Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Objective: The present study aims to assess the stressful life events for patients with substance abuse in Baghdad city.
Methodology: A descriptive study was carried out at (Baghdad teaching hospital and Ibn-Rushed Psychiatric hospital).
Starting from 1
st of December 2012 to 3
rd of July 2013, A non-probability (purposive) sample of 64 patients that
diagnosed with substance abuse, the data were collected through the use of semi-structured interview by
questionnaire, which consists of three parts sociodemographic data, medical information, and Life events scale
consists of 49-items distributed to six domains including, family and social domain, health domain, security, legal and
criminal domain, work and school do

In this work, synthesized N4,N4`-bis(2, 3, 4 nitro benzylidene) biphenyi-4-4`-diamine(B1-B3) , was tested as an inhibitors in controlling the corrosion of carbon steel in NaCl 3.5% solution by using open circuit potential (OCP),at four different temperatures (293, 303, 313 and 323 K). Furthermore, the surface morphology was investigated using the Atomic force microscopy (AFM). The effect of using different Schiff bases and temperature was also investigated. Schiff bases was synthesized and characterized via using. Fourier Transform Infrared Spectroscopy (FT-IR)and Atomic Force Microscope (AFM) characterized . The experimental results shown that Schiff bases can consider as an excellent corrosion inhibitors for carbon steel in NaCl 3

Previous studies on the synthesis and characterization of metal chelates with uracil by elemental analysis, conductivity, IR, UV-Vis, NMR spectroscopy, and thermal analysis were covered in this review article. Reviewing these studies, we found that uracil can be coordinated through the electron pair on the N1, N3, O2, or O4 atoms. If the uracil was a mono-dentate ligand, it will be coordinated by one of the following atoms: N1, N3 or O2. But if the uracil was bi-dentate ligand, it will be coordinated by atoms N1 and O2, N3 and O2 or N3 and O4. However, when uracil forms complexes in the form of polymers, coordination occurs through the following atoms: N1 and N3 or N1 and O4.

The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio

ne,؛Stability constants were determined for complexes of amino acids : L-leuc tryptophane and Aspartic acid with thorium (IV ) and uranyle ( U02++) ions at ؛ serine

Ortho amino hydrazobenzene (L) has been prepared from the reaction of ortho amino phenyl thiol with phenyl hyrazan in mole ratio(1:1). It has been characterized by elemental analysis (C, H, N), IR, UV–Vis. The complexes of the bivalent ions (Co, Ni, Cu, Zn, Pd, Cd, Hg and Pb) and the trivalent (Cr) have been prepared and characterized too. The structural have been established by elemental analysis(C,H,N), IR , UV – Vis spectra , conductivity measurements , atomic absorption and magnetic susceptibility . The complexes showed characteristic behaviour of octahedral geometry around the metal ion and the( N,N) ligand coordinated in bidentate modeexcept with pd showed square planer. ? ,kf , ?max for the complexes were estimated too . ? for Co