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Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.

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Publication Date
Tue Dec 09 2025
Journal Name
Petroleum And Coal
Extraction and Analysis of Compressional, Shear, and Stoneley Slowness, Rock Mechanical Properties, and Shear Anisotropy Using Sonic Scanner Data
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The Sonic Scanner is a multifunctional instrument designed to log wells, assess elastic characteristics, and support reservoir characterisation. Furthermore, it facilitates comprehension of rock mechanics, gas detection, and well positioning, while also furnishing data for geomechanical computations and sand management. The present work involved the application of the Sonic Scanner for both basic and advanced processing of oil-well-penetrating carbonate media. The study aimed to characterize the compressional, shear, Stoneley slowness, rock mechanical properties, and Shear anisotropy analysis of the formation. Except for intervals where significant washouts are encountered, the data quality of the Monopole, Dipole, and Stoneley modes is gen

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
The Remediation of Congo Red-Contaminated Groundwater by using a Permeable Reactive Barrier Through Modified Waterworks Sludge MgAl-LDH
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This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions.

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Publication Date
Tue May 27 2025
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
Preparation, kinetics, and thermodynamic investigation of Janus green dye removal from aqueous solutions using MnO2 nanoparticles as an adsorbent
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In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Thu Sep 01 2016
Journal Name
Revista Brasileira De Zootecnia
Effect of using insect larvae meal as a complete protein source on quality and productivity characteristics of laying hens
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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Ground State Structure of Helium and Phosphorus Isotopes using the Radial Wave Functions of Harmonic-Oscillator and Hulthen Potentials
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     The ground state density distributions and electron scattering Coulomb form factors of Helium (4,6,8He) and Phosphorate (27,31P) isotopes are investigated in the framework of nuclear shell model. For stable (4He) and (31P) nuclei, the core and valence parts are studied through Harmonic-oscillator (HO) and Hulthen potentials. Correspondingly, for exotic (6,8He) and (27P) nuclei, the HO potential is applied to the core parts only, while the Hulthen potential is applied to valence parts. The parameters for HO and Hulthen are chosen to reproduce the available experimental size radii for all nuclei under study. Finally, the CO component of electron scattering charge form factors are also investigated. Unfortunately, there is no

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Publication Date
Fri Jan 20 2023
Journal Name
Journal Of Electronic Materials
Influence of Dry and Wet Etching on AlInSb Contact Resistivity, Transfer Length, and Sheet Resistance Using Circular Transmission Model
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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Asphaltene Precipitation Investigation Using a Screening Techniques for Crude Oil Sample from the Nahr-Umr Formation/Halfaya Oil Field
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Many oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Textural Analysis of Functionalized Mesoporous Silica Using Sodium Silicate as Precursor and Silicone Surfactant as Template
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Three mesoporous silica with different functional group were prepared by one-step synthesis based on the simultaneous hydrolysis and condensation of sodium silicate with organo - silane in the presence of template surfactant polydimethylsiloxane - polyethyleneoxide (PDMS - PEO). The prepared materials were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), atomic force microscopy (AFM) and nitrogen adsorption/desorption experiments. The results indicate that the preparation of methyl and phenyl functionalized silica were successful and the mass of methyl and phenyl groups bonded to the silica structure are 15, 38 mmol per gram silica. The average diameter of the silica particles are 103.51,

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Publication Date
Tue Nov 15 2022
Journal Name
Journal Of Mechanical Engineering
Enhancement of Mechanical Properties and Corrosion Resistance of Cast Iron Alloy Using CO<inf>2</inf> Laser Surface Treatment
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This work aimed to study the effect of laser surface treatment on the mechanical characteristics and corrosion behaviour of grey cast iron type A159. Many technical applications used conventional surface treatment, but laser surface hardening has recently been used to enhance the surface properties of many alloys. The mechanical characteristics, including microstructure, microhardness, and wear resistance of A159 grey cast iron, were studied, in addition to corrosion behaviour. The experimental laser parameters in this work were 0.9, 1.2, and 1.5 KW power with continuous wave carbon dioxide lasers with scanning speeds of 10 and 12 mm/s were used. The results found that phase-transitional alterations in microstructure were influenced by lase

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