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Complex network based Fourier analysis for signal processing
Vijayan Vijesh, K. Satheesh Kumar, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2024, objavljeni znanstveni prispevek na konferenci

Ključne besede: fourier analysis, complex network, signal processing
Objavljeno v RUNG: 15.04.2024; Ogledov: 22; Prenosov: 0
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Tanusree Saha, 2023, doktorska disertacija

Opis: Complex systems in condensed matter are characterized by strong coupling between different degrees of freedom constituting a solid. In materials described by many-body physics, these interactions may lead to the formation of new ground states such as excitonic insulators, Mott insulators, and charge and spin density waves. However, the inherent complexity in such materials poses a challenge to identifying the dominant interactions governing these phases using equilibrium studies. Owing to the distinct timescales associated with the elementary interactions, such complexities can be readily addressed in the non-equilibrium regime. Additionally, these materials might also show the emergence of new, metastable “hidden“ phases under non-equilibrium. The thesis investigates the ultrafast timescales of fundamental interactions in candidate systems by employing time-and angle-resolved photoemission spectroscopy in the femtosecond time domain. In the (supposed) excitonic insulator model system Ta2NiSe5, the timescale of band gap closure and the dependence of rise time (of the photoemission signal) on the photoexcitation strength point to a predominantly electronic origin of the band gap at the Fermi level. The charge density wave (CDW) - Mott insulator 1T-TaS2 undergoes photoinduced phase transition to two different phases. The initial one is a transient phase which resembles the systems’s high temperature equilibrium phase, followed by a long-lived “hidden“ phase with a different CDW amplitude and is primarily driven by the CDW lattice order. For the spin density wave system CaFe2As2 where multiple bands contribute in the formation of Fermi surfaces, selective photoexcitation was used to disentangle the role played by different electron orbitals. By varying the polarization of photoexcitation pulses, it is observed that dxz/dyz orbitals primarily contribute to the magnetic ordering while the dxy orbitals have dominant role in the structural order. The findings of the present study provide deeper perspectives on the underlying interactions in complex ground phases of matter, therefore, initiating further experimental and theoretical studies on such materials.
Ključne besede: complex systems, charge density wave, excitonic insulator, metastable phase, Mott insulator, non-equilibrium, spin density wave, timescales, time- and angle-resolved photoemission, ultrafast dynamics
Objavljeno v RUNG: 01.06.2023; Ogledov: 1283; Prenosov: 26
.pdf Celotno besedilo (13,34 MB)

A solution technique to cascading link failure prediction
Niknaz Nakhaei, Morteza Ebrahimi, Ahmad Hosseini, 2022, izvirni znanstveni članek

Ključne besede: Failure prediction, Complex networks, Cascading failure, Bayesian Belief Networks, Operations Research
Objavljeno v RUNG: 14.02.2023; Ogledov: 914; Prenosov: 0
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Markov chain : a novel tool for electronic ripple analysis
Vijayan Vijesh, K. Satheesh Kumar, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2022, izvirni znanstveni članek

Ključne besede: complex network, Markov chain, rectifier, time series, ripple
Objavljeno v RUNG: 29.11.2022; Ogledov: 999; Prenosov: 0
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Correlation between FeCl2 electrolyte conductivity and electrolysis efficiency
Uroš Luin, Matjaž Valant, Iztok Arčon, 2022, objavljeni povzetek znanstvenega prispevka na konferenci

