• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1101-1106
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• 2005

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.35-37
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• 2013

UCI is contributing to establishing and administrating CMS to improve the quality of contents efficiently and effectively. In these days, enterprises are also making a new try to manage copyrights of digital contents by use of DRM(Digital Right Management). UCI would be a good solution to solve this overburden. The objective of our research is to study on practical uses of various digital contents models on the basis of UCI. We introduce two business cases; one is publishment of digital contents and the other is DB service of digital contents.

• Journal of Magnetics
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• v.17 no.2
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• pp.115-123
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• 2012

Contactless electrical power transfer through an air gap is a revived technology for supplying energy to many movable applications including Maglev. In this paper, magnetic equivalent circuits and analytical models of contactless electrical power transfer systems are developed and evaluated through experiment. Overall coupling coefficient and overall efficiency are introduced as means for evaluating the systems' performance. Compensating capacitors in primary and secondary sides of the systems improve the overall coupling coefficient and overall efficiency. Using the analytical models, the effects of different parameters and variables such as air gap and load current are analyzed to give a high coupling coefficient and an improved efficiency of power transfer for different compensation structures.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.803-814
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• 2016

Recent times have seen an exponential increase in the amount of spatial data, which is in many cases associated with temporal data. Recent advances in computer technology and computation of hierarchical Bayesian models have enabled to analyze complex spatio-temporal data. Our work aims at modeling data of daily average nitrogen dioxide (NO2) levels obtained from 25 air monitoring sites in Seoul between 2003 and 2010. We considered an independent Gaussian process model and an auto-regressive model and carried out estimation within a hierarchical Bayesian framework with Markov chain Monte Carlo techniques. A Gaussian predictive process approximation has shown the better prediction performance rather than a Hierarchical auto-regressive model for the illustrative NO2 concentration levels at any unmonitored location.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1995.10a
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• pp.135-136
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• 1995

Resent advances in computer technology have introduced a sophisticated capability for computing the biological fate of toxicants in a biological system. This methodology, which has drastically altered risk assessment skill in toxicology, is designed using all the mechanistic information, and all claim better accuracy with extrapolating capability Iron animal to people than conventional pharmacokinetic methods. Biologically based mathematical models in which the specific mechanistic steps governing tissue disposition(pharmacokinetics) and toxic action (pharmacodynamics) of chemicals are constructed in quantitative terms by a set of equations loading to prediction of the outcome of specific toxicological experiments by computer simulation. pharmacokinetic and pharmacodynamic models are useful in risk assessment because their mechanistic biological basis permits the high-to-low dose, route to route and interspecies extrapolation of the tissue disposition and toxic action of chemicals.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.1-7
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• 2020

As the demand for health screening increases, there is a need for efficient design of screening items. We build machine learning models for health screening and recommend screening items to provide personalized health care service. When offline, a synthetic data set is generated based on guidelines and clinical results from institutions, and a machine learning model for each screening item is generated. When online, the recommendation server provides a recommendation list of screening items in real time using the customer's health condition and machine learning models. As a result of the performance analysis, the accuracy of the learning model was close to 100%, and server response time was less than 1 second to serve 1,000 users simultaneously. This paper provides an adaptive and automatic recommendation in response to changes in the new screening environment.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.47-55
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• 2008

The Internet is one of the most infrastructure for information technology in school education. Providing the Internet with a proper bandwidth is an important element for efficient school education for information technology, especially because several instructional models based on new Internet technologies are under development. To support these instructional models, it is important for the schools to provide the proper Internet bandwidth wherever necessary. In this paper, the amount and pattern of internet usage in school were analyzed. Based on this analysis, we propose how to figure out a proper bandwidth for a different ladder of schools.

• Structural Engineering and Mechanics
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• v.30 no.2
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• pp.225-245
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• 2008

T-splines are recently proposed mathematical tools for geometric modeling, which are generalizations of B-splines. Local refinement can be performed effectively using T-splines while it is not the case when B-splines or NURBS are used. Using T-splines, patches with unmatched boundaries can be combined easily without special techniques. In the present study, an analysis framework using T-splines is proposed. In this framework, T-splines are used both for description of geometries and for approximation of solution spaces. This analysis framework can be a basis of a CAD/CAE integrated approach. In this approach, CAD models are directly imported as the analysis models without additional finite element modeling. Some numerical examples are presented to illustrate the effectiveness of the current analysis framework.

• 한국컴퓨터산업교육학회:학술대회논문집
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• 2003.11a
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• pp.127-133
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• 2003

The data models which express all types of video information physically and logically. and the definition of spatiotemporal relationship of video data objects In This paper, we classifies meta-model for efficient management on spatiotemporal relationship between two objects in video image data, suggests meta-models based on Rambaugh's OMT technique, and expanded user model to apply the adaptive model, established from hyper-media or web agent to VOD. The proposed meta-model uses data's special physical feature: the effects of camera's and editing effects of shot, and 17 spatial relations on Allen's 13 temporal relations, topology and direction to include logical presentation of spatiotemporal relation for possible spatiotemporal reference and having unspecified applied mediocrity.

• Interdisciplinary Bio Central
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• v.3 no.3
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• pp.9.1-9.5
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• 2011

Entity Attribute Value (EAV) is the widely used solution to represent high dimensional and sparse data, but EAV is not search efficient for knowledge extraction. In this paper, we have proposed a search efficient data model: Optimized Entity Attribute Value (OEAV) for physical representation of high dimensional and sparse data as an alternative of widely used EAV. We have implemented both EAV and OEAV models in a data warehousing en-vironment and performed different relational and warehouse queries on both the models. The experimental results show that OEAV is dramatically search efficient and occupy less storage space compared to EAV.