• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1545-1559
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• 2023

In the cloud environment, microservices are implemented through Kubernetes, and these services can be expanded or reduced through the autoscaling function under Kubernetes, depending on the service request or resource usage. However, the increase in the number of nodes or distributed microservices in Kubernetes and the unpredictable autoscaling function make it very difficult for system administrators to conduct operations. Artificial Intelligence for IT Operations (AIOps) supports resource management for cloud services through AI and has attracted attention as a solution to these problems. For example, after the AI model learns the metric or log data collected in the microservice units, failures can be inferred by predicting the resources in future data. However, it is difficult to construct data sets for generating learning models because many microservices used for autoscaling generate different metrics or logs in the same timestamp. In this study, we propose a cloud data refining module and structure that collects metric or log data in a microservice environment implemented by Kubernetes; and arranges it into computing resources corresponding to each service so that AI models can learn and analogize service-specific failures. We obtained Kubernetes-based AIOps learning data through this module, and after learning the built dataset through the AI model, we verified the prediction result through the differences between the obtained and actual data.

• 한국시뮬레이션학회논문지
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• 제5권2호
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• pp.13-24
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• 1996

Workflow is an ordered sequence of interdependent component data activities each of which can be executed on an integrated information system by accessing a remote information system. In our previous research [4], we proposed a distributed CIM Workflow system which consists of a workflow execution model called DAF-Net and an agent-based information systems called AIMIS. Given a component data activity, there needs an interaction protocol among agents which allocates the component data activity to a relevant information systems exist. The objective of this research is to propose and test two protocols: ARR(Asynchronous Request and Response)protocol and NCL(Negotiation with Case based Learning) protocol. To test the effectiveness of the protocols, we applied the PVM(Parallel Virtual Machine) software to simulate the distributed CIM Workflow system. PVM provides a distributed computing environment in which users can run different software processes in different computers while allowing communication among the processes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권2호
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• pp.151-156
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• 2005

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) and a Classifier System(CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in given environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local one. The proposed system will be more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• 한국산업정보학회논문지
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• 제25권2호
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• pp.57-72
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• 2020

철광석의 가격은 여러 국가와 기업들의 수요와 공급에 따라서 높은 변동성이 지속되고 있다. 이러한 비즈니스 환경에서 철광석의 가격을 예측하는 것은 중요해졌다. 본 연구는 머신러닝 기법을 이용하여 철광석이 거래되는 시점으로부터 한 달 전에 철광석 거래가격을 미리 예측하는 모형을 개발하고자 하였다. 예측 모형은 시계열 데이터를 활용한 예측 방법론으로 많이 활용되고 있는 시차분포 모형과 다층신경망 (Multi-layer perceptron), 순환신경망 (Recurrent neural network), 그리고 장단기 기억 네트워크 (Long short-term memory)와 같은 딥 러닝(Deep Learning) 모형을 사용하였다. 측정지표를 통해 개별 모형을 비교한 결과에 따르면, LSTM 모형이 예측 오차가 가장 낮은 것으로 나타났다. 또한, 앙상블 기법을 적용한 모형들을 비교한 결과, 시차분포와 LSTM의 앙상블 모형이 예측오차가 가장 낮은 것으로 나타났다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1794-1797
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• 2003

We developed a web-based virtual laboratory system for electronic circuit experiments on the client/ server distributed environment. Through our virtual laboratory, the learners will be capable of learning the concepts and theories related to electronic circuit experiments and how to operate the experimental equipments such as multimeters, function generators, digital oscilloscopes and DC power suppliers. The proposed virtual laboratory system is composed of four important components: Principle Classroom to explain the concepts and theories of electronic circuit operations, Virtual Experiment Classroom to provide interactive multimedia contents about the syllabus of off-line laboratory class, Assessment Classroom, and Management System. With the aid of the Management System every classroom is organically tied together collaborating to achieve maximum learning efficiency. We have obtained several affirmative effects such as high learning standard, reducing the total experimental hours and the damage rate for experimental equipments.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2008년도 제39차 동계학술발표논문집 16권2호
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• pp.153-158
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• 2009

SCORM(Sharable Content Object Reference Model)은 세계 e-Learning 표준화 분야에서 가장 주목을 받고 있는 ADL(Advanced Distributed Learning)의 표준화 모델이다. SCORM2004 RTE(Run-Time Environment) 에서 상호작용 데이터 모델(Interaction Data Model)의 기능을 활용하면 LMS(Learning Management System)가 문항을 자동 생성하여 문제은행을 보다 쉽게 구현할 수 있다. 내용학습 후에 형성평가를 실시하기 위한 문항을 학습자가 원하는 만큼 공급할 수 있다. 본 연구는 일반계 고등학교 수학교과의 삼각함수 성질을 학습하는 데 있어 RTE의 상호작용 데이터 모델로 구현한 문제은행을 갖춘 반복학습 콘텐츠를 개발하여 학습효과를 높이고자 한다.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.89-96
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• 2023

Intrusion detection has been widely studied in both industry and academia, but cybersecurity analysts always want more accuracy and global threat analysis to secure their systems in cyberspace. Big data represent the great challenge of intrusion detection systems, making it hard to monitor and analyze this large volume of data using traditional techniques. Recently, deep learning has been emerged as a new approach which enables the use of Big Data with a low training time and high accuracy rate. In this paper, we propose an approach of an IDS based on cloud computing and the integration of big data and deep learning techniques to detect different attacks as early as possible. To demonstrate the efficacy of this system, we implement the proposed system within Microsoft Azure Cloud, as it provides both processing power and storage capabilities, using a convolutional neural network (CNN-IDS) with the distributed computing environment Apache Spark, integrated with Keras Deep Learning Library. We study the performance of the model in two categories of classification (binary and multiclass) using CSE-CIC-IDS2018 dataset. Our system showed a great performance due to the integration of deep learning technique and Apache Spark engine.

• 한국비블리아학회지
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• 제35권2호
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• pp.135-156
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• 2024

새로운 정보환경에 직면한 사서는 지식과 기술에 적극적인 대처가 필요하지만, 위탁 공공도서관 사서는 업무 공백의 우려나 제도적 장치의 미흡으로 외부 교육 참여에 부담을 느끼고 있어 지속적인 교육이 이루어지기 어렵다. 이에 본 연구에서는 사서가 함께 성장할 수 있는 환경을 조성하고자 학습공동체 활동 현황을 점검하고 그 효과를 파악하였다. 강남구립도서관 소속 사서 중 학습공동체 활동에 참여한 경험이 있는 사서를 대상으로 2023년 5월 20일부터 22일까지 온라인 설문조사를 실시하였으며, 101부를 배포하여 81부를 회수하고 분석 데이터로 활용하였다. 연구 결과, 사서들은 학습공동체 활동에 만족하고 있으며, 그 필요성에 대한 이해와 공감이 높은 것을 확인하였다. 따라서 학습공동체를 활성화하기 위한 방안으로 구성원의 협업을 촉진하는 문화를 형성하고, 학습공동체 활동에 대한 비전과 가치를 공유하며, 제도적 지원이 필요함을 제언하였다.

• Smart Structures and Systems
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• 제29권2호
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• pp.375-387
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• 2022

One of the latest teaching strategies is smart classroom teaching. Teaching is carried out with the assistance of smart teaching technologies to improve teacher-student contact, increase students' learning autonomy, and give fresh ideas for the fulfillment of students' deep learning. Computer-based technology has improved students' language learning and significantly motivating them to continue learning while also stimulating their creativity and enthusiasm. However, the difficulties and barriers that many EFL instructors are faced on seeking to integrate information and communication technology (ICT) into their instruction have raised discussions and concerns regarding ICT's real worth in the language classroom. This is a case study that includes observations in the classroom, field notes, interviews, and written materials. In EFL classrooms, both computer-based and non-computer-based activities were recorded and analyzed. The main instrument in this study was a survey questionnaire comprising 43 items, which was used to examine the efficiency of ICT integration in teaching and learning in public schools in Kuala Lumpur. A total of 101 questionnaires were delivered, while each responder being requested to read the statements provided. The total number of respondents for this study was 101 teachers from Kuala Lumpur's public secondary schools. The questionnaire was randomly distributed to respondents with a teaching background. This study indicated the accuracy of utilizing Teaching-Learning-Based Optimization (TLBO) in analyzing the survey results and potential for students to learn English as a foreign language using computers. Also, the usage of foreign language may be improved if real computer-based activities are introduced into the lesson.

• 한국환경교육학회지:환경교육
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• 제20권4호
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• pp.145-165
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• 2007

The purpose of this study is to investigate items for improving environmental education in elementary school for the more efficiency policies of environmental education. In this study, we investigated the relative importance of each items through Analytic Hierarchy Process for the various groups of the expert who is related with environmental education. We made hierarchical structure for efficiency education through brainstorming process. The hierarchical structure consisted of 3 high-level items and 8 low-level items. The questionnaires were distributed to 4 groups with 187 experts. After the consistency test of returned questionnaires, we gained 60 available questionnaires of experts. According to the generalization results of all groups, "The pro-environmental attitude of the teacher" is the most important. The second important thing is "The pro-environmental attitude of the schoolmaster" and the third is "Experiential learning and on-the-spot study concerning environment". And the following are "Budget for environmental education" and "Environmental education in discretionary activity", "Teaching materials for environmental education", "The cultivation of the experts on environmental education", "Environment event in school" in order. As the result, we have to intensify the pro-environmental attitude of the teachers and schoolmasters and develop experiential learning and on-the-spot study programs concerned environment to improve environmental education. At the same time, we need the more politic support related with budget for environmental education.