Lifelong Spectral Clustering

In the past decades, spectral clustering (SC) has become one of the most effective clustering algorithms. However, most previous studies focus on spectral clustering tasks with a fixed task set, which cannot incorporate with a new spectral clustering task without accessing to previously learned tasks. In this paper, we aim to explore the problem of spectral clustering in a lifelong machine learning framework, i.e., Lifelong Spectral Clustering (L2SC). Its goal is to efficiently learn a model for a new spectral clustering task by selectively transferring previously accumulated experience from knowledge library. Specifically, the knowledge library of L2SC contains two components: 1) orthogonal basis library: capturing latent cluster centers among the clusters in each pair of tasks; 2) feature embedding library: embedding the feature manifold information shared among multiple related tasks. As a new spectral clustering task arrives, L2SC firstly transfers knowledge from both basis library and feature library to obtain encoding matrix, and further redefines the library base over time to maximize performance across all the clustering tasks. Meanwhile, a general online update formulation is derived to alternatively update the basis library and feature library. Finally, the empirical experiments on several real-world benchmark datasets demonstrate that our L2SC model can effectively improve the clustering performance when comparing with other state-of-the-art spectral clustering algorithms.Comment: 9 pages,7 figure

Feedback-based debugging

National Research Foundation (NRF) Singapor

Temperature dependence of Mott transition in VO_2 and programmable critical temperature sensor

The temperature dependence of the Mott metal-insulator transition (MIT) is studied with a VO_2-based two-terminal device. When a constant voltage is applied to the device, an abrupt current jump is observed with temperature. With increasing applied voltages, the transition temperature of the MIT current jump decreases. We find a monoclinic and electronically correlated metal (MCM) phase between the abrupt current jump and the structural phase transition (SPT). After the transition from insulator to metal, a linear increase in current (or conductivity) is shown with temperature until the current becomes a constant maximum value above T_{SPT}=68^oC. The SPT is confirmed by micro-Raman spectroscopy measurements. Optical microscopy analysis reveals the absence of the local current path in micro scale in the VO_2 device. The current uniformly flows throughout the surface of the VO_2 film when the MIT occurs. This device can be used as a programmable critical temperature sensor.Comment: 4 pages, 3 figure

The Investigation of NOx Formation and Reduction during O2/CO2 Combustion of Raw Coal and Coal Char

AbstractThis study investigated the behavior of NOx emissions during combustion of pulverized coal char and pulverized raw coal in O2/CO2 environments under nearly isothermal condition in a drop tube furnace. A representative Chinese coal Ling Nancang (LNC) and LNC CO2-char (made in CO2 condition) were studied with four different excess oxygen ratios (α=0.6, 0.8, 1.2, and 1.4). Combustion experiments were performed with an elevated concentration (850ppm) of NO. When α increased from 0.6 to 1.4, the total amount of NOx reduction was increased in both pulverized coal and char combustion. To investigate the effects of coal and char on NOx reburn reactions, LNC coal char and the raw coal combustion experiments were also performed under three high background NO concentrations (400, 850, and 1200ppm) in O2/CO2 atmosphere. During experiments with elevated NO concentrations, there was an increase in net NO reduction; however, there was also a decrease in the calculated NO reduction ratio