Beihang University

About: Beihang University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Computer science & Control theory. The organization has 67002 authors who have published 73507 publications receiving 975691 citations. The organization is also known as: Beijing University of Aeronautics and Astronautics.

New Approach to Delay-Dependent Stability Analysis and Stabilization for Continuous-Time Fuzzy Systems With Time-Varying Delay

Abstract: This paper is concerned with delay-dependent stability analysis and stabilization problems for continuous-time Takagi and Sugeno (T-S) fuzzy systems with a time-varying delay A new method for the delay-dependent stability analysis and stabilization is suggested, which is less conservative than other existing ones First, based on a fuzzy Lyapunov-Krasovskii functional (LKF), a delay-dependent stability criterion is derived for the open-loop fuzzy systems In the derivation process, some free fuzzy weighting matrices are introduced to express the relationships among the terms of the system equation, and among the terms in the Leibniz-Newton formula Then, a delay-dependent stabilization condition based on the so-called parallel distributed compensation (PDC) scheme is worked out for the closed-loop fuzzy systems The proposed stability criterion and stabilization condition are represented in terms of linear matrix inequalities (LMIs) and compared with the existing ones via two examples Finally, application to control of a truck-trailer is also given to illustrate the effectiveness of the proposed design method

Adaptive NMS: Refining Pedestrian Detection in a Crowd

Abstract: Pedestrian detection in a crowd is a very challenging issue. This paper addresses this problem by a novel Non-Maximum Suppression (NMS) algorithm to better refine the bounding boxes given by detectors. The contributions are threefold: (1) we propose adaptive-NMS, which applies a dynamic suppression threshold to an instance, according to the target density; (2) we design an efficient subnetwork to learn density scores, which can be conveniently embedded into both the single-stage and two-stage detectors; and (3) we achieve state of the art results on the CityPersons and CrowdHuman benchmarks.

Synergistically optimized electrical and thermal transport properties of SnTe via alloying high-solubility MnTe

Abstract: Lead chalcogenides are the most efficient thermoelectric materials. In comparison, SnTe, a lead-free analogue of PbTe, exhibits inferior thermoelectric performance due to low Seebeck coefficient and high thermal conductivity. In this report, we show that we can synergistically optimize the electrical and thermal transport properties of SnTe via alloying Mn. We report that the introduction of Mn (0–50%) induces multiple effects on the band structure and microstructure of SnTe: for the former, it can tune the Fermi level and promote the convergence of the two valence bands, concurrently enhancing the Seebeck coefficient; for the latter, it can profoundly modify the microstructure into an all-scale hierarchical architecture (including nanoscale precipitates/MnTe laminates, stacking faults, layered structure, atomic-scale point defects, etc.) to scatter phonons with a broad range of mean free paths, strongly reducing the lattice thermal conductivity. Meanwhile, most significantly, the Mn alloying enlarges the energy gap of the conduction band (C band) and the light valence band (L band), thereby suppressing the bipolar thermal conductivity by increasing the band gap. The integration of these effects yields a high ZT of 1.3 at 900 K for 17% Mn alloyed SnTe.

Photochemical processing of aqueous atmospheric brown carbon

Abstract: . Atmospheric brown carbon (BrC) is a collective term for light absorbing organic compounds in the atmosphere. While the identification of BrC and its formation mechanisms is currently a central effort in the community, little is known about the atmospheric removal processes of aerosol BrC. As a result, we report on a series of laboratory studies of photochemical processing of BrC in the aqueous phase, by direct photolysis and OH oxidation. Solutions of ammonium sulfate mixed with glyoxal (GLYAS) or methylglyoxal (MGAS) are used as surrogates for a class of secondary BrC mediated by imine intermediates. Three nitrophenol species, namely 4-nitrophenol, 5-nitroguaiacol and 4-nitrocatechol, were investigated as a class of water-soluble BrC originating from biomass burning. Photochemical processing induced significant changes in the absorptive properties of BrC. The imine-mediated BrC solutions exhibited rapid photo-bleaching with both direct photolysis and OH oxidation, with atmospheric half-lives of minutes to a few hours. The nitrophenol species exhibited photo-enhancement in the visible range during direct photolysis and the onset of OH oxidation, but rapid photo-bleaching was induced by further OH exposure on an atmospheric timescale of an hour or less. To illustrate the atmospheric relevance of this work, we also performed direct photolysis experiments on water-soluble organic carbon extracted from biofuel combustion samples and observed rapid changes in the optical properties of these samples as well. Overall, these experiments indicate that atmospheric models need to incorporate representations of atmospheric processing of BrC species to accurately model their radiative impacts.

Statistical physics-based reconstruction in compressed sensing

Abstract: Compressed sensing is triggering a major evolution in signal acquisition. It consists in sampling a sparse signal at low rate and later using computational power for its exact reconstruction, so that only the necessary information is measured. Currently used reconstruction techniques are, however, limited to acquisition rates larger than the true density of the signal. We design a new procedure which is able to reconstruct exactly the signal with a number of measurements that approaches the theoretical limit in the limit of large systems. It is based on the joint use of three essential ingredients: a probabilistic approach to signal reconstruction, a message-passing algorithm adapted from belief propagation, and a careful design of the measurement matrix inspired from the theory of crystal nucleation. The performance of this new algorithm is analyzed by statistical physics methods. The obtained improvement is confirmed by numerical studies of several cases.