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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
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
Image Segmentation for Skin Detection
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Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Wed Dec 13 2023
Journal Name
2023 3rd International Conference On Intelligent Cybernetics Technology & Applications (icicyta)
GPT-4 versus Bard and Bing: LLMs for Fake Image Detection
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The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

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Publication Date
Tue Jan 17 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Image Feature Extraction to Generate a Key for Encryption in Cyber Security Medical Environments
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Cyber security is a term utilized for describing a collection of technologies, procedures, and practices that try protecting an online environment of a user or an organization. For medical images among most important and delicate data kinds in computer systems, the medical reasons require that all patient data, including images, be encrypted before being transferred over computer networks by healthcare companies. This paper presents a new direction of the encryption method research by encrypting the image based on the domain of the feature extracted to generate a key for the encryption process. The encryption process is started by applying edges detection. After dividing the bits of the edge image into (3×3) windows, the diffusions

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Evaluation the Safety and Security Procedures used In X-ray Clinics in Al-Harthiya-Baghdad
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Abstract<p>Radiation is a form of energy, its emitted either in the form of particles such as α-particles and β-particles (beta particles including the electron and the positron) or waves such as sunlight, X-rays and γ-rays. Radiation found everywhere around us and it comes from many different sources naturally or man-made sources. In this study a questionnaire was distributed to people working in the field of X-rays that used for a medical imaging (X-ray and CT-scan) to evaluate the extent of awareness and knowledge in estimate the damage of ionizing radiation as a result of wrong use. The questionnaire was distributed to medical clinics in Al-Harithiya in Baghdad, which it’s considered as</p> ... Show More
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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Importance of Strategic Orientation Dimensions in the Iraqi National Security Service: An Analytical Study
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The current research aims to identify the level of strategic orientation and its dimensions (vision, mission, goals, and values) in the Iraqi National Security Service (INSS). The researchers followed the descriptive analytical approach as one of the forms of analysis and organized scientific interpretation to describe a specific phenomenon or problem, adopting the form questionnaire being the main source in collecting data and preparing for this. Based on the program of the Statistical Package of Social Sciences (SPSS 26) to analyze the data and come up with the final research results to identify the opinions of the intended sample on the subject of research, and the questionnaire of (20) paragraphs included the search variable, and was

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The use of water resources in light of the challenges of water security in Iraq
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Iraq suffers from lack of water resources supply because the headwaters of the rivers located outside its borders and the influence of upstream countries on the quantities of flowing water, in addition to the increase of pressure on available water as a result of population increase and not adopting the principle of rationalization where misuse and wastage and lack of strategic vision to treat and manage water use in accordance with the economic implications fall.  This is reflected fallout on water security and subsequently on national and food security, while the issue of using water resources is development top priority in different countries in the world because of the importance of water effect on the security of indivi

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Advanced Research In Dynamical And Control Systems
A surveyon work flow in service oriented systems
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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
The Investigation of Monitoring Systems for SMAW Processes
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The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non

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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Slab-beam Interaction in One-way Floor Systems
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This study focuses on the slab-beam interaction in one-way systems. In the context of this study, slab-beam interaction means how beam deflection can affect moment distribution in one-way slabs. This interaction is usually neglected in the traditional approximate analysis that is adopted in engineering practice and design codes. Slab positive moments have been considered as indicators on the accuracy of approximate methods, as they overestimate negative moments while underestimating positive moments.

After proposing of effecting parameters in slab-beam interaction including of panel length and width, beam dimensions, and slab thickness, Buckingham’s  theorem has been adopted to transform the dimensional-mo

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