Dynamic Gesture Recognition Based on Three-Stream Coordinate Attention Network and Knowledge Distillation

Gesture recognition has always been one of the important research directions in the field of computer vision. The dynamic gesture has the problems of complex backgrounds and many interference factors. The gesture recognition model based on deep learning usually has high computational cost and poor real-time performance. In addition, deep learning models are limited to recognizing existing categories in the training set and their performance largely depends on the amount of labeled data. To address the above problems, this paper presents a dynamic gesture recognition method named 3SCKI based on a three-stream coordinate attention (CA) network, knowledge distillation, and image-text contrastive learning. Specifically, 1) CA is utilized for feature fusion to make the model focus more on target gestures and reduce background interference, 2) traditional knowledge distillation loss is improved to reduce the amount of calculation and improve the real-time performance. Specifically, the guidance function is added to make the student network only learn the classification probability correctly identified by the teacher network, and 3) multi-granularity context prompt template integration method is proposed to construct an improved CLIP visual language model MG-CLIP. It aligns text and visual concepts from the image level to the object level to the part level. Through comparative learning of image features and text features, gesture classification is performed, enabling the model to identify image categories that have not appeared during the training phase. The proposed method is evaluated on the ChaLearn LAP large-scale isolated gesture dataset (IsoGD). The results show that our proposed method can obtain recognition rates of 65.87% on the validation set of IsoGD. For single mode data, 3SCKI can obtain the state-of-the-art recognition accuracy on RGB, Depth, and Optical Flow data (61.22%, 58.84%, and 50.30% of the validation set of IsoGD, respectively)

Sustainable Afterglow Room-Temperature Phosphorescence Emission Materials Generated Using Natural Phenolics

Long-lived afterglow room-temperature phosphorescence (RTP) from natural phenolics has seldom been reported yet this is essential for the development of sustainable afterglow RTP materials. With this research, we have prepared sustainable afterglow RTP materials (GA@SA) with a lifetime of up to ≈934.7 ms by embedding gallic acid (GA) within a Ca2+-crosslinked sodium alginate (SA) matrix. Theoretical simulations indicate that the restricted carbonyl moieties of the GA and H-type aggregates of GA in a SA matrix promoted the spin orbit coupling (SOC) of GA and induced afterglow emission. Moreover, afterglow RTP emission could be produced by embedding different types of natural phenolics such as, tannic acid, caffeic acid and chlorogenic acid into Ca2+-crosslinked networks of SA. As an illustration of potential applications, GA@SA was used to prepare anti-counterfeit afterglow clothing and paper. This work provides an innovative method for the activation of long-lived afterglow RTP from sustainable phenolics.</p

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction

Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles

The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction

Numerical Simulation of Vertical Well Depressurization with Different Deployments of Radial Laterals in Class 1-Type Hydrate Reservoir

Gas production efficiency is a key indicator in the commercial development of natural gas hydrates (NGHs). Based on the data from the first natural gas hydrate field test production in the Shenhu Sea area of China, the gas production capability of Class 1-type hydrate reservoirs was numerically evaluated by vertical well depressurization with different deployment schemes for radial laterals. The results showed that the radial laterals can effectively improve production efficiency and that the radial laterals deployed at the three-phase layer (TPL) have the best production performance. Compared with the single vertical well production, the completion length of the radial laterals is 150 m with a radius of 0.05 m, and the production pressure difference is set to 6 MPa. The cumulative gas production Vg reaches up to 594.10 × 104 ST m3, increased by about 208.53% after 360 days of production, which provides a reference for the development of natural gas hydrates with radial jet drilling (RJD) technology

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine