• Bioinformatics and Biosystems
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• 제2권2호
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• pp.52-57
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• 2007

The computational discovery of transcription factor binding site is one of the important tools in the genetic and genomic analysis. Rough prediction of gene regulation network and finding possible co-regulated genes are typical applications of the technique. Countless motif-discovery algorithms have been proposed for the past years. However, there is no dominant algorithm yet. Each algorithm does not give enough accuracy without extensive information. In this paper, we explore the possibility of combining multiple algorithms for the one integrated result in order to improve the performance and the convenience of researchers. Moreover, we apply new high order information that is reorganized from the set of basis predictions to the final prediction.

• 한국정보시스템학회지:정보시스템연구
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• 제14권3호
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• pp.53-58
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• 2005

In this study, we will employ a multi-agent for the search and extraction of data in a distributed environment. We will use an Integrator Agent in the proposed model on the Hierarchical Clustering and Association Rule Discovery(HCARD). The HCARD will address the inadequacy of other data mining tools in processing performance and efficiency when use for knowledge discovery. The Integrator Agent was developed based on CORBA architecture for search and extraction of data from heterogeneous servers in the distributed environment. Our experiment shows that the HCARD generated essential association rules which can be practically explained for decision making purposes. Shorter processing time had been noted in computing for clusters using the HCARD and implying ideal processing period than computing the rules without HCARD.

• Biomolecules & Therapeutics
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• 제19권1호
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• pp.1-8
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• 2011

G-protein coupled receptors (GPCRs) constitute an important class of drug targets and are involved in every aspect of human physiology including sleep regulation, blood pressure, mood, food intake, perception of pain, control of cancer growth, and immune response. Radiometric assays have been the classic method used during the search for potential therapeutics acting at various GPCRs for most GPCR-based drug discovery research programs. An increasing number of diverse small molecules, together with novel GPCR targets identified from genomics efforts, necessitates the use of high-throughput assays with a good sensitivity and specificity. Currently, a wide array of high-throughput tools for research on GPCRs is available and can be used to study receptor-ligand interaction, receptor driven functional response, receptor-receptor interaction,and receptor internalization. Many of the assay technologies are based on luminescence or fluorescence and can be easily applied in cell based models to reduce gaps between in vitro and in vivo studies for drug discovery processes. Especially, cell based models for GPCR can be efficiently employed to deconvolute the integrated information concerning the ligand-receptor-function axis obtained from label-free detection technology. This review covers various platform technologies used for the research of GPCRs, concentrating on the principal, non-radiometric homogeneous assay technologies. As current technology is rapidly advancing, the combination of probe chemistry, optical instruments, and GPCR biology will provide us with many new technologies to apply in the future.

• ETRI Journal
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• 제27권4호
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• pp.355-366
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• 2005

Automatic discovery of physical topology plays a crucial role in enhancing the manageability of modern metro Ethernet networks. Despite the importance of the problem, earlier research and commercial network management tools have typically concentrated on either discovering logical topology, or proprietary solutions targeting specific product families. Recent works have demonstrated that network topology can be determined using the standard simple network management protocol (SNMP) management information base (MIB), but these algorithms depend on address forwarding table (AFT) entries and can find only spanning tree paths in an Ethernet mesh network. A previous work by Breibart et al. requires that AFT entries be complete; however, that can be a risky assumption in a realistic Ethernet mesh network. In this paper, we have proposed a new physical topology discovery algorithm which works without complete knowledge of AFT entries. Our algorithm can discover a complete physical topology including inactive interfaces eliminated by the spanning tree protocol in metro Ethernet networks. The effectiveness of the algorithm is demonstrated by implementation.

• 대한안전경영과학회지
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• 제10권2호
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• pp.105-111
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• 2008

Six sigma has been evolved into three generations. The first generation focused on eliminating or reducing defects as Motorola originally developed and applied. The second generation focused on reducing costs and improving process efficiency as GE extended the first generation. The next generation of six sigma such as D2MAIC(Discovery, Define, Measure, Analyze, Improve, Control) and ICRA(Innovate, Configure, Realize, Attenuate) has been discussed since the beginning of the 21st century. Although the third generation of six sigma emphasizes value creation, but there are few specific tools for its implementation. In this thesis, some tools for finding opportunities for value creation are suggested. It is explained and discussed with examples how the tools can be applied.

• 스마트미디어저널
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• 제12권10호
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• pp.29-37
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• 2023

Human lifestyle is affected by the agricultural development in the last 12,000 years ago. The development of agriculture is one of the reasons that global population surged. To ensure sufficient food production for supporting human life, pesticides as a more effective and economical tools, are extensively used to enhance the yield quality and boost crop production. This study investigated the factors that affect crop production and whether the factors of pesticide usage are the most important factors in crop production using the dataset from Kaggle that provides information based on crops harvested by various farmers. Logistic regression is used to investigate the relationship between various factors and crop production. However, the logistic regression is unable to deal with predictors that are related to each other and identifying the greatest impact factor. Therefore, causal discovery is applied to address the above limitations. The result of causal discovery showed that crop condition is greatly impacted by the estimated insects count, where estimated insects count is affected by the factors of pesticide usage. This study enhances our understanding of the influence of pesticide usage on crop production and contributes to the progress of agricultural practices.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.125-133
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• 1999

The objective of knowledge discovery and data mining lies in the generation of useful insights from a store of data. This paper presents a framework for knowledge mining to provide a systematic approach to the selection and deployment of tools for automated learning. Every methodology has its strengths and limitations. Consequently, a multistrategy approach may be required to take advantage of the strengths of disparate technique while circumventing their individual limitations. For concreteness, the general framework for data mining in marketing is examined in the context of developing agents for optimizing a supply chain network.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.125-133
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• 1999

The objective of knowledge discovery and data mining lies in the generation of useful insights from a store of data. This paper presents a framework for knowledge mining to provide a systematic approach to the selection and deployment of tools for automated learning. Every methodology has its strengths and limitations. Consequently, a multistrategy approach may be required to take advantage of the strengths of disparate technique while circumventing their individual limitations. For concreteness, the general framework for data mining in marketing is examined in the context of developing agents for optimizing a supply chain network.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 1997년도 춘계학술대회
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• pp.3-5
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• 1997

Properties of a good drug include safety, efficacy, half-life and bioavailability. With the current approach to drug discovery based on receptor-based and cell-based screening methods, compounds are frequently moved into development with poor bioavailability. With low bioavailability, drug administration is typically limited to parenteral routes, thus limiting the potential wide-spread utility of these therapeutic agents. The first and most important factor limiting a drug's bioavailability is the intestinal membrane permeability which in turn determines the maximum fi:action of the dose administered that can be absorbed. We have recently utilized new intubation methods for performing permeability measurements in humans and establishing a fundamental human data base for correlating intestinal jejunal membrane permeabilities with permeabilities determined in other systems, e.g., animals, tissue culture, as well as physical chemical properties.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.271-272
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• 2014

범죄 수사에서 디지털 증거물이 증가됨에 따라, 법적으로 효용성이 큰 데이터를 추출할 수 있는 디지털 포렌식 도구에 대한 중요성이 높아지고 있다. 디지털 제품들은 빠르게 성장하고 있고, 포렌식 도구는 사용자와 사건에 맞도록 용이하게 구현 되어야 한다. 포렌식 업계나 정부에서는 소요 비용이 큰 포렌식 도구를 사용하고 있지만 메모리 한계, 사후 감사의 한계 등 한계성이 제시되고 있다. 이러한 문제를 해결하기 위하여 다양한 포렌식 도구가 빠르게 구현 할 수 있도록 오픈소스 포렌식 도구 개발이 필요하다. 본 논문에서는 현재 상용화 되고 있는 디지털 포렌식 기술들에 관해 연구하고, 이들의 한계성을 극복하기 위한 오픈 디지털 포렌식 기법들을 제시하고, 적용 방안에 대해 제안한다.