• ETRI Journal
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• v.42 no.2
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• pp.292-304
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• 2020

As side-channel analysis and machine learning algorithms share the same objective of classifying data, numerous studies have been proposed for adapting machine learning to side-channel analysis. However, a drawback of machine learning algorithms is that their performance depends on human engineering. Therefore, recent studies in the field focus on exploiting deep learning algorithms, which can extract features automatically from data. In this study, we survey recent advances in deep learning-based side-channel analysis. In particular, we outline how deep learning is applied to side-channel analysis, based on deep learning architectures and application methods. Furthermore, we describe its properties when using different architectures and application methods. Finally, we discuss our perspective on future research directions in this field.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.165-170
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• 2013

When we build up a 3D model from the given 2D images, linear algorithms are often used to reduce computational cost or for initialization of nonlinear algorithms. However, contemporary linear algorithms have apparently linear structures, but virtually they are implemented using SVD. The SVD is also implemented using numerical analysis algorithms that need initialization. Moreover, solutions using SVD are more difficult to analyze than closed-form solutions. To avoid from such inconvenient numerical analysis algorithms of the contemporary methods and for convenient analysis of solutions, this paper proposes a convenient linear method that produces a closed-form solution.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.385-396
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• 1999

In the process of structural design for large-scale structures with several thousands of degrees of freedom, a plethora of structural calculations with large amount of data storage are required to obtain the forces and displacements of the members. However, current computational environment with single microprocessor such as a personal computer or a workstation is not capable of generating a high-level of efficiency in structural analysis and design process for large-scale structures. In this paper, a high-performance parallel computing system interconnected by a network of personal computers is proposed for an efficient structural analysis. Two distributed structural analysis algorithms are developed in the form of distributed or parallel preconditioned conjugate gradient (DPCG) method. To enhance the performance of the developed distributed structural analysis algorithms, the number of communications and the size of data to be communicated are minimized. These algorithms are applied to the structural analyses of three large space structures as well as a 144-story tube-in-tube framed structure.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1047-1055
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• 2009

Since nuclear and chemical materials could damage people and disturb battlefield missions in a wide region, nuclear/chemical reconnaissance systems utilizing multiple mobile robots are highly desirable for rapid and safe reconnaissance. In this paper, we design a nuclear/chemical reconnaissance system including mobile robots. Also we propose time-efficient trajectory planning algorithms using grid coverage and contour finding methods for reconnaissance operation. For grid coverage, we performed in analysis on time consumption for various trajectory patterns generated by straight lines and arcs. We proposed BCF (Bounded Contour Finding) and BCFEP (Bounded Contour Finding with Ellipse Prediction) algorithms for contour finding. With these grid coverage and contour finding algorithms, we suggest trajectory planning algorithms for single, two or four mobile robots. Various simulations reveal that the proposed algorithms improve time-efficiency in nuclear/chemical reconnaissance missions in the given area. Also we conduct basic experiments using a commercial mobile robot and verify the time efficiency of the proposed contour finding algorithms.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.141-152
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• 1998

Based on the geometric representation an efficient al-gorithm is designed to find all articulation points of a permutation graph. The proposed algorithm takes only O(n log n) time and O(n) space where n represents the number of vertices. The proposed se-quential algorithm can easily be implemented in parallel which takes O(log n) time and O(n) processors on an EREW PRAM. These are the first known algorithms for the problem on this class of graph.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.19-26
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• 1996

In this paper, convergence properties of the LMS, LMF, and LVCMS algorithms are investigated under the assumption of the uncorrelated Gaussian input data. By treating these algorithms as special cases of more general algorithm family, unified results on these algorithms are obtained. First the upper bound on the step size parameter is obtained. Second, an expression for misadjustment is obtained. These theoretical results confirm earlier LMS works. Further, the results explain why the LMS and LVCMS algorithms are experiencing difficulties with plant noise having heavier tailed densities. Simulation results agree with theoretical expectation closely for various plant noise statistics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.4
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• pp.284-290
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• 2013

Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.313-328
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• 1998

In this paper we establish the equivalence between the generalized nonlinear mixed variational inequalities and the gener-alized resolvent equations. This equivalence is used to suggest and analyze a number of iterative algorithms for solving generalized vari-ational inequalities. We also discuss the convergence analysis of the propose algorithms. As special cases we obtain various known re-sults from our results.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.387-401
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• 2001

If the distance between two vertices becomes longer after the removal of a vertex u, then u is called a hinge vertex. In this paper, a linear time sequential algorithm is presented to find all hinge vertices of an interval graph. Also, a parallel algorithm is presented which takes O(n/P + log n) time using P processors on an EREW PRAM.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.777-779
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• 1999

A new distributed/parallel algorithm simulator, DASim(Distributed Algorithm Simulator), is proposed in this paper. The idea is to ease the task of design, analysis and implementation of distributed algorithms. A small high level language has been proposed for the purpose. Through this non-language specific high level language, the users are spared from the tedious details about how to program distributed or parallel algorithms. Further, visualization of these algorithms are pretty helpful to understand behaviors of these algorithms.