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With the aging of the population in China in recent years, the number of stroke patients is increasing day by day. The sequelae of stroke-induced foot drop are expected to regain some mobility after timely rehabilitation, but if patients do not receive early intervention, they may miss the best rehabilitation period and lose the ability to walk and stand completely. The traditional means of rehabilitation treatment is manual rehabilitation by rehabilitation physicians, but with the increase in the number of patients with movement disorders, the number of rehabilitation physicians has become significantly insufficient. The use of rehabilitation robots to provide adjunctive therapy to patients has become a common and effective means of rehabilitation worldwide. The early rehabilitation robots could only drive the patient to do passive rehabilitation and could not reflect the patient’s true motor intentions. Since EMG signals on the surface of the human body can advance the onset of human movement, they can be used to identify the intention of human movement. This paper validates and explores the experiment based on the underlying data.

This paper focuses on the impact of traceability technology adoption on supply chain coordination. We consider a fresh product supply chain consisting of two suppliers and one retailer with centralized and decentralized decision-making. Considering the factors of the tag cost of traceability technology and the freshness of the product, two scenarios-with and without traceability technology are analyzed. The mathematical model is applied to investigate the impact of applying traceability technology on decision-making and profit of supply chain when two suppliers compete. The results show that: (1) the fresh product supply chain with the traceability technology is more profitable than the case that without the traceability technology; (2) when the tag cost of the traceability technology is within the threshold, the supplier’s profit decreases with the increase of the tag cost, and it is always greater than the corresponding profit when comparing with the case that without adopting the traceability technology; (3) if the tag cost of the traceability technology is too high, the retailer can use cost sharing or bargaining with the supplier to encourage him to implement the technology.

The mission planning of Geostationary Earth Orbit (GEO) on-orbit refuelling with uncertain object satellites is studied in this paper. Three key problems should be resolved here: Object Satellite (OSc) selection, mission sequence planning and transfer trajectory optimization. The optimization goal is to select the OSc and find the optimal servicing sequence with the best optimization objective value. Three optimization objectives, i.e. fuel cost, the total number of the OScs and the sum of the OSc priority value are taken into account. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed. Multi-objective particle swarm optimization is employed to address the model. Several mission scenarios are compared and discussed. Numerical experiments indicate that 1) the method developed in this paper could address the problem efficiently; and 2) OSc distribution and varieties in optimization objective emphasis have considerable influences on the optimization results.

In view of the traffic flow data of non-stationary, the abnormal data detection is difficult.proposed basing on the wavelet analysis and least squares method of abnormal traffic flow data detection in this paper.First using wavelet analysis to make the traffic flow data of high frequency and low frequency component and separation, and then, combined with least square method to find abnormal points in the reconstructed signal data.Wavelet analysis and least square method, the simulation results show that using wavelet analysis of abnormal traffic flow data detection, effectively reduce the detection results of misjudgment rate and false negative rate.