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White Light Generation from Electroluminescence Devices Using TPD:PMMA/QDs/Alq<sub>3</sub>
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Quantum dots of CdSe, CdS and ZnS QDs were prepared by chemical reaction and used to fabricate organic quantum dot hybrid junction device. QD-LEDs were fabricated using layers of ITO/TPD: PMMA/CdSe/Alq3, ITO/TPD: PMMA/CdS/Alq3 and ITO/TPD: PMMA/ZnS/Alq3 devices which prepared by phase segregation method. The hybrid white light emitting devices consists, of three-layers deposited successively on the ITO glass substrate; the first layer was of N, N’-bis (3-methylphenyl)-N, N’-bis (phenyl) benzidine (TPD) polymer mixed with polymethyl methacrylate (PMMA) polymers. The second layer was QDs while the third layer was tris (8-hydroxyquinoline) aluminium (Alq3). The results of the optical properties show that the prepared QDs were nanocrystalline with defects formation. The calculated of energy gaps from photoluminescence (PL) spectrometer were 2.38, 2.69 and 3.64 eV for CdSe, CdS and ZnS respectively. The generated white light has acceptable efficiency using confinement effect which makes the energy gap larger, so that the direction of the light sites are toward the center of white light color. The hybrid junction devices (EL devices) were characterized by room temperature PL and electroluminescence (EL). Current-voltage (I–V) characteristics indicate that the output current is good compared to the few voltages ( 8-10.3 V) used which gives acceptable results to get a generation of white light. The EL spectrum reveals a broad emission band covering the range from 350 - 700 nm. The emissions causing this white luminescence were identified depending on the chromaticity coordinates (CIE 1931). The correlated color temperature (CCT) was found to be about 6250, 5310 and 5227K respectively. Fabrication of EL-devices from semiconductors material (CdSe, CdS and ZnS QDs) with hole injection organic polymer (TPD) and electron injection from organic molecules (Alq3) was effective in white light generation

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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Publication Date
Fri Feb 28 2020
Journal Name
Iraqi Journal Of Agricultural Sciences (ijas)
PHYTOTOXICITY TEST OF KEROSENE-CONTAMINATED SOIL USING BARLEY
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This study was aimed to determine a phytotoxicity experiment with kerosene as a model of a total petroleum hydrocarbon (TPHs) as Kerosene pollutant at different concentrations (1% and 6%) with aeration rate (0 and 1 L/min) and retention time (7, 14, 21, 28 and 42 days), was carried out in a subsurface flow system (SSF) on the Barley wetland. It was noted that greatest elimination 95.7% recorded at 1% kerosene levels and aeration rate 1L / min after a period of 42 days of exposure; whereas it was 47% in the control test without plants. Furthermore, the percent of elimination efficiencies of hydrocarbons from the soil was ranged between 34.155%-95.7% for all TPHs (Kerosene) concentrations at aeration rate (0 and 1 L/min). The Barley c

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Risk Assessment in BOT Contracts using AHP Technique
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The process of risk assessment in the build-operate transfer (BOT) project is very important to identify and analyze the risks in order to make the appropriate decision to respond to them. In this paper, AHP Technique was used to make the appropriate decision regarding response to the most prominent risks that were generated in BOT projects, which includes a comparison between the criteria for each risk as well as the available alternatives and by mathematical methods using matrices to reach an appropriate decision to respond to each risk.Ten common risks in BOT contracts are adopted for analysis in this paper, which is grouped into six main risk headings.The procedures followed in this paper are the questionnaire method

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Fri Jan 01 2016
Journal Name
Bio-inspired Computing – Theories And Applications
Image Segmentation Using Membrane Computing: A Literature Survey
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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 duri

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Publication Date
Sun Mar 30 2025
Journal Name
Iraqi Journal Of Science
Segmentation of Aerial Images Using Different Clustering Techniques
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The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

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Publication Date
Sun Nov 01 2020
Journal Name
Iraqi Journal Of Laser
Urinary Tract Lithotripsy Using Holmium: YAG (2100nm) Laser
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Background: Laser urinary stone lithotripsy is an established endourological modality. Ho:YAG(2100nm) laser have broadened  the indications for ureteroscopic stone managements  to include larger stone sizes throughout the whole urinary tract.

Purpose: To evaluate the effectiveness and safety of Holmium: YAG(2100nm) laser lithotripsy with a semirigid uretero scope for urinary stone calculi in a prospective cohort of 17 patients.

Patients and Methods: Holmium: YAG(2100nm) laser lithotripsy was performed with a semirigid ureteroscope in 17 patients from September 2016 to December  2016. Calculi were located in the lower ureter in 9 patients (52.9%), the midure

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Publication Date
Mon Jan 01 2018
Journal Name
Engineering And Technology Journal
Text File Hiding Randomly Using Secret Sharing Scheme
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Exchange of information through the channels of communication can be unsafe. Communication media are not safe to send sensitive information so it is necessary to provide the protection of information from disclosure to unauthorized persons. This research presented the method to information security is done through information hiding into the cover image using a least significant bit (LSB) technique, where a text file is encrypted using a secret sharing scheme. Then, generating positions to hiding information in a random manner of cover image, which is difficult to predict hiding in the image-by-image analysis or statistical analyzes. Where it provides two levels of information security through encryption of a text file using the secret sha

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