• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.239-242
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• 2008

As the distributed generation becomes more reliable and economically feasible, it is expected that a higher application of the distributed generation units would be interconnected to the existing grids. In this context, the Micro Gas Turbines (MGT) by using Bio-gas is being considered as a promising solution. In order to propose a feasible concept of those technologies such as improving environmental effect and economics, we performed a sensitivity study for a biomass fueled MGT using a simulation model. The study consists of 1) the fundamental modeling using manufacturer's technical specifications, 2) the correction with the experimental data, and 3) the prediction of off-design characteristics. The performance analysis model was developed by PEPSE-GT 72, commercial steam/gas turbine simulation technicque.

• Journal of Korean Neurosurgical Society
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• v.61 no.3
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• pp.376-385
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• 2018

Recent discoveries of brain tumor-related genes and fast advances in genomic testing technologies have led to the era of molecular diagnosis of brain tumor. Molecular profiling of brain tumor became the significant step in the diagnosis, the prediction of prognosis and the treatment of brain tumor. Because traditional molecular testing methods have limitations in time and cost for multiple gene tests, next-generation sequencing technologies are rapidly introduced into clinical practice. Targeted sequencing panels using these technologies have been developed for brain tumors. In this article, focused on pediatric brain tumor, key discoveries of brain tumor-related genes are reviewed and cancer panels used in the molecular profiling of brain tumor are discussed.

• IE interfaces
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• v.24 no.2
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• pp.151-155
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• 2011

In this study, we propose a signomial classification method with ₀-regularization (₀-)which seeks a sparse signomial function by solving a mixed-integer program to minimize the weighted sum of the ₀-norm of the coefficient vector of the resulting function and the $L_1$-norm of loss caused by the function. $SC_0$ gives an explicit description of the resulting function with a small number of terms in the original input space, which can be used for prediction purposes as well as interpretation purposes. We present a practical implementation of $SC_0$ based on the mixed-integer programming and the column generation procedure previously proposed for the signomial classification method with $SL_1$-regularization. Computational study shows that $SC_0$ gives competitive performance compared to other widely used learning methods for classification.

• Atmosphere
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• v.23 no.1
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• pp.103-112
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• 2013

In this study, we developed a fog classification algorithm to classify fog type based on fog generation mechanism. For the analysis period of 1986-2005, 15,748 fog events had been reported from the 40 observational sites in South Korea. Thus, practically, it is almost impossible to individually classify the fog type of the whole fog events occurred in South Korea manually. In this study, the characteristics of fog during the research period were investigated and the fog classification flowchart were developed base on the analysis, and the fog classification algorithm was applied for the classification of fogs occurred at the observational sites. Finally, the classified fog-type and hindcasted fog occurance results obtained from the flowchart were evaluated for verification.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.80-86
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• 2015

As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is needed to estimate power outputs of wind generation resources. As a result, geographic information such as latitude and longitude plays a key role to estimate power outputs of spatially distributed wind farms. In this paper, we introduce spatial correlation analysis to estimate the power outputs produced by wind farms that are geographically distributed. We present spatial correlation analysis of empirical power output data for the JEJU Island and ERCOT ISO (Texas) wind farms and propose the Correlation Decay Distance (CoDecDist) model based on geographic correlation analysis to enhance the estimation of wind power outputs.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.51-54
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• 2003

Internal defects such as chevron crack occasionally occur in the process of cold extrusion or cold drawing. It is known that the existence and property of inclusion greatly influences the generation of the internal crack. However, in the plastic working field, research about the effect of the inclusion on the fracture is not theoretically analyzed. This paper describes effects of the physical property of inclusion on the internal fracture generation in the process. Prediction of fracture was evaluated by critical damage value calculated by the equation of Cockcroft & Latham and its change by the inclusion physical property such as size and stiffness was investigated.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.294-312
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• 2010

Data Technology (DT) is a new technology which deals with data collection, data analysis, information generation from data, knowledge generation from modelling and future prediction. DT is a newly emerged interdisciplinary science & technology in this 21st century knowledge society. Even though the main body of DT is applied statistics, it also contains management information system (MIS), quality management, process system analysis and so on. Therefore, it is an interdisciplinary science and technology of statistics, management science, industrial engineering, computer science and social science. In this paper, first of all, the definition of DT is given, and then the effects and the basic properties of DT, the differences between IT and DT, the 6 step process for DT application, and a DT example are provided. Finally, the relationship among DT, e-Statistics and Data Mining is explained, and the direction of DT development is proposed.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.04a
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• pp.117-120
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• 2009

The rolling of flat slabs or sheet metal is probably the most advanced technique of metalworking technology. In spite of this very intensive activity, the problem if edge cracking has not been resolved. Although edge cracking is a major industrial problem, relatively little well-documented experimental work has been published on subject. Despite the paucity of exact experiments, it is reasonably certain from published data that three causes contribute to its occurrence; (1) limited ductility of the rolled material (2) uneven deformation at the edges and (3) variations in stresses along the width of the rolled material, particular near the edge. The present study was carried out to show the generation of edge cracking using ductile fracture criteria and FE-simulation. The validity of simulated results was verified by rolling experiments of steel strip.

• New & Renewable Energy
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• v.10 no.2
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.4
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• pp.265-272
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• 2011

The electrical load profiles of end-users must be analysed properly to introduce distributed generation system efficiently. In this study, numerical simulation for predicting a residential electrical load profile was developed to satisfy categorized electricity consumption range. We applied bottom-up approach to compose electrical load profile by using data from official reports and statistics. The electrical load profile produced from the simulation predicted peak times of public report accurately and agreed well with the standard residential electrical load profile of official reports within average error of 16.2%.