• Journal of Nutrition and Health
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• 제27권2호
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• pp.192-206
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• 1994

This study was conducted to find out the weak points of present Korean food composition table, so that to suggest the revision direction. Korean food composition table in Appendix of Recommended Dietary Allowances for Korean, 5th edition, was analyzed by comparing with 6 other food composition tables such as one other Korean food composition table, and those of Japan(two), U.S.A., East Asia and Near East. The content analysis was applied as the method of this study. As result, many drawbacks like classification of food components, etc. were pointed out. The best solution to improve these drawbacks in present food composition table is establishing on organization entirely in charge of food composition table. In this way the organization can carry out food analysis systematically and continuously. Then new food items can be added, old food items be eliminated based upon people's food consumption pattern change. Also we need to analyze our own foods consumed by our people instead of borrowing the other country's data.

• 한국정보통신학회논문지
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• 제10권3호
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• pp.556-563
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• 2006

문서 영상에서 표 영역을 분류하고 구조를 파악하려면 표를 구성하는 직선과 데이터를 추출할 수 있어야 한다. 그러나 영상 입력 장치의 오차나 영상축소로 인해 표를 구성하는 직선이 끊어지거나 길이가 변하며 직선에 노이즈나 문자가 붙어 표로부터 직선과 데이터의 정확한 추출이 어렵다. 본 논문에서 는 1차원 메디안 필터를 이용하여 표를 구성하는 수평선과 수직선을 추출한다. 1차원 메디안 필터는 필터링 방향의 직선을 추출하는 과정에서 노이즈와 필터링 방향에 수직한 직선을 제거할 뿐 아니라 직선의 끊어진 부분이 필터 탭 길이보다 짧은 경우 끊어진 부분을 연결한다. 또한 수직선을 추출하는 과정에서 직선에 붙어 있던 문자들을 분리함으로써 상용제품을 포함한 기존의 방법에 비해 표 영역 분류 및 구조 분석을 위한 직선과 데이터 추출이 우수한 방법을 제안한다.

• Preventive Nutrition and Food Science
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• 제9권2호
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• pp.190-193
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• 2004

This review was conducted to evaluate the 'Korean Food Composition Table' and establish it as an internationally accepted database by examining its contents and evolution over time. The food composition table has been published by National Rural Living Science Institute, every 5 years, listing the nutrient content for each food, as both the raw agricultural product and processed foods, since the 1$^{st}$ edition in 1979 by RDA (Rural Development Administration). This is the basic data applied to the evaluation of the nutritional value of foods in Korea. The data is used as a useful tool in many fields, not only for the establishment of the National Food Supply Plan but also for nutritional research, the draft of National Food Policy, and in clinical and epidemiological research. The database is also utilized by food service providers and food processors, etc. Consumers and the international society have been interested in the quality and safety of foods and raw agricultural products. As these data expand in volume, the type of foods included in the composition table is expanded to cover new additions for the convenience of users of the 'Nutrient Data Base' as judged by the publishers. The form of these reports varies, according to the current information, from a simple booklet to CD-ROM and to the Web service. We expect to continue to make improvements in the National Standard Table for food composition through expanding both the quantity and quality of data in an orderly manner. This effort can help food composition data to be comprehensively developed systematically and gradually at the national level.l.

• 한국지능시스템학회논문지
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• 제20권2호
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• pp.173-180
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• 2010

공개되는 데이터에서 각 개인의 민감한 정보를 보호하기 위한 방법으로 데이터 익명화에 관한 연구가 활발히 이루어지고 있다. 대부분의 연구들은 익명화 요구 사항에 위배되지 않으면서, 효율적인 시간 내 레코드들을 일반화하는 기법을 중심으로 연구를 진행하고 있다. 익명화 작업이 많은 시간이 요구되는 문제임을 고려한다면, 민감한 정보에 대한 프라이버시 침해의 우려가 있는지, 익명화가 요구되는지를 미리 검사하는 것은 개인 정보 보호차원뿐만 아니라 데이터의 활용성 및 시간적 효율성 측면에서도 매우 중요하다. 또한, 그러한 침해의 우려가 있다면 어떤 유형의 공격에 취약한지를 미리 판단함으로써 그에 적절한 익명화 방식을 결정하는 것도 중요하다. 본 논문에서는 민감한 속성에 대한 공격 유형을 크게 2가지로 분류한다. 그리고 데이터가 이들 공격으로부터 안전한가의 여부를 검사할 수 있는 기법을 제시하고, 불안정하다면 어떠한 공격에 취약하고 대략 어떤 방식의 일반화가 요구되는가를 제시한다. 본 연구에서는 익명화되기 전의 테이블뿐만 아니라, 익명화된 테이블, 그리고 익명화가 되었지만 삽입, 삭제로 인해 변경된 테이블도 공격성 검사 대상이 된다. 뿐만 아니라 익명화된 테이블도 민감한 정보를 제대로 보호하고 있는지 혹은 삽입 삭제로 인해 재익명화 작업이 필요한지의 여부도 본 연구의 결과로 결정할 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.788-790
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• 2006

The algorithm of calculating NUC table, based on Image data collection, is based on two basic assumptions. These basic assumptions are as follow: one is the NUC is of a linear nature. The other is all pixel see the same statistical distribution for large number of lines. We generated NUC tables for a radiometric calibration & validation of KOMPSAT-2 using a dark cal. Data.

• 한국식품영양학회지
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• 제26권4호
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• pp.886-894
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• 2013

The National Standard Food Composition Table published by the Rural Development Administration (RDA) provides the foundations in research, nutrition monitoring, policy and dietary practices in Korea. This databases consists of several sets of data including food descriptions, nutrients, portion weights, and source of data. The National Standard Food Composition Table have been published since 1970 and, recently, new version (8th edition) of Food Composition Table which has quantitative and qualitative nutrient data is released in 2011. In addition, the User-friendly Food Composition Table is divided into adult, children, and elderly categories depending on the subjects because we need different nutrients according to various ages. The Tables of Food Functional Composition is firstly edited in 2009. RDA published the minerals and fatty acids composition table, tables of amino acid, fat-soluble vitamin composition table, and the cholesterol table. The resulting database will be widely used. The users of the databases are from diverse fields, includeing federal agencies, the food industry, health professionals, restaurants, software application developers, academia and research organizations, international organizations, and foreign governments ect. Therefore, consistent improvements of the database is important, so that people can better address such health challenges by providing reliable and accurate data.

• Journal of Community Nutrition
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• 제5권2호
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• pp.65-71
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• 2003

In Current Standard Tables of Food Composition in Japan (Fifth Revised Edition), standard composition values of food used regularly in Japan are shown by values per 100g of their edible portion, with one value of standard composition per one foodstuff as a rule. In the Explanation (Chapter 1) and Reference Data (Chapter 4) of the original table, the most important matters are mentioned, including the table of the weight change rate by cooking, the table of the outline of the cookery, and the formula of the actual amount of intake nutrition. These are helpful for an understanding of the actual amount of intake nutrition. The formula for the amount of purchase in consideration of the amount of refuse is also shown. Information concerning foodstuffs and composition items in the table as well as important points in the reference column are concurrently written in English. As related studies, the composition tables by values per 100m1 or considered loss, the table or the formula for estimation of the amount of sucrose, and the list of the composition extant rate after cooking, among others, are also provided. Users should understand the original composition table, and then suggest how to utilize it. (J Community Nutrition 5(2) : 65∼71, 2003)

• Structural Engineering and Mechanics
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• 제61권2호
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• pp.267-274
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• 2017

In this study was investigated of possibility using the recorded micro tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model steel structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model steel structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model steel structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.8% are differences.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.695-697
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• 2006

Elshayal $Smart{\copyright}$ software is an almost First Arabian GIS $software{\copyright}$ which completely developed by Arabian developers team and independent of any commercial software package. The software current Features are View and Edit shape files, build new layers, add existing layers, remove layers, swap layers, save layers, set layer data sources, layer properties, zoom in & zoom out, pan, identify, selecting features, invert selection, show data table, data query builder, location query builder, build network, find shortest path, print map, save map image, copy map image to clipboard, save project map, edit move vertex, edit move features, snap vertexes, set vertex XY, move settings, converting coordinate system, applying VB script, copy selected features to another layer, move selected features to another layer, delete selected features, edit data table, modify table structure, edit map features, drawing new features, GPS tracking, 3D view, etc... The software expected Features are: Viewing raster image and image geo-referencing, read other map formats such as DXF Format and Tiger Line Format.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.717-729
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• 2004

The contour method which was originally designed for $2{\times}2{\times}2$ contingency table is studied for $2{\times}2{\times}K$ and $2{\times}3{\times}K$ tables. Whereas a contour plot for a $2{\times}2{\times}K$ table is represented on unit squared two dimensional plane, a contour plot of a $2{\times}3{\times}K$ table can be expressed with a regular hexahedron on three dimensional space. Based on contour plots for categorical data fitted to all possible three dimensional log-linear models, one might identify whether $2{\times}2{\times}k$ or $2{\times}3{\times}K$ tables are collapsible over the third variable.