The joint implementation of federated learning (FL) and explainable artificial intelligence (XAI) could allow training models from distributed data and explaining their inner workings while preserving essential aspect...
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In the In the Internet of Vehicles (IoV), intelligent decision-making is performed by objects with cognition. by comprehending both the social and physical worlds, Cognition Radio Network (CRN) is seen as a workable o...
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In the In the Internet of Vehicles (IoV), intelligent decision-making is performed by objects with cognition. by comprehending both the social and physical worlds, Cognition Radio Network (CRN) is seen as a workable option. The existence of dangerous devices (MD) further impairs network performance, although For services to be improved and safety metrics to be driven, spectrum availability and information exchange among vehicles are crucial. Recently, a blockchain approach has been added to CRN-based IoV to stop data modification from these Entities and enable the cars to monitor both legal and illegitimate network activity. In this paper, we provide security to IoV throughout spectrum sensors and details transfer using CRN by sensing the paths through with a decision-making technique called Method for Order Personal taste by Similarity to a Solution (topsis (TOPSIS), a technique that inspires the confidence of its Behavioral Users (CU) by analysing certain predefined attributes. The network also maintains a blockchain to track every action involving information that has been saved. Using different frequency sensing and security settings in comparison to an IoV baseline solution, the suggested method is thoroughly evaluated against a number of security criteria. Numerous simulations indicate that when compared to the baseline system, our suggested approach is around 70% more effective at identifying malicious nodes and DoS threats.
Ontologies are a standard for semantic schemata in many knowledge-intensive domains of human interest. They are now becoming increasingly important also in areas until very recently dominated by subsymbolic representa...
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Wireless energy transfer is an emerging technology that is used in networks of battery-powered devices in order to deliver energy and keep the network functional. Existing state-of-the-art studies have mainly focused ...
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The study presents an advanced neural network model for real-time remote evaluation and treatment of rheumatic diseases using sensor fusion. The model was developed for use in this investigation. The suggested system ...
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ISBN:
(数字)9798350353068
ISBN:
(纸本)9798350353075
The study presents an advanced neural network model for real-time remote evaluation and treatment of rheumatic diseases using sensor fusion. The model was developed for use in this investigation. The suggested system uses a wide variety of sensing modalities, such as image, motion, and biometric sensors. This is accomplished via artificial intelligence (AI) and the data gleaned from sensors. The neural network, which was trained on a dataset that was both varied and labeled, performs autonomous analyses of input data in order to accurately predict and categorize rheumatic diseases. The integration of the model into remote medical treatment is made easier by the fact that it is run on a Raspberry Pi inside a tele-rheumatology framework. This unique strategy not only improves diagnostic accuracy but also expands rheumatology services to geographically inaccessible or disadvantaged groups. As a result, the landscape of rheumatic healthcare delivery is completely transformed as a result of this new approach. For the purpose of ensuring the ethical use of this revolutionary technology, the procedures for data security and ethical concerns have been given priority.
Rapid technological advances in the domain of Wireless Power Transfer (WPT) pave the way for novel methods for power management in systems of wireless devices and recent research works have already started considering...
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This paper studies the discovery of approximate rules in property graphs. First, we propose a semantically meaningful measure of error for mining graph entity dependencies (GEDs) that almost hold, to tolerate errors a...
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In this paper, we consider a MEC-enabled metaverse scenario which consists of a remote metaverse server and an edge server that cooperates to provide services to mobile users. The edge server is deployed at the base s...
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Smart spaces are a rapidly emerging concept in technology. They result from the convergence of various novel technologies, such as the Internet of Things, Machine Learning and Artificial Intelligence, which allow for ...
Smart spaces are a rapidly emerging concept in technology. They result from the convergence of various novel technologies, such as the Internet of Things, Machine Learning and Artificial Intelligence, which allow for greater levels of automation and control within physical environments. The devices which are connected to the IoT network are equipped with sensors to acquire and exchange data. As a result, the IoT has transformed how we live, work, and play. However, the deployment in smart spaces is not always the best due to the issues arising from network node positioning. Therefore, we are investigating solutions to this problem with a novel approach which utilises Voronoi diagrams in conjunction with the algorithmic genetic technique. First, the initial positions of the IoT nodes will be determined by simulating a homogeneous Poisson point process in the smart space environment. Then, after dividing the area into the Voronoi cells, the genetic algorithm will optimise the position towards achieving full network coverage within the smart space. Experimental results prove the 100% network coverage within the specified area.
In recent years, hardware acceleration in large-scale computing fields such as Artificial Intelligence and High Performance Computing, faces hardware resource shortages. To overcome this problem, we propose Reconfigur...
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