Nanjing University of Science and Technology

About: Nanjing University of Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Control theory & Catalysis. The organization has 31581 authors who have published 36390 publications receiving 525474 citations. The organization is also known as: Nánjīng Lǐgōng Dàxué & Nánlǐgōng.

Stabilizing nanostructures in metals using grain and twin boundary architectures

Abstract: Forming alloys with impurity elements is a routine method for modifying the properties of metals. An alternative approach involves the incorporation of interfaces into the crystalline lattice to enhance the metal's properties without changing its chemical composition. The introduction of high-density interfaces in nanostructured materials results in greatly improved strength and hardness; however, interfaces at the nanoscale show low stability. In this Review, I discuss recent developments in the stabilization of nanostructured metals by modifying the architectures of their interfaces. The amount, structure and distribution of several types of interfaces, such as high- and low-angle grain boundaries and twin boundaries, are discussed. I survey several examples of materials with nanotwinned and nanolaminated structures, as well as with gradient nanostructures, describing the techniques used to produce such samples and tracing their exceptional performances back to the nanoscale architectures of their interfaces. The incorporation of structural defects, in particular of interfaces, into crystalline lattices results in enhanced material properties. In this Review, different types of boundaries and interfaces are discussed, including high- and low-angle grain boundaries, twin boundaries, nanotwinned and nanolaminated structures, and gradient nanostructures.

Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey

Abstract: Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data and text documents. Researchers have published many articles in the field of topic modeling and applied in various fields such as software engineering, political science, medical and linguistic science, etc. There are various methods for topic modelling; Latent Dirichlet Allocation (LDA) is one of the most popular in this field. Researchers have proposed various models based on the LDA in topic modeling. According to previous work, this paper will be very useful and valuable for introducing LDA approaches in topic modeling. In this paper, we investigated highly scholarly articles (between 2003 to 2016) related to topic modeling based on LDA to discover the research development, current trends and intellectual structure of topic modeling. In addition, we summarize challenges and introduce famous tools and datasets in topic modeling based on LDA.

Robust sparse coding for face recognition

Abstract: Recently the sparse representation (or coding) based classification (SRC) has been successfully used in face recognition. In SRC, the testing image is represented as a sparse linear combination of the training samples, and the representation fidelity is measured by the l 2 -norm or l 1 -norm of coding residual. Such a sparse coding model actually assumes that the coding residual follows Gaussian or Laplacian distribution, which may not be accurate enough to describe the coding errors in practice. In this paper, we propose a new scheme, namely the robust sparse coding (RSC), by modeling the sparse coding as a sparsity-constrained robust regression problem. The RSC seeks for the MLE (maximum likelihood estimation) solution of the sparse coding problem, and it is much more robust to outliers (e.g., occlusions, corruptions, etc.) than SRC. An efficient iteratively reweighted sparse coding algorithm is proposed to solve the RSC model. Extensive experiments on representative face databases demonstrate that the RSC scheme is much more effective than state-of-the-art methods in dealing with face occlusion, corruption, lighting and expression changes, etc.