Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

Baqubah city has grown extremely rapidly. The rate of growth exceeds the growth of services that must grow side by side with the growth of population. There are natural features that affect the growth of Baqubah city such as Dieyala river, Alssariya river, in addition to agricultural areas .All these natural features affect the growth of Baqubah city in the running form being seen . In this research the remote sensing and geographic information system (GIS) techniques are used for monitoring urban expansion and forecasting the probable axes to the growth of the city, and found that the probability of Baqubah growth to east is preferred due to Baqubah growth to the east would never interfere with natural features. Also in this res

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

This study was conducted in the Department of Employment and Loans at the Ministry of Labor and Social Affairs to indicate the importance and impact of both the empowerment and the functional flexibility in evaluating the performance of the employees. To achieve the objectives of the study, the data was collected through a questionnaire form designed for this purpose based on previous studies. Data obtained for a significant evaluation of the relationship between the components of both the empowerment and the functional flexibility with the components of the evaluation and determining the degree of importance of each component of both the empowerment and functional flexibility for the components of the evaluation by the extractio

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

The research aimed to evaluate the financial performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq to know the strengths and weaknesses that affect its performance, as well as to compare its performance in the years between (2017-2019), which are characterized by security stability with its performance in previous years (2014 -2016) which is characterized by security instability, to assess the extent of its ability to achieve growth in performance, by answering the main question, what is the evaluation of the performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq in the light of financial indicators?

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed