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.

Retracted: Optimization of Ultrasound-Assisted Extraction of Natural Pigments from Amaranthus tricolor L Leaves

Abstract: The above article, published online on 27 March 2015 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editors in Chief, Charles Brennan and Brijesh K. Tiwari, and Wiley Periodicals, Inc. The retraction has been agreed due to evidence indicating that the peer review of this paper was compromised. It is believed that the paper was accepted based on recommendations from reviewers not suitably qualified. Reference Prakash Maran, J. and Priya, B. 2015. Optimization of ultrasound-assisted extraction of natural pigments from Amaranthus tricolor L Leaves. J. Food Process. Preserv. 39, 2314–2321. doi: 10.1111/jfpp.12478.

Characterization and experimental validation of a semi-empirical fuel cell model for investigating the water dynamics on the electrical behavior of a 5 kW Ballard stack system using Nafion 117 polymer membrane

Abstract: There has been increasing interest in the development of Polymer Electrolyte Membrane Fuel Cells (PEMFCs) in recent years as they are the most promising clean energy source for applications in industrial, automotive, portable, and stationary devices. In the present study, characterization of a semi-empirical polymer electrolyte membrane fuel cell model for a test bench of a 5 kW Ballard fuel cell system using a Nafion 117 membrane is performed for the effect of water dynamics on its electrical behavior as it is viewed as a serious issue by fuel cell researchers. The model performance is evaluated for its static and dynamic behavior through the experimental results obtained from a 5 kW Ballard fuel cell stack system to investigate the internal water phenomena of the membrane. The findings of the investigation indicate that the performance of PEMFCs can be significantly improved by maintaining the membrane water content, H2O/SO3−H+, to its optimal value. Thus, the developed model serves as a benchmark tool for the scientific and industrial community to optimize and evaluate the structural design of the PEMFC system for its scale up in terms of its water dynamics.

Fuzzy fast classification algorithm with hybrid of ID3 and SVM

Abstract: The Classification of data is usually very large database that is the reason we want to classify the large data into different fragmentation of its same type. Already many algorithms have been used for classification like Id3, rule based algorithm, decision tree based algorithm, k-nearest-neighbor classification and so on. And these algorithm mainly used for classifying the algorithm accurately and the concept of fast classification is lagging behind in the previous algorithms. In this paper we analysis the efficiency and accuracy of using the entropy, id3 and SVM algorithm with our proposed method of using entropy and fuzzy classification with lower and upper approximation to reduce the computation work for more accuracy classification. We use id3 algorithm to classify the complex member that lie between the lower and upper approximation. Now we use SVM algorithm to classify the other data members thus by hybrid of both the algorithm with our approximation we get the best result of the algorithm Fuzzy Fast Classification FFC. The result of experiments shows that the improved fuzzy fast classification algorithm considerably reduces the computational complexity and improves the speed of classification particularly in the circumstances of the large data.

ECG de-noising based on hybrid technique

Abstract: From early years, Electrocardiogram (ECG) signal has a vital role in diagnosis process and finding information regarding heart diseases. Good quality ECG is used by doctors for identification of physiological and pathological phenomena. For minimum signal degradation, De-noising is performed to reduce noise intensity level. As signal is corrupted by noise, de-noising is important and usual in many applications. Effective suppression of noise in ECG is a classical problem. The proposed method is a hybrid technique, combining Empirical Mode Decomposition (EMD) and Wavelet thresholding. EMD has good ability to decompose the signal. Wavelet thresholding is good in removing the noise from decomposed signal. Using the advantages of both methods, performance of de-noising has been improved. EMD is applied to decompose the noisy Electrocardiogram (ECG) into a series of intrinsic mode functions (IMF) then thresholding is done on each IMF. Finally, the signal is reconstructed with the processed IMF to get the de-noised ECG. From the results it is clear that the proposed method has improved performance.