• Journal of KIISE
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• v.44 no.11
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• pp.1156-1164
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• 2017

Existing studies on automatic bug triage were mostly used the method of designing the prediction system based on the machine learning algorithm. Therefore, it can be said that applying a high-performance machine learning model is the core of the performance of the automatic bug triage system. In the related research, machine learning models that have high performance are mainly used, such as SVM and Naïve Bayes. In this paper, we apply Deep Learning, which has recently shown good performance in the field of machine learning, to automatic bug triage and evaluate its performance. Experimental results show that the Deep Learning based Bug Triage system achieves 48% accuracy in active developer experiments, un improvement of up to 69% over than conventional machine learning techniques.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.701-706
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• 2019

The advent of the AI(: Artificial Intelligence) has applied to many industrial and general applications have havingact on our lives these days. Various types of machine learning methods are supported in this field. The supervised learning method of the machine learning has features and targets as an input in the learning process. There are many supervised learning methods as well and their performance varies depends on the characteristics and states of the big data type as an input data. Therefore, in this paper, in order to compare the performance of the various supervised learning method with a specific big data set, the supervised learning methods supported in the Tensorflow and the Sckit-Learn are simulated and analyzed in the Jupyter Notebook environment with python.

• Journal of Korean society of Dental Hygiene
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• v.21 no.2
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• pp.193-201
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• 2021

Objectives: We evaluated the learning objectives of dental hygiene courses based on Bloom's learning objectives, and analyze the degree of match with the dental hygienist's job for each detailed subject. Methods: The 5th edition of 'Dental hygiene and learning objectives' was analyzed by subject based on Bloom's cognitive domain classification from March 10 to April. In addition, the degree of match between the contents of the secondary job analysis of the dental hygienist and the learning objectives for each detailed subject were analyzed. Results: The total number of dental hygiene learning objectives was 2,975 (2,762 theory, 52 practice). Among the cognitive domains, the comprehension domain was the most common (79.8%), and the skill domain was very low (4.9%). In the job for each detailed subject of dental hygiene, the most frequently performed was 'dental prophylaxis and practice' with 103 subjects. Conclusions: Overall, dental hygiene learning objectives are mostly theory-oriented, so it is necessary to expand and improve in the direction related to the jobs that clinical dental hygienists perform in the field. In addition, it is necessary to continuously develop timely learning goals, and prepare active strategies for developing high-quality items.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.656-666
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• 2022

The purpose of this study is to evaluate the effect on the grit, learning reality, and learning satisfaction for nursing students using the flipped learning teaching method. We developed a flipped learning educational program using ADDIE model for nursing students and evaluated the program effect. As a result of this study, the grit (t=-3.07, p=.003), the learning presence (t=-4.87, p<.001) and the learning satisfaction (t=-5.18, p<.001) significantly increased after flip learning method application. The Grit shown to have a significant positive correlation with learning presence (r = .47, p<.001), and learning satisfaction (r = .26, p<.005). The learning presence shown to have a significant positive correlation with learning satisfaction (r = .548, p<.001). The flipped learning teaching method may improve the grit, learning reality, and learning satisfaction. Various efforts will be needed to lay the foundation for flipped learning teaching methods in the field of nursing education in the future.

• Korean Medical Education Review
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• v.18 no.3
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• pp.125-131
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• 2016

Recent changes in educational paradigms that emphasize the performance or outcomes of education are redefining how learning objectives are being described as 'learning outcomes' in various academic disciplines. Medical education is not an exception to this trend. However, it has come to our attention that the key concepts and appropriate descriptions of learning outcomes have not been well understood among educators and that this lack of understanding has hindered our efforts to implement the practice in the field. This study aims to provide a direction to establish and describe learning outcomes by examining previous studies that have focused on setting learning objectives as well as learning outcomes. Setting and describing learning outcomes starts from reflection on the approach of behavioral learning objectives, which overemphasizes learner's acquired knowledge, skills, and attitude in each classroom rather than actual performance. On the other hand, the learning outcome approach focuses on what the learner is able to do as a result of a learning experience. This approach is more learner-friendly and encourages students to lead and be responsible for their learning process. Learning outcomes can best be described when the relevance of actual contexts and the hierarchy of learning objectives are considered. In addition, they should be in the form of context, task, performance, and level, as well as be planned with proper assessment and feedback procedures. When these conditions are met, the learning outcome approach is beneficial to students as it presents a curriculum that is more open to learners. Despite these advantages of the learning outcome approach, there is a possible concern that setting the learning outcomes and describing them can restrict evaluation to lower cognitive skills if the concept of learning outcome is narrowly interpreted or is set too low. To avoid such narrow applications, it is important for educators to understand the comprehensiveness of the learning outcome setting and to consider long-term outcomes embedded in an organizational vision rather than only short-term behavioral outcomes.

• 대한공업교육학회지
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• v.45 no.1
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• pp.63-83
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• 2020

The purpose of this study is to provide the basic materials needed to plan the NCS Learning Module to be used effectively in practical courses. In this study, teachers and students' satisfaction surveys were collected about the NCS (National Competency Standards) learning module, career and field practice, practical environment used in the construction subject course. This study was conducted on public high schools in Chungcheong province (including Daejeon), which is operating practice course using the NCS learning module. The research questions are as follows; First, how was the satisfaction of teachers and students in the practical subject class using NCS learning module? Second, what is the degree of satisfaction of teacher's career and field practice guidance, student's career decision and field practice after the practical course using NCS learning module? Third, the satisfaction level of the developed NCS learning module and practical subject class using the same was determined by setting whether the number of training of NCS-related teachers or the presence or absence of on-the-job training of students were affected? The results of the study are as follows; As a result of comparing the teachers' and students' satisfaction, the students showed satisfaction in all items, whereas the teachers showed 'content level', 'interest', 'necessary knowledge', 'skill acquisition', 'Improvement of practical skills (level of skill performance)', 'scale of experimental practice', and 'items of experimental practice equipment' were dissatisfied. It was found that the number of NCS related teachers' training (or absence) or the presence of students on the field had an effect on the satisfaction of the developed NCS learning module and the practical course using it. In order to fully utilize the developed NCS learning module in the practical course, it is required to develop and construct the teaching material of the teacher who can serve as an intermediary for conceptualization and understanding of job skills. It is necessary to increase the number of education and training specialists to positively reflect the demands of the education field.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.755-764
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• 2019

Currently commercially available light field cameras are difficult to acquire 5D light field video since it can only acquire the still images or high price of the device. In order to solve these problems, we propose a deep learning based method for synthesizing the light field video from monocular video. To solve the problem of obtaining the light field video training data, we use UnrealCV to acquire synthetic light field data by realistic rendering of 3D graphic scene and use it for training. The proposed deep running framework synthesizes the light field video with each sub-aperture image (SAI) of $9{\times}9$ from the input monocular video. The proposed network consists of a network for predicting the appearance flow from the input image converted to the luminance image, and a network for predicting the optical flow between the adjacent light field video frames obtained from the appearance flow.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.27-32
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• 2020

In this paper, we propose an algorithm to measure the accumulated status of scrap boxes where metal scraps are accumulated. The accumulated status measuring is defined as a multi-class classification problem, and the method with deep learning classify the accumulated status using only the scrap box image. The learning was conducted by the Transfer Learning method, and the deep learning model was NASNet-A. In order to improve the accuracy of the model, we combined the Random Forest classifier with the trained NASNet-A and improved the model through post-processing. Testing with 4,195 data collected in the field showed 55% accuracy when only NASNet-A was applied, and the proposed method, NASNet with Random Forest, improved the accuracy by 88%.

• Journal of Construction Engineering and Project Management
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• v.1 no.2
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• pp.11-17
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• 2011

Recent demands from construction industry have emphasized the capability for graduates to have improved skills both technical and non-technical such as problem solving, interpersonal communication. To satisfy these demands, problem-based learning that is an instructional method characterized by the use of real world problem has been adopted and has proven its effectiveness various disciplines. However, in spite of the importance of field senses and dealing with real problem, construction engineering education has generally focused on traditional lecture-oriented course. In order to improve limitations of current construction education and to satisfy recent demands from construction industry, this paper proposes a new educational approach that is Failure-Based Learning for using combination of the procedural characteristics of the problem-based learning theory in construction technology education utilizing failure information that has the educational value in the construction area by reinterpreting characteristics of construction industry and construction failure information. The major results of this study are summarized as follows. 1) Educational effect of problem-based learning methodology and limitation of application in construction area 2) The educational value of the information on construction failure and limitation in application of the information in construction sector 3) Anticipated effect from application of the failure-based learning 4) Development and application of the failure-based learning conceptual model.

• Journal of Ocean Engineering and Technology
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• v.34 no.2
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• pp.147-154
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• 2020

Underwater acoustics that is the study of the phenomenon of underwater wave propagation and its interaction with boundaries, has mainly been applied to the fields of underwater communication, target detection, marine resources, marine environment, and underwater sound sources. Based on the scientific and engineering understanding of acoustic signals/data, recent studies combining traditional and data-driven machine learning methods have shown continuous progress. Machine learning, represented by deep learning, has shown unprecedented success in a variety of fields, owing to big data, graphical processor unit computing, and advances in algorithms. Although machine learning has not yet been implemented in every single field of underwater acoustics, it will be used more actively in the future in line with the ongoing development and overwhelming achievements of this method. To understand the research trends of machine learning applications in underwater acoustics, the general theoretical background of several related machine learning techniques is introduced in this paper.