• Journal of Chest Surgery
• /
• v.34 no.4
• /
• pp.311-321
• /
• 2001

배경: 본 연구에서는 16년간 본원에서 시행한 완전방실중격결손 환자의 수술성적을 고찰하고 수술후 사망 및 술후 잔존 좌측방실판막부전의 발생에 관여하는 위험인자들을 분석하고자 하였다. 대상 및 방법: 본원에서 84년 7월부터 2000년 6월까지 수술한 완전방실중격결손 환자 70명의 임상기록을 후향적으로 연구관 하였다. 70명의 대상환자중 남아 환아는 36명 여아 환아는 34명이었고 연령분포는 1개월에서 19세였다.(평균나이는 32.$\pm$71.9개월). 이중 다운증후군이었던 환자는 39명(55.7%)이었으며 술후 라스텔리 분류 A형이 42명(60.0%), B형이 6명(8.6%), C형이 20명(28.6%)이었고 기록상으로 분류를 확인 할 수 없는 경우가 2명 (2.9%)이었다. 결과: 9(12.9%)명에서 술후 조기사망했으며, 이를 기간별로 비교해 보면 1996년 이전은 20.0%, 1996년 이후 최근 5년간은 7.7% 였으며 둘 사이의 통계학적 유의한 차이는 없었다. 술후 10명(14.3%)에서 3도이상의 잔존좌측방실판막부전을 보였다. 5년 및 10년 장기 생존율은 79.4%였고, 4명의 환자에서 5례의 재수술을 시행하였으며 5년간의 7.7% 였으며 둘이상의 통계학적 유의한 차이는 없었다. 술후 10명(14.3%)에서 3도이상의 잔존 좌측방실판막부전을 보였다. 5년 및 10년 장기 생존율은 79.4% 였고, 4명의 환자에서 5례의 재수술을 시행했으며 5년 및 10년 장기 재수술 회피율은 91.4%였다. 수술후 사망에 관여하는 위험인자 분석을 시행하여 술후 잔존좌측방식판막부전이 3도 이상인 겨우 오즈비가 38.5 (p<0.001)로 통계적으로 유의한 위험 인자로 나타났다. 또한 술후 잔존좌측방실판막부전의 발생에 관여하여 위험인자 분석을 시행하여 술후 좌측방실판막의 교련을 교정한 경우 오즈비가 6.72(p=0.02)로 통계적으로 유의한 위험인자로 나타났다. 결론: 1세이하 환아를 포함한 완전방실중격결손증의 수술은 낮은 수술사망율과 재수술율 그리고 양호한 장기성적으로 보였다. 또한 이에는 3도 이상의 잔존 좌측방실판막부전의 발생이 술후 사망에 중요한 위험인자로 기여하여 수술적 교정후 잔존 좌측방실판막부전의 정도를 줄이고 좌측방실판막의 양호환 교합을 유지하기 위해서는 완전방실중격결손증의 방실판막의 다양한 해부학적 형태로 따른 개별적인 접근법이 유효하다고 생각한다.고 생각한다.

• Korean Journal of Psychosomatic Medicine
• /
• v.23 no.1
• /
• pp.20-25
• /
• 2015

Objective:To review the patterns of the dermatologic consultations of psychiatric adolescent inpatient and to explore the relationship between the dermatologic disorders and psychiatric disorders. Methods:We retrospectively studied the data from 22 cases referred by psychiatric adolescent for a dermatologic consultation over 10 years in Daegu Catholic University Medical Center and compared with the data from 108 cases referred by the other department adolescent patients. Results:The mean age of patients was 15.9. The male to female ratio was 1:1.44. The most common psychiatric and dermatologic disorder was major depressive disorder and acne, respectively. The most frequent reason for consultation was to ask for dermatologic disease or condition(54.5%) followed by to perform cosmetic procedure of patients need(40.9%) and to perform dermatologic test(4.6%). Conclusions:More than just a cosmetic disfigurement, dermatologic disorders are associated with a variety of psychopathologic problems that can affect the patient. Increased understanding of biopsychosocial approaches and liaison among psychiatrists and dermatologists could be beneficial.

• Journal of Korean Society of Forest Science
• /
• v.107 no.4
• /
• pp.402-411
• /
• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• 재활복지
• /
• v.21 no.3
• /
• pp.129-146
• /
• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.346-353
• /
• 2020

The purpose of this study was to explore types of longitudinal changes in interactions between mothers and 4-year-old children in primary school as well as the effects on media device addiction. To explore interaction types between mothers and children, latent class growth modeling (LCGM) and BCH were used in a three-step approach. Data from the 6-10th wave of the Panel Study of Korea Children were used. First, the trajectory of the mother-child interactions was linear and decreased across time. This linear decrease was classified into the following three trajectories: high-decreasing, average-deceasing, and low-decreasing. Second, BCH was performed to examine media device addiction in each trajectory, and the findings show that children who had low initial mother-child interactions over time were more likely to experience daily disturbances in adaptive functions such as withdraw or tolerance than other groups of children. The results indicate that maximizing the quality of mother-child interactions in childhood through primary school can lower media device addiction in children.

