March 2023 arXiv papers — page 119

Yves André

The Tate conjecture has two parts: i) Tate classes are linear combination of algebraic classes, ii) semisimplicity of Galois representations (for smooth projective varieties). B. Moonen proved that i) implies ii) in characteristic 0, using $p$-adic Hodge theory. We show that an unconditional result lies behind this implication: the {\it observability} of ari

Mingming Xiu, Yang Nie, Qing Song, Chun Liu

As a method of image restoration, image super-resolution has been extensively studied at first. How to transform a low-resolution image to restore its high-resolution image information is a problem that researchers have been exploring. In the early physical transformation methods, the high-resolution pictures generated by these methods always have a serious

Bowen Dong, Jiaxi Gu, Jianhua Han, Hang Xu

Existing open-world universal segmentation approaches usually leverage CLIP and pre-computed proposal masks to treat open-world segmentation tasks as proposal classification. However, 1) these works cannot handle universal segmentation in an end-to-end manner, and 2) the limited scale of panoptic datasets restricts the open-world segmentation ability on thin

Linh T. Nguyen, Lam Duc Nguyen, Thong Hoang, Dilum Bandara

Various data-sharing platforms have emerged with the growing public demand for open data and legislation mandating certain data to remain open. Most of these platforms remain opaque, leading to many questions about data accuracy, provenance and lineage, privacy implications, consent management, and the lack of fair incentives for data providers. With their t

Hao Zhou, Chongyang Zhang, Yanjun Chen, Chuanping Hu

Temporal grounding aims to retrieve moments of the described event within an untrimmed video by a language query. Typically, existing methods assume annotations are precise and unique, yet one query may describe multiple moments in many cases. Hence, simply taking it as a one-vs-one mapping task and striving to match single-label annotations will inevitably

Francisco Pérez-Galarce, Karim Pichara, Pablo Huijse, Márcio Catelan

In recent decades, machine learning has provided valuable models and algorithms for processing and extracting knowledge from time-series surveys. Different classifiers have been proposed and performed to an excellent standard. Nevertheless, few papers have tackled the data shift problem in labeled training sets, which occurs when there is a mismatch between

Zhenwei Zhang, Haorui Yan, Ke Tang, Yuping Duan

The challenges in recovering underwater images are the presence of diverse degradation factors and the lack of ground truth images. Although synthetic underwater image pairs can be used to overcome the problem of inadequately observing data, it may result in over-fitting and enhancement degradation. This paper proposes a model-based deep learning method for

Etienne Roberge, Guillaume Fornes, Jean-Philippe Roberge

Combining 3D vision with tactile sensing could unlock a greater level of dexterity for robots and improve several manipulation tasks. However, obtaining a close-up 3D view of the location where manipulation contacts occur can be challenging, particularly in confined spaces, cluttered environments, or without installing more sensors on the end effector. In th

Fadi Sun, Jinwu Ye

Topological phases and topological phase transitions (TPT) are among the most fantastic phenomena in Nature. Here we show that injecting a current may lead to new topological phases, especially new gapless topological metallic phases with extended Fermi surfaces (FSs) through novel class of TPTs in the bulk or the boundary. Specifically, we study the quantum

Tiancheng Song, Yanyu Jia, Guo Yu, Yue Tang

The superconductor to insulator or metal transition in two dimensions (2D) provides a valuable platform for studying continuous quantum phase transitions (QPTs) and critical phenomena. Distinct theoretical models, including both fermionic and bosonic localization scenarios, have been developed, but many questions remain unsettled despite decades of research.

Augustine Ukpebor, James C. Addy, Kamal Ali, Ali A. Humos

Various studies have been developed to monitor the gaping behavior of bivalves (oysters) in response to environmental factors. This work aims to fully automate oyster spawning detection in real-time by building on previous efforts. The sensor system developed at Jackson State University, Mississippi, employs the Hall effect phenomenon to accurately measure t

Yue Zhou

It is well-known that the Selberg integral is equivalent to the Morris constant term identity. In 2009 Warnaar obtained the Selberg integral for the Lie algebra $A_n$. In this paper, from the point view of constant term identities, we obtain a $q$-Morris constant term identity of type $A_n$ and its several symmetric function generalizations. The type $A_n$ $

Sungbok Shin, Sanghyun Hong, Niklas Elmqvist

Designing a visualization is often a process of iterative refinement where the designer improves a chart over time by adding features, improving encodings, and fixing mistakes. However, effective design requires external critique and evaluation. Unfortunately, such critique is not always available on short notice and evaluation can be costly. To address this

Qi Zhao, Bai Yan, Taiwei Hu, Xianglong Chen

Metaheuristics are prominent gradient-free optimizers for solving hard problems that do not meet the rigorous mathematical assumptions of analytical solvers. The canonical manual optimizer design could be laborious, untraceable and error-prone, let alone human experts are not always available. This arises increasing interest and demand in automating the opti

Judith Perera, Ewan Tempero, Yu-Cheng Tu, Kelly Blincoe

To effectively manage Technical Debt (TD), we need reliable means to quantify it. We conducted a Systematic Mapping Study (SMS) where we identified TD quantification approaches that focus on different aspects of TD. Some approaches base the quantification on the identification of smells, some quantify the Return on Investment (ROI) of refactoring, some compa

Joshua Harrington, Matthew Litman, Tony W. H. Wong

For an integer $b\geq 2$, a positive integer is called a $b$-Niven number if it is a multiple of the sum of the digits in its base-$b$ representation. In this article, we show that every arithmetic progression contains infinitely many $b$-Niven numbers.

Ruinan Li, Xinyu Wang

The purpose of this paper is twofold. Firstly, we prove transportation inequalities ${\bf T_2}(C)$ on the space of continuous paths with respect to the uniform metric for the law of the solution to a class of non-linear monotone stochastic partial differential equations (SPDEs) driven by the Wiener noise. Furthermore, we also establish the ${\bf T_1}(C)$ pro

Qi Zhao, Qiqi Duan, Bai Yan, Shi Cheng

Metaheuristics have gained great success in academia and practice because their search logic can be applied to any problem with available solution representation, solution quality evaluation, and certain notions of locality. Manually designing metaheuristic algorithms for solving a target problem is criticized for being laborious, error-prone, and requiring

Yabin Wang, Xiaopeng Hong, Zhiheng Ma, Tiedong Ma

Task allocation plays a vital role in multi-robot autonomous cleaning systems, where multiple robots work together to clean a large area. However, most current studies mainly focus on deterministic, single-task allocation for cleaning robots, without considering hybrid tasks in uncertain working environments. Moreover, there is a lack of datasets and benchma

Jike Zhong, Hong-You Chen, Wei-Lun Chao

Batch Normalization (BN) is widely used in {centralized} deep learning to improve convergence and generalization. However, in {federated} learning (FL) with decentralized data, prior work has observed that training with BN could hinder performance and suggested replacing it with Group Normalization (GN). In this paper, we revisit this substitution by expandi

Liyan Xu, Yihang Li, Hang Yin, Hongbin Yu

Improving energy efficiency is vital for the 5G mobile telecommunication network, while the conventional temporal shutdown strategy is exhausting its energy-saving potential. Inspired by the symmetricity between the temporal peaks and valleys and the geographical hot and cold-spots in network traffic, we propose a new strategy for telecom energy-saving which

Mikael Mazur, Nicolas K. Fontaine, Megan Kelleher, Valey Kamalov

In this work we demonstrate an FPGA-based coherent optical frequency domain reflectometry setup for cable monitoring. Using coherent detection for averaging and narrowband filtering, we significantly improve the signal-to-noise ratio (SNR) compared to traditional intensity-only techniques while also enabling continuous monitoring of phase and polarization. I

Regina S. Burachik, Bethany I Caldwell, C. Yalçın Kaya, Walaa M. Moursi

We explore the relationship between the dual of a weighted minimum-energy control problem, a special case of linear-quadratic optimal control problems, and the Douglas-Rachford (DR) algorithm. We obtain an expression for the fixed point of the DR operator as applied to solving the optimal control problem, which in turn devises a certificate of optimality tha

Kaan Gokcesu, Hakan Gokcesu

We study the adversarial online learning problem and create a completely online algorithmic framework that has data dependent regret guarantees in both full expert feedback and bandit feedback settings. We study the expected performance of our algorithm against general comparators, which makes it applicable for a wide variety of problem scenarios. Our algori

Xiao Lu, Zhan-Jiang Lian, Xue-Wei Li, Zao-Chun Gao

The variation after projection (VAP) method is expected to be an efficient way of getting the optimized nuclear wave functions, so that they can be as close as possible to the exact shell model ones. However, we found there are two additional problems that may seriously affect the convergence of the VAP iteration. The first problem is, if a randomly selected

Bei Zhou, Søren Riis

The study of large Condorcet domains (CD) has been a significant area of interest in voting theory. In this paper, our goal is to search for large CDs that are hitherto unknown. With a straightforward combinatorial definition, searching for large CDs is naturally suited for algorithmic optimisations. For each value of n>2, one can ask for the size of the lar

Yuhan Yao, Vikram Ravi, Suvi Gezari, Sjoert van Velzen

We conduct a systematic tidal disruption event (TDE) demographics analysis using the largest sample of optically selected TDEs. A flux-limited, spectroscopically complete sample of 33 TDEs is constructed using the Zwicky Transient Facility over three years (from October 2018 to September 2021). We infer the black hole (BH) mass ($M_{\rm BH}$) with host galax

Lei Zhou, Huidong Liu, Joseph Bae, Junjun He

Can we use sparse tokens for dense prediction, e.g., segmentation? Although token sparsification has been applied to Vision Transformers (ViT) to accelerate classification, it is still unknown how to perform segmentation from sparse tokens. To this end, we reformulate segmentation as a sparse encoding -> token completion -> dense decoding (SCD) pipeline. We

Xiao Lu, Zhan-Jiang Lian, Zao-Chun Gao

Angular momentum projection plays a key role in studying quantum many-body systems with rotational invariance such as atomic nuclei. At a given spin $J$, one can generate $2J+1$ angular momentum projected states labeled with $-J\leq K \leq J$ from a deformed Slater determinant. Usually, a nuclear wave function with $K$-mixing can be expressed as a superposit

Robert S. Markiewicz, Bahadur Singh, Christopher Lane, Arun Bansil

We discuss the evolution of high-order Van Hove singularities (hoVHSs) that carry faster-than logarithmic divergences over a wide range of parameters in cuprate-like electronic band dispersions. Numerical analysis gives insight into the quantization of the VHS power-law-exponent pV and into transitions between hoVHSs with different values of pV. The cuprates

Dat Thanh Nguyen, Andre Kaup

In recent years, we have witnessed the presence of point cloud data in many aspects of our life, from immersive media, autonomous driving to healthcare, although at the cost of a tremendous amount of data. In this paper, we present an efficient lossless point cloud compression method that uses sparse tensor-based deep neural networks to learn point cloud geo

Xiao Lu, Zhan-Jiang Lian, Zao-Chun Gao

In this paper, we study the mixing of one-particle-one-hole projected states with the variation after projection (VAP) wave functions in attempt to improve the approximation of this method. It turns out that when minimizing only the lowest (yrast) energy with given spin and parity, the one-particle-one-hole projected states can not be mixed into the converge

Dat Thanh Nguyen, Kamal Gopikrishnan Nambiar, Andre Kaup

In recent years, several point cloud geometry compression methods that utilize advanced deep learning techniques have been proposed, but there are limited works on attribute compression, especially lossless compression. In this work, we build an end-to-end multiscale point cloud attribute coding method (MNeT) that progressively projects the attributes onto m

Leopoldo Bertossi, Jorge E. Leon

The use of Shap scores has become widespread in Explainable AI. However, their computation is in general intractable, in particular when done with a black-box classifier, such as neural network. Recent research has unveiled classes of open-box Boolean Circuit classifiers for which Shap can be computed efficiently. We show how to transform binary neural netwo

Dimitris Bertsimas, Kimberly Villalobos Carballo

We develop a non-parametric, data-driven, tractable approach for solving multistage stochastic optimization problems in which decisions do not affect the uncertainty. The proposed framework represents the decision variables as elements of a reproducing kernel Hilbert space and performs functional stochastic gradient descent to minimize the empirical regulari

Wenjun Lin, Paul Babyn, Yan yan, Wenjun Zhang

This research paper explores the use of ChatGPT in database management. ChatGPT, an AI-powered chatbot, has limitations in performing tasks related to database management due to the lack of standardized vocabulary and grammar for representing database semantics. To address this limitation, the paper proposes a solution that involves developing a set of synta

AlsharifHasan Mohamad Aburbeian, Huthaifa I. Ashqar

The credit card has become the most popular payment method for both online and offline transactions. The necessity to create a fraud detection algorithm to precisely identify and stop fraudulent activity arises as a result of both the development of technology and the rise in fraud cases. This paper implements the random forest (RF) algorithm to solve the is

