April 2020 arXiv papers — page 26

Basudeb Sain, Thomas Zentgraf

Metasurface saturable absorbers may result in versatile mode-locking that allows one to obtain stable ultrashort laser pulses with high repetition rates and peak powers, along with broadband operation, within fiber to solid-state laser cavities.

Oğul Esen, Serkan Sütlü

We present the Hamiltonian (Lie-Poisson) analysis of the Vlasov plasma, and the dynamics of its kinetic moments, from the matched pair decomposition point of view. We express these (Lie-Poisson) systems as couplings of \textit{mutually interacting} (Lie-Poisson) subdynamics. The mutual interaction is beyond the well-known semi-direct product theory. Accordin

Jean-Michel Coron, Long Hu, Guillaume Olive, Peipei Shang

In this article we are interested in the boundary stabilization in finite time of one-dimensional linear hyperbolic balance laws with coefficients depending on time and space. We extend the so called "backstepping method" by introducing appropriate time-dependent integral transformations in order to map our initial system to a new one which has desired stabi

Eyuri Wakakuwa, Yoshifumi Nakata

We analyze a task in which classical and quantum messages are simultaneously communicated via a noisy quantum channel, assisted with a limited amount of shared entanglement. We derive direct and converse bounds for the one-shot capacity region, represented by the smooth conditional entropies and the error tolerance. The proof is based on the randomized parti

Tianyang Li, Zhongyi Han, Benzheng Wei, Yuanjie Zheng

This paper addresses the new problem of automated screening of coronavirus disease 2019 (COVID-19) based on chest X-rays, which is urgently demanded toward fast stopping the pandemic. However, robust and accurate screening of COVID-19 from chest X-rays is still a globally recognized challenge because of two bottlenecks: 1) imaging features of COVID-19 share

Peide Cai, Yuxiang Sun, Hengli Wang, Ming Liu

Traditional methods for autonomous driving are implemented with many building blocks from perception, planning and control, making them difficult to generalize to varied scenarios due to complex assumptions and interdependencies. Recently, the end-to-end driving method has emerged, which performs well and generalizes to new environments by directly learning

Dominik Köppl, Daiki Hashimoto, Diptarama Hendrian, Ayumi Shinohara

One of the most well-known variants of the Burrows-Wheeler transform (BWT) [Burrows and Wheeler, 1994] is the bijective BWT (BBWT) [Gil and Scott, arXiv 2012], which applies the extended BWT (EBWT) [Mantaci et al., TCS 2007] to the multiset of Lyndon factors of a given text. Since the EBWT is invertible, the BBWT is a bijective transform in the sense that th

Menglei Zhou, Askar B. Abdikamalov, Dimitry Ayzenberg, Cosimo Bambi

The analysis of the thermal spectrum of geometrically thin and optically thick accretion disks of black holes, the so-called continuum-fitting method, is one of the leading techniques for measuring black hole spins. Current models normally approximate the disk as infinitesimally thin, while in reality the disk thickness is finite and increases as the black h

Hugo L. Hammer, Anis Yazidi, Michael A. Riegler, Håvard Rue

For incremental quantile estimators the step size and possibly other tuning parameters must be carefully set. However, little attention has been given on how to set these values in an online manner. In this article we suggest two novel procedures that address this issue. The core part of the procedures is to estimate the current tracking mean squared error (

Mingjie Shao, Wing-Kin Ma

In this paper we consider maximum-likelihood (ML) MIMO detection under one-bit quantized observations and binary symbol constellations. This problem is motivated by the recent interest in adopting coarse quantization in massive MIMO systems--as an effective way to scale down the hardware complexity and energy consumption. Classical MIMO detection techniques

Moumita Naskar, Muktish Acharyya

The two dimensional Spin-1 Blume-Capel ferromagnet is studied by Monte Carlo simulation with Metropolis algorithm. Starting from initial ordered spin configuration the reversal of magnetisation is investigated in presence of a magnetic field ($h$) applied in the opposite direction. The variations of the reversal time with the strength of single site anisotro

Qile Zhu, Jianlin Su, Wei Bi, Xiaojiang Liu

Variational Autoencoder (VAE) is widely used as a generative model to approximate a model's posterior on latent variables by combining the amortized variational inference and deep neural networks. However, when paired with strong autoregressive decoders, VAE often converges to a degenerated local optimum known as "posterior collapse". Previous approaches con

Roland R. Netz

The effect of evaporation on droplet sedimentation times is crucial for estimating the risk of infection from virus-containing airborne droplets. For droplet radii in the range 100 nm < R < 60 {\mu}m, evaporation can be described in the stagnant-flow approximation and is diffusion limited. Analytical equations are presented for the droplet evaporation rate,

Nikolaos S. Papageorgiou, Vicenţiu D. Rădulescu, Dušan D. Repovš

We consider a nonlinear Dirichlet problem driven by a nonhomogeneous differential operator with a growth of order $(p-1)$ near $+\infty$ and with a reaction which has the competing effects of a parametric singular term and a $(p-1)$-superlinear perturbation which does not satisfy the usual Ambrosetti-Rabinowitz condition. Using variational tools, together wi

Salihah Alwadani, Heinz H. Bauschke, Xianfu Wang

Nonexpansive mappings play a central role in modern optimization and monotone operator theory because their fixed points can describe solutions to optimization or critical point problems. It is known that when the mappings are sufficiently "nice", then the fixed point set of the composition coincides with the intersection of the individual fixed point sets.

Kun Cheng, Yuebin Bai, Yuan Zhou, Chao Yu

Autonomous driving vehicles (ADVs) are implemented with rich software functions and equipped with many sensors, which in turn brings broad attack surface. Moreover, the execution environment of ADVs is often open and complex. Hence, ADVs are always at risk of safety and security threats. This paper proposes a fast method called Multi-IF, using multiple invoc

Frederic Koehler, Elchanan Mossel

Arrow's Theorem concerns a fundamental problem in social choice theory: given the individual preferences of members of a group, how can they be aggregated to form rational group preferences? Arrow showed that in an election between three or more candidates, there are situations where any voting rule satisfying a small list of natural "fairness" axioms must p

Toshiki Kurita, Masahiro Takada, Takahiro Nishimichi, Ryuichi Takahashi

We use a suite of $N$-body simulations to study intrinsic alignments (IA) of halo shapes with the surrounding large-scale structure in the $\Lambda$CDM model. For this purpose, we develop a novel method to measure multipole moments of the three-dimensional power spectrum of the $E$-mode field of halo shapes with the matter/halo distribution, $P_{\delta E}^{(

Yerlan Nessipbayev, Kanat Tulenov

In this paper, we provide a direct proof for the equivalence of K.M. Chong's and De la Vall\'{e}e Poussin's criteria of weak compactness of a subset $K$ of $L_1(0,1)$ in terms of some Orlicz function. Furthermore, we discuss the equivalence in $L_1(0, \infty)$.

P. B. Blakie, D. Baillie, L. Chomaz, F. Ferlaino

We present a theory for the emergence of a supersolid state in a cigar-shaped dipolar quantum Bose gas. Our approach is based on a reduced three-dimensional (3D) theory, where the condensate wavefunction is decomposed into an axial field and a transverse part described variationally. This provides an accurate fully 3D description that is specific to the regi

Ye Xia, Gwendolyn Lee

We outline a contact-tracing strategy based on proximity sensing using mobile devices. We discuss what an ideal system should look like and what it can do. We show that, when adopted sufficiently broadly, such a contact-tracing strategy can bring COVID-19 under complete control, end the need of social distancing, and return the society to full normalcy. We a

Kazutaka Kanno, Makoto Naruse, Atsushi Uchida

Photonic reservoir computing is an emergent technology toward beyond-Neumann computing. Although photonic reservoir computing provides superior performance in environments whose characteristics are coincident with the training datasets for the reservoir, the performance is significantly degraded if these characteristics deviate from the original knowledge us

Vahid Roostapour, Aneta Neumann, Frank Neumann

Evolutionary algorithms are bio-inspired algorithms that can easily adapt to changing environments. Recent results in the area of runtime analysis have pointed out that algorithms such as the (1+1)~EA and Global SEMO can efficiently reoptimize linear functions under a dynamic uniform constraint. Motivated by this study, we investigate single- and multi-objec

Jinwei Zhang, Hang Zhang, Mert Sabuncu, Pascal Spincemaille

A learning-based posterior distribution estimation method, Probabilistic Dipole Inversion (PDI), is proposed to solve quantitative susceptibility mapping (QSM) inverse problem in MRI with uncertainty estimation. A deep convolutional neural network (CNN) is used to represent the multivariate Gaussian distribution as the approximated posterior distribution of

Vedansh Arya, Agnid Banerjee

In this paper, we establish strong backward uniqueness for solutions to sublinear parabolic equations of the type (1.1). The proof of our main result Theorem 1.1 is achieved by means of a new Carleman estimate and a Weiss type monotonicity that are tailored for such parabolic sublinear operators.

