• 제목/요약/키워드: resource based learning

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A Joint Allocation Algorithm of Computing and Communication Resources Based on Reinforcement Learning in MEC System

  • Liu, Qinghua;Li, Qingping
    • Journal of Information Processing Systems
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    • 제17권4호
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    • pp.721-736
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    • 2021
  • For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

Re-engineering Adult Education Programme-an Online Learning Curricular Perspective

  • Mathai, K.J.;Karaulia, D.S.
    • 한국멀티미디어학회논문지
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    • 제6권4호
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    • pp.685-697
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    • 2003
  • The Web based multimedia programmes/courses are becoming widely available in recent years. Most of these courses focus on Behaviorist way of learning, which does not promote deep learning in any way. For Adults this approach further incapacitated, as it does not satisfy Andragogical needs. The search for Constructivist way of learning through the web applied to Indian conditions led to need for developing a curriculum development approach that would promote construction of knowledge through web based collaboration. This paper attempts to reengineer existing curriculum development processes and lays out a framework of‘Problem Based Online Learning (PBOL)’curriculum design. In this context, entire curriculum development life cycle is evolved and explained. This is a part of doctoral work (Ph.D), which is in progress and being undertaken by K.James Mathai, and guided of Dr.D.S.Karaulia.

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클라우드 컴퓨팅 환경에서 빅데이터 처리를 위한 ART 기반의 적응형 자원관리 방법 (Adaptive Resource Management Method base on ART in Cloud Computing Environment)

  • 조규철;김재권
    • 한국시뮬레이션학회논문지
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    • 제23권4호
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    • pp.111-119
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    • 2014
  • 클라우드 환경은 빅데이터의 이슈와 데이터 분석을 가능하게 하는 기술로서, 이를 위한 자원 관리 기법이 필요하다. 현재까지의 자원관리 기법은 한정된 계산 방법을 이용하여 자원의 편중의 문제점이 있으며, 이를 해결하기 위해서 자원관리는 자원이력 정보를 활용한 학습기반의 스케줄링이 필요하다. 본 논문에서는 ART(Adaptive Resonance Theory)기반의 적응형 자원관리 기법을 제안한다. 제안하는 기법은 클라우드환경에서 모니터링 및 자원이력을 이용하여 작업의 적합한 할당이 가능하다. 제안하는 방법은 무감독 학습방법을 사용하며, 적응형 자원 관리를 통하여 서비스의 안정성과 데이터 처리성능을 향상시키는 것을 목적으로 한다. 제안하는 방법은 체계적인 자원관리가 가능하고 가용자원을 효율적으로 활용하여 요구 성능을 향상시킬 수 있다는 장점이 있다.

방송콘텐츠 기반 e-PBL을 위한 온라인 학습모듈 설계 및 개발 (The Design and development of online learning modules for the broadcasting content-based e-PBL)

  • 정준환
    • 한국컴퓨터정보학회논문지
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    • 제17권1호
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    • pp.105-115
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    • 2012
  • 본 연구는 방송콘텐츠를 일방향적인 정보전달도구의 차원이 아닌 풍부한 내용이 담긴 소프트웨어, 즉 단순히 정보를 제공하던 것에서 지식구성과 창출 과정을 촉진하는 학습자원으로서의 가능성에 주목하고, 이러한 가능성을 e-Learning의 교수 학습모형 중에 하나인 e-PBL을 통해 구체적으로 구현해 보고자 했다. 이를 위해 온라인 학습환경 설계 및 개발에 무게중심을 두고 연구를 진행했다. 특히, 본 연구는 온라인 학습커뮤니티 개발을 비롯하여 방송콘텐츠의 활용을 극대화하기 위한 전략적 방안들이 집약된 학습모듈 설계 및 개발과정에 초점을 두었다. 또한 이를 적용하고 그 타당성을 검증함으로서 학습모듈이 갖는 차별성을 증명하고자 하였다.

