After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

The study aimed to identify the reality of the application of cost accounting system in the contracting institutions in Saudi Arabia, and the extent of the reflection of the application of this system on the effectiveness and efficiency of the general performance of these institutions. Where the research community consists of the contracting institutions operating in the Saudi Arabia, and then a suitable random sample was selected from seventy one institutions. The researchers used the historical method to track the previous studies as well as the descriptive approach to conducting the field study. The study data were analyzed by SPSS statistical program.

The results of this study conclude that there is a

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

Detergent is one of the pollutants that poses significant threats to ecological systems. Detergents can also dissolve in wastewater and negatively impact the efficiency of wastewater treatment facilities. They are used for a variety of functions, most notably hygiene, and are an integral aspect of human life. This means that there are a variety of routes by which detergent components can reach the environment. In this Study, twenty-three detergent samples from local markets in Baghdad. The aim of this study is to investigate the concentration of heavy metals Cobalt (Co), Chromium (Cr),Lead (Pb),Zinc (Zn), Iron (Fe) and Cadmium (Cd) in some detergents using Atomic Absorption Spectrophotometer. The results of the concentration of heavy elemen

The study of the distribution of major oxides and heavy metals in some plants collecting and analyzing eighteen plant samples of vegetables including carrot, onion, eggplant, cucumber, and okra obtained from Abu Ghraib land located about 20 km west of Baghdad, Iraq. Eighteen plant samples of vegetables,.Heavy metals can have a severe impact if released into the environment, even in trace quantities. These can enter the food chain from aquatic and agricultural ecosystems and indirectly threaten human health.. Trace elements and oxides of As, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, Se, Th, U, V, and Zn were measured in plant samples using an X-Ray Fluorescence Instrument (XRF). TEs analyses of vegetables were performed in the Iraqi German Lab

The fluorescence emission of Rhodamine 6G (R6G) and Acriflavine dyes in PMMA polymer have been studied by changing the irradiation and exposure time of laser light to know the effect of this parameter. It was found that the fluorescence intensity decreases in the polymer samples doped dyes as the exposure time increases and then reaches stabilization at long times, this behavior called photobleaching, which have been shown in liquid phase less than solid phase. Using 2nd harmonic with wavelength 530 nm laser, the photobleaching effect in the two dye-doped polymers different solvent but same was studied. It was observed that photobleaching of by different solution and by using dip spin coating the photobleaching seem in liquid phase more