• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4865-4875
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• 2013

This study is to examine that there are differences in Holland personality types and talent of elementary school students depending on cerebral hemisphere and their relationship. The study is targeted 679 elementary school students. To examined the hypothesis, frequency analysis, t-test, correlation analysis, using SPSS 18.0 were conducted. First, The elementary school students, artistic and enterprising types appeared more evident in the right-brain than left-brain. Second, there are positively conspicuous differences between RIC group and SAE group in left-brain. Third, in comparison with cerebral hemisphere and talent of elementary school students, creative, nature, communicative and body appeared more evident in the right-brain. Fourth, there are positive relationships in Holland personality types, cerebral hemisphere, and talent. However, there is no relationship between left-brain and artistic type, right-brain and social type.

• Journal of Physiology & Pathology in Korean Medicine
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• v.26 no.1
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• pp.128-132
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• 2012

In this paper, we performed a quantitative analysis of face color according to the health status of four constitution types. 205 Korean male in age from 65 to 80 were participated in this study and 85 subjects were finally selected for the analysis. Imaging process techniques were employed to extract feature variables associated with face color from a frontal facial image. Using the extracted feature variables, the correlations between face color and health status, face color and health status in each constitution type, and face color and four constitution types in heath status group were investigated. As the result, it was observed that the face color of healthy group contained more red component and less blue component than unhealthy group. For each constitution type, the face parts showing a significant difference according to health status were different. This is the first work which reports the correlation between the face color and health status of four constitution types with a objective method, and the numerical data for the face color according to the health status of four constitution types will be an objective standard to diagnose a patient's health status.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1078-1099
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• 2021

Traditional image steganography hides secret information by embedding, which inevitably leaves modification traces and is easy to be detected by steganography analysis tools. Since coverless steganography can effectively resist steganalysis, it has become a hotspot in information hiding research recently. Most coverless image steganography (CIS) methods are based on mapping rules, which not only exposes the vulnerability to geometric attacks, but also are less secure due to the revelation of mapping rules. To address the above issues, we introduced camouflage images for steganography instead of directly sending stego-image, which further improves the security performance and information hiding ability of steganography scheme. In particular, based on the different sub-features of stego-image and potential camouflage images, we try to find a larger similarity between them so as to achieve the reversible steganography. Specifically, based on the existing CIS mapping algorithm, we first can establish the correlation between stego-image and secret information and then transmit the camouflage images, which are obtained by reversible sub-feature retrieval algorithm. The received camouflage image can be used to reverse retrieve the stego-image in a public image database. Finally, we can use the same mapping rules to restore secret information. Extensive experimental results demonstrate the better robustness and security of the proposed approach in comparison to state-of-art CIS methods, especially in the robustness of geometric attacks.

• Genomics & Informatics
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• v.19 no.4
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• pp.40.1-40.11
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• 2021

Mutation signatures represent unique sequence footprints of somatic mutations resulting from specific DNA mutagenic and repair processes. However, their causal associations and the potential utility for genome research remain largely unknown. In this study, we performed PanCancer-scale correlative analyses to identify the genomic features associated with tumor mutation burdens (TMB) and individual mutation signatures. We observed that TMB was correlated with tumor purity, ploidy, and the level of aneuploidy, as well as with the expression of cell proliferation-related genes representing genomic covariates in evaluating TMB. Correlative analyses of mutation signature levels with genes belonging to specific DNA damage-repair processes revealed that deficiencies of NHEJ1 and ALKBH3 may contribute to mutations in the settings of APOBEC cytidine deaminase activation and DNA mismatch repair deficiency, respectively. We further employed a strategy to identify feature-driven, de novo mutation signatures and demonstrated that mutation signatures can be reconstructed using known causal features. Using the strategy, we further identified tumor hypoxia-related mutation signatures similar to the APOBEC-related mutation signatures, suggesting that APOBEC activity mediates hypoxia-related mutational consequences in cancer genomes. Our study advances the mechanistic insights into the TMB and signature-based DNA mutagenic and repair processes in cancer genomes. We also propose that feature-driven mutation signature analysis can further extend the categories of cancer-relevant mutation signatures and their causal relationships.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.74-80
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• 2021

Cells regulate their shapes and motility by sensing the cues from the internal and external microenvironment. Under different circumstances, microglia, the brain resident immune cells, undergo dynamic phenotypic changes, one of which is a remarkable periodic oscillatory migration in vitro. However, very little is known about the kinematic and dynamic perspectives of this oscillatory behavior. In this study, we tracked the changes in cell morphology and nuclear displacement, and visualized the forces using traction force microscopy (TFM). By correlation analyses, we confirmed that the lamellipodia formation preceded the nuclear translocation. Moreover, traction, developed following lamellipodia formation, was found to be localized and fluctuated at two ends of the oscillating cells. Taken together, our results imply that oscillatory microglial cells feature a viscoelastic migration, which will contribute to the field of cell mechanics.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1345-1354
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• 2020

