• 품질경영학회지
• /
• 제48권2호
• /
• pp.297-307
• /
• 2020

Purpose: The purpose of this study is to analyze the factors that affect ammunition performance by applying data mining techniques to the Ammunition Stockpile Reliability Program (ASRP) data of the 155mm propelling charge. Methods: The ASRP data from 1999 to 2017 have been utilized. Logistic regression and decision tree analysis were used to investigate the factors that affect performance of ammunition. The performance evaluation of each model was conducted through comparison with an artificial neural networks(ANN) model. Results: The results of this study are as follows; logistic regression and the decision tree analysis showed that major defect rate of visual inspection is the most significant factor. Also, muzzle velocity by base charge and muzzle velocity by increment charge are also among the significant factors affecting the performance of 155mm propelling charge. To validate the logistic regression and decision tree models, their classification accuracies have been compared with the results of an ANN model. The results indicate that the logistic regression and decision tree models show sufficient performance which conforms the validity of the models. Conclusion: The main contribution of this paper is that, to our best knowledge, it is the first attempt at identifying the significant factors of ASPR data by using data mining techniques. The approaches suggested in the paper could also be extended to other types ammunition data.

• 한국의류학회지
• /
• 제40권5호
• /
• pp.894-909
• /
• 2016

This study analyzed a somatotype that was more suitable to a virtual fitting model and to improve the reality of a virtual model size. We analyzed 1,868 women 18-59 years old from the 6th Size Korea data. First, factor analysis was done for abstracting new criteria for dividing the somatotype; subsequently, we selected the waist height proportion to stature (body proportion) and drop (torso shape). Next, the cluster analysis was done with these criteria and 7 body proportion types and 11 torso shapes were distinguished. A virtual model size for the most common somatotype was also developed by a regression analysis of constituting sizes of each factor that was compared with body sizes well as with Clo's virtual model size. The model of this research showed a high similarity in sizes with body as well as improved better realisty than the Clo model which presented size problems such as longer limbs, bigger bust, smaller waist and a smaller arm circumference than the real body.

• 한국의류학회지
• /
• 제41권6호
• /
• pp.1109-1123
• /
• 2017

This study analyzed a somatotype of teenager's that was suitable to improve the reality of a virtual model size. We analyzed 843 teenagers 12-18 years old from the 6th Size Korea data. First, factor analysis was done for abstracting new criteria and dividing the somatotype; subsequently, we selected the waist height proportion to stature (body proportion) and drop (torso shape). Next, the cluster analysis was done with these criteria; subsequently, 5 body proportion types and 7 torso shapes were distinguished. A virtual model size for 4 somatotype with more than 50 persons was also designed by a regression analysis that constituted sizes for each factor. The designed model size was compared with body size as well as with Clo's virtual model size. The research model showed a high similarity in sizes with body as well as improved reality over the Clo model that presented size problems such as low waist height, bigger bust, and smaller thigh circumference than the real body.

• Journal of Preventive Veterinary Medicine
• /
• 제42권4호
• /
• pp.143-147
• /
• 2018

The present study aimed to develop growth prediction models of Listeria monocytogenes in processed meat products, such as mixed pressed hams, to perform accurate microbial risk assessments. Considering cold storage temperatures and the amount of time in the stages of consumption after opening, the growth of L. monocytogenes was determined as a function of temperature at 0, 5, 10, and $15^{\circ}C$, and time at 0, 1, 3, 6, 8, 10, 15, 20, 25, and 30 days. Based on the results of these measurements, a Baranyi model using the primary model was developed. The input parameters of the Baranyi equation in the variable temperature for polynomial regression as a secondary model were developed: $SGR=0.1715+0.0199T+0.0012T^2$, $LT=5.5730-0.3215T+0.0051T^2$ with $R^2$ values 0.9972 and 0.9772, respectively. The RMSE (Root mean squared error), $B_f$ (bias factor), and $A_f$ (accuracy factor) on the growth prediction model were determined to be 0.30, 0.72, and 1.50 in SGR (specific growth rate), and 0.10, 0.84, and 1.35 in LT (lag time), respectively. Therefore, the model developed in this study can be used to determine microorganism growth in the stages of consumption of mixed pressed hams and has potential in microbial risk assessments (MRAs).

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
• /
• pp.116-118
• /
• 2003

This paper describes a Accelerated Life Test (ALT) with the electrical contact erosion suitable to the evaluations of high-reliability and durability devices such as magnetic contactor. Recently, an electrical devices company was interested in accelerated life test (ALT), the product liability (PL) and the short-term testing model of electrical life test (ELT). In order to estimate a model for testing fee and period, need to the statistical analysis method with the acceleration factor(AF). Usually customer/manufacturer regard their device failure to the over-current or heavy duty condition, while devices view shape of contact erosion owing to operational duty problem. In this paper, additional method of evaluation estimated the operated cycles by weight of contact erosion with a used of regression analysis by MINITAB.

• 시스템엔지니어링학술지
• /
• 제7권2호
• /
• pp.21-30
• /
• 2011

The contractor management for the effective defense project is essential factor in the modern defense acquisition project. The occurrence of Improper Businessman causes the reason in which defense acquisition project is unable to be reasonably fulfilled and setback to the deployment of defense weapon system. In this paper, we develop a prediction model for the effective defense project by using the Discriminant Analysis, the Logistic Regression & Artificial Neural Network and analyse the core variables that determine the Improper Businessman in many variables. It is expected that our model can be used to improve the project management capability of defense acquisition and contribute to the establishment of efficient procurement procedure through entry of the reliable domestic manufacturer.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
• /
• pp.239-242
• /
• 2006

Impervious surface is an important index for the estimation of urbanization and environmental change. In addition, impervious surface has an influence on the parameters of rainfall-runoff model during rainy season. The increase of impervious surface causes peak discharge increasing and fast concentration time in urban area. Accordingly, impervious surface estimation is an important factor of urban rainfall-runoff model development and calibration. In this study, impervious surface estimation is performed by using remote sensing images such as landsat-7 ETM+ and high resolution satellite image and regression tree algorithm based on case study area ? Jungnang-cheon basin in Korea.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2001년도 추계학술대회 논문집
• /
• pp.475-480
• /
• 2001

In this study, a empirical equation which can be feasibly used to evaluate minimal track buckling strength without exact numerical analysis is presented. Parameter studies we carried out to investigate the effects of the individual factor on buckling strength. In order to simulate track buckling in the field as precisely as possible, a rigorous buckling model which accounts for all the important parameters is adopted. A empirical equation for prediction of minimal track buckling strength is derived by taking nonlinear regression of data which are obtained from numerical analyses. Its characteristics and applicability are investigated by comparing the results by the presented equation with the one by the equation which was presented in japan, and is frequently using in korea when designing track structure.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 추계학술대회 논문집 전력기술부문
• /
• pp.187-189
• /
• 2004

This paper investigates the effect of weather factors(such as winds, rain, snows, temperature, clouds and humidity) on transmission line outages. The result shows that weather variables have significant effects on the transmission line historical outages and the relationship between them is nonlinear. Multiple regression analysis using Logit model is proved to be appropriate in forecasting line failure rate in KEPCO systems. It could also provide system operators with useful informations about system operation and planing.

• Communications for Statistical Applications and Methods
• /
• 제22권5호
• /
• pp.415-434
• /
• 2015

In this paper we overview the literature on common features analysis of economic time series. Starting from the seminal contributions by Engle and Kozicki (1993) and Vahid and Engle (1993), we present and discuss the various notions that have been proposed to detect and model common cyclical features in macroeconometrics. In particular, we analyze in details the link between common cyclical features and the reduced-rank regression model. We also illustrate similarities and differences between the common features methodology and other popular types of multivariate time series modelling. Finally, we discuss some recent developments in this area, such as the implications of common features for univariate time series models and the analysis of common autocorrelation in medium-large dimensional systems.