Z. Y. Ge

Z. Y. Ge

Contact Details

Z. Y. Ge

Pubs By Year

Pub Categories

Nuclear Experiment (8)
Computer Science - Sound (8)
Solar and Stellar Astrophysics (7)
Computer Science - Computation and Language (6)
Computer Science - Computer Vision and Pattern Recognition (6)
Mathematics - Numerical Analysis (5)
Physics - Materials Science (5)
Physics - Instrumentation and Detectors (4)
Computer Science - Learning (3)
Mathematics - Analysis of PDEs (2)
Physics - Plasma Physics (2)
Astrophysics of Galaxies (2)
High Energy Physics - Phenomenology (2)
Astrophysics (1)
High Energy Physics - Theory (1)
Mathematics - Differential Geometry (1)
Mathematics - Mathematical Physics (1)
Physics - Mesoscopic Systems and Quantum Hall Effect (1)
Physics - Fluid Dynamics (1)
Computer Science - Networking and Internet Architecture (1)
Physics - Accelerator Physics (1)
Computer Science - Neural and Evolutionary Computing (1)
Computer Science - Artificial Intelligence (1)
Computer Science - Multimedia (1)
Mathematical Physics (1)

Publications Authored By Z. Y. Ge

The mechanism proposed here is for real-time speaker change detection in conversations, which firstly trains a neural network text-independent speaker classifier using in-domain speaker data. Through the network, features of conversational speech from out-of-domain speakers are then converted into likelihood vectors, i.e. Read More

This work presents a novel framework based on feed-forward neural network for text-independent speaker classification and verification, two related systems of speaker recognition. With optimized features and model training, it achieves 100% classification rate in classification and less than 6% Equal Error Rate (ERR), using merely about 1 second and 5 seconds of data respectively. Features with stricter Voice Active Detection (VAD) than the regular one for speech recognition ensure extracting stronger voiced portion for speaker recognition, speaker-level mean and variance normalization helps to eliminate the discrepancy between samples from the same speaker. Read More

Aiming for the simulation of colloidal droplets in microfluidic devices, we present here a numerical method for two-fluid systems subject to surface tension and depletion forces among the suspended droplets. The algorithm is based on a fast, second-order-accurate solver for the incompressible two-phase Navier-Stokes equations, and uses a level set method to capture the fluid interface. The four novel ingredients proposed here are, firstly, an interface-correction level set method (iCLS) that efficiently preserves mass. Read More

It is shown by particle-in-cell simulation that intense circularly polarized (CP) laser light can be contained in the cavity of a solid-density circular Al-plasma shell for hundreds of light-wave periods before it is dissipated by laser-plasma interaction. A right-hand CP laser pulse can propagate almost without reflection into the cavity through a highly magnetized overdense H-plasma slab filling the entrance hole. The entrapped laser light is then multiply reflected at the inner surfaces of the slab and shell plasmas, gradually losing energy to the latter. Read More

We intent to use stellar models with and without alpha-enhancement, as well as asteroseismic analysis, to study two alpha-enhanced stars, KIC 7976303 and KIC 8694723. For the alpha-enhanced models, we adopt [alpha/Fe] = 0.2, and 0. Read More

Oxygen and carbon are important elements in stellar populations. Their behavior refers to the formation history of the stellar populations. C and O abundances would also obviously influence stellar opacities and the overall metal abundance $Z$. Read More

Generation of relativistic electron (RE) beams during ultraintense laser pulse interaction with plasma targets is studied by collisional particle-in-cell (PIC) simulations. Strong magnetic field with transverse scale length of several local plasma skin depths, associated with RE currents propagation in the target, is generated by filamentation instability (FI) in collisional plasmas, inducing a great enhancement of the divergence of REs compared to that of collisionless cases. Such effect is increased with laser intensity and target charge state, suggesting that the RE divergence might be improved by using low-Z materials under appropriate laser intensities in future fast ignition experiments and in other applications of laser-driven electron beams. Read More

We present the performances of two 92% enriched $^{130}$TeO$_2$ crystals operated as thermal bolometers in view of a next generation experiment to search for neutrinoless double beta decay of $^{130}$Te. The crystals, 435 g each, show an energy resolution, evaluated at the 2615 keV $\gamma$-line of $^{208}$Tl, of 6.5 and 4. Read More

Main sequence turn-off (MSTO) stars have advantages as indicators of Galactic evolution since their ages could be robustly estimated from atmospheric parameters. Hundreds of thousands of MSTO stars have been selected from the LAMOST Galactic sur- vey to study the evolution of the Galaxy, and it is vital to derive accurate stellar parameters. In this work, we select 150 MSTO star candidates from the MSTO stars sample of Xiang that have asteroseismic parameters and determine accurate stellar parameters for these stars combing the asteroseismic parameters deduced from the Kepler photometry and atmospheric parameters deduced from the LAMOST spectra. Read More

Fine-grained classification is a relatively new field that has concentrated on using information from a single image, while ignoring the enormous potential of using video data to improve classification. In this work we present the novel task of video-based fine-grained object classification, propose a corresponding new video dataset, and perform a systematic study of several recent deep convolutional neural network (DCNN) based approaches, which we specifically adapt to the task. We evaluate three-dimensional DCNNs, two-stream DCNNs, and bilinear DCNNs. Read More

Speech recognition, especially name recognition, is widely used in phone services such as company directory dialers, stock quote providers or location finders. It is usually challenging due to pronunciation variations. This paper proposes an efficient and robust data-driven technique which automatically learns acceptable word pronunciations and updates the pronunciation dictionary to build a better lexicon without affecting recognition of other words similar to the target word. Read More

The concept of isochronous mass spectrometry (IMS) applying two time-of-flight (TOF) detectors originated many years ago at GSI. However, the corresponding method for data analysis has never been discussed in detail. Recently, two TOF detectors have been installed at CSRe and the new working mode of the ring is under test. Read More

In this paper, we present direct mass measurements of neutron-rich $^{86}$Kr projectile fragments conducted at the HIRFL-CSR facility in Lanzhou by employing the Isochronous Mass Spectrometry (IMS) method. The new mass excesses of $^{52-54}$Sc nuclides are determined to be -40492(82), -38928(114), -34654(540) keV, which show a significant increase of binding energy compared to the reported ones in the Atomic Mass Evaluation 2012 (AME12). In particular, $^{53}$Sc and $^{54}$Sc are more bound by 0. Read More

Modifications of the electronic bands of thin FeSe films due to oxygen vacancies in the supporting SrTiO 3 (001) substrate - and the interplay with spin-orbit coupling, magnetism, and epitaxy - are investigated by first-principles supercell calculations. Unfolded (k-projected) bands show that the oxygen vacancies both provide electron doping to the interface FeSe layer and also have notable effects on the details of the bands around the Fermi level, including renormalizing the width of the Fe-3d band near the Fermi level by a factor of about 0.6, and causing a splitting of ~40 meV at the M point for the checkerboard antiferromagnetic configuration. Read More

Previous accent classification research focused mainly on detecting accents with pure acoustic information without recognizing accented speech. This work combines phonetic knowledge such as vowels with acoustic information to build Guassian Mixture Model (GMM) classifier with Perceptual Linear Predictive (PLP) features, optimized by Hetroscedastic Linear Discriminant Analysis (HLDA). With input about 20-second accented speech, this system achieves classification rate of 51% on a 7-way classification system focusing on the major types of accents in English, which is competitive to the state-of-the-art results in this field. Read More

Authorship attribution refers to the task of automatically determining the author based on a given sample of text. It is a problem with a long history and has a wide range of application. Building author profiles using language models is one of the most successful methods to automate this task. Read More

Researches have shown accent classification can be improved by integrating semantic information into pure acoustic approach. In this work, we combine phonetic knowledge, such as vowels, with enhanced acoustic features to build an improved accent classification system. The classifier is based on Gaussian Mixture Model-Universal Background Model (GMM-UBM), with normalized Perceptual Linear Predictive (PLP) features. Read More

Various algorithms for text-independent speaker recognition have been developed through the decades, aiming to improve both accuracy and efficiency. This paper presents a novel PCA/LDA-based approach that is faster than traditional statistical model-based methods and achieves competitive results. First, the performance based on only PCA and only LDA is measured; then a mixed model, taking advantages of both methods, is introduced. Read More

This paper presents a method for detecting mispronunciations with the aim of improving Computer Assisted Language Learning (CALL) tools used by foreign language learners. The algorithm is based on Principle Component Analysis (PCA). It is hierarchical with each successive step refining the estimate to classify the test word as being either mispronounced or correct. Read More

Systems based on automatic speech recognition (ASR) technology can provide important functionality in computer assisted language learning applications. This is a young but growing area of research motivated by the large number of students studying foreign languages. Here we propose a Hidden Markov Model (HMM)-based method to detect mispronunciations. Read More

In the past few years, several case studies have illustrated that the use of occupancy information in buildings leads to energy-efficient and low-cost HVAC operation. The widely presented techniques for occupancy estimation include temperature, humidity, CO2 concentration, image camera, motion sensor and passive infrared (PIR) sensor. So far little studies have been reported in literature to utilize audio and speech processing as indoor occupancy prediction technique. Read More

In recent years, there has been an increasing number of information technologies utilized in buildings to advance the idea of "smart buildings". Among various potential techniques, the use of Wi-Fi based indoor positioning allows to locate and track smartphone users inside a building, therefore, location-aware intelligent solutions can be applied to control and of building operations. These location-aware indoor services (e. Read More

In practice, training language models for individual authors is often expensive because of limited data resources. In such cases, Neural Network Language Models (NNLMs), generally outperform the traditional non-parametric N-gram models. Here we investigate the performance of a feed-forward NNLM on an authorship attribution problem, with moderate author set size and relatively limited data. Read More

In the paper, we propose three new hp discontinuous Galerkin methods for the elasticity problem and make a comparison of the three numerical methods. And we prove the optimal order of convergence in energy norm and $L^2$-norm by the superpenalization technique. Finally, we give a numerical example to verify our theoretical results. Read More

This paper explores a pragmatic approach to multiple object tracking where the main focus is to associate objects efficiently for online and realtime applications. To this end, detection quality is identified as a key factor influencing tracking performance, where changing the detector can improve tracking by up to 18.9%. Read More

Isochronous mass spectrometry (IMS) in storage rings is a powerful tool for mass measurements of exotic nuclei with very short half-lives down to several tens of microseconds, using a multicomponent secondary beam separated in-flight without cooling. However, the inevitable momentum spread of secondary ions limits the precision of nuclear masses determined by using IMS. Therefore, the momentum measurement in addition to the revolution period of stored ions is crucial to reduce the influence of the momentum spread on the standard deviation of the revolution period, which would lead to a much improved mass resolving power of IMS. Read More

We present a novel deep convolutional neural network (DCNN) system for fine-grained image classification, called a mixture of DCNNs (MixDCNN). The fine-grained image classification problem is characterised by large intra-class variations and small inter-class variations. To overcome these problems our proposed MixDCNN system partitions images into K subsets of similar images and learns an expert DCNN for each subset. Read More

The ratios $r_{01}$ and $r_{10}$ of small to large separations of KIC 2837475 primarily exhibit an increase behavior in the observed frequency range. The calculations indicate that only the models with overshooting parameter $\delta_{\rm ov}$ between approximately 1.2 and 1. Read More

Fine-grained categorisation has been a challenging problem due to small inter-class variation, large intra-class variation and low number of training images. We propose a learning system which first clusters visually similar classes and then learns deep convolutional neural network features specific to each subset. Experiments on the popular fine-grained Caltech-UCSD bird dataset show that the proposed method outperforms recent fine-grained categorisation methods under the most difficult setting: no bounding boxes are presented at test time. Read More

We propose a local modelling approach using deep convolutional neural networks (CNNs) for fine-grained image classification. Recently, deep CNNs trained from large datasets have considerably improved the performance of object recognition. However, to date there has been limited work using these deep CNNs as local feature extractors. Read More

In the work, the numerical methods are designed for the Bogoliubov-Tolmachev-Shirkov model in superconductivity theory. The numerical methods are novel and effective to determine the critical transition temperature and approximate to the energy gap function of the above model. Finally, a numerical example confirming the theoretical results is presented. Read More

This paper concerns with finite element approximations of a quasi-static poroelasticity model in displacement-pressure formulation which describes the dynamics of poro-elastic materials under an applied mechanical force on the boundary. To better describe the multiphysics process of deformation and diffusion for poro-elastic materials, we first present a reformulation of the original model by introducing two pseudo-pressures, one of them is shown to satisfy a diffusion equation, we then propose a time-stepping algorithm which decouples (or couples) the reformulated PDE problem at each time step into two sub-problems, one of which is a generalized Stokes problem for the displacement vector field (of the solid network of the poro-elastic material) along with one pseudo-pressure field and the other is a diffusion problem for the other pseudo-pressure field (of the solvent of the material). In the paper, the Taylor-Hood mixed finite element method combined with the $P_1$-conforming finite element method is used as an example to demonstrate the viability of the proposed multiphysics approach. Read More

In this paper, a new stabilized discontinuous Galerkin method within a new function space setting is introduced, which involves an extra stabilization term on the normal fluxes across the element interfaces. It is different from the general DG methods. The formulation satisfies a local conservation property and we prove well posedness of the new formulation by Inf-Sup condition. Read More

