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

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

In this study, sawdust as a cheap method and abundant raw material was utilized to produce active carbon (SDAC). Physiochemical activation was utilized where potassium hydroxide   used as a chemical activating agent and carbon dioxide was used as a physical activating agent. Taguchi method of experimental design was used to find the optimum conditions of SDAC production. The produced SDAC was characterized using SEM to investigate surface morphology and BET to estimate the specific surface area. SDAC was used in aqueous lead ions adsorption. Adsorption process was modeled statistically and represented by an empirical model. The highest specific surface area of SDAC was 688.3 m2/gm. Langmuir and Freundlich isotherms were used to

The main objective of present work is to describe the feasibility of friction stir welding (FSW) for
joining of low carbon steel with dimensions (3 mm X 80 mm X 150 mm). A matrix (3×3) of welding
parameters (welding speed and tool rotational speed) was used to see influence of each parameter on
properties of welded joint .Series of (FSW) experiments were conducted using CNC milling machine
utilizing the wide range of rotational speed and transverse speed of the machine. Effect of welding
parameters on mechanical properties of weld joints were investigated using different mechanical tests
including (tensile and microhardness tests ). Micro structural change during (FSW) process was
studied and different welding zones

In this research, the effect of multi-walled carbon nanotubes (MWCNTs) on the alumina/chromia (Al₂O₃/Cr₂O₃) nanocomposites has been investigated. Al₂O₃/Cr₂O₃-MWCNTs nanocomposites with variable contents of Cr₂O₃ and MWCNTs were fabricated using coprecipitation process and followed by spark plasma sintering. XRD analysis revealed a good crystallinity of sintered nanocomposites samples and there was only one phase presence of Al₂O₃-Cr₂O₃ solid solution. Density, Vickers microhardness, fracture toughness and fracture strength have been measured in the sintered samples. The results show tha

Moisture induced damage in asphaltic pavement might be considered as a serious defect that contributed to growth other distresses such as permanent deformation and fatigue cracking. This paper work aimed through an experimental effort to assess the behaviour of asphaltic mixtures that fabricated by incorporating several dosages of carbon fiber in regard to the resistance potential of harmful effect of moisture in pavement. Laboratory tests were performed on specimens containing fiber with different lengths and contents. These tests are: Marshall Test, the indirect tensile test and the index of retained strength. The optimum asphalt contents were determined based on the Marshall method. The preparation of asphaltic mixtures involved