In recent years, the integration of computation, communication, and physical systems has led to the emergence of a new paradigm called Cyber-Physical Systems (CPSs). Examples of CPS are ubiquitous, including home auto...
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Dynamical solvers for combinatorial optimization are usually based on 2nd degree polynomial interactions, such as the Ising model. These exhibit high success for problems that map naturally to their formulation. Howev...
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In this paper, we investigate the problem of event-based covert attack detection in cyber-physical systems. We first investigate event-based covert attacks and discuss how covert attacks can be launched in event-based...
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The successful commercialization of satellite communication systems using low earth orbit (LEO) satellites has received significant attention. In this paper, we study the ability of shape retrieval for flying objects ...
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This paper proposes a selective driving algorithm for a high-efficiency operation of an inductive power transfer (IPT) system in which the double-D quadrature pad (DDQP) is applied. Initially, the IPT pads are manufac...
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This paper describes a wrist-wearable non-resonant vibrational energy harvester (1.4 cc in volume and 3.2 gram in weight, with two arrays of wound copper coils adjacent to a movable array of magnets suspended by ferro...
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Modern vehicles are incorporating a wide array of technologies, leading to a substantial increase in data requirements. Concurrently, as vehicles integrate more Electronic Control Units (ECUs), there is a shift in the...
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Many empirical studies have demonstrated the performance benefits of conditional computation in neural networks, including reduced inference time and power consumption. We study the fundamental limits of neural condit...
An in-band co-polarized (IBCP) low scattering beamscanning metasurface (MTS)-based array is proposed using the time-reversal (TR) synthesis. The proposed 4 × 4 MTS-based array consists of double-layer Jerusalem-c...
The ensemble is a technique that strategically combines basic models to achieve better accuracy ***,combination methods,and selection topology are the main factors determining ensemble ***,it is a challenging task to ...
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The ensemble is a technique that strategically combines basic models to achieve better accuracy ***,combination methods,and selection topology are the main factors determining ensemble ***,it is a challenging task to design an efficient ensemble *** though numerous paradigms have been proposed to classify ensemble schemes,there is still much room for *** paper proposes a general framework for creating ensembles in the context of ***,the ensemble framework consists of four stages:objectives,data preparing,model training,and model *** is comprehensive to design diverse *** proposed ensemble approach can be used for a wide variety of machine learning *** validate our approach on real-world *** experimental results show the efficiency of the proposed approach.
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