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Strengthening cloud data protection based on a novel cyber security framework
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Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the IRF algorithm. It optimizes feature importance weights during training and improves the model's ability to detect intrusions in cloud environments accurately. The proposed detection model is implemented in Python software. In the findings assessment phase, we effectively assessed the performance of our proposed DB-IRF in detecting earthquake incidents across multiple evaluation metrics such as Accuracy (97.5%), Precision (97.96%), F1 Score (98.48%) and Recall (97.85%). We also conducted a comparison analysis with other conventional methodologies. Our experimental results demonstrate the capability and reliability of the recommended framework.

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Optimal UAV Deployment for Data Collection in Deadline-based IoT Applications
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The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Thu Aug 01 2024
Journal Name
Electronics
A Survey: Security Vulnerabilities and Protective Strategies for Graphical Passwords
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As technology advances and develops, the need for strong and simple authentication mechanisms that can help protect data intensifies. The contemporary approach to giving access control is through graphical passwords comprising images, patterns, or graphical items. The objective of this review was to determine the documented security risks that are related to the use of graphical passwords, together with the measures that have been taken to prevent them. The review was intended to present an extensive literature review of the subject matter on graphical password protection and to point toward potential future research directions. Many attacks, such as shoulder surfing attacks, SQL injection attacks, and spyware attacks, can easily ex

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
Impact of Anchored CFRP Composites on the Strengthening of Partially Damaged PC Girders
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This manuscript investigated the effect of anchorage CFRP wrapping sheets, bolts, and laminate interlock on increasing the efficiency of flexural strengthening for the post-tension girder using CFRP composites techniques longitudinal laminates at the soffit for partially damaged loss of about 14.3% from its area of prestressed concrete beams, and the impact on restoring the original flexural capacity of PC girder. Mitigating delamination of the soffit of horizontal laminates (CFRP). The texture of the laminate and anchorages influenced the stress of the laminate carbon fiber, the mode of crack propagation and failure, and consequently, the beam's attitude has been investigated in this manuscript. The experimental findi

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Influence of hybrid anchors on externally-bonded FRP laminates used for flexural strengthening
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Publication Date
Wed Jan 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Influence of anchorage systems on externally-bonded CFRP sheets used for flexural strengthening
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Abstract<p>Strengthening with carbon fiber-reinforced polymers (CFRP) has become one of the most significant methods of enhancing the flexural strength of reinforced concrete members. Extensive research has shown that externally-bonded CFRP sheets tend to debond from the soffit of the concrete members at much lower strains, compared with CFRP rupture strain. Different types of anchorage system have been developed to prevent or delay the debonding type failure, which leads to a higher utilisation of the CFRP sheets before failure occurs. This paper summarises some of the most efficient types of anchorage systems that have shown significant enhancement in terms of increasing the flexural bending c</p> ... Show More
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Publication Date
Wed Aug 01 2007
Journal Name
Al-nahrain Journal For Engineering Sciences
Monitoring and Control on Impressed Current Cathodic Protection for Oil Pipelines
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This research is devoted to design and implement a Supervisory Control and Data Acquisition system (SCADA) for monitoring and controlling the corrosion of a carbon steel pipe buried in soil. A smart technique equipped with a microcontroller, a collection of sensors and a communication system was applied to monitor and control the operation of an ICCP process for a carbon steel pipe. The integration of the built hardware, LabVIEW graphical programming and PC interface produces an effective SCADA system for two types of control namely: a Proportional Integral Derivative (PID) that supports a closed loop, and a traditional open loop control. Through this work, under environmental temperature of 30°C, an evaluation and comparison were done for

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Publication Date
Mon Apr 20 2026
Journal Name
Nauchforum
TRANSLATION STRATEGIES OF PHRASEOLOGICAL UNITS FROM ITALIAN INTO RUSSIAN: BASED ON V. ARDONE’S NOVEL THE TRAIN OF CHILDREN
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The translation of phraseological units is among the most challenging tasks in literary translation, as fixed expressions convey denotative, connotative, and cultural meanings that resist full equivalence. This study classifies the strategies employed in the Russian translation of Viola Ardone’s The Train of Children, drawing on the frameworks of Vinay and Darbelnet, Newmark, and Koller. Analysis of 37 idioms reveals five strategies, with phraseological equivalence prevailing, while compensation—though less frequent—emerges as stylistically most significant.

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