• Asia pacific journal of information systems
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• 제8권3호
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• pp.51-73
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• 1998

This paper is to evaluate the application potentials of data mining in the areas of Supply Chain Management (SCM) and to suggest the architectures of Decision Support Systems (DSS) that support data mining activities. We first briefly introduce data mining and review the recent literatures on SCM and then evaluate data mining applications to SCM in three aspects: marketing, operations management and information systems. By analyzing the cases about pricing models in distribution channels, demand forecasting and quality control, it is shown that artificial intelligence techniques such as artificial neural networks, case-based reasoning and expert systems, combined with traditional analysis models, effectively mine the useful knowledge from the large volume of SCM data. Agent-based information system is addressed as an important architecture that enables the pursuit of global optimization of SCM through communication and information sharing among supply chain constituents without loss of their characteristics and independence. We expect that the suggested architectures of intelligent DSS provide the basis in developing information systems for SCM to improve the quality of organizational decisions.

• 수면정신생리
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• 제17권2호
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• pp.63-68
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• 2010

Narcolepsy is a central neurologic system disease. It begins early in life with disabling symptoms including excessive daytime sleepiness, cataplexy, sleep paralysis, hypnagogic hallucination and nocturnal sleep fragmentation. Patient with typical symptoms of narcolepsy is diagnosed by objective data from nocturnal polysomnography and multiple sleep latency tests. Narcolepsy is controlled with various medications. Nowadays, modafinil with favorable side effects profiles compared with traditional stimulant is mainly used. Gamma hydroxyl butyrate is effective in cataplexy. Cataplexy is also controlled with antidepressant such as Venlafaxine, SSRI, and TCA. As the knowledge of pathophysiology of narcolepsy expands, new treatment including immunological method, application of hypocretin and histamine systems have been tried.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.714-716
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• 1995

This Paper presents a novel and systematic approach to a self-learning controller. The proposed controller is built on a neural network consisting of a standard back propagation (BNN) and approxinate reasoning (AR). The fuzzy inference and knowledge representation are carried out by the neural network structure and computing, instead of logic inference. An architecture similar to that used by traditional model reference adaptive control system (MRAC) is employed.

• Korean Journal of Acupuncture
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• 제26권4호
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• pp.157-172
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• 2009

Objective : The purpose of this study is to review and summarize the research on a burn. Methods : We reviewed 16 studies about burn which were relative to oriental medicine. We selected those studies from Korean studies Information Service System and Korean Traditional Knowledge Portal. Result : Selected 16 studies were divided into 12 trial articles, 3 case reports and 1 review article. Most of studies reported that oriental medical treatment of burn were effective. Conclusion : Further studies needed for burn and more clinical data would be needed to prove the effects of oriental medical treatment in burn.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권9호
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• pp.1653-1667
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• 2011

Privacy is one of the most important and difficult research issues in ubiquitous computing. It is qualitative rather than quantitative. Privacy preserving mainly relies on policy based rules of the system, and users cannot adjust their privacy disclosure rules dynamically based on their wishes. To make users understand and control their privacy measurement, we present a scheme to quantize the personal privacy. We aim to configure the person's privacy based on the numerical privacy level which can be dynamically adjusted. Instead of using the traditional simple rule engine, we implement this scheme in a complex way. In addition, we design the scenario to explain the implementation of our scheme. To the best of our knowledge, we are the first to assess personal privacy numerically to achieve precision privacy computing. The privacy measurement and disclosure model will be refined in the future work.

