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A lightweight encryption authentication scheme using rectangle and chaotic logistic map algorithm for smart grid

Smart Grid is the advanced power grid system that combines renewable energy resources like wind, solar, biogas with the existing power system. Besides that, it provides two-way communication using a large number of electronic devices between the customer and providers which is also known as Advanced Metering Infrastructure (AMI). The devices are resource constraint devices and sensitive information is communicating through them. Therefore, in this paper, these constraints are taken under consideration and designed a lightweight encryption authentication scheme for AMI. The lightweight RECTANGLE and chaotic Logistic map algorithms are taken under consideration. These algorithms encrypt the information along with generating authentication tags. These tags are used on the receiver side to verify the authenticity of the data. The algorithm is simulated in MATLAB and various performance parameters calculated for it. After that, it is compared with the existing algorithms.

Published by: Arun Kumar, Puneet Jain

Author: Arun Kumar

Paper ID: V7I1-1178

Paper Status: published

Published: January 23, 2021

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Research Paper

Hybrid the artificial intelligence and swarm-based optimization algorithm for load forecasting in the smart grid

Electricity load forecasting algorithms are used in the smart grid to predict the electricity demand in the future. Besides that, it helps in reducing the electricity generation cost. In the literature, three types of load forecasting are done such as short-term, medium-term, and long-term. In this paper, the short term forecasting is done. The short-term forecasting algorithm predicts the electricity demand from a few hours to several weeks ahead. Due to the nonlinear, nonstationary, and non-seasonal nature of the electric load time series, accurate forecasting is challenging. In this paper, Artificial Intelligence (AI) and the swarm optimization algorithm is hybrid in order to improve the prediction of load forecasting. We have considered Artificial Neural Network (ANN) and Binary Particle Swarm Optimization (BPSO) algorithms in our work. The BPSO algorithm used to improve the learning rate in the ANN network. The experimental results were simulated in MATLAB and various performance metrics such as RMSE, MAPE, minimum and maximum error determined. The results show that the proposed algorithms provide better results as compared to the existing algorithms.

Published by: Kuljeet Singh Sandhu, Puneet Jain

Author: Kuljeet Singh Sandhu

Paper ID: V7I1-1179

Paper Status: published

Published: January 23, 2021

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Research Paper

Strength analysis of styrene-butadiene latex modified cement concrete

Polymer Modified Concrete (P.M.C.) has been discovered to be more potent than conventional cement because of its excellent strength and raised perseverance, so to enhance the performance, certain polymers are blended in with concrete. The impact of Styrene Butadiene Rubber (S.B.R.) over the compressive strengths, tensile strengths, and carbonation of cement has been examined in this investigation, and the ideal polymer content for concrete has additionally been resolved. This examination was attempted to decide the impacts of polymer expansion on compressive and tensile strengths utilizing concrete at nearby ambient temperature with a consistent water-cement proportion blend design. The mixes were prepared with a 0 %, 5 %, 10 %, 15 % and 20 % cement-latex ratio of Styrene-Butadiene Rubber. The fresh concrete slump test was performed while the compressive and tensile strengths were analyzed at various ages. S.B.R. latex has been appeared to have an unfavorable effect at an early age, even though applying S.B.R. latex to concrete at 28 days brings about improved compressive and tensile strength. However, the dosage of S.B.R. latex for mixtures rich in cement needs to be optimized in order to preserve the desired concrete workability.

Published by: Prafull Kumar Swarnkar, Abhay Srivastava

Author: Prafull Kumar Swarnkar

Paper ID: V7I1-1189

Paper Status: published

Published: January 23, 2021

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Research Paper

Design and fabrication of semi-automatic dishwasher machine

Though a lot of human activities are automated in the present competitive world. There is a lag in the automated dishwasher. Some machines are already designed with the help of high-velocity water only; hence there is a chance of uncleanliness and not removing tough strains in dishes. In order to overcome the above problems a special machine called – Semiautomatic Dishwasher Machine” with shower and water jet introduced in this work. The project is to design and fabricate a semiautomatic dishwasher that is efficient and overcome human work. In the market existing dishwasher, the spray arm is not sufficient to spray water in each part of the dish. So, keeping this in mind, we designed the circular rack and spray arm in the center of the machine which will spray the water equally and effectively in each and every area of the dish. The machine has less cycle time, less energy consumption, less water required for cleaning as compared to a manual machine.

Published by: Akash Gautam Gaurkhede, Dr. Mahendra P. Nawathe

Author: Akash Gautam Gaurkhede

Paper ID: V7I1-1187

Paper Status: published

Published: January 22, 2021

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Research Paper

Hybrid the bat and particle swarm optimization for demand-side management in the smart grid

The main goal of the demand side management program is shaping the load demand from peak load period to off-load period to reduce the generation cost. In the literature, various types of load shaping objectives available such as load shifting, valley filling, and peak clipping. In this paper, two optimization algorithms hybrid for load shaping. We have considered the BAT and Particle Swarm Optimization (PSO) algorithms in our work. These algorithms turn on/off the devices in an optimal way to reduce the cost and load consumption. The algorithm is simulated in MATLAB for two case studies in which 3 and 5 devices are taken under consideration. We have measured the total load consumption, cost, and execution time for the proposed algorithm and compared it with the existing algorithms. The results show that the proposed algorithm provides less load consumption and cost as compared to Normal ON-OFF and PSO algorithm.

Published by: Navdeep Singh Dhaliwal, Puneet Jain

Author: Navdeep Singh Dhaliwal

Paper ID: V7I1-1181

Paper Status: published

Published: January 22, 2021

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Research Paper

Enhance data hiding capacity and reduce variability using image steganography for smart grid

In the Smart Grid (SG) network, the sensitive data is communicated over the network and it prone to attacks. In order to overcome these attacks, security algorithms like cryptography and steganography are used. Steganography algorithms provide imperceptibility by hiding the secret data in the cover image whereas cryptography algorithms scramble the data using a private key and scramble data gives attention to the attacker. In steganography, the Least Significant Bit (LSB) is the most preferred data hiding algorithm. In the LSB algorithm, the data is split into 1-bit chunks and hide in the cover image LSB bit. The LSB algorithm provides less variability with less embedding capacity. In this paper, we have designed an algorithm that provides better embedding capacity and lesser variability. Initially, the cover pixel read is read and its intermediate bits 5th and 6th are taken as a reference to hiding k-bits of data using the LSB algorithm. The benefit of taking the intermediate bits of the cover pixel as a reference is that no need to communicate reference bits information with the receiver. After that, the LSB bit of the stego image generated after data hiding is circularly rotated in order to reduce the variability. The experimental results were performed on the standard dataset images and various performance metrics calculated for it. Lastly, the proposed algorithm is compared with the existing algorithms and found that the proposed algorithm achieves randomness and better embedding capacity.

Published by: Muzamil Lateef Wagay, Puneet Jain

Author: Muzamil Lateef Wagay

Paper ID: V7I1-1180

Paper Status: published

Published: January 22, 2021

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