Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things, which enables gadgets to connect with one another mostly without human involvement, is made possible by AI. In line with this, The Ad Hoc Routing Function (ARF) AI computation is used for multi-rule simplification, the use of Adaptive Cloud Computing Virtual Machine Asset Allotment Technique (ACC-VMRA) is advised. To confirm its viability, the applied developments of IoT and CC in smart cities is examined and duplicated. The experiment results show that the recommended enhancement calculation is more productive than other currently used methods.
The present study aims at investigating classroom verbal and nonverbal communication at the departments of English language . An observation checklist has been constructed , which is distributed into several domains that include a number of items to investigate classroom communication . Face validity and reliability coefficient have been computed. The checklist has been applied on 86 instructors at the Colleges of Education and Arts, Departments of English Language at the Universities of ThiQar, Basrah ,and Maysan . One sample t- test and Two independent sample t-test formulas have been used. Final results reveal that college instructors use verbal communication inside their classrooms and non- verbal communication has not been employed by
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreThe turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
... Show MoreThe Purpose of this study is mainly to improve the competitive position of products economic units using technique target cost and method reverse engineering and through the application of technique and style on one of the public sector companies (general company for vegetable oils) which are important in the detection of prices accepted in the market for items similar products and processing the problem of high cost which attract managerial and technical leadership to the weakness that need to be improved through the introduction of new innovative solutions which make appropriate change to satisfy the needs of consumers in a cheaper way to affect the decisions of private customer to buy , especially of purchase private economic units to
... Show MorePhotocatalytic materials are being investigated as effective bactericides due to their superior ability to inactivate a broad range of dangerous microbes. In this study, the following two types of bacteria were employed for bactericidal purposes: Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus). The shape, crystal structure, element percentage, and optical properties of Ag9(SiO4)2NO3 were examined after it was successfully synthesized by a standard mixing and grinding processing route. Bactericidal efficiency was recorded at 100% by the following two types of light sources: solar and simulated light, with initial photocatalyst concentration of 2 µg/mL, and 97% and 95% of bactericidal acti
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This research aims to apply the Performance Focused Activity Based Costing System in the offices of scientific and advisory services at the University of Technology for the purpose of measuring the cost of services provided by these offices in order to reduce costs. To test the hypothesis of the research, the research was applied in the consulting offices of the University of Technology through the financial statements for the year ending 12/31/2017 of the Scientific and Consulting Services Office of the University of Technology, because the data of these years were issued and audited by the Federal Office of Financial Supervision.
A number of
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