• Journal of Korean Home Economics Education Association
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• v.30 no.1
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• pp.43-63
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• 2018

The purpose of this study is to examine the various contexts affecting life culture through practical reasoning process and to select the goal and contents system of unification education in middle school home economics to form healthy unification community and to develop teaching and learning process. Based on the Unification Education Guidelines, Unification Education Pre-Study, Pre-Study on North Korean Defectors, and Analysis of the 2015 Revision Home Economics Curriculum in Korea, Goal and content system. Based on this, we developed a teaching and learning process and a student activity place applying practical reasoning process after extracting practical problems, and prepared a final development plan based on the results of two expert group evaluations. The results of this study are summarized as follows. First, the goal of unification education in the middle school home economics class is to 'Based on the social-cultural context, we develop the ability to cultivate healthy reunification by respecting the differences between the cultures of the two Koreas and discovering common values in a unified society and resolving practical issues in a unified society.'. Second, the content system of middle school home economics unification education was selected as the core theme of 'Unification Education Focused on the Living Culture'. The content elements were comprehending the socio - cultural context that affects the life culture of the two Koreas, Related language, maintenance of diversity of dietary culture in each region including North Korean food, social norms and attire, correct housing value and common living etiquette. Based on the goals of unification education in the middle school home school curriculum, we selected practical issues as 'What should we do to create a healthy unified community?'. Third, the teaching and learning process of unification education in junior high school home economics education is to recognize the problem of unification, to analyze the factors affecting the life culture of the two Koreas, to grasp the effect of the action and the ripple effects, to select alternative methods, And 4 subjects for 8 teaching learning course plan, and 35 teaching materials.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1978.06a
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• pp.9.2-9
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• 1978

Monaural and binaural hearing aid performance under quiet and noisy conditions were compared in regard to (1) the degree of hearing impairment, (2) the symmetry of pure tone audiogram, (3) the automatic gain control of the hearing aid. (4) hearing impairement with recruitment and, word discrimination ability. Performance using binaural hearing aids was consistently superior to that using monaural hearing aids. The results were as follows. 1. Speech detection thresholds were enhanced by a mean of 4.25dB when tested with danavox 747 PP stereo type hearing aid and by a mean of 4.12 dB when tested hearing aids connected seperately to the right and left ears. 2. Binaurally tested speech reception thresholds were superior to monaurally tested thresholds by a mean of 3.56dB when tested in quiet and by a mean of 5.56dB when tested in noise. 3. Binaurally tested word discrimination scores were also superior by a mean of 17.09% in quiet and by a mean 19.63% in noise. 4. Both SRT and word discrimination scores were performed best by subjects with moderately-severe impairement. The performance by one mildly impaired subject was the poorest of all performances. The levels of performance order were; moderately-severe loss, severe loss. moderate loss and mild loss. 5. The data obtained using AGC aids when compaired with that of linear amplification show that when AGC aids were worn in both ears. the results were very poor but when one AGC aid was worn in one ear and linear amplification in the other. the results were good. 6. The advantages of binaural hearing aids were obvious even in cases 1) with great diferences in hearing thresholds between right and left ears, 2) when the subject was unable to discriminate words without vision and. 3) when the subject had extreme recruitme t phenomenon.

• Korean Journal of Food Science and Technology
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• v.53 no.3
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• pp.278-289
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• 2021

The rapid aging of society has led to a surge in cognitive dysfunction in the elderly. As there is limited evidence for the development of dementia in medicine, a shift in focus on prevention strategies using bioactive compounds in food is required. This systematic review evaluated the effects of various bioactive compounds on age-associated cognitive decline. The literature was searched for terms related to bioactive compounds in cognitive decline and article selection was limited to clinical randomized controlled trials for a single bioactive compound. We identified 21 studies that evaluated the strength of the evidence. ω-3 fatty acids and vitamin B presented a strong evidence level, whereas vitamin D and E, anserine/carnosine, and chromium were defined as having moderate levels of evidence. ω-3 fatty acids relieved cognitive decline and reduced amyloid β-related protein accumulation. Vitamin B decreased homocysteine levels, which is accompanied by alleviation of cognitive function. In conclusion, ω-3 and vitamin B have the potential to improve age-associated cognitive decline.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.