January 2022 arXiv papers — page 76

Thomas Pike, Robert Colter, Mark Bailey, Jackie Kazil

The Python ecosystem represents a global, data rich, technology-enabled network. By analyzing Python's dependency network, its top 14 most imported libraries and cPython (or core Python) libraries, this research finds clear evidence the Python network can be considered a problem solving network. Analysis of the contributor network of the top 14 libraries and

Qing Li, Y. Yu, Kai. H. Luo

Modeling liquid-vapor phase change using the lattice Boltzmann (LB) method has attracted significant attention in recent years. In this paper, we propose an improved three-dimensional (3D) thermal multiphase LB model for simulating liquid-vapor phase change. The proposed model has the following features. First, it is still within the framework of the thermal

Ramakrishna Vaikuntapu, Vineet Sahula, Lava Bhargava

Many fabless semiconductor companies outsource their designs to third-party fabrication houses. As trustworthiness of chain after outsourcing including fabrication houses is not established, any adversary in between, with malicious intent may tamper the design by inserting Hardware Trojans (HTs). Detection of such HTs is of utmost importance to assure the tr

Chen-Hsiu Huang, Ja-Ling Wu

mage steganography is the process of hiding information which can be text, image, or video inside a cover image. The advantage of steganography over cryptography is that the intended secret message does not attract attention and is thus more suitable for secret communication in a highly-surveillant environment such as civil disobedience movements. Internet m

Pinhe Wang, Limin Shi, Bao Chen, Zhanyi Hu

How to use multiple optical satellite images to recover the 3D scene structure is a challenging and important problem in the remote sensing field. Most existing methods in literature have been explored based on the classical RPC (rational polynomial camera) model which requires at least 39 GCPs (ground control points), however, it is not trivial to obtain su

Wojciech Flieger, Janusz Gluza

We study a geometric structure of a physical region of neutrino mixing matrices as part of the unit ball of the spectral norm. Each matrix from the geometric region is a convex combination of unitary PMNS matrices. The disjoint subsets corresponding to a different minimal number of additional neutrinos are described as relative interiors of faces of the unit

Ziwei Fan, Zhiwei Liu, Alice Wang, Zahra Nazari

Sequential recommendation models the dynamics of a user's previous behaviors in order to forecast the next item, and has drawn a lot of attention. Transformer-based approaches, which embed items as vectors and use dot-product self-attention to measure the relationship between items, demonstrate superior capabilities among existing sequential methods. However

De-Chang Dai, Glenn Starkman, Dejan Stojkovic

We analyze the existing rotation-curve data of the Milky Way and M31 galaxies that extends to very large distances and low accelerations. We find a systematic downward trend in the weak acceleration (large distances) segment of the radial acceleration. A similar downward trend has been noticed in the $\Lambda$CDM EAGLE simulation, while the deviation from th

Phillip Harris

Let $G$ be a random torsion-free nilpotent group generated by two random words of length $\ell$ in $U_n(\mathbb{Z})$. Letting $\ell$ grow as a function of $n$, we analyze the step of $G$, which is bounded by the step of $U_n(\mathbb{Z})$. We prove a conjecture of Delp, Dymarz, and Schafer-Cohen, that the threshold function for full step is $\ell = n^2$.

Alessandro Gimigliano, Monica Idà

We study the relation between the type of a double point of a plane curve and the curvilinear 0-dimensional subschemes of the curve at the point. An Algorithm related to a classical procedure for the study of double points via osculating curves is described and proved. Eventually we look for a way to create examples of rational plane curves with given singul

Jiaying Yin, Jing Fu, Jingjin Wu, Shiming Zheng

Fog computing offers a flexible solution for computational offloading for Internet of Things (IoT) services at the edge of wireless networks. It serves as a complement to traditional cloud computing, which is not cost-efficient for most offloaded tasks in IoT applications involving small-to-medium levels of computing tasks. Given the heterogeneity of tasks a

Chen Wu, Bo Du, Liangpei Zhang

Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most end-to-end networks are proposed for supervised change detection, and unsupervised change detection models depend on traditional pre-detection methods. Therefore, we proposed a fully convolutional change detection framework with generative advers

