• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1455_1456
• /
• 2009

$SF_6$ is the most commonly used insulating gas in electrical systems. But In these days $SF_6$ mixtures and alternative gas has been studied because of global warming. so although many studies have been carried out about binary gas mixtures with $SF_6$, few studies were presented about breakdown characteristics of $SF_6/CF_4$ mixtures. At present study the breakdown characteristics of $SF_6/CF_4$ mixtures in quasi-uniform field was performed. This experiments were carried out under AC voltages. The rod-rod electrode was used with 5 mm gap distance. The mixture of $SF_6/CF_4$ containing 20%,50%,70% of $SF_6$ were compared with pure $SF_6$ and $CF_4$ gas and gas pressure ranged from 0.1 to 0.5 MPa. The show that the breakdown voltages of gas were linearly increased according to the pressure in quasi-uniform field. For breakdown vlotage values of $(E/P)_{crit}$ are important. Because If values of (E/P) is a little more than $(E/P)_{crit}$, electrons rapidly increase and streamer discharge gernerates. Through this experiments values of $(E/P)_{crit}$ are found to vary with the ratio of $SF_6/CF_4$ mixture according to the following relationship. $V_b=(E/P)_{crit}{\cdot}p{\cdot}d$

• Journal of KIISE:Computer Systems and Theory
• /
• v.35 no.8
• /
• pp.372-377
• /
• 2008

Multiclass cancer classification has been actively investigated based on gene expression profiles, where it determines the type of cancer by analyzing the large amount of gene expression data collected by the DNA microarray technology. Since gene expression data include many genes not related to a target cancer, it is required to select informative genes in order to obtain highly accurate classification. Conventional rank-based gene selection methods often use ideal marker genes basically devised for binary classification, so it is difficult to directly apply them to multiclass classification. In this paper, we propose a novel method for multiclass gene selection, which does not use ideal marker genes but directly analyzes the distribution of gene expression. It measures the class-discriminability by discretizing gene expression levels into several regions and analyzing the frequency of training samples for each region, and then classifies samples by using the naive Bayes classifier. We have demonstrated the usefulness of the proposed method for various representative benchmark datasets of multiclass cancer classification.

• Journal of Korea Multimedia Society
• /
• v.10 no.4
• /
• pp.450-461
• /
• 2007

In this paper, we propose the method to use power-saving mode (PSM) applicable to non real-time traffic and PSM applicable to real-time traffic simultaneously, for VoIP traffic with silence suppression. The proposed method uses PSC II during talk-spurt interval of parties A and/or B and uses PSC I or probabilistic sleep interval decision (PSID) method during mutual silence interval, respectively. To evaluate the performance of hybrid PSM (HPSM) based on PSC II or PSID method, we present average buffering delay, energy consumption of mobile station and VoIP packet drop probability with simulation runs. Results shows that proposed HPSM decreases energy consumption of mobile station up to 25 % while satisfying the packet drop probability within QoS requirement in case of end-to-end VoIP connection.

• Smart Structures and Systems
• /
• v.16 no.2
• /
• pp.243-262
• /
• 2015

Optimal sensor placement (OSP) is a critical issue in construction and implementation of a sophisticated structural health monitoring (SHM) system. The uncertainties in the identified structural parameters based on the measured data may dramatically reduce the reliability of the condition evaluation results. In this paper, the information entropy, which provides an uncertainty metric for the identified structural parameters, is adopted as the performance measure for a sensor configuration, and the OSP problem is formulated as the multi-objective optimization problem of extracting the Pareto optimal sensor configurations that simultaneously minimize the appropriately defined information entropy indices. The nondirective movement glowworm swarm optimization (NMGSO) algorithm (based on the basic glowworm swarm optimization (GSO) algorithm) is proposed for identifying the effective Pareto optimal sensor configurations. The one-dimensional binary coding system is introduced to code the glowworms instead of the real vector coding method. The Hamming distance is employed to describe the divergence of different glowworms. The luciferin level of the glowworm is defined as a function of the rank value (RV) and the crowding distance (CD), which are deduced by non-dominated sorting. In addition, nondirective movement is developed to relocate the glowworms. A numerical simulation of a long-span suspension bridge is performed to demonstrate the effectiveness of the NMGSO algorithm. The results indicate that the NMGSO algorithm is capable of capturing the Pareto optimal sensor configurations with high accuracy and efficiency.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.1_2
• /
• pp.10-18
• /
• 2004

