Current cloud-based systems face the challenge of managing storage and eliminating redundant data associated with the exponentially growing multimedia content, where numerous semantically similar but nonidentical file...
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As the usage of multi-cloud setups grows, resource management will become a major concern. Because of the dynamic nature of these environments, as well as fluctuating workloads and service-level targets, an effective ...
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Introduces an innovative application of 5G MIMO data in singular value decomposition (SVD) focusing on deep learning beam-selection and intelligent network analytics. This research explores the potential of leveraging...
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Wireless sensor network (WSN) applications are added day by day owing to numerous global uses (by the military, for monitoring the atmosphere, in disaster relief, and so on). Here, trust management is a main challenge...
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In today's Internet routing infrastructure,designers have addressed scal-ing concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary *** tactical...
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In today's Internet routing infrastructure,designers have addressed scal-ing concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary *** tactical Mobile Ad-hoc Network(MANET),hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out,self-mending and *** in the routing process is one of the key aspects to increase MANET performance by coordinat-ing the pathways using multiple criteria and *** present a Group Adaptive Hybrid Routing Algorithm(GAHRA)for gathering portability,which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile *** on this aspect,the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach,with the objectives of enhancing the out-put of MANET routing computation in each *** analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.
Interoperability is a crucial aspect of the effective functioning of Internet of Things (IoT) devices, particularly in the healthcare industry. Although the use of IoT devices in healthcare has brought numerous benefi...
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The grading of fruits relies on inspections, experiences, and observations, with a proposed system integrating machine learning techniques to assess fruit freshness. By analyzing 2D fruit portrayals based on shape and...
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Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the desig...
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Beam scanning for joint detection and communication in integrated sensing and communication(ISAC) systems plays a critical role in continuous monitoring and rapid adaptation to dynamic environments. However, the design of sequential scanning beams for target detection with the required sensing resolution has not been tackled in the *** bridge this gap, this paper introduces a resolution-aware beam scanning design. In particular, the transmit information beamformer, the covariance matrix of the dedicated radar signal, and the receive beamformer are jointly optimized to maximize the average sum rate of the system while satisfying the sensing resolution and detection probability requirements.A block coordinate descent(BCD)-based optimization framework is developed to address the non-convex design problem. By exploiting successive convex approximation(SCA), S-procedure, and semidefinite relaxation(SDR), the proposed algorithm is guaranteed to converge to a stationary solution with polynomial time complexity. Simulation results show that the proposed design can efficiently handle the stringent detection requirement and outperform existing antenna-activation-based methods in the literature by exploiting the full degrees of freedom(DoFs) brought by all antennas.
Machine uptime is highly important as the repairing time takes longer which affects the production and the manufacturing industry focus on new ways of being competitive. Manufacturing and assembly parts of the machine...
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Developing an automatic and credible diagnostic system to analyze the type,stage,and level of the liver cancer from Hematoxylin and Eosin(H&E)images is a very challenging and time-consuming endeavor,even for exper...
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Developing an automatic and credible diagnostic system to analyze the type,stage,and level of the liver cancer from Hematoxylin and Eosin(H&E)images is a very challenging and time-consuming endeavor,even for experienced pathologists,due to the non-uniform illumination and *** several Machine Learning(ML)and Deep Learning(DL)approaches are employed to increase the performance of automatic liver cancer diagnostic systems,the classi-fication accuracy of these systems still needs significant improvement to satisfy the real-time requirement of the diagnostic *** this work,we present a new Ensemble Classifier(hereafter called ECNet)to classify the H&E stained liver histopathology images *** proposed model employs a Dropout Extreme Learning Machine(DrpXLM)and the Enhanced Convolutional Block Attention Modules(ECBAM)based residual *** applies Voting Mechanism(VM)to integrate the decisions of individual classifiers using the average of probabilities ***,the nuclei regions in the H&E stain are seg-mented through Super-resolution Convolutional Networks(SrCN),and then these regions are fed into the ensemble DL network for classifi*** effectiveness of the proposed model is carefully studied on real-world *** results of our meticulous experiments on the Kasturba Medical College(KMC)liver dataset reveal that the proposed ECNet significantly outperforms other existing classifica-tion networks with better accuracy,sensitivity,specificity,precision,and Jaccard Similarity Score(JSS)of 96.5%,99.4%,89.7%,95.7%,and 95.2%,*** obtain similar results from ECNet when applied to The Cancer Genome Atlas Liver Hepatocellular Carcinoma(TCGA-LIHC)dataset regarding accuracy(96.3%),sensitivity(97.5%),specificity(93.2%),precision(97.5%),and JSS(95.1%).More importantly,the proposed ECNet system consumes only 12.22 s for training and 1.24 s for ***,we carry out the Wilcoxon statistical test to determine whether the ECN
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