Yaser Rowshan

For given graph $H$ and graphical property $P$, the conditional chromatic number $\chi(H,P)$ of $H$, is the smallest number $k$, so that $V(H)$ can be decomposed into sets $V_1,V_2,\ldots, V_k$, in which $H[V_i]$ satisfies the property $P$, for each $1\leq i\leq k$. When property $P$ be that each color class contains no copy of $G$, we write $\chi_{G}(H)$ in

Kaj Bostrom, Zayne Sprague, Swarat Chaudhuri, Greg Durrett

In settings from fact-checking to question answering, we frequently want to know whether a collection of evidence (premises) entails a hypothesis. Existing methods primarily focus on the end-to-end discriminative version of this task, but less work has treated the generative version in which a model searches over the space of statements entailed by the premi

Waleed Ahsan, Wenqiang Yi, Yuanwei Liu, Arumugam Nallanathan

In this paper, we propose a deep state-action-reward-state-action (SARSA) $\lambda$ learning approach for optimising the uplink resource allocation in non-orthogonal multiple access (NOMA) aided ultra-reliable low-latency communication (URLLC). To reduce the mean decoding error probability in time-varying network environments, this work designs a reliable le

MyungJoo Ham, Sangjung Woo, Jaeyun Jung, Wook Song

Modern consumer electronic devices often provide intelligence services with deep neural networks. We have started migrating the computing locations of intelligence services from cloud servers (traditional AI systems) to the corresponding devices (on-device AI systems). On-device AI systems generally have the advantages of preserving privacy, removing network

Jiawen Deng, Jingyan Zhou, Hao Sun, Chujie Zheng

Offensive language detection is increasingly crucial for maintaining a civilized social media platform and deploying pre-trained language models. However, this task in Chinese is still under exploration due to the scarcity of reliable datasets. To this end, we propose a benchmark --COLD for Chinese offensive language analysis, including a Chinese Offensive L

Róbert Kovács

There are several models for heat conduction - non-Fourier equations - in the literature that are important for various practical problems. These models manifest themselves in partial differential equations, and the application of which requires developing efficient and reliable solution methods. In the present paper, we focus on the analytical solutions of

Andrea Di Lorenzo

We provide a general method for computing rational Chow rings of moduli of smooth complete intersections. We specialize this result in different ways: to compute the integral Picard group of the associated stack ; to obtain an explicit presentation of rational Chow rings of moduli of smooth complete intersections of codimension two; to prove old and new resu

Lei Yan, Zhijin Qin, Rui Zhang, Yongzhao Li

Semantic communications have shown its great potential to improve the transmission reliability, especially in the low signal-to-noise regime. However, resource allocation for semantic communications still remains unexplored, which is a critical issue in guaranteeing the semantic transmission reliability and the communication efficiency. To fill this gap, we

Wenbin Wu, Zeping Shi, Yuhan Du, Yuxiang Wang

Landau band crossings typically stem from the intra-band evolution of electronic states in magnetic fields and enhance the interaction effect in their vicinity. Here in the extreme quantum limit of topological insulator HfTe5, we report the observation of a topological Lifshitz transition from inter-band Landau level crossings using magneto-infrared spectros

Seyed A. Esmaeili, Sharmila Duppala, Davidson Cheng, Vedant Nanda

Online bipartite-matching platforms are ubiquitous and find applications in important areas such as crowdsourcing and ridesharing. In the most general form, the platform consists of three entities: two sides to be matched and a platform operator that decides the matching. The design of algorithms for such platforms has traditionally focused on the operator's

Yoshitaka Ogisu

It is well known that differences in the average number of friends among social groups can cause inequality in the average wage and/or unemployment rate. However, the impact of social network structure on inequality is not evident. In this paper, we show that not only the average number of friends but also the heterogeneity of degree distribution can affect

Angelo Felice Lopez, Roberto Muñoz, José Carlos Sierra

On any smooth $n$-dimensional variety we give a pretty precise picture of rank $r$ Ulrich vector bundles with numerical dimension at most $\frac{n}{2}+r-1$. Also, we classify non-big Ulrich vector bundles on quadrics and on the Del Pezzo fourfold of degree $6$.

