• Journal of Physiology & Pathology in Korean Medicine
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• v.29 no.2
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• pp.160-167
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• 2015

The purpose of this study was to investigate the correlation of Intima-Media Thickness of common carotid artery(CCA-IMT) and The Second Derivative of Photoplethysmogram Waveforms(SDPTG). 38 subjects with acute ischemic stroke were recruited from the patients admitted to Dong-Eui Medical Center from the June 2013 to January 2014. We assessed 38 patient's SDPTG data and CCA-IMT data by B Mode ultrasonography. then 38 subjects were divided into two groups by the CCA-IMT difference; CCA-IMT 〈 0.8 mm group(n=11), CCA-IMT $$\geq_-$$ 0.8 mm group(n=27). We analyzed their characteristics, risk factor, blood test result, life style by CCA-IMT difference. As a result, Age, Hypertension were significantly higher in the CCA-IMT $$\geq_-$$ 0.8 mm group then in the CCA-IMT < 0.8 mm group. Regular exercise were significantly higher in the CCA-IMT < 0.8 mm group then in the CCA-IMT $$\geq_-$$ 0.8 mm group. The result of Multiple regression analysis on the factors affecting the CCA-IMT was hypertension, total cholesterol, age. and The result of Pearson's Correlation analysis on CCA-IMT and SDPTG is that e/a ratio, SDPTG AI were respectively and significantly correlated with CCA-IMT. According to the analysis, the Relationship between CCA-IMT and SDPTG in Ischemic Stroke Patients were founded. We suggest that further investigation with larger and better controlled trials of the Relationship between CCA-IMT and SDPTG could contribute to better understand the effects of risk factors on atherosclerosis.

• Journal of the Korean Wood Science and Technology
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• v.23 no.3
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• pp.66-72
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• 1995

The rate of fixation of the components were evaluated in CCA-Type B and CCFZ-treated radiata pine sapwood by quantitative analysis of solution expressed from the treated wood. The leaching characteristics of radiata pine blocks treated with CCA-Type B and CCFZ were also evaluated by the AWPA standard leaching test. Both fixation and leaching charactersistics of CCA-Type B were compared with CCA-Type C treated wood samples. The rate of CCA-Type B fixation was a little faster than that of CCFZ. However, significant amounts of arsenic was unfixed in the CCA-Type B treated samples and consequently leached. These significant quantities of arsenic liberated from the CCA-Type B treated wood during service may pose some environmental concerns. Arsenic was no longer detectable from CCA-Type C treated samples when fixation was complete, even though the fixation of CCA-Type C was slower in some degree than CCA-Type B. In summary, it could be said that CCFZ was much safer preservative than CCA-Type B by the criterion based on the relative hazard assessed by absolute amount of unfixed element present in the treated wood. Also the decision that CCA preservative has to move from Type B to Type C should be made sooner or later for continuous use of CCA preservative in the future.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.139-147
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• 2015

Steady state visual evoked potential (SSVEP) has been actively studied because of its short training time, relatively higher signal-to-noise ratio, and higher information transfer rate. There are two popular analysis methods for SSVEP signals: power spectral density analysis (PSDA) and canonical correlation analysis (CCA). However, the PSDA is known to be vulnerable to noise due to the use of a single channel. Although conventional CCA is more accurate than PSDA, it may not be appropriate for the real-time SSVEP-based BCI system when it has short time window length because it uses sinusoidal signals as references. Therefore, the two methods are not efficient for the real-time BCI system that requires a short TW and a high recognition accuracy. To overcome this limitation of the conventional methods, this paper proposes a frequency recognition method with a combination of CCA and PSDA using the difference between powers of canonical variables obtained from the results of CCA. Experimental results show that the performance of the combination of CCA and PSDA is better than that of CCA for the case of a short TW.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.8
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• pp.1404-1422
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• 2011

In this paper, a new clear channel assessment (CCA) method: cascaded-CCA, is proposed. The primary motivation for the proposed approach is to integrate the respective advantages of two standard CCA mechanisms, energy detect and preamble detect, to arrive at a new dual threshold CCA family that can provide greater flexibility towards tuning MAC performance. Cascaded-CCA integrates energy efficiency of the energy detector (ED) and the reliability of the preamble detector (PD). The probability of detection/false alarm and power consumption of cascaded-CCA in the CCA modules of IEEE 802.11b are analyzed and compared with ED and PD as an example. The performance of cascaded-CCA is explored via MATLAB simulations that implement the CCA modules and medium access control (MAC) protocol for IEEE 802.11 and IEEE 802.15.4. Simulation results showed that cascaded-CCA improves the energy efficiency significantly compared to ED-only or PD-only CCA. In addition, ED, PD, and cascaded CCA are applied to a cognitive network scenario to validate the effectiveness of the proposed cascaded-CCA.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.157-176
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• 2024

