• Sleep Medicine and Psychophysiology
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• v.1 no.1
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• pp.20-28
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• 1994

The field of applied biofeedback as one of psychophysiological self regulation techniques began in the united states in 1950s. Biofeedback may be described as information about the effects of a response that is given to the person making that response in order to improve ways of controlling that response. This article reviewed various definitions of biofeedback, learning models, mediating processes, instrumentations to be considered during biofeedback practice, treatment procedures and clinical applications.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.289-291
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• 2002

Host of source separation methods focus on stationary sources so higher-order statistics is necessary In this paler we consider a problem of source separation when sources are second-order nonstationary stochastic processes . We employ the natural gradient method and develop learning algorithms for both 1inear feedback and feedforward neural networks. Thus our algorithms possess equivariant property Local stabi1iffy analysis shows that separating solutions are always locally stable stationary points of the proposed algorithms, regardless of probability distributions of

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.718-724
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• 1991

In this paper, we proposed an algorithm to improve the memory efficiency by means of learning thresholds in spite of correlations among input patterns to be memorized. The proposed algorithm does not need preprocess correlations among input patterns but processes them with a threshold on a neural network. When memory contents are destroyed by correlation, nearly all patterns can be properly recovered with past learning. Through experiments we show how out algorithm can improve the memory efficiency.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.120-126
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• 2020

Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.769-779
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• 2020

Self-efficacy has been extensively evaluated, but no studies have investigated the effect of self-efficacy on the self-reliance of women in poor-households economic productivity. This study analyzes self-efficacy as a personal factor, learning processes, and social support as an environmental factor towards the achievement of self-reliance in women from poor-households in productive economy businesses. Despite the dominant logic of this scheme, there is a need for field-based data regarding whether the variable really supports the sustainable empowerment of poor-households women. This study used the quantitative method through the survey technique. The samples of this study included 250 people collected from five regencies in Indonesia by using a multiple-stage random sampling. The data were analyzed with structural equation modeling. The results show that social support has a significant positive impact on the learning process; social support has a direct negative impact on self-efficacy. The learning process has a direct positive influence on self-efficacy, while social support has a non-significant impact on self-reliance. The learning process has a direct influence on self-reliance. Social support and the learning process both have significant positive impact on self-efficacy. Social support, learning process, and self-efficacy simultaneously have a positive impact on self-reliance in productive economic activities.

• Journal of Korean Elementary Science Education
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• v.25 no.4
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• pp.407-418
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• 2006

The purpose of this study was to survey the problem of teachers' narrative reporting of children's science learning in elementary school report cards. For the purposes of this study, a questionnaire, comprised of 6 questions and an analysis tool (Cronbach's $\alpha=.70$) were developed to categorize the answers. The survey was conducted by 53 teachers, who are currently taking 5th ade in elementary school, and the results are as follows: First, they interpreted the same content of report cards in a variety of different ways. Second, they exhibited a number of different principles and criteria in terms of preparing the content of narrative report cards. Third, they experienced difficulties in preparing narrative report cards on science teaming which required explanation of complete processes. Fourth, most teachers surveyed answered that the content of their narrative reports on science learning did not communicate specifically the students' achievement and further studies. Fifth, the activities related to preparing the content of the science learning on narrative reports was widely perceived to be useless for teachers' professional development. Finally, teachers made a number of alternative proposals to overcome the current, perceived problems of teachers' narrative reporting for children's science learning in report cards. Based on the results of this analysis, alternative forms and content of narrative reports on science learning were discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.742-746
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• 2006

Evaluation of learning ability of students is classified a step of diagnostic, formative and summative evaluation. This step-by-step evaluation is the standard of synthesis judgement, from a student's prior learning of preparation state to devotion of learning process and even learning result. In this paper, we propose the method of synthesis learning evaluation which is considered evaluation of each step in using fuzzy inference. In order to get objective evaluation of learning ability, we applied to the weights by evaluation steps. And we reflected defuzzification values of final evaluation membership function interval obtained by fuzzy inference about diagnostic, formative and summative evaluation. As a result, it processes definite inference ensures objectivity and shows validity of the synthesis evaluation method.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.209-217
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• 2019

Due to the development of artificial intelligence and image recognition technology that play important roles in the field of 4th industry, office automation systems and unmanned automation systems are rapidly spreading in human society. The proposed algorithm first finds the variances of the differences between the tile values constituting the learning characters and the experimental character and then recognizes the experimental character according to the distribution of the three learning characters with the smallest variances. In more detail, for 100 learning data characters and 10 experimental data characters, each character is defined as the number of black pixels belonging to 15 tile areas. For each character constituting the experimental data, the variance of the differences of the tile values of 100 learning data characters is obtained and then arranged in the ascending order. After that, three learning data characters with the minimum variance values are selected, and the final recognition result for the given experimental character is selected according to the distribution of these character types. Moreover, we compare the recognition result with the result made by a neural network of basic structure. It is confirmed that satisfactory recognition results are obtained through the processes that subdivide the learning characters and experiment characters into tile sizes and then select the recognition result using variances.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.216-222
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• 2021

Advances in technology have given educators a tool to empower them to assist with developing the best possible human resources. Teachers at universities prefer to use more modern technological advances to help them educate their students. This opens up a necessity to research the capabilities of cloud-based learning services so that educational solutions can be found among the available options. Based on that, this essay looks at models and levels of deployment for the e-learning cloud architecture in the education system. A project involving educators explores whether gement Systems (LMS) can function well in a collaborative remote learning environment. The study was performed on how Blackboard was being used by a public institution and included research on cloud computing. This test examined how Blackboard Learn performs as a teaching tool and featured 60 participants. It is evident from the completed research that computers are beneficial to student education, especially in improving how schools administer lessons. Convenient tools for processing educational content are included as well as effective organizational strategies for educational processes and better ways to monitor and manage knowledge. In addition, this project's conclusions help highlight the advantages of rolling out cloud-based e-learning in higher educational institutions, which are responsible for creating the integrated educational product. The study showed that a shift to cloud computing can bring progress to educational material and substantial improvement to student academic outcomes, which is related to the increased use of better learning tools and methods.

• Korean Journal of English Language and Linguistics
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• v.2 no.3
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• pp.373-401
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• 2002

It is often observed that Korean migrant students overseas experience various kinds of anxieties learning English as a second language although they are in an English-speaking country like New Zealand. The context of learning English as a second language is explored by examining language anxieties experienced by recent Korean migrant students in New Zealand. 177 students were surveyed using questionnaires asking their anxieties over various contexts of English learning processes. The three stages of language anxiety of Input, Processing, and Output showed that there were some degrees of anxiety among the students at each stage depending on their ages, age at migration, and duration of residence, in particular. Students tended to experience more language anxiety in school than outside the school. It was also clear that students were experiencing more anxieties with English than with Korean in the four language skills of speaking, listening, reading and writing. Writing was commonly found in English and Korean to be the most frequent source of anxiety among the four language skills. Some implications from the results are suggested for parents, teachers, and students.