March 2020 arXiv papers — page 59

Meng Fai Lim

Let $A$ be an abelian variety defined over a number field $F$ with supersingular reduction at all primes of $F$ above $p$. We establish an equivalence between the weak Leopoldt conjecture and the expected value of the corank of the classical Selmer group of $A$ over a $p$-adic Lie extension (not neccesasily containing the cyclotomic $\Zp$-extension). As an a

Yunhao Ge, Jiaping Zhao, Laurent Itti

Object pose increases intraclass object variance which makes object recognition from 2D images harder. To render a classifier robust to pose variations, most deep neural networks try to eliminate the influence of pose by using large datasets with many poses for each class. Here, we propose a different approach: a class-agnostic object pose transformation net

Zelin Deng, Xiaolong Yan, Shengjun Zhang, Colleen P. Bailey

A maximally stable extreme region (MSER) analysis based convolutional neural network (CNN) for unified defect detection framework is proposed in this paper. Our proposed framework utilizes the generality and stability of MSER to generate the desired defect candidates. Then a specific trained binary CNN classifier is adopted over the defect candidates to prod

Jan Ambjørn, Yuki Sato, Tomo Tanaka

We study the zero-temperature criticality of the Ising model on two-dimensional dynamical triangulations to contemplate its physics. As it turns out, an inhomogeneous nature of the system yields an interesting phase diagram and the physics at the zero temperature is quite sensitive about how we cool down the system. We show the existence of a continuous para

Martin Scharlemann

Suppose T is a Heegaard splitting surface for a compact orientable 3-manifold M, and S is a reducing sphere for M. In 1968 Haken showed that there is then also a reducing sphere S* for the Heegaard splitting. That is, S* is a reducing sphere for M and the surfaces T and S* intersect in a single circle. In 1987 Casson and Gordon extended the result to boundar

Simon Riche, Geordie Williamson

We apply Treumann's "Smith theory for sheaves" in the context of the Iwahori--Whittaker model of the Satake category. We deduce two results in the representation theory of reductive algebraic groups over fields of positive characteristic: (a) a geometric proof of the linkage principle; (b) a character formula for tilting modules in terms of the $\ell$-canoni

Minho Hwang, Brijen Thananjeyan, Samuel Paradis, Daniel Seita

Automation of surgical subtasks using cable-driven robotic surgical assistants (RSAs) such as Intuitive Surgical's da Vinci Research Kit (dVRK) is challenging due to imprecision in control from cable-related effects such as cable stretching and hysteresis. We propose a novel approach to efficiently calibrate such robots by placing a 3D printed fiducial coord

Liangying Yin, Carlos Kwan-long Chau, Yu-Ping Lin, Pak-Chung Sham

Genome-wide association studies(GWAS) have proven to be highly useful in revealing the genetic basis of complex diseases. At present, most GWAS are studies of a particular single disease diagnosis against controls. However, in practice, an individual is often affected by more than one condition/disorder. For example, patients with coronary artery disease(CAD

Fahad Islam, Oren Salzman, Aditya Agarwal, Maxim Likhachev

In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts are moving, robots have limited time to pick them up. This brings the requirement for fast and reliable motion planners that could provide provable real-time planning guarantees,

D. M. Ghilencea

We study quadratic gravity $R^2+R_{[\mu\nu]}^2$ in the Palatini formalism where the connection and the metric are independent. This action has a {\it gauged} scale symmetry (also known as Weyl gauge symmetry) of Weyl gauge field $v_\mu= (\tilde\Gamma_\mu-\Gamma_\mu)/2$, with $\tilde\Gamma_\mu$ ($\Gamma_\mu$) the trace of the Palatini (Levi-Civita) connection

Farah Sarwar, Anthony Griffin, Saeed Ur Rehman, Timotius Pasang

In this work we consider the task of detecting sheep onboard an unmanned aerial vehicle (UAV) flying at an altitude of 80 m. At this height, the sheep are relatively small, only about 15 pixels across. Although deep learning strategies have gained enormous popularity in the last decade and are now extensively used for object detection in many fields, state-o

Saeed Nosratabadi, Amir Mosavi, Puhong Duan, Pedram Ghamisi

This paper provides the state of the art of data science in economics. Through a novel taxonomy of applications and methods advances in data science are investigated. The data science advances are investigated in three individual classes of deep learning models, ensemble models, and hybrid models. Application domains include stock market, marketing, E-commer

Jiawei Wu, Jianxue Li, Yang Xiao, Jun Liu

Routing is one of the key functions for stable operation of network infrastructure. Nowadays, the rapid growth of network traffic volume and changing of service requirements call for more intelligent routing methods than before. Towards this end, we propose a definition of cognitive routing and an implementation approach based on Deep Reinforcement Learning

Sofya Prakhova, Volker Rehbock, Igor Suleimanov

In this paper, we incorporate seasonal variations of insolation into the global climate model C-GOLDSTEIN. We use a new approach for modelling insolation from the space perspective presented in the authors' earlier work and build it into the existing climate model. Realistic monthly temperature distributions have been obtained after running C-GOLDSTEIN w

Safiqul Islam, Praveen Kumar, G. S. Khadekar, Tapas K Das

We intend to study a new class of cosmological models in $f(R, T)$ modified theories of gravity, hence define the cosmological constant $Λ$ as a function of the trace of the stress energy-momentum-tensor $T$ and the Ricci scalar $R$, and name such a model "$Λ(R, T)$ gravity" where we have specified a certain form of $Λ(R, T)$. $Λ(R, T)$ is also defin

M. V. Gorbatenko, V. P. Neznamov

The report considers the interaction of scalar particles, photons and fermions with the gravitational and electromagnetic Schwarzschild, Reissner-Nordström, Kerr and Kerr-Newman fields. The behavior of effective potentials in the relativistic Schrödinger-type second-order equations is analyzed. It was found that the quantum theory is incompatible with the hy

Han Liu, Shantao Liu

EQL, also named as Extremely Simple Query Language, can be widely used in the field of knowledge graph, precise search, strong artificial intelligence, database, smart speaker ,patent search and other fields. EQL adopt the principle of minimalism in design and pursues simplicity and easy to learn so that everyone can master it quickly. EQL language and lambd

Jerrin Thomas Panachakel, A. G. Ramakrishnan, A. G. Ramakrishnan

This paper proposes a novel approach that uses deep neural networks for classifying imagined speech, significantly increasing the classification accuracy. The proposed approach employs only the EEG channels over specific areas of the brain for classification, and derives distinct feature vectors from each of those channels. This gives us more data to train a

Romit Maulik, Junghwa Choi, Wesley Wehde, Prasanna Balaprakash

Given the importance of public support for policy change and implementation, public policymakers and researchers have attempted to understand the factors associated with this support for climate change mitigation policy. In this article, we compare the feasibility of using different supervised learning methods for regression using a novel socio-economic data

S. Son

A new x-ray amplification mechanism is considered in an interaction between a x-ray and an intense visible-light laser in a plasma. In normal circumstances, the x-ray amplification from this type of the physical processes is implausible because its phase, which is the \textbf{non-resonant} perturbation, is not suitable for transferring the energy from the vi

Mohammad R. Piri, Saeid Alikhani

We introduce and study the dominated edge coloring of a graph. A dominated edge coloring of a graph $G$ is a proper edge coloring of $G$ such that each color class is dominated by at least one edge of $G$. The minimum number of colors among all dominated edge coloring is called the dominated edge chromatic number, denoted by $χ_{dom}^{\prime}(G)$. We obtain

David Speyer, Lauren K. Williams

The Dressian and the tropical Grassmannian parameterize abstract and realizable tropical linear spaces; but in general, the Dressian is much larger than the tropical Grassmannian. There are natural positive notions of both of these spaces -- the positive Dressian, and the positive tropical Grassmannian (which we introduced roughly fifteen years ago) -- so it

Alessio Chiapperini, Marino Miculan, Marco Peressotti

Directed bigraphs are a meta-model which generalises Milner's bigraphs by taking into account the request flow between controls and names. A key problem about these bigraphs is that of bigraph embedding, i.e., finding the embeddings of a bigraph inside a larger one.We present an algorithm for computing embeddings of directed bigraphs, via a reduction to

Zijian Wang, Wen Chen, Feifei Gao, Jun Li

In this paper, we consider a dual-hop Multiple Input Multiple Output (MIMO) wireless relay network in the presence of imperfect channel state information (CSI), in which a source-destination pair both equipped with multiple antennas communicates through a large number of half-duplex amplify-and-forward (AF) relay terminals. We investigate the performance of

Antonio Petraglia, Carmina Sirignano, Raffaele Buompane, Antonio D'Onofrio

An environmental survey was carried out in order to provide an adequate and updated assessment of the radiological impact that the decommissioning operations of the Garigliano NNP may have procured to the environment of the surrounding area. Some isotopes of uranium (235U, 236U, 238U) and plutonium (239Pu, 240Pu) and some γ-emitter radionuclides (60Co, 137Cs

Sihua Wang, Mingzhe Chen, Changchuan Yin, Walid Saad

In this paper, the problem of minimizing energy and time consumption for task computation and transmission is studied in a mobile edge computing (MEC)-enabled balloon network. In the considered network, each user needs to process a computational task in each time instant, where high-altitude balloons (HABs), acting as flying wireless base stations, can use t

Jerrin Thomas Panachakel, A. G. Ramakrishnan, T. V. Ananthapadmanabha

The recent advances in the field of deep learning have not been fully utilised for decoding imagined speech primarily because of the unavailability of sufficient training samples to train a deep network. In this paper, we present a novel architecture that employs deep neural network (DNN) for classifying the words "in" and "cooperate" from th

Andreas Heuer

The forecasting of sports events is of broad interest from the applied but also from the theoretical perspective. In this work the question is addressed for the example of the German soccer Bundesliga how a theoretically optimum forecast of the goal difference of a match can be characterized. This involves a careful analysis of the random contributions in a

Wilhelm von Waldenfels

The resolvent function of an operator in a Banach space is defined on an open subset of the complex plane and is holomorphic. It obeys the resolvent equation. A generalization of this equation to Schwartz distributions is defined and a Schwartz distribution, which satisfies that equation is called a resolvent distribution. In important cases the resolvent di

Mohamadreza Ahmadi, Andrew Singletary, Joel W. Burdick, Aaron D. Ames

Multi-agent partially observable Markov decision processes (MPOMDPs) provide a framework to represent heterogeneous autonomous agents subject to uncertainty and partial observation. In this paper, given a nominal policy provided by a human operator or a conventional planning method, we propose a technique based on barrier functions to design a minimally inte

Tsuyoshi Miezaki

In a previous study, we presented a construction of spherical 3-designs. In the current study, using this construction, we present new optimal antipodal spherical codes in the space of spherical harmonics. Our construction is a generalization of Bondarenko's work.

Tapan Kumar Pradhan, Pradipta Kumar Panigrahi

Fluid convection during protein crystallization plays a significant role in determining crystal growth rate and crystal quality. Crystals grown in reduced flow strength gives better quality crystal. Hence, tuning the flow strength is very essential in the crystal growth process. In this work, we have demonstrated a new method to suppress the flow strength us

Oscar Delgado-Mohatar, Julian Fierrez, Ruben Tolosana, Ruben Vera-Rodriguez

Blockchain technologies provide excellent architectures and practical tools for securing and managing the sensitive and private data stored in biometric templates, but at a cost. We discuss opportunities and challenges in the integration of blockchain and biometrics, with emphasis in biometric template storage and protection, a key problem in biometrics stil

Alexandre Morin, Jorge Samper-González, Anne Bertrand, Sebastian Stroer

BACKGROUND:Automated volumetry software (AVS) has recently become widely available to neuroradiologists. MRI volumetry with AVS may support the diagnosis of dementias by identifying regional atrophy. Moreover, automatic classifiers using machine learning techniques have recently emerged as promising approaches to assist diagnosis. However, the performance of

Freddy Delbaen

We give two equivalent definitions of sigma algebras that are atomless conditionally to a smaller sigma algebra.

Suat Gumussoy, Wim Michiels

We present a numerical method to plot the root locus of Single-Input-Single-Output (SISO) dead-time systems with respect to the controller gain or the system delay. We compute the trajectories of characteristic roots of the closed-loop system on a prescribed complex right half-plane. We calculate the starting, branch and boundary crossing roots of root-locus

Suat Gumussoy, Wim Michiels

We analyze and design H-infinity controllers for general time-delay systems with time-delays in systems' state, inputs and outputs. We allow the designer to choose the order of the controller and to introduce constant time-delays in the controller. The closed-loop system of the plant and the controller is modeled by a system of delay differential algebra

Rajan Puri

For the cubic ab-family of equations with $a\neq0$, it is proved that there exists an initial data in the Sobolev space $H^s$, $s<3/2$, with non-unique solutions on the circle.

