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Data-efficient deep reinforcement learning with expert demonstration for active flow control
The Physics of Fluids, 2022Deep reinforcement learning (RL) is capable of identifying and modifying strategies for active flow control. However, the classic active formulation of deep RL requires lengthy active exploration.
Changdong Zheng +6 more
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IEEE Transactions on Power Systems, 2022
Regarding the continuing increase of anthropogenic carbon emissions in the power system with growing energy consumption, researchers have focused on managing the demand side to achieve low-carbon transition.
Yunqi Wang, J. Qiu, Yuechuan Tao
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Regarding the continuing increase of anthropogenic carbon emissions in the power system with growing energy consumption, researchers have focused on managing the demand side to achieve low-carbon transition.
Yunqi Wang, J. Qiu, Yuechuan Tao
semanticscholar +1 more source
Data flow control in an online system
Microprocessors and Microsystems, 1979Abstract Valuable computer time and memory space is saved by using a microprocessor (Mostek F8) to control the flow of data in a multichannel laboratory data collection system. Special digital converters transmit serial BCD signals with added control bits.
Arthur C. Parker, Philip Loughery
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Lattice-Modeled Information Flow Control of Big Sensing Data Streams for Smart Health Application
IEEE Internet of Things Journal, 2019Internet of Things (IoT) provides a promising opportunity to build powerful data analytics systems with real time event detection for smart health, and therefore wearable IoT has become a rising source of big data streams for smart health, for which ...
Deepak Puthal
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Variability of data dependences and control flow
2014 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2014Thread-level speculation and profile-guided parallelization techniques exploit the fact that many statically detected data and control flow dependences do not manifest themselves in every possible program execution. Instead, many of these may-dependences only occur infrequently, e.g.
Tobias J. K. Edler von Koch +1 more
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LUCON: Data Flow Control for Message-Based IoT Systems
2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE), 2018Today's emerging Industrial Internet of Things (IIoT) scenarios are characterized by the exchange of data between services across enterprises. Traditional access and usage control mechanisms are only able to determine if data may be used by a subject ...
J. Schütte, G. Brost
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Modeling multidimensional data and control flow
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 1993Multidimensional (M-D) signal processing is a key component of most real-time signal and data processing VLSI systems in industry. Handling the M-D nature of data in an efficient way is crucial to arrive at acceptable system implementations. This aspect of design has often been ignored up to now in high-level synthesis.
Frank H. M. Franssen +4 more
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Unified specification of control and data flow
1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002Many signal processing systems use event driven mechanisms-typically based on finite state machines (FSMs)-to control the operation of computationally intensive (data flow) parts. The state machines in turn are often fueled by external inputs as well as by feedback from the signal processing portions of the system. Packet-based transmission systems are
Thorsten Grötker +2 more
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The Intelligent Traffic Flow Control System Based on 6G and Optimized Genetic Algorithm
IEEE transactions on intelligent transportation systems (Print)With the acceleration of urbanization, the problem of urban traffic congestion has become increasingly serious. This study aims to develop an intelligent traffic flow control system based on sixth-generation (6G) communication technology to achieve real ...
Caichang Ding +5 more
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π0: A Vision-Language-Action Flow Model for General Robot Control
arXiv.orgRobot learning holds tremendous promise to unlock the full potential of flexible, general, and dexterous robot systems, as well as to address some of the deepest questions in artificial intelligence.
Kevin Black +23 more
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