| 3 | Theoretical Study of Screening Dependence of Aluminium Doped MgB_2显示文摘The screening dependence of superconducting state parameters(λ, μ*, T_c, and N_0V(1) of six alloys of aluminium doped Mg B2 systems are studied in the BCS–Eliashberg–Mc Millan framework by employing five forms of dielectric screening function, viz. random phase approximation(RPA), Harrison, Geldart and Vosko(GV), Hubbard and Overhauser in conjunction with Ashcroft's potential. It is observed that electron-phonon coupling strength λ and Coulomb pseudopotential μ*are quite sensitive to the form of dielectric screening, whereas transition temperature T_c, isotope effect exponent α and effective interaction strength N_0V(1 show weak dependence on the form of dielectric screening function. It is found that the RPA form of dielectric screening function yields the best results for transition temperature T_c for all alloys of the Mg-Al-B system. The results obtained using GV screening are much higher than the experimental results. This shows that all the four dielectric screenings used here almost describe superconductivity in all the alloys of the Mg-Al-B system, but the GV screening is not suitable for such an alloy system. | Gargee Sharma Smita Sharma | 2018 | Chinese Physics Letters2018，35，3： | 0 |
| 4 | GRADE: Deep learning and garlic routing-based secure data sharing framework for IIoT beyond 5G显示文摘The rise of automation with Machine-Type Communication(MTC)holds great potential in developing Industrial Internet of Things(IIoT)-based applications such as smart cities,Intelligent Transportation Systems(ITS),supply chains,and smart industries without any human intervention.However,MTC has to cope with significant security challenges due to heterogeneous data,public network connectivity,and inadequate security mechanism.To overcome the aforementioned issues,we have proposed a blockchain and garlic-routing-based secure data exchange framework,i.e.,GRADE,which alleviates the security constraints and maintains the stable connection in MTC.First,the Long-Short-Term Memory(LSTM)-based Nadam optimizer efficiently predicts the class label,i.e.,malicious and non-malicious,and forwards the non-malicious data requests of MTC to the Garlic Routing(GR)network.The GR network assigns a unique ElGamal encrypted session tag to each machine partaking in MTC.Then,an Advanced Encryption Standard(AES)is applied to encrypt the MTC data requests.Further,the InterPlanetary File System(IPFS)-based blockchain is employed to store the machine's session tags,which increases the scalability of the proposed GRADE framework.Additionally,the proposed framework has utilized the indispensable benefits of the 6G network to enhance the network performance of MTC.Lastly,the proposed GRADE framework is evaluated against different performance metrics such as scalability,packet loss,accuracy,and compromised rate of the MTC data request.The results show that the GRADE framework outperforms the baseline methods in terms of accuracy,i.e.,98.9%,compromised rate,i.e.,18.5%,scalability,i.e.,47.2%,and packet loss ratio,i.e.,24.3%. | Nilesh Kumar Jadav Riya Kakkar Harsh Mankodiya Rajesh Gupta Sudeep Tanwar Smita Agrawal Ravi Sharma | 2023 | Digital Communications and Networks2023，9，2： | 0 |
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