• Journal of The Korean Association For Science Education
• /
• v.42 no.5
• /
• pp.543-555
• /
• 2022

This study aims to identify the trends in 'Aesthetic Science-Education' research through bibliographic analysis and provide future implications for research in this field. To this research, 100 studies were extracted using the search function of the Web of Science provided by Clarivate Analytics. Detailed bibliometrics was analyzed using the Bibliometrix package of the R program. As a result of the analysis, the average number of papers increased from 1993 to 2022, and academic journals in which related papers were published were evenly distributed locally. As a result of keyword analysis, papers with top citations, author collaboration networks, and literature co-citation networks, Aesthetic Science-Education could be classified as inducing aesthetic experience by integrating art in science education, and categories using 'formalist aesthetic' and 'emotional response'. The implications derived from this study are as follows: first, the aesthetic aspects of science should be actively studied to emphasize 'Agency' and 'Active Learning' in future science education. Second, it is necessary to develop a new approach to science education by further utilizing the 'formalist aesthetic' of science in science education. Third, the aesthetic aspect of science can change the perception of the Nature of Science of teachers, pre-service science teachers, and students. Fourth, it is necessary to discover implications for utilizing aesthetic aspects in science education through extensive research on the aesthetic aspects of science for teachers, students, and pre-service teachers. This study is meaningful because it provides an overview of the 'Aesthetic Science-Education' research to realize the above implications.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.241-265
• /
• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.2B
• /
• pp.173-179
• /
• 2009

Industrial water supplied by water resource project is essential input materials along with labor, capital and land for companies. It is very important to stably secure these input materials in order for the industry to generate additional values. If the supply of industrial water is stopped, it is known damage for the industry is greater than domestic water or agriculture water based on same amount of supply. Like this, the actual value of industrial water has been highly acknowledged from the intuitive perspective, but study on the value and benefits of industrial water has been rarely conducted. Therefore, this study verified the value of industrial water supplied from water resource project, and used marginal production value as a measure to estimate the benefits of industrial water in the analysis of economic efficiency. As a result of empirical analysis using Cobb-Douglas production function and Translog production function, industries' average marginal production value was $5,427KRW/m^3$ and $5,583KRW/m^3$ respectively. The marginal production value for eleven industries were estimated by using same method. The marginal production value by industries presented by this study will be used as important data to calculate benefits of industrial water in the future. Moreover, the result of this study will provide reasonable criteria for decision making on the allocation of water in emergency situation, and problem of resource supply from water resource project.

• Clinical and Experimental Reproductive Medicine
• /
• v.35 no.4
• /
• pp.303-308
• /
• 2008

Purpose: The purpose of this study is to determine the effect of preoperative semen parameters on both seminal improvement and pregnancy rates following varicocelectomy. Methods: This survey was done in 278 patients who underwent microsurgical inguinal varicocelectomy from January 2001 until October 2006. By the total motile sperm counts (TMSC) before operation, the patients were stratified into three groups. Group A (mild oligoasthenospermia) was defined as above 20 million, group B (moderate oligoasthenospermia) was defined as between 5 and 20 million, and group C (severe oligoasthenospermia) was defined as below 5 million. Improvement rates of TMSC and pregnancy rates following varicocelectomy of each groups were compared. Results: The average TMSC of all the patients was 25.75 million before operation and after operation, it was 80.24 million, showing an average increase of 54.49 million (211.6%). To take a look at mean absolute increase (mean relative increase proportion), group A showed 67.90 million (131.2%), group B 62.20 million (482.5%) and group C 26.33 million (1841.2%). The patients with varicocele whose semen parameter is in bad condition show relatively a low mean absolute increase but high mean relative increase proportion. There was no significant difference in natural pregnancy rate among each groups (p=0.119, p=0.059). Conclusions: Even in the varicocele patient whose semen parameter was in bad condition before surgical operation. varicocelectomy could be chosen as the first treatment to male infertility.

• Journal of radiological science and technology
• /
• v.40 no.2
• /
• pp.205-211
• /
• 2017

There is a need for aggressive diagnosis and treatment in middle-aged and high-risk individuals who are more likely to progress from nonalcoholic fatty liver to hepatitis. In this study, nonalcoholic fatty liver was divided into severe, moderate, and severe, and classified by quantitative method using computer analysis of GLCM algorithm. The purpose of this study was to evaluate the characteristics of ultrasound images in the local fat avoidance region. Normal, mild, moderate, severe fatty liver, and focal fat sparing area, 80 cases, respectively. Among the parameters of the GLCM algorithm, the values of the Autocorrelation, Square of the deviation, Sum of averages and Sum of variances with high recognition rate of the liver ultrasound image were calculated. The average recognition rate of the GLCM algorithm was 97.5%. The result of local fat avoidance image analysis showed the most similar value to the normal parenchyma. Ultrasonography can be easily accessed by primary screening, but there may be differences in the accuracy of the test method or the correspondence of results depending on proficiency. GLCM algorithm was applied to quantitatively classify the degree of fatty liver. Local fat avoidance region was similar to normal parenchyma, so it could be predicted to be homogeneous liver parenchyma without fat deposition. We believe that GLCM computer image analysis will provide important information for differentiating not only fatty liver but also other lesions.