November 2019 arXiv papers — page 49

Minh Le

Deep neural networks have achieved impressive performance and become the de-facto standard in many tasks. However, troubling phenomena such as adversarial and fooling examples suggest that the generalization they make is flawed. I argue that among the roots of the phenomena are two geometric properties of common deep learning architectures: their distributed

Keisuke Sugiura, Hiroshi Kobayashi, Shu-ichiro Inutsuka

The members of asteroid families have various shapes. We investigate the origin of their shapes by high-resolution impact simulations for catastrophic disruptions using a Smoothed Particle Hydrodynamics code. Collisional remnants produced through our simulations of the catastrophic disruptions mainly have spherical or bilobed shapes. However, no flat remnant

Soheil Salehi, Ronald F. DeMara

A Compressive Sensing (CS) approach is applied to utilize intrinsic computation capabilities of Spin-Orbit Torque Magnetic Random Access Memory (SOT-MRAM) devices for IoT applications wherein lifetime energy, device area, and manufacturing costs are highly-constrained while the sensing environment varies rapidly. In this manuscript, we propose the Adaptive C

D. Hernandez, L. Quinones, C. Charnay, M. Velazquez

In this paper, we evaluate the structural stability of a natural Cuban clay (an adsorbent of organic pollutants) after an adsorption-desorption process. The clay under study was palygorskite, and sulfamethoxazole was the emerging contaminant. The materials were characterized by X-ray diffraction, attenuated total reflection infrared spectroscopy and zeta pot

Andres Quiros-Granados, JAvier Trejos-Zelaya

The term structure of interest rates or yield curve is a function relating the interest rate with its own term. Nonlinear regression models of Nelson-Siegel and Svensson were used to estimate the yield curve using a sample of historical data supplied by the National Stock Exchange of Costa Rica. The optimization problem involved in the estimation process of

U. D. Jentschura

We investigate the particle-antiparticle symmetry of the gravitationally coupled Dirac equation, both on the basis of the gravitational central-field problem and in general curved space-time backgrounds. First, we investigate the central-field problem with the help of a Foldy-Wouthuysen transformation. This disentangles the particle from the antiparticle sol

Angelo Antonio Salatino

Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. The literature presents several approaches to identifying the emergence of new research topics, which rely on the assumption that the topic is already exhibiting a certain degree of p

Svitlana Alkhimova

The object of research in this study is quality of CBV perfusion map, considering detection of perfusion ROI as a key component in processing of dynamic susceptibility contrast magnetic resonance images of a human head. CBV map is generally accepted to be the best among others to evaluate location and size of stroke lesions and angiogenesis of brain tumors.

Khondokar Fida Hasan, Tarandeep Kaur, Md. Mhedi Hasan, Yanming Feng

Over the past few years, we have experienced great technological advancements in the information and communication field, which has significantly contributed to reshaping the Intelligent Transportation System (ITS) concept. Evolving from the platform of a collection of sensors aiming to collect data, the data exchanged paradigm among vehicles is shifted from

Azim Ahmadzadeh, Sushant S. Mahajan, Dustin J. Kempton, Rafal A. Angryk

We use a well-known deep neural network framework, called Mask R-CNN, for identification of solar filaments in full-disk H-alpha images from Big Bear Solar Observatory (BBSO). The image data, collected from BBSO's archive, are integrated with the spatiotemporal metadata of filaments retrieved from the Heliophysics Events Knowledgebase (HEK) system. This

Bruce Knuteson

As the decade turns, we reflect on nearly thirty years of successful manipulation of the world's public equity markets. This reflection highlights a few of the key enabling ingredients and lessons learned along the way. A quantitative understanding of market impact and its decay, which we cover briefly, lets you move long-term market prices to your advan

Wentao Jiang, Felix M. Mayor, Rishi N. Patel, Timothy P. McKenna

Tuning and reconfiguring nanophotonic components is needed to realize systems incorporating many components. The electrostatic force can deform a structure and tune its optical response. Despite the success of electrostatic actuators, they suffer from trade-offs between tuning voltage, tuning range, and on-chip area. Piezoelectric actuation could resolve all

Guido Cantelmo, Kucharski Rafal, Constantinos Antoniou

Big, transport-related datasets are nowadays publicly available, which makes data-driven mobility analysis possible. Trips with their origins, destinations and travel times are collected in publicly available big databases, which allows for a deeper and richer understanding of mobility patterns. This paper proposes a low dimensional approach to combine these

