• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.25-43
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• 1996

This paper presents the optimal and practical constant-stress accelerated life test plans for the lognormal lifetime distribution tinder assumptions of intermittent inspection and Type-I censoring. In an optimal plan, the low stress level and the proportions of test units allocated at each stress are determined under given inspection scheme and number of inspections such that the asymptotic variance of the maximum likelihood estimator of a certain quantile at use condition is minimized. Although the practical plan adopts the same design criterion, it involves three rather than two overstress levels in order to compromise the practical deficiencies of the optimal plan. Computational experiments are conducted to choose an allocation plan and a inspection scheme of the practical plan and to compare with test plans over a range of parameter values.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.43-47
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• 2016

대전 관평천 유역의 도시계획에 의해 개발된 도시지역을 대상으로 우수 관거 최종 유출부에 설치한 모니터링시스템을 이용하여 복수의 강우사상에 대해 연속으로 유출량 자료를 획득하였다. 본 연구는 연속적으로 획득한 유출량 자료를 바탕으로 SWMM(storm water management model)을 보정하고 최적의 수문학적 매개변수를 산정하는데 있다. SWMM의 수문학적 매개변수는 기본 침투식인 Curve Number, Horton 및 Green-Ampt를 바탕으로 각각의 경우에 맞는 유역의 조도계수 및 저류 깊이를 산정하였다. 현재 도시 개발에 따른 유출변화를 모의하는데 있어 국외에서 연구된 매개변수를 적용하고 있다. 번 연구에서 구한 매개변수는 향후 도시개발에 따른 유출 변화를 SWMM을 이용하여 분석하기 위한 기초자료를 활용 할 수 있을 것으로 판단된다.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.16-24
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• 2019

The performance of the battery management system (BMS) algorithm is important for ensuring the stability and efficient operation of battery packs. Such a performance is determined by the internal parameters of the electrical equivalent circuit model (EECM). This study proposes a performance improvement and verification of battery parameters for the BMS algorithm using electrical experiments and tools. The parameters were extracted through electrical characteristic experiments, and an EECM based on Ah counting was designed. Simulation results using the EECM were compared with actual experimental data to determine the best parameter extraction method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.15-28
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• 2019

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.45-50
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• 2022

The etching with high selectivity of silicon dioxide over silicon nitride is essential in semiconductor fabrication, and gas phase etch (GPE) can increase the competitiveness of the selective dielectric etch. In this work, GPE of plasma enhanced chemical vapor deposited SiO₂ was performed, and the effects of process parameters, such as temperature, partial pressure ratio, and gas supply cycle, are investigated in terms of etch rate and within wafer uniformity. Employing multiple regression analysis, the importance of each parameter elements is analyzed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.272-288
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• 1990

The uncertainty quantification process in probabilistic Risk Assessment usually involves a specification of the uncertainty in the input data and the propagation of this uncertainty to the final risk results. The distributional sensitivity analysis is to study the impact of the various assumptions made during the quantification of input parameter uncertainties on the final output uncertainty. The uncertainty importance of input parameters, in this case, should reflect the degree of changes in the whole output distribution and not just in a point estimate value. A measure of the uncertainty importance is proposed in the present paper. The measure is called the distributional sensitivity measure(DSM) and explicitly derived from the definition of the Kullback's discrimination information. The DSM is applied to three typical discrimination information. The DSM is applied to three typical cases of input distributional changes: 1) Uncertainty is completely eliminated, 2) Uncertainty range is increased by a factor of 10, and 3) Type of distribution is changed. For all three cases of application, the DSM-based importance ranking agrees very well with the observed changes of output distribution while other statistical parameters are shown to be insensitive.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.754-757
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• 2005

Construction firms attempt to improve project performance by adopting technology. However, the advantages gained from technology utilization are still not clear. Lack of information regarding technology benefits has resulted in industry reluctance to implement new technology. Therefore, there are needs for studies that quantify the impacts of technology utilization on project performance. An industry-wide survey was used to collect project data from 70 capital facility projects on the issue of technology usage and project owner satisfaction parameter. This paper reports on integration/automation technology usage in the Taiwanese construction industry and associated impacts on project owner satisfaction. In addition, integration and automation technology findings are presented by project phase. The analyses indicate that projects with owner satisfaction have, on average, higher levels of technology utilization than projects with owner dissatisfaction for all technology usage metrics analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.74-96
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• 2023

At present, the smart grid has become one of the indispensable infrastructures in people's lives. As a commonly used communication method, wireless communication is gradually, being widely used in smart grid systems due to its convenient deployment and wide range of serious challenges to security. For the insecurity of the schemes based on large integer factorization and discrete logarithm problem in the quantum environment, an identity-based key management scheme for smart grid over lattice is proposed. To assure the communication security, through constructing intra-cluster and inter-cluster multi-hop routing secure mechanism. The time parameter and identity information are introduced in the relying phase. Through using the symmetric cryptography algorithm to encrypt improve communication efficiency. Through output the authentication information with probability, the protocol makes the private key of the certification body no relation with the distribution of authentication information. Theoretic studies and figures show that the efficiency of keys can be authenticated, so the number of attacks, including masquerade, reply and message manipulation attacks can be resisted. The new scheme can not only increase the security, but also decrease the communication energy consumption.

• Journal of applied mathematics & informatics
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• v.41 no.2
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• pp.449-468
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• 2023

This paper deals in the study of the estimation of the parameters of Erlang distribution based on rank set sampling and some of its modifications. Here we considered Maximum Likelihood (ML) and the Bayesian technique to estimate the shape and scale parameter of Erlang distribution based on RSS and its some modifications such as ERSS, MRSS, and MRSSu. The derivation for unknown parameters of Erlang distribution is well presented using normal approximation to the asymptotic distribution of ML estimators. But due to the complexity involves in the integral, the Bayes estimator of unknown parameters is obtained using MCMC method. Further, we compared the MSE of estimation in different sampling schemes with different set sizes and cycle size. A real-life data application is also given to illustrate the efficiency of the proposed scheme.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.