Linear Convergence of Adaptively Iterative Thresholding Algorithms for Compressed Sensing

This paper studies the convergence of the adaptively iterative thresholding (AIT) algorithm for compressed sensing. We first introduce a generalized restricted isometry property (gRIP). Then we prove that the AIT algorithm converges to the original sparse solution at a linear rate under a certain gRIP condition in the noise free case. While in the noisy case, its convergence rate is also linear until attaining a certain error bound. Moreover, as by-products, we also provide some sufficient conditions for the convergence of the AIT algorithm based on the two well-known properties, i.e., the coherence property and the restricted isometry property (RIP), respectively. It should be pointed out that such two properties are special cases of gRIP. The solid improvements on the theoretical results are demonstrated and compared with the known results. Finally, we provide a series of simulations to verify the correctness of the theoretical assertions as well as the effectiveness of the AIT algorithm.Comment: 15 pages, 5 figure

Mining Mid-level Features for Action Recognition Based on Effective Skeleton Representation

Recently, mid-level features have shown promising performance in computer vision. Mid-level features learned by incorporating class-level information are potentially more discriminative than traditional low-level local features. In this paper, an effective method is proposed to extract mid-level features from Kinect skeletons for 3D human action recognition. Firstly, the orientations of limbs connected by two skeleton joints are computed and each orientation is encoded into one of the 27 states indicating the spatial relationship of the joints. Secondly, limbs are combined into parts and the limb's states are mapped into part states. Finally, frequent pattern mining is employed to mine the most frequent and relevant (discriminative, representative and non-redundant) states of parts in continuous several frames. These parts are referred to as Frequent Local Parts or FLPs. The FLPs allow us to build powerful bag-of-FLP-based action representation. This new representation yields state-of-the-art results on MSR DailyActivity3D and MSR ActionPairs3D

Design and Integration of JUNO-OSIRIS

The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino detection experiment characterized by an acrylic sphere, measuring 35.4 m in diameter, containing 20,000 tons of liquid scintillator. This sphere is encompassed by as many as 17,600 photomultiplier tubes (PMTs) with a 20-inch diameter, achieving an overall coverage of 77.9%. With these impressive capabilities, the JUNO experiment aims to achieve an exceptional effective energy resolution of 3% at 1 MeV. The Online Scintillator Internal Radioactivity Investigation System (OSIRIS) serves as a precursor detector, around 100 m aside in horizontal of the site of the JUNO detector underground, tasked with monitoring and examining the purity of the liquid scintillator prior to its transfer to the JUNO central detector. The OSIRIS, also as a pre-detector of JUNO, is constructed with a cylindrical acrylic vessel designed to hold 18 tons of liquid scintillator. It is situated within a 9-m height cylindrical tank filled with 550 tons of pure water. This detector was specifically engineered to search for the fast coincidence decays of $^{214}$Bi -$^{214}$Po and $^{212}$Bi -$^{212}$Po in the decay chains of $^{238}$U and $^{232}$Th, respectively.OSIRIS has been designed to reach a sensitivity of 10$^{-16}$ g/g for U/Th to test scintillator radiopurity to the level required for the detection of solar neutrinos. Additionally, 64 20-inch microchannel plate PMTs (MCP PMTs) were positioned around the liquid scintillator vessel to observe incoming interactions, along with an additional 12 20-inch MCP PMTs for the water Cherenkov muon veto system. The OSIRIS pre-detector has been fully constructed and integrated, providing a plenty of preliminary results from the air runs. The next step in the process involves commencing the filling soon, aiming to involve an in-depth examination of the impurities within the liquid scintillator.Comment: 4 pages, 4 figure