• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.1-14
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• 2009

A currently domestic governmental R&D business is early to 100. And this is each managed individually in 15 professional organizations of research and management by characteristics of a business. For this Reason, A redundant investment issue regarding national R&D occurs, and an issue regarding efficiency of R&D investment by insufficiency of systematic R&D research project and result management is continuously raised. Ministry of Education Science and Technology establishing National Science & Technology Information Service(NTIS) in order to solve these issues. NTIS is the national R&D Portal System which can support efficiency of research and development to result utilization in planning of national research and development. In this paper We consider integrated DB constructions and Information Linking of R&D Participants/Projects/Results information in a NTIS system for data quality Improvement. and then We analyze the cause of the data quality problem, and we propose the improvement plan for data quality elevation of NTIS system.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.689-699
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• 2020

The National Science and Technology Information Center (NDSL) database, which provides academic papers at home and abroad, collects, builds, and manages data collected from various sources. In this study, we analyzed the DB paper schema and DB metadata that are currently constructed and managed to derive an integrated DB schema that can manage the high-value-added papers and manage them efficiently by analyzing distributed DB papers. Also, the final academic information data items were determined through comparison and analysis using the Web of Science and SCOPUS schemas that are currently purchased and possessed. The academic information data items constructed and serviced through this study were summarized into seven papers, authors, abstracts, institutions, themes, journals, and references, and defined as core contents under construction. The integrated DB schema was created through this study, and the results of this study will be used as a basis for constructing the integrated DB collection of high quality academic papers and designing the integrated system.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.17-23
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• 2019

In this paper, quality control (QC) is applied to each meteorological element of weather data collected from seven IoT sensors such as temperature. In addition, we propose a method for estimating the data regarded as error by means of machine learning. The collected meteorological data was linearly interpolated based on the basic QC results, and then machine learning-based QC was performed. Support vector regression, decision table, and multilayer perceptron were used as machine learning techniques. We confirmed that the mean absolute error (MAE) of the machine learning models through the basic QC is 21% lower than that of models without basic QC. In addition, when the support vector regression model was compared with other machine learning methods, it was found that the MAE is 24% lower than that of the multilayer neural network and 58% lower than that of the decision table on average.

• Database Research
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• v.34 no.3
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• pp.86-98
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• 2018

Point-of-Interest(POI) recommendation systems suggest the most interesting POIs to users considering the current location and time. With the rapid development of smartphones, internet-of-things, and location-based social networks, it has become feasible to accumulate huge amounts of user POI visits. Therefore, instant recommendation of interesting POIs at a given time is being widely recognized as important. To increase the performance of POI recommendation systems, several studies extracting users' POI sequential preference from POI check-in data, which is intended for implicit feedback, have been suggested. However, when constructing a model utilizing sequential preference, the model encounters possibility of data distortion because of a low number of observed check-ins which is attributed to intensified data sparsity. This paper suggests refinement of temporal intervals based on data confidence. When building a POI recommendation system using temporal intervals to model the POI sequential preference of users, our methodology reduces potential data distortion in the dataset and thus increases the performance of the recommendation system. We verify our model's effectiveness through the evaluation with the Foursquare and Gowalla dataset.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.

• The Journal of Bigdata
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• v.5 no.2
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• pp.69-76
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• 2020

This study was conducted with the support of the Information and Communication Technology Promotion Center, funded by the government (Ministry of Science and ICT) in 2019. Highly pathogenic avian influenza (HPAI) is an acute infectious disease of birds caused by highly pathogenic avian influenza virus infection, causing serious damage to poultry such as chickens and ducks. High pathogenic avian influenza (HPAI) is caused by focusing on winter rather than year-round, and sometimes does not occur at all during a certain period of time. Due to these characteristics of HPAI, there is a problem that does not accumulate enough actual data. In this paper study, GAN network was utilized to generate actual similar data containing missing values and the process is introduced. The results of this study can be used to measure risk by generating realistic simulation data for certain times when HPAI did not occur.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.670-675
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• 2022

In the era of the 4th industrial revolution, everything is data-centric. The type and amount of data may be central, and new data may be required in special circumstances. As 3D printers are used in various fields, there are fields that are newly challenged. In particular, in the medical field, new attempts that have not been considered before are taking place. This paper is a study to enable research in fields that require physical properties of the human body. In the meantime, research using human organs has mainly used the materials made of silicon. We measure the physical properties of the human body from cadavers, apply these characteristics to develop new materials, and develop artificial organs with 3D printers. Using the artificial organs made in this way, you can practice surgery with a robot that removes kidney stones. In this paper, we would like to introduce a series of research processes to develop advanced materials similar to human organs.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.3
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• pp.241-248
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• 2023

The value of experimentally obtained data becomes highest when they are properly analyzed based on valid logics. Many physical and chemical properties such as electrical and magnetic properties, chemical reaction rates, etc. are known to be thermally activated; thus, a proper understanding of thermally-activated processes is of importance. However, there are still a number of papers published with falsely analyzed data. In this contribution, we would like to revisit the meaning of thermally-activated processes, and then reanalyze a data set published misinterpreted. By showing a step-by-step procedure for the reanalysis, we would like to help researchers who may come across such data in the future not to make mistakes in their analysis.

• Digital Contents
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• no.12 s.91
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• pp.74-79
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• 2000

데이터베이스에서 기초정보로 포함되는 여러가지 수학 기호와 수식은 일반 문자들과는 다른 독특한 처리 방법을 필요로 한다. 워드프로세서에 포함되어 있는 수식 편집기가 이런 기능을 처리하는 대표적 예인데, 과학기술분야에서는 이전부터 TeX과 Tex의 매크로 패키지인 LaTeX의 규칙이 많이 이용되고 있다. 이외에도 한글의 수식편집기에도 사용되는 eqn, SGML계열의 수식 DTD등 수식표현을 위한 문법은 여러가지가 있다. 과학기술분야의 출판물이나 학술지 제공 서비스는 웹상으로 옮겨가는 추세이며, 다양한 애플리케이션간의 데이터 교환 언어로 XML이 부상하고 있다.

• The Science & Technology
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• v.32 no.9 s.364
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• pp.18-20
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• 1999

1백40억년 전의 대폭발(빅뱅)로 우주가 탄생했다는 우주대폭발생성론은 1992년 인공위성 코비(우주배경방사 탐색기)가 보내온 데이터로 과학적인 뒷받침을 받기 시작했다. 그런데 우주가 대폭발로 시작되었다는 것을 1948년 박사학위논문에서 수학적으로 처음 제시한 사람은 랠프 알퍼(Ralph Alpher,79세)였다는 사실을 알고 있는 사람은 많지 않다. 대신 뒤늦게 빅뱅이론을 뒷받침하는 우주배경방사를 발견하여 1978년 노벨물리학상을 받은 펜지아스(Amo Penzios)와 윌슨(Robert Wilson)은 세계적인 명사로 널리 알려져 있으나.