Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

     In recent years images have been used widely by online social networks providers or numerous organizations such as governments, police departments, colleges, universities, and private companies. It held in vast databases. Thus, efficient storage of such images is advantageous and its compression is an appealing application. Image compression generally represents the significant image information compactly with a smaller size of bytes while insignificant image information (redundancy) already been removed for this reason image compression has an important role in data transfer and storage especially due to the data explosion that is increasing significantly. It is a challenging task since there are highly complex unknown correlat

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Infrared photoconductive detectors working in the far-infrared region and room temperature were fabricated. The detectors were fabricated using three types of carbon nanotubes (CNTs); MWCNTs, COOH-MWCNTs, and short-MWCNTs. The carbon nontubes suspension is deposited by dip coating and drop–casting techniques to prepare thin films of CNTs. These films were deposited on porous silicon (PSi) substrates of n-type Si. The I-V characteristics and the figures of merit of the fabricated detectors were measured at a forward bias voltage of 3 and 5 volts as well as at dark and under illumination by IR radiation from a CO2 laser of 10.6 μm wavelengths and power of 2.2 W. The responsivity and figures of merit of the photoconductive detector

       In this work, a pollution-sensitive Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) technology is designed and implemented for sensing refractive indices and concentrations of polluted  water . The overall construction of the sensor is achieved by splicing short lengths of PCF (ESM-12) solid core on one side with traditional multimode fiber (MMF) and depositing a gold nanofilm of 50nm thickness on the end of the PCF sensor. The PCF- SPR experiment was carried out with various samples of polluted water including(distilled water, draining water, dirty pond water, chemical water, salty  water and oiled water). The location of the resonant wavelength peaks is seen to move to longer wavelengths (red shift)

This research prepared polymer blend contains from epoxy resin (Ep) and polyurethane
)Pu) as a matrix material of percentage (90 %) from epoxy and ) 10 (% polyurethane and
reinforced by PVC fibers and aluminum fibers two dimension knitted mat with fractional
volume(15 %), and study impact strength before and after reinforcing at temperatures of
(20,40,60(
o
CØŒand the results have shown that the reinforcing matrix materials by fibers
increased impact strength values that rise from(3.387kJ/m2) to (151.62kJ/m2) of composite
material (Ep+Pu+PVC(and thus ) Ep+Pu+PVC+Al.F) at last (Ep+Pu+Al.F (. following
composite material so that temperatures increase led to rise impact strength values except the
polymer

The production and analysis of an optimal interference pattern for the optical fiber interferometer of a 193.1THz continuous laser source was simulated by comparing the spectral spectroscopy of the two arms of interferometer to be used as a heterodyne detection in sensing the body range, speed, and direction of movement by delaying the time between the arms.

     The study showed that the fringe pattern can be sensed a range by the free spectral range FSR and the velocity by the fringe separation FS and the direction by the fringe spatial frequency FSF.

Membrane manufacturing system was operated using dry/wet phase inversion process. A sample of hollow fiber membrane was prepared using (17% wt PVC) polyvinyl chloride as membrane material and N, N Dimethylacetamide (DMAC) as solvent in the first run and the second run was made using (DMAC/Acetone) of ratio 3.4 w/w. Scanning electron microscope (SEM) was used to predict the structure and dimensions of hollow fiber membranes prepared. The ultrafiltration experiments were performed using soluble polymeric solute poly ethylene glycol (PEG) of molecular weight (20000 Dalton) 800 ppm solution 25 °C temperature and 1 bar pressure. The experimental results show that pure water permeation increased from 25.7 to 32.2 (L/m2.h.bar) by adding aceton