• The Journal of Information Technology
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• v.10 no.3
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• pp.33-45
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• 2007

Systolic Array Processor is used for designing the special purpose processor in Digital Signal Processing, Computer Graphics, Neural Network Applications etc., since it has the characteristic of parallelism, pipeline processing and architecture of regularity. But, in case of using general design method, it has intial waiting period as large as No. of PE-1. And if the connected system needs parallel and simultaneous outputs, processor has some problems of the performance, since it generates only one output at each clock in output state. So in this paper, one dimensional Systolic Array Processor that is designed according to the dependance of data and operations using the partitioned sub-matrix is proposed for the purpose of improving the performance. 1-D Systolic Array using 4 partitioned sub-matrix has efficient method in case of considering those two problems.

• Atmosphere
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• v.23 no.1
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• pp.33-37
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• 2013

In meteorology, exploitation of Kalman filter as a data assimilation system is virtually impossible due to simultaneous requirements of adjoint model and large computer resource. The other substitute of utilizing ensemble Kalman filter is only affordable by compensating an enormous usage of computing resource. Furthermore, the latter employs ensemble integration sets for evolving the background error covariance matrix by compensating the dynamical feature of the temporal evolution of weather conditions. We propose a new implementation method that works without the adjoint model by utilizing the explicit expression of the background error covariance matrix in backward evolution. It will also break a barrier in the evolution of the covariance matrix. The method may be applied with a slight modification to the real time assimilation or the retrospective analysis.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.211-215
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• 1989

The structure of A matrix of one machine connected to the infinite bus is described for a full model. The A matrix can be partitioned to submatrices which depend on the initial operating point and do not depend on it. When the dynamic properties for several different operating points are desired, those submatrices can be obtained through simple column operations. Furthermore, the elements of A matrix car be directly calculated from the manufacturer's data. RMS quantities of the state variables for the initial operating point are used. This approach can save the labor for calculating the elements of A matrix for the dynamic stability analysis.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.101-107
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• 2008

A composite mechanics for discontinuous fiber reinforced polymer matrix composites(PMC) is analysed in order to predict fiber axial stresses. In continuum approach. frictional slip which usually takes place between fibers and polymers is accounted to derive PMC equations. The interfacial friction stress is treated by the product of the coefficient of friction and the compressive stress norma1 to the fiber/matrix interface. The residual stress and the Poisson's contraction implemented by the rule of mixture(ROM) are considered for the compressive stress normal to the fiber/matrix interface. In addition. the effects of fiber aspect ratio and fiber volume fraction on fiber axial stresses are evaluated using the derived equations. Results are illustrated numerically using the present equations with reasonable materials data. It is found that the fiber axial stress in the center region shows no great discrepancy for different fiber aspect ratios and fiber volume fractions while some discrepancies are shown in the fiber end region.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.31-34
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• 2004

For solving multiresponse problems, a variety of loss function approaches have been proposed assuming that a cost matrix is known and fixed. However a cost matrix is also an important factor in loss function approaches, because the optimal solution is very sensitive to the cost matrix. In this paper. we propose a novel method for adjusting the cost matrix by considering the predictive ability of the estimated response models. Simulation results for the generated data set show that the proposed method is competitive with previously reported methods.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.6
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• pp.53-62
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• 1998

A simple analytical and finite element(FE) models are used to study the tensile properties of Al matrix composite with continuous TiNi fibers. The effects of residual stresses caused by the shape momory effects have been compared for various mechanical behaviors as a function of fiber volume fraction and degree of pre-strain and fiber configurations. It is found that both the back stress in the Al matrix induced by stiffness of TiNi fibers and the compressive stress in the matrix are caused of the strengthening mechanisms. Both theoretical and analytical results show quite good agreement and are closed to the experimental data except in high volume content.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.575-585
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• 2016

Longitudinal studies repeatedly measure outcomes over time. Therefore, repeated measurements are serially correlated from same subject (within-subject variation) and there is also variation between subjects (between-subject variation). The serial correlation and the between-subject variation must be taken into account to make proper inference on covariate effects (Diggle et al., 2002). However, estimation of the covariance matrix is challenging because of many parameters and positive definiteness of the matrix. To overcome these limitations, we propose autoregressive moving average Cholesky decomposition (ARMACD) for the linear mixed models. The ARMACD allows a class of flexible, nonstationary, and heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the random effects covariance matrix. We analyze a real dataset to illustrate our proposed methods.

• The Journal of Economics, Marketing and Management
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• v.7 no.1
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• pp.39-50
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• 2019

Purpose - The article views the theoretical basis of adaptation concentric matrix models in the analysis of the financial condition of the organization. Presented the elements counting procedures in the assessment of economic stability. Research design, data, and Methodology - Used the economic indicates in the concentric matrix models. The article views the specific using the concentric matrix models in the analysis of the financial condition of the organization. Results - The concentric matrix models can be adaptation to the analysis of financial conditions of organizations and to the comparative analysis. In the process of analysis of economic stability can be used "a field of efficiency". The classical variant of methods is transformed. The detailed assessment of influence of individual factors defined the additional methods. Conclusions - In the article the methods are demonstrated on the material of organization (Hyundai Elevator Co, China Communications Construction Company).

• International conference on construction engineering and project management
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• 2015.10a
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• pp.210-212
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• 2015

The growth-share matrix is a portfolio planning tool developed by the Boston Consulting Group (BCG) to assist competitive positioning in the international market including those in the construction industry. This matrix is helpful in balancing the firm's cash-flow, and it can suggest strategic directions for each business unit. However, its effectiveness and applicability have long been debated in the academic field due to the complex and unique industrial context of construction. To solve the dispute, this research clarifies the applicability of theories underlying the growth-share matrix to the construction industry. Empirical research based on actual financial data of Korean construction firms is adopted for the statistical analysis including one-way analysis of variance and correlation analysis. The results of this research show that empirical findings on the relationship between performance variables. In this context, this research can provide important insights on the concept of portfolio management in the construction industry.

• 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.