• 한국컴퓨터정보학회논문지
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• 제23권1호
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• pp.85-90
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• 2018

The new information service has been demanded due to the recent mobile internet activation, and the government is promoting the activation of the private use of the public data by putting up the Government 3.0. According to government policy, many public sectors provide public data, but the railway sector is inferior to other public sector. In the case of national railway corporation, urban railway is now operated by 14 corporations such as Seoul Metro through the nation and high-speed railway is now operated by Korea Railroad Corporation and Supreme Railways. It is very difficult to standardize and integrate data due to mutual interests of national railway corporation. This paper describes a way to standardize and integrate rail passengers information collected through research project.

• 항공우주기술
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• 제7권2호
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• pp.38-45
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• 2008

It is challenging to build the integrated information system for a large scale cooperative R & D project. To develop the aircraft program which especially has several leading agencies and is supported by many demestic/foreign participating companies, the common data flow in harmony is the core factor to achieve a development goal. For this, the development are carried out maintaining the existing management systems of agencies and companies. As a first step, the standard for the common data information and the classification category of technical data are defined. Second, the work flow standards are also set. Based on the foundation, the efficient technical data management system are built including the function of storage, inquiry, revision, link, approval, submission, etc.

• 대한예방한의학회지
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• 제21권2호
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• pp.69-78
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• 2017

Objectives : This study aims to analyze the public investment for Korean Medicine R&D to facilitate the future strategic planning. Methods : All government supported research projects for Korean Medicine that were invested in 2009, 2012, 2015 were searched in the NTIS (National Science & Technology Information Service) Database. Research budgets were analyzed by government departments, R&D agents, R&D steps, and research fields. CAGR (Compound Annual Growth Rate) was derived from each Korean Medicine research field. Differences of research budgets among research fields were tested using Chi square analysis. Results : A total of 891 projects supported in 2009, 2012, and 2015 was analyzed. The amount of research budgets has increased, from 49,839 million won in 2009 to 106,536 million won in 2015 showing 13.5% of CAGR. Ministry of Science, ICT, and Future Planning, and Ministry of Health and Welfare were the biggest sponsors in Korean Medicine R&D. Chi square analysis showed that, in this period, there were statistically significant differences of research budgets in Korean Medicine technology equipment field and infrastructure field. Conclusions : To diversify the Korean Medicine R&D, unequal research funding among government departments should be relieved, and virtuous cycle of Industry-University-Institute Collaboration in Korean Medicine need to be built.

• 대한의용생체공학회:의공학회지
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• 제42권5호
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• pp.241-249
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• 2021

Recently, artificial intelligence for diagnosis system of obstetric diseases have been actively studied. Artificial intelligence diagnostic assist systems, which support medical diagnosis benefits of efficiency and accuracy, may experience problems of poor learning accuracy and reliability when inappropriate images are the model's input data. For this reason, before learning, We proposed an algorithm to exclude unread cervical imaging. 2,000 images of read cervical imaging and 257 images of unread cervical imaging were used for this study. Experiments were conducted based on the statistical method Radiomics to extract feature values of the entire images for classification of unread images from the entire images and to obtain a range of read threshold values. The degree to which brightness, blur, and cervical regions were photographed adequately in the image was determined as classification indicators. We compared the classification performance by learning read cervical imaging classified by the algorithm proposed in this paper and unread cervical imaging for deep learning classification model. We evaluate the classification accuracy for unread Cervical imaging of the algorithm by comparing the performance. Images for the algorithm showed higher accuracy of 91.6% on average. It is expected that the algorithm proposed in this paper will improve reliability by effectively excluding unread cervical imaging and ultimately reducing errors in artificial intelligence diagnosis.

• 한국IT서비스학회지
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• 제15권2호
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

• 한국콘텐츠학회논문지
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• 제20권9호
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• pp.1-10
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• 2020

