• Journal of Korea Game Society
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• v.19 no.3
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• pp.65-74
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• 2019

This study presented specific alternatives for the use of digital storytelling elements as college education and provided basic data for future Serious games to be more popularized and used as reference materials in various academic circles by considering the criteria for the quality evaluation of game contents, which had been pointed out as limitations of functional games. In particular, the factors to be considered were mainly in developing functional games to learn the clinical reasoning process.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.186-198
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• 2019

The means to train plan of local culture promotion personnel through the migrant women refers to the knowledge education of local cultural personnel through the accurate recognition of Korean culture and local culture and related information to foreign immigrants and workers in each region of the country. Through education courses in four areas, such as international manners, local promotion education, cultural heritage, and experience learning, the immigrant women will present a leading direction in which they can expect to play a role as experts in regional culture and public relations through the mother country's language.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.82-86
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• 2021

The article analyzes the psychological and pedagogical scientific literature on the problem of motivation of students' educational activity, compiled and implemented a diagnostic research program, studied the system of conditions for the development of motivation for educational activity of students, compiled and implemented a program for the development of motivation for educational activity of students, highlighted the features of motivation for educational activity of students and conducted a comparative study analysis.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.500-509
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• 2022

With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers' professional skills in an accelerated manner and perfect the education system.

• Annual Conference of KIPS
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• 2022.11a
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• pp.113-115
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• 2022

치과 진료는 대부분 인간의 시각에 의존하여 진단과 진료가 이루어진다. 하지만 미세한 치아 손상의 경우 의사가 육안으로 확인하기 어려울 수 있으며, 의사의 실력 및 피로 누적에 의해 조기에 발견을 하지 못할 가능성이 높아진다. 만약 미세한 치아 손상을 조기에 발견하지 못할 경우 시간이 지남에 따라 손상 부위가 커지고, 이를 치료하기 위해 더 큰 비용과 고통이 따르기 때문에 치과에서의 조기 발견이 매우 중요하다. 한편, 인류는 디지털 헬스케어 기술을 개발하여 보다 정확한 진단을 할 수 있게 되었고, 의료 서비스를 효율적으로 제공할 수 있게 되었다. 이에 본 논문에서는 위의 문제를 해결하기 위해 디지털 헬스케어를 사용하여 빅데이터와 딥러닝을 활용한 지능형 전자 루페에 대해 탐구하였다.

• Annual Conference of KIPS
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• 2023.05a
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• pp.493-495
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• 2023

Deep learning methods and attention mechanisms have been incorporated to improve facial emotion recognition, which has recently attracted much attention. The fusion approaches have improved accuracy by combining various types of information. This research proposes a fusion network with self-attention and local attention mechanisms. It uses a multi-layer perceptron network. The network extracts distinguishing characteristics from facial images using pre-trained models on RAF-DB dataset. We outperform the other fusion methods on RAD-DB dataset with impressive results.

• Annual Conference of KIPS
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• 2023.11a
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• pp.587-588
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• 2023

최근 텍스트 생성형 인공지능인 ChatGPT가 화두가 되면서 생성형 인공지능을 이용한 서비스에 사람들의 관심이 높아졌다. 이를 활용하여 시간과 비용이 많이 드는 분야인 외국어 작문 학습을 자기 주도적으로 학습할 수 있을 것이라 조망하였다. 따라서 텍스트 생성형 인공지능인 ChatGPT API를 활용하여 사용자가 자기 주도적으로 외국어를 학습할 수 있는 방향성을 제시하고 더욱 쉽고 저렴한 비용으로 외국어를 익힐 수 있도록 하는 시스템을 개발한다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.59-87
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• 2023

The aim of this study is to provide practical instances of implementing picture book reading sessions within school libraries to enhance language proficiency and foster emotional stability among lower-grade multicultural students hailing from foreign backgrounds. The research outlines the design and execution of a picture book reading program tailored for multicultural students, with analysis based on the outcomes of actual classroom implementations. In the course of the study, existing literature pertaining to the use of picture books for enhancing multicultural education and language skills was reviewed. This informed the development of a structured class procedure by extracting core components. Indeed, 43 multicultural students in five classes in the first and second grades of A Elementary School in Gyeonggi-do were given three pilot classes for each class for 20 weeks and a total of 100 picture book reading classes, each with 17 main lessons. This study establishes the positive impact of picture book reading classes on the Korean language comprehension of multicultural students. The results confirm positive improvements in students' ability to understand Korean, as evidenced by enhanced Korean expression and presentation skills, increased library usage, and a positive shift in classroom attitude. The procedure for reading picture books using school libraries proposed in this study was actually conceived and developed in the course of class operation in the school education field, reflecting the changes brought about by the increase of multicultural students and the need to improve the class environment. Through this practical investigation, important insights have been extracted regarding how picture book reading sessions designed for elementary school students from multicultural backgrounds can enhance the classroom environment and elevate learning outcomes.

• 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.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.