Ahmad Hamarshe, Huthaifa I. Ashqar, Mohammad Hamarsheh

The concept of Software Defined Networking (SDN) represents a modern approach to networking that separates the control plane from the data plane through network abstraction, resulting in a flexible, programmable and dynamic architecture compared to traditional networks. The separation of control and data planes has led to a high degree of network resilience,

Alessandro Alla, Angela Monti, Ivonne Sgura

Dynamic Mode Decomposition (DMD) is an equation-free method that aims at reconstructing the best linear fit from temporal datasets. In this paper, we show that DMD does not provide accurate approximation for datasets describing oscillatory dynamics, like spiral waves and relaxation oscillations, or spatio-temporal Turing instability. Inspired from the classi

David J. Yoon, Keenan Burnett, Johann Laconte, Yi Chen

In this paper, we present a fast, lightweight odometry method that uses the Doppler velocity measurements from a Frequency-Modulated Continuous-Wave (FMCW) lidar without data association. FMCW lidar is a recently emerging technology that enables per-return relative radial velocity measurements via the Doppler effect. Since the Doppler measurement model is li

Shuangyao Huang, Haibo Zhang, Zhiyi Huang

This paper presents a novel solution to address the challenges in achieving energy efficiency and cooperation for collision avoidance in UAV swarms. The proposed method combines Artificial Potential Field (APF) and Particle Swarm Optimization (PSO) techniques. APF provides environmental awareness and implicit coordination to UAVs, while PSO searches for coll

Ahmad Z. Fino, Michael Ruzhansky, Berikbol T. Torebek

In this paper, we consider the Cauchy problem for the degenerate parabolic equations on the Heisenberg groups with power law non-linearities. We obtain Fujita-type critical exponents, which depend on the homogeneous dimension of the Heisenberg groups. The analysis includes the case of porous medium equations. Our proof approach is based on methods of nonline

Bumho Kim, Jicheng Jin, Zhi Wang, Li He

To enable new nonlinear responses, metamaterials are created by organizing structural units (meta-atoms) which are typically on the scale of about a hundred nanometers. However, truly altering atomic symmetry and enabling new nonlinear responses requires control at the atomic-scale, down to a few angstroms. Here we report the discovery of 3D nonlinear optica

David J. Yoon, Timothy D. Barfoot

In this paper, we present an algorithm for learning time-correlated measurement covariances for application in batch state estimation. We parameterize the inverse measurement covariance matrix to be block-banded, which conveniently factorizes and results in a computationally efficient approach for correlating measurements across the entire trajectory. We tra

Marius Lemm, Carla Rubiliani, Israel Michael Sigal, Jingxuan Zhang

We study general lattice bosons with long-range hopping and long-range interactions decaying as $|x-y|^{-\alpha} $ with $\alpha\in (d+2,2d+1)$. We find a linear light cone for the information propagation starting from suitable initial states. We apply these bounds to estimate the minimal time needed for quantum messaging, for the propagation of quantum corre

Sandip Das, Frank Slyne, Daniel Kilper, Marco Ruffini

Ultra-low end-to-end latency is one of the most important requirements in 5G networks and beyond to support latency-critical applications. Cloud-RAN and MEC are considered as the key driving technology that can help reduce end-to-end latency. However, the use of MEC nodes poses radical changes to the access network architecture. As it brings the processing a

Yasamin Jafarian, Tuanfeng Y. Wang, Duygu Ceylan, Jimei Yang

Clothes undergo complex geometric deformations, which lead to appearance changes. To edit human videos in a physically plausible way, a texture map must take into account not only the garment transformation induced by the body movements and clothes fitting, but also its 3D fine-grained surface geometry. This poses, however, a new challenge of 3D reconstructi

Iheanyi Omezuruike Okonko, Chisom Chimbundum Adim, Blessing Jachinma Okonko, Edith Ijeego Mba

Hepatitis A virus (HAV) infection has been greatly reduced in most developed countries through the use of vaccine and improved hygienic conditions. However, the magnitude of the problem is underestimated and there are no well-established Hepatitis A virus prevention and control strategies in Nigeria. The aim of this study was to determine the prevalence of H

Nesreen Mufid

Automation technology has become an integral part of our daily lives, whether it's in our homes, cars, or workplaces. Thanks to the various communication interfaces and standards available today, implementing monitoring and automation systems has become a straightforward and efficient task.

