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1.
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: ključnih besedah
Summary of found: ...present work reports the spectral, nonlinear time series, fractal, and complexity analysis of vesicular (VB) and...
Keywords: Breath sound analysis, Fractal dimension, Nonlinear time series analysis, Sample entropy, Hurst exponent, Principal component analysis
Published: 28.06.2022; Views: 138; Downloads: 0
.pdf Fulltext (2,73 MB)

2.
Soot effected sample entropy minimization in nanofluid for thermal system design
Sankaranarayana Iyer Sankararaman, K. Satheesh Kumar, Vimal Raj, Mohanachandran Nair Sindhu Swapna, 2020, original scientific article

Abstract: The present work suggests a method of improving the thermal system efficiency, through entropy minimisation, and unveils the mechanism involved by analysing the molecular/particle dynamics in soot nanofluids (SNFs) using the time series, power spectrum, and wavelet analyses of the thermal lens signal (TLS). The photothermal energy deposition in the SNF lowers the refractive index due to the temperature rise. It triggers the particle dynamics that are investigated by segmenting the TLS and analysing the refractive index, phase portrait, fractal dimension (D), Hurst exponent (H), and sample entropy (SampEn). The wavelet analysis gives information about the relation between the entropy and the frequency components. When the phase portrait analysis reflects the complex dynamics from region 1 to 2 for all the samples, the SampEn analysis supports it. The decreasing value of D (from 1.59 of the base fluid to 1.55 and 1.52) and the SampEn (from 1.11 of the base fluid to 0.385 and 0.699) with the incorporation of diesel and camphor soot, indicate its ability to lower the complexity, randomness, and entropy. The increase of SampEn with photothermal energy deposition suggests its relation to the thermodynamic entropy (S). The lowering of thermal diffusivity value of the base fluid from 1.4 × 10−7 m2/s to 1.1 × 10−7 and 0.5 × 10−7 m2 /s upon diesel and camphor soot incorporation suggests the heat-trapping and reduced molecular dynamics in heat dissipation.
Found in: ključnih besedah
Summary of found: ...and analysing the refractive index, phase portrait, fractal dimension (D), Hurst exponent (H), and sample...
Keywords: soot, entropy, thermal system, photothermal, time series, nanofluid, fractal
Published: 30.06.2022; Views: 113; Downloads: 0
.pdf Fulltext (2,27 MB)

3.
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: ključnih besedah
Summary of found: ...A first report of unveiling the fractality and fractal nature of severe acute respiratory...
Keywords: Fractality, SARS CoV, Coronavirus, Fractal dimension, Multifractal
Published: 30.06.2022; Views: 106; Downloads: 0
.pdf Fulltext (1,48 MB)

4.
The efflorescent carbon allotropes: Fractality preserved blooming through alkali treatment and exfoliation
SWAPNA MOHANACHANDRAN NAIR SINDHU, SANKARARAMAN S, 2020, original scientific article

Abstract: The work reported in the paper elucidates morphological modification induced nanoart and surface area enhancement of graphite, graphene, and soot containing carbon allotropes through ultrasonication and alkali-treatment. The field emission scanning electron microscopic (FESEM) analysis of the samples before and after exfoliation reveals the formation of brilliant flower-like structures from spindle-like basic units due to Ostwald ripening. The x-ray diffraction analysis of the samples gives information about structural composition. The fractal analysis of the FESEM images indicates a multifractal structure with the dimensions—box-counting dimension D0 (1.72), information dimension D1 (1.66), and correlation dimension D2 (1.63)—preserved upon exfoliation. The process of ultra-sonication assisted liquid phase exfoliation resembles blooming as if the carbon allotropes are efflorescent.
Found in: ključnih besedah
Summary of found: ...samples gives information about structural composition. The fractal analysis of the FESEM images indicates a multifractal...
Keywords: carbon allotropes, fractal dimension, soot, fractality, alkali treatment, exfoliation
Published: 04.07.2022; Views: 84; Downloads: 0
.pdf Fulltext (8,02 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: ključnih besedah
Keywords: fractal analysis, seed germination, Vigna radiata
Published: 04.07.2022; Views: 119; Downloads: 0
.pdf Fulltext (2,74 MB)

6.
Fractal Applications in Bio-Nanosystems
SANKARARAMAN S, SWAPNA MOHANACHANDRAN NAIR SINDHU, 2019, review article

Abstract: We live in a world of high complexity in all means. The present article is an attempt to elucidate the potential of fractal analysis in understanding and quantifying the complexity. Of several methods of fractal analysis, we have used only the box counting and power spectral methods for explaining the potential of the technique. The application of fractal analysis in bio-nanosystems, thin films, are forensic science are exemplified though our own work.
Found in: ključnih besedah
Keywords: fractal application, bionanosystem
Published: 04.07.2022; Views: 89; Downloads: 0
.pdf Fulltext (508,87 KB)

7.
Fractal and inertia moment analyses for thin film quality monitoring
SWAPNA MOHANACHANDRAN NAIR SINDHU, 2022, original scientific article

Abstract: The widespread applications of thin films in optronics demand innovative techniques for its characterizations. The work reported here proposes electronic speckle pattern interferometry and fractal-based methods for assessing the quality of thin films taking the industrially relevant molybdenum oxide (MoO3) incorporated niobium oxide (Nb2O5) films. The films with different levels of MoO3 incorporation (1, 2, 3, 5, and 10 wt. %) are prepared by radio frequency sputtering. The study reveals the structure modifications of Nb2O5 from the orthorhombic to monoclinic phases with an associated morphological variation revealed through atomic force microscopy and field-emission scanning electron microscopy analyses. The films’ specklegrams are recorded under thermal stress; the inertia moment (IM) and fractal analyses are computed and compared with the root-mean-square surface roughness of the films. The lacunarity analysis of the AFM films agrees well with the specklegrams. Thus, the lower IM and lacunarity values of the specklegrams can be regarded as indicators of the good quality of thin films.
Found in: ključnih besedah
Keywords: cross-correlation, fractal dimension, inertia moment, lacunarity, speckle, surface roughness.
Published: 30.06.2022; Views: 123; Downloads: 0
.pdf Fulltext (2,33 MB)

