As a challenging pattern recognition task, speech emotion recognition has attracted more and more attention in recent years and is widely used in medical, Affective Computing, and other fields. In this paper, we proposed a parallel network of ResNet-CNN-Transformer Encoder. The Res-Net is used to alleviate the problems caused by the deepening of the network. The CNN calculates the fewer parameters to increase the fitting expression ability of the network. Due to the traditional recurrent neural network, with a long-term dependence on the feature extraction of speech and text sequences and sequence attributes not capturing long-distance features, the multi attention mechanism of the transformer coding layer is used to parallelize the sequence, improve the processing speed and extract the emotional semantic information in the sequence. Experiments are carried out on the RAVDESS dataset. Our results demonstrate the effectiveness of the proposed method and make a significant improvement compared with the previous results.

With the continuous advancement of science and technology, the application of high-temperature superconductivity has developed rapidly. The high-temperature superconducting (HTS) motor replacing the copper coil in the traditional motor with HTS winding is increasingly used in power equipment, and the effective thermal management of HTS winding is vital in ensuring the life and effective operation of the HTS motor. In this study, five enhancement structures of indirect oil cooling channels were designed to improve the heat dissipation capacity of the HTS motor winding, and the enhancement effects of the different structures were comprehensively evaluated through numerical simulation using Fluent software 2022R1. The best enhancement structure was selected through structural optimization. The results showed that the Nusselt number of the gap-type enhanced structure was higher than that of the V- and staggered-type structures at the same flow velocity and 68% higher than that of the bare pipe. At the same inlet flow velocity and with a pressure drop limit of 30 kPa, the performance evaluation criterion value of the gap-type structure was 39% and 63% higher than that of the staggered- and V-type structures, respectively. The gap type is the optimal enhancement structure and can effectively improve the heat dissipation of the HTS winding coil.

Digital-physical hybrid real-time simulation (hybrid simulation) platform integrates the advantages of both digital simulation and physical simulation by combining the physical simulation laboratory and the real-time digital simulator. Based on a 400 V/50 kVA hybrid simulation platform with 500 kVA short-circuit capacity, the hybrid simulation methodology and a Hausdorff distance based accuracy evaluation method are proposed. The case validation of power system fault recurrence is performed through this platform, and the stability and accuracy are further validated by comparing the hybrid simulation waveform and field-recorded waveform and by evaluating the accuracy with the proposed error index. Two typical application scenarios in power systems are studied subsequently. The static var generator testing shows the hybrid simulation platform can provide system-level testing conditions for power electronics equipment conveniently. The low-voltage ride through standard testing of a photovoltaic inverter indicates that the hybrid simulation platform can be also used for voltage standard testing for various power system apparatus with low cost. With this hybrid simulation platform, the power system simulation and equipment testing can be implemented with many advantages, such as short period of modelling, flexible modification of parameter and network, low cost, and low risk. Based on this powerful tool platform, there will be more application scenarios in future power systems.