Integrative analysis for better understanding of complex biological systems gains more attention. Observing subjects from various perspectives and conducting integrative analysis of those multiple datasets enables a deeper understanding of the subject. In this paper, we compared two methods that simultaneously consider two datasets gathered from the same objects, canonical correlation analysis (CCA) and co-inertia analysis (CIA). Since CCA cannot handle the case when the data exhibit high-dimensionality, two strategies were considered instead: Utilization of a ridge constant (CCA-ridge) and substitution of covariance matrices of each data to identity matrix and then applying penalized singular value decomposition (CCA-PMD). To illustrate CIA and CCA, both extensions of CCA and CIA were applied to NCI60 cell line data. It is shown that both methods yield biologically meaningful and significant results by identifying important genes that enhance our comprehension of the data. Their results shows some dissimilarities arisen from the different criteria used to measure the relationship between two sets of data in each method. Additionally, CIA exhibits variations dependent on the weight matrices employed.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.393-406
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• 2009

This paper introduces two functions added to the current version of ns-2 simulator for better accuracy of IEEE 802.15.4 network simulations. The first one is to automatically place hidden nodes over the ring topology in which the coordinator is centered, when the number of hidden nodes and total number of nodes is given. Collisions of signals can be distinguished into the trace file according to the ways of participation of hidden nodes. The second one is the CCA deferment algorithm described in IEEE 802.15.4-2006 standard which is not implemented in the current version of ns-2. Owing to these additional functions, we can carry out the precise analysis of the performance effects of hidden nodes and CCA deferment algorithm on 802.15.4 networks. Simulation results present at least 66% of performance degradation in throughput and drastic increase of collision probability up to 90% from 65% by just a single hidden node. Besides, 2006 standard for CCA deferment algorithm gives 19% lower collision probability and 38% higher performance.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1139-1149
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• 2014

Multivariate volatility is summarized through canonical correlation analysis (CCA). Along with the standard CCA, non-negative and sparse canonical correlation analysis (NSCCA) is introduced to make sure that volatility coefficients are non-negative and the number of coefficients in the volatility CCA is as small as possible. Various multivariate financial time series are analyzed to illustrate the main contribution of the paper.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.2
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• pp.151-157
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• 2023

Backgrounds/Aims: Cholangiocarcinoma (CCA) can be classified as intrahepatic CCA or extrahepatic CCA (eCCA). We intended to analyze and reports the survival outcomes for eCCA. Methods: Surveillance, epidemiology, and end results (SEER) registry, site recode C24.0, was used to select cases of eCCA from 2000 to 2018. Patients with incomplete data or ages <18 years were excluded. Results: Male (52.69%) and White race (77.99%) predominated. Compared with 2000-2006, survival increased in 2013 (adjusted hazard ratio [HRadj]: 0.68, 95% confidence interval [CI] 0.58-0.70; p < 0.01). Surgery with chemoradiotherapy (HRadj: 0.69, 95% CI 0.60-0.7; p < 0.01) and surgery with chemotherapy (HRadj: 0.72, 95% CI 0.62-0.83; p < 0.01) improved survival over surgery alone. Compared with surgery without lymph node (LN) removal, surgery of four or more regional LN reduced the risk of death by 58% (HRadj: 0.42, 95% CI 0.36-0.51; p < 0.01). Compared with patients without surgery, patients who underwent bile duct excision (HRadj: 0.82, 95% CI 0.72-0.94; p < 0.01), simple or extended lobectomy (HRadj: 0.85, 95% CI 0.75-0.95; p = 0.009), and hepatectomy (HRadj: 0.80, 95% CI 0.72-0.88; p < 0.01) significantly improved survival. Patients with distal CCA had a 17% higher survival than perihilar CCA (HRadj: 0.83, 95% CI 0.74-0.92; p < 0.01) and LN dissection was equally beneficial for both subgroups (p < 0.01). Conclusions: Surgery with chemoradiotherapy has a proven increase in the 5-year survival of the eCCA. LN resection, bile duct excision, lobectomy, and hepatectomy have better outcomes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.105-110
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• 2012

The CCA (canonical correlation analysis) is a well known analysis tool that measures the linear relationship between two variable sets and it can be used for blind source separation (BSS). In previous works, a blind source separation scheme based on the CCA and auto regression was proposed. Unfortunately, the proposed scheme requires high signal-to-noise ratio for successful source separation. In this paper, we propose an improved BSS scheme based on the CCA and auto regression by eliminating the main diagonal elements of auto covariance matrix. Compared to the previously proposed BSS scheme, the proposed BSS scheme not only offers better source separation performance but also requires low computational complexity.

• The Journal of the Acoustical Society of Korea
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• v.36 no.4
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• pp.279-284
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• 2017

The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.