An Optimized Method for Terrain Reconstruction Based on Descent Images

An optimization method is proposed to perform high-accuracy terrain reconstruction of the landing area of Chang'e III. First, feature matching is conducted using geometric model constraints. Then, the initial terrain is obtained and the initial normal vector of each point is solved on the basis of the initial terrain. By changing the vector around the initial normal vector in small steps a set of new vectors is obtained. By combining these vectors with the direction of light and camera, the functions are set up on the basis of a surface reflection model. Then, a series of gray values is derived by solving the equations. The new optimized vector is recorded when the obtained gray value is closest to the corresponding pixel. Finally, the optimized terrain is obtained after iteration of the vector field. Experiments were conducted using the laboratory images and descent images of Chang'e III. The results showed that the performance of the proposed method was better than that of the classical feature matching method. It can provide a reference for terrain reconstruction of the landing area in subsequent moon exploration missions

Large eddy simulation of ship airflow control with steady Coanda effect

This paper numerically studies the steady Coanda effect for drag reduction and airwake manipulations on the Chalmers ship model (CSM) using large eddy simulation with wall-adapting local-eddy viscosity model. Numerical methods are validated by experimental data acquired from the baseline CSM. In creating the flow control model, the hanger base of the baseline CSM is modified with Coanda surfaces and injection slots along its roof edge and two side edges. Four representative cases are studied: a no-jet case and three cases with the same momentum coefficient of the jet flow activated at different locations (roof, sides, and combined). The results show that the four cases have various performances in drag reduction and vortex structures on the deck. They are also different in mean and turbulent quantities as well as POD (proper orthogonal decomposition) modes in their airwake. It is found that the roof-jet has a stronger Coanda effect and is more vectored toward the low-speed area (LSA) on the deck than the side-jets that detach earlier from the Coanda surface. The energization process is, therefore, different where the roof-jet is more effective that directly brings high momentum to LSA and side-jets manipulate shear layers for mixing enhancement. The cases with roof-jet achieve better mitigation of flow re-circulation and higher recovery of streamwise velocity with lower turbulent fluctuation in the airwake. POD analysis suggests that the roof-jet can stabilize the wake

Drag reduction of ship airflow using steady Coanda effect

This paper studies the steady Coanda effect for reducing the aerodynamic drag of the Chalmers ship model (CSM) using Large Eddy Simulation (LES) with Wall-Adapting Local-Eddy Viscosity (WALE) model. The flow control mechanism is explored, and the analysis of energy efficiency is conducted to evaluate the net benefit of the flow control. Validating the numerical methods, the predicted aerodynamic drag of the ship and pressure coefficients distribution on the baseline CSM agree well with the experimental measurements and the maximum discrepancy is 4.2%. In creating the flow control models, the hanger base of the baseline CSM is modified with a Coanda surface and two different sizes of jet-blowing slots, 1%h (hanger height) and 2%h, respectively. A drag reduction of 5.34% is achieved by the 1%h slot-size case. The 2%h slot-size case further increases the drag reduction to 6.22% but has doubled power consumption. It is found that vectoring vorticity towards the low-speed area on deck is effective for enhancing the energization. Finally, the analysis of energy efficiency indicates that the net benefit is achieved in both flow control cases, and the case with the 1%h slot size is 11.9% more efficient due to a stronger Coanda effect

Comparison of flow characteristics behind squareback bluff-bodies with and without wheels

The wake dynamics of two referenced variations of the squareback Windsor model with and without wheels is numerically studied by performing improved delayed detached eddy simulation. Numerical assessments are validated against publicly available experimental data. The focus of this study is on the wake states influenced by the wheels and the thick oncoming floor boundary layer. Results show that the addition of the wheels significantly changes the aerodynamic forces, the underbody flow, and the wake topology. The wake bi-stability is also enhanced with wheels in place due to the increased curvature of lateral shear layers in the near wake. However, the bi-stable behavior is largely suppressed when immersed in a thick boundary layer. These alterations depend on the degree of interaction between the wake recirculation and the bottom flow, and such degree is strongly affected by the underbody flow momentum. The evolution of low-order flow organizations and complementary spectral analysis highlight the differences in the coherent dynamics of the wake. The finding of this present work suggests that the wake bi-stability behind the squareback body can exist not only for a simplified geometry but also for a more realistic car with wheels in real-world upstream conditions

