• Journal of Fisheries and Marine Sciences Education
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• v.18 no.1
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• pp.31-38
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• 2006

Reaseach efforts regarding the handicap system for the fair determination of the ranking of yacht racing for various sizes have started in the end of 19th century led by Europe and America.The development of the handicap system started in 1952 as inshore and offshore races began. A simple empirical handicap system has been selected by IOR and IMS rule in mid 70's, and more advanced technique based on theoretical and computer simulation has been selected in late 70's by IMS rule. While each techniques have relative merits, it is found that the simple empirical handicap system is more effective than the advanced technique in term of reliability and easiness of use as more racing records are accumulated.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.891-906
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• 2014

This study suggests the hedging rule of MIP (Mixed Integer Programing) in counting the risk evaluation criteria of the objective function and constraints in order to provide the optimum operating rule in reservoir system as constraining water shortage as much as possible which may happen in the downstream control point of water supply in the aspect of water system management. The proposed model is applied to the Han-river reservoir system for two testing periods (Case I: Jan. 1993~Dec. 1997, Case II: Jan. 1999~Dec. 2003). The model based on the hedging rule with trigger volume, estimated in this study shows that in Case I, the monthly minimum discharge was $310.6{\times}10^6m^3$ in the single operation, $56.3{\times}10^6m^3$ in the joint operation, and $317.5{\times}10^6m^3$ in the hedging rule and also, in Case II, the monthly minimum discharge was found to be $204.2{\times}10^6m^3$ in the single operation, $111.2{\times}10^6m^3$ in the joint operation, and $243.7{\times}10^6m^3$ in the hedging rule. In conclusion, the hedging rule, proposed in this study can decrease vulnerability while guarantees reliability and resiliency.

• Journal of the Korea Society for Simulation
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• v.9 no.3
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• pp.27-41
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• 2000

As the application domains of rule-based systems become larger and more complicated, the integration of rule-based systems within the database systems has become the topic of many research works. This paper suggests a simulation modeling using expert system and database. The integration methods employed in this research are as follows. First, we defined new states and state transition functions to interrelate simulation model and expert system. Second, we designed and implemented FCL(Fact Class Library) as a interface of expert system and database. FCL has facilities of filtering data from database, and assigning a meaning to the filtered data. Also, FCL detects the violation of the integrity rules in database, as the result of inference is reflected. Some implementation problems are pointed out and the methods to solve these problems are discussed in this paper, We developed a simulation model of the grating production line and executed it to validate the functions of the proposed method.

• ETRI Journal
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• v.41 no.4
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• pp.515-527
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• 2019

This paper discusses the design, implementation, and potential use of an ontology-based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.

• Journal of the Korean Home Economics Association
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• v.40 no.11
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• pp.1-9
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• 2002

Nowadays, the use of apparel CAD system is important to the mass production of ready to wear Especially, computer-based grading is the most important process to improve the fitness of clothes and to reduce the time needed to make patterns of several sizes. The purpose of this study was to suggest a standard sizing system for junior-high school girls' lower clothes and to suggest a grading method according to the sizing systems. The subjects were 402 junior-high school girls of 13 to 15 year's-old. The size intervals of waist girth and hip girth were 3㎝ and 4㎝ respectively. The sizing system, which had frequencies more than 4.5%, was classified 8 cases. For regular grading, two types of group were classified into 58-82/61-86/64-90/67-94 and 61-82/64-86/67-90/70-94. Among them, 61-86 and 64-86 size were adopted the basic size for the development of grading. According to the sizing system, hand-made patterns were manufactured. By measure of the each part of the slacks, new grading rule patterns were developed by each size. A new grading rule was different from the Moonwha grading rule. This result will contribute to clothing fitness of consumer and the amount of production.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.129-136
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• 2023

In this paper, we describe a rule-based risk classification algorithm to perform Risk-based Inspection (RBI) on imported goods at customs. The RBI system is a method to automatically select which cargos have to be inspected and manage potential risks in boarder. In this study, we designed a rule-based risk classification algorithm for RBI solutions and implemented them using the Svelte web application framework. The risk classification algorithm proposed in this paper uses different indicative risk factors such as HS code, country of origin, importer's reliability, trade relationships, and logistics routes to classify cargos into Green, Yellow, and Red channels. To achieve this, we assigned risk categories to each risk factor and randomly generated risk scores within a specific range for each risk category. This system is expected to contribute to the increased efficiency of customs operations and protect public safety by minimizing the risk of imported hazardous materials.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.225-232
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• 2023

With the recent increase of multiple robots cooperating in smart manufacturing logistics environments, it has become very important how to predict the safety and efficiency of the individual tasks and dynamically assign them to the best one of available robots. In this paper, we propose a novel task policy learner based on deep relational reinforcement learning for predicting the safety and efficiency of tasks in a multi-robot manufacturing logistics environment. To reduce learning complexity, the proposed system divides the entire safety/efficiency prediction process into two distinct steps: the policy parameter estimation and the rule-based policy inference. It also makes full use of domain-specific knowledge for policy rule learning. Through experiments conducted with virtual dynamic manufacturing logistics environments using NVIDIA's Isaac simulator, we show the effectiveness and superiority of the proposed system.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.15-27
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• 2000

The paper proposes a hybrid fire fighting control intelligent system(H-FFIS) using rules and cases to detect fire in Integrated Platform Management System. By far most conventional systems have been based on rule-based system in which expert knowledges are expressed with production rules. It is hard to express the knowledges to detect fire with production rules only. The knowledges of fire detection are often based on previously encountered situations of fires. For improvement of system capability renewing and adding of rules is needed in an already build-up system and such adding and renewing procedures could hinder users from fluent utilization of the system. We design and implement H-FFIS. Compared with rule-based FFIS(Fire Fighting control Intelligent System), H-FFIS extended with case-based reasoning shows that the system proposed here can lead to an improvement in fire detection rate.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.35-44
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• 2015

The purpose of this study is to analyze user-generated rules in online games and to define the way of players' identities are developed. This study focuses on the online game League of Legends, which originated from use map system. Based on rule theory, this study analyzes the characteristics of user-generated rules. As the result, this study proves that the main rule of online game is not the rules made by developers, but the emergent rules made by players. Through rule-detection and rule-selection process, user-generated rules change the game system. Therefore, the result of this study expects to show meaningful roles of players in game system.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.246-250
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• 2005

Recommand Systems are being used by an ever-increasing number of E-Commerce to help customers find products to purchase. Recommend Systems offer a technology that allows personalized recommendations of items of potential interest to users based on information about similarities and dissimilarities among different customers tastes. In this paper, we design and build a Recommend System using the historical customer movie purchase transactions and extracts the knowledge needed to make association recommendations to new customers.