• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.29-45
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• 2002

In this study, we consider infinite supply of raw materials and backlogged demands as given two boundary conditions. And we need not make any specific assumptions about the inter-arrival of external demand and service time distributions. We propose a numeric model and an algorithm in order to compute the first two moments of inter-departure process. Entropy enables us to examine the convergence of this process and to derive measurable relations of this process. Also, lower bound on the variance of inter-departure process plays an important role in proving the existence and uniqueness of an optimal solution for a numeric model and deriving the convergence order of augmented Lagrange multipliers method applied to a numeric model. Through these works, we confirm some structural properties and numeric examples how the validity and applicability of our study.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.305-310
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• 1998

This research conducted concerning measures for the influence reduction to an investigation in the structure of offshore breakwater maintenance, an evaluation, a reexamination of the forecast, and a peripheral sediment transport environment. Furthermore, it aimed at the establishment of the beach transformation forecast method based on a hydraulic model study and a numeric simulation. A good result was obtained from a hydraulic model experiment and a numeric simulation as part of the basic research. And a qualitative evaluation of the flow field around the structure became possible since a numeric simulation examined flow field characteristics.

• ETRI Journal
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• v.43 no.1
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• pp.95-108
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• 2021

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.185-207
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• 1998

This research investigates computer generated hybrid second-order model of two numerically based approaches to risk classification : discriminant analysis and neural networks. The hybrid second-order models are derived by rule induction using the ID3 and tested in the several different kinds of data. This new hybrid approach is designed to combine the high prediction accuracy and robustness of DA or NN with perspicuity of ID3. The hybrid model also eliminates the problem of contradictory inputs of ID3. After doing empirical test for the validity of hybrid model using small and medium companies' bankrupt data, hybrid model shows high perspicuity, high prediction accuracy for bankrupt, and simplicity for rules. The hybrid model also shows high performance regardless the type of data such as numeric data, non-numeric data, and combined data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.99-107
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• 2009

This paper presents an enhanced hybrid model based on Independent Component Analysis(ICA) in order to features of numeric characters in license plates. ICA which is used only in high dimensional statistical features doesn't consider statistical features in low dimension and correlation between numeric characters. To overcome the drawbacks of ICA, we propose an improved ICA with the hybrid model using both Principle Component Analysis(PCA) and Linear Discriminant Analysis(LDA). Experiment results show that the proposed model has a superior performance in feature extraction and recognition compared with ICA only as well as other hybrid models.

• Earthquakes and Structures
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• v.10 no.4
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• pp.811-828
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• 2016

This study aims to present nonlinear time history analysis results of double leaf cavity wall (DLCW) reinforced concrete structure exposed to shake table tests. Simulation of the model was done by a Finite Element (FE) program. Shake table experiment was performed at the National Civil Engineering Laboratory in Lisbon, Portugal. The results of the experiment were compared with numeric DLCW model and numeric model of reinforced concrete structure with unreinforced masonry wall (URM). Both DLCW and URM models have two bays and two stories. Dimensions of the tested structure and finite element models are 1:1.5 scaled according to Cauchy Froude similitude law. The URM model has no experimental results but the purpose is to compare their performance level with the DLCW model. Results of the analysis were compared with experimental response and were evaluated according to ASCE/SEI 41-06 code.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.122-130
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• 2009

The analysis of human movement requires the knowledge of the Hill type muscle parameters, the muscle-tendon and moment arm length change as a function of joint angles. However, values of a subject's muscle parameters are very difficult to identify. It turns out from a sensitivity analysis that the tendon slack length and maximum muscle force are the two critical parameters among the Hill-type muscle model. Therefore, it could be claimed that the variation of the tendon slack length and maximum muscle force from the Delp's reference data will change the muscle characteristics of a subject remarkably. A numeric optimization method to search these tendon parameters specific to a subject is proposed, and the accuracy of the developed algorithm is evaluated through a numerical simulation.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.272-277
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• 2005

We introduce a new approach to optimize the parameters in biological kinetic models by quantifier elimination (QE), in combination with numerical simulation methods. The optimization method was applied to a model for the inhibition kinetics of HIV proteinase with ten parameters and nine variables, and attained the goodness of fit to 300 points of observed data with the same magnitude as that obtained by the previous optimization methods, remarkably by using only one or two points of data. Furthermore, the utilization of QE demonstrated the feasibility of the present method for elucidating the behavior of the parameters in the analyzed model. The present symbolic-numeric method is therefore a powerful approach to reveal the fundamental mechanisms of kinetic models, in addition to being a computational engine.

• Journal of Environmental Science International
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• v.18 no.8
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• pp.847-855
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• 2009

As a part of effort to establish an offshore wind resource assessment system of the Korean Peninsula, a numeric wind simulation using mesoscale climate model MM5 and a spatial distribution of offshore wind extracted from SAR remote-sensing satellite image is compared and analyzed. According to the analyzed results, the numeric wind simulation is found to have wind speed over predication tendency at the coastal sea area. Therefore, it is determined that a high-resolution wind simulation is required for complicated coastal landforms. The two methods are verified as useful ways to identify the spatial distribution of offshore wind by mutual complementation and if the meteor-statistical comparative analysis is performed in the future using adequate number of satellite images, it is expected to derive a general methodology enabling systematic validation and correction of the numeric wind simulation.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.212-220
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• 2009

In many studies, the Numeric Integration (NI) method has been widely used to calculate pollutant loads from the watershed because it is easy to apply. However, there have been many needs for more accurate pollutant loads estimation method with the restricted number of water quality samples. However, the ESTIMATOR model does not allow the users to define the regression model to explain the measured flow and water quality relationship, indicating the ESTIMATOR model is not flexible. The LOADEST model allows the user to choose the model type from 11 predefined general forms of regression equations. Annual loads of T-N and T-P with the LOADEST model were 0.70 times and 0.84 times of those by NI method, respectively. The coefficient of determination ($R^2$) of the LOADEST regression for the T-N and T-P were 0.92 and 0.72, respectively. This indicates that the load estimation regression model with the LOADEST for the study watershed explains the relationship between the observed flow and water quality data well reasonably well. Based on these findings, we suggest that the LOADEST model estimated regression equation could be used to estimate pollutant loads using the measured flow data for the study watershed.