• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.199-206
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• 2020

I suggested the design learning environment based on affordance concept approach for supporting and improving learners' behavior and outcome for convergent design education in this study. The design learning space should be applied teaching and learning activity, especially learners' behavior, physical space condition to support the design thinking process. The design learning space needs openness, individuality and connectivity to support the learners' behavioral to immerse, participate, cooperate, understand, think and fulfill the design thinking process. The composition principles of the learning environment for convergent design education supports communication and collaboration among members for independence and interaction. The spaces for design research and teaching needs high privacy while facilitating visual communications through special materials and wall structure design. Also, for connectivity to improve the learners' physical and visual contact, the environment of the classrooms requires flexibility and mobility by providing an open space integrating unit cells for realizing learning purpose. These are provided by formed of an open structure for inducing visual communication and physical contact to involve the design activities and the mutual interchange.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.7-21
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• 2024

There are various machine learning techniques such as Reinforcement Learning, Deep Learning, Neural Network Learning, and so on. In recent, Large Language Models (LLMs) are popularly used for Generative AI based on Reinforcement Learning. It makes decisions with the most optimal rewards through the fine tuning process in a particular situation. Unfortunately, LLMs can not provide any explanation for how they reach the goal because the training is based on learning of black-box AI. Reinforcement Learning as black-box AI is based on graph-evolving structure for deriving enhanced solution through adjustment by human feedback or reinforced data. In this research, for mutually exclusive decision-making, Mutually Exclusive Learning (MEL) is proposed to provide explanations of the chosen goals that are achieved by a decision on both ends with specified conditions. In MEL, decision-making process is based on the tree-based structure that can provide processes of pruning branches that are used as explanations of how to achieve the goals. The goal can be reached by trade-off among mutually exclusive alternatives according to the specific contextual conditions. Therefore, the tree-based structure is adopted to provide feasible solutions with the explanations based on the pruning branches. The sequence of pruning processes can be used to provide the explanations of the inferences and ways to reach the goals, as Explainable AI (XAI). The learning process is based on the pruning branches according to the multi-dimensional contextual conditions. To deep-dive the search, they are composed of time window to determine the temporal perspective, depth of phases for lookahead and decision criteria to prune branches. The goal depends on the policy of the pruning branches, which can be dynamically changed by configured situation with the specific multi-dimensional contextual conditions at a particular moment. The explanation is represented by the chosen episode among the decision alternatives according to configured situations. In this research, MEL adopts the tree-based learning model to provide explanation for the goal derived with specific conditions. Therefore, as an example of mutually exclusive problems, employment process is proposed to demonstrate the decision-making process of how to reach the goal and explanation by the pruning branches. Finally, further study is discussed to verify the effectiveness of MEL with experiments.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.121-129
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• 2021

This paper deals with a super-resolution that improves the resolution of side scan sonar images using learning-based compressive sensing. Learning-based compressive sensing combined with deep learning and compressive sensing takes a structure of a feed-forward network and parameters are set automatically through learning. In particular, we propose a method that can effectively extract additional information required in the super-resolution process through various initialization methods. Representative experimental results show that the proposed method provides improved performance in terms of Peak Signal-to-Noise Ratio (PSNR) and Structure Similarity Index Measure (SSIM) than conventional methods.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.262-265
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• 2018

Deep learning, a sub-field of machine learning changing the prospects of artificial intelligence (AI) because of its recent advancements and application in various field. Deep learning deals with algorithms inspired by the structure and function of the brain called artificial neural networks. This works reviews basic architecture and recent advancement of deep structured learning. It also describes contemporary applications of deep structured learning and its advantages over the treditional learning in artificial interlligence. This study is useful for the general readers and students who are in the early stage of deep learning studies.

• The Journal of Korean Association of Computer Education
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• v.6 no.4
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• pp.181-193
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• 2003

The purpose of this study was to find effects of hypertext structure and self-direction on learning performance. To reach the goal, we got 69 H highschool students and tested self-direction we treat hypertext program to them. The results found were that hypertext style(non-structure, structure) didn't effect on academic achievement but did effect 1earner's self direction. Also, we found interactive effect of hypertext structure and self-direction on academic achievement. Following studies have limits verified learning effect, because this studies are carried out in short-term research. Further studies need the study of effect of hypertext structure and self-direction on academic achievement for a long-term research. Also, further studies should accomplish the study considering learner characteristics besides self-direction and will need succeeding studies including various learning contents besides computer general curriculum.

