• Journal of the Korea Society for Simulation
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• v.25 no.1
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• pp.11-20
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• 2016

Recently in the field of defense Modeling and Simulation (M&S), Component-Based Development technology is widely applying to save the cost and increase the reusability of weapon system development. Related with this, researches for rapid reconfiguration and simulation of the component-standardized weapon system is actively carrying out. To rapidly reconfigure the new weapon system, complex and various functions of component information has to be effectively searched. So, it requires differentiated search technique unlike existing Keyword-based Search method. Semantic Search System provides semantically related information among the extensive information. In this research, metadata of weapon system components and their representative functional words are built as an ontology. And it provides an ontology-based semantic search system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3516-3541
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• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1259-1265
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• 2014

In this paper, the real-time attitude determination based Matlab using low-cost receivers was designed and evaluated. The GNSS attitude determination system was implemented to operation in real-time by TimerCallback in MATLAB. The TTM(Transmission Time Misalignment) of U-blox receiver was confirmed through zero baseline tests and this problem was revised. The computed attitude by the high-cost NovAtel receiver was compared to the computed attitude by the low-cost U-blox receiver. As a result of this, the performance of attitude determination systems by low-cost receiver was confirmed. To determine baseline, LAMBDA and BC-LAMBDA for integer ambiguities search methods were used. To confirm suitable integer ambiguity search method in real-time attitude determination algorithm, determined baselines by two methods were compared, and it was confirmed that BC-LAMBDA is more suitable. As a result of this, the operation of real-time attitude determination system was confirmed using 3 low-cost receivers.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.177-192
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• 2005

In this paper, we introduce a structural redundancy method. It reduces the query processing cost incurred when reconfiguring an XML document from divided XML data in shredding XML documents into relations. The fundamental idea is that query performance can be enhanced by analyzing query patterns and replicating data essential for the query performance. For the practical and effective structural redundancy, we analyzed three types of ID, VALUE, and SUBTREE replication. In addition, if given XML data and queries are very large and complex, it can be very difficult to search optimal redundancy set. Therefore, a heuristic search method is introduced in this paper. Finally, XML query processing cost arising by employing the structural redundancy, and the efficiency of proposed search method arc analyzed experimentally It is manifest that XML read query is performed more quick]y but XML update query is performed more slowly due to the additional update consistency cost for replicas. However, experimental results showed that in-place ID replication is useful even in having excessive update cost. It was also observed that multiple-place SUBTREE replication can enhance read query performance remarkably if only update cost is not excessive.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.430-435
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• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.39-47
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• 2010

Constraint satisfaction optimization problem is a kind of optimization problem involving cost minimization as well as complex constraints. Local search and constraint programming respectively have been used for solving such problems. In this paper, I propose a method to integrate local search and constraint programming to improve search performance. Basically, local search is used to solve the given problem. However, it is very difficult to find a feasible neighbor satisfying all the constraints when we use only local search. Therefore, I introduced constraint programming as a tool for neighbor generation. Through the experimental results using weighted N-Queens problems, I confirmed that the proposed method can significantly improve search performance.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.177-187
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• 2006

It is known that over one million car navigation devices are being currently used in Korea. Most. if not all, route guidance systems, however, Provide only one "best" route to users, not providing any options for various types of users to select. The current practice dose not consider each individual's different preferences. These days, a vast amount of information became available due to the rapid development in information processing technology. Thus, users Prefer choices to be given and like to select the one that suits him/her the "best" among available information. To provide such options in this Paper, we developed an algorithm that provides alternative routes that may not the "least cost" ones, but ones that are close to the "least cost" routes for users to select. The algorithm developed and introduced in the paper utilizes a link-based search method, rather than the traditional node-based search method. The link-based algorithm can still utilize the existing transportation network without any modifications, and yet enables to provide flexible route guidance to meet the various needs of users by allowing transfer to other modes and/or restricting left turns. The algorithm developed has been applied to a toy network and demonstrated successful implementation of the multi-path search algorithm for multi-purpose activities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.237-245
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• 2017

Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users' needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30's, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.12
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• pp.73-87
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• 1991

This paper presents a new approach to the scheduling problem in the high level synthesis. In this approach, iterative rescheduling processes starting with ASAP(As Soon As Possible) scheduling result are performed in a branch-and-bound manner so to arrive at the scheduling result of the lowest hardware cost under the given timing constraint. At each iteration step, only the selected nodes are considered for rescheduling, and the lower bound cost estimation is performed to avoid the unnecessary attempts to search for an optimal result. This branch-and-bound method turns out to be effective in pruning the search space, and thus reducing run time considerably in many cases.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2287-2290
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• 2003

In this paper, an image vector quantization method is proposed not only to improve the compression ratio but also to reduce the computation cost. The proposed method could save the computation cost of codebook generation and encoding by using the modified LBG algorithm of Partial Search Partial Distortion (PSPD) in wavelet domain, by which the code book was constructed together with the partial codebook search, the partial code vector elements, and the interruption criterion. We have designed and implemented the vector quantizer to verify the improvement in reducing compression ratio in encoding processing and reducing the computation cost.