• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.10
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• pp.2637-2646
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• 1995

Combustion instability in solid-propellant rocket motors depends on the balance between acoustic energy gains and losses of the system. The objective of this paper is to demonstrate the capability of the program which predicts the standard longitudinal stability using acoustic modes based on linear stability analysis and T-burner test results of propellants. Commercial ANSYS 5.0A program can be used to calculate the acoustic characteristic of a rocket motor. The linear stability prediction was compared with the static firing test results of rocket motors.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.10a
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• pp.111-118
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• 1997

Generally, H-section is used for columns and beams in the middle and low building steel structure, But it has a axis and a weak axis. Thus if H-section is used for columns, the structure needs reinforcement on the weak axis. Therefore recently, square hollow section(S.H.S) is used for columns because it is able to cover the vulnerability of H-section. Structural analysis is usually executed under the assumption that connections are either ideally pinned joint or fully joint. Actually all connections are semi-rigid which possess a rotational stiffness. Therefore it can be designed economically as using the property of connections which has a rotational stiffness. This paper presents a prediction model curve which is fitted with Kishi-Chen Power Model about the behavior of connection between H-beam and S.H.S column in the previous experimental paper. It also suggests the new analysis algorithm considering the non-linear of semi-rigid connection and the geometrical non-linear under the effect of axial force.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.3
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• pp.106-113
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• 2009

Various statistical classification methods have been used to establish prediction model of underground cultural assets in our country. Among them, linear discriminant analysis, logistic regression, decision tree, neural network, and support vector machines are used in this paper. We introduced the basic concepts of above-mentioned classification methods and applied these to the analyses of real data of I city. As a results, five different prediction models are suggested. And also model comparisons are executed by suggesting correct classification rates of the fitted models. To see the applicability of the suggested models for a new data set, simulations are carried out. R packages and programs are used in real data analyses and simulations. Especially, the detailed executing processes by R are provided for the other analyser of related area.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.209-217
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• 1993

The multicollinearity problem in a multiple linear regression model may present deleterious effects on predictions. Thus, its is desirable to consider the optimal fractions with respect to the unbiased estimate of the mean squares errors of the predicted values. Interstingly, the optimal fractions can be also illuminated by the Bayesian inerpretation of the general James-Stein estimators.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1126-1130
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• 2010

Speech production can be viewed as a filtering operation in which a sound source excites a vocal tract filter. The vocal tract is modeled as a chain of cylinders of varying cross-sectional area in linear prediction acoustic tube modeling. In this modeling the most common implementation assumes equal length of tube sections. Therefore, to model complex vocal tract shapes, a large number of tube sections are needed. This paper proposes a new vocal tract model with unfixed sectionlengths, which uses the reduced lattice filter for modeling the vocal tract. This model transforms the lattice filter to reduced structure and the Burg algorithm to modified version. When the conventional and the proposed models are implemented with the same order of linear prediction analysis, the proposed model can produce more accurate results than the conventional one. To implement a system within similar accuracy level, it may be possible to reduce the stages of the lattice filter structure. The proposed model produces the more similar vocal tract shape than the conventional one.

• Membrane and Water Treatment
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• v.1 no.3
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• pp.181-192
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• 2010

A linear quantitative structure-property relationship (QSPR) model is presented for the prediction of rejection in permeation through membrane. The model was produced by using the multiple linear regression (MLR) technique on the database consisting of retention data of 25 pesticides in 4 different membrane separation experiments. Among the 3224 different physicochemical, topological and structural descriptors that were considered as inputs to the model only 50 were selected using several criteria of elimination. The physical meaning of chosen descriptor is discussed in detail. The accuracy of the proposed MLR models is illustrated using the following evaluation techniques: leave-one-out cross validation procedure, leave-many-out cross validation procedure and Y-randomization.

• Progress in Medical Physics
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• v.34 no.3
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• pp.23-32
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• 2023

Purpose: In radiomics analysis, to evaluate features, and predict genetic characteristics and survival time, the pixel values of lesions depicted in computed tomography (CT) and magnetic resonance imaging (MRI) images are used. CT and MRI offer three-dimensional images, thus producing three-dimensional features (Features_3d) as output. However, in reports, the superiority between Features_3d and two-dimensional features (Features_2d) is distinct. In this study, we aimed to investigate whether a difference exists in the prediction accuracy of radiomics analysis of lung cancer using Features_2d and Features_3d. Methods: A total of 38 cases of large cell carcinoma (LCC) and 40 cases of squamous cell carcinoma (SCC) were selected for this study. Two- and three-dimensional lesion segmentations were performed. A total of 774 features were obtained. Using least absolute shrinkage and selection operator regression, seven Features_2d and six Features_3d were obtained. Results: Linear discriminant analysis revealed that the sensitivities of Features_2d and Features_3d to LCC were 86.8% and 89.5%, respectively. The coefficients of determination through multiple regression analysis and the areas under the receiver operating characteristic curve (AUC) were 0.68 and 0.70 and 0.93 and 0.94, respectively. The P-value of the estimated AUC was 0.87. Conclusions: No difference was found in the prediction accuracy for LCC and SCC between Features_2d and Features_3d.

• Journal of Navigation and Port Research
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• v.27 no.5
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• pp.487-492
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• 2003

The paper describes on the implementation of marine casualty prediction model that is one of the main part of Korean MArine Casualty FOrecasting System (K-MACFOS). In this work, Cell Distributed Linear-In-the-Parameter (CD-LIP) model is proposed and discussed its usability with comparing Baltic model and revised LIP model. As evaluation results by regression analysis of variance, it is known that the CD-LIP model gives best performance to the marine casualty numerical D/B of the target sea area.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.60-65
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• 2003

The paper describes on the implementation of marine casualty prediction model that is one of the main part of Marine Casualty Forecasting System (MCFS). In this work, Cell Distributed Linear-In-the Parameter (CD-LIP) model is developed and compared with Baltic model using regression analysis of variance. As comparing, it is known that the proposed CD-LIP model has less residual than the Baltic model and, it gives best performance to the marine casualty numeric D/B of target area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.701-704
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• 2014

This Paper proposed the analysis and prediction method of beverage sales. We assumed weather had a relationship with beverage sales. We got the output as sales amount from a temperature and humidity of weather as input by using polynomial equation. We had modelling as quadric function with input and output data. In order to verify the effectiveness of proposed method, the sales data were collected over a 4 months during February 2014. The results showed that the proposed method can estimate sales data.