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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 propose different approaches and we analysis and evaluation of these mobile P2P network security issues and submit some proposal solutions to resolve the related problems with threats and other different attacks since these threats and attacks will be serious issue as networks are growing up especially with mobility attribute in current P2P networks.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Linguistic Fuzzy Trust Model over Oscillating Wireless Sensor Networks
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Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Tue May 09 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
TIME MANAGEMENT AND WORK PRESSURE AND THEIR RELATIONSHIP TO ADMINISTRATIVE LEADERSHIP/ A CASE STUDY AT THE HIGHER INSTITUTE FOR ADMINISTRATIVE DEVELOPMENT OF SECURITY AND ADMINISRATIVE: TIME MANAGEMENT AND WORK PRESSURE AND THEIR RELATIONSHIP TO ADMINISTRATIVE LEADERSHIP/ A CASE STUDY AT THE HIGHER INSTITUTE FOR ADMINISTRATIVE DEVELOPMENT OF SECURITY AND ADMINISRATIVE
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The research aims to determine the strength of the relationship between time management and work pressure and administrative leadership, where he was taken a sample of (47) of the administrative leadership at the Higher Institute of security and administrative development in the Ministry of Interior was used questionnaire as a key tool in collecting data and information and analyzed the answers to the sample surveyed by using Statistical program (spss) in the arithmetic mean of the calculation and test (t) and the correlation coefficient, the research found the most important results: the existence of significant moral positive relationship between both time management and work pressure and administrative leadership, the leadership of th

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Mon Sep 01 2014
Journal Name
Al-khwarizmi Engineering Journal
Trajectory Tracking Control for a Wheeled Mobile Robot Using Fractional Order PIaDb Controller
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Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PIaDb (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of The College Of Languages (jcl)
Formal and Functional Perspectives in the Analysis of Hyperboles in Obama's Speeches
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     Hyperbole is an obvious and intentional exaggeration in the sense that it takes things to such an extreme that the audience goes too far and then pulls itself back to a more reasonable position, i.e. it is an extravagant statement or figure of speech not intended to be taken literally. This paper focuses on the formal and functional perspectives in the analysis of hyperbole which American candidates produce in their speeches in electoral campaigns, for it is hypothesized that candidates in their electoral campaigns use hyperbolic expressions excessively to persuade voters of the objectives of their electoral campaign programs. Hence, it aims to analyze hyperbole in context to determine the range of pragmatic func

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Tue Aug 05 2014
Journal Name
International Journal Of Pharmacy And Pharmaceutical Sciences
FORMULATION AND EVALUATION OF FLOATING ORAL IN-SITU GEL OF METRONIDAZOLE
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