The purpose of this study is to avoid delays and cost changes that occur in emergency reconstruction projects especially in post disaster circumstances. This study is aimed to identify the factors that affect the real construction period and the real cost of a project against the estimated period of construction and the estimated cost of the project. The case study is related to the construction projects in Iraq. Thirty projects in different areas of construction in Iraq were selected as a sample for this study. Project participants from the projects authorities provided data about the projects through a data collection distributed survey made by the authors. Mathematical data analysis was used to construct a model to predict change in time and cost of the projects before the start of the construction. The artificial neural networks analysis was selected as a mathematical approach. The most important factors identified leading to schedule delays and cost increase were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. The use of the ANN model for such a problem is expected to be an effective method for modeling this complicated phenomenon.
A mathematical method with a new algorithm with the aid of Matlab language is proposed to compute the linear equivalence (or the recursion length) of the pseudo-random key-stream periodic sequences using Fourier transform. The proposed method enables the computation of the linear equivalence to determine the degree of the complexity of any binary or real periodic sequences produced from linear or nonlinear key-stream generators. The procedure can be used with comparatively greater computational ease and efficiency. The results of this algorithm are compared with Berlekamp-Massey (BM) method and good results are obtained where the results of the Fourier transform are more accurate than those of (BM) method for computing the linear equivalenc
... Show MoreThis study involves the investigation of the effect of nitrogen laser with 337.1 nm wavelength on the sensitivity of Staphylococcus aureus bacteria by using local therapeutic due to burns. Thirty six isolate of Staphylococcus aureus bacteria were isolated from 25 patients suffering from sever burns, each isolate of bacteria was irradiated with nitrogen laser at (5, 10, 15 and 30) pulses/second repetition rates for 1, 5, 10, 20 and 30 minutes for each repetition rate. The effects of nitrogen laser on the local therapeutics sensitivity of bacteria were obtained using Kirby Baur method. Changes in the sensitivity of bacteria to local therapeutics (Tetracyclin, Chloramphenicol, Flumizin and Fucidin) occur at high repetition rate(30 pulses/seco
... Show MoreThe research aimed to compare the performance of the commercial and the Islamic banks listed in the Palestinian's Stock Exchange .To achieve the objectives of the study we selected all the commercial and the Islamic banks listed in the Palestinian Stock Exchange to obtain the necessary data for the analysis process during the period of (2009-2013) .the comparison based on the performance indicators ( liquidity rate, profitability rate ,the activity rate and the market rate).
a statistical method was used to analyze the date to find the performance differences between the commercial banks,
... Show More<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
... Show MoreChurning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MoreThis effort is related to describe and assess the performance of the Iraqi cement sample planned for oil well-cementing jobs in Iraq. In this paper, major cementing properties which are thickening time, compressive strength, and free water in addition to the rheological properties and filtration of cement slurry underneath definite circumstances are experimentally tested. The consequences point to that the Iraqi cement after special additives encounter the requests of the API standards and can consequently is used in cementing jobs for oil wells. At this research, there is a comparative investigation established on experimental work on the effectiveness of some additives that considered as waste materials which are silica fume, bauxite,
... Show MoreIn the present study, silver nanoparticles (AgNPs) were prepared using an eco-friendly method synthesized in a single step biosynthetic using leaves aqueous extract of Piper nigrum, Ziziphus spina-christi, and Eucalyptus globulus act as a reducing and capping agents, as a function of volume ratio of aqueous extract(100ppm) to AgNO3 (0.001M), (1: 10, 2: 10, 3: 10). The nanoparticles were characterized using UV-Visible spectra, X-ray diffraction (XRD). The prepared AgNPs showed surface Plasmon resonance centered at 443, 440, and 441 nm for sample prepared using extract Piper nigrum, Ziziphus spina-christi, and Eucalyptus respectively. The XRD pattern showed that the strong intense peaks