Contemporary architecture has witnessed a new innovative trend in design characterized by the creation of interesting free-flowing structures that reflect expressiveness of form and design, as well as the uniqueness of structure and approaches of construction. These fascinating structures are often perceived as landmarks that blend harmoniously into their surroundings. In the last two decades, parametric design and advanced computational tools, with prefabrication and construction techniques, enabled architects and engineers to explore new materials and methods to create such impressive structures, breaking the obsolete ways of thinking. Several examples of free-form structures lack obviously to explore architectural potentialities,

The research focuses on determining the role of customer relationship management in improving financial performance by surveying the opinions of a number of employees of a number of Iraqi private banks. The customer has become the focus of attention and the most important factors of success and profitability and competition. Therefore, decisions related to the customer are important decisions that support the process of making, And follow-up of administrative decisions, including financial decisions aimed at improving the financial performance of banks and distinguish them from competitors.    Thus, the techniques used in customer relations management programs to collect, analyze and use data and information have beco

This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

An in-depth experimental study of the matrix effect of antifreeze (ethylene glycol) and water contamination of engine oil through FT-IR spectroscopy. With a comparison of the percent by volume concentration of contaminated fresh 15W-40 engine oil, there appeared to be a noticeable reduction in the O–H stretching signal in the infrared spectrum when ethylene glycol based antifreeze was included as a contaminant. The contaminants of distilled water, a 50/50 mixture of water and commercial ethylene glycol antifreeze, and straight ethylene glycol antifreeze were compared and a signal reduction in the O–H stretch was clearly evident when glycol was present. Doubling the volume of the 50/50 mixture as compared to water alone still res

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att