HPSBA: A MODIFIED HYBRID FRAMEWORK WITH CONVERGENCE ANALYSIS FOR SOLVING WIRELESS SENSOR NETWORK COVERAGE OPTIMIZATION PROBLEM

HPSBA: A Modified Hybrid Framework with Convergence Analysis for Solving Wireless Sensor Network Coverage Optimization Problem

Complex optimization (CO) problems have been solved using swarm intelligence (SI) methods.One of the CO problems is the Wireless Sensor Network (WSN) coverage optimization problem, which plays an important role in Internet of Things (IoT).A novel hybrid algorithm is proposed, named hybrid particle swarm butterfly algorithm (HPSBA), by combining the

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Experimental Investigation of Using E10 and E15 Blend Fuels as a Fuel on Performance Parameters of the Cooling System of an Engine

This research investigates the impact of E10 and E15 fuel blends on the cooling system performance parameter of an engine compared to pure gasoline.The paper was done by experimenting on a CT 400.01 four-cylinder, four-stroke, water-cooled petrol engine.Various parameters were recorded during the experiments, including the cooling water outlet temp

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THE IMAGE OF THE CITY INTERPRETED THROUGH BIOSENSORS PATH ANALYSIS AND IDENTIFICATION OF PERCEPTUAL POLES IN THE NARNI CASE STUDY

The research aims to interpret the image of the city, according to the conventions defined by Kevin Lynch, obtained from the analysis of the impact of environmental stimuli on the person.The study relates the digital Sinus reconstruction of the spaces analysed with the detection of the trend of valence obtained on a statistical sample using an EEG

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Wind barriers offer short-term solution to fugitive dust

Wind-blown fugitive dust is a widespread problem in the arid west resulting from land disturbance or abandonment and increasingly limited water supplies.Soil-derived particles obstruct visibility, cause property damage and contribute to violations of health-based air quality standards for fine particles (PM-10).These dry lands are often difficult t

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A Self-Attention-Guided 3D Deep Residual Network With Big Transfer to Predict Local Failure in Brain Metastasis After Radiotherapy Using Multi-Channel MRI

A noticeable proportion of larger brain metastases (BMs) are not locally controlled after stereotactic radiotherapy, and it may take months before local Sinus progression is apparent on standard follow-up imaging.This work proposes and investigates new explainable deep-learning models to predict the radiotherapy outcome for BM.A novel self-attentio

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