9 results match your criteria: "Sreenivasa Institute of Technology and Management Studies[Affiliation]"

In robotic arm controllers, the ability to shift signal levels is crucial for interfacing between different voltage domains in a processor. The level shifter (LS) has been used to convert signals operating near threshold voltage to signals operating well above the threshold voltage. Researchers have developed current mirror-based LSs to employ current mirrors, which duplicate the current from one transistor and accurately replicate it in another, ensuring precise current matching.

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Article Synopsis
  • Deep Learning (DL) models are being effectively used to analyze MRI scans for Alzheimer's Disease (AD), leveraging Cloud Computing to manage computational demands.
  • The article provides a systematic tutorial on medical imaging datasets, presenting a case study that compares three DL models: Convolutional Neural Networks (CNN), Visual Geometry Group 16 (VGG-16), and an ensemble approach for AD MRI classification.
  • Results indicate that CNN achieved the highest accuracy at 99.285%, while VGG-16 and the ensemble model scored lower, emphasizing the effectiveness of the proposed cloud-based framework for secure and efficient medical image processing.
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Integrating deep learning techniques for effective river water quality monitoring and management.

J Environ Manage

November 2024

Institute of Environmental Engineering, National Sun Yat-Sen University, Kaohsiung, 804, Taiwan; Center for Emerging Contaminants Research, National Sun Yat-Sen University, Kaohsiung, 804, Taiwan; The International University of Management, Centre for Environmental Studies, Main Campus, Dorado Park Ext 1, Windhoek, Namibia; Destinies Biomass Energy and Farming Pty Ltd, P.O. Box 7387, Swakopmund, Namibia. Electronic address:

Effective river water quality monitoring is essential for sustainable water resource management. In this study, we established a comprehensive monitoring system along the Kaveri River, capturing real-time data on multiple critical water quality parameters. The parameters collected encompassed water contamination levels, turbidity, pH measurements, temperature, and total dissolved solids (TDS), providing a holistic view of river water quality.

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Accurately estimating Battery State of Charge (SOC) is essential for safe and optimal electric vehicle operation. This paper presents a comparative assessment of multiple machine learning regression algorithms including Support Vector Machine, Neural Network, Ensemble Method, and Gaussian Process Regression for modelling the complex relationship between real-time driving data and battery SOC. The models are trained and tested on extensive field data collected from diverse drivers across varying conditions.

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The distorted Born iterative (DBI) method is considered to obtain images with high-contrast and resolution. Besides satisfying the Born approximation condition, the frequency-hopping (FH) technique is necessary to gradually update the sound contrast from the first iteration and progress to the actual sound contrast of the imaged object in subsequent iterations. Inspired by the fact that the higher the frequency, the higher the resolution.

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Tin oxide (SnO ) nanocrystalline powders doped with erbium ion (Er ) in different molar ratios (0, 3, 5, and 7 mol%) were prepared using a solid-state reaction technique. These samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), ultraviolet-visible absorption, visible upconversion, and near-infrared luminescence techniques. XRD analysis revealed the tetragonal rutile structure of SnO and the average crystallite size was about 32 nm.

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Synergistic effects of Mg doping on TiOfor improved toxic gas sensing performance at room temperature.

J Phys Condens Matter

September 2023

Department of Physics, Sreenidhi University, Ghatkesar, Hyderabad, Telangana 501301, India.

The gas sensing characteristics of magnesium (Mg)-doped titanium dioxide (TiO) films were investigated using a spray pyrolysis method. TiOThin films with varying Mg doping concentrations (0, 2.5, and 5 weight percentages) were deposited and tested for their gas detection ability to organic compounds such as ethanol, butanol, toluene, xylene, and formaldehyde at room temperature.

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In recent years, both machine learning and computer vision have seen growth in the use of multi-label categorization. SMOTE is now being utilized in existing research for data balance, and SMOTE does not consider that nearby examples may be from different classes when producing synthetic samples. As a result, there can be more class overlap and more noise.

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Extensive quantum chemical calculation have been carried out to investigate the Fourier Transform Infrared(FT-IR), Fourier Transform Raman(FT-RAMAN) and Nuclear magnetic resonance(NMR), and Ultra Violet-Visible(UV-vis) spectra of 2-(4-Cyanophenylamino) acetic acid. The molecular structure, fundamental vibrational frequencies and intensities of the vibrational bands were interpreted with the aid of optimizations and normal coordinate force field calculations based on density functional theory (DFT) and ab initio HF methods with 6-311++G(d,p) basis set. The theoretical vibrational wavenumbers are compared with the experimental values.

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