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A novel Radon-based multi-carrier direct sequence code division multiple access transceiver design and simulation
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Multi-carrier direct sequence code division multiple access (MC-DS-CDMA) has emerged recently as a promising candidate for the next generation broadband mobile networks. Multipath fading channels have a severe effect on the performance of wireless communication systems even those systems that exhibit efficient bandwidth, like orthogonal frequency division multiplexing (OFDM) and MC-DS-CDMA; there is always a need for developments in the realisation of these systems as well as efficient channel estimation and equalisation methods to enable these systems to reach their maximum performance. A novel MC-DS-CDMA transceiver based on the Radon-based OFDM, which was recently proposed as a new technique in the realisation of OFDM systems, will be used here as a basic building block in the design of MC-DS-CDMA transceiver to increase the orthogonality against the multipath frequency selective fading channels. Simulation results are provided to demonstrate the significant gains in performance and simplicity due to the proposed techniques. Copyright © 2010 Inderscience Enterprises Ltd.

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Publication Date
Sat Jun 26 2021
Journal Name
2021 Ieee International Conference On Automatic Control & Intelligent Systems (i2cacis)
Vulnerability Assessment on Ethereum Based Smart Contract Applications
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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
BCI-Based Smart Room Control using EEG Signals
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In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model duri

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Publication Date
Wed Jan 01 2020
Journal Name
University Of Plymouth
Intrinsic Control Strategies for Herpesvirus-based Vaccine Vectors
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Publication Date
Sat Oct 19 2024
Journal Name
Iraqi Statisticians Journal
Forecasting Gold prices by hybrid ANFIS-based algorithm
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In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

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Publication Date
Wed Jun 24 2020
Journal Name
Neuroimaging - Neurobiology, Multimodal And Network Applications
Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease
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Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
BCI-Based Smart Room Control using EEG Signals
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In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model during di

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Publication Date
Mon May 15 2017
Journal Name
International Journal Of Image And Data Fusion
Image edge detection operators based on orthogonal polynomials
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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Al-nahrain University Science
Breaking Knapsack Cipher Using Population Based Incremental Learning
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Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Genetic –Based Face Retrieval Using Statistical Features
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Content-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In add

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