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Describing the Wavefront Aberrations of the Hexagonal Aperture Using Modified Zernike Polynomials
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n Segmented Optical Telescope (NGST) with hexagonal segment of spherical primary mirror can provide a 3 arc minutes field of view. Extremely Large Telescopes (ELT) in the 100m dimension would have such unprecedented scientific effectiveness that their construction would constitute a milestone comparable to that of the invention of the telescope itself and provide a truly revolutionary insight into the universe. The scientific case and the conceptual feasibility of giant filled aperture telescopes was our interested. Investigating the requirements of these imply for possible technical options in the case of a 100m telescope. For this telescope the considerable interest is the correction of the optical aberrations for the coming wavefront, the modified Zernike polynomials for hexagonal aperture were used to describe the wavefront aberrations and to predict the initial state for the adaptive optics corrections.

Publication Date
Tue Aug 13 2024
Journal Name
Brazilian Dental Science
Poly ether keton keton polymer deposition on laser surface structured commercial pure titanium using magnetron sputtering
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Objective: This study aimed to evaluate the effect of coating titanium (Ti) dental implant with polyether ketone ketone (PEKK) polymer using magnetron sputtering on osseointegration, trying to overcome some of the problems associated with Ti alloys. Material and Methods: Implants were prepared from grade (II) commercially pure titanium (CP Ti), then laser was used to induce roughness on the surface of Ti. PEKK was deposited on the surface of Ti implants by radiofrequency (RF) magnetron sputtering technique. The implants were divided in to three groups: without coating (Ls), with PEKK coating using argon (Ar) as sputtering gas (Ls-PEKK-Ar), and with PEKK coating using nitrogen (N) as sputtering gas (Ls-PEKK-N). All the implants were implante

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Publication Date
Wed Nov 27 2024
Journal Name
International Journal Of Integrated Engineering
Noise Modeling and Removal from Electrocardiogram Signals: A Study Using Wavelet Transform with Graphical User Interface
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The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)

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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Computer Model Application for Sorting and Grading Citrus Aurantium Using Image Processing and Artificial Neural Network
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Abstract<p>This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin</p> ... Show More
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Publication Date
Tue Jun 04 2024
Journal Name
International Journal Of Operational Research
Pascal's triangle graded mean defuzzification approach for solving fuzzy assignment models by using pentagonal fuzzy numbers
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The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Existence And Controllability Results For Fractional Control Systems In Reflexive Banach Spaces Using Fixed Point Theorem
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       In this paper, a fixed point theorem of nonexpansive mapping is established to study the existence and sufficient conditions for the controllability of nonlinear fractional control systems in reflexive Banach spaces. The result so obtained have been modified and developed in arbitrary space having Opial’s condition by using fixed point theorem deals with nonexpansive mapping defined on a set has normal structure. An application is provided to show the effectiveness of the obtained result.

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Publication Date
Sat Sep 01 2018
Journal Name
J Indian Soc Periodontol.
Osteoporosis effect on posterior mandible in preimplanted area for postmenopausal females using cone-beam computed tomography
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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Polluted Water Sensor Based on Carbon Quantum Dots/Alq3 Using Drop Casting and Spin Coating Techniques
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Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of

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Publication Date
Sun Jun 23 2019
Journal Name
American Rock Mechanics Association
Using an Analytical Model to Predict Collapse Volume During Drilling: A Case Study from Southern Iraq
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Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Producing Hydrogen Energy Using Cr2O3-TNFs Nanocomposite with Animal (Chitosan) Extract via Ultrasonic and Hydrothermal Techniques
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In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape struct

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Publication Date
Fri Jan 01 2016
Journal Name
Advances In Computing
A New Abnormality Detection Approach for T1-Weighted Magnetic Resonance Imaging Brain Slices Using Three Planes
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Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

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