Xinjian Luo, Xianglong Zhang

Federated learning (FL) is a decentralized model training framework that aims to merge isolated data islands while maintaining data privacy. However, recent studies have revealed that Generative Adversarial Network (GAN) based attacks can be employed in FL to learn the distribution of private datasets and reconstruct recognizable images. In this paper, we ex

Wei Liang Quek, Ning Ning Chung, Vee-Liem Saw, Lock Yue Chew

In this paper, we propose an Empirically-based Monte Carlo Bus-network (EMB) model as a test bed to simulate intervention strategies to overcome the inefficiencies of bus bunching. The EMB model is an agent-based model which utilizes the positional and temporal data of the buses obtained from the Global Positioning System (GPS) to constitute: (1) a set of em

Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah

The success of reinforcement learning for real world robotics has been, in many cases limited to instrumented laboratory scenarios, often requiring arduous human effort and oversight to enable continuous learning. In this work, we discuss the elements that are needed for a robotic learning system that can continually and autonomously improve with data collec

Noshin Amiri, Iman Naderi

Steganography is a method that can improve network security and make communications safer. In this method, a secret message is hidden in content like audio signals that should not be perceptible by listening to the audio or seeing the signal waves. Also, it should be robust against different common attacks such as noise and compression. In this paper, we pro

Nozhan Hosseini, Mahfuza Khatun, Changyu Guo, Kairui Du

Future cellular systems will make use of millimeter wave (mmWave) frequency bands. Many users in these bands are located indoors, i.e., inside buildings, homes, and offices. Typical building material attenuations in these high frequency ranges are of interest for link budget calculations. In this paper, we report on a collaborative measurement campaign to fi

Shih-Hao Tseng, Carmen {Amo Alonso}, SooJean Han

System Level Synthesis (SLS) parametrization facilitates controller synthesis for large, complex, and distributed systems by incorporating system level constraints (SLCs) into a convex SLS problem and mapping its solution to stable controller design. Solving the SLS problem at scale efficiently is challenging, and current attempts take advantage of special s

Sehun Chun

A novel high-order numerical scheme is proposed to compute the covariant derivative, particularly for divergence and curl, on any curved surface. The proposed scheme does not require the construction of a curved axis or metric tensor, which would deteriorate the accuracy of the covariant derivative and prevent its application to complex surfaces. As an appli

Yan Peng

For massless scalar fields, a relation $\Delta_{n}=\frac{\sqrt{3}}{2}\pi$ for $n\rightarrow \infty$ was observed in the scalar-Gauss-Bonnet theory. In the present paper, we extend the discussion by including a nonzero scalar field mass. For massive scalar fields, we show that the relation $\Delta_{n}=\frac{\sqrt{3}}{2}\pi$ for $n\rightarrow \infty$ still hol

Amin Keshavarzi, Abolfazl T. Haghighat, Mahdi Bohlouli

In today's information technology (IT) era, a major part of the costs is being spent on computational needs. Enterprises are in efforts to increase their Return on Investment (ROI) and individuals are trying to reduce their costs. In this regard, cloud computing which emerges as a fifth utility can reduce costs and enhance performance of IT solutions. A larg

Shih-Hao Tseng, Jing Shuang Li

Synthesizing controllers for large, complex, and distributed systems is a challenging task. Numerous proposed methods exist in the literature, but it is difficult for practitioners to apply them -- most proposed synthesis methods lack ready-to-use software implementations, and existing proprietary components are too rigid to extend to general systems. To add

Qi Yan, Xian'an Jin

Gross, Mansour and Tucker introduced the partial-dual orientable genus polynomial and the partial-dual Euler genus polynomial. They computed these two partial-dual genus polynomials of four families of ribbon graphs, posed some research problems and made some conjectures. In this paper, we introduce the notion of signed sequences of bouquets and obtain the p

Mahdi Bohlouli, Frank Schulz, Lefteris Angelis, David Pahor

The amount of data in the world is expanding rapidly. Every day, huge amounts of data are created by scientific experiments, companies, and end users' activities. These large data sets have been labeled as "Big Data", and their storage, processing and analysis presents a plethora of new challenges to computer science researchers and IT professionals. In addi

Xuan Wang, Weili Liu, Aabhas Chauhan, Yingjun Guan

We created this EVIDENCEMINER system for automatic textual evidence mining in COVID-19 literature. EVIDENCEMINER is a web-based system that lets users query a natural language statement and automatically retrieves textual evidence from a background corpora for life sciences. It is constructed in a completely automated way without any human effort for trainin

