Water scarcity is one of the most important problems facing humanity in various fields such as economics, industry, agriculture, and tourism. This may push people to use low-quality water like industrial-wastewater. The application of some chemical compounds to get rid of heavy metals such as cadmium is an environmentally harmful approach. It is well-known that heavy metals as cadmium may induce harmful problems when present in water and invade to soil, plants and food chain of a human being. In this case, man will be forced to use the low quality water in irrigation. Application of natural materials instead of chemicals to remove cadmium from polluted water is an environmental friendly approach. Attention was drawn in this research work to use some natural minerals as zeolite, bentonite and montmorillonite to adsorb cadmium element from polluted water. Various concentrations of cadmium in solutions 10, 30 and 50 ppm were treated with three different ratios of each mineral; 1, 3 and 5% (W/V). The obtained results proved that increasing the ratio of amendments to 5% increased Cd adsorption from solution particularly at 50ppm Cd. Zeolite obtained the highest ratio of adsorption (47.90 ppm), followed by montmorillonite (44.99 ppm) and the lowest was bentonite (38.97 ppm). Therefore, it can be recommended that addition of zeolite is the most favorable material to remove Cd element from polluted water.
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreThe use of biopolymer material Chitosan impregnated granular activated carbon CHGAC as adsorbent in the removal of lead ions pb.2+ from aqueous solution was studied using batch adsorption mode. The prepared CHGAC was characterized by Scanning Electronic Microscopy (SEM) and atomic-absorption pectrophotometer. The adsorption of lead ions onto Chitosan-impregnated granular activated carbon was examined as a function of adsorbent weight, pH and
contact time in Batch system. Langmuir and Freundlich models were employed to analyze the resulting experimental data demonstrated that better fitted by Langmuir isotherm model than Freundlich model, with good correlation coefficient. The maximum adsorption capacity calculated f
Many of the proposed methods introduce the perforated fin with the straight direction to improve the thermal performance of the heat sink. The innovative form of the perforated fin (with inclination angles) was considered. Present rectangular pin fins consist of elliptical perforations with two models and two cases. The signum function is used for modeling the opposite and the mutable approach of the heat transfer area. To find the general solution, the degenerate hypergeometric equation was used as a new derivative method and then solved by Kummer's series. Two validation methods (previous work and Ansys 16.0‐Steady State Thermal) are considered. The strong agreement of the validation results (0.3
Electrocoagulation is an electrochemical method for treatment of different types of wastewater whereby sacrificial anodes corrode to release active coagulant (usually aluminium or iron cations) into solution, while simultaneous evolution of hydrogen at the cathode allows for pollutant removal by flotation or settling. The Taguchi method was applied as an experimental design and to determine the best conditions for chromium (VI) removal from wastewater. Various parameters in a batch stirred tank by iron metal electrodes: pH, initial chromium concentration, current density, distance between electrodes and KCl concentration were investigated, and the results have been analyzed using signal-to-noise (S/N) ratio. It was found that the r
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreAdsorption techniques are widely used to remove organics pollutants from waste water particularly, when using low cost adsorbent available in Iraq. Al-Khriet powder which was found in legs of Typha Domingensis is used as bio sorbent for removing phenolic compounds from aqueous solution. The influence of adsorbent dosage and contact time on removal percentage and adsorb ate amount of phenol and 4- nitro phenol onto Al-Khriet were studied. The highest adsorption capacity was for 4-nitrophenol 91.5% than for phenol 82% with 50 mg/L concentration, 0.5 gm. dosage of adsorbent and pH 6 under a batch condition. The experimental data were tested using different isotherm models. The results show that Freundlich model resulted in the best fit also
... Show MoreThis research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and
... Show MoreFace recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.