• The KIPS Transactions:PartA
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• v.19A no.1
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• pp.45-50
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• 2012

The demand for faster execution time and lower energy consumption has compelled architects of embedded processors to customize it to the needs of their target applications. These processors consequently provide a rich set of specialized instructions in order to enable programmers to access these features. Such an instruction is typically a $multi$-$output$ $instruction$ (MOI), which outputs multiple results parallely in order to exploit inherent underlying hardware parallelism. Earlier study has exhibited that MOIs help to enhance performance in aspect of instruction counts and code size. However the earlier algorithm does not consider the register pressure. So, some selected MOIs introduce register spill/reload code that increases the code size and instruction count. To attack this problem, we introduce a novel iterated instruction selection algorithm based on the register pressure of each selected MOIs. The experimental results show the suggested algorithm achieves 3% code-size reduction and 2.7% speed-up on average.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.601-607
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• 2012

Objective: The aim of this study is to classify between intentional and natural blinks in vision based eye tracking system. Through implementing the classification method, we expect that the great eye tracking method will be designed which will perform well both navigation and selection interactions. Background: Currently, eye tracking is widely used in order to increase immersion and interest of user by supporting natural user interface. Even though conventional eye tracking system is well focused on navigation interaction by tracking pupil movement, there is no breakthrough selection interaction method. Method: To determine classification threshold between intentional and natural blinks, we performed experiment by capturing eye images including intentional and natural blinks from 12 subjects. By analyzing successive eye images, two features such as eye closed duration and pupil size variation after eye open were collected. Then, the classification threshold was determined by performing SVM(Support Vector Machine) training. Results: Experimental results showed that the average detection accuracy of intentional blinks was 97.4% in wearable eye tracking system environments. Also, the detecting accuracy in non-wearable camera environment was 92.9% on the basis of the above used SVM classifier. Conclusion: By combining two features using SVM, we could implement the accurate selection interaction method in vision based eye tracking system. Application: The results of this research might help to improve efficiency and usability of vision based eye tracking method by supporting reliable selection interaction scheme.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.954-962
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• 2019

It is well known that the variance of tally is biased in a Monte Carlo calculation based on the power iteration method. Several studies have been conducted to estimate the real variance. Among them, the batch method, which was proposed by Gelbard and Prael, has been utilized actively in many Monte Carlo codes because the method is straightforward, and it is easy to implement the method in the codes. However, there is a problem when utilizing the batch method because the estimated variance varies depending on batch size. Often, the appropriate batch size is not realized before the completion of several Monte Carlo calculations. This study recognizes this shortcoming and addresses it by permitting selection of an appropriate batch size.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1175-1180
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• 1991

The purpose of this paper is to improve the matching accuracy in identifying corresponding points in the area-based matching for the processing of stereo vision. For the selection of window size, a new method is proposed based on frequency domain analysis. The effectiveness of the proposed method is confirmed through a series of experiments. To overcome disproportionate distortion in stereo image pair, a new matching method using the warped window is also proposed. In the algorithm, the window is warped according to imaging geometry. Experiments on a synthetic image show that the matching accuracy is improved by 14.1% and 4.2% over the rectangular window method and image warping method each.

• 대한예방의학회:학술대회논문집
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• 2003.04a
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• pp.30-37
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• 2003

o Cohort study became the major approach to study of chronic diseases such as CVD and cancer o Cohort can be population-based or volunteer-based o Types of be population-be categorized by source population and selection mechanism o More and more cohort studies involve biological specimens, such as blood, urine, toenail, cheek cells, etc. o Multi-center and multi-national collaboration is an effective way to increase sample size. o Current statistical method typically use time-to-event analysis by Cox proportional hazard model.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.147-158
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• 2019

The purpose of this study is to identify differences based on demographic characteristics and travel-related characteristics: first, whether travelers used a domestic travel agency and second whether travelers purchased a full-package travel program. A sample selection probit model was used to provide simultaneous evaluation of the different characteristics of outbound travelers. The present study investigates how tourists make decisions based on two travel-pattern choices. It then goes on to explore the characteristics of outbound travelers from South Korea. The data is drawn from a nationwide survey in South Korea, and a total of 859 surveys were used for analysis. Due to the interdependent nature of the choices, a sample selection probit model was used to estimate outbound tourists' use of domestic travel agency and purchase of full travel package. Significant determinants of domestic travel agency use are identified as age, gender, marital status, party size, children, length of travel, and travel distance, while those of full travel package purchase are age, marital status, and travel purpose. Estimated results provide manifestations of differing travel needs of outbound travelers. the results of this study demonstrate differences between travel-agency users and full-package travel-program consumers and provide determinants that affect the purchase of full-package travel.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.159-169
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• 2019

Objective: Models for genomic selection assume that the reference population is an unselected population. However, in practice, genotyped individuals, such as progeny-tested bulls, are highly selected, and the reference population is created after preselection. In dairy cattle, the intensity of selection is higher in males than in females, suggesting that cows can be added to the reference population with less bias and loss of accuracy. The objective is to develop formulas applied to any genomic prediction studies or practice with preselected animals as reference population. Methods: We developed formulas for calculating the reliability and bias of genomically enhanced breeding values (GEBV) in the reference population where individuals are preselected on estimated breeding values. Based on the formulas presented, deterministic simulation was conducted by varying heritability, preselection percentage, and the reference population size. Results: The number of bulls equal to a cow regarding the reliability of GEBV was expressed through a simple formula for the reference population consisting of preselected animals. The bull population was vastly superior to the cow population regarding the reliability of GEBV for low-heritability traits. However, the superiority of reliability from the bull reference population over the cow population decreased as heritability increased. Bias was greater for bulls than cows. Bias and reduction in reliability of GEBV due to preselection was alleviated by expanding reference population. Conclusion: Cows are easier in expanding reference population size compared with bulls and alleviate bias and reduction in reliability of GEBV of bulls which are highly preselected than cows by expanding the cow reference population.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.203-214
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• 2014

In this study, a meta-analysis was conducted to investigate the effect of community-based rehabilitation on patients with brain injury by ICF factor in previous studies and examine the application of recent community-based rehabilitation program. Total 15 articles that satisfied the selection criteria were divided by ICF factors to obtain the effect size. Homogeneity and publication bias were tested for those selected papers. As a result, the overall effect size of community-based rehabilitation was 0.22; the effect size by physical function and structure among the ICF factors came to be 0.21; and the effect size of activity and participation was 0.20, indicating a small effect size. The studies involved in a meta-analysis were considered as the absence of heterogeneity and publication bias, which indicates that the results of this study are subjectively reliable. These results well explained the level of change on ICF factors, especially physical function and structure, activity and participation, in other words, the intervention effect of community-based rehabilitation on patients with brain injury.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.201-208
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• 2014

The performance of a landmine detection system depends on consistent extractions of the features of landmines. Since landmines have diverse sizes, it is critical to select an appropriate window size to represent the landmine region consistently. Conventional detection systems are incapable of extracting consistent landmine features because they employ fixed window sizes. This paper proposes a window size selection method according to the size of a landmine. The proposed method selects an appropriate window size based on the type of a landmine estimated from the response signal of the system. Data on various types of soils and landmines were generated from a simulation program to evaluate the performance of the proposed method. The results verified that the proposed method, which employs an adaptive window size, yields a better landmine detection rate than the conventional methods, which employ fixed window sizes.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.59-66
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• 2018

The performance of a network intrusion detection system using the machine learning method depends heavily on the composition and the size of the feature set. The detection accuracy, such as the detection rate or the false positive rate, of the system relies on the feature composition. And the time it takes to train and detect depends on the size of the feature set. Therefore, in order to enable the system to detect intrusions in real-time, the feature set to beused should have a small size as well as an appropriate composition. In this paper, we show that the size of the feature set can be further reduced without decreasing the detection rate through using Pearson correlation coefficient between features along with the multi-objective genetic algorithm which was used to shorten the size of the feature set in previous work. For the evaluation of the proposed method, the experiments to classify 10 kinds of attacks and benign traffic are performed against NSL_KDD data set.