April 2020 arXiv papers — page 29

Sergey A. Timoshin, Toyohiko Aiki

The present paper is concerned with a nonlinear partial differential control system subject to a state-dependent and nonconvex control constraint. This system models the dynamics of populations in the vegetation--prey--predator framework and takes account of diffusive and hysteresis effects appearing in the process. We prove the existence of solutions to our

Ramy A. Zeineldin, Mohamed E. Karar, Jan Coburger, Christian R. Wirtz

Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid-Attenuated Inversion Recovery (FLAIR) MRI modality can provide the physician with information about tumor

José Garres-Díaz, Enrique D. Fernández-Nieto, Anne Mangeney, Tomás Morales de Luna

A non-hydrostatic depth-averaged model for dry granular flows is proposed, taking into account vertical acceleration. A variable friction coefficient based on the $\mu(I)$ rheology is considered. The model is obtained from an asymptotic analysis in a local reference system, where the non-hydrostatic contribution is supposed to be small compared to the hydros

Victor F. Los

New exact completely closed homogeneous Generalized Master Equations (GMEs), governing the evolution in time of equilibrium two-time correlation functions for dynamic variables of a subsystem of s particles (s<N) selected from N>>1 particles of a classical many-body system, are obtained These time-convolution and time-convolutionless GMEs differ from the kno

Kawin Ethayarajh

Most NLP datasets are not annotated with protected attributes such as gender, making it difficult to measure classification bias using standard measures of fairness (e.g., equal opportunity). However, manually annotating a large dataset with a protected attribute is slow and expensive. Instead of annotating all the examples, can we annotate a subset of them

Ming Zhang, Jie Jiang

We investigate the stable circular orbits of the spinning test particles around the accelerating Kerr black hole on the equatorial plane. To this end, we first calculate the equations of motion and analyze the parameter space for the particles. We study the effect of the particle's spin and the black hole's acceleration on the conserved angular momentum, con

Rui Wang, Xuemeng Hu, Deyu Zhou, Yulan He

Recent years have witnessed a surge of interests of using neural topic models for automatic topic extraction from text, since they avoid the complicated mathematical derivations for model inference as in traditional topic models such as Latent Dirichlet Allocation (LDA). However, these models either typically assume improper prior (e.g. Gaussian or Logistic

Adrian Groza

In the context of the Covid-19 pandemic, many were quick to spread deceptive information. I investigate here how reasoning in Description Logics (DLs) can detect inconsistencies between trusted medical sources and not trusted ones. The not-trusted information comes in natural language (e.g. "Covid-19 affects only the elderly"). To automatically convert into

Sejeong Kim, Yae Chan Lim, Ryeong Myeong Kim, Johannes E. Fröch

Valley polarization is amongst the most critical attributes of atomically thin materials. However, achieving a high contrast from monolayer transition metal dichalcogenides (TMDs) has so far been challenging. In this work, a giant valley polarization contrast up to 45% from a monolayer WS2 has been achieved at room temperature by using a single chiral plasmo

François Lique, Alexandre Zanchet, Niyazi Bulut, Javier R. Goicoechea

SH$^+$ is a surprisingly widespread molecular ion in diffuse interstellar clouds. There, it plays an important role triggering the sulfur chemistry. In addition, SH$^+$ emission lines have been detected at the UV-illuminated edges of dense molecular clouds, \mbox{so-called} photo-dissociation regions (PDRs), and toward high-mass protostars. An accurate deter

Zygmunt Lalak, Anna Nakonieczna, Łukasz Nakonieczny

In this article we investigated the influence of the gravity induced higher dimensional operators on the issue of vacuum stability in a model containing two interacting scalar fields. As a framework we used the curved spacetime Effective Field Theory (cEFT) applied to the aforementioned system in which one of the scalars is heavy. After integrating out the h

Anubhav Mathur, Surjeet Rajendran, Erwin H. Tanin

The superradiant instability of black hole space-times has been used to place limits on ultra-light bosonic particles. We show that these limits are model dependent. While the initial growth of the mode is gravitational and thus model independent, the ability to place a limit on new particles requires the mode to grow unhindered to a large number density. No

Renato Macedo, Daniel Pellegrino, Joedson Santos

A famous result of S. Kwapie\'{n} asserts that a linear operator from a Banach space to a Hilbert space is absolutely $1$-summing whenever its adjoint is absolutely $q$-summing for some $1\leq q<\infty$; this result was recently extended to Lipschitz operators by Chen and Zheng. In the present paper we show that Kwapie\'{n}'s and Chen--Zheng theorems hold in

Fei Sun

Population dynamics are often affected by sudden environmental perturbations. Parameters of stochastic models are often imprecise due to various uncertainties. In this paper, we formulate a stochastic multimolecular biochemical reaction model that includes L\'{e}vy jumps and interval parameters. Firstly, we prove the existence and uniqueness of the positive

S. H. Han, Z. Z. Zhou, C. Y. Sheng, J. H. Liu

Half-Heusler compounds usually exhibit relatively higher lattice thermal conductivity that is undesirable for thermoelectric applications. Here we demonstrate by first-principles calculations and Boltzmann transport theory that the BiBaK system is an exception, which has rather low thermal conductivity as evidenced by very small phonon group velocity and rel

Matteo M. Wauters, Emanuele Panizon, Glen B. Mbeng, Giuseppe E. Santoro

We propose a reinforcement learning (RL) scheme for feedback quantum control within the quan-tum approximate optimization algorithm (QAOA). QAOA requires a variational minimization for states constructed by applying a sequence of unitary operators, depending on parameters living ina highly dimensional space. We reformulate such a minimum search as a learning

Ivan Kojadinovic, Ghislain Verdier

The aim of sequential change-point detection is to issue an alarm when it is thought that certain probabilistic properties of the monitored observations have changed. This work is concerned with nonparametric, closed-end testing procedures based on differences of empirical distribution functions that are designed to be particularly sensitive to changes in th

Ce Ju, Dashan Gao, Ravikiran Mane, Ben Tan

The success of deep learning (DL) methods in the Brain-Computer Interfaces (BCI) field for classification of electroencephalographic (EEG) recordings has been restricted by the lack of large datasets. Privacy concerns associated with EEG signals limit the possibility of constructing a large EEG-BCI dataset by the conglomeration of multiple small ones for joi

Łukasz Nakonieczny

The effective field theory (EFT) turns out to be an instrument of an immense value in all aspects of modern particle physics being theory, phenomenology or experiment. In the paper I will show how to extend the systematic top down approach to construction of the EFT proposed by Hitoshi Murayama (LBL, Berkeley) and separately by John Ellis (King's Coll. Londo

Malte Schröder, Andreas Bossert, Moritz Kersting, Sebastian Aeffner

Few African countries have reported COVID-19 case numbers above $1\,000$ as of April 18, 2020, with South Africa reporting $3\,034$ cases being hit hardest in Sub-Saharan Africa. Several African countries, especially South Africa, have already taken strong non-pharmaceutical interventions that include physical distancing, restricted economic, educational and

Daniele Marangotto

We consider which is the maximum information measurable from the decay distributions of polarised baryon decays via amplitude analysis in the helicity formalism. We focus in particular on the analytical study of the $\Lambda^+_c \to pK^-\pi^+$ decay distributions, demonstrating that the full information on its decay amplitudes can be extracted from its distr

Èric Pairet, Juan David Hernández, Marc Carreras, Yvan Petillot

Safe autonomous navigation is an essential and challenging problem for robots operating in highly unstructured or completely unknown environments. Under these conditions, not only robotic systems must deal with limited localisation information, but also their manoeuvrability is constrained by their dynamics and often suffer from uncertainty. In order to cope

Rahul Goel, Rajesh Sharma

In the last decade, humanity has faced many different pandemics such as SARS, H1N1, and presently novel coronavirus (COVID-19). On one side, scientists are focusing on vaccinations, and on the other side, there is a need to propose models that can help us in understanding the spread of these pandemics as it can help governmental and other concerned agencies

Peixiang Zhong, Chen Zhang, Hao Wang, Yong Liu

Empathetic conversational models have been shown to improve user satisfaction and task outcomes in numerous domains. In Psychology, persona has been shown to be highly correlated to personality, which in turn influences empathy. In addition, our empirical analysis also suggests that persona plays an important role in empathetic conversations. To this end, we

Feng Guo, Do Sang Kim, Liguo Jiao, Tien-Son Pham

Let $f$ be a real polynomial function with $n$ variables and $S$ be a basic closed semialgebraic set in $\Bbb{R}^n$. In this paper, we are interested in the problem of identifying the type (local minimizer, maximizer or not extremum point) of a given isolated KKT point $x^*$ of $f$ over $S.$ To this end, we investigate some properties of the tangency variety

Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang

Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac structures, is a crucial first step for clinical diagnosis and treatment. However, direct segmentation of LGE-MRIs is challenging due to its attenuated contrast. Since most clinical studies have relied on man

M. Javadi

A systematic treatment of graphene-semiconductor junction is presented. Finite density of states at the Fermi level of graphene leads to exotic electronic properties at graphene-semiconductor interface. Quite generally, the Schottky-Mott limit and the sum rule of barrier heights are violated due to the internal potential of graphene. By merging the principal

Ulaş Özdem

We have applied isovector and isoscalar tensor current to evaluate the tensor form factors of the $ N(1535) \rightarrow N $ transition with the help of the light-cone QCD sum rule method. In numerical computations, have used the most general forms of the interpolating current for the nucleon and the tensor current together with two different sets of the inpu

Hao Cheng, Fanxu Meng, Ke Li, Yuting Gao

Filter is the key component in modern convolutional neural networks (CNNs). However, since CNNs are usually over-parameterized, a pre-trained network always contain some invalid (unimportant) filters. These filters have relatively small $l_{1}$ norm and contribute little to the output (\textbf{Reason}). While filter pruning removes these invalid filters for

Qi She, Fan Feng, Qi Liu, Rosa H. M. Chan

This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Lifelong Object Recognition Challenge) with methods and results from the top $8$ finalists (out of over~$150$ teams). The competition dataset (L)ifel(O)ng (R)obotic V(IS)ion (OpenLORIS) - Object Recognition (OpenLORIS-object) is designed for driving lifelong/continual learning research and

Moritz S. Fischer, Ahmad A. Hujeirat

Relativistic jets are intrinsic phenomena of active galactic nuclei (AGN) and quasars. They have been observed to also emanate from systems containing compact objects, such as white dwarfs, neutron stars and black hole candidates. The corresponding Lorentz factors, $\Gamma$, were found to correlate with the compactness of the central objects. In the case of

Xiang Xu, Yanxiang Zhao

We study some maximum principle preserving and energy stable schemes for the Allen-Cahn-Ohta-Kawasaki model with fixed volume constraint. With the inclusion of a nonlinear term in the Ohta-Kawasaki free energy functional, we show that the Allen-Cahn-Ohta-Kawasaki dynamics is maximum principle preserving. We further design some first order energy stable numer

Zhenzhen Lu, Yongguang Yu, YangQuan Chen, Guojian Ren

In this paper, a mathematical model is proposed to analyze the dynamic behavior of COVID-19. Based on inter-city networked coupling effects, a fractional-order SEIHDR system with the real-data from 23 January to 18 March, 2020 of COVID-19 is discussed. Meanwhile, hospitalized individuals and the mortality rates of three types of individuals (exposed, infecte

Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal, Saptarshi Ghosh

Computing similarity between two legal documents is an important and challenging task in the domain of Legal Information Retrieval. Finding similar legal documents has many applications in downstream tasks, including prior-case retrieval, recommendation of legal articles, and so on. Prior works have proposed two broad ways of measuring similarity between leg

Imre Barany, Peter Frankl

It is well-known that a line can intersect at most $2n-1$ cells of the $n \times n$ chessboard. Here we consider the high dimensional version: how many cells of the $d$-dimensional $n\times \ldots \times n$ box can a hyperplane intersect? We also prove the lattice analogue of the following well-known fact. If $K,L$ are convex bodies in $R^d$ and $K\subset L$

Jiaxing Zhao, Shuzhe Shi, Nu Xu, Pengfei Zhuang

Heavy flavor supplies a chance to constrain and improve the hadronization mechanism. We have established a sequential coalescence model with charm conservation and applied it to the charmed hadron production in heavy ion collisions. The charm conservation enhances the earlier hadron production and suppresses the later production. This relative enhancement (s

Chi-Hua Chen

In recent years, deep neural networks have been applied to obtain high performance of prediction, classification, and pattern recognition. However, the weights in these deep neural networks are difficult to be explained. Although a linear regression method can provide explainable results, the method is not suitable in the case of input interaction. Therefore

Donya Nojavanzadeh, Zhenwei Liu, Ali Saberi, Anton A. Stoorvogel

This paper studies output synchronization problems for heterogeneous networks of continuous- or discrete-time right-invertible linear agents in presence of unknown, non-uniform and arbitrarily large input delay based on localized information exchange. It is assumed that all the agents are introspective, meaning that they have access to their own local measur

