This paper presents a low-power, battery-less biopotential-recording integrated circuit (IC) designed for implantable leadless cardiac monitoring applications, addressing the full autonomy based on wireless energy har...
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With the advance of 5G technologies and the development of space-air-ground-sea applications,the fast and efficient collection and processing of the explosive growth of sensing data have become significant and *** thi...
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With the advance of 5G technologies and the development of space-air-ground-sea applications,the fast and efficient collection and processing of the explosive growth of sensing data have become significant and *** this paper,considering the Age of Information(AoI),the limited coverage of Base Stations(BS),and the constrained computation capability of Unmanned Aerial Vehicle(UAV),we propose a hybrid communication framework that utilizes UAVs as relays to optimize the collection of sensing *** aim to minimize the average AoI of the data among all sensor nodes while considering the energy consumption constraints of sensor nodes,which is formulated as a Mixed Integer NonLinear programming(MINLP).To address this problem,we decompose it into communication resource allocation and computation resource ***,the average AoI of the whole system is minimized and the average energy consumption constraint of sensor nodes is *** simulation results show that our proposed method can achieve significant performance *** specific,our proposed method can reduce the average AoI by 20％,11％,and 43％compared to the three counterparts,Data Transmission Directly Algorithm(DTDA),Max Weight Algorithm(MWA),and matching algorithm,respectively.
RowHammer vulnerabilities pose a significant threat to modern DRAM-based systems, where rapid activation of DRAM rows can induce bit-flips in neighboring rows. To mitigate this, state-of-the-art host-side RowHammer mi...
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The reliance on fossil fuels can be reduced by adopting renewable energy technologies, such as solar photovoltaic systems, which produce clean energy. As a result, consumers connected to the local grid can use a grid-...
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In this paper, we investigate an explicit transform selection method that merges transform sets of the two intra prediction modes used for predictor blending, aimed at the new blending intra prediction (BIP) tools (i....
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The use of solar photovoltaic (PV) technology has significantly increased as a solution for providing electricity to off-grid or remote users, as well as for reducing energy costs for grid-connected users. The main co...
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With significant expansion in wind farm capacity,wake disturbances from upstream wind turbines have emerged as a detrimental factor,adversely affecting the generated power of downstream ***,the conventional power pred...
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With significant expansion in wind farm capacity,wake disturbances from upstream wind turbines have emerged as a detrimental factor,adversely affecting the generated power of downstream ***,the conventional power prediction models usually neglect the wake effect between adjacent wind *** bridge this gap,this paper proposes a novel power prediction model that considers the wake effect and its boundary layer compensation,to enable joint spatial and temporal wind power prediction for wind ***,a two-dimensional convolutional neural network is adopted to extract the key features and reconstruct wind power prediction ***,utilizing historical data,a long short-term memory algorithm is employed to investigate the correlation between elemental characteristics and wind ***,a 3D-Gaussian Frandsen wake model that accounts for the wake effect and boundary layer compensation in wind farms is developed to precisely calculate the spatial wind speed ***,these distributions allow the power outputs of wind turbines in wind farms to be estimated more accurately via the rotor equivalent wind ***,several case studies are conducted to validate the effectiveness of the proposed *** results demonstrate that the suggested approach yields favorable outcomes in predicting both wind speed and wind power.
Thanks to their long-range dependencies, transformers obtain state-of-the-art performance in diverse research fields such as computer vision and audio processing. In practical scenarios, convolutional neural networks ...
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This paper reports a miniature indirect unipolar corona charger with multiple discharge sites for high efficiency in nanoparticle charging, sizing and detection. A novel scalable and stackable design using multiple mu...
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High resolution radar imaging at millimeter wave frequencies is of high importance. To achieve high resolution in range direction, large bandwidth is utilized. However, generating high output power at millimeter wave ...
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