• Korea Trade Review
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• v.44 no.6
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• pp.1-21
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• 2019

In the case of a sea transport contract, the decision of the governing law, together with the choice of lex fori, shall be a legal issue in all legal disputes involving damage to the goods. In sea transport contracts, a paramount clause is often established in conjunction with the governing law clause, which can lead to conflict between these two clauses. Most B/L's back clauses contain a paramount clause that provides that the Hague Rules, Hague-Visby Rules, or foreign laws that prevail over other provisions of the terms. The Hague Rules and the Hague-Visby Rules, however, set different standards regarding the extent of the sea carrier's liability. Therefore, in the interpretation of ground conditions, it is an important question whether the Hague Rules or the Hague-Visby Rules are applied or whether each rule is applied as a law. For example, the paramount clause in the Superior Pescadores case was problematic in the interpretation of the term 'Hague Rules.' In this case, the English Court held that the expression 'Hague Rules' could be used to mean the Hague-Visby Rules, and not exclusively the Hague Rules. Therefore, the Hague-Visby Rules were applied in the judgment of this case, which suggests that this case can be a valuable precedent in future legal matters.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• The KIPS Transactions:PartB
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• v.17B no.4
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• pp.317-326
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• 2010

To improve the diagnosis and prescription for military personnel, it is required to adopt Clinical Decision Support System (CDSS) in armed forces hospitals. The objective of this paper is to suggest a CDSS for armed forces hospitals using semantic web technologies. To this end, we designed military medical ontologies and military medical rules which consist of the various concepts and rules for supporting medical activities. We developed a semantic web-based CDSS to demonstrate the use of the ontologies and rules for treating military patients. We also showed the process of semantic search for the medical records which are created from the semantic web-based CDSS.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.1-23
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• 2004

This study identifies communication patterns of groups using synchronous text communication medium for their group decision-making, and examines how these patterns are associated with creative solutions to problems. Our research suggests that certain communication behavior of groups, when appropriately organized, can be of help in enhancing creative production of outcomes. A qualitative study was conducted on communication patterns based on an analysis of text-based electronic conversation protocols. Specifically this research tried to overcome existing studies on electronic groups by focusing on interactive process of communication among participants. The major study conclusion; are: (1) The production of creative outcome may depend on the process or sequence of discussion among group members with synchronous text communication medium. That is, proper interactive responses and appropriate control of the discussion process are essential to obtain a high level of performance. (2) It is importantto make discuss rules based on meta-cognitive and interactive protocols in the early stage. Explicit rules relating to internal group processes as well as communication medium use are even more important to groups with electronic communication medium than face-to-face groups.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.10-19
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• 2013

Dispatching rule plays an important role in a hybrid flow shop. Finding the appropriate dispatching rule becomes more challenging when there are multiple criteria, uncertain demands, and dynamic manufacturing environment. Using a single dispatching rule for the whole shop or a set of rules based on a single criterion is not sufficient. Therefore, a multi-criteria decision making technique using 'the order preference by similarity to ideal solution' (TOPSIS) and 'analytic hierarchy process' (AHP) is presented. The proposed technique is aimed to find the most suitable set of dispatching rules under different manufacturing scenarios. A simulation based case study on a PCB manufacturing process is presented to illustrate the procedure and effectiveness of the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.263-266
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• 1995

Comtputer Aided Process Planning(CAPP) has been emerged as playing a key role in Computer Integrated Manufactunng(CIM) as the most critical link to integrate CAD and CAM. A modified variant CAPP system based on process planning rule base is developed in this paper. This CAPP system generates process plans automatically according to the GT code data provided as input. In order to execute process planning, various process planning rules are constructed in the form of decision tree and the inference engine that extracts the process plan based on the tree-structured rules are implemented.

• The Journal of Information Systems
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• v.14 no.2
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• pp.55-74
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• 2005

In order to purchase a product cheaper, a lot of customers have been trying to search one or more marketplaces. Ever since the commercial use of the Internet, several types of marketplaces have been operating successfully on the Internet. Some of them are online shopping malls, auction markets, and group-buying markets. They have the price settlement mechanisms of their own. Online shopping malls where many stores are located support a customer to purchase the product that matches his/her requests such as price, function, design, and so forth. In online auction market, a customer can buy the product by making bids sequentially and competitively until a final price is reached. In online group-buying market, a customer can purchase the product by aggregating the orders from several buyers so that cheaper prices can be negotiated. The cheaper customers could purchase the same product item, the more satisfied they would be. However, it is very difficult for the customer to determine the marketplace to purchase, considering different kinds of marketplaces at the same time. Even though the purchasing price is cheapest in one marketplace, it is very difficult for customers to convince it the cheapest for all marketplaces. Therefore, rules and methods have been developed for purchase decision making in multiple marketplaces to reach the optimal purchase decision as a whole. They can maximize customer's utility and resolve the conflicts with other marketplaces through multi-agent negotiation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.94-100
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• 2010

Data Mining is mainly used for pattern extracting and information discovery from collected data. However previous methods is difficult to reflect changing patterns with time. In this paper, we introduce Streaming Decision Tree(SDT) analyzing data with continuity, large scale, and changed patterns. SDT defines continuity data as blocks and extracts rules using a Decision Tree's learning method. The extracted rules are combined considering time of occurrence, frequency, and contradiction. In experiment, we applied time series data and confirmed resonable result.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.63-74
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• 1991

An expert scheduling system on real time basis for computer-aided manufacturing systems has been developed. In developing expert scheduling system, the most time-consuming job is to obtain rules from expert schedulers. An efficient process of obtaining rules directly form the schedules produced by expert schedulers is proposed. By the process, a set of complete and minimal set of rules is obtained. During a real time scheduling, when given information on possible values of elements, the rules produce possible values of decision elements, where logical explanations of the result may be offered in terms of chaining rules. The learning and scheduling processes have been simulated with an automated manufacturing line engaged in the production of circuit boards.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.27-36
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• 2000

The problem of discovering association rules is an emerging research area, whose goal is to extract significant patterns or interesting rules from large databases and several algorithms for mining association rules have been applied to item-oriented sales transaction databases. Data warehouses and OLAP engines are expected to be widely available. OLAP and data mining are complementary; both are important parts of exploiting data. Our study shows that data cube is an efficient structure for mining association rules. OLAP databases are expected to be a major platform for data mining in the future. In this paper, we present an efficient and effective algorithm for mining association rules using data cube. The algorithm can be applicable to enhance the power of competitiveness of business organizations by providing rapid decision support and efficient database marketing through customer segmentation.