• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.105-110
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• 1995

In this paper, we shall convey preservation of some partial orderings and closures of some positive ageing classes under k-out-of-n systems of like components. That is, if the life time of a component A is larger than that of a component B in any of the NBU, DMRL, NBUE, HNBUE, NBUFR and NBUFRA orderings, then a k-out-of-n system formed by i.i.d.. components of type A has larger life time, in that ordering, than that of a similar system consisting of n i.i.d. components type of B. And using these partial orderings, closures of positive aging classes(NBU, DMRL, NBUE, HNBUE, NBUFR and NBUFRA) under the coherent system like components.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.24-31
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• 2023

The solid-state drive (SSD) possesses higher input and output speeds, more resistance to physical shock, and lower latency compared with regular hard disks; hence, it is an increasingly popular storage device. However, tiny components on an internal printed circuit board (PCB) hinder the manual detection of malfunctioning components. With the rapid development of artificial intelligence technologies, automatic detection of components through convolutional neural networks (CNN) can provide a sound solution for this area. This study proposes applying the YOLOv5 model to SSD PCB component detection, which is the first step in detecting defective components. It achieves pioneering state-of-the-art results on the SSD PCB dataset. Contrast experiments are conducted with YOLOX, a neck-and-neck model with YOLOv5; evidently, YOLOv5 obtains an mAP@0.5 of 99.0%, essentially outperforming YOLOX. These experiments prove that the YOLOv5 model is effective for tiny object detection and can be used to study the second step of detecting defective components in the future.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.647-655
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• 2006

In this paper, we consider multiple comparisons for the ratio of the failure rates in two components system that the lifetimes of the components have independent exponential distributions. Also we suggest Bayesian multiple comparisons procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Finally, we give numerical examples to illustrate our procedure.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.127-134
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• 1997

A method is proposed for the choice of the number of principal components in principal component regression based on the predicted error sum of squares. To do this, we approximately evaluate that statistic using a linear approximation based on the perturbation expansion. In this paper, we apply the proposed method to various data sets and discuss some properties in choosing the number of principal components in principal component regression.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.559-568
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• 2006

In this paper, we develop the noninformative priors for the linear mixed models when the parameter of interest is the ratio of variance components. We developed the first and second order matching priors. We reveal that the one-at-a-time reference prior satisfies the second order matching criterion. It turns out that the two group reference prior satisfies a first order matching criterion, but Jeffreys' prior is not first order matching prior. Some simulation study is performed.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.139-141
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• 2003

GNSS 시스템을 구축하는데 있어서 기존의 절차지향이나 객채지향 방법에서 벗어나 컴포넌트 개발(CBD) 방법론을 이용하는 것이 재사용성, 유지 보수성, 비용 절감 및 효율성 측면에서 적합하다는 타당성이 제기되고 있다. 따라서 본 논문에서는 기존의 여러 CBD 방법론 중 GNSS 문제 도메인에 가장 적합한 UML Components 방법론을 테일러링하여 GNSS 컴포넌트 추출을 위한 프로세스를 정의한 후에, 그 프로세스에 마라 GNSS 컴포넌트를 추출한다.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.163-172
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• 1999

We propose a cross-validatory method for the choice of the number of principal components in principal component regression based on the magnitudes of correlations with y. There are two different manners in choosing principal components, one is the order of eigenvalues(Shin and Moon, 1997) and the other is that of correlations with y. We apply our method to various data sets and compare results of those two methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1078-1084
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• 2010

This paper presents a speech enhancement system which restores the amplitude components and phase components by discrete Fourier transform (DFT), using neural network training by back-propagation algorithm. First, a neural network is trained using DFT amplitude components and phase components of noisy speech signal, then the proposed system enhances speech signals that are degraded by white noise using a neural network. Experimental results demonstrate that speech signals degraded by white noise are enhanced by the proposed system using the neural network, whose inputs are DFT amplitude components and phase components. Based on measuring spectral distortion measurement, experiments confirm that the proposed system is effective for white noise.

• International Journal of Contents
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• v.5 no.1
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• pp.15-20
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• 2009

In this paper, we propose u-Learning management systems which are designed and implemented based on learning activities oriented components. The proposed systems are composed of components which can process the functionalities for coming into actions of learning activities. Specially, each component is broken into class units by which learning activities of users can be performed on various devices. When users by to connect the proposed learning management system, the system explores devices of users and the corresponding connection program, and then selects components that are fitted to the activities and combines them in a real-time. Our system provides u-Learning environment so that users can use the learning activity services taking no influence on time, place, various devices and programs. That is different from traditional e-Learning system which cannot support various devices of users directly.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1883-1887
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• 2008

Most of digital media contents are composed with video and audio, picture and animation informations. Sometime, there is some deviation of information recognition quality for the video and audio information according to information receiver's characteristics or the understanding. But visual information using the text provide most clear and accurate ways for information recognition to human being. In this paper, we propose a new broadcasting system(BSDMC) to transmit clear and accurate meaning of the digital media contents. We implement general-purpose components to display the video, picture, text and symbol simultaneously. Only plug-in and call these components with proper parameters on the application developing tool, we can easily develop the multimedia contents broadcasting system. These components are implemented based on the object-oriented framework and modular structure so that increase the reusability and can be develop other applications quick and reliable.