• Journal of dental hygiene science
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• v.21 no.1
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• pp.8-18
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• 2021

The purpose of this study is to provide the general history of fostering dentists in Japan and introducing their new roles. This research was conducted based on the government policy report on dentists and the information published by each educational institution. Based on the collected data, the official websites were used to represent the latest statistics of the institutions. The number of dentists in Japan has increased. The government established the National Examination for Dentists to guarantee the quality of dentists. After the standards for developing questions for the national examination were established in 1985, the contents of the examination have been appropriately improved by revising the standards every four years. This improvement has required dental students to study a variety of subjects for six years at dental school. Since dentists in Japan are required to respond to various demands from the nation; the Model Core Curriculum for Dental Education was developed to teach medical ethics and abilities to ensure that dentists conduct themselves professionally. Recently, the roles of dentists have been changing in Japan. When providing dental services to older patients over the age of 65, dentists and other dental professions focus on maintaining oral functions, such as saliva secretion, bite force, tongue movement, and masticatory/swallowing functions. However, oral function-related services for children are different. In addition to providing essential dental services, dental practitioners also provide special treatment, such as oral muscle training, myofunctional therapy, health guidance, and space retainers to the child patients with developmental insufficiency in oral functions. Dentistry in Japan has undergone numerous changes over the years and has continued to offer high-quality dental health services. Thus, information gained from the Japanese experience may be helpful to dental professions in other developed countries for planning oral health measures.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.680-691
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• 2022

Virtual farm is a kind of virtual reality for education and training, which realizes a change in attitude toward farming and aims for economic performance through revisiting the virtual farm. With the recent introduction of P2E-type virtual reality, a way to connect virtual farming experiences with practical benefits is being considered. However, few studies have been conducted on the factors that influence the success of virtual farms. Hence, the purpose of this study is to examine whether the quality of virtual farm contents and system quality affect user satisfaction with virtual farm experience based on the DeLone & McLean's IS Success Model. In addition, we will examine whether satisfaction with the virtual farm significantly contributes to the change in attitude toward farming. In addition, we demonstrate whether digital incentives contribute to the activation of P2E-type virtual farms.

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.57-62
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• 2022

In order to support women with career breaks to re-enter the labor market, it is not only necessary to discover and select promising jobs, but also to provide objective and accurate job information on selected promising jobs so that women with career breaks can make reasonable career choices. need arises. It can be pointed out that the government support course has no burden of tuition compared to the general course, and because the quality of education is high, it is possible to select trainees with a high willingness to find employment through competition in the recruitment process. In addition, the government support process secures relatively high-quality programs and instructors, increasing trainees' concentration, satisfaction, and willingness to find a job. Job literacy and employment preparation education are obligatory, job design support through job counseling, and continuous follow-up support. The system also works. Accordingly, if systematic and continuous development and support are made in the process of selecting promising occupations for women with career breaks and designing education and training programs, it is expected that women with career breaks will be more active in their re-entry into the labor market.

• Korean Journal of Acupuncture
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• v.39 no.3
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• pp.71-83
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• 2022

Objectives : Instructional design is the systematic approach to the Analysis, Design, Development, Implementation, and Evaluation of learning materials and activities. We aimed to apply the rapid prototyping to instructional systems design (RPISD) in meridianology laboratory, a subject in which students train acupuncture to develop lesson plan. Methods : The needs of the stakeholders including client, subject matter expert and students were analyzed using the performance needs analysis model. Task analysis was implemented by observation and interview. First prototype was drafted and implemented in meridianology laboratory class once. The second prototype was modified from the first, by usability evaluation of the stakeholders. Results : The client requested an electronically documented manual to improve the quality of acupuncture training. The learner requested an extension of practice time and detailed practice guidelines. The main problems of students' performance were some cases of violation of clean needle technique, the lack of communication between the operator and recipient in direct, and lack of confidence in their own performance. Stakeholders were generally satisfied with the proposed first prototype. Second prototype of lesson plan was produced by modifying some contents. Conclusions : A lesson plan was developed by applying the systematic RPISD model. It is expected that the developed instructional design may contribute to the quality improvement of meridianology laboratory education.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.393-398
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• 2022

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint(TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement(ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement(ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.150-150
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• 2023

