Adaptive UNet-based Lung Segmentation and Ensemble Learning with CNN-based Deep Features for Automated COVID-19 Diagnosis

Multimedia Tools and Applications - COVID-19 disease is a major health calamity in twentieth century, in which the infection is spreading at the global level. Developing countries like Bangladesh,...     

Machine learning model for mapping of music mood and human emotion based on physiological signals

Emotion is considered a physiological state that appears whenever a transformation is observed by an individual in their environment or body. While studying the literature, it has been observed that combining the electrical activity of the brain, along with other physiological signals for the accurate analysis of human emotions is yet to be explored in greater depth. On the basis of physiological signals, this work has proposed a model using machine learning approaches for the calibration of music mood and human emotion. The proposed model consists of three phases (a) prediction of the mood of the song based on audio signals, (b) prediction of the emotion of the human-based on physiological signals using EEG, GSR, ECG, Pulse Detector, and finally, (c) the mapping has been done between the music mood and the human emotion and classifies them in real-time. Extensive experimentations have been conducted on the different music mood datasets and human emotion for influential feature extraction, training, testing and performance evaluation. An effort has been made to observe and measure the human emotions up to a certain degree of accuracy and efficiency by recording a person’s bio- signals in response to music. Further, to test the applicability of the proposed work, playlists are generated based on the user’s real-time emotion determined using features generated from different physiological sensors and mood depicted by musical excerpts. This work could prove to be helpful for improving mental and physical health by scientifically analyzing the physiological signals.

     

3D Face Recognition Using a Fusion of PCA and ICA Convolution Descriptors

Neural Processing Letters - This paper introduces a hybrid filter bank-based convolutional network to develop a 3D face recognition system in different orientations. The filter banks approach has...     

A hybrid deep learning model by combining convolutional neural network and recurrent neural network to detect forest fire

Multimedia Tools and Applications - Forest fire poses a serious threat to wildlife, environment, and all mankind. This threat has prompted the development of various intelligent and computer vision...     

Effect of A‐ or B‐site doping of perovskite calcium manganite on structure,resistivity, and thermoelectric properties

Bismuth‐, lanthanum‐, and molybdenum‐doped calcium manganite (CaMnO₃, abbreviated Mn113) are synthesized by solid‐state synthesis route from their respective oxide precursors at a same doping level (x=0.05). Depending on the ionic sizes, trivalent dopants (Bi³⁺ and La³⁺) replace Ca²⁺(A site), while penta/hexavalent dopant Mo⁵⁺/Mo⁶⁺ replaces Mn⁴⁺ (B site) in the Mn113 structure. XRD of all three doped samples confirm formation of single phase. In all three samples, doping causes unit cell volume to expand, while volume expansion is maximum for the Mo‐Mn113. The transport behavior of the doped samples follows small polaron hopping mechanism. Resistivity of the doped samples depends not only on the carrier concentration but also on the effective bandwidth determined by the structural distortion introduced by the dopant ions. Bi‐Mn113 has highest resistivity at the both temperature end, while La‐Mn113 has the lowest. Thermopower is determined by the carrier concentration only and does not depend on dopant type, having value ~260 μV/K at 1000 K. At high (>800 K), S reaches a saturation value and becomes independent of T. La‐Mn113 is having highest figure of merit (zT) 0.19 at 1000 K.     

Oxidation of tetralin to 1-tetralone over CrAPO-5

A chromium-incorporated microporous aluminophosphate, CrAPO-5, was tested as a catalyst for the oxidation of tetralin using either a combination of aldehyde and O₂ (1 atm) or tert-butyl hydroperoxide as an oxidant system. The former resulted in significantly improved catalytic performance (69.6% yield to 1-tetralone) over the latter (38.5% yield to 1-tetralone) at 80 °C in 8 h, and conversion increased in the sequence of acetaldehyde?isobutyl aldehyde<pivalaldehyde. CrAPO-5 also exhibited good activity and high selectivity (53.7% yield to 1-tetralone) after 24 h using pivalaldehyde and O₂ at room temperature. Hot filtration and recycle experiments established that oxidation takes place mostly on Cr sites in CrAPO-5. A plausible reaction mechanism involving acylperoxy radicals and oxo-chromium(V) species on CrAPO-5 was proposed for the tetralin oxidation.     

Mineral element composition of spinach

An extensive study has been made on the mineral element compositions of spinach leaves and stems. Twenty two locally grown different spinach samples have been analysed for 16 elements using ICP and atomic absorption spectrophotometric techniques. Both spinach leaves and stems were analysed separately. A detailed elucidation of the inorganic matrix in spinach leaves and stems has been provided. © 1998 SCI.     

Cavitation Erosion Studies on Friction Stir Processed Hydroturbine Steel

Cavitation erosion (CE) of various components in hydroturbines is a critical issue. Several attempts have been made in the past to counter CE through various surface modification techniques. In this study, a novel attempt has been made to modify the surface properties of hydroturbine steel with the aid of friction stir processing (FSP). Metallurgical characterization of the processed steel was undertaken with the help of XRD, SEM/EDS, EBSD and optical microscopy. For mechanical characterization micro-hardness and cavitation erosion studies were conducted. EBSD results confirmed the presence of grains in nano range. Processed steel showed gain in hardness of the order of 160?% in comparison to unprocessed steel. XRD results show a significant variation in the type and quantity of various phases in pre- and post processed steel. It was observed that FSPed steel showed a significant improvement in the erosion resistance in contrast to the unprocessed steel.