The Editor-in-Chief has retracted this article because it contains significant textual overlap with two prior publications with no common authors [1, 2]. The Publisher was not able to confirm a current contact email f...
Application development is a very important aspect when it comes to business. From small-scale companies to Fortune Companies everyone has an application through which they are running their business whether it is a w...
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In this article, a design approach to a radial-resonant wide beamwidth circular sector patch antenna is advanced. As properly evolved from a U-shaped d ipole, a prototype magnetic dipole can be fit in the radial direc...
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In this article, a design approach to a radial-resonant wide beamwidth circular sector patch antenna is advanced. As properly evolved from a U-shaped d ipole, a prototype magnetic dipole can be fit in the radial direction of a circular sector patch radiator, with its length set as the positive odd-integer multiples of onequarter wavelength. In this way, multiple TM0m（m = 1,2,...） modes resonant circular sector patch antenna with short-circuited circumference and widened E-plane beamwidth can be realized by proper excitation and perturbations. Prototype antennas are then designed and fabricated to validate the design approach. Experimental results reveal that the E-plane beamwidth of a dual-resonant antenna fabricated on air/Teflon substrate can be effectively broadened to 128°/120°, with an impedance bandwidth of 17.4%/7.1%, respectively. In both cases, the antenna heights are strictly limited to no more than 0.03-guided wavelength. It is evidently validated that the proposed approach can effectively enhance the operational bandwidth and beamwidth of a microstrip patch antenna while maintaining its inherent low profile merit.
The proliferation of Internet of Things (loT) devices has introduced significant security challenges due to the increased attack surface and the inherent vulnerabilities of interconnected systems. This paper proposes ...
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ISBN:
(数字)9798331504960
ISBN:
(纸本)9798331504977
The proliferation of Internet of Things (loT) devices has introduced significant security challenges due to the increased attack surface and the inherent vulnerabilities of interconnected systems. This paper proposes a novel security framework that integrates Artificial Intelligence (AI)-infused software and Virtual Replica Models, or Digital Twins, to enhance the robustness of loT systems. The framework leverages AI-driven anomaly detection and predictive analysis to identify potential threats in real-time, while Digital Twins provide a virtual replica of the loT ecosystem for continuous monitoring and simulation-based threat assessment. By fusing these technologies, the proposed solution enables proactive security measures, ensuring rapid response to cyberattacks and continuous system optimization. Extensive simulations and experimental results demonstrate the system's ability to reduce attack detection times by 30%, while improving overall system resilience and minimizing false positive rates. This approach provides a scalable and adaptable solution for securing loT infrastructures in various industries.
Trajectory representation learning (TRL) is an intermediate step in handling trajectory data to realize various downstream machine-learning tasks. While most previous TRL research focuses on modeling structured moveme...
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In Discrete Variable Quantum Key Distribution (DV-QKD), homodyne detection method is frequently employed for its simplicity in use, effectiveness in terms of error correction, and suitability with contemporary optical...
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This research focuses on the primary aspects that influence the usage of renewable energy sources in microgrids. These aspects include energy demand, the amount of solar irradiation, and the capacity of the batteries....
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In this paper, we present a new mission planning optimisation method for coverage missions involving Uncrewed Aerial systems (UAS) and Ground Vehicles (GV) to minimize the mission planning time and the UAS and GV rout...
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In this paper, we present a new mission planning optimisation method for coverage missions involving Uncrewed Aerial systems (UAS) and Ground Vehicles (GV) to minimize the mission planning time and the UAS and GV route length. Optimal planning of paths for the UAS and GV using the Mixed Integer Linear Program (MILP), often struggles with computational inefficiency and limited scalability in scenarios with a growing number of waypoints and vehicles. To overcome the MILP computational issues, we present a reinforcement learning technique based on rollout policy optimisation called as Multi-Agent Rollout Policy Optimisation (MARPO). Through simulations, we showcase MARPO’s ability to match the precision of conventional MILP formulation in small instances and excel in scalability and computational efficiency in larger cases. Additionally, MARPO is compared with a heuristic method, Multi-Agent Greedy Path-Finding Algorithm (MAGPA), and the superior performance of MARPO in terms of total path length and computational efficiency is demonstrated. Several simulations are presented to showcase the advantages of MARPO. In simulations with 1 UAS and 1 UGV, MARPO achieved path lengths up to 1.56% longer than MILP’s optimum for 9 to 25 waypoints, while significantly reducing computation time by up to 99.88%. In larger scenarios of 36 and 49 waypoints, where MILP was infeasible, MARPO provided convincing solutions with greatly enhanced computational efficiency, demonstrating its robust scalability and effectiveness. Authors
Recently,there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy(DR).DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged peopl...
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Recently,there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy(DR).DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed *** detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus *** article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy(DLLSHDM-DR)on Retinal Fundus *** proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making *** the DLLSHDM-DR technique,image preprocessing is initially performed to improve the quality of the fundus ***,the DLLSHDM-DR applies HybridNet for producing a collection of feature *** retinal image classification,the DLLSHDM-DR technique exploits the Emperor Penguin Optimizer(EPO)with a Deep Recurrent Neural Network(DRNN).The application of the EPO algorithm assists in the optimal adjustment of the hyperparameters related to the DRNN model for DR detection showing the novelty of our *** assuring the improved performance of the DLLSHDMDR model,a wide range of experiments was tested on the EyePACS *** comparison outcomes assured the better performance of the DLLSHDM-DR approach over other DL models.
This work proposes simply wideband four-element L-shaped notch-patch (LNP) MIMO antenna for 5G new radio (NR) networks. The proposed LNP MIMO antenna comprised of four-port antenna elements. The single antenna scheme ...
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ISBN:
(数字)9798331543952
ISBN:
(纸本)9798331543969
This work proposes simply wideband four-element L-shaped notch-patch (LNP) MIMO antenna for 5G new radio (NR) networks. The proposed LNP MIMO antenna comprised of four-port antenna elements. The single antenna scheme contained L-shaped with notch microstrip patch antenna and modified ground plane. The proposed LNP MIMO antenna at 4.5 GHz (center frequency) can be provided impedance bandwidth (IBW) of 64% (3.57 – 6.45 GHz). The LNP MIMO antenna has been evaluated the MIMO performance metrics, including transmission coefficient (isolation), envelop correlation coefficient (ECC), diversity gain (DG), and mean effective gain (MEG). The simulated results of the LNP MIMO antenna achieved isolation of 20 dB, ECC of below 0.005, DG of above 9.975 dB, and MEG of approximately -3 dB. All simulated results are in good satisfactory, rendering the proposed LNP MIMO antenna suitable for 5G applications.
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