研究者詳細 - 武藤　佳恭

論文 - 武藤　佳恭

分割表示 >> ／全件表示 211 件中 1 - 211 件目

We should learn the past lessons

武藤佳恭

Science (eLetter, 30 October 2017) http://science.sciencemag.org/content/358/6362/459/tab-e-letters （Science） 2017年10月

研究論文（学術雑誌）, 単著, 査読有り

What should publishers do actions to researchers before they taking ResearchGate to court?

武藤佳恭

Science (eLetter, 26 October 2017) http://science.sciencemag.org/content/358/6360/161/tab-e-letters （Science） 2017年10月

研究論文（学術雑誌）, 単著, 査読有り

Brexit and EU science problem is like a "Whack-A-Mole" global-players game

武藤佳恭

Science(eLetter, 23 October 2017) http://science.sciencemag.org/content/358/6361/279/tab-e-letters 2017年10月

研究論文（学術雑誌）, 査読有り

Communication codes have been oscillating

武藤佳恭

Science (eLetter, 12 October 2017) http://science.sciencemag.org/content/357/6353/763.2/tab-e-letters 2017年10月

研究論文（学術雑誌）, 査読有り

Finland has several solutions for diversity initiatives problems

武藤佳恭

Science (eLetter, 12 October 2017) http://science.sciencemag.org/content/357/6356/1101/tab-e-letters 2017年10月

研究論文（学術雑誌）, 査読有り

Tuna has efficient hydrodynamic multiple small fins for stability

武藤佳恭

Science (eLetter, Oct 7 2017) http://science.sciencemag.org/content/357/6348/251/tab-e-letters 2017年10月

単著

Balanced heat flux (flow) is needed in thermoelectric power generation

武藤佳恭

Science (eLetter, Oct 6 2017) http://science.sciencemag.org/content/357/6358/eaak9997/tab-e-letters 2017年10月

単著

Flat heat pipes can enhance electrocaloric cooling by improving heat dissipation to the air

武藤佳恭

Science (eLetter, September 26 2017) http://science.sciencemag.org/content/357/6356/1130/tab-e-letters 2017年09月

共著

Machine learning should be used for improving weather forecast

武藤佳恭

Science (eLetter, September 18 2017) http://science.sciencemag.org/content/357/6356/1073/tab-e-letters 2017年09月

単著

Japanese postdocs are getting older

武藤佳恭

Science (eLetter, September 8 2017) http://science.sciencemag.org/content/357/6355/951/tab-e-letters 2017年09月

単著

Adding random bias plays a key role for suppressing the effect of bias itself

武藤佳恭

Science (eLetter, September 7 2017) http://science.sciencemag.org/content/357/6354/849/tab-e-letters 2017年09月

単著

Openness is a key for successfully driving profit organizations

武藤佳恭

Science (eLetter, August 28 2017) http://science.sciencemag.org/content/357/6353/759/tab-e-letters 2017年08月

Durability is a key for energy harvesting

武藤佳恭

Science (eLetter, August 25 2017) http://science.sciencemag.org/content/357/6353/773/tab-e-letters 2017年08月

単著

A conflict of interest plays a key role in shaping Wikipedia

武藤佳恭

Science (eLetter, August 22 2017) http://science.sciencemag.org/content/357/6351/557.2/tab-e-letters 2017年08月

単著

The role of government is changing

武藤佳恭

Science (eLetter, August 22 2017) http://science.sciencemag.org/content/357/6350/431/tab-e-letters 2017年08月

単著

There is no perfect review system

武藤佳恭

Science (eLetter, August 7 2017) http://science.sciencemag.org/content/357/6349/343/tab-e-letters 2017年08月

単著

Automated reasoning, self-organization, and optimization should be added in AI Glossary

武藤佳恭

Science (eLetter, August 4 2017) http://science.sciencemag.org/content/357/6346/19/tab-e-letters 2017年08月

単著

Open source software is indeed based on modularity and abstraction

武藤佳恭

science (eLetter, July 24 2017) http://science.sciencemag.org/content/357/6347/128/tab-e-letters 2017年07月

単著

Reproducibility is a key for real peer-reviewed evaluations

武藤佳恭

science (eLetter, July 21 2017) http://science.sciencemag.org/content/357/6348/256/tab-e-letters 2017年07月

単著

GPU and open source software play a key role for advancing deep learning

武藤佳恭

science (eLetter, July 20 2017) http://science.sciencemag.org/content/357/6346/16/tab-e-letters 2017年07月

単著

Embedded security is needed in BMI devices

武藤佳恭

science (eLetter, July 20 2017) http://science.sciencemag.org/content/356/6345/1338/tab-e-letters 2017年07月

単著

Why shouldn't we combine satellite data with mobile data?

武藤佳恭

science (eLetter, July 14 2017) http://science.sciencemag.org/content/357/6347/118/tab-e-letters 2017年07月

単著

Deja vu for U.S. and Japan nuclear waste

武藤佳恭

science (eLetter, July 6 2017) http://science.sciencemag.org/content/356/6345/1313/tab-e-letters 2017年07月

単著

Weighted relative citation ratio means the research success?

武藤佳恭

science (eLetter, June 29 2017) http://science.sciencemag.org/content/356/6342/997/tab-e-letters 2017年06月

単著

J1, H-2B, L1, B1, E2, TN1, and E3 are all nonimmigrant visas for temporary working in the US

武藤佳恭

science (eLetter, June 6 2017) http://science.sciencemag.org/content/356/6339/695.1/tab-e-letters 2017年06月

単著

Infrasound monitoring is needed for investigating noise pollution

武藤佳恭

science (eLetter, May 5 2017) http://science.sciencemag.org/content/356/6337/531/tab-e-letters 2017年05月

単著

The large government funds should be shared with many researchers

武藤佳恭

science (eLetter, April 20 2017) http://science.sciencemag.org/content/356/6334/123/tab-e-letters 2017年04月

単著

Amateurism is the mother of invention

武藤佳恭

science (eLetter, April 15 2017) http://science.sciencemag.org/content/356/6334/144/tab-e-letters 2017年04月

単著

Statistical syllogism and deductive syllogism in software packages

武藤佳恭

science (eLetter, April 12 2017) http://science.sciencemag.org/content/355/6324/468/tab-e-letters 2017年04月

単著

Problems of photovoltaics solar energy

武藤佳恭

science (eLetter, April 14 2017) http://science.sciencemag.org/content/356/6334/141/tab-e-letters 2017年04月

単著

Ensemble methods significantly improve prediction

武藤佳恭

science (eLetter, April 12 2017) http://science.sciencemag.org/content/355/6324/515/tab-e-letters 2017年04月

単著

Inductive and deductive reasoning must be merged for enhancing prediction and breaking its limits

武藤佳恭

science (eLetter, April 8 2017) http://science.sciencemag.org/content/355/6324/468/tab-e-letters 2017年04月

単著

Ensemble methods can improve election prediction

武藤佳恭

science (eLetter, April 7 2017) http://science.sciencemag.org/content/355/6324/515/tab-e-letters 2017年04月

単著

Cooling power can be improved by overlaying metamaterials

武藤佳恭

science (eLetter, March 31 2017) http://science.sciencemag.org/content/355/6329/1062/tab-e-letters 2017年03月

単著

Confined unfrozen water plays a key role for water pipe repairs

武藤佳恭

science advances (eLetter, March 14 2017) http://advances.sciencemag.org/content/2/8/e1600763/tab-e-letters 2017年03月

単著

Magma energy power plant

武藤佳恭

science (eLetter, March 11 2017) http://science.sciencemag.org/content/355/6329/1001/tab-e-letters 2017年03月

単著

How will open source hardware influence our business and education in the future?

武藤佳恭

Proc. of Hawaii International Conference on Education, 2017 2017年

共著, 査読有り

Learning Distributed Representations of Texts and Entities from Knowledge Base

武藤佳恭

Trans. of ACL, 2017 TACL 2017年

共著, 査読有り

Linkify: Enhancing Text Reading Experience by Detecting and Linking Helpful Entities to Users

武藤佳恭

IEEE Intelligent Systems 2017年

共著, 査読有り

Analyzing human decision making process with intention estimation using cooperative pattern task

Itoda Kota, Watanabe Norifumi, Takefuji Yoshiyasu

249 - 258 2017年

Realizing flexible cooperative group behavior of human and social robots or agents needs a mutual understanding of each intention or behaviors of participants. To understand cooperative intelligence in group behavior, we must clarify the decision-making process with intention estimation in multiple persons. Multi-people decision-making process have top-down intention sharing and bottom-up decision making based on the intention inference and amendment based on the each participants’ behavior. This study suggests the cooperative pattern task focusing on the selection process of others whom to be noticed and balancing process of each intention to achieve the shared purpose. In the 2D grid world of an abstract cooperative environment with restricted modal-ity of subjects, they communicate with each other in a nonverbal way and infer their intention based on their behavior to achieve the purpose. We analyzed the human subjects’ behavior and clarified their policy of behavior and concepts which assumed to be shared by each subject for preventing misunderstanding of each intention. Two main results were obtained through the experiment. First, optimal behavior based on the purpose in minimal steps prevent the misunderstanding of each intention. Second, the narrowing down the number of subjects who change their policy assumed to reduce the burden of intention inference.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

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.

Access to Document (DOI)

Damageless information hiding technique using neural network

Naoe Kensuke, Takefuji Yoshiyasu

253 - 256 2008年

In this paper, we propose a new information hiding technique without embedding any information into the target content by using neural network trained on frequency domain. Proposed method can detect a hidden bit codes from the content by processing the selected feature subblocks into the trained neural network. Hidden codes are retrieved from the neural network only with the proper extraction key provided. The extraction key, in proposed method, are the coordinates of the selected feature subblocks and the network weights generated by supervised learning of neural network. The supervised learning uses the coefficients of the selected feature subblocks as set of input values and the hidden bit patterns are used as teacher signal values of neural network. With our proposed method, we are able to introduce a information hiding scheme with no damage to the target content.

Access to Document (DOI)

Can we survive an Internet blackout?

Takefuji Yoshiyasu

IEEE Technology and Society Magazine 26 （ 3 ） 8 2007年09月

ISSN 0278-0097

Access to Document (DOI)

Can we survive an internet blackout?

武藤佳恭

IEEE TECHNOLOGY AND SOCIETY MAGAZINE 26 （ 3 ） 8 - 8 2007年01月

研究論文（学術雑誌）, ISSN 0278-0097

Access to Document (DOI)

Resonance restriction technique for the resolution-based retrieval of palindrome in escherichia coli genome sequence

Ando Ruo, Takefuji Yashiyasu

205 - 208 2007年

In this paper we propose a novel biological reasoning technique to find genetic palindrome using the resolution- based ATP (automated theorem proving) computing strategy. To retrieve the palindromic sequence, we apply automated deduction software with some resolution strategies to increase program performance. While the conventional reasoning or logic programming oriented method is basically top-down process, our method is bottom-up, resolution-based and also enhanced by direction and restriction reasoning strategies. Proposal method is divided into two steps. First, each element of sequence is represented as one state clause. Second, biological reasoning program resolve these states to retrieve palindrome motif from genetic sequence. Besides, to make this resolution process faster, we apply a reasoning strategy called resonance restriction. This resolution strategy blocks the biological reasoning by avoiding expression that do not mach the patterns set by researchers. This pattern is called “resonator” which is expressed by symbol patterns in automated reasoning. In our model, researcher assigns resonators to the gap between repeated regions which prevent his program from redundant search related non-symmetric parts of genetic sequence. Resonators restrict discovery process by discarding clauses generated around the gap between palindromic motifs, which enhance sharply the performance of reasoning program. In experiment, we translate whole genome sequence of Escherichia coli into clausal representation. Numerical results are presented about the retrieval of palindrome in Escherichia coli to valid the effectiveness of proposal technique. We validate that resonance restriction makes reasoning process faster with experimental output of generated clauses, CPU time.

A novel approach for a file-system integrity monitor tool of Xen virtual machine

Quynh Nguyen Anh, Takefuji Yoshiyasu

194 - 202 2007年

File-system integrity tools (FIT) are commonly deployed host-based intrusion detections (HIDS) tool to detect unauthorized file-system changes. While FIT are widely used, this kind of HIDS has many drawbacks: the intrusion detection is not done in real-time manner, which might render the whole scheme useless if the attacker can somehow take over the system with privileged access in the time between. The administrator also has a lot of problems to keep the base-line database updating. Besides, the database and the FIT itself are vulnerable if the attacker gains local privileged access.This paper presents a novel approach to address the outstanding problems of the current FIT. We propose a design and implementation of a tool named XenFIT for Xen virtual machines. XenFIT can monitor and fires alarms on intrusion in real-time manner, and our approach does not require to create and update the database like in the legacy methods. XenFIT works by dynamically patching memory of the protected machine, so it is not necessary to install any kernel code or user-space application into the protected machines. As a result, XenFIT is almost effortless to deploy and maintain. In addition, thanks to the advantage introduced by Xen, the security polices as well as the detection process are put in a secure machine, so XenFIT is tamper-resistant with attack, even in case the attacker takes over the whole VM he is penetrating in. Finally, if deploying strictly, XenFIT is able to function very stealthily to avoid the suspect of the intruder.

Access to Document (DOI)

Damageless watermark extraction using nonlinear feature extraction scheme trained on frequency domain

Naoe Kensuke, Takefuji Yoshiyasu

117 - 142 2007年

In this chapter, we propose a new information hiding and extracting method without embedding any information into the target content by using a nonlinear feature extraction scheme trained on frequency domain. The proposed method can detect hidden bit patterns from the content by processing the coefficients of the selected feature subblocks to the trained neural network. The coefficients are taken from the frequency domain of the decomposed target content by frequency transform. The bit patterns are retrieved from the network only with the proper extraction keys provided. The extraction keys, in the proposed method, are the coordinates of the selected feature subblocks and the neural network weights generated by the supervised learning of the neural network. The supervised learning uses the coefficients of the selected feature subblocks as the set of input values, and the hidden bit patterns are used as the teacher signal values of the neural network, which is the watermark signal in the proposed method. With our proposed method, we are able to introduce a watermark scheme with no damage to the target content.

Access to Document (DOI)

Symbolic computation for DS-CDMA code acquisition using first order logic

Ando Ruo, Takefuji Yoshiyasu

241 - 250 2007年

Code division multiple access (CDMA) is widely used because of its effectiveness to send multiple signal and confidentiality of career signal. We present a formulation of state-space problem of which solution is directed by redundant reasoning control method for semiheuristic and lightweight DS-CDMA code acquisition. The reasoning of the state-space problem provides us with the way to find a K bit synchronized sequence among K dephased sequences with less calculation cost, compared with serial search and matched filter. In this process, redundancy-restriction method, called weighting strategy, enhances the searching ability of FOL (first order logic) reasoning for the faster and lightweight code acquisition. The combination of weighting strategy and correlator enables us to achieve the peak-detection within K/3 times of calculating inner products and its measurement. Our system is evaluated by the reduced cost of proving state-space problem using weighting strategy and its robustness of using the proposal code acquisition framework. Experiment shows that the proposal method is robust if K/N sequences are grouped with N ranging from 3 to 5.

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Parallel analysis for lightweight network incident detection using nonlinear adaptive systems

Ando Ruo, Takefuji Yoshiyasu

319 - 325 2007年

The rapid increasing of security incidents imposes a great burden on Internet users and system administrators. In this paper we discuss a parallel analysis for lightweight network incident detection using nonlinear adaptive systems. We run AID (anomaly intrusion detection) and MID (misuse intrusion detection) systems in parallel. Two detectors generate binary output misuse = {YES/NO} and anomaly = {YES/NO}. Then, we can determine whether we need to perform network or security operation. We apply clustering algorithm for AID and classification algorithm for MID. The nonlinear adaptive system is trained for running MID and AID in parallel. Proposed parallel system is more lightweight and simple to operate even if the number of incident patterns is increased. Experimental results in the case where false positive is frequently caused show that our method is functional with a recognition rate of attacks less than 10%, while finding the anomaly status. Also, performance evaluation show that proposed system can work with reasonable CPU utilization compared with conventional serial search based system.

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Secure image archiving using novel digital watermarking techniques

Ando Ruo, Takefuji Yoshiyasu

399 - 412 2007年

With the rapid advance in digital network, digital libraries, and particularly WWW (World Wide Web) services, we can retrieve many kinds of images on personal and mobile computer anytime and anywhere. At the same time, secure image archiving is becoming a major research area because the serious concern is raised about copyright protection and authority identification in digital media. A more sophisticated technique is required for future multimedia copyright protection. In this chapter we propose a secure image archiving using novel digital-watermarking techniques. Firstly, a nonlinear adaptive system (neural network) is applied for frequency-based digital watermarking. Secondly, we discuss application-oriented watermarking method for GIS image archiving. This chapter is divided into two parts. First section is about the way to apply nonlinear adaptive system for frequency-based image watermarking. We propose a new asymmetric technique employing nonlinear adaptive system trained on frequency domain. Our system uses two public keys to prevent removal attack and archive more fragile watermarking. In embedding, location information of frequency domain, where adaptive system is trained, is binalized, expressed in hexadecimal number, and encrypted in asymmetric cryptosystem. Encrypted location information is embedded in several parts of digital host contents. In generating key, supervised neural networks learn to assign the array of coefficients to teacher signal corresponding to the message to insert. This is one kind of transform-based method to generate public key from private key. In extracting, we use key matrix created by one-way signal processing of adaptive system. Proposal method is tested in still image, and we have empirically obtained the results that the proposal model is functional in implementing more secure and fragile watermarking compared with previous techniques, such as correlation and transform-based asymmetric watermarking. Several experiments are reported to validate the effectiveness of our watermarking method. Second section is about the application of GIS image archiving using digital watermarking technique. Recently, the utilization of GIS (geographical information system) is becoming rapidly pervasive. Consequently, new methodology of archiving and managing images is a pressing problem for GIS users. It is also expected that as the utilization of GIS becomes widely spread, protecting copyright and confidential images will be more important. In this chapter, we propose a three-layer image data format that makes it possible to synthesize two kinds of related images and analysis information in one image data size. To achieve the confidentiality of one hidden image, we apply the private watermarking scheme, where the algorithm is closed to the public. In the proposal model, encoder netlist embedded in the third layer is generated by FOL prover to achieve more secure and less information to decode it, compared with one operation of another block cipher such as RSA. Proposal system users can process two images without the cost of maintaining key and decoding operation.

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Device driver based computer in broadband age

Takefuji Yoshiyasu, Shoji Koichiro, Nozaki Takashi

251 - 258 2007年

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Towards a tamper-resistant kernel rootkit detector

Quynh Nguyen Anh, Takefuji Yoshiyasu

276 - 283 2007年

A variety of tools and architectures have been developed to detect security violations to Operating System kernels. However, they all have fundamental flaw in the design so that they fail to discover kernel-level attack. Few hardware solutions have been proposed to address the outstanding problem, but unfortunately they are not widely accepted. This paper presents a software-based method to detect intrusion to kernel. The proposed tool named XenKIMONO, which is based on Xen Virtual Machine, is able to detect many kernel rootkits in virtual machines with small penalty to the system's performance. In contrast with the traditional approaches, XenKIMONO is isolated with the kernel being monitored, thus it can still function correctly even if the observed kernel is compromised. Moreover, XenKIMONO is flexible and easy to deploy as it absolutely does not require any modification to the monitored systems.

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O(log₂M) self-organizing map algorithm without learning of neighborhood vectors

Kusumoto Hiroki, Takefuji Yoshiyasu

IEEE Transactions on Neural Networks 17 （ 6 ） 1656 - 1661 2006年11月

ISSN 1045-9227

In this letter, a new self-organizing map (SOM) algorithm with computational cost O(log₂M) is proposed where M² is the size of a feature map. The first SOM algorithm with O(M²) was originally proposed by Kohonen. The proposed algorithm is composed of the subdividing method and the binary search method. The proposed algorithm does not need the neighborhood functions so that it eliminates the computational cost in learning of neighborhood vectors and the labor of adjusting the parameters of neighborhood functions. The effectiveness of the proposed algorithm was examined by an analysis of codon frequencies of Escherichia coli (E. coli) K12 genes. These drastic computational reduction and accessible application that requires no adjusting of the neighborhood function will be able to contribute to many scientific areas.

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Hot list strategy for faster paramodulation based graph coloring

Ando Ruo, Takefuji Yoshiyasu

WSEAS Transactions on Computers 5 （ 7 ） 1596 - 1599 2006年07月

ISSN 1109-2750

In this paper, we discuss the effectiveness of applying the ATP (automated theorem proving) strategy called hot list strategy for N-coloring graph problem The process of graph coloring is formulated by equality substitution of paramodulation. It is showed that hot list strategy is useful to control the reasoning process driven by paramodulation. This ATP strategy are designed to deal with a substantial delay in going to a retained conclusion, which makes it possible to reduce the CPU time occurred by redundant generated clauses. Hot list strategy enables reasoning program to look ahead for faster resolution. In proposal graph coloring method, hot list strategy prevents paramodulation to generate much retained information thus reduce CPU time to reach the conclusion. Experiment shows that paramodulation could used for formulating graph coloring problem and hot list strategy is suitable for controlling paramoudlation based resolution. We measured CPU time and the number of generated clauses in solving coloring problem of Petersen graphs. Five kinds of Petersen graphs are formulated and processed by proposal theorem proving program.

A practical and light-weight data capture tool for Xen virtual machine

Quynh Nguyen Anh, Takefuji Yoshiyasu

WSEAS Transactions on Computers 5 （ 5 ） 1053 - 1060 2006年05月

ISSN 1109-2750

Honeypot is a common solution to investigate attacker's activities, but the data capture tool, one of the key components of high-interaction honeypot architecture, faces a major difficulty: it is very hard to hide its presence. For example Sebek, the de-factor data capture tool, suffers from this problem: the intruder can easily uncover it even without privileged access right. This paper presents a design and implementation of a light-weight "camera" software in Xen virtual machine environment: the camera can be put into the virtual machine honeypot to gather necessary data about intruder's action. The camera tool is named XenKamera, which aims to collect TTY data from consoles of observed honeypot, then replays the collected data in on-line or off-line manner as the administrator wishes. Simply put, XenKamera allows us to watch the intruder as if we were looking over his shoulder while he is typing. In order to prevent the intruder from discovering XenKamera, a special architecture is proposed, so the data recording process becomes stealth, hard to detect and circumvent. To protect the gathered data, the TTY logging is secretly transferred to a separate virtual machine and safely kept there. Experiments demonstrate that XenKamera is effective and reliable. Besides to serve for honeypot purpose, XenKamera is designed to be so light-weight that it is practical and can also be used in the production systems to record the working sessions, and the administrator can rely on the logging data to investigate and trouble-shoot administration.

Faster resolution based metamorphic virus detection using ATP control strategy

Ando Ruo, Anh Quynh Nguyen, Takefuji Yoshiyasu

WSEAS Transactions on Information Science and Applications 3 （ 2 ） 260 - 266 2006年02月

ISSN 1790-0832

In this paper we propose a resolution based detection method for detecting metamorphic computer virus. Our method is the application of formal verification using theorem proving, which deduce parts of viral code from the large number of obfuscated operations and re-assemble those in order to reveal the signature of virus. While previously many kinds of the symbolic emulation based methods have been applied for metamorphic virus, no resolution strategy based method is proposed. It is showed that the complexity of metamorphic virus can be solved if the obfuscated viral code is canonicalized and simplified using resolution based state pruning and generation. To make our detection method more feasible and effective, redundancy-control strategies are applied for the resolution process. In this paper the strategies of demodulation and subsumption are applied for eliminating the redundant path of resolution. Experiment shows that without these strategies, resolving metamorphic code into several simplified operations is almost impossible, at least is not feasible in reasonable computing time. The statistics of reasoning process in detecting obfuscated API call is also presented. We divide obfuscated API call into four modules according to the types of metamorphic techniques and compare the conventional resolution with our method applying redundancy-control strategy.

A novel stealthy data capture tool for honeypot system

Quynh Nguyen Anh, Takefuji Yoshiyasu

WSEAS Transactions on Computers 5 （ 1 ） 209 - 215 2006年01月

ISSN 1109-2750

Data capture tool is one of the core components of a honeypot system. The most vital requirement of this component is: it must function as stealthily as possible, so the intruder is not aware of its presence. Currently Sebek is the most sophisticated tool for this purpose. Unfortunately Sebek is rather easy to detect, even with unprivileged right access. This paper presents a novel approach to improve Sebek on this aspect. We proposes a design and implementation of a tool named Xebek, which is based on Xen technology, to fix the most outstanding problems of Sebek. Our experimental results prove that Xebek is much more covert, while the reliability and efficient are improved significantly.

A novel approach to secured and central logging data

Quynh Nguyen Anh, Takefuji Yoshiyasu

WSEAS Transactions on Computers 5 （ 1 ） 201 - 208 2006年01月

ISSN 1109-2750

Logging data is valuable and important information to reveal the attacker's activities and recover broken system. Unfortunately, once the attacker successfully penetrates a protected system, he never fails to either modify the logging data, or even worse, delete them to cover his traces. To avoid such a disaster, it is best to keep logging data in another machine by forwarding them to a central logging server. However, this approach has a flaw: while transmitting on network, data could be illegally sniffed or the traffic might be secretly redirected to a malicious machine. This paper proposes a novel method named Xenlog to secure logging data for systems run on Xen virtual machine: the solution does not use network stack to send data. Experimental and resulted tool proves that this approach is more secure than the traditional solution, while logging process is far more effective (nearly 24 times faster) and more reliable.

A real-time integrity monitor for xen virtual machine

Quynh Nguyen Anh, Takefuji Yoshiyasu

2006年

File-system integrity tools (FIT) are commonly deployed to assist forensic investigation after security incidents and as host-based intrusion detections (HIDS) tool to detect unauthorized file-system changes. Basically all the current solutions employ the same tactic: the administrator specifies a list of critical files and directories that needs to be monitored, then uses the FIT to create a base-line database that tracks general parameters about these files. The FIT is then re-run periodically, and if it detects the modifies of the file-system against the information stored in the database, the report on the changed file is generated. However, this strategy is far from perfect: the intrusion detection cannot be done in real-time, which might render the whole scheme useless if the attacker can somehow take over the system with privileged access in the time between. The administrator also has a lot of problems to keep the database updating. Besides, he must do everything he can to protect the database and the FIT itself from compromising by the attacker, which is not an easy task especially if the attacker gains local access. This paper presents a novel approach to address the outstanding problems of the current FIT. We propose a design and implementation of a tool named XenRIM for Xen virtual machines. XenRIM can monitor and fires alarms on intrusion in real-time manner, and our approach does not require to create and update the database like in the legacy methods. As a result, XenRIM is almost effortless to deploy and maintain. Thanks to the advantage introduced by Xen, the detection polices are centralized in a secure virtual machine and resistant to tampering. Even better, if deploying strictly this tool is able to function very stealthily to avoid the suspect of the attacker. Our experimental result demonstrates that XenRIM incurs very low performance overhead (less than 4%), which makes the solution attractive and practical for production systems.

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A central and secured logging data solution for Xen virtual machine

Quynh Nguyen Anh, Takefuji Yoshiyasu

218 - 224 2006年

Logging data is a valuable and an important information to reveal the attacker's activities and to recover broken system. Unfortunately, once the attacker successfully penetrates a protected system, he never fails to either modify the logging data, or even worse, delete them to cover his traces. To avoid such a disaster, it is best to keep logging data in another machine by forwarding them to a central logging server. However, this approach has a flaw: while transmitting on network, the data could be illegally sniffed or the traffic might be secretly redirected to a malicious machine. This paper proposes a novel method named Xenlog to secure logging data for systems run on Xen virtual machine: the solution does not use network stack to send data. Experimental and resulted tool proves that this approach is more secure than the traditional solution, while logging process is far more effective (nearly 21 times faster) and more reliable.

Towards an invisible honeypot monitoring system

Quynh Nguyen Anh, Takefuji Yoshiyasu

111 - 122 2006年

Honeypot is a decoy system to trap attackers, and data capture tool is one of the components of the honeypot architecture. Being used to collect the intruder's activities inside the honeypot, this key component must be able to function as stealthily as possible, so the intruder does not know that he is under watch. Unfortunately Sebek, a de-facto tool for this purpose in the modern honeypot technology, is rather easy to detect, even with unprivileged right access. This paper proposes to use Xen Virtual Machine to deploy honeypot, and takes the advantage introduced by Xen to fix some of the outstanding problems of Sebek. We present a design and implementation of a Xen-based system named Xebek as a solution. While Xebek provides similar features as Sebek does, our system is more "invisible" and harder to defeat. The experimental results also demonstrate that Xebek is more flexible, while the reliability and efficiency are significantly improved over its counterpart.

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Self debugging mode for patch-independent nullification of unknown remote process infection

Ando Ruo, Takefuji Yoshiyasu

85 - 95 2005年

The rapid increase of software vulnerabilities shows us the limitation of patch-dependent countermeasures for malicious code. We propose a patch-independent protection technique of remote infection which enables each process to identify itself with "being infected" and nullify itself spontaneously. Our system is operating system independent and therefore does not need software rebuilding. Previously, no method for stopping malicious process without recompiling source code or re-building software has been proposed. In proposal system, target process is running under self debugging mode which is activated by enhancing debug() exception handler and utilizing MSR debug register. In this paper we show the effectiveness of proposal method by protecting the remote process infection without patching security holes. Implemention of device driver call back function and BranchIP recorder provides the real-time prevention of unregistered worm attack through Internet. In experiment, function test of stack buffer overflow of Win32.SQLExp.Worm is presented. Also CPU utilization corresponding to the number of calling function and some database operations is showed.

Object segmentation using maximum neural networks for the gesture recognition system

Yoshiike Noriko, Takefuji Yoshiyasu

Neurocomputing 51 213 - 224 2003年04月

ISSN 0925-2312

In this paper, we present a new clustering method for segmentations of moving target and non-target objects. We assume that the moving target object has the following conditions: (1) object motion data continuity inter-frame, and (2) object motion data continuity intra-frame. In our model, clusters tend to form as filling these two conditions. The experimental results showed the effectiveness of the proposed algorithm and the performance of this model in terms of the quality of the recognition results. Our algorithm is able to clean the input noise by removing non-target objects before the recognition process.

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Two-stage orthogonal network incident detection for the adaptive coordination with SMTP proxy

Ando Ruo, Takefuji Yoshiyasu

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2776 424 - 427 2003年

ISSN 0302-9743

In this paper we present an adaptive detection and coordination system which consists of anomaly and misuse detector combined by lightweight neural networks to synchronize with specific data control of proxy server.The proposed method is able to correct false positive of anomaly detector for the unusual changes in the segment monitored by the subsequent misuse detector. The orthogonal outputs of these two detectors can be applied for the switching condition between the parameter settings and the protective data modification of proxy. In the unseen attacks our model detects, the forwarding delay time set in the proxy server according to the detection intervals enable us to protect the system faster and prevent effectively the malicious code from spreading.

Solving vehicle routing problems by maximum neuron model

Yoshiike Noriko, Takefuji Yoshiyasu

Advanced Engineering Informatics 16 （ 2 ） 99 - 105 2002年04月

ISSN 1474-0346

In this paper, we propose a new clustering method for the first phase of a two-phase method of the vehicle routing problems (VRPs) and the traveling salesman problems (TSPs). In the first phase, the customers are grouped as several delivery areas for vehicle by using maximum neuron model. In the second phase, the TSPs for each areas are solved by using elastic net model proposed by Andrew et al. Conventional maximum neuron model proposed by Takefuji et al. is not suitable for these continuous problems. But by including a self-organization rule to this model, the solution quality is improved. Our simulation results show that maximum neuron model can achieve to obtain better solutions than other methods for some kinds of problems in VRPs and TSPs.

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Development of an imaging hyperspectral camera using the ultraviolet and visible wavelength AOTF

Kurosaki Hirohisa, Shingu Hirokimi, Enkyo Shigeharu, Suzuki Takao, Tanioka Kenkichi, Takefuji Yoshiyasu

594 - 603 2002年

A spectroscopic camera has been developed which has spectral resolution of less than 1.5nm in the ultraviolet (UV) and visible wavelength bands (320-580 nm). Its main components are a specially coated UV objective lens, a UV Acousto-Optic Tunable Filter (AOTF) with a thermo-electric cooling system, and a imaging system based on a high-gain avalanche rushing amorphous photoconductor (HARP) developed by NHK Science and Technical Research Laboratories. Research is currently under way to develop the hyperspectral camera into a sensor package for airborne and ultimately space-based remote sensing applications. This paper presents the basic principle and configuration of the hyperspectral camera, and gives details of tests to measure its performance. The results of spectral resolution tests analyzing very close two spectra from a helium-discharge lamp demonstrate the camera's high spectral resolution performance. Full color and spectral images obtained by a spectrometry experiment are also presented to demonstrate the camera's hyperspectral capabilities.

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neural computing for Iroha-Uta generation

Y Takefuji, Y. Yoshiike, M. Kitabata

IPSJ Tran. on Mathatical Modeling and Its Applications 42 （ SIG(TOM4) ） 2001年05月

研究論文（学術雑誌）, 共著, 査読有り

Mixed Pattern Segmentation by Using Chaotic Neural Network

Y.Takefuji, Y.Fukuhara,

IPSJ Tansactions on Mathmatical Modeling and Its Applications 42 （ SIG(TOM4) ） 2001年05月

研究論文（学術雑誌）, 共著, 査読有り

Boxed Economy Simulation Platform and foundation model

Iba T., Takabe Y., Chubachi Y., Takefuji Y.

34 - 38 2001年

The authors propose a "Boxed Economy Simulation Platform", which is a sharable basis for agent-based economic simulations. By providing the basic design of the social model, which we call "Boxed Economy Foundation Model", it enables collaborative research more efficiently. Sharing and cumulating the model components can be promoted by domain-specific design at the level of social model rather than the level of abstract general purpose model. It will be able to contribute to remove factors that have been making it difficult for social scientists to participate in and conduct agent-based research.

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Third eye approach to innovative designs and applications into the 21st century

Oka S., Takefuji Y., Huang W.

Engineering Applications of Artificial Intelligence 13 （ 5 ） 543 - 548 2000年10月

ISSN 0952-1976

The field of remote sensing and sensor technology has undergone tremendous development in the past decades. Sensors technologies of all kinds such as electro-optics, acoustic, active/passive UV to LWIR, ground-penetrating radar, passive mm wavelength, X-ray tomography, neutron activation imaging, multi-spectral, hyper-spectral, and ultra-spectral imaging, will provide valuable images that normal CCD camera cannot offer. By combining algorithms and images taken by sensors at different part of the electromagnetic spectrum, we will be able to extract valuable images automatically. By using multi-spectral images and processing them with neural network computing, our `Third Eye' team is able to extract human face features from those images. In this paper, we will present an application for detecting human facial parts, images taken by different imaging systems and sensors, and the current status of image processing applications.

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Perspectives of unlicensed information infrastructure using spread spectrum technology

IEEE COMMUNICATIONS MAGAZINE 38 （ 5 ） 58 2000年05月

共著

Boxed Economy Model Fundamental Concepts and Perspectives

Iba Takashi, Hirokane Masaharu, Takabe Yohei, Takenaka Heizo, Takefuji Yoshiyasu

941 - 944 2000年

In this paper, the concept of Boxed Economy model is proposed. Boxed Economy model is an agent-based microeconomic simulation which is intended to make predictions and explanations of the real economic movements in the general economy. We suggest the importance of reusable design with object-oriented framework in the field of agent-based economic simulation. Two frameworks at the different level are described in this paper: "Boxed Simulator Framework" and "Boxed Economy Framework". The source code and model is going to be open to public for sharing and co-improving.

The third eye approach to innovative designs and applications into the 21st century: human recognition system by nonlinear oscillations

Engineering Applications of Artificial Intelligence 13 （ 5 ） 543-548 2000年

研究論文（学術雑誌）, 共著

Human face Detection System by KenzanNET

Int. journal of knowledge-based intelligent engineering system 4 （ 4 ） 237-243 2000年

研究論文（学術雑誌）, 共著, 査読有り

Verifying of the Detected Eye Part by Multidirectional Associative Memory

Int. journal of knowledge-based intelligent engineering system 4 （ 4 ） 219-229 2000年

研究論文（学術雑誌）, 共著

Detection of Human Facial Parts using Infrared and Visible Images

Int. journal of knowledge-based intelligent engineering system 4 （ 4 ） 213-218 2000年

研究論文（学術雑誌）, 共著

A self-Organized Oscillation in Detectiong Time-Varing Human Faces

Int. journal of knowledge-based intelligent engineering system 4 （ 4 ） 243-253 2000年

共著, 査読有り

Neural network parallel algorithm for one-dimensional gate assignment problems

Tsuchiya Kazuhiro, Takefuji Yoshiyasu, Kurotani Ken Ichi

Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi) 129 （ 2 ） 71 - 77 1999年11月

ISSN 0424-7760

A near-optimum parallel algorithm for solving the one-dimensional gate assignment problem is presented in this paper, where the problem is NP-hard and one of the most fundamental layout problems in VLSI design. The proposed system is composed of n×n processing elements based on the artificial two-dimensional maximum neural network for (n+2)-gate assignment problems. Our algorithm has discovered improved solutions in the benchmark problems compared with the best existing algorithms. The proposed approach is applicable to other VLSI layout problems such as the PLA (Programmable Logic Array) folding problem.

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ATM and Wireless Experiments for Remote Lectures

Takefuji Yoshiyasu, Takahashi Naoko, Tsuchida Hisasumi, Fukuhara Yoshimi, Neff Raymond

IEEE Communications Magazine 37 （ 3 ） 98 - 101 1999年03月

ISSN 0163-6804

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TELE-LEARNING: THE "KILLER APP"? - ATM AND WIRELESS EXPERIMENTS FOR REMOTE LECTURES - Two experiments of remote lectures are detailed: A wireless experiment between two buildings in the Philippines and an ATM experiment between Japan and the United States

Takefuji, Y; Takahashi, N; Tsuchida, H; Fukuhara, Y; Neff, R

IEEE communications magazine 37 （ 3 ） 98- 1999年03月

共著

Human Detecting System by Hybrid Self-Organization Classification Scheme and CombNET

Chashikawa, T., Fujii, K., Takefuji, Y.

ARTIFICIAL INTELLIGENCE IN REAL TIME CONTROL 1998 7 131-136 1999年03月

共著

An Image Blocking Neural System for Children on the Internet

Kamakura, Y., Takefuji, Y

ARTIFICIAL INTELLIGENCE IN REAL TIME CONTROL 1998 7 127-130 1999年03月

共著

Recognition of Human Shapes by Deformable Template and Neural Network

Tate, S., Oka, S., Takefuji, Y.

ARTIFICIAL INTELLIGENCE IN REAL TIME CONTROL 1998 7 137-142 1999年03月

共著

PART C - Solid-State Devices, Quantum Electronics, Integrated Circuits, Optoelectronics, Information Processing, Communication Systems, Computer Control, Learning Theory and Pattern Recognition - A Neural Network Parallel Algorithm for One-Dimensional Gate Assignment Problems

Tsuchiya, Kazuhiro; Takefuji, Yoshiyasu; Kurotani, Ken-ichi

Electrical engineering in Japan 129 （ 2 ） 71- 1999年03月

共著

ATM and Wireless Experiments for Remote Lecures

武藤佳恭

IEEE communications magazine 1999年03月

単著

SPECIAL ISSUE ON PULSE COUPLED NEURAL NETWORKS - REGULAR ISSUE BRIEF PAPERS - Microcode Optimization with Neural Networks

Bharitkar, S; Tsuchiya, K; Takefuji, Y

IEEE transactions on neural networks 10 （ 3 ） 698- 1999年03月

共著

情報流通ダイナミズムのマルチエージェント型シミュレーション－人工社会モデルに対するコミュニケーションモジュールの適用－

武藤佳恭他

進化経済学論集，第3集（進化経済学会第3階大阪大会研究報告） 1999年03月

共著

Microcode optimization with neural networks

Bharitkar Sunil, Tsuchiya Kazuhiro, Takefuji Yoshiyasu

IEEE Transactions on Neural Networks 10 （ 3 ） 698 - 703 1999年

ISSN 1045-9227

Microcode optimization is an NP-complete combinatorial optimization problem. This paper proposes a new method based on the Hopfield neural network for optimizing the wordwidth in the control memory of a microprogrammed digital computer. We present two methodologies, viz., the maximum clique approach, and a cost function based method to minimize an objective function. The maximum clique approach albeit being near O(1) in complexity, is limited in its use for small problem sizes, since it only partitions the data based on the compatibility between the microoperations, and does not minimize the cost function. We thereby use this approach to condition the data initially (to form compatibility classes), and then use the proposed second method to optimize on the cost function. The latter method is then able to discover better solutions than other schemes for the benchmark data set.

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Near-optimal parallel algorithm for one-dimensional gate assignment in VLSI layout

Tsuchiya K., Takefuji Y.

Integrated Computer-Aided Engineering 6 （ 3 ） 249 - 257 1999年

ISSN 1069-2509

A novel approach to the one-dimensional gate assignment problem is presented in this paper where the problem is NP-hard and one of the most fundamental layout problems in VLSI design. The proposed system is composed of n×n processing elements called the artificial two-dimensional maximum neurons for (n+2)-gate assignment problems. We have discovered the improved solutions in the benchmark problems over the best existing algorithms. The proposed parallel algorithm is also applicable to other VLSI layout problems.

エージェントベース経済モデルによるシミュレーション分析-バブルの生成と崩壊-

武藤佳恭他

日本シミュレーション＆ゲーミング学会第10回全国大会 1998年11月

共著

情報流通ダイナミズムのエージェントネットワーク型シミュレーション

武藤佳恭他

日本シミュレーション＆ゲーミング学会第10回全国大会 1998年11月

共著

An Image Blocking Neural System for Children on the Internet

Kamakura, Y., Takefuji, Y.

Symposium on Artificil intelligence in real-time control 1998年10月

共著

ニューラルネットを用いた係り受け制約による文生成

武藤佳恭他

第57回情報処理学会全国大会 1998年10月

共著

HUMAN DETECTION SYSTEM BY HYBRID SELF-ORGANIZATION CLASSIFICATION SCHEME AND CombNET

Takefuji, Y. et al

Symposium on Artificial Intelligence in Real-Time Contol 1998 IFAC 1998年10月

共著

RECOGNITION OF HUMAN SHAPES FROM VIDEO IMAGES BY DEFORMABLE TEMPLATES MATCHING AND NEURAL NETWORK

Takefuji, Y. et al

Symposium on Artificial Intelligence in Real-Time Contol 1998 IFAC 1998年10月

共著

マルチエージェント社会における役割分担の生成－蟻のコロニーにおける食料運搬－

武藤佳恭, 他

情報処理学会第57回全国大会 1998年09月

共著

Agent-based Artificial Market Model-The Case Study of De-Facto Standard on VCR Market

Iba, T., Takenaka, H., Takefuji, Y.

International conference, 3rd Multi-agent systems 1998年07月

共著

A Self-Organized Oscillation in Detecting Time-Varing Human Faces

takefuji,Y. et al

EANN '98 1998年06月

共著

Comfirmation of the Detected Eye by Bidirectional Associtive Memory

Takefuji, Y. et al

EANN '98 1998年06月

共著

にゅーっるネットワークを用いた顔パーツの確率的な抽出

武藤佳恭他

第39回日本人間工学会全国大会 1998年05月

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最新のニューラルネット手法による画像知識処理技術の確立と応用の開発

武藤佳恭他

情報処理振興事業教会（創造的ソフトウェア育成事業編） 1998年05月

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ハイパースペクトラム画像解析による人物の肌の特徴抽出

武藤佳恭他

日本人間工学会誌　34（特別）（日本人間工学会第39回大会講演集） 1998年05月

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Grouping Complex Face Parts by Nonlinear Oscillations

Takefuji, Y. et al

European Symposium on ANN 1998年04月

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Adaptation of Neural Agent in Dynamic Environment: Hybrid System of Genetic Algorithm and Neural Network

Takefuji, Y.et al

Second International Conference on Knowledge-based Intelligent Electronic Systems (KES '98) 1998年04月

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Agent-based Artificial Market Model

Takefuji, Y. et al

International Conference of Multi-Agent System '98 (ICMAS '98) 1998年04月

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Open Architecture of Infrastracture for Socialized Mobile Agents

Takeda, K., Takefuji, Y.

International conference ICCIMA1998 1998年02月

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ニューラルコンピューティングを用いた現代いろは歌の作成

武藤佳恭他

第57回情報処理学会全国大会 1998年

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A new self-organization classification algorithm for remote-sensing images

Oka Souichi, Ogawa Tomoaki, Oda Takayoshi, Takefuji Yoshiyasu

IEICE Transactions on Information and Systems E81-D （ 1 ） 132 - 136 1998年

ISSN 0916-8532

This paper presents a new self-organization classification algorithm for remote-sensing images. Kohonen and other scholars have proposed self-organization algorithms. Kohonen's model easily converges to the local minimum by tuning the elaborate parameters. In addition to others, S.C. Amatur and Y. Takefuji have also proposed self-organization algorithm model. In their algorithm, the maximum neuron model (winner-take-all neuron model) is used where the parameter-tuning is not needed. The algorithm is able to shorten the computation time without a burden on the parameter-tuning. However, their model has a tendency to converge to the local minimum easily. To remove these obstacles produced by the two algorithms, we have proposed a new self-organization algorithm where these two algorithms are fused such that the advantages of the two algorithms are combined. The number of required neurons is the number of pixels multiplied by the number of clusters. The algorithm is composed of two stages: in the first stage we use the maximum self-organization algorithm until the state of the system converges to the local-minimum, then, the Kohonen self-organization algorithm is used in the last stage in order to improve the solution quality by escaping from the local minimum of the first stage. We have simulated a LANDSAT-TM image data with 500 pixel × 100 pixel image and 8-bit gray scaled. The results justifies all our claims to the proposed algorithm.

Adaptation of neural agent in dynamic environment

Iba Takashi, Takefuji Yoshiyasu

575 - 584 1998年

The purpose of this study is to propose the adaptive agent as hybrid of Genetic Algorithm and Neural Network, and to clarify the effectiveness of the combination of two mechanisms in the dynamic environment. Evolution and learning can be explained as the mechanism of searching a solution in the enormous possibilities at the population level and individual level respectively. Genetic algorithm and neural network are computational models. Genetic algorithm is suitable for global search, and neural network at the local search. Combination of genetic algorithm and neural network seems natural from the biological viewpoint. There are two ways of combination of genetic algorithm and neural network, that is Darwinian and Lamarckian framework. In Lamarckian framework the acquired traits during the lifetime can be passed on to the offspring directly, and in Darwinian framework, these cannot be passed on. We propose `Neural Agent' whose initial weights of their neural networks are determined by their genome data, as a simple model of hybrid system of genetic algorithm and neural network. We examine which framework is better in the dynamic system. The result of our simulation shows Darwinian framework is better than Lamarckian.

Neural computing for the m-way graph partitioning problem

Saito Takayuki, Takefuji Yoshiyasu

IEICE Transactions on Information and Systems E80-D （ 9 ） 942 - 947 1997年09月

ISSN 0916-8532

The graph partitioning problem is a famous combinatorial problem and has many applications including VLSI circuit design, task allocation in distributed computer systems and so on. In this paper, a novel neural network for the m-way graph partitioning problem is proposed where the maximum neuron model is used. The unidirected graph with weighted nodes and weighted edges is partitioned into several subsets. The objective of partitioning is to minimize the sum of weights on cut edges with keeping the size of each subset balanced. The proposed algorithm was compared with the genetic algorithm. The experimental result shows that the proposed neural network is better or comparable with the other existing methods for solving the m-way graph partitioning problem in terms of the computation time and the solution quality.

A Neural Network Parallel Algorithm for Meeting Schedule Problems

Tsuchiya Kazuhiro, Takefuji Yoshiyasu

Applied Intelligence 7 （ 3 ） 205 - 213 1997年

ISSN 0924-669X

A parallel algorithm for solving meeting schedule problems is presented in this paper where the problem is NP-complete. The proposed system is composed of two maximum neural networks which interact with each other. One is an M x S neural network to assign meetings to available time slots on a timetable where M and S are the number of meetings and the number of time slots, respectively. The other is an M x P neural network to assign persons to the meetings where P is the number of persons. The simulation results show that the state of the system always converges to one of the solutions. Our empirical study shows that the solution quality of the proposed algorithm does not degrade with the problem size.

A neural network approach to facility layout problems

Tsuchiya Kazuhiro, Bharitkar Sunil, Takefuji Yoshiyasu

European Journal of Operational Research 89 （ 3 ） 556 - 563 1996年03月

ISSN 0377-2217

A near-optimum parallel algorithm for solving facility layout problems is presented in this paper where the problem is NP-complete. The facility layout problem is one of the most fundamental quadratic assignment problems in Operations Research. The goal of the problem is to locate N facilities on an N-square (location) array so as to minimize the total cost. The proposed system is composed of N x N neurons based on an artificial two-dimensional maximum neural network for an N-facility layout problem. Our algorithm has given improved solutions for several benchmark problems over the best existing algorithms.

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A neural network approach to PLA folding problems

Tsuchiya Kazuhiro, Takefuji Yoshiyasu

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 15 （ 10 ） 1299 - 1305 1996年

ISSN 0278-0070

A near-optimum parallel algorithm for solving PLA folding problems is presented in this paper where the problem is NP-complete and one of the most fundamental problems in VLSI design. The proposed system is composed of n X n neurons based on an artificial two-dimensional maximum neural network where n is the number of inputs and outputs or the number of product lines of PLA. The two-dimensional maximum neurons generate the permutation of inputs and outputs or product lines. Our algorithm can solve not only a simple folding problem but also multiple, bipartite, and constrained folding problems. We have discovered improved solutions in four benchmark problems over the best existing algorithms using the proposed algorithm.

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Neural network parallel algorithm for meeting schedule problems

Tsuchiya Kazuhiro, Takefuji Yoshiyasu, Kurotani Ken ichi, Wakahara Kunio

173 - 177 1996年

A parallel algorithm for solving meeting schedule problems is presented in this paper where the problem is NP-complete. The proposed system is composed of two maximum neural networks which interact with each other. One is an M×S neural network to assign meetings to available time slots on a timetable where M and S are the number of meetings and the number of time slots, respectively. The other is an M×P neural network to assign persons to the meetings where P is the number of persons. The simulation results show that the state of the system always converges to one of the solutions and that the solution quality of the proposed algorithm does not degrade with the problem size.

