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1.
Development of prototype of electronic speckle interferometry based spirometer
SANKARARAMAN SANKARANARAYANA IYER, RAJ VIMAL, SREEJYOTHI S, KUMAR SUNIL, KUMAR ARUN, SWAPNA MOHANACHANDRAN NAIR SINDHU, 2021, original scientific article

Abstract: The paper reports the design, construction, and calibration of the prototype of a spirometer based on electronic speckle interferometry (ESPI). The conventional ESPI setup is modified by incorporating a DNM (DiaphragmNozzle-Mouthpiece) module comprising a metallic diaphragm, regulated airflow channel, and a mouthpiece. The exhaled air after a deep breathe is channelled to the DNM module where the diaphragm gets deformed. From the circular fringe pattern obtained by subtracting the speckled images before and after deformation of the metallic diaphragm, the radius of curvature (R) due to deformation is calculated using the principle of Newton’s rings. The value of R and peak expiratory flow rate (PEFR) from the standard spirometer reading are correlated. From the 640 observations spread over the range 100 - 500 L/min in the standard spirometer, an empirical relation is set in terms of R from the scatter plot. The ESPI spirometer (ESPIS) is validated by determining the value of R corresponding to a particular PEFR from the empirical relation and also from the standard spirometer. The PEFR calculated from ESPIS matches well with the standard spirometer reading, which suggests that the system designed and constructed can be used for biomedical applications for assessing lungs’ efficiency.
Found in: osebi
Keywords: Speckle, Spirometer, DNM module, ESPIS, Peak expiratory flow rate
Published: 28.06.2022; Views: 85; Downloads: 0
.pdf Fulltext (2,38 MB)

2.
Unravelling the potential of phase portrait in the auscultation of mitral valve dysfunction
SANKARARAMAN SANKARANARAYANA IYER, RAJ VIMAL, RENJINI A, SREEJYOTHI S, SWAPNA MOHANACHANDRAN NAIR SINDHU, 2021, original scientific article

Abstract: The manuscript elucidates the potential of phase portrait, fast Fourier transform, wavelet, and time-series analyses of the heart murmur (HM) of normal (healthy) and mitral regurgitation (MR) in the diagnosis of valve-related cardiovascular diseases. The temporal evolution study of phase portrait and the entropy analyses of HM unveil the valve dysfunctioninduced haemodynamics. A tenfold increase in sample entropy in MR from that of normal indicates the valve dysfunction. The occurrence of a large number of frequency components between lub and dub in MR, compared to the normal, is substantiated through the spectral analyses. The machine learning techniques, K-nearest neighbour, support vector machine, and principal component analyses give 100% predictive accuracy. Thus, the study suggests a surrogate method of auscultation of HM that can be employed cost-effectively in rural health centres.
Found in: osebi
Keywords: phase portrait, auscultation, mitral valve dysfunction, heart murmur, nonlinear time series analysis
Published: 28.06.2022; Views: 96; Downloads: 0
.pdf Fulltext (2,02 MB)

3.
Nonlinear time series and principal component analyses: Potential diagnostic tools for COVID-19 auscultation
SANKARARMAN S, SREEJYOTHI S, RENJINI A, RAJ VIMAL, SWAPNA MOHANACHANDRAN NAIR SINDHU, 2020, original scientific article

Abstract: The development of novel digital auscultation techniques has become highly significant in the context of the outburst of the pandemic COVID 19. The present work reports the spectral, nonlinear time series, fractal, and complexity analysis of vesicular (VB) and bronchial (BB) breath signals. The analysis is carried out with 37 breath sound signals. The spectral analysis brings out the signatures of VB and BB through the power spectral density plot and wavelet scalogram. The dynamics of airflow through the respiratory tract during VB and BB are investigated using the nonlinear time series and complexity analyses in terms of the phase portrait, fractal dimension, Hurst exponent, and sample entropy. The higher degree of chaoticity in BB relative to VB is unwrapped through the maximal Lyapunov exponent. The principal component analysis helps in classifying VB and BB sound signals through the feature extraction from the power spectral density data. The method proposed in the present work is simple, cost-effective, and sensitive, with a far-reaching potential of addressing and diagnosing the current issue of COVID 19 through lung auscultation.
Found in: osebi
Keywords: Breath sound analysis, Fractal dimension, Nonlinear time series analysis, Sample entropy, Hurst exponent, Principal component analysis
Published: 28.06.2022; Views: 118; Downloads: 0
.pdf Fulltext (2,73 MB)

