• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.1
• /
• pp.29-33
• /
• 2004

I propose a personalized digital library system (PDLS) based on an advanced distributed agent platform. The new platform is developed by improving the DECAF (Distributed Environment-Centered Agent Framework) which is one of the conventional distributed agent development toolkits. Also, a mobile ORB (Object Request Broker), Voyager, and a new multi agent negotiation algorithm are adopted to develop the advanced platform. The new platform is for mobile multi agents as well as the distributed environment, whereas the DECAF is for the distributed and non-mobile environment. From the results of the simulation the searched time of PDLS is lower, as the numbers of servers and agents are increased. And the user satisfaction is four times greater than the conventional client-server model. Therefore, the new platform has some optimality and higher performance in the distributed mobile environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.268-271
• /
• 2003

In this paper, we propose a new framework based on negotiatory mobile multi agent system, and implement a mobile multi agent environment based on DECAF(Distributed Environment-Centered Agent Framework) which is one of the distributed agent development toolkit so as to implement a new PDS(Personal Digital Library System). The new framework has some optimality and higher performance in distributed environments.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2002.11b
• /
• pp.412-416
• /
• 2002

멀티 에이전트 시스템은 여러 개의 에이전트들이 상호 협동해서 효율적으로 하나의 문제를 해결하는 것을 말한다. 우리는 멀티 에이전트 개발도구인 DECAF 에이전트 프레임워크를 사용하여 분산 모바일 환경을 고려한 멀티 에이전트 시스템을 개발하였다. 본 논문의 시스템은 현재 보편화된 모바일 환경에 적용시킬 수 일도록 크게 클라이언트 측과 프레임워크 군으로 분리시켜 개발하였고. 해당 시스템을 여행 스케쥴링 문제 영역에 적용시켜서 구현해 보았다.

• Journal of KIISE:Software and Applications
• /
• v.31 no.12
• /
• pp.1637-1648
• /
• 2004

When digital libraries are developed by the traditional client/sever system using a single agent on the distributed environment, several problems occur. First, as the search method is one dimensional, the search results have little relationship to each other. Second, the results do not reflect the user's preference. Third, whenever a client connects to the server, users have to receive the certification. Therefore, the retrieval of documents is less efficient causing dissatisfaction with the system. I propose a new platform of mobile multiagents for a personal digital library to overcome these problems. To develop this new platform I combine the existing DECAF multiagents platform with the Voyager mobile ORB and propose a new negotiation algorithm and scheduling algorithm. Although there has been some research for a personal digital library, I believe there have been few studies on their integration and systemization. For searches of related information, the proposed platform could increase the relationship of search results by subdividing the related documents, which are classified by a supervised neural network. For the user's preference, as some modular clients are applied to a neural network, the search results are optimized. By combining a mobile and multiagents platform a new mobile, multiagents platform is developed in order to decrease a network burden. Furthermore, a new negotiation algorithm and a scheduling algorithm are activated for the effectiveness of PDS. The results of the simulation demonstrate that as the number of servers and agents are increased, the search time for PDS decreases while the degree of the user's satisfaction is four times greater than with the C/S model.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.7
• /
• pp.71-78
• /
• 2017

There are several algorithms to classify emotion, such as Support-vector-machine (SVM), Bayesian decision rule, etc. However, many researchers have insisted that these methods have minor problems. Therefore, in this paper, we propose a novel method for emotion recognition based on Electroencephalogram (EEG) signal using the Gradient method which was proposed by Han. We also utilize a database for emotion analysis using physiological signals (DEAP) to obtain objective data. And we acquire four channel brainwaves, including Fz (${\alpha}$), Fp2 (${\beta}$), F3 (${\alpha}$), F4 (${\alpha}$) which are selected in previous study. We use 4 features which are power spectral density (PSD) of the above channels. According to performance evaluation (4-fold cross validation), we could get 85% accuracy in valence axis and 87.5% in arousal. It is 5-7% higher than existing method's.