Kongu Engineering College

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

Design and development of high performance solar photovoltaic inverter with advanced modulation techniques to improve power quality

Abstract: In addition to the focus towards growing demand on electrical energy due to the increase in population, industries, consumer loads, etc., the need for improving the quality of electrical power also needs to be considered. The design and development of solar photovoltaic (PV) inverter with reduced harmonic distortions is proposed. Unlike the conventional solar PV inverters, the proposed inverter provides the advantages of reduced harmonic distortions thereby intend towards the improvement in power quality. This inverter comprises of multiple stages which provides the required 230VRMS, 50 Hz in spite of variations in solar PV due to temperature and irradiance. The reduction of harmonics is governed by applying proper switching sequences required for the inverter switches. The detailed analysis is carried out by employing different switching techniques and observing its performance. With a separate mathematical model for a solar PV, simulations are performed in MATLAB software. To show the advantage ...

Improving secured ID-based authentication for cloud computing through novel hybrid fuzzy-based homomorphic proxy re-encryption

Abstract: Cloud computing environment (CCE) can empower an association to re-appropriate computing resources to increase monetary benefits For both developers and the cloud users (CUs), CCE is transparent Accordingly, it presents new difficulties when contrasted with precedent types of distributed computing The precision of assessment results in CCE security risk assessment to take care of the issue of the multifaceted nature of the system and the classified fuzzy cloud method (CFCM) applied to CCE chance ID stage that captures the CCE risk factors through a complete investigation of CCE security area Current CCE frameworks present a specific restriction on ensuring the client’s INFO privacy We offer a homomorphic proxy re-encryption (HPRE) in this paper that enables various CU to share INFO that they redistributed HPRE encrypted utilizing their PubKs with the plausibility by a close procedure such as INFO remotely The test of giving secrecy, uprightness, and access control (AC) of INFO facilitated on cloud stages is not provided for by conventional AC models CFCM models were created through the duration of numerous decades to satisfy the association’s necessities, which accepted full authority over the physical structure of the assets The hypothesis of the INFO proprietor, an INFO controller, and a supervisor is available in the equivalent trusted area Besides, CCESR features like the essential unit, fuzzy set (FS) hypothesis, and EW strategy utilized to precisely measure the likelihood of CCE security risks (SR) and the subsequent damages of CCESR estimation Eventually, the computation and authentication model specified, and the lack of CCE SECU threat evaluation examined

Association Rule Mining with Dynamic Adaptive Support Thresholds for Associative Classification

Abstract: The first and foremost task in any associative classification algorithm is mining of the association rules. Many studies have shown that the minimum support measure plays a key role in building an accurate classifier. Without the knowledge of the items and their frequency, user specified support measures are inappropriate, seldom may they coincide. .In this paper, we propose an approach called DASApriori i.e) Dynamic Adaptive Support Apriori to calculate the minimum support for mining class association rules and to build a simple and accurate classifier. Our experiments on 5 databases from UCI repository show that it achieves the best balance between the rule set size and classification accuracy even without the use of rule pruning techniques when compared with other associative classification approaches.

Another approach to solution of fuzzy differential equations by Modified Euler's method

Abstract: In this paper, numerical algorithms for solving “Fuzzy ordinary differential equations” are considered. A scheme based on the Modified Euler's method is discussed in detail and this is followed by a complete error analysis. Mathematics Subject Classification: 34A12; 65L05.