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

Thirteen isolates were collected from various clinical sources during the periodfrom 22/10/2017 to 22/12/2017. All the isolates were diagnosed based on the microscopic and biochemical propertiesby Vitek-2 Compact system. All isolates formed biofilm 100%, with 30% of isolatesbiofilm produced strongly and 70% on medium. The results of the present study have shown the presence of Curli fimbriae genes in E. cloacae bacteria from cases of urinary tract infections, infected patient with blood bacteremia and inflammation of wounds. Curli fimbriae is considered to be an important factor in the virulence of E.cloacae bacteria, which plays an important role in adhering and combining cells on solid surfaces to form the biofilmand helps in the adhesion

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

Aim of the Study: The paper aims at identifying the extent of the role of strategic leadership represented by its four dimensions (administrative, transformational, political, moral) in fulfilling the requirements of university governance (Context, message and Goal, Management orientation, Independence, Issue, Sharing)

Methodology: A survey is applied to (107) members of the teaching staff at the college of Administration and Economics/ University of Mosul.  To achieve the goals of the study, the researcher makes use of a number of tools such as:  questionnaire, statistical tools and methods (repetitions, perce

In this work, the possibility of utilizing osmosis phenomenon to produce energy as a type of the renewable energy using Thin Film Composite Ultra Low Pressure membrane TFC-ULP was studied. Where by forward osmosis water passes through the membrane toward the concentrated brine solution, this will lead to raise the head of the high brine solution. This developed static head may be used to produce energy. The aim of the present work is to study the static head developed and the flux on the high brine water solution side when using forward and reverse osmosis membranes for an initial concentration range from 35-300 g/l for each type of membrane used at room temperature and pressure conditions, and finally calculating the maximum possible po

The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t

Entropy generation was studied for new type of heat exchanger (shell and double concentric tubes heat exchanger). Parameters of hot oil flow rate, temperature of inlet hot oil and pressure drop were investigated with the concept of entropy generation. The results showed that the value of entropy generation increased with increasing the flow rate of hot oil and when cold water flow rate was doubled from 20 to 40 l/min, these values were larger. On the other hand, entropy generation increased with increasing the hot oil inlet temperature at a certain flow rate of hot oil. Furthermore, at a certain hot oil inlet temperature, the entropy generation increased with the pressure drop at different hot oil inlet flow rates. Final