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This study investigates the digestion of cow dung (CD) for biogas production at laboratory scales. The study was carried out through anaerobic fermentation using cow dung as substrate. The digester was operated at ambient temperatures of 39.5 °C for a period of 10 days. The effect of iron powder in controlling the production of hydrogen sulfide (H2S) has been tested. The optimum concentration of iron powder was 4g/L with the highest biogas production. A Q – swatch Nd:YAG laser has been used to mix and homogenize the components of one of the six digesters and accelerate digestion. At the end of digestion, all digestions effluent was subjected to 5 laser pulses with 250mJ/pules to dispose waste biomass.

Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p

In this study, ceramic purifier (CP) was produced from a mixture of Iraqi raw materials. This ceramic mixture was prepared using Bentonite as a Clay, Porcelanite as a Silica, and Limestone as a flux. The produced ceramic filter was formed by semi-dry compressing method and was fired at 1200 C?. Physical properties of the produced CP were measured. A hydraulic test rig was constructed to study the hydraulic conductivity of the produced CP. The average hydraulic conductivity of the produced CP was 55 times that of commercial types of ceramic filters. The mineral composition of the produced ceramics was found by X-Ray tests. Tests results showed that all of the produced ceramics filters composed mainly of low Cristobalte and Tridoymite in addi

This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (3³) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

PPSU hollow fiber nanofiltration membranes are prepared by applying two concentrations and various extrusion pressures according to the phase inversion method. Cross-sectional area and outer structures were characterized by using scanning electron microscope (SEM) and atomic force microscopy (AFM). In additional to the pore size distribution, either the mean roughness or the mean pore size of the PPSU hollow fiber surfaces was evaluated by AFM. It was found that the morphology of the PPSU fibers had both sponge-like and finger-like structures through different extrusion pressures and PPSU concentrations. The mean pore size and mean roughness for inner and outer surfaces were seen to be decreased with the increase of extrusion pressure at

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima