Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Objective. This study aimed to evaluate the orthodontic bond strength and enamel-preserving ability of a hydroxyapatite nanoparticles-containingself-etch system following exposure to various ageing methods. Materials and Methods. Hydroxyapatite nanoparticles (nHAp) were incorporated into an orthodontic self-etch primer (SEP, Transbond™ plus) in three different concentrations (5%, 7%, and 9% wt) and tested versus the plain SEP (control) for shear bond strength (SBS), adhesive remnant index (ARI) scores, and enamel damage in range-finding experiments using premolar teeth. The best-performing formulation was further exposed to the following four artificial ageing methods: initial debonding, 24 h water storage, one-month water stora

This study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be comp

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

In this study, sulfur was removed from imitation oil using oxidative desulfurization process. Silicoaluminophosphate (SAPO-11) was prepared using the hydrothermal method with a concentration of carbon nanotubes (CNT) of 0% and 7.5% at 190 °C crystallization temperature. The final molar composition of the as-prepared SAPO-11 was Al2O3: 0.93P2O5: 0.414SiO2. 4% MO/SAPO-11 was prepared using impregnation methods. The produced SAPO-11 was described using X-ray diffraction (XRD) and Brunauer-Emmet-Teller (N2 adsorption–desorption isotherms). It was found that the addition of CNT increased the crystallinity of SAPO-11. The results showed that the surface area of SAPO-11 containing 7.5% CNT was 179.54 m2/g, and the pore volume was 0.31

In this study, sulfur was removed from imitation oil using oxidative desulfurization process. Silicoaluminophosphate (SAPO-11) was prepared using the hydrothermal method with a concentration of carbon nanotubes (CNT) of 0% and 7.5% at 190 °C crystallization temperature. The final molar composition of the as-prepared SAPO-11 was Al₂O₃: 0.93P²O⁵: 0.414SiO². 4% MO/SAPO-11 was prepared using impregnation methods. The produced SAPO-11 was described using X-ray diffraction (XRD) and Brunauer-Emmet-Teller (N² adsorption–desorption isotherms). It was found that the addition of CNT increased the crystallinity of SAPO-11. The results showed that the surface area of SAPO-11 cont

This research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri