• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.768-770
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• 2015

We performed integration and standardization of the omics data related agriculture. To do this, we requires progressed computational methods and bioinformatics infrastructures for integration, standardization, mining, and analysis. It makes easier biological knowledge to find. we potentialize registration a row and processed data in NABIC (National Agricultural Biotechnology Information Center) and its processed analysis results were offered related researchers. And we also provided various analysis pipelines, NGS analysis (Reference assembly, RNA-seq), GWAS, Microbial community analysis. In addition, the our system was carried out based on the design and build the quality assurance in management omics information system and constructed the infrastructure for utilization of omics analyze system. We carried out major improvement quality of omics information system. First is Improvement quality of registration category for omics based information. Second is data processing and development platform for web UI about related omics data. Third is development of proprietary management information for omics registration database. Forth is management and development of the statistics module producers about omics data. Last is Improvement the standard upload/ download module for Large omics Registration information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1179-1187
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• 2019

In today's technology environment, most big data-based applications and solutions are based on real-time processing of streaming data. Real-time processing and analysis of big data streams plays an important role in the development of big data-based applications and solutions. In particular, in the maritime data processing environment, the necessity of developing a technology capable of rapidly processing and analyzing a large amount of real-time data due to the explosion of data is accelerating. Therefore, this paper analyzes the characteristics of NiFi, Kafka, and Druid as suitable open source among various open data technologies for processing big data, and provides the latest information on external linkage necessary for maritime service analysis in Korean e-Navigation service. To this end, we will lay the foundation for applying open data framework technology for real-time data processing.

• Journal of the Korean Society of Tobacco Science
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• v.17 no.1
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• pp.5-14
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• 1995

Efficient algorithms for the automatic classification of flue-cured tovacco ripeness and grading have been developed The ripeness of the tobacco was classified into 4 levels vased on the color. The lab-built simple RGB color measuring system was utilized for detecting the light reflectance of the tobacco leaves. The measured data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The spectrophotometer was used to detect the light reflectance and absorption of the graded tobacco leaves in the frequency ranges of the visible light The measured data and the statistical analysis was performed to investigate the light characteristics of the graded samples. The measured data were obtained from samples of 5 different grades directly without considering the leaf positions. Those data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The neural network based sensor information processing showed successful results for grading of tobacco leaves.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.101-108
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• 2011

The small and medium sprayer has developed to spray well fruit trees and roadside trees with pesticides for pests control within 60 meters. This study was carried out to analyze and evaluate its performance using image processing. While it sprayed with pesticides on the area of 20m in width and 60m in length, it was experimented 5 places by 5m from 0 to 25m width and 6 places by 10m from 10 to 60m length. The experimental image data of each sheet on places were averaged after binarization process. According to the image data, it was sprayed on all working area. However, when sprayer moved 0.3m/s velocity, the place at 15m of width and 30m of length was sprayed more than any other sprayed area, but the place at 15m of width and 60m of length was sprayed less.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.86-94
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• 2003

Electronically available biological literature has been accumulated exponentially in the course of time. So, researches on automatically acquiring knowledge from these tremendous data by text mining technology become more and more prosperous. However, most of the previous researches are technology oriented and are not well focused in practical extraction target, hence result in low performance and inconvenience for the bio-researchers to actually use. In this paper, we propose a more biology oriented target domain specific text mining system, that is, POSTECH bio-text mining system (POSBIOTM), for signal transduction pathway extraction, especially for G protein-coupled receptor (GPCR) pathway. To reflect more domain knowledge, we specify the concrete target for pathway extraction and define the minimal pathway domain ontology. Under this conceptual model, POSBIOTM extracts interactions and entities of pathways from the full biological articles using a machine learning oriented extraction method and visualizes the pathways using JDesigner module provided in the system biology workbench (SBW) [14]

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.409-411
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• 2015

최근 사물인터넷에 대한 발전이 빠르게 이루어짐에 따라서 인터넷 상의 보안 이슈 또한 증가하고 있다. 이에 따라 데이터를 안전하고 은밀하게 통신하기 위한 공개키 기반 구조 (public-Key Infrastructure: PKI) 기술이 발전하고 있다. PKI는 신뢰할 수 있는 기관에서 개인이나 기관을 식별할 수 있는 인증서를 저장하고 있으며 이를 활용할 수 있도록 돕는 디렉토리 서비스를 제공한다. 특히 기존의 PKI 구조에는 사용자의 경험이 담겨있는 패스워드 기반으로 개인키를 암호화 하고 있다. 이는 사용자 인증과 데이터 암호화와 같은 강력한 보안 서비스를 제공하고 있지만 이 또한 취약점을 내포하고 있다. 본 논문에서는 공개키 기반 구조의 핵심 요소에 대해 논의하며 보안 취약점을 분석한다. 이를 통해 안전한 사물인터넷 환경을 위한 연구 방향을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.294-297
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• 2009

다방면적인 과학기술의 발달은 우리에게 대량의 데이터와 또한 새로운 영역으로의 접근 가능성을 열어주었다. 유전자 정보와 같은 대량의 정보를 다루는 시대가 열리면서 바이오 데이터를 분석하여 새로운 연관성과 정보를 찾아내는 바이오인포매틱스가 고부가가치 창출을 위한 학문으로 특히 부각되고 있다. 본 논문에서는 이러한 연구의 일환으로 보다 효율적인 바이오 데이터 분석을 위해 BNP에 내장된 생태계 모방 알고리즘의 특성을 연구하고, 이를 분류화에 접목시킨 방법에 대해 논하고자 한다.

• Journal of Microbiology and Biotechnology
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• v.27 no.5
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• pp.939-942
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• 2017

The cellular composition and metabolic compounds of Leuconostoc mesenteroides ATCC 8293 were analyzed after cultivation in an anaerobic chemostat. The macromolecular composition was 24.4% polysaccharide, 29.7% protein, 7.9% lipid, 2.9% DNA, and 7.4% RNA. Its amino acid composition included large amounts of lysine, glutamic acid, alanine, and leucine. Elements were in the order of C > O > N > H > S. The metabolites in chemostat culture were lactic acid (73.34 mM), acetic acid (7.69 mM), and mannitol (9.93 mM). These data provide a first view of the cellular composition of L. mesenteroides for use in metabolic flux analysis.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.101-111
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• 2015

Establishment of appropriate data in certain formats is essential for agricultural water cycle analysis, which involves complex interactions and uncertainties such as climate change, social & economic change, and watershed environmental change. The main objective of this study was to develop web-based Data processing and Model linkage Techniques for Agricultural Water-Resource analysis (AWR-DMT). The developed techniques consisted of database development, data processing technique, and model linkage technique. The watershed of this study was the upper Cheongmi stream and Geunsam-Ri. The database was constructed using MS SQL with data code, watershed characteristics, reservoir information, weather station information, meteorological data, processed data, hydrological data, and paddy field information. The AWR-DMT was developed using Python. Processing technique generated probable rainfall data using non-stationary frequency analysis and evapotranspiration data. Model linkage technique built input data for agricultural watershed models, such as the TANK and Agricultural Watershed Supply (AWS). This study might be considered to contribute to the development of intelligent watercycle analysis by developing data processing and model linkage techniques for agricultural water-resource analysis.