Earticle

본 논문에서는 시맨틱웹의 온톨로지 기술과의 융합을 통한 시맨틱 강의계획서 템플릿을 정의하고 있다. 교수학습 설계도로서 강의계획서는 매우 중요한 의미를 가지고 있으나 이질적인 비구조화, 단편적인 내용구조, 타서비스와의 연계 부족, 재사용성 부족 등으로 인해 실제로는 단순한 조회에 그치고 있다. 본 논문에서는 강의계획서기반의 교수학습 정보시스템 구축을 위해 보다 구조화된 의미기반의 강의계획서 템플릿을 설계한다. 제안하는 기법은 강의계획서 계층구조 정의, Bloom 인지 분류 모형을 적용한 학습활동, 능력 및 학습성과 모델링, 학습주제 온톨로지 설계 등을 포함함으로써 강의계획서 중심의 학습연계 서비스를 가능하게 한다. 실제 자바 프로그래밍 강의에의 적용 및 실험을 통해 제안한 템플릿의 유용성과 신뢰성을 보인다.

In this paper, we design a semantic-based syllabus template including learning ontologies. A syllabus has been considered as a important blueprint of teaching in universities. However, the currentsyllabus has no importance in real world because most of all syllabus management systems provide simplefunctionalities such as, creation, modification, and retrieval. In this paper, our approach consists of definitionof hierarchical structure of syllabus and semantic relationships of syllabuses, formalization of learninggoals, learning activity, and learning evaluation using Bloom’s taxonomy and design of learning subjectontologies for improving the usability of syllabus. We prove the correctness of our proposed methodsaccording to implementing a real syllabus for JAVA programing course and experiments for retrievingsyllabuses.

In order to solve the safety hazards caused by the operation failure of elevators, pump rooms, fire control facilities, access control and other equipment and facilities in colleges, this paper uses the Internet of Things technology to realize the ubiquitous access of equipment and facilities in colleges, and collect the operating status data of the equipment and facilities in real time. Establish an equipment and facility operation data center, use big data and deep learning technology to realize online monitoring and real-time early warning of equipment and facilities, and send the monitoring and early warning information to managers and equipment maintenance personnel for processing, and realize the monitoring, early warning, and processing of equipment and facilities Automated process management to build an intelligent monitoring system for college equipment and facilities.

전통적인 웹기반의 학습시스템은 다양한 학습콘텐츠를 운영한다. 그러나 학습자가 자신에게 적절한 학습콘텐츠를 선택하는 것은 쉬운 일이 아니다. 본 논문에서는 학습자가 학습을 계획할 때 학습이력 및 다양한 학습정보를 담고 있는 학습자 프로파일을 기초로 하여, 학습자에게 가장 적합한 선호도와 피드백을 제공할 수 있는 학습콘텐츠 제공 방법을 제안하였다. 즉 학습자의 프로파일을 분석하여 학습자에게 제공할 긍정적 피드백과 평가를 결정한다. 또한 학습자가 틀린 부분에 대한 지식을 스스로 학습할 수 있도록 학습콘텐츠를 적응적으로 제공한다. 그 결과, 학습자 프로파일 분석을 통해 긍정적인 피드백을 바탕으로 자신이 오류를 배울 수 있도록 하여, 학습의 적용 결과가 가장 잘 나오는 형태로 학습 콘텐츠를 적응적으로 제공해 주는 기법을 적용하였다. 본 논문에서 구현한 지능형 학습시스템은 실제 학습자에게 적용하였으며 사용한 학습자들을 대상으로 학습 만족도를 설문하여 그 결과를 분석하였다.

Typical Web-based learning system is operating the variety of learning contents. However, it is not easy to efficiently select appropriate learning contents. In this paper, we propose a learning content delivery method that can provide the most suitable preferences and feedback to the learner. By analyzing the profile of the learner, it determines the positive feedback and evaluation to be provided to the learner. The result of applying learning techniques were applied to provide the best learning content to adaptively out the form. The proposed method appears as a learning experience and learning outcomes are higher after a study was conducted to suggest that could help in the learning progress of the students themselves. This paper are applied to real learners. And the learners using the system were surveyed by the questionnaire on learning experience and learning outcomes were analyzed.

This study proposes the development of an AI-based smart desk-and-chair system designed to enhance students’ posture, health, and learning efficiency. In modern smart classrooms, physical environments are optimized, but poor posture still leads to health issues and reduced concentration. The proposed system uses AI technologies such as posture recognition via vision sensors and voice-controlled mode switching. The hardware includes motorized desk and chair adjustments, LED lighting, and a liftable bookshelf, all controlled by Arduino and Raspberry Pi. Each learning mode (focus, rest, reading, sleep) dynamically adjusts furniture position and lighting color temperature. A lightweight AI model enables real-time posture analysis, while voice commands trigger environment changes. The system is tested for accuracy, response speed, and usability. Results show posture recognition accuracy above 90%, confirming its effectiveness. This integrated solution contributes to personalized learning environments and promotes healthier study habits for students.

정보통신기술의 발달 및 이용 증가로 인해 우편 사업의 매출 비중이 감소하고 경영수지 적자를 기록하고 있다. 이에 대한 개선 방법 중 미래의 우편 물량을 예측하고 해당 결과를 통해 미리 대비하는 효율적인 운영 방법을 제시한다. 본 논문은 특정 지역에서 발생할 우편 물량을 예측하는 방법으로 GAN(Generative Adversarial Network)을 이용한 데이터 증폭 기술과 딥러닝 기반 우편 물량 예측 기술을 통합한 지능형 우편 물량 예측 기술을 제시한다.

