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Journal of Intelligence and Information Systems,
Vol. 11, No. 3, December 2005
Applying Rescorla-Wagner Model to Multi-Agent Web Service and Performance Evaluation for Need Awaring Reminder Service
Oh Byung Kwon, Keon Ho Choi, and Sung Chul Choi
Vol. 11, No. 3, Page: 1 ~ 23
Keywords : RFID, Semantic web, Agent technology, Reminder system, Reminder system, Ubiquitous service
Abstract
Personalized reminder systems have to identify the user's current needs dynamically and proactively based on the user's current context. However, need identification methodologies and their feasible architectures for personalized reminder systems have been so far rare. Hence, this paper aims to propose a proactive need awaring mechanism by applying agent, semantic web technologies and RFID-based context subsystem for a personalized reminder system which is one of the supporting systems for a robust ubiquitous service support environment. RescorlaWagner model is adopted as an underlying need awaring theory. We have created a prototype system called NAMA(Need Aware Multi-Agent)-RFID, to demonstrate the feasibility of the methodology and of the mobile settings framework that we propose in this paper. NAMA considers the context, user profile with preferences, and information about currently available services, to discover the user's current needs and then link the user to a set of services, which are implemented as web services. Moreover, to test if the proposed system works in terms of scalability, a simulation was performed and the results are described.
Collision Avoidance and Deadlock Resolution for AGVs in an Automated Container Terminal
Jaeho Kang, Lee Choi, Byoungho Kang, Kwang Ryel Ryu, and Kap Hwan Kim
Vol. 11, No. 3, Page: 25 ~ 43
Keywords : Automated Container Terminal, Automated Guided Vehicle (AGV), Collision Avoidance
Abstract
In modern automated container terminals, automated guided vehicle (AGV) systems are considered a viable option for the horizontal tansportation of containers between the stacking yard and the quayside cranes. AGVs in a container terminal move rather freely and do not follow fixed guide paths. For an efficient operation of such AGVs, however, a sophisticated traffic management system is required. Although the flexible routing scheme allows us to find the shortest possible routes for each of the AGVs, it may incur many coincidental encounters and path intersections of the AGVs, leading to collisions or deadlocks. However, the computational cost of perfect prediction and avoidance of deadlocks is prohibitively expensive for a real time application. In this paper, we propose a traffic control method that predicts and avoids some simple, but at the same time the most frequently occurring, cases of deadlocks between two AGVs. More complicated deadlock situations are not predicted ahead of time but detected and resolved after they occur. Our method is computationally cheap and readily applicable to real time applications. The efficiency and effectiveness of our proposed methods have been validated by simulation.
The Synchronization Method for Cooperative Control of Chaotic UAV
Young-Chul Bae
Vol. 11, No. 3, Page: 45 ~ 55
Keywords : Chaos UAV, Synchronization, Unstable Limit cycle
Abstract
In this paper, we propose a method to a synchronization of chaotic UAVs(Unmanned Aerial Vehicle) that have unstable limit cycles in a chaos trajectory surface. We assume all obstacles in the chaos trajectory surface have a Van der Pol equation with an unstable limit cycle. The proposed methods are assumed that if one of two chaotic UAVs receives the synchronization command, the other UAV also follows the same trajectory during the chaotic UAVs search on the arbitrary surface.
A Study on The Development Methodology for Intelligent College Road Map Advice System
Doug-Won Choi, Kyung-Pil Cho, and Jin-Gyu Shin
Vol. 11, No. 3, Page: 57 ~ 67
Keywords : Data mining, AHP, Factor Analysis
Abstract
Data mining techniques enable us to generate useful information for decision support from the data sources which are generated and accumulated in the process of routine organizational management activities. College administration system is a typical example that produces a warehouse of student records as each and every student enters a college and undertakes the curricular and extracurricular activities. So far, these data have been utilized to a very limited student service purposes, such as issuance of transcripts, graduation evaluation, GPA calculation, etc. In this paper, we utilized Holland career search test results, TOEIC score, course work list and GPA score as the input for data mining, and we were able to generate knowledge and rules with regard to the college road map advisory service. Factor analysis and AHP(Analytic Hierarchy Process) were the primary techniques deployed in the data mining process. Since these data mining techniques are very powerful in processing and discovering useful knowledge and information from large scale student databases, we can expect a highly sophisticated student advisory knowledge and services which may not be obtained from the human student advice experts.
Purchase Prediction Model using the Support Vector Machine
Hyunchul Ahn, Kyoung-jae Kim, and Ingoo Han
Vol. 11, No. 3, Page: 69 ~ 81
Keywords : Purchase prediction model, Support vector machines, Logistic regression, Customer relationship management
Abstract
As the competition in business becomes severe, companies are focusing their capacity on customer relationship management (CRM) for survival. One of the important issues in CRM is to build a purchase prediction model, which classifies customers into either purchasing or non-purchasing groups. Until now, various techniques for building purchase prediction models have been proposed. However, they have been criticized because their performances are generally low, or it requires much effort to build and maintain them. Thus, in this study, we propose the support vector machine (SVM) a tool for building a purchase prediction model. The SVM is known as the technique that not only produces accurate prediction results but also enables training with the small sample size. To validate the usefulness of SVM, we apply it and some of other comparative techniques to a real-world purchase prediction case. Experimental results show that SVM outperforms all the comparative models including logistic regression and artificial neural networks.
Design of Contact Scheduling System(CSS) for Customer Retention
Jae Sik Lee, and You Jung Cho
Vol. 11, No. 3, Page: 83 ~ 101
Keywords : Customer Relationship Management, Sequential Pattern Mining, Scheduling, Decision Tree
Abstract
Customer retention is one of the major issues in life insurance industry, in which competition is increasingly fierce. There are many things for the life insurers to do many things to retain the customers. One of those things is to make sure to keep in touch with all customers. When an insurance-planner resigned, his/her customers must be taken care of by some planner-assistants. This article outlines the design of Contact Scheduling System (CSS) that supports planner-assistants for contacting the customers. Planner-assistants are unable to share the resigned insurance-planner's experience and knowledge regarding the customer relationship management. The CSS developed by employing both Classification And Regression Tree (CART) technique and Sequential Pattern Mining (SPM) technique has a two-stage process. In the first stage, it segments the customers into eight groups by CART model. Then it generates contact scheduling information consisting of contact-purpose, contact-interval and contact-channel, according to the segment's typical contact pattern. Contact-purpose is derived by schedule-driven, event-driven, or business-rule-driven. Schedule-driven contact is determined by SPM model. In the operation of CSS in a realistic situation, it shows a practicality in supporting planner-assistants to keep in touch with the customers efficiently and effectively.
A Decision Model for BRE Introduction
Jung Eun Ju, and Sang Hoe Koo
Vol. 11, No. 3, Page: 103 ~ 115
Keywords : BRE(Business Rule Engine), IT Introduction Decision Model
Abstract
For today's enterprises to survive in the current rapidly changing business environments, it is imperative to make quick and successful decisions to various challenges. In making important business decisions, if enterprises utilize business rules and knowledge, properly and promptly, they may effectively reduce the chance of failures. However, in most of today's information systems, these rules and knowledge are not managed in centralized and systemic manner. They disperse over entire enterprises' information systems, and sometimes reside in the heads or memos of enterprises' employees. BRE (Business Rule Engines) is a solution that systematically and centrally manages these business knowledge and rules of an enterprise. With BREs, any business user is able to store, edit, retrieve and utilize business rules and knowledge in centralized repository, without IT development skills. And with BRE, enterprises could improve business intelligence and attain strategic advantages over other enterprises. However, since there is no clear criteria for BRE introductions, it is not easy to decide whether or not to introduce the expensive BRE solution to an enterprise. In this research we propose a decision model for BRE introduction. Using this model, business analysts considering BRE introduction, readily make decisions on BRE introduction.
Design of Middleware for Face Recognition based on WIPI Platform
Kyoung-Yul Bae
Vol. 11, No. 3, Page: 117 ~ 127
Keywords : Face Recognition, Face Detection, Mobile Middleware
Abstract
Proportionately with a rapid development of mobile instrument technology, the number of mobile contents utilizing computing environment's graphic technology or image processing is increasing. In this paper, I designed a middleware which supports facial detection and recognition system based WIPI(Wireless Internet Platform for Interoperability), the Korean standard mobile platform. The facial recognition middleware introduced the object oriented concepts, to apply to recognition security and other contents by using mobile camera. This can reduce the development time and cost by dividing process while developing software. Therefore, it would be applied to content security or technology transfer with other company. Facial recognition middleware system is composed of face detection module and face recognition module, and proposes the application contents design method based on WIPI platform.
Utilizing Distributed Ontology Repository in Multi-Agent System Environment
SungTae Kim, KyengWhan Jee, and JungJin Yang
Vol. 11, No. 3, Page: 129 ~ 139
Keywords : MAS, Ontology Repository, Web Services
Abstract
The rapid growth of IT technologies enables the quality of human's daily life to be improved dramatically, Contrasting to the services in previous computing environment directed by user's request, the services in ubiquitous computing era of new IT technology are provided through recognizing users intention and utilizing context-aware information suited to the user. According to the contextual information, agents need to set a dynamic goal to achieve and work collaboratively with other agents. Agents that take control over their behaviors with capability of communicating with other agents become a thrust in this up-coming computing environment. This work focuses on building ontologies, shared knowledge bases among agents, to improve semantical interoperability among agents. More attention is given to the construction and effective management of ontology repository along with its requirement and organization. Ontology agent suggested takes an initiative role to manage the repository in a distributed manner and to facilitate the use of ontology in a multi-agent environment.
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