Joseph Janssen, Shizhe Meng, Asad Haris, Stefan Schrunner

Scientists and statisticians often want to learn about the complex relationships that connect two time-varying variables. Recent work on sparse functional historical linear models confirms that they are promising for this purpose, but several notable limitations exist. Most importantly, previous works have imposed sparsity on the historical coefficient funct

Ibrahim Ethem Hamamci, Sezgin Er, Enis Simsar, Anjany Sekuboyina

Due to the necessity for precise treatment planning, the use of panoramic X-rays to identify different dental diseases has tremendously increased. Although numerous ML models have been developed for the interpretation of panoramic X-rays, there has not been an end-to-end model developed that can identify problematic teeth with dental enumeration and associat

Victor Monzon Baeza

Multiple access is the base for increasing the capacity in multi-user communication networks. However, the growing demand for higher data rates and the number of users who requires communication services has led to the scarcity of orthogonal resources in current wireless communications. On the other hand, integrating the satellite within terrestrial networks

Sergiy S. Vasylyev, Yi Yang, Kishore C. Patra, Alexei V. Filippenko

We present six epochs of optical spectropolarimetry of the Type IIP supernova (SN) 2021yja ranging from $\sim$ 25 to 95 days after the explosion. An unusually high continuum linear polarization of $p \sim 0.9\%$ is measured during the early photospheric phase, followed by a steady decrease well before the onset of the nebular phase. This behavior has not bee

Minh C. Tran, Kunal Sharma, Kristan Temme

In this work, we study and improve two leading error mitigation techniques, namely Probabilistic Error Cancellation (PEC) and Zero-Noise Extrapolation (ZNE), for estimating the expectation value of local observables. For PEC, we introduce a new estimator that takes into account the light cone of the unitary circuit with respect to a target local observable.

Eric Dohner, Hanna Terletska, Herbert F Fotso

Although most studies of strongly correlated systems away from equilibrium have focused on clean systems, it is well known that disorder may significantly modify observed properties in various nontrivial ways. The nonequilibrium interplay of interaction and disorder in these systems thus requires further investigation. In the present paper, we use the recent

Sanjar Shaymatov, Kimet Jusufi, Mirzabek Alloqulov, Bobomurat Ahmedov

The purpose of this paper is to examine the epicyclic motion of charged particles in the vicinity of a magnetically charged stringy black hole subject to an electromagnetic field. This investigation is motivated by the established fact that magnetic fields have a significant impact on the motion of charged particles in the vicinity of a black hole. It has be

Qin Liu, Meng Zheng, Benjamin Planche, Zhongpai Gao

Automatic medical volume segmentation often lacks clinical accuracy, necessitating further refinement. In this work, we interactively approach medical volume segmentation via two decoupled modules: interaction-to-segmentation and segmentation propagation. Given a medical volume, a user first segments a slice (or several slices) via the interaction module and

Konstantin Mischaikow, Charles Weibel

This paper concerns the computation and identification of the (homological) Conley index over the integers, in the context of discrete dynamical systems generated by continuous maps. We discuss the significance with respect to nonlinear dynamics of using integer, as opposed to field, coefficients. We translate the problem into the language of commutative rin

Sudipta Ghosh, Ian Zemke

We prove a number of fundamental properties about instanton knot Floer homology. Our arguments rely on general properties of sutured Floer theories and apply also in the Heegaard Floer and monopole Floer settings, where many of our results were already known. Our main result is the connected sum formula for instanton knot Floer homology. An extension of this

Victor O. Rivelles

We discuss the long range interactions mediated by continuous spin particles. We start by deriving the propagator for a continuous spin particle using the antifield BRST formalism. Then we couple the continuous spin particle to a conserved current to find the interaction energy due to static disturbances of the vacuum. For sources having charges of the same

Leonie Neufeld

We study weighted sums of free identically distributed self-adjoint random variables with weights chosen randomly from the unit sphere and show that the Kolmogorov distance between the distribution of such a weighted sum and Wigner's semicircle law is of order $n^{-1/2}$ with high probability. Replacing the Kolmogorov distance by a weaker pseudometric, we ob

Calvin Leng, David Kempe

We introduce a search problem generalizing the typical setting of Binary Search on the line. Similar to the setting for Binary Search, a target is chosen adversarially on the line, and in response to a query, the algorithm learns whether the query was correct, too high, or too low. Different from the Binary Search setting, the cost of a query is a monotone n

Manoj Bhardwaj, Alexander V. Osipov

In this paper, we proved that a clopen version $S_1(C_O, C_O)$ of the Rothberger property and Borel strong measure zeroness are independent. For a zero-dimensional metric space $(X, d)$, $X$ satisfies $S_1(C_O, C_O)$ if, and only if, $X$ has Borel strong measure zero with respect to each metric which has a same topology as d has. In a zero-dimensional space,

Mahya Morid Ahmadi, Faiq Khalid, Radha Vaidya, Florian Kriebel

Dynamic partial reconfiguration enables multi-tenancy in cloud-based FPGAs, which presents security challenges for tenants, IPs, and data. Malicious users can exploit FPGAs for remote side-channel attacks (SCAs), and shared on-chip resources can be used for attacks. Logical separation can ensure design integrity, but on-chip resources can still be exploited.

Karim Johannes Becher, Saurabh Gosavi

We discuss and relate finiteness conditions for certain field invariants which are studied in quadratic form theory. This includes the $u$-invariant, the reduced stability index and the symbol lengths for Galois cohomology groups with coefficients in $\mu_2=\{+1,-1\}$, as well as a new invariant called the splitting height.

Weiyang Liu, Longhui Yu, Adrian Weller, Bernhard Schölkopf

The neural collapse (NC) phenomenon describes an underlying geometric symmetry for deep neural networks, where both deeply learned features and classifiers converge to a simplex equiangular tight frame. It has been shown that both cross-entropy loss and mean square error can provably lead to NC. We remove NC's key assumption on the feature dimension and the

Fábio Botler, Andrea Jiménez, Carla N. Lintzmayer, Adrián Pastine

The analogue of Hadwiger's conjecture for the immersion relation states that every graph $G$ contains an immersion of $K_{\chi(G)}$. For graphs with independence number 2, this is equivalent to stating that every such $n$-vertex graph contains an immersion of $K_{\lceil n/2 \rceil}$. We show that every $n$-vertex graph with independence number 2 contains eve

Aparna P. A. Subramanyam, Jan Jenke, Alvin Noe Ladines, Ralf Drautz

Interatomic potentials provide a means to simulate extended length and time scales that are outside the reach of ab initio calculations. The development of an interatomic potential for a particular material requires the optimization of the parameters of the functional form of the potential. We present a parameterization protocol for analytic bond-order poten

Jonathan Bayless, Paul Kinlaw, Jared Duker Lichtman

For $k\ge1$, let $R_k(x)$ denote the reciprocal sum up to $x$ of numbers with $k$ prime factors, counted with multiplicity. In prior work, the authors obtained estimates for $R_k(x)$, extending Mertens' second theorem, as well as a finer-scale estimate for $R_2(x)$ up to $(\log x)^{-N}$ error for any $N > 0$. In this article, we establish the limiting behavi

Xingyu Liu, Alex Leonardi, Lu Yu, Chris Gilmer-Hill

In many practical scenarios -- like hyperparameter search or continual retraining with new data -- related training runs are performed many times in sequence. Current practice is to train each of these models independently from scratch. We study the problem of exploiting the computation invested in previous runs to reduce the cost of future runs using knowle

Alan Cefali Signor, Gabriel Antonio Carita, Maria Helena Moreira Morais

We present a numerical study on the stability of all fourth- and fifth-order retrograde mean motion resonances (1/3, 3/1, 1/4, 4/1, 2/3, and 3/2) in the 3-body problem composed of a solar mass star, a Jupiter mass planet, and an additional body with zero mass (elliptic restricted problem) or masses corresponding to either Neptune, Saturn, or Jupiter (planeta

Dimitrios Panteleimon Giakatos, Pavlos Sermpezis, Athena Vakali

Today online social networks have a high impact in our society as more and more people use them for communicating with each other, express their opinions, participating in public discussions, etc. In particular, Twitter is one of the most popular social network platforms people mainly use for political discussions. This attracted the interest of many researc

Marcus Gerhold, Arnd Hartmanns

The Competition on Software Verification (SV-COMP) is a large computational experiment benchmarking many different software verification tools on a vast collection of C and Java benchmarks. Such experimental research should be reproducible by researchers independent from the team that performed the original experiments. In this reproduction report, we presen

Huanqia Cai, Fanglei Xue, Lele Xu, Lili Guo

Image matting aims to predict alpha values of elaborate uncertainty areas of natural images, like hairs, smoke, and spider web. However, existing methods perform poorly when faced with highly transparent foreground objects due to the large area of uncertainty to predict and the small receptive field of convolutional networks. To address this issue, we propos