A neural network algorithm for the no-three-in-line problem

Tsuchiya Kazuhiro, Takefuji Yoshiyasu

Neurocomputing 8 （ 1 ） 43 - 49 1995年

ISSN 0925-2312

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Balloon net discovering improved solutions in one of unsolved problems in geometry

Fujisawa Kimiya, Takefuji Yoshiyasu

2208 - 2210 1995年

A balloon net model is introduced and demonstrated for discovering improved solutions in one of unsolved problems in geometry which is referred to as a problem of `Spreading points in a square'. How should n points be arranged in a unit square so that the minimum distance between them is the greatest? Note that d(n) is the greatest possible minimum distance between n points in a unit square. Exact results are known for n≤9 and n = 14, 16, 25, and 36. Many investigators including Schaer, Meir, Kirchner, Wengerodt, Goldberg, Schluter, Valette and others have studied this geometrical problem for many years. The best known result is summarized in the book of `Unsolved Problems in Geometry' (H.T. Croft. K.J. Falconer and R.K. Guy/1991). We have found improved solutions for n = 13 and n = 15 by the proposed algorithm.

Scaling properties of neural networks for job-shop scheduling

Foo Simon Y., Takefuji Yoshiyasu, Szu Harold

Neurocomputing 8 （ 1 ） 79 - 91 1995年

ISSN 0925-2312

This paper investigates the scaling properties of neural networks for solving job-shop scheduling problems. Specifically, the Tank-Hopfield linear programming network is modified to solve mixed integer linear programming with the addition of step-function amplifiers. Using a linear energy function, our approach avoids the traditional problems associated with most Hopfield networks using quadratic energy functions. Although our approach requires more hardware (in terms of processing elements and resistive interconnects) than a recent approach by Zhou et al. [2], the neurons in the modified Tank-Hopfield network do not perform extensive calculations unlike those described by Zhou et al.

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Presenting the special issue on optimization and combinatorics

Szu Harold, Takefuji Yoshiyasu, Foo Simon Y.

Neurocomputing 8 （ 1 ） 3 - 4 1995年

ISSN 0925-2312

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Neural computing approach to Japanese electoral system

Saito Takayuki, Takefuji Yoshiyasu

2202 - 2207 1995年

In December 1994, Japanese single-member constituency system for the House of Representatives was established where Japan is divided into three hundred constituencies. A single representative will be elected from each constituency. Zoning three hundred constituencies was accomplished by hand calculators in Japan where zoning the constituencies is a very elaborate task because several constraints must be satisfied. This paper presents a neural computing approach for automatically zoning constituencies. Our method was examined by using 25 Tokyo constituencies. Ideally, the weight of a single vote in a certain population to elect a representative should be equal to that of the other constituencies. Based on the established rule, the ratio of the lightest weight to the heaviest weight must be within two. Our result shows that our ratio is 1.28 while the current (official) ratio is 1.47.

Neural network parallel computing for multi-layer channel routing problems

Suzuki Kyotaro, Amano Hideharu, Takefuji Yoshiyasu

Neurocomputing 8 （ 2 ） 141 - 156 1995年

ISSN 0925-2312

Multi-layer channel routing is one of cumbersome jobs in automatic layout design of VLSI chips and PCBs. As VLSI chips have been used in every field of electrical engineering, it becomes more important to reduce the layout design time. With the advancement of the VLSI technology, four-layer problems can be treated and the algorithms for more than four-layer problems will be demanded in the near future. Proposed algorithm can treat 2 × n-layer problems in parallel. In this paper, the algorithm is introduced and implemented on a multiprocessor system. By minimizing the communication overhead and load unbalance between processors, the performance with 8 processors is improved by between 6 and 6.5 times compared with the sequential version.

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Parallel algorithm for time-slot assignment problems in TDM hierarchical switching systems

Funabiki Nobuo, Takefuji Yoshiyasu

IEEE Transactions on Communications 42 （ 10 ） 2890 - 2898 1994年10月

ISSN 0090-6778

This paper presents a parallel algorithm for time-slot assignment problems in TDM hierarchical switching systems, based on the neural network model. The TDM systems are operated in repetitive frames composed of several time-slots. A time-slot represents a switching configuration where one packet is transmitted through an I/O line. The goal of our algorithm is to find conflict-free time-slot assignments for given switching demands. The algorithm runs on a maximum of n²×m processors for m-time-slot problems in n×n TDM systems. In small problems up to a 24×24 TDM system, the algorithm can find the optimum solution in a nearly constant time, when it is performed on n²×m processors.

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Comment on "The facility layout problem"

Bharitkar Sunil, Tsuchiya Kazuhiro, Takefuji Yoshiyasu

European Journal of Operational Research 75 （ 1 ） 233 - 234 1994年05月

ISSN 0377-2217

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A Parallel Algorithm for Traffic Control Problems in Three-Stage Connecting Networks

Funabiki N., Takefuji Y.

Journal of Parallel and Distributed Computing 20 （ 2 ） 236 - 240 1994年02月

ISSN 0743-7315

A parallel heuristic algorithm for traffic control problems in three-stage connecting networks is presented in this paper. A three-stage connecting network consists of an input crossbar switching stage, an intermediate crossbar switching stage, and an output crossbar switching stage. The goal of our algorithm is to quickly and efficiently find a conflict-free switching assignment for communication demands through the network. The algorithm requires n² × m processing elements for the network composed of n input/output switches and m intermediate switches, where it runs not only on a sequential machine, but also on a parallel machine with maximally n² × m processors. The algorithm was verified by 1100 simulation runs with the network size from 10² × 7 to 50² × 27. The simulation results show that the algorithm can find a solution in nearly constant time with n² × m processors.

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Modified Hopfield-Tank neural networks applied to the 'unitized' maximum flow problem

Munakata Toshinori, Takefuji Yoshiyasu, Johansson Henrik

IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 41 （ 2 ） 174 - 177 1994年02月

ISSN 1057-7122

Two new approaches called 'graph unitization' are proposed to apply neural networks similar to the Hopfield-Tank models to determine optimal solutions for the maximum flow problem. They are: (1) n-vertex and n²-edge neurons on a unitized graph; (2) m-edge neurons on a unitized graph. Graph unitization is to make the flow capacity of every edge equal to 1 by placing additional vertices or edges between existing vertices. In our experiments, solutions converged most of the time, and the converged solutions were always optimal, rather than near optimal.

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Constrained optimization with use of two-dimensional maximum neurons

Yip Percy P C, Takefuji Yoshiyasu

4667 - 4671 1994年

Job-shop scheduling based on modified tank-hopfield linear programming networks

Foo Simon Y., Takefuji Yoshiyasu, Szu Harold

Engineering Applications of Artificial Intelligence 7 （ 3 ） 321 - 327 1994年

ISSN 0952-1976

The Tank-Hopfield linear programming network is modified to solve job-shop scheduling, a classical optimization problem. Using a linear energy function, the approach described in this paper avoids the traditional problems associated with most Hopfield networks using quadratic energy functions. Although this approach requires more hardware (in terms of processing elements and resistive interconnects) than a recent approach by Zhou et al. (IEEE Trans. Neural Networks 2, 175-179, 1991) the neurons in the modified Tank-Hopfield network do not perform extensive calculations, unlike those described by Zhou et al.

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Parallel algorithm for broadcast scheduling problems in packet radio networks

Funabiki Nobuo, Takefuji Yoshiyasu

IEEE Transactions on Communications 41 （ 6 ） 828 - 831 1993年06月

ISSN 0090-6778

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Neural network approach to topological via-minimization problems

Funabiki Nobuo, Takefuji Yoshiyasu

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 12 （ 6 ） 770 - 779 1993年06月

ISSN 0278-0070

Topological via-minimization (TVM) algorithms in two-layer channels based on the artificial neural network model are presented in this paper. TVM problems require not only assigning wires or nets between terminals without an intersection to one of two layers, but also a minimization of the number of vias, which are the single contacts of nets between two layers. The goal of our algorithms is to embed the maximum number of nets without an intersection. Two types of TVM problems are examined: split rectangular TVM (RTVM) problems and split circular TVM (CTVM) problems. Our algorithms require 3 n processing elements for the n-net split RTVM problems, and 5 n processing elements for the n-net split CTVM problems. The algorithms were verified by solving seven problems with 20 to 80 nets. The algorithms can be easily extended for more-than-two-layer problems.

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Comparisons of seven neural network models on traffic control problems in multistage interconnection networks

Funabiki Nobuo, Takefuji Yoshiyasu, Lee Kuo Chun

IEEE Transactions on Computers 42 （ 4 ） 497 - 501 1993年04月

ISSN 0018-9340

This paper presents performance comparisons of seven neural network models on traffic control problems in multistage interconnection networks. The decay term, three neuron models, and two heuristics were evaluated. The goal of the traffic control problems is to find conflict-free switching configurations with the maximum throughput. Our simulation results show that the hysteresis McCulloch-Pitts neuron model without the decay term and with two heuristics has the best performance.

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A parallel multi-layer channel router on the HVH model

Funabaki Nobuo, Takefuji Yoshiyasu

Parallel Computing 19 （ 1 ） 63 - 77 1993年

ISSN 0167-8191

With the advancement of the silicon technology multi-layered VLSI circuits and PCBs (printed circuit boards) have been widely used. Based on the neural network model this paper presents the first parallel algorithm for multi-layer channel routing problems on the HVH model which minimize wiring areas in VLSI circuits and PCBs. The algorithm requires n × m × 2s processing elements for the n-net-m-track-3s-layer problem. The algorithm not only runs on a sequential machine but also on a parallel machine with maximally n × m × 2s processors. The algorithm is verified by solving seven benchmark problems where it finds better solutions than the existing algorithms for 6-12-layer problems in nearly constant time on a parallel machine.

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O(1) approximate parallel algorithm for the n-task-n-person assignment problem

Cho Yong Beom, Kurokawa Takakazu, Takefuji Yoshiyasu, Kim Hwa

1503 - 1505 1993年

A parallel algorithm for the n-task-n-person assignment problem is presented in this paper. The proposed algorithm is based on the artificial neural network model where a large number of simple processing elements are used. Through a large number of simulation runs, it was empirically shown that the state of the system can converge to the solution within a hundred iteration steps regardless of the problem size n. The proposed algorithm using n² processing elements requires computational bounds of a nearly O(1) time.

Near-optimum parallel algorithm for one-dimensional gate assignment problems

Tsuchiya Kazuhiro, Takefuji Yoshiyasu

1499 - 1502 1993年

CMOS analog/digital circuit of the hysteresis McCulloch-Pitts neuron for Ramsey numbers

Cho Yong Beom, Tsuchiya Kazuhiro, Takefuji Yoshiyasu

Analog Integrated Circuits and Signal Processing 2 （ 4 ） 313 - 322 1992年11月

ISSN 0925-1030

A parallel algorithm for finding Ramsey numbers is presented where analog/digital CMOS circuits for the hysteresis McCulloch-Pitts binary neuron are described. The hysteresis McCulloch-Pitts binary neuron model is used in order to suppress the oscillatory behaviors of neural dynamics so that the convergence time is shortened. The proposed algorithm using the hysteresis McCulloch-Pitts binary neuron found five Ramsey numbers. The analog CMOS sigmoid circuit with variable gain controls has been fabricated and tested using the SAC data acquisition board interfaced with a TMS 32010 processor. Hysteresis can be implemented by the positive feedback in the fabricated CMOS analog circuit.

Quantitative measurement of two-component pH-sensitive colorimetric spectra using multilayer neural networks

Lin Chii Wann, LaManna Joseph C., Takefuji Yashiyasu

Biological Cybernetics 67 （ 4 ） 303 - 308 1992年08月

ISSN 0340-1200

The purpose of this research was to develop a noise tolerant and faster processing approach for in vivo and in vitro spectrophotometric applications where distorted spectra are difficult to interpret quantitatively. A PC based multilayer neural network with a sigmoid activation function and a generalized delta learning rule was trained with a two component (protonated and unprotonated form) pH-dependent spectrum generated from microspectrophotometry of the vital dye neutral red (NR). The network makes use of the digitized absorption spectrum between 375 and 675 nm. The number of nodes in the input layer was determined by the required resolution. The number of output nodes determined the step size of the quantization value used to distinguish the input spectra (i.e. defined the number of distinct output steps). Mathematic analysis provided the conditions for which this network is guaranteed to converge. Simulation results showed that features of the input spectrum were successfully identified and stored in the weight matrix of the input and hidden layers. After convergent training with typical spectra, a calibration curve was constructed to interpret the output layer activity and therefore, predict interpolated pH values of unknown spectra. With its built-in redundant presentation, this approach needed no preprocessing procedures (baseline correction or intensive signal averaging) normally used in multicomponent analyses. The identification of unknown spectra with the activities of the output layer is a one step process using the convergent weight matrix. After learning from examples, real time applications can be accomplished without solving multiple linear equations as in the multiple linear regression method. This method can be generalized to pattern oriented sensory information processing and multi-sensor data fusion for quantitative measurement purposes.

