The interband Zener-Klein interband tunneling in the field-effect transistors (FETs) with the graphene channels consisting of the reverse-biased p-i-n junctions enables the negative dynamic conductance associated with...
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Various machine learning techniques have been proposed to improve the effectiveness of Intrusion Detection systems (IDS), where IDS is one of the important parts of the network that functions to maintain network secur...
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For many years, there were many different ways to arrange a vehicle's information using just the license plate. The number on a vehicle's license plate is the primary symbol used to identify it. The industries...
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This study assesses the performance of different cross-validation splits for brain-signal-based Auditory Attention Decoding (AAD) using deep neural networks on three publicly available Electroencephalography datasets....
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Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods...
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The need for autonomous unmanned aerial vehicles (UAVs) is rapidly increasing for various industrial applications today. However, the realization of UAV autonomy requires a careful mix of Artificial Intelligence (AI) ...
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With 5G and beyond promises to realize massive machine-type communications, a wide range of applications have driven interest in complex heterogeneous networked systems, including multi-agent optimization, large-scale...
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ISBN:
(数字)9798350370997
ISBN:
(纸本)9798350371000
With 5G and beyond promises to realize massive machine-type communications, a wide range of applications have driven interest in complex heterogeneous networked systems, including multi-agent optimization, large-scale distributed learning, 5G service provisioning, etc. This trend highlights the essence of seamless control, management, and security mechanisms to be in place for the next-generation networked cyber-physical systems (CPS). In this paper, we interpret trust as a relation among networked collaborating entities that can set forth a measure for evaluating the status of network components and secure the execution of the collaborative protocol. In this paper, we will first elaborate on the importance of trust as a metric and then present a mathematical framework for trust computation and aggregation within a network. We consider two use-case examples where trust can be incorporated into the next-generation networked CPS and improve the security of decision-making, i.e. i) federated learning (FL), and ii) network resource provisioning. Finally, we explain the challenges associated with aggregating the trust evidence and briefly explain our ideas to tackle them.
Next Point-of-Interest (POI) recommendation plays a vital role in human mobility prediction within Location-based Social Networks (LSBN), assisting individuals to decide on their next destination. However, traditional...
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With the pervasiveness of Stochastic Shortest-Path (SSP) problems in high-risk industries, such as last-mile autonomous delivery and supply chain management, robust planning algorithms are crucial for ensuring success...
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Anomaly prediction, aiming to predict abnormal events before occurrence, plays a key role in significantly reducing costs and minimizing potential threats to mechanical devices. Monitoring machines using fixed-length ...
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