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Opis: Fingerprint recognition is the most popular biometric identification method currently employed in security applications. Though there are several optical methods for fingerprint analysis based on intensity recording, phase recording alone can give the precise result. Interference and diffraction phenomenon are capable of recording phase variations. In the present method diffraction patterns corresponding to the fingerprints are generated and the spacing between the ridges is calculated. The spacing between ridges is found to be in agreement with the value measured using the software ImageJ. The fingerprint impressions of more than thirty-five persons are recorded and analyzed using the statistical tools in Matlab.The fingerprints are also subjected to fractal analysis. The program could successfully identify a fingerprint from the database. The present work is the first report of fingerprint analysis from diffraction pattern
Najdeno v: osebi
Ključne besede: Diffraction, Skew, Kurtosis, Fractals
Objavljeno: 30.06.2022; Ogledov: 485; Prenosov: 0
Polno besedilo (1020,06 KB)

Opis: Graphene has emerged as a potential material in various scientific disciplines, ranging from material science, engineering, and more recently biomedicine. The paper describes the investigation of the presence of graphene and graphene oxide (GO) in the carbon soot of internal combustion diesel engines. The UV-Visible, Fourier transform infrared (FTIR), X- ray diffraction (XRD), Photoluminescent (PL) and Raman spectroscopic analysis of the sample provided a conclusive evidence of the formation of graphene and GO. The Field Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive Spectrum (EDX) of the sample show carbon nanoparticles (CNPs) of size less than 50nm. The High -Resolution Transmission Electron Microscopy (HR-TEM) analysis confirmed the formation of graphene sheets with carbon nanospheres attached to it. The study reveals the possible exploitation of the diesel soot for potential applications in science and technology
Najdeno v: osebi
Ključne besede: Graphene, Graphene oxide, Carbon nanoparticles, Combustion, Carbon nanotube
Objavljeno: 30.06.2022; Ogledov: 506; Prenosov: 0
Polno besedilo (1,27 MB)

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.
Najdeno v: osebi
Ključne besede: Complex network analysis, Auscultation, Croup cough, Pertussis Spectral analysis, Machine learning techniques
Objavljeno: 30.06.2022; Ogledov: 584; Prenosov: 0
Polno besedilo (1,71 MB)

Opis: 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.
Najdeno v: osebi
Ključne besede: cross-correlation, fractal dimension, inertia moment, lacunarity, speckle, surface roughness.
Objavljeno: 30.06.2022; Ogledov: 491; Prenosov: 0
Polno besedilo (2,33 MB)

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.
Najdeno v: osebi
Ključne besede: wet cough, dry cough, complex network, quadratic SVM, neural net
Objavljeno: 30.06.2022; Ogledov: 478; Prenosov: 0
Polno besedilo (1018,61 KB)