Ge Zhu, Yujia Yan, Juan-Pablo Caceres, Zhiyao Duan

Non-linguistic filler words, such as "uh" or "um", are prevalent in spontaneous speech and serve as indicators for expressing hesitation or uncertainty. Previous works for detecting certain non-linguistic filler words are highly dependent on transcriptions from a well-established commercial automatic speech recognition (ASR) system. However, certain ASR syst

Ignacio García Marco, Pedro A. García-Sánchez, Ignacio Ojeda, Christos Tatakis

A numerical semigroup is said to be universally free if it is free for any possible arrangement of its minimal generating set. In this work, we establish that toric ideals associated with universally free numerical semigroups can be generated by their set of circuits. Additionally, we provide a characterization of universally free numerical semigroups in ter

Abhisek Panda, Smruti R. Sarangi

Serverless computing systems are becoming very popular. Large corporations such as Netflix, Airbnb, and Coca-Cola use such systems for running their websites and IT systems. The advantages of such systems include superior support for auto-scaling, load balancing, and fast distributed processing. These are multi-QoS systems where different classes of applicat

Héctor Barge, José M. R. Sanjurjo

In this paper we study the relationship of the Brouwer degree of a vector field with the dynamics of the induced flow. Analogous relations are studied for the index of a vector field. We obtain new forms of the Poincar% \'{e}-Hopf theorem and of the Borsuk and Hirsch antipodal theorems. As an application, we calculate the Brouwer degree of the vector field o

Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, Paul Stewart

Cancer has relational information residing at varying scales, modalities, and resolutions of the acquired data, such as radiology, pathology, genomics, proteomics, and clinical records. Integrating diverse data types can improve the accuracy and reliability of cancer diagnosis and treatment. There can be disease-related information that is too subtle for hum

Samuel Goldman, John Bradshaw, Jiayi Xin, Connor W. Coley

Computational predictions of mass spectra from molecules have enabled the discovery of clinically relevant metabolites. However, such predictive tools are still limited as they occupy one of two extremes, either operating (a) by fragmenting molecules combinatorially with overly rigid constraints on potential rearrangements and poor time complexity or (b) by

Pushpendra Yadav, K. V. Adarsh, Amit Agarwal

Photo-excited electrons and holes in insulators, above a critical density and below a critical temperature, can condense to form an electron-hole liquid (EHL) phase. However, observing the EHL phase at room temperature is extremely challenging. Here, we introduce the monolayer MoSi$_2$Z$_4$ (Z= N, As, P) series of compounds as a promising platform for observ

Debdarsan Niyogi, J. Srinivasan

It is important to predict how the Global Mean Temperature (GMT) will evolve in the next few decades. The ability to predict historical data is a necessary first step toward the actual goal of making long-range forecasts. This paper examines the advantage of statistical and simpler Machine Learning (ML) methods instead of directly using complex ML algorithms

Amrita Mandal, Bibhas Adhikari

Orthogonal matrices which are linear combinations of permutation matrices have attracted enormous attention in quantum information and computation. In this paper, we provide a complete parametric characterization of all complex, real and rational orthogonal permutative matrices of order $4.$ We show that any such matrix can always be expressed as a linear co

Kohei Kobayashi

To implement quantum information technologies, carefully designed control for preparing a desired state plays a key role. However, in realistic situation, the actual performance of those methodologies is severely limited by decoherence. Therefore, it is important to evaluate how close we can steer the controlled state to a desired target state under decohere

B. J. Lynch, N. M. Viall, A. K. Higginson, L. Zhao

Connecting the solar wind observed throughout the heliosphere to its origins in the solar corona is one of the central aims of heliophysics. The variability in the magnetic field, bulk plasma, and heavy ion composition properties of the slow wind are thought to result from magnetic reconnection processes in the solar corona. We identify regions of enhanced v

Gemma Canet Tarrés, Dan Ruta, Tu Bui, John Collomosse

We propose PARASOL, a multi-modal synthesis model that enables disentangled, parametric control of the visual style of the image by jointly conditioning synthesis on both content and a fine-grained visual style embedding. We train a latent diffusion model (LDM) using specific losses for each modality and adapt the classifier-free guidance for encouraging dis

Venkatesh Vadde, Bhaskaran Muralidharan, Abhishek Sharma

We demonstrate a magnetic tunnel junction injected with spin Hall current to exhibit linear rotation of magnetization of the free-ferromagnet using only the spin current. Using the linear resistance change of the MTJ, we devise a circuit for the rectified linear activation (ReLU) function of the artificial neuron. We explore the role of different spin Hall e

