11 hasil untuk "Punit Gupta"
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Federated learning inspired Antlion based orchestration for Edge computing environment
Edge computing is a scalable, modern, and distributed computing architecture that brings computational workloads closer to smart gateways or Edge devices. This computing model delivers IoT (Internet of Things) computations and processes the IoT requests from the Edge of the network. In a diverse…
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Hybrid Bacterial Colony Optimization and Particle Swarm Optimization for load balancing in fog computing
Fog computing minimizes latency and bandwidth consumption by processing data near the source, but it has the challenge of workload balancing across the dynamic and resource limited fog nodes. Uneven task assignment can result in bottlenecks, idle resources, and lowered Quality of Service (QoS)…
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Availability optimization of power generating units used in sewage treatment plants using metaheuristic techniques
Metaheuristic techniques have been utilized extensively to predict industrial systems’ optimum availability. This prediction phenomenon is known as the NP-hard problem. Though, most of the existing methods fail to attain the optimal solution due to several limitations like slow rate of convergence…
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A Harris Hawk Optimisation system for energy and resource efficient virtual machine placement in cloud data centers
Virtualisation is a major technology in cloud computing for optimising the cloud data centre’s power usage. In the current scenario, most of the services are migrated to the cloud, putting more load on the cloud data centres. As a result, the data center’s size expands resulting in increased energy…
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Investigating the performance of multivariate LSTM models to predict the occurrence of Distributed Denial of Service (DDoS) attack
In the current cybersecurity landscape, Distributed Denial of Service (DDoS) attacks have become a prevalent form of cybercrime. These attacks are relatively easy to execute but can cause significant disruption and damage to targeted systems and networks. Generally, attackers perform it to make…
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Augmented Ensemble Model (AEM) for health trends prediction on social networks
Social Media has given an exponential rise to an ever-connected world. Health data that was earlier viewed as hospital records or clinical records is now being shared as text over social media. Information and updates regarding the outbreak of a pandemic, clinical visit results, general health…
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Stochastic modeling and parameter estimation of turbogenerator unit of a thermal power plant under classical and Bayesian inferential framework
The work reported in present study deals with the development of a novel stochastic model and estimation of parameters to assess reliability characteristics for a turbogenerator unit of thermal power plant under classical and Bayesian frameworks. Turbogenerator unit consists of five components…
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UMobileNetV2 model for semantic segmentation of gastrointestinal tract in MRI scans
Gastrointestinal (GI) cancer is leading general tumour in the Gastrointestinal tract, which is fourth significant reason of tumour death in men and women. The common cure for GI cancer is radiation treatment, which contains directing a high-energy X-ray beam onto the tumor while avoiding healthy…
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An efficient ranking deep neural network algorithm for the prediction of Ca 2+ binding sites of the protein
The Ca2+ binding sites of proteins are critical for their function, particularly in processes such as signal transduction, enzyme regulation, and structural stability. In this study, the calcium-binding sites of NtEhCaBP1 (Entamoeba histolytica calcium-binding protein). This paper proposes…
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Optimized technique for speaker changes detection in multispeaker audio recording using pyknogram and efficient distance metric
Segmentation process is very popular in Speech recognition, word count, speaker indexing and speaker diarization process. This paper describes the speaker segmentation system which detects the speaker change point in an audio recording of multi speakers with the help of feature extraction and…
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ConvLSTM-based tropical cyclone intensity estimation and classification using satellite imagery over the North Indian ocean
Tropical cyclones pose significant threats to coastal regions, and have a major negative influence on the environment and society. Precise cyclone identification and intensity estimation are crucial for effective early warning systems and disaster prevention. Traditional methods rely on manual…