• The Journal of the Convergence on Culture Technology
• /
• v.10 no.1
• /
• pp.471-476
• /
• 2024

With the spread of various smart devices and computing devices, big data generation is occurring widely. Machine learning is an algorithm that performs reasoning by learning data patterns. Among the various machine learning algorithms, the algorithm that attracts attention is deep learning based on neural networks. Deep learning is achieving rapid performance improvement with the release of various applications. Recently, among deep learning algorithms, attempts to analyze data using graph structures are increasing. In this study, we present a graph generation method for transferring to a deep learning network. This paper proposes a method of generalizing node properties and edge weights in the graph generation process and converting them into a structure for deep learning input by presenting a matricization We present a method of applying a linear transformation matrix that can preserve attribute and weight information in the graph generation process. Finally, we present a deep learning input structure of a general graph and present an approach for performance analysis.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.2
• /
• pp.162-170
• /
• 2015

Commute time embedding involves computing the spectral decomposition of the graph Laplacian. It requires the computational burden proportional to $o(n^3)$, not suitable for large scale dataset. Many methods have been proposed to accelerate the computational time, which usually employ the Nystr${\ddot{o}}$m methods to approximate the spectral decomposition of the reduced graph Laplacian. They suffer from the lost of information by dint of sampling process. This paper proposes to reduce the errors by approximating the spectral decomposition of the graph Laplacian using that of the affinity matrix. However, this can not be applied as the data size increases, because it also requires spectral decomposition. Another method called approximate commute time embedding is implemented, which does not require spectral decomposition. The performance of the proposed algorithms is analyzed by computing the commute time on the patch graph.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.9
• /
• pp.1965-1970
• /
• 2011

This paper proposes the method of switching function implementation using switching function extraction based on graph over finite fields. After we deduce the matrix equation from path number of directional graph, we propose the switching function circuit algorithm, also we propose the code assignment algorithm for nodes which is satisfied the directional graph characteristics with designed circuits. We can implement more optimal switching function compare with former algorithm, also we can design the switching function circuit which have any natural number path through the proposed switching function circuit implementation algorithms. Also the proposed switching function implementation using graph theory over finite fields have decrement number of input-output, circuit construction simplification, increment arithmetic speed and decrement cost etc.

• The Korean Journal of Applied Statistics
• /
• v.15 no.1
• /
• pp.85-105
• /
• 2002

To explore the relationships among frequencies for sets of alleles, within or between loci, is one of the first analyses in population genetic study. The general question is whether the frequency of a set of alleles is the same as the product of each of the separate allele frequencies. For two alleles of a single locus, Hardy-Weinberg equilibrium is tested and for an allele from each of two loci, linkage disequilibrium is tested. However, it is more useful if we can quantify and graphically represent this information. In this study, we suggest graphical methods to find associations between alleles. We also analyze the STR data of Korean population as an illustration.

• The Korean Journal of Applied Statistics
• /
• v.28 no.1
• /
• pp.49-60
• /
• 2015

Various kinds of ordination methods such as correspondence analysis and canonical correspondence analysis are used in community ecology to visualize relationships among species, sites, and environmental variables. Ter Braak (1986), Jackson and Somers (1991), Parmer (1993), compared the ordination methods using eigenvalue and distance graph. However, these methods did not show the relationship between population and biplot because they are only based on surveyed data. In this paper, a method that measures the extent to show population information to biplot was introduced to compare ordination methods objectively.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.36-40
• /
• 1987

