• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.512-520
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• 2019

It is quite useful to represent speeches visually for learners who study foreign languages as well as the hearing impaired who cannot directly hear speeches, and a number of researches have been presented in the literature. They remain, however, at the level of representing the characteristics of speeches using colors or showing the changing shape of lips and mouth using the animation-based representation. As a result of such approaches, those methods cannot tell the users how far their pronunciations are away from the standard ones, and moreover they make it technically difficult to develop such a system in which users can correct their pronunciation in an interactive manner. In order to address these kind of drawbacks, this paper proposes a speech visualization model based on the relative distance between the user's speech and the standard one, furthermore suggests actual implementation directions by applying the proposed model to the visualization of Korean vowels. The method extract three formants F1, F2, and F3 from speech signals and feed them into the Kohonen's SOM to map the results into 2-D screen and represent each speech as a pint on the screen. We have presented a real system implemented using the open source formant analysis software on the speech of a Korean instructor and several foreign students studying Korean language, in which the user interface was built using the Javascript for the screen display.

• The Korean Journal of Psychodrama
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• v.21 no.2
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• pp.73-95
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• 2018

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 .

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.4
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• pp.325-336
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• 2019

There are many bamboo weir (Juk-Bang-Ryeum) with the highest preservation value as a fisheries heritage from Sacheon to Namhae area in the Korea Hanrye National Marine Park. It was designated as a Korea National Cultural Property Sightseeing No. 71, and also as an important fishery asset listed in the Korea National Important Fisheries Heritage No. 3. It is an important cultural heritage that should be preserved for the future as a community asset to the local residents, and should be preserved as it's original form because of unique traditional fishery style in the world as well as natural environment oriented fishing system. The purpose of this study is to review the value of Juk-Bang-Ryeum in the South Sea as well as to preserve the tradition of it. This paper will make a contribution to the registration of it on the list of World Important Agricultural and Fishery Heritage (GIAHS), which is recognized by the United Nations Food and Agriculture Organization (FAO). To make basic data for listing on it, we will analyze the characteristics and structure of Juk-Bang-Ryeum, and also research the value of it from the historical literature review as well state of arts. We also develop a scheme for listing on FAO GIAHS through checking necessary items step by step. Finally, we suggest some idea to preserve it more effectively.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.12
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• pp.439-451
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• 2019

This study is about the historical records of anchovy which has fluent nutritions as well as the representative side dish in Korean food culture and life. The formal first record about anchovy is in the Uhaeieobo written by Damjeung in 1803. Another important historical record about anchovy are Hyeonsaneobo(Jasaneobo) written by Jeong Yak-jeon in 1814, and Eomyeonggo(Fish name list) of Nanhoeomogji written by Seo Yu-gu in 1820. The anchovies were used for food in Korea even before the Chosun Dynasty, but they were not noticed by people. Because at that time, fishing tools and instruments such as nets were not developed enough to raise enough catches and food processing technology were not developed. Since then, in the Japanese colonial era, it has been actively developing agricultural fertilizers using anchovies. In addition, the processing technology that can be used as an edible food using anchovy has been rapidly developed. Now, the anchovy industry has very important position in Korea's fisheries industry. Among them, 'Jukbangryum anchovy' catching bamboo weir tool which has been existed for over five hundred years in Namhae province, not only creates great high economic value, but also has cultural value. Therefore, the historical literature study on anchovy can be used as an invaluable resource not only for the study of fishery from an industrial point of view, but also for the registration of world cultural heritage and GIAHS (Globally Important Agricultural Heritage System) of 'Jukbangryum' which is traditional fishery catching instrument in Korea.

• Smart Media Journal
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• v.11 no.5
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• pp.17-25
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• 2022

Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.728-737
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• 2021

In the meantime, broadcasting CG has gone through the process of dismantling, changing, and distorting, while broadcasting CG in broadcasting programs utilizes the expanded background of 'temporality' and 'formality'. This is to create an audiovisual language that appeals to human synesthesia by expressing the meaning to be conveyed in three dimensions. Broadcast CG goes beyond simple instructional and informational broadcast graphic operation, and increases the pure aesthetic value and sensibility of the video considering readability and formativeness, and through this, the audiovisual information perfection of the broadcast program is derived and acts as a very important factor. Therefore, this paper examines the results of broadcast CG production and utilization methods at existing local broadcasters, and identifies the limitations of local broadcasters' CG production and utilization through case analysis for each broadcast program type. We want to derive a model that is a compromise line. In addition, I would like to suggest a plan that can be applied more actively and practically to local broadcasting programs. In order to solve this problem, this study first examines "Analysis of cases of use of broadcasting CG production in broadcasting programs" and then "more efficient broadcasting CG production techniques by identifying problems in broadcasting CG production methods and utilization of local broadcasters" and how to actively use it". In addition, the results of this study are expected to contribute to the establishment of a new role and practical broadcast CG production model for broadcast graphic designers in charge of broadcast CG production and the technical perspective of broadcast program production by local broadcasters.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.153-162
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• 2022

Relevance. Innovative activities in education should be aimed at ensuring the comprehensive development of the individual and professional development of students. The main idea of modular technology is that the student should learn by himself, and the teacher manages his learning activities. The advantage of modular technology is the ability of the teacher to design the study of the material in the most interesting and accessible forms for this part of the study group and at the same time achieve the best learning results. Innovative Moodle technology. it is gaining popularity every day, significantly expanding the space of teaching and learning, allowing students to study inter-faculty university programs in depth. The purpose of this study is to assess the quality of implementation of the e-learning system Moodle. The study was conducted at the South Ukrainian National Pedagogical University named after K. D. Ushinsky in order to identify barriers to the effective implementation of innovative distance learning technologies Moodle and introduce a new model that will have a positive impact on the development of e-learning. Methodology. The paper used a combination of theoretical and empirical research methods. These include: scientific analysis of sources on this issue, which allowed us to formulate the initial provisions of the study; analysis of the results of students 'educational activities; pedagogical experiment; questionnaires; monitoring of students' activities in practical classes. Results. This article evaluates the implementation of the principles of distance learning in the process of teaching and learning at the University in terms of quality. The experiment involved 1,250 students studying at the South Ukrainian National Pedagogical University named after K. D. Ushinsky. The survey helped to identify the main barriers to the effective implementation of modern distance learning technologies in the educational process of the University: the lack of readiness of teachers and parents, the lack of necessary skills in applying computer systems of online learning, the inability to interact with the teaching staff and teachers, the lack of a sufficient number of academic consultants online. In addition, internal problems are investigated: limited resources, unevenly distributed marketing advantages, inappropriate administrative structure, and lack of innovative physical capabilities. The article allows us to solve these problems by gradually implementing a distance learning model that is suitable for any university, regardless of its specialization. The Moodle-based e-learning system proposed in this paper was designed to eliminate the identified barriers. Models for implementing distance learning in the learning process were built according to the CAPDM methodology, which helps universities and other educational service providers develop and manage world-class online distance learning programs. Prospects for further research focus on evaluating students' knowledge and abilities over the next six months after the introduction of the proposed Moodle-based program.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.109-117
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• 2023

Schedule delays present a major risk factor, as they can adversely affect construction projects, such as through increasing construction costs, claims from a client, and/or a decrease in construction quality due to trims to stages to catch up on lost time. Risk management has been conducted according to the importance and priority of schedule delay risk, but quantification of risk on the depth of schedule delay tends to be inadequate due to limitations in data collection. Therefore, this research used the BERT (Bidirectional Encoder Representations from Transformers) language model to convert the contents of aconstruction log, which comprised unstructured data, into WBS (Work Breakdown Structure)-based structured data, and to form a model of classification and quantification of risk. A process was applied to eight highway construction sites, and 75 cases of rain schedule delay risk were obtained from 8 out of 39 detailed work kinds. Through a K-S test, a significant probability distribution was derived for fourkinds of work, and the risk impact was compared. The process presented in this study can be used to derive various schedule delay risks in construction projects and to quantify their depth.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1007-1014
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• 2023

Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.