Weijie Zheng, Huanhuan Chen, Xin Yao

In real-world applications, many optimization problems have the time-linkage property, that is, the objective function value relies on the current solution as well as the historical solutions. Although the rigorous theoretical analysis on evolutionary algorithms has rapidly developed in recent two decades, it remains an open problem to theoretically understa

Xinyue Zheng, Peng Wang, Qigang Wang, Zhongchao Shi

Prior work in standardized science exams requires support from large text corpus, such as targeted science corpus fromWikipedia or SimpleWikipedia. However, retrieving knowledge from the large corpus is time-consuming and questions embedded in complex semantic representation may interfere with retrieval. Inspired by the dual process theory in cognitive scien

Canwen Xu, Jiaxin Pei, Hongtao Wu, Yiyu Liu

Recently, large-scale datasets have vastly facilitated the development in nearly all domains of Natural Language Processing. However, there is currently no cross-task dataset in NLP, which hinders the development of multi-task learning. We propose MATINF, the first jointly labeled large-scale dataset for classification, question answering and summarization.

Ye Xue, Yifei Shen, Vincent Lau, Jun Zhang

Massive MIMO has been regarded as a key enabling technique for 5G and beyond networks. Nevertheless, its performance is limited by the large overhead needed to obtain the high-dimensional channel information. To reduce the huge training overhead associated with conventional pilot-aided designs, we propose a novel blind data detection method by leveraging the

Weijie Yuan, Fan Liu, Christos Masouros, Jinhong Yuan

In this paper, we develop a predictive beamforming scheme based on the dual-functional radar-communication (DFRC) technique, where the road-side units estimates the motion parameters of vehicles exploiting the echoes of the DFRC signals. Compared to the conventional feedback-based beam tracking approaches, the proposed method can reduce the signaling overhea

Su Zhu, Ruisheng Cao, Kai Yu

Natural language understanding (NLU) converts sentences into structured semantic forms. The paucity of annotated training samples is still a fundamental challenge of NLU. To solve this data sparsity problem, previous work based on semi-supervised learning mainly focuses on exploiting unlabeled sentences. In this work, we introduce a dual task of NLU, semanti

Wenbo Li, Yaodong Cui, Yintao Ma, Xingxin Chen

In this paper, we introduce a new dataset, the driver emotion facial expression (DEFE) dataset, for driver spontaneous emotions analysis. The dataset includes facial expression recordings from 60 participants during driving. After watching a selected video-audio clip to elicit a specific emotion, each participant completed the driving tasks in the same drivi

Federico Binda, Doosung Park, Paul Arne Østvær

In this work we develop a theory of motives for logarithmic schemes over fields in the sense of Fontaine, Illusie, and Kato. Our construction is based on the notion of finite log correspondences, the dividing Nisnevich topology on log schemes, and the basic idea of parameterizing homotopies by $\overline{\square}$, i.e. the projective line with respect to it

Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky

Many natural language processing and information retrieval problems can be formalized as the task of semantic matching. Existing work in this area has been largely focused on matching between short texts (e.g., question answering), or between a short and a long text (e.g., ad-hoc retrieval). Semantic matching between long-form documents, which has many impor

Peter Bonventre, Luis Alexandre Pereira

We give an explicit description of the rigidification of an $\infty$-operad as a simplicial operad. This description is based on the notion of dendroidal necklace, extending work of Dugger and Spivak from the categorical context to the operadic context, although with a different framework, which relates constructions involving necklaces to a standard factori

Hiroshi Tsuji

In this paper, we study the symmetrized Talagrand inequality that was proved by Fathi and has a connection with the Blaschke-Santal\'{o} inequality in convex geometry. As corollaries of our results, we have several refined functional inequalities under some conditions. We also give an alternative proof of Fathi's symmetrized Talagrand inequality on the real

Wuhao Chen, Dmitrii V. Semenok, Alexander G. Kvashnin, Ivan A. Kruglov

Following the discovery of high-temperature superconductivity in the La-H system, where for the recently discovered fcc-LaH10 a record critical temperature Tc = 250 K was achieved [Drozdov et al., Nature, 569, 528 (2019) and Somayazulu et al., Phys. Rev. Lett. 122, 027001 (2019)], we studied the formation of new chemical compounds in the barium-hydrogen syst

Xiaoqing Geng, Xiwen Chen, Kenny Q. Zhu, Libin Shen

Few-shot relation classification seeks to classify incoming query instances after meeting only few support instances. This ability is gained by training with large amount of in-domain annotated data. In this paper, we tackle an even harder problem by further limiting the amount of data available at training time. We propose a few-shot learning framework for

Yichen Zhu, Cheng Li, David B. Dunson

Classification algorithms face difficulties when one or more classes have limited training data. We are particularly interested in classification trees, due to their interpretability and flexibility. When data are limited in one or more of the classes, the estimated decision boundaries are often irregularly shaped due to the limited sample size, leading to p

Zitong Yu, Xiaobai Li, Xuesong Niu, Jingang Shi

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e.g., remote healthcare). Existing end-to-end rPPG and heart rate (HR) measurement methods from facial videos are vulnerable to the less-constrained scenarios (e.g., with head movement and bad illumination). In this lett

Yuntian Chen, Dongxiao Zhang

In this study, we propose an ensemble long short-term memory (EnLSTM) network, which can be trained on a small dataset and process sequential data. The EnLSTM is built by combining the ensemble neural network (ENN) and the cascaded long short-term memory (C-LSTM) network to leverage their complementary strengths. In order to resolve the issues of over-conver

Tript Sharma, Utkarsh Upadhyay, Ganesh Bagler

Cultures across the world are distinguished by the idiosyncratic patterns in their cuisines. These cuisines are characterized in terms of their substructures such as ingredients, cooking processes and utensils. A complex fusion of these substructures intrinsic to a region defines the identity of a cuisine. Accurate classification of cuisines based on their c

Ezra Day-Roberts, Rafael M. Fernandes, Alex Kamenev

The electronic spectrum of the Penrose rhombus quasicrystal exhibits a macroscopic fraction of exactly degenerate zero energy states. In contrast to other bipartite quasicrystals, such as the kite-and-dart one, these zero energy states cannot be attributed to a global mismatch $\Delta n$ between the number of sites in the two sublattices that form the quasic

Krzysztof Dȩbicki, Xiaofan Peng

We investigate asymptotics of the tail distribution of sojourn time $$ \int_0^T \mathbb{I}(X(t)> u)dt, $$ as $u\to\infty$, where $X$ is a centered stationary Gaussian process and $T$ is an independent of $X$ nonnegative random variable. The heaviness of the tail distribution of $T$ impacts the form of the asymptotics, leading to four scenarios: the case of i

Dara Bahri, Heinrich Jiang, Maya Gupta

Modern machine learning models are often trained on examples with noisy labels that hurt performance and are hard to identify. In this paper, we provide an empirical study showing that a simple $k$-nearest neighbor-based filtering approach on the logit layer of a preliminary model can remove mislabeled training data and produce more accurate models than many

Li Fu, Xiaoxiao Li, Libo Zi

Modeling unit and model architecture are two key factors of Recurrent Neural Network Transducer (RNN-T) in end-to-end speech recognition. To improve the performance of RNN-T for Mandarin speech recognition task, a novel transformer transducer with the combination architecture of self-attention transformer and RNN is proposed. And then the choice of different

I Gede Mahendra Darmawiguna, Gede Aditra Pradnyana, I Gede Partha Sindu, I Putu Prayoga Susila Karimawan

The aim of this project is the development of Virtual Reality Application in order to document one kind of Balinese cultural heritages which are Temples. The Bali Temple VR application will allow users to do the virtual tour and experience the landscape of the temples and all objects inside the temples. The application gives on-site tour guide using virtual

Aji Resindra Widya, Yusuke Monno, Masatoshi Okutomi, Sho Suzuki

Gastric endoscopy is a standard clinical process that enables medical practitioners to diagnose various lesions inside a patient's stomach. If any lesion is found, it is very important to perceive the location of the lesion relative to the global view of the stomach. Our previous research showed that this could be addressed by reconstructing the whole stomac

Saeed Anwar, Cong Phuoc Huynh, Fatih Porikli

We propose to learn a fully-convolutional network model that consists of a Chain of Identity Mapping Modules and residual on the residual architecture for image denoising. Our network structure possesses three distinctive features that are important for the noise removal task. Firstly, each unit employs identity mappings as the skip connections and receives

Ceren B. Dağ, Kai Sun

Dynamical detection of quantum phases and phase transitions (QPT) in quenched systems with experimentally convenient initial states is a topic of interest from both theoretical and experimental perspectives. Quenched from polarized states, longitudinal magnetization decays exponentially to zero in time for the short-range transverse-field Ising model (TFIM)

