BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo

Bounded by the inherent ambiguity of depth perception, contemporary multi-view 3D object detection methods fall into the performance bottleneck. Intuitively, leveraging temporal multi-view stereo (MVS) technology is the natural knowledge for tackling this ambiguity. However, traditional attempts of MVS has two limitations when applying to 3D object detection scenes: 1) The affinity measurement among all views suffers expensive computational cost; 2) It is difficult to deal with outdoor scenarios where objects are often mobile. To this end, we propose BEVStereo++: by introducing a dynamic temporal stereo strategy, BEVStereo++ is able to cut down the harm that is brought by introducing temporal stereo when dealing with those two scenarios. Going one step further, we apply Motion Compensation Module and long sequence Frame Fusion to BEVStereo++, which shows further performance boosting and error reduction. Without bells and whistles, BEVStereo++ achieves state-of-the-art(SOTA) on both Waymo and nuScenes dataset

Risk assessment of deep excavation construction based on combined weighting and nonlinear FAHP

Deep excavation construction safety has become a challenging and crucial aspect of modern infrastructure engineering, and its risk assessment is frequently carried out using the Fuzzy Analytic Hierarchy Process (FAHP). However, when using FAHP to evaluate the risks of deep excavation construction, the results of the weightings obtained through subjective weighting are heavily influenced by the subjective factors of the evaluators. In addition, using linear operators to calculate the risk level can easily cause a weakening effect on the influence of prominent risk factors, resulting in poor rationality of the evaluation results. To address these problems, this paper constructs a deep excavation construction risk evaluation model based on combined weighting and nonlinear FAHP. The WBS-RBS method is used to guide the construction of the risk evaluation index system for deep excavation construction. The combined weighting values of subjective and objective weightings are calculated through the game theory combined weighting method. The fuzzy relation matrix is constructed using the membership degree vector obtained from the expert evaluation method. Nonlinear operators are introduced for comprehensive calculation. According to the maximum membership degree principle, the final risk level of the excavation construction is obtained. The newly constructed model is applied to the risk analysis of the deep excavation construction of the Rongmin Science and Innovation Park project in Xi’an. The evaluation result for the excavation construction risk is N= [0.3125, 0.3229, 0.1939, 0.0854, 0.0854], and according to the maximum membership degree principle, the risk level of the excavation is classified as Level 2, which is a relatively low risk. Based on the deep excavation construction of the Rongmin Science and Innovation Park project, this paper discusses the differences between the new model and the traditional FAHP evaluation method, further verifies the reliability of the new model, optimizes the construction plan based on the evaluation results, avoids risks, and determines its guiding significance

Prediction for the surface settlement of double-track subway tunnels for shallow buried loess based on peck formula

In the process of constructing double-track subway tunnels in shallow buried loess areas, the interaction of double-track tunnels is significantly influenced by the net distance and the cross-section size, which is challenging to control the surface settlement. Therefore, the surface settlement prediction is essential while constructing double-track subway tunnels in shallow buried loess areas. The paper analyzed the surface settlement law of shallow buried double-track tunnels in loess areas through theoretical research and numerical simulation. The research results show that with the decrease of the net distance, the surface settlement superimposed curve was double V shape -W shape - single V shape. When the superimposed curve is double V shape and W shape, the Peck formula was used to calculate the surface settlement curve of the single-track tunnel, then superimposed to obtain the final surface settlement curve. When the superimposed surface settlement curve was V shape, based on the Peck formula, the formula for predicting the surface settlement suitable for symmetry and asymmetry was established. The net distance ratio and the area ratio were defined, and considering the tunnel’s interaction, the value and position of the maximum were corrected. Then numerical tests were carried out 16 times with different net distance ratios and area ratios, to determine the parameters of increments and position offsets of the maximum regarding the net distance ratio and the area ratio. Finally, two engineering were conducted for verifying the rationality and applicability exhibited by the prediction formula. The prediction formula served for predicting the surface settlement of double-track subway tunnels in shallow buried loess areas. Which can reduce construction risks and assure the safety of buildings above the ground

Electromagnetic Design of High-Speed and High-Thrust Cross-Shaped Linear Induction Motor

In order to improve the thrust density and efficiency of linear induction motors (LIM) in large load transport situations, a cross-shaped linear induction motors (CSLIM) structure is proposed in this paper. Firstly, for analyzing the characteristics of CSLIM, the magnetic field and electromagnetic thrust expression of long primary double-sided linear induction motors (LP-DSLIM) when considering the saturation of iron core are deduced, based on which the effect of iron saturation on electromagnetic thrust is analyzed. Secondary, the equivalent circuit of CSLIM is proposed and the effect of coupling on the electromagnetic thrust is analyzed. The results show that, the maximum electromagnetic thrust is reduced and the corresponding slip frequency is increased when iron saturation and coupling. For improving the problem of iron core saturation and coupling of CSLIM, a structure with square-type iron and lap winding is further proposed, and the rationality of CSLIM structure is verified by comparing the finite element simulation results of flux density on core, eddy current on secondary and the electromagnetic thrust

BEVStereo: Enhancing Depth Estimation in Multi-View 3D Object Detection with Temporal Stereo

Restricted by the ability of depth perception, all Multi-view 3D object detection methods fall into the bottleneck of depth accuracy. By constructing temporal stereo, depth estimation is quite reliable in indoor scenarios. However, there are two difficulties in directly integrating temporal stereo into outdoor multi-view 3D object detectors: 1) The construction of temporal stereos for all views results in high computing costs. 2) Unable to adapt to challenging outdoor scenarios. In this study, we propose an effective method for creating temporal stereo by dynamically determining the center and range of the temporal stereo. The most confident center is found using the EM algorithm. Numerous experiments on nuScenes have shown the BEVStereo's ability to deal with complex outdoor scenarios that other stereo-based methods are unable to handle. For the first time, a stereo-based approach shows superiority in scenarios like a static ego vehicle and moving objects. BEVStereo achieves the new state-of-the-art in the camera-only track of nuScenes dataset while maintaining memory efficiency. Codes have been released

