12,961 research outputs found
Exploring Time-Sensitive Variational Bayesian Inference LDA for Social Media Data
There is considerable interest among both researchers and the mass public in understanding the topics of discussion on social media as they occur over time. Scholars have thoroughly analysed sampling-based topic modelling approaches for various text corpora including social media; however, another LDA topic modelling implementation—Variational Bayesian (VB)—has not been well studied, despite its known efficiency and its adaptability to the volume and dynamics of social media data. In this paper, we examine the performance of the VB-based topic modelling approach for producing coherent topics, and further, we extend the VB approach by proposing a novel time-sensitive Variational Bayesian implementation, denoted as TVB. Our newly proposed TVB approach incorporates time so as to increase the quality of the generated topics. Using a Twitter dataset covering 8 events, our empirical results show that the coherence of the topics in our TVB model is improved by the integration of time. In particular, through a user study, we find that our TVB approach generates less mixed topics than state-of-the-art topic modelling approaches. Moreover, our proposed TVB approach can more accurately estimate topical trends, making it particularly suitable to assist end-users in tracking emerging topics on social media
Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
We propose a novel denoising framework for task functional Magnetic Resonance
Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the
brain functional connectivity via dictionary learning and sparse coding (DLSC).
In order to address the limitations of the unsupervised DLSC-based fMRI
studies, we utilize the prior knowledge of task paradigm in the learning step
to train a data-driven dictionary and to model the sparse representation. We
apply the proposed DLSC-based method to Human Connectome Project (HCP) motor
tfMRI dataset. Studies on the functional connectivity of cerebrocerebellar
circuits in somatomotor networks show that the DLSC-based denoising framework
can significantly improve the prominent connectivity patterns, in comparison to
the temporal non-local means (tNLM)-based denoising method as well as the case
without denoising, which is consistent and neuroscientifically meaningful
within motor area. The promising results show that the proposed method can
provide an important foundation for the high-resolution functional connectivity
analysis, and provide a better approach for fMRI preprocessing.Comment: 8 pages, 3 figures, MLMI201
Evaluating Similarity Metrics for Latent Twitter Topics
Topic modelling approaches such as LDA, when applied on a tweet corpus, can often generate a topic model containing redundant topics. To evaluate the quality of a topic model in terms of redundancy, topic similarity metrics can be applied to estimate the similarity among topics in a topic model. There are various topic similarity metrics in the literature, e.g. the Jensen Shannon (JS) divergence-based metric. In this paper, we evaluate the performances of four distance/divergence-based topic similarity metrics and examine how they align with human judgements, including a newly proposed similarity metric that is based on computing word semantic similarity using word embeddings (WE). To obtain human judgements, we conduct a user study through crowdsourcing. Among various insights, our study shows that in general the cosine similarity (CS) and WE-based metrics perform better and appear to be complementary. However, we also find that the human assessors cannot easily distinguish between the distance/divergence-based and the semantic similarity-based metrics when identifying similar latent Twitter topics
Relaxed 2-D Principal Component Analysis by Norm for Face Recognition
A relaxed two dimensional principal component analysis (R2DPCA) approach is
proposed for face recognition. Different to the 2DPCA, 2DPCA- and G2DPCA,
the R2DPCA utilizes the label information (if known) of training samples to
calculate a relaxation vector and presents a weight to each subset of training
data. A new relaxed scatter matrix is defined and the computed projection axes
are able to increase the accuracy of face recognition. The optimal -norms
are selected in a reasonable range. Numerical experiments on practical face
databased indicate that the R2DPCA has high generalization ability and can
achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure
Scattering of Giant Holes
We study scalar excitations of high spin operators in N=4 super Yang-Mills
theory, which are dual to solitons propagating on a long folded string in AdS_3
x S^1. In the spin chain description of the gauge theory, these are associated
to holes in the magnon distribution in the sl(2,R) sector. We compute the
all-loop hole S-matrix from the asymptotic Bethe ansatz, and expand in leading
orders at weak and strong coupling. The worldsheet S-matrix of solitonic
excitations on the GKP string is calculated using semiclassical quantization.
We find an exact agreement between the gauge theory and string theory results.Comment: 13 pages. v2: minor corrections, references adde
Memory-built-in quantum teleportation with photonic and atomic qubits
The combination of quantum teleportation and quantum memory of photonic
qubits is essential for future implementations of large-scale quantum
communication and measurement-based quantum computation. Both steps have been
achieved separately in many proof-of-principle experiments, but the
demonstration of memory-built-in teleportation of photonic qubits remains an
experimental challenge. Here, we demonstrate teleportation between photonic
(flying) and atomic (stationary) qubits. In our experiment, an unknown
polarization state of a single photon is teleported over 7 m onto a remote
atomic qubit that also serves as a quantum memory. The teleported state can be
stored and successfully read out for up to 8 micro-second. Besides being of
fundamental interest, teleportation between photonic and atomic qubits with the
direct inclusion of a readable quantum memory represents a step towards an
efficient and scalable quantum network.Comment: 19 pages 3 figures 1 tabl
Bone Marrow Stem Cell Treatment for Ischemic Heart Disease in Patients with No Option of Revascularization: A Systematic Review and Meta-Analysis
PMCID: PMC3686792This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Accurate masses and radii of normal stars: modern results and applications
This paper presents and discusses a critical compilation of accurate,
fundamental determinations of stellar masses and radii. We have identified 95
detached binary systems containing 190 stars (94 eclipsing systems, and alpha
Centauri) that satisfy our criterion that the mass and radius of both stars be
known to 3% or better. To these we add interstellar reddening, effective
temperature, metal abundance, rotational velocity and apsidal motion
determinations when available, and we compute a number of other physical
parameters, notably luminosity and distance. We discuss the use of this
information for testing models of stellar evolution. The amount and quality of
the data also allow us to analyse the tidal evolution of the systems in
considerable depth, testing prescriptions of rotational synchronisation and
orbital circularisation in greater detail than possible before. The new data
also enable us to derive empirical calibrations of M and R for single (post-)
main-sequence stars above 0.6 M(Sun). Simple, polynomial functions of T(eff),
log g and [Fe/H] yield M and R with errors of 6% and 3%, respectively.
Excellent agreement is found with independent determinations for host stars of
transiting extrasolar planets, and good agreement with determinations of M and
R from stellar models as constrained by trigonometric parallaxes and
spectroscopic values of T(eff) and [Fe/H]. Finally, we list a set of 23
interferometric binaries with masses known to better than 3%, but without
fundamental radius determinations (except alpha Aur). We discuss the prospects
for improving these and other stellar parameters in the near future.Comment: 56 pages including figures and tables. To appear in The Astronomy and
Astrophysics Review. Ascii versions of the tables will appear in the online
version of the articl
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