• Molecules and Cells
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• v.23 no.2
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• pp.123-131
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• 2007

Extracellular stresses induce heat shock response and render cells resistant to lethal stresses. Heat shock response involves induction of heat shock proteins (Hsps). Recently the roles of Hsps in neurodegenerative diseases and cancer are attracting increasing attention and have accelerated the study of heat shock response mechanism. This review focuses on the stress sensing steps, molecules involved in Hsps production, diseases related to Hsp malfunctions, and the potential of proteomics as a tool for understanding the complex signaling pathways relevant to these events.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1128-1135
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• 2003

e-Transformation of an enterprise requires the collaboration of business processes to be suited to the business participants' purpose. To realize this collaboration, business processes should be implemented as components and the system developers could be able to reuse the components for their specific purpose. The first step of this collaboration is the discovery of exact components for business processes. A dilemma, however, is the fact that there are thousands or even millions of business processes which vary from one enterprise to another. Moreover, business processes could be decomposed into multiple levels of semantics and classified into several process areas. In general, discovery of exact business processes requires understanding of widely adopted classification schemes such as CBPC, OAGIS, or SCOR. To cope with this obstacle, business process metadata should be defined and managed regardless of specific classification schemes to support effective discovery and reuse of business processes components. In this paper, a methodology to discover business process components published in different semantic levels is proposed. The proposed methodology represents the metadata of business process components as topic maps stored in a registry and utilizes the powerful features of topic maps for process discovery. TM4J, an open-source topic map engine, is modified to support concept matching and navigation. With the implemented tool, application system developers can discover and publish the business process components effectively.

• Mass Spectrometry Letters
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• v.1 no.1
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• pp.13-16
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• 2010

The active components in a plant extract can be represented as mass profiles. We introduce here a new, multi-compound discovery method known as Scaling of Correlations between Activity and Mass Profiles (SCAMP). In this method, a correlation coefficient is used to quantify similarities between the extract activity and mass profiles. The method was evaluated by first measuring the anti-oxidation activity of eleven fractions of an Astragali Radix extract using DPPH assays. Next, 15 T Fouriertransform ion cyclotron resonance (FT-ICR) MS was employed to generate mass profiles of the eleven fractions. A comparison of correlation coefficients indicated two compounds at m/z 285.076 and 286.076 that were strong antioxidants. Principal component analyses of these profiles yielded the same result. FT-ICR MS, which offers a mass resolving power of 500,000, was used to discern isotopic fine structures and indicated that the molecular formula corresponding to the peak at m/z 285.076 was $C_{16}H_{13}O_5$. SCAMP in combination with high-resolution MS can be applied to any type of mixture to study pharmacological activity and is a powerful tool for active compound discovery in plant extract studies.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.399-417
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• 2020

In this study, we tried to analyze the relative importance of features for various functions provided by Discovery. We identified a total of 36 assessment items in five categories including contents, search function, serendipity, interactivity, and ease of use based on literature review. In order to objectively evaluate the relative importance of each evaluation element, an AHP technique was adopted. As a result, 'Easy of use' received the highest weighted value among the five categories, followed by 'contents', 'search function', 'interactivity', and 'serendipity'. In addition, among all the 36 assessment items, 'Quality of data for central index' had higher weighted value. These findings can be used as basic data to adopt a discovery tool for libraries.

• 한국생물공학회:학술대회논문집
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• 2003.10a
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• pp.138-140
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• 2003

• 한국인삼전략화협의회:학술대회논문집
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• v.2003 no.09
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• pp.54-63
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• 2003

"Korea ginseng (Panax ginseng C.A Meyer) is an important medicinal plant. Its root has been used as an herbal medicine that provides resistance to stress and disease, and prevents exhaustion since the ancient time. Ginsenosides, glycosylated triterpene (saponin), are considered to be the main active compounds of the ginseng root. Despite of considerable commercial interests of ginsenosides, very little is known about the genes and their biochemical pathways for ginsenoside biosynthesis. This work will focus on the identification of genes involved in ginsenoside biosynthesis and the dissection of ginsenoside biosynthetic pathway using a functional genomics tool. Expression sequence tags (ESTs) provide a valuable tool to discovery the genes in secondary metabolite biosynthesis. We generated over 21,155 ginseng ESTs that is now sufficient to facilitate discovering the genes involved in ginsenoside biosynthesis such as oxidosqualene cyclase(OSC), cytochrome P450 and glycosyltransferase. With ESTs information, microarray technology will be used for the analysis of gene expression, and the identification of genes including transcription factors expressed in tissues under given experimental condition. Heterogous system such as yeast and plants will allow us to do the functional analysis. And selected ginseng hairy root which show variation in ginsenoside production will be used as a material for functional analysis of candidate gene. Functional genomics approach will successfully accelerate gene discovery, and also provide promises of metabolic engineering for the ginsenoside production."

• Journal of Power Electronics
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• v.10 no.6
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• pp.643-646
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• 2010

An interactive web-based teaching tool for a power semiconductor course at the University of Central Florida is presented in this paper. A novel approach is introduced using Technology Aided Design Tools (TCAD) to generate time-lapsed 2D semiconductor device cross-section embedded in a webpage using $Adobe^{(R)}$ Flash (web design tool) platform to create interactive movies that demonstrate complex device physical phenomenon. Students can step through the interactive movies forward, backward, pausing, or looping. Each step represents a giving bias condition. Current-voltage plots are represented along with the semiconductor device and a visual point is placed on the IV curve to indicate the current bias conditions. The changes are then reflected in the 2D cross-section movie area and the IV plot. This tool was implemented in a classroom setting to augment the lectures or for discovery learning.

• Journal of Korean Academy of Nursing
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• v.36 no.4
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• pp.652-661
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• 2006

Purpose. The purposes of this study were to apply data mining tool to nursing specific knowledge discovery process and to identify the utilization of data mining skill for clinical decision making. Methods. Data mining based on rough set model was conducted on a large clinical data set containing NMDS elements. Randomized 1000 patient data were selected from year 1998 database which had at least one of the five most frequently used nursing diagnoses. Patient characteristics and care service characteristics including nursing diagnoses, interventions and outcomes were analyzed to derive the meaningful decision rules. Results. Number of comorbidity, marital status, nursing diagnosis related to risk for infection and nursing intervention related to infection protection, and discharge status were the predictors that could determine the length of stay. Four variables (age, impaired skin integrity, pain, and discharge status) were identified as valuable predictors for nursing outcome, relived pain. Five variables (age, pain, potential for infection, marital status, and primary disease) were identified as important predictors for mortality. Conclusions. This study demonstrated the utilization of data mining method through a large data set with stan dardized language format to identify the contribution of nursing care to patient's health.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.877-885
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• 2009

In this paper, we propose the SINDI-Grid which is a high-performance framework for scientific and technological knowledge discovery using the grid computing. By using the advantages of the grid computing providing data repository of large-volume and high-speed computing power, the SINDI-Grid framework provides a variety of grid services for distributed data analysis and scientific knowledge processing. And the SINDI-Workflow tool exploits these services so that performs the design and execution for scientific and technological knowledge discovery applications which integrate various information processing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2316-2332
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• 2024

In this paper, we introduce a web-based system that leverages the capabilities of the ρ(rho)-algorithm, which is a Structure Information Control Net (SICN)-oriented process mining algorithm, with open-source platforms, including Django, Graphviz, and Cytoscape, to facilitate the rediscovery and visualization of business process models. Our approach involves discovering SICN-oriented process models from process instances from the IEEE XESformatted process enactment event logs dataset. This discovering process is facilitated by the ρ-algorithm, and visualization output is transformed into either a JSON or DOT formatted file, catering to the compatibility requirements of Cytoscape or Graphviz, respectively. The proposed system utilizes the robust Django platform, which enables the creation of a userfriendly web interface. This interface offers a clear, concise, modern, and interactive visualization of the rediscovered business processes, fostering an intuitive exploration experience. The experiment conducted on our proposed web-based process discovery system demonstrates its ability and efficiency showing that the system is a valuable tool for discovering business process models from process event logs. Its development not only contributes to the advancement of process mining but also serves as an educational resource. Readers, students, and practitioners interested in process mining can leverage this system as a completely free process miner to gain hands-on experience in rediscovering and visualizing process models from event logs.