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Signal Processing Techniques for Robust Spectrum Sensing
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Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper , we present the system design approach to meet this challenge with technique , The design space is diverse as it involves various types of primary user signals, We analysis of signal processing approaches and identify the regimes where these techniques are applicable. The goal of this paper is to present a practical system design view of spectrum sensing functionality.

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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formation Evaluation for Nasiriyah Oil Field Based on The Non-Conventional Techniques
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The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence. The techniques used in this paper are:

  • Apparent resistivity Rwa
  • Rxo /Rt

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of ATP7B variants with clinical correlation in children with Wilson disease
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Publication Date
Thu Jan 01 2015
Journal Name
Agriculture And Agricultural Science Procedia
The Influence of the Water Quality on the Droplet Spectrum Produced by Agricultural Nozzles
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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluation of Stability of Cefamandol and Ceftazidime with Clavulanic Acid Against Extended Spectrum ?- Lactamase
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The aim of this study is to evaluate in-vitro activity of Cefamandol (Cfm) and Ceftazidime (Cfz), in combination with Clavulanic acid (CA) against ten complicated multiresistant uropathogenic E.coli .One hundred clinical strains were isolated from patients with chronic urinary tract infections (UTIs), these isolates were identified by the Api identification systems. The antimicrobial susceptibility tests were determined by Kirby-Bauer method, all of them were sensitive to Imipenem (Imp). Ten strains were chosen for the present study, they were resistant to Ampicillin (Amp), Amoxicillin (Amo), Carbenicillin (Cb), Ticarcillin (Tic), Azlocillin (Azl), Amoxicillin\ Potassium Clavulanate {Augmentin(Amc)}, (Amo\CA), Ticarcillin\ Potas

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Processing Eruca sativa leaves in the nanoscale and study its effectiveness for removing Cibacron red dye from their aqueous solutions
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    The discharge of dyes into the water is a significant source of pollution, which is especially concerning given that textile mills are the primary contributor. Nanomaterial-based solutions to this issue have required extensive research and investigation due to their complex nature. In this research, novel nanoparticle were successfully synthesized using the leaves of the Eruca sativa plant. The nano was analyzed using scanning and transmission electron microscopy (SEM and TEM) measurements, and their crystal structure was determined using the X-ray diffraction technique (XRD). The incorporation of NPs resulted in an increase in the uptake of the Cibacron red dye. At a contact time of 30 minutes, observed a faster adsor

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Publication Date
Sat Nov 02 2013
Journal Name
International Journal Of Computer Applications
Mixed Transforms Generated by Tensor Product and Applied in Data Processing
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Finding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.

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Publication Date
Tue Feb 01 2022
Journal Name
Case Studies In Thermal Engineering
Robust composite temperature control of electrical tube furnaces by using disturbance observer
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As one type of resistance furnace, the electrical tube furnace (ETF) typically experiences input noise, measurement noise, system uncertainties, unmodeled dynamics and external disturbances, which significantly degrade its temperature control performance. To provide precise, and robust temperature tracking performance for the ETF, a robust composite control (RCC) method is proposed in this paper. The overall RCC method consists of four elements: First, the mathematical model of the ETF system is deduced, then a state feedback control (SFC) is constructed. Third, a novel disturbance observer (DO) is designed to estimate the lumped disturbance with one observer parameter. Moreover, the stability of the closed loop system including controller

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Robust Estimations of Cluster Analysis: Practical Application in Administrative and Financial Corruption
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Cluster analysis (clustering) is mainly concerned with dividing a number of data elements into clusters. The paper applies this method to create a gathering of symmetrical government agencies with the aim to classify them and understand how far they are close to each other in terms of administrative and financial corruption by means of five variables representing the prevalent administrative and financial corruption in the state institutions. Cluster analysis has been applied to each of these variables to understand the extent to which these agencies are close to other in each of the cases related to the administrative and financial corruption.           

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Publication Date
Mon Sep 03 2012
Journal Name
The International Archives Of The Photogrammetry, Remote Sensing And Spatial Information Sciences
CALIBRATION OF FULL-WAVEFORM ALS DATA BASED ON ROBUST INCIDENCE ANGLE ESTIMATION
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Abstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r

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