• Journal of the KSME
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• v.55 no.10
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• pp.36-39
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• 2015

이 글에서는 초고온가스로 노심 흑연 구조물의 신뢰성 평가 관련 이해를 돕기 위해 원자력급 흑연의 일반적인 특성, 흑연 구조물의 파손 평가 모델 및 이론, ASME 응력 평가 모델에 대해 기술하고자 한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.11
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• pp.1067-1074
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• 2010

In this study, RBDO(Reliability Based Design Optimization) was performed for a supersonic double-wedge inlet. By considering uncertainty of design with given design space, the pressure recovery was transformed into the probabilistic constraint while the inlet drag was considered as a deterministic objective function. To save computational analysis cost and to search good design space, Latin-Hypercube design of experiment and the Kriging model were incorporated and then RBDO was performed. Monte-Carlo simulation was performed to verify the accuracy of AFORM(Advanced First Order Reliability Method). It was found that AFORM result agreed very well with the Monte-Carlo simulation result. The system reliability was guaranteed by considering uncertainty of the design variables. In case of considering diverse uncertainty of system design, RBDO was found to be useful.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1287-1294
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• 2004

Recently relationships between reliability measures and the coverage have been developed for evaluation of software reliability. Particularly the mean value function of the coverage-based software reliability growth model is important because of its key role in rep-resenting the software reliability growth. In this paper, we first review the problems of the existing mean value functions with respect to the assumptions on which they are based. Then a new mean value function is proposed. The new mean value function is developed for a general testing environment in which imperfect fault detection and repeated construct execution are allowed. Finally performance of the proposed model is empirically evaluated by applying it to a real data set.

• The Transactions of the Korea Information Processing Society
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• v.4 no.5
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• pp.1267-1276
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• 1997

In this paper, the optimal model for specific test data was selected autimatically among sofware reliability growh models bassed on NAPP(Non Homogeneous Posission Preocess), and in result the tool for the reliability estimating scales was implemented.Whith the implemented tool, software optimal rekiability estimating scales(total expected number errors, error detection rate, expected number of errors remaining in the sortware, reliability, ete) could be predicted. By the reliability estimating scales gained form this, sofware development and projecr management could be applied. In order to test the optimal of the implemented tool, the comparicon with other paper and analization was done by using actual error data.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.133-142
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• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• Journal of the Korean GEO-environmental Society
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• v.25 no.7
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• pp.29-34
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• 2024

Frost heave is one of the significant engineering characteristics of frozen ground and causes severe damages on geo-structures. Although thermo-hydro coupled analyses have been developed to predict frost heave behavior, these analyses involve excessive input parameters and have primarily been validated for frost heave in clayey soils. Frost heave mainly occurs in silty soils, which have relatively higher permeability compared to clayey soils, necessitating careful attention. This study introduces empirical models and verifies their reliability for silty soils. By using the validated model, the correlation of key input parameters is derived, which is expected to enhance the applicability of thermal-mechanical analysis for geo-structures on frozen ground in the future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.195-198
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• 2002

고농도오존이 발생되는 원인과 환경적 요인의 상호관계를 모델링하기 위해 신경회로 망과 같은 지능제어 기법들이 많이 적용되어 왔다 분석과 모델링을 위해 유전자 알고리즘과 같은 최적화 방법을 적용하기도 하지만, 고농도 오존이 발생되는 메커니즘이 매우 복잡하고, 비선형적이며, 패턴파악이 어렵기 때문에 고농도 오존의 예측 모델링에는 여전히 문제점이 있다 따라서 본 논문에서는 신뢰수준과 신뢰구간을 이용하여 초농도 오존을 예측할 수 있는 모델링 방법을 서술하였다 예측값의 신뢰수준의 평가는 예측에 대한 실측값을 구하여 신뢰구간내의 데이터의 개수를 파악함으로써 신뢰성을 평가할 수 있다. 또한 이 테스트는 우리가 가지고 있지 않은 데이터에 대한 유효성을 평가하는데 적용될 수 있다 그리고 본 논문에서는 GMDH(Group Method of data handling)의 전형적인 알고리즘에 바탕을 두고 있는 DPNN(Dynamic Polynomial Neural Network)를 이용하여 예측 모델을 구성하였다. DPNN은 데이터 해석이 용이하고 비선형적인 동적 시스템 예측에 유용하게 적용될 수 있는 장점을 가지고 있다.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.42-49
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• 2006

In this paper, we proposed a model to evaluate confidence and satisfaction of health information web-sites visited by general health consumers. In order to propose the evaluation model, lots of foreign and domestic researches are investigated and analyzed. Based on these analyses, confidence and satisfaction standards for the model are proposed. A process for evaluation and a method for calculation of evaluation value by the standards are proposed, too. The proposed model can be utilized as a tool for analyzing conventional health information web-sites and can be utilized as check lists for developments in case of health information web-sites under construction.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.837-844
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• 2002

In general, software test is carried out to detect or repair errors in system during software development process. Namely, we can evaluate software reliability through collecting and removing the faults detected in testing phase. Software reliability growth model evaluates reliability of software mathematically. Many kinds of software reliability growth modeling which modeling the processes of detecting, revising and removing the faults detected in testing phase have been proposed in many ways. and, it is assumed that almost of these modeling have one typed detect and show the uniformed detection rate. In this study, significance levels of the faults detected in test phase are classified according to how they can affect on the whole system and then the fault detection capability of them is applied. From this point of view, We here by propose a software reliability growth model with faults detection capability according considering fault significance levels and apply some fault data to this proposed model and finally verify its validity by comparing and estimating with the existing modeling.

• Journal of KIISE:Information Networking
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• v.28 no.4
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• pp.578-585
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• 2001

IP Multicast that provides best-efforts service does not guarantee reliable delivery of multicast packets. In recent years, there are many approaches to support reliable multicast, but those are insufficient for implementing scalable and reliable multicast over Internet. We propose a Reliable Multicast Architecture(RMA) for scalable and reliable multicast. The RMA model guarantees reliability using a receiver initiated retransmission mechanism, and scalability using a feedback suppression mechanism by Multicast Router(MR). Furthermore, it utilizes underlying multicast routing information to minimize the cost of protocol modification and overheads. Our performance analyses show that RMA is much superior to previous works in the point of scalability and compatibility.