The aim of the research is to measure the length between the variable the efficiency of the tax examiner with its dimensions represented by (scientific questions, practical process (experience), training and development, impartiality and independence, ethics of the profession) and the approved variable discovering the artificial adaptation of profits, and the degree of arrangement of those dimensions its importance and priority, and the research problem has been identified In a main question that is there any effect of copying the images of the image examiner in discovering the adaptation, the financial statements and reports of the companies (X, Y) and the banks (A, B) were relied on in the interpretation of the results, the facilities of the personal interviews in them, and the data was analyzed by relying on the statistical program ( SPSS V.18) and (AMOS V.24) coefficient coefficient of variation, coefficient coefficient, coefficient coefficient, coefficient, coefficient, and among the most prominent results it reached was showing that there is an innovative coefficient that has a significant effect on the dimensions of the tax examiner’s efficiency collectively or individually in discovering localization This indicates the extent of the great positive impact that achieves great success in discovering the artificial profits.
Iraqi siliceous rocks were chosen to be used as raw materials in this study which is concern with the linear shrinkage and their related parameters. They are porcelinite from Safra area (western desert) and Kaolin Duekla, their powders were mixed in certain percentage, to shape compacts and sintered. The study followed with thermal and chemical treatments, which are calcination and acid washing. The effects on final compact properties such as linear shrinkage were studied. Linear shrinkage was calculated for sintered compacts to study the effects of calcination processes, chemical washing, weight percentage, sintering processes, loading moment were studied on this property where the compacts for groups is insulating materials.
Linear
Zinc oxide nanoparticles sample is prepared by the precipitation method. This method involves using zinc nitrate and urea in aqueous solution, then (AgNO3) Solution with different concentrations is added. The obtained precipitated compound is structurally characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR). The average particle size of nanoparticles is around 28nm in pure, the average particle size reaches 26nm with adding AgNO3 (0.05g in100ml =0.002 M) (0.1g in100ml=0.0058M), AgNO3 (0.2g in 100ml=0.01M) was 25nm. The FTIR result shows the existence of -CO, -CO2, -OH, and -NO2- groups in sample and oxides (ZnO, Ag2O).and used an
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أن الطرق اللامعلمية هي نوع من الطرق الاحصائية الاستدلالية التي يمكن استخدامها للتوصل إلى أستنتاجات لذا كان حرص المؤلف على أصدار هذا الكتاب والذي يعمل على توضيح ( لماذا ؟ ومتى ؟ وكيف ؟ ) تستخدم كل طريقة إحصائية . وبإمكان القاريء سواء أكان أستاذا ً جامعيا ً أو باحثا ً أو طالبا ً في الدراسات العليا ( الماجستير والدكتوراه ) أو طالبا ً في الدراسات الأولية أن يتتبع جميع الخطوات لحساب كل قانون إحصائي وبدءا ً من عملية إدخ
... Show MoreThe presence of dyes in wastewater has become a major issue all over the world. The discharge of dyes in the environment is concerned for both toxicological and esthetical reasons. In this study, the removal of dyes from aqueous solution by electrocoagulation using aluminum electrodes as cathode and anode were investigated with the electrocoagulation cell of 1litter. The study included: the impact of various operating parameters on the dyes removal efficiency like pH, NaCl concentration, distance between electrodes, voltage, initial dyes concentration and type of electrodes. The dye (congo red) concentrations were (50, 100, 150, and 200 ppm), stirring speed was 120 rpm at room temperature. pH used was maintained constant
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Abstract Kidney stones are one of the most common and most painful medical problems known (1). Nurses assess and monitor patients through diagnosis and treatment and teach patients how to avoid recurrence of stones (2). A descriptive study was conducted on 150 patients diagnosed with recurrent kidney stones, who were attending the out patients consultation urology disease clinics at surgical specialties, Al-Kadhimia, Al-Yarmook, and Al-Karama Teaching Hospital and Extracorporeal shock wave lithotripsy (ESWL) departments for the period from the 1st of Feb. 2002 through to the end of May 2004. The aim of
his analysis aims to establish Riemann-Liouville derivation andintegral operators regarding the recently suggested seven-parameter Mittag-Leffler function then investigates the corresponding special cases. In addition,certain notable results associated with those new operators have been dis-cussed
Objective: Assess type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot. Find out the relationship between of type 2 diabetic patients’ knowledge regarding preventive measures of diabetic foot with certain sociodemographic characteristics
Methodology: A descriptive study was carried out from (2nd January 2022 to 26th March 2022). A non –probability (purposive) sample of (60) adult patients who are diagnosed with type2 diabetes mellitus these patients have met the study criteria which was selected from Imam AL-Hussein Medical-City. The study instrument consist of two section: (Demographic Information Sheet, and Foot Care Outcome Expectation
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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