Isochronous mass spectrometry (IMS) in storage rings is a successful technique for accurate mass measurements of short-lived nuclides with relative precision of about $10^{-5}-10^{-7}$. Instabilities of the magnetic fields in storage rings are one of the major contributions limiting the achievable mass resolving power, which is directly related to the precision of the obtained mass values. A new data analysis method is proposed allowing one to minimise the effect of such instabilities. Read More

The aim of this paper is to determinate the fundamental parameters of six exoplanet host (EH) stars and their planets. While techniques for detecting exoplanets yield properties of the planet only as a function of the properties of the host star, hence, we must accurately determine parameters of EH stars at first. For this reason, we constructed a grid of stellar models including diffusion and rotation-induced extra-mixing with given ranges of input parameters (i. Read More

The oscillations of the solar-like star HD 49933 have been observed thoroughly by CoRot. Two dozens of frequency shifts, which are closely related with the change in magnetic activity, have been measured. To explore the effects of the magnetic activity on the frequency shifts, we calculate frequency shifts for the radial and $l = 1$ p-modes of HD 49933 with the general variational method, which evaluates the shifts using a spatial integral of the product of a kernel and some sources. Read More

The nonzero vacuum expectative values of sneutrinos induce spontaneously R-parity and lepton number violation, and generate three tiny Majorana neutrino masses through the seesaw mechanism in the $\mu\nu$SSM, which is one of Supersymmetric extensions beyond Standard Model. Applying effective Lagrangian method, we study the transition magnetic moment of Majorana neutrinos in the model here. Under the constraints from neutrino oscillations, we consider the two possibilities on the neutrino mass spectrum with normal or inverted ordering. Read More

The frequency ratios and of HD 49933 exhibit an increase at high frequencies. This behavior also exists in the ratios of other stars, which is considered to result from the low signal-to-noise ratio and the larger line width at the high-frequency end and could not be predicted by stellar models in previous work. Our calculations show that the behavior not only can be reproduced by stellar models, but can be predicted by asymptotic formulas of the ratios. Read More

Within framework of the $\mu$ from $\nu$ Supersymmetric Standard Model ($\mu\nu$SSM), three exotic right-handed neutrino superfields induce new sources for lepton-flavor violation. In this work, we investigate muon conversion to electron in nuclei within the $\mu\nu$SSM in detail. With a 125 GeV Higgs, the numerical results indicate that the $\mu-e$ conversion rates in nuclei within the $\mu\nu$SSM can reach the experimental upper bound, which could be detected with the future experimental sensitivities. Read More

In this paper, a new variational formulation based on discontinuous Galerkin technique for a reaction-diffusion problem is introduced, and the discontinuous Galerkin technique of this work is different from the general discontinuous Galerkin methods. The well posedness of the new formulation is given. Finally, it is pointed that the new variational formulation will be helpful to design better hybrid numerical methods which will not only strongly stable in spatial variable and absolutely stable in temporal variable but also be optimally convergent. Read More

Bolometers are ideal devices in the search for neutrinoless Double Beta Decay. Enlarging the mass of individual detectors would simplify the construction of a large experiment, but would also decrease the background per unit mass induced by alpha-emitters located close to the surfaces and background arising from external and internal gamma's. We present the very promising results obtained with a 2. Read More

$TeO_2$ crystals are used as bolometers in experiments searching for Double Beta Decay without emission of neutrinos. One of the most important issues in this extremely delicate kind of experiments is the characterization of the background. The knowledge of the response to $\alpha$ particles in the energy range where the signal is expected is therefore a must. Read More

Affiliations: 1Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 2Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 3Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA, 4Laboratori Nazionali del Gran Sasso, I-67010, Assergi, 5Dipartimento di Fisica dell'Universita' di Genova I - 16126 - Italy, 6Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 7Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 8Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 9Sezione INFN di Roma, P-le Aldo Moro 2, Roma I-00185 - Italy, 10Dipartimento di Fisica dell'Universita' di Genova I - 16126 - Italy, 11Università "La Sapienza", Dipartimento di Fisica, P-le Aldo Moro 2, Roma I-00185 - Italy, 12Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 13Shanghai Institute of Ceramics Chinese Academy of Sciences, Jiading district, Shanghai 201800, P. R. China, 14Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 15Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 16Dipartimento di Fisica e Matematica dell'Università dell'Insubria, Como I-22100 - Italy, 17Laboratori Nazionali del Gran Sasso, I-67010, Assergi, 18Laboratori Nazionali del Gran Sasso, I-67010, Assergi, 19Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA, 20Lawrence Livermore National Laboratory, Livermore, CA 94550 - USA, 21Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA, 22Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA, 23Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA, 24Laboratori Nazionali del Gran Sasso, I-67010, Assergi, 25Shanghai Institute of Applied Physics Chinese Academy of Sciences, Shanghai 201800, P. R. China, 26Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 27Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 28University of Wisconsin, Madison, WI 53706 - USA, 29Laboratori Nazionali del Gran Sasso, I-67010, Assergi, 30Dipartimento di Fisica e Matematica dell'Università dell'Insubria, Como I-22100 - Italy, 31Lawrence Livermore National Laboratory, Livermore, CA 94550 - USA, 32Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 33Università "La Sapienza", Dipartimento di Fisica, P-le Aldo Moro 2, Roma I-00185 - Italy, 34Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 35Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 36Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 37Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 38Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 39Dipartimento di Fisica e Matematica dell'Università dell'Insubria, Como I-22100 - Italy, 40Lawrence Livermore National Laboratory, Livermore, CA 94550 - USA, 41Dipartimento di Fisica dell'Università di Milano-Bicocca I-20126 - Italy, 42Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA, 43Shanghai Institute of Applied Physics Chinese Academy of Sciences, Shanghai 201800, P. R. China, 44Università "La Sapienza", Dipartimento di Fisica, P-le Aldo Moro 2, Roma I-00185 - Italy, 45Shanghai Institute of Applied Physics Chinese Academy of Sciences, Shanghai 201800, P. R. China, 46Shanghai Institute of Ceramics Chinese Academy of Sciences, Jiading district, Shanghai 201800, P. R. China

High purity TeO2 crystals are produced to be used for the search for the neutrinoless double beta decay of 130Te. Dedicated production lines for raw material synthesis, crystal growth and surface processing were built compliant with radio-purity constraints specific to rare event physics experiments. High sensitivity measurements of radio-isotope concentrations in raw materials, reactants, consumables, ancillaries and intermediary products used for TeO2 crystals production are reported. Read More

In this paper, we will prove the existence of infinitely many positive solutions to the following supercritical problem by using the Liapunov-Schmidt reduction method and asymptotic analysis: {ll}\Delta u + u^{p}+f(x)=0, u>0 {in} R^{n}, \lim_{|x|\to\infty}u(x)\to 0. Read More

Three energy mechanisms invoking large-scale magnetic fields are incorporated in a model to interpret jet production in black hole (BH) systems, i.e., the Blandford-Znajek (BZ), the magnetic coupling (MC) and Blandford-Payne (BP) processes. Read More

We report the observation of negative magnetoresistance in the ferromagnetic semiconductor GaMnAs at low temperatures ($T<3$ K) and low magnetic fields ($0< B <20$ mT). We attribute this effect to weak localization. Observation of weak localization provides a strong evidence of impurity band transport in these materials, since for valence band transport one expects either weak anti-localization due to strong spin-orbit interactions or total suppression of interference by intrinsic magnetization. Read More

We present a detailed investigation of exchange-dominated nonpropagating spin-wave modes in a series of 100 nm Ga$_{1 - x}$Mn$_{x}$As films with Mn concentrations $x$ ranging from 0.02 to 0.08. Read More

In noncommutative space, we examine the problem of a noninteracting and harmonically trapped Bose-Einstein condensate, and derive a simple analytic expression for the effect of spatial noncommutativity on energy spectrum of the condensate. It indicates that the ground-state energy incorporating the spatial noncommutativity is reduced to a lower level, which depends upon the noncommutativity parameter $\theta$. The appeared gap between the noncommutative space and commutative one for the ground-state level of the condensate should be a signal of spatial noncommutativity. Read More

Annealing can increase the Curie temperature and net magnetization in uncapped (Ga,Mn)As films, effects that are suppressed when the films are capped with GaAs. Previous polarized neutron reflectometry (PNR) studies of uncapped (Ga,Mn)As revealed a pronounced magnetization gradient that was reduced after annealing. We have extended this study to (Ga,Mn)As capped with GaAs. Read More

This paper shows that when the Riemannian metric on a contact manifold is blown up along the direction orthogonal to the contact distribution, the corresponding harmonic forms rescaled and normalized in the $L^2$-norms will converge to Rumin's harmonic forms. This proves a conjecture in Gromov `` Carnot-Caratheodory spaces seen from within '', IHES preprint, 1994. This result can also be reformulated in terms of spectral sequences, after Forman, Mazzeo-Melrose. Read More