Informatics Publishing Limited

V. Mohanraj , A. Mala

Abstract

The proposed project uses an Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) Controller to an Interleaved Soft Switching Boost Converter for a stand alone system. This topology used to raise the efficiency of the converter of the PV power conditioning system. It minimizes switching losses by adopting a resonant soft-switching method. The overall efficiency is increased when compared with the conventional hard switching interleaved boost converter. ANN based Maximum power point tracking gives accurate tracking of operating points and improves panel efficiency. Simulation is done using MATLAB Software. The simulation results show the low input current ripple, high overall efficiency and good transient response is achieved.

Keywords

Maximum Power Point Tracking (MPPT), Interleaved Soft Switching Boost Converter (ISSBC), Resonant Switching, Artificial Neural Network (ANN), Backpropogation Feed forward Network

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S. David Samuel Azariya ¹, V. Mohanraj ¹, J. Jeba Emilyn ¹, G. Jothi ²

Affiliations
1 Department of Information Technology, Sona College of Technology, IN
2 Department of Computer Applications, Sona College of Arts and Science, IN

Abstract

Missing data is a regular concern on data that professionals have to deal with. Efficient analysis techniques have to be followed to find interesting patterns. In this study, we are comparing 16 different imputation methods namely Linear, Index, Values, Nearest, Zero, slinear, Quadratic, Cubic, Barycentric, Krogh, Polynomial, Spline, Piecewise Polynomial, From derivatives, Pchip and Akima. These techniques are performed on real time UCI dataset and are under Missing Completely at a Random (MCAR) assumption, our result suggests the nearest, zero, quadratic and polynomial imputation methods which provides above 96% of accuracy when compared to the other techniques.

Keywords

Missing Data, Imputation Methods, Missing Completely at Random.

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M. Hema Kumar ¹, V. Mohanraj ², Y. Suresh ², J. Senthilkumar ², G. Nagalalli ³

Affiliations
1 Department of Biomedical Engineering, Mahendra Institute of Technology, Namakkal, Tamil Nadu, IN
2 Department of Information Technology, Sona College of Technology, Salem, Tamil Nadu, IN
3 Department of Electronics and Communication Engineering, Sona College of Technology, Salem, Tamil Nadu, IN

Abstract

Wireless Sensor Network (WSN) is most vulnerable to routing attacks which affects the confidentiality and integrity services of the data transmitted between any nodes. Many research efforts have been taken to propose secure routing schemes for improving the data security against routing attacks in WSN. The existing secure routing schemes are not able to dynamically discover the trust path between nodes for ensuring secure transmission without compromising confidentiality and integrity service. To address this issue, a real-time, two-hop neighbour, strategically secure routing scheme is proposed in this paper. According to the strategy of two-hop neighbours, the method selects the forwarding node according to the trust measures computed based on trust energy support and trust forwarding support of the two hop nodes. Further, the data security is enforced at the attribute level. The Blockchain mechanism is enforced where a single block contains information of specific attribute of data which restrict the user who have access to the attribute only can read the data present in the block. The data encryption is performed according to different encryption standards maintained by the system, unique for different attributes. According to the Hash code present in the Blockchain, the user can decode the key and scheme to obtain the original data. The proposed approach improves the performance in secure routing and increases the data security performance.

Keywords

WSN, Data Security, Secure Routing, Two Hop Neighbour Strategy, Blockchain, QoS.

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