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Implementation of RWP and Gauss Markov Mobility Model for Multi-UAV Networks in Search and Rescue Environment
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Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms.  In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are described in depth, together with the movement patterns they are related with. Furthermore, two-simulation scenarios conduct with help of an NS-3 simulator. The first scenario investigates the effect of UAV Speed by varying it from 10 to 50 m/s. the second scenario investigates the effect of the size of the transmitting packet by varying it from 64 to 1024 bytes. The performance of GM and RWP was compared based on packet delivery ratio (PDR), goodput, and latency metrics. Results indicate that the GM model provides the highest PDR and lowest latency in such high mobility environments.

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Publication Date
Wed Apr 15 2026
Journal Name
Experimental And Theoretical Nanotechnology
Utilization of multitemporal satellite imagery and forest canopy density (FCD) model for analyzing changes in forest density in Mosul province, Iraq
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Forest cover in Mosul Province experienced significant changes following the 2014 occupation. These changes can be effectively analyzed using multitemporal remote sensing imagery. This study aims to evaluate the ability of multi-temporal Landsat 8 images and the Forest Canopy Density (FCD) model to detect changes in forest canopy density in a protected forest in Mosul Governorate during the period from 2014 to 2025. The remote sensing data used in this research are Landsat 8 images captured on March 21, 2014, and April 4, 2025. The method employed is FCD modeling, which produces pixel-level canopy density estimates. The results of the FCD model are then used to analyze changes in canopy density following the occupation. The findings of this

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Publication Date
Tue Jan 29 2019
Journal Name
Journal Of The College Of Education For Women
Analysis of the Chemistry Book second grade intermediate according to science and technology, society and Environment issues (S.T.S.E)
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The aim of the present research is to know the following : What are the Science and technology, society and environment issues (S.T.S.E) which included in the content of thechemistry Book second grade intermediate ? And to achieve the objective of search The two researchers has prepares a list of science and technology, society and environment issues (STSE) consisted of (9) key issues namely (Air quality and the atmosphere, sustainable development, water security, health and preventive security, mineral resources investment, pollution of various kinds, energy, food industry, production of weapons technology) and from which (70) sub-issues emerge,Arbitrators competent agreement has been received . Then, thetwo researchers analyzed the con

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Mathematical Modelling of Gene Regulatory Networks
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    This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr

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Publication Date
Fri Jun 03 2022
Journal Name
Basra Journal Of Science
Morphological and Electrical properties of Polyvinylpyrrolidone/Multi-walled Carbon Nanotubes Nanocomposite with Graphene
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The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio

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Publication Date
Fri May 29 2026
Journal Name
Construction Materials
Synergistic Effects of Multi-Walled Carbon Nanotubes and SBS on Asphalt Binder Performance
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The performance and durability of asphalt pavements are strongly influenced by the rheological properties of asphalt binders, particularly under severe climatic and traffic conditions. This study investigates the synergistic effects of incorporating multi-walled carbon nanotubes (CNTs) at dosages ranging from 0.25% to 1% into AC 40-50 asphalt binders modified with 4% Styrene–Butadiene–Styrene (SBS). A comprehensive experimental program involving physical, rheological, and chemical characterization tests was conducted, including penetration, softening point, viscosity, storage stability, a Dynamic Shear Rheometer (DSR), Multiple Stress Creep Recovery (MSCR), Linear Amplitude Sweep (LAS), Fourier Transform Infrared Spectroscopy (F

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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Publication Date
Thu Apr 01 2021
Journal Name
Basra Journal Of Science
Preparation and Characterization of Polyvinylpyrrolidone/Multi-walled Carbon Nanotubes Nanocomposite hybrid with Graphene
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In this work, polyvinylpyrrolidone (PVP), Multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybrid with Graphene (Gr) by casting method. The morphological and optical properties were investigated. Fourier Transformer-Infrared (FT-IR) indicates the presence of primary distinctive peaks belonging to vibration groups that describe the prepared samples. Scanning Electron Microscopy (SEM) images showed a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The results of the optical study show decrease in the energy gap with increasing MWCNT and graphene concentration. The absorption coefficient spectra indicate the presence of two absorption peaks at 282 and 287 nm attributed to the π-π* electronic tr

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Publication Date
Thu Apr 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Automatic human ear detection approach using modified adaptive search window technique
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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Generating a Strong Key for a Stream Cipher Systems Based on Permutation Networks
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The choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.

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