Adaptive Graph-Based Feature Normalization for Facial Expression Recognition

Facial Expression Recognition (FER) suffers from data uncertainties caused by ambiguous facial images and annotators' subjectiveness, resulting in excursive semantic and feature covariate shifting problem. Existing works usually correct mislabeled data by estimating noise distribution, or guide network training with knowledge learned from clean data, neglecting the associative relations of expressions. In this work, we propose an Adaptive Graph-based Feature Normalization (AGFN) method to protect FER models from data uncertainties by normalizing feature distributions with the association of expressions. Specifically, we propose a Poisson graph generator to adaptively construct topological graphs for samples in each mini-batches via a sampling process, and correspondingly design a coordinate descent strategy to optimize proposed network. Our method outperforms state-of-the-art works with accuracies of 91.84% and 91.11% on the benchmark datasets FERPlus and RAF-DB, respectively, and when the percentage of mislabeled data increases (e.g., to 20%), our network surpasses existing works significantly by 3.38% and 4.52%

Measurement of Volumetric Deformation, Strain Localization, and Shear Band Characterization during Triaxial Testing using a Photogrammetry-Based Method

Triaxial Testing Has Been Routinely Used as a Standard Laboratory Test that Allows Correct Determination of Soil Characteristics. Previously the Volumetric Strain of the Triaxial Specimen Was Considered to Be Uniformly Distributed Along with the Specimen during the Isotropic and Deviatoric Loading. Although This Assumption Might Hold True under Isotropic Loading, the Effects of Restrained Ends and Disturbance during the Procedures of Specimen Installation and Testing Can Cause Nonuniform Strains throughout the Whole Specimen. This Paper Investigates the Effects of Specimen Preparation and Misalignment on the Strain Uniformity Along with the Soil Specimen during Triaxial Testing. a Series of Consolidated Drained Tests at Several Stress Paths Were Conducted on Sand Specimens. a Photogrammetry-Based Method Was Applied at Different Stages of Specimen Preparation and Testing to Provide a Three-Dimensional Full-Field Deformation Measurement of the Surface of the Triaxial Soil Specimen. One Commercial Camera Was Used to Capture Images for the Triaxial Specimen, and a Developed Application for Data Processing and Post-Processing Was Utilized to Ensure Automatic and Fast Processing of the Developed Photogrammetric-Based Method. the Local Displacement Data Provided by the Photogrammetry-Based Method Enabled the Evaluation of the Strain Localization and the Volumetric Strain Nonuniformity Analysis at Different Heights Along with the Specimen. the Triaxial Test Results Demonstrated that the Soil Specimen during Triaxial Testing Has Deformed Nonuniformly in the Axial, Radial, and Circumferential Directions. the Plots of the Strain Localization Precisely Presented the Variation of Local Strains and the Magnitude of Deformation after the Saturation Stage. These Results Prove the Soil Specimen Volume is Not Constant during Saturation, and Unavoidable Disturbance Had Occurred during the Specimen Preparation Steps and Saturation. the Results Proved that the Specimen Misalignment during Triaxial Testing Leads to Scattering in the Triaxial Test Results. Further Discussion Was Presented About the Shear Band Characterization Including Shear Band Thickness, Formation, and Propagation

Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning

Malicious jamming launched by smart jammer, which attacks legitimate transmissions has been regarded as one of the critical security challenges in wireless communications. Thus, this paper exploits intelligent reflecting surface (IRS) to enhance anti-jamming communication performance and mitigate jamming interference by adjusting the surface reflecting elements at the IRS. Aiming to enhance the communication performance against smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS) and reflecting beamforming at the IRS is formulated. As the jamming model and jamming behavior are dynamic and unknown, a win or learn fast policy hill-climbing (WoLF-PHC) learning approach is proposed to jointly optimize the anti-jamming power allocation and reflecting beamforming strategy without the knowledge of the jamming model. Simulation results demonstrate that the proposed anti-jamming based-learning approach can efficiently improve both the IRS-assisted system rate and transmission protection level compared with existing solutions.Comment: This paper appears in the Proceedings of IEEE Global Communications Conference (GLOBECOM) 2020. A full version appears in IEEE Transactions on Wireless Communications. arXiv:2004.1253

Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach

Malicious jamming launched by smart jammers can attack legitimate transmissions, which has been regarded as one of the critical security challenges in wireless communications. With this focus, this paper considers the use of an intelligent reflecting surface (IRS) to enhance anti-jamming communication performance and mitigate jamming interference by adjusting the surface reflecting elements at the IRS. Aiming to enhance the communication performance against a smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS), and reflecting beamforming at the IRS is formulated while considering quality of service (QoS) requirements of legitimate users. As the jamming model and jamming behavior are dynamic and unknown, a fuzzy win or learn fast-policy hill-climbing (WoLFPHC) learning approach is proposed to jointly optimize the anti-jamming power allocation and reflecting beamforming strategy, where WoLFPHC is capable of quickly achieving the optimal policy without the knowledge of the jamming model, and fuzzy state aggregation can represent the uncertain environment states as aggregate states. Simulation results demonstrate that the proposed anti-jamming learning-based approach can efficiently improve both the IRS-assisted system rate and transmission protection level compared with existing solutions

Fracture Propagation Behavior of Bedding Shale in the Process of Multistage Cluster Fracturing considering the Intercluster Stress Interference

AbstractStaged multicluster fracturing in horizontal wells is the key technology for forming complex fractures in shale reservoirs. The existence of shale bedding plays a conspicuous role for the propagation path of hydraulic fractures, affecting the propagation of the fracture height direction prominently. A 3D finite element model containing three clusters signed as side clusters and middle cluster was established based on the cohesive zone model and the dynamic distribution mechanism of interfracture flow. And the correctness of the model was verified by literature comparison. Some factors including cluster spacing, horizontal stress difference, shale bedding strength, perforation density, injection rate, and viscosity of fracturing fluid which influenced fracture propagation behavior of bedding shale were simulated. The results indicate that the stress interference of the middle cluster by the clusters on both sides will be prominently obvious when the cluster spacing is less than 10 m. Multiclusters will penetrate across the shale bedding when the horizontal stress difference is more than 4 MP, which will conspicuously reduce the activated probability of discontinuities and the complexity of fracture geometry. In correspondence with increase of horizontal stress difference, the interference between clusters also increases prominently, which will conspicuously decrease the propagation of the middle cluster. In order to comprehensively equalize the length of multiclusters, the inhibition of intercluster stress interference on the middle cluster propagation can be counteracted by improving pressure drop in perforation. The high injection rate and viscosity of fracturing fluid will contribute to the shale bedding shear slip increasingly, which is conducive to the formation of complex fractures in areas with well-developed bedding. The study has a certain guiding significance for the operation parameter design of multicluster fracturing in bedded shale