The Journal of the Convergence on Culture Technology
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v.6
no.1
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pp.63-68
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2020
The need for literal education, matching the rapid changes in the media has been increasing in recent years. However, it is true that not enough research has been done on the efficiency of literacy compared to the increasing need. For example, empirical approaches such as studies on the effects of integrated media literacy on youth learning. Thus, this paper took multimedia education, which is different from existing image education, as a subject of research and studied the results of education that fused text and video and sound to teenagers in terms of learning effectiveness. It is an academic quest to see if multimedia education really has positive ㄷ effect for teenagers' learning. As a result of both quantitative and qualitative research as a method of research, multimedia education was concluded to be meaningful in improving learning ability, and based on this, it presented a practical-oriented learner participation education while expanding appearance such as language education through multimedia education. The suggestions for these various education policies will spread to the confidence that multimedia education can be the center of all learning activities as the core of education that achieves an all-round personality, not just an aid to existing education.
Recently, the neural network-based deep learning algorithm has dramatically improved performance compared to the classical Gaussian mixture model based hidden Markov model (GMM-HMM) automatic speech recognition (ASR) system. In addition, researches on end-to-end (E2E) speech recognition systems integrating language modeling and decoding processes have been actively conducted to better utilize the advantages of deep learning techniques. In general, E2E ASR systems consist of multiple layers of encoder-decoder structure with attention. Therefore, E2E ASR systems require data with a large amount of speech-text paired data in order to achieve good performance. Obtaining speech-text paired data requires a lot of human labor and time, and is a high barrier to building E2E ASR system. Therefore, there are previous studies that improve the performance of E2E ASR system using relatively small amount of speech-text paired data, but most studies have been conducted by using only speech-only data or text-only data. In this study, we proposed a semi-supervised training method that enables E2E ASR system to perform well in corpus in different domains by using both speech or text only data. The proposed method works effectively by adapting to different domains, showing good performance in the target domain and not degrading much in the source domain.
Objectives: The purpose of this study was to investigate career competency, tasks, and job satisfaction of public servants, public institutions, and researchers. Methods: The survey was conducted about career competency, job satisfaction, and satisfaction on work life. Next, they interviewed on the characteristics of each job by two or three dimensions. The following conclusions were obtained from July to August 2017. Results: Career competencies were GPA with 3.87, 818 points of TOEIC score, and ITQ certification. Public servants required the information on literacy skills for employment and job performance, while civil servants need more than one year of clinical experience in the dental hospital. The non-commissioned officer needed a written test and fitness training. The health insurance review and assessment center required more than one year of experience from general hospital or medical institutions. Researchers required a research career, language skill, and professors required research and teaching experiences with clinical experience more than three years. The main job tasks were as follows; for public servants, they were official document processing and community projects. For the civilian workers and military/noncommissioned officers, they were medical assistant and administrative works. The employees of the health insurance review and assessment service are examining the medical expenses and the medical examination, the researchers are experimenting, researching and writing articles, and the teaching staff are lecturing and conducting individual research. Conclusions: The results of job satisfaction survey showed that occupational satisfaction was the highest in civil servants, researchers, and teaching professions. Job security was the highest in health workers and health inspectors' evaluation centers, and time vacancy was the highest in civilian workers and military/noncommissioned officers. If you want to work in such an institution, you should prepare elements that match your basic literacy and job specific characteristics. And we should try to increase the satisfaction of work even after work.
Lee, Jae Hueng;Kim, Ji Hee;Jung, Jae Hun;Jo, Min Gun;Lee, Eun Mi
Journal of Korean Medical Ki-Gong Academy
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v.16
no.1
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pp.1-58
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2016
Objects : The purpose of this study is to understand trends of "Qigong"-related study since 2008 and to help guide the research direction of Qigong study. Methods : The computerized Korean database was searched from January 2008 until September 2016. The search terms used were 'Qi', 'Qigong', 'Doin', 'Meditation', 'bioenergy', 'training', 'life nurturing' and random or Korean language terms. Results : 1. A total of 140,914 studies were searched in this study. A total of 2,147 studies were finally selected as Qigong-related studies. 2. The average number of Qigong-related studies published in Korea since 2008 is 252.6 per year and there was no significant difference in the number of studies published by year 3. Results according to the subject categories, 805 cases were in the humanities and 2 cases were in the agriculture & maritime field. 4. Results according to the middle subject categories, philosophy was the largest with 280 studies. 5. As a result of Qigong categories showed that meditation was the highest with 1,043 (48.58%) not including duplication. 6. As a result of research method, the most frequent method was Analysis research with 1,138(53.00%) cases and the experimental research was the least with 118(5.50%) cases. 7. When the authors were investigated, the result was the most in 35 cases by Kim Byung-chae. 8. The journal that published the most Qigong-related studies was "J. of The Studies of Taoism and Culture" (52), and Dongguk University (75) had the largest number of Qigong-related studies. Conclusions : 1. Since 2008, there is no significant difference between the yearly and yearly the number of Qigong-related studies. 2. Since 2008, Qigong-related studies have been the most successful in the field of humanities, but it has been regularly published in various other field. 3. Since 2008, Qigong-related studies has shown a remarkable decline in category on External Qigong Therapy(外氣發功) and Science of Qi(氣科學). However, category on Nae-Dan(內丹), meditation, Do-In (導引) has continued steadily every year. And did not show a tendency to increase or decrease.
Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.
The purpose of this study is to investigate the impact of semi-closed vocal training-based Vocal Aerobic Treatment on the voice improvement of soprano. Study subject was one soprano who appealed to the suffering of her voice problem due to vocal cord nodule. A study method of conducting pre/post acoustic evaluation and subjective voice evaluation to compare the measures was used; Vocal Aerobic Treatment was carried out twice a week for a total of 32 session. In the acoustic evaluation, MDVP (multi-dimensional voice program) and VRP (voice range profile) were used to evaluate the pitch, voice quality, and voice range; in the subjective voice evaluation, SVHI (singing voice handicap index) was used to assess voice satisfaction. As a result of the pitch evaluation, the soprano maintained a proper Fo. As a result of the voice quality evaluation, the jitter, shimmer, and the noise harmonic ratio numbers decreased compared to the numbers shown before the treatment. As a result of the voice range evaluation, the scope of the range was broadened, with the number of semitone increasing from 30 to 35. As for the subjective voice evaluation, the result of the total score obtained after the survey report divided by the number of questions showed a decrease from 3.6 to 0.6. The soprano herself reported of having a minor extent of a voice problem. The summary of the above results reflects that Vocal Aerobic Treatment is useful in the voice improvement of vocalists However, as this study is case research regarding the Vocal Aerobic Treatment effect on one soprano, further research on the treatment effect covering many other vocalists is necessary. Also, there is a need for follow-up studies regarding voice management and voice treatment program on not only the vocalists but also the voice users in many other professions.
Objective: The purpose of this study was to systematically arrange previous ones on developmental effects of play in early childhood through a meta-analysis. Methods: For this purpose, the researchers searched for variety of databases and analyzed 110 studies, which were 90 graduate theses and 20 journals from 2005-2016. Results: First, the total developmental effect size of infant play was 1.21, with the effect size of the experimental group being 38.7% higher than that of the control group. The total developmental effect size was .81, however when inserted effect size was calculated, so it was supposed that the current effect size might be decreased, if missing studies were included. Second, effect size appears in all developmental areas, though actual effect size of sub-factors of child development tends to be mostly decreased: The fall in physical development fell down from 1.28 to .95 that emotional development was 1.42 to .86. The fall in social development was considerable from 1.13 to .85 that cognitive development was 1.19 to 1.07. In language development, it didn't change much. It stayed about the same as 1.30. The fall In creativity development stood at just below from 1.00 to .69. Third, effect size by moderating variables was examined to show that there were statistically significant difference in measurement, age, total number of training and types of activities between two groups. Conclusion/Implications: The results of this study have an implication, in that the study verified that infant play reflects and promotes child development and functions as a tool for developmental change, by illuminating effects of it child development.
An end-to-end speech recognition model consisting of a single integrated neural network model was recently proposed. The end-to-end model does not need several training steps, and its structure is easy to understand. However, it is difficult to understand how the model recognizes speech internally. In this paper, we visualized and analyzed the attention-based end-to-end model to elucidate its internal mechanisms. We compared the acoustic model of the BLSTM-HMM hybrid model with the encoder of the end-to-end model, and visualized them using t-SNE to examine the difference between neural network layers. As a result, we were able to delineate the difference between the acoustic model and the end-to-end model encoder. Additionally, we analyzed the decoder of the end-to-end model from a language model perspective. Finally, we found that improving end-to-end model decoder is necessary to yield higher performance.
The purpose of this study is to show an example of the integrated application of The Transactional Analysis and Psychodrama in order to help various experimental attempts and Empowering of psychodramatists. The Drama Triangle, a game model developed by Kaufman, can be well explained through the Psychodrama. Linda Condon introduced role reversal, mirroring, and auxiliary ego, double ego technique that helps act in psychodrama through a model for restoring dysfunction. The Acting out of Psychodrama provides emotional experiences and experiences that can not be presented in Transactional analysis. Through the couching technique Psychodrama, it is possible to accurately inform the situation of the victim, the persecutor, and the rescuer who plays the psychological game. Also, couching technique can perform role training for solution. The concept of the ego state of The Transactional analysis can be useful for the director to understand the Protagonist's language and attitude and to set the scene. This paper shows an example of the application of the Transactional Analysis approach and the Psychodrama integration through the act of the drama triangle game, which is the concept of Transactional Analysis, and it is meaningful to propose a circular relationship framework of the role developed by the author .
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.15
no.1
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pp.56-61
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2022
In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.
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