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Adaptive Kalman-based hybrid car following strategy using TD3 and CACC
In autonomous driving, the hybrid strategy of deep reinforcement learning and cooperative adaptive cruise control (CACC) can fully utilize the advantages of the two algorithms and significantly improve the performance of car following.
Joint Optimization of DNN Inference Delay and Energy under Accuracy Constraints for AR Applications
The high computational complexity and high energy consumption of artificial intelligence (AI) algorithms hinder their application in augmented reality (AR) systems.
$q$-Analogues of $π$-Series by Applying Carlitz Inversions to $q$-Pfaff-Saalsch{ü}tz Theorem
By applying multiplicate forms of the Carlitz inverse series relations to the $q$-Pfaff-Saalsch{\"u}tz summation theorem, we establish twenty five nonterminating $q$-series identities with several of them serving as $q$-analogues of infinite series expressions for $\pi$ and $1/\pi$, including some typical ones discovered by Ramanujan (1914) and Guillera.
Number Theory Combinatorics 33D15, 05A30, 11B65, 33D05
Cooling-Aware Resource Allocation and Load Management for Mobile Edge Computing Systems
Driven by explosive computation demands of Internet of Things (IoT), mobile edge computing (MEC) provides a promising technique to enhance the computation capability for mobile users.
An Online Learned Elementary Grouping Model for Multi-target Tracking
We introduce an online approach to learn possible elementary groups (groups that contain only two targets) for inferring high level context that can be used to improve multi-target tracking in a data-association based framework.
