In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net ***,a Petri net for the deadlock control of such systems is *** a...
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In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net ***,a Petri net for the deadlock control of such systems is *** admissible markings and first-met inadmissible markings(FIMs)are ***,place invariants are designed via an integer linear program(ILP)to survive all admissible markings and prohibit all FIMs,keeping the underlying system from reaching deadlocks,livelocks,bad markings,and the markings that may evolve into them by firing uncontrollable *** also ensures that the obtained deadlock-free supervisor does not observe any unobservable *** addition,the supervisor is guaranteed to be admissible and structurally minimal in terms of both control places and added *** condition under which the supervisor is maximally permissive in behavior is ***,experimental results with the proposed method and existing ones are given to show its effectiveness.
This work proposes a physical layer security (PLS) framework leveraging integrated sensing and communication (ISAC) to facilitate secure communication. The framework employs a multi-antenna full-duplex (FD), dual-func...
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The global greenhouse effect and air pollution problems have been getting deteriorated in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have ...
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ISBN:
(纸本)9781665493291
The global greenhouse effect and air pollution problems have been getting deteriorated in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered by fossil fuels in the next few decades, so as to effectively alleviate the global greenhouse effect and air pollution problems. In addition to electric vehicles that will replace traditional fuel vehicles as the main ground transportation vehicles in the future, drones have also gradually been widely used for military and civilian purposes recently. The recent literature estimated that drones will become the major means of transport for goods delivery services before 2040, and the development of passenger drones will also extend the traditional human ground transportation to low-altitude airspace transportation. In recent years, the literature has proposed the use of renewable power supply, battery swapping and charging stations to refill the battery of drones. However, the uncertainty of renewable power generation cannot guarantee the stable power supply of drones. It may even be very possible that a large number of drones need to be charged during the same period, causing congestion in charging stations or battery swapping facilities and delaying the arranged schedules of drones. Although studies have proposed to employ moving electric vehicles along with wireless charging technology to provide electricity to drones with urgent needs, the charging schemes are still oversimplified and have many restrictions. In addition, different charging options, such as charging stations and battery exchange services, as well as wireless charging for drones, should be provided to fit the individual need of each drone. In view of this, this work presented a joint solution of routing and charging management to meet the mission characteristics of various drones by providing adaptive routing and charging plans to i
We present a novel approach for test-time adaptation via online self-training, consisting of two components. First, we introduce a statistical framework that detects distribution shifts in the classifier's entropy...
ISBN:
(纸本)9798331314385
We present a novel approach for test-time adaptation via online self-training, consisting of two components. First, we introduce a statistical framework that detects distribution shifts in the classifier's entropy values obtained on a stream of unlabeled samples. Second, we devise an online adaptation mechanism that utilizes the evidence of distribution shifts captured by the detection tool to dynamically update the classifier's parameters. The resulting adaptation process drives the distribution of test entropy values obtained from the self-trained classifier to match those of the source domain, building invariance to distribution shifts. This approach departs from the conventional self-training method, which focuses on minimizing the classifier's entropy. Our approach combines concepts in betting martingales and online learning to form a detection tool capable of quickly reacting to distribution shifts. We then reveal a tight relation between our adaptation scheme and optimal transport, which forms the basis of our novel self-supervised loss. Experimental results demonstrate that our approach improves test-time accuracy under distribution shifts while maintaining accuracy and calibration in their absence, outperforming leading entropy minimization methods across various scenarios.
Currently, the dominant encoding method for computer-generated holograms is phase-only holography. The Gerchberg-Saxton (GS) algorithm is a commonly used approach for hologram generation. However, it suffers from issu...
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Lung cancer is nowadays becoming a common disease that is fatal to the life of any human being. However, modern diagnosis systems have significantly improved to detect such disease at an early stage and helping the me...
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The successful and complete downlink transmission of critical data from an unmanned aerial vehicle (UAV) base station, such as control command and intelligence information, is essential for ground users to perform spe...
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In this work, we develop a scheme for constructing continuous approximations (referred to as abstractions) of a class of discrete-time control systems with partially unknown dynamics. The abstraction, itself a nonline...
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Computing in the cloud refers to a model that offers inexpensive, scalable computing resources like CPU, storage, and network bandwidth. Allows users to access a shared pool of resources via the internet on an as-need...
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Multi-access Edge Computing (MEC) enhances the capabilities of 5G by enabling the computation closer to the end-user for real-time and context-aware services. One of the main challenges of MEC is the migration of the ...
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