Heavy metals contamination in aquatic ecosystems is considered one of the most important threats of aquatic life. Submerge aquatic plants Ceratophyllum demersum in its non living form used for the removal of trace elements. This article studied the ability of the fine powder of C.demersum for the removal of some heavy metals (HM) like copper, cadmium, lead and chrome from aqueous solution with in variable experimental factors. The study occupy two treatments the first included different hydrogen ions pH within a range of 4, 5,6and 8 with a constant HM concentration (1000 ppm).While the second treatment represented by using variable HM concentrations within a range of (250,500,750and 1000 ppm) with a constant pH=7.In both treatments the amount of dried plant was 1g.According to analysis of variance the data obtained from this study revealed that removal efficiency of lead Pb reached to 99.9% where as the lower removal percentage % was for chrome Cr about 80%. Also the results indicated that C.demersum had high capabilities to remove trace elements, therefore it can be used for refining the waste water.
This study examines experimentally the performance of a horizontal triple concentric tube heat exchanger TCTHE made of copper metal using water as cooling fluid and oil-40 as hot fluid. Hot fluid enters the inner annular tube of the TCTHE in a direction at a temperature of 50, 60 and 70 oC and a flow rate of 20 l/hr. On the other hand, the cooling fluid enters the inner tube and the outer annular tube in the reverse direction (counter current flow) at a temperature of 25 oC and flow rates of 10, 15, 20, 25, 30 and 35 l/hr. The TCTHE is composed of three copper tubes with outer diameters of 34.925 mm, 22.25 mm, and 9.525 mm, and thicknesses of 1.27 mm, 1.143 mm, and 0.762 mm, respectively. TCTHE tube's length was 670
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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In this work Laser wireless video communication system using intensity modualtion direct
detection IM/DD over a 1 km range between transmitter and receiver is experimentally investigated and
demonstrated. Beam expander and beam collimeter were implemented to collimete laser beam at the
transmitter and focus this beam at the receiver respectively. The results show that IM/DD communication
sysatem using laser diode is quite attractive for transmitting video signal. In this work signal to noise
ratio (S/N) higher than 20 dB is achieved in this work.
Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application
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