쿠버네티스 환경에서의 강화학습 기반 자원 고갈 탐지 및 대응 기술에 관한 연구 (Reinforcement Learning-Based Resource exhaustion attack detection and response in Kubernetes)

  • 김리영;김성민
    • 융합보안논문지
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    • 제23권5호
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    • pp.81-89
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    • 2023
  • 쿠버네티스는 컨테이너 통합 관리를 위한 대표적인 오픈소스 기반 소프트웨어로, 컨테이너에 할당된 자원을 모니터링하고 관리하는 핵심적인 역할을 한다. 컨테이너 환경이 보편화됨에 따라 컨테이너를 대상으로 한 보안 위협이 지속적으로 증가하고 있으며, 대표적인 공격으로는 자원 고갈 공격이 있다. 이는 악성 크립토마이닝 소프트웨어를 컨테이너 형태로 배포하여 자원을 탈취함으로써, 자원을 공유하는 호스트 및 다른 컨테이너의 동작에 영향을 끼친다. 선행 연구는 자원 고갈 공격의 탐지에 초점이 맞춰져 있어 공격 발생 시 대응하는 기술은 부족한 실정이다. 본 논문은 쿠버네티스 환경에서 구동되는 컨테이너를 대상으로 한 자원 고갈 공격 및 악성 컨테이너를 탐지하고 대응하기 위한 강화학습 기반 동적 자원 관리 프레임워크를 제안한다. 이를 위해, 자원 고갈 공격 대응 관점에서의 강화학습 적용을 위한 환경의 상태, 행동, 보상을 정의하였다. 제안한 방법론을 통해, 컨테이너 환경에서의 자원 고갈 공격에 강인한 환경을 구축하는 데 기여할 것으로 기대한다.

문제중심학습 연계 시뮬레이션 기반 교육이 간호대학생의 학습동기, 학습전략 및 학업성취도에 미치는 효과 (The Effect of Education based on Simulation with Problem-based Learning on Nursing Students' Learning Motivation, Learning Strategy, and Academic Achievement)

  • 조옥희;황경혜
    • 한국콘텐츠학회논문지
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    • 제16권7호
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    • pp.640-650
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    • 2016
  • 본 연구는 문제중심학습 연계 시뮬레이션 기반 교육을 개발하고 적용하여 간호학생의 학습동기, 학습전략과 학업성취도에 미치는 효과를 검증하고자 시도하였다. 연구대상자는 간호학과 4학년 학생 69명으로 2015년 9월부터 10월까지 문제중심학습 연계 시뮬레이션 기반 교육을 개발, 적용하고 학습동기, 학습전략, 학업성취도를 설문조사하였다. 연구결과, 문제중심학습 연계 시뮬레이션 기반 교육 후 통제 동기(외재 동기)는 감소하고, 자율성 동기(확인된 동기, 내재 동기)는 증가하였으며, 자원관리전략 활용 정도가 향상되었다. 학업성취도(학업성과, 교육만족도) 모두 확인된 동기와 학습전략(인지전략, 메타인지전략, 자원관리전략)과 정상관관계가 있었다. 결론적으로 문제중심학습 연계 시뮬레이션 기반 교육은 간호대학생의 자율성 동기를 증진하고 자원관리전략의 활용 정도를 향상시키는데 효과적인 교육전략으로 볼 수 있다. 문제중심학습 연계 시뮬레이션 기반 교육을 다양한 간호 상황에서 적용하여 학습 관련 변인에 영향을 미치는 요인과 매개변수를 파악하는 연구가 필요하다.

A Reinforcement learning-based for Multi-user Task Offloading and Resource Allocation in MEC

  • Xiang, Tiange;Joe, Inwhee
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2022년도 춘계학술발표대회
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    • pp.45-47
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    • 2022
  • Mobile edge computing (MEC), which enables mobile terminals to offload computational tasks to a server located at the user's edge, is considered an effective way to reduce the heavy computational burden and achieve efficient computational offloading. In this paper, we study a multi-user MEC system in which multiple user devices (UEs) can offload computation to the MEC server via a wireless channel. To solve the resource allocation and task offloading problem, we take the total cost of latency and energy consumption of all UEs as our optimization objective. To minimize the total cost of the considered MEC system, we propose an DRL-based method to solve the resource allocation problem in wireless MEC. Specifically, we propose a Asynchronous Advantage Actor-Critic (A3C)-based scheme. Asynchronous Advantage Actor-Critic (A3C) is applied to this framework and compared with DQN, and Double Q-Learning simulation results show that this scheme significantly reduces the total cost compared to other resource allocation schemes

Factors Influencing Life-Long Learning: An Empirical Study of Young People in Vietnam

  • NGUYEN, Lan;LUU, Phong;HO, Ha
    • The Journal of Asian Finance, Economics and Business
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    • 제7권10호
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    • pp.909-918
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    • 2020
  • This study, not only investigates the important role of lifelong learning in shaping young people's knowledge and in maximizing their potential, but also aims to shed light on the influencing factors of lifelong learning of young people in Vietnam. The author applied STATA and SPSS to analyze quantitative data collected from questionnaires with 332 respondents aged between 19 years old and 24 years old. Based on a holistic review of literature, this study concludes that four driver factors affect young people's lifelong learning ability, comprising: organizational culture, motivation, human resource development, and domestic private type of enterprise. The results emphasize the positivity of organizational culture, human resource development, and the nature of work, especially organizational culture and human resource development, which are dominant reasons for young people to maintain lifelong learning. The relationship between demographics and lifelong learning was tested and it indicated that male has a stronger interest in learning than female. The result of the study also shows the impact of different types of business sectors on employees' learning intentions. It points out that the domestic private type of enterprise is the most effective factor that has a positive relationship with the lifelong learning of the individual.

Short Term Spectrum Trading in Future LTE Based Cognitive Radio Systems

  • Singh, Hiran Kumar;Kumar, Dhananjay;Srilakshmi, R.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권1호
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    • pp.34-49
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    • 2015
  • Market means of spectrum trading have been utilized as a vital method of spectrum sharing and access in future cognitive radio system. In this paper, we consider the spectrum trading with multiple primary carrier providers (PCP) leasing the spectrum to multiple secondary carrier providers (SCP) for a short period of time. Several factors including the price of the resource, duration of leasing, and the spectrum quality guides the proposed model. We formulate three trading policies based on the game theory for dynamic spectrum access in a LTE based cognitive radio system (CRS). In the first, we consider utility function based resource sharing (UFRS) without any knowledge of past transaction. In the second policy, each SCP deals with PCP using a non-cooperative resource sharing (NCRS) method which employs optimal strategy based on reinforcement learning. In variation of second policy, third policy adopts a Nash bargaining while incorporating a recommendation entity in resource sharing (RERS). The simulation results suggest overall increase in throughput while maintaining higher spectrum efficiency and fairness.

Effects of Blended-TBL on Students' Self-Regulated Learning

  • PARK, Eunsook
    • Educational Technology International
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    • 제10권1호
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    • pp.137-155
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    • 2009
  • The purpose of this research is to develop Blended-TBL(Team Based Learning) model that emphasizes the active participation and teamwork of students in on-off blended learning environment, and apply it into the college course and explore whether self-regulated learning between one group pretest and posttest is different. For this, this research investigated the concept and the characteristics of Team Based Learning, and developed the Blended-TBL Model to apply it into the college course, and finally prove effects of Blended-TBL model on self-regulated learning using Motivated Strategies for Learning Questionnaire (MSLQ). The participants in this study were 57 college students. They participated in on-off blended-TBL course for 15weeks. Participants followed the content grounded and the problem solving steps in collaborative team-based learning. This research practiced a quantitative research to find out the statistical difference of the self-regulated learning between pretest and posttest using SPSS. The result revealed that Blended-TBL students improved self-regulated learning including motivation, cognitive, metacognitive, and resource management. Based on this result, this research discussed the effects of Blended-TBL on Self-Regulated Learning and suggested the further study.