This study examines the causes of time delays and cost overruns in a selection of thirty post-disaster reconstruction projects in Iraq. Although delay factors have been studied in many countries and contexts, little data exists from countries under the conditions characterizing Iraq during the last 10-15 years. A case study approach was used, with thirty construction projects of different types and sizes selected from the Baghdad region. Project data was gathered from a survey which was used to build statistical relationships between time and cost delay ratios and delay factors in post disaster projects. The most important delay factors identified were contractor failure, redesigning of designs/plans and change orders, security is

Background: Parenteral nutrition (PN) is a life‑saving intervention for neonates who are unable to meet their nutritional requirements through enteral feeding. Despite its essential role, PN is frequently associated with metabolic, electrolyte, and hepatobiliary complications. Objective: To evaluate the frequency and pattern of metabolic, electrolyte, and hepatobiliary complications associated with PN administration in neonates. Methods: A prospective case-series study was conducted in two tertiary neonatal intensive care units (NICUs) in Baghdad, Iraq. Term and preterm neonates who received PN for at least five days were included. PN‑related metabolic, electrolyte, hepatobiliary, and hematological complications were recorded an

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

<p>Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heur

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The physicochemical behaviour of dodecyltrimethylammonium bromide (DTAB) in water and ethanol-water mixture in the presence and absence of ZnSO₄ were studied by measuring the conductivity at 298.15 K. The pre-micellar (S₁) and post-micellar slopes (S₂) were obtained and calculated the degree of dissociation (α) and the critical micelle concentration (cmc). With an increase in ethanol content, the cmc and α of DTAB increased whereas, in the presence of ZnSO₄, the cmc and α decreased. By using cmc and α, thermodynamic properties as the standard free energy of micellization ( ) were evaluated. With an increase in ethanol content, the negative values of  are decreased indicating less spont

Sea level rise (SLR) due to climate change is affecting the coastline, causing shoreline changes, the degradation of mangrove forests, and the destruction of coastal resources. This is the cause of a huge amount of mangrove degradation in many parts of the Ganges–Brahmaputra–Meghna delta. A total of 90% of people have been forced to migrate from the island due to extreme weather conditions. In this study, remote sensing (RS) and geographic information system (GIS) techniques were used for LULC change and shoreline shift analyses of Ghoramara Island. LULC classification was carried out using thirty years of Landsat datasets with intervals of ten years (1990 and 2000) and intervals of five years (2005, 2010, 2015, and 2020). The classific