Identical video sharing across social networks results in redundant video data traffic, consuming additional bandwidth, storage resources, and data usage. A novel method is proposed to optimise redundant video-sharing...
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Music streaming services are getting increasingly popular as a result of the prevalent need for web and smart gadgets. Melophiles are drawn toward a range of musical genres and create a unique digital footprint. The e...
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Early identification of skin cancer is mandatory to minimize the worldwide death rate as this disease is covering more than 30% of mortality rates in young and adults. Researchers are in the move of proposing advanced...
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Network virtualization (NV) plays a crucial role in modern network management. One of the fundamental challenges in NV is allocating physical network (PN) resources to the demands of the virtual network requests (VNRs...
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Chronic kidney disease (CKD) is a prominent disease that causes loss of functionality in the kidney. Doctors can now more easily gather patient health status data due to the growth of the Internet of Health Things (Io...
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Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various ***,certain limitations need to be addressed *** provisioning of detection mechanism wit...
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Capturing the distributed platform with remotely controlled compromised machines using botnet is extensively analyzed by various ***,certain limitations need to be addressed *** provisioning of detection mechanism with learning approaches provides a better solution more broadly by saluting multi-objective *** bots’patterns or features over the network have to be analyzed in both linear and non-linear *** linear and non-linear features are composed of high-level and low-level *** collected features are maintained over the Bag of Features(BoF)where the most influencing features are collected and provided into the classifier ***,the linearity and non-linearity of the threat are evaluated with Support Vector Machine(SVM).Next,with the collected BoF,the redundant features are eliminated as it triggers overhead towards the predictor ***,a novel Incoming data Redundancy Elimination-based learning model(RedE-L)is built to classify the network features to provide robustness towards BotNets *** simulation is carried out in MATLAB environment,and the evaluation of proposed RedE-L model is performed with various online accessible network traffic dataset(benchmark dataset).The proposed model intends to show better tradeoff compared to the existing approaches like conventional SVM,C4.5,RepTree and so ***,various metrics like Accuracy,detection rate,Mathews Correlation Coefficient(MCC),and some other statistical analysis are performed to show the proposed RedE-L model's *** F1-measure is 99.98%,precision is 99.93%,Accuracy is 99.84%,TPR is 99.92%,TNR is 99.94%,FNR is 0.06 and FPR is 0.06 respectively.
Hyperspectral imaging has transformed remote sensing by offering detailed spectral data for monitoring environmental changes, like urban development and terrestrial cover variations. However, existing change detection...
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In the densification of Device-to-Device(D2D)-enabled Social Internet of Things(SIoT)networks,improper allocation of resources can lead to high interference,increased signaling overhead,latency,and disruption of Chann...
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In the densification of Device-to-Device(D2D)-enabled Social Internet of Things(SIoT)networks,improper allocation of resources can lead to high interference,increased signaling overhead,latency,and disruption of Channel State Information(CSI).In this paper,we formulate the problem of sum throughput maximization as a Mixed Integer Non-Linear Programming(MINLP)*** problem is solved in two stages:a tripartite graph-based resource allocation stage and a time-scale optimization *** proposed approach prioritizes maintaining Quality of Service(QoS)and resource allocation to minimize power consumption while maximizing sum *** results demonstrate the superiority of the proposed algorithm over standard benchmark *** of the proposed algorithm using performance parameters such as sum throughput shows improvements ranging from 17%to 93%.Additionally,the average time to deliver resources to CSI users is minimized by 60.83%through optimal power *** approach ensures QoS requirements are met,reduces system signaling overhead,and significantly increases D2D sum throughput compared to the state-of-the-art *** proposed methodology may be well-suited to address the challenges SIoT applications,such as home automation and higher education systems.
In an educational ecosystem, accurate and complete management of student’s records is a complex and error-prone process. Blockchain is a promising solution to add substantial value around enhanced efficiency, privacy...
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Convolutional neural networks (ConvNets) have become increasingly popular for image classification tasks. All contemporary computer vision problems are being dominated by ConvNets. Conventional training methods using ...
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