The information required for construction quantities surveying is not only generated by various participants in different construction phases but also stored in different forms including graphics, text, tables, or various combinations of the three. To report a bill of quantities (BOQ), the project manager has to continuously excerpt information from various resources and record it on papers. Without adequate staff and time, this repetitive and tedious process is difficult for the project manager to handle properly and thus reduces the effectiveness and the accuracy of the quantities surveying process which creates problems during the design, tender, and construction supervision of construction projects for designers and contractors practicing because receipts are based upon actual quantities, such variations have an obvious impact on the contractor’s cash flow, once the actual quantities frequently vary from the estimated quantities listed in the BOQ. Hence, automation quantity surveying system has been developed by using GIS to extract the
data required for the quantity of different components of any construction project from AutoCAD drawings (spatial data), to report a BOQ after querying, manipulation, and analyzing these data. The system has been implemented on the construction project of Al khawarizmy College at Baghdad University in Baghdad. The main results of using this system are automatic generation a bill of quantity (BOQ) directly from design drawing, with overcome to design changing, accurate, fast, and effective method for estimating the quantities, fewer errors in cost estimating, and better documentation for continuously reusing information in all construction phases. The accuracy of GIS quantities had been proved by comparing these quantities with the quantities of site surveying. Then determining the accuracy percentage (A%) of GIS quantities which equals (98.85%), and the regression line that equals 0.999. These values mean; there are big correlation between the estimated quantities by GIS and the quantities of site surveying.
Background and Objectives: Wound healing is a complex process with overlapping phases haemostasis, inflammation, proliferation and maturation/matrix remodeling. Each phase of wound healing requires different management strategies, and inappropriate treatment can delay wound healing. The aim of the present study was to evaluate the efficacy of topical application of calmodulin as a significant augmentation of the granulation tissue production process of wound healing and to express of genes CaMKK2, MaP2K6 and CXCR4 at site of wound defect, that have versatile effects on the body and they belong to Ca/camodulin related genes. Material and Methods: In this study thirty albino male rats, weighting (300-400) gram, aged (6-8) months, wil
... Show MoreThis study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin
In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)
Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
... Show MoreE-commerce is the most important result of information technology in this day and age, has resulted in the use of commercial transactions to changes in economic, social, and psychological, and produced a new type of shopping, jobs, and create new job opportunities, and changed the traditional work environment. The challenge currently facing economic units is how to transfer this technology and its integration within the community, especially after the massive developments that have occurred in the areas of commercial and congested markets units, the economic and the products and services the many and varied and intensified competition among these units to achieve a profit, leading to the emergence of e-commerce as on
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