned in the case of a large individual difference degree, i.e., the individual difference degree of Kansei Texture with price information provides a useful strategy for estimating the possibility of returned goods. Moreover, the relationship between stress and individual difference is also shown. Further validity verification is planned in order to realize practical applications in the real market.
Cooperative Salvo Attack Using Guidance Law of Multiple Missiles
Authors: Zeng Jie ,   School of Automation, Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, Dou Lihua , Xin Bin
Published: April 2016

In this article, a guidance problem for cooperative salvo attack of multiple missiles against a single stationary target is investigated. The proposed guidance law combines the well-known PNG law and cooperative acceleration command, which is based on the feedback of state error between the current missile and the mean value of participant missiles. The state variable in this paper is used as the approximate calculation of time-to-go. The cooperative acceleration command is designed to adjust the flight path and impact time, which leads the multi-missiles to hit the common target simultaneously. During the engagement, the velocities of missiles are not changed and presetting impact time is not needed. Simulation results show the effectiveness of the proposed guidance law.
Active Learning Based on Manual Skills for Students in Mechatronics Course
Authors: Xiao Liang ,   Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, Zhang Jie , She Jinhua , Chen Shumei ,   Environment Research Institute, Waseda University,   Department of Liberal Arts, Tokyo University of Technology
Published: April 2016

There is a growing trend at universities to switch from conventional teaching methods, which focus on knowledge transfer, to methods based on the concept of active learning. Many such methods have been devised and tested to show the validity of this concept. In this study, a project was designed and implemented that teaches some simple principles of aeronautics by having students construct and fly a remote-controlled (RC) model airplane. The goals are to motivate students to study mechatronics and to foster teamwork and communication. This paper explains the project. Its effectiveness was demonstrated in three trials with three groups of students.
The Determinants of the Textile Index: Linear or Nonlinear
Authors: Xu Bing ,   Research Institute of Econometrics and Statistics, Zhejiang Gongshang University, He Jinghui , Yao Yanyun ,   School of Mathematics, Physics and Information Science, Shaoxing College of Arts and Sciences
Published: April 2016

This paper analyzes the Keqiao Textile Index of China, which reflects China Textile City, the leading wholesale textile market in China. China Textile City is a textile entrepot with the most extensive scale and the largest line of business in China, and it is the largest specialized market for light textile in Asia as well. Thus, it is worthwhile to analyze this index. In this paper, 10 variables that represent the factors that significantly influence the Textile Index are selected from the set of possible variables that are deemed to be valid to the index. 6 variables are identified as nonlinear and 4 as linear by the nonparametric method. Then, varying-coefficient partially linear models are established, dividing the index into five terms: one nonparametric term and four linear terms. Each of the five terms comprises approximately 20% of the index, with the linear terms accounting for nearly 80%. Among the six nonparametric variables, cotton index A plays the most important role. The empirical and simulated results consistently show that the percent of each of the five terms would not vary substantially during the sample period if cotton index A were not more than twice the sample mean. Thus, textile prices can be regulated by properly adjusting the cotton price.
Hybrid Genetic Algorithm Based on Chaotic Migration Strategy for Solving Flow Shop Scheduling Problem with Fuzzy Delivery Time
Authors: Dai Wen-Zhan ,   School of Information and Electronic Engineering, Zhejiang Gongshang University, Xia Kai
Published: April 2016

In this paper, a hybrid genetic algorithm based on a chaotic migration strategy (HGABCM) for solving the flow shop scheduling problem with fuzzy delivery times is proposed. First, the initial population is divided into several sub-populations, and each sub-population is isolated and evolved. Next, these offspring are further optimized by a strategy that combines NEH heuristic algorithm proposed by M. Navaz, J.-E. Enscore, I. Ham in 1983 with a newly designed algorithm that has excellent local search capability, thereby enhancing the strategy’s local search capability. Then, the concept of a chaotic migration sequence is introduced to guide the ergodic process of the migration of individuals effectively so that information is exchanged sufficiently among sub-populations and the process of falling into a local optimal solution is thereby avoided. Finally, several digital simulations are provided to demonstrate the effectiveness of the algorithm proposed in this paper.
WaveletLp-Norm Support Vector Regression with Feature Selection
Authors: Ye Ya-Fen ,   Zhijiang College, Zhejiang University of Technology, Shao Yuan-Hai , Li Chun-Na ,   College of Economics, Zhejiang University
Published: April 2016

This paper proposes waveletLp-norm support vector regression (Lp-WSVR) to solve feature selection and regression problems effectively. Unlike conventional support vector regression (SVR), linearLp-WSVR ensures that useful features are selected based on theoretical analysis. By using the wavelet kernel,Lp-WSVR approaches any curve in quadratic continuous integral space that leads to improving regression performance. Results of experiments show the superiority ofLp-WSVR in both feature selection and regression performances. ApplyingLp-WSVR to Chinese real estate prices shows that the most significant and powerful factor contributing to Chinese housing prices is monetary growth.
A Stock Trading Strategy Based on Time-Varying Quantile Theory
Authors: Liu Tiantian ,   Department of Statistics, Zhejiang Gongshang University, Qiu Ning , Gu Wentao
Published: April 2016

Many of the trading strategies viewed as highly important by to financial market investors, we developed based on fundamental and technical analysis. We propose a stock trading strategy based on time-varying quantile analysis and apply it to the stock market in the People’s Republic of China. Comparing results for both the buy-and-hold strategy and a popular NARX-based neural network trading strategy showed that our strategy performed well.
Nonparametric Optimization of Preference in Technical Efficiency in China
Authors: Zeng Juying ,   School of Mathematics and Statistics, Zhejiang University of Finance & Economics
Published: April 2016

Applying nonparametric path-converged approach, the research innovatively provides the measurement of preference in technical efficiency by the ratio of labor elasticity to capital elasticity and further attempts to realize the optimization of preference in technical efficiency by a strategy of 30% abolishment of initial Drug Addition and a strategy with combination of smoothed governmental fiscal expenditure, which sheds fresh light on promoting hospitals’ efficiency in China from perspective of management engineering. With sample data of provincial public hospitals in Zhejiang Province during period of 200901-201306, the research obtains following conclusions. First, benchmark preference in technical efficiency shows production has shifted from physical capital preference to labor skilled preference in technical efficiency. Second, the changing trend of preference in technical efficiency validates initial Drug Addition and governmental fiscal expenditure pushes and restrains the labor skilled preference in technical efficiency respectively. Third, the strategy of 30% abolishment of Drug Addition will strengthen labor skilled preference in technical efficiency with less promotion intensity of initial Drug Addition. The strategy with combination of governmental fiscal expenditure restrains labor skilled preference in technical efficiency. The facts validate great urgency of raising payments for doctors and nurses so as to promoting efficiency effectively.
Polynomial Controller Design Using Disturbance Observer
Authors: Han Hugang ,   Prefectural University of Hiroshima, Lam Hak-Keung ,   King’s College London
Published: April 2016

Disturbance observer-based control provides a promising approach to handle system disturbance and improve robustness. In this paper, a new fuzzy disturbance observer (FDO) is proposed into the SOS-based approach, where the polynomial fuzzy model is used to develop the system controller. Compared with other works published so far, the FDO mainly features two things: 1) the estimation error between the FDO and disturbance shrinks asymptotically to zero if the disturbance has a constant steady-state value; 2) parameters involved in the FDO is adjusted on the basis of the polynomial fuzzy model which is basically nonlinear. Finally, computer simulations are provided to illustrate the effectiveness of the proposed approach.