In this paper, the ability of using corn leaves as low-cost natural biowaste adsorbent material for the removal of Indigo Carmen (IC) dye was studied. Batch mode system was used to study several parameters such as, contact time (4 days), concentration of dye (10-50) ppm, adsorbent dosage (0.05-0.25) gram, pH (2-12) and temperature (30-60) ^oC. The corn leaf was characterized by Fourier-transform infrared spectroscopy device before and after the adsorption process of the IC dye and scanning electron microscope device was used to find the morphology of the adsorbent material. The experimental data was imputing with several isotherms where it fits with Freundlich (R² = 0.9

This paper presents the ability to use cheap adsorbent (corn leaf) for the removal of Malachite Green (MG) dye from its aqueous solution. A batch mode was used to study several factors, dye concentration (50-150) ppm, adsorbent dosage (0.5-2.5) g/L, contact time (1-4) day, pH (2-10), and temperature (30-60)   The results indicated that the removal efficiency increases with the increase of adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature. An SEM device characterized the adsorbent corn leaves. The adsorption's resulting data were in agreement with Freundlich isotherm according to the regression analysis, and the kinetics data followed pseudo-first-or

The aim of present study is to determine the optimum parameters of friction stir welding process and known the most important parameter along with percentage contribution of each parameter which effect on tensile strength and joint efficiency of FS welded joint of  dissimilar aluminum alloys AA2024-T3 and AA7075-T73 of 3 mm thick plates by applied specific number of experiments using Taguchi method .AA2024 was placed on the advancing side and AA7075 on the retreating side. FSW was achieved under three different rotation speeds (898, 1200 and 1710) rpm, three different welding speeds (20, 45 and 69) mm\min , three different pin profiles (cylindrical, threaded cylindrical and cone) and tool tilt angle 2^◦. Taguchi method w

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured to simulate steady state harmonic load at different operating frequencies. Total of 84 physical models were performed. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were tested at the surface and at 50 mm depth below model surface. Meanwhile the investigated parameters of the soil condition include dry and saturated sand for two relative densities 30% and 80%. The response of the footing was ela

The surface finish of the machining part is the mostly important characteristics of products quality and its indispensable customers’ requirement. Taguchi robust parameters designs for optimizing for surface finish in turning of 7025 AL-Alloy using carbide cutting tool has been utilized in this paper. Three machining variables namely; the machining speeds (1600, 1900, and 2200) rpm, depth of cut (0.25, 0.50, 0.75) mm and the feed rates (0.12, 0.18, 0.24) mm/min utilized in the experiments. The other variables were considered as constants. The mean surface finish was utilized as a measuring of surface quality. The results clarified that increasing the speeds reduce the surface roughness, while it rises with increasing the depths and fee

  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead