August 2022 arXiv papers — page 117

Zhikang Wang, Yue Bi, Tong Pan, Xiaoyu Wang

Multiple instance learning (MIL) is a powerful approach to classify whole slide images (WSIs) for diagnostic pathology. A fundamental challenge of MIL on WSI classification is to discover the \textit{critical instances} that trigger the bag label. However, previous methods are primarily designed under the independent and identical distribution hypothesis (\t

Siddharth H. Nair, Vijay Govindarajan, Theresa Lin, Yan Wang

We propose a Stochastic MPC (SMPC) approach for autonomous driving which incorporates multi-modal, interaction-aware predictions of surrounding vehicles. For each mode, vehicle motion predictions are obtained by a control model described using a basis of fixed features with unknown weights. The proposed SMPC formulation finds optimal controls which serves tw

Xiaolong Luo, Wanzhong Song, Songlin Bai, Yu Li

In terms of 3D imaging speed and system cost, the single-camera system projecting single-frequency patterns is the ideal option among all proposed Fringe Projection Profilometry (FPP) systems. This system necessitates a robust spatial phase unwrapping (SPU) algorithm. However, robust SPU remains a challenge in complex scenes. Quality-guided SPU algorithms ne

Davide Bacciu, Alessio Conte, Francesco Landolfi

Downsampling produces coarsened, multi-resolution representations of data and it is used, for example, to produce lossy compression and visualization of large images, reduce computational costs, and boost deep neural representation learning. Unfortunately, due to their lack of a regular structure, there is still no consensus on how downsampling should apply

Julius Kraemer

For a radical extension K of odd prime degree the ring O_K of integers is constructed as a product of subrings with the following property: for all prime divisors q of the discriminant of O_K there is a q-maximal factor. The discriminant of O_K is the greatest common divisor of the discriminants of all factors. The results are applied to give a criterion for

Y. Kipreos, Margaret Campbell-Brown, P. Brown, D. Vida

The Daytime Sextantids meteor shower, part of the Phaethon-Geminid Stream Complex (PGC), is closely related to the Geminids, currently the strongest meteor shower visible at the Earth. The DSX share a similar orbit to asteroid 2005 UD, but the nature of the association remains unclear. From optical data we find that DSX meteors ablate similarly to Geminids,

Anas Abudaqa, Mohd Faiz Hilmi, Norziani Dahalan

Currently, job satisfaction and turnover intentions are the significant issues for oil and gas companies in the United Arab Emirates (UAE). These issues need to be addressed soon for the performance of the oil and gas companies. Thus, the aim related to the current study is to examine the impact of job burnout, emotional intelligence, and job satisfaction on

Gaspard Lambrechts, Adrien Bolland, Damien Ernst

Reinforcement learning aims to learn optimal policies from interaction with environments whose dynamics are unknown. Many methods rely on the approximation of a value function to derive near-optimal policies. In partially observable environments, these functions depend on the complete sequence of observations and past actions, called the history. In this wor

Silvio Dolfi, Emanuele Pacifici, Lucia Sanus

Let $G$ be a finite group, and let ${\rm{cd}}(G)$ denote the set of degrees of the irreducible complex characters of $G$. Define then the character degree graph $\Delta(G)$ as the (simple undirected) graph whose vertices are the prime divisors of the numbers in ${\rm{cd}}(G)$, and two distinct vertices $p$, $q$ are adjacent if and only if $pq$ divides some n

Maximiliano Cristiá, Gianfranco Rossi

Let $\mathcal{L}_{\mathcal{X}}$ be the language of first-order, decidable theory $\mathcal{X}$. Consider the language, $\mathcal{L}_{\mathcal{RQ}}(\mathcal{X})$, that extends $\mathcal{L}_{\mathcal{X}}$ with formulas of the form $\forall x \in A: \phi$ (restricted universal quantifier, RUQ) and $\exists x \in A: \phi$ (restricted existential quantifier, REQ)

Martin Strohmeier, Mauro Leonardi, Sergei Markochev, Fabio Ricciato

Knowledge about the exact positioning of aircraft is crucial in many settings. Consequently, the opportunistic and independent localization of aircraft based on their communication has been a longstanding problem and subject of much research. Originating from military settings, the capability to conduct aircraft localization has moved first towards the insti

Manli Liu, Weixiong Mai, Guokuan Shao

Given several sequences of Hermitian holomorphic line bundles $\{(L_{kp}, h_{kp})\}_{p=1}^{\infty}$, we establish the distribution of common zeros of random holomorphic sections of $L_{kp}$ with respect to singular measures. We also study the dimension growth for a sequence of pseudo-effective line bundles.