Opis: The electrolysis efficiency is an important aspect of the Power-to-Solid energy storage technology (EST) based on the iron chloride electrochemical cycle [1]. This cycle employs an aqueous FeCl2 catholyte solution for the electro-reduction of iron. The metal iron deposits on the cathode. The energy is stored as a difference in the redox potential of iron species. Hydrogen, as an energy carrier, is released on demand over a fully controlled hydrogen evolution reaction between metallic Fe0 and HCl (aq) [1]. Due to these characteristics, the cycle is suitable for long-term high-capacity and high-power energy storage. In a previous work [2] we revealed that the electrolyte conductivity linearly increases with temperature. Contrary, the correlation between the electrolyte concentration and efficiency is not so straightforward. Unexpectedly small efficiency variations were found between 1 and 2.5 mol dm-3 FeCl2 (aq) followed by an abrupt efficiency drop at higher concentrations. To explain the behavior of the observed trends and elucidate the role of FeCl2 (aq) complex ionic species we performed in situ X-ray absorption studies. We made a dedicated experimental setup, consisting of a tubular oven and PMMA liquid absorption cell, and performed the measurements at the DESY synchrotron P65 beamline. The XAS investigation covered XANES and EXAFS analyses of FeCl2 (aq) at different concentrations (1 - 4 molL-1) and temperatures (25 - 80 °C). We found that at low temperature and low FeCl2 concentration the octahedral first coordination sphere around Fe is occupied by one Cl ion at a distance of 2.33 (±0.02) Å and five water molecules at a distance of 2.095 (±0.005) Å [3]. The structure of the ionic complex gradually changes with an increase in temperature and/or concentration. The apical water molecule is substituted by a chlorine ion to yield a neutral Fe[Cl2(H2O)4]0. The transition from the single charged Fe[Cl(H2O)5]+ to the neutral Fe[Cl2(H2O)4]0 causes a significant drop in the solution conductivity, which well correlates with the existing conductivity models [3]. [1] M. Valant, “Procedure for electric energy storage in solid matter. United States Patent and Trademark Office. Patent No. US20200308715,” Patent No. US20200308715, 2021. [2] U. Luin and M. Valant, “Electrolysis energy efficiency of highly concentrated FeCl2 solutions for power-to-solid energy storage technology,” J. Solid State Electrochem., vol. 26, no. 4, pp. 929–938, Apr. 2022, doi: 10.1007/S10008-022-05132-Y. [3] U. Luin, I. Arčon, and M. Valant, “Structure and Population of Complex Ionic Species in FeCl2 Aqueous Solution by X-ray Absorption Spectroscopy,” Molecules, vol. 27, no. 3, 2022, doi: 10.3390/molecules27030642.
Ključne besede: Iron chloride electrochemical cycle, Power-to-Solid energy storage, XANES, EXAFS, electrical conductivity, electrolyte complex ionic species structure and population
Objavljeno v RUNG: 26.09.2022; Ogledov: 1469; Prenosov: (1 glas)
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Unwrapping Aortic valve dysfunction through complex network analysis: A biophysics approach
Mohanachandran Nair Sindhu Swapna, 2022, izvirni znanstveni članek

Ključne besede: Aortic valve dysfunction, complex network analysis
Objavljeno v RUNG: 14.09.2022; Ogledov: 1009; Prenosov: 0
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Graph based feature extraction and classification of wet and dry cough signals: A machine learning approach
Mohanachandran Nair Sindhu Swapna, 2021, izvirni znanstveni članek

Opis: This article proposes a unique approach to bring out the potential of graph-based features to reveal the hidden signatures of wet (WE) and dry (DE) cough signals, which are the suggestive symptoms of various respiratory ailments like COVID 19. The spectral and complex network analyses of 115 cough signals are employed for perceiving the airflow dynamics through the infected respiratory tract while coughing. The different phases of WE and DE are observed from their time-domain signals, indicating the operation of the glottis. The wavelet analysis of WE shows a frequency spread due to the turbulence in the respiratory tract. The complex network features namely degree centrality, eigenvector centrality, transitivity, graph density and graph entropy not only distinguish WE and DE but also reveal the associated airflow dynamics. A better distinguishability between WE and DE is obtained through the supervised machine learning techniques (MLTs)—quadratic support vector machine and neural net pattern recognition (NN), when compared to the unsupervised MLT, principal component analysis. The 93.90% classification accuracy with a precision of 97.00% suggests NN as a better classifier using complex network features. The study opens up the possibility of complex network analysis in remote auscultation.
Ključne besede: wet cough, dry cough, complex network, quadratic SVM, neural net
Objavljeno v RUNG: 30.06.2022; Ogledov: 1041; Prenosov: 0
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Complex network-based cough signal analysis for digital auscultation: a machine learning approach
Mohanachandran Nair Sindhu Swapna, 2022, izvirni znanstveni članek

Opis: The paper proposes a novel approach to bring out the potential of complex networks based on graph theory to unwrap the hidden characteristics of cough signals, croup (BC), and pertussis (PS). The spectral and complex network analyses of 48 cough sounds are utilized for understanding the airflow through the infected respiratory tract. Among the different phases of the cough sound time-domain signals of BC and PS – expulsive (X), intermediate (I), and voiced (V) - the phase ‘I’ is noisy in BC due to improper glottal functioning. The spectral analyses reveal high-frequency components in both cough signals with an additional high-intense low-frequency spread in BC. The complex network features created by the correlation mapping approach, like number of edges (E), graph density (G), transitivity (), degree centrality (D), average path length (L), and number of components () distinguishes BC and PS. The higher values of E, G, and for BC indicate its musical nature through the strong correlation between the signal segments and the presence of high-intense low-frequency components in BC, unlike that in PS. The values of D, L, and discriminate BC and PS in terms of the strength of the correlation between the nodes within them. The linear discriminant analysis (LDA) and quadratic support vector machine (QSVM) classifies BC and PS, with greater accuracy of 94.11% for LDA. The proposed work opens up the potentiality of employing complex networks for cough sound analysis, which is vital in the current scenario of COVID-19.
Ključne besede: Complex network analysis, Auscultation, Croup cough, Pertussis Spectral analysis, Machine learning techniques
Objavljeno v RUNG: 30.06.2022; Ogledov: 1299; Prenosov: 0
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