City University of Hong Kong

About: City University of Hong Kong is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 19778 authors who have published 60149 publications receiving 1738681 citations. The organization is also known as: CityU.

Recent developments in stainless steels

Abstract: This article presents an overview of the developments in stainless steels made since the 1990s. Some of the new applications that involve the use of stainless steel are also introduced. A brief introduction to the various classes of stainless steels, their precipitate phases and the status quo of their production around the globe is given first. The advances in a variety of subject areas that have been made recently will then be presented. These recent advances include (1) new findings on the various precipitate phases (the new J phase, new orientation relationships, new phase diagram for the Fe–Cr system, etc.); (2) new suggestions for the prevention/mitigation of the different problems and new methods for their detection/measurement and (3) new techniques for surface/bulk property enhancement (such as laser shot peening, grain boundary engineering and grain refinement). Recent developments in topics like phase prediction, stacking fault energy, superplasticity, metadynamic recrystallisation and the calculation of mechanical properties are introduced, too. In the end of this article, several new applications that involve the use of stainless steels are presented. Some of these are the use of austenitic stainless steels for signature authentication (magnetic recording), the utilisation of the cryogenic magnetic transition of the sigma phase for hot spot detection (the Sigmaplugs), the new Pt-enhanced radiopaque stainless steel (PERSS) coronary stents and stainless steel stents that may be used for magnetic drug targeting. Besides recent developments in conventional stainless steels, those in the high-nitrogen, low-Ni (or Ni-free) varieties are also introduced. These recent developments include new methods for attaining very high nitrogen contents, new guidelines for alloy design, the merits/demerits associated with high nitrogen contents, etc.

An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination

Abstract: This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

On the mathematical foundations of learning

Abstract: (1) A main theme of this report is the relationship of approximation to learning and the primary role of sampling (inductive inference). We try to emphasize relations of the theory of learning to the mainstream of mathematics. In particular, there are large roles for probability theory, for algorithms such as least squares, and for tools and ideas from linear algebra and linear analysis. An advantage of doing this is that communication is facilitated and the power of core mathematics is more easily brought to bear. We illustrate what we mean by learning theory by giving some instances. (a) The understanding of language acquisition by children or the emergence of languages in early human cultures. (b) In Manufacturing Engineering, the design of a new wave of machines is anticipated which uses sensors to sample properties of objects before, during, and after treatment. The information gathered from these samples is to be analyzed by the machine to decide how to better deal with new input objects (see [43]). (c) Pattern recognition of objects ranging from handwritten letters of the alphabet to pictures of animals, to the human voice. Understanding the laws of learning plays a large role in disciplines such as (Cognitive) Psychology, Animal Behavior, Economic Decision Making, all branches of Engineering, Computer Science, and especially the study of human thought processes (how the brain works). Mathematics has already played a big role towards the goal of giving a universal foundation of studies in these disciplines. We mention as examples the theory of Neural Networks going back to McCulloch and Pitts [25] and Minsky and Papert [27], the PAC learning of Valiant [40], Statistical Learning Theory as developed by Vapnik [42], and the use of reproducing kernels as in [17] among many other mathematical developments. We are heavily indebted to these developments. Recent discussions with a number of mathematicians have also been helpful. In

Emergent Behavior in Flocks

Abstract: We provide a model (for both continuous and discrete time) describing the evolution of a flock. Our model is parameterized by a constant beta capturing the rate of decay-which in our model is polynomial-of the influence between birds in the flock as they separate in space. Our main result shows that when beta<1/2 convergence of the flock to a common velocity is guaranteed, while for betages1/2 convergence is guaranteed under some condition on the initial positions and velocities of the birds only