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3. Speckle interferometric investigation of argon pressure-induced surface roughness modifications in RF-sputtered MoO[sub]3 filmS. Soumya, R. Arun Kumar, Sankararaman Sreejyothi, Vimal Raj, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2021, original scientific article Abstract: Film quality analysis is of more considerable signifcance due to its diversifed applications in various felds of technology.
The present work reports the speckle interferometric analysis of the argon pressure-induced surface roughness modifcations
of RF sputtered MoO3 flms. The paper suggests a new method of surface quality analysis of thin flms through a parameter
δ, which is the diference between the initial and fnal inertia moment values in the study of the thermal-induced dynamic
speckle pattern. The limitations of root mean square surface roughness analysis of the atomic force microscopic image of the
flms is also exemplifed. The research suggests that argon pressure plays a vital role in the surface property of RF sputtered
flms and also that the dynamic speckle analysis can give precise information about the quality of flms. The contour plot of
particle displacement vector under thermal stress, suggests the degree of uniformity in the distribution of particles in the flm.
Keywords: speckle pattern interferometry, time history of speckle pattern, cross correlation, inertia moment
Published in RUNG: 04.07.2022; Views: 2716; Downloads: 0
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4. Is SARS CoV-2 a multifractal? : unveiling the fractality and fractal structureMohanachandran Nair Sindhu Swapna, Sankararaman Sreejyothi, Vimal Raj, Sankaranarayana Iyer Sankararaman, 2021, original scientific article Abstract: A first report of unveiling the fractality and fractal nature of severe acute respiratory syndrome coronavirus (SARS CoV-2)
responsible for the pandemic disease widely known as coronavirus disease 2019 (COVID 19) is presented. The fractal analysis of
the electron microscopic and atomic force microscopic images of 40 coronaviruses (CoV), by the normal and differential box-counting method, reveals its fractal structure. The generalised dimension indicates the multifractal nature of the CoV. The higher
value of fractal dimension and lower value of Hurst exponent (H) suggest higher complexity and greater roughness. The
statistical analysis of generalised dimension and H is understood through the notched box plot. The study on CoV clusters also
confirms its fractal nature. The scale-invariant value of the box-counting fractal dimension of CoV yields a value of 1.820. The study opens the possibility of exploring the potential of fractal analysis in the medical diagnosis of SARS CoV-2.
Keywords: Fractality, SARS CoV, Coronavirus, Fractal dimension, Multifractal
Published in RUNG: 30.06.2022; Views: 2825; Downloads: 0
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5. Time series and fractal analyses of wheezing : a novel approachMohanachandran Nair Sindhu Swapna, Ammini Renjini, Vimal Raj, Sankararaman Sreejyothi, Sankaranarayana Iyer Sankararaman, 2020, original scientific article Abstract: Since the outbreak of the pandemic Coronavirus Disease 2019, the world is in search of novel non-invasive methods for safer
and early detection of lung diseases. The pulmonary pathological symptoms refected through the lung sound opens a possibility of detection through auscultation and of employing spectral, fractal, nonlinear time series and principal component
analyses. Thirty-fve signals of vesicular and expiratory wheezing breath sound, subjected to spectral analyses shows a clear
distinction in terms of time duration, intensity, and the number of frequency components. An investigation of the dynamics
of air molecules during respiration using phase portrait, Lyapunov exponent, sample entropy, fractal dimension, and Hurst
exponent helps in understanding the degree of complexity arising due to the presence of mucus secretions and constrictions
in the respiratory airways. The feature extraction of the power spectral density data and the application of principal component analysis helps in distinguishing vesicular and expiratory wheezing and thereby, giving a ray of hope in accomplishing
an early detection of pulmonary diseases through sound signal analysis.
Keywords: auscultation, wheeze, fractals, nonlinear time series analysis, sample entropy
Published in RUNG: 30.06.2022; Views: 2792; Downloads: 0
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6. Downscaling of sample entropy of nanofluids by carbon allotropes : a thermal lens studyMohanachandran Nair Sindhu Swapna, Vimal Raj, Sankararaman Sreejyothi, K. Satheesh Kumar, Sankaranarayana Iyer Sankararaman, 2020, original scientific article Abstract: The work reported in this paper is the first attempt to delineate the molecular or particle dynamics from the thermal lens signal of carbon allotropic nanofluids (CANs), employing time series and fractal analyses. The nanofluids of multi-walled carbon nanotubes and graphene are prepared in base fluid, coconut oil, at low volume fraction and are subjected to thermal lens study. We have studied the thermal diffusivity and refractive index variations of the medium by analyzing the thermal lens (TL) signal. By segmenting the TL signal, the complex dynamics
involved during its evolution is investigated through the phase portrait, fractal dimension, Hurst exponent, and sample entropy using time series and fractal analyses. The study also explains how the increase of the photothermal energy turns a system into stochastic and anti-persistent. The sample entropy (S) and refractive index analyses of the TL signal by segmenting into five regions reveal the evolution of S with the increase of enthalpy. The lowering of S in CAN along with its thermal diffusivity (50%–57% below) as a result of heat-trapping suggests
the technique of downscaling sample entropy of the base fluid using carbon allotropes and thereby opening a novel method of improving the efficiency of thermal systems.
Keywords: carbon allotropic nanofluids, time series, entropy, MWCNT, thermal lens signal
Published in RUNG: 30.06.2022; Views: 2828; Downloads: 0
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