研究者詳細 - 武藤　佳恭

論文 - 武藤　佳恭

分割表示 211 件中 41 - 60 件目／全件表示 >>

Pedestrian meta-strategy analysis of collision avoidance with two autonomous agents

Miyamoto Kensuke, Takefuji Yoshiyasu, Watanabe Norifumi

467 - 469 2016年02月

In this paper, we aim to build an agent model that enables cooperative behaviors by estimation human intention. Human changes their action decision process by other's behavior. So, we analyze human behavior with switching action decision process. We have targeted collision avoidance as an example of a simple cooperative behavior. We have set two agents with Meta-Strategy model to a virtual environment SIGVerse. We have analyzed subject's walking trajectories, when two agents have different behavior strategies. It was confirmed that subjects switch their avoidance behaviors by agents' strategies.

Access to Document (DOI)

Effectiveness of ensemble machine learning over the conventional multivariable linear regression models

武藤佳恭

Proc. of Hawaii International Conference on Education, 2016 2016年

共著

A New Mathematical Model of Mutually Complementary for Corporate Alliances: Selection of Optimal Partners Using 8 Characteristic

武藤佳恭

Proc. of global conf. on business and finance, 2016(outstanding research award) 2016年

共著

A mathematical model for optimal corporate alliances:evidence from Japan

武藤佳恭

Int. J. of Management and Marketing Research, Vol.9, No.1, 2016, pp.63-80 2016年

共著

Black box is not safe at all

武藤佳恭

science (eLetter, Oct. 20 2016) http://science.sciencemag.org/content/352/6293/1573/tab-e-letters 2016年

単著

Model-based Behavioral Causality Analysis of Handball with Delayed Transfer Entropy

Itoda Kota, Watanabe Norifumi, Takefuji Yoshiyasu

85 - 91 2015年

In goal-type ball games, such as handball, basketball, hockey or soccer, teammates and opponents share the same field. They switch dynamically their behaviors and relationships based on other players' behaviors or intentions. Interactions between players are highly complicated and hard to comprehend, but recent technological developments have enabled us to acquire positions or velocities of their behaviors. We focus on handball as an example of goal-type ball games and analyze causality between teammates' behaviors from tracking data with Hidden Semi-Markov Model (HSMM) and delayed Transfer Entropy (dTE). Although 'off-the-ball' behaviors are a crucial component of cooperation, most research tends to focus on 'on-the-ball' behaviors, and relations of behaviors are only known as tacit knowledge of coaches or players. In contrast, our approach quantitatively reveals player's relationships of 'off-the-ball' behaviors. The extracted causal models are compared to the corresponding video scenes, and we claim that our approach extracts causal relationships between teammates' behaviors or intentions and clarifies roles of the players in both attacking and defending phase.

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An end-to-end entity linking approach for tweets

Yamada Ikuya, Takeda Hideaki, Takefuji Yoshiyasu

55 - 56 2015年

Modeling of cooperative behavior agent based on collision avoidance decision process

Miyamto Kensuke, Yoshioka Hiroaki, Watanabe Norifumi, Takefuji Yoshiyasu

257 - 260 2014年10月

Recent years, robots are useful at home such as cleaning task or communication tools. So there are a lot of studies about cooperative behavior with robots. In order to realize cooperative tasks with robots, it is necessary that robots estimate human intention from human behavior and act in the context based on the intention. In this research, we construct an agent model that enables coordinated behavior by estimating human intention. We focus on collision avoidance as an example of a simple cooperative behavior. We implemented that a agent has Meta-Strategy model in a virtual environment. We have a collision avoidance experiment between virtual agent and human subject and analyzed subject's behavior. It was confirmed that the agent's behavior can influence the human avoidance behavior from experimental results. By indicating the agent's intention, we consider it is possible to achieve cooperative collision avoidance.

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Evaluating the helpfulness of linked entities to readers

Yamada Ikuyai, Ito Tomotaka, Usami Shinnosuke, Takagi Shinsuke, Takeda Hideaki, Takefuji Yoshiyasu

169 - 178 2014年

When we encounter an interesting entity (e.g., a person's name or a geographic location) while reading text, we typically search and retrieve relevant information about it. Entity linking (EL) is the task of linking entities in a text to the corresponding entries in a knowledge base, such as Wikipedia. Recently, EL has received considerable attention. EL can be used to enhance a user's text reading experience by streamlining the process of retrieving information on entities. Several EL methods have been proposed, though they tend to extract all of the entities in a document including unnecessary ones for users. Excessive linking of entities can be distracting and degrade the user experience. In this paper, we propose a new method for evaluating the helpfulness of linking entities to users. We address this task using supervised machine-learning with a broad set of features. Experimental results show that our method significantly outperforms baseline methods by approximately 5.7%-12% F1. In addition, we propose an application, Linkify, which enables developers to integrate EL easily into their web sites.