Saeed Anwar, Nick Barnes, Lars Petersson

Deep convolutional neural networks perform better on images containing spatially invariant degradations, also known as synthetic degradations; however, their performance is limited on real-degraded photographs and requires multiple-stage network modeling. To advance the practicability of restoration algorithms, this paper proposes a novel single-stage blind

Jushaan Kalra, Devansh Batra, Nirav Diwan, Ganesh Bagler

The availability of an accurate nutrition profile of recipes is an important feature for food databases with several applications including nutritional assistance, recommendation systems, and dietary analytics. Often in online databases, recipes are obtained from diverse sources in an attempt to maximize the number of recipes and variety of the dataset. This

Doowon Koh, Thang Pham

In this paper, we prove a new point-sphere incidence bound in vector spaces over finite fields. More precisely, let $P$ be a set of points and $S$ be a set of spheres in $\mathbb{F}_q^d$. Suppose that $|P|, |S|\le N$, we prove that the number of incidences between $P$ and $S$ satisfies \[I(P, S)\le N^2q^{-1}+q^{\frac{d-1}{2}}N,\] under some conditions on $d,

Zhijie Fan, Gia-Wei Chern, Shi-Zeng Lin

We study superconductivity in a family of one dimensional incommensurate system with $s$-wave pairing interaction. The incommensurate potential can alter the spatial characteristics of electrons in the normal state, leading to either extended, critical, or localized wave functions. We find that superconductivity is significantly enhanced when the electronic

Tript Sharma, Utkarsh Upadhyay, Jushaan Kalra, Sakshi Arora

Cultures across the world have evolved to have unique patterns despite shared ingredients and cooking techniques. Using data obtained from RecipeDB, an online resource for recipes, we extract patterns in 26 world cuisines and further probe for their inter-relatedness. By application of frequent itemset mining and ingredient authenticity we characterize the q

Daris Samart, Phongpichit Channuie

In this work, we study the possible existence of gravitational phase transition from AdS to dS asymptotic geometries in Einstein-Gauss-Bonnet gravity by adding the Maxwell one-form field ($A_\mu$) and the Kalb-Ramond two-form field ($B_{\mu\nu}$) as impurity substitutions. The phase transitions proceed via the bubble nucleation of spherical thin-shells descr

Tong Zhou

Requirements are investigated in this paper for each descriptor form subsystem, with which a causal/impulse free networked dynamic system (NDS) can be constructed. For this purpose, a matrix rank based necessary and sufficient condition is at first derived for the causality/impulse freeness of an NDS, in which the associated matrix depends affinely on subsys

Daniel Severo, Giuliano Netto Flores Cruz, Alcides Carlos de Araújo, André Marques dos Santos

This technical note aims to provide a brief introduction to the projection models used by the group to project future scenarios for states and municipalities in real-time, according to the disease's behavior in previous days. However, the parameters can be modified by the user to design customized scenarios. The proposed model begins with the calculation of

Xingyi Cheng, Weidi Xu, Kunlong Chen, Shaohua Jiang

Chinese Spelling Check (CSC) is a task to detect and correct spelling errors in Chinese natural language. Existing methods have made attempts to incorporate the similarity knowledge between Chinese characters. However, they take the similarity knowledge as either an external input resource or just heuristic rules. This paper proposes to incorporate phonologi

Rui Peng, David Navarro-Alarcon, Victor Wu, Wen Yang

In this paper, in order to pursue high-efficiency robotic arc welding tasks, we propose a method based on point cloud acquired by an RGB-D sensor. The method consists of two parts: welding groove detection and 3D welding trajectory generation. The actual welding scene could be displayed in 3D point cloud format. Focusing on the geometric feature of the weldi

Amin Ebrahimi, Chris R. Kleijn, Ian M. Richardson

The high degree of uncertainty and conflicting literature data on the value of the permeability coefficient (also known as the mushy zone constant), which aims to dampen fluid velocities in the mushy zone and suppress them in solid regions, is a critical drawback when using the fixed-grid enthalpy-porosity technique for modelling non-isothermal phase-change

Yorie Nakahira, Andres Ferragut, Adam Wierman

Many modern schedulers can dynamically adjust their service capacity to match the incoming workload. At the same time, however, unpredictability and instability in service capacity often incur operational and infrastructure costs. In this paper, we seek to characterize optimal distributed algorithms that maximize the predictability, stability, or both when s

