• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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• pp.241-248
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• 2006

Web is greatly contributing in providing a variety of information. Especially, as media for the purpose of development and education of human resources, the role of web is important. Furthermore, E-Learning through web plays an important role for each enterprise and an educational institution. Also, above all, fast and various searches are required in order to manage and search a great number of educational contents in web. Therefore, most of present information is composed in HTML, so there are lots of restrictions. As a solution to such restriction, XML a standard of Web document, and its various search functions is being extended and studied variously. This paper proposes a search system able to search XML in E-Learning or var ious contents of non-XML using mobile device PDA.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.726-731
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• 2021

Due to the COVID-19 pandemics, Romanian schools functioned online since March 2020, with more or less all school activities being implemented online, using the digital resources and technology. Although none of the key factors involved in education (teachers, pupils, parents) were prepared (emotionally, technically, economically etc.), online education was imposed ad a necessity to continue the teaching-learning-evaluation process, and teachers at all school levels were forced to rapidly adapt to online schooling. In this paper, we aim to investigate the perception of all three educational actors (pupils, parents and teachers) regarding the efficacy of online teaching and learning, based on a survey with 7701 respondents. Research data is relevant for online schooling in Romania between March 2020 and March 2021.

• 반도체디스플레이기술학회지
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• 제20권4호
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• pp.151-156
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• 2021

Low-end IoT devices do not have enough computation and memory resources for DNN learning and inference. Integer quantization of real-type neural network models can reduce model size, hardware computational burden, and power consumption. This paper describes the design and implementation of a web-based quantization platform for CNN deep learning accelerator chips. In the web service platform, we implemented visualization of the model through a convenient UI, analysis of each step of inference, and detailed editing of the model. Additionally, a data augmentation function and a management function of files that store models and inference intermediate results are provided. The implemented functions were verified using three YOLO models.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.27-32
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• 2022

Due to the COVID-19 pandemics, Romanian schools functioned online since March 2020, with more or less all school activities being implemented online, using the digital resources and technology. Although none of the key factors involved in education (teachers, pupils, parents) were prepared (emotionally, technically, economically etc.), online education was imposed ad a necessity to continue the teaching-learning-evaluation process, and teachers at all school levels were forced to rapidly adapt to online schooling. In this paper, we aim to investigate the perception of all three educational actors (pupils, parents and teachers) regarding the efficacy of online teaching and learning, based on a survey with 7701 respondents. Research data is relevant for online schooling in Romania between March 2020 and March 2021.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.327-347
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• 2024

Edge computing is frequently employed in the Internet of Vehicles, although the computation and communication capabilities of roadside units with edge servers are limited. As a result, to perform distributed machine learning on resource-limited MEC systems, resources have to be allocated sensibly. This paper presents an Improved MADDPG algorithm to overcome the current IoV concerns of high delay and limited offloading utility. Firstly, we employ the MADDPG algorithm for task offloading. Secondly, the edge server aggregates the updated model and modifies the aggregation model parameters to achieve optimal policy learning. Finally, the new approach is contrasted with current reinforcement learning techniques. The simulation results show that compared with MADDPG and MAA2C algorithms, our algorithm improves offloading utility by 2% and 9%, and reduces delay by 29.6%.

• 상하수도학회지
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• 제38권2호
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• pp.83-93
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• 2024

In this study, we present a sewer pipe inspection technique through a combination of active sonar technology and deep learning algorithms. It is difficult to inspect pipes containing water using conventional CCTV inspection methods, and there are various limitations, so a new approach is needed. In this paper, we introduce a inspection method using active sonar, and apply an auto encoder deep learning model to process sonar data to distinguish between normal and abnormal pipelines. This model underwent training on sonar data from a controlled environment under the assumption of normal pipeline conditions and utilized anomaly detection techniques to identify deviations from established standards. This approach presents a new perspective in pipeline inspection, promising to reduce the time and resources required for sewer system management and to enhance the reliability of pipeline inspections.

• International journal of advanced smart convergence
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• 제13권3호
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• pp.335-344
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• 2024

This study explores advanced machine learning techniques for improving crop yield prediction in smart farming, utilizing multi-temporal spectral data from drone-based multispectral imagery. Conducted in garlic orchards in Andong, Gyeongbuk Province, South Korea, the research examines the effectiveness of various vegetation indices and cutting-edge models, including LSTM, CNN, Random Forest, and XGBoost. By integrating these models with the Analytic Hierarchy Process (AHP), the study systematically evaluates the factors that influence prediction accuracy. The integrated approach significantly outperforms single models, offering a more comprehensive and adaptable framework for yield prediction. This research contributes to precision agriculture by providing a robust, AI-driven methodology that enhances the sustainability and efficiency of farming practices.

• International Journal of Computer Science & Network Security
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• 제22권8호
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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.

• 한국산학기술학회논문지
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• 제22권1호
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• pp.159-170
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• 2021

연구개발(R&D)의 주요 목적이 과거 지식 창출 중심에서 기술이전 및 사업화를 통한 경제적 이익 창출 중심으로 변화함에 따라 공공성(public character)을 내재한 공공기술 역시 사회적 기여와 더불어 경제성을 확보할 수 있는 방안이 요구되고 있다. 한국 또한 대학 및 정부출연연구소의 기술창업 활성화를 위해 2015년부터 '공공기술 기반 시장연계 창업탐색 지원사업(한국형 아이코어 사업)'을 실시하여 기초·원천 연구성과의 사업화를 선도할 수 있는 핵심인력 양성에 힘을 기울이고 있다. 본 연구는 기업가정신 교육 관련 선행연구와 동 사업의 성과분석을 목적으로 실시한 설문조사 결과를 토대로 '창업학습', '적용도', '비즈니스 모델', 그리고 '재무적 자원' 등 사업성과와 관련한 4개의 요인을 도출하였고, 가설 검증 및 구조방정식모델 분석을 통해 이러한 영향요인 간의 관계를 실증하였다. 연구결과를 요약하면, 아이코어 사업의 성과인 '재무적 자원'에 미치는 '창업학습'의 직접적인 영향은 통계적으로 확인되지 않았지만, '창업학습'으로부터 유의한 수준에서 긍정적인 영향을 받는 '적용도'와 '비즈니스 모델'이 '재무적 자원'에 긍정적인 영향을 미침에 따라 결과적으로 '창업학습'이 '재무적 자원'에 미치는 간접효과가 검증되었다. 특히 '창업학습'이 '적용도'에 미치는 높은 수준의 영향과 '적용도'가 '비즈니스 모델'과 '재무적 자원'에 미치는 영향 역시 유의한 수준에서 긍정적으로 나타남에 따라 '재무적 자원'에 긍정적인 영향을 미치는 핵심요인들이 확인되었다. 따라서 이러한 분석 결과를 바탕으로 본 연구는 공공기술기반 창업교육에 대한 이론적 및 실무적 시사점을 도출하였고, 향후 효과적인 공공기술 사업화를 위한 지원사업의 개선 방향을 제시하고 있다.

• 한국지반공학회논문집
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• 제37권5호
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• pp.47-63
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• 2021

최근 디지털 트윈 관점의 3차원 지하공간 지도의 수요 및 유관분야의 연계 활용 요구가 증대되고 있다. 그러나 전국단위의 지반조사 자료의 방대함과 이를 활용함에 있어 공간적/추계학적 기법 적용의 불확실성으로 인해 신뢰도 높은 지역적 지반특성화 연구와 그에 따른 최적화 모델 제시에 어려움이 있다. 따라서 본 연구에서는 서울지역 3차원 지하공간의 공학적 지층분류를 위해 다층 퍼셉트론(MLP) 기반의 최적 학습모델을 구축하였다. 먼저, 서울지역에 분포하는 시추공별 층상구조 및 3차원 공간좌표를 표준화 서식에 따라 지반정보 데이터베이스로 구축하고 기계학습을 위한 결측치 보정, 정규화 등의 데이터 전처리를 하였다. MLP 모델의 파라미터 최적화와 정밀도 및 정확도 관련 모델 성능 평가를 통해 최적의 피팅 모델을 설계하였다. 이후 3차원 지반 공간레이어 구축을 위한 수치표고모델 기반 격자망을 구성하고, 단위격자별 MLP기반 예측모델 적용을 통한 층상구조를 결정하고 이를 가시화하였다. 구축된 3차원 지반모델은 범용적인 지구통계학적 공간보간 기법의 적용 결과 및 지질도의 표토층 성상과 비교하여 그 성능을 평가하였다.