Results 71 to 80 of about 1,298,312 (212)
Learning to Control the Cloud.
, 2023 With the growth of the cloud industry in recent years, the energy consumption of the underlying infrastructure is a major concern.The need for energy efficient resource management and control in the cloud becomes increasingly important as one part of the solution, where the other is to reduce the energy consumption of the hardware itself.Resource ...
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Situated Poetry Learning Using Multimedia Resource Sharing Approach
, 2013 [[abstract]]Educators have emphasized the importance of situating students in an authentic learning environment. By using such approach, teachers can encourage students to learn Chinese poems by browsing content resources and relevant online multimedia ...
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Frontiers in Medicine, 2020 With the ultimate aim of early diagnosis of dementia, a new body balance assessment system with integrated head-mounted display-based virtual reality (VR) has been developed.
Yu Imaoka +4 more
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Sensors, 2019 Passengers travelling on the London underground tubes currently have no means of knowing their whereabouts between stations. The challenge for providing such service is that the London underground tunnels have no GPS, Wi-Fi, Bluetooth, or any kind of ...
Khuong An Nguyen +4 more
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A Survey on Reinforcement Learning for Optimal Decision‐Making and Control of Intelligent Vehicles
CAAI Transactions on Intelligence TechnologyReinforcement learning (RL) has been widely studied as an efficient class of machine learning methods for adaptive optimal control under uncertainties. In recent years, the applications of RL in optimised decision‐making and motion control of intelligent
Yixing Lan +5 more
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Teaching Self-Control Procedures to Learning Disabled Youths [PDF]
, 1981 This research was published by the KU Center for Research on Learning, formerly known as the University of Kansas Institute for Research in Learning Disabilities.This study developed and evaluated a self-instructional booklet that teaches adolescents to ...
Dennis, Connie +2 more
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Control Strategy of a Multiple Hearth Furnace Enhanced by Machine Learning Algorithms
, 2019 An enhanced control strategy for a multiple hearth furnace for the purpose of kaolin production is developed and presented in this paper. Mineralogy-driven machine learning algorithms play a key role in the optimization strategy of the furnace.
Jämsä-Jounela, Sirkka-Liisa +3 more
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Distributed learning for multi-agent control of a dynamic system [PDF]
, 2011 This thesis describes an investigation of self-organising, distributed control of dynamic, non-linear systems. The distribution is achieved through a multi-agent based approach. The self-organisation is addressed through reinforcement learning.
Pay, Mungo L
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, 2010 This paper considers iterative learning control law design for both trial-to-trial error convergence and along the trial performance. It is shown how a class of control laws can be designed using the theory of linear repetitive processes for this problem
Hladowski, Lukasz +5 more
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Dynamic task selection: Effects of feedback and learner control on efficiency and motivation [PDF]
, 2009 Corbalan, G., Kester, L., & Van Merriënboer, J .J. G. (2009). Dynamic task selection: Effects of feedback and learner control on efficiency and motivation.
Corbalan Perez, G. +3 more
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