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Research Paper

Comparative analysis of tuning technique of fuzzy logic PID controllers and classical PID controllers over armature control DC motor

This paper give solution of tuning technique of PID (Proportional integral derivative) controller by using Ziegler-Nichols and fuzzy logic technique applied in speed control of DC motor. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are regulate according to fuzzy logic technique. The Fuzzy logic Proportional integral derivative FLPID controller is designed according to fuzzy rules. Twenty five self tuning rules are programmed for PID controller. Two inputs are applied to PID controller one for speed error actual speed and the second is rate of change in speed error. The Parameter of PID controllers are used to control the speed of the DC Motor. The MATLAB model for speed control of DC motor using fuzzy logic is easy and less calculation required. The results proof that the designed self-tuned PID controller perform optimum speed control of DC motor, and compared the FLPID conventional PID controller.

Published by: Dr. Abhishek Kumar, Arpana Kumari, Arvind Kumar

Author: Dr. Abhishek Kumar

Paper ID: V6I5-1367

Paper Status: published

Published: October 15, 2020

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Research Paper

A disease prediction system based on Machine Learning algorithms and ensembles using real-time data gathered through wearable medical sensors

Even with an Annual expenditure $ 8.2 billion (F.Y. 2018-19), Indian healthcare system is far from being affordable and accessible. While the economic development has been gaining momentum since the last decade, India needs major reforms in existing healthcare system. Technology has an important role to play in streamlining the health infrastructure. A Disease prediction system has been proposed to address various deficiencies and provide affordable, readily-available and cost-effective healthcare. The proposed system can effectively predict life threatening diseases like Diabetes and Heart Disease. The system has been implemented by using Machine Learning Algorithms and enhanced to be more accurate than the existing systems. The system is backed by robust Machine Learning Algorithms and ensembles that will predict presence/absence of the diseases accurately. Accurate analysis of medical data benefits early disease detection, patient care and community services. To overcome the difficulty of incomplete data, the system uses Wearable Medical Sensors to gather Real-time data and make prediction based on the collected data. Presently, we demonstrate the system for two diseases but it can be scaled for tackling more diseases. The Disease Prediction system will not only reduce the burden on existing healthcare and diagnosis system but also provide personalized medication.

Published by: Sameer Kulkarni, Gargi Hartalkar, Bhumika Mahajan, Pranav Jawaji

Author: Sameer Kulkarni

Paper ID: V6I5-1339

Paper Status: published

Published: October 15, 2020

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Research Paper

Assessment of metal contamination by using pollution indices in groundwater sources that used for drinking purpose in Olpad taluka, surat, India

The present study was conducted to judge pollution situation and evaluates their sources and distribution of Heavy Metals in the ground water sources of Olpad taluka, Surat, Gujarat, India. Ground water sources such as hand pump bore well, tube well and open well are used for drinking purpose in different villages of Olpad taluka. Heavy metal pollution index (HPI), Heavy Metal Evaluation Index (HEI) and Degree of Contamination (Cd) is representing a quality of water in terms of index numbers that represents the heavy metal load in the ground water sources. Monthly sampling was done from seven sampling sites (Feb’ 2015 to July’ 2015). Heavy metals concentration in water samples were measured by following standard method of APHA and analysed by Atomic Absorption Spectrophotometer. Heavy metals like, Cu, Ni, Zn, Fe, Mn, Cd, Pb and Cr were analysed from monthly collected samples. Heavy metal affects the health in a wide range if it is present above the permissible limit. Based on calculated results of HPI, HEI and Cd it was found that the water was contaminated with metals.

Published by: Patel Monali, Kapila Manoj

Author: Patel Monali

Paper ID: V6I5-1329

Paper Status: published

Published: October 15, 2020

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Review Paper

Explaining Global warming through Quantum Mechanics

The paper goes over climate change and global warming followed by a quantum mechanical approach to explain global warming. By using the principles of the radiative theory and spectroscopic data from the HITRAN database for greenhouse gases along with data from the AIRS satellite, we were able to claim that the principles of radiative theory and quantum mechanics can indeed be used to explain climate change.

Published by: Aditya Iyer, Mitali Arun

Author: Aditya Iyer

Paper ID: V6I5-1359

Paper Status: published

Published: October 15, 2020

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Research Paper

Fuzzy logic technique applied in tuning of PID controller to control speed of DC motor

This paper give solution of tuning technique of PID (Proportional integral derivative) controller by using fuzzy logic technique applied in speed control of DC motor. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are regulate according to fuzzy logic technique. The Fuzzy logic Proportional integral derivative controller (FLPIDC) is designed according to fuzzy rules. Twenty five self tuning rules are programmed for PID controller. Two inputs are applied to PID controller one for speed error actual speed and the second is rate of change in speed error. The Parameter of PID controllers are used to control the speed of the DC Motor. The MATLAB model for speed control of DC motor using fuzzy logic is easy and less calculation required. The results proof that the designed self-tuned PID controller perform optimum speed control of DC motor, compared to conventional PID controller.

Published by: Dr. Abhishek Kumar

Author: Dr. Abhishek Kumar

Paper ID: V6I5-1366

Paper Status: published

Published: October 15, 2020

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Research Paper

Self-balancing of a Two wheeler using Gyroscopic effect

In this day and age automation has become more of a necessity than a luxury. Today despite of having a number of preventive safety measures to avoid road accident by two wheelers according to the surveys two wheeler lead in the number of road accidents. The need for a self-stabilizing system for two wheelers is on high demand among the customers. This paper determines a method to develop a self-balancing bike using gyroscopic effect. Gyroscopic effects finds its application in stabilizing systems for sectors like Military’s rocket guidance systems, aeronautics and aerospace industries, ships etc. We have incorporated this principle in our two wheeler model. In our current model we have used Inertial Measurement Unit(IMU), Encoder and servo motors, Momentum wheel to generate a counter torque to balance the roll in the two wheeler. The 3D model was designed using CAD modelling software and code was generated in the Arduino software. Designing and fabrication of the two wheeler was completed and was tested for different tilt angle subjected to varying rotational speed of momentum wheel to counter balance and stabilize itself.

Published by: Yadhukrishnan, Ishaan Rahul Saxena

Author: Yadhukrishnan

Paper ID: V6I5-1358

Paper Status: published

Published: October 15, 2020

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