• International conference on construction engineering and project management
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• 2005.10a
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• pp.791-795
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• 2005

A simulation model is proposed to evaluate the effect of correlations between activity durations on the overall project duration. The proposed model incorporates NORTA, a recent developed statistical method, into the simulation process to allow arbitrarily specified marginal distributions for activity durations and any desired correlation structure. The generality is of practical value when systematic data is not available and planners have to rely on arbitrary experts' estimation, which may involve a mixed situation when some activity durations are continuously distributed whereas others are discrete outcomes. The proposed model is validated by showing that the correlation coefficients of the simulation results are close to the originally specified ones. The simulation results are compared to two conventional approaches: PERT and simulation without correlation. The comparisons illustrate that the proposed model can provide important management information, which would otherwise be distorted due to the neglect of the correlations between activity durations.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.101-104
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• 2008

In this study, rainfall adjust and forecasting using artificial neural network(ANN) which includes a correlation coefficient is application in Seoul region. It analyzed one-hour rainfall data which has been reported in 25 region in seoul during from 2000 to 2006 at rainfall observatory by AWS. The ANN learning algorithm apply for input data that each region using cross-correlation will use the highest correlation coefficient region. In addition, rainfall adjust analyzed the minimum error based on correlation coefficient and determination coefficient related to the input region. ANN model used back-propagation algorithm for learning algorithm. In case of the back-propagation algorithm, many attempts and efforts are required to find the optimum neural network structure as applied model. This is calculated similar to the observed rainfall that the correlation coefficient was 0.98 in missing rainfall adjust at 10 region. As a result, ANN model has been for suitable for rainfall adjust. It is considered that the result will be more accurate when it includes climate data affecting rainfall.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.459-466
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• 1999

I broadband ISDN every packet will show different result if it would be processed according to its usage by the server. That is, normal data won't show big differences if they would be processed at normal speed. But it will improve the quality of service to process some kinds of data - for example real time video or voice type data or some data for a bid to by something through the internet - more fast than the normal type data. solution for this problem was suggested - priority packets. But the analyses of them are under way. Son in this paper a switching system for an output queuing model in a single server was assumed and some packets were given priorities and analysed. And correlation, simulating real life situation, was given too. These packets were analysed through three cases, first packets having no correlation, second packets having only correlation and finally packets having priority three cases, first packets having no correlation, second packets having only correlation and finally packets having priority and correlation. The result showed that correlation doesn't affect the mean delay time and the high priority packets have improved mean delay time regardless of the arrival rate. Those packets were assumed to be fixed-sized like ATM fixed-sized cell and the contention strategy was assumed to be short bus contention method for the output queue, and the mean delay length and the maximum 버퍼 length not to lose any packets were analysed.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.645-654
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• 2004

In this paper, we develop the Bayesian test procedure for the intraclass correlation coefficient in the unbalanced one-way random effect model based on the reference priors. That is, the objective is to compare two nested model such as the independent and intraclass models using the factional Bayes factor. Thus the model comparison problem in this case amounts to testing the hypotheses $H_1:\rho=0$ versus $H_2:{\rho}{\neq}0$. Some real data examples are provided.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.230-235
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• 2011

COMS (Communication, Ocean and Meteorological Satellite) is a geostationary satellite and was developed by KARI for communication, ocean and meteorological observations. COMS was tested under vacuum and very law temperature conditions in order to correlate thermal model and to verify thermal design. The test was performed by using KARI large thermal vacuum chamber. The COMS S/C thermal model was successfully correlated versus the 2 thermal balance test phases. After model correlation, temperatures deviation of all individual unit were less than $5^{\circ}C$ and global deviation and standard deviation also satisfied the requirements, less than $2^{\circ}C$ and $3^{\circ}C$. The final flight prediction was performed by using the correlated thermal model.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.220-227
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• 2002

This paper describes an integrated approach process to carry out pre-test, model correlation and updating analysis on the sub-frame of a vehicle. In this study, it was found that the modal test could be more efficient when the exciting point was selected on the area with high driving point residue. Such area could be located with the aid of finite element modal analysis. The model correlation was appraised in conjunction with the modal parameters between modal test and finite elements analysis. Also, the finite element model updating was obtained the good resultant using the iteration method based on sensitivity analysis results that carried out the variation of natural frequencies and MAC for the material properties. Finally, optimization of vehicle subframe was carried out the analysis of core location and physical properties by tow steps.

• Journal of computational fluids engineering
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• v.16 no.3
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• pp.59-65
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• 2011

COMS (Communication, Ocean and Meteorological Satellite) is a geostationary satellite and was developed by KARI for communication, ocean and meteorological observations. COMS was tested under vacuum and very low temperature conditions in order to correlate thermal model and to verify thermal design. The test was performed by using KARI large thermal vacuum chamber. The COMS S/C thermal model was successfully correlated versus the 2 thermal balance test phases. After model correlation, temperatures deviation of all individual units were less than $5^{\circ}C$ and global deviation and standard deviation also satisfied the requirements, less than $2^{\circ}C$ and $3^{\circ}C$. The final flight prediction was performed by using the correlated thermal model.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.26-32
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• 2020

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2
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• pp.92-101
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• 2008

To dissolve the multi-layered model problems, and to complement 2-layered model's simplicity, assumed fluid-fluid-solid 3-layered model. Generally it is known that if the sediment thickness is more than 10 wavelength, the half space's influence to the in-water acoustic field could be disregarded. By tracking the maximum correlation coefficient of calculated results and experimental ones we confirmed that the requirement could be more realized. To calculate the maximum correlation coefficient we used single sensor transmission loss. On the assumption that the sediment sound velocity was 1813 m/s and frequency range 50 kHz to 120 kHz, the conversion condition was from 2.5 to 7.7 wavelength.

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.