Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Conducting biopolymer electrolyte based on pectin with magnesium chloride salt for magnesium battery application

Abstract: Currently, biopolymer electrolytes are attracting a great deal of interest as substitute for synthetic polymer electrolytes in electrochemical devices, as they are carbon neutral, sustainable, reduce dependency on non-renewable fossil fuels and easily biodegradable. Some of the biopolymers under research are chitosan, pectin, agar–agar, cellulose acetate and carrageenan. The current work deals with the study of ion conducting polymer electrolyte, pectin with magnesium chloride salt for magnesium battery application. Biopolymer electrolytes of different compositions of pectin with different concentrations of magnesium chloride salt are prepared by solution casting technique and subjected to various studies like by X-ray diffraction (XRD), Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), AC impedance spectroscopy and linear sweep voltammetry (LSV). XRD analysis has been used to identify the amorphous/crystalline nature of the sample. The complex formation between the polymer pectin and the magnesium chloride salt has been analyzed by FTIR spectroscopy. DSC analysis is a thermo-analytical technique which is used to observe the glass transition temperature (Tg) of the samples. AC impedance technique has been used to find the ionic conductivities of the sample. The electrochemical stability of the polymer electrolyte has been analyzed by linear sweep voltammetry. Among the prepared polymer electrolytes, 30 M wt% pectin: 70 M wt% MgCl2 offers the highest ionic conductivity of 1.14 × 10−3 S cm−1. The electrochemical stability of the highest conducting sample is 2.05 V. The primary magnesium battery has been constructed using the highest conducting sample, 30 M wt% pectin: 70 M wt% MgCl2, and the battery performance has been studied.

Economics and impact of recycling solar waste materials on the environment and health care

Abstract: The growth of the renewable energy sector with solar energy resources playing a pivotal role, the proliferation of waste generated from the industry is a cause for concern. Globally the installed solar capacity is over 500 GW and is expected to rise further to 5000 GW by 2050. This phenomenal growth is expected to generate huge solar waste of up to 15% given the anticipated life span of 25 years. While the recent trends in solar research are aimed at improving little efficiency importance​ is given to waste disposal of dismantled solar power panels. Though recycling is an option, few companies are capable of handling recycling efficiently. To address this problem while ensuring environmental conservation and resource availability & recycling, the technologies adopted in the field are discussed and reviewed in this article. By 2050 60 million tons of solar waste will be there if it is not recycled properly. There view provides an in-depth assessment and the various technical aspects of the solar panel waste recycling and recovery, environmental protection, waste management. The economics of solar power recycling, impact on health and environmental and policies are discussed to ensure feasible and non-toxic technology for further development.

Skin lesion classification using decision trees and random forest algorithms

Abstract: Any superficial skin growth that does not resemble the surrounding area is referred to as skin lesion. It can occur in the form of mole, bump, cyst, rash or other changes that can be classified either as primary or secondary lesion. While primary skin lesions correspond to those changes in color or texture, secondary lesions occur as a primary lesion progression. Skin lesion image segmentation and classification at the early stages can help the patients recover through proper medication and treatment. Many algorithms for segmentation and classification are available in the literature but they all fail to extract lesion boundaries perfectly and classify them with more accuracy. To improve the reliability of the skin image segmentation and classification, we propose to use decision trees and random forest algorithms in this works and compare them with different data sets. The proposed method can generate high-resolution feature maps that can help to preserve the spatial details of the image. While tested against the ISIC 2017 and HAM10000 dataset, we found that the proposed method is more accurate as compared to the existing algorithms in this domain and is also very robust to artifacts or hair fibers present in the skin images.

Remote monitoring and control of LQR-PI controller parameters for an oil pipeline transport system:

Abstract: Today’s main energy sources such as natural gas, petrol, and petroleum products are transported via pipelines that are safe at long distances. Most of these pipelines are buried and their integrity...

Treatment and Reuse of Tannery Waste Water by Embedded System

Abstract: Due to scarcity of water problem in India especially southern part of India the large number small and medium scale industries are facing hectic loss in production. On the other hand the effluent discharged from these industries contaminates the water table and water sources. In this juncture, a novel technology should be developed to overcome these problems. Hence the present work focuses attention on the novel methods for treatment of tanner effluent and reuse for other purposes. For this purpose the experiments have been conducted by embedding UF and RO. Experiments have been performed for both UF and RO by varying the pressure and load to the membranes against the flux. Finally, based on the experimental results a suitable embedded system has been suggested for treating tannery effluent.