Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

In the present study, free convection heat and mass transfer of fluid in a square packed bed enclosure is numerically investigated. For the considered geometrical shape, the left vertical wall of enclosure was assumed to be kept at high temperature and concentration while the opposite wall was kept at low temperature and concentration with insulating both the top and bottom walls of enclosure. The Brinkman– Forchheimer extended Darcy model was used to solve the momentum equations, while the energy equations for fluid and solid phases were solved by using the local thermal non-equilibrium (LTNE) model.Computations are performed for a range of the Darcy number from 10-5 to 10-1, the porosity from 0.5 to 0.9, and buoyancy ratio from -15 t

The study included three topics, the definition of the personality of Imam al-Bazazi, his scientific biography, his elders, his writings, his students and his death, selected issues of his weightiness related to purity, and the Imam al-Bazazi is Muhammad ibn Muhammad ibnShihabibn Yusuf, known in al-Kardari al-Hanafi al-Balzazi. The other doctrines, the author relied in his book on the sources of the previous scholars of the Hanafis, and make them the basis in his book, the author did not adopt the definitions of language and terminology, and rarely mention the evidence Shariah adopted by scientists in their opinions, and limited to mention only opinions, In front of the first issue spotlessly water user, and the second issue that sleep l

The study aims to enrich the information of planners, policymakers, and water resources managers for planning and operating dams. This research aims to address the following question: What are the environmental, economic, and social impacts of the construction and operation of dams on the environment and society? The study assumes that good management is the ideal solution to solve the problems of negative effects resulting from the construction and operation of dams. The research relied on the descriptive analytical approach in studying the positive and negative impacts of Haditha Dam and the government's role. A questionnaire was conducted for 30 specialists in urban and regional planning to find out the most important strategies for sust

This research is drawn from a doctoral dissertation, studying the approach of Sheikh Abd al-Qadir al-Muhajir al-Sanandji al-Kurdi (1303 AH) on the issue of proving the existence of God Almighty.
Sheikh Abd al-Qadir al-Sanandji was one of the scholars well versed in mental sciences. He has many books, all of them in the sciences of speech and wisdom, and among his books is the book (Raising the Eyebrow in Explanation of Ithbat al-Wajib), which is still a manuscript that has not been printed.
Through this book, the researcher studied the evidence of Sheikh Abdul Qadir to prove the existence of God Almighty, and compared it with the evidence of philosophers and theologians.
At the beginning, he presented a study on the import

The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana