Dual-density-based reweighted ℓ1\ell_{1}-algorithms for a class of ℓ0\ell_{0}-minimization problems

The optimization problem with sparsity arises in many areas of science and engineering such as compressed sensing, image processing, statistical learning and data sparse approximation. In this paper, we study the dual-density-based reweighted $\ell_{1}$-algorithms for a class of $\ell_{0}$-minimization models which can be used to model a wide range of practical problems. This class of algorithms is based on certain convex relaxations of the reformulation of the underlying $\ell_{0}$-minimization model. Such a reformulation is a special bilevel optimization problem which, in theory, is equivalent to the underlying $\ell_{0}$-minimization problem under the assumption of strict complementarity. Some basic properties of these algorithms are discussed, and numerical experiments have been carried out to demonstrate the efficiency of the proposed algorithms. Comparison of numerical performances of the proposed methods and the classic reweighted $\ell_1$-algorithms has also been made in this paper

Algorithms and stability analysis for optimization problems with sparsity

The optimization models with sparsity arise in many areas of science and engineering, such as compressive sensing, image processing, statistical learning and machine learning. In this thesis, we study a general 10-minimization model, which can be used to deal with many practical applications. Firstly, we show some theoretical properties of the solutions of this model. Then, two types of re-weighted 11-algorithms will be developed from both the perspectives of primal and dual spaces, respectively. The primal re-weighted 11-algorithms will be derived through the 1st-order approximation of the so-called merit functions for sparsity. The dual re-weighted 11-algorithms for the general 10-model will be developed based on the reformulation of the general 10-model as a certain bilevel programming problem under the assumption of strict complementarity. We conduct numerical experiments to demonstrate the efficiency of the primal and dual re-weighted 11-algorithms and compare with some existing algorithms. We also establish a general stability result for a class of 11-minimization approach which is broad enough to cover many important special cases. Unlike the existing stability results developed under the null space property and restricted isotonic property, we use a classic Hoffman's theorem to establish a restricted-weak-RSP-based stability result for this class of 11-minimization approach

Optical property measurements of lithium chloride aqueous solution for a novel solar neutrino experiment

The lithium chloride aqueous solution has great potential to be the detection medium of a novel solar neutrino detector. The nuclide Li-7 provides a charged-current interaction channel with a high cross-section for the MeV-scale solar electron-neutrinos, enabling measurement of the solar neutrino spectrum. This work measures the optical properties and the light yields of a saturated lithium chloride solution. After adsorption with activated carbon and recrystallization, the solution shows little absorption in the sensitive wavelength range of the bialkali photomultipliers. The attenuation length is evaluated to reach 50 meters at 430 nm. In addition to being a pure Cherenkov detector medium, a scintillation component, carbostyril 124, is added to the LiCl aqueous solution. Both Cherenkov and scintillation are observed, making a water-based lithium-rich Cherenkov scintillation detector possible.Comment: 12 pages, 8 figures. Major revisio

InfoPattern: Unveiling Information Propagation Patterns in Social Media

Social media play a significant role in shaping public opinion and influencing ideological communities through information propagation. Our demo InfoPattern centers on the interplay between language and human ideology. The demo (Code: https://github.com/blender-nlp/InfoPattern ) is capable of: (1) red teaming to simulate adversary responses from opposite ideology communities; (2) stance detection to identify the underlying political sentiments in each message; (3) information propagation graph discovery to reveal the evolution of claims across various communities over time. (Live Demo: https://incas.csl.illinois.edu/blender/About

Cyclic Deformation Behavior of Additive-Manufactured IN738LC Superalloys from Virgin and Reused Powders

In laser powder bed fusion (L-PBF), most powders are not melted in the chamber and collected after the printing process. Powder reuse is appreciable without sacrificing the mechanical properties of target components. To understand the influences of powder reuse on mechanical performance, a nickel-based superalloy, IN738LC, was investigated. Powder morphology, microstructure and chemical compositions of virgin and reused powders were characterized. An increase in oxygen content, generally metallic oxides, was located on the surface of powders. Monotonic tensile and cyclic fatigue were tested. Negligible deterioration in strength and tensile ductility were found, while scattered fatigue performance with regard to fatigue life was shown. Deformation and fatigue crack propagation mechanisms were discussed for describing the powder degradation effects