The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

Three strain of Bacillus cereus were obtained from soil sours Laboratories of Biology Department/ College of Science/ University of Baghdad. The bacteria secreted extracellular xylanase in liquid cultur the test ability of xylanase production from these isolates was studied semi quantitative and quantitative screening appeared that Bacillus cereus X3 was the highest xylanase producer. The enzyme was partial purification 191 fold from cultur by reached step by 4 U/mg proteins by ammonium sulfat precipitation 80%, Ion exchang DEAE-cellulos chromatography Characterization study of the partial purifation enzyme revealed that the enzyme had a optimum activity pH8 and activity was stable in the pH rang (8-10) for 30min. maximal activity was attai

The study includs,effect of concentration of Lead 0.2 ,0.3 , 0.5, 5 , 10 mg/L and Zinc 0.1,0.5 , 2 , 4 , 8 mg/L lonely or to gether on growth green algae( Scenedesmus quadricauda var . longispina) according to the total qauntity for the cells and the adsorption of the algae to the zn,pb concentration .growth curve and dubbling time growth were calculated with or without there heavy metals . Results shows that there are significant differences (P<0.01) for growth curve and the control. (7.5201 cell /h)and with dubbling times (9.87 cell/h). The heavy metals(Pb, Zn). shows antagonistic effect when both used in media.

Lead selenide PbSe thin films of different thicknesses (300, 500, and 700 nm) were deposited under vacuum using thermal evaporation method on glass substrates. X-ray diffraction measurements showed that increasing of thickness lead to well crystallize the prepared samples, such that the crystallite size increases while the dislocation density decreases with thickness increasing. A.C conductivity, dielectric constants, and loss tangent are studied as function to thickness, frequency (10kHz-10MHz) and temperatures (293K-493K). The conductivity measurements confirm confirmed that hopping is the mechanism responsible for the conduction process. Increasing of thickness decreases the thermal activation energy estimated from Arhinus equation is

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

As a result of the increase in wireless applications, this led to a spectrum problem, which was often a significant restriction. However, a wide bandwidth (more than two-thirds of the available) remains wasted due to inappropriate usage. As a consequence, the quality of the service of the system was impacted. This problem was resolved by using cognitive radio that provides opportunistic sharing or utilization of the spectrum. This paper analyzes the performance of the cognitive radio spectrum sensing algorithm for the energy detector, which implemented by using a MATLAB Mfile version (2018b). The signal to noise ratio SNR vs. Pd probability of detection for OFDM and SNR vs. BER with CP cyclic prefix with energy dete

Laser cleaning of materials’ surfaces implies the removal of deposited pollutants without affecting the material. Nanosecond Nd:YAG pulsed laser, operating at 1064 nm and 532nm, was utilized. Different laser intensities and number of pulses were used on metallic and non-metallic surfaces under O2 and Ar environments to remove metal oxide and crust. Cleaning efficiency was studied by optical microscope. The results indicated the superiority of 1064 nm over the 532 nm wavelength without any detectable damage to materials’ surfaces. Marble cleaned in Oxygen gas environment was better than in Ar gas.