The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order to provide high-quality random, unpredictable, and non-regenerated keys, the chaotic map has been used in the proposed system. In the experiments, the NIST statistical analysis which includes ten statistical tests has been employed to check the randomness of the generated binary bits key. The obtained random cryptographic keys are successful in the tests of NIST, in addition to a considerable degree of aperiodicity.
In this paper, a new class of non-convex functions called semi strongly (
Water pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale
... Show MoreContents IJPAM: Volume 116, No. 3 (2017)
This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p
... Show MoreFerric oxide nanoparticles Fe3O4NPs have been prepared by the coprecipitation method, which were used to functionalize the surface of electrospun nanofibers of polyacrylonitrile to increase their effectiveness in adsorption of Congo red (CR) dye from their aqueous solutions. The effect factors of adsorption were systematically investigated such as adsorbent mass, initial concentration, contact time, temperature, ionic strength and pH. The maximum adsorbed amount of the dye was at 0.003g of adsorbent. The adsorption of dye increased with increasing initial dye concentration and the system reaches to the equilibrium state at 150 min. The adsorbed dye capacity decreases with increasing temperature which indicates to the exothermic nature of ad
... Show MoreThe azo dye brilliant reactive red K-2BP (λmax = 534 nm) is widely used for coloring textiles because of its low-cost and tolerance fastness properties. Wastewaters treatment that contains the dye by conventional ways is usually inadequate due to its resistance to biological and chemical degradation. During this study, the continuous reactor of an advanced oxidation method supported the use of H2O2/sunlight, H2O2/UV, H2O2/TiO2/sunlight, and H2O2/TiO2/UV for decolorization of brilliant reactive red dye from the effluent. The existence of an optimum pH, H2O2 concentration, TiO2 concentration, and d
... Show MoreIn this study, successive electrocoagulation (EC) and electro-oxidation (EO) processes were used to minimize some of the major pollutants in real wastewater, such as organics (detected by chemical oxygen demand (COD)), and turbidity. The wastewater utilized in the present study was collected from the Midland Refinery Company in Baghdad-Iraq. The performance of the successive batch EC-EO processes was studied by utilizing Graphite and Aluminum (Al) as monopolar anode electrodes and stainless steel (st.st.) as the cathode. The Taguchi experimental design approach was used to attain the best experimental conditions for COD reduction as a major response. Starting from chemical oxygen demand COD of (600 ppm), the effects of current density (C
... Show MoreIn this study, successive electrocoagulation (EC) and electro-oxidation (EO) processes were used to minimize some of the major pollutants in real wastewater, such as organics (detected by chemical oxygen demand (COD)), and turbidity. The wastewater utilized in the present study was collected from the Midland Refinery Company in Baghdad-Iraq. The performance of the successive batch EC-EO processes was studied by utilizing Graphite and Aluminum (Al) as monopolar anode electrodes and stainless steel (st.st.) as the cathode. The Taguchi experimental design approach was used to attain the best experimental conditions for COD reduction as a major response. Starting from chemical oxygen demand COD of (600 ppm), the effects of current densi
... Show MoreThe objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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