Active flow control of the airflow of a ship at yaw

This paper implements the steady Coanda effect active flow control (AFC) on the Chalmers ship model (CSM) to study its influence on the ship\u27s side force and airwake under the yaw effect. The study is conducted numerically using Large Eddy Simulation (LES) with Wall-Adapting Local-Eddy Viscosity (WALE) model. Numerical methods are validated by the experimental data acquired from the baseline CSM under 10∘ port-side wind. The model with AFC is created by modifying the square-shaped hanger base to the Coanda surface and added with injection slots along the base\u27s roof edge and two side edges. The results show that the base-shape modification significantly alters the vortex structure on deck from z-direction vortex (ZV) to streamwise vortex (SV), and the steady Coanda effect with a momentum coefficient (Cμ) of 0.02 further enhances the SV with the removal of port-side vortex (PV). The side force and yaw moment are reduced by 5.27% and 7.97%, respectively in the AFC case due to the reduction of port-side (windward) ship-surface pressure. Furthermore, the current AFC can suppress the low-speed region and alleviate the velocity gradient in the lateral direction, which mitigates the regions of high TKE (turbulent kinetic energy) and high shear stress along the port-side deck

Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers

Lip reading has witnessed unparalleled development in recent years thanks to deep learning and the availability of large-scale datasets. Despite the encouraging results achieved, the performance of lip reading, unfortunately, remains inferior to the one of its counterpart speech recognition, due to the ambiguous nature of its actuations that makes it challenging to extract discriminant features from the lip movement videos. In this paper, we propose a new method, termed as Lip by Speech (LIBS), of which the goal is to strengthen lip reading by learning from speech recognizers. The rationale behind our approach is that the features extracted from speech recognizers may provide complementary and discriminant clues, which are formidable to be obtained from the subtle movements of the lips, and consequently facilitate the training of lip readers. This is achieved, specifically, by distilling multi-granularity knowledge from speech recognizers to lip readers. To conduct this cross-modal knowledge distillation, we utilize an efficacious alignment scheme to handle the inconsistent lengths of the audios and videos, as well as an innovative filtering strategy to refine the speech recognizer's prediction. The proposed method achieves the new state-of-the-art performance on the CMLR and LRS2 datasets, outperforming the baseline by a margin of 7.66% and 2.75% in character error rate, respectively.Comment: AAAI 202

The relationship between health belief and sleep quality of Chinese college students: The mediating role of physical activity and moderating effect of mobile phone addiction

BackgroundPoor sleep quality has become a common health problem encountered by college students.MethodsHealth belief scale (HBS), physical activity rating scale (PARS-3), mobile phone addiction tendency scale (MPATS) and Pittsburgh sleep quality index (PSQI) were adopted to analyze the data collected from survey questionnaires, which were filled out by 1,019 college students (including 429 males and 590 females) from five comprehensive colleges and universities from March 2022 to April 2022. The data collected from survey questionnaires were analyzed using SPSS and its macro-program PROCESS.Results(1) Health belief, physical activity, mobile phone addiction and sleep quality are significantly associated with each other (P < 0.01); (2) physical activity plays a mediating role between health belief and sleep quality, and the mediating effects account for 14.77%; (3) mobile phone addiction can significantly moderate the effect size of health belief (β = 0.062, p < 0.05) and physical activity (β = 0.073, P < 0.05) on sleep quality, and significantly moderate the effect size of health belief on physical activity (β = −0.112, p < 0.001).ConclusionThe health belief of college students can significantly improve their sleep quality; college students’ health belief can not only improve their sleep quality directly, but also improve their sleep quality through physical activity; mobile phone addiction can significantly moderate the effect size of health belief on sleep quality, the effect size of health belief on physical activity, and the effect size of physical activity on sleep quality

Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction

Exploring spatial-temporal dependencies from observed motions is one of the core challenges of human motion prediction. Previous methods mainly focus on dedicated network structures to model the spatial and temporal dependencies. This paper considers a new direction by introducing a model learning framework with auxiliary tasks. In our auxiliary tasks, partial body joints' coordinates are corrupted by either masking or adding noise and the goal is to recover corrupted coordinates depending on the rest coordinates. To work with auxiliary tasks, we propose a novel auxiliary-adapted transformer, which can handle incomplete, corrupted motion data and achieve coordinate recovery via capturing spatial-temporal dependencies. Through auxiliary tasks, the auxiliary-adapted transformer is promoted to capture more comprehensive spatial-temporal dependencies among body joints' coordinates, leading to better feature learning. Extensive experimental results have shown that our method outperforms state-of-the-art methods by remarkable margins of 7.2%, 3.7%, and 9.4% in terms of 3D mean per joint position error (MPJPE) on the Human3.6M, CMU Mocap, and 3DPW datasets, respectively. We also demonstrate that our method is more robust under data missing cases and noisy data cases. Code is available at https://github.com/MediaBrain-SJTU/AuxFormer.Comment: Accpeted to ICCV202