Risk factors can be considered unique in construction projects, especially in tendering phase. This research is directed to recognize and evaluate the importance of critical risk factors in the tendering phase related to Iraq’s construction project. As a rule, construction projects are impacted by risk factors throughout the project life cycle; without identifying and allocating these risk factors, the project cannot succeed. In this paper, the open and closed questionnaires are used to categorize the critical risk factors in tendering phase. Research aims to recognize the factors that influence the success of tendering phase, to determine the correct response to the risk’s factors in this research article, (IBM, SPSS, V23) package has

Background: The present study aimed to assess the distribution, prevalence, severity of malocclusion in Baghdad governorate in relation to gender and residency Materials and Methods: A multi-stage stratified sampling technique was used in this investigation to make the sample a representative of target population. The sample consisted of 2700 (1349 males and 1351 females) intermediate school students aged 13 years representing 3% of the total target population. A questionnaire was used to determine the perception of occlusion and orthodontic treatment demand of the students and the assessment procedures for occlusal features by direct intraoral measurement using veriner and an instrument to measure the rotated and displaced teeth. Results a

Braces in straight bridge systems improve the lateral-torsional buckling resistance of the girders by reducing the unbraced length, while in horizontally curved and skew bridges, the braces are primary structural elements for controlling deformations by engaging adjacent girders to act as a system to resist the potentially large forces and torques caused by the curved or skewed geometry of the bridge. The cross-frames are usually designed as torsional braces, which increase the overall strength and stiffness of the individual girders by creating a girder system that translates and rotates as a unit along the bracing lines. However, when they transmit the truck’s live load forces, they can produce fatigue cracks at their connection

Objective: To determine the ability of uVDBP to discern SRNS from steroid-sensitive nephrotic syndrome (SSNS) in Iraqi children. Materials and Methods: This cross-sectional study enrolled children with SRNS (n=31) and SSNS (n=32) from the pediatric nephrology clinic of Babylon Hospital for Maternity and Pediatrics over three months. Patients' characteristics in terms of demographics, clinical data, and urinary investigations were collected. Quantitative analysis of uVDBP levels was undertaken via a commercially available ELISA kit. Results: The median uVDBP values were significantly higher (p-value<0.001) in the SRNS group (median=10.26, IQR=5.91 μg/mL) than in the SSNS group (median=0.953, IQR=4.12 μg/mL). A negative correlati

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci