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Energy Aware Scheme for Underwater Wireless Sensor Networks
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The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifespan. This study introduces a novel Seeker Optimization based Energy Aware Clustering Scheme for Underwater Wireless Sensor Networks (SOEACS-UWN). The presented SOEACS-UWN model follows the operation on a collection of solutions named search population (i.e., human team) and considered optimization procedure as a searching process of optimum solutions via human teams. The SOEACS-UWN model constructs a fitness function for effectual CH choices using diverse variables namely distance, residual energy, node degree, centrality, and link quality. The simulation analysis of the SOEACS-UWN model is tested and the outcomes were investigated under diverse aspects. The experimental outcomes demonstrated the supremacy of the SOEACS-UWN model over other approaches.

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Science And Research (ij
Simulation of Chlorine Decay in Al-Gukook WaterDistribution Networks Using EPANET
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The approach of the research is to simulate residual chlorine decay through potable water distribution networks of Gukookcity. EPANET software was used for estimating and predicting chlorine concentration at different water network points . Data requiredas program inputs (pipe properties) were taken from the Baghdad Municipality, factors that affect residual chlorine concentrationincluding (pH ,Temperature, pressure ,flow rate) were measured .Twenty five samples were tested from November 2016 to July 2017.The residual chlorine values varied between ( 0.2-2mg/L) , and pH values varied between (7.6 -8.2) and the pressure was very weak inthis region. Statistical analyses were used to evaluated errors. The calculated concentrations by the calib

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Publication Date
Tue Dec 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering
Analysis of threats and security issues evaluation in mobile P2P networks
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Technically, mobile P2P network system architecture can consider as a distributed architecture system (like a community), where the nodes or users can share all or some of their own software and hardware resources such as (applications store, processing time, storage, network bandwidth) with the other nodes (users) through Internet, and these resources can be accessible directly by the nodes in that system without the need of a central coordination node. The main structure of our proposed network architecture is that all the nodes are symmetric in their functions. In this work, the security issues of mobile P2P network system architecture such as (web threats, attacks and encryption) will be discussed deeply and then we prop

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Publication Date
Thu Aug 30 2018
Journal Name
Iraqi Journal Of Science
Towards Generating Robust Key Based on Neural Networks and Chaos Theory
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There are large numbers of weakness in the generated keys of security algorithms. This paper includes a new algorithm to generate key of 5120 bits for a new proposed cryptography algorithm for 10 rounds that combine neural networks and chaos theory (1D logistic map). Two methods of neural networks (NN) are employed as Adaline and Hopfield and the results are combined through several sequential operation. Carefully integrating high quality random number generators from neural networks and chaos theory to obtain suitable key for randomness and complexity.

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Detection of COVID-19 in X-Rays by Convolutional Neural Networks
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      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

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Publication Date
Fri Feb 04 2022
Journal Name
Iraqi Journal Of Science
Community Tracking in Time Evolving Networks: An Evolutionary Multi-objective Approach
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In real world, almost all networks evolve over time. For example, in networks of friendships and acquaintances, people continually create and delete friendship relationship connections over time, thereby add and draw friends, and some people become part of new social networks or leave their networks, changing the nodes in the network. Recently, tracking communities encountering topological shifting drawn significant attentions and many successive algorithms have been proposed to model the problem. In general, evolutionary clustering can be defined as clustering data over time wherein two concepts: snapshot quality and temporal smoothness should be considered. Snapshot quality means that the clusters should be as precise as possible durin

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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
AndroidTrack: An Investigation of Using Social Networks’ Applications in Android Platforms
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     In this paper, time spent and the repetition of using the Social Network Sites (SNS) in Android applications are investigated. In this approach, we seek to raise the awareness and limit, but not eliminate the repeated uses of SNS, by introducing AndroidTrack. This AndroidTrack is an android application that was designed to monitor and apply valid experimental studies in order to improve the impacts of social media on Iraqi users. Data generated from the app were aggregated and updated periodically at Google Firebase Real-time Database. The statistical factor analysis (FA) was presented as a result of the user’s interactions.

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Photoluminescence Spectra From The Direct Energy Gap of a-SiQDs
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Publication Date
Fri Apr 05 2013
Journal Name
Journal Of Intelligent Material Systems And Structures
Increasing the power of piezoelectric energy harvesters by magnetic stiffening
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A piezoelectric cantilever beam with a tip mass at its free end is a common energy harvester configuration. This article introduces a new principle of designing such a harvester that increases the generated power without changing the resonance frequency of the harvester: the attraction force between two permanent magnets is used to add stiffness to the system. This magnetic stiffening counters the effect of the tip mass on the efficient operation frequency. Five set-ups incorporating piezoelectric bimorph cantilevers of the same type in different mechanical configurations are compared theoretically and experimentally to investigate the feasibility of this principle: theoretical and experimental results show that magnetically stiffened harve

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