• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.305-313
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• 2019

Generalized canonical correlation analysis (GCCA) extends the canonical correlation analysis (CCA) to the case of more than two sets of variables and there have been many studies on how two-set canonical solutions can be generalized. In this paper, we derive certain stationary equations which can lead the higher-order solutions of several GCCA methods and suggest a type of iterative procedure to obtain the canonical coefficients. In addition, with some numerical examples we present the methods for graphical display, which are useful to interpret the GCCA results obtained.

• Honam Mathematical Journal
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• v.33 no.1
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• pp.19-25
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• 2011

Let G be the general linear group GL(n,$\mathbb{C}$), $W_0$ the Weyl group of G and W the extended a neWeyl group of G. Then it is well-known that W is a union of the double cosets $W_{0x}W_0$ as x moves over the set of dominant weights of W. It is also known that each double coset $W_{0x}W_0$ contains a unique element $m_x$ of the shortest length. These shortest length elements belong to what are called the canonical left cells. However, it is still an open problem to find the canonical left cell containing a given $m_x$. One of the mai purposes of this paper is to introduce a new approach to attack this question. In particular, we will present a conjecture which explicitly describes the canonical left cells containing an element $m_x$. We will show that our conjecture is true for some specific types of $m_x$.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.11
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• pp.1576-1584
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• 2008

In this study, canonical correlation analysis (CCA) was applied to estimate the relationship between three different sexual maturity traits (X set: days to first egg (DFE), weight of the first egg (WFE), body weight at first egg (BWFE)) and level of nutrient intake (Y set: energy (EI) and protein intake (PI)) or the egg production traits at two different periods (Z set: number of egg (NE1 and NET) and weight of egg (WE1 and WET) from 22 to 25 (Wfirst) and 22 to 33 wk of age (Wall), respectively), which were measured from 64 egg-type pullets (Isa Brown) manipulated for time of access to energy and protein sources to onset of egg production. Partial CCA (PCCA) was used to eliminate the contribution of differences in the levels of nutrient intake to canonical variables for X and Z sets at the first production period. Estimated canonical correlation coefficients between X set and Y set (0.429, p = 0.042), X set and Z set (0.390, p = 0.007 for Wfirst) and within Z set (between Wfirst and Wall; 0.780, p<0.001), and partial canonical correlation coefficient between X set and Z set (0.415, p = 0.009) were significant. Canonical weights and loadings from CCA indicated that the BWFE had the largest contribution compared to the DFE and WFE to variation of egg number produced at two different periods. The results from PCCA indicated that the contribution of PI and EI to the degree of the correlation between canonical variables for X and Z sets were unfavourable. In conclusion, the effect of body weight at sexual maturity upon the availability of nutrients can have a higher contribution to variation of egg production in pullets if the contribution of differences in nutrient intakes to onset of egg production were eliminated.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.63-68
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• 2005

Transcription factors regulate gene expression by binding to gene upstream region. Each transcription factor has the specific binding site in promoter region. So the analysis of gene upstream sequence is necessary for understanding regulatory mechanism of genes, under a plausible idea that assumption that DNA sequence motif profiles are closely related to gene expression behaviors of the corresponding genes. Here, we present an effective approach to the analysis of the relation between gene expression profiles and gene upstream sequences on the basis of kernel canonical correlation analysis (kernel CCA). Kernel CCA is a useful method for finding relationships underlying between two different data sets. In the application to a yeast cell cycle data set, it is shown that gene upstream sequence profile is closely related to gene expression patterns in terms of canonical correlation scores. By the further analysis of the contributing values or weights of sequence motifs in the construction of a pair of sequence motif profiles and expression profiles, we show that the proposed method can identify significant DNA sequence motifs involved with some specific gene expression patterns, including some well known motifs and those putative, in the process of the yeast cell cycle.

