• Korean journal of medical education
• /
• v.30 no.4
• /
• pp.359-364
• /
• 2018

Purpose: Learning physiological concepts and their practical applications in the appropriate contexts remains a great challenge for undergraduate medical students. Hence the present study aimed to analyze the learning experience of undergraduate medical students during an active learning process of 'preparation of models' depicting physiological concepts. Methods: A total of 13 groups, involving 55 undergraduate medical students with three to five individuals in each group, were involved in model preparation. A total of 13 models were exhibited by the students. The students shared their learning experiences as responses to an open-ended questionnaire. The students' responses were analyzed and generalized comments were generated. Results: Analysis of the results showed that the act of 'model preparation' improved concept understanding, retention of knowledge, analytical skills, and referral habits. Further, the process of 'model preparation' could satisfy all types of sensory modality learners. Conclusion: This novel active method of learning could be highly significant in students' understanding and learning physiology concepts. This approach could be incorporated in the traditional instructor-centered undergraduate medical curriculum as a way to innovate it.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.2
• /
• pp.165-171
• /
• 2017

It is difficult to recognize Human's facial expression in the real-world. For these reason, when database and test data have similar condition, we can accomplish high accuracy. Solving these problem, we need to many facial expression data. In this paper, we propose the algorithm for gathering many facial expression data within various environment and gaining high accuracy quickly. This algorithm is training initial model with the ASSL (Active Semi-Supervised Learning) using deep learning network, thereafter gathering unlabeled facial expression data and repeating this process. Through using the ASSL, we gain proper data and high accuracy with less labor force.

• Nuclear Engineering and Technology
• /
• v.54 no.9
• /
• pp.3283-3292
• /
• 2022

Based on the Deep Q-Network(DQN) algorithm of reinforcement learning, an active fault-tolerance method with incremental action is proposed for the control system with sensor faults of the once-through steam generator(OTSG). In this paper, we first establish the OTSG model as the interaction environment for the agent of reinforcement learning. The reinforcement learning agent chooses an action according to the system state obtained by the pressure sensor, the incremental action can gradually approach the optimal strategy for the current fault, and then the agent updates the network by different rewards obtained in the interaction process. In this way, we can transform the active fault tolerant control process of the OTSG to the reinforcement learning agent's decision-making process. The comparison experiments compared with the traditional reinforcement learning algorithm(RL) with fixed strategies show that the active fault-tolerant controller designed in this paper can accurately and rapidly control under sensor faults so that the pressure of the OTSG can be stabilized near the set-point value, and the OTSG can run normally and stably.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.351-357
• /
• 2022

This study was conducted for the purpose of developing a flipped learning teaching and learning model for physical education and competitive activities and confirming the validity of the model. We used the model research method as a research method to achieve the purpose of this study. First, we developed a flipped learning model for physical education and competitive activities through model development research, and then confirmed the validity of the model through model validation research. Based on the teaching and learning model developed through this study, students can change from passive learners to active learners in physical education classes, and it is expected that they can achieve class goals based on interactions between learners different from existing physical education classes through cooperative activities.

• The Journal of Korean Association of Computer Education
• /
• v.18 no.6
• /
• pp.81-88
• /
• 2015

Along with advent of Web 3.0 era and advanced technologies of IoT(Internet of Things), massive amounts of information are generated. Reflecting this trend, this paper developed a semi-automatic construction tool for named entity dictionary based on active learning. Our proposed method chose error candidates to verify among the preliminary results using initial trained model and re-trained the model for correctly labeled data by user. We adopt active learning approach for minimizing human effort utilized metadata features of Wikipedia. Based on experimental results using our tool, we show that 68.6% errors were automatically corrected.

• Educational Technology International
• /
• v.10 no.1
• /
• pp.137-155
• /
• 2009

The purpose of this research is to develop Blended-TBL(Team Based Learning) model that emphasizes the active participation and teamwork of students in on-off blended learning environment, and apply it into the college course and explore whether self-regulated learning between one group pretest and posttest is different. For this, this research investigated the concept and the characteristics of Team Based Learning, and developed the Blended-TBL Model to apply it into the college course, and finally prove effects of Blended-TBL model on self-regulated learning using Motivated Strategies for Learning Questionnaire (MSLQ). The participants in this study were 57 college students. They participated in on-off blended-TBL course for 15weeks. Participants followed the content grounded and the problem solving steps in collaborative team-based learning. This research practiced a quantitative research to find out the statistical difference of the self-regulated learning between pretest and posttest using SPSS. The result revealed that Blended-TBL students improved self-regulated learning including motivation, cognitive, metacognitive, and resource management. Based on this result, this research discussed the effects of Blended-TBL on Self-Regulated Learning and suggested the further study.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.5
• /
• pp.171-177
• /
• 2018

Recently there are many image datasets which has variety of data class and point to extract general features. But in order to this variety data class and point, deep learning model trained this dataset has not good performance in heterogeneous data feature local area. In this paper, we propose the structure which use sub-category and openset object detection methods to train more robust model, named multi-branch tree using ASSL. By using this structure, we can have more robust object detection deep learning model in heterogeneous data feature environment.

• Journal of Digital Convergence
• /
• v.7 no.3
• /
• pp.49-60
• /
• 2009

The aim of this study was to develop a model for teaching-teaming by applying Ubiquitous at a learning experience field, in which connect characteristics of both ubiquitous application learning and experience teaming, making use of them. A literature survey of concepts was conducted, with the main areas to find out relationships between ubiquitous application learning and experience learning. Experience learning by applying ubiquitous learning methods maximizes its efficiency of experience learning in considering ubiquitous learning methods's characteristics of dynamic, interaction, sharing. Also it makes communications through positive participation and active interaction, and leads to a process of internal examination. The research data suggests that critical factors of experiencing learning applying ubiquitous are acquiring information and memory, information integration and exquisiteness, emotional and social activity, producing activity, help activity.

• Journal of Korea Multimedia Society
• /
• v.20 no.11
• /
• pp.1720-1728
• /
• 2017

Active shape model is widely used in the field of image processing especially on arbitrary meaningful shape extraction from single gray level image. Cootes et. al. showed efficient detection of variable shape from image by using covariance and mean shape from learning. There are two stages of learning and testing. Hahn applied enhanced shape alignment method rather than using Cootes's rotation and scale scheme. Hahn did not modified the profile itself. In this paper, the method using directional one dimensional profile is proposed to enhance Cootes's one dimensional profile and the shape alignment algorithm of Hahn is combined. The performance of the proposed method was superior to Cootes's and Hahn's. Average landmark estimation error for each image was 27.72 pixels and 39.46 for Cootes's and 33.73 for Hahn's each.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.6
• /
• pp.15-21
• /
• 2018

The purpose of this study is to design a Content-based Korean Class model using Flipped learning for foreign students. The class model that presents on this paper will lead the language learning through content learning, also it will be enable the student more active and to have an initiative in the class. Prior to designing a Content-based Korean Class model using Flipped learning, the concepts and educational significance and characteristics of flip learning were reviewed through previous studies. Then, It emphasizes the necessity of teaching method adapting Flipped learning to Content-based teaching method in Korean language education. It also suggests standards and principles of composition in Contents-based teaching method using Flipped learning. After designing the instructional model based on the suggested standards and principles, it presents a course of instruction about how learning methods, contents and activities should be done step by step. The Content-based Korean class model using the Flipped learning will be an alternative approach to overcome the limitations of teacher-centered teaching methods and lecture-teaching methods which are the dominant of present classroom environment.