Guangxiu Liu, Maocai Pi, Long Zhou, Zhehong Liu

Topology, a mathematical concept in geometry, has become an ideal theoretical tool for describing topological states and phase transitions. Many topological concepts have found their physical entities in real or reciprocal spaces identified by topological/geometrical invariants, which are usually defined on orientable surfaces such as torus and sphere. It is

Moustafa Gharamti, Maciej Jarema, Samuel Kirwin-Jones

We present the v1.0.1 release of DFormPy, the first Python library providing an interactive visualisation of differential forms. DFormPy is also capable of exterior algebra and vector calculus, building on the capabilities of NumPy and matplotlib. This short paper will demonstrate the functionalities of the library, briefly outlining the mathematics involved

Xiaoyu Luo, Chengcheng Zhao, Chongrong Fang, Jianping He

Consensus in multi-agent dynamical systems is prone to be sabotaged by the adversary, which has attracted much attention due to its key role in broad applications. In this paper, we study a new false data injection (FDI) attack design problem, where the adversary with limited capability aims to select a subset of agents and manipulate their local multi-dimen

H. B. Lee, G. C. Kim, Byeong-Joo Kim, Young Jin Sohn

We studied a qubit based on flux-pinning effects in $\Delta$H=$\Delta$B region of a superconductor. When volume defects are many enough in a superconductor, $\Delta$H=$\Delta$B region on M-H curve is formed, which is the region that increased applied magnetic field ($\Delta$H) is the same as increasing magnetic induction ($\Delta$B). Magnetization (M) is con

Edoardo Bocchi, Francisco Gancedo

This paper studies the one-phase Muskat problem driven by gravity and surface tension. The regime considered here is unstable with the fluid on top of a dry region. By a novel approach using a depth-averaged formulation, we derive two asymptotic approximations for this scenario. The lower order approximation is the classical thin film equation, while the hig

Ahmad Alhilal, Tristan Braud, Bo Han, Pan Hui

Mobile cloud gaming enables high-end games on constrained devices by streaming the game content from powerful servers through mobile networks. Mobile networks suffer from highly variable bandwidth, latency, and losses that affect the gaming experience. This paper introduces Nebula, an end-to-end cloud gaming framework to minimize the impact of network condit

Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara

The multi-agent pickup and delivery (MAPD) problem, in which multiple agents iteratively carry materials without collisions, has received significant attention. However, many conventional MAPD algorithms assume a specifically designed grid-like environment, such as an automated warehouse. Therefore, they have many pickup and delivery locations where agents c

Hélène Esnault, Daqing Wan

v2: For a projective variety defined over a finite field with $q$ elements, it is shown that as algebraic integers, the eigenvalues of the geometric Frobenius acting on $\ell$-adic cohomology have higher than known $q$-divisibility beyond the middle dimension. This sharpens both Deligne's integrality theorem and the cohomological divisibility theorem proven

Battulga Gankhuu

In this paper, we introduce a dynamic Gordon growth model, which is augmented by a time--varying spot interest rate and the Gordon growth model for dividends. Using the risk--neutral valuation method and locally risk--minimizing strategy, we obtain pricing and hedging formulas for the dividend--paying European call and put options and equity--linked life ins

Feifei Zhou, Shupei Song, Yuxuan Deng, Ting Zhang

We report a mixed-signal data acquisition (DAQ) system for optically detected magnetic resonance (ODMR) of solid-state spins. This system is designed and implemented based on a Field-Programmable-Gate-Array (FPGA) chip assisted with high-speed peripherals. The ODMR experiments often require high-speed mixed-signal data acquisition and processing for general

Athanasios Chatzikaleas, Arick Shao

We reconsider the unique continuation property for a general class of tensorial Klein-Gordon equations of the form \begin{align*} \Box_{g} \phi + \sigma \phi = \mathcal{G}(\phi,\nabla \phi) \text{,} \qquad \sigma \in \mathbb{R} \end{align*} on a large class of asymptotically anti-de Sitter spacetimes. In particular, we aim to generalize the previous results

Aman Madaan, Niket Tandon, Peter Clark, Yiming Yang

Large LMs such as GPT-3 are powerful, but can commit mistakes that are obvious to humans. For example, GPT-3 would mistakenly interpret "What word is similar to good?" to mean a homophone, while the user intended a synonym. Our goal is to effectively correct such errors via user interactions with the system but without retraining, which will be prohibitively

Chengchao Zhao, Nan Liu, Yuheng Ma, Jiwei Zhang

In this paper we consider a linearized variable-time-step two-step backward differentiation formula (BDF2) scheme for solving nonlinear parabolic equations. The scheme is constructed by using the variable time-step BDF2 for the linear term and a Newton linearized method for the nonlinear term in time combining with a Galerkin finite element method (FEM) in s

F. A. Cárdenas-López, Xi Chen

We propose how to engineer the longitudinal coupling to accelerate the measurement of a qubit longitudinally coupled to a cavity, motivated by the concept of shortcuts to adiabaticity. Different modulations are inversely designed from two methods of inverse engineering and counter-diabatic driving, for achieving larger values of the signal-to-noise ratio (SN

Steffen Ahrens, Ciril Bosch-Rosa, Thomas Meissner

We replicate Meissner (2016), where debt aversion was reported for the first time in an intertemporal consumption and saving problem. While Meissner (2016) uses a German sample, our participants are US undergraduate students. All of the original study's main findings replicate with similar effect sizes. Additionally, we extend the original analysis by introd

A. Dubey, K. Gustavsson, G. Bewley, B. Mehlig

Saffman and Turner (1957) argued that the collision rate for droplets in turbulence increases as the turbulent strain rate increases. But the numerical simulations of Dhanasekaran et al. (2021) in a steady straining flow show that the Saffman-Turner model is oversimplified because it neglects droplet-droplet interactions. These result in a complex dependence

Marcella Contini

We have collected from different surveys some significant spectroscopic data observed from star-forming galaxies in the local Universe. The objects showing a relatively rich spectrum in number of lines from different elements were selected in order to constrain the models. In particular, we looked at the relatively weak lines such as [OIII]4363, HeII4686, He

Tri Minh Nguyen, Thin Nguyen, Truyen Tran

Motivation: Predicting the drug-target interaction is crucial for drug discovery as well as drug repurposing. Machine learning is commonly used in drug-target affinity (DTA) problem. However, machine learning model faces the cold-start problem where the model performance drops when predicting the interaction of a novel drug or target. Previous works try to s

Chuying Huang, Xu Wang

The strong convergence rate of the Euler scheme for SDEs driven by additive fractional Brownian motions is studied, where the fractional Brownian motion has Hurst parameter $H\in(\frac13,\frac12)$ and the drift coefficient is not required to be bounded. The Malliavin calculus, the rough path theory and the $2$D Young integral are utilized to overcome the dif

Nanyang Xu, Feifei Zhou, Xiangyu Ye, Xue Lin

Noise-induced control imperfection is an important problem in applications of diamond-based nano-scale sensing, where measurement-based strategies are generally utilized to correct low-frequency noises in realtime. However, the spin-state readout requires a long time due to the low photon-detection efficiency. This inevitably introduces a delay in noise-redu

Renchunzi Xie, Hongxin Wei, Lei Feng, Bo An

This paper studies weakly supervised domain adaptation(WSDA) problem, where we only have access to the source domain with noisy labels, from which we need to transfer useful information to the unlabeled target domain. Although there have been a few studies on this problem, most of them only exploit unidirectional relationships from the source domain to the t

Vandna Gokhroo, Fam Le Kien, Síle Nic Chormaic

The integration of cold atomic systems with optical nanofibres is an increasingly important experimental platform. Here, we report on the spectra observed during a strongly driven, single-frequency, two-photon excitation of cold rubidium atoms near an optical nanofibre. At resonance, two competitive processes, namely a higher excitation rate and stronger pus

János Balogh, György Dósa, Leah Epstein, Łukasz Jeż

We prove new lower bounds for suitable competitive ratio measures of two relaxed online packing problems: online removable multiple knapsack, and a recently introduced online minimum peak appointment scheduling problem. The high level objective in both problems is to pack arriving items of sizes at most 1 into bins of capacity 1 as efficiently as possible, b

Guillaume Penent, Nicolas Privault

We present an algorithm for the numerical solution of ordinary differential equations by random enumeration of the Butcher trees used in the implementation of the Runge-Kutta method. Our Monte Carlo scheme allows for the direct numerical evaluation of an ODE solution at any given time within a certain interval, without iteration through multiple time steps.

Aritram Dhar, Avi Mukhopadhyay, Rishabh Sarma

In a recent pioneering work, Andrews and Newman defined an extended function $p_{A,a}(n)$ of their minimal excludant or "mex" of a partition function. By considering the special cases $p_{k,k}(n)$ and $p_{2k,k}(n)$, they unearthed connections to the rank and crank of partitions and some restricted partitions. In this paper, we build on their work and obtain

Tariq M Khan

In this paper, a hardware architecture of a multimodal biometric system is presented that massively exploits the inherent parallelism. The proposed system is based on multiple biometric fusion that uses two biometric traits, fingerprint and iris. Each biometric trait is first optimised at the software level, by addressing some of the issues that directly aff

Praneeth Kumar Vippathalla, Navin Kashyap

In this paper, we propose a strategy for making DNA-based data storage information-theoretically secure through the use of wiretap channel coding. This motivates us to extend the shuffling-sampling channel model of Shomorony and Heckel (2021) to include a wiretapper. Our main result is a characterization of the secure storage capacity of our DNA wiretap chan

X. X. Li, X. Q. Shao, Weibin Li

We propose an adiabatic protocol for implementing a controlled-phase gate CZ$_{\theta}$ with continuous $\theta$ of neutral atoms through a symmetrical two-photon excitation process via the second resonance line, $6P$ in $^{87}$Rb, with a single-temporal-modulation-coupling of the ground state and intermediate state. Relying on different adiabatic paths, the

Thaweesak Trongtirakul, Kamonnit Pusorn, Umpaporn Peerawanichkul

Due to the COVID-19 as a pandemic, the government has forced the nationwide shutdown of several activities, including educational activities. It has resulted in gigantic migration of universities with education over the internet serving as the educational platform. Hand-on-based learning becomes a new challenge. This paper aims to investigate the effect of c

Francis Borceux, Federico Campanini, Marino Gran

In a recent article Facchini and Finocchiaro considered a natural pretorsion theory in the category of preordered sets inducing a corresponding stable category. In the present work we propose an alternative construction of the stable category of the category $\mathsf{PreOrd} (\mathbb C)$ of internal preorders in any coherent category $\mathbb C$, that enligh

Javier Selva, Anders S. Johansen, Sergio Escalera, Kamal Nasrollahi

Transformer models have shown great success handling long-range interactions, making them a promising tool for modeling video. However, they lack inductive biases and scale quadratically with input length. These limitations are further exacerbated when dealing with the high dimensionality introduced by the temporal dimension. While there are surveys analyzin

Jacob Beyer, Jonas B. Profe, Lennart Klebl

The functional renormalization group (FRG), an established computational method for quantum many-body phenomena, has been subject to a diversification in topical applications, analytic approximations and numerical implementations. Despite significant efforts to accomplish a coherent standard through benchmarks and the reproduction of previous results, no sys

Thomas Müller, Alex Evans, Christoph Schied, Alexander Keller

Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate. We reduce this cost with a versatile new input encoding that permits the use of a smaller network without sacrificing quality, thus significantly reducing the number of floating point and memory access operations: a small neural network is augme

Qianhui Xu, Yi Liu, Sijie Hao, Jiahui Qian

The ground-state magnetic structures of the Eu$^{2+}$ spins in recently discovered RbEu(Fe$_{1-x}$Ni$_{x}$)$_{4}$As$_{4}$ superconductors have been investigated by neutron powder diffraction measurements. It is found that as the superconductivity gets suppressed with the increase of Ni doping, the magnetic propagation vector of the Eu sublattice diminishes,

Jiangshan Lan, Kaiyu Fu, Chandan Mondal, Xingbo Zhao

We investigate the structure of the light meson with one dynamical gluon from the light-front QCD Hamiltonian, determined for their constituent quark-antiquark and quark-antiquark-gluon Fock sectors, together with a three-dimensional confinement. After fitting the light meson mass spectroscopy, the light-front wave functions provide a good quality descriptio

Zipeng Ye, Mengfei Xia, Ran Yi, Juyong Zhang

In this paper, we present a dynamic convolution kernel (DCK) strategy for convolutional neural networks. Using a fully convolutional network with the proposed DCKs, high-quality talking-face video can be generated from multi-modal sources (i.e., unmatched audio and video) in real time, and our trained model is robust to different identities, head postures, a

Joseph Schlessinger, Richard Bennet, Jacob Coakwell, Steven T. Smith

This study quantifies influence between media outlets by applying a novel methodology that uses causal effect estimation on networks and transformer language models. We demonstrate the obscured influence of state-controlled outlets over other outlets, regardless of orientation, by analyzing a large dataset of quotations from over 100 thousand articles publis

Zeyu Zhang, Thuy Vu, Alessandro Moschitti

Current answer sentence selection (AS2) applied in open-domain question answering (ODQA) selects answers by ranking a large set of possible candidates, i.e., sentences, extracted from the retrieved text. In this paper, we present Passage-based Extracting Answer Sentence In-place (PEASI), a novel design for AS2 optimized for Web-scale setting, that, instead,

Wanjun Ning, Zimu Xu, Jingjin Wu, Tiejun Tong

We consider a wireless network scenario applicable to metropolitan areas with developed public transport networks and high commute demands, where the mobile user equipments (UEs) move along fixed and predetermined trajectories and request to associate with millimeter-wave (mmWave) base stations (BSs). An effective and efficient algorithm, called the Sequence

Evangelia Gazaki, Toshiro Hiranouchi

For a curve $X$ over a $p$-adic field $k$, using the class field theory of $X$ due to S. Bloch and S. Saito we study the abelian geometric fundamental group $\pi_1^{\mathrm{ab}}(X)^{\mathrm{geo}}$ of $X$. In particular, it is investigated a subgroup of $\pi_1^{\mathrm{ab}}(X)^{\mathrm{geo}}$ which classifies the geometric and abelian coverings of $X$ which a

Zeyu Zhang, Thuy Vu, Alessandro Moschitti

Recent work has shown that an answer verification step introduced in Transformer-based answer selection models can significantly improve the state of the art in Question Answering. This step is performed by aggregating the embeddings of top $k$ answer candidates to support the verification of a target answer. Although the approach is intuitive and sound stil

Wei Xu

Traditional sociotechnical systems (STS) theory has been widely used, but there are many new characteristics in the STS environment as we enter the intelligence era, resulting in the limitations of traditional STS. Based on the "user-centered design" philosophy, this paper proposes a new framework of intelligent sociotechnical systems (iSTS) and outlines the

Hao Wang, Yangguang Li, Zhen Huang, Yong Dou

Unsupervised sentence embedding aims to obtain the most appropriate embedding for a sentence to reflect its semantic. Contrastive learning has been attracting developing attention. For a sentence, current models utilize diverse data augmentation methods to generate positive samples, while consider other independent sentences as negative samples. Then they ad

Varun Ramamohan, Shobhit Singhal, Aditya Raj Gupta, Nomesh Bhojkumar Bolia

Machine learning (ML) methods are used in most technical areas such as image recognition, product recommendation, financial analysis, medical diagnosis, and predictive maintenance. An important aspect of implementing ML methods involves controlling the learning process for the ML method so as to maximize the performance of the method under consideration. Hyp

Fan Wang, Chaofan Zhang, Fulin Tang, Hongkui Jiang

Mapping and localization are two essential tasks for mobile robots in real-world applications. However, largescale and dynamic scenes challenge the accuracy and robustness of most current mature solutions. This situation becomes even worse when computational resources are limited. In this paper, we present a novel lightweight object-level mapping and localiz

Tianyi Zhang, Dengji Zhao, Junyu Zhang, Sizhe Gu

We consider a cost sharing problem to connect all nodes in a weighted undirected graph, where the weight of each edge represents the cost to use the edge for the connectivity and the cost has to be shared among all connected nodes. There is one node called the source to which all the other nodes want to connect and it does not share the costs of the connecti

Borui Cai, Yong Xiang, Longxiang Gao, He Zhang

Knowledge graph completion (KGC) can predict missing links and is crucial for real-world knowledge graphs, which widely suffer from incompleteness. KGC methods assume a knowledge graph is static, but that may lead to inaccurate prediction results because many facts in the knowledge graphs change over time. Recently, emerging methods have shown improved predi

Samsil Arefin Mozumder, A S M Sharifuzzaman Sagar

Human existence is getting more sophisticated and better in many areas due to remarkable advances in the fields of automation. Automated systems are favored over manual ones in the current environment. Home Automation is becoming more popular in this scenario, as people are drawn to the concept of a home environment that can automatically satisfy users' requ

