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

The 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

Recently, 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

The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

Purpose/objective:

1 - To explain the financial impact of the activities and areas of human resources management and the adoption of the methodology for estimating costs on the basis of conduct and statement of how to assess costs and benefits of human resource activities.

2 - Measuring  human capital, and its impact on the financial statements.

Design/methodology/approach:

 Concentrated dimensions of the research paper's lack of financial statements prepared by the organizations for information mandated human resource its components of the three (attraction - development

The research aims to assess the claystone exposed in the Nfayil Formation (Middle Miocene) for Portland cement (P.C.) manufacturing based on mineralogy and geochemistry. The importance of the study is to avoid the miming of the agricultural soils that are mining now for the cement industry. Claystones of Nfayil Formation and the limestone of the Euphrates Formation were used to design the raw mixture as clay to limestone (1:3). The chemical composition (%) of the designed mixture was calculated using the Alligation Alternative Method (A.A.M.) as CaO (65.52), MgO (1.05), SiO2 (21.65), Al2O3 (7.43), Fe2O3 (2.62), Na2O3+K2O (1.52) and SO3 (0.26), which are suitable for P.C. The lime saturation factor (LSF = 92.8), silica saturation fac

هذه الدراسة مكرسة للخصائص الوظيفية والدلالية المعقدة للفئات اللفظية من التوتر والنوع في اللغة الروسية سيتم الكشف في هذه الدراسة عن السمات الدلالية والأسلوبية للفرق بين الأفعال المكتملة وغير المكتملة، قد تكون الاختلافات مرتبطة بخصائص المعاني المعجمية للكلمات، وكذلك معاني اللواحق المكونة للكلمات) السوابق واللواحق). يعكس استخدام هذه الفئة النحوية في أنماط مختلفة بوضوح تفاصيل كل منها، لأن درجة واقعية ال