Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

Abstract In the current contribution, a novel binuclear nickel(II) and zinc(II) complexes were prepared from a hexadentate ligand prepared via condensation of 3,3'-Bipyridine-6,6'-dicarbaldehyde , 2-amino-5-chlorobenzaldehyde and 2-Aminophenol .The symmetric ligand (H2DTPE) and its metal complexes were illustrated utilizing various techniques of physicochemical containing magnetic moment, analytical analysis and spectroscopy of mass, IR, 13C and 1H NMR, TGA and UV-Vis. The particles of MO Nanoscale were created from the labeled complex applying the ways of pyrolysis and utilizing methods of XRD, FT-IR, and FE-SEM, that specified close compatibility with the typical pattern for nanoparticles of NiO, ZnO and appeared the reasonable size in

A novel planar type antenna printed on a high permittivity Rogers’ substrate is proposed for early stage microwave breast cancer detection. The design is based on a p-shaped wide-slot structure with microstrip feeding circuit to eliminate losses of transmission. The design parameters are optimized resulting in a good reflection coefficient at −10 dB from 4.5 to 10.9 GHz. Imaging result using inhomogeneous breast phantom indicates that the proposed antenna is capable of detecting a 5 mm size cancerous tumor embedded inside the fibroglandular region with dielectric contrast between the target and the surrounding materials ranging from 1.7 : 1 to 3.6 : 1.

A total of 150 deep eutectic solvents (DESs) with varying salt, hydrogen bond donor, and molar ratios were studied to develop a screening tool for separating toluene-heptane mixtures. The activity coefficient at infinite dilution (γ∞) of each DES was predicted using COSMO-RS, and selectivity (S∞), capacity (C∞), and performance index (PI) were calculated. Key DES properties, including density, viscosity, melting/freezing point, surface tension, and conductivity, were compiled from the literature to create a DES property library. A comprehensive screening tool with four evaluation criteria was developed, which identified ethyl triphenylphosphonium bromide:ZnCl2 (1:4) as the optimal solvent for toluene-heptane separation. Tetrabutyl- b

This paper presents a new Azo dye that was prepared from the reaction of the Benzene-1,2-diamine and 1-(2,4,6-Trihydroxy-phenyl)-ethanone, Azo dye was used to prepare a new series of complexes with general formula: [Co2(H4L) Cl2(H2O)4] and [M2(H4L)Cl4(H2O)2] (M= Cr+3, Fe+3,Rh+3 and Ru+3). The prepared materials were different measurements including to infrared, ultraviolet-visible, and mass spectrometry, as well as thermo gravimetric analysis, differential calorimetry, and elemental analysis. Conductivity, magnetic susceptibility, metal content, and chlorine content of the complexes were also assessed. The complexes prepared from the dye were used to determine their ability to inhibit free radicals by measuring their antioxidant capacity us

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

KE Sharquie, HR Al-Hamamy, AA Noaimi, KA Ali, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3