• Advances in Energy Research
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• v.5 no.2
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• pp.91-105
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• 2017

Thermal hydraulic (TH) analysis of nuclear power reactors is utmost important. In this way, the numerical codes that preparing TH data in reactor core are essential. In this paper, a subchannel analysis of a Russian pressurized water reactor (WWER1000) core with enhanced numerical code is carried out. For this, in fluid domain, the mass, axial and lateral momentum and energy conservation equations for desired control volume are solved, numerically. In the solid domain, the cylindrical heat transfer equation for calculation of radial temperature profile in fuel, gap and clad with finite difference and finite element solvers are considered. The dependence of material properties to fuel burnup with Calza-Bini fuel-gap model is implemented. This model is coupled with Isotope Generation and Depletion Code (ORIGEN2.1). The possibility of central hole consideration in fuel pellet is another advantage of this work. In addition, subchannel to subchannel and subchannel to rod connection data in hexagonal fuel assembly geometry could be prepared, automatically. For a demonstration of code capability, the steady state TH analysis of a the WWER1000 core is compromised with Thermal-hydraulic analysis code (COBRA-EN). By thermal hydraulic parameters averaging Fuel Assembly-to-Fuel Assembly method, the one sixth (symmetry) of the Boushehr Nuclear Power Plant (BNPP) core with regular subchannels are modeled. Comparison between the results of the work and COBRA-EN demonstrates some advantages of the presented code. Using the code the thermal modeling of the fuel rods with considering the fission gas generation would be possible. In addition, this code is compatible with neutronic codes for coupling. This method is faster and more accurate for symmetrical simulation of the core with acceptable results.

• Journal of Korea Water Resources Association
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• v.37 no.8
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• pp.613-622
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• 2004

The simulation results of final closing by the developed model considering the flows through tide embankment of non-Darcy and through sluice gate agree well to the observed data which shows the model applicability. In comparative analysis with observed data, the simulation results by Homma(1958) are more accurate than those by Na(1987). The free flow equation with discharge coefficient, regardless of free or submerged flows, by Na based on the submergence ratio is applicable to the engineering practices. Because two simulated discharges are greater than the actual one, the correction of discharge coefficients reflecting the irregular section of actual closing gap situation is necessary. In the hydraulic analysis of final closing, the flow through tide embankment has been generally analysed by Darcy. Hydraulic analysis by the correct discharge through tide embankment of non-Darcy flow is necessary, because the ratio between flows through tide embankment and closing gap is relatively great at final closing.

• The Journal of Information Systems
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• v.22 no.3
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• pp.25-42
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• 2013

Recently various kinds of Information Technology services are created and the quantities of the data flow are increase rapidly. Not only that, but the data patterns that we deal with also slowly becoming diversity. As a result, the demand of discover the meaningful knowledge/information through the various mining analysis such as linkage analysis, sequencing analysis, classification and prediction, has been steadily increasing. However, solving the business problems using data mining analysis does not always concerning, one of the major causes of these limitations is there are some analyzed data can't accurately reflect the real world phenomenon. For example, although the time gap of purchasing the two products is very short, by using the traditional sequencing analysis, the precedence relationship of the two products is clearly reflected. But in the real world, with the very short time interval, the precedence relationship of the two purchases might not be defined. What was worse, the sequence of the purchase intention and the sequence of the purchase realization of the two products might be mutually be reversed. Therefore, in this study, an expanded sequencing analysis methodology has been proposed in order to reflect this situation. In this proposed methodology, the purchases that being made in a very short time interval among the purchase order which might not important will be notice, and the analysis which included the original sequence and reversed sequence will be used to extend the analysis of the data. Also, to some extent a very short time interval can be defined as the time interval, so an experiment were carried out to determine the varying based on the time interval for the actual data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.14-24
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• 2020

Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade's biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

• Environmental Analysis Health and Toxicology
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• v.23 no.4
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.388-394
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• 2007

In wireless network, we propose a predictive location update scheme which considers mobile user's(MU's) mobility patterns. MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• Journal of Korean Society for Quality Management
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• v.29 no.1
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• pp.160-172
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• 2001

The purpose of this study is to develop a successful strategy that can satisfy customer needs effectively based on the recognition of cognitive gaps toward the Internet shopping mall between managers and customers. Internet shopping mall becomes a main cyber space for future shopping, Despite some pessimistic view on the future of cyber shopping, the amount of purchase in Internet shopping has increased continuously and dramatically. In order to compare and analyze the cognitive difference between managers and customers, this study investigates the view of managers as Internet shopping mall operators as well as that of customers. Questionnaires and brief interviews were carried out to collect empirical data. Empirical results find the significant cognitive gap in the perception of importance of factors affecting shopping malls between managers and customers. After analysing the empirical data with statistical methods, this study finds that six of nine factors show significantly different views in perception of Internet shopping mall between managers and customers. The findings of this study can be employed to implement an Internet shopping mall strategy to better serve customer needs and requirements to gain competitive advantage in this emerging market with growing competition.

• Journal of Construction Engineering and Project Management
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• v.5 no.4
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• pp.16-22
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

• Journal of Korean society of Dental Hygiene
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• v.23 no.4
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• pp.303-309
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• 2023

Objectives: According to the Korea Education Development Institute, the college admission quota is expected to exceed the number of high school graduates, leading to an anticipated expansion in the gap between them. This paper aims to conduct an empirical analysis of the variables previously studied, with a specific focus on the admission competition rate for the department of dental hygiene. Methods: The research methodology is the multiple linear regression analysis. The research data contains the structured data from academy information, and the web-based unstructured data collected over the past 3 years. Results: After conducting the analysis, it was newly discovered that the university's online recognition and its location in the metropolitan area were statistically significant factors influencing the admission competition rate for the department of dental hygiene. Conclusions: The findings of this study are expected to be helpful in formulating admission strategies for universities to attract new students and identifying the factors that influence student attraction.