Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

Numerical study has been conducted to investigate the thermal performance enhancement of flat plate solar water collector by integrating the solar collector with metal foam blocks.The flow is assumed to be steady, incompressible and two dimensional in an inclined channel. The channel is provided with eight foam blocks manufactured form copper. The Brinkman-Forchheimer extended Darcy model is utilized to simulate the flow in the porous medium and the Navier-Stokes equation in the fluid region. The energy equation is used with local thermal equilibrium (LTE) assumption to simulate the thermofield inside the porous medium. The current investigation covers a range of solar radiation intensity at 09:00 AM, 12:00 PM, and 04:00

Nanoceria have shown numerous unique characteristics, such as biocompatibility and are excellent agents for biological applications. The aim of this study is to investigate cerium oxide nanoparticles for 2, 2- diphenyl-1-picryl-hydrazyl-hydrate (DPPH) free radical scavenging activity and their ability to offer protection against ionizing radiation. In vitro antioxidant activity study of nanoceria particles has shown good free radical scavenging activity for DPPH radical assayed within a concentration range of 0.01 to 0.05 g/l, at higher concentrations of nanoparticles showed reverse trend in absorbance and inhibition indicating this finite rang of concentration is suitable for scavenging free radicals, also nanoparticles were found to ha

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

An experimental and numerical investigation of the effect of using two types of nanofluids with suspending of (Al₂O₃ and CuO) nanoparticles in deionized water with a volume fraction of (0.1% vol.), in addition to use three types of fin plate configurations of (smooth, perforated, and dimple plate) to study the heat transfer enhancement characteristics of commercial fin plate heat sink for cooling computer processing unit. All experimental tests under simulated conditions by using heat flux heater element with input power range of (5, 16, 35, 70, and 100 W). The experimental parameters calculated are such as water and nanofluid as coolant with Reynolds number of (7000, 8000, 9400 and 11300); the air

The blade pitch angle (BPA) in wind turbine (WT) is controlled to maximize output power generation above the rated wind speed (WS). In this paper, four types of controllers are suggested and compared for BPA controller in WT: PID controller (PIDC), type-1 fuzzy logic controller (T1-FLC), type-2 fuzzy logic controller (T2-FLC), and hybrid fuzzy-PID controller (FPIDC). The Mamdani and Sugeno fuzzy inference systems (FIS) have been compared to find the best inference system used in FLC. Genetic algorithm (GA) and Particle swarm optimization algorithm (PSO) are used to find the optimal tuning of the PID parameter. The results of500-kw horizontal-axis wind turbine show that PIDC based on PSO can reduced 2.81% in summation error of power

The present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) membrane for heavy metal removal from wastewater and study the factors affecting the performance of these two membranes: feed concentrations for heavy metal ions, pressure, and flow rate. The experimental results showed, heavy metals concentration in permeate increase with raise in feed concentrations, decline with increase in flow rate. The raise of pressure, heavy metals concentration decreases for RO membrane, but for NF membrane the concentration decrease and then at high pressure increase. The rejection percentage for chromium in NF and RO is 99.7% and 99.9%, for copper is 98.4% and 99.3%, for zinc is 97.9% and 99.5%, for nickel is 97.2% and

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti