In their growth stages, cities become an aggregation of different urban contexts as a result of development or investment projects with other goals, which creates urban tension at several levels. Previous studies presented different approaches and methods to address specific aspects of urban stress, and thus contemporary visions and propositions varied, which required a field for research. The research, from a review of the proposals, the research problem emerged in need to study the indicators and trends of balanced urban development that address the tensions between different social, economic and urban contexts". Accordingly, the objective of the research is determined as "Building a comprehensive theoretical framework for indicators of balanced development and their various trends in addressing the manifestations of urban tension". The research hypothesis is that the indicators of balanced development to address urban tension are based on the disparity of forces and the causes and manifestations of tension. The research aims to present this knowledge by adopting the descriptive-analytical method of urban studies to reach the identification of the main themes of balanced urban development and to extract the most important indicators of its achievement. The possibility and formulas of their achievement were measured in the practical study. Three projects were selected that adopted balanced development to address urban tension; the research concluded that the balanced development strategy ensures the activation of the old fabric elements and their interaction with modern features in a manner that ensures the development and preservation of the existing fabric.
Introduction to Medical Physics for Pharmacy Students and Medical Groups - ISBNiraq.org
This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.
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In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .
English teachers in Iraq and other countries around the world up to this time use traditional methods to help students memorize new vocabularies. The sense of words or structure is not to be given in either the native tongue or the target language by definition, but is induced by the way the form is used in the situation. Situational Language Teaching (SLT) has recently become the needed method for improving speaking skills. It indicates the application of learning the language in actual and social exchange expressions so as to let learners do as required in classroom and non-classroom circumstances. This pilot study seeks to answer the following questions: Can SLT improve English speaking skills of target learners? How SLT contribute to th
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The current research aims to identify the role of family upbringing methods in shaping adolescent gender identity disorder, to identify the causes, components, and disorders of the gender identity of adolescents, and to develop practical visions and suggestions to reduce and stop gender identity disorder completely. Due to the sensitivity of the topic, a questionnaire of five open-ended questions was posted on Facebook to collect the needed data, where (20) respondents answered these questions. The researcher took these (20) respondents as the study sample. The results revealed that excessive emancipation within the family, failure to employ family protection laws, and failure to monitor and follow up on
... Show MoreBackground: Gastro oesophageal reflux disease (GERD) is characterized by diverse symptoms. There is an evidence for a genetic component to Gastro oesophageal reflux disease as supported by familial aggregation of this disease. Aim of the study was to investigate whether certain human leucocyte antigen genes HLA-DRB1 are associated with (GERD).Methods: Patients and controls were prospectively recruited from GIT center at Al-Kindy Teaching Hospital (Baghdad-Iraq) between January 2014 and July 2016. Sixty Iraqi Arab Muslim patients with a history of heartburn and dyspepsia were compared with 100 Iraqi Arab Muslims controls. All study patients and control groups underwent upper gastrointestinal endoscopic examinations and their serums were anal
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Abstract
Objectives: To assess patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention, and to find out the relationship between patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention
Methodology: A descriptive design was carried out at Al- Nasiriyah Heart Center in Thi-Qar Governorate for the period between May 19th, 2022 to October 25th, 2022. A non-probability sampling was used among (50) patients after their Percutaneous Coronary Intervention. The study instrument that used to collect data was composed of three parts namely: sociodemographic charac
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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