4.
Absolute Porosity Analysis in Carbon Allotropic Nanofluids: A Sankar–Swapna Model Approach
SANKARARAMAN S, SREEJYOTHI S, SWAPNA MOHANACHANDRAN NAIR SINDHU, 2020, original scientific article

Abstract: Porous materials have gained significant attention in recent years as a class of material exhibiting interesting chemical and physical properties. The existing methods of porosity analysis have limitations that prevent absolute porosity measurement. Hence, a technique independent of surface physical properties alone can give the absolute porosity of the material. The porosity greatly influences the thermal diffusivity of a material. The manuscript is the first report of employing the Sankar–Swapna model for analyzing the porosity variations in carbon allotropic nanofluids. The model helps not only in getting information about the absolute porosity variations among samples, but also suggests morphological modifications through the thermal diffusivity study using the sensitive single-beam thermal lens technique. The variations in thermal diffusivity and absolute porosity values are also correlated to morphological modifications based on the theoretical model and thereby proposing this as a surrogate method for absolute porosity analysis.
Found in: osebi
Keywords: absolute porosity, Sankar–Swapna model, thermal diffusivity, thermal lens, thermal conductivity
Published: 04.07.2022; Views: 76; Downloads: 0
.pdf Fulltext (1,96 MB)

5.
Investigation of Fractality and variation of fractal dimension in germinating seed
SANKARARAMAN S, SREEJYOTHI S, SWAPNA MOHANACHANDRAN NAIR SINDHU, 2020, original scientific article

Abstract: The fractal analysis has now been recognized as a potential mathematical tool in analyzing complex structures. The present work reports not only the fractal nature of Vigna radiata seed analyzed with the help of Field Emission Scanning Electron Microscopic images but also the variation of fractal dimension (FD) in a germinating seed. The variation of FD during germination in different media—water, salt, and diesel soot with carbon nanoparticles (CNPs)—is studied using the box-counting technique. The study is the first report of the fractality of seed. Irrespective of the media, the FD attains a maximum value on the day of germination and decreases after that. The time (T) for achieving maximum FD varies with the nature of stress. In the study, when the CNPs of diesel soot lower the T value, the salt raises the T value with respect to the control set. The Fourier Transform Infrared analysis of the seeds germinating in different media shows an increased rate of protein formation during the initial stage of germination and a steady state after that. In conjunction with the literature, the variation in the amino nitrogen, soluble nucleotide—RNA, and protein content of the seed during the initial days of germination gets reflected in its FD.
Found in: osebi
Keywords: fractal analysis, seed germination, Vigna radiata
Published: 04.07.2022; Views: 102; Downloads: 0
.pdf Fulltext (2,74 MB)

6.
Downscaling of sample entropy of nanofluids by carbon allotropes
Sankaranarayana Iyer Sankararaman, K. Satheesh Kumar, S. Sreejyothi, Vimal Raj, Mohanachandran Nair Sindhu Swapna, 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 antipersistent. 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.
Found in: osebi
Keywords: carbon allotropic nanofluids, time series, entropy, MWCNT, thermal lens signal
Published: 30.06.2022; Views: 99; Downloads: 0
.pdf Fulltext (4,22 MB)

7.
Time series and fractal analyses of wheezing
Sankaranarayana Iyer Sankararaman, S. Sreejyothi, Vimal Raj, A. Renjini, Mohanachandran Nair Sindhu Swapna, 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.
Found in: osebi
Keywords: auscultation, wheeze, fractals, nonlinear time series analysis, sample entropy
Published: 30.06.2022; Views: 103; Downloads: 0
.pdf Fulltext (2,46 MB)

8.
Is SARS CoV-2 a multifractal?
Sankaranarayana Iyer Sankararaman, Vimal Raj, S. Sreejyothi, Mohanachandran Nair Sindhu Swapna, 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 boxcounting 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.
Found in: osebi
Keywords: Fractality, SARS CoV, Coronavirus, Fractal dimension, Multifractal
Published: 30.06.2022; Views: 86; Downloads: 0
.pdf Fulltext (1,48 MB)

9.
Speckle interferometric investigation of argon pressure-induced surface roughness modifications in RF-sputtered MoO[sub]3 film
S. Soumya, R. Arun Kumar, S. 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.
Found in: osebi
Keywords: speckle pattern interferometry, time history of speckle pattern, cross correlation, inertia moment
Published: 04.07.2022; Views: 91; Downloads: 0
.pdf Fulltext (10,20 MB)

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