• 디자인학연구
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• 제17권4호
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• pp.279-288
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• 2004

교육인적자원부에서 인가한 대부분의 17개 원격대학에는 디자인관련학과가 개설되어있으며, 각 디자인관련 학과에서는 각 분야에 적절한 디자인 교육을 하고 있다. 대부분 디자인관련학과의 교육목표는 실무중심교육을 강조하면서도 사실상 컴퓨터나 저작도구 등을 배우는 강의 운영방식에서 벗어나지 못하고 있다. 따라서 현재 원격대학에서는 디자이너를 위한 사실상의 실기 수업이 제대로 이루어지지 못하고 있는 실정이다. 그렇다고 원격대학 학생들의 디자인력이 상대적으로 떨어진다는 것 또한 증명된 적이 없다. 이제 내년 2월이면 온라인 디자인전공자가 적게는 수십 명에서 많게는 수백 명의 첫 졸업생들이 사회로 배출된다. 이들에 대한 기대는 사회에서 염려하는 것과는 달리 쉽게 긍정적으로 나타날 수 있다. 왜냐하면, 이들은 이미 실무에서 디자인을 하고 있는 직장인이 73%(서울디지털대학교 멀티미디어학부 2004학년도 전기입시 기준)가 되기 때문에 원격대학은 교육을 통한 디자이너 양성이 목표가 아니라 이미 사회에 진출해 있는 디자이너를 위한 평생교육의 개념이 더욱 강하기 때문이다. 따라서 이런 학생들을 위한 바람직한 디자인교육을 위해서는 어떻게 해야 하는지에 대해 알아보고자 한다. 즉, 원격대학의 디자인 실무능력을 위한 교육법, 다양한 콘텐츠 활용에 따른 교육 효과, 실무자에게 필요한 교육과정, 초보자를 위한 디자인력 향상교육, 실무에서 요구하는 교육, 온라인 교육의 한계, 디자인 교육을 위한 차별화된 콘텐츠 등을 살펴본 후 원격 대학의 학생들이 온라인 콘텐츠를 통해 디자인의 가치를 어떻게 받아들이고, 디자인력을 어떻게 키워가야 하는지를 논의하였다.

• Journal of Breast Disease
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• 제6권2호
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• pp.52-59
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• 2018

Purpose: This study aimed to determine whether clinicopathological factors are potentially associated with successful breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC) and develop a nomogram for predicting successful BCS candidates, focusing on those who are diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative tumors during the pre-NAC period. Methods: The training cohort included 239 patients with an HR-positive, HER2-negative tumor (${\geq}3cm$), and all of these patients had received NAC. Patients were excluded if they met any of the following criteria: diffuse, suspicious, malignant microcalcification (extent >4 cm); multicentric or multifocal breast cancer; inflammatory breast cancer; distant metastases at the time of diagnosis; excisional biopsy prior to NAC; and bilateral breast cancer. Multivariate logistic regression analysis was conducted to evaluate the possible predictors of BCS eligibility after NAC, and the regression model was used to develop the predicting nomogram. This nomogram was built using the training cohort (n=239) and was later validated with an independent validation cohort (n=123). Results: Small tumor size (p<0.001) at initial diagnosis, long distance from the nipple (p=0.002), high body mass index (p=0.001), and weak positivity for progesterone receptor (p=0.037) were found to be four independent predictors of an increased probability of BCS after NAC; further, these variables were used as covariates in developing the nomogram. For the training and validation cohorts, the areas under the receiver operating characteristic curve were 0.833 and 0.786, respectively; these values demonstrate the potential predictive power of this nomogram. Conclusion: This study established a new nomogram to predict successful BCS in patients with HR-positive, HER2-negative breast cancer. Given that chemotherapy is an option with unreliable outcomes for this subtype, this nomogram may be used to select patients for NAC followed by successful BCS.

• 화약ㆍ발파
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• 제38권4호
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• pp.16-25
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• 2020

터널 발파 굴착 시 발생되는 진동을 저감시키기 위해 사용되는 MSP(Multi-setting smart-investigation of the ground and pre-large hole boring method) 공법은 1회 천공 시 수평방향으로 50m에 달하는 장거리를 천공하기 때문에 고 중량 해머비트와 롯드의 일방향 회전으로 롯드의 처짐과 우향 현상이 동반된다. 이는 전문가의 경험과 시공 이력을 바탕으로 가변적인 세팅을 통해 일부 보정되고 있다. 그러나 암반 특성, 장비 상태, 경험 부족 등은 목표 지점으로부터 천공 오차를 발생시키는 원인이 되며, 큰 이격 오차 발생 시 재시공으로 인한 공기 증가와 경제적 손실이 발생된다. 본 연구에서는 딥러닝을 활용하여 상황별 천공 장비의 최적 세팅조건 산정 모델을 개발하였으며, 학습 과정에서 발생 가능한 과적합 문제를 방지하기 위해 dropout, early stopping, pre-training 기법들을 사용하여 향상된 결과를 도출하였다. 본 연구를 통해 대구경 천공 장비의 상황별 초기세팅 산정 모델 개발의 높은 가능성을 확인했으며, 지속적인 데이터 수집과 다양한 인자들의 추가 학습을 통해 최적화된 세팅 가이드라인을 개발할 수 있을 것으로 기대된다.

• 감성과학
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• 제12권3호
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• pp.341-350
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• 2009

양궁의 슈팅과정에 대하여 정신 집중력과 긴장 이완도를 뇌파를 이용하여 평가하였다. 정신 집중과 긴장 이완 수준의 평가는 집중과 명상 알고리즘을 이용하여 수행되었다. 우수, 중급, 그리고 초급 양궁선수들이 야외 양궁장에서 근거리와 장거리 타깃을 대상으로 슈팅 훈련을 할 때 앞이마(Fp1)에 전극을 부착한 헤드밴드 형태의 휴대용 뇌파 시스템으로 뇌파를 기록하였다. 개인별로 기록된 뇌파는 집중과 명상 알고리즘을 이용하여 실시간으로 정신집중과 긴장이완 수준이 계산되었으며, 슈팅 과정에서 정신집중과 긴장이완 수준의 변화 형태가 분석되었다. 개인별로 각각의 슈팅에 대한 정신집중 및 긴장이완 수준 변화는 네 유형으로 분류되었으며, 이 변화 유형은 양궁 선수들의 경기력을 평가하는 신뢰성 있는 지표로 나타났다. 우수 선수의 경우 정신 집중과 긴장이완 수준이 슈팅과정의 진행에 따라 동시에 증가하는 형태로 나타났으며, 중급 선수의 경우 정신 집중도는 증가하는 반면 긴장 이완 수준은 감소하는 결과를 보여 주었다. 실시간으로 제공되는 정신 집중과 긴장 이완 수준의 변화는 양궁 선수들의 경기력 평가뿐만 아니라 훈련 시에 유익한 피드백이 되었다.

• 한국멀티미디어학회논문지
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• 제23권5호
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• pp.710-720
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• 2020

Tsunami occurred by a rapid change in the ocean floor is a natural disaster that causes serious damage worldwide. South Korea seems to be out of the range of this damage, but it is quite possible that South Korea will fall within the range due to the long-distance propagation features of tsunami and many earthquakes occurred in Japan. However, the analysis and preparation for tsunami have been still insufficient. In this paper, we propose a tsunami simulation model based on cellular automata for analyzing coastal inundation. The proposed model calculates the range of inundation in coastal areas by propagating the energy of tsunami using the interaction between neighboring cells. We define interaction rules and algorithms for the energy transfer and propose a software tool to effectively utilize the model. In addition, to verify and tune the simulation model, we used the actual tsunami data in 2010 at Dichato, Chile. As a case study, the proposed model was applied to analyze the coastal inundation according to tsunami height in Gwangali Beach, a famous site in Busan. It is expected that the simulation model can be a help to prepare an effective countermeasure against tsunami and be used for a virtual evacuating training.

• 한국운동역학회지
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• 제20권3호
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• pp.253-259
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• 2010

The aim of IAAF's Biomechanics project, initially launched at the 1987 World Championships in Rome, is to support athletes and coaches in the optimization and improvement of their training and competition performance. The IAF and the IAAF supports biomechanical projects, as a service to their Member Federations, starting from the IAAF World Championships in Rome 1987. In 1997, at the IAAF World Championships of Athens. In 1995, at the IAAF World Championships in Goteborg and in co-operation with the Swedish Sport Institute of Karlstad and under the leadership of Anders Bergstrom a biomechanical research on "Throws" was conducted. In 2005, at the IAAF World Championships in Helsinki on 100m - Pole vault, High Jump, Triple Jump, Javelin, under the leadership of Prof. Paavo Komi. The IAAF published the final report in 2008 with a supplement of NSA. In 2007, at the IAAF World Championships of Osaka, in co-operation with Osaka University of Health and Sport Sciences and under the leadership of Prof. Michiyoshi Ae the IAAF received a final report on; short sprint, distance running, high jump, long jump, shot put and javelin. In 2009, at the IAAF World Championships of Berlin, in co-operation with the DLV and the leadership of Helmar Hommel (GER). The purpose of this study is to draw up a plan to perform an effective biomechanics project at 2011 IAAF World championship in Daegu.

