arXiv subjects

Jun Hu

Publications and source records attributed to Jun Hu.

At least 145 records · Page 8Linked to original sources

arXiv2023

Skew cellularity of the Hecke algebras of type $G(\ell,p,n)$

This paper introduces (graded) skew cellular algebras, which generalise Graham and Lehrer's cellular algebras. We show that all of the main results from the theory of cellular algebras extend to skew cellular algebras and we develop a ``cellular algebra Clifford theory'' for the skew cellular algebras that arise as fixed point subalgebras of cellular algebras. As an application of this general theory, the main result of this paper proves that the Hecke algebras of type $G(\ell,p,n)$ are graded skew cellular algebras. In the special case when $p = 2$ this implies that the Hecke algebras of type $G(\ell,2,n)$ are graded cellular algebras. The proof of all of these results rely, in a crucial way, on the diagrammatic Cherednik algebras of Webster and Bowman. Our main theorem extends Geck's result that the one parameter Iwahori-Hecke algebras are cellular algebras in two ways. First, our result applies to all cyclotomic Hecke algebras in the infinite series in the Shephard-Todd classification of complex reflection groups. Secondly, we lift cellularity to the graded setting. As applications of our main theorem, we show that the graded decomposition matrices of the Hecke algebras of type $G(\ell,p,n)$ are unitriangular, we construct and classify their graded simple modules and we prove the existence of ``adjustment matrices'' in positive characteristic.

math.RT↗

arXiv2023

Finite element grad grad complexes and elasticity complexes on cuboid meshes

This paper constructs two conforming finite element grad grad and elasticity complexes on the cuboid meshes. For the finite element grad grad complex, an $H^2$ conforming finite element space, an $\boldsymbol{H}(\operatorname{curl}; \mathbb{S})$ conforming finite element space, an $\boldsymbol{H}(\operatorname{div}; \mathbb{T})$ conforming finite element space and an $\boldsymbol{L}^2$ finite element space are constructed. Further, a finite element complex with reduced regularity is also constructed, whose degrees of freedom for the three diagonal components are coupled. For the finite element elasticity complex, a vector $\boldsymbol{H}^1$ conforming space and an $\boldsymbol{H}(\operatorname{curl}\operatorname{curl}^{T}; \mathbb{S})$ conforming space are constructed. Combining with an existing $\boldsymbol{H}(\operatorname{div}; \mathbb{S}) \cap \boldsymbol{H}(\operatorname{div}\operatorname{div}; \mathbb{S})$ element and $\boldsymbol{H}(\operatorname{div}; \mathbb{S})$ element, respectively, these finite element spaces form two different finite element elasticity complexes. The exactness of all the finite element complexes is proved.

math.NA↗

arXiv2023

Experimental observation on a low-rank tensor model for eigenvalue problems

Here we utilize a low-rank tensor model (LTM) as a function approximator, combined with the gradient descent method, to solve eigenvalue problems including the Laplacian operator and the harmonic oscillator. Experimental results show the superiority of the polynomial-based low-rank tensor model (PLTM) compared to the tensor neural network (TNN). We also test such low-rank architectures for the classification problem on the MNIST dataset.

cs.LG↗

arXiv2023

Mass testing of the JUNO experiment 20-inch PMTs readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose, large size, liquid scintillator experiment under construction in China. JUNO will perform leading measurements detecting neutrinos from different sources (reactor, terrestrial and astrophysical neutrinos) covering a wide energy range (from 200 keV to several GeV). This paper focuses on the design and development of a test protocol for the 20-inch PMT underwater readout electronics, performed in parallel to the mass production line. In a time period of about ten months, a total number of 6950 electronic boards were tested with an acceptance yield of 99.1%.

physics.ins-det↗

arXiv2022

Nonconforming finite element methods of order two and order three for the Stokes flow in three dimensions

In this study, the nonconforming finite elements of order two and order three are constructed and exploited for the Stokes problem. The moments of order up to $k-1$ ($k=2,3$) on all the facets of the tetrahedron are used for DoFs (degrees of freedom) to construct the unisolvent $k$-order nonconforming finite element with the bubble function space of $P_{k+1}$ explicitly represented. The pair of the $k$-order element and the discontinuous piecewise $P_{k}$ is proved to be stable for solving the Stokes problem with the element-wise divergence-free condition preserved. The main difficulty in establishing the discrete inf-sup condition comes from the fact that the usual Fortin operator can not be constructed. Thanks to the explicit representation of the bubble functions, its divergence space is proved to be identical to the orthogonal complement space of constants with respect to $P_k$ on the tetrahedron, which plays an important role to overcome the aforementioned difficulty and leads to the desirable well-posedness of the discrete problem. Furthermore, a reduced $k$-order nonconforming finite element with a discontinuous piecewise $P_{k-1}$ is designed and proved to be stable for solving the Stokes problem. The lack of the Fortin operator causes difficulty in analyzing the discrete inf-sup condition for the reduced third-order element pair. To deal with this problem, the so-called macro-element technique is adopted with a crucial algebraic result concerning the property of functions in the orthogonal complement space of the divergence of the discrete velocity space with respect to the discrete pressure space on the macro-element. Numerical experiments are provided to validate the theoretical results.

math.NA↗

arXiv2022

Validation and integration tests of the JUNO 20-inch PMTs readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. JUNO will be able to study the neutrino mass ordering and to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range, spanning from 200 keV to several GeV. Given the ambitious physics goals of JUNO, the electronic system has to meet specific tight requirements, and a thorough characterization is required. The present paper describes the tests performed on the readout modules to measure their performances.

physics.ins-det↗

arXiv2022

Fill in the Blank: Context-aware Automated Text Input Generation for Mobile GUI Testing

Automated GUI testing is widely used to help ensure the quality of mobile apps. However, many GUIs require appropriate text inputs to proceed to the next page which remains a prominent obstacle for testing coverage. Considering the diversity and semantic requirement of valid inputs (e.g., flight departure, movie name), it is challenging to automate the text input generation. Inspired by the fact that the pre-trained Large Language Model (LLM) has made outstanding progress in text generation, we propose an approach named QTypist based on LLM for intelligently generating semantic input text according to the GUI context. To boost the performance of LLM in the mobile testing scenario, we develop a prompt-based data construction and tuning method which automatically extracts the prompts and answers for model tuning. We evaluate QTypist on 106 apps from Google Play and the result shows that the passing rate of QTypist is 87%, which is 93% higher than the best baseline. We also integrate QTypist with the automated GUI testing tools and it can cover 42% more app activities, 52% more pages, and subsequently help reveal 122% more bugs compared with the raw tool.

cs.SE↗

arXiv2022

SelfNeRF: Fast Training NeRF for Human from Monocular Self-rotating Video

In this paper, we propose SelfNeRF, an efficient neural radiance field based novel view synthesis method for human performance. Given monocular self-rotating videos of human performers, SelfNeRF can train from scratch and achieve high-fidelity results in about twenty minutes. Some recent works have utilized the neural radiance field for dynamic human reconstruction. However, most of these methods need multi-view inputs and require hours of training, making it still difficult for practical use. To address this challenging problem, we introduce a surface-relative representation based on multi-resolution hash encoding that can greatly improve the training speed and aggregate inter-frame information. Extensive experimental results on several different datasets demonstrate the effectiveness and efficiency of SelfNeRF to challenging monocular videos.

cs.CV↗

arXiv2022

Novel total hip surgery robotic system based on self-localization and optical measurement

This paper presents the development and experimental evaluation of a surgical robotic system for total hip arthroplasty (THA). Although existing robotic systems used in joint replacement surgery have achieved some progresses, the robot arm must be situated accurately at the target position during operation, which depends significantly on the experience of the surgeon. In addition, handheld acetabulum reamers typically exhibit uneven strength and grinding file. Moreover, the lack of techniques to real-time measure femoral neck length may lead to poor outcomes. To tackle these challenges, we propose a real-time traceable optical positioning strategy to reduce unnecessary manual adjustments to the robotic arm during surgery, an end-effector system to stabilise grinding, and an optical probe to provide real-time measurement of the femoral neck length and other parameters used to choose the proper prosthesis. The lengths of the lower limbs are measured as the prosthesis is installed. The experimental evaluation results show that, based on its accuracy, execution ability, and robustness, the proposed surgical robotic system is feasible for THA.

cs.RO↗

arXiv2022

Check on the features of potted 20-inch PMTs with 1F3 electronics prototype at Pan-Asia

The Jiangmen underground neutrino observatory (JUNO) is a neutrino project with a 20-kton liquid scintillator detector located at 700-m underground. The large 20-inch PMTs are one of the crucial components of the JUNO experiment aiming to precision neutrino measurements with better than 3% energy resolution at 1 MeV. The excellent energy resolution and a large fiducial volume provide many exciting opportunities for addressing important topics in neutrino and astro-particle physics. With the container #D at JUNO Pan-Asia PMT testing and potting station, the features of waterproof potted 20-inch PMTs were measured with JUNO 1F3 electronics prototype in waveform and charge, which are valuable for better understanding on the performance of the waterproof potted PMTs and the JUNO 1F3 electronics. In this paper, basic features of JUNO 1F3 electronics prototype run at Pan-Asia will be introduced, followed by an analysis of the waterproof potted 20-inch PMTs and a comparison with the results from commercial electronics used by the container #A and #B.

physics.ins-det↗

arXiv2022

An efficient semismooth Newton-AMG-based inexact primal-dual algorithm for generalized transport problems

This work is concerned with the efficient optimization method for solving a large class of optimal mass transport problems. An inexact primal-dual algorithm is presented from the time discretization of a proper dynamical system, and by using the tool of Lyapunov function, the global (super-)linear convergence rate is established for function residual and feasibility violation. The proposed algorithm contains an inner problem that possesses strong semismoothness property and motivates the use of the semismooth Newton iteration. By exploring the hidden structure of the problem itself, the linear system arising from the Newton iteration is transferred equivalently into a graph Laplacian system, for which a robust algebraic multigrid method is proposed and also analyzed via the famous Xu--Zikatanov identity. Finally, numerical experiments are provided to validate the efficiency of our method.

math.OC↗

arXiv2022

A Broad and General Sequential Sampling Scheme

In this paper, we propose a broad and general sequential sampling scheme, which incorporates four different types of sampling procedures: i) the classic Anscombe-Chow-Robbins purely sequential sampling procedure; ii) the ordinary accelerated sequential sampling procedure; iii) the relatively new k-at-a-time purely sequential sampling procedure; iv) the new k-at-a-time improved accelerated sequential sampling procedure. The first-order and second-order properties of this general sequential sampling scheme are fully investigated with two illustrations on minimum risk point estimation for the mean of a normal distribution and on bounded variance point estimation for the location parameter of a negative exponential distribution, respectively. We also provide extensive computational simulation studies and real data analyses for each illustration.

stat.ME↗

arXiv2022

Afterpulse measurement of JUNO 20-inch PMTs

In this article we present the large photo-multiplier tube (PMT) afterpulse measurement results of Jiangmen Underground Neutrino Observatory (JUNO) experiment. Totally 11 dynode-PMTs (R12860) from Hamamatsu company and 150 micro-channel plate PMTs (MCP-PMTs, GDB-6201) from NNVT company were tested, an afterpulse model is built according to the afterpulse time distribution and probability of occurrence for these two types of PMTs. The average ratio between the total afterpulse charge with the delay between 0.5 $μ$ s and 20 $μ$ s to the primary pulse charge is 5.6%(13.2%) for the tested MCP-PMTs (dynode-PMTs). JUNO experiment will deploy 20,012 20-inch PMTs, and this study will benefit the detector simulation, event reconstruction and data analysis of JUNO experiment.

physics.ins-det↗

arXiv2022

Piecewise dominant sequences and the cocenter of the cyclotomic quiver Hecke algebras

We study the cocenter of the cyclotomic quiver Hecke algebra $R^Λ_α$ associated to an {\it arbitrary} symmetrizable Cartan matrix $A=(a_{ij})_{i,j}\in I$, $Λ\in P^+$ and $α\in Q_n^+$. We introduce a notion called "piecewise dominant sequence" and use it to construct some explicit homogeneous elements which span the maximal degree component of the cocenter of $R^Λ_α$. We show that the minimal degree components of the cocenter of $R^Λ_α$ is spanned by the image of some KLR idempotent $e(ν)$, where each $ν\in I^α$ is piecewise dominant. As an application, we show that the weight space $L(Λ)_{Λ-α}$ of the irreducible highest weight module $L(Λ)$ over $\mathfrak{g}(A)$ is nonzero (equivalently, $R^Λ_α\neq 0$) if and only if there exists a piecewise dominant sequence $ν\in I^α$.

math.RT↗

arXiv2022

Real-time Hyper-Dimensional Reconfiguration at the Edge using Hardware Accelerators

