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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 on bits are applied to create a key used for encrypting the edge image. Four randomness tests are passed through NIST randomness tests to ensure whether the generated key is accepted as true. This process is reversible in the state of decryption to retrieve the original image. The encryption image that will be gained can be used in any cyber security field such as healthcare organization. The comparative experiments prove that the proposed algorithm improves the encryption efficiency has a good security performance, and the encryption algorithm has a higher information entropy 7.42 as well as a lower correlation coefficient 0.653.

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Fri Oct 25 2013
Journal Name
International Endodontic Journal
Fabrication and characterization of polymer composites for endodontic use
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Aim To develop a low-density polyethylene–hydroxyapatite (HA-PE) composite with properties tailored to function as a potential root canal filling material. Methodology Hydroxyapatite and polyethylene mixed with strontium oxide as a radiopacifier were extruded from a single screw extruder fitted with an appropriate die to form fibres. The composition of the composite was optimized with clinical handling and placement in the canal being the prime consideration. The fibres were characterized using infrared spectroscopy (FTIR), and their thermal properties determined using differential scanning calorimetry (DSC). The tensile strength and elastic modulus of the composite fibres and gutta-percha were compared, dry and after 1 month storage in

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Scientific & Engineering Research
Horizontal Fragmentation for Most Frequency Frequent Pattern Growth Algorithm
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Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.

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Publication Date
Tue Jan 08 2019
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
MANUFACTURING AND ANALYSIS CUSTOM FOOT ORTHOTIC FOR FLEXIBLE FLATFOOT
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This paper presents two main parts: The first part involves manufacturing the specimens form composite material for mechanical testing (tensile, flexural and fatigue tests), then design a custom foot orthesis (CFO) and manufacturing from composite lamination (3nylglass 2carbon fiber 3nylglass) for patient suffer from flexible flat foot since birth and over-pronation. The second part of this research involves a design a model of custom foot orthesis in (solid work 2018) and then analysis of custom foot orthosis in engineering analysis program (ANSYS V.18.2).The applied pressure in boundary condition adopted from Force Sensor Resistance (FSR 402 ) in various regions in foot after wearing composite CFO. Used a composite materials in engineerin

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Scopus (2)
Scopus
Publication Date
Thu Feb 11 2021
Journal Name
Journal Of Legal Sciences
The Consequences of Discovering Pharmaceutical Products for the Researcher
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The process of discovering pharmaceuticals is of great importance in our contemporary life, in a way that without life becomes almost impossible, as this process is the first building block in the field of pharmaceutical industries to search for new methods and means of treatment and treatment. But in fact, the fact that talking about this process is not that simple and easy, because this process is complicated and difficult in a way that makes it take a time range that in some cases reaches what is permissible ten years to reach a chemical formula that can be used later in the manufacturing process Pharmacokinetics, and during this long period of time, this process will have a set of effects, some of which are specific to the researcher di

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Publication Date
Tue Oct 30 2018
Journal Name
Iraqi Journal Of Physics
Synthesized copper nanoparticles by sonoelectrodeposition for gas filter applications
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Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

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Publication Date
Fri Jan 01 2021
Journal Name
Research Methods In Modern Urban Transportation Systems And Networks
Factors Affecting the Choice of Transportation for School Trips
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Scopus Crossref
Publication Date
Sat Nov 01 2014
Journal Name
Glob Dermatol
Podophyllin 25% as alternative effective topical therapy for keratoacanthoma
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KE Sharquie, AA Noaimi, Glob Dermatol, 2014 - Cited by 6

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Fracture Toughness and Hardness studying for Polymer-Ceramic Composite
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A particulate composite material was prepared by adding the Titanium dioxide (TiO2) with a particle size of (75-150) µm to Epoxy resin at weight percentage of (10%,20%,30%,40%,50%).The following some mechanical properties were studied,fracture toughness, hardness.casting preparation methods were used in this study includes preparing plate of matrix and composites. specimens were prepared according to ASTM for the Mechanical properties tests. After that Another samples were heat treated for three and six hour at 65C?. Fracture toughness (Kic) represent for stress intensity factor results were showed that the curve of three hours aging increases in fracture toughness (Kic) for composites but for six hours aging increases fracture tough

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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