• Steel and Composite Structures
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• v.49 no.4
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• pp.419-430
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• 2023

This paper is aimed at investigating the effect of multiple longitudinal stiffeners on the patch loading resistance of slender steel plate girders. Firstly, a numerical study is conducted through geometrically and materially nonlinear analysis with imperfections included (GMNIA), the model is validated with experimental results taken from the literature. The structural responses of girders with multiple longitudinal stiffeners are compared to the one of girders with a single longitudinal stiffener. Thereafter, a patch loading resistance model is developed through machine learning (ML) using symbolic regression (SR). An extensive numerical dataset covering a wide range of bridge girder geometries is employed to fit the resistance model using SR. Finally, the performance of the SR prediction model is evaluated by comparison of the resistances predicted using available formulae from the literature.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.451-454
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• 1999

An existing plasticity model using multiple failure criteria is modified to describe the behavior of reinforced concrete planar members under cyclic load. Multiple failure criteria are used to define both isotropic damage of compressive crushing and anisotropic damage of tensile cracking. A numerical method is developed to define multi-directional and non-orthogonal crack directions. The material model is implemented in the finite element analysis and verified by comparison with existing experiments of reinforced concrete shear wall.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.191-199
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• 2001

본 소고는 n명의 심사자가 k개의 객체를 평가하여 얻어진 불완전 순위자료에서 객체간 선호도에 있어 차이가 없다는 영가설을 검정하는 방법에 관한 연구이다. 주어진 자료에서 결측값들을 다중대체하는 방식을 제안하고 이들을 평균 p-값으로 묶는 몬테칼로방식의 임의순열 검정을 제안한다.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1079-1086
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• 2005

Most discussions of single imputation methods and the EM algorithm concern point estimation of population quantities with missing values. A second concern is how to get standard errors of the point estimates obtained from the filled-in data by single imputation methods and EM algorithm. Now we focus on how to estimate standard errors with incorporating the additional uncertainty due to nonresponse. There are some approaches to account for the additional uncertainty. The general two possible approaches are considered. One is the jackknife method of resampling methods. The other is multiple imputation(MI). These two approaches are reviewed and compared through simulation studies.

• Journal of Ginseng Research
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• v.18 no.1
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• pp.39-43
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• 1994

This study was performed to investigate the effect of ginseng saponin from Korean red ginseng on the learning and memory. Total (50, 100 mg/kg, bw) and panaxadiol saponin (15, 30 mg/kg, bw) treated groups did not show the difference of the time score and the number of error in comparison with control group. Panaxatriol saponin (15, 30 mg/kg, bw) significantly decreased both the time score and the number of error in water maze test. These results indicate that panaxatriol saponin from Korean red ginseng may improve the learning ability of rat in water multiple T-maze.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.777-786
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• 2007

This paper presents a modified simulated annealing algorithm to optimize linear scheduling projects with multiple resource constraints and its effectiveness is verified with a proposed problem. A two-stage solution-finding procedure is used to model the problem. Then the simulated annealing and the modified simulated annealing are compared in the same condition. The comparison results and the reasons of improvement by the modified simulated annealing are presented at the end.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.6
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• pp.442-448
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• 2013

There are two approaches in measuring colors (or chromaticity) in water, i.e., visual comparison method and spectrophotometric method. The color of sample was determined by comparing with that of platinum-cobalt standard solution in the visual comparison method. Single or multiple wavelengths are used for the spectrophotometric method. As the accuracy and precision of visual comparison method depend on the eye sight of the analyzer, the results are not so reliable and representative. In addition, it is hard to measure chromaticity less than 5 TCU. Single wavelength approach in spectrophotometric method, can be applied for groundwater or surface water with natural organic matter (i.e., humic substances) while it's hard to measure the color of wastewater which includes anthropogenic chemical compounds. The measurements with multiple wavelengths approach resulted in reliable data regardless of the source of sample water, i.e., surface water and wastewater. As dozens of measurements and complicated calculations for one sample were required for the multiple wavelengths approach, the approach could not be applied for field measurement. In the present study, the authors tested efficient method which could measure the color of water sample accurately and precisely regardless of the source of water. With the colorimeter with multiple wavelengths and calculation program, the colors of water samples could be measured within 3~4 seconds with accuracy and precision.

• ETRI Journal
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• v.16 no.3
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• pp.27-41
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• 1994

This paper provides a performance study of multistage interconnection networks in packet switching environment. In comparison to earlier work, the model is more extensive - it includes several parameters such as multiple-packet messages, variable buffer size, and wait delay at a source. The model is also uniformly applied to several representative networks and thus provides a basis for fair comparison as well as selection of optimal values for parameters. The complexity of the model required use of simulation. However, a partial analytical model is provided to measure the congestion in a network.

• Human Ecology Research
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• v.57 no.2
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• pp.295-305
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• 2019

This study examined the effects of social comparison orientation and stress coping styles on job-seeking stress experienced by university students. The participants of this study were 324 junior and senior students (151 males and 173 females) from six universities located in Seoul who were preparing for employment. They were asked to respond to a written questionnaire to measure research variables for the Job-Seeking Stress Scale, the Social Comparison Orientation Scale, and the Ways of Coping Checklist. The data were analyzed by means of descriptive statistics and a hierarchical multiple regression. The major findings of this study were as follows. First, social comparison orientation had a positive effect on job-seeking stress of university students, revealing that students with a high level of social comparison orientation were more likely to experience job-seeking stress. Second, both emotion-alleviation coping style and wishful thinking coping style increased level of job-seeking stress. In addition, problem-focused coping style had a negative influence on job-seeking stress, whereas social support seeking coping style had no significant effect on it. The results suggested that it would be possible to reduce job-seeking stress of university students by changing either social comparison or stress coping style.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.893-910
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• 2017

In this paper, we propose a simple online multiple object (human) tracking method, LKDeep (Lucas-Kanade feature and Detection based Simple Online Multiple Object Tracker), which can run in fast online enough on CPU core only with acceptable tracking performance for embedded surveillance purpose. The proposed LKDeep is a pragmatic hybrid approach which tracks multiple objects (humans) mainly based on LK features but is compensated by detection on periodic times or on necessity times. Compared to other state-of-the-art multiple object tracking methods based on 'Tracking-By-Detection (TBD)' approach, the proposed LKDeep is faster since it does not have to detect object on every frame and it utilizes simple association rule, but it shows a good object tracking performance. Through experiments in comparison with other multiple object tracking (MOT) methods using the public DPM detector among online state-of-the-art MOT methods reported in MOT challenge [1], it is shown that the proposed simple online MOT method, LKDeep runs faster but with good tracking performance for surveillance purpose. It is further observed through single object tracking (SOT) visual tracker benchmark experiment [2] that LKDeep with an optimized deep learning detector can run in online fast with comparable tracking performance to other state-of-the-art SOT methods.