AZ Khalaf, M kassim Haidir, LK Jasim, Iraqi Journal of Science, 2012

The paper deals with claims in construction projects in Iraq and studies their types, causes, impacts, resolution methods and then proposes a management system to control the impacts of claims. Two parts have been done to achieve the research objective (theoretical part and practical part). The findings showed that the main types of the claims are extra work claims, different site condition claims, delay claims and the main causes of the claims are variation of the orders, design errors and omission, delay in payments by owner, variation in quantities and scheduling errors. The claims have bad impacts on the cost by increasing (10% to 25%) and also on the duration of the project by increasing from (25% to 50%).The negotiation is the main

Controlling cost in construction projects is an essential issue. This study investigates the most critical problems that cause weakness in cost control in Iraqi construction projects. The quantitative technique was used by conducting a survey directed to professionals who work on construction projects. One hundred and sixty-four questionnaire forms were distributed to private sector companies, government companies, and government institutions, and the responses were subjected to the required statistical analysis. The results indicate that the most influential factors are the weakness in keeping up with the use of modern concepts, methods, and technologies, the delay in receiving the amounts due for work done from the owner, fluctuat

Construction projects have become a changing dramatically in recent decades and that the goal of the beneficiaries of the implementation of structural project is to complete the work with less time and within the cost of the specific and the best possible quality may sometimes happen that highlights the importance of time on the rest of the items at the implementation of projects for various reasons, including the need to use the project as soon as possible possible change rapidly to customer's requests, but the high cost of the project represents the biggest obstacle for entrepreneurs with its effects on the quality and the time workers, and is a measure of those elements in monetary terms is the key to integration between them, so the

Animation is an industry that is expanding more quickly than ever. Every child’s favorite activity is watching cartoons. Therefore, it is essential to be cautious of the kinds of cartoon films children and teenagers tend. Because children and teenagers are the target audience for these films. This study aims at exposing a hidden enactment, namely racism, in a well-known cartoon film, Lion King, which has been selected accurately by the researchers because it shapes a set of ideas about black people and constructs prejudiced beliefs in their minds. This study is to answer the inquiry ‘Is the ideology of racism imposed in Lion King? And how?’ The significance of the present paper lies in highlighting the educational function of

This research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w