• Journal of Elementary Mathematics Education in Korea
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• v.11 no.2
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• pp.177-197
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• 2007

This study discussed the climbing learning method which studied and practiced by Professor Saito Noboru. This is the learning method which is devised to know not only the relationship of the learning factors but the systemic or structural connection of whole studying contents- affects children's math learning ability through practical class to both the lower and the higher grades. To achieve the purpose of this study, these following issues were set; A. Develop the teaching and learning course of mathematics by applying the climbing learning method. B. Execute the mathematics lesson according to the climbing learning method and analyze the learning achievement. C. Analyze the difference between application of the climbing learning method and that of the learning method by student's level in mathematics. D. Analyze what the climbing learning method gives a shift of the recognition of learning mathematics. In order to accomplish these study issues, we analyzed the text book of math not only for children but also for teachers and developed the teaching and learning course applied the climbing learning method with advice of experts. It was chosen two different homogeneous groups each, third year for lower grade group and fifth year for higher grade group. It was done the experimental group lesson applying the climbing learning method and general lesson for the control group. After then, t-test against independent samples was done depending on the result of the student's assessment(T1, T2). These two groups' students were divided into smaller groups based on result of achievement level regardless of gender. These subgroups were confirmed the difference of learning ability between upper and lower level group. As regarding the result making out grades of faith and attitude for math, t-test was used on independent sample. At the same time, experimental groups were tested using learning attitude with the learning structure chart. Through this study the following results are obtained and the conclusion was drawn. Firstly, although applying the climbing learning method to the lesson does not have significant effect to the lower grade of elementary school student's achievement it has significant influence on the higher grade student's achievement. Second, as a result of analyzing the difference between the climbing learning method and the learning method by student's level in mathematics, it is of no beneficial effect to the lower grade both upper level and lower level. However, it has appreciable effect to the higher grade classes both upper level and low level. Especially, upper level students have higher effect than low level students. Third, climbing learning method does not affect to the faith and attitude of the lower grade students positively, but it has affirmative effect to the higher grade students'. As a result of the survey of the experimental groups which were applied to the climbing loaming method, the lesson by using the learning structure chart proved to be helpful to the both the lower and higher grade. The best advantage of using the learning structure chart, children say, is easily understood whole contents of studying and is useful for review. Furthermore, using the learning structure chart is more efficient compared with previous learning method and is given the successful result to self-directed learning. In conclusion, keeping up with the current of the thought of education, we suggest a scheme as a new teaching method from the constructive learning method which emphasize the self-directed learning.

• Journal of architectural history
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• v.13 no.4 s.40
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• pp.7-18
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• 2004

From the results of an examination of the transition process of the site plan divided into 5 stages based on literature and materials relating to the Sangju Confucian School as well as the construction history, we can see the general transition flow as follows. The arrangement form of Sangju Confucian School shows the structures with both the sacrificial rites function and the learning function in the early period. This shows a large general flow where the form with the learning function structure at the front and sacrificial rites function structure at the back changed to a form where the learning function structure was positioned behind the boarding facilities, after which there was a transformation which left only the learning function (the form where the learning function structure was positioned in front of the boarding facilities). The type where the learning function structure is positioned in front of the boarding facilities is hard to find in the Yeongnam area, also, there are not many examples of the 2 story Myeonglyundang (hall of confucianism teachings) throughout the country Sangju Confucian School which possess the value of rarity is appraised as being a precious material showing another area characteristic in Sangju of the Yeongnam area. Also, during the late Chosun period the scale of the Dongseojae (boarding facility) was reduced and the appearance of Yangsajae can be said to be a typical example of confucian school constructions of late Chosun era.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.993-1001
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• 2021

This study aims to determine the factors influencing student performance using the teaching and learning process through e-learning based on the unified theory of acceptance and use technology (UTAUT). This study also sets out to propose additional variables to expand the UTAUT model to be more suitable to use in higher education. This research conducted a literature review, expert interviews, and a self-administered survey involving 200 students at tertiary institutions in Riau province, Indonesia. The questionnaire data were analyzed using SmartPLS 2. This study shows that UTAUT constructs, namely, social influence, facility conditions, and effort expectancy have a significant influence on student behavior and performance, while the performance expectancy variable shows no significant effect. The additional variables, including lecturer characteristics, external motivation, and organizational structure, directly affect student performance. However, concerning student behavior, motivation and environment are the only variables with a significant effect. The results of this study suggest the behavior deteminant such as lecturer characteristics, motivation and environment, and organizational structure improve student performance. This study investigates factors affecting the performance of university students through the learning employing e-learning by developing the UTAUT constructs to include the lecturer characteristics, motivation and environment, and organizational structure in improving student performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.395-398
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• 1998

In this paper, a method for the improvement of learning speed and convergence rate was proposed applied it to physiological neural structure with the advantages of artificial neural networks and fuzzy theory to physiological neuron structure, To compare the proposed method with conventional the single layer perception algorithm, we applied these algorithms bit parity problem and pattern recognition containing noise. The simulation result indicated that our learning algorithm reduces the possibility of local minima more than the conventional single layer perception does. Furthermore we show that our learning algorithm guarantees the convergence.