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Nile red based dye D–π–A as a promising material for solar cell applications
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A recently reported Nile red (NR) dye conjugated with benzothiadiazole species paves the way for the development of novel organic-based sensitizers used in solar cells whose structures are susceptible to modifications. Thus, six novel NR structures were derived from two previously developed structures in laboratories. In this study, density functional theory (DFT) calculations and time-dependent DFT (TD-DFT) were used to determine the optoelectronic properties of the NR-derived moieties such as absorption spectra. Various linkers were investigated in an attempt to understand the impact of π-linkers on the optoelectronic properties. According to the findings, the presence of furan species led to the planarity of the molecule and a reduction in the band gap between the LUMO and the HOMO. Each one of the aforementioned molecules exhibited great delocalization of π-electrons. Based on the TD-DFT calculations, two furans had the highest value for the red-shift. There is an excellent correlation observed between the computed optoelectronic properties and calculated HOMO-LUMO gaps. In conclusion, the current work aimed at clarifying the impact of π-linkers on the photophysical properties of the NR-derived moieties. Also, the current study provided useful insights into the development of novel species used in optoelectronic devices.

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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
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
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PC-Based Controller for Shell and Tube Heat Exchanger
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PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Symlet Analysis for ECG-Based Diagnosis of Heart Dysfunction
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
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Publication Date
Tue Jul 14 2020
Journal Name
Baghdad Science Journal
The Green Synthesize of Zinc Oxide Catalyst Using Pomegranate Peels Extract for the Photocatalytic Degradation of Methylene Blue Dye
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In this study, the zinc oxide NPs have been synthesized from the fresh pomegranate peels extract using the precipitation method. The ZnO nanoparticles were produced from the reaction of fresh peels extract with zinc acetate salt which was used as zinc source in the presence of 2 M NaOH. The green synthesized nanoparticles were characterized through X-ray diffraction (XRD), UV-Vis diffuse reflection spectroscopy, Fourier transform infrared spectroscopy (FTIR), and Atomic force microscopy (AFM). The XRD patterns confirm the formation of hexagonal wurtzite phase structure for ZnO synthesized using pomegranate peels extract with average crystalline size of 28 nm. FTIR spectra identify the presence of many active functional groups for the pom

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Publication Date
Fri Jul 12 2024
Journal Name
Biomass Conversion And Biorefinery
Chitosan-triphosphate/food grade algae/montmorillonite clay for adsorptive removal of methyl violet 2B dye removal: Behnken design optimization
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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Evaluation Microstructure and the Mechanical Properties of Composite Material for Al-Matrix Reinforced by Ceramic Materials (Sic And Al2O3)
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In this investigation, the mechanical properties and microstructure of Metal Matrix Composites (MMCs) of Al.6061 alloy reinforced by ceramic materials SiC and Al2O3 with different additive percentages 2.5, 5, 7.5, and 10 wt.% for the particle size of 53 µm are studied. Metal matrix composites were prepared by stir casting using vortex technique and then treated thermally by solution heat treatment at 530 0C for 1 hr. and followed by aging at 175 0C with different periods. Mechanical tests were done for the samples before and after heat treatment, such as impact test, hardness test, and tensile test. Also, the microstructure of the metal matrix composites was examine

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Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
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Scopus (45)
Crossref (29)
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