Scheduling algorithms in distributed heterogeneous systems have been the subject of extensive research. However, with the advancement of technology, addressing real-time, reliability, and energy consumption issues in ...
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The processes of sowing and fertiliser application represent a significant aspect of agricultural production. In order to achieve efficient and precise seeding and fertiliser application, mass flow detection of seed a...
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Text classification is a fundamental task in natural language processing, and with a huge and rapidly growing body of research devoted to it. However, there has been little work on investigating noise robustness for t...
In pursuit-evasion the objective of the pursuer is to capture the evader. In this work, the faster pursuer is modeled to have limited range and therefore optimal strategies for the pursuer and evader change. Depending...
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Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-...
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Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.
Trust and reputation in production networks are of increasing importance, both from theoretical and practical points of view. One can find some case studies considering trustfulness in different areas such as supply c...
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Trust and reputation in production networks are of increasing importance, both from theoretical and practical points of view. One can find some case studies considering trustfulness in different areas such as supply chains, cloud, distributed and platform-based manufacturing as well – but considering trustfulness is not yet widespread in this field. The aim of the paper is twofold: first, to provide an overview about trust and reputation systems (TRSs) including definitions, classification of systems, rankings, challenges attack types, defense mechanisms and case studies. Second, to compose a requirement list – based on challenges found in the literature and consequences drawn – towards a TRS that can be used between production companies and supply chain members and is able to face the issues found in the scientific papers and introduced by the authors.
Since it is difficult to obtain a large number of the real samples of SAR images, the accuracy of synthetic aperture radar automatic target recognition (SAR-ATR) based on deep learning is often affected by the lack of...
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The application of learning-based control methods in robotics presents significant challenges. One is that model-free reinforcement learning algorithms use observation data with low sample efficiency. To address this ...
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The secondary system is very important for the reliable power supply and safe production of the power system. It includes secondary equipment and secondary circuits. The connection status of the secondary circuits wil...
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The biology of the brain can inspire the development of a wide range of intelligent information processing algorithms. Spatiotem-poral processing allows the brain to aggregate and represent information on multiple tim...
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