• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.379-386
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• 2021

This study was undertaken to develop a cascade-type continuous culture system (CCCS) that combines both ICT and biotechnology (BT), for the mass production of microalgae. This system is capable of maintaining the essential culture conditions of pH, temperature, carbon dioxide, and illuminance control, which are key parameters for the growth of microalgae, and is economical for producing microalgae regardless of the season or location. It has the added advantage of providing stable and high productivity. In the current study, this system was applied to culture microalgae for 71 days, with subsequent analysis of the experimental data. The initial O.D. of the culture measured from incubator 1 was 0.006. On the 71st day of culture, the O.D.s obtained were 0.399 (incubator 1), 0.961 (incubator 2), 0.795 (incubator 3), and 0.438 (incubator 4), thereby confirming the establishment of continuous culture. Thus, we present a smart-farm based on ISMC (in-situ monitoring and control) for a mass culture method. We believe that this developed technology is suitable for commercialization, and has the potential to be applied to hydroponics-based cultivation of microalgae and cultivation of high-value-added medicinal plants as well as other plants used in functional foods, cosmetics, and medical materials.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1925-1934
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• 2022

Monitoring nuclear activity for inaccessible areas using remote sensing technology is essential for nuclear non-proliferation. In recent years, deep learning has been actively used to detect nuclear-activity-related small objects. However, high-resolution satellite imagery containing small objects can result in class imbalance. As a result, there is a performance degradation problem in detecting small objects. Therefore, this study aims to improve detection accuracy by analyzing the effect of the ratio of small objects related to nuclear activity in the input data for the performance of the deep learning model. To this end, six case datasets with different ratios of small object pixels were generated and a U-Net model was trained for each case. Following that, each trained model was evaluated quantitatively and qualitatively using a test dataset containing various types of small object classes. The results of this study confirm that when the ratio of object pixels in the input image is adjusted, small objects related to nuclear activity can be detected efficiently. This study suggests that the performance of deep learning can be improved by adjusting the object pixel ratio of input data in the training dataset.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.3-12
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• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.119-130
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• 2011

On the point of data quality management, data quality is influenced by quality policy, quality organization, business process, and business rule. Business rules, guide of data manipulation, have effects on data quality directly. In case of building an integration database among distributed databases, defining business rule is more important because data integration needs to consider heterogeneous structure, code, and data standardization. Also data value has various figures depended on data type, unit, and transcription. Finally, database structure and data value problem have to be solved to improve data quality. For handling them, it is needed to draw database integration model and cleanse data in integrated database. NTIS(stands for National science and Technology Information Service) has an aim to serve users who need all information about national R&D by internet, and for that aim, it has a integrated database which has been made with several database sources. We prove that database integration model and data cleansing are needed to build a successful integrated database through NTIS case study.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.155-183
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• 2015

The rapid growth of information technologies and data networks has increased the volume of data generated from scholarly research and the possibilities of re-using and sharing such data. However, there is a serious problem of management and sharing of research data due to the lack of facilitating policies and supporting infrastructure. In particular, few data repositories exist that support systematic collection and sharing of research data in the humanities. In this regard, the Korea Research Memory (KRM) established by the Korea Research Foundation is a rare exception. The purpose of this research is to present specific processes and strategies that can facilitate the data collection, reuse and preservation through the KRM using task analysis and source document gathering as main focal points. In addition, in order for the effective collection and sharing of research data, the following recommendations are proposed: 1) the need for the adoption of data management plan related policies that govern the collection and sharing of research data generated from publicly funded research projects, 2) the need for training and support services for individual researchers and research institutes, 3) the need for training data specialists, and 4) the citation scheme and structure designed for research data.

• Journal of The Korean Association of Information Education
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• v.20 no.6
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• pp.543-552
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• 2016

Recently, a number of researches focus on social network analysis and it is applied to various fields not only in social science area but also in natural science area. Therefore, the social network analysis and the text analysis were conducted in order to analyze the current trend of the theses in information education field. The result indicated that the most frequently mentioned words were consistent with the development of information technology and the change in information education curriculum. That is, the mentioned words were computer aided instruction (CAI) and courseware for period 1, ICT for period 2, smart and scratch for period 3, and in period 4, computational thinking ability and coding appeared for the first time. Moreover, as the result of social network analysis, it concluded the research topics became more complicated and detailed as the words diversified throughout the period in which the simplified network in period 1 changed its configuration into a structure with more diversified words of higher centrality.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.11-11
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• 2003

