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

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

The study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Objectives: to evaluate patient knowledge with hemodialysis and to determine the effectiveness of Self-regulation Fluid Program on Patients with hemodialysis self-efficacy for fluid adherence in Al-Diwaniyah Teaching Hospital.

Methodology: A quasi-experimental design (two group design: pre-test and post-test) was used. This study was conducted in Al-Diwaniya Teaching Hospital for the period from (15^th of October 2018 to 20^th of May 2019) on a non-probability (purposive) sample consisting of (60 patients) treatment in hemodialysis units. A questionnaire was built as a data collection tool and consisted of four parts:

First part: Demographic characteristics of the pati

Objective(s): 1- Assess the effectiveness of health educational program on nurses' knowledge toward Hemodialysis at Pediatric Teaching Hospitals.

 2-To find out the relationship between nurses' knowledge about hemodialysis and their demographic Characteristics.

Methods: The study was designed in a pre-experimental pattern for the nurses' working in the Child Welfare Teaching Hospital and the Child's Central Teaching Hospital, and a targeted sample consisting of (30) nurses was selected. It is tested in three periods of pre-test, the first post-test, and the second post-test. Participants were tested before implementing the tutorial (tutorial lectures

The research aimed to achieve many objectives represented in two variables, which are the impacted factors and the aggregate planning alternatives of workforce in Educational Al- yarmouk Hospital , This research started from a problem focused on finding solutions to the demand’s  fluctuation  or the energy limitation while the study importance is emerged from diagnosis the suitable strategy and adopt the suitable alternatives due to their importance in meeting the demand for the health service submitted by the hospital .This study  based on choosing assumptions of connection relationship and the impact among the mentioned variables in the(surgery and internal diseases) departments. The research is dependent on ch