arXiv subjects

Rui Ma

Publications and source records attributed to Rui Ma.

At least 145 records · Page 8Linked to original sources

arXiv2021

RaidaR: A Rich Annotated Image Dataset of Rainy Street Scenes

We introduce RaidaR, a rich annotated image dataset of rainy street scenes, to support autonomous driving research. The new dataset contains the largest number of rainy images (58,542) to date, 5,000 of which provide semantic segmentations and 3,658 provide object instance segmentations. The RaidaR images cover a wide range of realistic rain-induced artifacts, including fog, droplets, and road reflections, which can effectively augment existing street scene datasets to improve data-driven machine perception during rainy weather. To facilitate efficient annotation of a large volume of images, we develop a semi-automatic scheme combining manual segmentation and an automated processing akin to cross validation, resulting in 10-20 fold reduction on annotation time. We demonstrate the utility of our new dataset by showing how data augmentation with RaidaR can elevate the accuracy of existing segmentation algorithms. We also present a novel unpaired image-to-image translation algorithm for adding/removing rain artifacts, which directly benefits from RaidaR.

cs.CV↗

arXiv2021

Toward Real-world Image Super-resolution via Hardware-based Adaptive Degradation Models

Most single image super-resolution (SR) methods are developed on synthetic low-resolution (LR) and high-resolution (HR) image pairs, which are simulated by a predetermined degradation operation, e.g., bicubic downsampling. However, these methods only learn the inverse process of the predetermined operation, so they fail to super resolve the real-world LR images; the true formulation deviates from the predetermined operation. To address this problem, we propose a novel supervised method to simulate an unknown degradation process with the inclusion of the prior hardware knowledge of the imaging system. We design an adaptive blurring layer (ABL) in the supervised learning framework to estimate the target LR images. The hyperparameters of the ABL can be adjusted for different imaging hardware. The experiments on the real-world datasets validate that our degradation model can estimate LR images more accurately than the predetermined degradation operation, as well as facilitate existing SR methods to perform reconstructions on real-world LR images more accurately than the conventional approaches.

eess.IV↗

arXiv2021

Closed-loop Feedback Registration for Consecutive Images of Moving Flexible Targets

Advancement of imaging techniques enables consecutive image sequences to be acquired for quality monitoring of manufacturing production lines. Registration for these image sequences is essential for in-line pattern inspection and metrology, e.g., in the printing process of flexible electronics. However, conventional image registration algorithms cannot produce accurate results when the images contain many similar and deformable patterns in the manufacturing process. Such a failure originates from a fact that the conventional algorithms only use the spatial and pixel intensity information for registration. Considering the nature of temporal continuity and consecution of the product images, in this paper, we propose a closed-loop feedback registration algorithm for matching and stitching the deformable printed patterns on a moving flexible substrate. The algorithm leverages the temporal and spatial relationships of the consecutive images and the continuity of the image sequence for fast, accurate, and robust point matching. Our experimental results show that our algorithm can find more matching point pairs with a lower root mean squared error (RMSE) compared to other state-of-the-art algorithms while offering significant improvements to running time.

cs.CV↗

arXiv2021

Fast Wireless Sensor Anomaly Detection based on Data Stream in Edge Computing Enabled Smart Greenhouse

Edge computing enabled smart greenhouse is a representative application of Internet of Things technology, which can monitor the environmental information in real time and employ the information to contribute to intelligent decision-making. In the process, anomaly detection for wireless sensor data plays an important role. However, traditional anomaly detection algorithms originally designed for anomaly detection in static data have not properly considered the inherent characteristics of data stream produced by wireless sensor such as infiniteness, correlations and concept drift, which may pose a considerable challenge on anomaly detection based on data stream, and lead to low detection accuracy and efficiency. First, data stream usually generates quickly which means that it is infinite and enormous, so any traditional off-line anomaly detection algorithm that attempts to store the whole dataset or to scan the dataset multiple times for anomaly detection will run out of memory space. Second, there exist correlations among different data streams, which traditional algorithms hardly consider. Third, the underlying data generation process or data distribution may change over time. Thus, traditional anomaly detection algorithms with no model update will lose their effects. Considering these issues, a novel method (called DLSHiForest) on basis of Locality-Sensitive Hashing and time window technique in this paper is proposed to solve these problems while achieving accurate and efficient detection. Comprehensive experiments are executed using real-world agricultural greenhouse dataset to demonstrate the feasibility of our approach. Experimental results show that our proposal is practicable in addressing challenges of traditional anomaly detection while ensuring accuracy and efficiency.

cs.LG↗

arXiv2021

A family of mixed finite elements for the biharmonic equations on triangular and tetrahedral grids

This paper introduces a new family of mixed finite elements for solving a mixed formulation of the biharmonic equations in two and three dimensions. The symmetric stress $\bmσ=-\nabla^{2}u$ is sought in the Sobolev space $H({\rm{div}}\bm{div},Ω;\mathbb{S})$ simultaneously with the displacement $u$ in $L^{2}(Ω)$. Stemming from the structure of $H(\bm{div},Ω;\mathbb{S})$ conforming elements for the linear elasticity problems proposed by J. Hu and S. Zhang, the $H({\rm{div}}\bm{div},Ω;\mathbb{S})$ conforming finite element spaces are constructed by imposing the normal continuity of $\bm{div}\bmσ$ on the $H(\bm{div},Ω;\mathbb{S})$ conforming spaces of $P_{k}$ symmetric tensors. The inheritance makes the basis functions easy to compute. The discrete spaces for $u$ are composed of the piecewise $P_{k-2}$ polynomials without requiring any continuity. Such mixed finite elements are inf-sup stable on both triangular and tetrahedral grids for $k\geq 3$, and the optimal order of convergence is achieved. Besides, the superconvergence and the postprocessing results are displayed. Some numerical experiments are provided to demonstrate the theoretical analysis.

math.NA↗

arXiv2021

Conforming finite element DIVDIV complexes and the application for the linearized Einstein-Bianchi system

This paper presents the first family of conforming finite element divdiv complexes on tetrahedral grids in three dimensions. In these complexes, finite element spaces of $H(\text{divdiv},Ω;\mathbb{S})$ are from a current preprint [Chen and Huang, arXiv: 2007.12399, 2020] while finite element spaces of both $H(\text{symcurl},Ω;\mathbb{T})$ and $H^1(Ω;\mathbb{R}^3)$ are newly constructed here. It is proved that these finite element complexes are exact. As a result, they can be used to discretize the linearized Einstein-Bianchi system within the dual formulation.

math.NA↗

arXiv2020

Electrostatics in a crooked nanochannel in a newly developed curvilinear coordinate system

Both biological and artificial nanochannels in crooked shape exhibit unusual transportational characteristics, bringing about a challenge to the traditional theoretical analysis of nanofluidics, partly due to their complicated boundary description. In this paper, by developing a curvilinear coordinate system for crooked nanochannels, we successfully solve the electrostatic Poisson-Boltzmann equation analytically for a two-dimensional nanochannel, with its effectiveness confirmed through numerical calculation. The influences of the geometric profile of the nanochannel on the distribution of electric potential, ionic concentration, and surface charge on channel walls can be quantitatively evaluated in a facilitated way in terms of these curvilinear coordinates. Such a technique can be widely applied to many nanofluidic systems.

cond-mat.soft↗

arXiv2020

Bogomolov multipliers of some groups of order $p^{6}$

Let $G$ be a finite group, $V$ a faithful finite-dimensional representation of $G$ over the complex field $\mathbb{C}$ and $\mathbb{C}(V)^{G}$ be the corresponding invariant field. The Bogomolov multiplier $B_{0}(G)$ of $G$ is canonically isomorphic to the unramified cohomological group $H_{\textrm{nr}}^{2}(\mathbb{C}(V)^{G},\mathbb{Q}/\mathbb{Z})$, which has been used by Saltman (1984) and Bogomolov (1988) to provide counter-examples to the rationality problem of $\mathbb{C}(V)^{P}$ for finite $p$-groups $P$ over $\mathbb{C}$. In this paper, we investigate the vanishing property of $B_{0}(P)$, where $P$ denotes a $p$-group of order $p^{6}$ for $p\geqslant 3$.

math.AG↗

arXiv2020

Energy Efficient Software Matching in Distributed Vehicular Fog Based Architecture with Cloud and Fixed Fog Nodes

The rapid development of vehicles on-board units and the proliferation of autonomous vehicles in modern cities create a potential for a new fog computing paradigm, referred to as vehicular fog computing (VFC). In this paper, we propose an architecture that integrates a vehicular fog (VF) composed of vehicles clustered in a parking lot with a fixed fog node at the access network and the central cloud. We investigate the problem of energy efficient software matching in the VF considering different approaches to deploy software packages in vehicles.

cs.NI↗

arXiv2020

An adaptive finite element scheme for the Hellinger--Reissner elasticity mixed eigenvalue problem

In this paper we study the approximation of eigenvalues arising from the mixed Hellinger--Reissner elasticity problem by using the simple finite element using partial relaxation of $C^0$ vertex continuity of stresses introduced recently by Jun Hu and Rui Ma. We prove that the method converge when a residual type error estimator is considered and that the estimator decays optimally with respect to the number of degrees of freedom.

math.NA↗

arXiv2020

MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects

For most of the object detectors based on multi-scale feature maps, the shallow layers are rich in fine spatial information and thus mainly responsible for small object detection. The performance of small object detection, however, is still less than satisfactory because of the deficiency of semantic information on shallow feature maps. In this paper, we design a Multi-scale Deconvolutional Single Shot Detector (MDSSD), especially for small object detection. In MDSSD, multiple high-level feature maps at different scales are upsampled simultaneously to increase the spatial resolution. Afterwards, we implement the skip connections with low-level feature maps via Fusion Block. The fusion feature maps, named Fusion Module, are of strong feature representational power of small instances. It is noteworthy that these high-level feature maps utilized in Fusion Block preserve both strong semantic information and some fine details of small instances, rather than the top-most layer where the representation of fine details for small objects are potentially wiped out. The proposed framework achieves 77.6% mAP for small object detection on the challenging dataset TT100K with 512 x 512 input, outperforming other detectors with a large margin. Moreover, it can also achieve state-of-the-art results for general object detection on PASCAL VOC2007 test and MS COCO test-dev2015, especially achieving 2 to 5 points improvement on small object categories.

cs.CV↗

arXiv2019

Identify the cells' nuclei based on the deep learning neural network

Identify the cells' nuclei is the important point for most medical analyses. To assist doctors finding the accurate cell' nuclei location automatically is highly demanded in the clinical practice. Recently, fully convolutional neural network (FCNs) serve as the back-bone in many image segmentation, like liver and tumer segmentation in medical field, human body block in technical filed. The cells' nuclei identification task is also kind of image segmentation. To achieve this, we prefer to use deep learning algorithms. we construct three general frameworks, one is Mask Region-based Convolutional Neural Network (Mask RCNN), which has the high performance in many image segmentations, one is U-net, which has the high generalization performance on small dataset and the other is DenseUNet, which is mixture network architecture with Dense Net and U-net. we compare the performance of these three frameworks. And we evaluated our method on the dataset of data science bowl 2018 challenge. For single model without any ensemble, they all have good performance.

cs.CV↗

arXiv2019

Optimal Superconvergence Analysis for the Crouzeix-Raviart and the Morley elements

In this paper, an improved superconvergence analysis is presented for both the Crouzeix-Raviart element and the Morley element. The main idea of the analysis is to employ a discrete Helmholtz decomposition of the difference between the canonical interpolation and the finite element solution for the first order mixed Raviart--Thomas element and the mixed Hellan--Herrmann--Johnson element, respectively. This, in particular, allows for proving a full one order superconvergence result for these two mixed finite elements. Finally, a full one order superconvergence result of both the Crouzeix-Raviart element and the Morley element follows from their special relations with the first order mixed Raviart--Thomas element and the mixed Hellan--Herrmann--Johnson element respectively. Those superconvergence results are also extended to mildly-structured meshes.

math.NA↗

arXiv2019

Partial relaxation of C^0 vertex continuity of stresses of conforming mixed finite elements for the elasticity problem

A conforming triangular mixed element recently proposed by Hu and Zhang for linear elasticity is extended by rearranging the global degrees of freedom. More precisely, adaptive meshes $\mathcal{T}_1$, $\cdots$, $\mathcal{T}_N$ which are successively refined from an initial mesh $\mathcal{T}_0$ through a newest vertex bisection strategy, admit a crucial hierarchical structure, namely, a newly added vertex $\boldsymbol{x}$ of the mesh $\mathcal{T}_\ell$ is the midpoint of an edge $e$ of the coarse mesh $\mathcal{T}_{\ell-1}$. Such a hierarchical structure is explored to partially relax the $C^0$ vertex continuity of symmetric matrix-valued functions in the discrete stress space of the original element on $\mathcal{T}_\ell$ and results in an extended discrete stress space. A feature of this extended discrete stress space is its nestedness in the sense that a space on a coarse mesh $\mathcal{T}$ is a subspace of a space on any refinement $\hat{\mathcal{T}}$ of $\mathcal{T}$, which allows a proof of convergence of a standard adaptive algorithm. The idea is extended to impose a general traction boundary condition on the discrete level. Numerical experiments are provided to illustrate performance on both uniform and adaptive meshes.

math.NA↗

arXiv2019

Energy Efficient Software Matching in Vehicular Fog

Along with the development of Internet of Things (IoT) and the rise of fog computing, more new joint technologies have been proposed. Vehicular Ad-hoc Networks (VANET) are one of the emergent technologies that come with a very promising role, where the spare processing capabilities of vehicles can be exploited. In this paper, we propose a fog architecture to provide services for end users based on a cluster of static vehicles in a parking lot referred to as a vehicular fog. The proposed vehicular fog architecture is connected to the central data center through an optical infrastructure. As the processing requests from users require specific software packages that may not be available in all vehicles, we study the software matching problem of task assignments in vehicular fog. The goal of this paper is to examine the effect of software packages variety in vehicles on the assignment decision and the overall power consumption. A mixed integer linear programming (MILP) model was utilized to optimize the power consumption of the overall architecture, considering different numbers of software packages in the vehicular fog. The results reveal a power saving of up to 27% when vehicles are uploaded with four or more different software packages out of a library of ten software packages in this example.

cs.NI↗

arXiv2019

Construction and Analysis of Posterior Matching in Arbitrary Dimensions via Optimal Transport

The posterior matching scheme, for feedback encoding of a message point lying on the unit interval over memoryless channels, maximizes mutual information for an arbitrary number of channel uses. However, it in general does not always achieve any positive rate; so far, elaborate analyses have been required to show that it achieves any positive rate below capacity. More recent efforts have introduced a random "dither" shared by the encoder and decoder to the problem formulation, to simplify analyses and guarantee that the randomized scheme achieves any rate below capacity. Motivated by applications (e.g. human-computer interfaces) where (a) common randomness shared by the encoder and decoder may not be feasible and (b) the message point lies in a higher dimensional space, we focus here on the original formulation without common randomness, and use optimal transport theory to generalize the scheme for a message point in a higher dimensional space. By defining a stricter, almost sure, notion of message decoding, we use classical probabilistic techniques (e.g. change of measure and martingale convergence) to establish succinct necessary and sufficient conditions on when the message point can be recovered from infinite observations: Birkhoff ergodicity of a random process sequentially generated by the encoder. We also show a surprising "all or nothing" result: the same ergodicity condition is necessary and sufficient to achieve any rate below capacity. We provide applications of this message point framework in human-computer interfaces and multi-antenna communications.

cs.IT↗

arXiv2018

A PMU-based Multivariate Model for Classifying Power System Events

Real-time transient event identification is essential for power system situational awareness and protection. The increased penetration of Phasor Measurement Units (PMUs) enhance power system visualization and real time monitoring and control. However, a malicious false data injection attack on PMUs can provide wrong data that might prompt the operator to take incorrect actions which can eventually jeopardize system reliability. In this paper, a multivariate method based on text mining is applied to detect false data and identify transient events by analyzing the attributes of each individual PMU time series and their relationship. It is shown that the proposed approach is efficient in detecting false data and identifying each transient event regardless of the system topology and loading condition as well as the coverage rate and placement of PMUs. The proposed method is tested on IEEE 30-bus system and the classification results are provided.

eess.SP↗

arXiv2018

An Inside Look at the Ti-MoS2 Contact in Ultra-thin Field Effect Transistor with Atomic Resolution

Two-dimensional molybdenum disulfide (MoS2) is an excellent channel material for ultra-thin field effect transistors. However, high contact resistance across the metal-MoS2 interface continues to limit its widespread realization. Here, using atomic-resolution analytical scanning transmission electron microscopy (STEM) together with first principle calculations, we show that this contact problem is a fundamental limitation from the bonding and interactions at the metal-MoS2 interface that cannot be solved by improved deposition engineering. STEM analysis in conjunction with theory shows that when MoS2 is in contact with Ti, a metal with a high affinity to form strong bonds with sulfur, there is a release of S from Mo along with the formation of small Ti/TixSy clusters. A destruction of the MoS2 layers and penetration of metal can also be expected. The design of true high-mobility metal-MoS2 contacts will require the optimal selection of the metal or alloy based on their bonding interactions with the MoS2 surface. This can be advanced by evaluation of binding energies with increasing the number of atoms within metal clusters.

cond-mat.mtrl-sci↗