오늘날 단일 슈퍼컴퓨터로는 처리가 불가능한 거대한 문제들의 해법이 시도되고 있는데, 이들은 지리적으로 분산된 슈퍼컴퓨터, 데이터베이스, 과학장비 및 디스플레이 장치 등을 초고속 통신망으로 연결한 GRID 환경에서 효과적으로 실행시킬 수 있다. GRID는 1990년대 중반 과학 및 공학용 분산 컴퓨팅의 연구 과정에서 등장한 것으로, 점차 응용분야가 넓어지고 있다. 그러나 GRID 같은 분산 환경은 기존의 단일 병렬 시스템과는 많은 점에서 다르며 이전의 기술들을 그대로 적용하기에는 무리가 있다. 기존 병렬 시스템에서는 주로 동기 알고리즘(synchronous algorithm)이 사용되는데, 직렬 연산과 같은 결과를 얻기 위해 동기화(synchronization)가 필요하며, 부하 균형이 필수적이다. 그러나 부하 균형은 이질 클러스터(heterogeneous cluster)처럼 프로세서들의 성능이 서로 다르거나, 지리적으로 분산된 계산자원을 사용하는 GRID 환경에서는 이기종의 문제뿐 아니라 네트워크를 통한 메시지의 전송 지연 등으로 유휴시간이 길어질 수밖에 없다. 이처럼 동기화의 필요성에 의한 연산의 지연을 해결하는 하나의 방안으로 비동기 반복법(asynchronous iteration)이 나왔으며, 지금도 활발히 연구되고 있다. 이는 알고리즘의 동기점을 가능한 한 제거함으로써 빠른 프로세서의 유휴 시간을 줄이는 것이 목적이다. 즉 비동기 알고리즘에서는, 각 프로세서는 다른 프로세서로부터 갱신된 데이터가 올 때까지 기다리지 않고 계속 다음 작업을 수행해 나간다. 따라서 동시에 갱신된 데이터를 교환한 후 다음 단계로 진행하는 동기 알고리즘에 비해, 미처 갱신되지 않은 데이터를 사용하는 경우가 많으므로 전체적으로는 연산량 대비의 수렴 속도는 느릴 수 있다 그러나 각 프로세서는 거의 유휴 시간이 없이 연산을 수행하므로 wall clock time은 동기 알고리즘보다 적게 걸리며, 때로는 50%까지 빠른 결과도 보고되고 있다 그러나 현재까지의 연구는 모두 어떤 수렴조건을 만족하는 선형 시스템의 해법에 국한되어 있으며 비교적 구현하기 쉬운 공유 메모리 시스템에서의 연구만 보고되어 있다. 본 연구에서는 행렬의 주요 고유쌍을 구하는 데 있어 비동기 반복법의 적용 가능성을 타진하기 위해 우선 이론적으로 단순한 멱승법을 사용하여 실험하였고 그 결과 순수한 비동기 반복법은 수렴하기 어렵다는 결론을 얻었다 그리하여 동기 알고리즘에 비동기적 요소를 추가한 혼합 병렬 알고리즘을 제안하고, MPI(Message Passing Interface)를 사용하여 수원대학교의 Hydra cluster에서 구현하였다. 그 결과 특정 노드의 성능이 다른 것에 비해 현저하게 떨어질 때 전체적인 알고리즘의 수렴 속도가 떨어지는 것을 상당히 완화할 수 있음이 밝혀졌다.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.442-445
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• 2005

It constructs a database generally and service it does, to use a commercial business DBMS that manages information and to use a retrieval system that supports a search, it adopts the gearing method of the DBMS and information retrieval system. But like this method is inconvenient must operate the DBMS and information retrieval system with duplication to be, there is a weak point where the data management and processing become accomplished with duplication. It presents the DB construction and information search and the management model of the KRISTAL-2002 information retrieval and management system base for the scientific and technical information data management and processing from the dissertation which it sees.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.181-190
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• 2013

In this paper, we designed file system in order to utilize data analysis by using correlation result from Daejeon correlator including related software development. Correlation results are consisted of visibility component (amplitude and phase) of radio source, but for data analysis of correlation result, various information such as weather, radio telescope position, observation time, radio source position, source type, and receiver noise temperature are needed. In this paper, we designed file system as a directory-structure for making use of these informations at Linux system for analyzing data and developed software to make file system. To verify the effectiveness of designed file system and developed software, file system generation experiment is conducted, and then astronomers accepted that there is no severe problem for scientific analysis using designed file system.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.2
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• pp.109-145
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• 2019

Citizens are becoming providers of weather information through crowdsourcing on the Internet. In Korea and abroad, national weather service organizations and companies are using weather information provided by citizens for weather forecasting. Recently, it is necessary to pay attention to the changes and the current status of the producers of meteorological information in the meteorological field as they are aware of the importance of information management including data in academia. In this paper, first, the present status and problems of the weather observation network constructed by each weather information producer were identified. Second, to confirm the crowdsourcing in the meteorological area, the researchers directly participated in the weather forecasting process through crowdsourcing and analyzed the collection, utilization, and the possibility of weather record information. Third, prospects for the utilization of weather information through crowdsourcing were presented.