• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2107-2115
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• 2007

In this paper, the scan conversion processor which converts the triangle represented by three vertices into pixel-level screen coordinates, depth coordinate, and color data is designed. The processor adopts scan-line algorithm which decomposes triangle into horizontal spans and then transforms the span into pixel data. By supporting top-left filling convention, it ensures that triangles that share an edge do not produce any dropouts or overlaps between adjacent polygons. It consists of about 21,400 gates and its maximum operating frequency is about 80 Mhz under 0.35um CMOS technology. Because its maximum pixel rate is about 80 Mpixels/sec, it can be applicable to mobile graphics application.

• Journal of Astronomy and Space Sciences
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• v.36 no.2
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• pp.45-60
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• 2019

The Earth's outer radiation belt has long received considerable attention mainly because the MeV electron flux in the belt varies often dramatically and at various time scales. It is now widely accepted that the wave-particle interaction is one of the major mechanisms responsible for such flux variations. The wave-particle interaction can accelerate electrons to MeV energies, explaining the observed flux increase events, and can also scatter the electrons' motion into the loss cone, resulting in atmospheric precipitation and thus contributing to flux dropouts. In this paper, we provide a review of the current state of research on relativistic electron scattering and precipitation due to the interaction with electromagnetic ion cyclotron (EMIC) waves in the inner magnetosphere. The review is intended to cover progress made over the last ~15 years in the theory and simulations of various issues, including quasilinear resonance diffusion, nonlinear interactions, nonresonant interactions, effects of finite normal angle on pitch angle scattering, effects due to rising tone emission, and ways to scatter near-equatorial pitch angle electrons. The review concludes with suggestions of a few promising topics for future research.

• Journal of the Korean Society of School Health
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• v.34 no.2
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• pp.123-132
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• 2021

Purpose: Adolescents are vulnerable to depression; however, many health policies for adolescents tend to target students in schools. This study aims to identify factors related to depression according to gender among adolescents who have ceased attending school either temporarily or permanently. Methods: The data were generated from the 5th Dropout Youth Panel Survey (2017), and this study included 318 students in the survey that had dropped out of school. The data were analyzed using hierarchical multiple linear regression to identify related factors in depression among the participants. The analyses were performed by SPSS 25.0 program. Results: The depression scores of the students who had ceased attending school were: 20.28±5.47 for boys; 21.23±5.88 for girls. Their depression scores are significantly associated with self-esteem (p<.001 for boys; p=.001 for girls) and social stigma (p=.002 for boys; p=.002 for girls). Among those, peer attachment (p=.050), community integration (p=.004), and community disorder (p<.001) were significantly associated with depression only in boys. Conclusion: The findings of this study suggest that strategies for managing depression in adolescents who have dropped out of school should address the differences in contributing factors according to gender. This study also suggests a basis for approaching such a strategy.

• Journal of the Korean Society of School Health
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• v.34 no.3
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• pp.151-160
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• 2021

Purpose: The purpose of this study was to identify predictors of suicidal attempts in adolescents over 5 years after school dropout. Methods: The data of the Panel Survey of School Dropouts (of 2013 to 2017) conducted by the National Youth Policy Institute were analyzed. The analysis used the 2013 survey data as the baseline and examined suicidal attempts from 2013 to 2017. A total of 776 adolescents were included in the analysis. Descriptive statistics, 𝝌² test, t-test, and multiple logistic regression were carried out using SAS 9.2. Results: About 11% (87 out of 776) of the adolescents with an experience of dropout attempted suicide between 2013 and 2017. The risk of suicidal attempts was significantly lower in female (AOR: 0.57, 95% CI: 0.87~0.93) than in male adolescents. The higher the self-esteem, the lower the risk of suicidal attempts (AOR: 0.87. 95% CI: 0.78~0.97). The higher the depression level (AOR: 1.10, 95% CI: 1.05~1.16) and the rate of parental abuse (AOR: 1.09, 95% CI: 1.02~1.18), the higher the risk of suicidal attempts. Conclusion: The findings of the study suggest that those who are male, depressed, have low self-esteem or have been abused by their parents are at high risk of suicidal attempts among the adolescents with dropout experiences. Therefore, early intervention is necessary for those at high risk.

• The Journal of Korean Physical Therapy
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• v.34 no.3
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• pp.104-109
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• 2022

Purpose: The purpose of this pilot study is to identify the problems and stability of a study to investigate "Effects of Squat Exercise according to Weight Support on Balance and Gait in Patients after Total Hip Replacement." before proceeding with the study. Methods: Twenty-two rehabilitation patients after THR surgery who met the selection criteria participated. The study subjects were randomly assigned to a squat group using a slider or a squat group using a reformer. The interventions were applied for two weeks. The patients were assessed using Berg balance scale (BBS), Timed up and go test (TUG), and 10-meter walking test (10MW). Results: Although twenty-two study subjects participated in this study, eight study subjects participated dropouts occurred during the study period. There was a significant difference within the group in BBS and TUG in two groups (p<0.05). The difference between the two groups was not significant in all outcome measures (p>0.05). The largest effect size was 1.21 and the smallest effect size was 0.39, all from the BBS. Conclusion: This pilot study suggest that it is feasible with minor adjustment to conduct a larger scale, powered RCT to examine the efficacy of squat exercise according to weight support with patients after THR.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1255-1262
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• 2021

