The purpose of this study is to demonstrate a simple high sensitivity vapor sensor for propanol ((CH3)2CHOH). A free space gap was employed in two arms of a Mach-Zehnder interferometer to serve as the sensing mechanism by adding propanol volume (0.2, 0.4, 0.6, 0.8, and 1) ml and to set the phase reference with a physical spacing of (0.5, 1, 1.5, and 2) mm. The propagation constant of transmitted light in the Mach-Zehnder interferometer’s gap changes due to the small variation in the refractive index inside sensing arm that will further shift the optical phase of the signal. Experimental results indicated that the highest sensitivity of propanol was about 0.0275 nm/ml in different liquid volume while highest phase shift was 0.182×103 i

CdS and CdS:Sn thin films were successfully deposited on glass
substrates by spray pyrolysis method. The films were grown at
substrate temperatures 300 C°. The effects of Sn concentration on the
structural and optical properties were studied.
The XRD profiles showed that the films are polycrystalline with
hexagonal structure grown preferentially along the (002) axis. The
optical studies exhibit direct allowed transition. Energy band gap
vary from 3.2 to 2.7 eV.

Spray pyrolysis technique (SPT) is employed to synthesize cadmium oxide nanostructure with 3% and 5% Cobalt concentrations. Films are deposited on a glass substrate at 350 ᵒC with 150 nm thickness. The XRD analysis revealed a polycrystalline nature with cubic structure and (111) preferred orientation. Structural parameters represent lattice spacing, crystallite size, lattice parameter and dislocation density. Homogeneous surfaces and regular distribution of atoms were showed by atomic force microscope (AFM) with 1.03 nm average roughness and 1.22 nm root mean square roughness. Optical properties illustrated a high transmittance more than 85% in the range of visible spectrum and decreased with Co concentration increasing. The absorption

Undoped and Iodine (I)–doped chrome oxide (Cr2O3)thin films have been prepared by chemical spray pyrolysis technique at substrate temperatures(773K) on glass substrate. Absorbance and transmittance spectra have been recorded as a function of wavelength in the range (340-800 nm) in order to study the optical properties such as reflectance, Energy gap of allowed direct transition, extinction coefficient refractive index, and dielectric constant in real and imagery parts all as a function of wavelength. It was found that all the investigated parameters affect by the doping ratios.

For the first time Iron tungstate semiconductor oxides films (FeWO4) was successfully synthesized simply by advanced controlled chemical spray pyrolysis technique, via employed double nozzle instead of single nozzle using tungstic acid and iron nitrate solutions at three different compositions and spray separately at same time on heated silicone (n-type) substrate at 600 °C, followed by annealing treatment for one hour at 500 °C. The crystal structure, microstructure and morphology properties of prepared films were studied by X-ray diffraction analysis (XRD), electron Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) respectively. According to characterization techniques, a material of well-crystallized monoclinic ph

Thin filis have been prepared from the tin disulphide (SnS2 ), the pure and the doped with copper (SnS2:Cu) with a percentages (1,2,3,4)% by using ahemical spray pyrolysis techniqee on substrate of glass heated up to(603K)and sith thicknesses (0.7±0.02)?m ,after that the films were treated thermally with a low pressure (10-3mb) and at a temperature of (473K) for one hour. The influence of both doping with copper and the thermal treatment on some of the physical characteristics of the prepared films(structural and optical) was studied. The X-ray analysis showed that the prepared films were polycrystalline Hexagonal type. The optical study that included the absorptance and transmitance spectra in the weavelength range (300-900)nm

    In this research, CNRs have been synthesized using pyrolysis of plastic waste(pp) at 1000 ° C for one hour in a closed reactor made from stainless steel, using magnesium oxide (MgO) as a catalyst. The resultant carbon nano rods were purified and characterized using energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of carbon rods were observed with the Field emission scanning electron microscopy (FESEM). The carbon was evenly spread and had the highest concentration from SEM-EDX characterization. The results of XRD and FESEM have shown that carbon Nano rods (CNRs) were present in Nano figures, synthesized at 1000 ° C and with pyrolysis temperature 400° C. One of t

AlPO4 catalysts supported with WO3 were prepared by impregnating the catalysts with ammonium metatungstate. The catalysts were checked by X-ray Diffraction (XRD), AFM, and SEM; also, the catalysts analysis was done by X-Ray (EDX). Finally, the N2 adsorption-desorption was used to measure the pore volume and surface area of the catalyst. The prepared catalyst has a surface area of 185.83 m2/g, pore volume of 0.645 cm3/g at a calcination temperature of 500°C for 3 hrs, and particle size of AlPO4 with an average of 35.36 nm. Transesterification of edible oil using WO3/AlPO4 was performed, it was observed that WO3/AlPO4 catalysts give high conversion of edible oil, and this is attributed to the high surface area, smaller particle size, and the

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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