Emily Ruppel, Sihang Liu, Elba Garza, Sukyoung Ryu

Early in the pandemic, we -- leaders in the research areas of programming languages (PL) and computer architecture (CA) -- realized that we had a problem: the only way to form new lasting connections in the community was to already have lasting connections in the community. Both of our academic communities had wonderful short-term mentoring programs to addre

Jian Wang, Dongding Lin, Wenjie Li

Recommendation dialogue systems aim to build social bonds with users and provide high-quality recommendations. This paper pushes forward towards a promising paradigm called target-driven recommendation dialogue systems, which is highly desired yet under-explored. We focus on how to naturally lead users to accept the designated targets gradually through conve

Hatice Boylan, Nils-Peter Skoruppa

We show that we can develop from scratch and using only classical language a theory of relative quadratic extensions of a given number field $K$ which is as explicit and easy as for the well-known case that $K$ is the field of rational numbers. As an application we prove a reciprocity law which expresses the number of solutions of a given quadratic equation

YuanFu Yang, Min Sun

With the rapid development of artificial intelligence and autonomous driving technology, the demand for semiconductors is projected to rise substantially. However, the massive expansion of semiconductor manufacturing and the development of new technology will bring many defect wafers. If these defect wafers have not been correctly inspected, the ineffective

I. A. Sattarov

In this paper the group structure of the $p$-adic ball and sphere are studied. The dynamical system of isometry defined on invariant sphere is investigated. We define the binary operations $\oplus$ and $\odot$ on a ball and sphere respectively, and prove that this sets are compact topological abelian group with respect to the operations. Then we show that an

Francois Baccelli, Sergey Foss, Vsevolod Shneer

Consider a migration process based on a closed network of N stations with K_N customers. Each station is a ./M/\infty queue with service (migration) rate mu. Upon departure, a customer is routed at random to another station. In addition to migration, these customers are subject to an SIS (Susceptible, Infected, Susceptible) dynamics: customers are either I f

S. K. Maurya, Ksh. Newton Singh, Santosh V Lohakare, B. Mishra

The current theoretical development identified as the gravitational decoupling via Complete Geometric Deformation (CGD) method that has been introduced to explore the nonmetricity $Q$ effects in relativistic astrophysics. In the present work, we have investigated the gravitationally decoupled anisotropic solutions for the strange star in the framework of $f(

Jian-Sheng Wang, Jiebin Peng, Zu-Quan Zhang, Yong-Mei Zhang

We review the description and modeling of transport phenomena among the electron systems coupled via scalar or vector photons. It consists of three parts. The first part is about scalar photons, i.e., Coulomb interactions. The second part is with transverse photons described by vector potentials. The third part is on $\phi=0$ or temporal gauge, which is a fu

Simone Devoto

We present the mixed QCD-EW two-loop virtual amplitudes for the neutral current Drell-Yan production, one of the bottlenecks for the complete calculation of the NNLO mixed QCD-EW corrections. We present the computational details and the first steps towards their automation. We describe the evaluation of all the relevant two-loop Feynman integrals using analy

Michael Zlotnikov

We explore the scenario that the observable universe emerged from the vicinity of a negative mass ring singularity, and all content of the universe travels at the same group velocity close to the speed of light on a geodesic trajectory along the axis of rotation of the singularity. In appropriate coordinate parametrization and evaluated on the trajectory, we

Apostolos Spanakis-Misirlis, Cameron L. Van Eck

The study of fast radio bursts (FRBs) is of great importance, and is a topic that has been extensively researched, particularly in recent years. While the extreme nature of FRBs can serve as a tool for researchers to probe the intergalactic medium and study exotic aspects of the Universe, keeping track of FRB properties is challenged by the frequent detectio

Xiangyu Hua, Fanbao Meng, Zongyao Huang, Zhaohang Li

Unconventional quantum states, most notably the two-dimensional (2D) superconductivity, have been realized at the interfaces of oxide heterostructures where they can be effectively tuned by the gate voltage ($V_G$). Here we report that the interface between high-quality EuO (111) thin film and KTaO3 (KTO) (110) substrate shows superconductivity with onset tr

Gauthier Tallec, Jules Bonnard, Arnaud Dapogny, Kévin Bailly

Face based affective computing consists in detecting emotions from face images. It is useful to unlock better automatic comprehension of human behaviours and could pave the way toward improved human-machines interactions. However it comes with the challenging task of designing a computational representation of emotions. So far, emotions have been represented

Reethika Ramesh, Anjali Vyas, Roya Ensafi

As more users adopt VPNs for a variety of reasons, it is important to develop empirical knowledge of their needs and mental models of what a VPN offers. Moreover, studying VPN users alone is not enough because, by using a VPN, a user essentially transfers trust, say from their network provider, onto the VPN provider. To that end, we are the first to study th

Liangdi Zhang

We study a logarithmic inverse-trace flow on compact connected Hermitian manifolds. We first establish a parabolic comparison principle and the resulting oscillation nonexpansiveness for admissible potentials modulo constants. We then introduce common-drift sub- and supersolutions. Their combination yields a uniform drift-corrected zero-order estimate for ar

Amit Kumar, Deepak Pal, Seema Kushwaha, Sumit Kumar Upadhyay

The main aim of the article is to find the Schur multiplier and the Lie exterior square of some finite multiplicative Lie algebras. For a non abelian simple group $K$ with trivial Schur multiplier, we see that the Schur multiplier of multiplicative Lie algebra $K$ is trivial and the Lie exterior square of $K$ is an improper multiplicative Lie algebra $K.$

Soumya Mukherjee, Michel Destrade, Artur L. Gower

Real-world solids, such as rocks, soft tissues, and engineering materials, are often under some form of stress. Most real materials are also, to some degree, anisotropic due to their microstructure, a characteristic often called the `texture anisotropy'. This anisotropy can stem from preferential grain alignment in polycrystalline materials, aligned micro-cr

Xinrui Li, Yakui Huang

The quadratic termination property is important to the efficiency of gradient methods. We consider equipping a family of gradient methods, where the stepsize is given by the ratio of two norms, with two dimensional quadratic termination. Such a desired property is achieved by cooperating with a new stepsize which is derived by maximizing the stepsize of the

Dharanidhar Dang, Amitash Nanda, Bill Lin, Debashis Sahoo

With Moore's law saturating and Dennard scaling hitting its wall, traditional Von Neuman systems cannot offer the GFlops/watt for compute-intensive algorithms such as CNN. Recent trends in unconventional computing approaches give us hope to design highly energy-efficient computing systems for such algorithms. Neuromorphic computing is a promising such approa

R. Dey, P. K. Netrakanti, D. K. Mishra, S. P. Behera

We present a detailed study on detector response to different radioactive sources and the measurements of non-reactor environmental backgrounds with the Indian Scintillator Matrix for Reactor Anti-Neutrinos (ISMRAN) detector setup consisting of 9$\times$10 Plastic Scintillator Bars (PSBs) array at BARC, Mumbai. These measurements are useful in the context of

Justin Sirignano, Jonathan F. MacArt

A deep learning (DL) closure model for large-eddy simulation (LES) is developed and evaluated for incompressible flows around a rectangular cylinder at moderate Reynolds numbers. Near-wall flow simulation remains a central challenge in aerodynamic modeling: RANS predictions of separated flows are often inaccurate, while LES can require prohibitively small ne

Haoyuan Zhang, Yonghong Hou, Wenjing Zhang, Wanqing Li

Recent contrastive based 3D action representation learning has made great progress. However, the strict positive/negative constraint is yet to be relaxed and the use of non-self positive is yet to be explored. In this paper, a Contrastive Positive Mining (CPM) framework is proposed for unsupervised skeleton 3D action representation learning. The CPM identifi

Zhenyu Wu, Ziwei Wang, Zibu Wei, Yi Wei

Recognizing objects in dense clutter accurately plays an important role to a wide variety of robotic manipulation tasks including grasping, packing, rearranging and many others. However, conventional visual recognition models usually miss objects because of the significant occlusion among instances and causes incorrect prediction due to the visual ambiguity

Aidyn Kassymov, J. P Velasquez-Rodriguez

In this note we extend several integral inequalities to the context of noncommutative Vilenkin groups. We prove some sharp weak and strong type estimates for the Hardy operator and the Hardy-Littlewood-P{\'o}lya operator on constant-order noncommutative Vilenkin groups. In particular for graded $\K$-Lie groups, where $\K$ is a non-archimedean local field, we

Jingzhi Liu, Kai Wang, Lebin Liu, Jiajun Mo

In this paper, we reported the preparation of YFe$_{0.5}$Cr$_{0.5}$O$_3$ by the sol-gel method and studied its structure and M\"ossbauer spectrum at variable temperatures. X-ray diffraction(XRD) analysis exhibits that the sample has the orthorhombic structure with the Pnma space group, and the energy dispersive spectroscopy (EDS) analysis shows that the samp

