• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.26-28
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• 2007

The motion estimation is the most important technique in the image compression of the video standards. In the case of next generation standards in the video codec as H.264, a high compression-efficiency can be also obtained by using a motion compensation. To obtain the accurate motion search, a motion estimation should be achieved up to 1/2 pixel and 1/4 pixel uiuts. To do this, the computational complexity is increased although the image compression rate is increased. Therefore, in this paper, we propose the advanced sub-pixel block matching algorithm to reduce the computational complexity by using a statistical characteristics of SAD(Sum of Absolute Difference). Generally, the probability of the minimum SAD values is high when searching point is in the distance 1 from the reference point. Thus, we reduced the searching area and then we can overcome the computational complexity problem. The main concept of proposed algorithm, which based on TSS(Three Step Search) method, first we find three minimum SAD points which is in integer distance unit, and then, in second step, the optimal point is in 1/2 pixel unit either between the most minimum SAD value point and the second minimum SAD point or between the most minimum SAD value point and the third minimum SAD point In third step, after finding the smallest SAD value between two SAD values on 1/2 pixel unit, the final optimized point is between the most minimum SAD value and the result value of the third step, in 1/2 pixel unit i.e., 1/4 pixel unit in totally. The conventional TSS method needs an eight.. search points in the sub-pixel steps in 1/2 pixel unit and also an eight search points in 1/4 pixel, to detect the optimal point. However, in proposed algorithm, only total five search points are needed. In the result. 23 % improvement of processing speed is obtained.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.579-586
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• 2019

Pilot Point Method (PPM) is one of the popular methods to search hydraulic conductivities in the inverse method using groundwater flow equations. In this study, the Simultaneous Search based Pilot Point Method (SSBM) was applied with diverse information (e.g. hydraulic heads and/or tracer concentration) applications over previously developed sensitivity based Pilot Point Method (e.g. D-optimality based Pilot Point Method: DBM). In the case of DBM, due to the minimized the variance size, tracer concentration can be recognized as a tool to control the searching space of hydraulic conductivities. SSBM reduced the procedure of hydraulic conductivity searching, though it produced more variance for exploring hydraulic conductivities. In addition, SSBM was dependent on the initial hydraulic conductivity values for search finalized hydraulic conductivities. When tracer concentration was applied, searching hydraulic conductivities was more preferable than only when hydraulic head was applied. Applications of various data for searching hydraulic conductivities is recommended as a more efficient way.

• 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.

• Convergence Security Journal
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• v.19 no.2
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• pp.73-81
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• 2019

In this paper, we propose a user-dependent mid-point navigation system using a time weighted mid-point navigation algorithm and a user preference based mid-point neighborhood recommendation system. The proposed system consists of a mid-point navigation module for calculating an mid-point by applying a time weight of each user based on a departure point between users, and a search module for providing a search for a route to the calculated mid-point. In addition, based on the mid-point search result, it is possible to increase the utilization rate of users by including a place recommending function based on user's preference. Experimental results show that the proposed system can increase the efficiency of using by the user-dependent mid-point navigation and place recommendation function.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.362-368
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• 2005

This paper is related to the fast block matching algorithm, especially a method for expanding the search pattern using the second local matching point in the adaptive hexagonal search. To reduce the local minima problem in fast motion estimation, the proposed method expands the search pattern by adding new searching points selected by using the second local matching point to conventional search pattern formed by the first local matching point in the adaptive hexagonal search. According to estimating the motion vector by applying block matching algorithm based on hexagonal search to the expanded search pattern, the proposed method can effectively carry out fast motion estimation to improve the performance in terms of compensated image quality.

• Women's Health Nursing
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• v.8 no.4
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• pp.608-618
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• 2002

