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Arungalai Vendan S.,Vellore Institute of Technology | Chinnadurai T.,Vellore Institute of Technology | Senthil Kumar K.,Veltech Technical University | Prakash N.,Thangavelu Engineering College
International Journal of Advanced Manufacturing Technology | Year: 2015

Polycarbonate (PC) and ABS materials have several beneficial characteristics which facilitates its application in various industrial sectors, while developing products based on these polymers it is essential to enable the scope of its weldability feature. Considering this critical factor, researchers have been involved in investigating the weldability behavior of the above-mentioned polymers. However, there are no complete reports addressing the feasibility of welding of polymer mixtures. It has been observed that combination of two polymers with proper understanding of inbuilt chemical structures has yielded a hybrid polymer whose properties in terms of its strength, chemical bonding, structural integrity, and range of flexibility are higher. Hence, in this study, a pivotal attempt is made to develop a hybrid polymer with a combination of 60 % PC and 40 % ABS. Further, the polymer is subjected to ultrasonics to examine the conduciveness of this material for welding. The parameters controlling the weldability using ultrasonic’s are also varied within a range in order to identify the optimum parametric values. Subsequently, the welded specimens are tested for evaluating its strength and quality. Tests from the insight of chemical engineering is also carried out to access the chemical structural stability and to monitor the formation of the plastic which preferably adopts a thermoplastic feature. The results establish the feasibility and credibility of these polymers for welding which is the industrial demand. © 2015 Springer-Verlag London Source

Ramapraba P.S.,Panimalar Institute of Technology | Ranganathan H.,Thangavelu Engineering College
International Journal of Applied Engineering Research | Year: 2015

Cervical cancer kills 260,000 women annually, and nearly 85% of these deaths occur in developing nations. Also it is the leading cause of cancer deaths in women. Disparities of health and poverty play a large role in this high mortality rate. This paper presents an automatic cervical cancer detection technique using colposcopic images. Wavelet and statistical based features are used to distinguish normal and abnormal tissue. The statistical features such as mean, standard deviation and skewness are obtained in the spatial domain. The wavelet energies are extracted from the wavelet decomposed image. Then these features are combined to form the feature vector and used for the detection. The segmented cancer region shows that the proposed fusion approach can detect the cancer affected region accurately than the wavelet and statistical features based approaches. © Research India Publications. Source

Shobana F.J.J.,Sri Lakshmi Ammal Engineering College | Narayanasamy R.,Thangavelu Engineering College
Eurasip Journal on Wireless Communications and Networking | Year: 2014

Wireless sensor networks face many threats which drain the energy. The performance of sensor network routing is much affected in the presence of selfish nodes with messages being delivered with a longer delay. Social network routing is a method in which the messages are selectively forwarded through the nodes where the encounters between these nodes are more likely to occur. Network reputations clearly speak about the quality of nodes involved in data forwarding. The idea is to utilise social network reputations of source or destinations for effective data forwarding in farmland sensor networks. © 2014, Shobana and Narayanasamy; licensee Springer. Source

Prakash N.,Thangavelu Engineering College | Arungalai Vendan S.,Vellore Institute of Technology
International Journal of Biological Macromolecules | Year: 2016

The ternary blends consisting of Chitosan (CS), Nylon 6 (Ny 6) and Montmorillonite clay (MM clay) were prepared by the solution blending method with glutaraldehyde. The prepared ternary blends were characterization by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Thermo gravimetric analysis (TGA), Differential scanning calorimetry (DSC) and Scanning electron microscope (SEM). The FTIR results showed that the strong intermolecular hydrogen bondings were established between chitosan, nylon 6 and montmorillonite clay. TGA showed the thermal stability of the blend is enhanced by glutaraldehyde as Crosslink agent. Results of XRD indicated that the relative crystalline of the pure chitosan film was reduced when the polymeric network was reticulated by glutaraldehyde. Finally, the results of scanning electron microscopy (SEM) indicated that the morphology of the blend was rough and heterogenous. Further, it confirms the interaction between the functional groups of the blend components. The extent of removal of the trace metals was found to be almost the same. The removal of these metals at different pH was also done and the maximum removal of the metals was observed at pH 4.5 for both trace metals. Adsorption studies and kinetic analysis have also been made. Moreover, the protonation of amine groups is induced an electrostatic repulsion of cations. When the pH of the solution was more than 5.5, the sorption rate began to decrease. Besides, the quantity of adsorbate on absorbent was fitted as a function in Langmuir and Freundlich isotherm. The sorption kinetics was tested for pseudo first order and pseudo second order reaction. The kinetic experimental data correlated with the second order kinetic model and rate constants of sorption for kinetic models were calculated and accordingly, the correlation coefficients were obtained. © 2015. Source

Kumar R.,Satyabama University | Ranganathan H.,Thangavelu Engineering College
International Journal of Applied Engineering Research | Year: 2014

Algorithms based on Machine Learning provides abundant scope to assess and classify a database built in the backdrop of biological states. This paper proposes a machine learning algorithm to scrutinize representative values of the subjects to yieldorganized classification. The scheme was implemented on two diverse states signifying values recorded under two different wavelengths. The effectiveness of the scheme is validated against indicators confusion matrix and Z-statistic. The algorithm symbolizes each state and the efficiency is measured by performance metric namely Precision, Recall and F-measure. The proposed classifiers exhibit 60% and 74. 40%, 66. 96% and 78. 80%, 0. 6328 and 0. 7653 respectively. © Research India Publications. Source

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