The research aims to delve into the nature of international financial reporting standards and the unified accounting system adopted in the Iraqi environment and financial ratios in the theoretical side. In the practical aspect, the results of some financial ratios of Basrah Gas Company were compared with the adoption of the financial statements prepared on the basis of the consolidated accounting system with the prepared financial statements Based on the International Financial Reporting Standards (IFRS). The research has reached a number of conclusions, including a difference in the accounting rules and practices between IFRS and the consolidated accounting system in force in Iraq. The adoption of IFRS has led to a decrease in profitabi

In this study, mesoporous silica (MPS) is made using the sol-gel method from a cheap source (Na2SiO3) using the surfactant hydroxycetyl hydroxyethyl dimonium chloride as a template. The task is the adsorption-based removal of the medication metoprolol (MP) at concentrations between 10 and 50 ppm. Variables such as: contact time, dose of adsorbent, starting concentration of adsorbate, and adsorption temperature were studied which show the equilibrium time and adsorbent dose are 40 min and 0.05 g respectively. The Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich isotherm models were fitted to the data obtained from the experiments. Comparing the outcomes showed that, of the four investigated isotherm models, the Freundlich equation m

This study synthesized nanocomposite photocatalyst materials from a mixture of Cu₂O nanoparticles, ZnO nanoparticles, and graphene oxide (GO) through coprecipitation and hydrothermal methods. This study aims to determine the optimum composition of Cu₂O/ZnO/GO nanocomposites in degrading methylene blue. The nanocomposite was synthesized in two steps:  1  the synthesis of Cu₂O and ZnO nanoparticles through the coprecipitation method and the preparation of GO through the modified Hummer method.  2  The preparation of Cu₂O and ZnO nanoparticles mixtures with GO through the hydrothermal method to form Cu₂O/ZnO/GO nanocomposites. The adsorption-photocatalysis process of methylene blue

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

A study of taxonomic quality of soil algae was conducted with some environmental variables in three sites of local gardens (Kadhimiya, Adhamiya and Dora) within the governorate of Baghdad for the period from October 2016 to March 2017. The study identified 28 species belonging to 16 species in which the predominance of blue green algae (18 species) Followed by Bacillarophyta algae (7 species) and three types of Chlorophyta. The study showed an increase in species of Oscillatoria. The results showed no significant differences between sites in temperature, pH and relative humidity, while there were clear differences between sites for salinity and nutrient The study showed a difference of irrigation water quality and use of different fertilize

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 included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in t

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol