March 2023 arXiv papers — page 79

Qianying Cao, Somdatta Goswami, George Em Karniadakis

We introduce the Laplace neural operator (LNO), which leverages the Laplace transform to decompose the input space. Unlike the Fourier Neural Operator (FNO), LNO can handle non-periodic signals, account for transient responses, and exhibit exponential convergence. LNO incorporates the pole-residue relationship between the input and the output space, enabling

Yoav Goldberg

It is an established assumption that pattern-based models are good at precision, while learning based models are better at recall. But is that really the case? I argue that there are two kinds of recall: d-recall, reflecting diversity, and e-recall, reflecting exhaustiveness. I demonstrate through experiments that while neural methods are indeed significantl

Philippos Papaphilippou, Thiem Van Chu

Network-on-chips (NoCs) are currently a widely used approach for achieving scalability of multi-cores to many-cores, as well as for interconnecting other vital system-on-chip (SoC) components. Each entity in 2D mesh-based NoCs has a router responsible for forwarding packets between the dimensions as well as the entity itself, and it is essentially a 5-port s

Miheer Dewaskar, Christopher Tosh, Jeremias Knoblauch, David B. Dunson

Likelihood-based inferences have been remarkably successful in wide-spanning application areas. However, even after due diligence in selecting a good model for the data at hand, there is inevitably some amount of model misspecification: outliers, data contamination or inappropriate parametric assumptions such as Gaussianity mean that most models are at best

SungJoon Park, Gyeonghun Kim, Kiho Kim, Dohun Kim

Quantum defects in diamonds have been studied as a promising resource for quantum science. The subtractive fabrication process for improving photon collection efficiency often require excessive milling time that can adversely affect the fabrication accuracy. We designed and fabricated a Fresnel-type solid immersion lens using the focused ion beam. For a 5.8

Alexandros Doumanoglou, Stylianos Asteriadis, Dimitrios Zarpalas

An important line of research attempts to explain CNN image classifier predictions and intermediate layer representations in terms of human-understandable concepts. Previous work supports that deep representations are linearly separable with respect to their concept label, implying that the feature space has directions where intermediate representations may

Jalal Al-Lami, Thibaut Dessolier, Talha Pirzada, Minh-Son Pham

Plastic inhomogeneity, particularly localised strain, is one of the main mechanisms responsible for failures in engineering alloys. This work studied the spatial arrangement and distribution of microstructure and their influence in the plastic inhomogeneity of Inconel 718 fabricated by additive manufacturing (AM). In particular, the density and spatial distr

Ruichen Wang, Dinesh Manocha

Radio applications are increasingly being used in urban environments for cellular radio systems and safety applications that use vehicle-vehicle, and vehicle-to-infrastructure. We present a novel ray tracing-based radio propagation algorithm that can handle large urban scenes with hundreds or thousands of dynamic objects and receivers. Our approach is based

Nguyen Ngoc Luan, Nguyen Mau Nam, Nguyen Dong Yen

This paper presents a study of generalized polyhedral convexity under basic operations on multifunctions. We address the preservation of generalized polyhedral convexity under sums and compositions of multifunctions, the domains and ranges of generalized polyhedral convex multifunctions, and the direct and inverse images of sets under such mappings. Then we

Alireza Nikzamir, Kasra Rouhi, Alexander Figotin, Filippo Capolino

We investigate how a single resonator with a time-modulated component extracts power from an external ambient source. However, the collected power is largely dependent on the precise choice of the modulation signal frequency. We focus on the power absorbed from external vibration using a one degree-of-freedom mechanical resonator where the damper has a time-

Kamil Moldosanov, Alexander Bykov, Nurlanbek Kairyev, Mikhail Khodzitsky

Purpose: The terahertz (THz) medical imaging is a promising noninvasive technique for monitoring the skin's conditions, early detection of the human skin cancer, and recovery from burns and wounds. It can be applied for visualization of healing process directly through clinical dressings and restorative ointments, minimizing the frequency of dressing changes

Monika di Angelo, Thomas Durieux, João F. Ferreira, Gernot Salzer

Blockchain programs (also known as smart contracts) manage valuable assets like cryptocurrencies and tokens, and implement protocols in domains like decentralized finance (DeFi) and supply-chain management. These types of applications require a high level of security that is hard to achieve due to the transparency of public blockchains. Numerous tools suppor

Shuo Wang, Junyan Lu

Background Deriving feature rankings is essential in bioinformatics studies since the ordered features are important in guiding subsequent research. Feature rankings may be distorted by influential points (IP), but such effects are rarely mentioned in previous studies. This study aimed to investigate the impact of IPs on feature rankings and propose a new me

Hanliang Zhang, Cristina David, Yijun Yu, Meng Wang

Dubbed a safer C, Rust is a modern programming language that combines memory safety and low-level control. This interesting combination has made Rust very popular among developers and there is a growing trend of migrating legacy codebases (very often in C) to Rust. In this paper, we present a C to Rust translation approach centred around static ownership ana

S. Mohammadzadeh, V. H. Nascimento, R. C. de Lamare, O. Kukrer

In this work, a simple and effective robust adaptive beamforming technique is proposed for uniform linear arrays, which is based on the power spectral estimation and uncertainty region (PSEUR) of the interference plus noise (IPN) components. In particular, two algorithms are presented to find the angular sector of interference in every snapshot based on the

Chowdhury Mohammad Sakib Anwar, Jorge Bruno, Renaud Foucart, Sonali SenGupta

We generalize the model of Gallice and Monzon (2019) to incorporate a public goods game with groups, position uncertainty, and observational learning. Contributions are simultaneous within groups, but groups play sequentially based on their observation of an incomplete sample of past contributions. We show that full cooperation between and within groups is p

Yuhao Zhang, Hang Zhang, Xiangru Xu

The proliferation of neural networks in safety-critical applications necessitates the development of effective methods to ensure their safety. This letter presents a novel approach for computing the exact backward reachable sets of neural feedback systems based on hybrid zonotopes. It is shown that the input-output relationship imposed by a ReLU-activated ne

Qingru Zhang, Minshuo Chen, Alexander Bukharin, Nikos Karampatziakis

Fine-tuning large pre-trained language models on downstream tasks has become an important paradigm in NLP. However, common practice fine-tunes all of the parameters in a pre-trained model, which becomes prohibitive when a large number of downstream tasks are present. Therefore, many fine-tuning methods are proposed to learn incremental updates of pre-trained

Fanglei Xue, Yifan Sun, Yi Yang

This paper explores an expression-related self-supervised learning (SSL) method (ContraWarping) to perform expression classification in the 5th Affective Behavior Analysis in-the-wild (ABAW) competition. Affective datasets are expensive to annotate, and SSL methods could learn from large-scale unlabeled data, which is more suitable for this task. By evaluati

Yanan Jia

As human-machine voice interfaces provide easy access to increasingly intelligent machines, many state-of-the-art automatic speech recognition (ASR) systems are proposed. However, commercial ASR systems usually have poor performance on domain-specific speech especially under low-resource settings. The author works with pre-trained DeepSpeech2 and Wav2Vec2 ac

Michelle Blom, Peter J. Stuckey, Vanessa Teague, Damjan Vukcevic

Elections where electors rank the candidates (or a subset of the candidates) in order of preference allow the collection of more information about the electors' intent. The most widely used election of this type is Instant-Runoff Voting (IRV), where candidates are eliminated one by one, until a single candidate holds the majority of the remaining ballots. Co

Behnam Ghavami, Lesley Shannon

This paper presents an overview of the integration of deep machine learning (DL) in FPGA CAD design flow, focusing on high-level and logic synthesis, placement, and routing. Our analysis identifies key research areas that require more attention in FPGA CAD design, including the development of open-source benchmarks optimized for end-to-end machine learning e

G. Ban, J. Chen, P. -J. Chiu, B. Clément

Models that postulate the existence of hidden sectors address contemporary questions, such as the source of baryogenesis and the nature of dark matter. Among the possible mixing processes, neutron-to-hidden-neutron oscillations have been repeatedly tested with ultra-cold neutron storage and passing-through-wall experiments in the range of small ($\delta m<2$

Miroslav Krstic, Luke Bhan, Yuanyuan Shi

Unlike ODEs, whose models involve system matrices and whose controllers involve vector or matrix gains, PDE models involve functions in those roles functional coefficients, dependent on the spatial variables, and gain functions dependent on space as well. The designs of gains for controllers and observers for PDEs, such as PDE backstepping, are mappings of s

P. C. Malta

A massive photon possesses a longitudinal polarization mode absent in its massless counterpart. Transverse and longitudinal modes follow different dispersion relations, the latter being much less attenuated than the former when passing through a conductor, suggesting the possibility of isolating longitudinal modes by shining intense light on a conducting wal

Taewan Kim, Purnanand Elango, Taylor P. Reynolds, Behçet Açıkmeşe

This paper presents a funnel synthesis algorithm for computing controlled invariant sets and feedback control gains around a given nominal trajectory for dynamical systems with locally Lipschitz nonlinearities and bounded disturbances. The resulting funnel synthesis problem involves a differential linear matrix inequality (DLMI) whose solution satisfies a Ly

Baptiste Goujaud, Aymeric Dieuleveut, Adrien Taylor

While many approaches were developed for obtaining worst-case complexity bounds for first-order optimization methods in the last years, there remain theoretical gaps in cases where no such bound can be found. In such cases, it is often unclear whether no such bound exists (e.g., because the algorithm might fail to systematically converge) or simply if the cu

Sylvia W Azumah, Nelly Elsayed, Zag ElSayed, Murat Ozer

Technological advancements have resulted in an exponential increase in the use of online social networks (OSNs) worldwide. While online social networks provide a great communication medium, they also increase the user's exposure to life-threatening situations such as suicide, eating disorder, cybercrime, compulsive behavior, anxiety, and depression. To tackl

Heather M. Whitney, Natalie Baughan, Kyle J. Myers, Karen Drukker

Purpose: The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify longitudinal representativeness of the demographic characteristics of the primary imaging dataset compared to the

Balázs Ádám Toldi, Imre Kocsis

Business process collaboration between independent parties can be challenging, especially if the participants do not have complete trust in each other. Tracking actions and enforcing the activity authorizations of participants via blockchain-hosted smart contracts is an emerging solution to this lack of trust, with most state-of-the-art approaches generating

Michele Girfoglio, Annalisa Quaini, Gianluigi Rozza

We introduce GEA (Geophysical and Environmental Applications), a new open-source atmosphere and ocean modeling framework within the finite volume C++ library OpenFOAM. Here, we present the development of a non-hydrostatic atmospheric model consisting of a pressure-based solver for the Euler equations written in conservative form using density, momentum, and

Chang Liu, Yu Shuai, Aishwarya Rath, Dennice F. Gayme

This work builds upon recent work exploiting the notion of structured singular values to capture nonlinear interactions in the analysis of wall-bounded shear flows. In this context, the structured uncertainty can be interpreted in terms of the flow structures most likely to be amplified (the optimal perturbations). Here we further analyze these perturbations

Abhishek Kaushik, Gareth J. F. Jones

Online Digital Assistants, such as Amazon Alexa, Google Assistant, Apple Siri are very popular and provide a range or services to their users, a key function is their ability to satisfy user information needs from the sources available to them. Users may often regard these applications as providing search services similar to Google type search engines. Howev

Gavin Stewart

We study the asymptotics for the Ablowitz-Ladik equation. By taking appropriate continuum limits, it can be shown that the behavior of the equation near degenerate frequencies is well approximated by a complex modified Korteweg-de Vries equation. Using this connection, we use the method of space-time resonances to derive a description of the modified scatter

T. Mitchell Roddenberry, Vincent P. Grande, Florian Frantzen, Michael T. Schaub

We establish a framework for signal processing on product spaces of simplicial and cellular complexes. For simplicity, we focus on the product of two complexes representing time and space, although our results generalize naturally to products of simplicial complexes of arbitrary dimension. Our framework leverages the structure of the eigenmodes of the Hodge

Chunqiu Steven Xia, Yifeng Ding, Lingming Zhang

Automated Program Repair (APR) aspires to automatically generate patches for an input buggy program. Traditional APR tools typically focus on specific bug types and fixes through the use of templates, heuristics, and formal specifications. However, these techniques are limited in terms of the bug types and patch variety they can produce. As such, researchers

Céline Degrande, Hao-Lin Li

We for the first time identify all the dimension-8 (dim-8) SMEFT operators that can have an interference with the SM with $E^4/\Lambda^4$ enhancement in the high energy limit for the processes $q\bar{q}\to WW/WZ$. Our results therefore explicitly show that the non-interference observed for the dimension-six does not extend to dimension-eight. We compute the

Kensuke Aoki

\v{C}esnavi\v{c}ius-Koshikawa constructed the A_inf-cohomology theory for semistable formal schemes over the ring of integers of C_p. We prove the p-adic Cartier isomorphism between the A_inf-cohomology and de Rham-Witt complexes for semistable formal schemes, extending the result of Bhatt-Morrow-Scholze in the smooth case.

Saidakhmat N. Lakaev, Alexander K. Motovilov, Saidakbar Kh. Abdukhakimov

We study the Schroedinger operators H_{\lambda\mu}(K), with K \in T_2 the fixed quasi-momentum of the particles pair, associated with a system of two identical fermions on the two-dimensional lattice Z_2 with first and second nearest-neighboring-site interactions of magnitudes \lambda \in R and \mu \in R, respectively. We establish a partition of the (\lambd

Ambroise Baril, Antoine Castillon, Nacim Oijid

We investigate the parameterized complexity of several problems formalizing cluster identification in graphs. In other words we ask whether a graph contains a large enough and sufficiently connected subgraph. We study here three relaxations of CLIQUE: $s$-CLUB and $s$-CLIQUE, in which the relaxation is focused on the distances in respectively the cluster and

Anahita Banaei, Shadrokh Samavi, Ebrahim Nasr Esfahani

Microarray technology is a new and powerful tool for the concurrent monitoring of a large number of gene expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression scheme

Hitesh Kumar, Bojan Mohar, Shivaramakrishna Pragada, Hanmeng Zhan

This paper investigates the asymptotic nature of graph spectra when some edges of a graph are subdivided sufficiently many times. In the special case where all edges of a graph are subdivided, we find the exact limits of the $k$-th largest and $k$-th smallest eigenvalues for any fixed $k$. It is expected that after subdivision, most eigenvalues of the new gr

Ryan D Schumm, Paul C Bressloff

Diffusion in heterogeneous media partitioned by semi-permeable interfaces has a wide range of applications in the physical and life sciences, including gas permeation in soils, diffusion magnetic resonance imaging (dMRI), drug delivery, thermal conduction in composite media, synaptic receptor trafficking, and intercellular gap junctions. At the single partic

William H. Press

Given two time series, A and B, sampled asynchronously at different times {t_A_i} and {t_B_j}, termed "ticks", how can one best estimate the correlation coefficient \rho between changes in A and B? We derive a natural, minimum-variance estimator that does not use any interpolation or binning, then derive from it a fast (linear time) estimator that is demonst

Louiza Fouli, Jonathan Montaño, Claudia Polini, Bernd Ulrich

The core of an ideal is defined as the intersection of all of its reductions. In this paper we provide an explicit description for the core of a monomial ideal $I$ satisfying certain residual conditions, showing that ${\rm core}(I)$ coincides with the largest monomial ideal contained in a general reduction of $I$. We prove that the class of lex-segment ideal

Christophe Charlier, Jonatan Lenells

We analyze the Boussinesq equation on the line with Schwartz initial data belonging to the physically relevant class of global solutions. In a recent paper, we determined ten main asymptotic sectors describing the large $(x,t)$-behavior of the solution, and for each of these sectors we provided the leading order asymptotics in the case when no solitons are p

Paul C Bressloff

In this paper we develop an encounter-based model of reaction-subdiffusion in a domain $\Omega$ with a partially absorbing interior trap $\calU\subset \Omega$. We assume that the particle can freely enter and exit $\calU$, but is only absorbed within $\calU$. We take the probability of absorption to depend on the amount of time a particle spends within the t

Paul C Bressloff

In this paper, we develop an encounter-based model of partial surface adsorption for fractional diffusion in a bounded domain. We take the probability of adsorption to depend on the amount of particle-surface contact time, as specified by a Brownian functional known as the boundary local time $\ell(t)$. If the rate of adsorption is state dependent, then the

Shi Chen, Qi Zhao

Humans have the innate capability to answer diverse questions, which is rooted in the natural ability to correlate different concepts based on their semantic relationships and decompose difficult problems into sub-tasks. On the contrary, existing visual reasoning methods assume training samples that capture every possible object and reasoning problem, and re

Bilal Hungund, Shilpa Rastogi

The money market and the capital market of the Indian financial markets have a symbiotic relationship in the development of the Indian economy. The nature and the characteristics of the markets differ to a large extent as the money market ensures liquidity in the system through the monetary policy by the regulators; capital markets propel and act as the engi

Thomas Settlemyre, Hua Zheng, Aldo Bonasera

Electron-positron pairs can be produced via the Schwinger mechanism in the presence of strong electric fields. In particular, the fields involved in $\alpha$ decay and nuclear fission are strong enough to produce them. The energy of the $e^+e^-$ pair is related to the relative distance and velocity of the daughter nuclei. Thus, the energy distribution of the

Catherine Searle

This article surveys results for Riemannian manifolds of positive and non-negative sectional curvature with symmetries.

M. L. Pumo, S. P. Cosentino, A. Pastorello, S. Benetti

With the aim of improving our knowledge about their nature, we conduct a comparative study on a sample of long-rising Type II supernovae (SNe) resembling SN 1987A. To do so, we deduce various scaling relations from different analytic models of H-rich SNe, discussing their robustness and feasibility. Then we use the best relations in terms of accuracy to infe

Setareh Medghalchi, Muhammad Zubair, Ehsan Karimi, Stefanie Sandlöbes-Haut

We study a cast Mg-4.65Al-2.82Ca alloy with a microstructure containing $\alpha$-Mg matrix reinforced with a C36 Laves phase skeleton. Such ternary alloys are targeted for elevated temperature applications in automotive engines since they possess excellent creep properties. However, in application, the alloy may be subjected to a wide range of strain rates a

Kacy Adams, Fernando Spadea, Conor Flynn, Oshani Seneviratne

In the present academic landscape, the process of collecting data is slow, and the lax infrastructures for data collaborations lead to significant delays in coming up with and disseminating conclusive findings. Therefore, there is an increasing need for a secure, scalable, and trustworthy data-sharing ecosystem that promotes and rewards collaborative data-sh

Renze Lou, Kai Zhang, Wenpeng Yin

Task semantics can be expressed by a set of input-output examples or a piece of textual instruction. Conventional machine learning approaches for natural language processing (NLP) mainly rely on the availability of large-scale sets of task-specific examples. Two issues arise: first, collecting task-specific labeled examples does not apply to scenarios where

Bao-An Li, Wen-Jie Xie

Within a Bayesian statistical framework using a Gaussian Process emulator for an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions at intermediate energies, we infer from the HADES proton flow data the posterior probability distribution functions of in-medium baryon-baryon scattering cross section modificat

David A. Clunie, Adam Flanders, Adam Taylor, Brad Erickson

This report addresses the technical aspects of de-identification of medical images of human subjects and biospecimens, such that re-identification risk of ethical, moral, and legal concern is sufficiently reduced to allow unrestricted public sharing for any purpose, regardless of the jurisdiction of the source and distribution sites. All medical images, rega

Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob R. Gardner

Understanding the gradient variance of black-box variational inference (BBVI) is a crucial step for establishing its convergence and developing algorithmic improvements. However, existing studies have yet to show that the gradient variance of BBVI satisfies the conditions used to study the convergence of stochastic gradient descent (SGD), the workhorse of BB

Waqas Manzoor, Samir Rawashdeh, Alireza Mohammadi

Koopman operator theory has proven to be a promising approach to nonlinear system identification and global linearization. For nearly a century, there had been no efficient means of calculating the Koopman operator for applied engineering purposes. The introduction of a recent computationally efficient method in the context of fluid dynamics, which is based

Nicolas Ginoux, Georges Habib

In this paper, we prove new rigidity results related to some generalised Ricci-Hessian equation on Riemannian manifolds.

Konstantia Nathanael, Sibo Cheng, Nina M. Kovalchuk, Rossella Arcucci

The properties of silver nanoparticles (AgNPs) are affected by various parameters, making optimisation of their synthesis a laborious task. This optimisation is facilitated in this work by concurrent use of a T-junction microfluidic system and machine learning approach. The AgNPs are synthesized by reducing silver nitrate with tannic acid in the presence of

Serguei N. Burmistrov

Spin waves that can propagate in normal and superconducting metals are investigated. Unlike normal metals, the velocity of spin waves becomes temperature-dependent in a superconductor. The low frequency spin waves survive within the narrow region below the superconducting transition temperature. At low temperatures the high frequency waves alone can propagat

Guodong Li, Ningning Wang, Sihuang Hu, Min Ye

The sub-packetization $\ell$ and the field size $q$ are of paramount importance in the MSR array code constructions. For optimal-access MSR codes, Balaji et al. proved that $\ell\geq s^{\left\lceil n/s \right\rceil}$, where $s = d-k+1$. Rawat et al. showed that this lower bound is attainable for all admissible values of $d$ when the field size is exponential

Nikos Papanikolaou, Renaud Lambiotte, Giacomo Vaccario

The adaptive voter model allows for studying the interplay between homophily, the tendency of like-minded individuals to attract each other, and social influence, the tendency for connected individuals to influence each other. However, it relies on graphs, and thus, it only considers pairwise interactions. We develop a minimal extension of the adaptive voter

Wonse Jo, Ruiqi Wang, Baijian Yang, Dan Foti

The interaction and collaboration between humans and multiple robots represent a novel field of research known as human multi-robot systems. Adequately designed systems within this field allow teams composed of both humans and robots to work together effectively on tasks such as monitoring, exploration, and search and rescue operations. This paper presents a

Vithursan Thangarasa, Abhay Gupta, William Marshall, Tianda Li

The pre-training and fine-tuning paradigm has contributed to a number of breakthroughs in Natural Language Processing (NLP). Instead of directly training on a downstream task, language models are first pre-trained on large datasets with cross-domain knowledge (e.g., Pile, MassiveText, etc.) and then fine-tuned on task-specific data (e.g., natural language ge

Daoji Huang, Jessica Striker

We characterize totally symmetric self-complementary plane partitions (TSSCPP) as bounded compatible sequences satisfying a Yamanouchi-like condition. As such, they are in bijection with certain pipe dreams. Using this characterization and the recent bijection of [Gao-Huang] between reduced pipe dreams and reduced bumpless pipe dreams, we give a bijection be

Shekoufeh Kolahdouz-Rahimi, Kevin Lano, Chenghua Lin

Improvement of software development methodologies attracts developers to automatic Requirement Formalisation (RF) in the Requirement Engineering (RE) field. The potential advantages by applying Natural Language Processing (NLP) and Machine Learning (ML) in reducing the ambiguity and incompleteness of requirement written in natural languages is reported in di

Sibo Cheng, Cesar Quilodran-Casas, Said Ouala, Alban Farchi

Data Assimilation (DA) and Uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical applications span from computational fluid dynamics (CFD) to geoscience and climate systems. Recently, much effort has been given in combining DA, UQ and machine learning (ML) techn

Manuel Malaver, Rajan Iyer

Taking local anisotropy into consideration, in this paper, some new analytical models of relativistic anisotropic charged quark stars in linear and quadratic regime have been developed. The Einstein-Maxwell field equations have been solved with a particular form of metric potential and electric field intensity. The plots generated show that physical variable

Daniel N. Blaschke, Khanh Dang, Saryu Fensin, Darby J. Luscher

We discuss the theoretical solution to the differential equations governing accelerating edge dislocations in anisotropic crystals. This is an important prerequisite to understanding high speed dislocation motion, including an open question about the existence of transonic dislocation speeds, and subsequently high rate plastic deformation in metals and other

Anjana A Mahesh, Charul Rajput, Bobbadi Rupa, B. Sundar Rajan

Ong and Ho developed optimal linear index codes for single uniprior index coding problems (ICPs) by finding a spanning tree for each of the strongly connected components of the corresponding information-flow graphs, following which Thomas et al. considered the same class of ICPs over Rayleigh fading channel. They developed the min-max probability of error cr

Yifan Hu

Current portable memory device relies heavily on flash memory technology for its implementation. New generation of non-volatile memory is likely to replace floating gates, charge-trapping memory currently still suffering from inadequate retention performance and slow programming speeds as well as small memory window. In contrast, the use of HfO$_2$/Al$_2$O$_

Carolina Benedetti, Kolja Knauer, Jerónimo Valencia-Porras

We characterize matroids whose polytopes are order polytopes as a special class of lattice path matroids, called snakes. This shows that snakes are exactly the objects lying in the intersection of the Neggers-Stanley conjecture and a conjecture of de Loera, Haws, and Köppe. We then characterize Gorenstein lattice path matroid polytopes, yielding a new class

Haozhi Cao, Yuecong Xu, Jianfei Yang, Pengyu Yin

Continual Test-Time Adaptation (CTTA) generalizes conventional Test-Time Adaptation (TTA) by assuming that the target domain is dynamic over time rather than stationary. In this paper, we explore Multi-Modal Continual Test-Time Adaptation (MM-CTTA) as a new extension of CTTA for 3D semantic segmentation. The key to MM-CTTA is to adaptively attend to the reli

Uzi Pereg, Christian Deppe, Holger Boche

Communication over a classical multiple-access channel (MAC) with entanglement resources is considered, whereby two transmitters share entanglement resources a priori before communication begins. Leditzky et al. (2020) presented an example of a classical MAC, defined in terms of a pseudo telepathy game, such that the sum rate with entangled transmitters is s

Vijaya Raghavan T. Ramkumar, Elahe Arani, Bahram Zonooz

Deep neural networks (DNNs) are often trained on the premise that the complete training data set is provided ahead of time. However, in real-world scenarios, data often arrive in chunks over time. This leads to important considerations about the optimal strategy for training DNNs, such as whether to fine-tune them with each chunk of incoming data (warm-start

Mark Abdelshiheed, John Wesley Hostetter, Xi Yang, Tiffany Barnes

Metacognitive skills have been commonly associated with preparation for future learning in deductive domains. Many researchers have regarded strategy- and time-awareness as two metacognitive skills that address how and when to use a problem-solving strategy, respectively. It was shown that students who are both strategy-and time-aware (StrTime) outperformed

Khaled Alshehri, Anas M. Salhab, Ali Arshad Nasir

In this paper, we study the performance of multiple reconfigurable intelligent surfaces (RISs)-aided unmanned aerial vehicle (UAV) communication networks over Nakagami-$m$ fading channels. For that purpose, we used accurate closed-form approximations for the channel distributions to derive closed-form approximations for the outage probability (OP), average s

Steven Holte, Gopalan Nadathur

The ability to compose code in a modular fashion is important to the construction of large programs. In the logic programming setting, it is desirable that such capabilities be realized through logic-based devices. We describe an approach for doing this here. In our scheme a module corresponds to a block of code whose external view is mediated by a signature

Xiyu Wang, Yuecong Xu, Jianfei Yang, Bihan Wen

Continuous Video Domain Adaptation (CVDA) is a scenario where a source model is required to adapt to a series of individually available changing target domains continuously without source data or target supervision. It has wide applications, such as robotic vision and autonomous driving. The main underlying challenge of CVDA is to learn helpful information o

Yuecong Xu, Jianfei Yang, Yunjiao Zhou, Zhenghua Chen

For video models to be transferred and applied seamlessly across video tasks in varied environments, Video Unsupervised Domain Adaptation (VUDA) has been introduced to improve the robustness and transferability of video models. However, current VUDA methods rely on a vast amount of high-quality unlabeled target data, which may not be available in real-world

Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina, Tiffany Barnes

Deductive domains are typical of many cognitive skills in that no single problem-solving strategy is always optimal for solving all problems. It was shown that students who know how and when to use each strategy (StrTime) outperformed those who know neither and stick to the default strategy (Default). In this work, students were trained on a logic tutor that

Yuji Matsumoto, Sota Arakawa

Shock wave heating is a leading candidate for the mechanisms of chondrule formation. This mechanism forms chondrules when the shock velocity is in a certain range. If the shock velocity is lower than this range, dust particles smaller than chondrule precursors melt, while chondrule precursors do not. We focus on the low-velocity shock waves as the igneous ri

Fan Lu, Kai Zhu, Wei Zhai, Kecheng Zheng

Semantically coherent out-of-distribution (SCOOD) detection aims to discern outliers from the intended data distribution with access to unlabeled extra set. The coexistence of in-distribution and out-of-distribution samples will exacerbate the model overfitting when no distinction is made. To address this problem, we propose a novel uncertainty-aware optimal

Xingtao Jia, Hui-Min Tang, Shi-Zhuo Wan

Antiferromagnetic (AF) spintronics is merit on ultra-high operator speed and stability in the presence of magnetic field. To fully use the merit, the device should be pure rather than hybrid with ferromagnet or ferrimagnet. For the magnetism in the antiferromagnet is canceled by that of different sublattices, breaking the symmetry in the material can revive

Mark Abdelshiheed, Mehak Maniktala, Song Ju, Ayush Jain

Based on strategy-awareness (knowing which problem-solving strategy to use) and time-awareness (knowing when to use it), students are categorized into Rote (neither type of awareness), Dabbler (strategy-aware only) or Selective (both types of awareness). It was shown that Selective is often significantly more prepared for future learning than Rote and Dabble

Richard Cushman

Our goal is to find a representative of each orbit of the coadjoint action of the generalized Galile group on the dual of its Lie algebra. Our line of argument follows that of Cushman and van der Kallen, but differs in the details.

Prateek Verma, Chris Chafe

We propose a learnable content adaptive front end for audio signal processing. Before the modern advent of deep learning, we used fixed representation non-learnable front-ends like spectrogram or mel-spectrogram with/without neural architectures. With convolutional architectures supporting various applications such as ASR and acoustic scene understanding, a

Xiyuxing Zhang, Yuntao Wang, Jingru Zhang, Yaqing Yang

Cough monitoring can enable new individual pulmonary health applications. Subject cough event detection is the foundation for continuous cough monitoring. Recently, the rapid growth in smart hearables has opened new opportunities for such needs. This paper proposes EarCough, which enables continuous subject cough event detection on edge computing hearables b

Youshan Zhang

In this paper, we present a small cow stall number dataset named CowStallNumbers, which is extracted from cow teat videos with the goal of advancing cow stall number detection. This dataset contains 1042 training images and 261 test images with the stall number ranging from 0 to 60. In addition, we fine-tuned a ResNet34 model and augmented the dataset with t

Jiexin Ding, Bowen Zhao, Yuqi Huang, Yuntao Wang

Automatic unknown word detection techniques can enable new applications for assisting English as a Second Language (ESL) learners, thus improving their reading experiences. However, most modern unknown word detection methods require dedicated eye-tracking devices with high precision that are not easily accessible to end-users. In this work, we propose GazeRe

Lorenzo Galati Giordano, Giovanni Geraci, Marc Carrascosa, Boris Bellalta

What will Wi-Fi 8 be? Driven by the strict requirements of emerging applications, next-generation Wi-Fi is set to prioritize Ultra High Reliability (UHR) above all. In this paper, we explore the journey towards IEEE 802.11bn UHR, the amendment that will form the basis of Wi-Fi 8. We first present new use cases calling for further Wi-Fi evolution and associat

Zisu Li, Cheng Liang, Yuntao Wang, Yue Qin

Gestures performed accompanying the voice are essential for voice interaction to convey complementary semantics for interaction purposes such as wake-up state and input modality. In this paper, we investigated voice-accompanying hand-to-face (VAHF) gestures for voice interaction. We targeted hand-to-face gestures because such gestures relate closely to speec

Sacha Ichbiah, Anshuman Sinha, Fabrice Delbary, Hervé Turlier

Traditional methods for biological shape inference, such as deep learning (DL) and active contour models, face important limitations in 3D. DL approaches require large annotated datasets, which are often impractical to obtain, while active contour methods depend on carefully tuned heuristics for intensity attraction and shape regularization. We introduce del

Yaohou Fan, Chetan Arora, Christoph Treude

Stop words, which are considered non-predictive, are often eliminated in natural language processing tasks. However, the definition of uninformative vocabulary is vague, so most algorithms use general knowledge-based stop lists to remove stop words. There is an ongoing debate among academics about the usefulness of stop word elimination, especially in domain

Pingyu Wu, Wei Zhai, Yang Cao, Jiebo Luo

Weakly supervised object localization (WSOL) is a challenging task aiming to localize objects with only image-level supervision. Recent works apply visual transformer to WSOL and achieve significant success by exploiting the long-range feature dependency in self-attention mechanism. However, existing transformer-based methods synthesize the classification fe

Yuhang Yang, Wei Zhai, Hongchen Luo, Yang Cao

Grounding 3D object affordance seeks to locate objects' ''action possibilities'' regions in the 3D space, which serves as a link between perception and operation for embodied agents. Existing studies primarily focus on connecting visual affordances with geometry structures, e.g. relying on annotations to declare interactive regions of interest on the object

Abdallah Zaid Alkilani, Tolga Çukur, Emine Ulku Saritas

Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield a corrected image. Unsupervised learning in these unwarping-based methods is commonly attained via a similarity constraint between the unwarped images in reversed-PE directions, n