• Journal of Food Hygiene and Safety
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• v.15 no.3
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• pp.252-255
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• 2000

This study was conducted to investigate the application of ATP bioluminescence to measure the degree of microbial contamination from raw meat, meat processing and milk processing lines. Samples collected from slaughter house, meat and milk processing plants were tested for estimation of bacterial number by using ATP bioluminescence and conventional method. The former result was transffered to R-mATP value(log RLU/ml), and the latter transffered to CFU(log/ml). Correlation coefficient(r) between aerobic counts(CFU, log/ml) and R-mATP(log RLU/ml) value was 0.93(n=408). R-mATP of aerobic counts from beef, pork, chicken was 0.93(n=220), and that was 0.93(n=187) between meat processing and dairy processing plants. In addition, Correlation coefficient(r) between aerobic counts and R-mATP was 0.87(n=252) under 1$\times$10${^5}$/ml of bacterial count and 0.74(n=152) over 10${^5}$ respectively.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.123-129
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• 2000

This paper addresses a new double detection algorithm which is based on the fuzzy control in the adaptive echo canceller of communication system. In this method, the two input of the fuzzy inference for detecting double talk condition are used. The one is the cross-correlation coefficient between the error signal and the primary signal which is the summed signal of the real echo signal and the near-end signal. The other is the cross-correlation coefficient between the estimation error signal and the primary signal. The fuzzy controller made a fuzzification for two inputs by the membership functions of trapezoid and them became the composition using inference rules. The composed result is defuzzificated by the center gravity method. The output is compared with two threshold values to detect double talk and echo path variation effectively. It is confirmed by computer simulation that this fuzzy double talk detector is able to track echo path variation accurately.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.59-66
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• 2006

This study was to construct the linear density predictive models on the on-ramp junctions in urban freeway. From the analyses of the real-time traffic characteristic data, and the construction and verification of the linear density predictive models, the models showed a considerable explanatory power with the determination coefficients ($R^2$) of over 0.7 between the density and speed data. Also, they showed a considerably high correlativeness with the correlation coefficients (r) of over 0.8 between the calculated density data and the expected ones estimated by the models.

• Journal of Life Science
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• v.8 no.5
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• pp.557-562
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• 1998

This study was conducted to investigate the influence of soil moisture on the photosynthetic rate, transpiration rate, stomatal conductance, leaf water content and its any correlation in soybean. Followings were achieved as a conclusion. At the soil moisture was moved from drought condition to saturation condition, the photosynthetic rate, transpiration rate, stomatal conductance and leaf water content were gradually increased on the period of re-watering treatment. The recovery of photosynthetic rate was faster than others. There were positive correlation with the photosynthetic rate and leaf water content, the stomatal conductance and leaf water content, the photosynthetic rate and stomatal conductance respectively, but the correlation coefficient of photosynthetic rate and leaf water content was high.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.604-610
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• 2000

A stereo acoustic echo canceller has significant cross-correlation between each channel signal. As the result, the adaptive filter coefficient that estimates the acoustic echo path of a receiving room can misconverge to the path or converge slowly. In this paper, a new preprocessor using absolute difference in stereo signals is proposed to reduce cross-correlations and to improve the removal efficiency of the stereo acoustic echo. Compared to the previous preprocessor using a half wave rectifier, the newly proposed preprocessor showed better performance according to computer simulation. In addition, when the paths of transmitting room were changed the performance of the proposed preprocessor was not degraded.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.4
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• pp.335-345
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• 2008

In this study, we suggest a stochastic finite element scheme for the probabilistic analysis of the composite laminated plates, which have been applied to variety of mechanical structures due to their high strength to weight ratios. The applied concept in the formulation is the weighted integral method, which has been shown to give the most accurate results among others. We take into account the elastic modulus and in-plane shear modulus as random. For individual random parameters, independent stochastic field functions are assumed, and the effect of these random parameters on the response are estimated based on the exponentially varying auto- and cross-correlation functions. Based on example analyses, we suggest that composite plates show a less coefficient of variation than plates of isotropic and orthotropic materials. For the validation of the proposed scheme, Monte Carlo analysis is also performed, and the results are compared with each other.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.12 no.2
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• pp.225-236
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• 2001

Introduction：Test anxiety is a pervasive problem among high school students in Korea. While anxiety in test situations may actually facilitate the performance of some students, more often it is disruptive and leads to performance decrements. Over the past years, many child psychiatrists have become concerned with understanding the nature of test anxiety, but it is not clearly understood yet. In order to understand the nature of test anxiety, the relationship between test anxiety and depression, state anxiety, trait anxiety was examined. In addition, the relationships between the subscores of test anxiety (worry and emotionality) and the subscores of CDI, state anxiety or trait anxiety were examined. Methods：The Test Anxiety Inventory, Chidlren's Depression Inventory, State-Trait Anxiety Inventory were administered to 425 high school students in Seoul. The relationships between test anxiety and other measures were tested using Pearson correlation coefficients and to test the causal ralationship among the variables, regression analysis was performed. Results：The correlation coefficients between test anxiety and depression, state anxiety, trait anxiety were 0.56(p<0.05), 0.75(p<0.05), 0.53(p<0.05) respectively. The correlation coefficients between subscales of test anxiety and depression were all significant. The correlation between subscales of test anxiety and state and trait anxiety were also statistically significant. Conclusions：This study indicates that test anxiety is closely related with depression, state and trait anxiety. In addition, the subscales of test anxiety are significantly related with those of the depression. The correlation coefficients between test anxiety and state-trait anxiety are also statistically significant. Thus, in order to develop the preventive and effective methods for treatment, these psychopathological characteristics should be kept in mind.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.2
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• pp.118-128
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• 1999

There are many ultrasonic measurement methods that are used in nondestructive testing applications. Some typical applications include material property determination, microstructural characterization. and flaw detection. Ultrasonic parameters such as velocity and attenuation are most commonly required in these applications. The accuracy and repeatability of testing results are dependent on both the hardware used to generate and receive the ultrasonic waves and on the analysis software for calculating these parameters. In this study, five analysis algorithms were implemented on a computer for measuring wave speed in a pulse echo. immersion testing configuration. In velocity measurements comparisons were made between the overlap. cross-correlation. Fourier transform. Hilbert transform, wavelet transform algorithms. Velocity measurement was applied to an isotropic steel sample using the five analysis algorithms. Frequency-dependent phase/group velocity and attenuation were also measured using the Fourier transform and wavelet transform algorithms on a composite laminate containing voids.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.504-511
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• 2014

This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.