• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.235-245
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• 2005

The rapid development of computer network technology has brought the Internet as the major infrastructure to our society. But the rapid increase in malicious computer intrusions using such technology causes urgent problems of protecting our information society. The recent trends of the intrusions reflect that the intruders do not break into victim host directly and do some malicious behaviors. Rather, they tend to use some automated intrusion tools to penetrate systems. Most of the unknown types of the intrusions are caused by using such tools, with some minor modifications. These tools are mostly similar to the Previous ones, and the results of using such tools remain the same as in common patterns. In this paper, we are describing design and implementation of attacker-traceback system, which traces the intruder based on the multi-agent architecture. The system first applied SOM to classify the unknown types of the intrusion into previous similar intrusion classes. And during the intrusion analysis stage, we formalized the patterns of the tools as a knowledge base. Based on the patterns, the agent system gets activated, and the automatic tracing of the intrusion routes begins through the previous attacked host, by finding some intrusion evidences on the attacked system.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.855-864
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• 2001

With the increasing importance and complexity of EC (Electronic Commerce) across the Internet, the need and expectation for intelligent software agents to support both consumers and suppliers through the whole process of EC are growing rapidly. To realize the intelligent EC. a multiagent based EC system. which includes foundational technologies such as the establishment of standard product ontology the definition of message and negotiation protocol and brockering, is required. In this paper we propose an intelligent EC System named ICOMA(Intelligent electronic CO mmerce system based on Multi-Agent) as an open infrastructure of multiagent-based EC. Concretely we have proposed. designed and implemented an architecture of multiagent-based EC system including 6-types of agents message protocol for inter-agent negotiation, personalized produst retrieval and filtering., We have confirmed the effectiveness of the system through experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2033-2038
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• 2003

This paper describes an integrated navigation strategy for the autonomous service robot PSR. The PSR is under development at the KIST for service tasks in indoor public environments. The PSR is a multi-functional mobile-manipulator typed agent, which works in daily life. Major advantages of proposed navigation are as follows: 1) Structured control architecture for a systematic integration of various software modules. A Petri net based configuration design enables stable control flow of a robot. 2) A range sensor based generalized scheme of navigation. Any range sensor can be selectively applied using the proposed navigation scheme. 3) No need for modification of environments. (No use of artificial landmarks.) 4) Hybrid approaches combining reactive behavior as well as deliberative planner, and local grid maps as well as global topological maps. A presented experimental result shows that the proposed navigation scheme is useful for mobile service robot in practical applications.

• Asia pacific journal of information systems
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• v.15 no.2
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• pp.195-218
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• 2005

The emergence of ubiquitous computing environment will change the service architecture of business information systems such as Decision Support System(DSS), which will be a new application. Recent mobile DSSs allow the decision makers to be benefited from web and mobile technology. However, they seldom refer to context data, which are useful for proactive decision support. Meanwhile, ubiquitous applications so far provide restricted personalization service using context and preference of the user, that is, they do not fully make use of decision making capabilities. Hence, this paper aims to describe how the decision making capability and context-aware computing are jointly used to establish ubiquitous applications. To do so, an amended DSS paradigm: CKDDM(Context-Knowledge-Dialogue-Data-Model) is proposed in this paper. What will be considered for the future decision support systems when we regard ubiquitous computing technology as an inevitable impact that enforces the change of the way of making decisions are described. Under the CKDDM paradigm, a framework of ubiquitous decision support systems(ubiDSS) is addressed with the description of the subsystems within. To show the feasibility of ubiDSS, a prototype system, CAMA-myOpt(Context-Aware Multi Agent System-My Optimization) has been implemented as an illustrative example system.

• Journal of Microbiology and Biotechnology
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• v.14 no.1
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• pp.74-80
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• 2004

Aspergillus fumigatus is one of the most common fungi in the human environment, both in-doors and out-doors. It is the main causative agent of invasive aspergillosis, a life-threatening mycosis among immunocompromised patients. The genome has been sequenced by an international consortium, including the Wellcome Trust Sanger Institute (U.K.) and The Institute for Genomic Research (TIGR, U.S.A.), and a ten times whole genome shotgun sequence assembly has been made publicly available. In this study, we identified tricarboxylic acid (TCA) cycle enzymes of A. fumigatus by comparative analysis with four other fungal species. The open reading frames showed high amino acid sequence similarity with the other fungal citric acid enzymes and well-conserved functional domains. All genes present in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans, and Neurospora crassa were also found in A. fumigatus. In addition, we identified four A. fumigatus genes coding for enzymes in the glyoxylate shunt, which may be required for fungal virulence. The architecture of multi-gene encoded enzymes, such as isocitrate dehydrogenase, 2-ketoglutarate, succinyl-CoA synthetase, and succinate dehydrogenase was well conserved in A. fumigatus. Furthermore, our results show that genes of A. fumigatus can be detected reliably using GlimmerM.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.147-163
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• 2004

For the purchase of a cheaper product on the Internet, many customers have been trying to search online shopping mall sites and visit comparison-pricing shops that compare prices and other criteria of the product. Others have been participating into online auction markets or group-buying markets. However, a lot of online shopping malls, auction markets, and group-buying markets provide the same product with different prices. Since these marketplaces have different price settlement mechanism, it is very difficult for the customers to determine marketplace to purchase, considering different kinds of marketplaces at the same time. To overcome such limitations, decision rules and solution procedures for purchase decision making are necessary, which can cover multiple marketplaces simultaneously. For this purpose, purchase decision making in each market must be conducted to maximize customer's utility, and conflicts with other marketplaces must be resolved. Therefore, we have developed the rules and methods that can negotiate cooperatively the purchase decision making in several marketplaces, and designed an architecture of Intelligent Buyer Agent and a message structure to support the idea.

• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.99-125
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• 2007

Recently, as the development of Ubiquitous Smart Space (USS) such as U-City is proliferating, preparing a development methodology dedicated to USS characteristics has become one of the crucial issues to increase the productivity of the USS projects. However, since the legacy development methodologies such as traditional UML do not consider the critical components of ubiquitous computing space such as context-awareness, service oriented architecture and multi-agent communication, they are not optimized for USS analysis and design. Hence, the purpose of this paper is to propose a USS-sophisticated development methodology. To do so, a hybrid approach, BPR-USS for space reengineering and UML-USS by amending UML with corresponding toolkit based on StarUML has been implemented. To show the feasibility of the approach described in this paper, an illustrative example with an actual USS development project for a multiplex space in Seoul is shown.

• Journal of KIISE:Information Networking
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• v.32 no.1
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• pp.100-109
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• 2005

A Mobile Ad-Hoc Network (MANET) supports a multi-hop wireless network without any prepared base station (BS). The MANET is capable of building a mobile network automatically without any help from DHCP servers for address allocation or routers to forward or route messages. Many routing protocols have been proposed for the MANET, but these specify the most optimized or shortest path from a source to a destination, and they assume that nodes are pre-configured before communication. To make up for this, address allocation algorithms, such as MANETConf [1] and prophet address allocation algorithm [2], have been proposed. Especially, MANETConf proposes address allocation algorithm with duplication address check. In this paper, we present a dynamic node configuration protocol based on 2-tierd hierarchical network architecture for mobile ad-hoc network, modified from [1]. Especially, it reduces the number of broadcast message exchange between nodes when a new node somes into a network, which lessens network overhead, remarkably. This protocol is based on two-tired structure, and it ensures address allocation with simple duplication address defection mechanism.