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Accelerated charging of PCM in coil heat exchangers via central return tube and inlet positioning: A 3D analysis
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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Enhancement of Hydrothermally Co3O4 Thin Films as H2S Gas Sensor by Loading Yttrium Element
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The gas sensing properties of Co3O4 and Co3O4:Y nano structures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for Co3O4 and Co3O4:Y thin films. XRD analysis shows that all films are polycrystalline in nature, having a cubic structure, and the crystallite size is (11.7)nm for cobalt oxide and (9.3)nm for the Co3O4:10%Y. The SEM analysis of thin films obviously indicates that Co3O4 possesses a nanosphere-like structure and a flower-like structure for Co3O4:Y.

The sen

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Publication Date
Mon Jan 29 2024
Journal Name
Proceedings Of The International Conference On Research Advances In Engineering And Technology - Itechcet 2022
Effect of length to diameter ratio on column bearing capacity stabilized with sodium silicate
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The numerical analysis was conducted to studying the influence of length to diameter ratio (L/D) on the behavior of the soil treated with sand columns treated with 8% sodium silicate for both floating and end bearing type by using finite element method (Plaxis 3D Foundation ) for isolated foundation of real dimensions. The analysis’s study indicate that in the floating type the best improvement ratio was achieved at (L/D=8) when using columns with a diameter of (0.5, 0.7), but when using columns with a diameter of 0.3 m, it was noticed that the bearing improvement ratio increases with increasing (L/d). While the results of the analysis for end bearing type show that the higher improvement ratio was achieved at (L/D=4) when using columns w

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Publication Date
Mon Mar 18 2019
Journal Name
Al-khwarizmi Engineering Journal
Effect of optimal shot peening time on fatigue life for aluminum alloy 6061-T651
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The compressive residual stresses generated by shot peening, is increased in a direct proportional way with shot peening time (SPT). For each metal, there is an optimum shot peening time (O.S.T) which gives the optimum fatigue life. This paper experimentally studied to optimize shot peening time of aluminium alloy 6061-T651 as well as using of and analysis of variance (ANOVA).

Two types of fatigue test specimens’ configuration were used, one without notch (smooth) and the other with a notch radius (1,25mm), each type was shot peened at different time. The (O.S.T) was experimentally estimated  to be 8 minutes reaching the surface stresses at maximum peak of -184.94 MPa.

A response surface methodology (RSM) is presen

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Publication Date
Tue Jun 30 2020
Journal Name
Pakistan Journal Of Phytopathology
PROTECTIVE EFFECT OF OLIVE POLYPHENOLS ON WATERMELON AGAINST FUSARIUM OXYSPORUM F. SP. NIVEUM INFECTION
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Publication Date
Sat Apr 25 2020
Journal Name
Asian Journal Of Agriculture And Biology
Biodegradation of plastic wastes by confused flour beetle Tribolium confusum Jacquelin du Val larvae
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Publication Date
Wed Apr 01 2015
Journal Name
Mathematical Methods In The Applied Sciences
An inverse problem of finding the time-dependent diffusion coefficient from an integral condition
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Publication Date
Sat Mar 01 2025
Journal Name
Journal Of Ecological Engineering
Synthesis of sulfated zirconia-HY zeolite catalysts doped by platinum metal for hydroisomerization reaction
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Detecting the antibacterial activity of green synthesized silver (Ag) nanoparticles functionalized with ampicillin (Amp)
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In the current study, synthesis and characterization of silver nanoparticles (AgNPs) before and after functionalization with ampicillin antibiotic and their application as anti-pathogenic agents towards bacteria were investigated. AgNPs were synthesized by a green method from AgNO3 solution with glucose subjected to microwave radiation. Characterization of the nanoparticles was conducted using UV-Vis spectroscopy, scanning electron microscopy (SEM), zeta potential determination and Fourier transform infrared (FTIR) spectroscopy. From SEM analysis, the typical silver nanoparticle particle size was found to be 30 nm and Zeta potential measurements gave information about particle stability. Analysis of FTIR patterns and UV-VIS spectroscopy con

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Publication Date
Sun Jun 15 2025
Journal Name
Iraqi Journal Of Laser
Performance Enhancement of Metasurface Grating Polarizer Using Deep Learning for Quantum Key Distribution Systems
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

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