arXiv subjects

Hui Zhu

Publications and source records attributed to Hui Zhu.

At least 55 records · Page 3Linked to original sources

arXiv2022

LAMOST MRS-N Observations of the W80 Region

The spectral observations and analysis for the W80 Region are presented by using the data of Medium-Resolution Spectroscopic Survey of Nebulae (MRS-N) with the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST). A total of 2982 high-quality nebular spectra have been obtained in the 20 square degree field of view (FoV) which covers the W80 complex, and the largest sample of spectral data have been established for the first time. The relative intensities, radial velocities (RVs), and Full Widths at Half Maximum (FWHMs) are measured with the high spectral resolution of LAMOST MRS, for H$α$ $λ$ 6563 Å, [\ion{N}{ii}] $λ$$λ$ 6548 Å, 6584 Å\ , and [\ion{S}{ii}] $λ$$λ$ 6716 Å, 6731 Å\ emission lines. In the field of view of whole W80 Region, the strongest line emissions are found to be consistent with the bright nebulae, NGC 7000, IC 5070, and LBN 391, and weak line emissions also truly exist in the Middle Region, where no bright nebulae are detected by the wide-band optical observations. The large-scale spectral observations to the W80 Region reveal the systematic spatial variations of RVs and FWHMs, and several unique structural features. A 'curved feature' to the east of the NGC 7000, and a 'jet feature' to the west of the LBN 391 are detected to be showing with larger radial velocities. A 'wider FWHM region' is identified in the eastern part of the NGC 7000. The variations of [\ion{S}{ii}] / H$α$ ratios display a gradient from southwest to northeast in the NGC 7000 region, and manifest a ring shape around the 'W80 bubble' ionized by an O-type star in the L935. Further spectral and multi-band observations are guaranteed to investigate in detail the structural features.

astro-ph.SR↗

arXiv2022

Unusually high HCO+/CO ratios in and outside supernova remnant W49B

Galactic supernova remnants (SNRs) and their environments provide the nearest laboratories to study SN feedback. We performed molecular observations toward SNR W49B, the most luminous Galactic SNR in the X-ray band, aiming to explore signs of multiple feedback channels of SNRs on nearby molecular clouds (MCs). We found very broad HCO+ lines with widths of dv = 48--75 km/s in the SNR southwest, providing strong evidence that W49B is perturbing MCs at a systemic velocity of $V_{LSR}=61$--65 km/s, and placing W49B at a distance of $7.9\pm 0.6$ kpc. We observed unusually high-intensity ratios of HCO+ J=1-0/CO J=1-0 not only at shocked regions ($1.1\pm 0.4$ and $0.70\pm 0.16$), but also in quiescent clouds over 1 pc away from the SNR's eastern boundary (> 0.2). By comparing with the magnetohydrodynamics shock models, we interpret that the high ratio in the broad-line regions can result from a cosmic-ray (CR) induced chemistry in shocked MCs, where the CR ionization rate is enhanced to around 10--100 times of the Galactic level. The high HCO+/CO ratio outside the SNR is probably caused by the radiation precursor, while the luminous X-ray emission of W49B can explain a few properties in this region. The above results provide observational evidence that SNRs can strongly influence the molecular chemistry in and outside the shock boundary via their shocks, CRs, and radiation. We propose that the HCO+/CO ratio is a potentially useful tool to probe an SNR's multichannel influence on MCs.

astro-ph.GA↗

arXiv2022

The Data Processing of the LAMOST Medium-Resolution Spectral Survey of Galactic Nebulae (LAMOST MRS-N Pipeline)

The Large sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) medium-resolution spectral survey of Galactic Nebulae (MRS-N) has conducted for three years since Sep. 2018 and observed more than 190 thousands nebular spectra and 20 thousands stellar spectra. However, there is not yet a data processing pipeline for nebular data. To significantly improve the accuracy of nebulae classification and their physical parameters, we developed the MRS-N Pipeline. This article presented in detail each data processing step of the MRS-N Pipeline, such as removing cosmic rays, merging single exposure, fitting sky light emission lines, subtracting skylight, wavelength recalibration, measuring nebular parameters, creating catalogs and packing spectra. Finally, a description of the data products, including nebular spectra files and parameter catalogs, is provided.

astro-ph.SR↗

arXiv2022

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Since the science white paper of the Large High Altitude Air Shower Observatory (LHAASO) published on arXiv in 2019 [e-Print: 1905.02773 (astro-ph.HE)], LHAASO has completed the transition from a project to an operational gamma-ray astronomical observatory LHAASO is a new generation multi-component facility located in Daocheng, Sichuan province of China, at an altitude of 4410 meters. It aims at measuring with unprecedented sensitivity the spectrum, composition, and anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$~eV, and acting simultaneously as a wide aperture (one stereoradiant) continuously operating gamma-ray telescope in the energy range between 10$^{11}$ and $10^{15}$~eV with the designed sensitivity of 1.3\% of the Crab Unit (CU) above 100 TeV. LHAASO's capability of measuring simultaneously different shower components (electrons, muons, and Cherenkov/fluorescence light), will allow it to investigate the origin, acceleration, and propagation of CR through measurement of the energy spectrum, elemental composition, and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO will play a key role in CR physics and gamma-ray astronomy for a general and comprehensive exploration of the high energy universe and will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. The LHAASO Collaboration organized an editorial working group and finished all editorial work of this science book, to summarize the instrumental features and outline the prospects of scientific researches with the LHAASO experiment.

astro-ph.HE↗

arXiv2021

Fermi-LAT detection of extended gamma-ray emission in the vicinity of SNR G045.7$-$00.4: evidence for escaping cosmic rays interacting with the surrounding molecular clouds

We present the analysis of Fermi Large Area Telecope (LAT) data of the gamma-ray emission in the vicinity of a radio supernova remnant (SNR), G045.7$-$00.4. To study the origin of the gamma-ray emission, we also make use of the CO survey data of Milky Way Imaging Scroll Painting to study the massive molecular gas complex that surrounds the SNR. The whole size of the GeV emission is significantly larger than that of the radio morphology. Above 3 GeV, the GeV emission is resolved into two sources: one is spatially consistent with the position of the SNR with a size comparable to that of the radio emission, and the other is located outside of the western boundary of the SNR and spatially coincident with the densest region of the surrounding molecular cloud. We suggest that the GeV emission of the western source may arise from cosmic rays (CRs) which have escaped the SNR and illuminated the surrounding molecular cloud. We find that the gamma-ray spectra of the western source can be consistently explained by this scenario with a total energy of $\sim 10^{50}{\rm erg}$ in escaping CRs assuming the escape is isotropic.

astro-ph.HE↗

arXiv2021

LAMOST Medium-Resolution Spectral Survey of Galactic Nebulae (LAMOST-MRS-N): Subtraction of Geocoronal Halpha Emission

We introduce a method of subtracting geocoronal Halpha emissions from the spectra of LAMOST medium-resolution spectral survey of Galactic nebulae (LAMOST-MRS-N). The flux ratios of the Halpha sky line to the adjacent OH lambda6554 single line do not show a pattern or gradient distribution in a plate. More interestingly, the ratio is well correlated to solar altitude, which is the angle of the sun relative to the Earth's horizon. It is found that the ratio decreases from 0.8 to 0.2 with the decreasing solar altitude from -17 to -73 degree. Based on this relation, which is described by a linear function, we can construct the Halpha sky component and subtract it from the science spectrum. This method has been applied to the LAMOST-MRS-N data, and the contamination level of the Halpha sky to nebula is reduced from 40% to less than 10%. The new generated spectra will significantly improve the accuracy of the classifications and the measurements of physical parameters of Galactic nebulae.

astro-ph.IM↗

arXiv2020

Laser Data Based Automatic Generation of Lane-Level Road Map for Intelligent Vehicles

With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm

cs.CV↗

arXiv2020

TargetDrop: A Targeted Regularization Method for Convolutional Neural Networks

Dropout regularization has been widely used in deep learning but performs less effective for convolutional neural networks since the spatially correlated features allow dropped information to still flow through the networks. Some structured forms of dropout have been proposed to address this but prone to result in over or under regularization as features are dropped randomly. In this paper, we propose a targeted regularization method named TargetDrop which incorporates the attention mechanism to drop the discriminative feature units. Specifically, it masks out the target regions of the feature maps corresponding to the target channels. Experimental results compared with the other methods or applied for different networks demonstrate the regularization effect of our method.

cs.CV↗

arXiv2020

Lic-Sec: an enhanced AppArmor Docker security profile generator

Along with the rapid development of cloud computing technology, containerization technology has drawn much attention from both industry and academia. In this paper, we perform a comparative measurement analysis of Docker-sec, which is a Linux Security Module proposed in 2018, and a new AppArmor profile generator called Lic-Sec, which combines Docker-sec with a modified version of LiCShield, which is also a Linux Security Module proposed in 2015. Docker-sec and LiCShield can be used to enhance Docker container security based on mandatory access control and allows protection of the container without manually configurations. Lic-Sec brings together their strengths and provides stronger protection. We evaluate the effectiveness and performance of Docker-sec and Lic-Sec by testing them with real-world attacks. We generate an exploit database with 42 exploits effective on Docker containers selected from the latest 400 exploits on Exploit-db. We launch these exploits on containers spawned with Docker-sec and Lic-Sec separately. Our evaluations show that for demanding images, Lic-Sec gives protection for all privilege escalation attacks for which Docker-sec failed to give protection.

cs.CR↗

arXiv2020

On the radial velocity calibrations in the LAMOST Medium-Resolution Spectroscopic Survey of Nebulae

Accurate radial velocity determinations of optical emission lines (i.e. [NII]$λλ$6548,6584, H$α$, and [SII]$λλ$6717,6731) are very important for investigating the kinematics and dynamics properties of nebulae. The second stage survey program of Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) has started a sub-survey of nebulae (MRS-N) which will spectroscopically observe the optical emission lines of a large sample of nebulae near the Galactic plane. Until now, 15 MRS-N plates have been observed from 2017 September to 2019 June. Based on fitting the sky emission lines in the red band spectra of MRS-N, we investigate the precision of wavelength calibration and find there are systematic deviations of radial velocities (RVs) from $\sim$0.2 to 4 km/s for different plates. Especially for the plates obtained in 2018 March, the systematic deviations of RVs can be as large as $\sim$4 km/s, which then go down to $\sim$0.2-0.5 km/s at the end of 2018 and January 2019. A RVs calibration function is proposed for these MRS-N plates, which can simultaneously and successfully calibration the systematic deviations and improve the precision of RVs.

astro-ph.SR↗

arXiv2020

LAMOST Medium-Resolution Spectral Survey of Galactic Nebula (LAMOST MRS-N): An overview of Scientific goals and Survey plan

Since Sep. 2018, LAMOST started the medium-resolution (R $\sim 7500$) spectral survey (MRS). We proposed the spectral survey of Galactic nebulae, including \hii\ regions, HH objects, supernova remnants, planetary nebulae and the special stars with MRS (LAMOST MRS-N). LAMOST MRS-N covers about 1700 square degrees of the northern Galactic plane within $40^\circ < l < 215^\circ$ and $-5^\circ < b < 5^\circ$. In this 5-year survey, we plan to observe about 500 thousand nebulae spectra. According to the commissioning observations, the nebulae spectra can provide precise radial velocity with uncertainty less than 1 km s$^{-1}$. These high-precision spectral data are of great significance to our understanding of star formation and evolution.

astro-ph.GA↗

arXiv2020

Hadronic vs leptonic models for $γ$-ray emission from VER J2227+608

Recent observations of VER J2227+608 reveal a broken power $γ$-ray spectrum with the spectral index increasing from $\sim 1.8$ in the GeV energy range to $\sim 2.3$ in the TeV range. Such a spectral break can be attributed to radiative energy loss of energetic electrons in the leptonic scenario for the $γ$-ray emission, which, in combination with characteristic age of the nearby pulsar, can be used to constrain magnetic field in the emission region. We show that the radio and X-ray observations can also be explained in such a scenario. In the hadronic scenario, the spectral break can be attributed to diffusion of energetic ions in a turbulent medium and detailed spectral measurement can be used to constrain the diffusion coefficient. These two models, however, predict drastically different spectra above 100 TeV, which will be uncovered with future high-resolution observations, such as LHAASO and/or CTA.

astro-ph.HE↗

arXiv2020

Mitigating Query-Flooding Parameter Duplication Attack on Regression Models with High-Dimensional Gaussian Mechanism

Public intelligent services enabled by machine learning algorithms are vulnerable to model extraction attacks that can steal confidential information of the learning models through public queries. Differential privacy (DP) has been considered a promising technique to mitigate this attack. However, we find that the vulnerability persists when regression models are being protected by current DP solutions. We show that the adversary can launch a query-flooding parameter duplication (QPD) attack to infer the model information by repeated queries. To defend against the QPD attack on logistic and linear regression models, we propose a novel High-Dimensional Gaussian (HDG) mechanism to prevent unauthorized information disclosure without interrupting the intended services. In contrast to prior work, the proposed HDG mechanism will dynamically generate the privacy budget and random noise for different queries and their results to enhance the obfuscation. Besides, for the first time, HDG enables an optimal privacy budget allocation that automatically determines the minimum amount of noise to be added per user-desired privacy level on each dimension. We comprehensively evaluate the performance of HDG using real-world datasets and shows that HDG effectively mitigates the QPD attack while satisfying the privacy requirements. We also prepare to open-source the relevant codes to the community for further research.

cs.CR↗

arXiv2020

Localizing Interpretable Multi-scale informative Patches Derived from Media Classification Task

Deep convolutional neural networks (CNN) always depend on wider receptive field (RF) and more complex non-linearity to achieve state-of-the-art performance, while suffering the increased difficult to interpret how relevant patches contribute the final prediction. In this paper, we construct an interpretable AnchorNet equipped with our carefully designed RFs and linearly spatial aggregation to provide patch-wise interpretability of the input media meanwhile localizing multi-scale informative patches only supervised on media-level labels without any extra bounding box annotations. Visualization of localized informative image and text patches show the superior multi-scale localization capability of AnchorNet. We further use localized patches for downstream classification tasks across widely applied networks. Experimental results demonstrate that replacing the original inputs with their patches for classification can get a clear inference acceleration with only tiny performance degradation, which proves that localized patches can indeed retain the most semantics and evidences of the original inputs.

cs.CV↗

arXiv2020

DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners

Convolutional neural networks (ConvNets) are widely used in real life. People usually use ConvNets which pre-trained on a fixed number of classes. However, for different application scenarios, we usually do not need all of the classes, which means ConvNets are redundant when dealing with these tasks. This paper focuses on the redundancy of ConvNet channels. We proposed a novel idea: using an interpretable manner to find the most important channels for every single class (dissect), and dynamically run channels according to classes in need (reconstruct). For VGG16 pre-trained on CIFAR-10, we only run 11\% parameters for two-classes sub-tasks on average with negligible accuracy loss. For VGG16 pre-trained on ImageNet, our method averagely gains 14.29\% accuracy promotion for two-classes sub-tasks. In addition, analysis show that our method captures some semantic meanings of channels, and uses the context information more targeted for sub-tasks of ConvNets.

cs.CV↗

arXiv2020

Enhancement of hydroxyapatite dissolution through structure modification by Krypton ion irradiation

Hydroxyapatite synthesized by a wet chemical route was subjected to heavy Krypton ion irradiation of 4MeV at various fluences. Glancing incidence Xray diffraction results confirmed the phase purity of irradiated HA with a moderate contraction in lattice parameters, and further indicated the irradiation induced structural disorder, evidenced by broadening of the diffraction peaks. High resolution transmission electron microscopy observations indicated that the applied Kr irradiation induced significant damage in the hydroxyapatite lattice. Specifically, cavities were observed with their diameter and density varying with the irradiation fluences, while a radiation induced crystalline to amorphous transition with increasing ion dose was identified. Raman and Xray photoelectron spectroscopy analysis further indicated the presence of irradiation induced defects. Ion release from pristine and irradiated materials following immersion in Trisbuffer showed that dissolution in vitro was enhanced by irradiation. We examined the effects of irradiation on the early stages of the mouse osteoblast like cells response. A cell counting kit 8 assay was carried out to investigate the cytotoxicity of samples, and viable cells can be observed on the irradiated materials.

physics.app-ph↗

arXiv2020

Towards More Efficient and Effective Inference: The Joint Decision of Multi-Participants

Existing approaches to improve the performances of convolutional neural networks by optimizing the local architectures or deepening the networks tend to increase the size of models significantly. In order to deploy and apply the neural networks to edge devices which are in great demand, reducing the scale of networks are quite crucial. However, It is easy to degrade the performance of image processing by compressing the networks. In this paper, we propose a method which is suitable for edge devices while improving the efficiency and effectiveness of inference. The joint decision of multi-participants, mainly contain multi-layers and multi-networks, can achieve higher classification accuracy (0.26% on CIFAR-10 and 4.49% on CIFAR-100 at most) with similar total number of parameters for classical convolutional neural networks.

cs.CV↗

arXiv2019

Control of three dimensional water waves

We study the exact controllability for spatially periodic water waves with surface tension, by localized exterior pressures applied to free surfaces. We prove that in any dimension, the exact controllability holds within arbitrarily short time, for sufficiently small and regular data, provided that the region of control satisfies the geometric control condition. This result was previously obtained by Alazard, Baldi, and Han-Kwan for 2-D water waves. Our proof combines an iterative scheme, that reduces the controllability of the original quasi-linear equation to that of a sequence of linear equations, with a semiclassical approach for the linear control problems.

math.AP↗