Tao Xue, Jinfu Zhu, Jingjun Wen, Jirong Cang

Sufficient current pulse information of nuclear radiation detectors can be retained by direct waveform digitization owing to the improvement of digitizer's performance. In many circumstances, reasonable cost and power consumption are on demand while the energy resolution and PSD performance should be ensured simultaneously for detectors. This paper will

Arnob Ray, Arindam Mishra, Dibakar Ghosh, Tomasz Kapitaniak

We report rare and recurrent large spiking events in a heterogeneous network of superconducting Josephson junctions (JJ) connected through a resistive load and driven by a radio-frequency (rf) current in addition to a constant bias. The intermittent large spiking events show characteristic features of extreme events (EE) since they are larger than a statisti

Oluwafemi Azeez

It is expensive to generate real-life image labels and there is a domain gap between real-life and simulated images, hence a model trained on the latter cannot adapt to the former. Solving this can totally eliminate the need for labeling real-life datasets completely. Class balanced self-training is one of the existing techniques that attempt to reduce the d

Rajesh Chitnis, Graham Cormode

Parameterized complexity attempts to give a more fine-grained analysis of the complexity of problems: instead of measuring the running time as a function of only the input size, we analyze the running time with respect to additional parameters. This approach has proven to be highly successful in delineating our understanding of \NP-hard problems. Given this

Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang

Visual events are usually accompanied by sounds in our daily lives. However, can the machines learn to correlate the visual scene and sound, as well as localize the sound source only by observing them like humans? To investigate its empirical learnability, in this work we first present a novel unsupervised algorithm to address the problem of localizing sound

Bilel Selmi

The aim of this paper is to study the behavior of the multifractal Hewitt-Stromberg dimension functions under projections in Euclidean space. As an application, we study the multifractal analysis of the projections of a measure. In particular, we obtain general results for the multifractal analysis of the orthogonal projections on $m$-dimensional linear subs

Remzi Celebi, Joao Rebelo Moreira, Ahmed A. Hassan, Sandeep Ayyar

It is essential for the advancement of science that scientists and researchers share, reuse and reproduce workflows and protocols used by others. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of research data, and emphasize a number of important points regarding the means by which digital objects are found and reus

Amirul Islam

The evolution of internet of vehicles (IoV) and the growing use of mobile devices with the development of the Internet of Things, demand has grown for alternative wireless communication technologies. As a promising alternative, optical-camera communication (OCC) has emerged that uses light-emitting diode (LED) and camera as transmitter and receiver respectiv

Alvin Peng, Fei Liu

Flooding due to Hurricane Florence led to billions of dollars in damage and nearly a hundred deaths in North Carolina. These damages and fatalities can be avoided with proper prevention and preparation. Modelling such flooding events can provide insight and precaution based on principles of fluid dynamics and GIS technology. Using topography and other geogra

Zhendong Guo, Zhanhong Ye, Weihao Shao, Lili Jing

Photoacoustic microscopy (PAM) is a promising imaging modality because it is able to reveal optical absorption contrast in high resolution on the order of a micrometer. It can be applied in an endoscopic approach by implementing PAM into a miniature probe, termed as photoacoustic endoscopy (PAE). Here we develop a miniature focus-adjustable PAE (FA-PAE) prob

Santu Mondal, Sourav Dutta, Subenoy Chakraborty

The present work deals with scalar field cosmology in the framework of a quantum gravity modified Einstein-Hilbert Lagrangian with variable $G$ and $Λ$. Using Renormalization group, variable $G$ behaves as a minimally coupled filed (not the scalar-tensor theory) and variable $Λ$ can be interpreted as a potential function. The point Lagrangian for this model

Arjun Krishna, A S Akil Arif Ibrahim

In this report, we introduce a video hashing method for scalable video segment copy detection. The objective of video segment copy detection is to find the video (s) present in a large database, one of whose segments (cropped in time) is a (transformed) copy of the given query video. This transformation may be temporal (for example frame dropping, change in

Samuel Sepúlveda, Mauricio Diéguez, Gonzalo Farías, Cristina Cachero

Context: The importance of defining learning outcomes and the planning stage for a systematic literature review. Objective: A protocol for carrying out a systematic literature review about the evidence for the tool support for the learning outcomes and the teaching-learning process using Bloom's taxonomy to address it. Method: The definition of a protoco

Saba Eskandarian, Mihai Christodorescu, Payman Mohassel

Widely used payment splitting apps allow members of a group to keep track of debts between members by sending charges for expenses paid by one member on behalf of others. While offering a great deal of convenience, these apps gain access to sensitive data on users' financial transactions. In this paper, we present a payment splitting app that hides all t

Lehilton Lelis Chaves Pedrosa, Hugo Kooki Kasuya Rosado

We consider the $k$-prize-collecting Steiner tree problem. An instance is composed of an integer $k$ and a graph $G$ with costs on edges and penalties on vertices. The objective is to find a tree spanning at least $k$ vertices which minimizes the cost of the edges in the tree plus the penalties of vertices not in the tree. This is one of the most fundamental

Andrew Hoyt, Matthew Guzdial, Yalini Kumar, Gillian Smith

In level co-creation an AI and human work together to create a video game level. One open challenge in level co-creation is how to empower human users to ensure particular qualities of the final level, such as challenge. There has been significant prior research into automated pathing and automated playtesting for video game levels, but not in how to incorpo

Yifeng Gao, Jessica Lin

Detecting repeating patterns of different lengths in time series, also called variable-length motifs, has received a great amount of attention by researchers and practitioners. Despite the significant progress that has been made in recent single dimensional variable-length motif discovery work, detecting variable-length \textit{subdimensional motifs}---patte

L. X. Gutiérrez-Guerrero, Adnan Bashir, Marco A. Bedolla, E. Santopinto

We compute masses of positive parity spin-$1/2$ and $3/2$ baryons composed of $u$, $d$, $s$, $c$ and $b$ quarks in a quark-diaquark picture. The mathematical foundation for this analysis is implemented through a symmetry-preserving Schwinger-Dyson equations treatment of a vector-vector contact interaction, which preserves key features of quantum chromodynami

Vasilios Mavroudis

Financial exchange operators cater to the needs of their users while simultaneously ensuring compliance with the financial regulations. In this work, we focus on the operators' commitment for fair treatment of all competing participants. We first discuss unbounded temporal fairness and then investigate its implementation and infrastructure requirements f

Volodymyr M. Gorkavenko

Despite the undeniable success of the Standard Model of particle physics (SM) there are some phenomena (neutrino oscillations, baryon asymmetry of the Universe, dark matter, etc.) that SM cannot explain. These phenomena indicate that the SM has to be modified. Most likely there are new particles beyond the SM. There are many experiments to search for new phy

Stanisław Jadach, Maciej Skrzypek

High energy, high luminosity, future lepton colliders, circular or linear, may possibly give us hint about fundamental laws of Nature governing at very short distances and very short time intervals, the same which have brought our Universe to live. Currently considered projects are on one hand linear electron-positron colliders, which offer higher energy and

Danilo Dominguez Perez, Wei Le

App quality has been shown to be the most important indicator of app adoption. To assure quality, developers mainly use testing to find bugs in app and apply structural and GUI test coverage criteria. However, mobile apps have more behaviors than the GUI actions, e.g. an app also handles events from sensors and executes long-running background tasks through

Jingru Yi, Hui Tang, Pengxiang Wu, Bo Liu

Instance segmentation of biological images is essential for studying object behaviors and properties. The challenges, such as clustering, occlusion, and adhesion problems of the objects, make instance segmentation a non-trivial task. Current box-free instance segmentation methods typically rely on local pixel-level information. Due to a lack of global object

James Davis

In order to answer questions about top conference publication patterns, citation data is collected and analyzed for several computer science conferences, with focus on computer vision and graphics. Both top and second tier conferences are included, and sampling occurred for two different 5 year periods. Example questions include: Do top conferences contain w

Yingchao Lu, Shengtai Li, Hui Li, Kirk A. Flippo

Three-dimensional FLASH radiation-magnetohydrodynamics (radiation-MHD) modeling is carried out to study the hydrodynamics and magnetic fields in the shock-shear derived platform. Simulations indicate that fields of tens of Tesla can be generated via Biermann battery effect due to vortices and mix in the counter-propagating shock-induced shear layer. Syntheti

Laura Cruciani, Nicolas Grandi

We construct the electron star solution to the model that was recently proposed by Kiritsis and Li in order to describe a holographic superconductor at finite doping. We do so by finding a map between the doped model and the standard undoped one. In this way, we are able to describe the holographic metallic phase at finite doping. In particular, we study the

Yingchao Lu, Hui Li, Kirk A. Flippo, Kwyntero Kelso

Proton radiography is used in various high-energy-density (HED) plasma experiments. In this paper, we describe a Monte Carlo and ray-tracing simulation tool called MPRAD that can be used for modeling the deflection of proton beams in arbitrary three dimensional electromagnetic fields, as well as the diffusion of the proton beams by Coulomb scattering and sto

Yudier Peña Pérez, Ricardo Abreu Blaya, Martín Patricio Árciga Alejandre, Juan Bory Reyes

In this work we propose a biquaternionic reformulation of a fractional monochromatic Maxwell system. Additionally, some examples are given to illustrate how the quaternionic fractional approach emerges in linear hydrodynamic and elasticity.

Sarthak Parikh

Conformal blocks play a central role in CFTs as the basic, theory-independent building blocks. However, only limited results are available concerning multipoint blocks associated with the global conformal group. In this paper, we systematically work out the $d$-dimensional $n$-point global conformal blocks (for arbitrary $d$ and $n$) for external and exchang

Christopher A. George, Bradley M. West

We address the challenge of applying existing convolutional neural network (CNN) architectures to compressed images. Existing CNN architectures represent images as a matrix of pixel intensities with a specified dimension; this desired dimension is achieved by downgrading or cropping. Downgrading and cropping are attractive in that the result is also an image

Junjia Wang, Adrien Rousseau, Mei Yang, Tony Low

The mid-infrared (MIR) spectral range is of immense use for civilian and military applications. The large number of vibrational absorption bands in this range can be used for gas sensing, process control and spectroscopy. In addition, there exists transparency windows in the atmosphere such as that between 3.6-3.8 $μ$m, which are ideal for free-space optical

Sergei Dyda, Christopher S. Reynolds, Yan-Fei Jiang

We use multi-frequency radiation hydrodynamics (rad-HD) to simulate radiative acceleration of a spherically symmetric stellar wind. We demonstrate the rad-HD capabilities of Athena++ for a series of test problems with multi-group radiation transfer. We then model the radiative transfer of a single spectral line through a spherically symmetric, isothermal, &#

Olga Rumyantseva, Andrey Sarantsev, Nikolay Strigul

In this work, we employ autoregressive models developed in financial engineering for modeling of forest dynamics. Autoregressive models have some theoretical advantage over currently employed forest modeling approaches such as Markov chains and individual-based models, as autoregressive models are both analytically tractable and operate with continuous state

E. M. B. Thiemann, F. G. Eparvier, D. Woodraska, P. C. Chamberlin

The Geostationary Operational Environmental Satellite R (GOES-R) series of four satellites are the next generation NOAA GOES satellites. Once on orbit and commissioned, they are renamed GOES 16-19, making critical terrestrial and space weather measurements through 2035. GOES 16 and 17 are currently on orbit, having been launched in 2016 and 2018, respectivel

Kai-Cheng Yang, Onur Varol, Pik-Mai Hui, Filippo Menczer

Efficient and reliable social bot classification is crucial for detecting information manipulation on social media. Despite rapid development, state-of-the-art bot detection models still face generalization and scalability challenges, which greatly limit their applications. In this paper we propose a framework that uses minimal account metadata, enabling eff

Yao Wang, Yi-Jun Chang, Jun Gao, Yong-Heng Lu

Graphene, a one-layer honeycomb lattice of carbon atoms, exhibits unconventional phenomena and attracts much interest since its discovery. Recently, an unexpected Mott-like insulator state induced by moiré pattern and a superconducting state are observed in magic-angle-twisted bilayer graphene, especially, without correlations between electrons, which gives

E. K. Anderson, A. F. Schmidt-May, P. K. Najeeb, G. Eklund

We report the first experimental evidence of spontaneous electron emission from a homonuclear dimer anion through direct measurements of $\rm{Ag}_2^- \rightarrow \rm{Ag}_2 + \rm{e}^-$ decays on milliseconds and seconds time scales. This observation is very surprising as there is no avoided crossing between adiabatic energy curves to mediate such a process. T

Philippe Brax, Carsten van de Bruck, Anne-Christine Davis

We consider the implications of the swampland conjectures on scalar-tensor theories defined in the Einstein frame in which the scalar interaction is screened. We show that chameleon models are not in the swampland provided the coupling to matter is larger than unity and the mass of the scalar field is much larger than the Hubble rate. We apply these conditio

Hamed H. Aghdam, Abel Gonzalez-Garcia, Joost van de Weijer, Antonio M. López

The cost of drawing object bounding boxes (i.e. labeling) for millions of images is prohibitively high. For instance, labeling pedestrians in a regular urban image could take 35 seconds on average. Active learning aims to reduce the cost of labeling by selecting only those images that are informative to improve the detection network accuracy. In this paper,

Gigi Y. C. Leung, Ryan Leaman, Glenn van de Ven, Giuseppina Battaglia

The five globular clusters (GCs) of the Fornax dSph are puzzling for two reasons; the mass in GCs is high with respect to the galaxy's old stellar mass, and their survival and large distance (> 1 kpc) is at odds with naive expectations of dynamical friction. We present here a semi-analytic model, simultaneously addressing both problems in a comprehensive

Anupam Gupta, Euiwoong Lee, Jason Li

In the $k$-cut problem, we are given an edge-weighted graph and want to find the least-weight set of edges whose deletion breaks the graph into $k$ connected components. Algorithms due to Karger-Stein and Thorup showed how to find such a minimum $k$-cut in time approximately $O(n^{2k-2})$. The best lower bounds come from conjectures about the solvability of

Lorenzo Brasco, Guido De Philippis, Giovanni Franzina

We prove that on a smooth bounded set, the positive least energy solution of the Lane-Emden equation with sublinear power is isolated. As a corollary, we obtain that the first $q-$eigenvalue of the Dirichlet-Laplacian is not an accumulation point of the $q-$spectrum, on a smooth bounded set. Our results extend to a suitable class of Lipschitz domains, as wel

David Wurm, Douglas H. Beck, Tim Chupp, Skyler Degenkolb

The neutron's permanent electric dipole moment $d_n$ is constrained to below $3\times10^{-26} e~\text{cm}$ (90% C.L.) [ arXiv:hep-ex/0602020, arXiv:1509.04411 ], by experiments using ultracold neutrons (UCN). We plan to improve this limit by an order of magnitude or more with PanEDM, the first experiment exploiting the ILL's new UCN source SuperSUN.

Jung-Shen B. Tai, Ivan I. Smalyukh

Starting from Gauss and Kelvin, knots in fields were postulated behaving like particles, but experimentally they were found only as transient features or required complex boundary conditions to exist and couldn't self-assemble into three-dimensional crystals. We introduce energetically stable micrometer-sized knots in helical fields of chiral liquid crys

Fanghui Liu, Xiaolin Huang, Yudong Chen, Jie Yang

In this paper, we propose a fast surrogate leverage weighted sampling strategy to generate refined random Fourier features for kernel approximation. Compared to the current state-of-the-art method that uses the leverage weighted scheme [Li-ICML2019], our new strategy is simpler and more effective. It uses kernel alignment to guide the sampling process and it

Rolf Haag

The present article includes the enumeration of $n$-polygons with two certain symmetry properties: For a number $3m$ of vertices, we count the $3m$-polygons with $m$ symmetry axes and the $3m$-polygons, that match after three elementary rotations, but have no symmetry axes. For those polygons we give complete lists of representatives of their equivalence-cla

Ivan Vendrov, Tyler Lu, Qingqing Huang, Craig Boutilier

Effective techniques for eliciting user preferences have taken on added importance as recommender systems (RSs) become increasingly interactive and conversational. A common and conceptually appealing Bayesian criterion for selecting queries is expected value of information (EVOI). Unfortunately, it is computationally prohibitive to construct queries with max

MohammadAmin Fazli, Alireza Amanihamedani

This paper aims to investigate how a central authority (e.g. a government) can increase social welfare in a network of markets and firms. In these networks, modeled using a bipartite graph, firms compete with each other \textit{à la} Cournot. Each firm can supply homogeneous goods in markets which it has access to. The central authority may take different po

Sebastian Ankargren, Måns Unosson, Yukai Yang

We propose a Bayesian vector autoregressive (VAR) model for mixed-frequency data. Our model is based on the mean-adjusted parametrization of the VAR and allows for an explicit prior on the 'steady states' (unconditional means) of the included variables. Based on recent developments in the literature, we discuss extensions of the model that improve th

Chun-Hsiang Chan, Bundit Laekhanukit, Hao-Ting Wei, Yuhao Zhang

In the k-Connected Directed Steiner Tree problem (k-DST), we are given a directed graph G=(V, E) with edge (or vertex) costs, a root vertex r, a set of q terminals T, and a connectivity requirement k>0; the goal is to find a minimum-cost subgraph H of G such that H has k internally disjoint paths from the root r to each terminal t . The k-DST problem is a na

C. N. Kozameh, J. I. Nieva, G. D. Quiroga

The center of mass and spin for isolated sources of gravitational radiation that move at relativistic speeds are defined. As a first step, we also present these definitions in flat space. This contradicts some general wisdom given in textbooks claiming that such definitions are not covariant and thus, have no physical meaning. We then generalize the definiti

Giulio Malavolta, Pedro Moreno-Sanchez, Aniket Kate, Matteo Maffei

Permissionless blockchains protocols such as Bitcoin are inherently limited in transaction throughput and latency. Current efforts to address this key issue focus on off-chain payment channels that can be combined in a Payment-Channel Network (PCN) to enable an unlimited number of payments without requiring to access the blockchain other than to register the

R. Gonzalez Felipe, A. Perez Martınez, H. Perez Rojas, G. Quintero Angulo

We study a possible mechanism for astrophysical jet production from a neutron star composed by a partially bosonized npe-gas. We obtain that the expulsion of a stable stream of matter might be triggered by the quantum magnetic collapse of one or various components of the gas, while its collimation is due to the formation of a strong self-generated magnetic f

Jonathan B. Freund, Jonathan F. MacArt, Justin Sirignano

Machine learning for scientific applications faces the challenge of limited data. We propose a framework that leverages a priori known physics to reduce overfitting when training on relatively small datasets. A deep neural network is embedded in a partial differential equation (PDE) that expresses the known physics and learns to describe the corresponding un

Daniel González-Campos, Marco Antonio Pérez-de la Rosa, Juan Bory-Reyes

In this paper we consider the problem of reconstructing solutions to a generalized Moisil-Teodorescu system in Jordan domains of $\mathbb{R}^{3}$ with rectifiable boundary. In order to determine conditions for existence of solutions to the problem we embed the system in an appropriate generalized quaternionic setting.

Xinshao Wang, Elyor Kodirov, Yang Hua, Neil M. Robertson

Set-based person re-identification (SReID) is a matching problem that aims to verify whether two sets are of the same identity (ID). Existing SReID models typically generate a feature representation per image and aggregate them to represent the set as a single embedding. However, they can easily be perturbed by noises--perceptually/semantically low quality i

Nabiullah Khan, Talha Usman, Mohd Aman

Inspired by the framework of operational methods and based on the generating functions of Legendre-Gould Hopper polynomials and Sheffer sequences, we discuss certain new mixed type polynomials and their important properties. We show that the use of operational nature allows the relevant polynomials to be unified and general in nature. It is illustrated how t

Aleksandra Grokhovskaya, Sergei N. Dodonov

We present the results of methodological works on automated analysis of the large scale distribution of galaxies. Selecting candidates for clusters and groups of galaxies was carried out using two complementary methods of determining the density contrast maps in the narrow layers of the three-dimensional large scale distribution of galaxies: the filtering al

Tristram Bogart, John Goodrick, Kevin Woods

Let $f_1(n), \ldots, f_k(n)$ be polynomial functions of $n$. For fixed $n\in\mathbb{N}$, let $S_n\subseteq \mathbb{N}$ be the numerical semigroup generated by $f_1(n),\ldots,f_k(n)$. As $n$ varies, we show that many invariants of $S_n$ are eventually quasi-polynomial in $n$, such as the Frobenius number, the type, the genus, and the size of the $Δ$-set. The

Jacob Lustig-Yaeger, Victoria S. Meadows, Andrew P. Lincowski

Near-term studies of Venus-like atmospheres with JWST promise to advance our knowledge of terrestrial planet evolution. However, the remote study of Venus in the Solar System and the ongoing efforts to characterize gaseous exoplanets both suggest that high altitude aerosols could limit observational studies of lower atmospheres, and potentially make it chall

Samuel W. Yee, Joshua N. Winn, Heather A. Knutson, Kishore C. Patra

WASP-12b is a transiting hot Jupiter on a 1.09-day orbit around a late-F star. Since the planet's discovery in 2008, the time interval between transits has been decreasing by $29\pm 2$ msec year$^{-1}$. This is a possible sign of orbital decay, although the previously available data left open the possibility that the planet's orbit is slightly eccent

Jean-Jacques Forneron

Quasi-Monte Carlo (qMC) methods are a powerful alternative to classical Monte-Carlo (MC) integration. Under certain conditions, they can approximate the desired integral at a faster rate than the usual Central Limit Theorem, resulting in more accurate estimates. This paper explores these methods in a simulation-based estimation setting with an emphasis on th

Alex G. Kim, Eric V. Linder

Peculiar-velocity surveys of the low-redshift universe have significant leverage to constrain the growth rate of cosmic structure and test gravity. Wide-field imaging surveys combined with multi-object spectrographs (e.g. ZTF2, LSST, DESI, 4MOST) can use Type Ia supernovae as informative tracers of the velocity field, reaching few percent constraints on the

Laurent Eyer, Maria Süveges, Joris De Ridder, Sara Regibo

In astronomy, we are witnessing an enormous increase in the number of source detections, precision, and diversity of measurements. Additionally, multi-epoch data is becoming the norm, making time-series analyses an important aspect of current astronomy. The Gaia mission is an outstanding example of a multi-epoch survey that provides measurements in a large d

Shao-Lun Huang, Anuran Makur, Gregory W. Wornell, Lizhong Zheng

We consider the problem of identifying universal low-dimensional features from high-dimensional data for inference tasks in settings involving learning. For such problems, we introduce natural notions of universality and we show a local equivalence among them. Our analysis is naturally expressed via information geometry, and represents a conceptually and com

Harun Siljak

This chapter presents the pioneering work in applying reversible computation paradigms to wireless communications. These applications range from developing reversible hardware architectures for underwater acoustic communications to novel distributed optimisation procedures in large radio-frequency antenna arrays based on reversing Petri nets. Throughout the

S. K. J. Pacif, Md Salahuddin Khan, L. K. Paikroy, Shalini Singh

In view of late-time cosmic acceleration, a dark energy cosmological model is revisited wherein Einstein's cosmological constant is considered as a candidate of dark energy. Exact solution of Einstein field equations (EFEs) is derived in a homogeneous isotropic background in classical general relativity. The solution procedure is adopted, in a model inde

Pierrick Coupé, Boris Mansencal, Michaël Clément, Rémi Giraud

Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images. To address this problem, previous DL methods proposed to use a single convolution neural network (CNN) or few independent CNNs. In this paper, we present a novel ensemble method b

R. J. Bueno Rogerio, C. H. Coronado Villalobos, D. Beghetto, A. R. Aguirre

In the present essay we review the underlying physical information behind the first concrete example describing a mass dimension one fermion - namely Elko spinors. We start the program exploring the physical information by evaluating the Elko bilinear forms, both within the proper orthochronous Lorentz subgroup as well as within the VSR theory. As we shall s

O. V. Selyugin

Taking into account the PDFs, obtained by different Collaborations, the momentum transfer dependence of GPDs of the nucleons is obtained. The calculated electromagnetic and gravitomagnetic form factors of nucleons are used for the description of different form factors and the nucleons elastic scattering in a wide energy and momentum transfer region with a mi

Monica Arul, Ahsan Kareem

This paper introduces EQShapelets (EarthQuake Shapelets) a time-series shape-based approach embedded in machine learning to autonomously detect earthquakes. It promises to overcome the challenges in the field of seismology related to automated detection and cataloging of earthquakes. EQShapelets are amplitude and phase-independent, i.e., their detection sens

Wenxiang Jiao, Michael R. Lyu, Irwin King

Real-time emotion recognition (RTER) in conversations is significant for developing emotionally intelligent chatting machines. Without the future context in RTER, it becomes critical to build the memory bank carefully for capturing historical context and summarize the memories appropriately to retrieve relevant information. We propose an Attention Gated Hier

Philippe Gimenez, Hema Srinivasan

Given two semigroups $\langle A\rangle$ and $\langle B\rangle$ in ${\mathbb N}^n$, we wonder when they can be glued, i.e., when there exists a semigroup $\langle C\rangle$ in ${\mathbb N}^n$ such that the defining ideals of the corresponding semigroup rings satisfy that $I_C=I_A+I_B+\langleρ\rangle$ for some binomial $ρ$. If $n\geq 2$ and $k[A]$ and $k[B]$ a

Erick Schultz S. A. Caetano, Denise Fonseca Resende, Samir Angelo Milani Martins, Erivelton Geraldo Nepomuceno

In systems identification, the studied phenomena are accompanied by uncertainties, whether arising from measurement data or computational calculations. Interval data provides a valuable way to represent available information on complex problems where uncertainty, inaccuracy, or variability must be taken into account. The present work aims to determine interv

X. Zhu, B. Sudret

Due to limited computational power, performing uncertainty quantification analyses with complex computational models can be a challenging task. This is exacerbated in the context of stochastic simulators, the response of which to a given set of input parameters, rather than being a deterministic value, is a random variable with unknown probability density fu

Lucas Gren, Alfredo Goldman, Christian Jacobsson

With the agile approach to managing software development projects comes an increased dependability on well functioning teams, since many of the practices are built on teamwork. The objective of this study was to investigate if, and how, team development from a group psychological perspective is related to some work practices of agile teams. Data were collect

David Luong, Sreeraman Rajan, Bhashyam Balaji

Quantum two-mode squeezing (QTMS) radars and noise radars detect targets by correlating the received signal with an internally stored recording. A covariance matrix can be calculated between the two which, in theory, is a function of a single correlation coefficient. This coefficient can be used to decide whether a target is present or absent. We can estimat

Azim Ahmadzadeh, Maxwell Hostetter, Berkay Aydin, Manolis K. Georgoulis

In analyses of rare-events, regardless of the domain of application, class-imbalance issue is intrinsic. Although the challenges are known to data experts, their explicit impact on the analytic and the decisions made based on the findings are often overlooked. This is in particular prevalent in interdisciplinary research where the theoretical aspects are som

Lucas Gren, Alfredo Goldman, Christian Jacobsson

Research has shown that the maturity of small workgroups from a psychological perspective is intimately connected to team agility. We, therefore, tested if agile team members appreciated group development psychology training. Our results show that the participating teams seem to have a very positive view of group development training and state that they now

Giorgio Galanti, Fabrizio Tavecchio, Marco Landoni

Very-high-energy (VHE) BL Lac spectra extending above $10 \, \rm TeV$ provide a unique opportunity for testing physics beyond the standard model of elementary particle and alternative blazar emission models. We consider the hadron beam, the photon to axion-like particle (ALP) conversion, and the Lorentz invariance violation (LIV) scenarios by analyzing their

Jason Horng, Halleh B. Balch, Allister F. McGuire, Hsin-Zon Tsai

The use of electric fields for signalling and control in liquids is widespread, spanning bioelectric activity in cells to electrical manipulation of microstructures in lab-on-a-chip devices. However, an appropriate tool to resolve the spatio-temporal distribution of electric fields over a large dynamic range has yet to be developed. Here we present a label-f

Umar Ozgunalp, Rui Fan, Shanshan Cheng, Yuxiang Sun

In this paper, a robust lane detection algorithm is proposed, where the vertical road profile of the road is estimated using dynamic programming from the v-disparity map and, based on the estimated profile, the road area is segmented. Since the lane markings are on the road area and any feature point above the ground will be a noise source for the lane detec

Cosimo Flavi

We determine the successive pages of the Frölicher spectral sequence of the Iwasawa manifold and some of its small deformations, providing new examples and counterexamples on its properties, including the behaviour under small deformations.

Junjie Wang, Xiangfeng Wang, Bo Jin, Junchi Yan

Generalized zero-shot learning (GZSL) tackles the problem of learning to classify instances involving both seen classes and unseen ones. The key issue is how to effectively transfer the model learned from seen classes to unseen classes. Existing works in GZSL usually assume that some prior information about unseen classes are available. However, such an assu

Nieves R. Brisaboa, Antonio Fariña, Daniil Galaktionov, Tirso V. Rodeiro

Representing the trajectories of mobile objects is a hot topic from the widespread use of smartphones and other GPS devices. However, few works have focused on representing trips over public transportation networks (buses, subway, and trains) where a user's trips can be seen as a sequence of stages performed within a vehicle shared with many other users.

Eric Crawford, Joelle Pineau

The ability to detect and track objects in the visual world is a crucial skill for any intelligent agent, as it is a necessary precursor to any object-level reasoning process. Moreover, it is important that agents learn to track objects without supervision (i.e. without access to annotated training videos) since this will allow agents to begin operating in n

Aritra Basu, Andrew Fletcher, S. A. Mao, Blakesley Burkhart

In this paper we present a detailed analysis of the Faraday depth (FD) spectrum and its clean components obtained through the application of the commonly used technique of Faraday rotation measure synthesis to analyze spectro-polarimetric data. In order to directly compare the Faraday depth spectrum with physical properties of a magneto-ionic medium, we gene