8.
Fractal and time-series analyses based rhonchi and bronchial auscultation: A machine learning approach
SWAPNA MOHANACHANDRAN NAIR SINDHU SWAPNA,, 2022, original scientific article

Abstract: Objectives: The present work reports the study of 34 rhonchi (RB) and Bronchial Breath (BB) signals employing machine learning techniques, timefrequency, fractal, and non-linear time-series analyses. Methods: The timefrequency analyses and the complexity in the dynamics of airflow in BB and RB are studied using both Power Spectral Density (PSD) features and non-linear measures. For accurate prediction of these signals, PSD and nonlinear measures are fed as input attributes to various machine learning models. Findings: The spectral analyses reveal fewer, low-intensity frequency components along with its overtones in the intermittent and rapidly damping RB signal. The complexity in the dynamics of airflow in BB and RB is investigated through the fractal dimension, Hurst exponent, phase portrait, maximal Lyapunov exponent, and sample entropy values. The greater value of entropy for the RB signal provides an insight into the internal morphology of the airways containing mucous and other obstructions. The Principal Component Analysis (PCA) employs PSD features, and Linear Discriminant Analysis (LDA) along with Pattern Recognition Neural Network (PRNN) uses non-linear measures for predicting BB and RB. Signal classification based on phase portrait features evaluates the multidimensional aspects of signal intensities, whereas that based on PSD features considers mere signal intensities. The principal components in PCA cover about 86.5% of the overall variance of the data class, successfully distinguishing BB and RB signals. LDA and PRNN that use nonlinear time-series parameters identify and predict RB and BB signals with 100% accuracy, sensitivity, specificity, and precision. Novelty: The study divulges the potential of non-linear measures and PSD features in classifying these signals enabling its application to be extended for low-cost, non-invasive COVID-19 detection and real-time health monitoring.
Found in: ključnih besedah
Keywords: lung signal, fractal analysis, sample entropy, non­linear time­series, machine learning techniques
Published: 30.06.2022; Views: 121; Downloads: 0
.pdf Fulltext (1,50 MB)

9.
Evolution of fractal dimension in pulsed laser deposited MoO3 film with ablation time and annealing temperature
SWAPNA MOHANACHANDRAN NAIR SINDHU, 2021, original scientific article

Abstract: The multifractal analysis is a potential method for assessing thin flm surface morphology and its changes due to diferent deposition conditions and post-deposition treatments. In this work, the multifractal analysis is carried out to understand the surface morphology—root mean square (RMS) surface roughness—of nanostructured MoO3 flms prepared by pulsed laser deposition technique by varying the ablation time and post-deposition annealing. The XRD analysis shows the evolution of crystalline nature with annealing temperature. The XRD pattern of all the annealed flms shows the characteristic peak of the orthorhombic MoO3 phase. The FESEM and AFM analysis reveals the morphological modifcation with ablation time and annealing temperature. The multifractal analysis of the AFM images shows that the box—counting, information and correlation dimension varies with the annealing temperature. The study also reveals the inverse relation between the fractal dimension and the RMS surface roughness due to the annealing induced particle size variation and reorientation. The fractal dimension’s evolution in the pulsed laser deposited MoO3 flm with ablation time and annealing temperature is also investigated. Thus, the study reveals the potential of multifractal analysis in the thin flm surface characterizatio
Found in: ključnih besedah
Keywords: Multifractal analysis · Pulsed laser deposition · Molybdenum oxide · Atomic force microscopy · Fractal dimension
Published: 04.07.2022; Views: 88; Downloads: 0
.pdf Fulltext (2,53 MB)

10.
Neural net pattern recognition based auscultation of croup cough and pertussis using phase portrait features
SWAPNA MOHANACHANDRAN NAIR SINDHU, 2021, original scientific article

Abstract: Cough signal analysis for understanding the pathological condition has become important from the outset of the exigency posed by the epidemic COVID-19. The present work suggests a surrogate approach for the classification of cough signals - croup cough (CC) and pertussis (PT) – based on spectral, fractal, and nonlinear time-series techniques. The spectral analysis of CC reveals the presence of more frequency components in the short duration cough sound compared to PT. The musical nature of CC is unveiled not only through the spectral analysis but also through the phase portrait features – sample entropy (S), maximal Lyapunov exponent (L), and Hurst exponent (Hb). The modifications in the internal morphology of the respiratory tract, giving rise to more frequency components associated with the complex airflow dynamics, get staged through the higher fractal dimension of CC. Among the two supervised classification tools, cubic KNN (CKNN) and neural net pattern recognition (NNPR), used for classifying the CC and PT signals based on nonlinear time series parameters, NNPR is found better. Thus, the study opens the possibility of identification of pulmonary pathological conditions through cough sound signal analysis.
Found in: ključnih besedah
Summary of found: ...and pertussis (PT) – based on spectral, fractal, and nonlinear time-series techniques. The spectral analysis...
Keywords: Croup cough Pertussis Fractal dimension Phase portrait Sample entropy Machine learning techniques
Published: 04.07.2022; Views: 82; Downloads: 0
.pdf Fulltext (5,42 MB)

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