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Complex network-based cough signal analysis for digital auscultation: a machine learning approach
Mohanachandran 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: 1567; Downloads: 0
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Bioacoustic signal analysis through complex network features
Mohanachandran 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: 1385; Downloads: 0
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Analysing security checkpoints for an integrated utility-based information system
Sunil 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: 2255; Downloads: 10
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NETRA : a vigilant eye on the Internet
2019, interview

Keywords: Surveillance, Network Monitoring, NETRA, Network Traffic Regulation
Published in RUNG: 03.04.2021; Views: 2368; Downloads: 63
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Design & analysis of clustering based intrusion detection schemes for e-governance
Rajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2016, published scientific conference contribution

Abstract: The problem of attacks on various networks and information systems is increasing. And with systems working in public domain like those involved under E-Governance are facing more problems than others. So there is a need to work on either designing an altogether different intrusion detection system or improvement of the existing schemes with better optimization techniques and easy experimental setup. The current study discusses the design of an Intrusion Detection Scheme based on traditional clustering schemes like K-Means and Fuzzy C-Means along with Meta-heuristic scheme like Particle Swarm Optimization. The experimental setup includes comparative analysis of these schemes based on a different metric called Classification Ratio and traditional metric like Detection Rate. The experiment is conducted on a regular Kyoto Data Set used by many researchers in past, however the features extracted from this data are selected based on their relevance to the E-Governance system. The results shows a better and higher classification ratio for the Fuzzy based clustering in conjunction with meta-heuristic schemes. The development and simulations are carried out using MATLAB.
Keywords: particle swarm optimization, intrusion detection, anomaly detection, intrusion detection system, network intrusion detection
Published in RUNG: 02.04.2021; Views: 2212; Downloads: 9
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Internet traffic surveillance & network monitoring in India : case study of NETRA
Rajan Gupta, Sunil K. Muttoo, 2016, original scientific article

Abstract: Internet traffic surveillance is gaining importance in today’s digital world. Lots of international agencies are putting in efforts to monitor the network around their countries to see suspicious activities and illegal or illegitimate transmission of messages. India, being a center of attraction for terrorist activities, is also working towards the development of such surveillance systems. NETRA or Network Traffic Analysis is one such effort being taken by the Indian Government to filter suspicious keywords from messages in the network. But is it good enough to be used at the highest level for security analysis or does the system design needs to be improved as compared to other similar systems around the world; this question is answered through this study. The comparison of NETRA is done against Dish Fire, Prism, and Echelon. The design of the NETRA scheme and implementation level analysis of the system shows few weaknesses like limited memory options, limited channels for monitoring, pre-set filters, ignoring big data demands, security concerns, social values breach and ignoring ethical issues. These can be covered through alternate options which can improve the existing system. The Inclusion of self-similarity models, Self-Configuring Network Monitoring, and smart monitoring through early intrusion detections can be embedded in the architecture of existing surveillance system to give it more depth and make it more robust.
Keywords: cyber attacks, NETRA, network monitoring, network traffic analysis, surveillance system, spy system
Published in RUNG: 01.04.2021; Views: 2100; Downloads: 55
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A cellular network database for fingerprint positioning systems
Donatella Gubiani, Paolo Gallo, Andrea Viel, Andrea Dalla Torre, Angelo Montanari, 2019, published scientific conference contribution

Abstract: Besides being a fundamental infrastructure for communication, cellular networks are increasingly exploited for positioning via signal fingerprinting. Here, we focus on cellular signal fingerprinting, where an accurate and comprehensive knowledge of the network is fundamental. We propose an original multilevel database for cellular networks, which can be automatically updated with new fingerprint measurements and makes it possible to execute a number of meaningful analyses. In particular, it allows one to monitor the distribution of cellular networks over countries, to determine the density of cells in different areas, and to detect inconsistencies in fingerprint observations.
Keywords: Cellular network, Signal fingerprinting, Multilevel database, Data analysis
Published in RUNG: 17.09.2019; Views: 3572; Downloads: 0
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Dealing with network changes in cellular fingerprint positioning systems
Andrea Viel, Paolo Gallo, Angelo Montanari, Donatella Gubiani, Andrea Dalla Torre, Federico Pittino, Chris Marshall, 2017, published scientific conference contribution

Abstract: Besides being a fundamental infrastructure for communication, cellular networks are exploited for positioning through signal fingerprinting. Maintaining the fingerprint database consistent and up-to-date is a challenging task in many fingerprint positioning systems, e.g., in those populated by a crowd-sourcing effort. To this end, detecting and tracking the changes in the configurations of cellular networks over time is recognized as a relevant problem. In this paper, we show that to cope with this problem we can successfully exploit information provided by Timing Advance (TA). As a by-product, we prove that TA can improve the fingerprint candidate selection phase, reducing the number of fingerprints to provide as input to positioning algorithms. The effectiveness of the proposed improvements has been tested on a fingerprint positioning system with a large fingerprint dataset collected over a period of 2 years.
Keywords: fingerprint positioning systems, cellular communication networks, network changes
Published in RUNG: 13.06.2018; Views: 4116; Downloads: 0
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ADRIART.CE Advancing Digital & Regional Interactions in the Art Teaching of Central Europe : A curriculum-developed CEEPUS network with a vision
Peter Purg, unpublished invited conference lecture

Keywords: CEEPUS, network, vision, curriculum, development
Published in RUNG: 10.04.2017; Views: 4302; Downloads: 0
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Dealing with network changes and trajectories in patio-temporal databases for positioning systems
Andrea Viel, 2015, master's thesis

Keywords: database, positioning systems, cellular network
Published in RUNG: 25.01.2017; Views: 4489; Downloads: 0
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