Thapar University

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

Review and the state of the art: Sol-gel and melt quenched bioactive glasses for tissue engineering.

Abstract: Biomaterial development is currently the most active research area in the field of biomedical engineering. The bioglasses possess immense potential for being the ideal biomaterials due to their high adaptiveness to the biological environment as well as tunable properties. Bioglasses like 45S5 has shown great clinical success over the past 10 years. The bioglasses like 45S5 were prepared using melt-quenching techniques but recently porous bioactive glasses have been derived through sol-gel process. The synthesis route exhibits marked effect on the specific surface area, as well as degradability of the material. This article is an attempt to provide state of the art of the sol-gel and melt quenched bioactive bioglasses for tissue regeneration. Fabrication routes for bioglasses suitable for bone tissue engineering are highlighted and the effect of these fabrication techniques on the porosity, pore-volume, mechanical properties, cytocompatibilty and especially apatite layer formation on the surface of bioglasses is analyzed in detail. Drug delivery capability of bioglasses is addressed shortly along with the bioactivity of mesoporous glasses. © 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 104B: 1248-1275, 2016.

Energy-aware Virtual Machine Migration for Cloud Computing - A Firefly Optimization Approach

Abstract: Energy efficiency has grown into a latest exploration area of virtualized cloud computing paradigm. The increase in the number and the size of the cloud data centers has propagated the need for energy efficiency. An extensively practiced technology in cloud computing is live virtual machine migration and is thus focused in this work to save energy. This paper proposes an energy-aware virtual machine migration technique for cloud computing, which is based on the Firefly algorithm. The proposed technique migrates the maximally loaded virtual machine to the least loaded active node while maintaining the performance and energy efficiency of the data centers. The efficacy of the proposed technique is exhibited by comparing it with other techniques using the CloudSim simulator. An enhancement in the average energy consumption of about 44.39 % has been attained by reducing an average of 72.34 % of migrations and saving 34.36 % of hosts, thereby, making the data center more energy-aware.

Hybrid Microgrid Many-Objective Sizing Optimization With Fuzzy Decision

Abstract: The economics, reliability, and carbon efficiency of hybrid microgrid systems (HMSs) are often in conflict; hence, a reasonable design for the sizing of the initial microgrid is important. In this article, we propose an improved two-archive many-objective evolutionary algorithm (TA-MaEA) based on fuzzy decision to solve the sizing optimization problem for HMSs. For the HMS simulated in this article, costs, loss of power supply probability, pollutant emissions, and power balance are considered as objective functions. For the proposed algorithm, we employ two archives with different diversity selection strategies to balance convergence and diversity in the high-dimensional objective space. In addition, a fuzzy decision making method is proposed to further help decision makers obtain a solution from the Pareto front that optimally balances the objectives. The effectiveness of the proposed algorithm in solving the HMS sizing optimization problem is investigated for the case of Yanbu, Saudi Arabia. The experimental results show that, compared with the two-archive evolutionary algorithm for constrained many-objective optimization (C-TAEA), the clustering-based adaptive many-objective evolutionary algorithm (CA-MOEA), and the improved decomposition-based evolutionary algorithm (I-DBEA), the proposed algorithm can reduce the system costs by 7%, 13%, and 21%, respectively.

HaBiTs: Blockchain-based Telesurgery Framework for Healthcare 4.0

Abstract: Telesurgery has a huge potential to deliver a real-time healthcare surgical services to the remote or distant locations with high quality and accuracy over the wireless communication channel. It provides benefits to the society with improved precision and accuracy in diagnosis procedures. However, the existing telesurgery system has the security, privacy, and interoperability issues, which limits its applicability in healthcare centers across the world in future. To mitigate these issues, in this paper, we propose, a framework named as HaBiTs (blockchain-based secure and flawless inter-operable telesurgery), where security can be achieved with immutability and interoperability by Smart Contracts (SCs). SC is a piece of code written in solidity or other blockchain specific languages to establish the trust between all the parties connected through blockchain and also eliminate the need of an intermediary for data sharing. Finally, we highlight some issues of the traditional telesurgery system and how they are mitigated with usage of the proposed HaBiTs framework.