• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.148-156
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• 2013

This study tried to analyse the effect of young children's sexuality, ages, temperament and emotional intelligence upon the peer competence. The subjects were 250 children from H and W childcare center in J city. Date were analysed by multiple regression analysis with SPSS. According to this research, there are three specific results. First, a general tendency of children's temperament, emotional intelligence and peer competence is related with normal distribution. The Second indicated that the peer competence was closely associated with young children's sexuality, ages, temperament and emotional intelligence. Finally the emotional intelligence was the strongest predictor for peer competence of young children and sexuality and temperament also notable variables. Therefore, according to this research, a special education program for improvement of peer competence is strongly desired.

• Journal of Korean Critical Care Nursing
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• v.11 no.2
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• pp.51-62
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• 2018

Purpose : This study aimed to provide primary data for developing a program to enhance communication competence by identifying the patient-centered communication competency level of Intensive Care Unit (ICU) nurses and the related factors. Method : Data were collected from August 28th to October 8th, 2015, from 199 ICU nurses working in 30 tertiary hospitals. The study questionnaire included items assessing the patient-centered communication competency of ICU nurses, nursing organizational culture, types of communication, the Teamwork Measurement Tool, the Perceived Nursing Work Environment tool, and the Wong & Law Emotional Intelligence Scale. The collected data were analyzed using descriptive statistics, a correlation test, and a multiple regression. Results : The ICU nurses' mean score on patient-centered communication competency was 3.97 points. The factors influencing the patient-centered communication competency level of ICU nurses were professionalism (p =.002), innovation-oriented organizational culture (p =.015), and emotional intelligence (p<.001). These variables explained 42.2% of the total variance in the patient-centered communication competency of ICU nurses. Conclusion : These findings suggest the need for developing a patient-centered communication competency improvement program that focuses on improving ICU nurses' professionalism and emotional intelligence, and facilitates the creation of an innovation-oriented organizational culture.

• Journal of Technologic Dentistry
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• v.35 no.4
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• pp.377-385
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• 2013

Purpose: This research conducted by using Department of Dental Laboratory Technology students investigates interpersonal and emotional intelligence impact on psychological happiness. Methods: Study was conducted in the Daegu-Gyeongbuk area Department of Dental Laboratory Technology students, based on 132 people who were enrolled college students. Data analysis, frequency analysis, factor analysis, reliability test, correlation analysis, multiple regression analysis was carried out and SPSS/WIN 18.0 was used. Results: Interpersonal factors utilize emotions, emotional self-control and emotional awareness. Others turned positive (+) was found to affect the psychological, emotional factors utilized in euphoria, emotional adjustment and were found to have positive effects. Conclusion: Looking at the above results gathered from dental engineering students, improvement in interpersonal relationships, and psychological welfare have improve more effectively through utilizing and controlling emotions, including the ability to set their own goals for the future. Motivational training programs for strengthening study habits is more important than what can be based in dental college engineering students. In conjunction with an active lifestyle, future professional dental health services for patients and clinicians care about the improvement of his own psychological happiness was inspire by the care received from home and school and the resulting map is considered to require constant attention.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.233-236
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• 2014

The purpose of this study is for the students who are naturally diverse in personality and behavior in the alternative school to examine the effect of the computer subject achievement and how to increase the student's interest in learning by means of the implementation of Howard Gardener, the Multiple-Intelligence Hypothesis. To verify this study, two groups of sophomore students from an Alternative High School located in Hwasung : The Experimental group consisted of 20 students who would participate in the Computer Science program by learning or applying new skills, based on the Multiple Intelligence Hypothesis. The Comparison Group consisted of 19 students who would follow the standardized Computer Science teaching and lesson plan. During five weeks, the multiple-Intelligence effect was executed in the search groups comparing the differences of the pre-test and pro-test. Pro-test showed following results: Firstly, the experiment search group showed a higher significant improvement in the subject achievement, compared to the comparison group. Secondly, the experiment search group showed a much higher increase in the interest of learning, compared to the comparison group. Thirdly, the experiment search group did not show any differences of the social development compared to the comparison group.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.231-237
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• 2017

Threat intelligences collected from cyber incident sharing system and security events collected from Security Information & Event Management system are analyzed and coped with expanding malicious code rapidly with the advent of big data. Analytical classification of the threat intelligence in cyber incidents requires various features of cyber observable. Therefore it is necessary to improve classification accuracy of the similarity by using multi-profile which is classified as the same features of cyber observables. We propose a multi-profile ensemble model performed similarity analysis on cyber incident of threat intelligence based on both attack types and cyber observables that can enhance the accuracy of the classification. We see a potential improvement of the cyber incident analysis system, which enhance the accuracy of the classification. Implementation of our suggested technique in a computer network offers the ability to classify and detect similar cyber incident of those not detected by other mechanisms.

• Journal of The Korean Association For Science Education
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• v.21 no.1
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• pp.13-21
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• 2001

This study examined the influences of project activities based on multiple intelligences to science achievement of elementary school children. The proportions of variance of science achievement explained by General Intelligence(GI) and Multiple Intelligences(MI) were analyzed, then the influences of project activities, which used various aspects of MI were investigated. Two classes of grade 5 at Pusan in Korea were selected for the study. On the basis of science achievement of prior term, the subjects were classified into upper-, average-, and lower-achievement groups. GI and MI were measured for each child, and the relationships of these measures with prior science achievement were analyzed using multiple regression analyses. In order to investigate the effects of the project activities on science achievement, the classes were divided into the control and experimental groups, which the former group learned science topics using the traditional teaching and learning method and the latter group performed the projects about the same topics using their own multiple intelligences. Then, their achievements were analyzed by ANOVA. Results showed that the proportion of variance explained by MI was higher about two times than that of explained by GI. Project activities contributed to the improvement of science achievement of average and upper achievers, however, in the case of under achievers, this effect was not statistically significant.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.127-134
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• 2007

There are many researches about the intelligent stock trading systems with the help of the advance of the artificial intelligence such as machine learning techniques, Though the establishment of the reasonable trading policy plays an important role in the performance of the trading systems most researches focused on the improvement of the predictability. Also some previous works, which treated the trading policy, treated the simplified versions dependent on the predictors in less systematic ways. In this paper, we propose the integrated multiple simulation' as a method of optimizing trading performance of stock trading systems. The propose method is adopted in the NXShell a development environment for neural network based stock trading systems. Under the proposed integrated multiple simulation', we simulate the multiple tradings for all combinations of the neural network's outputs and the trading policy parameters, evaluate the learning performance according to the various metrics and establish the optimal policy for a given prediction module based on the resulting performance. In the experiment, we present the trading policy comparison results using the stock value data from the KOSPI and KOSDAQ.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.37-43
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• 2007

Coordination of multiple UAVs is an essential technology for various applications in robotics, automation, and artificial intelligence. In general, it includes 1) waypoints assignment and 2) trajectory generation. In this paper, we propose a new method for this problem. First, we modify the concept of the standard visibility graph to greatly improve the optimality of the generated trajectories and reduce the computational complexity. Second, we propose an efficient stochastic approach using simulated annealing that assigns waypoints to each UAV from the constructed visibility graph. Third, we describe a method to detect collision between two UAVs. FinallY, we suggest an efficient method of controlling the velocity of UAVs using A* algorithm in order to avoid inter-UAV collision. We present simulation results from various environments that verify the effectiveness of our approach.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2052-2061
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• 2021

Objective: The role of preoperative overt hepatic encephalopathy (OHE) in the neurophysiological mechanism of cognitive improvement after liver transplantation (LT) remains elusive. This study aimed to explore changes in sub-regional thalamic functional connectivity (FC) after LT and their relationship with neuropsychological improvement using resting-state functional MRI (rs-fMRI) data in cirrhotic patients with and without a history of OHE. Materials and Methods: A total of 51 cirrhotic patients, divided into the OHE group (n = 21) and no-OHE group (n = 30), and 30 healthy controls were enrolled in this prospective study. Each patient underwent rs-fMRI before and 1 month after LT. Using 16 bilateral thalamic subregions as seeds, we conducted a seed-to-voxel FC analysis to compare the thalamic FC alterations before and after LT between the OHE and no-OHE groups, as well as differences in FC between the two groups of cirrhotic patients and the control group. Correction for multiple comparisons was conducted using the false discovery rate (p < 0.05). Results: We found abnormally increased FC between the thalamic sub-region and prefrontal cortex, as well as an abnormally decreased FC between the bilateral thalamus in both OHE and no-OHE cirrhotic patients before LT, which returned to normal levels after LT. Compared with the no-OHE group, the OHE group exhibited more extensive abnormalities prior to LT, and the increased FC between the right thalamic subregions and right inferior parietal lobe was markedly reduced to normal levels after LT. Conclusion: The renormalization of FC in the cortico-thalamic loop might be a neuro-substrate for the recovery of cognitive function after LT in cirrhotic patients. In addition, hyperconnectivity between thalamic subregions and the inferior parietal lobe might be an important feature of OHE. Changes in FC in the thalamus might be used as potential biomarkers for recovery of cognitive function after LT in cirrhotic patients.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.