• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.157-158
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• 2014

본 논문에서는 모바일용 맞춤형 웰니스 콘텐츠 추천을 위한 사용자 프로파일을 제안한다. 제안하는 프로파일에는 웰니스 콘텐츠를 제공받는 사용자의 웰니스 5 영역(신체, 정서, 사회, 지식, 정신) 각각의 선호도가 포함되어 있으며 사용자의 신변에 위험을 초래할 수 있는 신체적 제약 조건도 포함한다. 이 프로파일을 이용하면 사용자에게 맞춤형 웰니스 콘텐츠를 추천함에 있어 웰니스 5 영역을 모두 고려할 수 있으며 추가적으로 사용자의 질환 정보를 프로파일로 유지함으로서 사용자의 신체적 조건에 맞지 않는 콘텐츠를 선별하여 제외시키는 필터 및 안전 장치의 역할도 가능하게 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1338-1341
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• 2021

현재 대한민국 운송업에서 두 번째로 큰 비율(19.2%)을 차지하고 있는 수상 운송업에서는 연간 많은 재해가 발생하고 있으며 그 손해는 4백억 원에 달한다. 본 연구는 수상 운송업에서의 재해율과 경제적 손실을 최소화하기 위해 신체 측정기기 및 항만 작업 분배시스템을 설계하였다. 신체 측정기기는 심박, 알코올, 적외선 온도 센서 등을 활용하여 작업자의 신체 정보를 측정한다. 이 결과를 아두이노로 전송한 뒤 사용자의 집중도와 피로도를 분석하여 적절한 작업 분배 서비스를 제공한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.577-578
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• 2017

Existing exercise management systems provided exercise information to the user. However, there is a problem that the accuracy is low due to the absence of an algorithm for analyzing the user's body information and providing information. In this paper, BMI(Body Mass Index) and BMR(Basal Metabolic Rate) values are analyzed to analyze user's body information. It also recommends exercise intensity and momentum to the user and graphs the history of the exercise device that the user has used. Through this, it is considered that the information corresponding to the user's body can be provided and the exercise management can be carried out.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1109-1115
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• 2012

In this paper, we propose a system that recommends the appropriate menu using the fuzzy rules and the case database. The rules are defined by using the user's body information such as height and weight and these information is often vague. Due to its fuzziness, we use the fuzzy logic to represent the information. In our system, it firstly gets the body information for computing the BMI (Body Mass Index) values. Then it combines the muscle mass factor and BMI values to make a fuzzification for calculating the obesity rate. It finally recommends the most relative menu by comparing with the user's obesity rate from each cases in the database. We implement the system on the Android platform and show that our proposed method can achieve reasonable performance through the various experiments,

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.85-96
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• 2015

Despite the growth of body-related industry has generated considerable interest in this topic among both academics and practitioners, there has been lack of studies that explore body esteem toward online fashion products leads to purchase intentions, which self-monitoring moderates the relationship between body esteem toward online fashion products and purchase intentions. To fill this gap, this study aim to propose a research model where body esteem influences on the purchase intentions, with self-monitoring as a moderator. In order to test hypotheses, response from 172 consumers were achieved, and the proposed model was estimated by using hierarchical moderated regression analysis. The empirical results showed that body esteem negatively related to purchase intentions toward online fashion products. Additionally, this study indicated that the moderating effects of self-monitoring exist between body esteem and purchase intentions toward online fashion products, thereby implying the importance of contingent role of self-monitoring in managing online channels.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.139-145
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• 2019

The purpose of this study was to determined the effects of music rope skipping exercise on dynamic, static balance, and body compositions in intellectual disabilities men. The subjects were twenty men who were randomly devide into two groups (exercise group, n=10, and non-exercise group, n=10). The subjects done the music rope skipping exercise three times per week for 60 minutes each time for 12 weeks. As a results, there were significantly improved the dynamic and static balance abilities after music rope skipping exercise for 12 weeks. Also, There were significant differences in body weight and percent of body fat after the exercise program. Accordingly, It was effective improved on body balance abilities and body compositions after music rope skipping for 12 weeks in intellectual disabilities men.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.201-208
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• 2021

This study aims to provide the relevant basis upon which prediction of dyslipidemia should be made based on body information. Using the National Health Insurance big data (3,312,971 people) canonical correlation analysis was performed between body information and lipid-profile. Body information included age, height, weight and waist circumference, while the lipid-profile included total cholesterol, triglycerides, HDL cholesterol and LDL cholesterol. As a result, when the waist circumference and the weight are large, triglycerides increase and HDL cholesterol level decreases. In terms of age, weight, waist circumference, and HDL cholesterol, the canonical variates (the degree of influence) were significantly different according to sex. In particular, the canonical variate was dramatically changed around the forties and fifties in women in terms of weight, waist circumference, and HDL cholesterol. The canonical correlation results of the health care big data presented in this study will help construct a predictive model that can evaluate an individual's health status based on body information that can be easily measured in a non-invasive manner.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.45-54
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• 2022

The purpose of this study was to identify affecting factors on health behaviors among university students. A cross-sectional study was conducted with a sample of 161 participants between May and June 2020. The authors assessed functional health literacy, health self-efficacy, and health behaviors. Mean score of functional health literacy and health self-efficacy was 10.14±1.39 and 3.96±0.60, respectively. Of the subjects, 9.9% were smokers, 23.0% were problem drinking, 96.9% were those who needed monitoring of their eating habits, 63.4% were those with low or moderate physical activity, and 29.8% were those who were overweight or obesity. Gender and functional health literacy had an effect on smoking and eating habits, respectively. Gender and health self-efficacy were affecting factors on physical activity. Researchers should be sought strategies to promote health behavior considering gender, functional health literacy and health self-efficacy.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.611-624
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• 2012

'Gesture' is the most intuitive means of communication except the voice. Therefore, there are many researches for method that controls computer using gesture input to replace the keyboard or mouse. In these researches, the method of user detection and main body parts estimation is one of the very important process. in this paper, we propose user objects detection and main body parts estimation method on inaccurate depth information for pose estimation. we present user detection method using 2D and 3D depth information, so this method robust to changes in lighting and noise and 2D signal processing 1D signals, so mainly suitable for real-time and using the previous object information, so more accurate and robust. Also, we present main body parts estimation method using 2D contour information, 3D depth information, and tracking. The result of an experiment, proposed user detection method is more robust than only using 2D information method and exactly detect object on inaccurate depth information. Also, proposed main body parts estimation method overcome the disadvantage that can't detect main body parts in occlusion area only using 2D contour information and sensitive to changes in illumination or environment using color information.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.27-28
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• 2019

수술 시 시행되는 마취 과정에서 저혈압, 빈맥 등의 합병증이 다양한 정도로 발생한다. 이는 환자의 수술 후 심근경색이나 급성 신장 손상과 같은 심각한 합병증을 야기할 수 있으며 이러한 합병증들은 환자를 사망에 이르게 하는 원인이 되기도 한다. 본 연구에서는 머신러닝 기법을 활용해 전신마취 유도 중 저혈압 발생 환자를 예측하고자 한다. 순천향대학교 부천병원에서 수집된 207명 환자의 데이터를 이용하여 저혈압 발생 환자를 탐지하는 모델을 구축하였다. 의무 기록정보에 나타난 성별, 나이, 몸무게, 키, 신체적 상태 정보와 마취 유도 단계의 생체 신호 정보를 이용하였다. 신체적 상태 정보를 제외한 전체 피쳐를 모두 사용하였을 때, 탐지 정확도 68.06%, 관련 논문을 바탕으로 중요 피쳐만을 사용하여 실험하였을 때, 정확도 71.53%였으며, 환자의 신체적 상태 피쳐를 포함하여 실험하였을 때, 정확도 75%로 가장 우수한 결과를 얻었다.