• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1855-1862
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• 2022

Various indoor location-based services can be provided through indoor presence determination and indoor positioning technology using Beacon. However, since the BLE signal advertised by the beacon has an unstable RSSI due to problems such as multi-path fading, it is difficult to guarantee the accuracy of indoor presence determination. In this paper, data were collected while the classroom door was open to ensure accuracy in various situations. Based on the collected data, we propose an indoor presence determination method considering the characteristics of the signal. The proposed method uses support vector machine, showed about 10% accuracy improvement compared to the results using raw RSSI only. This method has the advantage of being able to accurately determine indoor presence with only one receiver. It is expected that the proposed method can implement a low-cost system for determining indoor presence with high accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.826-832
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• 2016

In this paper, we propose a tongue diagnosis system for determining the presence of specific taste crack area as a first step in the digital tongue diagnosis system that anyone can use easily without special equipment and expensive digital tongue diagnosis equipment. Training DB was developed by the Haar-like feature, Adaboost learning on the basis of 261 pictures which was collected in Oriental medicine. Tongue candidate regions were detected from the input image by the learning results and calculated the average value of the HUE component to separate only the tongue area in the detected candidate regions. A tongue area is separated through the Connected Component Labeling from the contour of tongue detected. The palate regions were divided by the relative width and height of the tongue regions separated. Image on the taste area is converted to gray image and binarized with each of the average brightness values. A crack in the presence or absence was determined via Connected Component Labeling with binary images.

• 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 Advanced Navigation Technology
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• v.26 no.4
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• pp.226-234
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• 2022

With advances in autonomous vehicles and networked control, there is a growing interest in the consensus control of a multi-agents system to control multi-agents with distributed control beyond the control of a single agent. Since consensus control is a distributed control, it is bound to have delay in a practical system. In addition, it is often difficult to have a very accurate mathematical model for a system. Even though a reinforcement learning (RL) method was developed to deal with these issues, it often experiences slow convergence in the presence of large uncertainties. Thus, we propose a slide RL which combines the sliding mode control with RL to be robust to the uncertainties. The structure of a sliding mode control is introduced to the action in RL while an auxiliary sliding variable is included in the state information. Numerical simulation results show that the slide RL provides comparable performance to the model-based consensus control in the presence of unknown time-varying delay and disturbance while outperforming existing state-of-the-art RL-based consensus algorithms.

• Journal of Korean Elementary Science Education
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• v.34 no.2
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• pp.252-263
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• 2015

This study analyzed the effects of science outdoor activity applying a Brain-Based Evolutionary (ABC-DEF) approach on elementary school students' interest and academic achievement. Samples of the study were composed of 3 classes of 67 sixth graders in Seoul, Korea. Unit of 'Ecosystem and Environment' was selected as a object of the research. Textbook- and teachers' guidebook-based instruction was implemented in comparison group, brain-based evolutionary approach within classroom in experimental group A, and science outdoor learning by a brain-based evolutionary approach in experimental group B. In order to analyze the quantitative differences of students' interests and achievements, three tests of 'General Science Attitudes', 'Applied Unit-Related Interests', and 'Applied Unit-Related Achievement' were administered to the students. To find out the characteristics which would not be apparently revealed by quantitative tests, qualitative data such as portfolios, daily records of classroom work, and interview were also analyzed. The major results of the study are as follows. First, for post-test of interest, a statistically significant difference between comparison group and experimental group B was found. Especially, the 'interests about biology learning' factor, when analyzed by each item, was significant in two questions. Results of interviews the students showed that whether the presence or absence of outdoor learning experience influenced most on their interests about the topic. Second, for post-test of achievement, the difference among 3 groups according to high, middle, and low levels of post-interest was not statistically significant, but the groups of higher scores in post-interest tends to have higher scores in post-achievement. It can be inferred that outdoor learning by a brain-based evolutionary approach increases students' situational interests about leaning topic. On the basis of the results, the implications for the research in science education and the teaching and learning in school are discussed.

• Journal of The Korean Society of Integrative Medicine
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• v.2 no.2
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• pp.89-96
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• 2014

Purpose : In this study, we selected three research subjects to attempt to clear learning motivation of college students is what impact the stress coping style and stress test. First, age, gender, the future career after graduation, the presence or absence of part-time job is, its impact on learning motivation. Second, learning motivation is what effect the stress of the test. Third, based on the motivation of learning, how deal pursuing efforts form the social support, the center of the problem-solving approach, seeking to avoid the reaction to stress how different form. Methods : K University occupational therapy and one, two, three grade 100 students (male 22 people, female 78) to target age, sex, and after graduation, part-time status, motivation, stress, stress coping style questionnaire for distribution and was written. Results : First of all, women's social support form graduation course, more robust than pursue blank after the synchronization uncertainty and stress, and graduated from the trading center and avoid the use of career, more form. Second, motivation and stress test, a difference between the notice could not see. Third, the higher the motivation of learning, problem-solving, Action form to the center to use as many as you, but avoid using too much in the center form is addressed. Conclusion : As a result of the study that came out of the course after graduating from ensure that learning motivation is high, the more the uncertainty, the more to cope with stress in the center of the form to avoid form address was used. Because of this, the student careers after graduation, to make sure that can help you to compare efforts over is believed to be necessary.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.151-157
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• 2018

Most previous studies of software fault prediction have focused on supervised learning models for binary classification that determines whether an input module has faults or not. However, binary classification model determines only the presence or absence of faults in the module without considering the complex characteristics of the fault, and supervised model has the limitation that it requires a training data set that most development groups do not have. To solve these two problems, this paper proposes severity-based ternary classification model using unsupervised learning algorithms, and experimental results show that the proposed model has comparable performance to the supervised models.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.254-260
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• 2022

The purpose of this study was to identify the obstacles facing gifted students with learning disabilities (GSLDs) from the point of view of their teachers in the Makkah region and to find suggested solutions to overcome these obstacles. The study covered Makkah, Jeddah and Taif and used semi-structured interviews which included open-ended questions. The study findings indicated that there were several educational obstacles including the absence of adapted courses or specialized teachers for GSLDs category and the insufficient time for the students to express their talents. According to the findings, there were also societal obstacles including the society's failure to expect the presence of talents along with disabilities, or its denial or rejection of their talents in addition to ridiculing them. The findings also confirmed the existence of administrative obstacles including the lack of community partnership. There were also family obstacles such as the family's lack of encouragement for the students, and ignorance of the nature of GSLDs. The study came up with a number of solutions and proposals related to awareness, educational institutions, education and competitions for talented people with learning disabilities.

• Computers and Concrete
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• v.30 no.1
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• pp.43-74
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• 2022

Machine learning technique is recently opening new opportunities to identify the complex shear transfer mechanisms of reinforced concrete (RC) beam members. This study employed 1224 shear test specimens to train decision tree-based machine learning (ML) programs, by which strong correlations between shear capacity of RC beams and key input parameters were affirmed. In addition, shear contributions of concrete and shear reinforcement (the so-called V_c and V_s) were identified by establishing three independent ML models trained under different strategies with various combinations of datasets. Detailed parametric studies were then conducted by utilizing the well-trained ML models. It appeared that the presence of shear reinforcement can make the predicted shear contribution from concrete in RC beams larger than the pure shear contribution of concrete due to the intervention effect between shear reinforcement and concrete. On the other hand, the size effect also brought a significant impact on the shear contribution of concrete (V_c), whereas, the addition of shear reinforcements can effectively mitigate the size effect. It was also found that concrete tends to be the primary source of shear resistance when shear span-depth ratio a/d<1.0 while shear reinforcements become the primary source of shear resistance when a/d>2.0.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3944-3951
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• 2021

Several reasons such as no free lunch theorem indicate that there is not a universal Feature selection (FS) technique that outperforms other ones. Moreover, some approaches such as using synthetic dataset, in presence of large number of FS techniques, are very tedious and time consuming task. In this study to tackle the issue of dependency of estimation accuracy on the selected FS technique, a methodology based on the heterogeneous ensemble is proposed. The performance of the major learning algorithms of neural network (i.e. the FFNN-BR, the FFNN-LM) in combination with the diverse FS techniques (i.e. the NCA, the F-test, the Kendall's tau, the Pearson, the Spearman, and the Relief) and different combination techniques of the heterogeneous ensemble (i.e. the Min, the Median, the Arithmetic mean, and the Geometric mean) are considered. The target parameters/transients of Bushehr nuclear power plant (BNPP) are examined as the case study. The results show that the Min combination technique gives the more accurate estimation. Therefore, if the number of FS techniques is m and the number of learning algorithms is n, by the heterogeneous ensemble, the search space for acceptable estimation of the target parameters may be reduced from n × m to n × 1. The proposed methodology gives a simple and practical approach for more reliable and more accurate estimation of the target parameters compared to the methods such as the use of synthetic dataset or trial and error methods.