• Journal of the Korea Society of Computer and Information
• /
• v.23 no.1
• /
• pp.85-90
• /
• 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.

• Aerospace Engineering and Technology
• /
• v.7 no.2
• /
• pp.38-45
• /
• 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.

• Journal of Society of Preventive Korean Medicine
• /
• v.21 no.2
• /
• pp.69-78
• /
• 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.

• Journal of Biomedical Engineering Research
• /
• v.42 no.5
• /
• pp.241-249
• /
• 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.

• Journal of Information Technology Services
• /
• v.15 no.2
• /
• pp.51-63
• /
• 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

• The Journal of the Korea Contents Association
• /
• v.20 no.9
• /
• pp.1-10
• /
• 2020

National R & D data covers information in all fields from basic science research to industrialization, but it is expressed in technical terms, which make it difficult for the public to use. Accordingly, NTIS developed and launched the data curation service 'R&D issue service', which selects national R&D information on national and social issues and provides them to the public. Therefore, this study aims to analyze the effect of a data curation service on NTIS users' access to R&D data and suggest how to develop the curation service. The R&D issue service extracts issue from the news article and provide related national R&D projects, achievements and major research institute. All raw data used for the service are open to the public, organized in a report format and provided as PDF files. In addition, automative process is developed for all NTIS users to make individual issue packaging like administrator. The results show that 'R&D issue service' launching increases users' access and convenience to R&D data related to major issues, and the number of page views of users increased after the service was opened.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_4
• /
• pp.1341-1350
• /
• 2019

This research deals with algorithm for forest fire severity classification using multi-temporal KOMPSAT-3A image to mapping forest fire areas. The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution and multi-spectral imagery with infrared and high resolution electro-optical bands. However, there is a lack of research to classify forest fire severity using KOMPSAT-3A. Therefore, the purpose of this study is to analyze forest fire severity using KOMPSAT-3A images. In addition, this research used pre-fire and post-fire Sentinel-2 with differenced Normalized Burn Ratio (dNBR) to taking for burn severity distribution map. To test the effectiveness of the proposed procedure on April 4, 2019, Gangneung wildfires were considered as a case study. This research used the probability density function for the classification of forest fire damage severity based on R software, a free software environment of statistical computing and graphics. The burn severities were estimated by changing NDVI before and after forest fire. Furthermore, standard deviation of probability density function was used to calculate the size of each class interval. A total of five distribution of forest fire severity were effectively classified.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2168-2187
• /
• 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
• /
• v.32 no.2
• /
• pp.57-67
• /
• 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.

• Fashion & Textile Research Journal
• /
• v.23 no.2
• /
• pp.226-236
• /
• 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.