Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

To maintain a sustained competitive position in the contemporary environment of  knowledge  economy,  organizations  as an open social systems must have an ability to learn and know  how to adapt to rapid changes  in a proper fashion so that organizational objectives will be achieved efficiently and effectively.  A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t

 The research aimed to find the effectiveness of teaching impact of the reflex learning strategy on the fifth class female student achievement of the geography content material). The researcher adopted the null hypotheses (there are no statistically significant differences at (0,05) level between the women score mean of the experimental group student who has been taught by the cement material assigned by the reflex learning strategy, and that of the control group who have been taught by the traditional method on the achievement test. The researcher adopted the post-test experimental design to measure students’ achievement. The population of the present study has been limited to the fifth literary class female stud

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Background: University students in Iraq face rising obesity risk linked to physical inactivity, prolonged sedentary behavior, insufficient sleep, and academic stress. Longitudinal evidence examining the combined influence of these behaviors on weight status in Iraqi universities remains limited. Objective: This study examined six-month longitudinal associations of physical activity, sedentary behavior, sleep duration, and perceived stress with body mass index and percentage body fat among Iraqi university students. Methods: A prospective multi-behavioral study was conducted at six public universities in Iraq. Six hundred undergraduate students aged 18–25 years were followed monthly during one academic semester. Validated questionn

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

News headlines are key elements in spreading news. They are unique texts written in a special language which enables readers understand the overall nature and importance of the topic. However, this special language causes difficulty for readers in understanding the headline. To illuminate this difficulty, it is argued that a pragmatic analysis from a speech act theory perspective is a plausible tool for a headline analysis. The main objective of the study is to pragmatically analyze the most frequently employed types of speech acts in the news headlines covering COVID-19 in Aljazeera English website. To this end, Bach and Harnish's (1979) Taxonomy of Speech Acts has been adopted to analyze the data. Thirty headlines have been collected f

Introduction/Aim. Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in pediatric population and adolescents. Limited data is available on the characteristics of RMS in Iraqi pediatric patients. The aim of the study was to examine the clinical and histological aspects of RMS in Iraqi children, with a focus on their response to treatment, prognosis, and survival. Methods. A retrospective cohort study was conducted at the Oncology Unit of Children's Welfare Teaching Hospital, Medical City, Baghdad, Iraq and included patients who were newly diagnosed with RMS and received treatment during the period between January 1, 2015, and December 31, 2019. The patients were followed up from the time of diagnosis until October 1, 2020.

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

The gastrointestinal system is one of the many organs in the body that have been affected by the new viral illness known as coronavirus disease 2019 (COVID-19). To find out the GIT symptoms are into patients with Covid-19 and how they correspond with the severity of the illness. At the Al-Shifaa facility, 172 patients infected with COVID-19 participated in our study. A clinical examination, laboratory tests (CRP, D.Dimer, and serum ferritin), a chest CT scan, and a medical history were performed on each patient. The severity of the illness and other factors were taken into consideration while evaluating the gastrointestinal symptoms. Data collection from 172 patients, 91 patients infected with COVID-19 infection, 91 patients (52.9%) had GIT