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Jia Li

Publications and source records attributed to Jia Li.

At least 595 records · Page 33Linked to original sources
arXiv2016

Hidden Markov Models on Variable Blocks with a Modal Clustering Algorithm and Applications

Motivated by high-throughput single-cell cytometry data with applications to vaccine development and immunological research, we consider statistical clustering in large-scale data that contain multiple rare clusters. We propose a new hierarchical mixture model, namely Hidden Markov Model on Variable Blocks (HMM-VB), and a new mode search algorithm called Modal Baum-Welch (MBW) for efficient clustering. Exploiting the widely accepted chain-like dependence among groups of variables in the cytometry data, we propose to treat the hierarchy of variable groups as a figurative time line and employ a HMM-type model, namely HMM-VB. We also propose to use mode-based clustering, aka modal clustering, and overcome the exponential computational complexity by MBW. In a series of experiments on simulated data HMM-VB and MBW have better performance than existing methods. We also apply our method to identify rare cell subsets in cytometry data and examine its strengths and limitations.

stat.ME↗
arXiv2016

Modeling Photographic Composition via Triangles

The capacity of automatically modeling photographic composition is valuable for many real-world machine vision applications such as digital photography, image retrieval, image understanding, and image aesthetics assessment. The triangle technique is among those indispensable composition methods on which professional photographers often rely. This paper proposes a system that can identify prominent triangle arrangements in two major categories of photographs: natural or urban scenes, and portraits. For the natural or urban scene pictures, the focus is on the effect of linear perspective. For portraits, we carefully examine the positioning of human subjects in a photo. We show that line analysis is highly advantageous for modeling composition in both categories. Based on the detected triangles, new mathematical descriptors for composition are formulated and used to retrieve similar images. Leveraging the rich source of high aesthetics photos online, similar approaches can potentially be incorporated in future smart cameras to enhance a person's photo composition skills.

cs.CV↗
arXiv2016

Storm Detection by Visual Learning Using Satellite Images

Computers are widely utilized in today's weather forecasting as a powerful tool to leverage an enormous amount of data. Yet, despite the availability of such data, current techniques often fall short of producing reliable detailed storm forecasts. Each year severe thunderstorms cause significant damage and loss of life, some of which could be avoided if better forecasts were available. We propose a computer algorithm that analyzes satellite images from historical archives to locate visual signatures of severe thunderstorms for short-term predictions. While computers are involved in weather forecasts to solve numerical models based on sensory data, they are less competent in forecasting based on visual patterns from satellite images. In our system, we extract and summarize important visual storm evidence from satellite image sequences in the way that meteorologists interpret the images. In particular, the algorithm extracts and fits local cloud motion from image sequences to model the storm-related cloud patches. Image data from the year 2008 have been adopted to train the model, and historical thunderstorm reports in continental US from 2000 through 2013 have been used as the ground-truth and priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing more accurate thunderstorm forecasts.

cs.CV↗
arXiv2015

Graphene/g-C2N bilayer:gap opening, enhanced visible light response and electrical field tuning band structure

Opening up a band gap of the graphene and finding a suitable substrate are two challenges for constituting the nano-electronic equipment. A new two-dimensional layered crystal g-C2N (Nat. Commun. 2015, 6, 1--7) with novel electronic and optical properties can be effectively synthesized via a wet-chemical reaction. And g-C2N can be used as a suitable substrate to open the band gap of graphene as much as 0.239 eV, which is large enough for the band gap opening at room temperature. The physics behind the band gap opening is that g-C2N substrate can produce the inhomogeneous electrostatic potential over the graphene layer. The imposition of external electrical field can tune the band gap of the hybrid of graphene/g-C2N effectively from the semiconductors to the metal. The hybrid graphene/g-C2N displays an enhanced optical activity compared with the pure g-C2N monolayer.

cond-mat.mtrl-sci↗
arXiv2015

Monolayer charge-neutral graphene on platinum with extremely weak electron-phonon coupling

Epitaxial growth of graphene on transition metal substrates is an important route for obtaining large scale graphene. However, the interaction between graphene and the substrate often leads to multiple orientations, distorted graphene band structure, large doping and strong electron-phonon coupling. Here we report the growth of monolayer graphene with high crystalline quality on Pt(111) substrate by using a very low concentration of an internal carbon source with high annealing temperature. The controlled growth leads to electronically decoupled graphene: it is nearly charge neutral and has extremely weak electron-phonon coupling (coupling strength $λ$ $\approx$ 0.056) as revealed by angle-resolved photoemission spectroscopic measurements. The thermodynamics and kinetics of the carbon diffusion process is investigated by DFT calculation. Such graphene with negligible graphene-substrate interaction provides an important platform for fundamental research as well as device applications when combined with a nondestructive sample transfer technique.

cond-mat.mtrl-sci↗
arXiv2015

Gaussian Mixture Models with Component Means Constrained in Pre-selected Subspaces

We investigate a Gaussian mixture model (GMM) with component means constrained in a pre-selected subspace. Applications to classification and clustering are explored. An EM-type estimation algorithm is derived. We prove that the subspace containing the component means of a GMM with a common covariance matrix also contains the modes of the density and the class means. This motivates us to find a subspace by applying weighted principal component analysis to the modes of a kernel density and the class means. To circumvent the difficulty of deciding the kernel bandwidth, we acquire multiple subspaces from the kernel densities based on a sequence of bandwidths. The GMM constrained by each subspace is estimated; and the model yielding the maximum likelihood is chosen. A dimension reduction property is proved in the sense of being informative for classification or clustering. Experiments on real and simulated data sets are conducted to examine several ways of determining the subspace and to compare with the reduced rank mixture discriminant analysis (MDA). Our new method with the simple technique of spanning the subspace only by class means often outperforms the reduced rank MDA when the subspace dimension is very low, making it particularly appealing for visualization.

stat.ML↗
arXiv2015

Theory of the Dirac Half Metal and Quantum Anomalous Hall Effect in Mn Intercalated Epitaxial Graphene

The prospect of a Dirac half metal, a material which is characterized by a bandstructure with a gap in one spin channel but a Dirac cone in the other, is of both fundamental interest and a natural candidate for use in spin-polarized current applications. However, while the possibility of such a material has been reported based on model calculations[H. Ishizuka and Y. Motome, Phys. Rev. Lett. 109, 237207 (2012)], it remains unclear what material system might realize such an exotic state. Using first-principles calculations, we show that the experimentally accessible Mn intercalated epitaxial graphene on SiC(0001) transits to a Dirac half metal when the coverage is > 1/3 monolayer. This transition results from an orbital-selective breaking of quasi-2D inversion symmetry, leading to symmetry breaking in a single spin channel which is robust against randomness in the distribution of Mn intercalates. Furthermore, the inclusion of spin-orbit interaction naturally drives the system into the quantum anomalous Hall (QAH) state. Our results thus not only demonstrate the practicality of realizing the Dirac half metal beyond a toy model but also open up a new avenue to the realization of the QAH effect.

cond-mat.str-el↗
arXiv2014

Big Graph Search: Challenges and Techniques

On one hand, compared with traditional relational and XML models, graphs have more expressive power and are widely used today. On the other hand, various applications of social computing trigger the pressing need of a new search paradigm. In this article, we argue that big graph search is the one filling this gap. To show this, we first introduce the application of graph search in various scenarios. We then formalize the graph search problem, and give an analysis of graph search from an evolutionary point of view, followed by the evidences from both the industry and academia. After that, we analyze the difficulties and challenges of big graph search. Finally, we present three classes of techniques towards big graph search: query techniques, data techniques and distributed computing techniques.

cs.DB↗
arXiv2014

Manganese reduction/oxidation reaction on graphene composites as a reversible process for storing enormous energy at a fast rate

Oxygen reduction/evolution reaction (ORR/OER) is a basic process for fuel cells or metal air batteries. However, ORR/OER generally requires noble metal catalysts and suffers from low solubility (10-3 molar per liter) of O2, low kinetics rate (10-6 cm2/s) and low reversibility. We report a manganese reduction/oxidation reaction (MRR/MOR) on graphene/MnO2 composites, delivering a high capacity (4200 mAh/g), fast kinetics (0.0024 cm2/s, three orders higher than ORR/OER), high solubility (three orders than O2), and high reversibility (100%). We further use MRR/MOR to invent a rechargeable manganese ion battery (MIB), which delivers an energy density of 1200 Wh/Kg (several times of lithium ion battery), a fast charge ability (3 minutes), and a long cycle life (10,000 cycles). MRR/MOR renders a new class of energy conversion or storage systems with a very high energy density enabling electric vehicles run much more miles at one charge.

cond-mat.mtrl-sci↗
arXiv2013

Volatility occupation times

We propose nonparametric estimators of the occupation measure and the occupation density of the diffusion coefficient (stochastic volatility) of a discretely observed Itô semimartingale on a fixed interval when the mesh of the observation grid shrinks to zero asymptotically. In a first step we estimate the volatility locally over blocks of shrinking length, and then in a second step we use these estimates to construct a sample analogue of the volatility occupation time and a kernel-based estimator of its density. We prove the consistency of our estimators and further derive bounds for their rates of convergence. We use these results to estimate nonparametrically the quantiles associated with the volatility occupation measure.

math.ST↗
arXiv2013

Parallel D2-Clustering: Large-Scale Clustering of Discrete Distributions

The discrete distribution clustering algorithm, namely D2-clustering, has demonstrated its usefulness in image classification and annotation where each object is represented by a bag of weighed vectors. The high computational complexity of the algorithm, however, limits its applications to large-scale problems. We present a parallel D2-clustering algorithm with substantially improved scalability. A hierarchical structure for parallel computing is devised to achieve a balance between the individual-node computation and the integration process of the algorithm. Additionally, it is shown that even with a single CPU, the hierarchical structure results in significant speed-up. Experiments on real-world large-scale image data, Youtube video data, and protein sequence data demonstrate the efficiency and wide applicability of the parallel D2-clustering algorithm. The loss in clustering accuracy is minor in comparison with the original sequential algorithm.

cs.LG↗
arXiv2013

An adaptively weighted statistic for detecting differential gene expression when combining multiple transcriptomic studies

Global expression analyses using microarray technologies are becoming more common in genomic research, therefore, new statistical challenges associated with combining information from multiple studies must be addressed. In this paper we will describe our proposal for an adaptively weighted (AW) statistic to combine multiple genomic studies for detecting differentially expressed genes. We will also present our results from comparisons of our proposed AW statistic to Fisher's equally weighted (EW), Tippett's minimum p-value (minP) and Pearson's (PR) statistics. Due to the absence of a uniformly powerful test, we used a simplified Gaussian scenario to compare the four methods. Our AW statistic consistently produced the best or near-best power for a range of alternative hypotheses. AW-obtained weights also have the additional advantage of filtering discordant biomarkers and providing natural detected gene categories for further biological investigation. Here we will demonstrate the superior performance of our proposed AW statistic based on a mix of power analyses, simulations and applications using data sets for multi-tissue energy metabolism mouse, multi-lab prostate cancer and lung cancer.

