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bsj-3189
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual resource, by combining two types of algorithms: dynamic algorithm (adaptive firefly) and static algorithm (weighted round robin). The results show improvement in resource utilization, increased productivity, and reduced response time.

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Assessing the performance of commercial Agisoft PhotoScan software to deliver reliable data for accurate3D modelling
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3D models delivered from digital photogrammetric techniques have massively increased and developed to meet the requirements of many applications. The reliability of these models is basically dependent on the data processing cycle and the adopted tool solution in addition to data quality. Agisoft PhotoScan is a professional image-based 3D modelling software, which seeks to create orderly, precise n 3D content from fixed images. It works with arbitrary images those qualified in both controlled and uncontrolled conditions. Following the recommendations of many users all around the globe, Agisoft PhotoScan, has become an important source to generate precise 3D data for different applications. How reliable is this data for accurate 3D mo

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Publication Date
Tue Mar 12 2019
Journal Name
Lubricants
Absorption Wavebands for Discriminating Oxidation Time of Engine Oil as Detected by FT-IR Spectroscopy
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Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.

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Publication Date
Sun Jan 01 2023
Journal Name
Alexandria Engineering Journal
Calcium/iron-layered double hydroxides-sodium alginate for removal of tetracycline antibiotic from aqueous solution
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Publication Date
Mon Apr 01 2019
Journal Name
International Journal Of Greenhouse Gas Control
CO2-wettability of sandstones exposed to traces of organic acids: Implications for CO2 geo-storage
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Wettability of CO2-brine-mineral systems plays a vital role during geological CO2-storage. Residual trapping is lower in deep saline aquifers where the CO2 is migrating through quartz rich reservoirs but CO2 accumulation within a three-way structural closure would have a high storage volume due to higher CO2 saturation in hydrophobic quartz rich reservoir rock. However, such wettability is only poorly understood at realistic subsurface conditions, which are anoxic or reducing. As a consequence of the reducing environment, the geological formations (i.e. deep saline aquifers) contain appreciable concentrations of various organic acids. We thus demonstrate here what impact traces of organic acids exposed to storage rock have on their wettabil

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Publication Date
Mon Jul 01 2024
Journal Name
Alexandria Engineering Journal
Comparison of some Bayesian estimation methods for type-I generalized extreme value distribution with simulation
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The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Geomate
METHODOLOGY FOR MONITORING THE FLEXURAL BEHAV-IOR OF STRUCTURAL CONCRETE MEMBERS WITH UNBONDED INTERNAL STEEL
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Publication Date
Thu Jun 01 2023
Journal Name
Chemical Physics Impact
An efficient Ag decorated CeO2 synergetic catalyst for improved catalytic reduction of lethal 4-nitrophenol
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Catalytic reduction is considered an effective approach for the reduction of toxic organic pollutants from the environment, but finding an active catalyst is still a big challenge. Herein, Ag decorated CeO2 catalyst was synthesized through polyol reduction method and applied for catalytic reduction (conversion) of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The Ag decorated CeO2 catalyst displayed an outstanding reduction activity with 99% conversion of 4-NP in 5 min with a 0.61 min−1 reaction rate (k). A number of structural characterization techniques were executed to investigate the influence of Ag on CeO2 and its effect on the catalytic conversion of 4-NP. The outstanding catalytic performances of the Ag-CeO2 catalyst can be assigne

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Publication Date
Mon Apr 28 2025
Journal Name
Chemical Papers
New chemiluminometric method for the determination of azithromycin in a continuous flow injection analysis system
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A novel analytical method is developed for the determination of azithromycin. The method utilizes continuous flow injection analysis to enhance the chemiluminescence system of luminol, H2O2, and Cr(III). The method demonstrated a linear dynamic range of 0.001–100 mmol L-1 with a high correlation coefficient (r) of 0.9978, and 0.001–150 mmol L-1 with a correlation coefficient (r) of 0.9769 for the chemiluminescence emission versus azithromycin concentration. The limit of detection (L.O.D.) of the method was found to be 18.725 ng.50 µL−1 based on the stepwise dilution method for the lowest concentration within the linear dynamic range of the calibration graph. The relative standard deviation (R.S.D. %) for n = 6 was less than 1.2%

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Publication Date
Tue Feb 01 2022
Journal Name
Advanced Powder Technology
Functionalization of mesoporous MCM-41 for the delivery of curcumin as an anti-inflammatory therapy
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