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
... Show MoreA new approach for baud time (or baud rate) estimation of a random binary signal is presented. This approach utilizes the spectrum of the signal after nonlinear processing in a way that the estimation error can be reduced by simply increasing the number of the processed samples instead of increasing the sampling rate. The spectrum of the new signal is shown to give an accurate estimate about the baud time when there is no apriory information or any restricting preassumptions. The performance of the estimator for random binary square waves perturbed by white Gaussian noise and ISI is evaluated and compared with that of the conventional estimator of the zero crossing detector.
In this study, a new type of circulating three-phase fluidized bed reactor was conducted by adding a spiral path and was named as spiral three-phase fluidized bed reactor (TPFB-S) to investigate the possibility for removing engine oil (virgin and waste form) from synthetic wastewater by using Ricinus communis (RC) leaves natural and activated by KOH. The biosorption process was conducted by changing particle diameter in the range 150–300 and 300–600 µm, liquid flow rate in the range 2.5–4.5 L/min and gas flow rate in range of 0–1 L/min, while other parameters initial oil emulsion concentration, pH, adsorbent concentration, agitation speed and contact time were kept constant at 2000 mg/L, 2,
In this research, deposition of titanium oxide (TiO2) and vanadium oxide (V2O5) thin film in different mixing percentage (0, 25 ,50, 75 and100)% on the substrate of glass .The coating thickness was ( 50 nm ).
In this research contact angle was measured and the effect of weather conditions. Results showed that the value of the contact angle of the prepared films reached its highest value at 50% (TiO2+V2O5) was 160º.
The results showed that the optical transmittance of TiO2 and V2O5 thin film decrease with increasing the deposition angle and decrease with increasing V2O5 pro
... Show MoreIn this work, pure and doped Vanadium Pentoxide (V2O5) thin films with different concentration of TiO2 (0, 0.1, 0.3, 0.5) wt were obtained using Pulse laser deposition technique on amorphous glass substrate with thickness of (250)nm. The morphological, UV-Visible and Fourier Transform Infrared Spectroscopy (FT-IR) were studied. TiO2 doping into V2O5 matrix revealed an interesting morphological change from an array of high density pure V2O5 nanorods (~140 nm) to granular structure in TiO2-doped V2O5 thin film .Transform Infrared Spectro
... Show MoreFurfural is one of the one of pollutants in refinery industrial wastewaters. In this study advanced oxidation process using UV/H2O2 was investigated for furfural degradation in synthetic wastewater. The results from the experimental work showed that the degradation of furfural decreases as its concentration increases, reaching 100% at 50mg/l furfural concentration and increasing the concentration of H2O2 from 250 to 500 mg/l increased furfural removal from 40 to 60%.The degradation of furfural reached 100% after 90 min exposure time using two UV lamps, where it reached 60% using one lamp after 240 min exposure time. The rate of furfural degradation k increased at the pH and initial concentratio
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