background: osteoporosis is a metabolic bone disease that affects women more than men, it is characterized by generalizes reduction of bone mineral density (BMD) leaving a fragile weak bone that is liable to fracture, gonial angle index (GAI) is one of the radio-morphometric indices, it has been controversial whether it is related to bone mineral density or ageing or none of them. The aim of study is to evaluate the role of cone beam computed tomography (CBCT) as a screening tool for diagnosis of osteoporosis and age effect in females using gonial angle index. Material and method: 60 females were divided into 3 groups according to age and (BMD) status into: Group1 (non-osteoporosis 20-30 years), Group2 (non-osteoporosis 50years and above),

    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,

The aerodynamic characteristics of general three-dimensional rectangular wings are considered using non-linear interaction between two-dimensional viscous-inviscid panel method and vortex ring method. The potential flow of a two-dimensional airfoil by the pioneering Hess & Smith method was used with viscous laminar, transition and turbulent boundary layer to solve flow about complex configuration of airfoils including stalling effect. Viterna method was used to extend the aerodynamic characteristics of the specified airfoil to high angles of attacks. A modified vortex ring method was used to find the circulation values along span wise direction of the wing and then interacted with sectional circulation obtained by Kutta-Joukowsky the

     The research aims to monitor environmental changes and study the state of desertification in the northeastern part of the Al-Najaf province, Iraq. The study area suffers from desertification and drought phenomena. Remote sensing systems "RS" and geographic information systems "GIS" are essential for monitoring environmental changes because they provide Earth observation satellites that contribute to detecting environmental changes. Two Sentinel 2 images were acquired on December 26, 2015, and November 29, 2021. The images were combined and used for indices calculations. Normalized vegetation difference index "NDVI,” Normalized difference index "NDWI," soil exposure index "BSI," and Normalized difference index "NDBI." The resul

In this study, the Earth's surface was studied in Razzaza Lake for 25 years, using remote sensing methods. Images of the satellites Landsat 5 (TM) and 8 (OLI) were used to study and determine the components of the land cover. The study covered the years 1995-2021 with an interval of 5 years, as this region is uninhabited, so the change in the land cover is slow. The land cover was divided into three main classes and seven subclasses and classified using the maximum likelihood classifier with the help of training sets collected to represent the classes that made up the land cover. The changes detected in the land cover were studied by considering 1995 as a reference year. It was found that there was a significant reduction in the water mass

In this study, the Earth's surface was studied in  Razzaza Lake for 25 years, using remote sensing methods. Images of the satellites Landsat 5 (TM) and 8 (OLI) were used to study and determine the components of the land cover. The study covered the years 1995-2021 with an interval of 5 years, as this region is uninhabited, so the change in the land cover is slow. The land cover was divided into three main classes and seven subclasses and classified using the maximum likelihood classifier with the help of training sets collected to represent the classes that made up the land cover. The changes detected in the land cover were studied by considering 1995 as a reference year. It was found that there was a significant reduction in the water