September 2019 arXiv papers — page 22

Koretaka Yuge

Microscopic structures for fcc-based quaternary high-entropy alloys (HEA) in thermodynamically equilibrium state is examined based on first-principles (FP) calculation combined with our recently-developed theoretical approach. We find that (i) hierarchical ordering tendency for whole quaternary, and ternary and binary subsystems for the present five HEAs can

Md Sazzad Hossain, Andrew P Paplinski, John M Betts

In this paper, we propose a Dual Focal Loss (DFL) function, as a replacement for the standard cross entropy (CE) function to achieve a better treatment of the unbalanced classes in a dataset. Our DFL method is an improvement on the recently reported Focal Loss (FL) cross-entropy function, which proposes a scaling method that puts more weight on the examples

David Gerard-Varet

We present a gentle approach to the justification of effective media approximations, for PDE's set outside the union of $n \gg 1$ spheres with low volume fraction. To illustrate our approach, we consider three classical examples: the derivation of the so-called strange term, made popular by Cioranescu and Murat, the derivation of the Brinkman term in the Sto

Philip Bille, Inge Li Gørtz, Teresa Anna Steiner

Given a string $S$ of length $n$, the classic string indexing problem is to preprocess $S$ into a compact data structure that supports efficient subsequent pattern queries. In this paper we consider the basic variant where the pattern is given in compressed form and the goal is to achieve query time that is fast in terms of the compressed size of the pattern

Naomi Kirshner, Alex Samorodnitsky

Let $p \ge 2$. We improve the bound $\frac{\|f\|_p}{\|f\|_2} \le (p-1)^{s/2}$ for a polynomial $f$ of degree $s$ on the boolean cube $\{0,1\}^n$, which comes from hypercontractivity, replacing the right hand side of this inequality by an explicit bivariate function of $p$ and $s$, which is smaller than $(p-1)^{s/2}$ for any $p > 2$ and $s > 0$. We show the n

Leonid Kitchatinov, Alexander Nepomnyashchikh

Asteroseismology has revealed that cores of red giants rotate about one order of magnitude faster than their convective envelopes. This paper attempts an explanation for this rotational state in terms of the theory of angular momentum transport in stellar convection zones. A differential rotation model based on the theory is applied to a sequence of evolutio

Joel C. Zinn, Dennis Stello, Daniel Huber, Sanjib Sharma

We present the Bayesian Asteroseismology data Modeling (BAM) pipeline, an automated asteroseismology pipeline that returns global oscillation parameters and granulation parameters from the analysis of photometric time-series. BAM also determines if a star is likely to be a solar-like oscillator. We have designed BAM to specially process ${\it K2}$ light curv

Guilin Li, Xing Zhang, Zitong Wang, Matthias Tan

Recently, the efficiency of automatic neural architecture design has been significantly improved by gradient-based search methods such as DARTS. However, recent literature has brought doubt to the generalization ability of DARTS, arguing that DARTS performs poorly when the search space is changed, i.e, when different set of candidate operators are used. Regu

Jean-Christophe Bourin, Jingjing Shao

We study various convex functions on $R^n$ associated with positive definite matrices. This yiels some exotic Holder matrix inequalities.

Ion Necoara, Angelia Nedich

This paper deals with the convex feasibility problem, where the feasible set is given as the intersection of a (possibly infinite) number of closed convex sets. We assume that each set is specified algebraically as a convex inequality, where the associated convex function is general (possibly non-differentiable). For finding a point satisfying all the convex

Z. F. Li, S. H. Hua, X. Cheng, M. D. Ding

During non-flaring times, the radio flux of the Sun at the wavelength of a few centimeters to several tens of centimeters mostly originates from the thermal bremsstrahlung emission, very similar to the EUV radiation. Owing to such a proximity, it is feasible to investigate the relationship between the EUV emission and radio emission in a quantitative way. In

E. T. Akhmedov, O. Diatlyk, A. G. Semenov

We consider 2D Yukawa theory in the strong scalar wave background. We use operator and functional formalisms. In the latter the Schwinger--Keldysh diagrammatic technique is used to calculate retarded, advanced and Keldysh propagators. We use simplest states in the two formalisms in question, which appear to be different from each other. As the result two Kel

Yongchao Rao, Xiangmei Duan

Single atom catalysts (SACs) based on 2D materials are identified to be efficient in many catalytic reaction. In this work, the catalytic performance of Pd/Pt embedded planar carbon nitride (CN) for CO oxidation, has been investigated via spin$-$polarized density functional theory calculations. We find that Pd/Pt can be firmly anchored in the porous CN monol

Sören Christensen, Kristoffer Lindensjö

For a discrete time Markov chain and in line with Strotz' consistent planning we develop a framework for problems of optimal stopping that are time-inconsistent due to the consideration of a non-linear function of an expected reward. We consider pure and mixed stopping strategies and a (subgame perfect Nash) equilibrium. We provide different necessary and su

Yohsuke T. Fukai, Kazumasa A. Takeuchi

We study fluctuations of interfaces in the Kardar-Parisi-Zhang (KPZ) universality class with curved initial conditions. By simulations of a cluster growth model and experiments of liquid-crystal turbulence, we determine the universal scaling functions that describe the height distribution and the spatial correlation of the interfaces growing outward from a r

Rung-Yu Tseng, Tao-Wei Wang, Szu-Wei Fu, Chia-Ying Lee

Speech perception is key to verbal communication. For people with hearing loss, the capability to recognize speech is restricted, particularly in a noisy environment or the situations without visual cues, such as lip-reading unavailable via phone call. This study aimed to understand the improvement of vocoded speech intelligibility in cochlear implant (CI) s

Giovanni Molica Bisci, Dušan D. Repovš

The purpose of this paper is to study the existence of weak solutions for some classes of one-parameter subelliptic gradient-type systems involving a Sobolev-Hardy potential defined on an unbounded domain $\Omega_\psi$ of the Heisenberg group $\mathbb{H}^n=\mathbb{C}^n\times \mathbb{R}$ ($n\geq 1$) whose geometrical profile is determined by two real positive

Xuan-He Wang, Yue Jiang, Tianhong Wang, Xiao-Ze Tan

In this paper, the dilepton electromagnetic decays $\chi_{cJ}(1P) \to J/\psi e^+e^-$ and $\chi_{cJ}(1P) \to J\psi \mu^+\mu^-$, where $\chi_{cJ}$ denotes $\chi_{c0}$, $\chi_{c1}$ and $\chi_{c2}$, are calculated systematically in the improved Bethe-Salpeter method. The numerical results of decay widths and the invariant mass distributions of the final lepton p

German Enciso, Jinsu Kim

Stochastic models of chemical reaction networks are an important tool to describe and analyze noise effects in cell biology. When chemical species and reaction rates in a reaction system have different orders of magnitude, the associated stochastic system is often modeled in a multiscale regime. It is known that multiscale models can be approximated with a r

Haseeb Nazki, Sook Yoon, Alvaro Fuentes, Dong Sun Park

Acquisition of data in task-specific applications of machine learning like plant disease recognition is a costly endeavor owing to the requirements of professional human diligence and time constraints. In this paper, we present a simple pipeline that uses GANs in an unsupervised image translation environment to improve learning with respect to the data distr

Mateusz Szatkowski, Jan Masajada, Ireneusz Augustyniak, Klaudia Nowacka

The composite optical beams being a result of superposition, are a promising way to study the orbital angular momentum and its effects. Their wide range of applications makes them attractive and easily available due to the growing interest in the Spatial Light Modulators (SLM). In this paper, we present a simple method for generating composite vortex pattern

Yue Wang, Tong Wu, Yunlong Wang, Gao Wang

Models have been proposed to extract temporal patterns from longitudinal electronic health records (EHR) for clinical predictive models. However, the common relations among patients (e.g., receiving the same medical treatments) were rarely considered. In this paper, we propose to learn patient similarity features as phenotypes from the aggregated patient-med

Natalie Yu-Hsien Wang, Hsiao-Lan Sharon Wang, Tao-Wei Wang, Szu-Wei Fu

The combined electric and acoustic stimulation (EAS) has demonstrated better speech recognition than conventional cochlear implant (CI) and yielded satisfactory performance under quiet conditions. However, when noise signals are involved, both the electric signal and the acoustic signal may be distorted, thereby resulting in poor recognition performance. To

Shao-Wen Wei, Yu-Xiao Liu

The numerical study indicates that there exists a relation between the quasinormal modes and the Davies point for a black hole. In this paper, we analytically study this relation for the charged Reissner-Nordstr\"{o}m black holes in asymptotically flat and dS spacetimes. In the eikonal limit, the angular velocity $\Omega$ and the Lyapunov exponent $\lambda$

Daisuke Kazukawa

We investigate the relation between the concentration and the product of metric measure spaces. We have the natural question whether, for two concentrating sequences of metric measure spaces, the sequence of their product spaces also concentrates. A partial answer is mentioned in Gromov's book. We obtain a complete answer for this question.

Chang-Le Liu, Sze-Wei Fu, You-Jin Li, Jen-Wei Huang

In recent years, waveform-mapping-based speech enhancement (SE) methods have garnered significant attention. These methods generally use a deep learning model to directly process and reconstruct speech waveforms. Because both the input and output are in waveform format, the waveform-mapping-based SE methods can overcome the distortion caused by imperfect pha

Sandip Das, Krishna Kumar

We present results of numerical investigation on thermal flux in Rayleigh-B\'{e}nard magnetoconvection in the presence of a uniform vertical magnetic field. We have studied thermal flux in different viscous fluids with a range of Prandtl number ($0.1 \le \mathrm{Pr} < 6.5$) and a range of Chandrasekhar number ($50 \le \mathrm{Q} \le 2.5 \times 10^4$). The po

Tengyu Xu, Shaofeng Zou, Yingbin Liang

Gradient-based temporal difference (GTD) algorithms are widely used in off-policy learning scenarios. Among them, the two time-scale TD with gradient correction (TDC) algorithm has been shown to have superior performance. In contrast to previous studies that characterized the non-asymptotic convergence rate of TDC only under identical and independently distr

Natsumi Ikeno, Jorgivan M. Dias, Wei-Hong Liang, Eulogio Oset

We evaluate ratios of the $\chi_{c1}$ decay rates to $\eta$ ($\eta', K^-$) and one of the $f_0(1370)$, $f_0(1710)$, $f_2(1270)$, $f_2'(1525)$, $K^{*}_2(1430)$ resonances, which in the local hidden gauge approach are dynamically generated from the vector-vector interaction. With the simple assumption that the $\chi_{c1}$ is a singlet of SU(3), and the input f

Renata Jora, Salah Nasri

We determine the non-perturbative corrections to the gauge coupling constant and the topological charge in the Yang Mills theory. The method makes no explicit use of instanton calculations but instead relies on boundary properties of the quantum partition function. The approach may offer important clues regarding the behavior of the coupling constant and the

Avinash Khare, Avadh Saxena

We present a wide class of potentials which admit kinks and corresponding mirror kinks with either a power law or an exponential tail at the two extreme ends and a power-tower form of tails at the two neighbouring ends, i.e. of the forms $ette$ or $pttp$ where $e, p$ and $t$ denote exponential, power law and power-tower tail, respectively. We analyze kink st

Ruxandra Stoean, Dominic Iliescu, Catalin Stoean

The present paper puts forward an incipient study that uses a traditional segmentation method based on Zernike moments for extracting significant features from frames of fetal echocardiograms from first trimester color Doppler examinations. A distance based approach is then used on the obtained indicators to classify frames of three given categories that sho

Jie Song, Yixin Chen, Xinchao Wang, Chengchao Shen

Exploring the transferability between heterogeneous tasks sheds light on their intrinsic interconnections, and consequently enables knowledge transfer from one task to another so as to reduce the training effort of the latter. In this paper, we propose an embarrassingly simple yet very efficacious approach to estimating the transferability of deep networks,

Subir K. Das, Koyel Das, Nalina Vadakkayil, Saikat Chakraborty

Following quenches of initial configurations having long range spatial correlations, prepared at the demixing critical point, to points inside the miscibility gap, we study aging phenomena in solid binary mixtures. Results on the decay of the two-time order-parameter autocorrelation functions, obtained from Monte Carlo simulations of the two-dimensional Isin

S. V. Remizov, A. A. Zhukov, W. V. Pogosov, Yu. E. Lozovik

We propose a realization of two remarkable effects of Dicke physics in quantum simulation of light-matter many-body interactions with artificial quantum systems. These effects are a superradiant decay of an ensemble of qubits and the opposite radiation trapping effect. We show that both phenomena coexist in the crossover regime of a "moderately bad" single-m

Po-Ya Hsu

Demystifying effective connectivity among neuronal populations has become the trend to understand the brain mechanisms of Parkinson's disease, schizophrenia, mild traumatic brain injury, and many other unlisted neurological diseases. Dynamic modeling is a state-of-the-art approach to explore various connectivities among neuronal populations corresponding to

Hong Wang, Christfried Focke, Rob Sylvester, Nilesh Mishra

Modelling relations between multiple entities has attracted increasing attention recently, and a new dataset called DocRED has been collected in order to accelerate the research on the document-level relation extraction. Current baselines for this task uses BiLSTM to encode the whole document and are trained from scratch. We argue that such simple baselines

Hongchao Zhao, Zhe Liu, Zhiqiang Li, Shunbo Zhou

Existing works on control of tractor-trailers systems only consider the kinematics model without taking dynamics into account. Also, most of them treat the issue as a pure control theory problem whose solutions are difficult to implement. This paper presents a trajectory tracking control approach for a full-scale industrial tractor-trailers vehicle composed

Ali Rahmati, Seyyedali Hosseinalipour, Yavuz Yapici, Xiaofan He

The deployment of unmanned aerial vehicles (UAVs) is proliferating as they are effective, flexible and cost-efficient devices for a variety of applications ranging from natural disaster recovery to delivery of goods. We investigate a transmission mechanism aiming to improve the data rate between a base station (BS) and a user equipment through deploying mult

Roman Rausch, Michael Potthoff, Norio Kawakami

We present a novel pairing mechanism for electrons, mediated by magnons. These paired bound states are termed ``magnetic doublons''. Applying numerically exact techniques (full diagonalization and the density-matrix renormalization group, DMRG) to the Kondo lattice model at strong exchange coupling $J$ for different fillings and magnetic configurations, we d

Xueting Li, Sifei Liu, Shalini De Mello, Xiaolong Wang

This paper proposes to learn reliable dense correspondence from videos in a self-supervised manner. Our learning process integrates two highly related tasks: tracking large image regions \emph{and} establishing fine-grained pixel-level associations between consecutive video frames. We exploit the synergy between both tasks through a shared inter-frame affini

Elisa C. Baek, Mason A. Porter, Carolyn Parkinson

Although social neuroscience is concerned with understanding how the brain interacts with its social environment, prevailing research in the field has primarily considered the human brain in isolation, deprived of its rich social context. Emerging work in social neuroscience that leverages tools from network analysis has begun to pursue this issue, advancing

David Glick, Florian J. Boge

Tim Maudlin has claimed that EPR's Reality Criterion is analytically true. We argue that it is not. Moreover, one may be a subjectivist about quantum probabilities without giving up on objective physical reality. Thus, would-be detractors must reject QBism and other epistemic approaches to quantum theory on other grounds.

Maxim Durach, Robert Williamson, Morgan Laballe, Thomas Mulkey

We describe novel topological phases of iso-frequency k-space surfaces in bi-anisotropic optical materials - tri- and tetra-hyperbolic materials, which are induced by introduction of chirality. This completes the classification of iso-frequency topologies for bi-anisotropic materials, since as we show all optical materials belong to one of the following topo

Faizuddin Ahmed, Bidyut Bikash Hazarika, Debojit Sarma

In this paper, we present a type D, non-vanishing cosmological constant, vacuum solution of the Einstein's field equations, extension of an axially symmetric, asymptotically flat vacuum metric with a curvature singularity. The space-time admits closed time-like curves (CTCs) that appear after a certain instant of time from an initial spacelike hypersurface,

Shimon Garti, Yair Hayut

We prove that the consistency of the existence of a Dowker filter at $\kappa^+$ along with $2^\kappa=\kappa^+$ where $\kappa$ is regular and uncountable. Using Magidor forcing we also prove the consistency of the existence of a Dowker filter at $\mu^+$ where $\mu>{\rm cf}(\mu)>\omega$.

Ashish Kumar Tripathi, Kapil Sharma, Manju Bala

Over the last three decades more then sixty meta-heuristic algorithms have been proposed by the various authors. Such algorithms are inspired from physical phenomena, animal behavior or evolutionary concepts. These algorithms have been widely used for solving the various real world optimization problems. Researchers are continuously working to improve the ex

Florian J. Boge

A recent no-go theorem (Frauchiger and Renner, 2018) establishes a contradiction from a specific application of quantum theory to a multi-agent setting. The proof of this theorem relies heavily on notions such as 'knows' or `is certain that'. This has stimulated an analysis of the theorem by Nurgalieva and del Rio (2018), in which they claim that it shows th

Shin-Fang Ch'ng, Naoya Sogi, Pulak Purkait, Tat-Jun Chin

Planar markers are useful in robotics and computer vision for mapping and localisation. Given a detected marker in an image, a frequent task is to estimate the 6DOF pose of the marker relative to the camera, which is an instance of planar pose estimation (PPE). Although there are mature techniques, PPE suffers from a fundamental ambiguity problem, in that th

Huitao Shen, Pengfei Zhang, Yi-Zhuang You, Hui Zhai

The quantum neural network is one of the promising applications for near-term noisy intermediate-scale quantum computers. A quantum neural network distills the information from the input wavefunction into the output qubits. In this Letter, we show that this process can also be viewed from the opposite direction: the quantum information in the output qubits i

Youngmoon Jung, Yeunju Choi, Hoirin Kim

Voice activity detection (VAD), which classifies frames as speech or non-speech, is an important module in many speech applications including speaker verification. In this paper, we propose a novel method, called self-adaptive soft VAD, to incorporate a deep neural network (DNN)-based VAD into a deep speaker embedding system. The proposed method is a combina

Mark Andrea A. de Cataldo, Davesh Maulik, Junliang Shen

We study the topology of Hitchin fibrations via abelian surfaces. We establish the P=W conjecture for genus $2$ curves and arbitrary rank. In higher genus and arbitrary rank, we prove that P=W holds for the subalgebra of cohomology generated by even tautological classes. Furthermore, we show that all tautological generators lie in the correct pieces of the p

Károly Bezdek, Zsolt Lángi

In this note we introduce the problem of illumination of convex bodies in spherical spaces and solve it for a large subfamily of convex bodies. We derive from it a combinatorial version of the classical illumination problem for convex bodies in Euclidean spaces as well as a solution to that for a large subfamily of convex bodies, which in dimension three lea

Martin C. Towner, Martin Cupak, Robert M. Howie, Ben Hartig

The detection of fireballs streaks in astronomical imagery can be carried out by a variety of methods. The Desert Fireball Network--DFN--uses a network of cameras to track and triangulate incoming fireballs to recover meteorites with orbits. Fireball detection is done on-camera, but due to the design constraints imposed by remote deployment, the cameras are

Jinshuang Jin

We investigate the charge-states coherence underlying the nonequilibirum transport through a spinless double-dot Aharonov-Bohm (AB) interferometer. Both the current noise spectrum and real-time dynamics are evaluated with the well-established dissipaton-equation-of-motion method. The resulted spectrums show the characteristic peaks and dips, arising from coh

Rui Yan, Xiaoming Duan, Zongying Shi, Yisheng Zhong

This paper studies a 3D multiplayer reach-avoid differential game with a goal region and a play region. Multiple pursuers defend the goal region by consecutively capturing multiple evaders in the play region. The players have heterogeneous moving speeds and the pursuers have heterogeneous capture radii. Since this game is hard to analyze directly, we decompo

Patrick Bell, Hunter Brumley, Aaron Hill, Nathanael McGlothlin

We analyze finite and infinite words coming from the symbolic version of Chacon's transformation, focusing on distances between such words. Our main result is that if W = 0010 0010 1 0010 ... is the infinite word usually associated with Chacon's transformation, then the Hamming distance between W and any positive shift of W is strictly greater than 2/9; more

Yosef Ardhito Winatmoko, Ali Akbar Septiandri, Arie Pratama Sutiono

Aspect and opinion term extraction is a critical step in Aspect-Based Sentiment Analysis (ABSA). Our study focuses on evaluating transfer learning using pre-trained BERT (Devlin et al., 2018) to classify tokens from hotel reviews in bahasa Indonesia. The primary challenge is the language informality of the review texts. By utilizing transfer learning from a

Christopher T. Short, Matthew S. Mietchen, Eric T. Lofgren

Healthcare-associated infections (HAIs) remain a public health problem. Previous work showed intensive care unit (ICU) population structure impacts methicillin-resistant Staphylococcus aureus (MRSA) rates. Unexplored in that work was the transient dynamics of this system. We consider the dynamics of MRSA in an ICU in three different models: 1) a Ross-McDonal

Shay Vargaftik, Isaac Keslassy, Ariel Orda, Yaniv Ben-Itzhak

Decision-tree-based ensemble classification methods (DTEMs) are a prevalent tool for supervised anomaly detection. However, due to the continued growth of datasets, DTEMs result in increasing drawbacks such as growing memory footprints, longer training times, and slower classification latencies at lower throughput. In this paper, we present, design, and eval

R. Abdullaev, V. Chilin, B. Madaminov

Let $(\Omega_i,\mathcal A_i,\mu_i) $ be a measure space with finite measure $\mu_i$, and let $(L_{\log}(\Omega_i, \mathcal A_i,\mu_i), \|\cdot\|_{\log,\mu_i})$ be a $F$-space of all $\log$-integrable functions on $(\Omega_i,\mathcal A_i,\mu_1), \ i =1, 2 $. It is proved that $F$-spaces $(L_{\log}(\Omega_1, \mathcal A_1,\mu_1), \|\cdot\|_{\log,\mu_1})$ \and \

Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang, Yutao Jiao

In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications. Traditional cloudbased Machine Learning (ML) approaches require the data to be centralized in a cloud server or data center. However, th

