Thapar University

About: Thapar University is a education organization based out in Patiāla, Punjab, India. It is known for research contribution in the topics: Computer science & Cloud computing. The organization has 2944 authors who have published 8558 publications receiving 130392 citations.

Forecasting daily global solar irradiance generation using machine learning

Abstract: Rechargeable wireless sensor networks mitigate the life span and cost constraints propound in conventional battery operated networks. Reliable knowledge of solar radiation is essential for informed design, deployment planning and optimal management of self-powered nodes. The problem of solar irradiance forecasting can be well addressed by machine learning methodologies over historical data set. In proposed work, forecasts have been done using FoBa, leapForward, spikeslab, Cubist and bagEarthGCV models. To validate the effectiveness of these methodologies, a series of experimental evaluations have been presented in terms of forecast accuracy, correlation coefficient and root mean square error (RMSE). The r interface has been used as simulation platform for these evaluations. The dataset from national renewable energy laboratory (NREL) has been used for experiments. The experimental results exhibits that from few hours to two days ahead solar irradiance prediction is precisely estimated by machine learning based models irrespective of seasonal variation in weather conditions.

Tactile Internet for Smart Communities in 5G: An Insight for NOMA-Based Solutions

Abstract: In the last few years, there has been an exponential increase in the deployment of 5G-based test beds across the globe with an aim to reduce the latency for accessing various applications. The integration of generic services such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), critical machine-type communication (cMTC), and ultra-reliable low-latency communications (URLLC) can improve the performance of 5G-based applications. This service heterogeneity can be achieved by network slicing for an optimized resource allocation and an emerging technology, Tactile Internet, to achieve low latency, high bandwidth, service availability, and end-to-end security. In this paper, we discuss the application-specific nonorthogonal multiple access (NOMA)-based communication architecture for Tactile Internet which allows nonorthogonal resource sharing from a pool of eMBB, mMTC, cMTC, and URLLC devices to a shared base station. We summarize various variants of NOMA and their suitability for future low latency Tactile-Internet-based applications.

Enhancement of Cellulase Activity from a New Strain of Bacillus subtilis by Medium Optimization and Analysis with Various Cellulosic Substrates.

Abstract: The cellulase activity of Bacillus subtilis AS3 was enhanced by optimizing the medium composition by statistical methods. The enzyme activity with unoptimised medium with carboxymethylcellulose (CMC) was 0.07 U/mL and that was significantly enhanced by CMC, peptone, and yeast extract using Placket-Burman design. The combined effects of these nutrients on cellulase activity were studied using 22 full factorial central composite design. The optimal levels of medium components determined were CMC (1.8%), peptone (0.8%), and yeast extract (0.479%). The maximum enzyme activity predicted by the model was 0.49 U/mL which was in good agreement with the experimental value 0.43 U/mL showing 6-fold increase as compared to unoptimised medium. The enzyme showed multisubstrate specificity, showing significantly higher activity with lichenan and β-glucan and lower activity with laminarin, hydroxyethylcellulose, and steam exploded bagasse. The optimised medium with lichenan or β-glucan showed 2.5- or 2.8-fold higher activity, respectively, at same concentration as of CMC.

Anonymous Lightweight Chaotic Map-Based Authenticated Key Agreement Protocol for Industrial Internet of Things

Abstract: With an exponential increase in the popularity of Internet, the real-time data collected by various smart sensing devices can be analyzed remotely by a remote user (e.g., a manager) in the Industrial Internet of Things (IIoT). However, in the IIoT environment, the gathered real-time data is transmitted over the public channel, which raises the issues of security and privacy in this environment. Therefore, to protect illegal access by an adversary, user authentication mechanism is one of the promising security solutions in the IIoT environment. To achieve this goal, we propose a new user authenticated key agreement scheme in which only authorized users can access the services from the designated IoT sensing devices installed in the IIoT environment. In the proposed scheme, fuzzy extractor technique is used for biometric verification. Moreover, three factors, namely smart card, password and personal biometrics of a legal registered user are applied in the proposed scheme to increase the level of security in the system. The proposed scheme supports new devices addition after initial deployment of the devices, password/biometric change phase and also smart card revocation phase in case the smart card is lost or stolen by an adversary. In addition, the proposed scheme is lightweight in nature. We carry out the formal security analysis using the broadly accepted Real-Or-Random (ROR) model and also the non-mathematical (informal) security analysis on the proposed scheme. Furthermore, the formal security verification using the popularly-used AVISPA (Automated Validation of Internet Security Protocols and Applications) tool is carried out on the proposed scheme. The detailed security analysis assures that the proposed scheme can withstand several well-known attacks in the IIoT environment. A practical demonstration using the NS2 simulation study is also performed for the proposed scheme and other related existing schemes. Also, a detailed comparative study shows that the proposed scheme is efficient, and provides superior security in comparison to the other schemes.