In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

Pregnancy- including hypertension(PIH), also known as preeclampsia, is one of the major causes of maternal and fetal death. This study was carried out on 30 pregnant women with preeclampsia and 30 healthy pregnant women as control ranging in age mean ±SD (28.84±3.55) years , BMI (76.80±9.78) Kg/m2 and gestation age(30.82±0.75)week. The aim of this research was studied the plasma Metanephrine level and other biochemical parameters such as Hemoglobin(Hb), serum Protein, S. Albumin, Globulin, Albumin/Globulin ratio (Alb/Glu. ratio), S.Glutamate Pyruvate aminotransferase (GPT), S.Glutamate Oxaloacetate aminotransferase(GOT). The obtained results have been compared with 30 healthy pregnant women as control group. The result showed

Pregnancy- including hypertension(PIH), also known as preeclampsia, is one of the major causes of maternal and fetal death. This study was carried out on 30 pregnant women with preeclampsia and 30 healthy pregnant women as control ranging in age mean ±SD (28.84±3.55) years , BMI (76.80±9.78) Kg/m2 and gestation age(30.82±0.75)week. The aim of this research was studied the plasma Metanephrine level and other biochemical parameters such as Hemoglobin(Hb), serum Protein, S. Albumin, Globulin, Albumin/Globulin ratio (Alb/Glu. ratio), S.Glutamate Pyruvate aminotransferase (GPT), S.Glutamate Oxaloacetate aminotransferase(GOT). The obtained results have been compared with 30 healthy pregnant women as control group. The result showed that ther

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that