arXiv subjects

Fei Liu

Publications and source records attributed to Fei Liu.

At least 271 records · Page 15Linked to original sources

arXiv2019

Flooding simulation due to Hurricane Florence in North Carolina with HEC RAS

Flooding due to Hurricane Florence led to billions of dollars in damage and nearly a hundred deaths in North Carolina. These damages and fatalities can be avoided with proper prevention and preparation. Modelling such flooding events can provide insight and precaution based on principles of fluid dynamics and GIS technology. Using topography and other geographic data from USGS, HEC-RAS can solve the Shallow Water Equations over flooding areas to assist the study of inundation patterns. Simulation results from HEC-RAS agree with observations from NOAA in the flooding area studied. Modeled results from specific locations affected by Hurricane Florence near Neuse River, NC are compared with observations. While overall pattern of inundation is agreeable between model results and observations, there are also differences at very specific locations. Higher resolution topography data and precipitation data over the flooding area may improve the simulation result and reduce the differences.

physics.ao-ph↗

arXiv2019

Computing characteristic functions of quantum work in phase space

In phase space, we analytically obtain the characteristic functions (CFs) of a forced harmonic oscillator [Talkner et al., Phys. Rev. E, 75, 050102 (2007)], a time-dependent mass and frequency harmonic oscillator [Deffner and Lutz, Phys. Rev. E, 77, 021128 (2008)], and coupled harmonic oscillators under driving forces in a simple and unified way. For general quantum systems, a numerical method that approximates the CFs to $\hbar^2$ order is proposed. We exemplify the method with a time-dependent frequency harmonic oscillator and a family of quantum systems with time-dependent even power-law potentials.

cond-mat.stat-mech↗

arXiv2019

An investigation of the Brumadinho Dam Break with HEC RAS simulation

The Brumadinho dam disaster occurred on the 25 January, 2019 when Dam I, an upstream tailings dam at the Corrego do Feijao iron ore mine, 9 kilometres (5.6 mi) east of Brumadinho, Minas Gerais, Brazil, suffered a catastrophic failure. Over 248 people died and over 2.88 billion worth of property were lost or damaged due to the subsequent mud flow and flooding. This is merely 4 years after the previous Mariana dam break affecting over 1 million people downstream due to iron ore mining waste flowing downstream into river basin. To prevent a similar tragedy from reoccurring, it's useful to examine the cause of the Brumadinho dam break and compare observations with model simulations. HEC RAS, developed by US Army Corps of Engineers, is used to model the mud flow from the Brumadinho dam break based on the NASA SRTM elevation dataset over Brazil. The extent of the mud flow from the HEC RAS simulation matches the actual flooding due to the dam break. This simulation technique can later be used for future dam collapse predictions.

physics.comp-ph↗

arXiv2019

Multi-Document Summarization with Determinantal Point Processes and Contextualized Representations

Emerged as one of the best performing techniques for extractive summarization, determinantal point processes select the most probable set of sentences to form a summary according to a probability measure defined by modeling sentence prominence and pairwise repulsion. Traditionally, these aspects are modelled using shallow and linguistically informed features, but the rise of deep contextualized representations raises an interesting question of whether, and to what extent, contextualized representations can be used to improve DPP modeling. Our findings suggest that, despite the success of deep representations, it remains necessary to combine them with surface indicators for effective identification of summary sentences.

cs.CL↗

arXiv2019

Towards Annotating and Creating Sub-Sentence Summary Highlights

Highlighting is a powerful tool to pick out important content and emphasize. Creating summary highlights at the sub-sentence level is particularly desirable, because sub-sentences are more concise than whole sentences. They are also better suited than individual words and phrases that can potentially lead to disfluent, fragmented summaries. In this paper we seek to generate summary highlights by annotating summary-worthy sub-sentences and teaching classifiers to do the same. We frame the task as jointly selecting important sentences and identifying a single most informative textual unit from each sentence. This formulation dramatically reduces the task complexity involved in sentence compression. Our study provides new benchmarks and baselines for generating highlights at the sub-sentence level.

cs.CL↗

arXiv2019

Analyzing Sentence Fusion in Abstractive Summarization

While recent work in abstractive summarization has resulted in higher scores in automatic metrics, there is little understanding on how these systems combine information taken from multiple document sentences. In this paper, we analyze the outputs of five state-of-the-art abstractive summarizers, focusing on summary sentences that are formed by sentence fusion. We ask assessors to judge the grammaticality, faithfulness, and method of fusion for summary sentences. Our analysis reveals that system sentences are mostly grammatical, but often fail to remain faithful to the original article.

cs.CL↗

arXiv2019

MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance

A robust evaluation metric has a profound impact on the development of text generation systems. A desirable metric compares system output against references based on their semantics rather than surface forms. In this paper we investigate strategies to encode system and reference texts to devise a metric that shows a high correlation with human judgment of text quality. We validate our new metric, namely MoverScore, on a number of text generation tasks including summarization, machine translation, image captioning, and data-to-text generation, where the outputs are produced by a variety of neural and non-neural systems. Our findings suggest that metrics combining contextualized representations with a distance measure perform the best. Such metrics also demonstrate strong generalization capability across tasks. For ease-of-use we make our metrics available as web service.

cs.CL↗

arXiv2019

Sub-60 mV/decade switching with a cold metal as the injection source

Power dissipation is a great challenge for the continuous scaling down and performance improvement of CMOS technology, due to thermionic current switching limit of conventional MOSFETs. In this work, we show that this problem can be overcome by using cold metals as the transistor's injection source, which are different from conventional metals and can filter high energy electrons to break the Boltzmann tyranny. It is proved that the subthreshold swing (SS) of thermionic current of transistor using cold metal contact can be extremely smaller than 60 mV/decade at room temperature. Specifically, two-dimensional (2D) transition metal chalcogenide (TMD) cold metals of NbX$_2$ and TaX$_2$(X=S, Se, Te) are proposed as the injection source of FETs. Quantum transport simulations indicate that promising switching efficiency and on-state current can be achieved using TMD cold metal injection source, which is beneficial for energy efficient applications.

cond-mat.mes-hall↗

arXiv2019

The Referential Reader: A Recurrent Entity Network for Anaphora Resolution

We present a new architecture for storing and accessing entity mentions during online text processing. While reading the text, entity references are identified, and may be stored by either updating or overwriting a cell in a fixed-length memory. The update operation implies coreference with the other mentions that are stored in the same cell; the overwrite operation causes these mentions to be forgotten. By encoding the memory operations as differentiable gates, it is possible to train the model end-to-end, using both a supervised anaphora resolution objective as well as a supplementary language modeling objective. Evaluation on a dataset of pronoun-name anaphora demonstrates strong performance with purely incremental text processing.

cs.CL↗

arXiv2019

Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization

The most important obstacles facing multi-document summarization include excessive redundancy in source descriptions and the looming shortage of training data. These obstacles prevent encoder-decoder models from being used directly, but optimization-based methods such as determinantal point processes (DPPs) are known to handle them well. In this paper we seek to strengthen a DPP-based method for extractive multi-document summarization by presenting a novel similarity measure inspired by capsule networks. The approach measures redundancy between a pair of sentences based on surface form and semantic information. We show that our DPP system with improved similarity measure performs competitively, outperforming strong summarization baselines on benchmark datasets. Our findings are particularly meaningful for summarizing documents created by multiple authors containing redundant yet lexically diverse expressions.

cs.CL↗

arXiv2019

Scoring Sentence Singletons and Pairs for Abstractive Summarization

When writing a summary, humans tend to choose content from one or two sentences and merge them into a single summary sentence. However, the mechanisms behind the selection of one or multiple source sentences remain poorly understood. Sentence fusion assumes multi-sentence input; yet sentence selection methods only work with single sentences and not combinations of them. There is thus a crucial gap between sentence selection and fusion to support summarizing by both compressing single sentences and fusing pairs. This paper attempts to bridge the gap by ranking sentence singletons and pairs together in a unified space. Our proposed framework attempts to model human methodology by selecting either a single sentence or a pair of sentences, then compressing or fusing the sentence(s) to produce a summary sentence. We conduct extensive experiments on both single- and multi-document summarization datasets and report findings on sentence selection and abstraction.

cs.CL↗

arXiv2019

Guiding Extractive Summarization with Question-Answering Rewards

Highlighting while reading is a natural behavior for people to track salient content of a document. It would be desirable to teach an extractive summarizer to do the same. However, a major obstacle to the development of a supervised summarizer is the lack of ground-truth. Manual annotation of extraction units is cost-prohibitive, whereas acquiring labels by automatically aligning human abstracts and source documents can yield inferior results. In this paper we describe a novel framework to guide a supervised, extractive summarization system with question-answering rewards. We argue that quality summaries should serve as a document surrogate to answer important questions, and such question-answer pairs can be conveniently obtained from human abstracts. The system learns to promote summaries that are informative, fluent, and perform competitively on question-answering. Our results compare favorably with those reported by strong summarization baselines as evaluated by automatic metrics and human assessors.

cs.CL↗

arXiv2018

Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks

Forum threads are lengthy and rich in content. Concise thread summaries will benefit both newcomers seeking information and those who participate in the discussion. Few studies, however, have examined the task of forum thread summarization. In this work we make the first attempt to adapt the hierarchical attention networks for thread summarization. The model draws on the recent development of neural attention mechanisms to build sentence and thread representations and use them for summarization. Our results indicate that the proposed approach can outperform a range of competitive baselines. Further, a redundancy removal step is crucial for achieving outstanding results.

cs.CL↗

arXiv2018

On the Patterson-Sullivan measure for geodesic flows on rank $1$ manifolds without focal points

In this article, we consider the geodesic flow on a compact rank $1$ Riemannian manifold $M$ without focal points, whose universal cover is denoted by $X$. On the ideal boundary $X(\infty)$ of $X$, we show the existence and uniqueness of the Busemann density, which is realized via the Patterson-Sullivan measure. Based on the the Patterson-Sullivan measure, we show that the geodesic flow on $M$ has a unique invariant measure of maximal entropy. We also obtain the asymptotic growth rate of the volume of geodesic spheres in $X$ and the growth rate of the number of closed geodesics on $M$. These results generalize the work of Margulis and Knieper in the case of negative and nonpositive curvature respectively.

math.DS↗

arXiv2018

On the ergodicity of geodesic flows on surfaces without focal points

In this article, we study the ergodicity of the geodesic flows on surfaces with no focal points. Let $M$ be a smooth connected and closed surface equipped with a $C^\infty$ Riemannian metric $g$, whose genus $\mathfrak{g} \geq 2$. Suppose that $(M,g)$ has no focal points. We prove that the geodesic flow on the unit tangent bundle of $M$ is ergodic with respect to the Liouville measure, under the assumption that the set of points on $M$ with negative curvature has at most finitely many connected components.

math.DS↗

arXiv2018

On the mixing and Bernoulli properties for geodesic flows on rank 1 manifolds without focal points

If $(M,g)$ is a smooth compact rank $1$ Riemannian manifold without focal points, it is shown that the measure $μ_{\max}$ of maximal entropy for the geodesic flow is unique. In this article, we study the statistic properties and prove that this unique measure $μ_{\max}$ is mixing. Stronger conclusion that the geodesic flow on the unit tangent bundle $SM$ with respect to $μ_{\max}$ is Bernoulli is acquired provided $M$ is a compact surface with genus greater than one and no focal points.

math.DS↗

arXiv2018

The Decay Rate of Patterson-Sullivan Measures with Potential Functions and Critical Exponents

Basing upon the recent development of the Patterson-Sullivan measures with a Hölder continuous nonzero potential function, we use tools of both dynamics of geodesic flows and geometric properties of negatively curved manifolds to present a new formula illustrating the relation between the exponential decay rate of Patterson-Sullivan measures with a Hölder continuous potential function and the corresponding critical exponent.

math.DS↗

arXiv2018

Air Flow Analysis of a Rotating Cylinder through Numerical Simulation

The complete flow field surrounding a rotating cylinder is calculated by solving the Navier-Stokes equations using the finite difference method. The numerical simulation is performed on a transformed rectilinear grid, with axes representing the radial and angular dimensions. Different boundary conditions of the simulations are tested by changing the tangential speed of the rotating cylinder, ranging from subsonic to supersonic speed. The following variables in the modeled flow fields are analyzed: temperature, velocity, pressure, density, and stress. The large gradient of velocity near the cylinder is found to create high stress, which leads to rise in temperature. Pressure and density near the cylinder decreases as the speed of the cylinder increases. The proposed simulation method and analysis of air flow can be extended to the modeling of air flow around a Diabolo.

physics.comp-ph↗