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 study examines patterns of exposure of Iraqi university students to selective daily Iraqi newspapers and the motives of this exposure, as well as its associated factors that affect the average exposure. It tries to answer several questions, including those related to the levels of exposure of Iraqi university students to daily Iraqi newspapers and classification of patterns of selective exposure to daily Iraqi newspapers and the most prominent Iraqi daily newspapers that are selectively exposed by Iraqi university students. It also examines the motives of this selective exposure and factors that increase the degree of exposure to the daily Iraqi newspapers, and the most prominent stages in which Iraqi university students find their

Background: Age determination of skeletal remains is apart of many medico-legal as well as anthropological examination. Many anatomical structures have been studied, but the teeth and their measurements seem to be the most reliable method since teeth represent the most durable and resilient part of the skeleton. This study was undertaken for estimating the chronological age among Iraqi adult subjects based on various morphological variables of canine teeth using digital panoramic radiograph. Material and methods: The sample in the current study consisted of 240 Iraqi patients attending to the dental radiological clinic at College of dentistry/ Babylon University taking panoramic radiographs for different diagnostic purposes, the study samp

Objective: To determine the correlation between the second derivative of digital pulse wave and the QT variability index. Method: The cross-sectional study was conducted from October 2021 to May 2022 at the Department of Physiology, College of Medicine, University of Mustansiriyah, Baghdad, Iraq, and comprised healthy women. Samples were raised by simple random technique. Digital pulse waves were captured using a fingertip pulse wave transducer. Lab Chart Pro version 7.2 was used to automatically detect and quantify the amplitude of A, B, C, D and E waves expressed by the second derivative. QT interval of each beat was recorded by electrocardiogram, and was calculated automatically via Lab chart Pro version 7.2 without averaging. D

In this study, a platinum(II) complex ([Pt(H2L)(PPh3)] complex) containing a thiocarbohydrazone as the ligand was tested as an anti-proliferative agent against ovarian adenocarcinoma (Caov-3) and human colorectal adenocarcinoma (HT-29) through MTT assays. Apoptotic markers were tested by the AO/PI double staining assay and DNA fragmentation test. Flow cytometry was conducted to measure cell cycle distribution, while the p53 and caspase-8 pathways were tested via immunofluorescence assay. Results demonstrated that the cytotoxic effect of the Pt(II)- thiocarbohydrazone complexes against Caov-3 and HT-29 cells was highly significant, and this effect triggered the activation of the p53 and caspase-8 pathways. Besides, apoptosis stimulated by th

Abstract

This Research aims for harnessing critical and innovative thinking approaches besides innovative problem solving tools in pursuing continual quality improvement initiatives for the benefit of achieving operations results effectively in water treatment plants in Baghdad Water Authority. Case study has been used in fulfilling this research in the sadr city water treatment plant, which was chosen as a study sample as it facilitates describing and analyzing its current operational situation, collecting and analyzing its own data, in order to get its own desired improvement opportunity be done. Many statistical means and visual thinking promoting methods has been used to fulfill research task.

A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref

Al-Rustamiyah plant is the oldest and biggest sewage treatment plant in Iraq; it locates in the south of Baghdad city. The plant suffers from serious problems associated with overflow and low capacity. The present work aims to upgrade the heart of biological treatment process through suggesting the use of membrane bioreactor; (MBR). In this work, fouling of membrane during sewage treatment has been analyzed experimentally and theoretically by fouling mechanisms. Aeration has been applied in order to control fouling through producing effective diameters of air bubbles close to the membrane walls. Effect of air flow rate on flux decline was investigated. Hermia's models were used to investigate the fouling mechanisms. The results showed th