In this research work, a new type of concrete based on sulfur-melamine modification was introduced, and its various properties were studied. This new type of concrete was prepared based on the sulfur-melamine modification and various ingredients. The new sulfur-melamine modifier was fabricated, and its fabrication was confirmed by IR spectroscopy and TG analysis. The surface morphology resulted from this modifier was studied by SEM and EDS analysis. The components ratios in concrete, chemical and physical characteristics resulted from sulfur-melamine modifier, chemical and corrosion resistance of concrete, stability of concrete against water adsorption, stability of concrete against freezing, physical and mechanical properties and durability, modulus of elasticity, and thermal expansion coefficient of the studied sulfur concrete were investigated. The IR results confirmed the amino functional groups (attached melamine ring) and the formation of polymer sulfur chains. The sulfur-melamine modification thermic mass loss was one step. The mass loss processes of the modifier were endothermic processes. The obtained SEM results revealed that the sulfur-melamine modifier had a more porous structure, without any crystal forms. EDS analysis showed that the nitrogen atoms were accounted for 51.33% of total mass while the carbon was 30.94% of total mass. The stability of sulfur-melamine modifier-based concrete was very high in the various aggressive solutions. The low size of aggregates-based concrete had more density, i.e., 2417 kg\m3. The concrete density was decreased slowly with increase in the size of aggregate. The average deformation of studied concrete was (0.0030-0.0033), confirming that the deformation performance of concrete was better than the traditional concretes. The obtained results also confirmed that value of thermal expansion coefficient for sulfur-melamine modified concrete was 17.2×10-6\˚C.
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
... Show MoreIn this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I
... Show MoreThe Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita
... Show MoreRecently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.
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
... Show MoreAs one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord
... Show MoreBackground: Type 2 diabetes mellitusand chronic periodontitis hold a close relationship that has been the focus of many researches. Currently there is an appreciation to the role of adipose tissue-derived substances "the adipokines" in immune-inflammatory responses; also, there is an interest in using the simple non-invasive saliva in diagnosing and linking oral and general health problems. The current study aims to determine the periodontal health status in the chronic periodontitis patients with and without poorly or well controlled type 2 diabetes mellitus, measure the salivary levels of two adipokines "leptin and resistin", pH and flow rate and then correlate between these clinical periodontal, biochemical and physical parameters in eac
... Show MoreThe prevalence of diabetes is increasing rapidly and is now recognized as a significant global health problem. Diabetes occurs when a person does not produce enough insulin due to an imbalance in insulin production. This can lead to the failure of organs and tissues such as the kidneys, heart, blood vessels, eyes, nerves, and kidneys. As a result, early diagnosis and classification of type 2 diabetes mellitus (T2DM) are critical to aiding physician assessments. Subsequently, the current study aims to determine irisin levels in patients with T2DM and pre-DM as early predictors for disease cases. The current study included 138 subjects divided into three groups based on fasting blood glucose (FBG) and glycosylated hemoglobi
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