• 방송공학회논문지
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• 제9권2호
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• pp.164-173
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• 2004

본 논문에서는 등장인물 검출 및 인식과 함께 등장인물의 출연 구간 분석이 가능한 시스템을 제안한다. 드라마, 스포츠와 같은 방송 비디오는 그 특성상 인물이 중심이 되며 각 시점에 등장하는 주요 인물은 방송용 비디오의 중요한 특징이 된다. 본 논문에서는 비디오에서 등장하는 주요 인물을 자동으로 분석하는 ACAV(Automatic Cast-list Analysis in Videos) 시스템을 제안한다. ACAV 시스템은 등장인물을 자동 검출하여 인물 DB에 등록하는 FAGIS(FAce reGIStration)와 생성된 인물 DB을 이용하여 등장인물을 분석하는 FACOG(FAce reCOGnition)로 구성된다. 기존의 상용화된 등장인물 분석 시스템인 FaceIt과의 성능 비교를 통해 ACAV의 성능을 검증하였다. 얼굴 검출 실험에서 ACAV의 얼굴 검출률은 84.3%로 FaceIt 보다 약 30% 높았고, 얼굴 인식 실험에서도 ACAV의 얼굴 인식률은 75.7%로 FaceIt 보다 27.5% 높은 성능을 보였다. ACAV 시스템은 방송 멀티미디어 공급자를 위한 대용량 비디오 관리 시스템으로 이용될 수 있으며 일반 사용자를 대상으로 한 PVR(Personal Video Recorder), 모바일 폰 등의 비디오 관리 시스템으로도 이용될 수 있다.

• 공학교육연구
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• 제25권2호
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• pp.32-41
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• 2022

The purpose of this study was in a pandemic situation caused by COVID-19 to explore the online distance experiments and interaction of engineering freshmen, and to identify practical difficulties, resulting in to derive implications. Seven freshmen from engineering college participated in the interview, of which data were analyzed based on phenomenological analysis methods. The types of non-face-to-face experiments experienced by students were complete non-face-to-face experiment, mixed face-to-face experiment, and fusion face-to-face experiment. Students were completely isolated in time and space in complete non-face-to-face experiment. In biweekly mixed face-to-face experiment, isolation was halved. In fusion face-to-face experiment, isolation was removed. Non-face-to-face interactions can be characterized by restrictions on simultaneous activities, on rapport formation, and on observation opportunities. Based on these results, three implications were derived: First, it is necessary to allow students to manage time and space constraints on their own in non-face-to-face experiments. Second, support is needed to solve the difficulty of forming rapport, which is a characteristic of non-face-to-face interaction. Third, an opportunity to observe the interaction between other students and professors should be provided.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2001년도 제34회 추계학술대회 개최
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• pp.341-349
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• 2001

Heat distortion of the non-contacting mechanical face seal is affected by friction heat between primary seal and seal sheet. The fluid or gas in mechanical face seal maintains operating gap, cooling friction heat and lubricates at the face of seal. So we designed face of seal for inclined face. inclined face of seal improves fluid or gas flow at the face of seal and it increases circumferential velocity at outer radius of the seal so temperature of the seal is decreased by low heat transfer coefficient at there. In this paper, inclined face seal are analysed numerically using finite element method for proof improve inclined face seal performance. Angle of the incline face used for FEA is from 50$^{\circ}$to 90$^{\circ}$and for explaining the effects of inclined face in seal, we get temperature, face distortion, and stress in the seal with variable operating gap and rotating speeds. Result of analysis shows that angle of the incline face is 60$^{\circ}$come to good thermal distortion characteristics.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.277-301
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• 2021

Purpose The purpose of this study is to analyze the sentiment responses of the general public to non-face-to-face work using text mining methodology. As the number of non-face-to-face complaints is increasing over time, it is difficult to review and analyze in traditional methods such as surveys, and there is a limit to reflect real-time issues. Approach This study has proposed a method of the research model, first by collecting and cleansing the data related to non-face-to-face work among tweets posted on Twitter. Second, topics and keywords are extracted from tweets using LDA(Latent Dirichlet Allocation), a topic modeling technique, and changes for each section are analyzed through DTM(Dynamic Topic Modeling). Third, the complaints of non-face-to-face work are analyzed through the classification of positive and negative polarity in the COVID-19 section. Findings As a result of analyzing 1.54 million tweets related to non-face-to-face work, the number of IDs using non-face-to-face work-related words increased 7.2 times and the number of tweets increased 4.8 times after COVID-19. The top frequently used words related to non-face-to-face work appeared in the order of remote jobs, cybersecurity, technical jobs, productivity, and software. The words that have increased after the COVID-19 were concerned about lockdown and dismissal, and business transformation and also mentioned as to secure business continuity and virtual workplace. New Normal was newly mentioned as a new standard. Negative opinions found to be increased in the early stages of COVID-19 from 34% to 43%, and then stabilized again to 36% through non-face-to-face work sentiment analysis. The complaints were, policies such as strengthening cybersecurity, activating communication to improve work productivity, and diversifying work spaces.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2327-2330
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• 2003

This paper deals with face detection and recognition using ellipsodal information and wavelet packet analysis. We proposed two methods. First, Face detection method uses general ellipsodal information of human face contour and we find eye position on wavelet transformed face images A novel method for recognition of views of human faces under roughly constant illumination is presented. Second, The proposed Face recognition scheme is based on the analysis of a wavelet packet decomposition of the face images. Each face image is first located and then, described by a subset of band filtered images containing wavelet coefficients. From these wavelet coefficients, which characterize the face texture, the Euclidian distance can be used in order to classify the face feature vectors into person classes. Experimental results are presented using images from the FERET and the MIT FACES databases. The efficiency of the proposed approach is analyzed according to the FERET evaluation procedure and by comparing our results with those obtained using the well-known Eigenfaces method. The proposed system achieved an rate of 97％(MIT data), 95.8％(FERET databace)

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.305-309
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• 2006

In this paper, a face recognition algorithm system using Principle Component Analysis is proposed. The algorithm recognized a person by comparing characteristics (features) of the face to those of known individuals which is a face database of Intelligence Control Laboratory(ICONL). Experiments were simulated in order to demonstrate the performance of this algorithm due to face recognition which presented for the classification of face and non-face and the classification of known and unknown.

• 디지털산업정보학회논문지
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• 제17권3호
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• pp.121-132
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• 2021

The purpose of this study is to explore ways to improve the quality of real-time video lectures in a non-face-to-face environment using IPA (Importance-Performance Analysis). Recently, due to the impact of COVID-19 in universities, all remote classes are being implemented, so research is needed to raise learner awareness. Accordingly, factor analysis, mean analysis, correspondence analysis, and IPA analysis were performed based on the data of 632 students who responded from March 21 to June 30, 2021 for learners of K University in Chungbuk. First, overall satisfaction was low compared to importance, and the difference in system perception was the largest. Second, the difference in learner perception of real-time video lectures through the IPA matrix showed that the system error and screen cutoff were the largest. Third, the difficulty of lecture content, task and test feedback, etc. are classified. Accordingly, the satisfaction of real-time video lectures in non-face-to-face environments is low, suggesting that school-level support for quality improvement to improve learner satisfaction in non-face-to-face environments and the role of instructors are needed to improve learners' academic achievement.

• 한국의류학회지
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• 제31권11호
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• pp.1487-1499
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• 2007

In this study, photographs of 600 Korean females aged from 20 to 50years old were indirectly measured in Venus face 2D program. The measurements were analyzed by statistical methods. The purpose of this study was to differentiate the facial types of adult women for the beauty industry. As a result of factor analysis, 6 factors were selected the key factors of facial shape: head height(factor 1), head width(factor 2), side face width(factor 3), head width and circumference(factor 4), face length(factor 5), and side face width(factor 6). We categorized facial type into 5 groups with the previous 6 factor. 5 types were most common facial shapes: Oblong face(type 1), Square face(type 2), Oval face(type 3), Round face(type 4), Triangle face(type 5). The results of facial type analysis were showed that Round face(26.6%), Triangle face(25.3%), Oval face(22.3%), Square face(20.0%), Oblong face(5.7%).

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.193-200
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• 1999

Since Broms and Bennermark(1967) suggested the face stability criterion based on laboratory extrusion tests and field observations, the face stability of a tunnel driven in cohesive material has been studied by several authors. And recently, more general solution for the tunnel front is given by Leca and Panet(1988). They adopted a limit state design concept to evaluate the face stability of a shallow tunnel driven into cohesionless material and showed that the calculated upper bound solution represented the actual behavior reasonably well. In this study, two factors are simultaneously considered for assessing tunnel face stability: One is the effective stress acting on the tunnel front calculated by upper bound solution; and the other is the seepage force calculated by numerical analysis under the condition of steady state ground water flow. The model tests were performed to evaluate the seepage force acting on the tunnel front and these results were compared with results of numerical analysis. Consequently, the methodology to evaluate the stability of a tunnel face including limit analysis and seepage analysis is suggested under the condition of steady state ground water flow.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2017년도 제48회 춘계학술대회논문집
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• pp.776-777
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• 2017

고체 추진제의 성능을 계산하기 위해서는 그레인 burn-back 해석 과정이 필요하다. 기존의 그레인 burn-back 해석은 level set method를 사용하였으나 표면 이동 해석에서 문제가 발생 하였다. 이에 본 연구에서는 face offsetting method를 적용하여 표면 이동 해석을 수행 하였다. 해석 결과, face offsetting method가 그레인 burn-back 해석에 유용한 방법임을 확인 하였다.