1,695 research outputs found

    A Review on Renewable Energy Supply

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    The rapid increase in energy consumption, particularly in recent decades, has sparked concerns that the world's petroleum and other resource supplies would be depleted in the near future. The massive usage of fossil fuels has resulted in observable environmental devastation in a variety of ways. Fossil fuels account for almost 90% of total energy usage. The economy and technologies today are heavily reliant on natural resources, which are not replaced, as a result of industrialization and population expansion. Further, on the view of energy efficient system the renewable energy is highly appreciated in future tim

    Controlling spins in nanodevices via spin-orbit interaction, magnons and heat

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    Topologically distinct atomic insulators

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    Topological classification of quantum solids often (if not always) groups all trivial atomic or normal insulators (NIs) into the same featureless family. As we argue here, this is not necessarily the case always. In particular, when the global phase diagram of electronic crystals harbors topological insulators with the band inversion at various time-reversal invariant momenta KinvTI{\bf K}^{\rm TI}_{\rm inv} in the Brillouin zone, their proximal NIs display noninverted band-gap minima at KminNI=KinvTI{\bf K}^{\rm NI}_{\rm min}={\bf K}^{\rm TI}_{\rm inv}. In such systems, once topological superconductors nucleate from NIs, the inversion of the Bogoliubov de Gennes bands takes place at KinvBdG=KminNI{\bf K}^{\rm BdG}_{\rm inv}={\bf K}^{\rm NI}_{\rm min}, inheriting from the parent state. We showcase this (possibly general) proposal for two-dimensional time-reversal symmetry-breaking insulators. Then distinct quantized thermal Hall conductivity and responses to dislocation lattice defects inside the paired states (tied with KinvBdG{\bf K}^{\rm BdG}_{\rm inv} or KminNI{\bf K}^{\rm NI}_{\rm min}), in turn unambiguously identify different parent atomic NIs.Comment: Published version in PRB as a Letter: 7 pages, 4 figures (Supplemental Material as Ancillary file

    ACTIVE TEACHING-LEARNING SYSTEM AND CHALLENGES IN THE PROFESSIONAL EDUCATION

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    Now-a-days, the ways to develop professional educator have been changed. Students benefit more from teachers who are not only qualified and experienced but at the same time always have updated outcome base. Often need enrichment programmers to update the teachers and consequently to the students they teach. Even if a profession has people with the required qualifications and experience to stay in the job but no opportunities to improve, update knowledge base with changing time and growing needs, it affects their and also the students’ performance adversely. Based on this, only active teaching and learning system will give better development for upliftment of new comers

    Post-Quantum Secure Identity-Based Encryption Scheme Using Random Integer Lattices for IoT-Enabled AI Applications

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    Identity-based encryption is an important cryptographic system that is employed to ensure confidentiality of a message in communication. This article presents a provably secure identity based encryption based on post quantum security assumption. The security of the proposed encryption is based on the hard problem, namely Learning with Errors on integer lattices. This construction is anonymous and produces pseudo random ciphers. Both public-key size and ciphertext-size have been reduced in the proposed encryption as compared to those for other relevant schemes without compromising the security. Next, we incorporate the constructed identity based encryption (IBE) for Internet of Things (IoT) applications, where the IoT smart devices send securely the sensing data to their nearby gateway nodes(s) with the help of IBE and the gateway node(s) secure aggregate the data from the smart devices by decrypting the messages using the proposed IBE decryption. Later, the gateway nodes will securely send the aggregated data to the cloud server(s) and the Big data analytics is performed on the authenticated data using the Artificial Intelligence (AI)/Machine Learning (ML) algorithms for accurate and better predictions
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