BEVDepth: Acquisition of Reliable Depth for Multi-View 3D Object Detection

In this research, we propose a new 3D object detector with a trustworthy depth estimation, dubbed BEVDepth, for camera-based Bird's-Eye-View~(BEV) 3D object detection. Our work is based on a key observation -- depth estimation in recent approaches is surprisingly inadequate given the fact that depth is essential to camera 3D detection. Our BEVDepth resolves this by leveraging explicit depth supervision. A camera-awareness depth estimation module is also introduced to facilitate the depth predicting capability. Besides, we design a novel Depth Refinement Module to counter the side effects carried by imprecise feature unprojection. Aided by customized Efficient Voxel Pooling and multi-frame mechanism, BEVDepth achieves the new state-of-the-art 60.9% NDS on the challenging nuScenes test set while maintaining high efficiency. For the first time, the NDS score of a camera model reaches 60%. Codes have been released

Open Surgical Treatments of Osteoporotic Vertebral Compression Fractures

With an aging population, the osteoporotic vertebral compression fracture (OVCF) has become a constant concern for its physical and neurological complications, such as spinal kyphosis and refractory pains. Compared with traditional conservative treatments, the open surgery is more superior in some ways because of its direct decompression and correction. Various operation methods applying to different indications have been developed to deal with different fracture situations, including anterior, posterior, and combined surgery. In this review, we have concluded the latest developments of the surgery treating OVCF and the internal fixation as references for spinal surgeons of the choice of suitable treatments

FedMSA: A Model Selection and Adaptation System for Federated Learning

Federated Learning (FL) enables multiple clients to train a shared model collaboratively without sharing any personal data. However, selecting a model and adapting it quickly to meet user expectations in a large-scale FL application with heterogeneous devices is challenging. In this paper, we propose a model selection and adaptation system for Federated Learning (FedMSA), which includes a hardware-aware model selection algorithm that trades-off model training efficiency and model performance base on FL developers’ expectation. Meanwhile, considering the expected model should be achieved by dynamic model adaptation, FedMSA supports full automation in building and deployment of the FL task to different hardware at scale. Experiments on benchmark and real-world datasets demonstrate the effectiveness of the model selection algorithm of FedMSA in real devices (e.g., Raspberry Pi and Jetson nano)

Early Prediction of Shiraz Wine Quality Based on Small Volatile Compounds in Grapes

Wine producers perform early wine quality prediction based on berry morphology, the taste of the berry and the measurement of basic chemical parameters. Incorporating analysis on grape and wine volatiles could potentially achieve a more accurate prediction of wine quality, but forming these models requires careful selection of grapes, controlled fermentations, and standardised quality assessment. Here, we present 3 models for the prediction of quality in Shiraz wine. Modelling was performed by general regression analysis with 4-fold cross-validation: Model 1 (R2 = 99.97% and 4-foldR2 = 97.61%) for prediction of wine quality from wine volatiles, Model 2 (R2 = 99.89% and 4-foldR2 = 98.42%) for early prediction of wine quality from free-bound and glycosidically bound grape volatiles, and Model 3 (R2 = 91.62% and 4-foldR2 = 80.21%) for the prediction of wine quality from free grape volatiles only. The accuracy of these models presents an advancement in the early prediction of wine quality and provides a valuable tool to assist grape growers and winemakers to support the understanding of quality in the vineyard to better direct scarce resources

The Association between Socioeconomic Factors and Visual Function among Patients with Age-Related Cataracts

Background. With the development of the economy, socioeconomic factors, such as inequalities in the status of regional economies and the subsequent effects on health systems, have influenced the status of health. We explored the association between age-related cataracts and socioeconomic indicators, including the regional economy, health systems, and energy industries. Methods. This was a prospective, multicenter, Chinese population-based, cross-sectional study. A total of 830 participants from seven centers were enrolled. Data on the best-corrected visual acuity (BCVA), Lens Opacities Classification System III (LOCS III) score, Visual Function Index-14 (VF-14) score, total and subscale scores of the 25-item National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25), per capita disposable income (PCDI), medical resource-related indicators, and investments in the energy industry were obtained. Associations among these parameters were analyzed. Results. The PCDI ranking was correlated with the VF-14 score (R = −0.426, P<0.01), total score of NEI-VFQ-25 (r = −0.500, P<0.01), and BCVA (r = 0.278, P<0.01). The number of health agencies (r1 = 0.267, r2 = −0.303, r3 = −0.291,), practicing or assistant practicing doctors (r1 = -0.283, r2 = 0.427, r3 = 0.502,), registered nurses (r1 = −0.289, r2 = 0.409, r3 = 0.469, P<0.01), and health technicians (r1 = −0.278, r2 = 0.426, r3 = 0.500, P<0.01) per 10,000 of the population was each correlated with the BCVA, VF-14 score, and total score of NEI-VFQ-25, respectively. Health expenditure per capita was correlated with the VF-14 score (r = 0.287, P<0.01) and total score of NEI-VFQ-25 (r = 0.459, P<0.01). The LOCS III P score was correlated with investments in the energy industry (r = 0.485, P<0.001). Conclusions. Patients in higher economic regions with greater medical resources show a greater demand to undergo cataract surgery at a better subjective and objective visual function. The energy industry has a significant effect on cataracts, especially the posterior subcapsular cataract, and thus more attention should be paid to people in regions with abundant energy industries