The purpose of this study is to analyze the type of ego states and stress coping style on female college students who are in the course of nursing study. This study is performed in the view of Transactional Analysis and designed to scrutinize descriptive correlations between the type of ego states and stress coping style. The subject is consists of 144 freshmen and sophomore, 138 junior and senior students group, who are students of K nursing college located in Seoul. The sampling investigation period is on Sept. 14, 2002 to Oct. 26, 2002. The measuring instrument used for Transactional Analysis ego state is 50 items Ego-gram research paper devised by Dusay(1997). For studying coping style, Folkman & Lazarus's measurement(1984) was adopted, which is translated and modified by Han, and Oh,(1990). Statistic average and standard deviation were generated by using SPSS PC+, t-test and Pearson correlation. The results were as follows: 1) In the type of ego states on both groups(lower group : freshmen, sophomore upper group : junior, senior) indicated the arithmetic apex NP(maximum value), then the point A was high and the data made a down slope to point AC. In the comparison to type of ego states between two groups, only at point CP, the data value of upper year students represented higher than that of lower year ones by C(t=2.28, p=.023). In the psychological energy level of ego states, both groups indicated average level.2) Stress coping style of whole students were highly and affirmatively dedicated to research. Consecutive consequences follow like this(high to low) : the central point of problem, search for social support, hopeful aspect and indifference. Especially hopeful aspect(t=.67, p=.05), relaxation of tension(t=-2.16, p=.03) made significant difference each other in the view of arithmetic calculation 3) While verifying coping style in terms of ego states level between lower and upper students group, In type CP, high level ego states group indicated significant difference on stress coping style area than low leveled group and made such sequences as the central point of problem, hopeful aspect, search for social support, positive interest and relaxation of tension. In type NP, sequences such as the central point of problem, search for social support, positive interest and relaxation of tension were emerged with little differences. In type A, the central point of problem, positive interest and relaxation of tension. In type FC, hopeful aspect, search for social support, positive interest and relaxation of tension. In type AC, hopeful aspect and indifference were derived significantly different(p<.05). 4) In the aspect of relation between ego states and coping style, type CP presented the central point of problem and relaxation of tension, type NP presented positive interest, search for social support and the central point of problem, type A showed the central point of problem, positive interest and relaxation of tension, type FC showed relaxation of tension, positive interest, search for social support, indifference and the central point of problem, type AC showed hopeful aspect, indifference and the central point of problem. All the sequence shown above had high-to-low procedure and represented static relations each other(p<.05).

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.274-277
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• 2003

Millimeter-wave networking is composed of narrow beam link. High directivity of the beam provides either advantage or disadvantage in comparison with conventional wide-lobe microwave communications. In such networks, it is very substantial that beam connecting point to point is fixed in right direction. It is major requirement in the beam network to keep the beam in best direction. In this paper, We propose the method to find a best suited direction of the antenna's beam using the Genetic Algorithm in point-to-point link. Proposed method presume that each station knows his direction $\theta$$_1$,$\theta$$_2$ at every step of Genetic Algorithm, then it can be expected that GA is possible to search the ideal solution. Intensity of the received signal is evaluated by the multiplication of lengths to the point which the lobe meets with the horizontal line.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.273-281
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• 2004

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the prediction search algorithm for block matching using the temporal correlation of the video sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 1.06㏈ as depend on the video sequences and improved about 0.19∼0.46㏈ on an average except the full search(FS) algorithm.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.131-139
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• 2007

This paper proposed a multi-resolution algorithm. Its search point and complexity were compared with those of block match algorithm. Also the speed up comparison was made with the block match algorithm. The proposed multi-resolution NTSS-3 Level algorithm was compared again with its targets, TSS-3 Level algorithm and NTSS algorithm. The comparison results showed that the NTSS-3 Level algorithm was superior in search point and speed up. Accordingly, the proposed NTSS-3 Level algorithm was two to three times better in search point and two to four times better in complexity calculation than those of the compared object, the block match algorithm. In speed up, the proposed NTSS-3 Level algorithm was two times better. Accordingly, the proposed multi-resolution NTSS-3 Level algorithm showed PSNR ration portion excellency in search point and speed up.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.329-337
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• 2017

This paper proposes a search method that explores parameters C and σ values of support vector machines (SVM) to improve performance while maintaining search accuracy. A traditional grid search method requires tremendous computational times because it searches all available combinations of C and σ values to find optimal combinations which provide the best performance of SVM. To address this issue, this paper proposes a deep search method that reduces computational time. In the first stage, it divides C-σ- accurate metrics into four regions, searches a median value of each region, and then selects a point of the highest accurate value as a start point. In the second stage, the selected start points are re-divided into four regions, and then the highest accurate point is assigned as a new search point. In the third stage, after eight points near the search point. are explored and the highest accurate value is assigned as a new search point, corresponding points are divided into four parts and it calculates an accurate value. In the last stage, it is continued until an accurate metric value is the highest compared to the neighborhood point values. If it is not satisfied, it is repeated from the second stage with the input level value. Experimental results using normal and defect bearings show that the proposed deep search algorithm outperforms the conventional algorithms in terms of performance and search time.