• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (3)
• /
• pp.811-813
• /
• 2001

본 논문에서는 기존의 IP 망에서 호스트의 이동성을 지원하기 위한 Mobile IP 개념을 ATM 망에 적용할 경우, Mobile IP망에서 Home Agent와 Foreign Agent 사이에 존재하는 Mobile-IP 터널링 구간을 기존의 LAN 기반의 IP 터널링 구간과 ATM 망에서의 단거리 터널링(short-cut tunneling) 구간으로 구분하여 관리하는 방안을 제안하였다. Short-cut 터널링을 설정하기 위하여 NHRP를 이용하였으며 Shot-cut 터널링을 이용함으로써 HA 와 FA 사이에 데이터 전달 지연을 기존의 IP 터널링에서의 데이터 전달 지연보다 줄일 수 있음을 시뮬레이션을 통해 확인하였다.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
• /
• pp.37-44
• /
• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 1998년도 가을 학술발표논문집(II)
• /
• pp.368-373
• /
• 1998

Prepackaged system consists out of a dry mix which contains cement, sand, redispersible polymer powder and admixtures in the right proportions. The purpose of this study is to evaluate the quality of prepackaged-type polymer-modified mortar products using redispersible poly(ethylene-vinyl acetate)(EVA) powder. Polymer-modified mortars using the redispersible polymer powder with powdered with powdered shrinkage-reducing agent were prepared with cellulose fiber contents of 0, 0.5, 1.0% and shrinkage-reducing agent contents of 0, 4%, and tested for drying shrinkage, strength, adhesion in tension, water absorption. From the test results, the prepackaged-type polymer-modified mortar products with 4% of shrinkage-reducing agent content give good properties. and that their properties largely depends on the shrinkage-reducing agent content rather than the cellulose fiber contents.

• Journal of Communications and Networks
• /
• 제8권1호
• /
• pp.123-131
• /
• 2006

Several distributed architectures, incorporating mobile agent technology, have been recently proposed to answer the scalability limitations of their centralized counterparts. However, these architectures fail to address scalability problems, when distributed tasks requiring the employment of itinerant agents is considered. This is because they lack mechanisms that guarantee optimization of agents' itineraries so as to minimize the total migration cost in terms of the round-trip latency and the incurred traffic. This is of particular importance when MAs itineraries span multiple subnets. The work presented herein aspires to address these issues. To that end, we have designed and implemented an algorithm that adapts methods usually applied for addressing network design problems in the specific area of mobile agent itinerary planning. The algorithm not only suggests the optimal number of mobile agents that minimize the overall cost but also constructs optimal itineraries for each of them. The algorithm implementation has been integrated into our mobile agent framework research prototype and tested in real network environments, demonstrating significant cost savings.

• 한국콘크리트학회:학술대회논문집
• /
• 한국콘크리트학회 2006년도 춘계 학술발표회 논문집(II)
• /
• pp.617-620
• /
• 2006

This study is related to comprehending performance for watertightness and crack control of concrete added with crack reducing agent concerning to high strength concrete mixs. It was confirmed that watertightness of concrete added with agent could be improved by evaluation absorption ratio, permeability ratio and pore size distribution of hardened concrete. As well resistance to crack resulted from shrinkage was transferred to better state by the addition of agent.

• 한국건축시공학회지
• /
• 제12권1호
• /
• pp.64-72
• /
• 2012

Recently, prepackaged-type surface preparation materials using redispersible polymer powders are widely used for interior and exterior finishing in the construction work. The purpose of this study is to evaluate the performance and the quality of prepackaged-type surface preparation materials using a VA/E/MMA terpolymer powder. Surface preparation materials using a VA/E/MMA terpolymer powder were prepared with shrinkage reducing agent contents of 0, 4 % and cellulose fiber contents of 0, 0.5, 1.0 %, and tested for drying shrinkage, strengths, adhesion in tension, crack and impact resistance, water absorption, permeability. As a result, prepackaged-type surface preparation materials show outstanding performance depending on the shrinkage reducing agent and cellulose fiber contents.

