• Journal of the Korean Society of Physical Medicine
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• v.14 no.2
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• pp.97-105
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• 2019

PURPOSE: This study examined the factors related to school-based activity performance in school-aged children with spastic cerebral palsy (CP). METHODS: The Gross Motor Function Systems (GMFCS), Manual Ability Classification System (MACS), Communication Function Classification System (CFCS) as functional classifications, and the physical activity performance of the School Function Assessment (SFA) were measured in 79 children with spastic CP to assess the student's performance of specific school-related functional activities. RESULTS: All the function classification systems were correlated significantly with the physical activity performance of the SFA ($r_s=-.47$ to -.80) (p<.05). The MACS (${\beta}=-.59$), GMFCS (${\beta}=-.23$), CFCS (${\beta}=-.21$), and age (${\beta}=-.15$) in order were predictors of the physical activity performance of the SFA (84.8%)(p<.05). CONCLUSION: These functional classification systems can be used to predict the school-based activity performance in school-aged children with CP. In addition, they can contribute to the selection of areas for intensive interventions to improve the school-based activity performance.

• Journal of the Korea Fashion and Costume Design Association
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• v.1 no.1
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• pp.141-156
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• 1999

This paper is to analyze the classification of textile pattern design focusing on the 19th century in England. The purpose of this study is. firstly to research the thoughts and ideas of these design in the time of mid-Victorian age; Secondly. to classify the textile pattern design from many points of view. We could find such William Morris's thought and ideas of 19th century to reform from textile pattern design. We wish to use these studies for textile pattern designers to develop this tradition onward to modern and future trends.

• The Journal of the Korean dental association
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• v.19 no.12 s.151
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• pp.1027-1030
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• 1981

2065 patients who visited orthodontic department form 1977. 7. 16. to 1981. 9. 30. were surveyed on the yearly tendency of patient distribution and the state of Angle's Classification. The results were as follows: 1. There was increased visiting rate of patient per year except the year 1980. 2. 8-13 age group was 55% in total visiting patient and 20 age over group was 11.0%. 3. Class I malocclusion was 42.3% in total visiting patient, more Class III malocclusion was prevalent than Class II malocclusion.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.483-486
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• 2020

Age estimation and gender classification for human is a classic problem in computer vision. Almost research focus just only one task and the models are too heavy to run on low-cost system. In our research, we aim to apply multitasking learning to perform both task on a lightweight model which can achieve good precision on embedded system in the real time.

• Smart Media Journal
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• v.10 no.2
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• pp.22-29
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• 2021

In the past decade, deep learning has been applied to various medical image analysis tasks. Skeletal bone age estimation is clinically important as it can help prevent age-related illness and pave the way for new anti-aging therapies. Recent research has applied deep learning techniques to the task of bone age assessment and achieved positive results. In this paper, we propose a bone age prediction method using a deep convolutional neural network. Specifically, we first train a classification model that automatically localizes the most discriminative region of an image and crops it from the original image. The regions of interest are then used as input for a regression model to estimate the age of the patient. The experiments are conducted on a whole-body scintigraphy dataset that was collected by Chonnam National University Hwasun Hospital. The experimental results illustrate the potential of our proposed method, which has a mean absolute error of 3.35 years. Our proposed framework can be used as a robust supporting tool for clinicians to prevent age-related diseases.

• Journal of The Korean Association For Science Education
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• v.31 no.5
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• pp.709-719
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• 2011

The purpose of this study was to identify the differences in classification skills shown in classification activities between the gifted and regular students in elementary schools. The subjects for the research consisted of six gifted students in an institute for the gifted for science annexed to P school district in Gangwon-do and 6 students at B and M general elementary schools. Results were as follows: The time taken for classification activities of the gifted was shorter than regular regardless of subjects for classifying. The number of standards for classifying for the gifted was more than regular students. Coefficient for measuring classification skills of the gifted was higher than regulars regardless of age. Consequently, there was a difference in the time taken for classifying and generating the number of standards and in a numerical index of classification activities performed at science classes between the science gifted and the regular students.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.11-21
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• 2018

Research is carried out to categorize voices using Deep Learning technology. The study examines neural network-based sound classification studies and suggests improved neural networks for voice classification. Related studies studied urban data classification. However, related studies showed poor performance in shallow neural network. Therefore, in this paper the first preprocess voice data and extract feature value. Next, Categorize the voice by entering the feature value into previous sound classification network and proposed neural network. Finally, compare and evaluate classification performance of the two neural networks. The neural network of this paper is organized deeper and wider so that learning is better done. Performance results showed that 84.8 percent of related studies neural networks and 91.4 percent of the proposed neural networks. The proposed neural network was about 6 percent high.

• Journal of Nutrition and Health
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• v.26 no.8
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• pp.942-952
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• 1993

This study was to investigate if Body Mass Index(BMI) is adequate as a method of physique classification of Korean female college students. For this study 571 students were selected to examine physique classification by anthropometric index, and the correlation between the various anthropometric index and risk facters(blood pressure, triglyceride, hematocrit). The following results were obtained by this study. 1) Average age of the subjects is 19.6, height 158.2cm and weight 54.4g. 2) All anthropometric indices and body fat percentage are highly correlated (r>0.713), among them BMI shows high and significant positive correlation with weight(r=0.919) and skinfold thickness(r>0.601), but negative correlation with height(r=-0.086). 3) All anthropometric indices and body fat percentage show significant correlation with blood pressure and triglyceride. Among them BMI shows high and significant positive correlation with blood pressure and triglyceride. 4) FAT% III calculated of BMI shows significant with FAT% I and FAT% II by skinfold thickness, and high correlation with blood pressure and triglyceride. Therefore FAT% III is adequate for calculation method of body fat percentage.

• PNF and Movement
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• v.7 no.2
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• pp.21-26
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• 2009

Purpose : The aim of this study was to determine the reliability of parents and therapists-assessed manual ability using the Manual Ability Classification System (MACS) for children with cerebral palsy Methods : Subjects were 136 children with cerebral palsy using rehabilitation programs in 16 welfare centers. Reliability was determined using the intraclass correlation coefficient (ICC). Parents and therapists assessed manual ability of children using MACS. Result : The 136 children (Male 73, Female 63) mean age was 7y 5mo years [range 3y 11mo - 13y 5mo]. The overall agreement between parents-assessed and therapists- assessed MACS was good (ICC = 0.84, 95% confidence interval 0.77-0.88). Conclusion : The MACS offers a reliable method for population-based research and communicating about the manual ability of children with CP.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.28 no.1
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• pp.20-24
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• 2017

Laryngomalacia is the most common congenital anomaly that causes inspiratory stridor and airway obstruction in the newborn. Symptoms begin to appear after weeks of age, become worse at 4-8 months, improve between 8-12 months, and usually heal naturally at 12-18 months. Despite these common natural processes, the symptoms of the disease can be very diverse and, in severe cases, require surgical treatment. The diagnosis can be made by suspicion of clinical symptoms and direct observation of the larynx with the spontaneous breathing of the child. Typical laryngeal features include omega-shaped epiglottis, retroflexed epiglottis, short aryepiglottic fold, poor visualization of the vocal folds, and edema of the posterior glottis, including inspiratory supra-arytenoid tissue prolapse. In this review, we discuss the classification and treatment based on symptoms and laryngoscopic findings in patients with laryngomalacia.