Kohei Hayashi, Kei Nakagawa

In this paper, we focus on the generation of time-series data using neural networks. It is often the case that input time-series data have only one realized (and usually irregularly sampled) path, which makes it difficult to extract time-series characteristics, and its noise structure is more complicated than i.i.d. type. Time series data, especially from hy

Xiaoyun Zhao, Ning Yang, Philip S. Yu

Cross-domain recommendation (CDR) has been attracting increasing attention of researchers for its ability to alleviate the data sparsity problem in recommender systems. However, the existing single-target or dual-target CDR methods often suffer from two drawbacks, the assumption of at least one rich domain and the heavy dependence on domain-invariant prefere

Shuangjie Xu, Rui Wan, Maosheng Ye, Xiaoyi Zou

Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially for large instances, and that objects are too close to separate each other. Recent literature addresses these problems by time-consuming grouping processes such as dual-clustering, m

Dennis M. Heim

Initial momenta of de Broglie-Bohm trajectories generally do not obey quantum mechanical momentum distributions. The solution to this problem presented in the following leads to an extended hydrodynamic interpretation of quantum mechanics. To demonstrate the new formalism, it is applied to the double-slit experiment. From this example follows a proposal for

Ziwen Du, Ning Yang, Zhonghua Yu, Philip S. Yu

Traditional robust recommendation methods view atypical user-item interactions as noise and aim to reduce their impact with some kind of noise filtering technique, which often suffers from two challenges. First, in real world, atypical interactions may signal users' temporary interest different from their general preference. Therefore, simply filtering out t

Zhe Zhang, Xiaoyu Song

Cracks in clay are significant in geotechnical and geoenvironmental engineering (e.g., embankment erosion and stability of landfill cover systems). This article studies the mechanism of nucleation and growth of cracks in clay at the nanoscale through full-scale molecular dynamics simulations. The clay adopted is pyrophyllite, and the force field is CLAYFF. T

Mayank Verma, Alok Mishra, Ashoke De

The present work numerically investigates vortex-induced vibrations (VIV) of a two-dimensional circular cylinder with an axisymmetric slit at Reynolds number 500. The study examines the effects of slit shape (i.e., converging, diverging, and parallel slits), the effect of slit-area ratios, slit-width, and its angle with the freestream velocity on aerodynamic

Matias D. Cattaneo, Yingjie Feng, William G. Underwood

Dyadic data is often encountered when quantities of interest are associated with the edges of a network. As such it plays an important role in statistics, econometrics and many other data science disciplines. We consider the problem of uniformly estimating a dyadic Lebesgue density function, focusing on nonparametric kernel-based estimators taking the form o

Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong

Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases and question answering over knowledge bases. Since the inputs and outputs of SKG tasks are heterogeneous, they have been studied separately by different communities, which limits systematic and compatible research on SKG. In

Mayank Verma, Ashoke De

The paper presents the comparative study of the vortex-induced cooling of a heated channel for the four different cross-sections of the rigid cylinder, i.e., circular, square, semi-circular, and triangular, with or without the rigid/flexible splitter plate at the Reynolds number (based on the hydraulic diameter) of 200. The study presents a comprehensive ana

Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman

Organizations often collect private data and release aggregate statistics for the public's benefit. If no steps toward preserving privacy are taken, adversaries may use released statistics to deduce unauthorized information about the individuals described in the private dataset. Differentially private algorithms address this challenge by slightly perturbing

Malik A. Manan, Tariq M. Khan, Ahsan Saadat, Muhammad Arsalan

Diabetic retinopathy refers to the pathology of the retina induced by diabetes and is one of the leading causes of preventable blindness in the world. Early detection of diabetic retinopathy is critical to avoid vision problem through continuous screening and treatment. In traditional clinical practice, the involved lesions are manually detected using photog

Qi An, Patryk Szewczyk, Michael N Johnstone, James Jin Kang

Patients are often encouraged to make use of wearable devices for remote collection and monitoring of health data. This adoption of wearables results in a significant increase in the volume of data collected and transmitted. The battery life of the devices is then quickly diminished due to the high processing requirements of the devices. Given the importance

Arsal Imtiaz, Danish Khan, Hanjia Lyu, Jiebo Luo

The Israel-Palestine Conflict, one of the most enduring conflicts in history, dates back to the start of 20th century, with the establishment of the British Mandate in Palestine and has deeply rooted complex issues in politics, demography, religion, and other aspects, making it harder to attain resolve. To understand the conflict in 2021, we devise an observ

