91. Speckle interferometric probing of intrafilm thermal-induced particle dynamics in RF-sputtered MoO[sub]3 filmsS. Soumya, S. Sreejyothi, Vimal Raj, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2022, izvirni znanstveni članek Najdeno v: osebi
Ključne besede: speckle interferometry, thermal-induced particle dynamics, RF sputtering, MoO3 films
Objavljeno: 30.08.2022; Ogledov: 437; Prenosov: 17
 Polno besedilo (14,91 MB)
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92. Power spectral fractal dimension and wavelet features for mammogram analysisAmmini Renjini, Mohanachandran Nair Sindhu Swapna, Vimal Raj, Babatunde S. Emmanuel, Sankaranarayana Iyer Sankararaman, 2022, izvirni znanstveni članek Najdeno v: osebi
Ključne besede: power spectral fractal dimension, wavelet, mammogram analysis, machine learning
Objavljeno: 30.08.2022; Ogledov: 412; Prenosov: 18
Polno besedilo (1,58 MB)
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93. Markov chainVijayan Vijesh, K. Satheesh Kumar, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2022, izvirni znanstveni članek Najdeno v: osebi
Ključne besede: complex network, Markov chain, rectifier, time series, ripple
Objavljeno: 29.11.2022; Ogledov: 322; Prenosov: 0
Polno besedilo (1,17 MB) |
94. Improved photopyroelectric (PPE) configuration for thermal effusivity investigations of porous solidsDorin Dadarlat, Marcel Bojan, Mladen Franko, Dorota Korte, Robert Gutt, Nicoleta Cobirzan, Carmen Tripon, Mohanachandran Nair Sindhu Swapna, 2023, izvirni znanstveni članek Najdeno v: osebi
Ključne besede: photothermal techniques, photopyroelectric calorimetry, thermal effusivity, porous solids, building materials
Objavljeno: 12.04.2023; Ogledov: 176; Prenosov: 13
Polno besedilo (3,75 MB)
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95. Development of eco-friendly corrosion-resistant boron carbide coating from natural carbon precursor for electronic applicationsH. V. Saritha Devi, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2023, izvirni znanstveni članek Najdeno v: osebi
Ključne besede: carbides, boron carbide, thin films, corrosion resistance, electronics, natural carbon
Objavljeno: 25.04.2023; Ogledov: 152; Prenosov: 4
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97. Fractal and time-series analyses based rhonchi and bronchial auscultation: A machine learning approachSWAPNA MOHANACHANDRAN NAIR SINDHU SWAPNA,, 2022, izvirni znanstveni članek Opis: 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.
Najdeno v: osebi
Ključne besede: lung signal, fractal analysis, sample entropy, nonlinear timeseries, machine learning techniques
Objavljeno: 30.06.2022; Ogledov: 561; Prenosov: 0
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