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Studying the Correlation Between Supermassive Black Holes and Star Formation Rate for Samples of Seyfert Galaxies (Type 1 and 2)
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An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and the SFR in a factor of (ρ=0.551). Furthermore, different types of line-regressions were fitted between the data (e.g. linear, exponential, and power) to choose the more suitable line among the data and extract the mathematical formula that explain this behavior.

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Publication Date
Thu Feb 01 2024
Journal Name
Ain Shams Engineering Journal
Performance enhancement of high degree Charlier polynomials using multithreaded algorithm
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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
Study of desertification using remote sensing imagery in South Iraq
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Recently The problem of desertification and vegetation cover degradation become an environmental global challenge. This problem could be summarized as as the land cover changes. In this paper, the area of Al- Muthana in the south of Iraq will be consider as one of Semi-arid lands. For this purpose, the Ladsat-8 images can be used with 15 m in spatial resolution. In order to over Achieve the work, many important ground truth data must be collected such as, rain precipitation, temperature distribution over the seasons, the DEM of the region, and the soil texture characteristics. The extracted data from this project are tables, 2-D figures, and GIS maps represent the distributions of vegetation areas, evaporation / precipitation, river levels

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Scopus
Publication Date
Wed Apr 01 2020
Journal Name
Plant Archive
Genetic analysis of sorghum cultivars from USA using SSR markers
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Scopus
Publication Date
Mon Mar 04 2024
Journal Name
Journal Of Engineering
REMOVAL OF DIRECT BLUE DYE IN TEXTILEWASTEWATER EFFLUENT BY ELECTROCOAGULATION
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 Removal of direct blue dye by electrocoagulation method has been investigated using aluminum   electrode in a bench-scale electrochemical system. Current density, NaCl concentration,   electrocoagulation time, and dye concentration has been studied as effecting parameters in color   removal efficiency. Increasing of current density will increase the color removal efficiency and   energy consumption as well. While increasing NaCl concentration increase the color removal   efficiency but it decrease energy consumption. High dye concentration is needed for extra   electrocaogolation time to reach the same efficiency that obtained with low dye concentration .With   current applied 0.35 amps. and NaCl concentration of 2 g/l more

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Craniofacial Surgery
Radiographic Assessment of Nasopalatine Canal Using Cone Beam Computed Tomography
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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Scopus
Publication Date
Sun Jan 01 2023
Journal Name
Advances In The Theory Of Nonlinear Analysis And Its Application
Numerical identification of timewise dependent coefficient in Hyperbolic inverse problem
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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Patients' Satisfaction toward Nursing Care at Hemodialysis units
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Objectives: To assess patients' satisfaction to nursing care at hemodialysis units and determine the relationship
between patients' satisfaction and patients' demographic data.
Methodology: A descriptive study was carried out at hemodialysis units of Baghdad teaching hospitals from Feb.
4
th
, 2010 through Sep. 5
th, 2010. A purposive (non-probability) sample of (150) patients ta hemodialysis units ni
Baghdad teaching hospitals was selected. The data were collected through the use of constructing questionnaire
and by means of an interview technique with the patients; the questionnaire consists of two parts (1)
demographic data (2) patients' satisfaction to nursing care. The validity of the study questionnaire w

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Publication Date
Thu Feb 01 2024
Journal Name
Computers In Biology And Medicine
Model based smooth super-twisting control of cancer chemotherapy treatment
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Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and hypotheses subject to parametric uncertainties and exo

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Publication Date
Mon Aug 01 2022
Journal Name
Mathematics
Face Recognition Algorithm Based on Fast Computation of Orthogonal Moments
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Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

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