• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.1-10
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• 2022

Attempts to interpret human perspectives using computer vision have been developed in various fields. In this paper, we propose a method for evaluating the walking environment through semantic segmentation results of images from road images. First, the Kakao Map API was used to collect road images, and four-way images were collected from about 50,000 points in JeonJu. 20% of the collected images build datasets through crowdsourcing-based paired comparisons, and train various regression models using paired comparison data. In order to derive the walkability score of the image data, the ranking score is calculated using the Trueskill algorithm, which is a ranking algorithm, and the walkability and analysis using various regression models are performed using the constructed data. Through this study, it is shown that the walkability of Jeonju can be evaluated and scores can be derived through the correlation between pixel distribution classification information rather than human vision.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.1-8
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• 1992

A method analizing contact pressure between plate and elastic half space is presented by using F.E.M. With the method, the pressure intensities at surface nodes of half space cae be directly calculated by using flexibility matrix of half space. The method is originally presented by Y.K. Cheung et al.(3) Insted of Y.K. Cheung's method, which use a conception of equi-contact pressure area around each surface nodes of half space in the noded rectanqular element area. We use the equi-contact pressure area around the Gaussian integration points of half space surface in the noded isoparametric element area. Numarical examples are presented and compared with other's studies.

• The Mathematical Education
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• v.57 no.1
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• pp.55-74
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• 2018

The purpose of this study is first to examine the relative influence of each error source and to investigate the optimal measurement conditions to ensure satisfactory multiple reliability coefficients based on the teaching aptitude and personality test for pre-service teachers. Participants were 33 students enrolled in mathematics education in a graduate school of education located in the Seoul metropolitan area from 2013 to 2017. The main results were as follows. First, the estimated variance due to residual was highest, followed by nesting of items within domains, graduate students, interactions of graduate students with domains, and domains. Second, total 96 items, with 12 domains containing 8 items in each domain, with cut score of 598, and original 210 items, with 14 domains containing 15 items in each domain, with cut scores of 615 or 716 were optimal measurement conditions to reach acceptable reliability levels based on the joint consideration of dependability coefficients, cut score dependability coefficients, adjusted dependability coefficients, and standard errors of measurement. Third, larger deviations between the arithmetic mean and the cut score indicated higher reliability coefficients of the test results. Finally, this study suggests ways for practitioners to consider how to apply generalizability theory for criterion-referenced tests and how to develop future research based on limitations.

• Education of Primary School Mathematics
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• v.16 no.2
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• pp.163-182
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• 2013

The purpose of this study is an analysis on the 3rd graders' achievement in the elementary school. For this purpose, this study, first, analysed on the 3rd graders' achievement like the ratios of the achievement levels for whole students, sexual students, and regional students. Second, this study analysed the 3rd graders' assessment results like the total averages, averages for the contents area, sexual students, and regional students. Third, this study analysed students' special responses on the items.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.61-74
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• 2015

Structural equation modeling (SEM) is a widely used in social sciences such as education, business administration, and psychology. In SEM, the latent variable score is the estimate of the latent variable which cannot be observed directly. This study uses stagewise structural equation modeling(stagewise SEM; SSEM) by partitioning the whole model into several stages. The traditional estimation method minimizes the discrepancy function using the variance-covariance of all observed variables. This method can lead to inappropriate situations where exogenous latent variables may be affected by endogenous latent variables. The SSEM approach can avoid such situations and reduce the complexity of the whole SEM in estimating parameters.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.529-536
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• 2022

In the past two years, Severe Acute Respiratory Syndrome Coronavirus-2(SARS-CoV-2) has been hitting more and more to people. This paper proposes a novel U-Net Convolutional Neural Network to classify and segment COVID-19 lung CT images, which contains Sub Coding Block (SCB), Atrous Spatial Pyramid Pooling(ASPP) and Attention Gate(AG). Three different models such as FCN, U-Net and U-Net-SCB are designed to compare the proposed model and the best optimizer and atrous rate are chosen for the proposed model. The simulation results show that the proposed U-Net-MMFE has the best Dice segmentation coefficient of 94.79% for the COVID-19 CT scan digital image dataset compared with other segmentation models when atrous rate is 12 and the optimizer is Adam.

• Journal of Nutrition and Health
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• v.42 no.8
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• pp.682-690
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• 2009

The purpose of this study is to analyse the relation between dietary habit and nutrition knowledge, and ADHD (Attention Deficit Hyperactivity Disorder) in the middle school students in Seoul, Korea. Total study subjects were 631 students, 51.8% was male and 48.2% was female. In the assessment of predisposition of ADHD, 93% was normal group and 7% was ADHD group. As for the gender in ADHD group, 56.8% was male and 43.2% was female. Normal group showed the higher breakfast consumption rate than ADHD group (p < 0.05). Dietary habits were better in normal group than ADHD group. Nutrition knowledge scores of normal group was 7.38 out of 15 and scores of ADHD group was 5.77 out of 15 (p < 0.01). The nutrition knowledge score and the dietary habits score showed a positive correlation (p < 0.01). The nutrition knowledge score and snack meal purchasing frequency showed a negative correlation (p < 0.05). There are significant negative correlation between attention deficit hyperactivity score and nutrition knowledge score (p < 0.01). In conclusion, ADHD group showed lower level of nutrition knowledge and worse dietary habits than the normal group.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.157-168
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• 2014

We propose an novel artificial visual attention model that is capable of automatic detection and segmentation of saliency region on natural images in this paper. The proposed model is based on human visual perceptions in biological vision and contains there are main contributions. Firstly, we propose a novel framework of artificial visual attention model based on the opponent process theory using intensity and color features, and an entropy filter is designed to perceive salient regions considering the amount of information from intensity and color feature channels. The entropy filter is able to detect and segment salient regions in high segmentation accuracy and precision. Lastly, we also propose an adaptive combination method to generate a final saliency map. This method estimates scores about intensity and color conspicuous maps from each perception model and combines the conspicuous maps with weight derived from scores. In evaluation of saliency map by ROC analysis, the AUC of proposed model as 0.9256 approximately improved 15% whereas the AUC of previous state-of-the-art models as 0.7824. And in evaluation of salient region segmentation, the F-beta of proposed model as 0.7325 approximately improved 22% whereas the F-beta of previous state-of-the-art models.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.123-131
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• 2008

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of one's health like the physiological and the clinicopathological changes of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition a lot. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue region from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmenting, detecting the edge with a local minimum over a shading area from the structure of a tongue, correcting local minima or detecting the edge with the greatest color difference, selecting one edge to correspond to a tongue shape, and smoothing edges, where preprocessing consists of down-sampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue. Finally, the systematic procedure separated only a tongue region from a face image with a tongue, which was obtained from a digital tongue diagnosis system. Oriental medical doctors' evaluation for the results illustrated that the segmented region excluding a non-tongue region provides important information for the accurate diagnosis. The proposed method can be used for an objective and standardized diagnosis and for an u-Healthcare system.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.259-266
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• 2002

The main issue in software development is the ability of software project effort and cost estimation in the early phase of software life cycle. The regression models for project effort and cost estimation are presented by function point that is a software sire. The data sets used to conduct previous studies are of ten small and not too recent. Applying these models to 789 project data developed from 1990 ; the models only explain fewer than 0.53 $R^2$(Coefficient of determination) of the data variation. Homogeneous group in accordance with project delivery rate (PDR) divides the data sets. Then this paper presents general effort estimation models using project delivery rate. The presented model has a random distribution of residuals and explains more than 0.93 $R^2$ of data variation in most of PDR ranges.