A new furfural Schiff base derivative ligand (L-FSB) named N-(4- Bromo-2-methylphenyl)-1-(furan-2-yl)methanimine, was synthesized from the condensation reaction of furfural (fur) with 4-Bromo-2- methylaniline (bma) in 1:1molar ratio. A new series of VO(II), Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Cd(II) metal complexes are synthesized according to the metal content analysis in an 2:1 ligand:metal ratio. The stereochemistry of the ligand complexes have been deduced by Fourier Transform-Infra Red (FT-IR), Atomic Adsorption (A.A), Ultra violate-Visible Spectra (UV-Vis Spectra), (Mass Spectra, Proton,13Carbon-Nuclear Magnetic Resonance) (1H-NMR,13CNMR) for ligand), magnetic susceptibility at 25oC and conductivity measurements. Fr

Preparation of epoxy/ TiO2 and epoxy/ Al2O3 nanocomposites is studed and investigated in this paper. The nano composites are processed by different nano fillers concentrations (0, 0.01, 0.02 ,0.03, 0.04 ,0.05 ,0.07 and 0.1 wt%). The particles sized of TiO2,Al2O3 are about 20–50 nm.Epoxy resin and nano composites containing different shape nano fillers of (TiO2:Al2O3 composites),are shear mixing with ratio 1 to 1,with different nano hybrid fillers concentrations( 0.025 ,0.0 5 ,0.15 ,0.2, and 0.25 wt%) to Preparation of epoxy/ TiO2- Al2O3 hybrid composites. The mechanical properties of nanocomposites such as bending ,wearing, and fatigue are investigated as mechanical properties.

A phosphorus‐containing Schiff base was prepared from bis{3‐[2‐(4‐amino‐1,5‐dimethyl‐2‐phenylpyrazol‐3‐ylideneamino)ethyl]indol‐1‐ylmethyl}phosphinic acid and paraformaldehyde as a novel antibacterial compound. The reaction of the Schiff base ligand with VO(IV), Ni(II), Co(II), Cu(II), Zn(II), Cd(II), Hg(II), Pd(II) and Pt(IV) led to binuclear species of metal complexes, depending on the ratio of metal ion and ligand. The ligand and its complexes were investigated using elemental analysis, Fourier transform infrared, ¹H NMR, ¹³C NMR, UV–visible and mass spectra, thermogravimetric analysis, conductivity measurements and thermal analysis. The results showed that the S

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.