• 유체기계공업학회:학술대회논문집
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• 1998.12a
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• pp.97-104
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• 1998

The objective of this study is to understand the generation mechanism of sound and to develop a prediction method for the unsteady flow field and the acoustic pressure field of a centrifugal fan. Lowson's method is used to predict the acoustic pressure in a free field. A DVM(discrete vortex method) is used to model the centrifugal fan and to calculate the flow field. In order to compare the experimental data, a centrifugal fan and wedge introduced by Weidemann are used in the numerical calculation and the results are compared with the experimental data.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.695-700
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• 2001

The objective of this study is to evaluate the flexure strength of steel fiber reinforced concrete beams and the effect of the adding steel fiber to flexural strength, and is to compare the proposed equation with the previous equation for predicting the flexural strength of fiber reinforced concrete beams. Based on earlier published studies and tests, predictive equation is proposed for evaluating the flexural strength of steel fiber reinforced concrete beams. The proposed equation gave good prediction for the flexural strength of the tested beams.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.357.2-357
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• 2002

The blast vibration can generate occupants dissatisfy as well as damage of physics nearby building. Then blast vibration estimation issue important problems. But, now blast vibration prediction inside-outside country not established objective method according to blast number to express magnitude of vibration. In this study, Our propoes show our country problem of blast vibration about blast vibration measurement and this problems be able to find improve method. (omitted)

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.240-245
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• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.348-357
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• 2006

Ground Vibration Tests (GVT) are needed on au new aircraft types and as part of certification. Its first objective is to verify models used for the calculation and prediction of the dynamic behavior of the structure. The main objectives of this paper are to introduce 'the integrated approach of dynamic testing for aerospace structure' in detail and 'The research projects in which LMS participated in aerospace structural dynamic area'

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.299-306
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• 2000

General definition of data mining is the knowledge discovery or is to extract hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important work is to find association rules in data mining. The objective of this paper is to find customer's trend using association rule from analysis of database and the result can be used as fundamental data for CRM(Customer Relationship Management). This paper uses Apriori algorithm and FoodMart data in order to find association rules.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.11
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• pp.1038-1047
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• 2000

The objective of this study is to develop an optimized Artificial Neural Network(ANN) model to predict the descending time of room air temperature. For this, program for predicting room air temperature and ANN program using generalized delta rule were collected through simulation for predicting room air temperature. ANN was trained and the ANN model having the optimized values-learning rate, moment, bias, number of hidden layer, and number of neuron of hidden layer was presented.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.361-368
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• 1998

This paper sums up the study of the soundproof facilities to be placed on the test track section within the Seoul-Pusan H.S.T project. The objective of this study is to determine optimum design of soundproof including height, length, location, sound absorbing materials for test track(chonan-taejon). This paper shows the model to design the shape and materials of noise barrier for high speed trains(TGV, ICE, etc). Noise prediction is to be conducted by MITHRA. Various parameters affecting the noise propagation outdoors are surveyed and discussed in relation to H.S.T. noise.

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.511-544
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• 2016

Standards boost technological innovation by promoting information sharing, compatibility, stability and quality. Identifying groups of companies that particularly benefit from these functions of standards in their technological innovation and commercialization helps to customize planning and implementation of standards-related policies for demand groups. For this purpose, this study engages in profiling of SMEs whose R&D objective is to respond to standards as well as those who need to implement standards system for technological commercialization. Then it suggests a prediction model that can distinguish such companies from others. To this end, decision tree analysis is conducted for profiling of characteristics of subject SMEs through data mining. Subject SMEs include (1) those that engage in R&D to respond to standards (Group1) or (2) those in need of product standard or technological certification policies for commercialization purposes (Group 2). Then the study proposes a prediction model that can distinguish Groups 1 and 2 from others based on several variables by adopting discriminant analysis. The practicality of discriminant formula is statistically verified. The study suggests that Group 1 companies are distinguished in variables such as time spent on R&D planning, KoreanStandardIndustryClassification (KSIC) category, number of employees and novelty of technologies. Profiling result of Group 2 companies suggests that they are differentiated in variables such as KSIC category, major clients of the companies, time spent on R&D and ability to test and verify their technologies. The prediction model proposed herein is designed based on the outcomes of profiling and discriminant analysis. Its purpose is to serve in the planning or implementation processes of standards-related policies through providing objective information on companies in need of relevant support and thereby to enhance overall success rate of standards-related projects.

• The korean journal of orthodontics
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• v.37 no.1 s.120
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• pp.16-28
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• 2007

Objective: Evaluation of individual growth is important in orthodontics. The aim of this study was to develop a convenient software that can evaluate current growth status and predict further growth. Methods: Stature data of 2 to 20 year-old Koreans (4893 boys and 4987 girls) were extracted from a nationwide data. Age-sex-specific continuous functions describing percentile growth curves were constructed using natural cubic spline function (NCSF). Then, final stature prediction algorithm was developed and its validity was tested using longitudinal series of stature measurements on randomly selected 200 samples. Various accuracy measurements and analyses of errors between observed and predicted stature using NCSF growth curves were performed. Results: NCSF growth curves were shown to be excellent models in describing reference percentile stature growth curie over age. The prediction accuracy compared favorably with previous prediction models, even more accurate. The current prediction models gave more accurate results in girls than boys. Although the prediction accuracy was high, the error pattern of the validation data showed that in most cases, there were a lot of residuals with the same sign, suggestive of autocorrelation among them. Conclusion: More sophisticated growth prediction algorithm is warranted to enhance a more appropriate goodness of model fit for individual growth.