No abstract

As a new type of high-performance concrete material, glass powder (GP) concrete is beneficial to the environment and concrete performance. However, the specific application method still needs to be studied. This paper introduces the structure theory of glass and the mechanism by which glass powder affects concrete. Through experiments, the effects of glass powder particle size, content, alkali content, and other factors on alkali-silica reaction (ASR) expansion, mechanical properties, and durability of concrete are compared. It is proven that glass powder can be used as a gel material in concrete. The existing problems in the research are summarized, and the latest research perspectives and methods are suggested.

Multiple kernel clustering (MKC) optimally combines a group of predefined kernel matrices to improve clustering performance. Although demonstrating promising performance in various applications, most of existing approaches adopt the min–min formulation, which could be sensitive to perturbation with adversarial samples. Moreover, existing MKC algorithms often involve several hypermeters preventing them into further real applications. To address these issues, we propose a parameter‐free effective sparse simple multiple kernel k‐means algorithm with max–min optimization formulation in this paper. To be specific, we propose to optimize the widely used unsupervised kernel alignment criterion by minimizing the kernel coefficient and maximizing the clustering partition matrix. Unlike traditional min–min formulation, the max–min kernel alignment is robust to adversarial sample perturbation and free of hyper‐parameters. An optimization method based on semi‐infinite linear program is designed to solve the complicated optimization problem. Extensive experiments on six multiple kernel benchmark data sets demonstrate the effectiveness of the proposed method.

No abstract