In the totally unprecedented context of the COVID-19 health crisis, the widespread adoption of Industry 4.0 technologies, and the great interest in resilience, have been stronger than ever. Within this framework, the ...
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In the totally unprecedented context of the COVID-19 health crisis, the widespread adoption of Industry 4.0 technologies, and the great interest in resilience, have been stronger than ever. Within this framework, the present paper outlines the involvement of technologies emerging from the fourth industrial revolution in the fight against the epidemic expansion, and the results of this implication in terms of strengthening and achieving resilience in diverse fields. In order to gain a fuller understanding of these points, fourteen resilience domains related to the COVID-19 pandemic are defined. On the other hand, the third section of this paper digs into the literature to expose a variety of Industry 4.0 solutions developed to cope with the sanitary crisis. Afterwards, a fuzzy cognitive map is elaborated, using mental modeler, in order to emphasize the causal links between Industry 4.0 technologies and resilience domains. Subsequently, a simulation of this model is performed to evaluate the contribution of an optimized joint use of Industry 4.0 core technologies in the achievement of resilience in its different dimensions during the COVID-19 pandemic, and to discuss how the identified gaps or weaknesses can be addressed.
Video question answering(VideoQA)is a typical cross-modal understanding task. Its challenge lies in how to learn appropriate multimodal representation and cross-modal correlation for answer inference. Most existing ...
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Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. ...
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Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.
Hyperspectral unmixing can provide the composition of ground objects, while change detection can identify the changes of the same region over time. Therefore, unmixing based hyperspectral change detection can investig...
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The rapid adoption of smartphones and the explosive growth of data traffic due to these devices have been phenomenal. As the world anticipates more connected devices - the Internet of Things (IoT), vehicle-to-vehicle ...
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Maximizing influences in complex networks is a practically important but computationally challenging task for social network analysis, due to its NP-hard nature. Most current approximation or heuristic methods either ...
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Neural Radiance Fields have shown great potential to synthesize novel views with only a few discrete image observations of the world. However, the requirement of accurate camera parameters to learn scene representatio...
Neural Radiance Fields have shown great potential to synthesize novel views with only a few discrete image observations of the world. However, the requirement of accurate camera parameters to learn scene representations limits its further application. In this paper, we present adaptive positional encoding (APE) for bundle-adjusting neural radiance fields to reconstruct the neural radiance fields from unknown camera poses (or even intrinsics). Inspired by Fourier series regression, we investigate its relationship with the positional encoding method and therefore propose APE where all frequency bands are trainable. Furthermore, we introduce period-activated multilayer perceptrons (PMLPs) to construct the implicit network for the high-order scene representations and fine-grained gradients during backpropagation. Experimental results on public datasets demonstrate that the proposed method with APE and PMLPs can outperform the state-of-the-art methods in accurate camera poses and high-fidelity view synthesis.
An advanced coded modulation is proposed based on improved staircase codes using marked bits and geometrically-shaped constellations. Up to 0.95 dB SNR gain and 8.6% reach increase are achieved for beyond 800G data ce...
An advanced coded modulation is proposed based on improved staircase codes using marked bits and geometrically-shaped constellations. Up to 0.95 dB SNR gain and 8.6% reach increase are achieved for beyond 800G data center interconnects.
Open-set action recognition(OSAR) aims to recognize known classes and reject unknown classes. Most OSAR methods focus on learning a favorable threshold to distinguish known and unknown samples in a pure data-driven ma...
Open-set action recognition(OSAR) aims to recognize known classes and reject unknown classes. Most OSAR methods focus on learning a favorable threshold to distinguish known and unknown samples in a pure data-driven manner. However, these methods do not utilize the prior knowledge of action classes. In this paper, we propose to Leverage Attribute Knowledge (LAK) for OSAR. Specifically, the class-attribute knowledge learning is designed to integrate attribute knowledge into the model based on spatial-temporal features. Here, attributes are used as a bridge, linking known and unknown classes implicitly to make up the knowledge gap. Furthermore, a learnable relation matrix is adaptively adjusted during training to obtain the class-attribute relations that are expected to be generalized in open-set settings. Extensive experiments on three popular datasets show that the proposed method achieves state-of-the-art performance.
Electromagnetic radiation (EMR) safety has always been a critical reason for hindering the development of magneticenabled wireless power transfer technology. People focus on the actual received energy at charging devi...
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ISBN:
(数字)9798350383508
ISBN:
(纸本)9798350383515
Electromagnetic radiation (EMR) safety has always been a critical reason for hindering the development of magneticenabled wireless power transfer technology. People focus on the actual received energy at charging devices while paying attention to their health. Thus, we study this significant problem in this paper, and propose a universal safety guaranteed power-delivered-to-load (PDL) maximization scheme (called SafeGuard). Technically, we first utilize the off-the-shelf electromagnetic simulator to perform the EMR distribution analysis to ensure the universality of the method. Then, we innovatively introduce the concept of multiple importance sampling for achieving efficient EMR safety constraint extraction. Finally, we treat the proposed optimization problem as an optimal boundary point search problem from the perspective of space geometry, and devise a brand-new grid-based multi-constraint parallel processing algorithm to efficiently solve it. We implement a system prototype for SafeGuard, and conduct extensive experiments to evaluate it. The results indicate that our SafeGuard can obviously improve the achieved PDL by up to 1.75× compared with the state-of-the-art baseline while guaranteeing EMR safety. Furthermore, SafeGuard can accelerate the solution process by 29.12× compared with the traditional numerical method to satisfy the fast optimization requirement of wireless charging systems.
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