This dissertation depends on study of the topological structure in graph theory as well as introduce some concerning concepts, and generalization them into new topological spaces constructed using elements of graph. Thus, it is required presenting some theorems, propositions, and corollaries that are available in resources and proof which are not available. Moreover, studying some relationships between many concepts and examining their equivalence property like locally connectedness, convexity, intervals, and compactness. In addition, introducing the concepts of weaker separation axioms in α-topological spaces than the standard once like, α-feebly Hausdorff, α-feebly regular, and α-feebly normal and studying their properties. Furthermore, providing the necessary condition for α-feebly normality property to become hereditary. Also, using a new topological model for graphs are the edges represented as points which enables us to express in a topological language about combinatorial concepts. Moreover, showing that an α-connected orderable spaces are exactly α-topologized graphs. Finally, realizing the relationship between the α-topology on the vertex set and the once on the whole space by α-feebly regularity property.
Been manufacturing detector Altosalih optical pattern contact metal semiconductor through deposition poles of aluminum metal on the chips of crystal cadmium Tleraad (CdTe) with directional [111] and growing with laboratory and annealed at a temperature 80c for 30 minutes and eat Study of some electrical properties nailed and scoutNmadj ??????? copper with non ??????? models to see effect Alichoab well research deals impact Alichoab and frequency detector resistance
Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreThe purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift
... Show MoreIn this article, we recalled different types of iterations as Mann, Ishikawa, Noor, CR-iteration and, Modified SP_iteration of quasi δ-contraction mappings, and we proved that all these iterations equivalent to approximate fixed points of δ-contraction mappings in Banach spaces.
This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th
... Show MoreThis article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.
Forty eight isolates (41.02%) were obtained from 117 wound and burn samples. The isolates that showed high resistance for both antibiotic was two only that represent 4,1% from all isolates. The result of PCR product electrophoresis was referred that the gene is VIM gene. Lactose and raffinose showed double increasing in diameter of inhibition zone of imipenem with 1% that mean showed highest susceptibility that decreased with the concentration increasing, the same result were with meropenem. But no effect were detected on meropenem inhibition zone diameter. Mannose have no effect on the resistance in 1%, 3% and 7%. Results showed that only three case that increase the expression of gene, they were lactose at 1% concentration that increased
... Show MoreThe antibacterial activity of some extracts of A. eupatoria (aqueous and ethanolic) against some pathogenic bacteria (Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli ) and their activity on wound healing in rats , also the presence of some active compounds in both extracts were detected . The results showed that the ethanolic extract was more effective on inhibiting tested bacteria than the aqueous extract . P.aeruginosa was the most resistant bacteria, while highest inhibition zone appeared on E.coli (20 mm) .There was a moderate activity against S.aureus with inhibition zone 15 mm. by using ethanolic extract (10 mg/ml) . The phytochemical analysis for detection of active compounds revealed the presence of Carbohydrate
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