Browsing by Author "Ajith, A."

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    Analysis of Selected Binarization Techniques for Brain Tumor Magnetic Resonance Images
    (Institute of Electrical and Electronics Engineers Inc., 2023) Kumar, A.; Ajith, A.; Bhowmik, B.
    The identification and therapy of brain tumors have greatly improved as a result of recent developments in the field of medical imaging. Among the different imaging techniques, magnetic resonance imaging (MRI) is essential for identifying and describing brain tumors. However, accurately segmenting tumor regions from MRI scans remains a persistent challenge due to tumors' complex and diverse appearances. To address this challenge, extensive evaluation of novel approaches and comparative analysis of existing methods are essential to unlock the potential of binarization techniques. This paper presents the transformative capacity of binarization techniques in elevating overall brain tumor management. We select a set of binarization techniques for MRIs. The methods are implemented to find a better approach that can be employed for better segmentation and detection of brain tumors from the input MRI dataset. Consequently, we propose an alternative binarization technique. Through precise and personalized healthcare interventions, the proposed approach holds promise for enhancing patient outcomes and improving the quality of life for individuals affected by brain tumors. © 2023 IEEE.
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    Effect of pressure on the band structure of BC3
    (American Institute of Physics Inc. subs@aip.org, 2016) Manju, M.S.; Harikrishnan, H.; Ajith, A.; Valsakumar, M.C.
    Density functional theory (DFT) calculations were carried out to study the effect of pressure on the band structure of two dimensional BC3 sheet. BC3 is a semiconductor at ambient conditions having a band gap of ~0.3 eV. Electronic structure calculations are carried out on BC3 at pressures of 5, 20, 50 and 100 GPa. The system shows a semiconductor - metal transition by the application of pressure without any structural transition. © 2016 Author(s).
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    Machine learning and DFT investigation of CO, CO2 and CH4 adsorption on pristine and defective two-dimensional magnesene
    (Royal Society of Chemistry, 2023) Thomas, S.; Mayr, F.; Ajith, A.; Gagliardi, A.
    Adsorption study of environmentally toxic small gas molecules on two-dimensional (2D) materials plays a significant role in analyzing the performance of sensors. In this work, density functional theory (DFT) and machine learning (ML) techniques have been employed to systematically study the adsorption properties of CO, CO2, and CH4 gas molecules on the pristine and defective planar magnesium monolayer, known as magnesene (2D-Mg). The DFT analysis showed that mechanically robust 2D-Mg retains its metallicity in the presence of both mono and di-vacancy defects. Our observations have shown that 2D-Mg, whether defective or pristine, exhibits distinct adsorption behaviors towards CO, CO2, and CH4 gas molecules, including varying chemisorption and physisorption, charge transfer, and distance from the gas molecules. When analyzing the recovery time of gas molecules at room temperature, it is clear that adsorption energy has a direct correlation with the adsorption-desorption cycles, and CH4 possesses an ultra-low recovery time (15.27 ps) compared to CO2 (1.04 ns) and CO (0.90 μs) molecules. The analysis showed that defects do not have a significant impact on the work function of 2D-Mg. However, the work function decreased upon adsorption of CH4, resulting in improved sensitivity due to changes in the electronic properties. Additionally, we explored supervised ML regression models to evaluate their ability to act as a surrogate for the DFT-based adsorption energy calculation. Using both system statistics and smooth overlap of atomic position (SOAP)-based featurization, we observed that adsorption energies can be predicted with a mean absolute error of 0.10 eV. © 2023 The Royal Society of Chemistry.
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    Structural analysis of graphene and h-BN: A molecular dynamics approach
    (American Institute of Physics Inc. subs@aip.org, 2016) Thomas, S.; Ajith, A.; Valsakumar, M.C.
    Classical molecular dynamics simulation is employed to analyze pair correlations in graphene and h-BN at various temperatures to explore the integrity of their respective structures. As the temperature increases, the height fluctuations in the out-of-plane direction of both graphene and h-BN are found to increase. The positional spread of atoms also increases with temperature. Thus the amplitude of the peak positions in the radial distribution function (RDF) decreases with temperature. It is found that FWHM of peaks in the RDF of h-BN is smaller as compared to those of graphene which implies that the structure of h-BN is more robust as compared to that of graphene with respect to their respective empirical potential. © 2016 Author(s).
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    Structural and magnetic studies of tin doped α-Fe2O3 (α-SnxFe2-xO3) nanoparticles prepared by microwave assisted synthesis
    (American Institute of Physics Inc. subs@aip.org, 2016) Bindu, K.; Chowdhury, P.; Ajith, A.; Nagaraja, H.S.
    Hematite (α-Fe2O3) doped with tetravalent ions have potential applications in various fields such as gas sensors, memories, energy storage devices because of their electrical and magnetic properties. Microwave assisted synthesis was used to prepare Tin doped α-Fe2O3 [α-SnxFe2-xO3]. The structural and morphological studies were investigated using X-ray diffraction (XRD) and Scanning electron microscopy (SEM). XRD patterns revealed that α-Fe2O3 and α-SnxFe2-xO3 were having rhombohedral structure. The compositional study was done by Energy dispersive X-ray Spectroscopy (EDS). The magnetic properties were studied by Vibrating Sample Magnetometry (VSM). Results shows that the prepared samples were found to be antiferromagnetic in nature and the results are discussed in detail. © 2016 Author(s).
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    Young's modulus of defective graphene sheet from intrinsic thermal vibrations
    (Institute of Physics Publishing helen.craven@iop.org, 2016) Thomas, S.; Mrudul, M.S.; Ajith, A.; Valsakumar, M.C.
    Classical molecular dynamics simulations have been performed to establish a relation between thermally excited ripples and Young's modulus of defective graphene sheet within a range of temperatures. The presence of the out-of-plane intrinsic ripples stabilizes the graphene membranes and the mechanical stability is analyzed by means of thermal mean square vibration amplitude in the long wavelength regime. We observed that the presence of vacancy and Stone-Wales (SW) defects reduces the Young's modulus of graphene sheets. Graphene sheet with vacancy defects possess superior Young's modulus to that of a sheet with Stone-Wales defects. The obtained room temperature Young's modulus of pristine and defective graphene sheet is ∼ 1 TPa, which is comparable to the results of earlier experimental and atomistic simulation studies. © Published under licence by IOP Publishing Ltd.