• 대한원격탐사학회지
• /
• 제30권4호
• /
• pp.537-546
• /
• 2014

본 논문은 비 접근 지역에 존재하는 관심물체의 위치를 고해상도 광학 위성영상을 이용하여 찾아내기 위한 방법을 제안한다. 관심물체는 정확하게 규정된 크기와 모양을 갖는 것이 아니라, 개념적으로 유사한 패턴을 가진 물체들의 집합이다. 본 논문에서는 유사 객체 검색에서 Histogram of Gradients (HOG) feature를 이용하여 입력 영상의 관심물체의 특징을 추출하고, 추출된 특징 데이터를 이용하여 다른 영상들의 관심물체를 탐색하는 Support Vector Machine (SVM) 학습 및 분류기를 개발하였다. 제안한 방법은 관심물체를 자동으로 찾아줌으로써, 넓은 영역에서 수동으로 관심물체를 탐색하는데 소요되는 시간과 노력을 줄일 수 있는 효과가 있음을 확인하였다.

• 한국콘텐츠학회논문지
• /
• 제7권2호
• /
• pp.73-83
• /
• 2007

완전 일치 방법을 주로 사용하는 정보 검색 시스템에서 외래어 이형태를 검색할 수 있도록 위해서는 외래어 이형태를 자동 생성하는 전처리나 질의어 확장이 필요하다. 본 연구에서는 하나의 외래어가 입력되면, 이를 근거로 실제 사용될 만한 외래어 이형태들을 효과적으로 생성하기 위한 방법을 제안한다. 혼동 자소를 단순하게 치환하는 방법은 불필요한 이형태를 과도하게 생성하므로, 본 연구에서는 실제 문서에 사용된 외래어 이형태들로부터 혼동 패턴을 학습하고, 이를 확률로 계산하여 생성 순서를 조절하였다. 특히, 혼동 패턴에서 좌우문맥을 고려하고 지역 치환 확률과 전역 치환 확률을 계산하여 조기에 많이 사용하는 이형태를 생성하도록 하였다. KT SET 2.0에서 추출한 이형태 데이터에 대해 실험한 결과, 상위 20개의 생성으로도 평균 80% 이상 찾아내어 이 방법이 매우 효과적임을 보였다.

• Journal of Welding and Joining
• /
• 제16권5호
• /
• pp.56-66
• /
• 1998

During solidification or welding of alloys, the solute redistribution brings out microsegregation. The microsegregation causes the formation of non-equilibrium second phases, shrinkage and porosity degrading mechanical/chemical properties Therefore, it has been required to predict microsegregation quantitatively. To predict the degree of microsegregation, more exact and appropriate computer simulation technique has been actively used during last two decades. To predict the degree of microsegregation in weld metal, an advanced two dimensional model was suggested. In the new model, both primary and secondary arm regions were defined for the analysis region. The growth in the primary arm regina was assumed to be a planar for effective calculation. Especially, for the growth of a secondary arm, a simple and effective mathematical function was established to show the growing pattern, the solute diffusion in the solid phase was calculated by finite difference method (FDM). The solid-liquid interface movement was considered to be in local equilibrium state. The experiments for welding of 310S stainless steel were carried out in order to examined the reasonability and feasibility of this model. The concentration profiles of the solute predicted by this model were compared with those obtained from experimental works.

• 한국정보통신학회논문지
• /
• 제13권2호
• /
• pp.407-412
• /
• 2009

최근 용접공정은 무인화 및 자동화 시스템의 구축이 급속하게 발전하고 있으며 정확한 용접현상의 해석을 위하여 여러 가지 신호처리 알고리즘을 적용하고 있다. 본 논문에서는 아크용접의 모니터링시스템 구성에 있어서 용접품질을 실시간으로 판단할 수 있는 효율적인 신경회로망을 제시하고, 학습 데이터의 선정을 위한 전처리 과정을 제시하며, 학습된 신경회로망을 이용하여 실제 용접이 이루어지는 파형에 대한 평가를 보다 정밀하고 정확하게 평가할 수 있는 방법을 제시한다.

• 한국의류산업학회지
• /
• 제18권1호
• /
• pp.63-70
• /
• 2016

This study examines wearing conditions of skinny jeans for women in their 20's. The study is based on a questionnaire survey. The survey was conducted on 313 Korean 20's women living in Gwangju to analyze wearing dissatisfaction with skinny jeans. The final analysis included 298 responses and the content of the questionnaire consisted of 28 questions. The study used descriptive statistics for analysis using SPSS Statistics 20.0. According to the questionnaire survey, 20's women are the largest group that wear skinny jeans and they have a positive image of them. However, they do not know the exact size for skinny jeans, whereas they are knowledgeable about their general pants size. The results of the survey on the state of wearing dissatisfaction indicate that they think that the difference in size by each brand is the most difficult part when choosing skinny jeans and they felt lower body uncomfortableness in the waist and abdominal positions. It means that size subdivision and pattern development of skinny jeans should be suitable to all lower body types to resolve wearing dissatisfaction. This study represents base data for size subdivision and pattern development of skinny jeans.

• 대한기계학회논문집A
• /
• 제23권11호
• /
• pp.1929-1939
• /
• 1999

This paper presents a neural network approach, which was named PRONET, to 3D object recognition and pose calculation. 3D objects are represented using a set of centroidal profile patterns that describe the boundary of the 2D views taken from evenly distributed view points. PRONET consists of the training stage and the execution stage. In the training stage, a three-layer feed-forward neural network is trained with the centroidal profile patterns using an error back-propagation method. In the execution stage, by matching a centroidal profile pattern of the given image with the best fitting centroidal profile pattern using the neural network, the identity and approximate orientation of the real object, such as a workpiece in arbitrary pose, are obtained. In the matching procedure, line-to-line correspondence between image features and 3D CAD features are also obtained. An iterative model posing method then calculates the more exact pose of the object based on initial orientation and correspondence.

• Smart Structures and Systems
• /
• 제13권5호
• /
• pp.869-890
• /
• 2014

In this study, a damage detection approach using train-induced vibration response of the bridge is proposed, utilizing only direct structural analysis by means of introducing soft computing methods. In this approach, the possible damage patterns of the bridge are assumed according to theoretical and empirical considerations at first. Then, the running train-induced dynamic response of the bridge under a certain damage pattern is calculated employing a developed train-bridge interaction analysis program. When the calculated result is most identical to the recorded response, this damage pattern will be the solution. However, owing to the huge number of possible damage patterns, it is extremely time-consuming to calculate the bridge responses of all the cases and thus difficult to identify the exact solution quickly. Therefore, the soft computing methods are introduced to quickly solve the problem in this approach. The basic concept and process of the proposed approach are presented in this paper, and its feasibility is numerically investigated using two different train models and a simple girder bridge model.

• 한국인터넷방송통신학회논문지
• /
• 제11권4호
• /
• pp.113-118
• /
• 2011

서열 상동성 분석은 생명현상에 관여하는 물질을 정렬, 색인하여 데이터베이스 하는 것으로, 생명정보학의 유용성을 입증하는 분야이다. 본 논문에서는 구조가 복잡한 진핵생물의 서열 패턴을 단백질 서열로 변환하기 위해 은닉마르코프모델을 이용하는 GenScan 프로그램을 이용한다. 서열상동성 분석 중 최소거리 탐색 문제는 문제의 크기가 커지면 계산량이 기하급수적으로 증가하여 정확한 계산이 불가능해진다. 따라서 유사한 아미노산간의 치환과 상이한 아미노산간의 치환 점수를 차등화한 점수표를 적용하고, 은닉마르코프모델 등을 적용해 정교한 전이 확률모델을 적용한다. 변환된 서열을 서열 상동성 분석을 위해 사용되는 blast p를 이용하여, 은닉 마르코프 모델을 도입함으로 인해 단백질 구조 서열로 변환하는 데에 있어서 우수한 기능을 제공함을 알 수 있다.

• 근관절건강학회지
• /
• 제23권1호
• /
• pp.61-69
• /
• 2016

Purpose: The purpose of this study was to determine the effect of the Tai Chi exercise program (Sun style 31 forms) on fatigue, anxiety, and sleep patterns in nursing students. Methods: A quasi-experimental study with a non-equivalent control group pretest-posttest design was used. Nursing students who participated in this study were assigned to an experimental group (n=24), and a control group (n=26). The experimental group participated in Tai Chi exercise program for 60 minutes per session, and 3 times a week for 7 weeks. The Tai Chi exercise program consisted of 10 minutes for warm-up, 45 minutes for main session, and 5 minutes for cooling down exercises. The data were collected prior and after the intervention using self-administered questionnaires. Data were analyzed using descriptive statistics, $x^2$-test, Fisher's exact probability, t -test, and the general linear model. Results: After the application of the program, the experimental group showed a significant difference in fatigue (F=20.62, p<.001), anxiety (F=16.96, p<.001), and sleep pattern (F=15.70, p<.001) scores. Conclusion: These findings show that the Tai Chi exercise program can be an effective nursing intervention to improve sleep pattern and to reduce fatigue and anxiety in nursing students.

• Earthquakes and Structures
• /
• 제7권3호
• /
• pp.333-347
• /
• 2014

Multi-scale model can take both computational efficiency and accuracy into consideration when it is used to conduct elasto-plastic seismic response analysis for complex steel bridges. This paper proposed a method based on pushover analysis of member sharing the same section pattern to verify the accuracy of multi-scale model. A deck-through type steel arch bridge with a span length of 200m was employed for seismic response analysis using multi-scale model and fiber model respectively, the validity and necessity of elasto-plastic seismic analysis for steel bridge by multi-scale model was then verified. The results show that the convergence of load-displacement curves obtained from pushover analysis for members having the same section pattern can be used as a proof of the accuracy of multi-scale model. It is noted that the computational precision of multi-scale model can be guaranteed when length of shell element segment is 1.40 times longer than the width of section where was in compression status. Fiber model can only be used for the predictions of the global deformations and the approximate positions of plastic areas on steel structures. However, it cannot give exact prediction on the distribution of plastic areas and the degree of the plasticity.