• 한국IT서비스학회지
• /
• 제15권4호
• /
• pp.85-95
• /
• 2016

Recently, deep learning and machine learning have attracted considerable attention and many supporting frameworks appeared. In artificial intelligence field, a large body of research is underway to apply the relevant knowledge for complex problem-solving, necessitating the application of various learning algorithms and training methods to artificial intelligence systems. In addition, there is a dearth of performance evaluation of decision making agents. The decision making agent that can find optimal solutions by using reinforcement learning methods designed through this research can collect raw pixel data observed from dynamic environments and make decisions by itself based on the data. The decision making agent uses convolutional neural networks to classify situations it confronts, and the data observed from the environment undergoes preprocessing before being used. This research represents how the convolutional neural networks and the decision making agent are configured, analyzes learning performance through a value-based algorithm and a policy-based algorithm : a Deep Q-Networks and a Policy Gradient, sets forth their differences and demonstrates how the convolutional neural networks affect entire learning performance when using pixel data. This research is expected to contribute to the improvement of artificial intelligence systems which can efficiently find optimal solutions by using features extracted from raw pixel data.

• 한국정보과학회논문지:정보통신
• /
• 제33권5호
• /
• pp.343-354
• /
• 2006

무선 네트워크의 MANET(Mobile Ad Hoc Networks)에서 이동노드의 이동성을 보장하기 위해 제안된 Mobile IP를 통합하려는 시도에 대한 연구가 활발히 이루어지고 있다. 본 논문에서는 애드 혹 네트워크와 유선망의 통합망에서 노드들의 이동성 서비스를 지원하기 위한 방안을 제시한다. 통합망에서 Mobile IP 에이전트가 주기적으로 에이전트 광고메시지를 전달하여 자신의 애드 혹 네트워크 영역내부에 있는 이동노드들의 정보를 유지하기 위한 MAAM(Mobility Agent Advertisement Mechanism)과 에이전트 광고메시지에 대한 등록메시지를 중간노드가 취합(aggregation)하여 에이전트에게 전달하는 AMAAM (Aggregation based Mobility Agent Advertisement Mechanism) 메커니즘을 제안한다. 제안된 기법은 MIPMANET에서 에이전트 광고를 위한 메커니즘에 적용할 수 있다. 성능 평가는 ns2 시뮬레이션을 통해 패킷 전달 비율과 데이타 처리량 그리고 이동노드들의 에너지 소모량에 대해서 그 성능을 평가한다.

• 대한토목학회논문집
• /
• 제38권2호
• /
• pp.319-325
• /
• 2018

최근 집중호우, 잦은 강설 등 이상기후에 따라 아스팔트 콘크리트 포장의 포트홀 발생이 급증하고 있다. 포트홀은 교통사고와 직결되는 파손형태로 인명피해, 차량 및 도로시설물 파손 등의 피해가 증가하는 추세이다. 이에 따라 포트홀 발생을 저감하기 위해 아스팔트 콘크리트 혼합물에 박리방지제를 의무적으로 사용하도록 권장하고 있는 실정이다. 국내에서는 비교적 사용이 편리하고 경제적인 소석회를 박리방지제로 주로 사용하고 있다. 본 연구에서는 순환 유동층 보일러 가동시 발생하는 보일러 부산 애쉬를 박리방지제로 활용하는 연구를 수행하였다. 연구결과 보일러 부산 애쉬를 아스팔트 콘크리트 혼합물 중량의 1~3% 혼합한 결과 TSR 기준을 모두 만족하였다. 품질변동을 감안하여 골재, 혼합물 등 다양한 조건의 보일러 부산 애쉬를 검토하였으며 실험결과 TSR 평균 0.87, 동적수침 후 피복률 60% 이상으로 안정적으로 품질기준을 만족하는 것으로 나타났다. 이에 따라 보일러 부산 애쉬는 안정적으로 박리방지제 성능을 발현하여 아스팔트 콘크리트 포장의 포트홀 발생 저감에 매우 효과적일 것으로 판단된다.

• International Journal of Computer Science & Network Security
• /
• 제23권10호
• /
• pp.135-146
• /
• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.