In this study, the relationship between the bare soil temperature with respect to its salinity is presented, the bare soil feature is considered only by eliminating all other land features by classifying the site location by using the support vector machine algorithm, in the same time the salinity index that calculated from the spectral response from the satellite bands is calibrated using empirical salinity value calculated from field soil samples. A 2D probability density function is used to analyze the relationship between the temperature rising from the minimum temperature (from the sunrise time) due to the solar radiation duration tell the time of the satellite capturing the scene image and the calibrated salinity index is presented. T

Ferric oxide nanoparticles Fe3O4NPs have been prepared by the coprecipitation method, which were used to functionalize the surface of electrospun nanofibers of polyacrylonitrile to increase their effectiveness in adsorption of Congo red (CR) dye from their aqueous solutions. The effect factors of adsorption were systematically investigated such as adsorbent mass, initial concentration, contact time, temperature, ionic strength and pH. The maximum adsorbed amount of the dye was at 0.003g of adsorbent. The adsorption of dye increased with increasing initial dye concentration and the system reaches to the equilibrium state at 150 min. The adsorbed dye capacity decreases with increasing temperature which indicates to the exothermic nature of ad

This paper describes the synthesis of ?- Fe2O3 nanoparticles by sol-gel route using carboxylic acid(2-hydroxy benzoic acid) as gelatin media and its photo activity for degradation of cibacron red dye . Hematite samples are synthesized at different temperatures: 400, 500, 600, 700, 800 and 900 ?C at 700 ?C the ?-Fe2O3 nanoparticles are formed with particle size 71.93 nm. The nanoparticles are characterized by XRD , SEM, AFM and FTIR . The 0.046 g /l of the catalyst sample shows high photo activity at 3x10-5M dye concentration in acidic medium at pH 3.

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

Nano-crystalline iron oxide nanoparticles (magnetite) was synthesized by open vessel ageing process. The iron chloride solution was prepared by mixing deionized water and iron chloride tetrahydrate. The product was characterized by X-Ray, Surface area and pore volume by Brunauer-Emmet-Teller, Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy(FTIR)  .  The results showed that the XRD in compatibility of the prepared iron oxide (magnetite) with the general  structure of standard iron oxide, and in Fourier Transform Infrared Spectroscopy, it is strong crests in 586 bands, because of  the expansion vibration manner related to the metal oxygen absorption band (Fe–O bonds in the crystals of iron ox

In this paper, Response Surface Method (RSM) is utilized to carry out an investigation of the impact of input parameters: electrode type (E.T.) [Gr, Cu and CuW], pulse duration of current (I_p), pulse duration on time (T_on), and pulse duration off time (T_off) on the surface finish in EDM operation. To approximate and concentrate the suggested second- order regression model is generally accepted for Surface Roughness Ra, a Central Composite Design (CCD) is utilized for evaluating the model constant coefficients of the input parameters on Surface Roughness (Ra). Examinations were performed on AISI D2 tool steel. The important coefficients are gotten by achieving successfully an Analysis of V