• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1067-1069
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• 2003

The Earthquake Case Study and Disasters Information System based on GIS (MapECDIS 2002 for Windows), sponsored by Science and Technique Ministry of CHINA, is a GIS system developed to provide a tool for the government and the public to query and comprehend the disaster information (since 2221BC) and case study results (since 1966) of destructive earthquakes occurred in China. The system is expected to be useful for the earthquake forecast practice, the seismology research and earthquake disasters research as an applied assistant tool. The design idea and main functions of the system are introduced in the paper.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3612-3624
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• 2021

At present, in the case of pump fast optimization, there is a problem of rapid, accurate and effective prediction of cavitation performance. In "A Cavitation Performance Prediction Method for Pumps PART1-Proposal and Feasibility" [1], a new cavitation performance prediction method is proposed, and the feasibility of this method is demonstrated in combination with experiments of a mixed flow pump. However, whether this method is applicable to vane pumps with different specific speeds and whether the prediction results of this method are accurate is still worthy of further study. Combined with the experimental results, the research evaluates the sensitivity and accuracy at different flow rates. For a certain operating condition, the method has better sensitivity to different flow rates. This is suitable for multi-parameter multi-objective optimization of pump impeller. For the test mixed flow pump, the method is more accurate when the area ratios are 13.718% and 13.826%. The cavitation vortex flow is obtained through high-speed camera, and the correlation between cavitation flow structure and cavitation performance is established to provide more scientific support for cavitation performance prediction. The method is not only suitable for cavitation performance prediction of the mixed flow pump, but also can be expanded to cavitation performance prediction of blade type hydraulic machinery, which will solve the problem of rapid prediction of hydraulic machinery cavitation performance.

• Journal of KSNVE
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• v.7 no.4
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• pp.621-629
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• 1997

For computer aided design and costruction of low noisy power plants, indoor and outdoor noise prediction program has been developed. The program utilizes the predefined data of noise sources and building materials and has the faculty to estimate the source level using the empirical formula in case of the measured data not being available. In the noise prediction, the mutual noise propagation between indoor and outdoor sites are considered. The outdoor noise source in the calculation of geometric divergence effects is modelled as the omni-directional finite line or planar source according to the source geometry and the receiving points. Outdoor noise prediction is carried out to consider the diffraction effect due to plant structures as well as the attenuation effect due to atmospheric absorption and soft ground. The results of indoor and outdoor noise prediction for a recently constructed diesel engine power plant show good agreement with the measured.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1151-1160
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• 2006

The similarity weight, the pearson's correlation coefficient, which is used in the recommender system has a weak point that it cannot predict all of the prediction value. The similarity weight, the vector similarity, has a weak point of the high MAE although the prediction coverage using the vector similarity is higher than that using the pearson's correlation coefficient. The purpose of this study is to suggest how to raise the prediction coverage. Also, the MAE using the suggested method in this study was compared both with the MAE using the pearson's correlation coefficient and with the MAE using the vector similarity, so was the prediction coverage. As a result, it was found that the low of the MAE in the case of using the suggested method was higher than that using the pearson's correlation coefficient. However, it was also shown that it was lower than that using the vector similarity. In terms of the prediction coverage, when the suggested method was compared with two similarity weights as I mentioned above, it was found that its prediction coverage was higher than that pearson's correlation coefficient as well as vector similarity.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.3
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• pp.191-193
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• 2017

EFD-CFD Comparison Workshop was proposed based on the drag prediction workshop and high lift prediction workshop of AIAA. This workshop is organized to escalate the levels of wind tunnel test and computational fluid dynamics and to escalate the level of domestic aerodynamic technology through the collaboration of both areas. For three benchmark cases of which wind tunnel test results are available, comparison workshops have been held since 2015.

• ETRI Journal
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• v.44 no.2
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• pp.208-219
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• 2022

Crime amount prediction is crucial for optimizing the police patrols' arrangement in each region of a city. First, we analyzed spatiotemporal correlations of the crime data and the relationships between crime and related auxiliary data, including points-of-interest (POI), public service complaints, and demographics. Then, we proposed a crime amount prediction model based on 2D convolution and long short-term memory neural network (2DCONV-LSTM). The proposed model captures the spatiotemporal correlations in the crime data, and the crime-related auxiliary data are used to enhance the regional spatial features. Extensive experiments on real-world datasets are conducted. Results demonstrated that capturing both temporal and spatial correlations in crime data and using auxiliary data to extract regional spatial features improve the prediction performance. In the best case scenario, the proposed model reduces the prediction error by at least 17.8% and 8.2% compared with support vector regression (SVR) and LSTM, respectively. Moreover, excessive auxiliary data reduce model performance because of the presence of redundant information.

• Structural Engineering and Mechanics
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• v.16 no.6
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• pp.643-654
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• 2003

Two real-time modeling prediction (RMP) schemes are presented in this paper for analyzing the behavior of deep excavations during construction. The first RMP scheme is developed from the traditional AR(p) model. The second is based on the simplified Elman-style recurrent neural networks. An on-line learning algorithm is introduced to describe the dynamic behavior of deep excavations. As a case study, in-situ measurements of an excavation were recorded and the measured data were used to verify the reliability of the two schemes. They proved to be both effective and convenient for predicting the behavior of deep excavations during construction. It is shown through the case study that the RMP scheme based on the neural network is more accurate than that based on the traditional AR(p) model.

• Journal of ILASS-Korea
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• v.13 no.3
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• pp.117-125
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• 2008

The correlations for the prediction of maximum liquid-phase penetration in diesel spray are reviewed in this study. The existing models developed for the prediction of maximum liquid-phase penetration can be categorized as the zero-dimensional (empirical) model, the multi-dimensional model and the other model. The existing zero-dimensional model can be classified into four groups and the existing multidimensional models can be classified into three groups. The other model includes holistic hydraulic and spray model. The maximum liquid-phase penetration is mainly affected by nozzle diameter, fuel volatility, injection pressure, ambient gas pressure, ambient gas density and fuel temperature. In the case of empirical correlations incorporated with spray angle, the predicted results will be different according to the selection of correlation for spray angle. The research for the effect of boiling point temperatures on maximum liquid-phase penetration is required. In the case of multidimensional model, there exist problems of the grid and spray sub-models dependency effects.

• 유체기계공업학회:학술대회논문집
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• 1998.12a
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• pp.91-96
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• 1998

The broadband noise generated aerodynamically from a two-bladed axial flow fan has been measured and compared to the result of a self-noise prediction method. The prediction scheme is based on the experimental data set acquired from a series of aerodynamic and acoustic tests of two and three-dimensional airfoil blade sections. For low blade loading case the comparison showed a reasonably good agreement, but as the loading becomes larger the empirical formula overpredict the sound pressure level at high frequency range. This is probably due to the use of stationary wing data for the prediction of rotating blade case, which will be quite different in their vortex strength at the blade tip.

• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.111-118
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• 2007

What is CRM(Customer Relationship Management) means that planning, executing, and re-accessing the marketing strategy based on the customer character by analyzing the material related to customers. That is CRM is a strategy of customer service on the base of data. In the case of the telecommunications and a newspaper, there are restricted application of CRM, because they are provided services by paying a given amount of money within a given period of time. This paper develops CRM model(chum prediction model) that can apply to a newspaper. For model-building, real data were used which were collected from one of the major a newspaper company in Korea. Also, this paper verifies the efficient result.