Effect of substrate thickness on interfacial adhesive strength and thermal residual stress of second-generation high-temperature superconducting tape using peel test modeling

Second-generation high-temperature superconducting (2G HTS) tape is used in magnets and cables because of its outstanding electromagnetic characteristics. However, with the development of winding technology, thinner tapes are required in the construction of magnets. The effect of using thinner substrates on the resulting mechanical and electrical properties of 2G HTS tapes must thus be urgently understood. The interfacial adhesive strength is an important index used to characterize the mechanical strength of 2G HTS tape. Previous experimental studies have shown that thermal stress is one of the major factors in the delamination of the component tape used for magnet winding or cable assembly. In this study, the effect of substrate thickness on the interfacial adhesive strength of 2G HTS tape was investigated using peel test modeling. The thermal residual stresses accumulated during tape synthesis and caused by altered temperature during tape preparation and application at 77 K were also considered. To address the geometrical, physical, and boundary nonlinear problem, the finite element method was used. The simulation results indicate that interfacial stress caused by thermal shrinkage may separate the tape near the superconductor layer at the outer edge; however, no significant effect was observed for the central part. When the thermal residual stress was considered, the peel strength was reduced by approximately 20%. The substrate thickness also played an important role in the magnitude of thermal residual stress, which resulted in an increase of the peel strength with decreasing substrate thickness.     

A Highly Efficient Algorithm for Phased-Array mmWave Massive MIMO Beamforming

With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features—it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of a mobile communication system. As such, it is now considered a key technology for future mobile communications. MmWave communication technology also has a more open network architecture; it can deliver varied services and be applied in many scenarios. By contrast, traditional, all-digital precoding systems have the drawbacks of high computational complexity and higher power consumption. This paper examines the implementation of a new hybrid precoding system that significantly reduces both calculational complexity and energy consumption. The primary idea is to generate several sub-channels with equal gain by dividing the channel by the geometric mean decomposition (GMD). In this process, the objective function of the spectral efficiency is derived, then the basic tracking principle and least square (LS) techniques are deployed to design the proposed hybrid precoding. Simulation results show that the proposed algorithm significantly improves system performance and reduces computational complexity by more than 45% compared to traditional algorithms.     

面向电力物联网URLLC业务的智能网络切片管理方法

基于5G通信技术的电力物联网正在如火如荼地建设,随之产生的是用电信息采集、输变电状态监测以及精准负荷控制等新型电力物联网业务。为了满足这些业务对5G网络的超低时延和超高可靠性的需求,提出一种面向电力物联网URLLC(ultra reliable low latency communication)业务的智能网络切片管理方法。该方法综合运用5G切片和移动边缘计算(mobile edge computing,MEC)技术,建立电力业务传输和计算的时延、能耗以及可靠性模型,并通过DQN(deep Q network)算法对切片资源进行优化。仿真实验表明,所提出的智能网络切片管理方法的可靠性高于98%,且优于经典的基于坐标块下降方法和资源平均分配方法。     

Sum Rate Maximization-based Fair Power Allocation in Downlink NOMA Networks

Non-orthogonal multiple access (NOMA) has been seen as a promising technology for 5G communication. The performance optimization of NOMA systems depends on both power allocation (PA) and user pairing (UP). Most existing researches provide sub-optimal solutions with high computational complexity for PA problem and mainly focuses on maximizing the sum rate (capacity) without considering the fairness performance. Also, the joint optimization of PA and UP needs an exhaustive search. The main contribution of this paper is the proposing of a novel capacity maximization-based fair power allocation (CMFPA) with low-complexity in downlink NOMA. Extensive investigation and analysis of the joint impact of signal to noise ratio (SNR) per subcarrier and the channel gains of the paired users on the performance of NOMA in terms of the capacity and the user fairness is presented. Next, a closed-form equation for the power allocation coefficient of CMFPA as a function of SNR, and the channel gains of the paired users is provided. In addition, to jointly optimize UP and PA in NOMA systems an efficient low-complexity UP (ELCUP) method is proposed to be incorporated with the proposed CMFPA to compromise the proposed joint resource allocation (JRA). Simulation results demonstrate that the proposed CMFPA can improve the capacity and fairness performance of existing UP methods, such as conventional UP, and random UP methods. Furthermore, the simulation results show that the proposed JRA significantly outperforms the existing schemes and gives a near-optimal performance.     

Intelligent Deep Learning Model for Privacy Preserving IIoT on 6G Environment

In recent times, Industrial Internet of Things (IIoT) experiences a high risk of cyber attacks which needs to be resolved. Blockchain technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber attacks. Although blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network, the performance arrived at, in existing studies still needs improvement. In this scenario, the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT (PPBDL-IIoT) on 6G environment. The proposed PPBDL-IIoT technique aims at identifying the existence of intrusions in network. Further, PPBDL-IIoT technique also involves the design of Chaos Game Optimization (CGO) with Bidirectional Gated Recurrent Neural Network (BiGRNN) technique for both detection and classification of intrusions in the network. Besides, CGO technique is applied to fine tune the hyperparameters in BiGRNN model. CGO algorithm is applied to optimally adjust the learning rate, epoch count, and weight decay so as to considerably improve the intrusion detection performance of BiGRNN model. Moreover, Blockchain enabled Integrity Check (BEIC) scheme is also introduced to avoid the misrouting attacks that tamper the OpenFlow rules of SDN-based IIoT system. The performance of the proposed PPBDL-IIoT methodology was validated using Industrial Control System Cyber-attack (ICSCA) dataset and the outcomes were analysed under various measures. The experimental results highlight the supremacy of the presented PPBDL-IIoT technique than the recent state-of-the-art techniques with the higher accuracy of 91.50%.     