국가 R&D 데이터는 기초과학 연구부터 산업화 부분까지 전 분야에 대한 정보를 포괄하고 있지만 전문적인 용어로 표현되며 이로 인해 대중의 이용에는 어려움이 있다. 이에 NTIS 는 국가 R&D 데이터를 이용한 데이터 큐레이션 서비스를 개발하여 국가적인 현안과 사회적 이슈에 대해 국가 R&D 정보를 선별하여 제공하고 있다. 이에 본 연구에서는 NTIS 의 데이터 큐레이션 서비스인 이슈로 보는 R&D 서비스 분석을 통해 국가 R&D 정보를 이용한 데이터 큐레이션 서비스 구축 방안을 제안하고자 하며 이 서비스가 국가 R&D 정보에 대한 사용자의 접근성 향상에 미친 영항도 분석하였다. 이슈로 보는 R&D 서비스는 뉴스기사에서 추출한 이슈와 관련된 국가 R&D 과제, 성과, 주요 연구기관 등을 매핑하여 정리, 제공한다. 패키징에 이용된 데이터는 모두 오픈되어 있고 관련 자료는 보고서 형식으로 정리돠어 PDF 파일로 제공된다. 또한 해당 프로세스를 자동화 하여 관리자 뿐 만 아니라 NTIS 이용자라면 누구나 개인적인 이슈패키징을 가능하게 하였다. 이 밖에 Special Issue 코너를 개설하며 주요 현안에 대한 사용자의 접근,이용 편의성을 높였고 코너 개설 이후 접속자의 페이지뷰가 증가한 것으로 나타났다.

• 대한원격탐사학회지
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• 제35권6_4호
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• pp.1341-1350
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• 2019

본 연구는 산불 전후 KOMPSAT-3A 영상을 사용하여 산불피해지역을 분석하는 것을 목적으로 한다. KOMPSAT 시리즈 중 KOMPSAT-3A는 적외선 및 고해상도의 멀티 스펙트럼 밴드를 가진 VHR위성이다. 하지만, KOMPSAT-3A를 활용하여 산불피해강도를 분류하는 연구는 부족한 실정이다. 따라서 본 연구에서는 KOMPSAT-3A의 산불 피해강도를 분류하기 위한 새로운 알고리즘을 제시하는 것을 목표로 한다. 또한, 본 연구에서는 산불 피해지역에 대한 참조자료로 Sentinel-2로 생성한 dNBR을 사용하였다. 본 연구의 연구 지역은 2019년 4월 4일 강릉에서 발생한 산불 피해지역으로 선정하였다. 본 연구에서는 산불피해구간을 산정하기 위한 알고리즘으로 오픈 소스 통계 프로그램인 R software의 확률분포함수를 사용하였다. KOMPSAT-3A에서 산불 피해지역은 산불 전, 후 NDVI의 변화에 따라 생성되었다. 산불피해강도는 분포 함수의 표준 편차를 사용하여 각 등급 크기를 산정하였다. 총 5개 구간에 따른 산불 피해 강도가 효과적으로 분류되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• Mycobiology
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• 제32권2호
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• pp.57-67
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• 2004

For investigation of the species diversity of the Genus Crepidotus in Korea and constructing a key to Korean Crepidotus species, a total of 65 specimens, collected from 18 locations from 1982 to 2002, were observed for morphological characters of carpophores and other features. All the specimens have been preserved in the herbarium of the National Institute of Agricultural Sciences and Technology, R.D.A., Suwon, Korea. The specimens were identified according to the classification systems given by Hesler and Smith(1965), Nordstein(1990), Orton(1960), Pilat(1948), Senn-Irlet(1991, 1992, 1993) and Singer(1951, 1973, 1986). In this study, a total of 10 Crepidotus species were confirmed. Among them, Korean common names were designated to six unrecorded species as follows: C. uber, "끈적귀버섯"; C. hygrophanus, "곤약귀버섯"; C. latifolius, "꼬마무리귀버섯"; C. obscurus, "먼지귀버섯"; C. subverrucisporus, "분홍주름귀버섯"; and C. circinatus, "노란고리귀버섯". A key to 10 Crepidotus species has been constructed.

• 한국의류산업학회지
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• 제23권2호
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• pp.226-236
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• 2021

The purpose of this study was to classify the torso shape based on abdominal protrusion caused by changes in the physical characteristics of middle-aged women. This study analyzed 3D shape data of 401 females ranging in age from 40 to 59 years who participated in the 6th Size Korea project. Based on the Size Korea 3D measurement standard, 27 additional items such as height, protrusion, and angle were measured in the 3D scan data. Nine factors were extracted from the analysis of constituent factors of the torso: "vertical size of torso," "flatness and protrusion of abdomen," "torso front extrusion," "upper body height," "bust size and flatness," "size of belly and angle of lower abdomen," "hip length," "hip flatness," and "horizontal size of bust." As a result of the cluster analysis using these nine factors, the torsos of middle-aged women were classified into three types. Type 1 has upper abdominal deposition with a small and long upper body and an advanced abdomen; type 2 has lower abdominal deposition with a small and short torso and a small belly and hip flexion; and type 3 has central abdominal deposition with a big and long torso, large breasts, and protruding abdo¬men front. The middle-aged women were mostly distributed in Type 2. The above results will be useful as basic data for the development of clothing with improved fit to accommodate the changed physical characteristics of middle-aged women.