Tuong Do, Thanh-Toan Do, Huy Tran, Erman Tjiputra

In Visual Question Answering (VQA), answers have a great correlation with question meaning and visual contents. Thus, to selectively utilize image, question and answer information, we propose a novel trilinear interaction model which simultaneously learns high level associations between these three inputs. In addition, to overcome the interaction complexity,

Rory Smith, Gregory Ashton, Avi Vajpeyi, Colm Talbot

Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave astronomy. Usually, stochastic sampling algorithms are used to estimate posterior probability distributions over the paramete

Gregory Ashton, Eric Thrane, Rory J. E. Smith

In order to separate astrophysical gravitational-wave signals from instrumental noise, which often contains transient non-Gaussian artifacts, astronomers have traditionally relied on bootstrap methods such as time slides. Bootstrap methods sample with replacement, comparing single-observatory data to construct a background distribution, which is used to assi

Huan Wang, Shuai Li, Xiaoling Cui, Bo Liu

Supersolid, a fascinating quantum state of matter, features novel phenomena such as the non-classical rotational inertia and transport anomalies. It is a long standing issue of the coexistence of superfluidity and broken translational symmetry in condensed matter physics. By recent experimental advances to create tunable synthetic spin-orbit coupling in ultr

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski, Kevin A. Schneider

Breast cancer is one of the leading causes of death across the world in women. Early diagnosis of this type of cancer is critical for treatment and patient care. Computer-aided detection (CAD) systems using convolutional neural networks (CNN) could assist in the classification of abnormalities. In this study, we proposed an ensemble deep learning-based appro

Deirdre K. Mulligan, Joshua A. Kroll, Nitin Kohli, Richmond Y. Wong

The explosion in the use of software in important sociotechnical systems has renewed focus on the study of the way technical constructs reflect policies, norms, and human values. This effort requires the engagement of scholars and practitioners from many disciplines. And yet, these disciplines often conceptualize the operative values very differently while r

Tobias Schikarski, Holger Trzenschiok, Wolfgang Peukert, Marc Avila

We report on a comprehensive experimental-computational study of a simple T-shaped mixer for Reynolds numbers up to $4000$. In the experiments, we determine the mixing time by applying the Villermaux--Dushman characterization to a water-water mixture. In the numerical simulations, we resolve down to the smallest (Kolmogorov) flow scales in space and time. Ex

Binh D. Nguyen, Thanh-Toan Do, Binh X. Nguyen, Tuong Do

Traditional approaches for Visual Question Answering (VQA) require large amount of labeled data for training. Unfortunately, such large scale data is usually not available for medical domain. In this paper, we propose a novel medical VQA framework that overcomes the labeled data limitation. The proposed framework explores the use of the unsupervised Denoisin

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh kassani, Michal J. Wesolowski, Kevin A. Schneider

Automatic detection of leukemic B-lymphoblast cancer in microscopic images is very challenging due to the complicated nature of histopathological structures. To tackle this issue, an automatic and robust diagnostic system is required for early detection and treatment. In this paper, an automated deep learning-based method is proposed to distinguish between i

Jia Shi, Xiaoping Yuan

In this paper, we establish Anderson localization for the quantum kicked rotor model. More precisely, we proved that \begin{equation*} H=\tan\pi\left(x_0+my_0+\frac{m(m-1)}{2}\omega\right) \delta_{mn}+\epsilon S_\phi \end{equation*} has pure point spectrum with exponentially decaying eigenfunctions for almost all $\omega \in DC$ (diophantine condition).

Zhihong Liu, Jiajia Liu, Yong Zeng, Jianfeng Ma

Covert communication can prevent an adversary from knowing that a wireless transmission has occurred. In additive white Gaussian noise (AWGN) channels, a square root law is found that Alice can reliably and covertly transmit $\mathcal{O}(\sqrt{n})$ bits to Bob in $n$ channel uses. In this paper, we consider covert communications in noisy wireless networks, w

Alessandro Fanfarillo, Behrooz Roozitalab, Weiming Hu, Guido Cervone

The Analog Ensemble (AnEn) method tries to estimate the probability distribution of the future state of the atmosphere with a set of past observations that correspond to the best analogs of a deterministic Numerical Weather Prediction (NWP). This model post-processing method has been successfully used to improve the forecast accuracy for several weather-rela

Yao Zhu, Hongzhi Liu, Zhonghai Wu, Yang Song

Incompleteness is a common problem for existing knowledge graphs (KGs), and the completion of KG which aims to predict links between entities is challenging. Most existing KG completion methods only consider the direct relation between nodes and ignore the relation paths which contain useful information for link prediction. Recently, a few methods take relat

Bin Liu, Ke Meng, Zhao Yang Dong, Peter K. C. Wong

As rooftop solar PVs installed by residential customers penetrate in low voltage distribution network (LVDN), some issues, e.g. over/under voltage and unbalances, which may undermine the network's operational performance, need to be effectively addressed. To mitigate unbalances in LVDN, dynamic switching devices (PSDs) and static var compensator (SVC) are tw

Yi Wang, Zhen-Peng Bian, Junhui Hou, Lap-Pui Chau

Regularization is commonly used for alleviating overfitting in machine learning. For convolutional neural networks (CNNs), regularization methods, such as DropBlock and Shake-Shake, have illustrated the improvement in the generalization performance. However, these methods lack a self-adaptive ability throughout training. That is, the regularization strength

Yuxian Meng, Xiangyuan Ren, Zijun Sun, Xiaoya Li

In this paper, we investigate the problem of training neural machine translation (NMT) systems with a dataset of more than 40 billion bilingual sentence pairs, which is larger than the largest dataset to date by orders of magnitude. Unprecedented challenges emerge in this situation compared to previous NMT work, including severe noise in the data and prohibi

Jorge Alencar, Leonardo de Lima

Let $G$ be a simple graph. In 1986, Herbert Wilf asked what kind of graphs have an eigenvector with entries formed only by $\pm 1$? In this paper, we answer this question for the adjacency, Laplacian and signless Laplacian matrix of a graph. Besides, we generalize the concept of an exact graph to the adjacency and signless Laplacian matrices. Infinity famili

De-Cheng Zou, Yun Soo Myung

We study the scalarized charged black holes in the Einstein-Maxwell-Scalar (EMS) theory with scalar mass term. In this work, the scalar mass term is chosen to be $m^2_\phi=\alpha/\beta$, where $\alpha$ is a coupling parameter and $\beta$ is a mass-like parameter. It turns out that any scalarized charged black holes are not allowed for the case of $\beta \le

Jiangwei Xue, Chia-Fu Yu

In his pioneering work [Crelle's Journal, 1955], Eichler established the theory of trace formulas for Brandt matrices of quaternion orders. From it he derived a class number formula for Eichler orders in a totally definite quaternion algebra $D$. Extending Eichler's work, Pizer [Crelle's Journal, 1973] proved a formula for the type number of Eichler orders i

H. Okamura, M. Nagata, A. Tsubouchi, Y. Onuki

Optical conductivity [$\sigma(\omega)$] of YbCu$_2$Ge$_2$ has been measured at external pressures ($P$) to 20 GPa, to study the $P$ evolution of $f$ electron hybridized states. At $P$=0, $\sigma(\omega)$ shows a marked mid-infrared (mIR) peak at 0.37 eV, which is due to optical excitations from $f^{14}$ (Yb$^{2+}$) state located below the Fermi level. With i

Zheng Hui, Xinbo Gao, Yunchu Yang, Xiumei Wang

In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results. Thanks to the powerful representation capabilities of the deep networks, numerous previous ways can learn the complex non-linear mapping between low-resolution (LR) image patches and their high-resolution (HR) versions.

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

We introduce a transformer-based GNN model, named UGformer, to learn graph representations. In particular, we present two UGformer variants, wherein the first variant (publicized in September 2019) is to leverage the transformer on a set of sampled neighbors for each input node, while the second (publicized in May 2021) is to leverage the transformer on all

Baoan Sun, Liping Yu, Gang Wang, Xing Tong

Metallic glasses response to the mechanical stress in a complex and inhomogeneous manner with plastic strain highly localized into nanoscale shear bands. Contrary to the well-defined deformation mechanism in crystalline solids, understanding the mechanical response mechanism and its intrinsic correlation with the macroscopical plasticity in metallic glasses

Yaofeng Desmond Zhong, Naomi Ehrich Leonard

We present a continuous threshold model (CTM) of cascade dynamics for a network of agents with real-valued activity levels that change continuously in time. The model generalizes the linear threshold model (LTM) from the literature, where an agent becomes active (adopts an innovation) if the fraction of its neighbors that are active is above a threshold. Wit

Dennis Lee, Christian Szegedy, Markus N. Rabe, Sarah M. Loos

We design and conduct a simple experiment to study whether neural networks can perform several steps of approximate reasoning in a fixed dimensional latent space. The set of rewrites (i.e. transformations) that can be successfully performed on a statement represents essential semantic features of the statement. We can compress this information by embedding t

Lawrence Ong, Badri N. Vellambi, Jörg Kliewer, Parastoo Sadeghi

This paper studies pliable index coding, in which a sender broadcasts information to multiple receivers through a shared broadcast medium, and the receivers each have some message a priori and want any message they do not have. An approach, based on receivers that are absent from the problem, was previously proposed to find lower bounds on the optimal broadc

