The use of deep learning.
Many risks have adverse consequences for construction projects’ objectives such as quality, schedule, and cost. As engineering procurement construction (EPC) contracts gradually become one of the most common types used in implementing major large-scale construction projects, identifying common risk types and analyzing their root causes is important for developing measures to decrease and eliminate future risks in these types of contracts. The information about the main causes of risks was collected
Ticks (Acari: Ixodidae) are ectoparasites that infest livestock in every geographic region of the world and are vectors of several viral, bacterial, and protozoan pathogens to both animals and humans. There is little information is available is about tick presence in Buffalo Bubalus bubalis (Linnaeus, 1758) (Artiodactyla, Bovidae) in Iraq. The current study determined the species of ticks parasitizing Buffalo in some central and southern regions included: Baghdad (Al Fathelia), Karbala (Al-Hussainia), Wasit (Kut and Al-Suwairah), Al-Qadisia (Al- Diwaniyah, Al- Saniya, Al-Mihnawea, and Afak), Thi Qar (Al-Nasiriyah and Al-chibayish), Missan (Amara and Qalaat Salih) and Basrah (Al-Haretha, Al-Madena and Al-Deer). A total of 150 Buffal
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show More— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen
... Show MoreThis paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings an
This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while
... Show MoreThis article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while
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