하천 인근에 위치한 빗물펌프장은 유수지를 대상으로 적절한 규칙에 따라 펌프를 가동함으로써 도심지 및 농경지 침수 피 해를 예방하는 기능을 수행한다. 현재 대부분의 빗물펌프장은 유수지의 수위를 기준으로 단순한 규칙 기반의 펌프운영 정책을 사용하고 있다. 최근 지구온난화로 인한 기후 변화가 예측하기 어려운 강우량의 변화를 발생시키고 있다. 따라서 단순한 펌프 정책으로는 지구온난화로 인한 갑작스러운 유수지 변화에 적절하게 대처하기 어렵다. 본 논문은 강우량과 저수량, 유수지 수 위 등의 정보를 이용해 시스템이 적정 유수지 수위을 유지할 수 있도록 펌프 가동을 선택할 수 있는 심층 강화학습 기반의 자 동 빗물펌프 운용 방법을 제시한다. 제안한 방법의 타당성을 검증하기 위해 강우-유출 모의 모델인 Storm Water Management Model(SWMM)을 이용해 모의실험을 수행하고 현장에서 사용되고 있는 기존 펌프 정책과 성능을 비교하였다.

The rainwater pumping station located near a river prevents river overflow and flood damages by operating several pumps according to the appropriate rules against the reservoir. At the present time, almost all of rainwater pumping stations employ pumping policies based on the simple rules depending only on the water level of reservoir. The ongoing climate change caused by global warming makes it increasingly difficult to predict the amount of rainfall. Therefore, it is difficult to cope with changes in the water level of reservoirs through the simple pumping policy. In this paper, we propose a pump operating method based on deep reinforcement learning which has the ability to select the appropriate number of operating pumps to keep the reservoir to the proper water level using the information of the amount of rainfall, the water volume and current water level of the reservoir. In order to evaluate the performance of the proposed method, the simulations are performed using Storm Water Management Model(SWMM), a dynamic rainfall-runoff-routing simulation model, and the performance of the method is compared with that of a pumping policy being in use in the field.

Cyber education system service is in the field of software service which is highlighted after the latter half of 1990'. But the progress of this service is impeded by the lack of back office which contributes to the evaluation of learning achievement and the management of learning progress. This article points out the problem of current back office which is the most important in the cyber education system, and focuses on the new intelligent learning achievement evaluation module. First, we define the cause and effect between the learning stages using by fuzzy implication which is the important part of fuzzy theory. Next, we suggest the model which generates the results of the learning achievement evaluation. This model, suggested by this article, may contribute to the development of the cyber education system by improving the current on-line education service.

Recently, the prevalence of high-performance mobile devices and development of IT technologies, including augmented reality technology and location information service, etc. has led to the formation of an educational environment allowing learners to practice context learning theory ideally, subsequently contributing to active progress of relevant studies. Therefore, it is difficult to expect leaners to have an interest and a commitment since it cannot connect a lot of information coming through the perspective of the learner in a real-world environment with situated learning in real time. Accordingly, this paper proposes a intelligent English situated learning system that can practice situation context learning more reasonably using a location-based service and a recognition technology that automatically recognizes text information on street signboards that are easily accessible in everyday life, yet provide learners with a lot of information. The proposed system provides learners with English conversation learning contents that can be used in the business sector related to trade name recognized through text information on street signboards from images captured by cameras.

E-learning is the internet enabled learning. Internet has ongoing to restructuring education. Intelligent agent based e-learning provide a common infrastructure to assimilate varied software components. There are two sorts of e-learning synchronous and asynchronous. This paper described the detail of well-known agent based architecture for e-learning. E-learning is going to be gigantic. There are multiple benefits of e-learning; it is convenient, self-service mix, match, on demand any time anyplace, private learning, Self-paced and elastic. E-learning provide cost effective and virtual environment. E-learning gives the ability to user to collect the quantifiable and sensible material, examine, and distribute and custom e-learning knowledge from multiple e learning sources.

This paper presents a framework of intelligent tutorial system to incorporate adaptive learning and assess the relative performance of adaptive learning system over general classroom learning. In conventional classroom teaching and in distance learning the students may be from different backgrounds, their need of study and goal may be different; above all their ability to learn may not be similar. So teaching style and fitting teaching material may differ from student to student. A layered architecture of an Intelligent Tutorial System [ITS] for adaptive learning is proposed that assess the requirement, goal and capability of a student and dynamically sets a path for study, the instruction materials are dynamically selected as per the student’s level of understanding from a given set of instruction materials. The system monitors the student and changes the path of study automatically as per the performance. Formative and summative test are taken by the system for decision making – as to which material is best for student and for assessing student’s understanding level. The system also intelligently helps the user to overcome the misconceptions, as human teacher. Experimental results show the impressive improvement of the performances of students in distance mode learning using ITS following the proposed framework.

This paper describes the innovative Learner Intelligent Feedback System (IFS) in terms of a set of three agent: Interface Agent (IFA), Information Agent(IMA), and Intelligence Agent(ILA). The agent can deduce the correct answers to test questions and provide intelligent feedback and hints to the learner. The intelligent feedback system is : Firstly, system presents content in initial learning style. Secondly, learner takes a diagnostic test. Thirdly, system analyzes user performance. Fourth, system identifies concept deficiencies and chooses the best learning model. Finally, system dynamically creates a remedial course tailored to the learner. The learner takes the remedial course, at the end of which is another test. If the learner still does not get the concept, he or she is returned to another dynamically generated course presented in a different learning style. At the same time the tutor agent notifies that one of her students is having trouble. The Tutoring agents are the driving engine of the system. Their main tasks are to generate appropriate learning feedbacks for learners and provide new learning problems and advanced situations. IFS can be used for complete course training, including test from a remote site.