• 보건교육건강증진학회지
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• 제28권4호
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• pp.27-37
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• 2011

Objectives: This study aims to evaluate the outcomes of an education program for public health service workers in public hospitals, utilizing the Kirkpatrick model. Methods: The study participants were 118 staff in 48 public hospitals. Of the stages in the Kirkpatrick model(reaction, learning, behavior, and result), reaction and learning stages were analyzed in this study. A 10-item self-evaluation questionnaire was used to measure satisfaction level for the reaction, and achievement of learning purposes for the learning. The education program consisted of general courses and special two tract courses(Tract A: chronic diseases, Tract B: health promotion). Results: The highest score for reaction was for Tract A(score=4.4), whilst the lowest score for reaction was for lecture(score=3.0). Learning achievement was significantly different between pre-education and post-education(p<0.01), except for health technicians. Conclusions: The results of this study could be utilized to develop effective systematic education programs for public health service workers in public hospitals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4291-4310
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• 2015

This paper investigates the traffic offloading over unlicensed bands for two-tier multi-mode small cell networks. We formulate this problem as a Stackelberg game and apply a hierarchical learning framework to jointly maximize the utilities of both macro base station (MBS) and small base stations (SBSs). During the learning process, the MBS behaves as a leader and the SBSs are followers. A pricing mechanism is adopt by MBS and the price information is broadcasted to all SBSs by MBS firstly, then each SBS competes with other SBSs and takes its best response strategies to appropriately allocate the traffic load in licensed and unlicensed band in the sequel, taking the traffic flow payment charged by MBS into consideration. Then, we present a hierarchical Q-learning algorithm (HQL) to discover the Stackelberg equilibrium. Additionally, if some extra information can be obtained via feedback, we propose an improved hierarchical Q-learning algorithm (IHQL) to speed up the SBSs' learning process. Last but not the least, the convergence performance of the proposed two algorithms is analyzed. Numerical experiments are presented to validate the proposed schemes and show the effectiveness.

• 공학교육연구
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• 제11권4호
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• pp.115-127
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• 2008

본 연구의 목적은 공과대학생에게 루브릭을 활용한 학습전략 교육 프로그램을 실시하고 학습전략과 학업성취도에 미치는 효과를 검증하는 것이다. 연구대상은 서울시에 위치한 Y대학교 공과대학 58명이며, 총 9차시의 학습전략 교육 프로그램을 실시하고 학습전략 점수, 학점을 조사하였다. 연구결과 학생들의 학습전략 수준과 학업성취도에도 유의미한 향상이 있었다.

• 대한임베디드공학회논문지
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• 제14권4호
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• pp.207-218
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• 2019

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1526-1533
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• 2018

This study aims to provide implications for mobile foreign language vocabulary learning app by analyzing the effects of mobile vocabulary learning app based on character animation. For this purpose, we applied the learning application designed with character animation and text, and the application designed with text only to two groups of learners, and analyzed the effect. As a result, we found that application designed with character animation and text was useful in recognition frequency and duration concerning learning. Regarding learning outcomes, we found that it is useful not only in memory but also in learning interest and motivation. This study provides implications for learning method and design development of mobile-based foreign language vocabulary learning application which actively using recently.

• 공학교육연구
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• 제20권5호
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• pp.34-42
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• 2017

This study aimed to identify the causal relationships among self-regulated learning strategy, problem solving efficacy, task value and learning outcome, and mediation effect of self-regulated learning strategy in engineering capstone design course. The data were collected from 363 university students who enrolled in capstone design courses and analyzed using structural equation modeling method. The results were: first, problem-solving efficacy and task value exerted significant effects on self-regulated learning strategy. Second, self-regulated learning strategy exerted significant effects on learning outcome, but problem-solving efficacy and task value did not. Third, problem-solving efficacy and task value showed significant indirect effects on learning outcome, which confirmed that self-regulated learning strategy fully mediated between two exogenous variables and learning outcome.

• Korean Journal of Radiology
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• 제22권2호
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• pp.168-178
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• 2021