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WebSocket proxy system for mobile devices

Nakajima Hirotaka, Isshiki Masao, Takefuji Yoshiyasu

315 - 317 2013年

HTTP is absolute essential part of the Internet. However, in the large delayed network such as mobile data network, the performance of HTTP is influenced by 'TCP acknowledgement delay'. In this paper, HTTP over WebSocket proxy system is proposed to defeat the delay. In proposal, HTTP is used to achieve end-to-end communication. Each HTTP request and response is encapsulated into WebSocket packet at the client and server. In this paper, proposed system is implemented on Android smartphone and evaluated delay difference characteristics.

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Effect of rehabilitation by measuring brain function from fNIRS image

Shimizu Daisuke, Tanaka Toshiyuki, Takizawa Shigeo, Takefuji Yoshiyasu

1816 - 1819 2013年

Due to the influence of this aging society, the importance of rehabilitation is increasing in recent years, and new type of rehabilitation, self-exercise method, has been proposed. In order to verify such rehabilitation effect, we measure and compare several rehabilitation effects with fNIRS. We establish an analysis method of fNIRS rehabilitation data, and compare those rehabilitations, and consider what kind of rehabilitation is effective way. In this study, the effectiveness of self-exercise method is suggested.

The study of correlation between fNIRS and fMRI for the time lapse analysis of rehabilitation

Orikawa Jo, Tanaka Toshiyuki, Takizawa Shigeo, Takefuji Yoshiyasu

1507 - 1509 2011年

The rehabilitation technique of the motivative exercise based on Takizawa-Program is suggested to undergo rehabilitation of the increasing number of the hemiplegic patient recently. It is thought that this rehabilitation can reduce the burden of physical therapist and enable that the patients walk on themselves. But it's not become popular because the method of quantitative evaluation of rehabilitation effect is not built. Our research purpose is to examine how to change of brain functional active area by continued Takizawa-Program by hemiplegic patient. Then, we correlated during fNIRS and fMRI by projecting longitudinal plane of fMRI into two dimensional planes. We would like to examine the change of active area around brain functional lesions by projection algorithm.

SystemVerilog assertion for microarchitecture education considering situated nature of learning

Takahashi Ryuichi, Takefuji Yoshiyasu

112 - 113 2011年

SystemVerilog assertion (SVA) is a way to express properties that are expected to be true in a design described in Verilog HDL IEEE1364 standard. We have already reported that legitimate peripheral participation (LPP) works very well for the fine grain microprocessor design education on FPGA where the heart of the system is chosen as the way-in which is the first step for the observation in LPP. We have demonstrated its effectiveness on superscalar design education, while the prior pipeline design education failed. The failure was caused by the top down design methodology guided in the education for the pipelining which appeared to be too difficult. Appropriate scheme to observe the heart of the pipelining is needed. We have found that SVA plays a key role where two senior students succeeded to design pipelined RISC having 3 stages and pipelined CISC having 4 stages in 2 months. White box test by using SVA enables the two senior students to observe the heart of the pipelining very effectively.

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Micro secure socket layer for micro server

Hoa Nguyen Thanh, Naoe Kensuke, Takefuji Yoshiyasu

286 - 290 2010年

In this paper, we propose Micro Secure Socket Layer (MSSL) for 8-bit flash micro controller that is about 1.3 Kbytes in code size. We have analyzed and compared various cryptographic protocols in TCP/IP stack for 5$ Micro Server to propose a simple secure layer based on simple handshake processing and encryption. Additionally, we analyzed MSSL performance, compared with the current security protocols and proved that MSSL can secure the connection between Micro Server and Internet. Security implementation for Micro Server, which has very limited size of memory with a small processer, is very difficult and challenging task. Conventional researches have focused mainly on creating small sensor system and Micro Server that has multi-function with low cost and small memory size, but without much security considerations. Crackers can easily access to the sensor nodes or Micro Server. Therefore, minimum security is needed in the ubiquitous sensor networks. The proposed MSSL is very small in code size so it can be implemented and is suitable for small sensors and Micro Server systems.

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A new log-spectral amplitude estimator using the weighted Euclidean distortion measure for speech enhancement

Nguyen Anh Duc, Naoe Kensuke, Takefuji Yoshiyasu

675 - 679 2010年

This paper considers a perceptually motivated estimator for single-channel speech enhancement based on statistics and Bayesian estimation in the frequency domain. In detail, we propose a new speech log-spectral amplitude estimator where the cost function is the weighted Euclidean distortion measure of the speech log-spectral amplitude. That cost function is motivated by auditory masking effects of the human hearing system. The statistical assumptions used to develop the proposed estimator are the complex Gaussian distribution and independence of speech, noise discrete Fourier transform coefficients. We evaluate this estimator with speech signals contaminated by various noise sources at different input signal-to-noise ratios and find that it achieves better performance than the well-known minimum mean square error log-spectral amplitude estimator in terms of both noise reduction and speech quality.