• Journal of Technology Innovation
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• v.15 no.2
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• pp.83-102
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• 2007

This study extends the existing method of Technology Forecasting with Data Envelopment Analysis (TFDEA) by incorporating a ranking method into the model so that we can reduce the required number of DMUs (Decision Making Units). TFDEA estimates technological rate of change with the set of observations identified by DEA(Data Envelopment Analysis) model. It uses an excessive number of efficient DMUs(Decision Making Units), when the number of inputs and outputs is large compare to the number of observations. Hence, we investigated the possibility of incorporating CCCA(Constrained Canonical Correlation Analysis) into TFDEA so that the ranking of DMUs can be made. Using the ranks developed by CCCA(Constrained Canonical Correlation Analysis), we could limit the number of efficient DMUs that are to be used in the technology forecasting process. The proposed hybrid model could establish technology frontiers with the efficient DMUs for each generation of technology with the help of CCCA that uses the common weights. We applied our hybrid model to forecast the technological progress of main battle tank in order to demonstrate its forecasting capability with practical application. It was found that our hybrid model generated statistically more reliable forecasting results than both TFDEA and the regression model.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.117-123
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• 2006

Recently with the development of 3D modeling and digitizing tools, more and more models have been created, which leads to the necessity of the technique of 3D mode retrieval system. In this paper we investigate a new method for 3D model retrieval based on orthogonal projections. We assume that 3D models are composed of trigonal meshes. Algorithms process first by a normalization step in which the 3D models are transformed into the canonical coordinates. Then each model is orthogonally projected onto six surfaces of the projected cube which contains it. A following step is feature extraction of the projected images which is done by Moment Invariants and Polar Radius Fourier Transform. The feature vector of each 3D model is composed of the features extracted from projected images with different weights. Our System validates that this means can distinguish 3D models effectively. Experiments show that our method performs quit well.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.3
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• pp.10-17
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• 1995

this thesis proposes a new echo canceller that can be used in a fulll-duplex digital subscriber loopmodem. The modem suffers from nonlinear distortion such as transmitted pulse asymmetry, saturation in transformers, and nonlinearity of data converters. The proposed nonlinear echo canceller can compensate the nolinear distortion by using a nonlinear digital filter based on canonical pieceewise-linear (CPWL) function. Numerical results based on computer simulation are given in this paper. It is shown that the convergence characteristics depend on the initial values of weights of linear filters with absoluters and that the nonlinearity in digital-to-analog(D/A) converter can be compensated by a relatively small number linear filters with absoluters. It is also shown that the proposed algorithm has a faster convergence rate in comparison with Voterra algorithm.

• Journal of the Korean Wood Science and Technology
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• v.48 no.4
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• pp.548-561
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• 2020

Paecilomyces japonica is widely cultured to produce mycelium for medicinal and health food use. Illumination is an important factor in the growth and production of mycelium in submerged culture. The effects of different light-emitting diode (LED) combinations on the growth and cordycepin content as bioactive substances of mycelium were investigated. The results showed that the mycelium dry weights were lower under dark condition and red LED treatments. Dark condition, fluorescent light, and ultraviolet-A failed to increase the cordycepin content. Blue light was necessary to increase the cordycepin content, and a red-to-blue ratio of 3:7 induced the highest cordycepin content. The cordycepin contents of mycelium in submerged culture were significantly higher in a 12 h/day illumination time under red and blue (red-to-blue ratio of 3:7) LED treatments, showing an increase of up to 38% compared with those under the fluorescent-light control condition. The results demonstrated the roles of light with different wavelengths on the biosynthesis of cordycepin as bioactive substances. The low-heat release and replacement of traditional fluorescent lights with low-energy-consuming LEDs could increase the contents of bioactive substances. After optimization of the cordycepin production using response surface methodology (Box-Behnken design) to its canonical form, the optimum combination was found to be as follows: illumination time = 17.7 h/day, sugar content in the medium = 9.7 g/50 mL, and incubation time = 61.2 h. The model predicted a maximum response of 3779.2 ㎍/mL cordycepin yield.