Application of big data language recognition technology and GPU parallel computing in English teaching visualization system

International Journal of Speech Technology - With the development of multimedia technology and network technology applications, it is possible to implement online teaching systems in schools. This...     

基于特征建模的TDD系统大气波导干扰控制体系研究

大气波导干扰是特定气象条件下发生的时分双工（time-division duplex，TDD）系统内干扰，是TDD移动通信系统大规模组网面临的顽疾。在总结分析大气波导干扰成因和分类等的基础上，对大气波导干扰进行建模和表征，验证了海量干扰源在时域和频域的功率集总特征，并结合大量4G/5G现网实测数据给出了典型条件下内陆波导和海面波导的量化干扰信号传播模型，对于干扰的预测和预防具有重要意义。基于干扰特征，给出了TDD系统预防大气波导干扰的帧结构与组网的4项设计原则，5G现网数据表明干扰控制方案有效，上行干扰下降10 dB以上，相关原则对于6G系统的设计也具有指导意义。     

Influence of surfactants on rheological behaviors of polyacrylonitrile/dimethyl sulfoxide/silicon blending polymer solutions

KH550, KH560, CTAB, and F127 were adopted to modify silicon (Si) to improve the dispersity and stability of Si in the polyacrylonitrile/dimethyl sulfoxide (PAN/DMSO) polymer solutions. The influence of surfactants on rheological behaviors of PAN/DMSO/Si blending polymer solutions was investigated by an advanced solution and melt rotation rheometer. The homogeneity and stability were also studied. The results showed that the surfactants could change the viscosity dependence of blending polymer solutions on shear rate, temperature and storage time by increase the steric hindrance of Si. Among the four solutions, PAN/DMSO/Si blending polymer solution with F127 exhibited the lowest viscosity, activation energy and the smallest structural viscosity index and exhibited the trend close to the Newtonian fluids. Moreover, PAN/DMSO/Si blending polymer solution with F127 exhibited the best dispersity and stability, indicating its best physical properties and machinability.     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Electrospun Zn-doped Ga2O3 nanofibers and their application in photodegrading rhodamine B dye

Ultrawide band gap semiconductor materials have attracted considerable attention in recent years owing to their great potential in the photocatalytic field. In this study, Zn-doped Ga₂O₃ nanofibers with various concentrations were synthesized via electrospinning; they exhibited a superior photocatalytic degradation performance of rhodamine B dye compared to that of undoped Ga₂O₃ nanofibers. The Zn dopant replaced Ga sites via replacement doping, which could increase the concentration of oxygen vacancies and lead to enhanced photocatalytic properties. When the Zn concentration increased, a Ga₂O₃/ZnGa₂O₄ hybrid structure formed, which could further enhance the photocatalytic performance. The separation of photogenerated carriers due to Zn doping and heterojunctions were the primary causes of the enhanced photocatalytic performance. This study provides experimental data for the fabrication of high-performance photocatalysts based on Ga₂O₃ nanomaterials.     

Centimeter-scale low-damage micromachining on single-crystal 4H–SiC substrates using a femtosecond laser with square-shaped Flat-Top focus spots

Femtosecond (fs) lasers have been proved to be reliable tools for high-precision and high-quality micromachining of ceramic materials. Nevertheless, fs laser processing using a single-mode beam with a Gaussian intensity distribution is difficult to obtain large-area flat and uniform processed surfaces. In this study, we utilize a customized diffractive optical element (DOE) to redistribute the laser pulse energy from Gaussian to square-shaped Flat-Top profile to realize centimeter-scale low-damage micromachining on single-crystal 4H–SiC substrates. We systematically investigated the effects of processing parameters on the changes in surface morphology and composition, and an optimal processing strategy was provided. Mechanisms of the formation of surface nanoparticles and the removal of surface micro-burrs were discussed. We also examined the distribution of subsurface defects caused by fs laser processing by removing a thin surface layer with a certain depth through chemical mechanical polishing (CMP). Our results show that laser-induced periodic surface structures (LIPSSs) covered by fine SiO₂ nanoparticles form on the fs laser-processed areas. Under optimal parameters, the redeposition of SiO₂ nanoparticles can be minimized, and the surface roughness Sa of processed areas reaches 120 ± 8 nm after the removal of a 10 μm thick surface layer. After the laser processing, micro-burrs on original surfaces are effectively removed, and thus the average profile roughness Rz of 2 mm long surface profiles decreases from 920 ± 120 nm to 286 ± 90 nm. No visible micro-pits can be found after removing ~1 μm thick surface layer from the laser-processed substrates.     

Effects of upholstery materials on the burning behavior of real‐scale residential upholstered furniture mock‐ups

Fire spread and growth on real‐scale four cushion mock‐ups of residential upholstered furniture (RUF) were investigated with the goal of identifying whether changes in five classes of materials (barrier, flexible polyurethane foam, polyester fiber wrap, upholstery fabric, and sewing thread), referred to as factors, resulted in statistically significant changes in burning behavior. A fractional factorial experimental design plus practical considerations yielded a test matrix with 20 material combinations. Experiments were repeated a minimum of two times. Measurements included fire spread rates derived from video recordings and heat release rates (HRRs). A total of 13 experimental parameters (3 based on the videos and 10 on the HRR results), referred to as responses, characterized the measurements. Statistical analyses based on Main Effects Plots (main effects) and Block Plots (main effects and factor interactions) were used. The results showed that three of the factors resulted in statistically significant effects on varying numbers of the 13 responses. The Barrier and Fabric factors had the strongest main effects with roughly comparable magnitudes. Foam was statistically significant for fewer of the responses and its overall strength was weaker than for Barrier and Fabric. No statistically significant main effects were identified for Wrap or Thread. Multiple two‐term interactions between factors were identified as being statistically significant. The Barrier*Fabric interaction resulted in the highest number of and strongest statistically significant effects. The existence of two‐term interactions means that it will be necessary to consider their effects in approaches designed to predict the burning behavior of RUF.     

Statistical Piezotronic Effect in Nanocrystal Bulk by Anisotropic Geometry Control

Utilizing inner-crystal piezoelectric polarization charges to control carrier transport across a metal-semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano-electromechanical system (MEMS/NEMS), human-machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress-induced piezo-potential at the crystals’ interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m⁻¹ MPa⁻¹ and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing.     

Effects of (Li0.5Sm0.5)/W co-substitution and sintering temperature on the structure and electrical properties of ultrahigh Curie temperature piezoceramics,Ca0.92(Li0.5Sm0.5)0.08Bi2Nb2-xWxO9

With co-substitution of (Li_0.5Sm_0.5) at A site and W at B site, the electrical properties of modified Ca_0.92(Li_0.5Sm_0.5)_0.08Bi₂Nb_2-xW_xO₉ [(CLS)BN-xW, x = 0, 0.015 and 0.03] piezoceramics with ultrahigh Curie temperature (T_C) of > 930 °C were enhanced dramatically. The increased resistivity induced by the co-substitution ensure them to be polarized under an enough high field. Combined with the increase of spontaneous ferroelectric polarization (P_S), the significant enhancements in the piezoelectric, dielectric and ferroelectric properties can be obtained in the composition x = 0.015. Furthermore, the piezoelectric activity (d₃₃) and bulk resistivity (ρ_b) of (CLS)BN-0.015 W can be further enhanced at an appropriate sintering temperature. This optimum composition sintered at 1170 °C shows ultrahigh T_C of ～948 °C, d₃₃ of ～17.3 pC/N and ρ_b of ～6.9 MΩ cm at 600 °C, which are comparable to those of the reported high-temperature Aurivillius piezoceramics with T_C > 850 °C.