Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

     The research aims to analyze the impact of exchange rate fluctuations (EXM and EXN) and inflation (INF) on the gross domestic product (GDP) in Iraq for the period 1988-2020. The research is important by analyzing the magnitude of the macroeconomic and especially GDP effects of these variables, as well as the economic effects of exchange rates on economic activity. The results of the standard analysis using the ARDL model showed a long-term equilibrium relationship, according to the Bound Test methodology, from explanatory (independent) variables to the internal (dependent) variable, while the value of the error correction vector factor was negative and moral at a level less than (1%). The relationship bet

Abstract  

All central air conditioning systems contain piping system with various components, sizes, material, and layouts. If such systems in operating mode, the flow in piping system and its component such as valves can produce severe vibration due to some flow phenomenon’s. In this research, experimental measurements and numerical simulation are used to study the flow-induced vibration in valves. Computational fluid dynamics (CFD) concepts are included with one-way and two-way fluid-structure interaction concepts by using finite element software Package (ANSYS 14.57). Detection analysis is performed on flow characteristics under operation conditions and relations with structural vibration. Most of

In this work, zinc oxide nanoparticles (ZnONPs) and sawdust/epoxy composite (20:80) were mixed using a simple molding method with different ZnONPs concentrations of (0.1, 0.3, 0.5, 0.7, and 1.0 %). The samples of the nanocomposites were characterized by the Scanning Electron Microscopy (SEM) technique to demonstrate the homogeneity of the prepared ZnONPs/nanocomposites. The photocatalytic activity of the samples was examined using the methylene blue (MB) dye as a pollutant solution, through evaluation of the efficiency of the prepared compound in the treatment of organic pollutants under illumination by sunlight. The photocatalytic results showed that after 240 minutes of exposure to sunlight, the sample prepared using (0.5 vol.% of ZnON

The ceramic composite with different proportions of clay and silica was prepared with a grain size of 70 μm and the weight percentage was selected for four groups (clayx silica100-x) were x q15, 25, 30 and 50. In this manuscript, for each pressured sample, a sintering procedure was carried out for 3 hours under static air and at various sintering temperatures (1000, 1100, 1200, 1400)°C. After sintering, the density, porosity, water absorption, compression strength and thermal conductivity were measured. The best results were obtained using a mixture of 15% clay and 85% silica which were sintering at 1400°C for three hours under air.

Polycaprolactone polymer is widely used in medical applications due to its biocompatibility. Electro spinning was used to create poly (ε- caprolactone) (PCL) nanocomposite fiber mats containing hydroxyapatite (HA) at concentrations ranging from 0.05 to 0.4% wt. The chemical properties of the fabricated bio composite fibers were evaluated using FTIR and morphologically using field-emission scanning-electron microscopy (FESEM), Porosity, contact angle, as well as mechanical testing(Young Modulus and Tensile strength) of the nanofibers were also studied. The FTIR results showed that all the bonds appeared for the pure PCL fiber and the PCL/HA nano fibers. The FESEM nano fiber showed that the fiber diameter increased from 54.13 to 155.79 (n

The nonlinear refractive index and the nonlinear absorption coefficient of unmodified and functional poly(methyl methacrylate) PMMA films were studied before and after the addition of the filler by the z-scan technique, using a Q-switched Nd:YAG laser at two wavelengths: 532 nm and 1064 nm, and at three input energies (13, 33 and 53) mJ. Both linear and nonlinear refractive indices and absorption coefficients of polymer films were studied by using UV-VIS spectrophotometer. The results show that the creation of functional PMMA from unmodified PMMA will increase the nonlinear optical properties in the functional PMMA/copper matrix more than in the unmodified PMMA/copper matrix. Hence, the functional PMMA appears promising as a useful third

This research estimates the effect of independent factors like filler  (3%, 6%, 9%, 11% weight fraction), normal load (5N, 10N, 15N), and time sliding (5,7 , 9 minutes) on wear behavior of unsaturated polyester resin reinforced with jute fiber and waste eggshell and, rice husk powder composites by utilizing a statistical approach. The specimens polymeric composite prepared from resin unsaturated polyester filled with (4% weight fraction) jute fiber, and (3%, 6%, 9%, 11% weight fraction) eggshell, and rice husk by utilizing (hand lay-up) molding. Dry sliding wear experiments were carried utilizing a standard (pin on disc test setup) following a well designed empirical schedule that depends on Taguchi’s experimental design L9 (MINIT