• Investigative Magnetic Resonance Imaging
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• v.21 no.3
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• pp.171-176
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• 2017

Purpose: To compare different MR sequences for quantification of gadolinium concentration. Materials and Methods: Gadolinium contrast agents were diluted into 36 different concentrations. They were scanned using gradient echo (GRE) and ultrashort echo time (UTE) and R1, $R2^*$ and phase values were estimated from collected data. For analysis, ROI masks were made for each concentration and then ROI value was measured by mean and standard deviation from the estimated quantitative maps. Correlation analysis was performed and correlation coefficient was calculated. Results: Using GRE sequence, R1 showed a strong linear correlation at concentrations of 10 mM or less, and $R2^*$ showed a strong linear correlation between 10 to 100 mM. The phase of GRE generally exhibited a negative linear relationship for concentrations of 100 mM or less. In the case of UTE, the phase had a strong negative linear relationship at concentrations 100 mM or above. Conclusion: R1, which was calculated by conventional GRE, showed a high performance of quantification for lower concentrations, with a correlation coefficient of 0.966 (10 mM or less). $R2^*$ showed stronger potential for higher concentrations with a correlation coefficient of 0.984 (10 to 100 mM), and UTE phase showed potential for even higher concentrations with a correlation coefficient of 0.992 (100 mM or above).

• Journal of Korean Medicine Rehabilitation
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• v.27 no.4
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• pp.121-130
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• 2017

Objectives This study was designed to investigate the correlation between the gait analysis indices and Lumbar X-ray indicators. Methods 21 cases of patients who received treatment from October 2013 to February 2017 for abnormal posture were analyzed. Three indicators were measured in the lumbar spine X-ray. These indicators include Ferguson's angle, Lumbar lordotic angle, L4-5 IVD angle. Gait analysis indices were estimated by Treadmill Gait Analysis system. The data were analyzed to find out correlation between the gait analysis indices and Lumbar X-ray indicators. Spearman correlation was used. Results Ferguson's angle and Difference of gait balance of front and rear had a negative linear relationship, but there was no statistical significance. Lumbar lordotic angle and Difference of gait balance of front and rear had a negative linear relationship, but there was no statistical significance. L4-5 IVD angle and Difference of gait balance of right and left had a negative linear relationship, but there was no statistical significance. Conclusions Difference of gait balance of front and rear had strong level of a negative linear relationship with Ferguson's angle and Lumbar lordotic angle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.760-763
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• 2007

We studied how linear and nonlinear heart rate dynamics differ between normal fetuses and uncomplicated small-forgestational age (SGA) fetuses, aged 32-40 weeks' gestation. We analyzed each fetal heart rate time series for 20 min and quantified the complexity (nonlinear dynamics) of each fetal heart rate (FHR) time series by approximate entropy (ApEn) and correlation dimension (CD). The linear dynamics were analyzed by canonical correlation analysis (CCA). The ApEn and CD of the uncomplicated SGA fetuses were significantly lower than that of the normal fetuses in all three gestational periods (32-34, 35-37, 38-40 weeks). Canonical correlation ensemble in SGA fetuses is slightly higher than normal ones in all three gestational periods, especially at 35-37 weeks. Irregularity and complexity of the heart rate dynamics of SGA fetuses are lower than that of normal ones. Also, canonical ensemble in SGA fetuses is higher than in normal ones, suggesting that the FHR control system has multiple complex interactions. Along with the clear difference between the two groups' non-linear chaotic dynamics in FHR patterns, we clarified the hidden subtle differences in linearity (e.g. canonical ensemble). The decrease in non-linear dynamics may contribute to the increase in linear dynamics. The present statistical methodology can be readily and routinely utilized in Obstetrics and Gynecologic fields.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.280-295
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• 2015

Block cipher ARIA was first proposed by some South Korean experts in 2003, and later, it was established as a Korean Standard block cipher algorithm by Korean Agency for Technology and Standards. In this paper, we focus on the security evaluation of ARIA block cipher against the recent zero-correlation linear cryptanalysis. In addition, Partial-sum technique and FFT (Fast Fourier Transform) technique are used to speed up the cryptanalysis, respectively. We first introduce some 4-round linear approximations of ARIA with zero-correlation, and then present some key-recovery attacks on 6/7-round ARIA-128/256 with the Partial-sum technique and FFT technique. The key-recovery attack with Partial-sum technique on 6-round ARIA-128 needs $2^{123.6}$ known plaintexts (KPs), $2^{121}$ encryptions and $2^{90.3}$ bytes memory, and the attack with FFT technique requires $2^{124.1}$ KPs, $2^{121.5}$ encryptions and $2^{90.3}$ bytes memory. Moreover, applying Partial-sum technique, we can attack 7-round ARIA-256 with $2^{124.6}$ KPs, $2^{203.5}$ encryptions and $2^{152}$ bytes memory and 7-round ARIA-256 employing FFT technique, requires $2^{124.7}$ KPs, $2^{209.5}$ encryptions and $2^{152}$ bytes memory. Our results are the first zero-correlation linear cryptanalysis results on ARIA.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.27-34
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• 2014

In this paper, we investigate the statistical correlation of the time series for temperature measured at the heat box in the automobile drying process. We show, in terms of the sample variance, that a significant non-linear correlation exists in the time series that consist of absolute temperature changes. To investigate further the non-linear correlation, we utilize the volatility, an important concept in the financial market, and induce volatility time series from absolute temperature changes. We analyze the time series of volatilities in terms of the de-trended fluctuation analysis (DFA), a method especially suitable for testing the long-range correlation of non-stationary data, from the correlation perspective. We uncover that the volatility exhibits a long-range correlation regardless of the window size. We also analyze the cross correlation between two (inlet and outlet) volatility time series to characterize any correlation between the two, and disclose the dependence of the correlation strength on the time lag. These results can contribute as important factors to the modeling of forecasting and management of the heat box's temperature.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.24.2-24.2
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• 2008

We have examined the relative contributions of representative space weather proxies (geomagnetic aa index) to global warming (Global temperature anomaly) and compared them with that of green house effect characterized CO2 content from 1868 to 2005. For this we used Hadcrut3 temperature anomaly (Ta) data, aa index taken at two anti-podal subauroral stations (Canberra Australia and hartland England), and the CO2 data come from historical ice core records. From the comparison between Ta and aa index, we found several interesting results: (1) the linear correlation coefficient between two parameters increases until 1990 and then decreases rapidly, and (2) the scattered plots between two parameters shows different patterns before and after 1990. A partial correlation of Ta and two quantities (aa, CO2) also shows that the geomagnetic effect (aa index) is dominant until about 1990 and the CO2 effect becomes much more important after then. These results imply that the green house effect become very important since at least 1990. For a further analysis, we simply assume that Ta (total) = Ta (aa) + Ta (CO2) and made a linear regression between Ta and aa index from 1868 to 1990. A linear model is then made from the linear regression between energy consumption (a proxy of CO2 effect) and Ta (total) - Ta (aa) since 1990. This linear model makes it possible to predict the temperature anomaly in 2030, about 1 degree higher than the present temperature, which is much larger than in the previous century.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.521-529
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• 2012

Simple canonical correlation biplot is a graphical method to investigate two sets of variables and observations in simple canonical correlation analysis. If we consider the set of covariate variables that linearly affects two sets of variables, we can apply the partial canonical correlation biplot in partial canonical correlation analysis that removes the linear effect of the set of covariate variables on two sets of variables. On the other hand, we consider the set of covariate variables that linearly affect one set of variables but not the other. In this case, if we apply the simple or partial canonical correlation biplot, we cannot clearly interpret other two sets of variables. Therefore, in this study, we will apply the semi-partial canonical correlation analysis of Timm (2002) and remove the linear effect of the set of covariate variables on one set of variables but not the other. And we suggest the semi-partial canonical correlation biplot for interpreting the semi-partial canonical correlation analysis. In addition, we will compare shapes and shape the variabilities of the simple, partial and semi-partial canonical correlation biplots using a procrustes analysis.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1563-1571
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• 2003

A fast response NO analyzer was applied to investigate the relation between cycle-by-cycle NO emissions and combustion chamber pressure. NO emissions were sampled at an isolated exhaust manifold of 4-stroke spark ignition engine to avoid the interference of exhaust gas from other cylinders. The linear correlation analysis was performed with collected data of NO emissions and combustion chamber pressure with respect to the various air-fuel mixture ratios and engine loads. The sampled data sets were obtained during 200 cycles at each operating condition. The results showed that there was a typical pattern in NO emissions from an exhaust port through a cycle. It was possible to set a block of crank angle in which the linear correlation coefficient between NO emissions and combustion chamber pressure was high. As the engine load increased, NO emissions were more dependent on combustion chamber pressure after TDC. It was also analyzed that the correlation between two parameters with respect to air-fuel mixture ratio tended to increase as mixture went leaner. Furthermore, this correlation coefficient for the mixture near the lean limit seemed to be kept high even though combustion was unstable.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.730-736
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• 2012

PN(Pseudo Noise) sequences play an important role in wireless communications, such as in a CDMA(code division multiple access) communication system. If there is a crash when multiple users simultaneously connected to a system, then PN sequences with low correlation help to minimize multiple access interference in such communication system. In this paper we propose a family of non-linear extended binary sequences with low cross-correlations and the family include $m$-sequence, GMW sequence, Kasami sequence and No sequence with optimal cross-correlation in terms of Welch bound. And we analyze cross-correlation of these sequences.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.1
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• pp.85-93
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• 2020

The basic information of mean sea level data of all tidal monitoring stations in Korea was reviewed, and the correlation coefficients between the stations were analyzed. Mean sea level changes expected due to global climate change effects were found to show a high correlation of more than 0.75 regardless of the distance between the stations were analyzed. The data between certain stations were found to have negative correlation and low correlation of 0.25 or less, but this was determined by the influence of small data numbers and outliers. However, since these correlations assume a linear increase and a linear relationship, the estimation results may be distorted for data with fluctuating trends that deviate from this assumption. Based on the results of the changing patterns of the MSL data, it shows that a number of the MSL data do not follow the linear trend.