January 2022 arXiv papers — page 77

Hanjia Lyu, Jiebo Luo

Understanding political polarization on social platforms is important as public opinions may become increasingly extreme when they are circulated in homogeneous communities, thus potentially causing damage in the real world. Automatically detecting the political ideology of social media users can help better understand political polarization. However, it is

Samaa Elnagar, Manoj Thomas

Cognitive computing (COC) aims to embed human cognition into computerized models. However, there is no scientific classification that delineates the nature of Cognitive Computing. Unlike the medical and computer science fields, Information Systems (IS) has conducted very little research on COC. Although the potential to make important research contributions

M. Matushko, A. Zotov

We propose commuting set of matrix-valued difference operators in terms of the elliptic Baxter-Belavin $R$-matrix in the fundamental representation of ${\rm GL}_M$. In the scalar case $M=1$ these operators are the elliptic Macdonald-Ruijsenaars operators, while in the general case they can be viewed as anisotropic versions of the quantum spin Ruijsenaars Ham

Yuke Zhang, Yinghua Hu, Pierluigi Nuzzo, Peter A. Beerel

Sequential logic locking has been studied over the last decade as a method to protect sequential circuits from reverse engineering. However, most of the existing sequential logic locking techniques are threatened by increasingly more sophisticated SAT-based attacks, efficiently using input queries to a SAT solver to rule out incorrect keys, as well as remova

Matina Gkioulidou, M. Opher, M. Kornbleuth, K. Dialynas

We present a first comparison of Energetic Neutral Atom (ENA) heliosheath measurements, remotely sensed by the Interstellar Boundary Explorer (IBEX) mission and the Ion and Neutral Camera (INCA) on the Cassini mission, with modeled ENA inferred from interstellar pickup protons that have been accelerated at the termination shock, using hybrid simulations. The

Man Cheung Tsui

We show that the $n\times n$ matrix differential equation $\delta(Y)=AY$ with $n^2$ general coefficients cannot be simplified to an equation in less than $n$ parameters by using gauge transformations whose coefficients are rational functions in the matrix entries of $A$ and their derivatives. Our proof uses differential Galois theory and a differential analo

H. A. Weaver, S. B. Porter, J. R. Spencer, The New Horizons Science Team

Using the New Horizons LORRI camera, we searched for satellites near five Kuiper belt objects (KBOs): four cold classicals (CCs: 2011 JY31, 2014 OS393, 2014 PN70, 2011 HZ102) and one scattered disk object (SD: 2011 HK103). These objects were observed at distances of 0.092-0.290 au from the New Horizons spacecraft, achieving spatial resolutions of 136-430 km

Caitlin Lustig

In this paper, I propose a new concept for understanding the role of algorithms in daily life: algorithmic authority. Algorithmic authority is the legitimate power of algorithms to direct human action and to impact which information is considered true. I use this concept to examine the culture of users of Bitcoin, a crypto-currency and payment platform. Thro

Zhao Chen, Vincent Casser, Henrik Kretzschmar, Dragomir Anguelov

We propose GradTail, an algorithm that uses gradients to improve model performance on the fly in the face of long-tailed training data distributions. Unlike conventional long-tail classifiers which operate on converged - and possibly overfit - models, we demonstrate that an approach based on gradient dot product agreement can isolate long-tailed data early o

Yi Li, Volodymyr G. Yefremenko, Marharyta Lisovenko, Cody Trevillian

We demonstrate microwave-mediated distant magnon-magnon coupling on a superconducting circuit platform, incorporating chip-mounted single-crystal Y$_3$Fe$_5$O$_{12}$ (YIG) spheres. Coherent level repulsion and dissipative level attraction between the magnon modes of the two YIG spheres are demonstrated. The former is mediated by cavity photons of a supercond

Jinho Choi, Seng W. Loke, Jihong Park

This article aims to provide a unified and technical approach to semantic information, communication, and their interplay through the lens of probabilistic logic. To this end, on top of the existing technical communication (TC) layer, we additionally introduce a semantic communication (SC) layer that exchanges logically meaningful clauses in knowledge bases.

Medha Agarwal, Jason Xu

The principle of majorization-minimization (MM) provides a general framework for eliciting effective algorithms to solve optimization problems. However, they often suffer from slow convergence, especially in large-scale and high-dimensional data settings. This has drawn attention to acceleration schemes designed exclusively for MM algorithms, but many existi

Gabriele Inghirami, Hannah Elfner

To assess the degree of equilibration of the matter created in heavy-ion reactions at low to intermediate beam energies, a hadronic transport approach (SMASH) is employed. By using a coarse-graining method, we compute the energy momentum tensor of the system at fixed time steps and evaluate the degree of isotropy of the diagonal terms and the relative magnit

Amin Mekacher, Antonis Papasavva

Voat.co was a news aggregator website that shut down on December 25, 2020. The site had a troubled history and was known for hosting various banned subreddits. This paper presents a dataset with over 2.3M submissions and 16.2M comments posted from 113K users in 7.1K subverses (the equivalent of subreddit for Voat). Our dataset covers the whole lifetime of Vo

Rogerio Rossi, Kechi Hirama

Software technology has high impact on the global economy as in many sectors of contemporary society. As a product enabling the most varied daily activities, the software product has to be produced reflecting high quality. Software quality is dependent on its development that is based in a large set of software development processes. However, the implementat

Nagib Sabbag Filho, Rogerio Rossi

A set of steps for implementing a chatbot, to support decision-making activities in the software incident management process is proposed and discussed in this article. Each step is presented independently of the platform used for the construction of chatbots and are detailed with their respective activities. The proposed steps can be carried out in a continu

Yang Li, Bo Feng, Bin Wang, Shuchao Sun

In order to improve the penetration of renewable energy resources for distribution networks, a joint planning model of distributed generations (DGs) and energy storage is proposed for an active distribution network by using a bi-level programming approach in this paper. In this model, the upper-level aims to seek the optimal location and capacity of DGs and

Rogerio Rossi, Pollyana Notagiarcomo

The digital educational solutions are increasingly used demanding high quality functionalities. In this sense, standards and models are made available by governments, associations, and researchers being most used in quality control and assessment sessions. The eQETIC model was built according to the approach of continuous process improvement favoring the qua

Degang Sun, Yue Cui, Siye Wang, Yanfang Zhang

RFID as an important component technology of IoT faces important security risks while being rapidly applied, among which the discovery of unauthorized readers in space is crucial. There are some researches proposed the unauthorized reader detection algorithm based on commercial off the shell(COTS) devices, but these detection algorithms are often easily affe

Rogerio Rossi, Pollyana Notargiacomo Mustaro

Digital solutions have substantially contributed to the growth and dissemination of education. The distance education modality has been presented as an opportunity for worldwide students in many types of courses. However, projects of digital educational platforms require different expertise including knowledge areas such as pedagogy, psychology, computing, a

Xiunan Wang, Hao Wang, Pouria Ramazi, Kyeongah Nah

Understanding the joint impact of vaccination and non-pharmaceutical interventions on COVID-19 development is important for making public health decisions that control the pandemic. Recently, we created a method in forecasting the daily number of confirmed cases of infectious diseases by combining a mechanistic ordinary differential equation (ODE) model for

Rogerio Rossi, Kechi Hirama

Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing informatio

Terry A. Loring, Fredy Vides

In this document, some elements of the theory and algorithmics corresponding to the existence and computability of approximate joint eigenpairs for finite collections of matrices with applications to model order reduction, are presented. More specifically, given a finite collection $X_1,\ldots,X_d$ of Hermitian matrices in $\mathbb{C}^{n\times n}$, a positiv

Hourieh Khalajzadeh, Mojtaba Shahin, Humphrey O. Obie, John Grundy

Many software systems fail to meet the needs of the diverse end-users in society and are prone to pose problems, such as accessibility and usability issues. Some of these problems (partially) stem from the failure to consider the characteristics, limitations, and abilities of diverse end-users during software development. We refer to this class of problems a

MD Shah Alam, Rudra Gnawali, Joshua R. Hendrickson, Diane Beamer

The generation of rapidly tunable Optical Vortex (OV) beams is one of the most demanding research areas of the present era as they possess Orbital Angular Momentum (OAM) with additional degrees of freedom that can be exploited to enhance signal-carrying capacity by using mode division multiplexing and information encoding in optical communication. Particular

K. Sveshnikov, Yu. Voronina

The properties of the QED-vacuum energy $\hbox{$\cal E $}_{VP}$ under Coulomb super-criticality condition $Z>Z_{cr,1}$ are explored in essentially non-perturbative approach. It is shown that in the supercritical region $\hbox{$\cal E $}_{VP}$ is the decreasing function of the Coulomb source parameters, resulting in decay into the negative range as $\sim - Z^

Ruimeng Hu, Quyuan Lin

We study the stochastic effect on the three-dimensional inviscid primitive equations (PEs, also called the hydrostatic Euler equations). Specifically, we consider a larger class of noises than multiplicative noises, and work in the analytic function space due to the ill-posedness in Sobolev spaces of PEs without horizontal viscosity. Under proper conditions,

Daniel Ferguson, Francois G. Meyer

To characterize the location (mean, median) of a set of graphs, one needs a notion of centrality that is adapted to metric spaces, since graph sets are not Euclidean spaces. A standard approach is to consider the Frechet mean. In this work, we equip a set of graphs with the pseudometric defined by the norm between the eigenvalues of their respective adjacenc

Irina Bigoulaeva, Viktor Hangya, Iryna Gurevych, Alexander Fraser

The goal of hate speech detection is to filter negative online content aiming at certain groups of people. Due to the easy accessibility of social media platforms it is crucial to protect everyone which requires building hate speech detection systems for a wide range of languages. However, the available labeled hate speech datasets are limited making it prob

Jiaozi Wang, Giuliano Benenti, Giulio Casati, Wen-ge Wang

We study the statistical and dynamical properties of the quantum triangle map, whose classical counterpart can exhibit ergodic and mixing dynamics, but is never chaotic. Numerical results show that ergodicity is a sufficient condition for spectrum and eigenfunctions to follow the prediction of Random Matrix Theory, even though the underlying classical dynami

Abhinav Sagar

In this paper, we propose a novel network named Vision Transformer for Biomedical Image Segmentation (ViTBIS). Our network splits the input feature maps into three parts with $1\times 1$, $3\times 3$ and $5\times 5$ convolutions in both encoder and decoder. Concat operator is used to merge the features before being fed to three consecutive transformer blocks

Keith Moffat, Alexandra von Meier

In this paper, we introduce Voltage Phasor Control (VPC), also known as Phasor Based Control, as a novel way of implementing Optimal Power Flow (OPF). Unlike conventional OPF, in which the power flow optimization broadcasts power injections, the VPC power flow optimization broadcasts voltage phasor setpoints to feedback controllers distributed throughout the

Yuan Wang, Chunyuan Zhang, Tianzong Yu, Meng Ma

As an important algorithm in deep reinforcement learning, advantage actor critic (A2C) has been widely succeeded in both discrete and continuous control tasks with raw pixel inputs, but its sample efficiency still needs to improve more. In traditional reinforcement learning, actor-critic algorithms generally use the recursive least squares (RLS) technology t

Anna Clarke, Per Olof Gutman

This study offers an interdisciplinary approach to movement technique analysis, designed to deal with intensive interaction between an environment and a trainee. The free-fall stage of skydiving is investigated, when aerial maneuvers are performed by changing the body posture and thus deflecting the surrounding airflow. The natural learning process of body f

Hongguang Zhang, Hongdong Li, Piotr Koniusz

We propose a Multi-level Second-order (MlSo) few-shot learning network for supervised or unsupervised few-shot image classification and few-shot action recognition. We leverage so-called power-normalized second-order base learner streams combined with features that express multiple levels of visual abstraction, and we use self-supervised discriminating mecha

Suney Toste, David Holcman

We study here the escape time for the fastest diffusing particle from the boundary of an interval with point-sink killing sources. Killing represents a degradation that leads to the probabilistic removal of the moving Brownian particles. We compute asymptotically the mean time it takes for the fastest particle escaping alive and obtain the extreme statistic

Yunus Can Bilge, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis

This paper tackles the problem of zero-shot sign language recognition (ZSSLR), where the goal is to leverage models learned over the seen sign classes to recognize the instances of unseen sign classes. In this context, readily available textual sign descriptions and attributes collected from sign language dictionaries are utilized as semantic class represent

Marcos A. van Dam, Yolanda Martín Hernando, Miguel Núñez Cagigal, Luzma M. Montoya

Multiconjugate adaptive optics (MCAO) systems have the potential to deliver diffraction-limited images over much larger fields of view than traditional single conjugate adaptive optics systems. In MCAO, the high altitude deformable mirrors (DMs) cause a distortion of the pupil plane and lead to a dynamic misregistration between the DM actuators and the wavef

Raju Hazari, P Pal Chaudhuri

The reason of significantly higher transmissibility of SARS Covid (2019 CoV-2) compared to SARS Covid (2003 CoV) and MERS Covid (2012 MERS) can be attributed to mutations reported in structural proteins, and the role played by non-structural proteins (nsps) and accessory proteins (ORFs) for viral replication, assembly, and shedding. Envelope protein E is one

Philipp Klumpp, Tomás Arias-Vergara, Paula Andrea Pérez-Toro, Elmar Nöth

Current state of the art acoustic models can easily comprise more than 100 million parameters. This growing complexity demands larger training datasets to maintain a decent generalization of the final decision function. An ideal dataset is not necessarily large in size, but large with respect to the amount of unique speakers, utilized hardware and varying re

Andreas Blass, Yuri Gurevich, Alexander Volberg

In every state of a quantum particle, Wigner's quasidistribution is the unique quasidistribution on the phase space with the correct marginal distributions for position, momentum, and all their linear combinations.

Samaa Elnagar, Victoria Yoon, Manoj A. Thomas

Ontologies have been known for their semantic representation of knowledge. ontologies cannot automatically evolve to reflect updates that occur in respective domains. To address this limitation, researchers have called for automatic ontology generation from unstructured text corpus. Unfortunately, systems that aim to generate ontologies from unstructured tex

Alexander Aeppli, Anjun Chu, Tobias Bothwell, Colin J. Kennedy

Engineering a Hamiltonian system with tunable interactions provides opportunities to optimize performance for quantum sensing and explore emerging phenomena of many-body systems. An optical lattice clock based on partially delocalized Wannier-Stark states in a gravity-tilted shallow lattice supports superior quantum coherence and adjustable interactions via

Pierre-Henri Chavanis

We introduce a new logotropic model based on a complex scalar field with a logarithmic potential that unifies dark matter and dark energy. The scalar field satisfies a nonlinear wave equation generalizing the Klein-Gordon equation in the relativistic regime and the Schr\"odinger equation in the nonrelativistic regime. This model has an intrinsically quantum

Erda Wen, Dia'aaldin J. Bisharat, Robert J. Davis, Xiaozhen Yang

Symmetry indicators are a modern tool for characterizing topological phases that require only minimal computational expense but provide an elegant means of designing practical devices. This paper demonstrates how a rotational symmetry indicator can be used to construct and characterize a topologically robust waveguide, which is then verified experimentally o

Mohsen Asgari, Seyed Hossein Khasteh

Deep Reinforcement Learning solutions have been applied to different control problems with outperforming and promising results. In this research work we have applied Proximal Policy Optimization, Soft Actor-Critic and Generative Adversarial Imitation Learning to strategy design problem of three cryptocurrency markets. Our input data includes price data and t

Minh Tran, Loi Ly, Binh-Son Hua, Ngan Le

Capsule network is a recent new deep network architecture that has been applied successfully for medical image segmentation tasks. This work extends capsule networks for volumetric medical image segmentation with self-supervised learning. To improve on the problem of weight initialization compared to previous capsule networks, we leverage self-supervised lea

Irfan Mahmood, Hira Sohail, Allah Ditta

In this article, we derive the Darboux solutions of Ito type coupled KdV equation in Darboux framework which is associated with Hirota Satsuma systems. Then we generalise $N$-fold Darboux transformations in terms of Wronskians. We also derive the exact multi-solitonic solutions for the coupled field variables of that system in the background of zero seed sol

Pierre-Henri Chavanis

The logotropic model [P.H. Chavanis, Eur. Phys. J. Plus {\bf 130}, 130 (2015)] may be an interesting alternative to the $\Lambda$CDM model. It is able to account for the present accelerating expansion of the universe while solving at the same time the core-cusp problem of the CDM model. In the logotropic model, there is a single dark fluid. Its rest-mass pla

Naoki Koseki, Genki Ouchi

A perverse schober is a categorification of a perverse sheaf proposed by Kapranov--Schechtman. In this paper, we construct examples of perverse schobers on the Riemann sphere, which categorify the intersection complexes of natural local systems arising from the mirror symmetry for Calabi-Yau hypersurfaces. The Orlov equivalence plays a key role for the const

Roberto Alicandro, Lucia De Luca, Giuliano Lazzaroni, Mariapia Palombaro

We consider a discrete model of planar elasticity where the particles, in the reference configuration, sit on a regular triangular lattice and interact through nearest neighbor pairwise potentials, with bonds modeled as linearized elastic springs. Within this framework we introduce plastic slip fields, whose discrete circulation around each triangle detects

Rui Yang

The faster speed and operational convenience of two-qubit gate with flux bias control makes it an important candidate for future large-scale quantum computers based on high coherence flux qubits. Based on a properly designed two-spin gadget which has small gaps during the evolution of energy levels, we build a CNOT-equivalent gate which can reach a fidelity

George Jeffreys, Siu-Cheong Lau

We formulate a mathematical setup for computational neural networks using noncommutative algebras and near-rings, in motivation of quantum automata. We study the moduli space of the corresponding framed quiver representations, and find moduli of Euclidean and non-compact types in light of uniformization.

Ben Bogin, Shivanshu Gupta, Jonathan Berant

While recent work has convincingly showed that sequence-to-sequence models struggle to generalize to new compositions (termed compositional generalization), little is known on what makes compositional generalization hard on a particular test instance. In this work, we investigate what are the factors that make generalization to certain test instances challen

Ratna Pal, Koushik Ramachandran, Sivaguru Ravisankar

Let $E$ be a closed polar subset of $\mathbb{C}$. In this short note, we use elementary potential theoretic tools to show that any conformal map on $\mathbb{C}\setminus{E}$ is necessarily a M\"{o}bius map. As a consequence we obtain that the group of conformal automorphisms of the complement of a closed polar set $E$ is a discrete subgroup of the M\"{o}bius

Eckhart Spalding, Katie M. Morzinski, Phil Hinz, Jared Males

The Large Binocular Telescope (LBT) has two 8.4-m primary mirrors that produce beams that can be combined coherently in a "Fizeau" interferometric mode. In principle, the Fizeau PSF enables the probing of structure at a resolution up to three times better than that of the adaptive-optics-corrected PSF of a single 8.4-m telescope. In this work, we examined th

Stephan Rosswog

Computational fluid dynamics is a crucial tool to theoretically explore the cosmos. In the last decade, we have seen a substantial methodological diversification with a number of cross-fertilizations between originally different methods. Here we focus on recent developments related to the Smoothed Particle Hydrodynamics (SPH) method. We briefly summarize rec

Samuel Ewing, G. Stacey Staples

Zeon algebras have proven to be useful for enumerating structures in graphs, such as paths, trails, cycles, matchings, cliques, and independent sets. In contrast to an ordinary graph, in which each edge connects exactly two vertices, an edge (or, "hyperedge") can join any number of vertices in a hypergraph. In game theory, hypergraphs are called simple games

Philipp Kurzhals, Geoffroy Kremer, Thomas Jaouen, Christopher W. Nicholson

Electron-phonon coupling, i.e., the scattering of lattice vibrations by electrons and vice versa, is ubiquitous in solids and can lead to emergent ground states such as superconductivity and charge-density wave order. Strong coupling of phonons to electrons near the Fermi surface, which reduces the phonon lifetimes and broadens the phonon peaks in scattering

Nathan Kallus

Since the average treatment effect (ATE) measures the change in social welfare, even if positive, there is a risk of negative effect on, say, some 10% of the population. Assessing such risk is difficult, however, because any one individual treatment effect (ITE) is never observed, so the 10% worst-affected cannot be identified, while distributional treatment

A. Ait Ben Mennana, R. Benjedi, P. Buganu, R. Budaca

The deformation properties of 74Ge, 74Se and 74Kr are studied within the phenomenological Bohr-Mottelson model, having as input the experimental collective energy states, as well with Covariant Density Functional theories based on microscopic structural information. The results of these approaches are shown to be compatible in what concerns the presence of c

Andrew Zupon, Andrew Carnie, Michael Hammond, Mihai Surdeanu

Annotation inconsistencies between data sets can cause problems for low-resource NLP, where noisy or inconsistent data cannot be as easily replaced compared with resource-rich languages. In this paper, we propose a method for automatically detecting annotation mismatches between dependency parsing corpora, as well as three related methods for automatically c

Pierre Segonne, Yevgen Zainchkovskyy, Søren Hauberg

Probabilistic models often use neural networks to control their predictive uncertainty. However, when making out-of-distribution (OOD)} predictions, the often-uncontrollable extrapolation properties of neural networks yield poor uncertainty predictions. Such models then don't know what they don't know, which directly limits their robustness w.r.t unexpected

Yupei Liu, Jinyuan Jia, Hongbin Liu, Neil Zhenqiang Gong

Pre-trained encoders are general-purpose feature extractors that can be used for many downstream tasks. Recent progress in self-supervised learning can pre-train highly effective encoders using a large volume of unlabeled data, leading to the emerging encoder as a service (EaaS). A pre-trained encoder may be deemed confidential because its training requires

Vineet Ojha

SDSS J163401.94$+$480940.2 is a non-jetted radio-loud narrow-line Seyfert 1 (NLSy1) galaxy. Optical monitoring of this object was carried out in two intra-night sessions each $\geq$ 3 hrs with 3.6m DOT. Intra-night optical variability (INOV) characterization is presented for the first time for this source. We have detected an unexpected remarkable flare in o

Saba Baraghani, Zahra Barani, Yassamin Ghafouri, Amirmahdi Mohammadzadeh

We report on the preparation of inks containing fillers derived from quasi-two-dimensional charge-density-wave materials, their application for inkjet printing, and the evaluation of their electronic properties in printed thin film form. The inks were prepared by liquid-phase exfoliation of CVT-grown 1T-TaS$_2$ crystals to produce fillers with nm-scale thick

Xiyu Wang, Pengxin Guo, Yu Zhang

Domain Adaptation (DA) aims to leverage the knowledge learned from a source domain with ample labeled data to a target domain with unlabeled data only. Most existing studies on DA contribute to learning domain-invariant feature representations for both domains by minimizing the domain gap based on convolution-based neural networks. Recently, vision transform

Antoine Dahlqvist, Thibaut Lemoine

This paper considers the large N limit of Wilson loops for the two-dimensional Euclidean Yang-Mills measure on all orientable compact surfaces of genus larger or equal to one, with a structure group given by a classical compact matrix Lie group. We show their convergence for all loops on the torus and give a conjecture supported by partial results for other

Alexey Kroshnin, Eugene Stepanov, Dario Trevisan

For a given metric measure space $(X,d,\mu)$ we consider finite samples of points, calculate the matrix of distances between them and then reconstruct the points in some finite-dimensional space using the multidimensional scaling (MDS) algorithm with this distance matrix as an input. We show that this procedure gives a natural limit as the number of points i

Hossein Golestani, Rathijit Sen, Vinson Young, Gagan Gupta

Computer architecture design space is vast and complex. Tools are needed to explore new ideas and gain insights quickly, with low efforts and at a desired accuracy. We propose Calipers, a criticality-based framework to model key abstractions of complex architectures and a program's execution using dynamic event-dependence graphs. By applying graph algorithms

Lewis Bowen, Yuqing Frank Lin

The $f$-invariant is a notion of entropy for probability-measure-preserving actions of free groups. We show it is invariant under bounded orbit-equivalence.

Antoine Dahlqvist, Thibaut Lemoine

We compute the Large N limit of several objects related to the two-dimensional Euclidean Yang-Mills measure on compact connected orientable surfaces of genus larger or equal to one, with a structure group taken among the classical groups of order N. Our result shows the convergence of all Wilson loops for all loops within a topological disc and all simple lo

Aissa Guesmia

In this paper, we consider two systems of type Rao-Nakra sandwich beam in the whole line R with a frictional damping or an infinite memory acting on the Euler-Bernoulli equation. When the speeds of propagation of the two wave equations are equal, we show that the solutions do not converge to zero when time goes to infinity. In the reverse situation, we prove

Wanjun Zhong, Junjie Huang, Qian Liu, Ming Zhou

Tabular and textual question answering requires systems to perform reasoning over heterogeneous information, considering table structure, and the connections among table and text. In this paper, we propose a ChAin-centric Reasoning and Pre-training framework (CARP). CARP utilizes hybrid chain to model the explicit intermediate reasoning process across table

Peter M. Higgins, Alexei Vernitski

We characterise the respective semigroups of mappings that preserve, or that preserve or reverse orientation of a finite cycle, in terms of their actions on oriented triples and oriented quadruples. This leads to a proof that the latter semigroup coincides with the semigroup of all mappings that preserve intersections of chords on the corresponding circle.

Ahmet Yavuz Uluslu

In this paper, we present the first automatic lexical simplification system for the Turkish language. Recent text simplification efforts rely on manually crafted simplified corpora and comprehensive NLP tools that can analyse the target text both in word and sentence levels. Turkish is a morphologically rich agglutinative language that requires unique consid

Tengfeng Lin, Zhixiong Jin, Seongjin Choi, Hwasoo Yeo

The mortality rate for pedestrians using wheelchairs was 36% higher than the overall population pedestrian mortality rate. However, there is no data to clarify the pedestrians' categories in both fatal and nonfatal accidents, since police reports often do not keep a record of whether a victim was using a wheelchair or has a disability. Currently, real-time d

Swanhild Bernstein, Dmitrii Legatiuk

Clifford analysis has been the field of active research for several decades resulting in various methods to solve problems in pure and applied mathematics. However, the area of stochastic analysis has not been addressed in its full generality in the Clifford setting, since only a few contributions have been presented so far. Considering that the tools of sto

Pieter P. Tordoir, Anthony F. J. van Raan

Urban scaling, the superlinear increase of social and economic measures with increasing population, is an ubiquitous and well-researched phenomenon. This article is focused on socio-economic performance scaling, which could possibly be driven by increasing returns of the spatial size and density of interaction networks. If this is indeed the case, we should

Timm Oertel, Joseph Paat, Robert Weismantel

The Steinitz constant in dimension $d$ is the smallest value $c(d)$ such that for any norm on $\mathbb{R}^{ d}$ and for any finite zero-sum sequence in the unit ball, the sequence can be permuted such that the norm of each partial sum is bounded by $c(d)$. Grinberg and Sevastyanov prove that $c(d) \le d$ and that the bound of $d$ is best possible for arbitra

Alan Molinari, Saleh Gorji, Jan Michalička, Christian Kübel

Among the class of strongly-correlated oxides, La1-xSrxMnO3 $-$ a half metallic ferromagnet with a Curie temperature above room temperature $-$ has sparked a huge interest as a functional building block for memory storage and spintronic applications. In this respect, defect engineering has been in the focus of a long-standing quest for fabricating LSMO thin

Tobias Pfandzelter, David Bermbach

With the advent of large LEO satellite communication networks to provide global broadband Internet access, interest in providing edge computing resources within LEO networks has emerged. The LEO Edge promises low-latency, high-bandwidth access to compute and storage resources for a global base of clients and IoT devices regardless of their geographical locat

Stephan Baier, Anup Haldar

Let $p>5$ be a fixed prime. We obtain an asymptotic formula related to small solutions of quadratic congruences of the form $x_1^2+x_2^2\equiv x_3^2\bmod{p^n}$ where $\max\{|x_1|,|x_2|,|x_3|\}\le p^{\nu n}$ with $\nu>1/2$.

Diana Meleşteu, Mihai N. Pascu, Nicolae R. Pascu

In the present paper we show that in P\'{o}lya's urn model, for an arbitrarily fixed initial distribution of the urn, the corresponding random variables satisfy a convex ordering with respect to the replacement parameter. As an application, we show that in the class of convex functions, the absolute value of the error of Bernstein-Stancu operators is a non-d

Yiqing Hao, Yi Jin, Gaoyun An

Semantic segmentation methods can not directly identify abnormal objects in images. Anomaly Segmentation algorithm from this realistic setting can distinguish between in-distribution objects and Out-Of-Distribution (OOD) objects and output the anomaly probability for pixels. In this paper, a Prototype Guided Anomaly segmentation Network (PGAN) is proposed to

Tan Wan, L. Jeff Hong

Many large-scale production networks include thousands types of final products and tens to hundreds thousands types of raw materials and intermediate products. These networks face complicated inventory management decisions, which are often too complicated for inventory models and too large for simulation models. In this paper, by combing efficient computatio

Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long

The success of deep learning algorithms generally depends on large-scale data, while humans appear to have inherent ability of knowledge transfer, by recognizing and applying relevant knowledge from previous learning experiences when encountering and solving unseen tasks. Such an ability to acquire and reuse knowledge is known as transferability in deep lear

Shou-shan Bao, Shaoqi Hou, Hong Zhang

Wormholes bridging distant places of the universe are well-known solutions of general relativity. In particular, traversable wormholes which allow interstellar traveling are also popular in science fiction. However, no hint of their existence has been found yet. In this work, we propose using the gravitational wave (GW) scattering off spherical wormholes to

Hala Neji, Mohamed Ben Halima, Javier Nogueras-Iso, Tarek. M. Hamdani

Deep convolutional neural networks (Deep CNN) have achieved hopeful performance for single image super-resolution. In particular, the Deep CNN skip Connection and Network in Network (DCSCN) architecture has been successfully applied to natural images super-resolution. In this work we propose an approach called SDT-DCSCN that jointly performs super-resolution

Ismail Nikoufar, Davuod Saeedi

In this paper, we introduce the notion of conditional $h$-convex functions and we prove an operator version of the Jensen inequality for conditional $h$-convex functions. Using this type of functions, we give some refinements for Ky-Fan's inequality, arithmetic-geometric mean inequality, Chrystal inequality, and H$\ddot{o}$lder-McCarthy inequality. Many of t

Franco Strocchi

The extraordinary success of the Standard Model asks for a more rigorous control beyond the perturbative approach, which is affected by mathematical problems (interaction picture and canonical quantization, non-convergence of the perturbative series, trivialy results for the $\ph^4$ model and related models etc.). We shall briefly discuss sone non-perturbati

Dianwen Ng, Yunqi Chen, Biao Tian, Qiang Fu

Building efficient architecture in neural speech processing is paramount to success in keyword spotting deployment. However, it is very challenging for lightweight models to achieve noise robustness with concise neural operations. In a real-world application, the user environment is typically noisy and may also contain reverberations. We proposed a novel fea

Ismail Nikoufar, Davuod Saeedi

In this paper, we prove an operator version of the Jensen's inequality and its converse for $h$-convex functions. We provide a refinement of the Jensen type inequality for $h$-convex functions. Moreover, we prove the Hermite-Hadamard's type inequality and a multiple operator version of the Jensen's inequality for $h$-convex functions. In particular, a result

Chengqiang Lu, Mingyang Yin, Shuheng Shen, Luo Ji

Recommendation system has been a widely studied task both in academia and industry. Previous works mainly focus on homogeneous recommendation and little progress has been made for heterogeneous recommender systems. However, heterogeneous recommendations, e.g., recommending different types of items including products, videos, celebrity shopping notes, among m

Eleni Vafeiadi Bila, Brijesh Dongol, Ori Lahav, Azalea Raad

The rise of persistent memory is disrupting computing to its core. Our work aims to help programmers navigate this brave new world by providing a program logic for reasoning about x86 code that uses low-level operations such as memory accesses and fences, as well as persistency primitives such as flushes. Our logic, Pierogi, benefits from a simple underlying

Anindya Goswami, Ravishankar Kapildev Yadav

Given a semi-Markov law, using an additional parameter, we consider a family of stochastic flows corresponding to that law. Then we suitably select a particular flow, for which we obtain expressions of the meeting and merging probabilities of a pair of semi-Markov processes, solving the same equation but having two different initial conditions. A set of suff

Chnoor M. Rahman, Tarik A. Rashid, Aram Mahmood Ahmed, Seyedali Mirjalili

In this work, a new multiobjective optimization algorithm called multiobjective learner performance-based behavior algorithm is proposed. The proposed algorithm is based on the process of transferring students from high school to college. The proposed technique produces a set of non-dominated solutions. To judge the ability and efficacy of the proposed multi

Gaurav Satyanath, Jajati Keshari Sahoo, Rajendra Kumar Roul

Limited urban parking space combined with urbanization has necessitated the development of smart parking systems that can communicate the availability of parking slots to the end users. Towards this, various deep learning based solutions using convolutional neural networks have been proposed for parking space occupation detection. Though these approaches are

Ahai Chen, David M. Benoit, Yohann Scribano, André Nauts

A Smolyak algorithm adapted to system-bath separation is proposed for rigorous quantum simulations. This technique combines a sparse grid method with the system-bath concept in a specific configuration without limitations on the form of the Hamiltonian, thus achieving a highly efficient convergence of the excitation transitions for the "system" part. Our app

David London

At the present time, there are hints of new physics (NP) in several observables involving $b \to c \ell^- {\bar\nu}_\ell$ decays. In this talk, I describe measurable angular distributions for ${\bar B} \to D^* \mu^- {\bar\nu}_\mu$ and ${\bar B} \to D^* \tau^- (\to \pi^- \nu_\tau) {\bar\nu}_\tau$ decays, including the most general NP contributions. These angu