• Journal of Digital Convergence
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• v.14 no.6
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• pp.263-270
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• 2016

In this study, it was attempted to develop a grade-customized statistical analysis system that can be operated by a teacher without professional knowledge of statistics by utilizing profiling in the education sector. For this, with the convergence of techniques of profiling into the education sector, it examined the elements necessary for building a customized student multidimensional analysis system. Referring to the overall configuration and the current state to build multidimensional analysis system utilizing practical profiling, it showed the implementation result of the algorithm applied to each statistical method, and presented the differences and superiority to existing systems. Once the system based on the proposed techniques is built, considering differences of students' needs and abilities and clarifying precise objectives and standards, with the improvement of satisfaction in public education, it is possible not only to reduce expense of prior and private learning but also realize self-directed learning suitable to one's learning ability and aptitude.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.613-618
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• 2012

ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. And Ministry of Education emphasizes STEAM education. Most important is that "How instruct them". This means necessity of contents. So this paper suggests learning method of Stack and Queue using LEGO MINDSTORMS NXT. The main purpose is that how stack and queue are used, when robot explore realistic maze. Teaching and learning strategies are algorithm, flowchart, and NXT-G programming. Simple maze has path in left or right, but complex maze has three-way intersection. These are developed by authors. Master robot explores maze and push stack, and then return to entrance using stack. Master robot explores maze and transmits path to slave's queue. And then slave robot drives without exploration. Students can naturally learn principles and applications of them. Through these studies, it can improves ability of logical and creative thinking. Furthermore it can apply to ICT and STEAM education.

• Journal of the Korean Institute of Educational Facilities
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• v.27 no.3
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• pp.3-14
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• 2020

The purpose of this study is to discuss the planning direction of educational spaces to support children's healthy and creative learning based on bio_philic theory. This study analyzed the characteristics of the application of biophilic patterns in children's education space through case analysis. The conclusion of this study is summarized as follows. As a result of the analysis of children's classroom space, the pattern of 'A(Visual connection with nature), F(Dynamic & Diffuse Light), K(Prospect)' shows high application rate, but the pattern of 'C(Non-Rhythmic Sensory Stimuli), G(Connection with Natural Systems), I(Material Connection with Nature)' shows low application rate. In particular, there is a lack of connection with patterns such as hearing, smell, touch, taste stimulation and water experience, and curiosity through exploration of nature about 'B(Non-visual connection with nature), E(Presence of Water), N(Risk/Peril)' changes in nature and ecosystem. In the corridor and rest space, the pattern of 'A(Visual connection with nature), D(Thermal & Airflow Variability), F(Dynamic & Diffuse Light), G(Connection with Natural Systems), K(Prospect)' shows high application rate, but 'B(Non-visual connection with nature)' shows low application rate. In addition, the application of patterns related to the stimulation of curiosity through direct exploration of nature and the exploration of the patterns of 'E(Presence of Water), N(Risk/Peril)' is insufficient. Therefore, in the case of classroom spaces, the active use of nature as it is should be considered within the scope that does not cause visual confusion, and it should provide an area that can be experienced through the five senses. And corridors and rest spaces should be designed to introduce more active natural elements as spaces to recover stress caused by learning. In other words, the characteristics of children's education facilities need to be connected between classroom space, corridor, rest space and external space. This study is meaningful in that it analyzes and derives the application characteristics of 'biophilic design' which affects the 'Attention Restoration' of children's educational spaces through foreign cases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.505-513
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• 2009

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.449-459
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• 1996

The main goal of this paper is to introduce a novel definition for fuzzy mathematical morphology and a neural network implementation. The generalized- mean operator plays the key role for the definition. Such definition is well suited for neural network implementation. The first stage of the shared-weight neural network has adequate architecture to perform morphological operation. The shared- weight network performs classification based on the features extracted with the fuzzy morphological operation defined in this paper. Therefore, the parameters for the fuzzy definition can be optimized using neural network learning paradigm. Learning rules for the structuring elements, degree of membership, and weighting factors are precisely described. In application to handwritten digit recognition problem, the fuzzy morphological shared-weight neural network produced the results which are comparable to the state-of art for this problem.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.87-100
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• 2020

The purpose of this study is to examine whether some factors that influence the computerized accounting class in a university, namely the educational environment of the university, curriculum of the professor and his/her teaching methods, and the self-efficacy of the leaners manifest themselves in effective class satisfaction, class performance and class immersion which reflect these factors. As results, First, in the relationship between the class satisfaction, the professor, the students, and the educational environment of the university all had a significant influence. Second, in the relationship between the class performance, the professors and the students had a significant influence. However, class performance did not have a significant impact on the educational environment of the university and the program. Third, in the relationship between the factors of the classes and the classes immersion, which is one of the sub-elements of the learning performance, it was shown that the environment of the university and the students had a significant impact, while the program and the professor did not have an impact on the class immersion.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.145-150
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• 2021

The trend of learning as an online study platform continues, and motivation of learners for continued use of the platform is also becoming important. In addition to learning, various services use gamification techniques that excite users for continued use. This study analyzes successful service cases and proposes guidelines applicable to learning platforms to present ways to increase learners' interest and efficiency in online study platforms using reward systems and storytelling techniques among gamification elements. Based on the three guidelines drawn through this study, it can contribute to the digitization of educational infrastructure by increasing the immersion of learners within the online study platform that will be more commercialized in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1202-1208
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• 2020

In line with the current era of the 4th Industrial Revolution, it is necessary to prepare for the future by integrating AI elements in the ship sector. In addition, it is necessary to respond to this in the field of power management for the appearance of autonomous ships. In this study, we propose a battery-linked electric propulsion system (BLEPS) algorithm using machine learning's DNN. For the experiment, we learned the pattern of ship power consumption for each operation mode based on the ship data through LabView and derived the battery status through Python to check the flexibility of the generator and battery interlocking. As a result of the experiment, the low load operation of the generator was reduced through charging and discharging of the battery, and economic efficiency and reliability were confirmed by reducing the fuel consumption of 1% of LNG.

• Journal of IKEEE
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• v.26 no.3
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• pp.488-493
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• 2022

In manufacturing sites, bearing fault in eletrically driven motors cause the entire system to shut down. Stopping the operation of this environment causes huge losses in time and money. The reason of this bearing defects can be various factors such as wear due to continuous contact of rotating elements, excessive load addition, and operating environment. In this paper, a motor driving environment is created which is similar to the domestic manufacturing sites. In addition, based on the established environment, we propose a dataset for bearing fault detection by collecting changes in vibration characteristics that vary depending on normal and defective conditions. The sensor used to collect the vibration characteristics is Microphone G.R.A.S. 40PH-10. We used various machine learning models to build a prototype bearing fault detection system trained on the proposed dataset. As the result, based on the deep neural network model, it shows high accuracy performance of 92.3% in the time domain and 98.3% in the frequency domain.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.961-972
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• 2021

In this study, an educational program was developed so that artificial intelligence could be used as a transdisciplinary convergence education with other disciplines. The main educational content is designed for 8 hours using machine learning to help students understand the molecular structure dealt with in high school chemistry. The program developed in this study calculated the I-CVI (Item Content Validity Index) value through expert review, and as a result, none of the items were rejected with a score of .80 or higher. Because the program of this study combines the content elements of the chemistry subject and the information (artificial intelligence) subject academically, it is expected that the learner will be able to increase the convergence talent literacy. In addition, since it is not required to secure a additional number of hours for this educational program, the burden on teachers may be low.