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement in clinical use. Materials and Methods: PubMed MEDLINE and EMBASE were searched using the terms 'cognitive impairment' or 'Alzheimer' or 'dementia' and 'radiomic' or 'texture' or 'radiogenomic' for articles published until March 2020. From 258 articles, 26 relevant original research articles were selected. Two neuroradiologists assessed the quality of the methodology according to the RQS. Adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Results: The hippocampus was the most frequently analyzed (46.2%) anatomical structure. Of the 26 studies, 16 (61.5%) used an open source database (14 from Alzheimer's Disease Neuroimaging Initiative and 2 from Open Access Series of Imaging Studies). The mean RQS was 3.6 out of 36 (9.9%), and the basic adherence rate was 27.6%. Only one study (3.8%) performed external validation. The adherence rate was relatively high for reporting the imaging protocol (96.2%), multiple segmentation (76.9%), discrimination statistics (69.2%), and open science and data (65.4%) but low for conducting test-retest analysis (7.7%) and biologic correlation (3.8%). None of the studies stated potential clinical utility, conducted a phantom study, performed cut-off analysis or calibration statistics, was a prospective study, or conducted cost-effectiveness analysis, resulting in a low level of evidence. Conclusion: The quality of radiomics reporting in MCI and AD studies is suboptimal. Validation is necessary using external dataset, and improvements need to be made to feature reproducibility, feature selection, clinical utility, model performance index, and pursuits of a higher level of evidence.

• Ocean and Polar Research
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• v.23 no.4
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• pp.361-376
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• 2001

The characteristics of SST variability in the East Sea are analyzed using NOAA/AVHRR weekly SST data with about $0.18^{\circ}{\times}0.18^{\circ}$ resolution ($1981{\sim}2000$) and reconstructed historical monthly SST data with $2^{\circ}{\times}2^{\circ}$ resolution $(1950{\sim}1998)$. The distinct feature of wintertime SST is high variability in the western and eastern parts of $38^{\circ}{\sim}40^{\circ}$ latitudinal band, which are the northern boundary of warm current in the East Sea during winter. However, summertime SST exhibits variability with similar magnitude in the entire region of the East Sea. The analysis of remote correlation also shows that SST in the East Sea is closely correlated with that in the region of Kuroshio in winter, but in summer is related with that in the western and eastern regions of the same latitudes. From these results it is postulated that the SST variability in the East Sea may be related with the variations of East Korean Warm Current and Tsushima Warm Current in winter, but in summer probably with the variations of atmospheric components. In the analysis of ENSO related SST anomaly, a significant negative correlation between SST anomalies in the East Sea and SST anomalies in the tropical Pacific is found in the months of August-October (ASO). The SST in the ASO period shows more significant cooling in E1 $Ni\~{n}o$ events than warming in La $Ni\~{n}a$ events. Also, the regional analysis shows by the Student's t-test that the negative SST anomalies in the E1 $Ni\~{n}o$ events are more significant in the southwestern part of the East Sea.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.100-106
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• 2017

Sound quality engineering in automobile noise applications has become more and more important under the current quiet driving condition because various noise components masked under high noise level can be audible in quieter driving situation. Many researches have been carried out for subjective and objective assessments on automobile sounds and noises. In particular, the interior sound quality has been one of research fields that can give high-quality feature to automobile products. Although many works related to the interior sound quality have been progressed or completed in foreign countries, limited research results are presented in the country. In the study, subjective assessments are first performed with 20 subjects to select perceptual adjectives suitable to the assessment of car interior noises during acceleration. The selected perceptual adjectives are employed as the assessment scales to evaluate the acceleration noises in questionnaire procedures using 35 subjects, for which several noises are created through digital filtering of the acceleration noises measured. Mean values and standard deviations for subjective assessment scores obtained by the questionnaire procedures are calculated and their reliability are also verified. Finally, various statistical analyses such as the correlation analysis and the factor analysis are carried out to reveal the interrelationship between the assessment scales and the spectrum components of the acceleration noises.

• Journal of Distribution Science
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• v.20 no.2
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• pp.101-108
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• 2022

Purpose: In this logistics disturbance period, this study conducts research of distribution and logistics firms in Korea. The purpose of this exploratory research is to analyze global competitive capability influence on business performance. And give managerial implications and contribute to academics. Research design, data, and methodology: This research empirically analyzes the relationship between global competitive capability and business performance. As for business performance this research considered non-financial performance and measured with business performance fulfillment. As for antecedent variables, this research measured three global competitive capability constructs; preparation, utilization, intensive capability. And each construct includes two capability concepts. This study used 2,316 executing direct export distribution and logistics industry firmsfrom KOTRA's GCL data. This research used frequency analysis, reliability analysis, correlation analysis, and step-wise regression analysis by SPSS26. Results: The result shows that all the variables except export infra showed statistically significant. As results show, mid/long strategy & global mind of preparation capability, both communication and marketing of utilization capability and market strategy and product/goods/service of intensive capability give a positive influence on business performance fulfillment. Conclusions: Based on the results, this research provide implication for practical management, contribution to academic, and suggestion for feature research.