In the hybrid coolingsolar systems , a solar collectoris used to convertsolar energy intoheat sourcein order to super heat therefrigerant leave thecompressor,andthisprocess helpsin the transformation ofrefrigerant state from gaseous statetothe liquid statein upper two-thirdsof thecondenserinstead of the lower two-thirdssuchas in thetraditional air-conditioning systems and this willreduce theenergyneeded torun the process ofcooling.In this research two hybrid air-conditioning system with an evacuated tube solar collector were used, therefrigerant was R22 and the capacity was 2 tons each.The tilt angle of the evacuated tube solar collector was changed and the solar collector fluid was replaced into oil instead of water.A comparison wasi

The techniques of contemporary Iraqi painting and their reflection on the productions of students of art education is an important subject in the field of painting at the theoretical and practical levels in academic study, whether theoretical or practical. Al-Iraqi is one of the arts with historical roots and a distinguished position among other artistic genres. Painting has received a sufficient level of development through the use of various contemporary techniques to advance it for the better.
The methodological framework included the problem of research and the need for it, and then the importance of research came in shedding light on the techniques of contemporary Iraqi painting, and the impact of these techniques on the producti

The increasing drinking water demand in many countries leads to an increase in the use of desalination plants, which are considered a great solution for water treatment processes. Reverse osmosis (RO) and electro-dialysis (ED) systems are the most popular membrane processes used to desalinate water at high salinity. Both systems work by separating the ionic contaminates and disposing of them as a brine solution, but ED uses electrical current as a driving force while RO uses osmotic pressure. A direct comparison of reverse osmosis and electro-dialysis systems is needed to highlight process development similarities and variances. This work aims to provide an overview of previous studies on reverse osmosis and electro-dial

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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 new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

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

Introduction: Ostrich farming has emerged as a new livestock industry in Iraq, but scientists lack sufficient information on health concerns, including intestinal parasites that cause significant production losses and financial instability over extended periods. Methods: Researchers collected 150 fecal samples from ostriches that dwelled in central and southern Iraq for microscopic examination of intestinal parasite occurrence. Results: The six parasite species included Entamoeba sp., which made up 26.66% of the population, and Cryptosporidium sp. at 11.33%, Ascaridia galli at 10%, Giardia sp. at 4.6%, Raillietina sp. at 2%, and Trichostrongyl. Molecular analysis was performed on a subset of positive samples because Entamoeba sp. is