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Cladding Modified Fiber Bragg Grating for Copper Ions Detection
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This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed a good response in terms of significant wavelength shift in corresponding to varying Cu2+ concentrations when immersed in aqueous mediums. The sensors exhibited excellent repeatability towards Cu ions.The results demonstrate that the smaller FBG etching diameter, the better optical response in terms of wavelength and linearity. 

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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Scopus
Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Detection Of Candida Albicans Responsible For Vulvovaginitis In Women
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Background: The vaginal microbial ecosystem stability preclude many other organisms but sometimes the vaginal micro biota is disturbed and this cause change in the normal

balance causing symptoms of vulvuvaginitis like abnormal or increased vaginal discharge, redness and itching.

Objective: To prove C. albicans presence in their vagina clinically and laboratory by culture of vaginal swab on two media.

Type of the study: This study is a case control study

Methods: This study is a case control study in which 100 clinically patient women admitted to maternity hospital in kalar city and khanaqin hospital during the pe

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Publication Date
Sat Dec 01 2018
Journal Name
Digest Journal Of Nanomaterials And Biostructures
Nanostructured silicon trapping for single Escherichia coli bacteria detection
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The detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed

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Scopus
Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Nano Fluid Detection for HPHE System Using Different Lasers
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Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe

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Publication Date
Sun Oct 15 2023
Journal Name
Journal Of Yarmouk
Artificial Intelligence Techniques for Colon Cancer Detection: A Review
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Wed Jan 01 2020
Journal Name
Technology Reports Of Kansai University
Modified Robust AES Architecture
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Data security is a fundamental parameter on communication system development. The capability of protecting and securing the information is a great essence for the growth of the data security and electronic commerce. The cryptography has a significant influence upon information security systems against the variety of the attacks, in which higher complexity in secret keys results in the increase of security and the cryptography algorithms’ complexity. The sufficient and newer cryptographic methods’ versions may helpful in the reduction of the security attacks. The main aim of this research is satisfying the purpose of the information security through the addition of a new security level to the Advanced Encryption Standard (AES) algorithm

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Publication Date
Thu Oct 22 2020
Journal Name
2020 4th International Symposium On Multidisciplinary Studies And Innovative Technologies (ismsit)
Artificial Intelligence in Smart Agriculture: Modified Evolutionary Optimization Approach for Plant Disease Identification
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