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.

This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

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

In this research, the performance of a two kind of membrane was examined to recovering the nutrients (protein and lactose) from the whey produced by the soft cheese industry in the General Company for Food Products inAbo-ghraab.Wheyare treated in two stages, the first including press whey into micron filter made of poly vinylidene difluoride (PVDF) standard plate type 800 kilo dalton, The membrane separates the whey to permeate which represent is the main nutrients and to remove the fat and microorganisms.The second stage is to isolate the protein by using ultra filter made of polyethylsulphone(PES)type plate with a measurement of 10,60 kilo dalton and the recovery of lactose in the form of permeate.
The results showed that the percen

  In this study terpolymer resin  ) p-ABBF) was prepared by condensation of (p-amino benzoic acid) and (Biuret) with formaldehyde in (1:1:3) mol ratio using hydrolic acid as a reaction medium at 130±2 ℃ .The synthesized terpolymer resin was characterized by elemental analysis , FT-IR and (1H-NMR) spectroscopy. The intrinsic viscosity was determined. The thermal stability of the terpolymer was analyzed by (TGA and DSC).The morphological feature of the (p-ABBF) terpolymer resin was studied by scanning electron microscopy (SEM).Bach equilibrium method was employed to study analytical efficiency of the terpolymer resin towards certain trivalent and divalent metal ions such as (Cu+2,Ni+2, Co+2,Zn+2,Cd+2 and Cr+3( where thes

     The nuclear shell model was used to investigate the bulk properties of lithium isotopes (6,7,8,9,11Li), i.e., the ground state density distributions and C0 and C2 components of charge form factors. The theoretical treatment was based on supposing that the Harmonic-oscillator (HO) potential governs the core nucleons while the valence nucleon(s) move through Hulthen potential. Such assumptions were applied for both stable and exotic lithium isotopes. The HO size parameters (  and ), the core radii ( ) and the attenuation parameters (  and ) were fixed to recreate the available empirical size radii for lithium isotopes under study.

In this study, chalcones were synthesis by condensing 2-acetylpyridine with aromatic aldehyde derivatives in dilute ethanolic potassium hydroxide solution at room temperature according to Claisen-Schmidt condensation. After that, new heterocyclic derivatives such as Oxazine, Thiazine and Pyrazol were synthesis by reaction between chalcones with urea, thiourea and hydrazine hydrate respectively scheme 1. All these compounds wrer characterization by FTIR, 1H-NMR spectroscopy and elemental analysis.