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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 Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Improve Data Mining Techniques with a High-Performance Cluster
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Publication Date
Thu Jun 01 2023
Journal Name
Sustainable Engineering And Innovation
A review of enhanced image techniques using chaos encryption
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Secured multimedia data has grown in importance over the last few decades to safeguard multimedia content from unwanted users. Generally speaking, a number of methods have been employed to hide important visual data from eavesdroppers, one of which is chaotic encryption. This review article will examine chaotic encryption methods currently in use, highlighting their benefits and drawbacks in terms of their applicability for picture security.

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Tue Nov 01 2022
Journal Name
Standards
Observation of a Signal Suppressing Effect in a Binary Mixture of Glycol-Water Contamination in Engine Oil with Fourier-Transform Infrared Spectroscopy
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An in-depth experimental study of the matrix effect of antifreeze (ethylene glycol) and water contamination of engine oil through FT-IR spectroscopy. With a comparison of the percent by volume concentration of contaminated fresh 15W-40 engine oil, there appeared to be a noticeable reduction in the O–H stretching signal in the infrared spectrum when ethylene glycol based antifreeze was included as a contaminant. The contaminants of distilled water, a 50/50 mixture of water and commercial ethylene glycol antifreeze, and straight ethylene glycol antifreeze were compared and a signal reduction in the O–H stretch was clearly evident when glycol was present. Doubling the volume of the 50/50 mixture as compared to water alone still res

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of parameters of two-dimensional sinusoidal signal model by employing Deferential Evaluation algorithm and the use of Sequential approach in estimation
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Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

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Publication Date
Fri May 15 2009
Journal Name
Journal Of Planner And Development
Study of Change in Regional Land Use Using Remote Sensing Technology and Geographic Information Systems / Study Area (Hawr Al Huweiza) for the Years 1973-1990-2004
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his project try to explain the using ability of spatial techniques for land cover change detection on regional level with the time parameter and did select for explain these abilities study case (Hewaizah marsh ) . this area apply to many big changes with the time. These changes made action on characters and behaviors of this area as well as all activities in it . This Project concerting to recognize the Using importance of remote sensing and GIS Methodology in data collecting for the changes of land use and the methodology for the analyses and getting the results for the next using as a base data for development and drawing the plans as well as in regional planning .This project focus on practical

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Robust estimation of multiple linear regression parameters in the presence of a problem of heterogeneity of variance and outliers values
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Often times, especially in practical applications, it is difficult to obtain data that is not tainted by a problem that may be related to the inconsistency of the variance of error or any other problem that impedes the use of the usual methods represented by the method of the ordinary least squares (OLS), To find the capabilities of the features of the multiple linear models, This is why many statisticians resort to the use of estimates by immune methods Especially with the presence of outliers, as well as the problem of error Variance instability, Two methods of horsepower were adopted, they are the robust weighted least square(RWLS)& the two-step robust weighted least square method(TSRWLS), and their performance was verifie

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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Transactions On Robotics
Lidar-Level Localization With Radar? The CFEAR Approach to Accurate, Fast, and Robust Large-Scale Radar Odometry in Diverse Environments
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Violation of the Hormonal Spectrum in Polycystic Ovaries in Combination with Insulin Resistance. What is the Trigger: Insulin Resistance or Polycystic Ovary Disease?
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Polycystic ovary syndrome (PCOS) is the main cause of female infertility. The role of insulin resistance in the development of polycystic ovary is actively discussed here. The study included patients with PCOS without insulin resistance (n = 48) and with insulin resistance (n = 39). The comparison groups were patients with no history of PCOS: a control group without insulin resistance (n = 46) and a group of patients with insulin resistance (n = 45). The following parameters were determined in patients: FSH, LH, TSH, T3f, T4f, PRL, E2, 17-OHd, Pr, AMH, Test total, Testf, DHEAS, DHEASs, SHBG, ACTH, cortisol, IRI, IGF-1, C-peptide, and glucose level. The HOMA-IR index and the LH / FSH ratio and t

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Engineering
The Effect of Total Suspended Solids on the Electricity Generation in Microbial Fuel Cell Treating Actual Potato Chips Processing Wastewater
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This study aimed to investigate the effect of total suspended solids (TSS) on the performance of a continuously operated dual-chamber microbial fuel cell (MFC) proceeded by primary clarifier to treat actual potato chips processing wastewater. The system was also tested in the absence of the primary clarifier and the results demonstrated a significant effect of TSS on the polarization curve of the MFC which was obtained by operating the graphite anodic electrode against Ag/AgCl reference electrode. The maximum observed power and current densities were decreased form 102.42 mW/m2 and 447.26 mA/m2 to 80.16 mW/m2 and 299.10 mA/m2, respectively due to the adverse effect of TSS. Also

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