Polyaniline (PANI) and Ag/PANI nanocomposite thin films have prepared by microwave induced plasma. The Ag powder of average particle size of 50 nm, were used to prepare Ag/PANI nanocomposite thin films. The Ag/PANI nanocomposite thin films prepared by polymerization in plasma and characterized by UV-VIS, FTIR, AFM and SEM to study the effect of silver nanoparticles on the optical properties, morphology and structure of the thin films. The optical properties studies showed that the energy band gap of the Ag/PANI (5%wt silver) decreased from 3.6 to 3.2 eV, where the substrate location varied from 4.4 to 3.4 cm from the axis of the cylindrical plasma chamber. Also the optical energy gap decreased systematically from 3.3 to 3 eV with increas

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

Zigbee, which has the standard IEEE 802.15.4. It is advisable method to build wireless personal area network (WPAN) which demands a low power consumption that can be produced by Zigbee technique. Our paper gives measuring efficiency of Zigbee involving the Physical Layer (PL) and Media Access Control (MAC) sub-layer , which allow a simple interaction between the sensors. We model and simulate two different scenarios, in the first one, we tested the topological characteristics and performance of the IEEE802.15.4 standard in terms of throughput, node to node delay and figure of routers for three network layouts (Star, Mesh and Cluster Tree) using OPNET simulator. The second scenario investigates the self-healing feature on a mesh

Colloidal crystals (opals) made of close-packed polymethylmethacrylate (PMMA) were fabricated and grown by Template-Directed methods to obtain porous materials with well-ordered periodicity and interconnected pore systems to manufacture photonic crystals. Opals were made from aqueous suspensions of monodisperse PMMA spheres with diameters between 280 and 415 nm. SEM confirmed the PMMA spheres crystallized uniformly in a face-centered cubic (FCC) array. Optical properties of synthesized pores PMMA were characterized by UV–Visible spectroscopy. It shows that the colloidal crystals possess pseudo photonic band gaps in the visible region. A combination of Bragg’s law of diffraction and Snell’s law of refraction were used to calculate t

Sustainable development has recently gained significant attention in the field of water Quality (WQ), which is critical for a healthy lifestyle. Our work suggests an intelligent hybrid model for assessing water quality using a water portability dataset, which was used to evaluate the water quality. The dataset contains physical and chemical features such as pH, Organic Carbon, sulfate, etc. Based on the combination of a Decision Tree Algorithm (DTA) and fuzzy logic Approaches, the findings revealed that sulfate was the most important factor in the model, with an accuracy of 1.00, followed by pH with an accuracy of 0.9667, and solids and chloramines with an accuracy of 0.95. The other parameters achieved a similar accuracy of 0.9167, showing

2-hydrazinylbenzo[d]thiazole compound [1] is produced from reaction of 2-mercapto-benzothiazole with hydrazine hydride in ethanol. Compound [1] reacted with maleic anhydride in DMF to produce (Z)-4-(2-(benzo[d] thiazol-2yl) hydrazinyl)-4-oxobut-2-enoic acid [compound (2)]. While the treatment of compound [2] with the ammonium persulfate (NH4)2S2O8 (as the initiator) in order to produce compound [3], then compound [3] reacted with thionyl chloride in benzene to produce compound [4], finally compound [4] reaction with various drugs: cephalexin, amoxicillin, sulfamethizole, elecoxib obtained polymers [5–8]. The structure of synthesized compounds identified by spectral data: fourier transform infrared (FTIR) and proton nuclear magneti

To evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D