• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.67-73
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• 2014

We consider the mean value function for NHPP software reliability model and time series regression model in software failure data. We estimate parameters for the proposed models from two data sets. The values of SSE and MSE is presented from two data sets. We compare the predicted number of faults with the actual two data sets using the mean value function and regression curve.

• Convergence Security Journal
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• v.12 no.3
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• pp.115-121
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• 2012

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

• Journal of Power System Engineering
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• v.19 no.2
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• pp.70-77
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• 2015

Nowadays, car manufacturers applied many high strength steels such AHSS or UHSS to car bodies for weight lightening. Therefore, a variety of applied steel sheet to car bodies increased and the needs of simulation to evaluate weldability also increased in order to reduce the cost and time. In this study, resistance spot welding simulations for DP 780 Steel with 1.0 and 1.4 mm thickness were conducted with respect to lobe curve. 2 regression models to estimate tensile shear strength were suggested and they were second order polynomial regression model and optimized second order regression model. The performance of these models was evaluated in terms of the coefficient of determinant and average error rate.

• Animal Bioscience
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• v.37 no.5
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• pp.839-851
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• 2024

Objective: The main goal of our current study was to improve the growth curve of meat animals by decreasing the birth weight while achieving a finishing weight that is the same as that before selection but at younger age. Methods: Random regression model was developed to derive various selection indices to achieve desired gains in body weight at target time points throughout the fattening process. We considered absolute and proportional gains at specific ages (in weeks) and for various stages (i.e., early, middle, late) during the fattening process. Results: The point gain index was particularly easy to use because breeders can assign a specific age (in weeks) as a time point and model either the actual weight gain desired or a scaled percentage gain in body weight. Conclusion: The point gain index we developed can achieve the desired weight gain at any given postnatal week of the growing process and is an easy-to-use and practical option for improving the growth curve.

• Korean Journal of Food Science and Technology
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• v.29 no.2
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• pp.273-278
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• 1997

In order to investigate the punch properties of some vegetables-cucumber, radish, garlic, ginger and potato-force, distance, and time were measured with a texturometer, and the correlations between compositions and cell characteristics of samples were characterized. Many reflection and rupture points on the force-distance and distance-time curve were observed, and these points appeared when the cells of sample were resisted and yielded against the applied force. They were big and clear at the slow crosshead speed. The regression analysis for force-time and distance-time to the rupture point showed $R^{2}>0.95$. The rupture time and rupure force were 5.63 sec, 4.88 N in ginger and 4.15 sec, 2.00 N in cucumber. The rupture forces become large values at the fast crosshead speed. As cell sizes were increased, the moisture content and rupture distance were increased, while the viscosity of juice, density, regularity of cell, and slope of force-time were decreased. Rupture force, time and distance were decreased at the large specific gravity of samples. The slopes of distance-time curve were inversely proportional to slope of force-time curve.

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.103-122
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• 1992

The objective of this research is to develop a traffic accident forecasting model using traffic accident data in pusan from 1963 to 1991 and then to make short-term forecasts('93~'94) of traffic accidents in pusan. In this research, several forecasting models are developed. They include a multiple regression model, a time-series ARIMA model, a Logistic curve model, and a Gompertz curve model. Among them, the model which shows the most significance in forecasting accuracy is selected as the traffic accident forecasting model. The results of this research are as followings. 1. The existing model such as Smeed model which was developed for foreign countries shows only 47.8% explanation for traffic accident deaths in Korea. 2. A nonliner regression model ($R^2$=0.9432) and a Logistic curve model are appeared to be th gest forecasting models for the number of traffic accidents, and a Logistic curve model shows th most significance in predicting the accident deaths and injuries. 3. The forecasting figures of the traffic accidents in pusan are as followings: . In 1993, 31, 180 accidents are predicted to happen, and 430 persons are predicted to be deaths and 29, 680 persons are predicated to be injuries. . In 1994, 33, 710 accidents are predicted to happen, and 431.persons are predicted to be deat! and 30, 510 persons are predicted to be injuried. Therefore, preventive measures against traffic accidents are certainly required.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.125-136
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• 2005

As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.89-112
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• 2016

In this paper, as a determining factor of the Environment Kuznets Curve hypothesis, we analyzed the impact of technological innovation. In this paper, in order to empirically validate the role of technological innovation to an inverted U-shaped Environments Kuznets Curve hypothesis, we utilize the 2SLS considering relationship between R&D and the GDP per capita. Also, using the Panel VAR (Panel Vector Auto Regression) model to analyze with what time lag R&D per capita has impact on the emissions of greenhouse gases per capita. Empirical results show that R&D per capita(proxy of innovation) is a important factor to explain Environmental Kuznets Curve hypothesis, and that the external shock such as R&D per capita reduces greenhouse gas emissions per capita with about 3 time lag.

• Journal of the Korean Institute of Gas
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• v.21 no.5
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• pp.77-82
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• 2017

Thus, chemicals are managed under 9 related central government department and 16 relevant laws with program such as Process Safety Management and Offsite Consequence Analysis in korea. Guidelines for set the endpoint concentration for chemcals based on the ERPG-2 (Emergency Response Planning Guidelines-2) and AEGL-2 (Acute Exposure Guidelines Level-2). but ERPG and AEGL do not describe exposure for less than 10 minutes. because of this, each guidelines define criteria differently for short time less than 10 minutes exposure. This indefinite exposure criteria would give rise to a confusion in the chemical plants, and potentially lead to a critical decision making error when accidents happen. In an effort to apply guidelines with evenly-distributed initial time frame, AEGL concentrations within 10 minute exposure time were evaluated by examining statistical regression curves. The results were in good agreement with those from the Probit Function based on each AEGL grade to explain 3 different threshold levels of exposure effects. Resultant re-enforced guidelines for endpoint chemical concentrations are, therefore, to provide powerful tool to assess and manage the risk associated with any potential chemical accidents at an early stage.

• Korean Journal of Hydrosciences
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• v.4
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• pp.11-19
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• 1993

The peak flood discharge at a downstream station and the flood travel time between a pair of dams due to a specific flood release from the upper reservoir are computed using a hydraulic river channel routing method. The study covered the whole large reservoir system in the Han River, Korea. The computed flood discharges and the travel times between dams were correlated with the duration and the magnitude of flood release rate at the upstream reservoir, and hence a multiple regression model is proposed for each river reach between a pair of dams. The peak flood discharge at a downstream location can be converted to the peak flood stage by a rating curve. Hence, the proposed regression model could be used to forecast the peak flood stage at a downstream location and the flood travel time between dams using the information on the flood travel time, release rate and duration from the upper dam.