• East Asian mathematical journal
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• v.35 no.5
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• pp.597-612
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• 2019

In this study, we propose a new logarithmic barrier approach to solve linear programming problem using the projective method of Karmarkar. We are interested in computation of the direction by Newton's method and of the step-size using minorant functions instead of line search methods in order to reduce the computation cost. Our new approach is even more beneficial than classical line search methods. We reinforce our purpose by many interesting numerical simulations proved the effectiveness of the algorithm developed in this work.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.857-862
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• 2004

This paper analyzes properties of the recently developed nonlinear optimization method, Dynamic Encoding Algorithm for Searches (DEAS) [1]. DEAS locates local minima with binary strings (or binary matrices for multi-dimensional problems) by iterating the two operators; bisectional search (BSS) and unidirectional search (UDS). BSS increases binary strings by one digit (i.e., zero or one), while UDS performs increment or decrement to binary strings with no change of string length. Owing to these search routines, DEAS retains the optimization capability that combines the special features of several conventional optimization methods. In this paper, a special feature of BSS and UDS in DEAS is analyzed. In addition, a effective global search strategy is established by using information of DEAS. Effectiveness of the proposed global search strategy is validated through the well-known benchmark functions.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1011-1014
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• 1999

In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.21-36
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• 2009

As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.

• Journal of the Korean Society for Library and Information Science
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• v.17
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• pp.299-337
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• 1989

In this study, an Intermediary System for Searches has been designed and implemented. This System has some key functions as follows: First, in each stage of a search process, the information related to a definite term could be provided. Second, through displaying semantic categories for terms this system 'helps a searcher in modifying search terms when he fails to retrieve. Third, being consulted, this system could assist a searcher in making a Boolean search statement in terms of search specificity Fourth, to make a final search statement, a searcher could have several rounds of search cycles through displaying related terms, semantic categories, and frames.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.127-135
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• 1999

Multivarialbe Boiler-Turbine H_\infty Control System Genetic Algorithm Weighting Functions $W_1$(s), $W_2$(s), and design parameter $\gamma$ that are given by Glover-Doyle algorithm, to optimally follow the output of reference model. The first method to do this is that the gains of weighting functions $W_1$(s), $W_2$(s), and design parameter are optimized simultaneously by genetic algorithm with the tournament method that can search more diversely, in the search domain which guarantees the robust stability of system. And the second method is that not only by genetic algorithm with the roulette-wheel method that can search more fast, in that search domain. The boiler-turbine H_\infty control system designed by theabove second method has not only the robust stability to a modeling error but also the the better command tracking preformance than those of the H_\infty control system designed by trial-and-error method and the above first method. Also, this boiler-turbine H_\infty control system has the better performance than that of the LQG/LTR contro lsystem. The effectiveness of this boiler-turbineH_\infty control system is verified by computer simulation.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.829-839
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• 2004

Methods based on integer programming have been shown to be very effective in solving various crew pairing optimization problems. However, their applicability is limited to problems with linear constraints and objective functions. Also, those methods often require an unacceptable amount of time and/or memory resources given problems of larger scale. Heuristic methods such as neighborhood search, on the other hand, can handle large-scaled problems without too much difficulty and can be applied to problems having any form of objective functions and constraints. However, neighborhood search often gets stuck at local optima when faced with complex search spaces. This paper presents ,i hybrid algorithm of neighborhood search and integer programming, which nicely combines the advantages of both methods. The hybrid algorithm has been successfully tested on a large-scaled crew pairing optimization problem for a real subway line.

• Sleep Medicine and Psychophysiology
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• v.2 no.2
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• pp.105-114
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• 1995

Schiophrenia is characterized by a variety of cognitive dysfunctions. A number of research findings suggest that schizophrenic patients have global deficits in cognitive functions, such as attention, memory, executive functions, and motor functions. These cognitive deficits, once they arise, tend to become relatively stable. In spite of much efforts to search for the cognitive dysfunctions in schizophrenia, there are no specific deficits or localizations found. It is necessary that future neuropsychological research of schizophrenia should include relationships between symptoms and cognitive dysfunctions and their relationships to treatment.

• The Journal of Fisheries Business Administration
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• v.35 no.1
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• pp.57-85
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• 2004

To develop an blue tourism website(BTW) for electronic commerce(EC), information requirements of BTW are defined firstly. We defined information requirements of BTW from two aspects, i.e., front office and back office. Information requirements for front office were derived by consumer purchasing decision process. And information requirements for back office were derived by tourism value chain. Total 29 functions are identified as critical EC related functions of BTW. Among them, 25 functions were investigated into BTW. BTWs were searched by search engines - Yahoo and Empas - to Korean websites. There are 12 specialized BTWs, except one cyber museum website. For 12 websites, 25 functions were probed. By the results, in need recognition stage of blue tourism, only weather information was provided in most websites. In information search stage of blue tourism, package recommendation and various contents were provided in most websites. In consumption stage of blue tourism, traffic information were provided in most websites. And in after - sales service stage of blue tourism, bulletin board function was implemented in most websites. The rest of the functions were scarcely implemented. On the whole, it was concluded that most EC related functions of BTW in Korea were not implemented properly. To improve the status quo, it is expected in the dimension of individual website, that marketing planning, customized service, intelligent service, reinforcing purchasing assistance functions, customer relationship management, and escrow service etc. need to be implemented. And it is expected in the dimension of blue tourism industry, that standardizing product catalog, security assistance policy, information sharing by industrial database, finding referral model of BTW, elevating information mind, revising related laws etc. are needed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.235-238
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• 1996

In this paper, a new optimization method which is a kind of random searching is presented. The proposed method is called RasVal which is an abbreviation of Random Search Method with Variable Seaxch Length and it can search for a global minimum based on the probability density functions of searching, which can be modified using informations on success or failure of the past searching in order to execute intensified and diversified searching. By applying the proposed method to a nonlinear crane control system which can be controlled by the Universal Learning Network with radial basis function(R.B.P.), it has been proved that RasVal is superior in performance to the commonly used back propagation learning algorithm.