• 치과방사선
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• 제16권1호
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• pp.59-68
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• 1986

The purpose of this investigation was to locate the central plane of the image layer on the panoramic machine relative to a specific point on the machine. In the study of the central plane of the image layer of panoramic radiograph, using the Morrita Company PANEX-EC a series of 33 exposures were taken with the 4-5 experimental pins placed in the holes of the plastic model plate, then evaluated by human eye. The author analyzed the central plane of the image layer by Mitutoyo-A-221 and calculated horizontal and vertical magnification ratio in the central plane of the image layer determined experimentally. The results were as follows: 1. The location of the central plane of the image layer determined experimentally was to lateral, compared with manufactural central plane. 2. Horizontal magnification ratio in the central plane of the image layer determined experimentally was 9.25%. 3. Vertical magnification ratio in the central plane of the image layer determined experimentally was 9.17%.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2005년도 GIS/RS 공동 춘계학술대회
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• pp.345-349
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• 2005

Massive amount of satellite image processing such asglobal/continental-level analysis and monitoring requires automated and speedy georegistration. There could be two major automated approaches: (1) rigid mathematical modeling using sensor model and ephemeris data; (2) heuristic co-registration approach with respect to existing reference image. In case of ETM+, the accuracy of the first approach is known as RMSE 250m, which is far below requested accuracy level for most of satellite image processing. On the other hands, the second approach is to find identical points between new image and reference image and use heuristic regression model for registration. The latter shows better accuracy but has problems with expensive computation. To improve efficiency of the coregistration approach, the author proposed a pre-qualified matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with correlation coefficient. Throughout the pre-qualification approach, the computation time was significantly improved and make the registration accuracy is improved. A prototype was implemented and tested with the proposed algorithm. The performance test of 14 TM/ETM+ images in the U.S. showed: (1) average RMSE error of the approach was 0.47 dependent upon terrain and features; (2) the number average matching points were over 15,000; (3) the time complexity was 12 min per image with 3.2GHz Intel Pentium 4 and 1G Ram.

• 치과방사선
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• 제20권1호
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• pp.71-78
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• 1990

저자는 Panelipse Ⅱ의 상층 및 상의 확대변화를 관찰하기 위하여 모형판에 금속구를 위치시켜 3가지 Profile Index에서 각기 20장씩 방사선사진을 촬영하여 관찰한 결과를 다음과 같이 요약할 수 있었다. Profile Index의 증가에 따른 Panelipse Ⅱ 방사선상의 상층에 있어 모양의 변화는 없었고, 폭은 더 넓어졌으며, 회전축중심에서 외측으로 상층은 이동하였다. 방사선상에서 수평 수직확대는 공히 Profile Index가 증가함에 따라 그 범위가 커졌으며 이는 수평확대에 있어 수직확대보다 현저하였다.

• 한국정보통신학회논문지
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• 제20권1호
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• pp.193-199
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• 2016

최근 다양한 분야에서 소셜 네트워크 분석 기법을 통해 개체들간의 상호작용을 분석하는 연구들이 진행되고 있다. 본 논문에서는 한국정보통신학회 논문지의 저자약력에 기술되는 저자의 관심분야를 소셜 네트워크 분석기법을 통해 다양한 측면에서 분석하고자 한다. 분석결과 많은 저자들이 임베디드, 보안, 영상처리, 무선통신, 빅데이터, USN, 네트워크, RFID 등의 관심분야를 중심으로 연구하고 있음을 알 수 있다.

• 한국산림과학회지
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• 제90권6호
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• pp.747-755
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• 2001

본 연구는 산촌지역축제인 아카시아벌꿀축제에 대하여 방문객의 관광지 이미지의 구성요인을 도출하고, 방문객의 특성에 따라 관광지 이미지의 유의미한 차이가 있는 지를 분석하였다. 설문조사는 축제기간인 2001년 5월 12일에서 15일까지 축제장을 방문한 394명의 관광객을 대상으로 실시하였으며, 관광지 이미지 평가를 위한 설문항목은 선행연구를 기초로 20개를 설정하고 5점 Likert 척도를 적용하여 요인분석을 실시하였다. 아카시아벌꿀 축제의 관광지 이미지는 크게 환경, 태도 시설, 축제 프로그램, 그리고 상품요인 둥 4개 요인으로 구성되었다. 방문객의 특성에 따른 관광지 이미지의 변화는 최초방문객과 재방문객, 지역주민과 외지인, 그리고 벌꿀상품을 구매한 관광객과 구매하지 않은 관광객 사이에 이미지 평가에 대한 차이가 통계적으로 존재하는 지를 검정하였다. 그 결과 재방문객과 지역주민의 관광지 이미지가 환대성, 축제 내용 및 순서정보 제공과 같은 태도요인에서 긍정적인 것으로 나타났다. 또한 지역 벌꿀을 구매한 집단의 이미지는 구매하지 않은 집단보다도 상품의 가격과 품질뿐만 아니라 환경요인인 지역문화체험, 자연경관, 향수성, 분위기 등에서 긍정적인 것으로 평가되었다. 따라서 축제이미지 향상을 위하여는 주최측인 지방정부는 외부 관광객에게 축제에 대한 효과적인 정보제공과 함께 지역의 자연환경과 연계된 향토성과 체험성을 강조하는 프로그램의 개발이 필요한 것으로 판단된다.

