• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.49-58
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• 2006

When the movement of a node breaks the route in ad-hoc network, on-demand routing protocol performs the local route recovery or a new route search for the route maintenance. And when it performs the new route search or the local search, the packet which is transmitted can be delayed. There are ARMP and RPAODV as the methods reducing the delay resulted from the route-breakage. They predict the route-breakage and construct an alterative local route before the occurrence of the route-breakage. When the link state is unstable, the success rate of the alternative local route that can avoid the route-breakage can give a direct effect on the route-breakage and the transmission delay, To estimate the performance of routing protocols avoiding route-breakage, we suggest the numerical formulas of AODV, the representative on-demand routing protocol, and ARMP, RPAODV. To verify the efficiency and accuracy of the proposed numerical formulas, we analysis and compare with the results of the computer simulation and that of the numerical formulas.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.1
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• pp.117-127
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• 2008

The performance of a modified Armijo line search rule related to BFGS gradient type method with the results from other well-known line search rules are compared as well as analyzed. Although the modified Armijo rule does require as much computational cost as the other rules, it shows more efficient in finding local minima of unconstrained optimization problems. The sensitivity of the parameters used in the line search rules is also analyzed. The results obtained by implementing algorithms in Matlab for the test problems in [3] are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.101.4-101
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• 2001

Evolutionary algorithm has been receiving a remarkable attention due to the model-free and population-based parallel search attributes and much successful results are coming out. However, there are some problems in most of the evolutionary algorithms. The critical one is that it takes much time or large generations to search the global optimum in case of the objective function with multimodality. Another problem is that it usually cannot search all the local optima because it pays great attention to the search of the global optimum. In addition, if the objective function has several global optima, it may be very difficult to search all the global optima due to the global characteristics of the selection methods. To cope with these problems, at first we propose a preprocessing process, grid-filtering algorithm(GFA), and propose a new distributed evolutionary ...

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.100-102
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• 2001

본 논문에서는 방대한 양의 정보를 관리하고 검색하기 위한 데이터베이스와 검색엔진을 사용하지 않고 정보를 효율적으로 처리할 수 있는 XML 기반의 Local 검색 시스템을 설계하고 구현한다. CD-ROM이나 하드디스크와 같은 보조기억장치에 저장되어 있는 문서 파일을 효율적으로 관리하고 저장하기 위해서 인덱스를 XML 문서로 작성한다. 이러한 XML 문서의 태그를 이용해서 사용자가 원하는 문서 파일을 스크립트(Script) 언어를 사용해서 검색한다. 본 논문에서 제안한 시스템을 이용하면 빠른 검색시간과 효율적으로 문서들을 관리할 수 있다.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.465-472
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• 2019

Although there are various cultural events and cultural contents produced in the region, there is a lack of distribution and spread of regional information to expand related economic consumption. This study combined local advertising by local advertisers with the knowledge search method in question and answer format from a location-based service perspective for the purpose of spreading and using local cultural information. The approach looked at domestic and international cases of knowledge search based on region and location-based advertising research, presented community model of location inquiry based information service and revenue model of local advertisement. Through this, this study designed a question and answer based community and operational structure model of local advertising, and developed an information service system in the form of prototyping. By extending the distribution of question and answer data among users to location information, it is meaningful that a business service model was presented that combines local cultural content information and the demand for user access with the revenue model of local advertising.

• The Korea Journal of Herbology
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• v.21 no.2
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• pp.129-133
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• 2006

Objectives : Cervus elaphus species are some of the most medicinally important genera in the Oriental medicine. This study was performed to determine if Cenvus elaphus species could be identified by sequencing analysis and to verify Basic Local Alignment Search Tool (BLAST) search, which was used to assess genetic identification. Methods : The DNAs of Cervus elaphus species were extracted, amplified by PCR, and sequenced. The DNAs of Cervus species were identified by BLAST search in website. Results : By BLAST search one of Cervus elaphus species was identified as Cervus elaphussibericus but the other was identified as Cervus elaphus nelsoni. This work showed that identification can efficiently be performed by BLAST search. Conclusion : These results suggest that sequencing following BLAST search might be able to provide the identification of Cervus elaphus species.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.669-680
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• 2001

Genetic Algorithms are optimization algorithm that mimics biological evolution to solve optimization problems. Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex fitness landscapes. Hybrid genetic algorithm that is combined with local search called learning can sustain the balance between exploration and exploitation. The genetic traits that each individual in the population learns through evolution are transferred back to the next generation, and when this learning is combined with genetic algorithm we can expect the improvement of the search speed. This paper proposes a genetic algorithm based Cellular Learning with accelerated learning capability for function optimization. Proposed Cellular Learning strategy is based on periodic and convergent behaviors in cellular automata, and on the theory of transmitting to offspring the knowledge and experience that organisms acquire in their lifetime. We compared the search efficiency of Cellular Learning strategy with those of Lamarckian and Baldwin Effect in hybrid genetic algorithm. We showed that the local improvement by cellular learning could enhance the global performance higher by evaluating their performance through the experiment of various test bed functions and also showed that proposed learning strategy could find out the better global optima than conventional method.

• Korean journal of communication and information
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• v.31
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• pp.225-259
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• 2005

Local paper has basically a close relationship to local autonomy for which the ultimate goals are regional development and the promotion of resident welfare. In addition, it is able to have considerable effects on the politics and administration in the region. In Korea where the history and experience of local autonomy is not long, the roles of local paper have been stressed more in the sense that local community is larking in a series of mechanism to control regional politics and administration. On the basis of such relationship of two, in this paper will be empirically analyzed the tendency on how local paper had reported them after revitalizing of Korean local autonomy of 1991. For this, content analysis was used as the method for examining of the tendency. All articles concerning local autonomy were collected from editorial, commentary, remarks, and special topic series from Maeil-daily newspaper, which is being issued in Daegu and Gyoungbook regions. This study could find the distinctive trend of reporting, and also recommended the desirable roles for local paper according to the results revealed in the trend analysis. To mature local autonomy, especially, this study suggested that local parer needs to search a way that ran get the subject of reports diversify as well as ran make an in-depth reporting.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.3
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• pp.1-8
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• 2009

The objectives of this study are to apply univariate search and genetic algorithm to tank model, and compare the two optimization methods. Hydrologic data of Baran watershed during 1996 and 1997 were used for correction the tank model, and the data of 1999 to 2000 were used for validation. RMSE and R2 were used for the tank model's optimization. Genetic algorithm showed better result than univariate search. Genetic algorithm converges to general optima, and more population of potential solution made better result. Univariate search was easy to apply and simple but had a problem of convergence to local optima, and the problem was not solved although search the solution more minutely. Therefore, this study recommend genetic algorithm to optimize tank model rather than univariate search.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.375-387
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• 2005

This paper presents an application of parallel Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution systems. The main objective of service restoration of distribution systems is, when a fault or overload occurs, to restore as much load as possible by transferring the do-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints, which is a combinatorial optimization problem. This problem has many constraints with many local minima to solve the optimal switch position. This paper develops parallel GA-TS algorithm for service restoration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solutions of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper $10\%$ of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC cluster system consists of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through ethernet switch based fast ethernet. To show the validity of the proposed method, proposed algorithm has been tested with a practical distribution system in Korea. From the simulation results, we can find that the proposed algorithm is efficient for the distribution system service restoration in terms of the solution quality, speedup, efficiency and computation time.