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32. Markov chain : a novel tool for electronic ripple analysisVijayan Vijesh, K. Satheesh Kumar, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman, 2022, original scientific article Keywords: complex network, Markov chain, rectifier, time series, ripple
Published in RUNG: 29.11.2022; Views: 2344; Downloads: 1
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35. Crash course on cybersecurity : a manual for surviving in a networked worldMatej Kovačič, 2022, scientific monograph Keywords: information security, cybersecurity, network security, passwords, physical security, backup, encryption, data wiping, VPN, anonymization
Published in RUNG: 30.08.2022; Views: 2558; Downloads: 43
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36. Graph based feature extraction and classification of wet and dry cough signals: A machine learning approachMohanachandran Nair Sindhu Swapna, 2021, original scientific article Abstract: 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.
Keywords: wet cough, dry cough, complex network, quadratic SVM, neural net
Published in RUNG: 30.06.2022; Views: 2378; Downloads: 0
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37. Complex network-based cough signal analysis for digital auscultation: a machine learning approachMohanachandran Nair Sindhu Swapna, 2022, original scientific article Abstract: 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.
Keywords: Complex network analysis, Auscultation, Croup cough, Pertussis
Spectral analysis, Machine learning techniques
Published in RUNG: 30.06.2022; Views: 3350; Downloads: 0
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38. Bioacoustic signal analysis through complex network featuresMohanachandran Nair Sindhu Swapna, RAJ VIMAL, Sankararaman S, 2022, original scientific article Abstract: The paper proposes a graph-theoretical approach to auscultation, bringing out the potential of graph features in
classifying the bioacoustics signals. The complex network analysis of the bioacoustics signals - vesicular (VE) and
bronchial (BR) breath sound - of 48 healthy persons are carried out for understanding the airflow dynamics
during respiration. The VE and BR are classified by the machine learning techniques extracting the graph features
– the number of edges (E), graph density (D), transitivity (T), degree centrality (Dcg) and eigenvector centrality
(Ecg). The higher value of E, D, and T in BR indicates the temporally correlated airflow through the wider
tracheobronchial tract resulting in sustained high-intense low-frequencies. The frequency spread and high-frequencies in VE, arising due to the less correlated airflow through the narrow segmental bronchi and lobar,
appears as a lower value for E, D, and T. The lower values of Dcg and Ecg justify the inferences from the spectral
and other graph parameters. The study proposes a methodology in remote auscultation that can be employed in
the current scenario of COVID-19.
Keywords: Bioacoustic signal, Graph theory, Complex network, Lung auscultation
Published in RUNG: 30.06.2022; Views: 2468; Downloads: 0
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39. Analysing security checkpoints for an integrated utility-based information systemSunil K. Muttoo, Rajan Gupta, Saibal K. Pal, 2016, published scientific conference contribution Abstract: With the rising digital medium, the various digital applications are rising too. These applications can work in the private domain or public domain depending upon the environment and features. Of late, the public infrastructure in India is improving and thus digitisation of the services and processes are making it better for the government to function. Lots of new services and applications are planned through desktop-and mobile-based information systems. But any information system requires a good security cover for it to function correctly and efficiently. One such new system was proposed for integrating the various utility systems in Delhi, NCR, for which various security checkpoints are discussed in this paper. These are related to database security, network security, cryptography, and the user authentication process. These checkpoints will be helpful in making the newly proposed information system more secure and will also be helpful in analysing the need and scope of new security features in it. Security concerns are analysed at different levels of the information system and suggestions are made for the system which can be implemented in the currently proposed system. These suggestions can also be used in other similar systems as well as for improving and enhancing security at various levels.
Keywords: information systems, integrated utility system, database security, network security, data security, information system security, e-governance
Published in RUNG: 15.07.2021; Views: 3508; Downloads: 12
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