Ali Borji

I introduce a very simple method to defend against adversarial examples. The basic idea is to raise the slope of the ReLU function at the test time. Experiments over MNIST and CIFAR-10 datasets demonstrate the effectiveness of the proposed defense against a number of strong attacks in both untargeted and targeted settings. While perhaps not as effective as t

Tao Luo, Yang Xiang, Nung Kwan Yip

It is well known that elastic effects can cause surface instability. In this paper, we analyze a one-dimensional discrete system which can reveal pattern formation mechanism resembling the "step-bunching" phenomena for epitaxial growth on vicinal surfaces. The surface steps are subject to long-range pairwise interactions taking the form of a general Lennard-

Shijie Xie, Xiaohui Liu, Qiuxia Lu, Sun Yin

For Holstein model with Rashba spin-orbit coupling (SOC) we establish the nonlinear Schr\"odinger equations and obtain exact soliton solution analytically. It is found that the soliton is spin polarized determined both by the SOC and the electron-phonon (e-ph) interaction. The soliton can be used to describe the spin transport or spin current in organic semi

Sheng Shi, Yangzhou Du, Wei Fan

While deep learning makes significant achievements in Artificial Intelligence (AI), the lack of transparency has limited its broad application in various vertical domains. Explainability is not only a gateway between AI and real world, but also a powerful feature to detect flaw of the models and bias of the data. Local Interpretable Model-agnostic Explanatio

Menglin Jia, Mengyun Shi, Mikhail Sirotenko, Yin Cui

In this work we explore the task of instance segmentation with attribute localization, which unifies instance segmentation (detect and segment each object instance) and fine-grained visual attribute categorization (recognize one or multiple attributes). The proposed task requires both localizing an object and describing its properties. To illustrate the vari

Chao Min, Qingyu Chen, Erjia Yan, Yi Bu

Citation analysis, as a tool for quantitative studies of science, has long emphasized direct citation relations, leaving indirect or high order citations overlooked. However, a series of early and recent studies demonstrate the existence of indirect and continuous citation impact across generations. Adding to the literature on high order citations, we introd

Baoyu Jing, Zeya Wang, Eric Xing

Chest X-Ray (CXR) images are commonly used for clinical screening and diagnosis. Automatically writing reports for these images can considerably lighten the workload of radiologists for summarizing descriptive findings and conclusive impressions. The complex structures between and within sections of the reports pose a great challenge to the automatic report

Weiming Xiang, Hoang-Dung Tran, Xiaodong Yang, Taylor T. Johnson

The vulnerability of artificial intelligence (AI) and machine learning (ML) against adversarial disturbances and attacks significantly restricts their applicability in safety-critical systems including cyber-physical systems (CPS) equipped with neural network components at various stages of sensing and control. This paper addresses the reachable set estimati

J. Pace VanDevender, Ian Shoemaker, T. Sloan, Aaron P. VanDevender

Quark nuggets are a candidate for dark matter consistent with the Standard Model. Previous models of quark nuggets have investigated properties arising from their being composed of strange, up, and down quarks and have not included any effects caused by their self-magnetic field. However, Tatsumi found that the core of a magnetar star may be a quark nugget i

Prakirt Jhunjhunwala, Siva Theja Maguluri

Motivated by applications in data center networks, in this paper, we study the problem of scheduling in an input queued switch. While throughput maximizing algorithms in a switch are well-understood, delay analysis was developed only recently. It was recently shown that the well-known MaxWeight algorithm achieves optimal scaling of mean queue lengths in stea

James Allworth, Lloyd Windrim, Jeffrey Wardman, Daniel Kucharski

This paper presents the initial stages in the development of a deep learning classifier for generalised Resident Space Object (RSO) characterisation that combines high-fidelity simulated light curves with transfer learning to improve the performance of object characterisation models that are trained on real data. The classification and characterisation of RS

Yanan Wang, Jun Yan, Jianlu Zhang

For any compact connected manifold $M$, we consider the generalized contact Hamiltonian $H(x,p,u)$ defined on $T^*M\times\mathbb R$ which is conex in $p$ and monotonically increasing in $u$. Let $u_\epsilon^-:M\rightarrow\mathbb R$ be the viscosity solution of the parametrized contact Hamilton-Jacobi equation \[ H(x,\partial_x u_\epsilon^-(x),\epsilon u_\eps

