• International Journal of Reliability and Applications
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• v.3 no.3
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• pp.133-145
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• 2002

The traditional methods of evaluating the performance of a network by enumerating all possible states may quickly become computationally prohibitive, since the number of states grows exponentially as the number of components increases. In such cases, enumerating only the most probable states would provide a good approximation. In this paper, we propose a method which efficiently generates upper and lower bounds for coherent performance measures utilizing the most probable states. Compared with Yang and Kubat's method, our procedure significantly reduces the complexity and memory requirement per iteration for computing the bounds and thereby, achieves the given degree of accuracy or the coverage within a shorter time.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.903-905
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• 2000

For an accurate analysis of three dimensional linear magnetostatic problems, a new boundary integral equation formulation is presented. This formulation adopts difference magnetic field concept and uses single layer magnetic surface charge as unknown. The proposed method is capable of eliminating numerical cancellation errors inside ferromagnetic materials. In additions, computing time and storage memory are reduced by 75% in comparison with the reduced and total scalar potential formulation. Two examples are given to show its efficiency and accuracy.

• Journal of Semiconductor Engineering
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• v.1 no.1
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• pp.31-37
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• 2020

We present an approximate DRAM architecture for energy-efficient deep learning. Our key premise is that by bounding memory errors to non-critical information, we can significantly reduce DRAM refresh energy without compromising recognition accuracy of deep neural networks. To validate the key premise, we make extensive Monte-Carlo simulations for several well-known convolutional neural networks such as LeNet, ConvNet and AlexNet with the input of MINIST, CIFAR-10, and ImageNet, respectively. We assume that the highest-order 8-bits (in single precision) and 4-bits (in half precision) are protected from retention errors under the proposed architecture and then, randomly inject bit-errors to unprotected bits with various bit-error-rates. Here, recognition accuracies of the above convolutional neural networks are successfully maintained up to the 10^-5-order bit-error-rate. We simulate DRAM energy during inference of the above convolutional neural networks, where the proposed architecture shows the possibility of considerable energy saving up to 10 ~ 37.5% of total DRAM energy.

• Journal of the Korean Institute of Navigation
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• v.10 no.1
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• pp.129-138
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• 1986

A matrix partitioning method is proposed for the 2-D motion analysis of floating bodies. For the numerical solution, the boundary of a floating body is approximated with a series of line segments and the governing integral equation is transformed into a system of linear equations. A new solution procedure of resulting linear equation with complex coefficients is formulated and programmed using a matrix partitioning scheme and the Choleski decomposition. From the case study, it is found that the proposed method is efficient in the motion analysis of floating bodies, especially in the calculation of hydrodynamic coefficients. Also, it requires smaller memory size and less computing time compared with conventional methods.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.262-264
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• 2000

A numerical method for the analysis of 3D eddy current in conductors due to applied time varying field is suggested using the finite element method. In the approximation of the field quantifies, the edge element is used, because it reduce the required computer memory and the computing time compared with the nodal elements. With edge elements, furthermore, the field governing equations become simple because the electric scalar potential ${\phi}$ can be set to zero. The modified magnetic vector potential($A^*$) is used as a state variable. The analysed results are compared with the experimentally measured ones for the TEAM workshop problem3.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.41-50
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• 2009

A conventional middleware system is optimized for wired computing environments. The wireless mobile devices have several disadvantages of low-speed processors, small memory and narrow bandwidth of wireless network. To overcome those problem issues in wireless mobile environments, middleware and many middleware-related applications have to be changed of the small sized components. In this paper, we design a lightweight mobile middleware system called "LightMware" which is optimized for mobile environment and middleware applications

• Journal of Fisheries and Marine Sciences Education
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• v.16 no.2
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• pp.163-170
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• 2004

The rapid exchanges of mobile computing environment and development of wireless communication are providing many effects for learning activity of students. Recently, PDA system developers which are studying memory capacity, communication speed and size of screen support techniques to be capable of learning from students in the wireless or moving environment. In this viewpoints, this paper has a purpose to design multimedia learning system to be able to do with sound lecture contents. The implemented system largely consists of two parts which have the teacher module and students module. The one manages learning progress of students, class management, bulletin board and etc. The other is capable of using studying and bulletin functions. The main idea of this research is focus to upgrade the effect of learning without almost treating the existing studies, which can be listening sound lecture and also seeing text and image at the same time.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.172-180
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• 2022

Crypto-mining malware (known as crypto-jacking) is a novel cyber-attack that exploits the victim's computing resources such as CPU and GPU to generate illegal cryptocurrency. The attacker get benefit from crypto-jacking by using someone else's mining hardware and their electricity power. This research focused on the possibility of detecting the potential crypto-mining malware in an environment by analyzing both static and dynamic approaches of deep learning. The Program Executable (PE) files were utilized with deep learning methods which are Long Short-Term Memory (LSTM). The finding revealed that LTSM outperformed both SVM and RF in static and dynamic approaches with percentage of 98% and 96%, respectively. Future studies will focus on detecting the malware using larger dataset to have more accurate and realistic results.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.5
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• pp.457-467
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• 2000

본 논문에서는 분산 메모리 구조를 갖는 병렬 컴퓨터 상에서 방대한 크기를 갖는 볼륨 데이터의 효과적인 가시화를 위한 병렬 광선 투사법을 제안한다. 데이터의 압축을 기반으로 하는 본 기법은 다른 프로세서의 메모리로부터 데이터를 읽기보다는 자신의 지역 메모리에 존재하는 압축된 데이터를 빠르게 복원함으로써 병렬 렌더링 성능을 향상시키는 것을 목표로 한다. 본 기법은 객체-순서와 영상-순서 탐색 알고리즘 모두의 정점을 이용하여 성능을 향상시켰다. 즉, 블록 단위의 최대-최소 팔진트리의 탐색과 각 픽셀의 불투명도 값을 동적으로 유지하는 실시간 사진트리를 응용함으로써 객체-공간과 영상-공간 각각의 응집성을 이용하였다. 본 논문에서 제안하는 압축 기반 병렬 볼륨 렌더링 방법은 렌더링 수행 중 발생하는 프로세서간의 통신을 최소화하도록 구현되었는데, 이러한 특징은 프로세서 사이의 상당히 높은 데이터 통신 비용을 감수하여야 하는 PC 및 워크스테이션의 클러스터와 같은 더욱 실용적인 분산 환경에서 매우 유용하다. 본 논문에서는 Cray T3E 병렬 컴퓨터 상에서 Visible Man 데이터를 이용하여 실험을 수행하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.04a
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• pp.187-194
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• 1995

Traditional genetic algorithms(GA) have mostly used binary code for representing design variable. The binary code GA has many difficulties to solve optimization problems with continuous design variables because of its targe computer core memory size, inefficiency of its computing time, and its bad performance on local search. In this paper, a real code GA is proposed for dealing with the above problems. So, new crossover and mutation processes of read code GA are developed to use continuous design variables directly. The results of real code GA are compared with those of binary code GA for several single and multiple objective optimization problems. As results of comparisons, it is found that the performance of the real code GA is better than that of the binary code GA, and concluded that the rent code GA developed here can be used for the general optimization problem.