Fuyi Xu

The present paper is the continuation of work \cite{XC}, devoted to extending it to a critical functional framework which is not related to the energy space. Employing the special dissipative structure of the non-conservative viscous compressible two-fluid model with capillarity effects, we first exploit the maximal regularity estimates for the corresponding

Deepanshu Vasal, Randall Berry

In this paper, we consider a discrete-time Stackelberg mean field game with a leader and an infinite number of followers. The leader and the followers each observe types privately that evolve as conditionally independent controlled Markov processes. The leader commits to a dynamic policy and the followers best respond to that policy and each other. Knowing t

Monu Verma, Prafulla Saxena, Santosh Kumar Vipparthi, Girdhari Singh

In this paper, we propose a new feature descriptor Cross-Centroid Ripple Pattern (CRIP) for facial expression recognition. CRIP encodes the transitional pattern of a facial expression by incorporating cross-centroid relationship between two ripples located at radius r1 and r2 respectively. These ripples are generated by dividing the local neighborhood region

Ming Gong, He-Liang Huang, Shiyu Wang, Chu Guo

Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here,

Meng Zhao, Pedro Anjos, John Lowengrub, Wenjun Ying

We investigate the nonlinear dynamics of a moving interface in a Hele-Shaw cell subject to an in-plane applied electric field. We develop a spectrally accurate boundary integral method where a coupled integral equation system is formulated. Although the stiffness due to the high order spatial derivatives can be removed, the long-time simulation is still expe

Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi

A recurring challenge of crowdsourcing NLP datasets at scale is that human writers often rely on repetitive patterns when crafting examples, leading to a lack of linguistic diversity. We introduce a novel approach for dataset creation based on worker and AI collaboration, which brings together the generative strength of language models and the evaluative str

John Machacek

Walnut is a software that using automata can prove theorems in combinatorics on words about automatic sequences. We are able to apply this software to both prove new results as well as reprove some old results on avoiding squares and cubes in partial words. We also define the notion of an antisquare in a partial word and begin the study of binary partial wor

Kun Wang, Bing-Nan Lu

The nuclear deformations are of fundamental importance in nuclear physics. Recently we developed a multi-dimensionally constrained relativistic Hartree-Bogoliubov (MDCRHB) model, in which all multipole deformations respecting the $V_4$ symmetry can be considered self-consistently. In this work we extend this model by incorporating the angular momentum projec

Yiyang Jia, Dario Rosa, Jacobus J. M. Verbaarschot

We analyze a two-body nonhermitian two-site Sachdev-Ye-Kitaev model with the couplings of one site complex conjugated to the other site. This model, with no explicit coupling between the sites, shows an infinite number of phase transitions which is a consequence of the partition function factorizing into a product over Matsubara frequencies. We calculate the

Shiyu Wang

Writer identification has practical applications for forgery detection and forensic science. Most models based on deep neural networks extract features from character image or sub-regions in character image, which ignoring features contained in page-region image. Our proposed global regular network (GRN) pays attention to these features. GRN network consists

Frédéric Ouimet

In this paper, we develop a local limit theorem for the Student distribution. We use it to improve the normal approximation of the Student survival function given in Shafiei & Saberali (2015) and to derive asymptotic bounds for the corresponding maximal errors at four levels of approximation. As a corollary, approximations for the percentage points (or quant

Julián López-Gómez, Juan Carlos Sampedro

This paper establishes some hidden connections between the theory of generalized algebraic multiplicities, the intersection index of algebraic varieties, and the notion of orientability of vector bundles. The novel approach adopted in it facilitates the definition of several invariants closely related to the first Stiefel-Whitney fundamental class through so

Fritz Gesztesy, Roger Nichols

Using the variational characterization of the principal (i.e., smallest) eigenvalue below the essential spectrum of a lower semibounded self-adjoint operator, we prove strict domain monotonicity (with respect to changing the finite interval length) of the principal eigenvalue of the Friedrichs extension $T_F$ of the minimal operator for regular four-coeffici

Moïse Blanchard

We study the subject of universal online learning with non-i.i.d. processes for bounded losses. The notion of an universally consistent learning was defined by Hanneke in an effort to study learning theory under minimal assumptions, where the objective is to obtain low long-run average loss for any target function. We are interested in characterizing process