Objective: To provide an automatic method for segmentation and diameter measurement of type B aortic dissection (TBAD). Materials and Methods: Aortic computed tomography angiographic images from 139 patients with TBAD were consecutively collected. We implemented a deep learning method based on a three-dimensional (3D) deep convolutional neural (CNN) network, which realizes automatic segmentation and measurement of the entire aorta (EA), true lumen (TL), and false lumen (FL). The accuracy, stability, and measurement time were compared between deep learning and manual methods. The intra- and inter-observer reproducibility of the manual method was also evaluated. Results: The mean dice coefficient scores were 0.958, 0.961, and 0.932 for EA, TL, and FL, respectively. There was a linear relationship between the reference standard and measurement by the manual and deep learning method (r = 0.964 and 0.991, respectively). The average measurement error of the deep learning method was less than that of the manual method (EA, 1.64% vs. 4.13%; TL, 2.46% vs. 11.67%; FL, 2.50% vs. 8.02%). Bland-Altman plots revealed that the deviations of the diameters between the deep learning method and the reference standard were -0.042 mm (-3.412 to 3.330 mm), -0.376 mm (-3.328 to 2.577 mm), and 0.026 mm (-3.040 to 3.092 mm) for EA, TL, and FL, respectively. For the manual method, the corresponding deviations were -0.166 mm (-1.419 to 1.086 mm), -0.050 mm (-0.970 to 1.070 mm), and -0.085 mm (-1.010 to 0.084 mm). Intra- and inter-observer differences were found in measurements with the manual method, but not with the deep learning method. The measurement time with the deep learning method was markedly shorter than with the manual method (21.7 ± 1.1 vs. 82.5 ± 16.1 minutes, p < 0.001). Conclusion: The performance of efficient segmentation and diameter measurement of TBADs based on the 3D deep CNN was both accurate and stable. This method is promising for evaluating aortic morphology automatically and alleviating the workload of radiologists in the near future.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2004년도 춘계학술대회
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• pp.275-287
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• 2004

The purpose of the present study was to explore the plan to promote the e-Learning industry. The e-Learning is defined as the method of teaming or educational to access information and knowledge through Internet without time and boundary barriers. To promote e-Learning industry, first, establishing national strategy for e-Learning industry. Second, establishing e-Learning center to solve the problem of contents and technology standard. Third, right understanding of e-Leaning.

• Journal of Gastric Cancer
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• 제6권3호
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• pp.167-172
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• 2006

목적: 조기위암 치료에 있어서 복강경 위암 수술이 새로운 패러다임으로 정착하고 있다. 기존에 시행하고 있던 개복에 의한 위절제술에 익숙한 경험 많은 외과의사들은 복강경 위암 수술은 시간이 많이 소요되며 기술적으로 습득하는데 많은 제약이 있음을 느끼며 복강경 수술에 소극적 자세를 취하는 경향이 있다. 이에 저자 등은 개복 위절제술에 경험이 풍부한 외과의사에 의한 복강경 위절제술의 learning curve를 결정하고, 이에 영향을 미치는 요인들을 분석하였다. 대상 및 방법: 2005년 4월부터 2006년 3월까지 한 명의 술자에 의하여 수술전 조기 위암(cT1N0)으로 진단 받고 복강경 보조하 원위부 위절제술(LADG) 및 $D1+{\beta}$ 림프절 곽청을 시행 받은 62명을 대상으로 하였으며 복강경 위절제술 시행을 위하여 전문팀을 구성하였다. 대상 환자를 6명씩 한 그룹으로 총 10그룹(마지막 그룹은 8명으로 구성함)으로 나누어 각 그룹의 평균 수술시간을 비교하여 learning curve 극복 전후의 나이, 성별, 수술 후 합병증, 절개창의 길이, 수혈유무, 적출된 림프절 개수, 수술 전 후 혈색소 변화 등을 분석하였다. 결과: 평균 수술 시간을 분석한 결과 여섯 번째 그룹 (31st case)부터 수술 시간의 Plateau를 보였다. 이에 저자들은 learning curve 극복시점을 30th case (7개월)로 간주하였으며 극복 전후 집단 간의 평균 수술시간을 분석하였을 때 각각 $239.0{\pm}69.7$분과 $170.0{\pm}32.6$분으로 유의하게 나타났다(P<0.05), 양 군 간 평균나이, 성별, BMI, 수술 전후의 혈색소 수치변화, 적출된 림프절 개수 등은 유의한 차이를 보이지 않았다. 또한 절개창의 길이, 수혈유무, 수술 후 합병증 유무도 양 군 간에 통계적으로 유의하지 않았다. 결론: 저자들의 LADG learning curve 극복은 30예(7개월)로 다른 보고보다 일찍 도달할 수 있었다. 이는 개복 수술의 풍부한 경험, 전문 수술팀 구성, 그리고 단기간 집중적인 시술에 의한 것으로 생각된다.

• International Journal of Contents
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• 제9권3호
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• pp.35-41
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• 2013

This paper aims at investigating what Regional University E-Learning Centers (RUECs) has done in promoting e-learning in university education in Korea. First, the e-learning situation in university education in Korea is introduced. Secondly, the background of establishment of RUECs and its functions are explained in detail. Thirdly, a case of RUECs is suggested by using the CNU-University E-Learning Center. In particular, the performance of e-learning is evaluated based on the student satisfaction data, and a paired-t test is implemented to see if there was any difference between 'before' and 'after' e-learning. Lastly, some suggestions are made to promote the e-learning in university education.