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Using <scp>5G</scp> Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System
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ABSTRACT<p>The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing resource usage, managing mobility, ensuring cost‐efficiency, managing interference, and maximizing spectral efficiency. The fast advancement of artificial intelligence (AI) in several domains yields improved performance in contrast to traditional methods. Hence, including AI in 5G standards would enhance performance by catering to diverse end‐user applications. Initially, we provide an overview of concepts such as Industry 4.0, the 5G standard, and recent developments in the sphere of wireless communications in the future. The goal is to use 5G technology to look at current research problems. We present a new architecture for Industry 4.0 and 5G‐compliant smart healthcare systems. We develop and run the proposed model to investigate the current 5G methods using the Network Simulator (NS2). The results of the simulation show that 5G resource management and interference management approaches already in use face challenges including performance trade‐offs.</p>
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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform
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Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

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Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
CTJ: Input-Output Based Relation Combinatorial Testing Strategy Using Jaya Algorithm
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Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Performance of STBC Based MIMO-OFDM Using Pilot-aided Channel Estimation
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Many studies have been published to address the growing issues in wireless communication systems. Space-Time Block Coding (STBC) is an effective and practical MIMO-OFDM application that can address such issues. It is a powerful tool for increasing wireless performance by coding data symbols and transmitting diversity using several antennas. The most significant challenge is to recover the transmitted signal through a time-varying multipath fading channel and obtain a precise channel estimation to recover the transmitted information symbols. This work considers different pilot patterns for channel estimation and equalization in MIMO-OFDM systems. The pilot patterns fall under two general types: comb and block types, with

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Publication Date
Thu Jan 10 2019
Journal Name
Journal Of The College Of Education For Women
Personal intelligence relationship with the management agliation among teachers
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       Personal intelligence is thinking about an other person , understanding him, have sympathy and differentiation between people, and to appreciate their own point of view, with the sensitivity to their motives, behavior, and goals, so this intelligence involves dealing with a person or group of persons effectively and in normal or logical manner.

      Emotions management is to achieve emotional balance by controlling the emotions continuously, self disciplining, keeping away from excitement sources, and dealing with bad situations in constructive way to achieve the psychological stability .  

  • the study aims

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Publication Date
Sat Dec 30 2017
Journal Name
International Journal Of Science And Research (ijsr)
Color-based for tree yield fruits image counting
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Identifying the total number of fruits on trees has long been of interest in agricultural crop estimation work. Yield prediction of fruits in practical environment is one of the hard and significant tasks to obtain better results in crop management system to achieve more productivity with regard to moderate cost. Utilized color vision in machine vision system to identify citrus fruits, and estimated yield information of the citrus grove in-real time. Fruit recognition algorithms based on color features to estimate the number of fruit. In the current research work, some low complexity and efficient image analysis approach was proposed to count yield fruits image in the natural scene. Semi automatic segmentation and yield calculation of fruit

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Publication Date
Tue Sep 01 2020
Journal Name
Microprocessors And Microsystems
Design considerations for a microprocessor-based Doppler radar
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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
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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