• ETRI Journal
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• v.25 no.5
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• pp.297-304
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• 2003

A multimedia SoC often requires a large internal buffer, because it must store the whole search window to reduce the huge I/O bandwidth of motion estimation. However, the silicon area of the internal buffer increases tremendously as the search range becomes larger. This paper proposes a new method that greatly reduces the internal buffer size of a multimedia SoC while the computational cost, I/O bandwidth, and image quality do not change. In the proposed method, only the overlapped parts of search windows for consecutive macroblocks are stored in the internal buffer. The proposed method reduces the internal buffer. The proposed method reduces the internal buffer size to 1/5.0 and 1/8.8 when the search range is ${\pm}64{\times}{\pm}$64 and ${\pm}128{\times}{\pm}$128, respectively.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.19-43
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• 2011

Tuning the architecture of SVM (support vector machine) is to build an SVM model of better performance. Two different tuning methods of the grid search and the GA (genetic algorithm) have been addressed in the literature, each of which has its own methodological pros and cons. This paper suggests a combined method for tuning the architecture of SVM models, which employs the GAM (generalized additive models), the grid search, and the GA in sequence. The GAM is used for selecting input variables, and the grid search and the GA are employed for finding optimal parameter values of the SVM models. Applying the method to a bankruptcy prediction problem, we show that SVM model tuned by the proposed method outperforms other SVM models.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.70-77
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• 2000

This paper proposes a method of solving a unit commitment problem using tabu search (TS) which is heuristic algorithm. Ts is a local search method that starts from any initial solution and attempts to determine a better solution using memory structures. In this paper, to reduce the computation time for finding the optimal solution, changing tabu list size as intensification strategy and path relinking method as diversification strategy are proposed. To show the usefulness of the proposed method, we simulated for 10 units system and 110 units system. Numerical results show improvements in the generation costs and the computation time compared with priority list, genetic algorithm(GA), and hybrid GA.

• Korean Journal of Human Ecology
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• v.7 no.1
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• pp.61-74
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• 1998

The purpose of this study is to investigate the information search, information use and search outcomes. 420 students in Chungnam and Taejon area were surveyed. Questionnaire survey method and multiple regression and path analysis were used. Some major conclusions were as follows: 1) The levels of the information search, information use and search outcomes were relatively low. 2) The volumes of information search and the contents of information were mainly affected by psycho-behavioral variables. 3) The level of information use was affected by the content of information, desire to seek information, involvement, and previous knowledge. 4) The search outcome was affected positively by the information use, involvement, volume of information search, desire to seek information, and perceived risk. 5) The volume of information search and the information use were the parameter of the search outcomes.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.123-130
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• 2009

Motion estimation (ME) plays an important role in digital video compression. But it limits the performance of image quality and encoding speed and is computational demanding part of the encoder. To reduce computational time and maintain the image quality, integer pel and fractional pel ME methods are proposed in this paper. The proposed method for integer pel ME uses a hierarchical search strategy. This strategy method consists of symmetrical cross-X pattern, multi square grid pattern, diamond patterns. These search patterns places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the computational time. The proposed method for fractional pel uses full search pattern, center biased fractional pel search pattern and the proposed search pattern. According to block sizes, the proposed method for fractional pel decides the search pattern adaptively. Experiment results show that the speedup improvement of the proposed method over Unsymmetrical cross Multi Hexagon grid Search (UMHexagonS) and Full Search (FS) can be up to around $1.2{\sim}5.2$ times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

• The Journal of Korean Academic Society of Nursing Education
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• v.16 no.1
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• pp.83-91
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• 2010

Purpose: The purpose of this study was to investigate the effects of satisfaction in major and career search efficacy on nursing students' career search behavior. Method: Data were collected from 544 students by means of self reported questionnaires about satisfaction in major, career search efficacy and career search behavior from March 2 to April 5, 2010. Result: The average score of satisfaction in major, career search efficacy and career search behavior was 3.61, 3.37, and 2.39 respectively. There were positive correlations between satisfaction in major and career search behavior, between career search efficacy and career search behavior, and between satisfaction in major and career search efficacy. Satisfaction in major and career search efficacy were significant predictors of career search behavior. Conclusion: It is necessary to develop an effective intervention program to improve nursing student's satisfaction in major, career search efficacy and career search behavior.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.532-540
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• 2001

In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.

• 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 the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.85-91
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• 2013

This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.57-65
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• 2015

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.