The primary objective of this study was to identify the obstacles and problems encountered in the work of sports clubs according to the reality of the application of administrative automation. The present study was conducted in the sports club headquarters of Baghdad within the timeframe of October 2021 to December 2021. In the present study, a descriptive approach was used by the researchers in an analytical style according to the nature of the problem to be studied. The research community of the current study was composed of 100 sports clubs in the governorate of Baghdad. A total of 80 questionnaires were filled by the sample participants, who represented a percentage of 80% of the research community. After processing the results statistically using the SPSS software, the researchers concluded that sports clubs encounter a lot of difficulties regarding delay in implementing automation procedures in their administrative work, due to lack of financial allocations and lack of awareness among club workers regarding automation techniques.
Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
... Show MoreBackground: Asymmetry assessment is an important component of orthodontic diagnosis and treatment planning. Several studies attempted to find the relationship between craniometric asymmetry and skeletal jaws relationship and many authors found some extent of asymmetry in individuals with normal jaws relationship. The use of Computed tomography (CT) allows for the assessment of asymmetry on a dimensionally accurate volumetric image, aim of the study is to determine if there are differences in craniometric asymmetry between patient with skeletal class I and patients with skeletal class II relationship using Helical CT scan. Materials and Methods: Ninety individuals with clinically symmetrical faces were imaged with Helical CT scan, and aging
... Show MoreAutorías: Muhammad Hamza Shihab, Nuha Mohsin Dhahi. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2022. Artículo de Revista en Dialnet.
The research includes the synthesis and identification of the mixed ligands complexes of M(II) Ions in general composition [M(Lyn)2(phen)] Where L- lysine (C6H14N2O2) commonly abbreviated (LynH) as a primary ligand and 1,10-phenanthroline(C12H8N2) commonly abbreviated as "phen," as a secondary ligand . The ligands and the metal chlorides were brought in to reaction at room temperature in ethanol as solvent. The reaction required the following molar ratio [(1:1:2) (metal): phen:2 Lyn -] with M(II) ions, were M = Mn(II),Cu(II), Ni(II), Co(II), Fe(II) and Cd(II). Our research also includes studying the bio–activity of the some complexes prepared against pathogenic bacteria Escherichia coli(-),Staphylococcus(-) , Pseudomonas (-), Bacillus (-)
... Show MoreNew Schiff base ligand 2-((4-amino-5-(3, 4, 5-trimethoxybenzyl) pyrimidin- 2-ylimino) (phenyl)methyl)benzoic acid] = [HL] was synthesized using microwave irradiation trimethoprim and 2-benzoyl benzoic acid. Mixed ligand complexes of Mn((ІІ), Co(ІІ), Ni(ІІ), Cu(ІІ), Zn(ІІ) and Cd(ІІ) are reacted in ethanol with Schiff base ligand [HL] and 8-hydroxyquinoline [HQ] then reacted with metal salts in ethanol as a solvent in (1:1:1) ratio. The ligand [HL] is characterized by FTIR, UV-Vis, melting point, elemental microanalysis (C.H.N), 1H-NMR, 13C-NMR, and mass spectra. The mixed ligand complexes are characterized by infrared spectra, electronic spectra, (C.H.N), melting point, atomic absorption, molar conductance and magnetic moment me
... Show MoreThe Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and
... Show MoreIn this study, Titanium Dioxide Nanoparticles were synthesized by an easy and eco-friendly technique (green synthesis) using green tea leaves (Camillia sinensis), Nanoparticles were analyzed using structural and optical analysis, the X-ray pattern showed that Titanium Dioxide NPs had a tetragonal structure with (Face Centered Tetragonal) FCT crystal structure, the UV-visible recorded an absorbance peak near 350 nm and calculated energy band gap was 3.5 eV, all measurements were proved the purity and Nano size of prepared Nanoparticles. Biochemical parameters evaluation also mentioned in this research, these analyzes showed that Titanium Dioxide nanoparticles in particular dose (50 mg/kg) have the ability to reduce blood glucose
... Show MoreThis study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K
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