Variation orders are an on-going phenomenon in construction and industry projects worldwide, particularly in the province of Sulaimani, where the project's damage from cost and schedule overrun because of variation orders. However, the effect on project costs and time overrun of variation order has yet to be identified. This study evaluates the impact of variation orders on the cost and time off in the Sulaimani governorate. Two hundred twenty-eight projects from various construction sectors built between 2007-2012 were adopted to calculate the contract cost and schedule overruns due to variation orders. Data analysis was applied in the study were descriptive statistics. One-way ANOVA was also applied to determine whether the overrun of project cost and schedule significantly varied depending on project type, size, duration, location, and awarded years. The findings indicated that cost overruns are very common due to variation orders. 95.6% of the projects were studied being impacted, and overrun in project cost are also huge, with 16%. Time also overruns more common than cost overruns due to the variation orders. 98.7% of the projects were studied in Sulaimani were affected by time overrun with an average of 46.3% of initial duration observed. Findings also indicated that two out of five parameters measured in the analysis had a significant correlation with project cost overruns. Three out of five considered variables correlated with construction time overruns.
Mutans streptococci (MS) are a group of oral bacteria considered as the main cariogenic organisms. MS consists of several species of genus Streptococcus which are sharing similar phenotypes and genotypes. The aim of this study is to determine the genetic diversity of the core species of clinical strains of Streptococcus mutans, Streptococcus sobrinus and Streptococcus downei by using repitative extragenic palindromic (REP) primer. The DNA of the clinical strains of S. mutans (n=10), S. sobrinus (n=05) and S. downei (n=04) have been employed in the present study, which have been previously isolated from caries active subjects. The DNA of the clinical and reference strains was
... Show MoreTo evaluate and improve the efficiency of photovoltaic solar modules connected with linear pipes for water supply, a three-dimensional numerical simulation is created and simulated via commercial software (Ansys-Fluent). The optimization utilizes the principles of the 1st and 2nd laws of thermodynamics by employing the Response Surface Method (RSM). Various design parameters, including the coolant inlet velocity, tube diameter, panel dimensions, and solar radiation intensity, are systematically varied to investigate their impacts on energetic and exergitic efficiencies and destroyed exergy. The relationship between the design parameters and the system responses is validated through the development of a predictive model. Both single and mult
... Show MoreRoughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are ZH (9.2-13.8) m, Zd (4.3-8.1) m and Zo (0.24-0.48) m.
Spin coating technique used to prepare ZnPc, CdS and ZnPc/CdS blend thin films, these films annealed at 423K for 1h, 2h and 3h. Optical behavior of these films were examined using UV-Vis. and PL. The absorption spectrum of ZnPc shows a decreasing in absorption with the increase of annealing time while CdS spectrum give a clearly absorption peak at~510 nm. Energy gap of ZnPc increases from 1.41 to 1.52 eV by increasing the annealing time. Eg of CdS decrease by increasing annealing time, from 2.3 eV to 2.2 eV. The intensities of the peaks obtained from PL spectra were strongly dependent on annealing time and confirmed the results obtained from UV-Vis. D.C. conductivity measurement showed that all the thin films have two differen
... Show MoreTitanium alloy (Ti-6Al-4V) samples were nitrided in low pressure (1.3, 3 mbar) dc-glow discharge plasmas of nitrogen. The treating time was 5, 10 and 15 hour and the temperatures range of the samples during the nitriding process was close to 800oC. The obtained microstructures of the nitride layers were studied by x-ray diffraction and optical microscopy. The ε –Ti2N, ζ-Ti3N3-x and η-Ti3N2-x.phases were formed and addition to the solid solution of nitrogen in titanium, α (Ti,N). Micro hardness measurements exhibit an increment for the Ti-alloy specimens which nitrided at 800oC for 10 and 15h.Corrosion measurements were obtained for the Ti-6Al-4V alloy in Ringer solution after plasma nitriding. The clear improving in the corrosion r
... Show MoreAs one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller
... Show MoreWhenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas
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