Erik García Neefjes, David Nigro, Artur L. Gower, Raphaël C. Assier

We present a unified framework for the study of wave propagation in homogeneous linear thermo-visco-elastic (TVE) continua, starting from conservation laws. In free-space such media admit two thermo-compressional modes and a shear mode. We provide asymptotic approximations to the corresponding wavenumbers which facilitate the understanding of dispersion of t

Francisco Sánchez, Eduardo Battaner

The existence of life is one of the most fundamental problems of astrophysics. The intriguing existence of progressively complex and apparently improbable living beings should be a general tendency of life in the Universe. We are looking for general physical laws governing the growth of complexity in any astrophysical environment. We posit the existence of a

Hiroshi Nakahara, Kazuya Takeda, Keisuke Fujii

Recent measurement technologies enable us to analyze baseball at higher levels. There are, however, still many unclear points around the pitching strategy. The two elements make it difficult to measure the effect of pitching strategy. First, most public datasets do not include location data where the catcher demands a ball, which is essential information to

Ajinkya Gaikwad, Soumen Maity, Saket Saurabh

A set $D$ of vertices of a graph is a \emph{defensive alliance} if, for each element of $D$, the majority of its neighbours are in $D$. We consider the notion of local minimality in this paper. We are interested in finding a locally minimal defensive alliance of maximum size. In Locally Minimal Defensive Alliance problem, given an undirected graph $G$, a pos

Marco Castelli

We study some relations between left cancellative left semi-braces and other existing algebraic structures. In particular, we show that every left semi-brace arises from a left seminear-ring, extending the correspondence given by Rump between skew left braces and left near-rings in \cite{rump2019set}. Moreover, we show a correspondence between certain groups

Jacob Goldin, Julian Nyarko, Justin Young

Conducting causal inference with panel data is a core challenge in social science research. We adapt a deep neural architecture for time series forecasting (the N-BEATS algorithm) to more accurately impute the counterfactual evolution of a treated unit had treatment not occurred. Across a range of settings, the resulting estimator (``SyNBEATS'') significantl

Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li

Human leukocyte antigen (HLA) is an important molecule family in the field of human immunity, which recognizes foreign threats and triggers immune responses by presenting peptides to T cells. In recent years, the synthesis of tumor vaccines to induce specific immune responses has become the forefront of cancer treatment. Computationally modeling the binding

Zhi-zhong Xing, Jun-yu Zhu

The one-loop electroweak radiative corrections to coherent forward neutrino scattering in a medium slightly violates the tree-level universality of neutral-current contributions of three neutrino flavors to the matter potential that is relevant to neutrino oscillations in matter. We examine this small but nontrivial quantum effect by deriving the differentia

Sascha Lill

We construct an extension of Fock space and prove that it allows for implementing bosonic Bogoliubov transformations in a certain extended sense. While an implementation in the regular sense on Fock space is only possible if a certain operator $ v^* v $ is trace class (this is the well-known Shale-Stinespring condition), the extended implementation works wit

E. Mathian, H. Liu, L. Fernandez-Cuesta, D. Samaras

Unsupervised anomaly detection and localization is a crucial task as it is impossible to collect and label all possible anomalies. Many studies have emphasized the importance of integrating local and global information to achieve accurate segmentation of anomalies. To this end, there has been a growing interest in Transformer, which allows modeling long-rang

Abolfazl Lavaei, Mateo Perez, Milad Kazemi, Fabio Somenzi

We propose a compositional approach to synthesize policies for networks of continuous-space stochastic control systems with unknown dynamics using model-free reinforcement learning (RL). The approach is based on implicitly abstracting each subsystem in the network with a finite Markov decision process with unknown transition probabilities, synthesizing a str

Luca Arnaboldi, David Aspinall

We present a way to combine security and safety assessments using Bowtie Diagrams. Bowties model both the causes leading up to a central failure event and consequences which arise from that event, as well as barriers which impede events. Bowties have previously been used separately for security and safety assessments, but we suggest that a unified treatment

Xiaowen Chen, Maciej Winiarski, Alicja Puscian, Ewelina Knapska

Large interacting systems in biology often exhibit emergent dynamics, such as coexistence of multiple time scales, manifested by fat tails in the distribution of waiting times. While existing tools in statistical inference, such as maximum entropy models, reproduce the empirical steady state distributions, it remains challenging to learn dynamical models. We

Ziwei Dou, Xavier Ballu, Quan Dong, Yong Jin

In superconductor-normal-superconductor (SNS) junctions, dissipationless supercurrent is mediated via Andreev bound states (ABSs) controlled by the phase difference between the two superconductors. Theory has long predicted significant fluctuations, and thus a noise, of such supercurrent in equilibrium, due to the thermal excitation between the ABSs. Via the

Riccardo Falcone, Claudio Conti

An explicit Wigner formulation of Minkowski particle states for non-inertial observers is unknown. Here, we derive a general prescription to compute the characteristic function for Minkowski-Fock states in accelerated frames. For the special case of single-particle and two-particle states, this method enables to derive mean values of particle numbers and cor

Moumita Naskar, Muktish Acharyya

In the present chapter, we focus on the switching of magnetisation, or the metastable lifetime of a ferromagnetic system. In this regard, particularly the Ising model and the Blume-Capel model, have been simulated in the presence of an externally applied magnetic field by the Monte-Carlo simulation technique based on the Metropolis algorithm. Magnetisation s

Sean Cummins, Lorin Sweeney, Alan F. Smeaton

We investigate the memorability of a 5-season span of a popular crime-drama TV series, CSI, through the application of a vision transformer fine-tuned on the task of predicting video memorability. By investigating the popular genre of crime-drama TV through the use of a detailed annotated corpus combined with video memorability scores, we show how to extrapo

Abolfazl Lavaei, Sadegh Soudjani, Emilio Frazzoli

This work is concerned with the safety controller synthesis of stochastic hybrid systems, in which continuous evolutions are described by stochastic differential equations with both Brownian motions and Poisson processes, and instantaneous jumps are governed by stochastic difference equations with additive noises. Our proposed framework leverages the notion

Marco Discacciati, Claudia Garetto, Costas Loizou

This paper complements the study of the wave equation with discontinuous coefficients initiated in \cite{DGL:22} in the case of time-dependent coefficients. Here we assume that the equation coefficients are depending on space only and we formulate Levi conditions on the lower order terms to guarantee the existence of a very weak solution as defined in \cite{

Abolfazl Lavaei, Emilio Frazzoli

In this work, we propose a compositional scheme for the safety controller synthesis of interconnected discrete-time stochastic systems with Markovian switching signals. Our proposed approach is based on a notion of so-called control storage certificates computed for individual subsystems, by leveraging which, one can synthesize state-feedback controllers for

Yu Zhai, You Li, Hui Li, Frederick R. W. McCourt

The fundamental properties of molecules bridge experiment and theory. Transport properties (diffusion, thermal diffusion, thermal conductivity and viscosity) of binary mixtures are measurable in experiments, and well-defined in theory, but difficult to compute with high accuracy. In addition to high-accuracy inter-molecular potential energy curves (PECs), a

Hisashi Noma

The logistic regression analysis proposed by Schouten et al. (Stat Med. 1993;12:1733-1745) has been a standard method in current statistical analysis of case-cohort studies, and it enables effective estimation of risk ratio from selected subsamples. Schouten et al. (1993) also proposed the standard error estimate of the risk ratio estimator can be calculated

Yaosi Hu, Zhenzhong Chen

We propose a novel memory-enhancing mechanism for recurrent neural networks that exploits the effect of human cognitive appraisal in sequential assessment tasks. We conceptualize the memory-enhancing mechanism as Reinforcement Memory Unit (RMU) that contains an appraisal state together with two positive and negative reinforcement memories. The two reinforcem

Tao Zhang, Fang Yang

We introduce the concept of braided alternative bialgebra. The theory of cocycle bicrossproducts for alternative bialgebras is developed. As an application, the extending problem for alternative bialgebra is solved by using some non-abelian cohomology theory.

Veronica Vicuna-hernandez, Pegah Darvehi, Lorenzo Marrucci, Bruno Piccirillo

We present a method to generate monstar singularities via Pancharatnam-Berry phase by the coherent collinear superposition of two Free-Form Dark Hollow beams, $FFDH^{m}_{q}$, of topological charge $q$, and order of symmetry $m$. FFDH beams are generated with the geometrical parameters of a closed curve exploited to obtain a nonuniform rotation rate of the lo

Pradeep Kr. Banerjee, Kedar Karhadkar, Yu Guang Wang, Uri Alon

The quality of signal propagation in message-passing graph neural networks (GNNs) strongly influences their expressivity as has been observed in recent works. In particular, for prediction tasks relying on long-range interactions, recursive aggregation of node features can lead to an undesired phenomenon called "oversquashing". We present a framework for ana

Benteng Ma, Yushi Wang, Shen Wang

This technical report presents a comparative analysis of existing deep learning (DL) based approaches for brain tumor segmentation with missing MRI modalities. Approaches evaluated include the Adversarial Co-training Network (ACN) and a combination of mmGAN and DeepMedic. A more stable and easy-to-use version of mmGAN is also open-sourced at a GitHub reposit

Varun Bhardwaj, Kaushik Shukla, Frank Melandsø, Anowarul Habib

Lithium Niobate (LiNbO$_3$) is a piezoelectric crystal with a high electromechanical coupling coefficient. The development and miniaturization of acousto-electronics, and acousto-optics modulation filters, are primarily based on surface acoustic waves (SAWs) and bulk wave propagation in anisotropic crystals, such as LiNbO$_3$, Lithium Tantalate, and Quartz).

Karl Glazebrook, T. Nanayakkara, C. Jacobs, N. Leethochawalit

We present a first look at the reddest 2-5$\mu\rm m$ sources found in deep images from the GLASS Early Release Science program. We undertake a general search, i.e. not looking for any particular spectral signatures, for sources detected only in bands redder than reachable with the Hubble Space Telescope, and which would likely not have been identified in pre

Prakrit Joshi, Omar Hisham Alsadoon, Abeer Alsadoon, Nada AlSallami

Background and Aim: Over-fitting issue has been the reason behind deep learning technology not being successfully implemented in oral cancer images classification. The aims of this research were reducing overfitting for accurately producing the required dimension reduction feature map through Deep Learning algorithm using Convolutional Neural Network. Method

Bowen Yang, Qingwen Zhang, Ruoyu Geng, Lujia Wang

Having good knowledge of terrain information is essential for improving the performance of various downstream tasks on complex terrains, especially for the locomotion and navigation of legged robots. We present a novel framework for neural urban terrain reconstruction with uncertainty estimations. It generates dense robot-centric elevation maps online from s

Kaspar Rosager Ludvigsen, Shishir Nagaraja, Angela Daly

The world is currently strongly connected through both the internet at large, but also the very supply chains which provide everything from food to infrastructure and technology. The supply chains are themselves vulnerable to adversarial attacks, both in a digital and physical sense, which can disrupt or at worst destroy them. In this paper, we take a look a

Nikita Medvedev, Zuzana Kuglerová, Mikako Makita, Jaromír Chalupský

Materials exposed to ultrashort intense x-ray irradiation may experience various damaging conditions depending on the in-situ temperature. A pre-heated target exposed to intense x-rays plays a crucial role in numerous systems of physical-technical importance, ranging from the heavily-, and repeatedly radiation-loaded optics at x-ray free-electron laser facil

Wei Hu, Xiaojuan Yin

The rigidity degree of a generator-cogenerator determines the dominant dimension of its endomorphism algebra, and is closely related to a recently introduced homological dimension -- rigidity dimension. In this paper, we give explicit formulae for the rigidity degrees of all indecomposable modules over representation-finite self-injective algebras by develop

N. Filonov

In 1954, G. Polya conjectured that the counting function $N(\Omega,\Lambda)$ of the eigenvalues of the Laplace operator of the Dirichlet (resp. Neumann) boundary value problem in a bounded set $\Omega\subset R^d$ is lesser (resp. greater) than $(2\pi)^{-d} \omega_d |\Omega| \Lambda^{d/2}$. Here $\Lambda$ is the spectral parameter, and $\omega_d$ is the volum

Jiaxin Qi, Kaihua Tang, Qianru Sun, Xian-Sheng Hua

Out-Of-Distribution generalization (OOD) is all about learning invariance against environmental changes. If the context in every class is evenly distributed, OOD would be trivial because the context can be easily removed due to an underlying principle: class is invariant to context. However, collecting such a balanced dataset is impractical. Learning on imba

Nicholas Mirin, Heather Mattie, Latifa Jackson, Zainab Samad

Rapidly evolving technology, data and analytic landscapes are permeating many fields and professions. In public health, the need for data science skills including data literacy is particularly prominent given both the potential of novel data types and analysis methods to fill gaps in existing public health research and intervention practices, as well as the

Heng Zhang, Guangjin Pan, Shugong Xu, Shunqing Zhang

Network slicing is a critical driver for guaranteeing the diverse service level agreements (SLA) in 5G and future networks. Inter-slice radio resource allocation (IS-RRA) in the radio access network (RAN) is very important. However, user mobility brings new challenges for optimal IS-RRA. This paper first proposes a soft and hard hybrid slicing framework wher

Alen Pavlic, Cooper Lars Harshbarger, Luca Rosenthaler, Jess Gerrit Snedeker

Precise manipulation of fluids and objects on the micro scale is seldom a simple task, but nevertheless crucial for many applications in life sciences and chemical engineering. We present a microfluidic chip fabricated in silicon-glass, featuring one or several pairs of acoustically excited sharp edges at side channels that drive a pumping flow throughout th

Yupeng Yang

In the mixed dark matter scenarios consisting of primordial black holes (PBHs) and weakly interacting massive particles (WIMPs), WIMPs can be accreted onto PBHs to form ultracompact minihalos (UCMHs) with a density spike in the early universe. Compared with the classical dark matter halo, UCMHs are formed earlier and have a higher density of center. Since th

Alexander Molochkov

The review of vacuum and matter restructuring in space-time with boundaries is presented. We consider phase properties of confining gauge theories and strongly interacting fermion systems. In particular, the chiral and deconfinement phase transitions properties in the presence of Casimir plates. We also discuss mass scale shifts in such systems and their pos

Krishnadas M., K. P. Harikrishnan, G. Ambika

The financial markets are understood as complex dynamical systems whose dynamics is analysed mostly using nonstationary and brief data sets that usually come from stock markets. For such data sets, a reliable method of analysis is based on recurrence plots and recurrence networks, constructed from the data sets over the period of study. In this study, we do

Hyeonsu B. Kang, Joseph Chee Chang, Yongsung Kim, Aniket Kittur

Reviewing the literature to understand relevant threads of past work is a critical part of research and vehicle for learning. However, as the scientific literature grows the challenges for users to find and make sense of the many different threads of research grow as well. Previous work has helped scholars to find and group papers with citation information o

Yin Zhang, Can Xu, XianJun Wu, Yan Zhang

Tag-aware recommendation is a task of predicting a personalized list of items for a user by their tagging behaviors. It is crucial for many applications with tagging capabilities like last.fm or movielens. Recently, many efforts have been devoted to improving Tag-aware recommendation systems (TRS) with Graph Convolutional Networks (GCN), which has become new

Marino Gran, Jérôme Scherer

We extend the group-theoretic notion of conditional flatness for a localization functor to any pointed category, and investigate it in the context of homological categories and of semi-abelian categories. In the presence of functorial fiberwise localization analogous results to those obtained in the category of groups hold, and we provide existence theorems

Jinfeng Deng, Hang Dong, Chuanyu Zhang, Yaozu Wu

Topological photonics provides a novel platform to explore topological physics beyond traditional electronic materials and stimulates promising applications in topologically protected light transport and lasers. Classical degrees of freedom such as polarizations and wavevectors are routinely used to synthesize topological light modes. Beyond the classical re

Marie-Pierre Béal, Maxime Crochemore

We design alignment-free techniques for comparing a sequence or word, called a target, against a set of words, called a reference. A target-specific factor of a target $T$ against a reference $R$ is a factor $w$ of a word in $T$ which is not a factor of a word of $R$ and such that any proper factor of $w$ is a factor of a word of $R$. We first address the co

Ronen Eldan, Avi Wigderson, Pei Wu

We study the probability of Boolean functions with small max influence to become constant under random restrictions. Let $f$ be a Boolean function such that the variance of $f$ is $\Omega(1)$ and all its individual influences are bounded by $\tau$. We show that when restricting all but a $\rho=\tilde{\Omega}((\log(1/\tau))^{-1})$ fraction of the coordinates,

Guozhong Li, Byron Choi, Jianliang Xu, Sourav S Bhowmick

Time series shapelets are discriminative subsequences that have been recently found effective for time series clustering (TSC). The shapelets are convenient for interpreting the clusters. Thus, the main challenge for TSC is to discover high-quality variable-length shapelets to discriminate different clusters. In this paper, we propose a novel autoencoder-sha

Mohammad Taha Askari, Lutz Lampe, Jeebak Mitra

Probabilistic amplitude shaping (PAS) is a practical means to achieve a shaping gain in optical fiber communication. However, PAS and shaping in general also affect the signal-dependent generation of nonlinear interference. This provides an opportunity for nonlinearity mitigation through PAS, which is also referred to as a nonlinear shaping gain. In this pap

Filomena Feo, Futoshi Takahashi

In this note, we characterize the equality case of the sharp $L^2$-Euclidean logarithmic Sobolev inequality with monomial weights, exploiting the idea by Bobkov and Ledoux \cite{Bob}. Our approach is new even in the unweighted case. Also, we show that the same strategy yields the equality case of the sharp $L^p$-Euclidean logarithmic Sobolev inequality for $