The proportion of students dropping out of universities is increasing year by year, and they are trying to identify risk factors and eliminate them in advance to prevent dropouts. However, there is a problem in the management of students at risk of dropping out and the forecast is inaccurate because crisis students are managed through the univariable analysis of specific risk factors. In this paper, we identify risk factors for university dropout and analyze multivariables through machine learning method to predict university dropout. In addition, we derive the optimization method by evaluation performance for various prediction methods and evaluate the correlation and contribution between risk factors that cause university dropout.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.285-291
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• 2022

The number of people enrolling in universities is rising due to the simplicity of applying and the benefit of earning a bachelor's degree. However, the on-time graduation rate has declined since plenty of students fail to complete their courses and take longer to get their diplomas. Even though there are various reasons leading to the aforementioned problem, it is crucial to emphasize the cause originating from the management and care of learners. In fact, understanding students' difficult situations and offering timely Number of Test data and advice would help prevent college dropouts or graduate delays. In this study, we present a machine learning-based method for early detection at-risk students, using data obtained from graduates of the Faculty of Information Technology, Dainam University, Vietnam. We experiment with several fundamental machine learning methods before implementing the parameter optimization techniques. In comparison to the other strategies, Random Forest and Grid Search (RF&GS) and Random Forest and Random Search (RF&RS) provided more accurate predictions for identifying at-risk students.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.47-54
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• 2023

For Bengali music emotion classification, deep learning models, particularly CNN and RNN are frequently used. But previous researches had the flaws of low accuracy and overfitting problem. In this research, attention-based Conv1D and BiGRU model is designed for music emotion classification and comparative experimentation shows that the proposed model is classifying emotions more accurate. We have proposed a Conv1D and Bi-GRU with the attention-based model for emotion classification of our Bengali music dataset. The model integrates attention-based. Wav preprocessing makes use of MFCCs. To reduce the dimensionality of the feature space, contextual features were extracted from two Conv1D layers. In order to solve the overfitting problems, dropouts are utilized. Two bidirectional GRUs networks are used to update previous and future emotion representation of the output from the Conv1D layers. Two BiGRU layers are conntected to an attention mechanism to give various MFCC feature vectors more attention. Moreover, the attention mechanism has increased the accuracy of the proposed classification model. The vector is finally classified into four emotion classes: Angry, Happy, Relax, Sad; using a dense, fully connected layer with softmax activation. The proposed Conv1D+BiGRU+Attention model is efficient at classifying emotions in the Bengali music dataset than baseline methods. For our Bengali music dataset, the performance of our proposed model is 95%.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.137-146
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• 2023

The dropout of university freshmen is a very important issue in the financial problems of universities. Moreover, the dropout rate is one of the important indicators among the external evaluation items of universities. Therefore, universities need to predict dropout students in advance and apply various dropout prevention programs targeting them. This paper proposes a method to predict such dropout students in advance. This paper is about a method for predicting dropout students. It proposes a method to select dropouts by applying logistic regression using a shift sigmoid classification function using only quantitative data from the first semester of the first year, which most universities have. It is based on logistic regression and can select the number of prediction subjects and prediction accuracy by using the shift sigmoid function as an classification function. As a result of the experiment, when the proposed algorithm was applied, the number of predicted dropout subjects varied from 100% to 20% compared to the actual number of dropout subjects, and it was found to have a prediction accuracy of 75% to 98%.

• Journal of Korean society of Dental Hygiene
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• v.16 no.4
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• pp.559-566
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• 2016

Objectives: This research has executed a new oral health promotion program among the elderly residents of a long-term care center, which purpose was to verify its effectiveness of oral health promotion through the improvement of their oral function. Methods: This study has selected the elderly over the age of 65, capable of communication, who use a long-term care center over the period of two months between July and September 2014. The subjects who remained until the final analysis numbered 50 excluding the dropouts during the program session (experimental: 33, control : 17). The oral stretching program was exercised two days a week, for total of two months. Each function was assessed by the standardized methods and measurement equipment. Also the sum of each function was converted into the oral health grade. Results: The oral function score of the experimental group also showed a statistically significant difference after the execution of the program, where the oral function score of experimental group increased $6.70{\pm}1.30$ from $4.95{\pm}0.89$ after the execution of the program (p<0.05), while the comparison group showed no valid statistical difference with the score result of $5.00{\pm}0.87$ down from $5.11{\pm}0.93$ after the execution of the program (p>0.05). Conclusions: Therefore if the oral health promotion program is reflected to the welfare policy in the future, it can be said that it contributes to the improved health status of the elderly who reside in the long-term care centers.