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PDF Comparison based on Various FSO Channel Models under Different Atmospheric Turbulence
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Recently, wireless communication environments with high speeds and low complexity have become increasingly essential. Free-space optics (FSO) has emerged as a promising solution for providing direct connections between devices in such high-spectrum wireless setups. However, FSO communications are susceptible to weather-induced signal fluctuations, leading to fading and signal weakness at the receiver. To mitigate the effects of these challenges, several mathematical models have been proposed to describe the transition from weak to strong atmospheric turbulence, including Rayleigh, lognormal, Málaga, Nakagami-m, K-distribution, Weibull, Negative-Exponential, Inverse-Gaussian, G-G, and Fisher-Snedecor F distributions. This paper extensively studies and analyses different probability density functions (PDFs) that govern the FSO channel, considering various channel models. This paper aims to comprehensively understand how FSO channels can be effectively modeled using different PDFs. Accurate modeling is crucial for designing FSO systems that can operate optimally under potential environmental conditions. Selecting the appropriate PDF model plays a crucial role in determining the FSO channel's performance during system design. With a multitude of PDF models available, this study aims to identify the most effective PDF model to be employed in FSO channel modeling.

 

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Publication Date
Mon Dec 01 2014
Journal Name
2014 Ieee Student Conference On Research And Development
Feature extraction for co-occurrence-based cosine similarity score of text documents
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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Publication Date
Sun Oct 01 2023
Journal Name
Ieee Transactions On Industrial Electronics
Singular Perturbation-Based Adaptive Integral Sliding Mode Control for Flexible Joint Robots
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The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha

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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Sun Jul 01 2018
Journal Name
Ieee Transactions On Intelligent Transportation Systems
Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular Networks
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High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Synthesis, Anticancer and Antibacterial Activity of Mannose-based bis-1,2,3-Triazole Derivatives
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       In the current work, aromatic amines and alkyl halides have been converted to the corresponding azides 2a‒d and 4a-d by the reaction with sodium nitrite and sodium azide respectively for amines and sodium azide for halides. Then, dipropargyl ether derivative of D-mannose 8 has been synthesized from diacetone mannose that has been obtained by the treatment of D-mannose (5) with dry acetone in the presence of sulfuric acid. Then, aldol condensation has been used to prepare diol 7 from the mannose diacetonide 6. The reaction of compound 7 with propargyl bromide in alkaline media has been afforded dipropargyl

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Thu Jun 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Marginal Discrepancy and Fracture Resistance of CAD/CAM Ceramill Sintron Metal Copings with Different Porcelain Materials
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Background: This study was performed to compare the marginal fit changes and facture resistance of metal ceramic crowns constructed from Ceramill Sintron metal coping veneered with three different porcelain veneering materials (Vita Master Koromikos VMK, Willi Geller Creation CC and GC initial MC), also to evaluate the influence of thermocycling on load at fracture. Materials and Methods: Master brass die was scanned ,then metal coping was designed and milled from Ceramill Sintron blank to get 60 metal copings, then divided randomly into three groups(20 sample), then veneered with porcelain: VITA, Creation or GC. The marginal gaps were measured before and after porcelain veneering then marginal fit changes was calculated. Fracture resist

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Publication Date
Mon Jan 01 2007
Journal Name
Journal Of Al-nahrain University
STUDY FOR THE GROWTH RATE, VIABILITY AND MORPHOLOGICAL CHANGES OF LEISHMANIA TROPICA IN DIFFERENT CULTURE MEDIA
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This study included the estimation of growth rate, viability and morphological changes in different culture media (NNN, P-Y, RPMI- 1640, and Panmed). Promastigotes cultured in RPMI-1640 showed maximal growth rate after (2, 4, 6) days of cultivation (27.26 ± 0.05), (172.20 ± 0.1) and (343.81 ± 1.48) million parasites / ml for each day respectively, while P-Y media gave the highest mean of growth rat after (8 and 10) days of cultivation (307.16 ± 1.67) and (303.5 ± 4.96) million parasites / ml for each day respectively. P-Y medium showed the maximal percentage of viability after (2, 4, 6, 8, and 10) days of cultivation (99.76 ± 0.5) %, (98.30 ± 0.17) %, (96.1 ± 0.1) %, (92.5 ± 0.52) % and (87.26 ± 0.05) % for each day respectively.

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