• Genomics & Informatics
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• v.3 no.3
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• pp.63-67
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• 2005

Adaptive responses to diverse microbial pathogens might be limited in relatively few types. Host cell responses to pathogens are believed to be patterned or stereotyped along with species or class. We tried to compose the host response to Mycoplasma in terms of cellular gene expression. Although gene expression profile of two host HeLa and 293 cells were quite different each other, 30 genes were differentially expressed by mycoplasma infection in both of HeLa and 293 cells. Six of them (PR48, MADH4, MKPX, CRK, RBM7, NEK3) were related to cell cycle or proliferation. Another category of genes like IL1 HY1, KLRF1, TNFSF14, GBP1 were host defense to elicit immune responses. With this set of genes, we establish the prediction model for mycoplasma contamination.

• Journal of the Korean Institute of Gas
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• v.21 no.3
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• pp.70-76
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• 2017

Although various methods have been tried to measure the safety culture of firms, they are limited to derive the qualitative analysis results according to the subjective criteria that are not formalized according to the evaluation method. We developed a questionnaire that can be applied to a combined power plant, quantified the evaluation results using the system dynamics model based on the results, and conducted simulation through various scenarios. And to present the criteria for safety cultural policy.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.199-203
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• 2023

Influential trend that widely reflected the software engineering industry is service oriented architecture. Vendors are migrating towards cloud environment to benefit their organization. Companies usually offer products and services with a goal to solve problems at customer end. Because customers are more interested in solution of their problem rather than focusing on products or services. In software industry the approach in which customers' problems are solved by providing services is known as software as a service. However, software development life cycle encounters enormous changes when migrating software from product model to service model. Enough research has been done on the overall development process but a limited work has been done on the factors that influence requirements elicitation process. This paper focuses on those changes that influence requirement elicitation process and proposes a systematic methodology for transformation of software from product to service model in a successful manner. The paper then elaborates the benefits that inherently come along with elicitation process in cloud environment. The paper also describes the problems during transformation. The paper concludes that requirement engineering process turn out to be more profitable after transformation of traditional software from product to service model.

• Journal of The Korean Association For Science Education
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• v.40 no.3
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• pp.237-251
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• 2020

Issues on climate change we are facing, such as global warming, are very important as it affects our lives directly. To overcome this, efforts to reduce greenhouse gases emissions (e.g., carbon dioxide) are necessary and these efforts should be based on our integrated understanding of carbon cycle. The purpose of this study is to examine the research trend on carbon cycle education and to suggest the value and direction of carbon cycle education for students who will be citizens of the future. We analyzed 52 carbon cycle education related studies collected from academic research databases (RISS, KCI, ERIC, Google Scholar, and others). As a result, we conclude that resources are still limited and more researches on verification and utilization of developed program, development of accurate and comprehensive tools for students' recognition and level assessment, developing educational model or teacher professional development, providing more appropriate curriculum resources, and the use of various topics or materials for carbon cycle education are necessary. Students' comprehensive understanding of the carbon cycle is important to actively react to the changes in the global environment. Therefore, to support such learning opportunities, resources that can be connected to students' daily experiences to improve students' understanding of carbon cycle and replace misconceptions based on the verification of existing programs should be provided in the classroom as well as the curriculum. In addition, sufficient exemplary cases in carbon cycle education including various materials and topics should be provided through professional development to support teachers teaching strategies with carbon cycle.

• Journal of architectural history
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• v.31 no.1
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• pp.41-50
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• 2022

Traditional wooden buildings deform over time and are vulnerable to fire or earthquakes. Therefore, traditional wooden buildings require continuous management and repair, and securing architectural drawings is essential for repair and restoration. Unlike modernized CAD drawings, traditional wooden building drawings scan and store hand-drawn drawings, and in this process, many noise is included due to damage to the drawing itself. These drawings are digitized, but their utilization is poor due to noise. Difficulties in systematic management of traditional wooden buildings are increasing. Noise removal by existing algorithms has limited drawings that can be applied according to noise characteristics and the performance is not uniform. This study presents deep artificial neural network based noised reduction for architectural drawings. Front/side elevation drawings, floor plans, detail drawings of Korean wooden treasure buildings were considered. First, the noise properties of the architectural drawings were learned with both a cycle generative model and heuristic image fusion methods. Consequently, a noise reduction network was trained through supervised learning using training sets prepared using the noise models. The proposed method provided effective removal of noise without deteriorating fine lines in the architectural drawings and it showed good performance for various noise types.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

• IE interfaces
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• v.15 no.3
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• pp.279-285
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• 2002

A break-even analysis is a method used widely for profit planning or decisions in most companies. It is useful tool in financial studies because it is simple and offers useful insights from a modest amount of data. Although it is widely used, it has some weaknesses. It is limited in particular to the analysis for a short term time horizon or one period. We suggest a new break-even procedure to analyze projects with a long term time horizon as keeping the simplicity of a conventional break-even analysis. We will make efforts doing to include actual data for a cost or an income as much as possible rather than developing a mathematical model to improve unreality of a traditional break-even analysis. Also, we will use the spreadsheet software to solve problems.

• Korean Journal of Biological Psychiatry
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• v.18 no.2
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• pp.61-71
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• 2011

Substance addiction is a chronically relapsing disorder that has been characterized by a vicious cycle composed of intoxication, craving/anticipation, withdrawal, and response inhibition/bingeing. Here we summarize the findings from neuroimaging studies in addiction according to these behavioral components and suggest the integrated neurobiological model of drug addiction and related brain correlates. The roles of various prefrontal regions, thalamus, memory circuit, anterior cingulated, and insula were also suggested in addition to those of classical mesolimbic dopaminergic system and its responsivity. Limited studies of behavioral addiction demonstrated a similarity with substance addiction on the neurobiological basis. Based on the current understanding of neurobiology of addiction, further researches on interactions of behavioral components and their brain correlates, behavioral addiction, and therapeutic applications will be desired.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.125-136
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• 2005

As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.3
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• pp.347-354
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• 2020

Site characterization for decommissioning Kori Unit 1 is ongoing in South Korea after 40 years of successful operation. Kori Unit 1's containment building is assumed to be mostly radioactively contaminated, and therefore radiation exposure management and detailed contamination investigation are required for decommissioning and dismantling it safely. In this study, site-specific Derived Concentration Guideline Levels (DCGLs) were derived using the residual radioactivity risk evaluation tool, RESRAD-BUILD code. A conceptual model of containment building for Kori Unit 1 was set up and limited occupational worker building inspection scenario was applied. Depending on the source location, the maximum contribution source and exposure pathway of each radionuclide were analyzed. The contribution of radionuclides to dose and exposure pathways, by source location, is expected to serve as basic data in the assessment criteria of survey areas and classification of impact areas during further decommissioning and decontamination of sites.