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Edge intelligence is an emerging technology that integrates edge computing and deep learning to bring AI to the network’s edge. It has gained wide attention for its lower network latency and better privacy preservation abilities. However, the inference of deep neural networks is computationally demanding and results in poor real-time performance, making it challenging for resource-constrained edge devices. In this paper, we propose a hierarchical deep learning model based on TreeNet to reduce the computational cost for edge devices. Based on the similarity of the classification categories, w...

Person re-identification (Re-ID) has achieved great success in the supervised scenario. However, it is difficult to directly transfer the supervised model to arbitrary unseen domains due to the model overfitting to the seen source domains. In this paper, we aim to tackle the generalizable multi-source person Re-ID task (i.e., there are multiple available source domains, and the testing domain is unseen during training) from the data augmentation perspective, thus we put forward a novel method, termed MixNorm. It consists of domain-aware mix-normalization (DMN) and domain-aware center regulariz...

As the percentage of renewable energy sources grows, excess electrical power from renewables can be converted using electrolyzers to produce hydrogen, which can be stored, and later utilized by industries, homes, or the transportation system. Further, electrolyzers can also be utilized for frequency and voltage control to improve the stability of the power system. In this paper, a novel electrical circuit model for a 400W PEM electrolyzer is designed and validated using the experimental data from a reported paper for a 400W electrolyzer. To demonstrate its adaptive feature, the proposed 400W m...

Wire and arc additive manufacturing(WAAM) is a promising method for directly manufacturing parts with complex shapes. However, the accuracy of the existing welding parameter planning methods would dramatically decrease when bead geometry changes dynamically due to the long-term dependence, strong coupling, and hysteresis properties of the WAAM process. To this end, a non-autoregressive(NAR) dynamic model is proposed to predict the bead geometry, and an adaptive model predictive control(aMPC) method is proposed to plan welding parameters to achieve high manufacturing accuracy. First, in the pro...

In this article, an advanced nonlinear control scheme is proposed for a three-phase grid-connected inverter and a solar photovoltaic (PV) system connected dc–dc converter. The proposed control scheme is based on a nonlinear adaptive integral backstepping approach. The robustness of the proposed control scheme is achieved through maintaining stability of the overall system, extacting maximum power from the solar PV, and controlling active power. Moreover, the injection of less harmonic components into the grid, the superior performance against different atmospheric conditions, and external di...