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 of signatures, numbering 70 images, were used. Image preprocessing steps were performed on them, and their features were extracted using the median filter. After that, the eigenvector and eigenvalue were calculated using the PCA algorithm. Then the backpropagation neural network algorithm was applied for training and testing where the performance reached 6.7995e−07 for 82 epochs and the accuracy was 99.98%.
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The following dilution 5×10-1, 10-1, 10?2 , 10-3 gm/L for the indigenous isolate of Bacillus thuringiensis bacteria and the commercially isalate were used for experiments against the different stages of fig moth of E.cautella which exposed by filter paper method. The results showed that mortality of larval stages was increased with the increasing concentration of the biocide, in addition to increase in the mortality of the larval stages reached to the highest percentage in the third days of treatment of the larval stage in comparison with the first and second days of exposure. The results also showed that the sensitivity of larval stages was increased in first and second instars while reduced in the last instars .The high percentage
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Histologic changes were studied and physiological dosage crude alcoholic extract of seeds of the fenugreek plant for male mice eggs in different concentrations after oral to study testicular tissue and culverts where reason Abstract significant decrease
Abstract An experiment was conducted to study the effect of Glomus mosseae and two concentration (21 and 42%) of super phosphate. They used either to be separated or together with inoculation of G. mosseae on physiological characters of Horeum Vulagera . The results showed that all treatment affected significantly especially super phosphate at the above concentration together with G. mosseae. The effects appeared as an increase in plant height , leaves area , dry weight of total plant , stem dry weight , leaves dry weight , tiller’s number , flag leaf area , dry weight of flag and also increased in CGR , RGR , RGR- NAR , LAI . The yield component increased in number of spikes, number of spikelet’s / spike, number of grain / spike, weigh
... Show Morecharge transfer complex formed by interaction between the p- aminodiphenylamine (PADPA) as electron donor with iodine as electron acceptor in ethanol at 250C as evidenced by color change and absorption. The spectrum obtained from complex PADPA – Iodine shows absorptions bands at 586 nm. All the variables which affected on the stability of complex were studies such as temperature, pH, time and concentration of acceptor. The linearity of the method was observed within a concentration rang (10–165) mg.L-1 and with a correlation coefficient (0.9996), while the molar absorbitivity and sandell sensitivity were (4643.32) L.mol-1.cm-1 and (0.0943) μg.cm-2, respectively. The adsorption of complex PADPA–I2 was studied using adsorbent surfaces
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The aim of this research is to diagnose the impact of competitive dimensions represented by quality, cost, time, flexibility on the efficiency of e-learning, The research adopted the descriptive analytical method by identifying the impact of these dimensions on the efficiency of e-learning, as well as the use of the statistical method for the purpose of eliciting results. The research concluded that there is an impact of the competitive dimensions on the efficiency of e-learning, as it has been proven that the special models for each of the research hypotheses are statistically significant and at a level of significance of 5%, and that each of these dimensions has a positive impact on the dependent variable, and the research recommended
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