Avirup De, Anupam K. Singh, Sanjay Singh, Sunil Nair

We report a detailed investigation of the Ni$_{2}$MnGa shape memory alloy through magnetic, electronic, and thermal measurements. Our measurements of the anomalous Nernst effect (ANE) reveal that this technique is very sensitive to the onset of the pre-martensitic transition in sharp contrast to other transport measurements. With the ANE being sensitive to c

Hongliang Lu, Yan Wang, Xingxing Yu

Aharoni and Howard conjectured that, for positive integers $n,k,t$ with $n\ge k$ and $n\ge t$, if $F_1,\ldots, F_t\subseteq {[n]\choose k}$ such that $|F_i|>{n\choose k}-{n-t+1\choose k}$ for $i\in [t]$ then there exist $e_i\in F_i$ for $i\in [t]$ such that $e_1,\ldots,e_t$ are pairwise disjoint. Huang, Loh, and Sudakov proved this conjecture for $t<n/(3k^2)

Tian Xu

Motivated by recent progress on a spinorial analogue of the Yamabe problem in the geometric literature, we study a conformally invariant spinor field equation on the $m$-sphere, $m\geq2$. Via variational methods, we study analytic aspects of the associated energy functional, culminating in a blow-up analysis.

Fei Wang, Xuepeng Wang, Yi-Fan Zhao, Di Xiao

The Berry phase picture provides important insights into the electronic properties of condensed matter systems. The intrinsic anomalous Hall (AH) effect can be understood as a consequence of non-zero Berry curvature in momentum space. The realization of the quantum anomalous Hall effect provided conclusive evidence for the intrinsic mechanism of the AH effec

Weibin Chu, Qijing Zheng, Oleg V. Prezhdo, Jin Zhao

Recently we proposed that defect tolerance in the hybrid perovskites is due to their characteristic low-frequency lattice phonon modes that decrease the non-adiabatic coupling and weaken the overlap between the free carrier and defect states [Sci. Adv. 6 7, eaaw7453 (2020)]. Kim and Walsh disagree with the interpretation and argue that there are flaws in our

Hongliang Lu, Xingxing Yu, Xiaofan Yuan

K\"{u}hn, Osthus, and Treglown and, independently, Khan proved that if $H$ is a $3$-uniform hypergraph with $n$ vertices such that $n\in 3\mathbb{Z}$ and large, and $\delta_1(H)>{n-1\choose 2}-{2n/3\choose 2}$, then $H$ contains a perfect matching. In this paper, we show that for $n\in 3\mathbb{Z}$ sufficiently large, if $F_1, \ldots, F_{n/3}$ are 3-uniform

Seyed Fouad Karimian, Ramin Moradi, Sergio Cofre-Martel, Katrina M. Groth

Crack detection, length estimation, and Remaining Useful Life (RUL) prediction are among the most studied topics in reliability engineering. Several research efforts have studied physics of failure (PoF) of different materials, along with data-driven approaches as an alternative to the traditional PoF studies. To bridge the gap between these two techniques,

Sridip Pal, Zhengdi Sun

We derive Cardy-like formulas for the growth of operators in different sectors of unitary $2$ dimensional CFT in the presence of topological defect lines by putting an upper and lower bound on the number of states with scaling dimension in the interval $[\Delta-\delta,\Delta+\delta]$ for large $\Delta$ at fixed $\delta$. Consequently we prove that given any

Vladimir Vargas-Calderón, Herbert Vinck-Posada, Fabio A. González

Recently, the use of neural quantum states for describing the ground state of many- and few-body problems has been gaining popularity because of their high expressivity and ability to handle intractably large Hilbert spaces. In particular, methods based on variational Monte Carlo have proven to be successful in describing the physics of bosonic systems such

M. Cenk Erturk, Nozhan Hosseini, Hosseinali Jamal, Alphan Sahin

Urban air mobility (UAM) is a concept for creating an airborne transportation system that operates in urban settings with an on-board pilot and/or remote pilot in command (RPIC), or with a fully autonomous architecture. Although the passenger traffic will be mostly in and near urban environments, UAM is also being considered for air cargo, perhaps between ci

Victor Nijimbere

The non-elementary integrals involving elementary exponential, hyperbolic and trigonometric functions, $ \int x^\alpha e^{\eta x^\beta}dx, \int x^\alpha \cosh\left(\eta x^\beta\right)dx, \int x^\alpha \sinh\left(\eta x^\beta\right)dx, \int x^\alpha \cos\left(\eta x^\beta\right)dx$ and $\int x^\alpha \sin\left(\eta x^\beta\right)dx $ where $\alpha, \eta$ and

