• Nuclear Engineering and Technology
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• v.32 no.5
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• pp.521-529
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• 2000

A modified interfacial heat transfer correlation between a dispersed water droplet and ambient superheated steam is proposed and compared with available experimental data and other correlations. Modified one overcomes the inherent deficiencies of Lee and Ryley's interfacial heat transfer correlation that ignored the effects of steam superheating which can not be neglected especially in the reflood situation of a loss-of-coolant accident. Modified one is represented by (equation omitted) In the present correlation the effect of possible subcooling of a water droplet is not taken into consideration. Comparison of the above correlation with currently available measurement data for a water droplet in high temperature gas flow shows that the proposed one correlates well with the measurement data where the degree of superheating is negligible and considerable.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Proceedings of the KSEEG Conference
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• 2000.04b
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• pp.311-313
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• 2000

Identifying anomaly correlations between data sets is the basis for rationalizing geopotenial interpretation and theory. A procedure between the two or more geopotential data sets. Anomaly features that show direct, inverse, or no correlationsbetween the data may be separated by applying filters in the frequency domains of the data sets. The correlation filter passes or rejects wavenumbers between co-registered data sets based on the correlation coefficient between common wavenumbers as given by the cosine of their phase difference. This study includes as example of Magsat magnetic anomaly profile that illustrates the usefulness of the procedure for extracting correlative features between the sets.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.1-6
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• 2008

Precipitation and groundwater level data sets from Kum river watershed were analyzed and compared. The correlation between groundwater level and the moving average of precipitation was analyzed. Moving averaging technique is stochastic method and that was used to consider the effect of precipitation events on groundwater level fluctuation. Groundwater level generally follows seasonal precipitation pattern and low level occurs from early December to late April. Relatively high groundwater level is appeared in wet spell (July and August). The correlation between groundwater level and the moving average of precipitation to consider precedent precipitation events was analyzed with minimum two-year data sets. When the precipitation and groundwater level data set pair was selected the precipitation gauge station is closely located to groundwater level gauge station in the upstream direction to minimize the non-homogeneous precipitation distribution effect. The maximum correlation was occurred when the averaging periods were from 10 days to 150 days with Kum river watershed data. The correlation coefficients are influenced by data quality, missing data periods, or snow melt effect, etc. The maximum coefficient was 0.8886 for Kum river watershed data.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.281-286
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• 2005

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.39-48
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• 2017

In order to verify the effectiveness of marketing in the basketball stadium, this study measured and analyzed the gaze frequency and interest when the pupil was expanded by using the eye-tracking technology among various neuro marketing techniques of marketing. To analyze the section where the pupil size get expanded, interval of pupil size was higher than 2.275% (2 sigma data) and higher than 0.135% high (3 sigma data). Overall the valid data was analyzed by inflection points according to gaze frequency. We also analyzed the correlation between overall valid data and the ranges where the pupil size was significantly increased. The result showed that the correlation between overall valid data and pupil size 2 sigma data showed the highest correlation with 0.805. The pupil size 2 sigma data and pupil size 3 sigma data showed a correlation with 0.781, overall the valid data and pupil size 2 sigma data showed a correlation with 0.683. Therefore, it is concluded that, the section where the pupil size was expanded and the section at which gaze frequency is higher in the eye-tracking data were similar. However, the correlation between data of pupil size is determined to be significantly expanded and overall the valid data is decreased.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.2
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• pp.247-252
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• 2006

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn until signal is growing to abnormal state that the signal is over or under the set point. therefore cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without any additional sensors. By analyzing the data with high correlation coefficient(CC), correlation level of interactive data can be defined. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC. FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.1007-1016
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• 2011

This article deals with the problem of testing for the correlation coefficient in the bivariate normal distribution. We propose Bayesian hypothesis testing procedures for the bivariate normal correlation coefficient under the noninformative prior. The noninformative priors are usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. A simulation study and an example are provided.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.445-452
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• 2008

Preliminary results are reported on ship detection using coherence images computed from cross-correlating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, cross-correlation of multi-look images yields the different degrees of coherence between the images and water. In this paper, the polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV images, In the next step, we examine the technique when the dual-polarization data are split into two multi-look images, It was shown that the inter-look cross-correlation method could be applicable in the performance improvement of small ship detection and the land masking, It was also found that a simple combination of coherence images from each co-polarised (HH) inter-look and cross-polarised (HV) inter-look data can provide much higher target-detection possibilities.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.83-89
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• 2000

This paper presents a pressure drop correlation for evaporation and condensation of alternative refrigerant with oil in micro-fin tubes. The correlation was developed from a data base consisting of oil-free pure and mixed refrigerants in micro-fin tube; Rl25 R134a. R32 R410a(R32/R125 50/50% mass), R22, R407c(R32/R125/R134a, 23/25/52% mass) and R32/R134a(25/75% mass). The micro-fin tube used in this paper had 60 0.2mm high fins with a 18 helix angle. The cross sectional flow area $(A_c)$ was $60.8 mm^2$ giving an equivalent smooth diameter$(D_e)$ of 8.8mm. The hydraulic diameter $(D_h)$ was estimated to the 5.45mm. The new correlation was obtained by replacing the friction factor and the tube-diameter in Bo Pierre correlation by a friction factor derived from pressure drop data for a micro-fin tube and the hydraulic diameter, respectively. This correlation was also used to predict some pressure data with a lubricant after using a mixing viscosity rule of lubricants and refrigerants. As a result, the new correlation was also well predicted to the measured data within a mean deviation of 19.0%.