• 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 Navigation and Port Research
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• v.48 no.1
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• pp.62-77
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• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.107-112
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• 2008

In the case of the deep reservoirs like the gas reservoirs in the East-sea, it is often difficult to observe AVO responses in CMP gathers. Because the reservoir becomes more consolidated as its depth deepens, P-wave velocity does not decrease significantly when the pore fluid is replaced by the gas. In this study, we analyzed the effects of Poisson's ratio difference on AVO response with a variety of Poisson's ratios for the upper and lower layers. The results show that, as the difference in Poisson's ratio between the upper and lower layers decreases, the change in the reflection amplitude with incidence angle decreases. To consider the limitation of AVO responses shown in the gas reservoir in East-sea, the velocity model was made by simulation Gorae V structure with seismic data and well logs. The results of comparing AVO responses observed from the synthetic data with theoretical AVO responses calculated by using material properties show that the amount of the change in reflection amplitude with increasing incident angle is very small when the difference in Poisson's ratio between the upper and lower layers is small. In addition, the characteristics of AVO responses were concealed by noise or amplitude distortion arisen during preprocessing. To overcome such limitations of AVO analysis of the data from deep reservoirs, we need to acquire precisely reflection amplitudes in data acquisition stage and use processing tools which preserve reflection amplitude in data processing stage.

• Convergence Security Journal
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• v.13 no.1
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• pp.3-10
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• 2013

In this paper, reliability software model considering fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the S-shaped distribution model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model was used. In a software failure data analysis considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of failure time data and reliability make out.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.57-66
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• 2007

본 논문에서는 통신망의 트래픽 제어를 위한 무한버퍼, 단일 서버와 배치도착과정을 갖는 대기행렬 모형을 고려하였다. 또한 고객 도착 형태와 서비스의 분포는 지수분포를 배치 흐름은 포아송 정상과정 및 배치크기는 기하분포를 따른다고 가정하였다. 서비스를 받기 위해 시스템으로 들어오는 배치의 크기는 시스템의 상태에 따라서 트래픽 제어가 가능하다. 이와 같은 조건에서 시스템에 있는 고객의 수와 배치크기에 대한 결합 확률분포를 분석하였고, 행렬기법을 적용하여 시스템 체재시간에 대한 분석이 수행되었다. 마지막으로 시스템의 주요 성능평가 척도에 대한 효율적인 제어기법에 대한 언급과 수치예제를 통해서 증명하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.171-177
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• 2016

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this study, reliability software cost model considering shape parameter based on life distribution from the process of software product testing was studied. The cost comparison problem of the Lomax distribution reliability growth model that is widely used in the field of reliability presented. The software failure model was used the infinite failure non-homogeneous Poisson process model. The parameters estimation using maximum likelihood estimation was conducted. For analysis of software cost model considering shape parameter. In the process of change and large software fix this situation can scarcely avoid the occurrence of defects is reality. The conditions that meet the reliability requirements and to minimize the total cost of the optimal release time. Studies comparing emissions when analyzing the problem to help kurtosis So why Kappa efficient distribution, exponential distribution, etc. updated in terms of the case is considered as also worthwhile. In this research, software developers to identify software development cost some extent be able to help is considered.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.6
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• pp.25-31
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• 2004

In this paper, we introduce kinetic Monte Carlo (kMC) methods for simulating diffusion process in nano-scale device fabrication. At first, we review kMC theory and backgrounds and give a simple point defect diffusion process modeling in thermal annealing after ion (electron) implantation into Si crystalline substrate to help understand kinetic Monte Carlo methods. kMC is a kind of Monte Carlo but can simulate time evolution of diffusion process through Poisson probabilistic process. In kMC diffusion process, instead of. solving differential reaction-diffusion equations via conventional finite difference or element methods, it is based on a series of chemical reaction (between atoms and/or defects) or diffusion events according to event rates of all possible events. Every event has its own event rate and time evolution of semiconductor diffusion process is directly simulated. Those event rates can be derived either directly from molecular dynamics (MD) or first-principles (ab-initio) calculations, or from experimental data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.306-311
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• 2016

Software reliability in the software development process is an important issue. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, reliability software cost model considering logarithmic and exponential fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software reliability model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. The logarithmic and exponential fault detection model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Tunnel and Underground Space
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• v.16 no.4 s.63
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• pp.334-346
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• 2006

The discrete element code in 2-D, PFC2D, has been used as a tool to simulate various phenomena in rock mechanics and rock engineering. However, the code has an disadvantage that procedure to determine micro-parameters, namely properties of particles and contacts is repetitive and time-consuming. In this study, we analyzed the effect of micro-parameters(for generation of a contact-bonded model) on macro-properties(that were measured numerically by uniaxial compressive test). Based on the analysis, also, the time-saving and reliable method was suggested to determine a complete set of micro-parameters. In order to verify the suggested method, numerical specimens were generated in PFC2D for 10 different rock types at home and abroad. By the two trials for each specimen, in the result, the Young's modulus, Poisson's ratio and uniaxial compressive strength could be reproduced with being in relative error by about 5% to the values obtained by laboratory tests.

• The Journal of Engineering Geology
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• v.26 no.4
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• pp.593-600
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• 2016

To understand the mechanical properties of rock masses and intact rock in Korea, data from 4,280 in situ and laboratory tests from 107 tunnels on general national roads were analyzed. The mechanical properties (unit weight, cohesion, friction angle, modulus of deformation, Young's modulus, Poisson's ratio, uniaxial compressive strength, tensile strength, coefficient of permeability, and specific gravity) were analyzed by rock types and strength of rock in each rock type. The results of analysis, the mean specific gravity was highest in gneiss. The coefficient of permeability and Poisson's ratio show the highest mean values in granite and metamorphic rock, respectively. In addition, the unit weight, cohesion and friction angle in sedimentary rock, modulus of deformation, Young's modulus, uniaxial compressive strength and tensile strength in volcanic rock have the highest mean values. The values for each mechanical property showed wide ranges by the heterogeneity and anisotropy of rock masses in spite of detailed analysis by rock type and classification of rocks according to the strength.