Due to the popularity of radar, receivers often “hear” a great number of other transmitters in
addition to their own return merely in noise. The dealing with the problem of identifying and/or
separating a sum of tens of such pulse trains from a number of different sources are often received on
the one communication channel. It is then of interest to identify which pulses are from which source,
based on the assumption that the different sources have different characteristics. This search deals with a
graphical user interface (GUI) to generate the radar pulse in order to use the required radar signal in any
specified location.

Prepositions have a key function, which is to associate parts of a sentence, called letters In addition, it adds the meanings of the verbs to the names, ie reached by them, and called by the coffin characters Qualities..

          I chose to search for the meaning of the preposition "from" in Surat Maryam to know its meanings in terms of originality and expansion, so the title of the research (the meanings of preposition "from" in terms of originality and expansion in Surat Maryam model(

The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

   Zinc-air fuel cells (ZAFCs) are a promising energy source that could compete with lithium-ion batteries and perhaps proton-exchange membrane fuel cells (PEMFCs) for next-generation electrified transportation and energy storage applications. In the present work, a flow-type ZAFC with mechanical rechargeable was adopted, combined with an auxiliary cell (electrolyzer) for zinc renewal and electrolyte recharge to the main cell. In this work a practical study was performed to calculate the cell capacity (Ah), as well as study the electrolysis cell efficiency by current efficiency, and study the effective parameters that have an influence on cell performance such as space velocity and current density. The best parameters were selected to

In this paper, we introduce weak and strong forms of ω-perfect mappings, namely the -ω-perfect, weakly -ω-perfect and strongly-ω-perfect mappings. Also, we investigate the fundamental properties of these mappings. Finally, we focused on studying the relationship between weakly -ω-perfect and strongly -ω-perfect mappings.

In this paper, we provide some types of - -spaces, namely, - ( )- (respectively, - ( )- , - ( )- and - ( )-) spaces for minimal structure spaces which are denoted by ( -spaces). Some properties and examples are given.
The relationships between a number of types of - -spaces and the other existing types of weaker and stronger forms of -spaces are investigated. Finally, new types of open (respectively, closed) functions of -spaces are introduced and some of their properties are studied.

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     Deep learning techniques allow us to achieve image segmentation with excellent accuracy and speed. However, challenges in several image classification areas, including medical imaging and materials science, are usually complicated as these complex models may have difficulty learning significant image features that would allow extension to newer datasets. In this study, an enhancing technique for object detection is proposed based on deep conventional neural networks by combining levelset and standard shape mask. First, a standard shape mask is created through the "probability" shape using the global transformation technique, then the image, the mask, and the probability map are used as the levelset input to apply the image segme

Text documents are unstructured and high dimensional. Effective feature selection is required to select the most important and significant feature from the sparse feature space. Thus, this paper proposed an embedded feature selection technique based on Term Frequency-Inverse Document Frequency (TF-IDF) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) for unstructured and high dimensional text classificationhis technique has the ability to measure the feature’s importance in a high-dimensional text document. In addition, it aims to increase the efficiency of the feature selection. Hence, obtaining a promising text classification accuracy. TF-IDF act as a filter approach which measures features importance of the te