Petrônio Cândido de Lima e Silva, Carlos Alberto Severiano Junior, Marcos Antonio Alves, Rodrigo Silva

In this paper we introduce a Non-Stationary Fuzzy Time Series (NSFTS) method with time varying parameters adapted from the distribution of the data. In this approach, we employ Non-Stationary Fuzzy Sets, in which perturbation functions are used to adapt the membership function parameters in the knowledge base in response to statistical changes in the time se

Akshay Agrawal, Stephen Boyd

We show how to efficiently compute the derivative (when it exists) of the solution map of log-log convex programs (LLCPs). These are nonconvex, nonsmooth optimization problems with positive variables that become convex when the variables, objective functions, and constraint functions are replaced with their logs. We focus specifically on LLCPs generated by d

Tailin Niu, Kangquan Li, Longjiang Qu, Qiang Wang

Permutation polynomials and their compositional inverses have wide applications in cryptography, coding theory, and combinatorial designs. Motivated by several previous results on finding compositional inverses of permutation polynomials of different forms, we propose a general method for finding these inverses of permutation polynomials constructed by the A

Benjamin Shickel, Tyler J. Loftus, Matthew Ruppert, Gilbert R. Upchurch

Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, preoperative risk-reduction, and postoperative resource use. We hypothesized that multi-task deep learning models would outperform random forest models in predicting postoperative complications, and that integrating high-resolution intraoperative physiological

Charles C. Margossian, Aki Vehtari, Daniel Simpson, Raj Agrawal

Gaussian latent variable models are a key class of Bayesian hierarchical models with applications in many fields. Performing Bayesian inference on such models can be challenging as Markov chain Monte Carlo algorithms struggle with the geometry of the resulting posterior distribution and can be prohibitively slow. An alternative is to use a Laplace approximat

Antonio De Felice, Andreas Doll, Shinji Mukohyama

We propose a modified gravity theory that propagates only two local gravitational degrees of freedom and that does not have an Einstein frame. According to the classification in JCAP 01 (2019) 017 [arXiv:1810.01047 [gr-qc]], this is a type-II minimally modified gravity theory. The theory is characterized by the gravitational constant $G_{\rm N}$ and a functi

Ken'ichi Tatematsu, Tie Liu, Gwanjeong Kim, Hee-Weon Yi

We mapped two molecular cloud cores in the Orion A cloud with the ALMA ACA 7-m Array and with the Nobeyama 45-m radio telescope. These cores have bright N$_2$D$^+$ emission in single-pointing observations with the Nobeyama 45-m radio telescope, have relatively high deuterium fraction, and are thought to be close to the onset of star formation. One is a star-

Qin Han, Xiang-Dong Li

SS433 is an extraordinary X-ray binary which is ejecting bipolar jets with $26\%$ of the speed of light. Associated with the supernova-like shell W50, SS433 is also probably one of the youngest X-ray binaries with an age of $\lesssim 10^5$ yr. However, the masses of the two components in SS433 and even the nature of the compact object are still under debate.

Soo-Min Kim, Han Cha, Seong-Lyun Kim, Chan-Byoung Chae

In this paper, we propose a reinforcement learning-based flexible duplex system for B5G with Sub-6 GHz. This system combines full-duplex radios and dynamic spectrum access to maximize the spectral efficiency. We verify this method's feasibility by implementing an FPGA-based real-time testbed. In addition, we compare the proposed algorithm with the result der

Tae Hun Jung, Hanju Yoo, Yuna Jin, Chae Eun Rhee

With emerging trends in the fifth generation and robotics, the Internet of Skills will enable us to deliver skills or expertise anywhere over the Internet. In this paper, we propose a wireless connected virtual reality and haptic communication open platform to show the proof of concept for multimodal teleoperation systems in real-time. We focus on a practica

Zi-Huai Zhang, Paul Stevenson, Gergo Thiering, Brendon C. Rose

Neutral silicon vacancy (SiV0) centers in diamond are promising candidates for quantum networks because of their excellent optical properties and long spin coherence times. However, spin-dependent fluorescence in such defects has been elusive due to poor understanding of the excited state fine structure and limited off-resonant spin polarization. Here we rep

Youngnam Lee, Byungsoo Kim, Dongmin Shin, JungHoon Kim

Intelligent Tutoring Systems (ITSs) have been developed to provide students with personalized learning experiences by adaptively generating learning paths optimized for each individual. Within the vast scope of ITS, score prediction stands out as an area of study that enables students to construct individually realistic goals based on their current position.