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An artificial maximum neural network

Takefuji Yoshiyasu, Lee Kuo Chun, Also Hideo

Biological Cybernetics 67 （ 3 ） 243 - 251 1992年07月

ISSN 0340-1200

A maximum neuron model is proposed in order to force the state of the system to converge to the solution in neural dynamics. The state of the system is always forced in a solution domain. The artificial maximum neural network is used for the module orientation problem and the bipartite subgraph problem. The usefulness of the maximum neural network is empirically demonstrated by simulating randomly generated massive nstances (examples) in both problems. In randomly generated more than one thousand instances our system always converges to the solution within one hundred iteration steps regardless of the problem size. Our simulation results show the effectiveness of our algorithms and support our claim that one class of NP-complete problems may be solvable in a polynomial time.

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Optimization neural networks for the segmentation of magnetic resonance images

Amartur S. C., Piraino D., Takefuji Y.

IEEE Transactions on Medical Imaging 11 （ 2 ） 215 - 220 1992年06月

ISSN 0278-0062

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Functional-link net computing

Pao Yoh Han, Takefuji Yoshiyasu

Computer 25 （ 5 ） 76 - 79 1992年05月

ISSN 0018-9162

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Neural network parallel computing for BIBD problems

Kurokawa Takakazu, Takefuji Yoshiyasu

IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 39 （ 4 ） 243 - 247 1992年04月

ISSN 1057-7130

Neural network parallel computing for balanced incomplete block design (BIBD) problems is presented. A design in which all the blocks contain the same number of varieties, and all the varieties occur in the same number of blocks, is called a block design. A block is said to be incomplete if it does not contain all the varieties. If a design is balanced, it is called a balanced incomplete block design. Two methods for BIBD problems have been proposed. One uses the notion of the finite fields, and the other uses the notion of the difference sets. In general, the conventional algorithms are only able to solve the problems that satisfy an affine plane or a finite projective plane. The proposed algorithm is able to solve BIBD problems regardless of the condition of an affine plane or a finite projective plane. The proposed algorithm was verified by simulation runs. The simulation results demonstrated that the number of iteration steps for the system to converge to the solution increases slightly with the problem size.

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A parallel string search algorithm

Takefuji Yoshiyasu, Tanaka Toshimitsu, Lee Kuo Chun

IEEE Transactions on Systems, Man and Cybernetics 22 （ 2 ） 332 - 336 1992年03月

ISSN 0018-9472

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Neural network parallel algorithm for clique vertex-partition problems

Funabiki Nobuo, Takefuji Yoshiyasu, Lee Kuo Chun, Cho Yong Beom

International Journal of Electronics 72 （ 3 ） 357 - 372 1992年03月

ISSN 0020-7217

A parallel algorithm based on a neural network model for solving clique vertex-partition problems in arbitrary non-directed graphs is presented in this paper. A clique of a graph G = (V, E) with a set of vertices V and a set of edges E is a complete subgraph of G where any pair of vertices is connected with an edge. A clique vertex-partition problem of a graph G is to partition every vertex in V into a set of disjointed cliques of G. The clique vertex-partition problem with the minimum number of cliques in an arbitrary graph is known to be NP-complete. The algorithm requires nm processing elements for the n vertex m partition problem. A total of 10 different problems with 8 vertex to 300 vertex graphs were examined where the algorithm found a solution in nearly constant time. The circuit diagram of the neural network model is also proposed in this paper.

Generalized maximum neural network for the module orientation problem

Lee Kuo Chun, Takefuji Yoshiyasu

International Journal of Electronics 72 （ 3 ） 331 - 355 1992年03月

ISSN 0020-7217

Several neuron models and artificial neural networks have been intensively studied since McCulloch and Pitts proposed the simplified neuron model in 1943. In this paper a generalized maximum neural network for parallel computing is introduced to solve the module orientation problem which belongs to the class of NP-complete problems. The goal of the module orientation problem in VLSI circuits or printed circuit boards is to minimize the total wire length by flipping each module with respect to its vertical and/or horizontal axes of symmetry. The circuit diagram of the generalized maximum neural network is shown and compared with the best known algorithm proposed by Libeskind-Hadas and Liu. The theoretical/empirical convergence analysis is discussed where a massive number of simulation runs were performed using more than one thousand instances. As far as we have observed the behavior of the proposed system, it converges within O(1) time regardless of the problem size and it performs better than the best known algorithm in terms of the solution quality and the computation time.

A parallel improvement algorithm for the bipartite subgraph problem

Lee Kuo Chun, Funabiki Nobuo, Takefuji Yoshiyasu

IEEE Transactions on Neural Networks 3 （ 1 ） 139 - 145 1992年01月

ISSN 1045-9227

The authors propose the first parallel improvement algorithm using the maximum neural network model for the bipartite subgraph problem. The goal of this NP-complete problem is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. A large number of instances have been simulated to verify the proposed algorithm, with the simulation result showing that the algorithm finds a solution within 200 iteration steps and the solution quality is superior to that of the best existing algorithm. The algorithm is extended for the K-partite subgraph problem where no algorithm has been proposed.

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A Parallel Algorithm for Channel Routing Problems

Funabiki Nobuo, Funabiki Nobuo, Takefuji Yoshiyasu

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 11 （ 4 ） 464 - 474 1992年

ISSN 0278-0070

A parallel algorithm for channel routing problems is presented in this paper. The channel routing problem is very important in the automatic layout design of VLSI circuits and printed circuit boards. The problem is to route the given interconnections between two rows of terminals on a multilayer channel where the channel area must be minimized. Although several algorithms have been proposed for two-layer problems, two-Iayer-and-over-the-cell problems, and three-layer problems, the current advancement of VLSI chip technology allows us to use four layers composed of two metal layers and two polysilicon layers for routing in a chip. The goal of the proposed parallel algorithm is to find the near-optimum routing solution for the given interconnections in a short time. The algorithm is applied for the four-layer channel routing problems where it requires n × m × 2 processing elements for the n-netm-track problem. The algorithm has three advantages over the conventional algorithms: 1) it can be easily modified for accommodating more than four-layer problems, 2) it runs not only on a sequential machine but also on a parallel machine with maximally n ×m × 2 processors, and 3) the program size is very small. The algorithm is verified by solving seven benchmark problems where the algorithm finds routing solutions in a nearly constant time with n × m × 2 processors.

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A parallel algorithm for solving unfriendly beehive problems

Rofkar J. D., Takefuji Y.

Neurocomputing 4 （ 3-4 ） 167 - 179 1992年

ISSN 0925-2312

This paper presents a general purpose algorithm for solving the Unfriendly Beehive Game. The proposed algorithm will utilize an artificial neural network to solve the problem. The neural network will use a simple partial differential (motion) equation expressed in terms of its natural constraints. Each constraint within the equation represents a simple connection to an artificial neuron. Each connection strength (or synaptic strength) is weighted by multiplicative constants and summed together. The result is an input that is adjusted in the direction that decreases the error or conflict. Using this information, the system derives a simple binary state output in an attempt to solve the puzzle. Given an overall time slot in which to resolve all conflicts, the system iteratively strives to arrive at the state of the global minimum. The proposed algorithm will be able to solve a variety of real-world problems, including: facility layouts for maximizing productivity and safety, classroom assignment for minimizing pupil conflict, crop and plant placement for maximizing yields, and chemical placement within shipping boxes to reduce the possibility of chemical interactions.

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A parallel algorithm for scheduling problem based on Hopfield model for the automated synthesis of digital systems

Nourani-Dargiri Mehrdad, Papachristou Christos A., Takefuji Yoshiyasu

910 1992年

Summary form only given. A novel scheduling approach has been developed based on the deterministic Hopfield model for high-level synthesis. The model uses a four-dimensional neural network architecture to schedule the operations of a dataflow graph and maps them to specific functional units. Neural network-based scheduling is achieved by formulating the scheduling problem in terms of an energy function and by using the motion equation corresponding to the variation of energy. The algorithm searches the scheduling space in parallel and finds the optimal schedule. The main contribution of the present work is an efficient scheduling algorithm under time and resource constraints. The algorithm is based on moves in the scheduling space, which correspond to moves towards the equilibrium point (lowest energy state) in the dynamic system space. The neurons' motion equation is the heart of this guided movement mechanism and guarantees that the state of the system always converges to the lowest energy state.

A neural network model for traffic controls in multistage interconnection networks

Funabiki Nobuo, Takefuji Yoshiyasu, Lee Kuo Chun

898 1992年

Summary form only given, as follows. A neural network model for traffic controls in multistage interconnection networks is discussed. The goal of the neural network model is to find conflict-free traffic flows to be transmitted among given I/O traffic demands in order to maximize the network throughput. The model requires n² processing elements for the traffic control in an n × n multistage interconnection network. The model runs not only on a sequential machine but also on a parallel machine with maximally n² processors. The model was verified by solving ten 32 × 32 network problems.

A neural network model for finding a near-maximum clique

Funabiki Nubuo, Takefuji Yoshiyasu, Lee Kuo Chun

Journal of Parallel and Distributed Computing 14 （ 3 ） 340 - 344 1992年

ISSN 0743-7315

A parallel algorithm based on the neural network model for finding a near-maximum clique is presented in this paper. A maximum clique of a graph G is a maximum complete subgraph of G where any two vertices are adjacent. The problem of finding a maximum clique is NP-complete. The parallel algorithm requires n processing elements for an n-vertex graph problem. The algorithm is verified by solving 230 different graph problems. The simulation results show that our computation time on a Macintosh IIfx is shorter than that of two better known algorithms on a Cray 2 and an IBM 3090 while the solution quality is similar. The algorithm solves a near-maximum clique problem in nearly constant time on a parallel machine with n processors.

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Neural computing in discovering RNA interactions

Takefuji Yoshiyasu, Ben-Alon Dora, Zaritsky Arieh

BioSystems 27 （ 2 ） 85 - 96 1992年

ISSN 0303-2647

High-order RNA structures are involved in regulating many biological processes; various algorithms have been designed to predict them. Experimental methods to probe such structures and to decipher the results are tedious. Artificial intelligence and the neural network approach can support the process of discovering RNA structures. Secondary structures of RNA molecules are probed by autoradiographing gels, separating end-labeled fragments generated by base-specific RNases. This process is performed in both conditions, denaturing (for sequencing purposes) and native. The resultant autoradiograms are scanned using line-detection techniques to identify the fragments by comparing the lines with those obtained by 'alkaline ladders'. The identified paired bases are treated by either one of two methods to find the foldings which are consistent with the RNases' 'cutting' rules. One exploits the maximum independent set algorithm; the other, the planarization algorithm. They require, respectively, n and n² processing elements, where n is the number of base pairs. The state of the system usually converges to the near-optimum solution within about 500 iteration steps, where each processing element implements the McCulloch-Pitts binary neuron. Our simulator, based on the proposed algorithm, discovered a new structure in a sequence of 38 bases, which is more stable than that formerly proposed.

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Neural network computing for knight's tour problems

Takefuji Yoshiyasu, Lee Kuo Chun

Neurocomputing 4 （ 5 ） 249 - 254 1992年

ISSN 0925-2312

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Neural network based algorithm for the scheduling problem in high-level synthesis

Nourani Mehrdad, Papachristou Christos, Takefuji Yoshiyasu

341 - 346 1992年

This paper presents a new scheduling approach for high-level synthesis based on a deterministic modified Hopfield model. Our model uses a four dimensional neural network architecture to schedule the operations of a data flow graph (DFG) and maps them to specific functional units. Neural Network-based Scheduling (NNS) is achieved by formulating the scheduling problem in terms of an energy function and by using the motion equation corresponding to the variation of energy. The algorithm searches the scheduling space in parallel and finds the optimal schedule. The main contribution of this work is an efficient parallel scheduling algorithm under time and resource constraints appropriate for implementing on a parallel machine. The algorithm is based on moves in the scheduling space, which correspond to moves towards the equilibrium point (lowest energy state) in the dynamic system space. Neurons' motion equation is the core of this guided movement mechanism and guarantees that the state of the system always converges to the lowest energy state.

Comments on 'O(n²) algorithms for graph planarization' by R. Jayakumar et al.

Takefuji Yoshiyasu, Lee Kuo Chun, Cho Yong Beom

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 10 （ 12 ） 1582 - 1583 1991年12月

ISSN 0278-0070

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An artificial hysteresis binary neuron

Takefuji Y., Lee K. C.

Biological Cybernetics 64 （ 5 ） 353 - 356 1991年03月

ISSN 0340-1200

A hysteresis binary McCulloch-Pitts neuron model is proposed in order to suppress the complicated oscillatory behaviors of neural dynamics. The artificial hysteresis binary neural network is used for scheduling time-multiplex crossbar switches in order to demonstrate the effects of hysteresis. Time-multiplex crossbar switching systems must control traffic on demand such that packet blocking probability and packet waiting time are minimized. The system using n×n processing elements solves an n×n crossbar-control problem with O(1) time, while the best existing parallel algorithm requires O(n) time. The hysteresis binary neural network maximizes the throughput of packets through a crossbar switch. The solution quality of our system does not degrade with the problem size.

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Artificial neural networks for four-coloring map problems and K-colorability problems

Takefuji Yoshiyasu, Lee Kuo Chun

IEEE Transactions on Circuits and Systems 38 （ 3 ） 326 - 333 1991年03月

ISSN 0098-4094

The computational energy required for solving a four-coloring map problem is determined. A parallel algorithm for solving the problem based on the McCulloch-Pitts binary neuron model and the Hopfield neural network, is presented. It is shown that the computational energy is always guaranteed to monotonically decrease with the Newton equation. A 4 × n neural array is used to color a map of n regions, where each neuron is a processing element that performs according to the proposed Newton equation. The capability of this system is demonstrated for a large number of simulation runs. The parallel algorithm is extended for solving the K-colorability problem.

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A Parallel Algorithm for Allocation of Spare Cells on Memory Chips

Funabiki Nobuo, Takefuji Yoshiyasu

IEEE Transactions on Reliability 40 （ 3 ） 338 - 346 1991年

ISSN 0018-9529

In manufacturing memory chips, Redundant Random Access Memory (RRAM) technology has been widely used because it not only provides repair of faulty cells but also enhances the production yield. RRAM has several rows and columns of spare memory cells which are used to replace the faulty cells. The goal of our algorithm is to find a spare allocation which repairs all the faulty cells in the given faulty-cell map. The parallel algorithm requires In processing elements for the n x n faulty-cell map problem. The algorithm is verified by many simulation runs. Under the simulation the algorithm finds one of the near-optimum solutions in a nearly constant time with 0(n) processors. The simulation results show the consistency of our algorithm. The algorithm can be easily extended for solving rectangular or other shapes of fault map problems. Reader Aids - Purpose: Present a new algorithm Special math needed for explanations: Probability Special math needed to use results: None Results useful to: Reliability theoreticians and analysts.

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A maximum neural network for the max cut problem

Lee Kuo Chun, Takefuji Yoshiyasu, Funabiki Nobuo

379 - 384 1991年

The max cut problem, one of the NP-complete problems, was chosen to test the capability of an artificial neural network. The algorithm based on the maximum neural network was tested by 1000 randomly generated examples, including up to 300 vertex problems. The simulation result shows that the proposed parallel algorithm using the maximum neural network generates better solutions than Hsu's algorithm within one hundred iteration steps, regardless of the problem size.

Analog maximum neural network circuits using the switched capacitor technique

Cho Yong Beom, Lee Kuo Chun, Takefuji Yoshiyasu, Funabiki Nobuo

1906 - 1911 1991年

A parallel neural network computing for the maximum clique problem

Lee Kuo Chun, Funabiki Nobuo, Cho Y. B., Takefuji Yoshiyasu

905 - 910 1991年

A novel computational model for large-scale maximum clique problems is proposed and tested. The maximum clique problem is first formulated as an unconstrained quadratic zero-one programming and it is solved by minimizing the weight summation over the same partition in a newly constructed graph. The proposed maximum neural network has the following advantages: (1) coefficient-parameter tuning in the motion equation is not required in the maximum neural network while the conventional neural networks suffer from it; (2) the equilibrium state of the maximum neural network is clearly defined in order to terminate the algorithm, while the existing neural networks do not have the clear definition; and (3) the maximum neural network always allows the state of the system to converge to the feasible solution, while the existing neural networks cannot guarantee it. The proposed parallel algorithm for large-size problems outperforms the best known algorithms in terms of computation time with much the same solution quality where the conventional branch-and-bound method cannot be used due to the exponentially increasing computation time.

A neural network approach to broadcasting in multihop packet radio networks

Funabiki Nobuo, Takefuji Yoshiyasu, Lee Kuo Chun, Cho Yong Beom, Kurokawa Takakazu, Aiso Hideo

2540 - 2545 1991年

A neural network model for broadcasting scheduling in multihop packet radio networks is presented. The problem of broadcast scheduling with a minimum number of time slots is NP-complete. The proposed neural network model finds a broadcasting schedule with a minimal number of time slots where it requires n processing elements for an n-node radio network. Fifteen different radio networks were examined where the neural network model found an m-time-slot solution in O(m) time with n processors.

A parallel algorithm for solving the 'Hip' games

Funabiki Nobuo, Takefuji Yoshiyasu

Neurocomputing 3 （ 2 ） 97 - 106 1991年

ISSN 0925-2312

A parallel algorithm for solving the 'Hip' games based on an artificial neural network model is presented in this paper. The game of 'Hip' is named because of the hipster's reputed disdain for 'squares'. The rule of the game is to place the counters on a checkerboard so that four of them do not mark the corners of a square. The square may be of any size and be tipped at any angle. Normally this game is played by two players, where the game on a six-by-six checkerboard is the maximum size for the solution. The solution means that every player can place all the counters on the checkerboard without violations. In other words, the goal of our algorithm is to find the pattern of a draw game between players where they should not mark the corners of a square. In order to enlarge the size of the checkerboard where a solution exists, we modified the game as n/2 players play on an n-by-n checkerboard where n is an even number. The proposed parallel algorithm requires m × n² processing elements for the m-player-n-by-n-checkerboard game to find the solution of the 'Hip' games. The algorithm is verified by solving six games where the size of the checkerboard is varied from 4 to 12.

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Quantitative measurement of two-component absorption spectra using multilayer semilinear neural networks

Lin C. W., LaManna J. C., Lee K. C., Takefuji Y.

Annals of Biomedical Engineering 19 （ 5 ） 615 - 616 1991年

ISSN 0090-6964

A PC-based multilayer neural network with sigmoid activation function, generalized delta learning rule and error back-propagation was trained with two individual components (protonated and unprotonated form) of pH dependent spectra between 400 and 700 nm generated from microspectrophotometry of Neutral Red (NR). The NR spectrum changes from one resembling the acid to one resembling the base as the solution's pH changes from acid to base. The number of nodes in the input layer was based on the degree of resolution required. The number of hidden layer units was related to the storage capacity and could be a function of maximum connection weight between input and the hidden layer. The number of output nodes determined the step size used to distinguish the input spectrum. Teaching patterns are binary encoded to compare to the activity in the output layer. Simulation results show that after successful convergence with the training spectra features of the input spectrum are separated and stored in the weight matrix of the input and hidden layers. A calibration curve can be constructed to interpret the output layer activity and therefore allow prediction of the pH. With its intrinsically redundant presentation, this novel approach to spectrophotometry needs no preprocessing procedures (baseline correction and extensive signal averaging) for spectral identification. Spectral distortion, e.g. due to light scattering effects, such as between phosphate buffer solutions and brain homogenates do not affect the outcome. This method was applied to the in vitro hippocampal slice preparation to measure anoxic pHi changes. The method can be generalized to adapt to any pattern oriented sensory information processing and multi-sensor fusion for quantitative measurement.

CMOS layout design of the hysteresis McCulloch-Pitts neuron

Kurokawa T., Lee K. C., Cho Y. B., Takefuji Y.

Electronics Letters 26 （ 25 ） 2093 - 2095 1990年12月

ISSN 0013-5194

A McCulloch-Pitts neuron is the simplified neuron model which has been successfully used for many optimisation problems. The neural network with the hysteresis property can suppress the oscillatory behaviours of neural dynamics so that the convergence time is shortened. In this paper, digital CMOS layout design of the hysteresis McCulloch-Pitts neuron is presented. Based on simulation results using the hysteresis McCulloch-Pitts binary neuron model, a 6-bit fixed point 2's complement arithmetic was adopted for the calculation of the input U of each neuron. Each neuron needs 204 transistors and requires a 399 λ × 368 λ layout area using the MOSIS scalable CMOS/bulk (SCMOS) VLSI technology with 2 μm rule of P well, double level metal. Layout design of the hysteresis McCulloch-Pitts neuron chip was completed, and fabrication of the chip and the design for the test circuit for the fabricated CMOS VLSI chip are underway at present.

A super-parallel sorting algorithm based on neural networks

Takefuji Yoshiyasu, Lee Kuo Chun

IEEE Transactions on Circuits and Systems 37 （ 11 ） 1425 - 1429 1990年11月

ISSN 0098-4094

A novel neural network parallel algorithm for sorting problems is presented. The proposed algorithm using O(n²) processors requires only two steps, and does not depend on the size of the problem, while the conventional parallel sorting algorithm using O(n) processors by F. T. Leighton (1984) needs the computation time O(log n²). A set of simulation results substantiates the proposed algorithm. The hardware system based on the proposed parallel algorithm is also presented.

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A parallel algorithm for estimating the secondary structure in ribonucleic acids

Takefuji Y., Lin C. W., Lee K. C.

Biological Cybernetics 63 （ 5 ） 337 - 340 1990年09月

ISSN 0340-1200

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Parallel algorithms for finding a near-maximum independent set of a circle graph

Takefuji Yoshiyasu, Chen Li Lin, Lee Kuo Chun, Huffman John

IEEE Transactions on Neural Networks 1 （ 3 ） 263 - 267 1990年09月

ISSN 1045-9227

A parallel algorithm for finding a near-maximum independent set in a circle graph is presented. An independent set in a graph is a set of vertices, no two of which are adjacent. A maximum independent set is an independent set whose cardinality is the largest among all independent sets of a graph. The algorithm is modified for predicting the secondary structure in ribonucleic acids (RNA). The proposed system, composed of an n neural network array (where n is the number of edges in the circle graph of the number of possible base pairs), not only generates a near-maximum independent set but also predicts the secondary structure of ribonucleic acids within several hundred iteration steps. The simulator discovered several solutions which are more stable structures, in a sequence of 359 bases from the potato spindle tuber viroid, than previously proposed structures.

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Analog components for the VLSI of neural networks

Foo Simon Y., Anderson Lisa R., Takefuji Yoshiyasu

IEEE Circuits and Devices Magazine 6 （ 4 ） 18 - 26 1990年07月

ISSN 8755-3996

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Parallel algorithm for tiling problems

Takefuji Yoshiyasu, Lee Kuo Chun

IEEE Transactions on Neural Networks 1 （ 1 ） 143 - 145 1990年03月

ISSN 1045-9227

A parallel algorithm for tiling with polyominoes is presented. The tiling problem is to pack polyominoes in a finite checkerboard. The algorithm using l × m × n processing elements requires O(1) time, where l is the number of different kinds of polyominoes on an m × n checkerboard. The algorithm can be used for placement of components or cells in a very large-scale integrated circuit (VLSI) chip, designing and compacting printed circuit boards, and solving a variety of two- or three-dimensional packing problems.

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Databases and cell-selection algorithms for VLSI cell libraries

Foo Simon Y., Takefuji Yoshiyasu

Computer 23 （ 2 ） 18 - 30 1990年02月

ISSN 0018-9162

The issues that must be addressed before commercial database management systems can be used to manage VLSI CAD data are defined. A survey is presented of approaches addressing four of the defined issues: design hierarchies and multilevel representations, design alternatives and version control, common interface between cell libraries, and efficient cell selection based on given design constraints. A frame-based model is considered as a case study of the special-purpose design database management system approach. This framework for capturing design data is based on semantic networks. It is well suited for application-specific ICs, yet general enough for other CAD/CAM environments. Benchmark results for the selection algorithms that run on top of the frame-based database system are presented.

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Implementing fuzzy rule-based systems on silicon chips

Lim Meng Hiot, Takefuji Yoshiyasu

IEEE Expert 5 （ 1 ） 31 - 45 1990年02月

ISSN 0885-9000

The authors address the implementation of a fuzzy simulator (FSIM) and discuss architectures for a general-purpose VLSI fuzzy-inference processor. The FSIM tool aids in the rapid prototyping of fuzzy production system (FPS), and represents a convenient transitional step in the implementation of an FPS on silicon. They present a brief theoretical review of fuzzy reasoning, introduce the FSIM, and discuss FPS development using the FSIM. An overall picture of the various stages involved in developing a fuzzy-inference processor is provided. The authors then outline the general architecture of a VLSI inference processor for FPSs. To further illustrate the development of a fuzzy inference processor, they describe an FPS example from conceptualization to implementation on silicon chips.

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A two step sorting algorithm

Takefuji Yoshiyasu, Lee Kuo Chun, Tanaka Toshimitsu

793 - 798 1990年

A parallel algorithm based on neural networks for solving sorting problems is presented. The proposed algorithm uses O(n²) processing elements called binary neurons, where n is the number of unsorted elements. It requires two and only two iteration steps, while the conventional parallel sorting algorithm using (On) processors proposed by F. T. Leighton (1984) requires the computation time O(log n). A set of simulation results substantiates the proposed algorithm. The hardware system based on the proposed parallel algorithm is also presented.

Computation scheme for the general purpose VLSI fuzzy inference engine as expert system

Takefuji Yoshiyasu, Lim Meng Hiot

Knowledge-Based Systems 2 （ 2 ） 109 - 116 1989年

ISSN 0950-7051

Fuzzy inference engines based on the existing fuzzy theory are inadequate to perform reliable decision making. Besides requiring the fuzzy sets and data to be normalized, the inference engine is also sensitive to noise in observational data. Inaccurate conclusions are produced if noise is present and also when the fuzzy sets are not normalized. In this paper, a new term 'similarity' (σ) and the method to compute σ to enhance the capability of fuzzy set theory for application in expert systems is introduced. Even though the complexity of the hardware engine is slightly increased, it actually reduces the overhead of computation by eliminating the need for normalization of fuzzy data. With reliable fuzzy data manipulation, it is easy to extend to a multi-dimensional membership function which has a wider scope of applications. To To implement the Very Large Scale Integration fuzzy inference engine, two general schemes of the hardware architecture that van be easily reconfigured to satisfy given performance requirements are discussed.

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A near-optimum parallel planarization algorithm

Takefuji Yoshiyasu, Lee Kuo Chun

Science 245 （ 4923 ） 1221 - 1223 1989年

ISSN 0036-8075

A near-optimum parallel planarization algorithm is presented. The planarization algorithm, which is designed to embed a graph on a plane, uses a large number of simple processing elements called neurons. The proposed system, composed of an N×N neural network array (where N is the number of vertices), not only generates a near-maximal planar subgraph from a nonplanar graph or a planar graph but also embeds the subgraph on a single plane within 0(1) time. The algorithm can be used in multiple-layer problems such as designing printed circuit boards and routing very-large-scale integration circuits.

Parallel distributed gradient descent and ascent methods

Takefuji Yoshiyasu

584 1989年

Design of parallel distributed Cauchy machines

Takefuji Yoshiyasu, Szu Harold

529 - 532 1989年

A parallel and stochastic version of Hopfield-like neural networks is presented. Cauchy color noise is assumed. The specific noise is desirable for fast convergence to a fixed point representing a neighborhood minimum. It can be quickly quenched at each iteration according to a proven cooling schedule in generating random states on the energy landscape. An exact Cauchy acceptance criterion is analytically derived for hill-climbing capability. The improvement is twofold: a faster cooling schedule (the inversely linear cooling schedule characterized by the Cauchy simulated annealing) and parallel executions of all neurons. Such a Cauchy machine can be electronically implemented, and the design is given.

Conjunctoid learning and performance algorithms

Jannarone R. J., Yu K. F., Takefuji Y.

Neural Networks 1 （ 1 SUPPL ） 186 1988年

ISSN 0893-6080

In its first 40 years the neural network learning (NNL) movement has produced an impressive array of learning models. We introduce a general family of fast and efficient NNL learning modules for binary events called 'conjunctoids', which employ an appropriate framework from probability theory; adapt a class of recently developed conjunctive models from psychometric theory; tailor sound statistical estimation and evaluation schemes to fit NNL learning needs; and allow VLSI implementations.

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MULTINOMIAL CONJUNCTOID STATISTICAL LEARNING MACHINES.

Takefuji Yoshiyasu, Jannarone Robert, Cho Yong B., Chen Tatung

12 - 17 1988年

Stochastic neural networks for solving job-shop scheduling. II - Architecture and simulations

Foo Yoon Pin Simon, Takefuji Yoshiyasu

283 - 290 1988年

The authors introduce a neural computation architecture based on a stochastic Hopfield neural network model for solving job-shop scheduling. A computation circuit computes the total completion times (costs) of all jobs, and the cost difference is added to the energy function of the stochastic neural network. Using a simulated annealing algorithm, the temperature of the system is slowly decreased according to an annealing schedule until the energy of the system is at a local or global minimum. By choosing an appropriate annealing schedule, near-optimal and optimal solutions to job-shop problems can be found. The architecture of the system is diagrammed at both the functional and circuit levels. Simulation results are presented.

ANALOG CIRCUIT DESIGN BASED ON NEURAL NETWORKS.

Cho Yong B., Takefuji Yoshiyasu

100 - 105 1988年

Neural networks have been studied for many years with the hope of achieving human-like performance in such fields as speech and image recognition. A recent resurgence has resulted from VLSI advances, neural network models, and learning algorithms. Neural networks are also very suitable in certain areas such as NP-complete constraint and satisfaction problems, due to the nature of parallel and distributed processing. Neural network models are composed of a mass of fairly simple computational elements and rich interconnections between the elements. Neural networks operate in a parallel and distributed fashion which may resemble biological neural networks. Behaviors of neurons and the strengths of synaptic interconnections are simulated by operational amplifiers and resistors respectively. Several examples are presented, including how to build neural network components based on analog circuits for simulating neural networks and conventional logic circuits.

Stochastic neural networks for solving job-shop scheduling. I - Problem representation

Foo Yoon Pin Simon, Takefuji Yoshiyasu

275 - 282 1988年

An application of neural networks is presented for solving job-shop scheduling, an NP-complete optimization problem with constaint satisfaction. In particular, the authors introduce a neural computation architecture based on a stochastic Hopfield neural-network model. First, the job-shop problem is mapped into a two-dimensional matrix representation of neurons similar to those for solving the traveling salesman problem (TSP). Constant positive and negative current biases are applied to specific neurons as excitations and inhibitions, respectively, to enforce the operation precedence relationships. At the convergence of neural network, the solution to the job-shop problem is represented by a set of cost function trees encoded in the matrix of stable states. Each node in the set of trees represents a job, and each link represents the interdependency between jobs. A computation circuit computes the total completion times (costs) of all jobs, and the cost difference is added to the energy function of the stochastic neural network. Using a simulated annealing algorithm, the temperature of the system is slowly decreased according to an annealing schedule until the energy of the system is at a local or global minimum. By choosing an appropriate annealing schedule, near-optimal and optimal solutions to job-shop problems can be found.

Binary neurons with analog communication links for solving large-scale optimization problems

Foo Yoon Pin Simon, Takefuji Yoshiyasu, Szu Harold

Neural Networks 1 （ 1 SUPPL ） 437 1988年

ISSN 0893-6080

We explore the applications of binary neurons with analog conductance or communication links in solving large-scale NP-complete optimization problems such as the classical traveling salesperson problems (TSP) and job-shop scheduling. In particular, the energy function of J.J. Hopfield and D.W. Tank neural network model is reformulated so that the network is likely to converge to a proportional number of valid solutions as the size of problem scales up. G.V. Wilson and G.S. Pawley identified the reasons for failure on the Hopfield and Tank computation algorithm in their attempts to solve a 10-city TSP. K. Sheff and H. Szu proposed a necessary and sufficient condition based on binary neurons and traceless energy for a Hopfield and Tank network to converge to stable states. In this paper, we study the effectiveness of this fast neural network convergent scheme through two case studies: an n-job m-machine job-shop problem and an N-city TSP.

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Novel approach to a rule-based general purpose program translator using paramodulation

Takefuji Yoshiyasu, Dowell Michael

Knowledge-Based Systems 1 （ 2 ） 90 - 93 1988年

ISSN 0950-7051

In this paper a rule-based Lisp dialect translator using paramodulation is presented as an example of a general purpose program translator application where the knowledge about the translation is embedded in rules. The advantage of using a rule-based system is to allow the user to supply his own rules for translation, thus the translator can be considered as a general purpose converter. Also, the rule-based LDT has the ability to test individual rules for correctness to aid in rule development. The translation being used for development is Franz to Common Lisp.

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Silicon multinomial conjunctoid statistical learning modules

Takefuji Yoshiyasu, Jannarone Robert J., Chen Tatung, Cho Yong B.

Neural Networks 1 （ 1 SUPPL ） 413 1988年

ISSN 0893-6080

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Conjunctoids

Jannarone Robert J., Yu Kai F., Takefuji Yoshiyasu

Neural Networks 1 （ 4 ） 325 - 337 1988年

ISSN 0893-6080

A general family of fast and efficient neural network learning modules for binary events is introduced. The family subsumes probabilistic as well as functional event associations; subsumes all levels of input/output association; yields truly parallel learning processes; provides for optimal parameter estimation; points toward a workable description of optimal model performance; and yields procedures that are simple and fast enough to be serious candidates for reflecting both neural functioning and real time machine learning. Examples as well as operational details are provided.

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ERROR CORRECTING SYSTEM BASED ON NEURAL CIRCUITS.

Takefuji Yoshiyasu, Hollis Paul, Foo Yoon Pin, Cho Yong B.

1987年

NEURAL NETWORK SCHEME FOR 3-DIMENSIONAL PATTERN RECOGNITION AND CONSTRUCTION.

Foo Yoon Pin Simon, Takefuji Yoshiyasu

1987年

A neural-based scheme for pattern recognition and construction of three-dimensional images from partial cues is presented. Clusters of neural nets operating concurrently are used to learn and recall patterns at X, Y, Z planes. Simulations are performed based on a Hopfield-like network to investigate the effect of learning trials and firing percentage of nodes per cycle. A method for computing the common features of input patterns is given. Results showed that maximum parallel processing can be achieved.

NEW MODEL OF NEURAL NETWORKS FOR ERROR CORRECTION.

Lii Dzung ji, Takefuji Yoshiyasu

1709 - 1710 1987年

AI BASED GENERAL PURPOSE CROSS ASSEMBLER.

Takefuji Yoshiyasu

75 - 80 1985年

A general-purpose cross assembler named gpca using Franz Lisp on a VAX11/750 with Berkeley Unix BSD4. 2 was developed. All the user has to do is to provide rule lists to a rule-database for code generation. The rule-based technique used in the gpca can enhance the productivity for developing cross assemblers for 4-, 8-, 16-, and 32-bit microprocessors in a short period of time through the rule independency. The implemented cross-assembler is composed of database management routines, lexical pattern matching routines, and a few other routines. The cross assembler, which is small enough to be understood completely by the user, has a flexibility and an expandability in terms of user extensible pseudo-operations and macro functions.

VLSI SPANNING TREE GENERATORS.

Takefuji Yoshiyasu, Brunson David

401 - 405 1984年

Authors propose parallel/pipelined and parallel/iterative spanning tree generators for directed and undirected graphs based on graph theory algorithms using adjacency matrices. A generator employing iterative logic circuits with high regularity suitable for VLSI implementation can be realized with O(n**2) gates where n is the number of nodes in a given graph. This generator can compute a spanning tree of an nXn adjacency matrix within O(n**2) gate delays. The organizations of spanning tree generators are discussed.

FAST MATRIX SOLVER IN GF(2).

Takefuji Yoshiyasu, Kurokawa Takakazu, Aiso Hideo

138 - 143 1983年

TMR METHOD FOR IMPROVING YIELD OF LARGE MEMORY CHIPS.

Takefuji Yoshiyasu, Adachi Yoshihiko, Aiso Hideo

Systems, computers, controls 13 （ 1 ） 47 - 53 1982年01月

ISSN 0096-8765

The yield of chips tends to decrease with the degree of integration of memory chips, which is presently a serious problem. A method is proposed to utilize the fault chips being discarded to produce a normal chip, increasing the apparent yield. The relation between the yield and the reliability of the fault memory chip system is discussed. Using the proposed method, the yield of 10% can be improved up to 40% without substantially decreasing the reliability of the fault chip memory system from that of a normal memory chip. The method was implemented using fault 16 K RAM, and the effectiveness of the method was verified.

NOVEL APPROACH TO FAULT-TOLERANT SEQUENTIAL CIRCUITS.

Takefuji Yoshiyasu, Adachi Yoshihiko, Aiso Hideo

206 - 209 1982年

NOVEL APPROACH TO FAULT-TOLERANT LOGIC AND YIELD ENHANCEMENT.

Takefuji Yoshiyasu, Adachi Yoshihiko, Aiso Hideo

56 - 64 1982年

NOVEL APPROACH TO FAULT-TOLERANT LOGIC.

Takefuji Yoshiyasu, Ikeda Masahiro

Journal of Information Processing 3 （ 3 ） 119 - 126 1980年

ISSN 0387-6101

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