Anna A. Taranenko

Perfect colorings (equitable partitions) of graphs are extensively studied, while the same concept for hypergraphs attracts much less attention. The aim of this paper is to develop basic notions and properties of perfect colorings for hypergraphs. Firstly, we introduce a multidimensional matrix equation for perfect colorings of hypergraphs and compare this d

Zeyu Zheng, Alex Infanger, Peter W. Glynn

In an influential paper, Courtois and Semal (1984) establish that when $G$ is an irreducible substochastic matrix for which $\sum_{n=0}^{\infty}G^n <\infty$, then the stationary distribution of any stochastic matrix $P\ge G$ can be expressed as a convex combination of the normalized rows of $(I-G)^{-1} = \sum_{n=0}^{\infty} G^n$. In this note, we give a shor

Zheng Wang

Domain generation algorithm (DGA) is used by botnets to build a stealthy command and control (C&C) communication channel between the C&C server and the bots. A DGA can periodically produce a large number of pseudo-random algorithmically generated domains (AGDs). AGD detection algorithms provide a lightweight, promising solution in response to the existing DG

Shannan Guan, Haiyan Lu, Linchao Zhu, Gengfa Fang

Existing 3D skeleton-based action recognition approaches reach impressive performance by encoding handcrafted action features to image format and decoding by CNNs. However, such methods are limited in two ways: a) the handcrafted action features are difficult to handle challenging actions, and b) they generally require complex CNN models to improve action re

Yonchanok Khaokaew, Indigo Holcombe-James, Mohammad Saiedur Rahaman, Jonathan Liono

Digital Assistants (DAs) can support workers in the workplace and beyond. However, target user needs are not fully understood, and the functions that workers would ideally want a DA to support require further study. A richer understanding of worker needs could help inform the design of future DAs. We investigate user needs of future workplace DAs using data

Agung Budiyono, Bobby E. Gunara, Bagus E. B. Nurhandoko, Hermawan K. Dipojono

We propose a characterization and a quantification of general quantum correlation which is exhibited even by a separable (unentangled) mixed bipartite state in terms of the nonclassical values of the associated Kirkwood-Dirac (KD) quasiprobability. Such a general quantum correlation, wherein entanglement is a subset, is not only intriguing from a fundamental

Agung Budiyono

What compels quantum measurement to violate the Bell inequalities? Suppose that regardless of measurement, one can assign to a spin-$\frac{1}{2}$ particle (qubit) a definite value of spin, called c-valued spin variable, but, it may take any continuous real number. Suppose further that measurement maps the c-valued spin variable from the continuous range of p

Fangzhou Gao, Meng Wang, Lianghao Zhang, Li Wang

Uncalibrated photometric stereo is proposed to estimate the detailed surface normal from images under varying and unknown lightings. Recently, deep learning brings powerful data priors to this underdetermined problem. This paper presents a new method for deep uncalibrated photometric stereo, which efficiently utilizes the inter-image representation to guide

Yuan Li, Dong Ye

We investigate the anisotropic elliptic equation $-\Delta_p^H u = g(u)$. Recently, Esposito, Riey, Sciunzi, and Vuono introduced an anisotropic Kelvin transform in their work \cite{ERSV2022} under the $(H_M)$ condition, where $H(\xi)=\sqrt{\langle M\xi,\xi\rangle}$ with a positive definite symmetric matrix $M$. Here, we emphasize that under the $(H_M)$ assum

Konstantin Golobokov, Junyi Chai, Victor Ye Dong, Mandy Gu

We present DeepGen, a system deployed at web scale for automatically creating sponsored search advertisements (ads) for BingAds customers. We leverage state-of-the-art natural language generation (NLG) models to generate fluent ads from advertiser's web pages in an abstractive fashion and solve practical issues such as factuality and inference speed. In addi

Srinjoy Bhuiya, Ayushman Kumar, Sankalok Sen

The real-time segmentation of drivable areas plays a vital role in accomplishing autonomous perception in cars. Recently there have been some rapid strides in the development of image segmentation models using deep learning. However, most of the advancements have been made in model architecture design. In solving any supervised deep learning problem related

Li-Xiang Cen

Regularized factorization is proposed to simulate time evolution for quantum lattice systems. Transcending the Trotter decomposition, the resulting compact structure of the propagator indicates a high-order Baker-Campbell-Hausdorff series. Regularized scheme of tensor network algorithms is then developed to determine the ground state energy for spin lattice