Sir Padampat Singhania University

About: Sir Padampat Singhania University is a education organization based out in Udaipur, India. It is known for research contribution in the topics: Encryption & Diesel fuel. The organization has 124 authors who have published 228 publications receiving 2066 citations. The organization is also known as: SPSU.

Prediction of the Onset of Diabetes Using Artificial Neural Network and Pima Indians Diabetes Dataset

Abstract: When a human body unable to respond to the insulin properly and/or unable to produce the required amount of insulin to regulate glucose, it means that the human body is suffering from Diabetes. Diabetes increases the risk of developing another disease like heart disease, kidney disease, and damage to blood vessels, nerve damage, and blindness. The diagnosis of diabetes using proper analysis of diabetes data is a significant problem. In this paper, an automatic diagnosis system is introduced and analyzed. For this purpose, a Three-Layered Artificial Neural Network (ANN) and Pima Indians Diabetes dataset are used. In this ANN based prediction model, a logistic-activation-function for activation of neurons, and the Quasi Newton method is used as the algorithm for the training. As a result cumulative gain plot and as a measure of the quality of this model the maximum gain score is used.

Identification of faults through wavelet transform vis-à-vis fast Fourier transform of noisy vibration signals emanated from defective rolling element bearings

Abstract: Fault diagnosis of rolling element bearings requires efficient signal processing techniques. For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuous wavelet transform (CWT) of vibration signals produced from a bearing with defects on inner race and rolling element, have been examined at low signal to noise ratio. Both simulated and experimental signals from identical bearings have been considered for the purpose of analysis. The bearings have been modeled as spring-mass-dashpot systems and the simulated signals have been obtained considering transfer functions for the bearing systems subjected to impulsive loads due to the defects. Frequency B spline wavelets have been applied for CWT and a discussion on wavelet selection has been presented for better effectiveness. Results show that use of CWT with the proposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection of bearings.

Effect of sliding speed and temperature on the tribological behavior of pongamia oil-based blended lubricant

Abstract: The increase in industrialization has created the demand for petroleum-based lubricants throughout the world. The decrease in availability of mineral oils and their hazards related to the environme...

An Analytical approach based on self organized maps (SOM) in Indian classical music raga clustering

Abstract: This paper is mainly focusing the aspects regarding the Self organized maps in the recognition of the Ragas and the strategy behind the Digital signal processing for the raga recognition and clustering of the same. Paper mainly describes all the features extraction mechanism for the SOM input and we devised an algorithm for creating the clusters of the raga based on their PCP (pitch class profiles) and the onsets detected. Our strategy is very promising that its providing better clusters of the raga patterns and the raga segments are very much clearly be distinguished from the other ragas, as we compared them with the formation of the key attributes. The Indian classical music history is very old and the need for identifying the music based on the raga onsets is very much helping for the music professionals and domestic users for identifying and detecting the raga types and using the same without the help or availability of any experts nearby. Thus our strategy is very promising in nature for the novice users and practitioners as well as home users. The very early learners would also find it very interesting and supportive after due course of frequent uses of it. At last we provided the future possibilities for the enhancements.