Byung Gyu Chae

The viewing-angle enlargement of a holographic image is a crucial factor for realizing the holographic display. The numerical aperture (NA) of digital hologram other than a pixel specification has been known to determine the angular field extent of image. Here, we provide a valid foundation for the dependence of viewing angle on the hologram numerical apertu

Danying Yu, Luqi Yuan, Xianfeng Chen

The exploration of flatband in photonics is fundamentally important, aiming to control the localization of light for potential applications in optical communications. We study the flatband physics in a synthetic space including the frequency axis of light. A ring-resonator array is used to construct a synthetic Lieb-type lattice, where the modulation phase d

Conghui Xu, Yongguang Yu, QuanChen Yang, Zhenzhen Lu

In this paper, a generalized fractional-order SEIR model is proposed, denoted by SEIQRP model, which has a basic guiding significance for the prediction of the possible outbreak of infectious diseases like COVID-19 and other insect diseases in the future. Firstly, some qualitative properties of the model are analyzed. The basic reproduction number $R_{0}$ is

Hao Zhang, Zhan Li, Zhixing Ren

Data center (DC) contains both IT devices and facility equipment, and the operation of a DC requires a high-quality monitoring (anomaly detection) system. There are lots of sensors in computer rooms for the DC monitoring system, and they are inherently related. This work proposes a data-driven pipeline (ts2graph) to build a DC graph of things (sensor graph)

Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato

Malicious jamming launched by smart jammers can attack legitimate transmissions, which has been regarded as one of the critical security challenges in wireless communications. With this focus, this paper considers the use of an intelligent reflecting surface (IRS) to enhance anti-jamming communication performance and mitigate jamming interference by adjustin

Sohee Cho, Ginkyeng Lee, Wonjoon Chang, Jaesik Choi

Recently deep neural networks demonstrate competitive performances in classification and regression tasks for many temporal or sequential data. However, it is still hard to understand the classification mechanisms of temporal deep neural networks. In this paper, we propose two new frameworks to visualize temporal representations learned from deep neural netw

Jun Ma, Yixin Wang, Xingle An, Cheng Ge

Purpose: Accurate segmentation of lung and infection in COVID-19 CT scans plays an important role in the quantitative management of patients. Most of the existing studies are based on large and private annotated datasets that are impractical to obtain from a single institution, especially when radiologists are busy fighting the coronavirus disease. Furthermo

Yuan Da Liao, Jian Kang, Clara N. Breiø, Xiao Yan Xu

Twisted bilayer graphene (TBG) provides a unique framework to elucidate the interplay between strong correlations and topological phenomena in two-dimensional systems. The existence of multiple electronic degrees of freedom -- charge, spin, and valley -- gives rise to a plethora of possible ordered states and instabilities. Identifying which of them are real

Jerry Wei, Arief Suriawinata, Xiaoying Liu, Bing Ren

The unique nature of histopathology images opens the door to domain-specific formulations of image translation models. We propose a difficulty translation model that modifies colorectal histopathology images to be more challenging to classify. Our model comprises a scorer, which provides an output confidence to measure the difficulty of images, and an image

J. A. S. Lima, A. Deppman

Nonadditive Tsallis $q$-statistics has successfully been applied for a plethora of systems in natural sciences and other branches of knowledge. Nevertheless, its foundations have been severely criticised by some authors based on the standard additive Boltzmann-Gibbs approach thereby remaining a quite controversial subject. In order to clarify some polemical

Karush Suri, Rinki Gupta

Sign Language is used by the deaf community all over world. The work presented here proposes a novel one-dimensional deep capsule network (CapsNet) architecture for continuous Indian Sign Language recognition by means of signals obtained from a custom designed wearable IMU system. The performance of the proposed CapsNet architecture is assessed by altering d

QHwan Kim, Wonho Jhe

Surface tension plays a ubiquitous role in phase transitions including condensation or evaporation of atmospheric liquid droplets. Especially, understanding of interfacial thermodynamics of the critical nucleus of 1 nm scale is important for molecular characterization of the activation energy barrier of nucleation. Here, we investigate surface tension of sph

William Kuszmaul, Alek Westover

We present an in-place algorithm for the partition problem that has linear work and polylogarithmic span. The algorithm uses only exclusive read/write shared variables, and can be implemented using parallel-for-loops without any additional concurrency considerations (i.e., the algorithm is EREW). A key feature of the algorithm is that it exhibits provably op

