On the Selection of a Composite Material for Two-Wheeler Foot Bracket Failure Prevention through Simulation and Mathematical Modeling

A foot bracket is a metal panel bracket used to mount and support the footrest in two-wheeler systems.It holds the footrest in place while rigidly supporting it.In working conditions,this element has often been observed to fail when specific load-fluctuation conditions are established at its rear end.Appropriate materials therefore need to be identified to overcome such a recurring failure.To address these issues,the present study has been implemented with the specific objective to determine the response of selected Al6061-T6 and Al7075-T6 Hybrid Metal Matrix Composites(HMMC).The results,obtained using the ANSYS Software,show that the selected composites can withstand 636,962 N/m^(2)of maximum stress and 8.88×10^(−6)m of minimum displacement.These results are also compared with relevant mathematical models and it is concluded that the identified material combination provides the required improvement of structural stability that can withstand the load fluctuation on the foot bracket.

Implementation of Hybrid Deep Reinforcement Learning Technique for Speech Signal Classification

Classification of speech signals is a vital part of speech signal processing systems.With the advent of speech coding and synthesis,the classification of the speech signal is made accurate and faster.Conventional methods are considered inaccurate due to the uncertainty and diversity of speech signals in the case of real speech signal classification.In this paper,we use efficient speech signal classification using a series of neural network classifiers with reinforcement learning operations.Prior classification of speech signals,the study extracts the essential features from the speech signal using Cepstral Analysis.The features are extracted by converting the speech waveform to a parametric representation to obtain a relatively minimized data rate.Hence to improve the precision of classification,Generative Adversarial Networks are used and it tends to classify the speech signal after the extraction of features from the speech signal using the cepstral coefficient.The classifiers are trained with these features initially and the best classifier is chosen to perform the task of classification on new datasets.The validation of testing sets is evaluated using RL that provides feedback to Classifiers.Finally,at the user interface,the signals are played by decoding the signal after being retrieved from the classifier back based on the input query.The results are evaluated in the form of accuracy,recall,precision,f-measure,and error rate,where generative adversarial network attains an increased accuracy rate than other methods:Multi-Layer Perceptron,Recurrent Neural Networks,Deep belief Networks,and Convolutional Neural Networks.

Medicinal Plant Using Ground State Stabilization of Natural Antioxidant Curcumin by Keto-Enol Tautomerisation

Curcumin is a medicinal agent that exhibits anti-cancer properties and bioactive pigment in Turmeric has a huge thera-peutic value.It has a keto-enol moiety that gives rise to many of its chemical properties.A recent study has shown thatketo-enol tautomerisation at this moiety is implicated the effect of curcumin.The tautomerisation of curcumin in methanol.acetone and acetonitrile are used in nuclear magnetic resonance(^(1)H,^(13)C)spectroscopy.It was characterized using UV,IRand Raman spectral values.The molecular electrostatic potential surface of the Curcumin has been visualized in elec-tropositive potential in the region of the CH^(3+) group and most electronegative potential in the two oxygen atom has verystrong binding group.In the following,the modality of structural and thermo dynamical parameters,electrophilicity(ω).chemical potential(μ),chemical hardness(η) and electronic charge transfer confirms the local reactivity.The rate constantof tautomerisation of curcumin shows strong temperature dependence.Molecular electrostatic potential and Temperature dependence of various thermodynamic properties like(C^(0)_(p,m),S^(0)_(m),and H^(0)_(m))is increase with increase in temperature formonomer and dimer of various electrical fields.