AbdElRahman A. ElSaid, Alexander G. Ororbia, Travis J. Desell

Hand-crafting effective and efficient structures for recurrent neural networks (RNNs) is a difficult, expensive, and time-consuming process. To address this challenge, we propose a novel neuro-evolution algorithm based on ant colony optimization (ACO), called ant swarm neuro-evolution (ASNE), for directly optimizing RNN topologies. The procedure selects from

Thomas Gurriet, Maegan Tucker, Claudia Kann, Guilhem Boeris

This paper presents an active stabilization method for a fully actuated lower-limb exoskeleton. The method was tested on the exoskeleton ATALANTE, which was designed and built by the French start-up company Wandercraft. The main objective of this paper is to present a practical method of realizing more robust walking on hardware through active ankle compensa

Lawrence Ong, Badri N. Vellambi, Jörg Kliewer

We characterise the optimal broadcast rate for a few classes of pliable-index-coding problems. This is achieved by devising new lower bounds that utilise the set of absent receivers to construct decoding chains with skipped messages. This work complements existing works by considering problems that are not complete-S, i.e., problems considered in this work d

Sankara Sai Chaithanya Rayudu, Pradeep Kiran Sarvepalli

Bicyclic codes are a generalization of the one dimensional (1D) cyclic codes to two dimensions (2D). Similar to the 1D case, in some cases, 2D cyclic codes can also be constructed to guarantee a specified minimum distance. Many aspects of these codes are yet unexplored. Motivated by the problem of constructing quantum codes, in this paper, we study some stru

Guang-Ming Zhang, Yi-Feng Yang, Fu-Chun Zhang

We propose the parent compound of the newly discovered superconducting nickelate Nd$_{1-x}$Sr$_{x}$NiO$_{2}$ as a self-doped Mott insulator, in which the low-density Nd-$5d$ conduction electrons couple to localized Ni-3$% d_{x^{2}-y^{2}}$ electrons to form Kondo spin singlets at low temperatures. This proposal is motivated with our analyses of the reported r

Alex Iosevich, Emmett Wyman

The classical Weyl Law says that if $N_M(\lambda)$ denotes the number of eigenvalues of the Laplace operator on a $d$-dimensional compact manifold $M$ without a boundary that are less than or equal to $\lambda$, then $$ N_M(\lambda)=c\lambda^d+O(\lambda^{d-1}).$$ In this paper, we show Duistermaat and Guillemin's result allows us to replace the $O(\lambda^{d

Yaguang Yang

This paper proposes a novel and simple algorithm of facet enumeration for convex polytopes. The complexity of the algorithm is discussed. The algorithm is implemented in Matlab. Some simple polytopes with known H-representations and V-representations are used as the test examples. Numerical test shows the effectiveness and efficiency of the proposed algorith

Kartik Ramkrishnan, Antonia Zhai, Stephen McCamant, Pen Chung Yew

The last level cache is vulnerable to timing based side channel attacks because it is shared by the attacker and the victim processes even if they are located on different cores. These timing attacks evict the victim cache lines using small conflict groups(SCG), and monitor the cache to observe when the victim uses these cache lines again. A conflict group i

Arie Levit, Alexander Lubotzky

We prove that all invariant random subgroups of the lamplighter group $L$ are co-sofic. It follows that $L$ is permutation stable, providing an example of an infinitely presented such a group. Our proof applies more generally to all permutational wreath products of finitely generated abelian groups. We rely on the pointwise ergodic theorem for amenable group

Markus D. Foote, Pouya Sabouri, Amit Sawant, Sarang C. Joshi

Motion estimation of organs in a sequence of images is important in numerous medical imaging applications. The focus of this paper is the analysis of 4D Respiratory Correlated Computed Tomography (RCCT) Imaging. It is hypothesized that the quasi-periodic breathing induced motion of organs in the thorax can be represented by deformations spanning a very low d

Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone

We consider the problem of controlling a large fleet of drones to deliver packages simultaneously across broad urban areas. To conserve energy, drones hop between public transit vehicles (e.g., buses and trams). We design a comprehensive algorithmic framework that strives to minimize the maximum time to complete any delivery. We address the multifaceted comp

Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski, Kevin A. Schneider

Breast cancer is one of the most common causes of cancer-related death in women worldwide. Early and accurate diagnosis of breast cancer may significantly increase the survival rate of patients. In this study, we aim to develop a fully automatic, deep learning-based, method using descriptor features extracted by Deep Convolutional Neural Network (DCNN) model