• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.419-426
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• 2022

In this paper, we propose a method to improve the accuracy of 3D human pose estimation model in various move motions. Existing human pose estimation models have some problems of jitter, inversion, swap, miss that cause miss coordinates when estimating human poses. These problems cause low accuracy of pose estimation models to detect exact coordinates of human poses. We propose a method that consists of detection and correction methods to handle with these problems. Deep learning-based outlier detection method detects outlier of human pose coordinates in move motion effectively and rule-based correction method corrects the outlier according to a simple rule. We have shown that the proposed method is effective in various motions with the experiments using 2D golf swing motion data and have shown the possibility of expansion from 2D to 3D coordinates.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.195-203
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• 2021

This is descriptive research aimed at determining the relations with appearance satisfaction and self-efficacy in controlling job-seeking stress and at providing basic data necessary to decide on an education direction for better career maturity and explore psychological resources. For data collection, convenience sampling was performed among dental hygiene students consenting to participate in the research in Chungcheong and Jeolla Provinces to complete a self-administered questionnaire from November 25 to December 13, 2019. Appearance satisfaction was positively correlated with self-efficacy and was negatively correlated with job-seeking stress; self-efficacy was negatively correlated with job-seeking stress. The factors affecting job-seeking stress were self-efficacy, appearance satisfaction, and major satisfaction. It would be necessary to develop a practical counseling program targeting the combination of positive appearance acceptance and improvement in self-efficacy on the basis of correct aesthetic values with the objective of reinforcing job-seeking competence intensively among dental hygiene majors.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.89-91
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• 2022

본 논문에서는 생체인식 수단 중 하나인 손금을 이용한 생체인식에서 Attention U-Net을 기반으로 손금을 추출하는 방법을 제안한다. 손바닥의 손금 중 주요선이라 불리는 생명선, 지능선, 감정선은 거의 변하지 않는 특징을 가지고 있다. 기존의 손금 추출 방법인 비슷한 색상에서 손금 추출, 제한된 Background에서 손금을 추출하는 것이 아닌 피부색과 비슷하거나, 다양한 Background에서 적용될 수 있다. 이를 통해 사용자를 인식하는 생체인식 방법에서 사용할 수 있다. 본 논문에서 사용된 Attention U-Net의 특징을 통해 손금의 Segmentation 영역을 Attention Coefficient를 업데이트하며 효율적으로 학습할 수 있음을 확인하였다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.207-208
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• 2023

본 연구는 국내·외 미디어 콘텐츠 연구 동향을 분석함으로써 재난 안전 중심에서 바라본 한국의 미디어 콘텐츠 연구 및 활용의 발전 방향을 제안하고자 한다. 연구방법은 국내논문 431편, 해외논문 400편을 수집하였다. 수집된 자료는 R 프로그램으로 분석을 하였다. 분석한 결과를 바탕으로 재난 중심으로 바라본 미디어의 속성과 역할을 파악하고 한국의 4차 산업 중심의 미디어 콘텐츠 연구 및 활용의 발전 방향을 제시하였으며, 이는 재난 안전산업 중심의 미디어 연구 분야에 큰 도움이 된다고 본다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.181-182
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• 2022

본 연구의 목적은 성인학습자 교과과정 '융합형' 교수법을 통해 학습자 특성에 맞는 수업방법을 적용하고 개선방안을 모색하고자 하였다. 본 연구의 교수법을 효율적으로 달성하기 위해 4차에 걸쳐 진행되었다. 1차 '융합형' 교수법 적용 탐색, 2차 교수법 적용 지도법 논의, 3차 교수법 적용 및 보완, 4차 학습자 만족도 조사 및 분석 체계로 이루어졌으며, '융합형' 교수법 적용으로 아동(보육) 관련 교과목, 청소년 관련 교과목 위주의 공통 융합지도(하브루타 교수법, PBL 교수법)가 담당교수 별로 이루어졌다. 연구결과 첫째, '융합형 교수법'의 이론적 근거를 마련하여야 한다. 둘째, 현장연계 교과목 수업에 연계(아동, 청소년) 관련 기관과의 협력이 필요하다. 셋째, 학습자 전체가 참여할 수 있는 (토론회, 공청회) 등 프로그램 개발이 필요하다. 넷째, 다양한 자료, 기술, 기법을 통해 학습자의 동기유발이 필요하다.

• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.36-48
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• 2019

The purpose of this study is to investigate case studies and industry needs for convergence education in the fields of electronics, software, and automobiles, which are the technical foundations of the Fourth Industrial Revolution. Through the literature review, the convergence education programs focusing on electronics, software, and automobile were derived. The areas were validated by the experts review who consisted of three industry experts and professors in the relevant fields. Domestic and foreign curriculum were investigated to understand the current state of technical convergence education in each field. Industry needs survey for technical convergence education was conducted in cooperation with the Sector Council of Industrial Resources. Research instruments consisted of three parts: needs for technical convergence education, needs for the specific convergence education in the field of electronics, software, and automobile, and opinions on convergence education. A total of 341 participants responded to the questionnaires: 132 in the electronic field, 100 in the software field, and 109 in the automobile field. The industry needs for convergence education were analyzed and implications were suggested. The results of this study are expected to provide a guideline for developing convergence education programs in higher education.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.10
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• pp.102-111
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• 2021

Maintainability is a major design parameter that includes availability as well as reliability in a RAM (reliability, availability, maintainability) analysis, and is an index that must be considered when developing a system. There is a lack of awareness of the importance of predicting and analyzing maintainability; therefore, it is dependent on past-experience data. To improve the utilization rate, maintainability must be managed as a key indicator to meet the user's requirements for failure maintenance time and to reduce life-cycle costs. To improve the maintainability-prediction accuracy in the detailed design stage, we present a maintainability-prediction method that applies Method B of the Military Standardization Handbook (MIL-HDBK-472) Procedure V, as well as a Korean maintainability-prediction software package that reflects the system complexity.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.7
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• pp.80-88
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• 2021

The behavior of the injection system was determined through FFT and PSD analysis of the pressure data of the common rail, and when the diesel fuel is mixed with water, the pressure data of the common rail, depending on the water content and engine rotation speed, represent a different frequency component distribution. Recently, a theory has been suggested that mixing diesel fuel with water controls engine overheating, fuel efficiency, NOx, CO, etc., but if water content exceeds 10%, it can have a fatal adverse effect on the engine's injection system. In the future, it is necessary to promote fault diagnosis and prediction studies of diesel engines using FFT and PSD results from common rail pressure data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.3
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• pp.1-7
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• 2021

With the advent of industry 4.0, big data and machine learning techniques are being widely adopted in the maintenance domain. Inverters are widely used in many engineering applications. However, overloading and complex operation conditions may lead to various failures in inverters. In this study, failure mode effect analysis was performed on inverters and voltages collected to investigate the over-voltage effect on capacitors. Several features were extracted from the collected sensor data, which indicated the health state of the inverter. Based on this correlation, the best features were selected for classification. Moreover, random forest classifiers were used to classify the healthy and faulty states of inverters. Different performance metrics were computed, and the classifiers' performance was evaluated in terms of various health features.