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Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion detection systems in the cloud may provide challenges. The pre-established IDS design may overburden a cloud segment due to the additional detection overhead. Within the framework of an adaptively designed networked system. We demonstrate how to fully use available resources without placing undue load on any one cloud server using an intrusion detection system (IDS) based on neural networks. To even more successfully detect new threats, the suggested IDS make use of neural network machine learning (ML).

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Tax audit and examination of electronic accounting information systems: proposed model / Applied research at the General Tax Authority
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Technology is one of the important influences in the development of professions in general and the profession of tax auditing and examination in particular because of the importance of this section in the General Tax Authority because of the service it provides is auditing the financial accounts provided to the department by the taxpayers to ensure the correctness of revenue and the achievement of tax justice. Where the research aims at the importance of using electronic accounting information systems in developing the work of the Tax Audit and Examination Department, to reduce the difficulties that the department may be using using manual systems, which is the need for time and effort to accomplish it, and to develop methods and procedu

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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Relative intensity distribution in the rotational structure for B1Σ+- A1Π and B1Σ+- X1Σ+ electronic systems of BeO molecule
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Theoretical spectroscopic study of  Beryllium Oxide has been carried out, Boltzmann distribution of P, Q and R branches in the range of (0<J<13) at temperature 4200K for (0-0) band for electronic transitions B1Σ+-A1Π and B1Σ-X1Σ. The Boltzmann distribution of these branches has a maximum values at equal J approximately while the values of relative population are different. For the B1Σ+- X1Σ+ transition the branch's lines extend towards lower wavenumber. This is because (Bv'-Bv") value is negative, i.e  Bv'< Bv" For B1Σ+-A1Π

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Publication Date
Wed Jan 01 2020
Journal Name
Arab Journal Of Basic And Applied Sciences
Boundary-domain integral method and homotopy analysis method for systems of nonlinear boundary value problems in environmental engineering
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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Agricult. Stat. Sci.
USE OF GEOGRAPHIC INFORMATION SYSTEMS IN PRODUCTION OF SALT MAPS PREVAILING IN AL-MAIMUNA PROJECT IN SOUTHERN Iraq
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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Laser
Hong-Ou-Mandel Dip Measurements of Two Independent Weak Coherent Pulses for Free Space Quantum Key Distribution Systems
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Preparation of identical independent photons is the core of many quantum applications such as entanglement swapping and entangling process. In this work, Hong-Ou-Mandel experiment was performed to evaluate the degree of indistinguishability between independent photons generated from two independent weak coherent sources working at 640 nm. The visibility was 46%, close to the theoretical limit of 50%. The implemented setup can be adopted in quantum key distribution experiments carried out with free space as the channel link, as all the devices and components used are operative in the visible range of the electromagnetic spectrum.

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Pilgrims tracking and monitoring based on IoT
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Abstract<p>The pilgrimage takes place in several countries around the world. The pilgrimage includes the simultaneous movement of a huge crowd of pilgrims which leads to many challenges for the pilgrimage authorities to track, monitor, and manage the crowd to minimize the chance of overcrowding’s accidents. Therefore, there is a need for an efficient monitoring and tracking system for pilgrims. This paper proposes powerful pilgrims tracking and monitoring system based on three Internet of Things (IoT) technologies; namely: Radio Frequency Identification (RFID), ZigBee, and Internet Protocol version 6 (IPv6). In addition, it requires low-cost, low-power-consumption implementation. The proposed </p> ... Show More
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Publication Date
Fri Jun 18 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Quadtree partitioning scheme of color image based
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Publication Date
Fri Jan 31 2025
Journal Name
Joiv : International Journal On Informatics Visualization
RC5 Performance Enhancement Based on Parallel Computing
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This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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