• 한국운동역학회지
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• 제23권4호
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• pp.295-306
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• 2013

The purpose of this study was to provide high school male shot putters training methods of gliding and delivery motion through comparative analysis of kinematic characteristics. To accomplish this purpose, three dimensional motion analysis was performed for the subjects(PKC, KKH, YDL) who participated in high school male shot putter competition on 92nd (2011), 93rd (2013) National Sports Festival. The subjects were filmed by four Sony HXR-MC2000 video cameras with 60 fields/s. The three-dimensional kinematic data of the glide, conversion and delivery phase were obtained by Kwon3d 3.1 version. The data of the shoulder rotational angles and projection angles were calculated with Matlab R2009a. The following conclusions had been made. With the analysis of the gliding and stance length ratio, the gliding length was shorter at the TG than the SG with short-long technique but the gliding and stance length ratio was 46.8:53.2% respectively. The deviation of the shots trajectory from APSS(Athlete-plus-shot-system) revealed that the PKC showed similar to "n-a-b-c-I" of skilled S-shape type, KKH and YDL showed "n-a-d-f-I'" of unskilled type. Furthermore, they showed smaller radial distance from the central axis of the APSS and the shots were away from the linear trajectory. From this characteristics, The PKC who performed more TG than SG had shorter glide with S-shape of APSS(skilled type) showed the better record than others with technical skill. But KKH and YDL had bigger glide ratio with "n-a-d-f-I'" of unskilled type and improved their records with technical factor. The projection factor had an effect on the record directly. Because PKC maintained more lower glide and transition posture with momentum transfer through COG's rapid horizontal velocity respectively the subject possessed the characteristics of high horizontal and vertical velocity with large turning radius from shot putter to APSS.

• 한국주거학회논문집
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• 제20권4호
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• pp.103-112
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• 2009

The purpose of this research was to find out the housing history of Sakhalin returnees in Ansan Gohyangmaeul since leaving hometown under the Japanese ruling period, who experienced two international migration for one's life. Face to face interview had been done with 20 returnees in the community center of Ansan Gohyangmaeul during October to December, 2008. The semi-structured questionnaire about housing the respondents lived in major life changes used to guide the individual interview. The results showed that personal life as well as housing histories were differed by the reason to move into Sakhalin, which still influenced the returnee' life up to now. The housing they had lived changed from barracks like a training camp, to Japanese small wooden cottage/row house, and then Russian brick house/ apartment. Housing alteration and addition and rebuilding were common to renew the old existing house. The boundary of residing area was mostly limited to the first residing location under soviet governing system throughout one's life without a long distance move. Housing satisfaction was very high in Gohyangmaeul because of the improvement of housing facilities and residence itself as well as the convenience of housing management, compared to former residence in Sakhalin. Economic and emotional aspects of life satisfaction were also high during about 8 years of living in the apartment. Forced movers still require the compensation on hand to either Korean or Japanese government no matter the amount. Social integration to the Korean community would be one of the main issues to new returnees as well as the already returned. In-depth interviews of case study need to reveal the unique housing experience of the forced mover according to the type of leaving hometown by oneself or by parents, and to returned region and time to motherland.

• 대한전자공학회논문지SD
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• 제48권9호
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• pp.22-30
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• 2011

최근 카메라를 통해 입력된 영상정보로부터 실시간으로 상황을 인지하고 자율 대응할 수 있는 지능형 영상 보안 시스템의 수요가 증가함에 따라, 고성능의 얼굴 인식 시스템이 요구되고 있다. 기존의 얼굴 인식 시스템의 성능 향상을 위해서는 원거리에서 획득된 저해상도 얼굴 영상 처리를 위한 솔루션이 반드시 필요하다. 따라서 본 논문에서는 실시간 감시가 요구되는 지능형 영상 보안 시스템의 얼굴 인식 성능 향상을 위한 저해상도 얼굴 영상 복원 알고리즘을 하드웨어로 구현하였다. 저해상도 얼굴 영상 복원 방법으로는 학습 기반의 초해상도 알고리즘을 사용한다. 해당 알고리즘은 먼저 고해상도 영상으로 구성된 학습 집합에서 주성분 분석(PCA)을 활용하여 복원에 필요한 사전 정보들을 추출하고, 저해상도 영상과의 관계를 모델링하여 가장 적합한 고해상도 얼굴을 복원해내는 것이다. 저해상도 얼굴 영상 복원 알고리즘을 임베디드 프로세서(S3C2440A)를 사용하여 구현하였을 때, 약 25 초의 긴 연산 시간이 소요되었다. 이는 실시간으로 사람을 판별 및 인식하기 위한 지능형 영상 보안 시스템의 구축에는 어려움이 있다. 이를 해결하기 위하여 얼굴 영역 초해상도의 연산을 하드웨어로 구현하고 Xilinx Virtex-4를 이용하여 검증하였다. 약 9MB의 학습 데이터를 사용하였으며, 100 MHz에서 약 30 fps의 속도로 연산이 가능하다. 이러한 학습 기반의 얼굴 영역 초해상도 알고리즘을 단일 하드웨어 IP로 설계함으로써 임베디드 환경에서의 실시간 처리가 가능할 뿐 만 아니라 기존의 다양한 얼굴 검출 시스템과의 통합이 용이하여 얼굴 인식 솔루션을 제공할 수 있을 것으로 판단된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.