• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.383-391
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• 2019

This study confirms the mediating effect of learning amotivation in the effect of an elementary school senior parental excessive interference on Internet addiction. To this end, 329 elementary school students in fifth and sixth grade were analyzed by collecting data on parental excessive interference, learning amotivation and Internet addiction. The results of the analysis are as follows. First, there was a significant static relationship between parental excessive interference, learning amotivation, and Internet addiction. Second, parental excessive interference had a significant effect on Internet addiction. Third, parental excessive interference had a significant effect on learning amotivation, and the learning amotivation affected a significant effect on Internet addiction. Through this process, it was confirmed that the learning amotivation has an indirect mediated effect on the effect of parental excessive interference on Internet addiction. Based on the results of this study, the educational implications of preventing Internet addiction among elementary school students and suggestions for follow-up research were discussed.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.7 no.2
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• pp.247-257
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• 1996

This is a preliminary report on the first segment of a continuing and prospective teaming disorder study project in Korea. Study subjects were 197 children, aged between 6 and 15 referred for psychiatric evaluation of scholastic problems. Demographic data, psychiatric diagnoses and intelligence and achievement test results were reviewed and analyzed. Analyses of data lead to the following conclusions : (1) About 20.8% of children referred for scholastic problems were diagnosed of teaming disorder(LD). The most prevalent diagnosis among these children with scholastic problem was emotional disorder, especially depressive disorder(33%), (2) The comorbid rate of attention deficit/hyperactivity disorder(ADHD) of 41 children with LD was 44%, (3) Male/female ratio was 5.8:1 among all of the LD children, 17:1 among children with LD and ADHD and 3.6:l among children with LD but without ADHD, (4) 83% of children with LD scored above middle level on socioeconomic status(SES), (5) Age, SES, IQ, family psychiatric history, past history of medical and psychiatric illness, onset of age, pattern of peer relationship, number of friends, presence of adaptation problem and academic achievements of children with LD and ADHD compared to those of children with LD but without ADHD. No significant differences between two groups were found on age, SES, IQ, family psychiatric history, past history of medical and psychiatric illness, pattern of peer relationship, number of friends and presence of adaptation problem. However, there were significant differences in academic achievements of Korean language total, speaking and listening score, arithmetic score, social science score and music score of children with LD and ADHD compared to those of children with LD but without ADHD. Also there was an ealier onset of age in LD and ADHD group when compared to LD but without ADHD group.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.25-30
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• 2009

Recent days intellectual systems using reinforcement learning are being researched at various fields of game and web searching applications. A good training models are called to be fitted with trainning data and also classified with new records accurately. A overfitted model with training data may possibly bring the unfavored fallacy of hasty generalization. But it would be unavoidable in actual world. The entropy and mutation model are suggested to reduce the overfitting problems on this paper. It explains variation of entropy and artificial development of entropy in datamining, which can tell development of mutation to survive in nature world. Periodical generation of maximum entropy are introduced in this paper to reduce overfitting. Maximum entropy model can be considered as a periodical generalization in intensified process of intellectual web searching.

• Journal of the Korean Academy of Pediatric Dentistry
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• v.48 no.2
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• pp.221-228
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• 2021

The aim of this study was to evaluate the use of easily accessible machine learning application to identify mesiodens, and to compare the ability to identify mesiodens between trained model and human. A total of 1604 panoramic images (805 images with mesiodens, 799 images without mesiodens) of patients aged 5 - 7 years were used for this study. The model used for machine learning was Google's teachable machine. Data set 1 was used to train model and to verify the model. Data set 2 was used to compare the ability between the learning model and human group. As a result of data set 1, the average accuracy of the model was 0.82. After testing data set 2, the accuracy of the model was 0.78. From the resident group and the student group, the accuracy was 0.82, 0.69. This study developed a model for identifying mesiodens using panoramic radiographs of children in primary and early mixed dentition. The classification accuracy of the model was lower than that of the resident group. However, the classification accuracy (0.78) was higher than that of dental students (0.69), so it could be used to assist the diagnosis of mesiodens for non-expert students or general dentists.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.574-579
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• 2009