Grzegorz Pastuszak, Adam Skowyrski, Andrzej Jamiołkowski

We give an algorithm determining whether a hermiticity-preserving superoperator is positive. In our approach we apply techniques of quantifier elimination theory for real numbers. Furthermore, we argue that quantifier elimination theory should play more significant role in quantum information theory and other areas as well.

Chu Wang, Babak Samari, Vladimir G. Kim, Siddhartha Chaudhuri

Affinity graphs are widely used in deep architectures, including graph convolutional neural networks and attention networks. Thus far, the literature has focused on abstracting features from such graphs, while the learning of the affinities themselves has been overlooked. Here we propose a principled method to directly supervise the learning of weights in af

Victor Vermehren Valenzuela, H. M. de Oliveira

This paper presents a new topology for photonic crystals to replace the monochromator, introducing them with a new alignment (the so-called extended Trinitron) to guide the chromatic pattern producing a spatial distribution similar to that of conventional diffraction gratings. The spectrophotometer uses a LED white light as light source instead of chambers w

Chelsey Edge, Sadman Sakib Enan, Michael Fulton, Jungseok Hong

In this paper we present LoCO AUV, a Low-Cost, Open Autonomous Underwater Vehicle. LoCO is a general-purpose, single-person-deployable, vision-guided AUV, rated to a depth of 100 meters. We discuss the open and expandable design of this underwater robot, as well as the design of a simulator in Gazebo. Additionally, we explore the platform&#39;s preliminary l

J Andrés Christen, Al Parker

In microbial studies, samples are often treated under different experimental conditions and then tested for microbial survival. A technique, dating back to the 1880&#39;s, consists of diluting the samples several times and incubating each dilution to verify the existence of microbial Colony Forming Units or CFU&#39;s, seen by the naked eye. The main problem

Masayuki Karasuyama, Hiroki Kasugai, Tomoyuki Tamura, Kazuki Shitara

Ion-conducting solid electrolytes are widely used for a variety of purposes. Therefore, designing highly ion-conductive materials is in strongly demand. Because of advancement in computers and enhancement of computational codes, theoretical simulations have become effective tools for investigating the performance of ion-conductive materials. However, an exha

Kananart Kuwaranancharoen, Shreyas Sundaram

The problem of finding the minimizer of a sum of convex functions is central to the field of optimization. Thus, it is of interest to understand how that minimizer is related to the properties of the individual functions in the sum. In this paper, we consider the scenario where one of the individual functions in the sum is not known completely. Instead, only

Albertine Weber, Flavio Ianelli, Sebastian Goncalves

The recent epidemic of Coronavirus (COVID-19) that started in China has already been &#34;exported&#34; to more than 140 countries in all the continents, evolving in most of them by local spreading. In this contribution we analyze the trends of the cases reported in all the Chinese provinces, as well as in some countries that, until March 15th, 2020, have mo

Nasrin Taghizadeh, Zeinab Borhanifard, Melika GolestaniPour, Heshaam Faili

NSURL-2019 Task 7 focuses on Named Entity Recognition (NER) in Farsi. This task was chosen to compare different approaches to find phrases that specify Named Entities in Farsi texts, and to establish a standard testbed for future researches on this task in Farsi. This paper describes the process of making training and test data, a list of participating teams

Manuel Bernal, Javier Civera

Developing real robotic systems requires a tight integration of mechanics, electronics and software. Most of the times, existing robotic platforms are either closed or expensive or both, and in-house solutions are costly to develop and maintain. Open-source and low-cost designs are essential to facilitate the access to real robotic platforms and enable furth

Nikolay Malkovsky, Vladimir Bataev, Dmitrii Sviridkin, Natalia Kizhaeva

The problem of out of vocabulary words (OOV) is typical for any speech recognition system, hybrid systems are usually constructed to recognize a fixed set of words and rarely can include all the words that will be encountered during exploitation of the system. One of the popular approach to cover OOVs is to use subword units rather then words. Such system ca

John Mern, Dorsa Sadigh, Mykel J. Kochenderfer

Poor sample efficiency is a major limitation of deep reinforcement learning in many domains. This work presents an attention-based method to project neural network inputs into an efficient representation space that is invariant under changes to input ordering. We show that our proposed representation results in an input space that is a factor of $m!$ smaller

Maximilian Bremer, John Bachan, Cy Chan, Clint Dawson

This paper proposes a first-order total variation diminishing (TVD) treatment for coarsening and refining of local timestep size in response to dynamic local variations in wave speeds for nonlinear conservation laws. The algorithm is accompanied with a proof of formal correctness showing that given a sufficiently small minimum timestep the algorithm will pro

Samet E. Arda, Anish NK, A. Alper Goksoy, Nirmal Kumbhare

Heterogeneous systems-on-chip (SoCs) are highly favorable computing platforms due to their superior performance and energy efficiency potential compared to homogeneous architectures. They can be further tailored to a specific domain of applications by incorporating processing elements (PEs) that accelerate frequently used kernels in these applications. Howev

Yifan Li, Xiaohui Yu, Nick Koudas

Recent advances in social and mobile technology have enabled an abundance of digital traces (in the form of mobile check-ins, association of mobile devices to specific WiFi hotspots, etc.) revealing the physical presence history of diverse sets of entities (e.g., humans, devices, and vehicles). One challenging yet important task is to identify k entities tha

Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi

Standardized benchmarks are crucial for the majority of computer vision applications. Although leaderboards and ranking tables should not be over-claimed, benchmarks often provide the most objective measure of performance and are therefore important guides for research. The benchmark for Multiple Object Tracking, MOTChallenge, was launched with the goal to e

Matej Kanduc, Won Kyu Kim, Rafael Roa, Joachim Dzubiella

In modern applications of heterogeneous liquid-phase nanocatalysis, the catalysts (e.g., metal nanoparticles) need to be typically affixed to a colloidal carrier system for stability and easy handling. &#34;Passive carriers&#34; (e.g., simple polyelectrolytes) serve for a controlled synthesis of the nanoparticles and prevent coagulation during catalysis. Rec

Simon Odense, Artur d&#39;Avila Garcez

Knowledge extraction is used to convert neural networks into symbolic descriptions with the objective of producing more comprehensible learning models. The central challenge is to find an explanation which is more comprehensible than the original model while still representing that model faithfully. The distributed nature of deep networks has led many to bel

Bernhard Endtmayer, Ulrich Langer, Thomas Wick

We derive efficient and reliable goal-oriented error estimations, and devise adaptive mesh procedures for the finite element method that are based on the localization of a posteriori estimates. In our previous work [SIAM J. Sci. Comput., 42(1), A371--A394, 2020], we showed efficiency and reliability for error estimators based on enriched finite element space

Jyri J. Lehtinen, Federico Spada, Maarit J. Käpylä, Nigul Olspert

One interpretation of the activity and magnetism of late-type stars is that these both intensify with decreasing Rossby number up to a saturation level, suggesting that stellar dynamos depend on both rotation and convective turbulence. Some studies have claimed, however, that rotation alone suffices to parametrise this scaling adequately. Here, we tackle the

Luis A. Pérez Rey

A disentangled representation of a data set should be capable of recovering the underlying factors that generated it. One question that arises is whether using Euclidean space for latent variable models can produce a disentangled representation when the underlying generating factors have a certain geometrical structure. Take for example the images of a car s

G. Karapetyan

We study the net-baryon production at forward rapidities within the Color Glass Condensate paradigm. At high energy regime, the leading baryon production mechanism is shown to change from recombination to independent fragmentation. The nuclear configurational entropy (NCE) constructed upon forward scattering amplitudes, allows to predict the two free paramet

Lev Klebanov, Yulia Kuvaeva, Zeev Volkovich

A model of scientific citation distribution is given. We apply it to understand the role of the Hirsch index as an indicator of scientific publication importance in Mathematics and some related fields. The proposed model is based on a generalization of such well-known distributions as geometric and Sibuja laws included now in a family of distributions. Real

Kovila P. L. Coopamootoo

While it is often claimed that users are empowered via online technologies, there is also a general feeling of privacy dis-empowerment. We investigate the perception of privacy and sharing empowerment online, as well as the use of privacy technologies, via a cross-national online study with N=907 participants. We find that perception of privacy empowerment d

Min-ge Xie, Zheshi Zheng

This note uses a conformal prediction procedure to provide further support on several points discussed by Professor Efron (Efron, 2020) concerning prediction, estimation and IID assumption. It aims to convey the following messages: (1) Under the IID (e.g., random split of training and testing data sets) assumption, prediction is indeed an easier task than es

Behzad Ghanbarian, Feng Liang, Hui-Hai Liu

Accurate modeling of gas relative permeability has practical applications in oil and gas exploration, production and recovery of unconventional reservoirs. In this study, we apply concepts from the effective-medium approximation (EMA) and universal power-law scaling from percolation theory. Although the EMA has been successfully used to estimate relative per

Chiyu Max Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang

Shape priors learned from data are commonly used to reconstruct 3D objects from partial or noisy data. Yet no such shape priors are available for indoor scenes, since typical 3D autoencoders cannot handle their scale, complexity, or diversity. In this paper, we introduce Local Implicit Grid Representations, a new 3D shape representation designed for scalabil

Mehran Soltani, Vahid Pourahmadi, Hamid Sheikhzadeh

In this paper, we present a downlink pilot design scheme for Deep Learning (DL) based channel estimation (ChannelNet) in orthogonal frequency-division multiplexing (OFDM) systems. Specifically, in the proposed scheme, a feature selection method named Concrete Autoencoder (ConcreteAE) is used to find the most informative locations for pilot transmission. This

Steven A. Frank, William Godsoe

The Price equation partitions the change in the expected value of a population measure. The first component describes the partial change caused by altered frequencies. The second component describes the partial change caused by altered measurements. In biology, frequency changes often associate with the direct effect of natural selection. Measure changes ref

Martina Lippi, Petra Poklukar, Michael C. Welle, Anastasiia Varava

We present a framework for visual action planning of complex manipulation tasks with high-dimensional state spaces such as manipulation of deformable objects. Planning is performed in a low-dimensional latent state space that embeds images. We define and implement a Latent Space Roadmap (LSR) which is a graph-based structure that globally captures the latent

Andrew T. T. McRae, Tim N. Palmer

In recent years, it has been convincingly shown that weather forecasting models can be run in single-precision arithmetic. Several models or components thereof have been tested with even lower precision than this. This previous work has largely focused on the main nonlinear `forward&#39; model. A nonlinear model (in weather forecasting or otherwise) can have

Alfredo Miranda, Julio D Rossi

In this paper we find viscosity solutions to an elliptic system governed by two different operators (the Laplacian and the infinity Laplacian) using a probabilistic approach. We analyze a game that combines the Tug-of-War with Random Walks in two different boars. We show that these value functions converge uniformly to a viscosity solution of the elliptic sy

Ya-Ping Lu, Shu-Fang Deng

Lattice polytope representation of natural numbers is introduced based on the fundamental theorem of arithmetic. The combinatorial and geometric properties of the polytopes are studied using Polymake and Qhull software. The volume of the polytope representing a natural number and the sum of the volumes of polytopes representing a subset of natural numbers ar

Katrin Madjar, Jörg Rahnenführer

An important task in clinical medicine is the construction of risk prediction models for specific subgroups of patients based on high-dimensional molecular measurements such as gene expression data. Major objectives in modeling high-dimensional data are good prediction performance and feature selection to find a subset of predictors that are truly associated

K. Godbey, A. S. Umar

In the search for superheavy elements quasifission reactions represent one of the reaction pathways that curtail the formation of an evaporation residue. In addition to its importance in these searches quasifission is also an interesting dynamic process that could assist our understanding of many-body dynamical shell effects and energy dissipation thus formi

E. Charpentier, F. Lapeyre, J. Gautier, L. Waszczuk

We demonstrate swept-source optical coherence tomography in real-time by high throughput digital Fresnel hologram rendering from optically-acquired interferograms with a high-speed camera. The interferogram stream is spatially rescaled with respect to wavelength to compensate for field-of-view dilation inherent to discrete Fresnel transformation. Holograms a

Yuzhou Liu, Balaji Thoshkahna, Ali Milani, Trausti Kristjansson

Music source separation has been a popular topic in signal processing for decades, not only because of its technical difficulty, but also due to its importance to many commercial applications, such as automatic karoake and remixing. In this work, we propose a novel self-attention network to separate voice and accompaniment in music. First, a convolutional ne

Nicholas C. Stone, Eugene Vasiliev, Michael Kesden, Elena M. Rossi

Tidal disruption events occur rarely in any individual galaxy. Over the last decade, however, time-domain surveys have begun to accumulate statistical samples of these flares. What dynamical processes are responsible for feeding stars to supermassive black holes? At what rate are stars tidally disrupted in realistic galactic nuclei? What may we learn about s

Mayuri Sathyanarayana Rao, Maximiliano Silva-Feaver, Aamir Ali, Kam Arnold

The Simons Observatory (SO) is an upcoming polarization-sensitive Cosmic Microwave Background (CMB) experiment on the Cerro Toco Plateau (Chile) with large overlap with other optical and infrared surveys (e.g., DESI, LSST, HSC). To enable the readout of \bigO(10,000) detectors in each of the four telescopes of SO, we will employ the microwave SQUID multiplex

Christine Bauer, Katharina Sophie Schmid, Christine Strauss

The analysis of consumers&#39; personal information (PI) is a significant source to learn about consumers. In online settings, many consumers disclose PI abundantly -- this is particularly true for information provided on social network services. Still, people manage the privacy level they want to maintain by disclosing by disclosing PI accordingly. In addit

Swati Mudra, Aniruddha Chakraborty

We propose a very simple one dimensional analytically solvable model for understanding the problem of electronic relaxation of molecules in solution. This problem is modeled by a particle diffusing under the influence of parabolic potential in presence of a sink of ultra-short width. The diffusive motion is described by the Smoluchowski equation and shape of

Amin Ghiasi, Ali Shafahi, Tom Goldstein

To deflect adversarial attacks, a range of &#34;certified&#34; classifiers have been proposed. In addition to labeling an image, certified classifiers produce (when possible) a certificate guaranteeing that the input image is not an $\ell_p$-bounded adversarial example. We present a new attack that exploits not only the labelling function of a classifier, bu

Yawei Li, Shuhang Gu, Christoph Mayer, Luc Van Gool

In this paper, we analyze two popular network compression techniques, i.e. filter pruning and low-rank decomposition, in a unified sense. By simply changing the way the sparsity regularization is enforced, filter pruning and low-rank decomposition can be derived accordingly. This provides another flexible choice for network compression because the techniques

Liang Zhang, Mariano Méndez, Diego Altamirano, Jinlu Qu

We present a systematic analysis of the phase lags associated with the type-C QPOs in GRS 1915+105 using RXTE data. Our sample comprises of 620 RXTE observations with type-C QPOs ranging from ~0.4 Hz to ~6.3 Hz. Based on our analysis, we confirm that the QPO phase lags decrease with QPO frequency, and change sign from positive to negative at a QPO frequency

Anoop Kunchukuttan, Pushpak Bhattacharyya

In this work, we present an extensive study of statistical machine translation involving languages of the Indian subcontinent. These languages are related by genetic and contact relationships. We describe the similarities between Indic languages arising from these relationships. We explore how lexical and orthographic similarity among these languages can be

Jiawei Li, Chuyu Wang, Ang Li, Dianqi Han

Passive RFID technology is widely used in user authentication and access control. We propose RF-Rhythm, a secure and usable two-factor RFID authentication system with strong resilience to lost/stolen/cloned RFID cards. In RF-Rhythm, each legitimate user performs a sequence of taps on his/her RFID card according to a self-chosen secret melody. Such rhythmic t

Olivier Nicole, Matthieu Lemerre, Sébastien Bardin, Xavier Rival

Operating system kernels are the security keystone of most computer systems, as they provide the core protection mechanisms. Kernels are in particular responsible for their own security, i.e. they must prevent untrusted user tasks from reaching their level of privilege. We demonstrate that proving such absence of privilege escalation is a pre-requisite for a

Andrew N. W. Hone, Theodoros E. Kouloukas

We study the integrability of a family of birational maps obtained as reductions of the discrete Hirota equation, which are related to travelling wave solutions of the lattice KdV equation. In particular, for reductions corresponding to waves moving with rational speed N/M on the lattice, where N,M are coprime integers, we prove the Liouville integrability o

Longteng Guo, Jing Liu, Xinxin Zhu, Peng Yao

Self-attention (SA) network has shown profound value in image captioning. In this paper, we improve SA from two aspects to promote the performance of image captioning. First, we propose Normalized Self-Attention (NSA), a reparameterization of SA that brings the benefits of normalization inside SA. While normalization is previously only applied outside SA, we

Marco Hartl, Diego F. Bedoya-Ríos, Marta Fernández-Gatell, Diederik P. L. Rousseau

Microbial fuel cells implemented in constructed wetlands (CW-MFCs), albeit a relatively new technology still under study, have shown to improve treatment efficiency of urban wastewater. So far the vast majority of CW-MFC systems investigated were designed as lab-scale systems working under rather unrealistic hydraulic conditions using synthetic wastewater. T