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Damageless image hashing using neural network

Naoe Kensuke, Takefuji Yoshiyasu

442 - 447 2010年

In this paper, we present a new key generation model for image hashing using neural network, which does not embed any data into the content but is able to extract meaningful data from target image. This model trains artificial neural network to assign predefined code and uses this trained artificial neural network weight and the coordinates of the selected feature sub blocks of target image as keys to extract the predefined code. In this model, the observed output signal from the trained neural network is used as image hash value which distinguishes the target image from other images. The proposed method contributes to secure image hashing for content identification without damaging or losing any detailed data of visual images. The proposed method realizes an application for image authentication, image similarity comparison, verification of image integrity and copyright protection of multimedia contents.

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Simplified IPsec protocol stack for micro server

Hoa Nguyen Thanh, Naoe Kensuke, Takefuji Yoshiyasu

International Journal of Network Security 11 （ 1 ） 46 - 54 2010年

ISSN 1816-353X

In this paper, we propose a simple IPSec protocol stack for Micro Server. We proposed an implementation of IPSec protocol stack which is constructed by Encapsulating Security Payload (ESP) protocol with Advanced Encryption Security (AES) encryption scheme, whereas authentication using MD5 algorithm is optional. Researchers have focused on creating a small system composed of sensors and a Micro Server where it has a small sized memory, multi-function, low cost, but without security consideration. The security problem in the Micro Server is a challenging task because of the very limited flash memory. Here, we have implemented the AES function as 2.704 Kbytes and the ESP protocol with this encryption function as 3.822Kbytes of code. Therefore, the proposed method has less than 4Kbytes in code size. Even including the authentication using MD5, the file size is less than 7Kbytes although this is still optional. In our proposed method, we have focused on implementing the encapsulation of the payload and ignored the key exchange procedure to simplify the secure communication compared to conventional IPSec protocol stack.

Micro Secure Socket Layer (MSSL) for micro server

Hoa Nguyen Thanh, Naoe Kensuke, Takefuji Yoshiyasu

74 - 75 2009年

In this paper, we propose Micro Secure Socket Layer (MSSL) for 8-bit flash micro controller that is about 1.3 Kbytes in code size. We have analyzed and compared various cryptographic protocols in TCP/IP stack for Micro Server to propose a simple secure layer based on simple handshake processing and encryption. Security implementation for Micro Server, which has very limited size of memory with a small processor, is very difficult and challenging task. However, security on the applications of ubiquitous sensors has become very important issues recently. Crackers can easily access to the sensor nodes or Micro Servers without security. Because the proposed MSSL is very small in code size, it can be implemented and is suitable for small sensors and Micro Server systems.

Access to Document (DOI)

Damageless digital watermarking by machine learning

Naoe Kensuke, Sasaki Hideyasu, Takefuji Yoshiyasu

545 - 550 2009年

Soft computing in the area of information security is a promising field for the creation of intelligent solutions. This paper discusses a method for digital watermarking using artificial neural networks to realize secure copyright protection of visual information without any damage. The discussed watermark extraction keys and feature extraction keys identify the secure and unique hidden patterns for proper digital watermarks. In the experiments, we have shown that the proposed method is robust to high pass filtering and JPEG compression of visual information, only for those watermark extraction keys which were able to identify the proper hidden bit patterns from original visual information using corresponding feature extraction keys. The proposed method is to contribute to secure visual digital watermarking without damaging or losing any detailed data of visual information.

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Key generation for static visual watermarking by machine learning

Naoe Kensuke, Sasaki Hideyasu, Takefuji Yoshiyasu

3089 - 3094 2009年

Digital watermarking became a key technology for protecting copyrights. In this paper, we propose a method of key generation scheme for static visual digital watermarking by using machine learning technology, neural network as its exemplary approach for machine learning method. The proposed method is to provide intelligent mobile collaboration with secure data transactions using machine learning approaches, herein neural network approach as an exemplary technology. First, the proposed method of key generation is to extract certain type of bit patterns as training data set for machine learning of digital watermark Second, the proposed method of watermark extraction is processed by presenting visual features by the training approach of machine learning technology. Third, the training approach is to converge the extraction key as the classifier, which is generated by the machine learning process is used as watermark extraction key. The proposed method is to contribute to secure visual information hiding without losing any detailed data of visual objects or any additional resources of hiding visual objects as molds to embed hidden visual objects.

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武藤 佳恭

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武藤　佳恭

論文 - 武藤　佳恭