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

This research is concerned with qualitatively studying the history of an ancient family, one of the most prominent noble, Alawite families, that assumed the position of the Student Union for the Alawite Supervision in the city of Nishapur in Khorasan during the centries (4-6 H./ 10-12 A.H.). Thus, the research aims to investgate the historical news, and the outstanding Zubarah figures who experience the supereme the religious, historical and scientific position in Khorasan generally and Nishapur particularily. It further aims at arriving at the true meaning of the name Zubarah, and to whom it was called, and the extent of this family’s affiliation to the noble Alawi House, and how they moved to live and settle in the cities of the East

Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

Adhesion (type 1 fimbriae) and host defense avoidance mechanisms (capsule or lipopolysaccharide) have been shown to be prevalent in Escherichia coli isolates associated with urinary tract infections. In this work, 50 uropathogenic Escherichia coli (UPEC) isolated from children with urinary tract infections were genotypically characterized by polymerase chain reaction (PCR) assay. We used two genes; fimH and kpsMTII, both of them previously identified in uropathogenic E.coli (UPEC) isolates. The PCR assay results identified fimH (90.0)% and kpsMTII (72.0)% isolates. In the present study, was also demonstrated that these genes may be included in both or one of them within a single isolate.

The present study aimed to investigate the anatomy, histology, and immunohistochemistry of parathyroid gland in two Iraqi mammals (Weasel, Herpestes javanicus and Long-ear hedgehog, Hemiechinus auritus) as a comparative study. A total of (20) animal for each species were used in the present study. Animals collected were immediately anesthesia and dissected to get the parathyroid gland. Methods of Humason and Bancroft and Stevens were employed for histological techniques. Different stains were used (Hematoxylin- Eosin stain-(H & E), Periodic Acid Schiff stain-(PAS), Azan stain, and Methyl Blue stain-(MB)) for staining the histological sections. Anti-calcitonin, code140778 marker used for immune-histochemical study. Results of the present stu