• Korean Journal of Health Education and Promotion
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• v.28 no.4
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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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• v.9 no.11
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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.

• Journal of Engineering Education Research
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• v.11 no.4
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• pp.115-127
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• 2008

This study was to examine the effects of the learning strategy educational program using rubrics on engineering students' study strategies and academic achievements. To examine the effects of treatment, 58 engineering undergraduates were used as subjects. Two instruments were employed in the study, learning strategies rubrics and self-reported GPA. Repeated Measure MANOVA, ANCOVA were conducted to analyze the effects of the treatment. The summary of results showed that the program using rubrics is significantly effective regarding the improvement of the engineering students' learning strategies and academic achievement.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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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.

• Journal of Korea Multimedia Society
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• v.21 no.12
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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.

• Journal of Engineering Education Research
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• v.20 no.5
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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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• v.22 no.2
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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.

• Proceedings of the Korea Association of Information Systems Conference
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• 2004.05a
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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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• v.6 no.3
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• pp.167-172
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• 2006

Purpose: The laparoscopy assisted gastrectomy has been increasingly reported as the treatment of choice for early gastric cancer. However, expert surgeons, who have performed a conventional open gastrectomy for a long time, tend to have a negative attitude toward laparoscopic procedures. The aim of this study was to determine the learning curve of a laparoscopy assisted distal gastrectomy (LADG) for a surgeon expert in performing an open gastrectomy and to analyze the factors that have an effect on a LADG. Materials and Methods: Between April 2005 and March 2006, 62 patients underwent a LADG with D1+beta lymph-node dissection. The 62 patients were divided into 10 sequential groups with 6 cases in each group (the last group was 8 cases), and the time required to reach the plateau of the learning curve was determined by examining the average operative times of these 10 groups. Other factors, such as sex, BMI, complications, transfusion requirements, the number of retrieved lymph nodes, and change of postoperative hemoglobin level, were also analyzed. Results: With the $5^{th}$ group (after 30 cases), the operative time reached a plateau (average: 170 min/operation). The differences between before the $30^{th}$ case and after the $31^{st}$ case with respect to changes in the postoperative hemoglobin level, the number of retrieved lymph nodes, the transfusion requirements, and the complications rate were not significant. Conclusion: According to an analysis of the operative time, experience with 30 LADGs in patients with early gastric cancer is the point at which the plateau of the learning curve (7 months) is reached. Abundant experience with a conventional open gastrectomy and a well-organized laparoscopic surgery team are important factors in overcoming the learning curie earlier.

• International Journal of Contents
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• v.9 no.3
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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.