HARQ Optimization for PDCP Duplication-Based 5G URLLC Dual Connectivity

Packet duplication (PD) with dual connectivity (DC) was newly introduced in the 5G New Radio (NR) specifications to meet the stringent ultra reliable low latency communication (URLLC) requirements. PD technology uses duplicated packets in the packet data convergence protocol (PDCP) layer that are transmitted via two different access nodes (ANs) to the user equipment (UE) in order to enhance the reliability performance. However, PD can result in unnecessary retransmissions in the lower layers since the hybrid automatic retransmission request (HARQ) operation is unaware of the transmission success achieved through the alternate DC link to the UE. To overcome this issue, in this paper, a novel duplication-aware retransmission optimization (DRO) scheme is proposed to reduce the resource usage induced by unnecessary HARQ retransmissions. The proposed DRO scheme can minimize the average channel use while satisfying the URLLC requirements. The proposed DRO scheme derives the optimal HARQ retransmission attempts for different ANs by solving a nonlinear integer programming (NLIP) problem. The performance of the proposed DRO scheme was evaluated using MATLAB simulation and is compared to the existing 5G HARQ support schemes. The simulations results show that the proposed DRO scheme can provide a 14.71% and 15.11% reduced average channel use gain compared to the selective data duplication upon failure (SDUF) scheme and latency-aware dynamic multi-connectivity algorithm (LADMA) scheme, respectively, which are the existing 5G PD schemes that use HARQ.     

Analysing the roles of CEO's financial literacy and financial constraints on Spanish SMEs technological innovation

Drawing on human capital and upper echelons theories, this study analyses how CEO's financial literacy influences a firm's technological innovation and investigates the mediating role of alleviating financial constraints of Small and Medium-sized Enterprises (SMEs) in the former relationship. We develop and test hypotheses applying a Structural Equation Model to a sample of 310 Spanish SMEs. The results show that CEO's financial literacy exerts both a direct and an indirect impact, through alleviating financial constraints, on a firm's technological innovation.     

A facile preparation of graphene/reduced graphene oxide/Ni(OH)2 two dimension nanocomposites for high performance supercapacitors

A Ni(OH)₂ composite with good electrochemical performances was prepared by a facile method. Ni(OH)₂ was homogeneously grown on the hydrophilic graphene/graphene oxide (G/GO) nanosheets, which can be prepared in large scale in my lab. Then G/GO/Ni(OH)₂ was reduced by L-Ascorbic acid to obtain G/RGO/Ni(OH)₂. Caused by the synergy effects among the components, the G/RGO/Ni(OH)₂ electrode showed good electrochemical properties. The G/RGO/Ni(OH)₂ electrode possessed a specific capacitance as high as 1510 F g⁻¹ at 2 A g⁻¹ and even 890 F g⁻¹ at 40 A g⁻¹. An asymmetric supercapacitor device consisting of G/RGO/Ni(OH)₂ and reduced graphene oxide (RGO) was installed and displayed a high energy density of 44.9 W h kg⁻¹ at the power energy density of 400.1 W kg⁻¹. It was verified that the G/GO nanosheets are ideal supporting material in supercapacitor.     

5G时代动态可变式校标设计及延展应用

目的探讨5G时代中国高校如何通过具有高识别度和多元变化的校标设计及延展应用,提升中国高校的国际品牌形象,助力中国高校的国际化进程。方法通过比较研究中国137所“双一流”高校与QS世界大学排名前100强高校的校标,以图像分析和统计学的方法揭示中国高校校标设计高度雷同化、辨识度低的现状,指出常见的圆形范式校标在国际竞争和品牌传播中所存在的局限性;借鉴西方品牌形象设计的成功案例,寻找5G时代中国高校校标设计的创新理念、设计方向以及具体的延展应用方法。结论强调独特性、高识别性的校标设计在高校品牌传播中的重要性,并创造性地提出了“动态可变式”校标设计及延展应用在5G时代必将成为高校品牌形象传播的主流趋势和重要手段。     

5G技术在融媒体传播中的创新应用

5G作为国家发展战略将促进全社会的创新发展,它的超大带宽、超低时延、超级连接能力将会给各行各业带来新的发展机遇,将促进各行各业的融合创新发展。5G高速率的实现,将给视频的传播提供新的高速通道,广播电视作为视频领域的领军者,必将引领融合媒体传播的创新发展。论文将简要探讨5G技术及其场景下融媒体传播技术的创新应用。