• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.44-50
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• 2024

This paper offers an overview of matrix formation and calculation techniques within the framework of General Linear Models (GLMs). It takes a sequential approach, beginning with a detailed exploration of matrix formation and calculation methods in regression analysis and univariate analysis of variance (ANOVA). Subsequently, it extends the discussion to cover multivariate analysis of variance (MANOVA). The primary objective of this study was to provide a clear and accessible explanation of the underlying matrices that play a crucial role in GLMs. Through linking, essentially different statistical methods, by fundamental principles and algebraic foundations that underpin the GLM estimation. Insights presented here aim to assist researchers, statisticians, and data analysts in enhancing their understanding of GLMs and their practical implementation in diverse research domains. This paper contributes to a better comprehension of the matrix-based techniques that can be extended to GLMs.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.73-80
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• 2004

Mass matrix, elastic stiffness matrix, load correction stiffness matrix by circulatory non-conservative force, and Winkler and Pasternak foundation matrix of framed structure in 2-D are calculated for stability analysis of divergence or flutter system. Then, a matrix equation of the motion for the non-conservative system is formulated and numerical results are presented to demonstrate the effect of some parameters with using Newmark method.

• Journal of Ocean Engineering and Technology
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• v.6 no.2
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• pp.125-132
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• 1992

This paper presents an approach for the derivation of frequency-dependent element matrices for vibration analysis of piping systems containing a moving medium. The dynamic stiffness matrix is deduced from transfer matrix, and, in turn, the frequency-dependent element matrices are derived. Numerical examples show that method gives more accurate results than those obtained using the conventional static shape function based element matrices.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.483-491
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• 2007

A closed form solution of a composite mechanics system is performed for the investigation of elastic-plastic behavior in order to predict fiber stresses, fiber/matrix interfacial shear stresses, and matrix yielding behavior in short fiber reinforced metal matrix composites. The model is based on a theoretical development that considers the stress concentration between fiber ends and the propagation of matrix plasticity and is compared with the results of a conventional shear lag model as well as a modified shear lag model. For the region of matrix plasticity, slip mechanisms between the fiber and matrix which normally occur at the interface are taken into account for the derivation. Results of predicted stresses for the small-scale yielding as well as the large-scale yielding in the matrix are compared with other theories. The effects of fiber aspect ratio are also evaluated for the internal elastic-plastic stress field. It is found that the incorporation of strong fibers results in substantial improvements in composite strength relative to the fiber/matrix interfacial shear stresses, but can produce earlier matrix yielding because of intensified stress concentration effects. It is also found that the present model can be applied to investigate the stress transfer mechanism between the elastic fiber and the elastic-plastic matrix, such as in short fiber reinforced metal matrix composites.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3482-3497
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• 2021

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.655-660
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• 2000

This paper presents the construction of consistent coefficient matrix elements for jointed structures using the reduction of flexibility and mass matrices. The reduced flexibility coefficient matrix hat little structural complexity than Guyan's stiffness matrix reduction since the only element of the original matrix, corresponding to the selected nodal degrees of freedom, contributes. The proposed method was applied to building equivalent coefficient matrices for a clamp jointed structure in finite element modal analysis of a cantilevered beam. The theoretical analysis results were compared with those experimental modal analysis, Comparison of both shows good agreement each other.

• Structural Engineering and Mechanics
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• v.39 no.5
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• pp.669-682
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• 2011

A Chebyshev spectral method (CSM) for the dynamic analysis of non-uniform Timoshenko beams under various boundary conditions and concentrated masses at their ends is proposed. The matrix-based Chebyshev spectral approach was used to construct the spectral differentiation matrix of the governing differential operator and its boundary conditions. A matrix condensation approach is crucially presented to impose boundary conditions involving the homogeneous Cauchy conditions and boundary conditions containing eigenvalues. By taking advantage of the standard powerful algorithms for solving matrix eigenvalue and generalized eigenvalue problems that are embodied in the MATLAB commands, chebfun and eigs, the modal parameters of non-uniform Timoshenko beams under various boundary conditions can be obtained from the eigensolutions of the corresponding linear differential operators. Some numerical examples are presented to compare the results herein with those obtained elsewhere, and to illustrate the accuracy and effectiveness of this method.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Earthquakes and Structures
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• v.22 no.4
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• pp.387-399
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• 2022

To study the seismic damage of masonry structures and understand the characteristics of the multi-intensity region, according to the Dujiang weir urbanization of China Wenchuan earthquake, the deterioration of 3991 masonry structures was summarized and statistically analysed. First, the seismic damage of multistory masonry structures in this area was investigated. The primary seismic damage of components was as follows: Damage of walls, openings, joints of longitudinal and transverse walls, windows (lower) walls, and tie columns. Many masonry structures with seismic designs were basically intact. Second, according to the main factors of construction, seismic intensity code levels survey, and influence on the seismic capacity, a vulnerability matrix calculation model was proposed to establish a vulnerability prediction matrix, and a comparative analysis was made based on the empirical seismic damage investigation matrix. The vulnerability prediction matrix was established using the proposed vulnerability matrix calculation model. The fitting relationship between the vulnerability prediction matrix and the actual seismic damage investigation matrix was compared and analysed. The relationship curves of the mean damage index for macrointensity and ground motion parameters were drawn through calculation and analysis, respectively. The numerical analysis was performed based on actual ground motion observation records, and fitting models of PGA, PGV, and MSDI were proposed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.11
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• pp.769-776
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• 1987

This paper deals with the topological observability analysis and the development of an observable island identification algorithm for state estimation in power systems, by using the incidence matrix and bus voltage grouping. An analogy of the DC power flow method to the DC circuit analysis is introduced, and all the relationships between power flows and phase angles are replaced by the corresponding current-voltage relation. As a result, a set of topological measurement equation expressed in the form of the incidince matrix is derived for the topological analysis, and the observability test is carried out by examining the rand of the measuremint matrix. The integer Gauss elimination method is introduced in the determination of matrix rand, so that the proposed observability test yields a precise observability criterion without any nearly-zero pivot problem encountered in the conventional algorithm. Also, an observable island identification algorithm reduced its computational time in comparision with the conventional algorithms. The proposed algorithms have been tested for sample systems, and their practicability has verified.