Karush Suri, Rinki Gupta

Recent advancements in diagnostic learning and development of gesture-based human machine interfaces have driven surface electromyography (sEMG) towards significant importance. Analysis of hand gestures requires an accurate assessment of sEMG signals. The proposed work presents a novel sequential master-slave architecture consisting of deep neural networks (

Rinki Gupta, Karush Suri

Surface electromyography (sEMG) has gained significant importance during recent advancements in consumer electronics for healthcare systems, gesture analysis and recognition and sign language communication. For such a system, it is imperative to determine the regions of activity in a continuously recorded sEMG signal. The proposed work provides a novel activ

Kazuya Nishimura, Ryoma Bise

Automated mitotic detection in time-lapse phasecontrast microscopy provides us much information for cell behavior analysis, and thus several mitosis detection methods have been proposed. However, these methods still have two problems; 1) they cannot detect multiple mitosis events when there are closely placed. 2) they do not consider the annotation gaps, whi

Karush Suri, Rinki Gupta

Surface electromyography (sEMG) is becoming exceeding useful in applications involving analysis of human motion such as in human-machine interface, assistive technology, healthcare and prosthetic development. The proposed work presents a novel dual stage classification approach for classification of grasping gestures from sEMG signals. A statistical assessme

Yanzhao Cao, Somak Das, Luke Oeding, Hans-Werner van Wyk

Stochastic Alternating Least Squares (SALS) is a method that approximates the canonical decomposition of averages of sampled random tensors. Its simplicity and efficient memory usage make SALS an ideal tool for decomposing tensors in an online setting. We show, under mild regularization and readily verifiable assumptions on the boundedness of the data, that

Karush Suri, Rinki Gupta

IMUs are gaining significant importance in the field of hand gesture analysis, trajectory detection and kinematic functional study. An Inertial Measurement Unit (IMU) consists of tri-axial accelerometers and gyroscopes which can together be used for formation analysis. The paper presents a novel classification approach using a Deep Neural Network (DNN) for c

Zhongyi Han, Xian-Jin Gui, Chaoran Cui, Yilong Yin

In non-stationary environments, learning machines usually confront the domain adaptation scenario where the data distribution does change over time. Previous domain adaptation works have achieved great success in theory and practice. However, they always lose robustness in noisy environments where the labels and features of examples from the source domain be

Peng Gao

We obtain an asymptotic formula for the fourth moment of central values of a family of quadratic Hecke $L$-functions in the Gaussian field under the generalized Riemann hypothesis (GRH). We also establish lower bounds unconditionally and upper bounds under GRH for higher moments of the same family.

Jerrod Parker, Jerry Zikun Chen

Recent algorithms in machine translation have included a value network to assist the policy network when deciding which word to output at each step of the translation. The addition of a value network helps the algorithm perform better on evaluation metrics like the BLEU score. After training the policy and value networks in a supervised setting, the policy a

Andrew Feit, Bérénice Mettler

Trained humans exhibit highly agile spatial skills, enabling them to operate vehicles with complex dynamics in demanding tasks and conditions. Prior work shows that humans achieve this performance by using strategies such as satisficing, learning hierarchical task structure, and using a library of motion primitive elements. A key aspect of efficient and vers

Laurie Bose, Jianing Chen, Stephen J. Carey, Piotr Dudek

We present a novel method of CNN inference for pixel processor array (PPA) vision sensors, designed to take advantage of their massive parallelism and analog compute capabilities. PPA sensors consist of an array of processing elements (PEs), with each PE capable of light capture, data storage and computation, allowing various computer vision processing to be

Xuan Luo, Hao Sun

The single longitudinal spin asymmetry $A_{UL}^{\sin(2\phi_h-2\phi_R)}$ of dihadron production in semi-inclusive deep inelastic scattering (SIDIS) is examined through helicity-dependent dihadron fragmentation function (DiFF) $G_1^\perp$. The correlation of the longitudinal polarization of a fragmenting quark with the transverse momenta of the produced hadron

Benjamin Shickel, Parisa Rashidi

Deep learning continues to revolutionize an ever-growing number of critical application areas including healthcare, transportation, finance, and basic sciences. Despite their increased predictive power, model transparency and human explainability remain a significant challenge due to the "black box" nature of modern deep learning models. In many cases the de

J. Osorio Morales, O. Santillán

As is well known, there exists warp drives in GR, such as the Alcubierre bubbles, which achieve an apparent faster than light travel \cite{alcubierre}. A result due to Gao and Wald \cite{gaowald} suggests that such a travel is unlikely for GR with matter satisfying both the Null Energy and the Null Generic Conditions. There exists a generalization of this st

