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Developing models to predicting the effect of crises on construction projects using MLR technique
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Total Dissolved Salt Prediction Using Neurocomputing Models: Case Study of Gypsum Soil Within Iraq Region
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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models
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Abstract<p>There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn</p> ... Show More
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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Engineering
Predicting Crop Coefficient Values of Cucumber (Cucumis sativus) inside Greenhouse
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The objective of the study was to predict crop coefficient (K) values for cucumber inside the greenhouse during the growing season 2014, using watermarks gypsum blocks and atmometer c apparatus during the growing stages and to compare the predicted values of the crop coefficient with different methods and approaches. The study was conducted in the greenhouses field within Al-Mahawil Township, 70 km south of Baghdad, Iraq. The watermarks soil water sensors and atmometer apparatus were used to measure crop evapotranspiration and reference evapotranspiration on daily basis, respectively. The comparison and the statistical analysis between the calculated K in this study and values obtained from greenhouse gave a good agreement. The root mean

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Publication Date
Wed Mar 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Design and implementation monitoring robotic system based on you only look once model using deep learning technique
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<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Effect of Using Extra Fins on the Pin Fin Classic Geometry for Enhancement Heat Sink Performance using EGM Method
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In the present study, the effect of new cross-section fin geometries on overall thermal/fluid performance had been investigated. The cross-section included the base original geometry of (triangular, square, circular, and elliptical pin fins) by adding exterior extra fins along the sides of the origin fins. The present extra fins include rectangular extra fin of 2 mm (height) and 4 mm (width) and triangular extra fin of 2 mm (base) 4 mm (height). The use of entropy generation minimization method (EGM) allows the combined effect of thermal resistance and pressure drop to be assessed through the simultaneous interaction with the heat sink. A general dimensionless expression for the entropy generation rate is obtained by con

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Publication Date
Thu Apr 20 2017
Journal Name
International Journal Of Science And Research (ijsr)
Effect of Different Sealer Systems on the Resistance to Vertical-Root-Fracture of Endodontically Treated Tooth
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Abstract: An unfavorable complication of root canal is vertical root fracture. The aim of present study is to evaluate the vertical root fracture of treated teeth filled with gutta percha and Resilon obturating material using different sealers. Forty mandibular premolars used in the study. Canals randomly divided into four groups (n=10). Group-A eugenol-based (Endofill) sealer with gutta percha; GroupB epoxy-amine (AH Plus) sealer with gutta percha; Group-C resin-based (Real Seal) sealer with Resilon; or Group-D epoxide-based (Perma Evolution) sealer with gutta percha. Roots mounted vertically in cold cure acrylic blocks and subjected to vertical loading with a crosshead speed of 1mm ̸min. The point at which fracture of the roots occurred

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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of feeding pattern on the stage of primary dentition eruption in relation to growth parameters
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Background: Feeding is a complicated process that involves the coordination of cardiovascular, respiratory, gastrointestinal (GI), and oropharyngeal mechanisms, with support from the musculoskeletal and craniofacial systems. The practice of feeding could be correlated with eruption stage and nutritional status in infants. Aim of the study: This study aimed to assess the relation of feeding patterns to a selected oral variable (stage of the eruption of primary teeth) and growth parameters among clinically healthy infants. Subjects and Methods: A cross-sectional comparative study on a sample of (300) infants aged between 6 and 18 months was performed in Karbala City, Iraq. The feeding pattern was investigated using an information sheet ans

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Publication Date
Fri Mar 20 2020
Journal Name
Fibers
Influence of Cooling Methods on the Behavior of Reactive Powder Concrete Exposed to Fire Flame Effect
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The construction of highly safe and durable buildings that can bear accident damage risks including fire, earthquake, impact, and more, can be considered to be the most important goal in civil engineering technology. An experimental investigation was prepared to study the influence of adding various percentages 0%, 1.0%, and 1.5% of micro steel fiber volume fraction (Vf) to reactive powder concrete (RPC)—whose properties are compressive strength, splitting tensile strength, flexural strength, and absorbed energy—after the exposure to fire flame of various burning temperatures 300, 400, and 500 °C using gradual-, foam-, and sudden-cooling methods. The outcomes of this research proved that the maximum reduction in mechanical prop

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