Quadtree, which is a hierarchical data structure, is a very important data structure to represent binary images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The operations of unaligned linear quadtrees, which are operations among the linear quadtrees with different origin, are able to perform the translated or rotated images efficiently. And this operations requires alignment of the linear quadtrees. In this paper, we present an efficient algorithm to perform alignment of unaligned linear quadtrees, using three-dimensional $n{\pm}n{\pm}n$ processors on RMESH(Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to route the locational codes of quardtree on the hierarchical structure of $n{\pm}n{\pm}n$ RMESH.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.1_2
• /
• pp.1-9
• /
• 2004

The important arithmetic operations over finite fields include exponentiation, division, and inversion. An exponentiation operation can be implemented using a series of squaring and multiplication operations using a binary method, while division and inversion can be performed by the iterative application of an AB$^2$ operation. Hence, it is important to develop a fast algorithm and efficient hardware for this operations. In this paper presents new bit-serial architectures for the simultaneous computation of multiplication and squaring operations, and the computation of an $AB^2$ operation over $GF(2^m)$ generated by an irreducible AOP of degree m. The proposed architectures offer a significant improvement in reducing the hardware complexity compared with previous architectures, and can also be used as a kernel circuit for exponentiation, division, and inversion architectures. Furthermore, since the Proposed architectures include regularity and modularity, they can be easily designed on VLSI hardware and used in IC cards.

• Journal of KIISE:Computer Systems and Theory
• /
• v.27 no.3
• /
• pp.235-244
• /
• 2000

This paper addresses a new method for constructing surface representation of 3D structures from a sequence of tomographic cross-sectional images, Firstly, we propose cell-boundary representation by transforming the cuberille space into cell space. A cell-boundary representation consists of a set of boundary cells with their 1-voxel configurations, and can compactly describe binary volumetric data. Secondly, to produce external surface from the cell-boundary representation, we define 19 modeling primitives (MP) including volumetric, planar and linear groups. Surface polygons are created from those modeling primitives using a simple table look-up operation. Comparing with previous method such as Marching Cube or PVP algorithm, our method is robust and does not make any crack in resulting surface model. Hardware implementation is expected to be easy because our algorithm is simple(scan-line), efficient and guarantees data locality in computation time.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.2
• /
• pp.87-94
• /
• 2017

Microsoft Office is an office suite of applications developed by Microsoft. Recently users with malicious intent customize Office files as a container of the Malware because MS Office is most commonly used word processing program. To attack target system, many of malicious office files using a variety of skills and techniques like macro function, hiding shell code inside unused area, etc. And, people usually use two techniques to detect these kinds of malware. These are Signature-based detection and Sandbox. However, there is some limits to what it can afford because of the increasing complexity of malwares. Therefore, this paper propose methods to detect malicious MS office files in Computer forensics' way. We checked Macros and potential problem area with structural analysis of the MS Office file for this purpose.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.626-629
• /
• 2004

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program for GLCM algorithm is newly implemented in the MS Visual IDE environment. While, additional texture imaging modules based on GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV texture variables, it composed of six types of second order texture function in the several quantization levels of 2(binary image), 8, and 16: Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality, four directions are provided as $E-W(0^{\circ}),\;N-E(45^{\circ}),\;S-W(135^{\circ}),\;and\;N-S(90^{\circ}),$ and W-E direction is also considered in the negative direction of E- W direction. While, two direction modes are provided in this program: Omni-mode and Circular mode. Omni-mode is to compute all direction to avoid directionality problem, and circular direction is to compute texture variables by circular direction surrounding target pixel. At the second phase of this study, some examples with artificial image and actual satellite imagery are carried out to demonstrate effectiveness of texture imaging or to help texture image interpretation. As the reference, most previous studies related to texture image analysis have been used for the classification purpose, but this study aims at the creation and general uses of texture image for urban remote sensing.

• Journal of the Korea Society for Simulation
• /
• v.27 no.2
• /
• pp.1-10
• /
• 2018

This paper presents an autonomous detection and aiming point computation of a battle tank by using RGB images. Maximally stable extremal regions algorithm was implemented to find features of the tank, which are matched with images extracted from streaming video to figure out the region of interest where the tank is present. The median filter was applied to remove noises in the region of interest and decrease camouflage effects of the tank. For the tank segmentation, k-mean clustering was used to autonomously distinguish the tank from its background. Also, both erosion and dilation algorithms of morphology techniques were applied to extract the tank shape without noises and generate the binary image with 1 for the tank and 0 for the background. After that, Sobel's edge detection was used to measure the outline of the tank by which the aiming point at the center of the tank was calculated. For performance measurement, accuracy, precision, recall, and F-measure were analyzed by confusion matrix, resulting in 91.6%, 90.4%, 85.8%, and 88.1%, respectively.