The reuse or recycling of waste materials in different aspects of life is served the objective of sustainability and be beneficial to society. In recent years, a wide variety of waste materials were used in pavement construction. One of these materials is glass that generally produces in large quantities and crushed glass can be considered feasible alternative source of aggregate for asphalt mixture production. This study focused on examining the asphalt mixture properties of wearing course using crushed glass as fine aggregates. Fine crushed glass with various percentages by total weight retained on sieve 2.36 mm, 0.3 mm and 0.075 mm was used in the study. The results indicate that mixes containing crushed glass had lower Marshall stabilities and tensile strengths compared to conventional mixes. Moreover, the moisture damage resistance of glass-asphalt mixture was acceptable and satisfy the specification requirements for percentages of glass replacement up to 30 percent. Consequently, adding 30 percent of glass by weight of three sizes is the optimal value which represents about 15.6 percent by weight of total aggregate with maximum size 2.36 mm. The study has concluded that recycling and reuse of waste glass in asphalt mixture could be possible and yield a result which satisfies the specification of asphalt concrete wearing course mixtures.
Recently The problem of desertification and vegetation cover degradation become an environmental global challenge. This problem could be summarized as as the land cover changes. In this paper, the area of Al- Muthana in the south of Iraq will be consider as one of Semi-arid lands. For this purpose, the Ladsat-8 images can be used with 15 m in spatial resolution. In order to over Achieve the work, many important ground truth data must be collected such as, rain precipitation, temperature distribution over the seasons, the DEM of the region, and the soil texture characteristics. The extracted data from this project are tables, 2-D figures, and GIS maps represent the distributions of vegetation areas, evaporation / precipitation, river levels
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This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.
Polyaniline organic Semiconductor polymer thin films have been prepared by oxidative polymerization at room temperature, this polymer was deposited on glass substrate with thickness 900nm, FTIR spectra was tested , the structural,optical and electrical properties were studied through XRD ,UV-Vis ,IR measurements ,the results was appeared that polymer thin film sensing to NH3 gas.
This study investigated the treatment of dairy wastewater using the electrocoagulation method with iron filings as electrodes. The study dealt with real samples collected from local factory for dairy products in Baghdad. The Response Surface Methodology (RSM) was used to optimize five experimental variables at six levels for each variable, for estimating chemical oxygen demand (COD) removal efficiency. These variables were the distance between electrodes, detention time, dosage of NaCl as electrolyte, initial COD concentration, and current density. RSM was investigated the direct and complex interaction effects between parameters to estimate the optimum values. The respective optimum value was 1 cm for the distance between electrodes, (6
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Leishmaniasis is a widespread parasitic disease that occurs as a result of infection with a unicellular parasite belonging to the genus Leishmania. Diagnosis by conventional methods is inaccurate and is not sensitive to confirm the genus infection. Here, we have investigated a methods for Leishmania genus diagnosis, which includes the technique of polymerase chain reaction to detect the presence of the parasite at in vitro for promastigote cultures using three genus-specific primer pairs to amplify HSP70, ITS, and ITS2. The results showed single band of ~1422, ~1020, and ~550 respectively. This study has proved the ability of these primer pairs to detect Leishmania infection and recommend them to be used for detection of leishmaniasis in
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With the development of information technology and means for information transfer it has become necessary to protect sensitive information. The current research presents a method to protect secret colored images which includes three phases: The first phase calculates hash value using one of hash functions to ensure that no tampering with or updating the contents of the secret image. The second phase is encrypting image and embedding it randomly into appropriate cover image using Random Least Significant Bit (RLSB) technique. Random hiding provides protection of information embedded inside cover image for inability to predict the hiding positions, as well as the difficult of determining the concealment positions through the analysis of im
... Show MoreA reliable differential pulse polarographic (DPP) method has been developed and applied for the determination of ibuprofen IBU in dosage form with dropping mercury electrode (DME) versus Ag/AgCl. The best peak was found at cathodic peak of -1.18 V in phosphate buffer at pH=4 and 0.025M of KNO3 as supporting electrolyte. In order to obtaine the highest sensitivity, instrumental and experimental parameters were examined including the type and concentration of supporting electrolyte, pH of buffer solution, pulse amplitude and voltage step time. Diffusion current showed a direct linear relationship to ibuprofen concentration in the range of (5 – 30) μg. mL-1 (2.43× 10-5
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
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