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.

Response surface modelling and optimization of treatment of meat industry wastewater using electrochemical treatment method

Abstract: In this present study, electrochemical (EC) treatment was used to treat meat industry wastewater. Effects of EC process variables such as pH, electrolysis time, current density and electrolyte dose on the removal efficiency of chemical oxygen demand (COD) and colour were examined. Four factors three level Box–Behnken response surface design (BBD) coupled with response surface methodology (RSM) was employed to optimize the EC process variables. Second order polynomial models were developed for the responses and three dimentional (3D) response surface plots were used to study the interactive effects of the process variables on the EC treatment efficiency. The experimental results showed that, EC effectively reduced the COD (92%) and colour (98%) of the meat industry wastewater under the optimum conditions such as pH of 7, electrolysis time of 45 min, current density of 35 mA/cm2 and electrolyte dose of 1.4 g/L, respectively. The operating cost of the treatment process under the optimum conditions is found to be 1.6 $/m3.

A Heuristic Angular Clustering Framework for Secured Statistical Data Aggregation in Sensor Networks.

Abstract: Clustering in wireless sensor networks plays a vital role in solving energy and scalability issues. Although multiple deployment structures and cluster shapes have been implemented, they sometimes fail to produce the expected outcomes owing to different geographical area shapes. This paper proposes a clustering algorithm with a complex deployment structure called radial-shaped clustering (RSC). The deployment structure is divided into multiple virtual concentric rings, and each ring is further divided into sectors called clusters. The node closest to the midpoint of each sector is selected as the cluster head. Each sector’s data are aggregated and forwarded to the sink node through angular inclination routing. We experimented and compared the proposed RSC performance against that of the existing fan-shaped clustering algorithm. Experimental results reveal that RSC outperforms the existing algorithm in scalability and network lifetime for large-scale sensor deployments.

Word and triphone based approaches in continuous speech recognition for Tamil language

Abstract: Building a continuous speech recognizer for the Indian language like Tamil is a challenging task due to the unique inherent features of the language like long and short vowels, lack of aspirated stops, aspirated consonants and many instances of allophones. Stress and accent vary in spoken Tamil language from region to region. But in formal read Tamil speech, stress and accents are ignored. There are three approaches to continuous speech recognition (CSR) based on the sub-word unit viz. word, phoneme and syllable. Like other Indian languages, Tamil is also syllabic in nature. Pronunciation of words and sentences is strictly governed by set of linguistic rules. Many attempts have been made to build continuous speech recognizers for Tamil for small and restricted tasks. However medium and large vocabulary CSR for Tamil is relatively new and not explored. In this paper, the authors have attempted to build a Hidden Markov Model (HMM) based word and triphone acoustic models. The objective of this research is to build a small vocabulary word based and a medium vocabulary triphone based continuous speech recognizers for Tamil language. In this experimentation, a word based Context Independent (CI) acoustic model for 371 unique words and a triphone based Context Dependent (CD) acoustic model for 1700 unique words have been built. In addition to the acoustic models a pronunciation dictionary with 44 base phones and trigram based statistical language model have also been built as integral components of the linguist. These recognizers give very good word accuracy for trained and test sentences read by trained and new speakers.

Influence of surface texture shape, geometry and orientation on hydrodynamic lubrication performance of plane-to-plane slider surfaces

Abstract: This paper investigates the effect of surface texturing on the tribological performance of hydrodynamic slider surfaces. The geometric parameters of the texture considered were the texture shape, bottom profile, orientation and depth. A theoretical model based on the steady-state Reynolds equation was solved numerically by finite difference method to analyse the effect of surface texturing. The optimum geometry of each texture shape was determined, for which, the film thickness was maximised and the friction coefficient was minimised. Among all the shapes, the square with a single wedge bottom profile outperformed. The performance of the triangle, the chevron and the ellipse was highly influenced by their orientation with respect to the sliding direction. Texture density was found to be more dominant in impacting the tribological performance than the texture aspect ratio. The results obtained were further discussed with respect to the studies available in literature to emphasise the significance of the findings. Copyright © 2016 John Wiley & Sons, Ltd.

Multi constraints applied energy efficient routing technique based on ant colony optimization used for disaster resilient location detection in mobile ad-hoc network

Abstract: A mobile ad-hoc network (MANET) is a group of advanced mobile devices which are capable of self-organization. Due to the diverse nature of mobile devices and wireless connectivity, MANET faces several issues like topology management, energy management due to battery power limits, data communication issues etc. The utilization rate of battery powered energy and QoS properties are significant in MANET. In order to address these issues, we propose a new ant colony inspired technique for energy efficient routing in MANET. The proposed technique is a multi-objective constraints applied energy efficient routing technique based on ant colony optimization in mobile adhoc networks (MCER-ACO). The proposed MCER-ACO technique selects the next hop node centered on the constraints, residual energy of mobile node, no of packets in path and dynamic movement of topology. By applying ant colony technique on objectives and constraints, probability of choosing next hop node as forwarding node is determined. From the performance evaluation carried out in this research work, it is proved that the proposed MCER-ACO approach is providing optimal energy efficient routing while comparing with few other existing methods.