현재 사용되고 있는 작업방식은 로봇과 positioner의 상대적인 위치 및 자세설정에 의하여 작업효율 및 성능향상을 꾀할 수 있음에도 불구하고 비효율적인 방법으로 사용하고 있는 실정이다. 이러한 문제점을 해결하기 위한 방법중의 하나로 로보트와 positioner시스템을 하나의 기구학적 모델로 제어하는 방법이 제시된 바 있다. 상기의 연구에서는 로보트와 positioner(이하 R-P 시스템)간의 협조 제어가 여유자유도제어 방법을 이용하여 가능한 것임을 보였다. 그러나 용접작업과 같은 positioner 위에서의 연속경로 작업에 있어서는 작업공간과 특이성(singularity) 등에 관련된 여러 가지 문제점을 안고 있다. 특이성은 외부의 물리적인 제약이나 로보트의 기하학적 구조의 문제로 발생될 수도 있는데 이때 자유도의 손실을 유발하므로 임의의 원하는 방향으로 움직일 수 없게 된다. 이러한 면에서 R-P 시스템의 조작 성능 평가가 중요한 의미를 갖는다. 본 연구에서는 실제 산업현장에서 이용되고 있는 5 자유도를 갖는 수직 다관절형 로보트와 positioner에 대하여 협조 제어 방법을 검토한다. 그리고 작업공간 내의 조작성능평가를 위하여 Jacobian 행렬을 이용한 조작성지수를 위하여 Jacobian 행렬을 이용한 조작성지수를 도입하고 주어진 작업단면에 대한 이들의 분포를 등고선 그래프로 시각화 한다. 또한 조작성지수를 최대화 하는 알고리즘을 R-P 시스템에 적용하고 시뮬레이션을 통하여 그 타당성을 검토한다

• Communications of Mathematical Education
• /
• v.30 no.2
• /
• pp.251-262
• /
• 2016

In this paper, we investigate the bracing rectangular frameworks problem and provide a new proof of this problem using the angle sequence according to deformed rectangular frameworks in a view of mathematising. And also we provide the algorithm to determine the rigidity of braced rectangular frameworks.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.5
• /
• pp.1168-1173
• /
• 2013

This paper proposes a new visualization method based on cloud technique which uses internal relationship of user correlation and external relation of social network to visualize user relationship hierarchy. The visualization method of this paper can well represent user-focused relationship hierarchy on social networks by a correlation matrix. The importance of a access node reflects into user relationship hierarchy by exploiting external relation of social network. Users of the method can well understand user relationships on account of representing user relationship hierarchy from social networks. In addition, the method use hadoop and hive for distribution storing and parallel processing which the result of calculation visualizes hierarchy graph using D3.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.2
• /
• pp.381-394
• /
• 2016

Graphical model represents conditional dependencies between variables as a graph with nodes and edges. It is widely used in various fields including physics, economics, and biology to describe complex association. Conditional dependencies can be estimated from a inverse covariance matrix, where zero off-diagonal elements denote conditional independence of corresponding variables. This paper proposes a efficient BCDR (block coordinate descent with random permutation) algorithm using graphics processing units and random permutation for the CONCORD (convex correlation selection method) based on the BCD (block coordinate descent) algorithm, which estimates a inverse covariance matrix based on pseudo-likelihood. We conduct numerical studies for two network structures to demonstrate the efficiency of the proposed algorithm for the CONCORD in terms of computation times.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.12
• /
• pp.889-898
• /
• 2022

In this paper, parallel computing method on the three-dimensional electromagnetic field is proposed. The present electromagnetic scattering analysis is conducted based on the time-harmonic vector wave equation and the finite element method. The edge-based element and 2^nd -order absorbing boundary condition are used. Parallelization of the elemental numerical integration and the matrix assemblage is accomplished by allocating the partitioned finite element subdomain for each processor. The graph partitioning library, METIS, is employed for the subdomain generation. The large sparse matrix computation is conducted by MUMPS, which is the parallel computing library based on the multi-frontal method. The accuracy of the present program is validated by the comparison against the Mie-series analytical solution and the results by ANSYS HFSS. In addition, the scalability is verified by measuring the speed-up in terms of the number of processors used. The present electromagnetic scattering analysis is performed for a perfect electric conductor sphere, isotropic/anisotropic dielectric sphere, and the missile configuration. The algorithm of the present program will be applied to the finite element and tearing method, aiming for the further extended parallel computing performance.