National Institute of Technology, Karnataka

About: National Institute of Technology, Karnataka is a education organization based out in Mangalore, Karnataka, India. It is known for research contribution in the topics: Computer science & Corrosion. The organization has 5017 authors who have published 7057 publications receiving 70367 citations.

Solar photocatalytically active, engineered silver nanoparticle synthesis using aqueous extract of mesocarp of Cocos nucifera (Red Spicata Dwarf)

Abstract: Silver nanoparticles synthesised using aqueous extract of Cocos nucifera (CN) mesocarp were evaluated for their photocatalytic activity under solar irradiation. The silver nanoparticles were synthesised by a green method of harnessing bioactive phytocomponents from the mesocarp of Cocos nucifera. Large-scale application of this process necessitates the manoeuvering of the process parameters for increasing the conversion of silver ions to nanoparticles. Process parameters influencing the morphological characteristics of silver nanoparticles such as precursor salt concentration and pH of the synthesis mixture were studied. The crystalline nanoparticles were characterised using UV-vis spectroscopy, XRD, FTIR, SEM and EDX analysis. CN extract and 5 mM silver nitrate solution at a ratio of 1:4 (v/v) in the synthesis mixture was found to be the optimum. Alkaline initial pH of the synthesis mixture was found to favour the synthesis of smaller sized monodispersed silver nanoparticles. Solar energy was har...

Effect of SiC Reinforcement on Microstructure and Mechanical Properties of Aluminum Metal Matrix Composite

Abstract: Aluminum reinforced with silicon carbide composites areextensively used in automobile industries and aerospaceowing to their favourable microstructure and improved mechanical behaviour with respect to pure aluminium but at a lower cost. Aluminium is remarkable for the low density and its ability to resist corrosion. The aim of present study istoevaluate the mechanical and microstructural properties of aluminum with silicon carbide (average particle size 30-45μm) reinforced in varying weight percentages (wt %) ranging from 0–15 wt% in a step of 5% each. Ultimate tensile strength, micro hardness and density of the fabricated composites were investigated as a function of varying SiC wt%. Microstructure analysis was carried out on casted composites using optical microscopy and scanning electron microscopy. From micrographs it is clear that fair distribution of reinforcing particles in the matrix and also observed some clustering and porosity in the cast material. Results revealed that, the addition of SiC reinforcement in the aluminum matrix increases the hardness and ultimate tensile strength gradually from 23 HV to 47 HV and 84 MPa to 130 MPa respectively.

Workplace Spirituality and Subjective Happiness Among High School Teachers: Gratitude As A Moderator

Abstract: Background and Objective Spirituality and well-being are two constructs related to optimal levels of human functioning. This study attempts to link the concept of spirituality at work and subjective happiness, which is a facet of well-being. The role of grateful disposition is also examined by incorporating gratitude as a moderator Method Data were collected using a structured questionnaire from high school teachers working with government schools in the southern region of India. Hypothesised relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) Results Results reveal significant relationships between workplace spirituality, subjective happiness, and gratitude. Gratitude was also found to be a significant moderator, which exercised a positive influence on the workplace spirituality-happiness relationship. Conclusion The study has contributed to the evolving literature on workplace spirituality by elucidating its relationship with positive psychology. Workplace spirituality could play a significant role in building substantial happiness for individuals in the long run.

Classification of vocal and non-vocal segments in audio clips using genetic algorithm based feature selection (GAFS)

Abstract: The technology of music information retrieval (MIR) is an emerging field that helps in tagging each portion of an audio clip. A majority of the subtasks of MIR need an application that segments vocal and non-vocal portions. In this paper, an effort has been made to segment the vocal and non-vocal regions using some novel features based on formant structure on top of standard features. The features such as Mel-frequency cepstral coefficients (MFCCs), linear prediction cepstral coefficients (LPCCs), frequency domain linear prediction (FDLP) values, statistical values of pitch, jitter, shimmer, formant attack slope (FAS), formant heights from base-to-peak (FH1), peak-to-base (FH2), formant angle values at peak (FA1), valley (FA2), and F5 have been considered. The classifiers such as artificial neural networks (ANN), support vector machines (SVM), and random forest (RF) have been considered for a comparative study as they are powerful enough to discover huge non-linear patterns. The concept of genetic algorithms with the support of neural networks has been used to select the relevant features rather considering all dimensions, named as a genetic algorithm based feature selection (GAFS). an accuracy of 89.23% before windowing and 95.16% after windowing is obtained with the optimal feature vector of length 32 using artificial neural networks. The system developed is capable of detecting singing voice segments with an accuracy of 98%.