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Directive and Steerable Radiation Pattern using SASPA Array
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This work examines the ability of a special type of smart antenna array known as Switched Active Switched Parasitic Antenna (SASPA) to produce a directive and electronically steerable radiation pattern. The SASPA array consists of antenna elements that are switchable between active and parasitic states by using P-Intrinsic-N (PIN) diodes. The active element is the element that is supplied by the radio frequency while short-circuiting the terminals of an element in the array results in a parasitic element. Due to the strong mutual coupling between the elements, a directional radiation pattern with high gain and a small beamwidth can be produced with only one active element operating at a time. By changing the parasitic state to the active state sequentially for all elements, the directed radiation pattern can be easily rotated. The antenna array structure used in this work is the uniform circular array (UCA) to achieve symmetrical radiation patterns and full coverage of the entire azimuth plane. Also, a novel method for reducing the mutual coupling effect in SASPA arrays is proposed in this work. By using this method, some parameters of the generated SASPA’s radiation pattern can be controlled. The simulated results obtained from this work depict that an N-element SASPA-UCA produces N-symmetrical, switchable, and steerable radiation patterns with high gain, small beamwidth, and a high Front-to-Back (F/B) ratio. Also, the results show that further improvements in these parameters can be achieved by increasing the number of elements in the array. Additional simulations demonstrate that by including decaying function weight in each element's circuitry, the mutual coupling between the components of the SASPA-UCA array can be minimized. The aforementioned parameters can then be efficiently modified using this mutual coupling reduction.

 

 

 

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Shadow Removal Using Segmentation Method
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Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
strong criminal capabilities، Using simulation .
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The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Vibration Control Analysis of a Smart Flexible Cantilever Beam Using Smart Material
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This paper features the modeling and design of a pole placement and output Feedback control technique for the Active Vibration Control (AVC) of a smart flexible cantilever beam for a Single Input Single Output (SISO) case. Measurements and actuation actions done by using patches of piezoelectric layer, it is bonded to the master structure as sensor/actuator at a certain position of the cantilever beam.
The smart structure is modeled based on the concept of piezoelectric theory, Bernoulli -Euler beam theory, using Finite Element Method (FEM) and the state space techniques. The number of modes is reduced using the controllability and observability grammians retaining the first three
dominant vibratory modes, and for the reduced syste

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Wed Apr 01 2020
Journal Name
Biochemical & Cellular Archives
SYNTHESIS, CHARACTERIZATION, ANTIOXIDANT, ANTICANCER HUMAN STUDIES AND BIOLOGICAL ACTIVITY OF MIXED LIGAND COMPLEXES USING SCHIFF BASE LIGAND AND HISTIDINE.
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الوصف Mixed ligand complexes of Cu (II), Co (II) and Zn (II) with 2-((4-(1-(4-chlorophenylimino) ethyl) phenylimino) methyl) phenol (L) and histidine (His) have been prepared and diagnosed by ¹H and13 C NMR, FT-IR and electronic spectral data, thermal gravimetric, molar conductance and metal analysis measurements. The ligand (L) shows a bidentate nature and the coordination occurs through N and O atoms of imine group and phenol group respectively whereas (His) behave as tridentate ligand, coordinating through the-NH2 group and carboxylate oxygen group and N atoms of imidazole ring. The analytical studies for three complexes have shown octahedral structure. The anticancer activity was screened against human cancer cell such Follicular

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Publication Date
Sun Jul 01 2018
Journal Name
Computers & Mathematics With Applications
Analytical and numerical solutions for the nonlinear Burgers and advection–diffusion equations by using a semi-analytical iterative method
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Textural Analysis of Functionalized Mesoporous Silica Using Sodium Silicate as Precursor and Silicone Surfactant as Template
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Three mesoporous silica with different functional group were prepared by one-step synthesis based on the simultaneous hydrolysis and condensation of sodium silicate with organo - silane in the presence of template surfactant polydimethylsiloxane - polyethyleneoxide (PDMS - PEO). The prepared materials were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), atomic force microscopy (AFM) and nitrogen adsorption/desorption experiments. The results indicate that the preparation of methyl and phenyl functionalized silica were successful and the mass of methyl and phenyl groups bonded to the silica structure are 15, 38 mmol per gram silica. The average diameter of the silica particles are 103.51,

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Teaching Using Adey- Shire Model and its Effect in Achievement and Critical Thinking for first intermediate students in Mathematics
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The aim of this research is to measure the effect of Adey- Shire model in the achievement and critical thinking of first intermediate female students in mathematics. The researcher adopted the experimental method with a post-test, the research of sample consists of (60) female students, divided into two groups with (30) students in the experimental group, that studied with Adey- Shire model, and (30) students in the control group who studied in the usual way. The two groups are equivalent in many variables. The researcher makes two tests of multiple choices, the first one is an achievement test consists (30) items and another test was for a critical thinking test with (25) items. The statistical analysis make to both tests is made with s

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