Daryl Cooper

There is a compactification of the space of representations of a finitely generated group into the groups of isometries of all spaces with $Δ$-thin triangles. The ideal points are actions on $\mathbb R$-trees. It is a geometric reformulation and extension of the Culler-Morgan-Shalen theory concerning limits of representations into $\operatorname{SL}(2,{\math

Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet

Locally Rotation Invariant (LRI) image analysis was shown to be fundamental in many applications and in particular in medical imaging where local structures of tissues occur at arbitrary rotations. LRI constituted the cornerstone of several breakthroughs in texture analysis, including Local Binary Patterns (LBP), Maximum Response 8 (MR8) and steerable filter

Ming Li, Huihui Qin, Chengjie Zhang, Shuqian Shen

Entanglement of high-dimensional and multipartite quantum systems offer promising perspectives in quantum information processing. However, the characterization and measure of such kind of entanglement is of great challenge. Here we consider the overlaps between the maximal quantum mean values and the classical bound of the CHSH inequalities for pairwise-qubi

Peter M Larsen

We review two standard methods for structural classification in simulations of crystalline phases, the Common Neighbour Analysis and the Centrosymmetry Parameter. We explore the definitions and implementations of each of their common variants, and investigate their respective failure modes and classification biases. Simple modifications to both methods are p

Ehsan Taher, Seyed Abbas Hoseini, Mehrnoush Shamsfard

Named entity recognition is a natural language processing task to recognize and extract spans of text associated with named entities and classify them in semantic Categories. Google BERT is a deep bidirectional language model, pre-trained on large corpora that can be fine-tuned to solve many NLP tasks such as question answering, named entity recognition, par

Christopher X. Ren, Matthew T. Calef, Alice M. S. Durieux, A. Ziemann

The detection and quantification of conflict through remote sensing modalities represents a challenging but crucial aspect of human rights monitoring. In this work we demonstrate how utilizing multi-modal data sources can help build a comprehensive picture of conflict and human displacement, using the Rohingya conflict in the state of Rakhine, Myanmar as a c

G. Molpeceres, J. Kästner

We investigated the behavior of H$_2$, main constituent of the gas phase in dense clouds, after collision with amorphous solid water (ASW) surfaces, one of the most abundant chemical species of interstellar ices. We developed a general framework to study the adsorption dynamics of light species on interstellar ices. We provide binding energies and their dist

Makars Šiškins, Martin Lee, Dominique Wehenkel, Richard van Rijn

The high flexibility, impermeability and strength of graphene membranes are key properties that can enable the next generation of nanomechanical sensors. However, for capacitive pressure sensors the sensitivity offered by a single suspended graphene membrane is too small to compete with commercial sensors. Here, we realize highly sensitive capacitive pressur

Yuan Gao, Robert Bregovic, Reinhard Koch, Atanas Gotchev

The Image-Based Rendering (IBR) approach using Shearlet Transform (ST) is one of the most effective methods for Densely-Sampled Light Field (DSLF) reconstruction. The ST-based DSLF reconstruction typically relies on an iterative thresholding algorithm for Epipolar-Plane Image (EPI) sparse regularization in shearlet domain, involving dozens of transformations

Frederic Paik Schoenberg

An extension of the Hawkes model where the productivity is variable is considered. In particular, the case is considered where each point may have its own productivity and a simple analytic formula is derived for the maximum likelihood estimators of these productivities. This estimator is compared with an empirical estimator and ways are explored of stabiliz

Qiuhao Hu, Mohammad Reza Amini, Hao Wang, Ilya Kolmanovsky

In this paper, a multi-horizon model predictive controller (MH-MPC) is developed for integrated power and thermal management (iPTM) of a power-split hybrid electric vehicle (HEV). The proposed MH-MPC leverages an accurate short-horizon vehicle speed preview and an approximate forecast over a longer shrinking horizon till the end of the driving cycle. This mu

Ryan R. Petersburg, J. M. Joel Ong, Lily L. Zhao, Ryan T. Blackman

The EXtreme PREcision Spectrograph (EXPRES) is an environmentally stabilized, fiber-fed, $R=137,500$, optical spectrograph. It was recently commissioned at the 4.3-m Lowell Discovery Telescope (LDT) near Flagstaff, Arizona. The spectrograph was designed with a target radial-velocity (RV) precision of 30$\mathrm{~cm~s^{-1}}$. In addition to instrumental innov