• Computers and Concrete
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• 제24권3호
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• pp.271-282
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• 2019

Concrete undergoes a series of thermo-based physio-chemical changes once exposed to elevated temperatures. Such changes adversely alter the composition of concrete and oftentimes lead to fire-induced explosive spalling. Spalling is a multidimensional, complex and most of all sophisticated phenomenon with the potential to cause significant damage to fire-exposed concrete structures. Despite past and recent research efforts, we continue to be short of a systematic methodology that is able of accurately assessing the tendency of concrete to spall under fire conditions. In order to bridge this knowledge gap, this study explores integrating novel artificial intelligence (AI) techniques; namely, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA), together with traditional statistical analysis (multilinear regression (MLR)), to arrive at state-of-the-art procedures to predict occurrence of fire-induced spalling. Through a comprehensive datadriven examination of actual fire tests, this study demonstrates that AI techniques provide attractive tools capable of predicting fire-induced spalling phenomenon with high precision.

• 산업공학
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• 제15권4호
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• pp.444-451
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• 2002

Recently, the interest in technology valuation is revived and increasing mainly due to the lack of suitability of the traditional valuation methods in explaining the market reaction to newly-emerging knowledge-oriented companies. Moreover, many firms are now gearing their efforts to the strategic use of technology asset such as technology licensing, transfer and commercialization. Firms are also trying to enhance their technological competitiveness by re-evaluating their technology level and thus identifying the strengths/weaknesses of their technology portfolio. To accomplish this objective, the development of an integrated evaluation system for technology assets is essential. This paper presents a technology valuation system developed for a steel manufacturing company in South Korea. The valuation framework is based on; (1) the multi-attribute evaluation of technological competitiveness using Analytic Hierarchical Process and; (2) the expected future benefit of the technology using four different methods of discounted cash flow estimation. The suggested framework will be easily applicable to various industries where technological competitiveness should be evaluated systematically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권11호
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• pp.3008-3025
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• 2012

In this paper, the downlink resource allocation of OFDMA system with decode-and-forward (DF) relaying is investigated. A non-convex optimization problem maximizing system throughput with users' satisfaction constraints is formulated with joint relay selection, subcarrier assignment and power allocation. We first transform it to a standard convex problem and then solve it by dual decomposition. In particular, an Optimal resource allocation scheme With Time-sharing (OWT) is proposed with combination of relay selection, subcarrier allocation and power control. Due to its poor adaption to the fast-varying environment, an improved version with subcarrier Monopolization (OWM) is put forward, whose performance promotes about 20% compared with that of OWT in the fast-varying vehicular environment. In fact, OWM is the special case of OWT with binary time-sharing factor and OWT can be seen as the tight upper bound of the OWM. To the best of our knowledge, such algorithms and their relation have not been accurately investigated in cooperative OFDMA networks in the literature. Simulation results show that both the system throughput and the users' satisfaction of the proposed algorithms outperform the traditional ones.

• 정보관리학회지
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• 제23권2호
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• pp.147-165
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• 2006

웹기반 교육 자료들이 폭발적으로 증가함에 따라 적합한 자료들에 보다 효과적으로 접근할 수 있는 방법이 요구되고 있다. 이러한 새로운 방법들 중의 하나로 사회적 네비게이션(social navigation) 기반의 사회적 검색(social searching)이 정보 검색 분야에서 제시되었는데, 이는 동료 이용자들로부터 제공된 정보를 바탕으로 검색 결과의 향상을 추구하는 기법이다. 본 연구에서는 개인화와 사회적 네비게이션에 근거한 웹 기반 사회적 검색 시스템을 구축하였으며 이용자 연구를 통해 이용자에게 적합하고 필수적인 정보를 제공할 수 있는 방법이라는 것을 검증하려 하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.7-12
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• 2005

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper. The expert system which introduces fuzzy logic in order to process uncertainties is called fuzzy expert system. The fuzzy expert system, however, has a potential problem which may lead to inappropriate results due to the ignorance of some information by applying fuzzy logic in reasoning process in addition to the knowledge acquisition problem. In order to overcome these problems, We construct fuzzy inference network by extending the concept of reasoning network in this paper. In the fuzzy inference network, the propositions which form fuzzy rules are represented by nodes. And these nodes have the truth values representing the belief values of each proposition. The logical operators between propositions of rules are represented by links. And the traditional propagation rule is modified.