• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.393-400
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• 2001

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.805-812
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• 2003

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.270-277
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• 1997

Plastic anisotropy is one of important factors which determine the drawability of a steel sheet. It has been mainly measured by mechanical tensile test. From the ultrasonic velocities propagating along the relative directions to the rolling direction, CODF(crystallite orientation distribution function) can be measured and ODC's(orientation distribution coefficients) has some correlations with the plastic anisotropy. In this study the correlations between the plastic anisotropy and ODC's of the cold rolled steel sheet were measured. From the results of ultrasonic velocity measurements the average normal anisotropy, $\bar{\gamma}$ and the average planar anisotropy, ${\Delta}r$ could be predicted within the accuracy of ${\pm}0.082$ and ${\pm}0.096$, respectively. Acoustic resonance method was applied to measure the ultrasonic velocities and EMAT's were used for generating and detecting the ultrasonic waves.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process(NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.49-59
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• 2022

The SHAPE algorithm has the advantage of being able to shape the pulse spectrum as desired and design it not to distort other characteristics, so it was used in the active sonar pulse design. In this paper, we propose a pulse design using the SHAPE algorithm for a multi-static sonar system to reduce the cross-correlation between frequency-adjacent pulses and prevent the performance degradation of the pulses themselves. The boundary function of the SHAPE algorithm is set to be limited to the pulse bandwidth. As a result of applying the proposed design method to the sinusoidal frequency modulated pulse, the peak cross-correlation level (PCCL), which means the degree of cross-correlation, was reduced by 44.23 dB. Although the PCCL decreased by several tens of dB, no significant change in the ambiguity function was observed, and the integrated sidelobe level (ISL), which means the average value of the side lobe, increased by 11.64 dB.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.641-648
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• 2022

In this study, the performance of the NHPP software reliability model with exponential distribution (Exponential Basic, Inverse Exponential, Lindley, Rayleigh) characteristics was comparatively analyzed, and based on this, the optimal reliability model was also presented. To analyze the software failure phenomenon, the failure time data collected during system operation was used, and the parameter estimation was solved by applying the maximum likelihood estimation method (MLE). Through various comparative analysis (mean square error analysis, true value predictive power analysis of average value function, strength function evaluation, and reliability evaluation applied with mission time), it was found that the Lindley model was an efficient model with the best performance. Through this study, the reliability performance of the distribution with the characteristic of the exponential form, which has no existing research case, was newly identified, and through this, basic design data that software developers could use in the initial stage can be presented.

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1169-1186
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• 2012

Storage function method has been used for flood forecasting in the major rivers in Korea, however, the researches on the relationship between the parameters and runoff characteristics was not sufficient. In addition, there has been a controversy about the optimized parameters without the consideration of the physical characteristics of the basin. Therefore, in this study, the SCE-UA method is used to optimize the parameters and the proposed method was applied with two stage optimization in the Jeongseon and Yeongwol watersheds located in the most upstream in the South Han river. The contour map was developed to investigate parameters and the error surface calculated from the runoff. The proposed parameters is to provide a range of the possible parameter set in a watershed, rather than a specific value. However, the applicability is examined using the average value of the proposed ranged parameters. In this study, the criticism about the optimization technique to find an optimal value having no physical meaning on a watershed is tried to avoid. The objective of this study is to provide a range of parameters for the flood forecasting model and the intuition about the behavior of the parameters, so the efficiency of flood forecasting is increased.

• Journal of Korean Ophthalmic Optics Society
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• v.13 no.3
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• pp.29-34
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• 2008

Purpose: In this study, we compared the physical properties of the compositions that were mixed with basic materials of HEMA (2-Hydroxyethyl methacrylate)/Silicone and BMA (Butyl methacrylate), MMA (Methyl methacrylate) by making the silicone contact lens. Method: Each sample of contact lenses was fabricated by cast mould method. We analyzed results by using average values of physical property of each sample. Results: In the composition of HEMA/Silicone/BMA, water contents of samples showed the value from 24.69% to 29.26%. Ultimate strength of samples showed the value from 0.109 kgf to 0.263 kgf. In the composition of HEMA/Silicone/MMA, swelling ratio of samples showed the value from 13.56% to 14.83%. Water contents of samples showed the value from 25.61% to 29.33%. Ultimate strength of samples showed the value from 0.107 kgf to 0.286 kgf. Conclusions: The compositions of percents of silicone were ranged from 0.20% to 11.50% and the composition percent of BMA and MMA was 5.15% in total. Swelling ratio and water contents increased with decreasing of BMA (Butyl methacrylate) and MMA (Methyl methacrylate) percent. In the composition of HEMA/Silicone/MMA, the values of ultimate strength increased with increasing of silicone percent to 4-MMA sample. In the composition of HEMA/Silicone/BMA, the values of ultimate strength decreased with increasing of silicone percent.