In this paper we present Hyper-Dimensional Reconfigurable Analytics at the Tactical Edge (HyDRATE) using low-SWaP embedded hardware that can perform real-time reconfiguration at the edge leveraging non-MAC (free of floating-point MultiplyACcumulate operations) deep neural nets (DNN) combined with hyperdimensional (HD) computing accelerators. We describe the algorithm, trained quantized model generation, and simulated performance of a feature extractor free of multiply-accumulates feeding a hyperdimensional logic-based classifier. Then we show how performance increases with the number of hyperdimensions. We describe the realized low-SWaP FPGA hardware and embedded software system compared to traditional DNNs and detail the implemented hardware accelerators. We discuss the measured system latency and power, noise robustness due to use of learnable quantization and HD computing, actual versus simulated system performance for a video activity classification task and demonstration of reconfiguration on this same dataset. We show that reconfigurability in the field is achieved by retraining only the feed-forward HD classifier without gradient descent backpropagation (gradient-free), using few-shot learning of new classes at the edge. Initial work performed used LRCN DNN and is currently extended to use Two-stream DNN with improved performance.

cs.CV↗

arXiv2022

Calibration Strategy of the JUNO-TAO Experiment

The Taishan Antineutrino Observatory (JUNO-TAO, or TAO) is a satellite detector for the Jiangmen Underground Neutrino Observatory (JUNO). Located near the Taishan reactor, TAO independently measures the reactor's antineutrino energy spectrum with unprecedented energy resolution. To achieve this goal, energy response must be well calibrated. Using the Automated Calibration Unit (ACU) and the Cable Loop System (CLS) of TAO, multiple radioactive sources are deployed to various positions in the detector to perform a precise calibration of energy response. The non-linear energy response can be controlled within 0.6% with different energy points of these radioactive sources. It can be further improved by using $^{12}\rm B$ decay signals produced by cosmic muons. Through the energy non-uniformity calibration, residual non-uniformity is less than 0.2%. The energy resolution degradation and energy bias caused by the residual non-uniformity can be controlled within 0.05% and 0.3%, respectively. In addition, the stability of other detector parameters, such as the gain of each silicon photo-multiplier, can be monitored with a special ultraviolet LED calibration system.

physics.ins-det↗

arXiv2022

Nighthawk: Fully Automated Localizing UI Display Issues via Visual Understanding

Graphical User Interface (GUI) provides a visual bridge between a software application and end users, through which they can interact with each other. With the upgrading of mobile devices and the development of aesthetics, the visual effects of the GUI are more and more attracting, and users pay more attention to the accessibility and usability of applications. However, such GUI complexity posts a great challenge to the GUI implementation. According to our pilot study of crowdtesting bug reports, display issues such as text overlap, component occlusion, missing image always occur during GUI rendering on different devices due to the software or hardware compatibility. They negatively influence the app usability, resulting in poor user experience. To detect these issues, we propose a fully automated approach, Nighthawk, based on deep learning for modelling visual information of the GUI screenshot. Nighthawk can detect GUIs with display issues and also locate the detailed region of the issue in the given GUI for guiding developers to fix the bug. At the same time, training the model needs a large amount of labeled buggy screenshots, which requires considerable manual effort to prepare them. We therefore propose a heuristic-based training data auto-generation method to automatically generate the labeled training data. The evaluation demonstrates that our Nighthawk can achieve average 0.84 precision and 0.84 recall in detecting UI display issues, average 0.59 AP and 0.60 AR in localizing these issues. We also evaluate Nighthawk with popular Android apps on Google Play and F-Droid, and successfully uncover 151 previously-undetected UI display issues with 75 of them being confirmed or fixed so far.

cs.SE↗

arXiv2022

On the center conjecture for the cyclotomic KLR algebras

The center conjecture for the cyclotomic KLR algebras $R_β^Λ$ asserts that the center of $R_β^Λ$ consists of symmetric elements in its KLR $x$ and $e(ν)$ generators. In this paper we show that this conjecture is equivalent to the injectivity of some natural map $\barι_β^{Λ,i}$ from the cocenter of $R_β^Λ$ to the cocenter of $R_β^{Λ+Λ_i}$ for all $i\in I$ and $Λ\in P^+$. We prove that the map $\barι_β^{Λ,i}$ is given by multiplication with a center element $z(i,β)\in R_β^{Λ+Λ_i}$ and we explicitly calculate the element $z(i,β)$ in terms of the KLR $x$ and $e(ν)$ generators. We present an explicit monomial basis for certain bi-weight spaces of the defining ideal of $R_β^Λ$ and of $R_β^Λ$. For $β=\sum_{j=1}^nα_{i_j}$ with $α_{i_1},\cdots, α_{i_n}$ pairwise distinct, we construct an explicit monomial basis of $R_β^Λ$, prove the map $\barι_β^{Λ,i}$ is injective and thus verify the center conjecture for these $R_β^Λ$.

math.RT↗