There have been much difficulties to construct an optimized neural network in complex nonlinear regression problems such as selecting the networks structure and avoiding overtraining problem generated by noise. In this paper, we propose a stepwise constructive method for neural networks using a flexible incremental algorithm. When the hidden nodes are added, the flexible incremental algorithm adaptively controls the number of hidden nodes by a validation dataset for minimizing the prediction residual error. Here, the ELM (Extreme Learning Machine) was used for fast training. The proposed neural network can be an universal approximator without user intervene in the training process, but also it has faster training and smaller number of hidden nodes. From the experimental results with various benchmark datasets, the proposed method shows better performance for real-world regression problems than previous methods.

• Annual Conference of KIPS
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• 2023.11a
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• pp.695-697
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• 2023

최근 몇 년 간 딥러닝 기반 모델의 규모와 복잡성이 증가하면서 강력하고, 높은 정확도가 확보되지만 많은 양의 계산 자원과 메모리가 필요하기 때문에 모바일 장치나 임베디드 시스템과 같은 리소스가 제한된 환경에서의 배포에 제약사항이 생긴다. 복잡한 딥러닝 모델의 배포 및 운영 시 요구되는 고성능 컴퓨터 자원의 문제점을 해결하고자 사전 학습된 대규모 모델로부터 가벼운 모델을 학습시키는 지식증류 기법이 제안되었다. 하지만 현대 딥러닝 기반 모델은 높은 정확도 대비 훈련 데이터에 과적합 되는 과잉 확신(overconfidence) 문제에 대한 대책이 필요하다. 본 논문은 효율적인 경량화를 위한 미리 학습된 모델의 과잉 확신을 방지하고자 초점 손실(focal loss)을 이용한 모델 보정 기법을 언급하며, 다양한 손실 함수 변형에 따라서 지식증류의 성능이 어떻게 변화하는지에 대해 탐구하고자 한다.

• Journal of Preventive Medicine and Public Health
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• v.26 no.4 s.44
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• pp.628-649
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• 1993

This study was conducted to investigate the factors related to the poor school performance of the elementary school children. Two schools in Taegu, one in the affluent area and the other in the poor area, were selected and a total of 175 children whose school performance was within low 10 percentile (poor performers) and 97 children whose school performance were within high 5 percentile (good performers) in each class of 2nd, 4th and 6th grades were tested for the physical health, behavioral problem and family background. Each child had gone through a battery of tests including visual and hearing acuity, anthropometry (body weight, height, head circumference), intelligence (Kodae Stanford-Binet test), test anxiety (TAI-K), neurologic examination by a developmental pediatrician and heavy metal content (Pb, Cd, Zn) in hair by atomic absorption spectrophotometry. A questionnaire was administered to the mothers for prenatal and prenatal courses of the child, family environment, child's developmental history, and child's behavioral and learning problems. Another questionnaire was administered to the teachers of the children for the child's family background, arithmatic & language abilities and behavioral problem. The poor school performance had a significant correlation with male gender, high birth order, broken home, low educational and occupational levels of parents, visual problem, high test anxiety score, attention deficit hyperactivity disorder (ADHD), poor physical growth (weight, height, head circumference) and low I.Q. score. The factors that had a significant correlation with the poor school performance in multiple logistic regression analysis were child's birth order (odds ratio=2.06), male gender(odds ratio=5.91), broken home(odds ratio=9.29), test anxiety score(odds ratio=1.07), ADHD (odds ratio=9.67), I.Q. score (odds ratio=0.85) and height less than Korean standard mean-1S.D.(odds ratio=11.12). The heavy metal contents in hair did not show any significant correlation with poor school performance. However the lead and cadmium contents were high in males than in females. The lead content was negatively correlated with child's grade(P<0.05) and zinc was positively correlated with grade (P<0.05). among the factors that showed a significant correlation with the poor school performance, high birth order, short stature and ADHD may be modified by a good family planning, good feeding practice for infant and child, and early detection and treatment of ADHD. Also, teacher and parents should restrain themselves from inducing excessive test anxiety by forcing the child to study and over-expecting beyond the child's intellectual capability.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.13 no.1
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• pp.93-103
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• 2002

The aim of this study is to examine the diagnostic profiles and related clinical variables of children with attention and hyperactivity in psychiatric outpatient clinic. Seventy one children with age range of 5 to 14 were diagnosed by DSM-IV, and assessment battery including KEDI-WISC, KPI-C, ADS(ADHD Diagnostic System) were completed. The subjects were divided into 3 diagnostic groups：ADHD only(n=17), ADHD comorbid(n=27), Other diagnosis(n=27). The results were as follows：In ADHD comorbid group, tic disorder, developmental language disorder, borderline intellectual function, oppositional defiant/conduct disorder, and learning disorder were combined in descending order. Other diagnosis group consisted of tic disorder, borderline intellectual function, depression/anxiety, oppositional defiant/conduct disorder, and others. There were significant differences in IQ, PIQ, and VIQ among the three groups, and ADHD only group showed higher scores of IQ and VIQ than ADHD comorbid group. On the KPI-C, there were no significant differences in all subscales among the three groups. On the visual ADS, omission error and sensitivity showed significant differences among the three groups, and ADHD comorbid group represented higher omission error and lower sensitivity than other diagnostic group. The findings indicated that the inattention and hyperactivity symptoms could be diagnosed into diverse psychiatric disorders in child psychiatry, and ADHD children with comorbidity will show more problems in academic performance and school adjustment.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.63-65
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• 1999

인터넷의 발달은 정보의 폭발적인 증가를 가져오게 되었고 더불어 일반인은 어디서나 쉽게 정보를 습득할 수 있게 되었지만 늘어나는 정보의 양이 원하는 정보의 습득을 방해하게 되었다. 이러한 정보 과잉현상을 해결하기 위해 사용자가 원하는 정보만을 여과해 주는 정보 여과 시스템이 연구되고 있다. 정보 여과 시스템은 사용자의 관심도를 파악하기 위 해 사용자 프로파일을 구축하고 이를 학습을 통해 갱신한다. 하지만 기존의 개인 프로파일을 이용한 정보 여과 시스템은 개인의 관심도를 분석하기 위해 에이전트가 학습하는 시간이 너무 오래 걸린다는 단점과 사용자의 능력에 따라 적합한 문서를 검색하기 위한 정보가 너무 한쪽으로만 치우치는 우려가 있다. 따라서 본 논문은 효과적인 프로파일 학습을 위해 비슷한 관심도를 갖는 다른 사용자로부터 학습을 받는 방법을 제안한다. 이를 위해 그룹 프로파일을 구축하는 방법과 그룹 프로파일을 이용한 효과적인 정보 여과 방법, 그리고 그룹 프로파일 학습방법에 대해 기술한다.

• Journal of Korean Home Economics Education Association
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• v.16 no.3
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• pp.99-113
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• 2004

This study evaluated the effects of maternal food environment on food behavior and hyperactivity of preschoolers. The subjects consisted of 270 children aged 5-6 years and 330 their mother. The food behavior and hyperactivity of the children were measured simultaneously by both children's mother and their teachers using the same checklists. And maternal food environment was performed by self-administered questionnaire. Mother's food value was significantly influenced by their employment status and parenting behavior. but was not affected by the levels of their education and household income. Children's hyperactivity was significant influenced by their sleep status, mother's education level and parenting behavior(p<0.05). A significant difference was noted children's food behavior with the teacher's assessment upon the association with hyperactivity(p<0.05) but was not significantly related to it by mother's checklist. The mother's food value(p<0.001) and food behavior(p<0.05) were significantly related to the their children's food behavior and hyperactivity. These results showed that maternal food environment plays an important role in children's food behavior and hyperactivity.