The electrical insulation of the manufacture sulfonated phenol-formaldehyde viscous material (product) has been studied with Polyvinyl-acetate (PVA) and toluene diisocyanate (TDI) blend has been prepared by fixing percentage by weight 3:1 and mixed with different percentages by weight of the product sulfonated phenol formaldehyde viscous mass (SPF). The Fourier transform infrared (FTIR) spectroscopy is done on (SPF) resin powder and prepared film of PVA-TDI-SPF viscous mass. The quality factor (Q), dissipation factor (D), parallel resistance (Rp), series resistance (Rs), parallel capacitance (Cp), series capacitance (Cs) and phase shift (?) are measured. The calculated maximum dielectric constant (??) is 3.49x107 at sample (1) wt.1% SPF viscous mass to the weight of (PVA-TDI), the minimum dielectric constant is 1.12x106 at sample (3) wt.3% of SPF viscous mass to PVA-TDI weight. The maximum dielectric loss factor (??) is 3.68x107 at sample (1) and the minimum dielectric loss is 2.04x106 for sample (3). The maximum conductance is 1.06x10-4 S at sample (1) and minimum conductance is 6.64x10-6 at sample (3). The maximum frequency dependent ac. conductivity (?ac) is 2.048 S m-1 for sample (1) and the minimum is 0.113 S m-1 at sample (3). The maximum total conductivity (?t) is 126.2 S m-1 for sample (1) and minimum (?t) is 1.129 S m-1 for sample (3). The maximum independent conductivity (?dc) is 124 S m-1 for sample (1) and minimum value is 1.015 S m-1 for sample (3). The maximum capacitive reactance (Xs) is 0.83 M? at sample (5) wt.5% SPF viscous mass to PVA-TDI weight and the minimum is 0.14 M? for sample (3).
In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.
One technique used to prepare nanoparticles material is Pulsed Laser Ablation in Liquid (PLAL), Silver Oxide nanoparticles (AgO) were prepared by using this technique, where silver target was submerged in ultra-pure water (UPW) at room temperature after that Nd:Yag laser which characteristics by 1064 nm wavelength, Q-switched, and 6ns pulse duration was used to irradiated silver target. This preparation method was used to study the effects of laser irradiation on Nanoparticles synthesized by used varying laser pulse energy 1000 mJ, 500 mJ, and 100 mJ, with 500 pulses each time on the particle size. Nanoparticles are characterized using XRD, SEM, AFM, and UV-Visible spectroscopy. All the structural peaks determined by the XRD
... Show MoreAbstract: The present study aimed to evaluate calcium, potassium, albumin, protein, creatinine, urea, uric acid levels, and the level of total sialic acid in the sera of patients with chronic renal failure who had been infected with Hepatitis C virus and in the sera of patients with chronic renal failure, and compare them with healthy volunteers. A total of 90 subjects with age 25-55 years, were divided into three groups. G1 represents 30 patients with chronic renal failure who had treated by dialysis and infected with chronic Hepatitis C virus (positive group). G2 represents 30 patients with chronic failure who had been treated by dialysis (negative group), while G3 represents 30 healthy volunteers (control group). The results showed
... Show MoreThere is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that
... Show MoreIraqi EFL teachers face problems in teaching “English for Iraq Series” for primary public school pupils. In this paper, the researchers are going to identify the main problems faced by our teachers and try to find solutions to these problems. To achieve the aim of the study, list of questions asked and from teachers’ responses, the researchers have got an idea about the main problems which are related to textbook material, parents, learners, environment and technology. Therefore, the researchers adapted a questionnaire to achieve the purpose of the study with some changes and modifications. This questionnaire with five point scale (strongly agree, agree, undecided, disagree, strongly disagree). To achieve face validity, the
... Show MoreInsurance companies seeking to develop programs to promote and market their services and to increase its customer through the use of modern technical marketing and reduce its dependence on agents and take advantage of work of the banks by alliances with them and including reinforcing get the parties to competitive advantages in the financial market , the insurance services intangible service stops marketed over the insurance awareness and requires exceptional promotional efforts. &nbs
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The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
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