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

In 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

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

A study of some biological aspects of the crustacean Isopod procellio scaber was carried out for the period April 2003 to march 2004 . The study consisted reproductive and morphological characteristies such as size , weight and length of the body . The result showed that the highest population density of P. scaber was 1120 individual/m2 in September 2003 and less density 403 ind/m2 in February 2004. The density was generally high in Spring and Autumn, low in Summer and Winter months.An increase of the sexual ratio appear in the females number compared to males number (p < 0.05) during most of year. Present study showed non significant increase in the length and dry weight for females compared to males in most of year months. There wer

Present study was conducted in order to assess Slabiaat water quality by measuring some physical and chemical factors of river water, the study included a choice of three stations along of Slabiaat River in Samawa city, water samples collected a monthly during the period from September 2013 August 2014. The study involved measuring the Air & water temperatures, pH, Electrical conductivity, Total dissolved solids, Dissolved oxygen, Total hardness, calcium hardness, magnesium, turbidity, and some types of bacteria in River water. The study results showed that the values of air & water temperatures have ranged between (20.1-36.6)?C , (10-21.8) in Slabiaat River, respectively . pH values ranged between (6.6-8.7). Electrical conductivity in