Fault Diagnosis of Train Axle Box Bearing Based on Multifeature Parameters

Failure of the train axle box bearing will cause great loss. Now, condition-based maintenance of train axle box bearing has been a research hotspot around the world. Vibration signals generated by train axle box bearing have nonlinear and nonstationary characteristics. The methods used in traditional bearing fault diagnosis do not work well with the train axle box. To solve this problem, an effective method of axle box bearing fault diagnosis based on multifeature parameters is presented in this paper. This method can be divided into three parts, namely, weak fault signal extraction, feature extraction, and fault recognition. In the first part, a db4 wavelet is employed for denoising the original signals from the vibration sensors. In the second part, five time-domain parameters, five IMF energy-torque features, and two amplitude-ratio features are extracted. The latter seven frequency domain features are calculated based on the empirical mode decomposition and envelope spectrum analysis. In the third part, a fault classifier based on BP neural network is designed for automatic fault pattern recognition. A series of tests are carried out to verify the proposed method, which show that the accuracy is above 90%

Selective-Stereo: Adaptive Frequency Information Selection for Stereo Matching

Stereo matching methods based on iterative optimization, like RAFT-Stereo and IGEV-Stereo, have evolved into a cornerstone in the field of stereo matching. However, these methods struggle to simultaneously capture high-frequency information in edges and low-frequency information in smooth regions due to the fixed receptive field. As a result, they tend to lose details, blur edges, and produce false matches in textureless areas. In this paper, we propose Selective Recurrent Unit (SRU), a novel iterative update operator for stereo matching. The SRU module can adaptively fuse hidden disparity information at multiple frequencies for edge and smooth regions. To perform adaptive fusion, we introduce a new Contextual Spatial Attention (CSA) module to generate attention maps as fusion weights. The SRU empowers the network to aggregate hidden disparity information across multiple frequencies, mitigating the risk of vital hidden disparity information loss during iterative processes. To verify SRU's universality, we apply it to representative iterative stereo matching methods, collectively referred to as Selective-Stereo. Our Selective-Stereo ranks $1^{st}$ on KITTI 2012, KITTI 2015, ETH3D, and Middlebury leaderboards among all published methods. Code is available at https://github.com/Windsrain/Selective-Stereo.Comment: Accepted to CVPR 202

SAGDA: Achieving O(ϵ−2)\mathcal{O}(\epsilon^{-2}) Communication Complexity in Federated Min-Max Learning

To lower the communication complexity of federated min-max learning, a natural approach is to utilize the idea of infrequent communications (through multiple local updates) same as in conventional federated learning. However, due to the more complicated inter-outer problem structure in federated min-max learning, theoretical understandings of communication complexity for federated min-max learning with infrequent communications remain very limited in the literature. This is particularly true for settings with non-i.i.d. datasets and partial client participation. To address this challenge, in this paper, we propose a new algorithmic framework called stochastic sampling averaging gradient descent ascent (SAGDA), which i) assembles stochastic gradient estimators from randomly sampled clients as control variates and ii) leverages two learning rates on both server and client sides. We show that SAGDA achieves a linear speedup in terms of both the number of clients and local update steps, which yields an $\mathcal{O}(\epsilon^{-2})$ communication complexity that is orders of magnitude lower than the state of the art. Interestingly, by noting that the standard federated stochastic gradient descent ascent (FSGDA) is in fact a control-variate-free special version of SAGDA, we immediately arrive at an $\mathcal{O}(\epsilon^{-2})$ communication complexity result for FSGDA. Therefore, through the lens of SAGDA, we also advance the current understanding on communication complexity of the standard FSGDA method for federated min-max learning.Comment: Published as a conference paper at NeurIPS 202

Association between vitamin D and systemic lupus erythematosus disease activity index in children and adolescents: A systematic review and meta-analysis

Purpose: To undertake a systematic and a meta-analysis in order to determine whether vitamin D is relevant to systemic lupus erythematosus (SLE) in children and adolescents. Methods: PubMed, Embase, Medline, and Cochrane Library were systematically searched from January 1, 1979 to December 30, 2018. Cross-sectional studies were conducted to compare vitamin D, systemic lupus erythematosus disease activity index (SLEDAI), parathormone (PTH), and calcium between children and adolescents with SLE and healthy children and adolescents. The primary outcomes were the vitamin D level and SLEDAI, whereas the secondary outcomes were vitamin D level, vitamin D deficiency level, PTH, and calcium. Results: A total of 98 articles were obtained, among which 7 studies met the inclusion criteria. The results indicate that serum vitamin D level in SLE group was lower than that in the healthy group. Patients with SLE were more vulnerable to vitamin D deficiency than the healthy group. However, correlation analysis indicate that vitamin D level was poorly correlated with SLEDAI (r = -0.04). Subgroup analysis of latitude and economic status was conducted. However, no correlation was indicated. PTH level was higher (p = 0.45), but calcium level was lower in patients with SLE than in healthy controls (p = 0.003). The correlation study indicated a poorly negative correlation between vitamin D and calcium (r = -0.09, p = 0.90), and negative correlation between vitamin D and PTH (r = - 0.44, p = 0.26). Conclusion: The results of this meta-analysis suggest that serum vitamin D level does not exhibit any correlation with SLEDAI

Augmented Reality Meets Tangibility: A New Approach for Early Childhood Education

Augmented Reality (AR) has been recognised as one of the promising technologies for the gaming industry. In this study, the authors intend to apply AR technology to develop an interactive educational game. This paper presents an AR featured educational game specifically designed for 4-7 years old pre-school children. The principal objective of this game is to enable children to learn various abstract concepts, such as colour mixing, mathematics and 2D-3D geometrical shape recognition. This game allows users to interact with both onscreen (intangible) and physical objects (tangible) at the same time; different interaction forms including the touch screen (click) and AR game (rotate) are designed for better interaction with the real world and learning. This paper focuses on the details of the design and interactive behaviour. Furthermore, beyond the needs of children, this game also serves for parents through the Token Economy method; parents can control the kids’ contacting time with portable devices, and track and modify their everyday learning patterns. A pilot study implementing mix method was used to gather user’s feedback is also described in this paper

Poly[[tetra­aqua­bis­(μ3-5-carboxybenzene-1,2,4-tri­carboxyl­ato)tricadmium] tetra­hydrate]

There are three independent CdII ions in the title complex, {[Cd3(C10H3O8)2(H2O)4]·4H2O}n, one of which is coordinated by four O atoms from three 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands and by two water mol­ecules in a distorted octa­hedral geometry. The second CdII ion is coordinated by five O atoms from four 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands and by one water mol­ecule also in a distorted octa­hedral geometry while the third CdII ion is coordinated by five O atoms from three 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands and by one water mol­ecule in a highly distorted octa­hedral geometry. The 5-carboxybenzene-1,2,4-tri­carboxyl­ate ligands bridge the CdII ions, resulting in the formation of a three-dimensional structure. Intra- and inter­molecular O—H⋯O hydrogen bonds are present throughout the three-dimensional structure