M. Ganesh, Frances Y. Kuo, Ian H. Sloan

We propose and analyze a quasi-Monte Carlo (QMC) algorithm for efficient simulation of wave propagation modeled by the Helmholtz equation in a bounded region in which the refractive index is random and spatially heterogenous. Our focus is on the case in which the region can contain multiple wavelengths. We bypass the usual sign-indefiniteness of the Helmholt

Lang Xie, Xiang-Gao Wang, Song-Mei Qin, WeiKang Zheng

Gamma-ray burst (GRB) 150910A was detected by {\it Swift}/BAT, and then rapidly observed by {\it Swift}/XRT, {\it Swift}/UVOT, and ground-based telescopes. We report Lick Observatory spectroscopic and photometric observations of GRB~150910A, and we investigate the physical origins of both the optical and X-ray afterglows, incorporating data obtained with BAT

Ke-Sheng Sun, Sheng-Kai Cui, Wei Li, Hai-Bin Zhang

We analyze the lepton flavor violating process $\mu-e$ conversion in the framework of the minimal R-symmetric supersymmetric standard model. The theoretical predictions are determined by considering the experimental constraint on parameter $\delta^{12}$ from the lepton flavor violating decay $\mu\rightarrow e \gamma$. The numerical results show that $\gamma$

Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian

Common methods for interpreting neural models in natural language processing typically examine either their structure or their behavior, but not both. We propose a methodology grounded in the theory of causal mediation analysis for interpreting which parts of a model are causally implicated in its behavior. It enables us to analyze the mechanisms by which in

Daniel Haehn, Loraine Franke, Fan Zhang, Suheyla Cetin Karayumak

Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graphical and h

S. B. Dubovichenko, N. A. Burkova, A. V. Dzhazairov-Kakhramanov, A. Yertaiuly

The total cross sections of the neutron radiative capture on 12B at astrophysical energies to the ground state of 13B have been calculated in the energy range of 10E-8 to 10 MeV within the framework of a modified potential cluster model with the classification of orbital states according to Young diagrams. Reaction rates in the temperature range of 0.01 to 1

Iqtadar Hussain, Amir Anees, Temadher Alassiry Al-Maadeed, M. T. Mustafa

With the tremendous benefits of internet and advanced communications, there is a serious threat from the data security perspective. There is a need of secure and robust encryption algorithm that can be implemented on each and diverse software and hardware platforms. Also, in block symmetric encryption algorithms, substitution boxes are the most vital part. I

Fanfan Li, Zhenlai Han, Ting-Hui Yang

In this work, we investigate the system of three species ecological model involving one predator-prey subsystem coupling with a generalist predator with negative effect on the prey. Without diffusive terms, all global dynamics of its corresponding reaction equations are proved analytically for all classified parameters. With diffusive terms, the transitions

Dara Bahri, Yi Tay, Che Zheng, Donald Metzler

Work in information retrieval has traditionally focused on ranking and relevance: given a query, return some number of results ordered by relevance to the user. However, the problem of determining how many results to return, i.e. how to optimally truncate the ranked result list, has received less attention despite being of critical importance in a range of a

Shulin Chen, Ying Zhang, Jinjin Zhao, Zhou Mi

Organic-inorganic hybrid perovskites (OIHPs) have attracted extensive research interest as a promising candidate for efficient and inexpensive solar cells. Transmission electron microscopy characterizations that can benefit the fundamental understanding and the degradation mechanism are widely used for these materials. However, their sensitivity to the elect

Yi Xie, Zhuohang Li, Cong Shi, Jian Liu

Recently, the vulnerability of DNN-based audio systems to adversarial attacks has obtained the increasing attention. However, the existing audio adversarial attacks allow the adversary to possess the entire user's audio input as well as granting sufficient time budget to generate the adversarial perturbations. These idealized assumptions, however, makes the

Charles Herrmann, Richard Strong Bowen, Neal Wadhwa, Rahul Garg

Autofocus is an important task for digital cameras, yet current approaches often exhibit poor performance. We propose a learning-based approach to this problem, and provide a realistic dataset of sufficient size for effective learning. Our dataset is labeled with per-pixel depths obtained from multi-view stereo, following "Learning single camera depth estima

Charles Baker, Huy The Nguyen

In this paper, we prove convergence of the high codimension mean curvature flow in the sphere to either a round point or a totally geodesic sphere assuming a pinching condition between the norm squared of the second fundamental form and the norm squared of the mean curvature and the background curvature of the sphere. We show that this pinching is sharp for