Assaf Naor, Robert Young

We prove that the $L_4$ norm of the vertical perimeter of any measurable subset of the $3$-dimensional Heisenberg group $\mathbb{H}$ is at most a universal constant multiple of the (Heisenberg) perimeter of the subset. We show that this isoperimetric-type inequality is optimal in the sense that there are sets for which it fails to hold with the $L_4$ norm re

Malgorzata Stawiska

We prove P. Alexandersson's conjecture that for every complex polynomial $p$ of degree $d \geq 2$ the convex hull $H_p$ of the Julia set $J_p$ of $p$ satisfies $p^{-1}(H_p) \subset H_p$. We further prove that the equality $p^{-1}(H_p) = H_p$ is achieved only if $p$ is affinely conjugated to the Chebyshev polynomial $T_d$ of degree $d$, to $-T_d$ or a monomia

Tichouk, Hao Sun, Xuan Luo

In this paper, the inclusive Pomeron-Pomeron, Reggeon-Reggeon, Pomeron-Reggeon as well as gluon-Pomeron(-Reggeon) and photon-Pomeron(-Reggeon) interactions for the $\rm \eta_{c}$ at the LHC energies have been examined in proton-proton, proton-nucleus and nucleus-nucleus collision modes. The cross section has been computed based on the NRQCD factorization and

Xuan Luo, Hao Sun

In this paper we study the Kotzinian-Mulders effect of a single hadron production in semi-inclusive deep inelastic scattering (SIDIS) within the framework of transverse momentum dependent (TMD) factorization. The asymmetry is contributed by the convolution of the Kotzinian-Mulders function $g_{1T}$ and the unpolarized fragmentation function $D_1$. As a TMD d

Nathan Inkawhich, Kevin J Liang, Lawrence Carin, Yiran Chen

Almost all current adversarial attacks of CNN classifiers rely on information derived from the output layer of the network. This work presents a new adversarial attack based on the modeling and exploitation of class-wise and layer-wise deep feature distributions. We achieve state-of-the-art targeted blackbox transfer-based attack results for undefended Image

Hailey Joren, Otkrist Gupta, Dan Raviv

Examining the authenticity of images has become increasingly important as manipulation tools become more accessible and advanced. Recent work has shown that while CNN-based image manipulation detectors can successfully identify manipulations, they are also vulnerable to adversarial attacks, ranging from simple double JPEG compression to advanced pixel-based

Luyining Gan, Jie Han

We show that for any fixed $\alpha>0$, cherry-quasirandom 3-graphs of positive density and sufficiently large order $n$ with minimum vertex degree $\alpha \binom n2$ have a tight Hamilton cycle. This solves a conjecture of Aigner-Horev and Levy.

Rowan Rowlands

Given a finite CAT(0) cubical complex, we define a flag simplicial complex associated to it, called the crossing complex. We show that the crossing complex holds much of the combinatorial information of the original cubical complex: for example, hyperplanes in the cubical complex correspond to vertex links in the crossing complex, and the crossing complex is

Qiao-Chu Li, Yuan-Pei Yang, Zi-Gao Dai

The first repeating fast radio burst (FRB), FRB 121102, was found to be associated with a spatially coincident, persistent nonthermal radio source, but the origin of the persistent emission remains unknown. In this paper, we propose that the persistent emission is produced via synchrotron-heating process by multiple bursts of FRB 121102 in a self-absorbed sy

Jonathan Karp, Max Bramberger, Martin Grundner, Ulrich Schollwöck

Sr$_2$MoO$_4$ is isostructural to the unconventional superconductor Sr$_2$RuO$_4$ but with two electrons instead of two holes in the Mo/Ru-t$_{2g}$ orbitals. Both materials are Hund's metals, but while Sr$_2$RuO$_4$ has a van Hove singularity in close proximity to the Fermi surface, the van Hove singularity of Sr$_2$MoO$_4$ is far from the Fermi surface. By

Darcy Camargo, Yuri Kifer, Ofer Zeitouni

We consider a one dimensional ballistic nearest-neighbor random walk in a random environment. We prove an Erd\H{o}s-R\'enyi strong law for the increments.

Chang-Yuan Chen, Yuan You, Xiao-Hua Wang, Fa-Lin Lu

In this work, we propose a new scheme to solve the angular Teukolsky equation for the particular case: $m=0, s=0$. We first transform this equation to a confluent Heun differential equation and then construct the Wronskian determinant to calculate the eigenvalues and normalized eigenfunctions. We find that the eigenvalues for larger $l$ are approximately giv