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PANI/MWCNT based humidity sensor
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Polyaniline Multi wall Carbon nanotube (PANI/MWCNTs) nanocomposite thin films have been prepared by Plasma jet polymerization at low frequency on glass substrate with preliminary deposited aluminum electrodes to form Al/PANI-MWCNT/Al surface-type capacitive humidity sensors, the gap between the electrodes about 50 μm and the MWCNTs weight concentration varied between 0, 1, 2, 3, 4%. The diameter of the MWCNTs was in the range of 8-15 nm and the length 10-55 μm. The capacitance-humidity relationships of the sensors were investigated at humidity levels from 35 to 90% RH. The electrical properties showed that the capacity increased with increasing relative humidity, and that the sensitivity of the sensor increases with the increase of the additive (MWCNTs); while each of the response time and the recovery time increasing with concentration. The change in MWCNTs concentration leads to a change in the energy gap as well as the initial capacity. The capacitance increases linearly with the relative humidity at MWCNTs concentration of 3% for thus the possibility of manufacturing humidity sensor with good specifications at this concentration.

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Electronic Security And Digital Forensics
LSB based audio steganography preserving minimum sample SNR
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Publication Date
Sat Jul 31 2021
Journal Name
Brain Sciences
Robust EEG Based Biomarkers to Detect Alzheimer’s Disease
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Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
EMG-Based Control of Active Ankle-Foot Prosthesis
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 Most below-knee prostheses are manufactured in Iraq without considering the fast progress in smart prostheses, which can offer movements in the desired directions according to the type of control system designed for this purpose. The proposed design appears to have the advantages of simplicity, affordability, better load distribution, suitability for subjects with transtibial amputation, and viability in countries with people having low socio-economic status. The designed prosthetics consisted of foot, ball, and socket joints, two stepper motors, a linkage system, and an EMG shield. All these materials were available in the local markets in Iraq. The experimental results showed t

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Publication Date
Thu Dec 01 2022
Journal Name
Al-khwarizmi Engineering Journal
BCI-Based Smart Room Control using EEG Signals
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In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model during di

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Publication Date
Tue Jul 31 2012
Journal Name
Journal Of Babylon University/pure And Applied Sciences/
An Evaluation of the Effect of Bleaching Agent on Microhardness of a New Silorane-Based Restorative System and Methacrylate-Based Restorative Material
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Abstract Rasha Hameid Jehad Baghdad University Background: The high reactivity of hydrogen peroxide used in bleaching agents have raised important questions on their potential adverse effects on physical properties of restorative materials. The purpose of this in vitro study was to evaluate the effect of in-office bleaching agents on the microhardness of a new Silorane-based restorative material in comparison to methacrylate-based restorative material. Materials and method: Forty specimens of Filtek™ P90 (3M ESPE,USA) and Filtek™ Supreme XT (3M ESPE, USA) of (8mm diameter and 3m height) were prepared. All specimens were polished with Sof-Lex disks (3M ESPE, USA). All samples were rinsed and stored in incubator 37˚C for 24 ho

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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF Study the Effect of Gold Film Thickness on the Sensitivity of the U Shape Fiber Sensor by the Occurrence of LSPR Phenomenon: Saffana Z. Maseer*, Bushra R. Mahdi
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Abstract: In this paper, a U-shaped probe with a curvature diameter of half a centimeter was implemented using plastic optical fibers. A layer of the outer shell of the fibers was removed by polishing to a D-section. The sensor was tested by immersing it in a sodium chloride solution with variable refractive index depending on solution concentrations ranging from 1.333 to 1.363. In this design, the sensor experienced a decrease in its intensity as the concentration of the solution increased. The next step The sensor was coated with a thin layer of gold with a thickness of 20 nm, and the sensor was tested with the same solutions which resulted in a shift in wavelengths where the shift in wavelength was 5.37 nm and sensiti

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Publication Date
Fri Dec 31 2010
Journal Name
International Journal Of Advancements In Computing Technology
A proposed Technique for Information Hiding Based on DCT
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The aim of this work is to design an algorithm which combines between steganography andcryptography that can hide a text in an image in a way that prevents, as much as possible, anysuspicion of the hidden textThe proposed system depends upon preparing the image data for the next step (DCT Quantization)through steganographic process and using two levels of security: the RSA algorithm and the digitalsignature, then storing the image in a JPEG format. In this case, the secret message will be looked asplaintext with digital signature while the cover is a coloured image. Then, the results of the algorithmare submitted to many criteria in order to be evaluated that prove the sufficiency of the algorithm andits activity. Thus, the proposed algorit

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Publication Date
Fri Sep 15 2017
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Graph-Based Text Representation: A Survey of Current Approaches
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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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