• The Journal of Asian Finance, Economics and Business
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• 제8권4호
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• pp.423-431
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• 2021

This paper examines the impact of university social responsibility on brand image and student satisfaction. Social responsibility impact on consumer behavior has been studied extensively. But the same impact has not been rigorously tested to the same extend in the education sector. Firstly, we analyze the perception of university social responsibility (USR) and its components, including (1) the quality of teaching programs, facilities, and academic staff; (2) supporting learning activities; and (3) human resource policies. Secondly, we investigate the relationship between university social responsibility, brand image, and student satisfaction. The study examined these relationships through a proposed economic model based on answers from a survey of 298 students at the University of Food Industry Ho Chi Minh City. From the above survey data, the author proceeds to quantify variables and, based on Cronbach's Alpha reliability coefficient, EFA factor analysis, and linear regression, to measure the impact of each social responsibility factor on business of the university and student satisfaction. The results show that university social responsibility actually affects the university's brand image and student satisfaction. Our findings suggest that universities should develop an appropriate marketing strategy to reinforce brand image and student satisfaction through the university social responsibility model.

• 한국수학교육학회지시리즈A:수학교육
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• 제42권5호
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• pp.683-696
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• 2003

In this paper, we propose an authoring methodology of differentiated instruction-learning materials in mathematics course using MathML and XSLT, and give utilizing suggestions of these materials as differentiated textbook and individual learning. Incorporating MathML into instruction-learning materials, there are many advantages such that view of the materials in web browser is improved since mathematical expressions are compatible with text, and an expression can be modified in more convenient way since the expression is represented in text format not an image. In authoring of differentiated materials, the author provides one document for various levels of students. Then, each level of materials is generated from the document via XSLT transformation. This enables author-driven progress control rather than student-driven which does in previous approaches, since students don't need to select components of the material.

• 한국실내디자인학회논문집
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• 제1호
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• pp.72-75
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• 1992

Lighting made interior space visible and to recognize space itself. Sp9ace and form are established not themselves , but lighting. and dextrous treatment of natural light accomplished poeteic space. Inflowing of lighting in interior space is main factor to decide space character and image . That was recognized in interior space through many centries. At this point, this study was described for that present inflowing of lighting adapting space character and right method in lighting program. The present study is to present the planning method of the most appropriate and the most rational natural lighting in planing for lighting. Under this premise the followings are made ; I. An introduction , the purpose, the sphere, and the method of this study are stated. II, The present writer studied the general characteristics of natural lighting. III. this author studied the factor of decision on control and representation skill of lighting along the following. IV. Analyzing interior space in which the natural lighting is introduced through some literature and case studies. Physics, psychology, structure, equipment, material. V. The last, the author rearranged the results of this study.

• 한국산업융합학회 논문집
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• 제27권3호
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• pp.563-572
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• 2024

Image processing and computer vision technologies are becoming increasingly important in a variety of application fields that require techniques and tools for sophisticated image analysis. In particular, image segmentation is a technology that plays an important role in image analysis. In this study, in order to identify recent research trends on image segmentation techniques, we used the Web of Science(WoS) database to analyze the R&D topography based on the network structure of the author's keyword co-occurrence matrix. As a result, from 2015 to 2023, as a result of the analysis of the R&D map of research articles on image segmentation, R&D in this field is largely focused on four areas of research and development: (1) researches on collecting and preprocessing image data to build higher-performance image segmentation models, (2) the researches on image segmentation using statistics-based models or machine learning algorithms, (3) the researches on image segmentation for medical image analysis, and (4) deep learning-based image segmentation-related R&D. The scientometrics-based analysis performed in this study can not only map the trajectory of R&D related to image segmentation, but can also serve as a marker for future exploration in this dynamic field.

• 한국의류학회지
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• 제20권6호
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• pp.1125-1137
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• 1996

The author reviewed seventy papers on social psychology of clothing and fashion marketing fields, which were published in the Journal of the Korean Society of Clothing and Textiles between 1983 and 1996. The market variables and consumer behavior variables were focused on. This review showed that the market variables had been divided into three groups of variables: 1) product variables (product image and product classification): 2) brand variables (brand image and brand positioning): and 3) store variables (store image, store type, and distribution system) Consumer behavior variables have been studied on the basis of EBM Consumer Behavior Model: 1) purchasing motivation as need recognition: 2) information using as search information: 3) evaluation criteria and choice criteria as alternative evaluatioin : 4) clothing purchase, brand choice and store choice as purchase: 5) degree of wear, satisfaction and dissatisfaction as outcome: and 6) clothing discard. Variables that influence on consumer behavior, including situation variables, clothing attitude variables, personal . social variables were added to develop a variable model of clothing consumer behavior using the EBM Consumer Behavior Model.