기작기반의 역학적 모델과 자료기반의 딥러닝 모델은 수질예측에 다양하게 적용되고 있으나, 각각의 모델은 고유한 구조와 가정으로 인해 장·단점을 가지고 있다. 특히, 딥러닝 모델은 우수한 예측 성능에도 불구하고 훈련자료가 부족한 경우 오차와 과적합에 따른 분산(variance) 문제를 야기하며, 기작기반 모델과 달리 물리법칙이 결여된 예측 결과를 생산할 수 있다. 본 연구의 목적은 주요 상수원인 댐 저수지를 대상으로 수심별 수온과 탁도를 예측하기 위해 기작기반과 자료기반 모델의 장점을 융합한 PGDL(Process-Guided Deep Learninig) 모델을 개발하고, 물리적 법칙 만족도와 예측 성능을 평가하는데 있다. PGDL 모델 개발에 사용된 기작기반 및 자료기반 모델은 각각 CE-QUAL-W2와 순환 신경망 딥러닝 모델인 LSTM(Long Short-Term Memory) 모델이다. 각 모델은 2020년 1월부터 12월까지 소양강댐 댐 앞의 K-water 자동측정망 지점에서 실측한 수온과 탁도 자료를 이용하여 각각 보정하고 훈련하였다. 수온 및 탁도 예측을 위한 PGDL 모델의 주요 알고리즘은 LSTM 모델의 목적함수(또는 손실함수)에 실측값과 예측값의 오차항 이외에 역학적 모델의 에너지 및 질량 수지 항을 제약 조건에 추가하여 예측결과가 물리적 보존법칙을 만족하지 않는 경우 penalty를 부가하여 매개변수를 최적화시켰다. 또한, 자료 부족에 따른 LSTM 모델의 예측성능 저하 문제를 극복하기 위해 보정되지 않은 역학적 모델의 모의 결과를 모델의 훈련자료로 사용하는 pre-training 기법을 활용하여 실측자료 비율에 따른 모델의 예측성능을 평가하였다. 연구결과, PGDL 모델은 저수지 수온과 탁도 예측에 있어서 경계조건을 통한 에너지와 질량 변화와 저수지 내 수온 및 탁도 증감에 따른 공간적 에너지와 질량 변화의 일치도에 있어서 LSTM보다 우수하였다. 또한 역학적 모델 결과를 LSTM 모델의 훈련자료의 일부로 사용한 PGDL 모델은 적은 양의 실측자료를 사용하여도 CE-QUAL-W2와 LSTM 보다 우수한 예측 성능을 보였다. 연구결과는 다차원의 역학적 수리수질 모델과 자료기반 딥러닝 모델의 장점을 결합한 새로운 모델링 기술의 적용 가능성을 보여주며, 자료기반 모델의 훈련자료 부족에 따른 예측 성능 저하 문제를 극복하기 위해 역학적 모델이 유용하게 활용될 수 있음을 시사한다.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Smart Media Journal
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• v.12 no.5
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• pp.17-27
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• 2023

Recently, automatic text summarization, which automatically summarizes only meaningful information for users, is being studied steadily. Especially, research on text summarization using Transformer, an artificial neural network model, has been mainly conducted. Among various studies, the GSG method, which trains a model through sentence-by-sentence masking, has received the most attention. However, the traditional GSG has limitations in selecting a sentence to be masked based on the degree of overlap of tokens, not the meaning of a sentence. Therefore, in this study, in order to improve the quality of text summarization, we propose SbGSG (Semantic-based GSG) methodology that selects sentences to be masked by GSG considering the meaning of sentences. As a result of conducting an experiment using 370,000 news articles and 21,600 summaries and reports, it was confirmed that the proposed methodology, SbGSG, showed superior performance compared to the traditional GSG in terms of ROUGE and BERT Score.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.289-310
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• 2023

Sharing and reusing data has become essential. Data repositories are a key tool for sharing and reusing this data. The purpose of this study is to propose the service of EcoBank, which is being built and operated by the National Institute of Ecology. To achieve the research purpose, 10 out of 123 foreign data repositories in the field of ecology registered on re3data.org were selected, investigated, and analyzed. As a result of the analysis, three services were derived in common. The three services consist of first, research data policy, second, research data quality review, and research data management training and workshops. Here, in order to share EcoBank's global data, it is necessary to register with a data repository registry such as re3data.org, and it is proposed that certification be promoted to ensure the reliability and quality of the repository.