Acrylic polymer/cement nanocomposites in dark and light colors have been developed for coating floors and swimming pools. This work aims to emphasize the effect of cement filling on the mechanical parameters, thermal stability, and wettability of acrylic polymer. The preparation was carried out using the casting method from acrylic polymer coating solution, which was added to cement nanoparticles (65 nm) with weight concentrations of (0, 1, 2, 4, and 8 wt%) to achieve high-quality specifications and good adhesion. Maximum impact strength and Hardness shore A were observed at cement ratios of 2 wt% and 4 wt%, respectively. Changing the filling ratio has a significant effect on the strain of the nanocomposites. The contact angle was i

In this study , Iraqi Bentonite clay was used as a filler for polyvinyl chloride polymer. Bentonite clay was prepared as a powder for some certain particle size ,followed by calcinations process at (300,700,900) OC ,then milled and sieved. The selected sizes were D ~75 µm and D ~150. After that polyvinyl Al-Cohool solution prepared and used as a coated layer covered the Bentonite powder before applied as a filler ,followed by drying , milling and sieving for limited recommend sizes. polyvinyl chloride solutions were prepared and adding of modified Bentonite power at certain quantities were followed .Sheet of these variables on the mechanical and thermal properties of the prepared reinforced particular polyvinyl chloride composite

This work aimed to study the effect of laser surface treatment on the mechanical characteristics and corrosion behaviour of grey cast iron type A159. Many technical applications used conventional surface treatment, but laser surface hardening has recently been used to enhance the surface properties of many alloys. The mechanical characteristics, including microstructure, microhardness, and wear resistance of A159 grey cast iron, were studied, in addition to corrosion behaviour. The experimental laser parameters in this work were 0.9, 1.2, and 1.5 KW power with continuous wave carbon dioxide lasers with scanning speeds of 10 and 12 mm/s were used. The results found that phase-transitional alterations in microstructure were influenced by lase

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class