281 research outputs found
Steady-State Analysis of Load Balancing with Coxian- Distributed Service Times
This paper studies load balancing for many-server ( servers) systems. Each
server has a buffer of size and can have at most one job in service and
jobs in the buffer. The service time of a job follows the Coxian-2
distribution. We focus on steady-state performance of load balancing policies
in the heavy traffic regime such that the normalized load of system is for We identify a set of policies that
achieve asymptotic zero waiting. The set of policies include several classical
policies such as join-the-shortest-queue (JSQ), join-the-idle-queue (JIQ),
idle-one-first (I1F) and power-of--choices (Po) with . The proof of the main result is based on Stein's method and state space
collapse. A key technical contribution of this paper is the iterative state
space collapse approach that leads to a simple generator approximation when
applying Stein's method
The localization of single pulse in VLBI observation
In our previous work, we propose a cross spectrum based method to extract
single pulse signals from RFI contaminated data, which is originated from
geodetic VLBI postprocessing. This method fully utilizes fringe phase
information of the cross spectrum and hence maximizes signal power, however the
localization was not discussed in that work yet. As the continuation of that
work, in this paper, we further study how to localize single pulses using
astrometric solving method. Assuming that the burst is a point source, we
derive the burst position by solving a set of linear equations given the
relation between residual delay and offset to a priori position. We find that
the single pulse localization results given by both astrometric solving and
radio imaging are consistent within 3 sigma level. Therefore we claim that it
is possible to derive the position of a single pulse with reasonable precision
based on only 3 or even 2 baselines with 4 milliseconds integration. The
combination of cross spectrum based detection and the localization proposed in
this work then provide a thorough solution for searching single pulse in VLBI
observation. According to our calculation, our pipeline gives comparable
accuracy as radio imaging pipeline. Moreover, the computational cost of our
pipeline is much smaller, which makes it more practical for FRB search in
regular VLBI observation. The pipeline is now publicly available and we name it
as "VOLKS", which is the acronym of "VLBI Observation for frb Localization Keen
Searcher".Comment: 11 pages, 4 figures, 3 tables, accepted for publication in A
Spin alignments of spiral galaxies within the large-scale structure from SDSS DR7
Using a sample of spiral galaxies selected from the Sloan Digital Sky Survey
Data Release 7 (SDSS DR7) and Galaxy Zoo 2 (GZ2), we investigate the alignment
of spin axes of spiral galaxies with their surrounding large scale structure,
which is characterized by the large-scale tidal field reconstructed from the
data using galaxy groups above a certain mass threshold. We find that the spin
axes of only have weak tendency to be aligned with (or perpendicular to) the
intermediate (or minor) axis of the local tidal tensor. The signal is the
strongest in a \cluster environment where all the three eigenvalues of the
local tidal tensor are positive. Compared to the alignments between halo spins
and local tidal field obtained in N-body simulations, the above observational
results are in best agreement with those for the spins of inner regions of
halos, suggesting that the disk material traces the angular momentum of dark
matter halos in the inner regions.Comment: 8 pages, 7 figures, accepted for publication in Ap
DNA methylation and regulatory elements during chicken germline stem cell differentiation
Funding for Open Access provided by the UMD Libraries' Open Access Publishing Fund.The production of germ cells in vitro would open important new avenues for stem biology and human medicine, but the mechanisms of germ cell differentiation are not well understood. The chicken, as a great model for embryology and development, was used in this study to help us explore its regulatory mechanisms. In this study, we reported a comprehensive genome-wide DNA methylation landscape in chicken germ cells, and transcriptomic dynamics was also presented. By uncovering DNA methylation patterns on individual genes, some genes accurately modulated by DNA methylation were found to be associated with cancers and virus infection, e.g., AKT1 and CTNNB1. Chicken-unique markers were also discovered for identifying male germ cells. Importantly, integrated epigenetic mechanisms were explored during male germ cell differentiation, which provides deep insight into the epigenetic processes associated with male germ cell differentiation and possibly improves treatment options to male infertility in animals and humans
Robust Face Recognition With Kernelized Locality-Sensitive Group Sparsity Representation
In this paper, a novel joint sparse representation method is proposed for robust face recognition. We embed both group sparsity and kernelized locality-sensitive constraints into the framework of sparse representation. The group sparsity constraint is designed to utilize the grouped structure information in the training data. The local similarity between test and training data is measured in the kernel space instead of the Euclidian space. As a result, the embedded nonlinear information can be effectively captured, leading to a more discriminative representation. We show that, by integrating the kernelized local-sensitivity constraint and the group sparsity constraint, the embedded structure information can be better explored, and significant performance improvement can be achieved. On the one hand, experiments on the ORL, AR, extended Yale B, and LFW data sets verify the superiority of our method. On the other hand, experiments on two unconstrained data sets, the LFW and the IJB-A, show that the utilization of sparsity can improve recognition performance, especially on the data sets with large pose variation
Revealing the cosmic web dependent halo bias
Halo bias is the one of the key ingredients of the halo models. It was shown
at a given redshift to be only dependent, to the first order, on the halo mass.
In this study, four types of cosmic web environments: clusters, filaments,
sheets and voids are defined within a state of the art high resolution -body
simulation. Within those environments, we use both halo-dark matter
cross-correlation and halo-halo auto correlation functions to probe the
clustering properties of halos. The nature of the halo bias differs strongly
among the four different cosmic web environments we describe. With respect to
the overall population, halos in clusters have significantly lower biases in
the {} mass range. In other
environments however, halos show extremely enhanced biases up to a factor 10 in
voids for halos of mass {}. Such a strong
cosmic web environment dependence in the halo bias may play an important role
in future cosmological and galaxy formation studies. Within this cosmic web
framework, the age dependency of halo bias is found to be only significant in
clusters and filaments for relatively small halos \la 10^{12.5}\msunh.Comment: 14 pages, 14 figures, ApJ accepte
Microlensing effect of charged spherically symmetric wormhole
We systematically investigate the microlensing effect of charged spherically
symmetric wormhole, where the light source is remote from the throat.
Remarkably, there will be at most three images by considering the charge part.
We study all situations including three images, two images, and one image,
respectively. The numerical result shows that the range of total magnification
is from to depending on various metrics. In the case of three
images, there will be two maximal values of magnification (a peak, and a gentle
peak) when the contribution via mass is much less than that of charge. However,
we cannot distinguish the case that forms three images or only one image as the
total magnification is of order . Finally, our theoretical investigation
could shed new light on exploring the wormhole with the microlensing effect.Comment: 10 pages, 9 figure
A Survey on Deep Multi-modal Learning for Body Language Recognition and Generation
Body language (BL) refers to the non-verbal communication expressed through
physical movements, gestures, facial expressions, and postures. It is a form of
communication that conveys information, emotions, attitudes, and intentions
without the use of spoken or written words. It plays a crucial role in
interpersonal interactions and can complement or even override verbal
communication. Deep multi-modal learning techniques have shown promise in
understanding and analyzing these diverse aspects of BL. The survey emphasizes
their applications to BL generation and recognition. Several common BLs are
considered i.e., Sign Language (SL), Cued Speech (CS), Co-speech (CoS), and
Talking Head (TH), and we have conducted an analysis and established the
connections among these four BL for the first time. Their generation and
recognition often involve multi-modal approaches. Benchmark datasets for BL
research are well collected and organized, along with the evaluation of SOTA
methods on these datasets. The survey highlights challenges such as limited
labeled data, multi-modal learning, and the need for domain adaptation to
generalize models to unseen speakers or languages. Future research directions
are presented, including exploring self-supervised learning techniques,
integrating contextual information from other modalities, and exploiting
large-scale pre-trained multi-modal models. In summary, this survey paper
provides a comprehensive understanding of deep multi-modal learning for various
BL generations and recognitions for the first time. By analyzing advancements,
challenges, and future directions, it serves as a valuable resource for
researchers and practitioners in advancing this field. n addition, we maintain
a continuously updated paper list for deep multi-modal learning for BL
recognition and generation: https://github.com/wentaoL86/awesome-body-language
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