• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.23-32
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• 2017

We can obtain useful knowledge from data by using a subgroup discovery algorithm. Subgroup discovery is a rule model learning method that finds data subgroups containing specific information from data and expresses them in a rule form. Subgroups are meaningful as they account for a high percentage of total data and tend to differ significantly from the overall data. Subgroup is expressed with conjunction of only literals previously. So, the scope of the rules that can be derived from the learning process is limited. In this paper, we propose a method to increase expressiveness of rules through internal disjunctive representation of attribute values. Also, we analyze the characteristics of existing subgroup discovery algorithms and propose an improved algorithm that complements their defects and takes advantage of them. Experiments are conducted with the traffic accident data given from Busan metropolitan city. The results shows that performance of the proposed method is better than that of existing methods. Rule set learned by proposed method has interesting and general rules more.

• International Commerce and Information Review
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• v.13 no.3
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• pp.143-166
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• 2011

This paper describes the characteristics and outline of rules of origin among Korea and USA, EU, ASEAN. The main focus of this paper is to conduct comparative analysis on rules of origin. Rules of origin are used to determine the country of origin of a product for purposes of international trade. There are two common types of rules of origin depending upon application, the preferential and non-preferential rules of origin Non-preferential rules of origin are used to determine the country of origin for certain purposes. The basis for the non-preferential rules originates from the Kyoto convention which states that if a product is wholly obtained or produced completely within one country the product shall be deemed having origin in that country. For a product which has been produced in more than one country, the product shall be determined to have origin in the country where the last substantial transformation took place. To determine exactly what was the last substantial transformation, three general rules are applied : Change of tariff classification(on any level, though 4-digit level is the most common), Value added-rule.(ad-valorem), and Specific process rule. While criteria of wholly obtained or produced in one country is almost similar to those of theses area and countries, in compliance with value percentages of Substantial Transformation, sufficient working or processing, Korea-US FTA adapts 'Regional Value Content', meanwhile Korea-EU FTA adapts 'Import Content' rule. Finally, Korea-US FTA and ASEAN FTA adapt FOB price for the calculation value added, on the other hand Korea-EU FTA adapts EXW price.

• Proceedings of the KWS Conference
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• 2002.05a
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• pp.68-70
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• 2002

A CCD camera with a laser strip was applied to realize the automation of welding process in GMAW. The Hough transformation was used to extract the laser stripe and to obtain specific weld points. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• 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.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.180-183
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• 2001

Glass fiber reinforced plastic(CFHP) tent pole fabricated by the pultrusion process with unidirectional glass fiber is two times as heavy as aluminum tent pole owing to the low specific modulus The first objective of this research is the design the high strength and light weight tent pole compete with. the second is the develope glass fiber carbon fiber hybrid tent pole pultrusion process. the third is the evaluate the mechanical properties of the hybrid tent pole compare to these of the duralumin tent pole.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.84-91
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• 2004

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc tight. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.9
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• pp.850-863
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• 2008

Business Process is a set of interrelated business functions, which are defined by various business process rule and that will lead a company to accomplishing a specific organizational goal. Many business organizations are using process modeling methods for their business process management, but mostly these methods are accomplished by Human-Based activities. These human-based activities cause unexpected design anomalies in modeling phase. If process engine executed without design anomalies detection, that will be lead to huge loss on costs. To ensure that there is no design anomalies in modeling phase and to detect anomalies of predefined actions within modeling tools are important issues in business process management. In this paper, we provide specific types of design anomalies, which can effectively use to detect design anomalies in business process modeling phase.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.823-835
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• 2019

Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.12
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• pp.2252-2260
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• 1992

This paper deals with development of expert process planning system which automatically generates process plan for manufacturing parts of injection mold. The specific domain of study is two-plate injection mold without support plate. Decision making rules for selection of machining processes machine tools, cutting tools and for determination of sequence of machining operations are acquired by interview of skilled process planner. The developed expert process planning system is programmed by using expert system shell CLIPS on the IBM PC/AT. The proposed system works well to real problems.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.1
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• pp.105-115
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• 1991

This paper describes an integrated CAD and CAPP system for prismatic parts of injection mold which generates a complete process plan automatically from CAD data of a part without human intervention. This system employs Auto CAD as a CAD model and GS-CAPP as an automatic process planning system for injection mold. The proposed CAD/CAPP system consists of three modules such as CAD data conversion module, manufacturing feature recognition module, and CAD/CAPP interface module. CAD data conversion module transforms design data of AutoCAD into three dimensional part data. Manufacturing feature recognition module extracts specific manufacturing features of a part using feature recognition rule base. Each feature can be recognized by combining geometry, position and size of the feature. CAD/CAPP interface module links manufacturing feature codes and other head data to automatic process planning system. The CAD/CAPP system can improve the efficiency of process planning activities and reduce the time required for process planning. This system can provide a basis for the development of part feature based design by analyzing manufacturing features.