Introduction: Breast cancer is the most common cancer and the major cause of cancer related deaths among Iraqi women. Due to the relatively late detection of breast cancer, the majority of the patients are still treated by modified radicle mastectomy. Aim: To assess the time lag between diagnosis of breast cancer and mastectomy among Iraqi patients; correlating the findings with other clinicopathological characteristics of the disease. Patients and methods: This retrospective study enrolled 226 Iraqi female patients who were diagnosed with breast cancer. Data were registered on the exact time period between signing the histopathological report and the surgical treatment. Other recorded variables included the age of the patients, their level

Background: Assessment is an important part of the learning cascade in education. Students realize it as an influential motivator to direct and guide their learning. The method of assessment determines the way the students reach high levels of learning. It has been documented that one of factor affecting students’ choice of learning approach is the way how assessment is being performed. Many methods of assessment namely multiple choice questions, essay questions and others are mainly used to assess basic science knowledge in undergraduate education. Objectives: The aim of this study is to compare multiple choice questions (MCQ) and essay questions (EQ) (record the success and failure rate of multiple choice questions (MCQ) and essay quest

Advertisement on smart phone shopping apps are a new way of driving users to satisfy their needs and influence their purchasing decisions, In this way, the research could be aimed to know The role of the relationship between the motivations for audience exposure to shopping apps advertisement and purchasing decisions, In order to achieve the objectives of the research, the researcher adopted the survey method and used the questionnaire and the scale to collect data and information, The researcher chose the "random sample multi stages", The sample size was (475) respondents from Baghdad city center (18 years and above) women and men.

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

     Organizations must interact with the environment around them, so the environment must be suitable for that interaction. These companies are now trying to become Learning Organizations because it try to face that challenges may rise from its environments. The Learning Organization is a concept that is becoming an increasingly widespread philosophy in modern companies, from the largest multinationals to the smallest ventures. What is achieved by this philosophy depends considerably on one's interpretation of it and commitment to it. This study gives a definition that we felt was the true ideology behind the Learning Organization and Group Working. A Learning Organization is one in which people at all levels

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m