stat.AP↗
arXiv2012

The transition from amorphous to crystalline in Al/Zr multilayers

The amorphous-to-crystalline transition in Al(1.0%wtSi)/Zr and Al(Pure)/Zr multilayers grown by direct-current magnetron sputtering system has been characterized over a range of Al layer thicknesses (1.0-5.0 nm) by using a series of complementary measurements including grazing incidence X-ray reflectometry, atomic force microscopy, X-ray diffraction and high-resolution transmission electron microscopy. The Al layer thickness transition exhibits the Si doped in Al could not only disfavor the crystallization of Al, but also influence the changing trends of surface roughness and diffraction peak position of phase Al<111>. An interesting feature of the presence of Si in Al layer is that Si could influence the transition process in Al(1%wtSi) layer, in which the critical thickness (1.6 nm) of Al(Pure) layer in Al(Pure)/Zr shifts to 1.8 nm of Al(1.0%wtSi) layer in Al(1.0%wtSi)/Zr multilayer. We also found that the Zr-on-Al interlayer is wider than the Al-on-Zr interlayer in both systems, and the Al layers do not have specific crystal orientation in the directions vertical to the layer from SAED patterns below the thickness (3.0 nm) of Al layers. Above the thickness (3.0 nm) of Al layers, the Al layers are highly oriented in Al<111>, so that the transformation from asymmetrical to symmetrical interlayers can be observed. Based on the analysis of all measurements, we build up a model with four steps, which could explain the Al layer thickness transition process in terms of a critical thickness for the nucleation of Al(Pure) and Al(1%wtSi) crystallites.

cond-mat.mtrl-sci↗
arXiv2012

Thermally induced structural modification in the Al/Zr multilayers

The effect of increasing temperature on the structural stability and interactions of two kinds of Al/Zr (Al(1%wtSi)/Zr and Al(Pure)/Zr) multilayer mirrors are investigated. All Al/Zr multilayers annealed from 200^{\circ}C to 500^{\circ}C, were deposited on Si wafers by using direct-current magnetron sputtering technology. A detailed and consistent picture of the thermally induced changes in the microstructure is obtained using an array of complementary measurements including grazing incidence X-ray reflectance, atomic force microscope, X-ray diffraction and high-resolution transmission electron microscopy. The first significant structural changes of two systems are observed at 250^{\circ}C, characterized by asymmetric interlayers appears at interface. At 290^{\circ}C, the interface consisted of amorphous Al-Zr alloy is transformed to amorphous Al-Zr alloy and cubic ZrAl3 in both systems. By 298^{\circ}C of Al(1%wtSi)/Zr and 295^{\circ}C of Al(Pure)/Zr multilayers, the interfacial phases of Al-Zr alloy transform completely into polycrystalline mixtures of hcp-ZrAl2 and cubic-ZrAl3, which smooth the interface boundary and lower the surface roughness in the multilayers. Up to 500^{\circ}C, the multilayer structure still exists in both systems, and the differences between the asymmetric interlayers are much larger in the multilayers. Finally, we discuss the transformation from symmetric to asymmetric in the annealing process for other systems.

cond-mat.mtrl-sci↗
arXiv2012

Dirac Fermion in Strongly-Bound Graphene Systems

It is highly desirable to integrate graphene into existing semiconductor technology, where the combined system is thermodynamically stable yet maintain a Dirac cone at the Fermi level. Firstprinciples calculations reveal that a certain transition metal (TM) intercalated graphene/SiC(0001), such as the strongly-bound graphene/intercalated-Mn/SiC, could be such a system. Different from free-standing graphene, the hybridization between graphene and Mn/SiC leads to the formation of a dispersive Dirac cone of primarily TM d characters. The corresponding Dirac spectrum is still isotropic, and the transport behavior is nearly identical to that of free-standing graphene for a bias as large as 0.6 V, except that the Fermi velocity is half that of graphene. A simple model Hamiltonian is developed to qualitatively account for the physics of the transfer of the Dirac cone from a dispersive system (e.g., graphene) to an originally non-dispersive system (e.g., TM).

cond-mat.mes-hall↗
arXiv2011

Activated dissociation of O2 on Pb(111) surfaces by Pb adatoms

We investigate the dissociation of O2 on Pb(111) surface using first-principles calculations. It is found that in a practical high-vacuum environment, the adsorption of molecular O2 takes place on clean Pb surfaces only at low temperatures such as 100 K, but the O2 easily desorbs at (elevated) room temperatures. It is further found that the Pb adatoms enhance the molecular adsorption and activate the adsorbed O2 to dissociate during subsequent room-temperature annealing. Our theory explains the observation of a two-step oxidation process on the Pb surfaces by the unique role of Pb adatoms.

physics.chem-ph↗