Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

Skeleton based action recognition distinguishes human actions using the trajectories of skeleton joints, which provide a very good representation for describing actions. Considering that recurrent neural networks (RNNs) with Long Short-Term Memory (LSTM) can learn feature representations and model long-term temporal dependencies automatically, we propose an end-to-end fully connected deep LSTM network for skeleton based action recognition. Inspired by the observation that the co-occurrences of the joints intrinsically characterize human actions, we take the skeleton as the input at each time slot and introduce a novel regularization scheme to learn the co-occurrence features of skeleton joints. To train the deep LSTM network effectively, we propose a new dropout algorithm which simultaneously operates on the gates, cells, and output responses of the LSTM neurons. Experimental results on three human action recognition datasets consistently demonstrate the effectiveness of the proposed model.Comment: AAAI 2016 conferenc

Experimental Study of Condensation Heat Transfer of R134a on Oil-infusion Surfaces

Dropwise condensation, since first recognized in 1930, has stimulated interest because its heat transfer coefficient (HTC) is much higher than film condensation. For some applications, not only a higher heat transfer performance is desired, but also the retention of the fluids on the surface can be a big issue. For example, the refrigerant retention in some enhanced tube can block the contact of the vapor-solid interface and increase the thermal resistance; it also can increase the charge of refrigerant because certain amount of refrigerant could not go through the system cycle. Many efforts were dedicated to modifying the surface and promote dropwise condensation, and most research focus on the condensation of water vapor. It is very challenging to promote dropwise condensation for working fluids with a lower surface tension than water, such as refrigerant. Research have been conducted on dropwise condensation for low surface tension fluids using oil-infusion surface, which is promoted by the contact of drop to the liquid-vapor interface instead of solid-vapor interface. However, the effectiveness and efficiency of the oil-infusion surface is still a critical challenge, and the heat transfer mechanism of dropwise condensation with such liquid-liquid interface stays unclear. In this work, condensation of R134a on oil-immerged surfaces is investigated. Heat transfer coefficient is measured, and formation of the condensate is observed using a high speed camera. Two cavity surfaces of different porous scale are examined, of which, one is nanoscale pores and another is microscale pores Mineral oil of low miscibility to R134a is soaked to be saturated in the cavity prior to the experiment. All experiments were conducted under saturated condition of ambient temperature (around 22 °C) in a pressure chamber. The subcool level of the condensation is 10 °C. Images of the local condensation formation is analyzed and heat transfer coefficient is also compared for different surfaces. The duration of the oil-infusion surface is also tested for both surfaces

Interval Estimation Methods for Discrete-Time Linear Time-Invariant Systems

International audienc

The role of tool offset on the microstructure and mechanical properties of Al/Cu friction stir welded joints

In this study, dissimilar butt joining of 6061 aluminum alloy and commercially pure copper via friction stir welding was performed with varying tool offset value. The mechanical properties were compared using transverse tensile testing. It was found that as the tool offset decreased from a position of 2 mm–0 mm, the ultimate tensile strength of the welded joint increased, and then decreased drastically when the offset was more than 1.6 mm. X-ray tomography results showed that an effective mechanical interlocking structure was formed with a chaotic interface along the joint line. In addition, in-situ tool temperatures measurement showed that the stir zone peak temperature was highly dependent on tool offset

Indoor Particulate Matter Transfer in CNC Machining Workshop and The Influence of Ventilation Strategies—A Case Study

Particulate matter in Computer Numerical Control (CNC) machining workshop is harmful to workers’ health. This paper studies particulate matter transfer and the performance of various ventilation strategies in a CNC machining workshop. To obtain the boundary condition of the particle field, instruments were installed to obtain the particle size attenuation characteristics and source strength, respectively. The results show that the 99% cumulative mass concentration of particles is distributed within 1.5 μm, and the release rate of particles from the full enclosure. Next, the indoor flow field and particle field were simulated by numerical simulation with the measured boundary conditions. The working area’s age of air, particle concentration, and ventilation efficiency were compared between four displacement ventilation methods and one mixed ventilation method. The results show that the working area’s mean particle concentration and ventilation efficiency under longitudinal displacement ventilation is better than other methods. At the same time, the mean age of air is slightly worse. In addition, mixed ventilation can obtain lower mean age of air, but the particle concentration is higher in the working area. The bilateral longitudinal ventilation can be improved by placing axial circulation fans with vertical upward outlets in the center of the workshop

Dual Antiplatelet Therapy vs. Single Antiplatelet Therapy After Transcatheter Aortic Valve Replacement: An Updated Systematic Review and Meta-Analysis

Background: Although mainstream guidelines recommend dual antiplatelet therapy (DAPT) with aspirin and clopidogrel in patients following transcatheter aortic valve replacement (TAVR), it is not evidence-based. We aim to investigate the safety and efficacy of DAPT vs. single antiplatelet therapy (SAPT) after TAVR, and review updated evidence.Methods: We systematically searched PubMed, Embase, and Cochrane for studies comparing DAPT to SAPT after TAVR from inception to November 30, 2020. The primary outcome was major adverse cardiac and cerebrovascular events, including all-cause mortality, cardiovascular death, myocardial infarction (MI), stroke, and major or life-threatening bleeding (LTB). Subgroup analysis was performed according to study type (randomized control trials vs. observational studies) using a fixed-effects model. The quality of evidence was assessed by two scoring systems and GRADE (Grading of Recommendations Assessment, Development, and Evaluation).Results: Twelve studies of 20,766 patients were included in our meta-analysis. Compared with SAPT, DAPT was associated with an increased risk for combined life threatening and major bleeding [OR 1.73 (1.19–2.51), p = 0.004] after TAVR. Such a difference was largely driven by major bleeding [OR 2.29 (1.68–3.11), p < 0.001]. There were no significant differences on major adverse cardiovascular events (MACE) [OR 1.19 (0.99–1.44), p = 0.07], cardiovascular mortality [OR 1.46 (0.93–2.30), p = 0.10], and stroke [OR 0.97 (0.80–1.16), p = 0.71].Conclusions: Compared with SAPT, post-TAVR DAPT was associated with increased risks of major or life-threatening bleeding without additional benefits of reducing thrombotic events. Future guidelines for post-TAVR antiplatelet strategy are expected to be updated as new high-quality evidence emerges.Systematic Review Registration: PROSPERO, Identifier: CRD42021230075

OpenBox: A Python Toolkit for Generalized Black-box Optimization

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning. However, users still face challenges when applying BBO methods to their problems at hand with existing software packages in terms of applicability, performance, and efficiency. This paper presents OpenBox, an open-source BBO toolkit with improved usability. It implements user-friendly inferfaces and visualization for users to define and manage their tasks. The modular design behind OpenBox facilitates its flexible deployment in existing systems. Experimental results demonstrate the effectiveness and efficiency of OpenBox over existing systems. The source code of OpenBox is available at https://github.com/PKU-DAIR/open-box