Recently, the development and application of the hydrological models based on Geographical Information System (GIS) has increased around the world. One of the most important applications of GIS is mapping the Curve Number (CN) of a catchment. In this research, three softwares, such as an ArcView GIS 9.3 with ArcInfo, Arc Hydro Tool and Geospatial Hydrologic Modeling Extension (Hec-GeoHMS) model for ArcView GIS 9.3, were used to calculate CN of (19210 ha) Salt Creek watershed (SC) which is located in Osage County, Oklahoma, USA. Multi layers were combined and examined using the Environmental Systems Research Institute (ESRI) ArcMap 2009. These layers are soil layer (Soil Survey Geographic SSURGO), 30 m x 30 m resolution of Digital Elevati

Three cohesionless free flowing materials of different density were mixed in an air fluidized bed to study the mixing process by calculating performance of mixing index according to Rose equation (1959) and to study the effect of four variables (air velocity, mixing time, particle size of trace component and concentration of trace component) on the mixing index and as well as on mixing performance. It was found that mixing index increases with increasing the air velocity, mixing time and concentration of trace component until the optimum value. Mixing index depends on the magnitude of difference in particle size The first set of experiments (salt then sand then cast iron) give higher mixing index and better performance of mixing than the

Background: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness

Background: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness

In this research, we present a nonparametric approach for the estimation of a copula density using different kernel density methods. Different functions were used: Gaussian, Gumbel, Clayton, and Frank copula, and through various simulation experiments we generated the standard bivariate normal distribution at samples sizes (50, 100, 250 and 500), in both high and low dependency. Different kernel methods were used to estimate the probability density function of the copula with marginal of this bivariate distribution: Mirror – Reflection (MR), Beta Kernel (BK) and transformation kernel (KD) method, then a comparison was carried out between the three methods with all the experiments using the integrated mean squared error. Furthermore, some

An efficient networks’ energy consumption and Quality of Services (QoS) are considered the most important issues, to evaluate the route quality of the designed routing protocol in Wireless Sensor Networks (WSNs). This study is presented an evaluation performance technique to evaluate two routing protocols: Secure for Mobile Sink Node location using Dynamic Routing Protocol (SMSNDRP) and routing protocol that used K-means algorithm to form Data Gathered Path (KM-DGP), on small and large network with Group of Mobile Sinks (GMSs). The propose technique is based on QoS and sensor nodes’ energy consumption parameters to assess route quality and networks’ energy usage. The evaluation technique is conducted on two routing protocols i

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre