arXiv subjects

Shuo Zhang

Publications and source records attributed to Shuo Zhang.

At least 289 records · Page 16Linked to original sources

arXiv2020

On the Secrecy of UAV Systems With Linear Trajectory

By observing the fact that moving in a straight line is a common flying behavior of unmanned aerial vehicles (UAVs) in normal applications, e.g., power line inspections, and air patrols along with highway/streets/borders, in this paper we investigate the secrecy outage performance of a UAV system with linear trajectory, where a UAV ($S$) flies in a straight line and transmits its information over the downlink to a legitimate receiver ($D$) on the ground while an eavesdropping UAV ($E$) trying to overhear the information delivery between $S$ and $D$. Meanwhile, some information is delivered to $S$ over the uplink from $D$, such as commanding messages to control $S$'s detecting operations, which can also be eavesdropped by $E$. The locations of $S$, $D$, and $E$ are randomly distributed. We first characterize the statistical characteristics (including cumulative distribution functions and probability density function) of the received signal-to-noise ratio over both downlink and uplink, and then the closed-form analytical expressions for the lower boundary of the secrecy outage probability of both downlink and uplink have also been derived accordingly. Finally, Monte-Carlo simulations are given to testify our proposed analytical models.

eess.SP↗

arXiv2020

Evaluating Conversational Recommender Systems via User Simulation

Conversational information access is an emerging research area. Currently, human evaluation is used for end-to-end system evaluation, which is both very time and resource intensive at scale, and thus becomes a bottleneck of progress. As an alternative, we propose automated evaluation by means of simulating users. Our user simulator aims to generate responses that a real human would give by considering both individual preferences and the general flow of interaction with the system. We evaluate our simulation approach on an item recommendation task by comparing three existing conversational recommender systems. We show that preference modeling and task-specific interaction models both contribute to more realistic simulations, and can help achieve high correlation between automatic evaluation measures and manual human assessments.

cs.IR↗

arXiv2020

3D Lidar Mapping Relative Accuracy Automatic Evaluation Algorithm

HD (High Definition) map based on 3D lidar plays a vital role in autonomous vehicle localization, planning, decision-making, perception, etc. Many 3D lidar mapping technologies related to SLAM (Simultaneous Localization and Mapping) are used in HD map construction to ensure its high accuracy. To evaluate the accuracy of 3D lidar mapping, the most common methods use ground truth of poses to calculate the error between estimated poses and ground truth, however it's usually so difficult to get the ground truth of poses in the actual lidar mapping for autonomous vehicle. In this paper, we proposed a relative accuracy evaluation algorithm that can automatically evaluate the accuracy of HD map built by 3D lidar mapping without ground truth. A method for detecting the degree of ghosting in point cloud map quantitatively is designed to reflect the accuracy indirectly, which takes advantage of the principle of light traveling in a straight line and the fact that light can not penetrate opaque objects. Our experimental results confirm that the proposed evaluation algorithm can automatically and efficiently detect the bad poses whose accuracy are less than the set threshold such as 0.1m, then calculate the bad poses percentage P_bad in all estimated poses to obtain the final accuracy metric P_acc = 1 - P_bad.

cs.CV↗

arXiv2020

Accelerating Neural Network Inference by Overflow Aware Quantization

The inherent heavy computation of deep neural networks prevents their widespread applications. A widely used method for accelerating model inference is quantization, by replacing the input operands of a network using fixed-point values. Then the majority of computation costs focus on the integer matrix multiplication accumulation. In fact, high-bit accumulator leads to partially wasted computation and low-bit one typically suffers from numerical overflow. To address this problem, we propose an overflow aware quantization method by designing trainable adaptive fixed-point representation, to optimize the number of bits for each input tensor while prohibiting numeric overflow during the computation. With the proposed method, we are able to fully utilize the computing power to minimize the quantization loss and obtain optimized inference performance. To verify the effectiveness of our method, we conduct image classification, object detection, and semantic segmentation tasks on ImageNet, Pascal VOC, and COCO datasets, respectively. Experimental results demonstrate that the proposed method can achieve comparable performance with state-of-the-art quantization methods while accelerating the inference process by about 2 times.

cs.CV↗

arXiv2020

Direct imaging of liquid-nanoparticle interface with atom probe tomography

Understanding the structure and chemical composition at the liquid-nanoparticle (NP) interface is crucial for a wide range of physical, chemical and biological processes. In this study, direct imaging of the liquid-NP interface by atom probe tomography (APT) is reported for the first time, which reveals the distributions and the interactions of key atoms and molecules in this critical domain. The APT specimen is prepared by controlled graphene encapsulation of the solution containing nanoparticles on a metal tip, with an end radius in the range of 50 nm to allow field ionization and evaporation. Using Au nanoparticles (AuNPs) in suspension as an example, analysis of the mass spectrum and three-dimensional (3D) chemical maps from APT provides a detailed image of the water-gold interface with near-atomic resolution. At the water-gold interface, the formation of an electrical double layer (EDL) rich in water (H2O) molecules has been observed, which results from the charge from the binding between the trisodium-citrate layer and the AuNP. In the bulk water region, the density of reconstructed H2O has been shown to be consistent, reflecting a highly packed density of H2O molecules after graphene encapsulation. This study is the first demonstration of direct imaging of liquid-NP interface using APT with results providing an atom-by-atom 3D dissection of the liquid-NP interface.

cond-mat.mtrl-sci↗

arXiv2020

Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation

Graph Neural Networks (GNNs) are powerful to learn the representation of graph-structured data. Most of the GNNs use the message-passing scheme, where the embedding of a node is iteratively updated by aggregating the information of its neighbors. To achieve a better expressive capability of node influences, attention mechanism has grown to be popular to assign trainable weights to the nodes in aggregation. Though the attention-based GNNs have achieved remarkable results in various tasks, a clear understanding of their discriminative capacities is missing. In this work, we present a theoretical analysis of the representational properties of the GNN that adopts the attention mechanism as an aggregator. Our analysis determines all cases when those attention-based GNNs can always fail to distinguish certain distinct structures. Those cases appear due to the ignorance of cardinality information in attention-based aggregation. To improve the performance of attention-based GNNs, we propose cardinality preserved attention (CPA) models that can be applied to any kind of attention mechanisms. Our experiments on node and graph classification confirm our theoretical analysis and show the competitive performance of our CPA models.

cs.LG↗

arXiv2020

NuSTAR and Chandra Observation of the Galactic Center Non-thermal X-ray Filament G0.13-0.11: A Pulsar Wind Nebula Driven Magnetic Filament

One of the most unique phenomena in the Galactic center region is the existence of numerous long and narrow filamentary structures within a few hundred parsecs of Sgr A$^{\star}$. While more than one than one hundred radio filaments have been revealed by MeerKAT, about two dozens X-ray filaments have been discovered so far. In this article, we report our analysis on the deep Chandra and NuSTAR observations of a non-thermal X-ray filament, G0.13-0.11, which is located adjacent to the Radio arc. Chandra revealed a unique morphology of G0.13-0.11, which is an elongated (0.1 pc in width and 3.2 pc in length) structure slightly bended towards the Radio arc. A pulsar candidate ($Γ\sim 1.4$) is detected in the middle of the filament, with a tail of diffuse non-thermal X-ray emission on one side of the filament. The filament is detected by NuSTAR up to 79 keV, with the hard X-ray centroid consistent with the pulsar candidate. We found that the X-ray intensity decays along the filament farther away from the pulsar candidate, dropping to half of its peak value at 2.2 pc away. This system is mostly likely a Pulsar Wind Nebula interacting with ambient interstellar magnetic field, where the filaments are kinetic jets from PWN as recently proposed. The nature of this filament adds to complex origin of the X-ray filaments, which serve as powerful tools to probe local and global powerful particle accelerators in the Galactic center.

astro-ph.HE↗

arXiv2020

An optimal piecewise cubic nonconforming finite element scheme for the planar biharmonic equation on general triangulations

This paper presents a nonconforming finite element scheme for the planar biharmonic equation which applis piecewise cubic polynomials ($P_3$) and possesses $\mathcal{O}(h^2)$ convergence rate in energy norm on general shape-regular triangulations. Both Dirichlet and Navier type boundary value problems are studied. The basis for the scheme is a piecewise cubic polynomial space, which can approximate the $H^4$ functions with $\mathcal{O}(h^2)$ accuracy in broken $H^2$ norm. Besides, an equivalence $(\nabla_h^2\ \cdot,\nabla_h^2\ \cdot)=(Δ_h\ \cdot,Δ_h\ \cdot)$, which is usually not true for nonconforming finite element spaces, is proved on the newly designed spaces. The finite element space does not correspond to a finite element defined with Ciarlet's triple; however, a set of locally supported basis functions of the finite element space is still figured out. The notion of the finite element Stokes complex plays an important role in the analysis and also the construction of the basis functions.

math.NA↗

arXiv2020

Web Table Extraction, Retrieval and Augmentation: A Survey

Tables are a powerful and popular tool for organizing and manipulating data. A vast number of tables can be found on the Web, which represents a valuable knowledge resource. The objective of this survey is to synthesize and present two decades of research on web tables. In particular, we organize existing literature into six main categories of information access tasks: table extraction, table interpretation, table search, question answering, knowledge base augmentation, and table augmentation. For each of these tasks, we identify and describe seminal approaches, present relevant resources, and point out interdependencies among the different tasks.

cs.IR↗

arXiv2020

Auto-completion for Data Cells in Relational Tables

We address the task of auto-completing data cells in relational tables. Such tables describe entities (in rows) with their attributes (in columns). We present the CellAutoComplete framework to tackle several novel aspects of this problem, including: (i) enabling a cell to have multiple, possibly conflicting values, (ii) supplementing the predicted values with supporting evidence, (iii) combining evidence from multiple sources, and (iv) handling the case where a cell should be left empty. Our framework makes use of a large table corpus and a knowledge base as data sources, and consists of preprocessing, candidate value finding, and value ranking components. Using a purpose-built test collection, we show that our approach is 40\% more effective than the best baseline.

cs.IR↗

arXiv2020

Novel Entity Discovery from Web Tables

When working with any sort of knowledge base (KB) one has to make sure it is as complete and also as up-to-date as possible. Both tasks are non-trivial as they require recall-oriented efforts to determine which entities and relationships are missing from the KB. As such they require a significant amount of labor. Tables on the Web, on the other hand, are abundant and have the distinct potential to assist with these tasks. In particular, we can leverage the content in such tables to discover new entities, properties, and relationships. Because web tables typically only contain raw textual content we first need to determine which cells refer to which known entities---a task we dub table-to-KB matching. This first task aims to infer table semantics by linking table cells and heading columns to elements of a KB. Then second task builds upon these linked entities and properties to not only identify novel ones in the same table but also to bootstrap their type and additional relationships. We refer to this process as novel entity discovery and, to the best of our knowledge, it is the first endeavor on mining the unlinked cells in web tables. Our method identifies not only out-of-KB (``novel'') information but also novel aliases for in-KB (``known'') entities. When evaluated using three purpose-built test collections, we find that our proposed approaches obtain a marked improvement in terms of precision over our baselines whilst keeping recall stable.

cs.IR↗

arXiv2020

Optimal quadratic element on rectangular grids for $H^1$ problems

In this paper, a piecewise quadratic finite element method on rectangular grids for the $H^1$ problems is presented. The proposed method can be viewed as a reduced rectangular Morley element. For the source problem, the convergence rate of this scheme is $O(h^2)$ in the energy norm on uniform grids. Besides, a lower bound of the $L^2$-norm error is also proved, which makes the capacity analysis of this scheme more clear. On the other hand, for the eigenvalue problem, the numerical eigenvalues by this element are shown to be the lower bounds of the exact ones. Some numerical results are presented, which show the potential of the proposed finite element.

math.NA↗

arXiv2020

SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey

The fundamental stellar atmospheric parameters T_eff and log g and 13 chemical abundances are derived for medium-resolution spectroscopy from LAMOST Medium-Resolution Survey (MRS) data sets with a deep-learning method. The neural networks we designed, named as SPCANet, precisely map LAMOST MRS spectra to stellar parameters and chemical abundances. The stellar labels derived by SPCANet are with precisions of 119 K for T_eff and 0.17 dex for log g. The abundance precision of 11 elements including [C/H], [N/H], [O/H], [Mg/H], [Al/H], [Si/H], [S/H], [Ca/H], [Ti/H], [Cr/H], [Fe/H], and [Ni/H] are 0.06~0.12 dex, while of [Cu/H] is 0.19 dex. These precisions can be reached even for spectra with signal-to-noise as low as 10. The results of SPCANet are consistent with those from other surveys such as APOGEE, GALAH and RAVE, and are also validated with the previous literature values including clusters and field stars. The catalog of the estimated parameters is available at \url{http://paperdata.china-vo.org/LAMOST/MRS_parameters_elements.csv}.

astro-ph.SR↗

arXiv2019

Quantum search for unknown number of target items hybridizing the fixed-point method with the trail-and-error method

For the unsorted database quantum search with the unknown fraction $λ$ of target items, there are mainly two kinds of methods, i.e., fixed-point or trail-and-error. (i) In terms of the fixed-point method, Yoder et al. [Phys. Rev. Lett. 113, 210501 (2014)] claimed that the quadratic speedup over classical algorithms has been achieved. However, in this paper, we point out that this is not the case, because the query complexity of Yoder's algorithm is actually in $O(1/\sqrt{λ_0})$ rather than $O(1/\sqrtλ)$, where $λ_0$ is a known lower bound of $λ$. (ii) In terms of the trail-and-error method, currently the algorithm without randomness has to take more than 1 times queries or iterations than the algorithm with randomly selected parameters. For the above problems, we provide the first hybrid quantum search algorithm based on the fixed-point and trail-and-error methods, where the matched multiphase Grover operations are trialed multiple times and the number of iterations increases exponentially along with the number of trials. The upper bound of expected queries as well as the optimal parameters are derived. Compared with Yoder's algorithm, the query complexity of our algorithm indeed achieves the optimal scaling in $λ$ for quantum search, which reconfirms the practicality of the fixed-point method. In addition, our algorithm also does not contain randomness, and compared with the existing deterministic algorithm, the query complexity can be reduced by about 1/3. Our work provides an new idea for the research on fixed-point and trial-and-error quantum search.

quant-ph↗

arXiv2019

M subdwarf research. I. Identification, modified classification system, and sample construction

We propose a revision of the system developed by L'epine et al. (2007) for spectroscopic M subdwarf classification. Based on an analysis of subdwarf spectra and templates from Savcheva et al. (2014), we show thatthe CaH1 feature originally proposed by Gizis (1997) is important in selecting reliable cool subdwarf spectra. This index should be used in combination with the [TiO5, CaH2+CaH3] relation provided by Lépine et al. (2007) to avoid misclassification results. In the new system, the dwarf-subdwarf separators are first derived from a sample of more than 80,000 M dwarfs and a "labeled" subdwarf subsample, these objects being all visually identified from their optical spectra. Based on these two samples, we re-fit the initial [TiO5, CaH1] relation, and propose a new [CaOH, CaH1] relation supplementing the [TiO5, CaH1] relation to reduce the impact of uncertainty in flux calibration on classification accuracy. In addition, we recalibrate the $ζ_{TiO/CaH}$ parameter defined in L'epine et al. (2007) to enable its successful application to LAMOST spectra. Using this new system, we select candidates from LAMOST Data Release 4 and finally identify a set of 2791 new M subdwarf stars, covering the spectral sequence from type M0 to M7. This sample contains a large number of objects located at low Galactic latitudes, especially in the Galactic anti-center direction, expanding beyond previously published halo- and thick disk-dominated samples. Besides, we detect magnetic activity in 141 objects. We present a catalog for this M subdwarf sample, including radial velocities, spectral indices and errors, activity flags, with a compilation of external data (photometric and GAIA DR2 astrometric parameters). The catalog is provided on-line, and the spectra can be retrieved from the LAMOST Data Release web portal.

astro-ph.SR↗

arXiv2019

A high accuracy nonconforming finite element scheme for Helmholtz transmission eigenvalue problem

In this paper, we consider a cubic $H^2$ nonconforming finite element scheme $B_{h0}^3$ which does not correspond to a locally defined finite element with Ciarlet$'$s triple but admit a set of local basis functions. For the first time, we deduce and write out the expression of basis functions explicitly. Distinguished from the most nonconforming finite element methods, $(δΔ_h\cdot,Δ_h\cdot)$ with non-constant coefficient $δ>0$ is coercive on the nonconforming $B_{h0}^3$ space which makes it robust for numerical discretization. For fourth order eigenvalue problem, the $B_{h0}^3$ scheme can provide $\mathcal{O}(h^2)$ approximation for the eigenspace in energy norm and $\mathcal{O}(h^4)$ approximation for the eigenvalues. We test the $B_{h0}^3$ scheme on the vary-coefficient bi-Laplace source and eigenvalue problem, further, transmission eigenvalue problem. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed scheme.

math.NA↗

arXiv2019

Quantum-enhanced least-square support vector machine: simplified quantum algorithm and sparse solutions

Quantum algorithms can enhance machine learning in different aspects. Here, we study quantum-enhanced least-square support vector machine (LS-SVM). Firstly, a novel quantum algorithm that uses continuous variable to assist matrix inversion is introduced to simplify the algorithm for quantum LS-SVM, while retaining exponential speed-up. Secondly, we propose a hybrid quantum-classical version for sparse solutions of LS-SVM. By encoding a large dataset into a quantum state, a much smaller transformed dataset can be extracted using quantum matrix toolbox, which is further processed in classical SVM. We also incorporate kernel methods into the above quantum algorithms, which uses both exponential growth Hilbert space of qubits and infinite dimensionality of continuous variable for quantum feature maps. The quantum LS-SVM exploits quantum properties to explore important themes for SVM such as sparsity and kernel methods, and stresses its quantum advantages ranging from speed-up to the potential capacity to solve classically difficult machine learning tasks.

quant-ph↗

arXiv2019

Exact quantum search based on analytical multiphase matching for known number of target items and the experimental demonstration on IBM Q

In [Phys. Rev. Lett. 113, 210501 (2014)], to achieve the optimal fixed-point quantum search in the case of unknown fraction (denoted by $λ$) of target items, the analytical multiphase matching (AMPM) condition has been proposed. In this paper, we find out that the AMPM condition can also be used to design the exact quantum search algorithm in the case of known $λ$, and the minimum number of iterations reaches the optimal level of existing exact algorithms. Experiments are performed to demonstrate the proposed algorithm on IBM's quantum computer. In addition, we theoretically find two coincidental phases with equal absolute value in our algorithm based on the AMPM condition and that algorithm based on single-phase matching. Our work confirms the practicability of the AMPM condition in the case of known $λ$, and is helpful to understand the mechanism of this condition.

quant-ph↗