• Journal of Internet Computing and Services
• /
• v.17 no.4
• /
• pp.1-9
• /
• 2016

Algorithms implementing distributed shared memory (DSM) were developed for ensuring consistency. The performance of DSM algorithms is dependent on system and usage parameters. However, ensuring these algorithms to tolerate faults is a problem that needs to be researched. In this study, we proposed fault-tolerant scheme for DSM system and analyzed reliability and fault-tolerant overhead. Using our analysis, we can choose a proper algorithm for DSM on error prone environment.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 1994.10a
• /
• pp.157-164
• /
• 1994

Finite element analysis of material deformation is successfully utilized to understand metal forming processes such as forging, extrusion and deep drawing. However, such analysis involves contact problems; a free node touches a die surface and a contact node slips along the die surface. In the present investigation, appropriate contact algorithms were developed assuming that a three dimensional surface can be divided into bilinear patches and that nodal velocities are linear during an incremental time. The algorithms were coded into a computer program and tested for a simple surface. Comparison of the test result with that obtained from a commercial code is presented and discussed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.1127-1132
• /
• 1991

Pneumatic control system has been used mainly for endpoint position control because of the compressibility, viscosity and low output stiffness of air which causes nonlinear flow characteristics. In this paper, pneumatic position control algorithms using fuzzy rule were developed to achieve faster and more stable response than conventional PI control algorithm. The performances of the proposed algorithms were compared by computer simulations with them of PI controller. From those simulations it was shown that the proposed algorithms are more efficient about settling time, steady state error and overshoot than PI control algorithm.

• Proceedings of the IEEK Conference
• /
• 2001.06a
• /
• pp.41-44
• /
• 2001

In this paper, we have investigated the adaptive sector antenna which can control the size and direction angle of sectors, and proposed the three sectorization algorithms which are based on distribution of users, distribution of codes and distribution of signal power, respectively. The BERs of each sectorization algorithms are compared through computer simulation. As results of the simulation, the sectorization algorithm based on signal power are better than the other in terms nf BER. We have simulated error performance the DS-CDMA/BPSK system with the antenna in AWGN, frequency non-selective Rayleigh fading and MAI channels.

• Journal of the military operations research society of Korea
• /
• v.13 no.1
• /
• pp.45-64
• /
• 1987

Power algorithms for analysis of variance tests are presented. In experimental design of operational tests and evaluations the selection of design parameters so as to attain an experiment with desired power is a difficult and important problem. An interactive computer program is presented which uses the power algorithms for ANOVA tests and creates graphical presentations which can be used to assist decision makers in statistical design. ANOVA tests and associated parameters (such as sample size, types and levels of treatments, and alpha-level)are examined.

• Proceedings of the IEEK Conference
• /
• 2002.07c
• /
• pp.1721-1723
• /
• 2002

In 3rd-generation mobile communication systems providing packet service, optimal scheduling algorithms we needed to increase service efficiency. In this paper, three scheduling algorithms (SP, EDF, and RPQ) which have been studied in the field of computer networks are applied with transmit power constraint to an interference-limited CDMA system, proving to be efficient.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.06e
• /
• pp.232-235
• /
• 1998

In this paper, we present the modified blind adaptive multiuser detector based on Constant Modulus Algorithm(CMA) for the demodulation of code-division multiple-access(CDMA) signals. Convergence issues are treated, and the performance of three algorithms is compared via computer simulations.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.89-93
• /
• 2009

Embedded systems are becoming more popular as many embedded platforms have become more affordable. It offers a compact solution for many different problems including computer vision applications. Texture classification can be used to solve various problems, and implementing it in embedded platforms will help in deploying these applications into the market. This paper proposes to deploy the texture classification algorithms onto the embedded computer vision (ECV) platform. Two algorithms are compared; grey level co-occurrence matrices (GLCM) and Gabor filters. Experimental results show that raw GLCM on MATLAB could achieves 50ms, being the fastest algorithm on the PC platform. Classification speed achieved on PC and ECV platform, in C, is 43ms and 3708ms respectively. Raw GLCM could achieve only 90.86% accuracy compared to the combination feature (GLCM and Gabor filters) at 91.06% accuracy. Overall, evaluating all results in terms of classification speed and accuracy, raw GLCM is more suitable to be implemented onto the ECV platform.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.49-62
• /
• 2023

There has been a rapid increase in the creation and alteration of new malware samples which is a huge financial risk for many organizations. There is a huge demand for improvement in classification and detection mechanisms available today, as some of the old strategies like classification using mac learning algorithms were proved to be useful but cannot perform well in the scalable auto feature extraction scenario. To overcome this there must be a mechanism to automatically analyze malware based on the automatic feature extraction process. For this purpose, the dynamic analysis of real malware executable files has been done to extract useful features like API call sequence and opcode sequence. The use of different hashing techniques has been analyzed to further generate images and convert them into image representable form which will allow us to use more advanced classification approaches to classify huge amounts of images using deep learning approaches. The use of deep learning algorithms like convolutional neural networks enables the classification of malware by converting it into images. These images when fed into the CNN after being converted into the grayscale image will perform comparatively well in case of dynamic changes in malware code as image samples will be changed by few pixels when classified based on a greyscale image. In this work, we used VGG-16 architecture of CNN for experimentation.

• ETRI Journal
• /
• v.21 no.2
• /
• pp.31-39
• /
• 1999

Given two sorted lists A=(a0, a1, ${\cdots}$,a${\ell}$-1}) and B=(b0, b1, ${\cdots}$, bm-1), we are to merge these two lists into a sorted list C=(c0,c1, ${\cdots}$, cn-1), where n=${\ell}$+m. Since this is a fundamental problem useful to solve many problems such as sorting and graph problems, there have been many efficient parallel algorithms for this problem. But these algorithms cannot be performed efficiently in the postal model since the communication latency ${\lambda}$, which is of prime importance in this model, is not needed to be considered for those algorithms. Hence, in this paper we propose an efficient merge algorithm in this model that runs in $$2{\lambda}{\frac{{\log}n}{{\log}({\lambda}+1)}}+{\lambda}-1$$ time by using a new property of the bitonic sequence which is crucial to our algorithm. We also show that our algorithm is near-optimal by proving that the lower bound of this problem in the postal model is $f_{\lambda}({\frac{n}{2}})$, where $${\lambda}{\frac{{\log}n-{\log}2}{{\log}([{\lambda}]+1)}{\le}f_{\lambda}({\frac{n}{2}}){\le}2{\lambda}+2{\lambda}{\frac{{\log}n-{\log}2}{{\log}([{\lambda}]+1)}}$$.