• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.425-428
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• 2004

Flexible assembly line (FAL) is a production system that assembles various parts in unidirectional flow line with many constraints and manufacturing flexibilities. In this research we deal with a FAL balancing problem with the objective of minimizing the maximum workload allocated to the stations. However, almost all the existing researches do not appropriately consider various constraints due to the problem complexity. Therefore, this thesis addresses a balancing problem of FAL with many constraints and manufacturing flexibilities, unlike the previous researches. To solve this problem we use a genetic algorithm (GA). To apply GA to FAL, we suggest a genetic representation suitable for FAL balancing and devise evaluation method for individual's fitness and genetic operators specific to the problem, including efficient repair method for preserving solution feasibility. The experimental results are reported.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.301-311
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• 2000

For effective part modifications which is necessary in the design process frequently, variational geometric modeling with constraint management being used in a wide. Most variational geometric modeling methods, however, manage just the constraints about sketch elements used for generation of primitives. Thus, not only constraint propagation but also re-build of various modeling operations stored in the modeling history is necessary iota part geometry modifications. Especially, re-build of high-cost Boolean operations is apt to deteriorate overall modeling efficiency abruptly. Therefore, in this paper we proposed an algorithm that can handle all geometric entities of the part directly. For this purpose, we introduced eight type geometric constraints to the various geometric calculations about all geometric entities in sweepings and Boolean operations as well as the existing constraints of the sketch elements. The algorithm has a merit of rapid part geometric modifications through only constraint propagation without rebuild of modeling operations which are necessary in the existing variational geometric modeling method.

• English Language & Literature Teaching
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• v.9 no.1
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• pp.23-48
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• 2003

This paper provides an analysis of the linear constituent order of the NP in three different types of languages based on 33 languages: the NP with the prenominal modifiers, the NP with the postnominal modifiers, and the NP with both prenominal and postnominal modifiers (the mixed NP). Languages have NPs that feature different linear order, of the NP constituents. We attribute such different linear constituent orders within the NP to the linguistic distance and the limits imposed by the constituency and adjacency. We use the various kinds of alignment constraints which properly reflect the linguistic distance between the noun and each constituent. Language universals on word order provide us some general orders of various NP constituents. If we adopt the linguistic distance, the limits imposed by the constituency and the adjacency, and the alignment constraints, we can explain the complicated differences of NP constituent orders of languages of the world.

• Journal of KIISE:Software and Applications
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• v.29 no.10
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• pp.755-765
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• 2002

In this paper, we observe various syntactic information for Korean parsing and propose a method to learn constraints and improve the efficiency of a parsing model by using the constraints. The proposed method has the following three characteristics. First, it improves the parsing efficiency since we use constraints that can prevent the parser from generating unsuitable candidates. Second, it is robust on a given Korean sentence because the attributes for the constraints are selected based on the syntactic and lexical idiosyncrasy of Korean. Third, it is easy to acquire constraints automatically from a treebank by using a decision tree learning algorithm. The experimental results show that the parser using acquired constraints can reduce the number of overgenerated candidates up to 1/2~1/3 of candidates and it runs 2~3 times faster than the one without any constraints.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.1-14
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• 2015

To conform to new emerging computing paradigm, various researches and challenges are being done. New information technologies make easy to access and acquire information in various ways. In other side, however, it also makes illegal access more powerful and various threat to system security. In this paper, we suggest a new extended access control method that make it possible to conform to security policies enforcement even with discrepancy between policy based constraints rules and query based constraints rules, based on their semantic information. New method is to derive security policy rules using context tree structure and to control the exceed granting of privileges through the degree of the semantic discrepancy. In addition, we illustrate prototype system architecture and make performance comparison with existing access control methods.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.654-661
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• 2015

Stairs are the most popular obstacles in buildings and factories. To enlarge the application areas of a field robotic platform, stair-climbing is very important mission. One important reason why a stair-climbing is difficult is that stairs are various in sizes. To achieve autonomous climbing of various-sized stairs, dynamic modeling is essential. In this research, an inverse dynamic modeling is performed to enable an autonomous stair climbing. Stair-climbing robotic platform with flip locomotion, named FilpBot, is analyzed. The FlipBot platform has advantages of robust stair-climbing of various sizes with constant speed, but the autonomous operation is not yet capable. Based on external constraints and the postures of the robot, inverse dynamic models are derived. The models are switched by the constraints and postures to analyze the continuous motion during stair-climbing. The constraints are changed according to the stair size, therefore the analysis results are different each other. The results of the inverse dynamic modeling are going to be used in motor design and autonomous control of the robotic platform.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.156-161
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• 1997

In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.141-153
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• 2017

A binary integer programming model is proposed for a complex timetabling problem in a university faculty which conducts various degree programs. The decision variables are defined with fewer dimensions to economize the model size of large scale problems and to improve modeling efficiency. Binary matrices are used to incorporate the relationships between the courses and students, and the courses and teachers. The model includes generally applicable constraints such as completeness, uniqueness, and consecutiveness; and case specific constraints. The model was coded and solved using Open Solver which is an open-source optimizer available as an Excel add-in. The results indicate that complicated timetabling problems with large numbers of courses and student groups can be formulated more efficiently with fewer numbers of variables and constraints using the proposed modeling framework. The model could effectively generate timetables with a significantly lower number of work hours per week compared to currently used timetables. The model results indicate that the particular timetabling problem is bounded by the student overlaps, and both human and physical resource constraints are insignificant.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1114-1116
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• 1999

This paper presents a new algorithm which evaluates production cost and reliability indices under various constraints of the thermal generation system. In order to consider the operational constraints of thermal units effectively, the proposed algorithm is based on Monte Carlo techniques instead of analytical ones which have difficulty in modelling the units with additional constraints. At that point, generating units are modelled into two types, base load units and peaking units. These generating unit models are used in state duration sampling simulation for which approach can readily consider the peaking unit operating cycles and easily calculates frequency-duration indices. The proposed production simulation algorithm is applied to the IEEE Reliability Test System, and performs the production simulation under the given constraints. The results show that the proposed algorithm is accurate, reliable and useful.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.951-956
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• 1990

The present paper describes a new technique for associating images employing a set of local constraints among pixels on an image. The technique describes the association problem in terms of consistent labeling which is an abstraction of various kinds of network constraints problems. In this particular research, a pixel and its gray value correspond to a unit and a label, respectively. Since constraints among units on an image are defined with respect to each n-tuple of pixels, performance of the present association technique largely depends on how to choose the n-tuples on an image plane. The main part of this paper is devoted to discussing this selection scheme and giving a solution to it as well as showing the algorithm of association. Also given are some results of the simulation performed on synthetic binary images to examine the performance of proposed technique, followed by the argument on further studies.