Andrew Manion

We define larger variants of the vector spaces one obtains by decategorifying bordered (sutured) Heegaard Floer invariants of surfaces. We also define bimodule structures on these larger spaces that are similar to, but more elaborate than, the bimodule structures that arise from decategorifying the higher actions in bordered Heegaard Floer theory introduced

You Lv, Wenming Hong

Consider the invariance principle for a random walk with random environment (denoted by $\mu$) in time on $\bfR$ in a weak quenched sense. We show that a sequence of the random probability measures on $\bfR$ generated by a bounded Lipschitz functional $f$ and $\mu$ will converge in distribution to another random probability measures, which is related to $f$

Wenchao Li, Zhan Wang, Yun Wang, Di Weng

In geographic data videos, camera movements are frequently used and combined to present information from multiple perspectives. However, creating and editing camera movements requires significant time and professional skills. This work aims to lower the barrier of crafting diverse camera movements for geographic data videos. First, we analyze a corpus of 66

Iman Lotfimahyari, Paolo Giaccone

Blockchains offer trust and immutability in non-trusted environments, but most are not fast enough for latency-sensitive applications. Hyperledger Fabric (HF) is a common enterprise-level platform that is being offered as Blockchain-as-a-Service (BaaS) by cloud providers. In HF, every new transaction requires a preliminary endorsement by multiple mutually un

José M. Carcione, Jing Ba

We analyze the management of the Italian pandemic during the five identified waves. We considered the following problems: (i) The composition of the CTS ("Scientific Technical Committee"), which was composed entirely of doctors, mainly virologists, without mathematical epidemiologists, statisticians, physicists, etc. In fact, a pandemic has a behavior descri

Bang Yang, Fenglin Liu, Yuexian Zou, Xian Wu

Natural Language Generation (NLG) accepts input data in the form of images, videos, or text and generates corresponding natural language text as output. Existing NLG methods mainly adopt a supervised approach and rely heavily on coupled data-to-text pairs. However, for many targeted scenarios and for non-English languages, sufficient quantities of labeled da

Adam Pardyl, Grzegorz Rypeść, Grzegorz Kurzejamski, Bartosz Zieliński

Active visual exploration addresses the issue of limited sensor capabilities in real-world scenarios, where successive observations are actively chosen based on the environment. To tackle this problem, we introduce a new technique called Attention-Map Entropy (AME). It leverages the internal uncertainty of the transformer-based model to determine the most in

Will LeVine, Benjamin Pikus, Pranav Raja, Fernando Amat Gil

Calibration of deep learning models is crucial to their trustworthiness and safe usage, and as such, has been extensively studied in supervised classification models, with methods crafted to decrease miscalibration. However, there has yet to be a comprehensive study of the calibration of vision-language models that are used for zero-shot inference, like CLIP

Wenchao Li, Sarah Schöttler, James Scott-Brown, Yun Wang

This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community e

Mario Villaizán-Vallelado, Matteo Salvatori, Belén Carro Martinez, Antonio Javier Sanchez Esguevillas

All industries are trying to leverage Artificial Intelligence (AI) based on their existing big data which is available in so called tabular form, where each record is composed of a number of heterogeneous continuous and categorical columns also known as features. Deep Learning (DL) has constituted a major breakthrough for AI in fields related to human skills

Boubakeur Bahri, Yassine Guerboussa

A finite abelian $p$-group having an automorphism $x$ such that $1+\ldots+x^{p-1}=0$, can be viewed as a module over an appropriate discrete valuation ring $\mathcal{O}$ containing $\mathbb{Z}_p$ (the ring of $p$-adic integer). This yields the natural problem of comparing the invariants of $A$ as a $\mathbb{Z}_p$-module to its invariants as an $\mathcal{O}$-

J. B. Climent, J. C. Guirado, M. Pérez-Torres, J. M. Marcaide

Radio observations of ultracool dwarfs, objects comprising brown dwarfs and the very lowest mass stars, have mainly focused on analyzing their light-curve and spectral energy distributions providing valuable insights into their magnetic fields. However, spatially-resolved studies of such magnetospheres have been elusive so far. Radio interferometric observat

Jeremy Speth, Nathan Vance, Benjamin Sporrer, Lu Niu

Camera-based physiological monitoring, especially remote photoplethysmography (rPPG), is a promising tool for health diagnostics, and state-of-the-art pulse estimators have shown impressive performance on benchmark datasets. We argue that evaluations of modern solutions may be incomplete, as we uncover failure cases for videos without a live person, or in th