March 2023 arXiv papers — page 109

Yiyi Zhu

Let $V$ be a vertex operator algebra, $T\in \mathbb{N}$ and $(M^k, Y_{M^k})$ for $k=1, 2, 3$ be a $g_k$-twisted module, where $g_k$ are commuting automorphisms of $V$ such that $g_k^T=1$ for $k=1, 2, 3$ and $g_3=g_1g_2$. Suppose $I(\cdot, z)$ is an intertwining operator of type $({array}{c} M^{3} M^{1} M^{2} {array}) $. We construct an $A_{g_1g_2}(V)$-$A_{g_

Rakib Hassan Pran

Recently, the Integrated Air Defense System (IADS) has become vital for the defense system as the military defense system is vital for national security. Placing Integrated Air Defense System batteries among locations to protect locations assets is a crucial problem because optimal solutions are needed for interceptor missiles to intercept attacker missiles

Xiang 'Anthony' Chen

To measure how HCI papers are cited across disciplinary boundaries, we collected a citation dataset of CHI, UIST, and CSCW papers published between 2010 and 2020. Our analysis indicates that HCI papers have been more and more likely to be cited by HCI papers rather than by non-HCI papers.

N Shashaank, Berker Banar, Mohammad Rasool Izadi, Jeremy Kemmerer

Modern noise-cancelling headphones have significantly improved users' auditory experiences by removing unwanted background noise, but they can also block out sounds that matter to users. Machine learning (ML) models for sound event detection (SED) and speaker identification (SID) can enable headphones to selectively pass through important sounds; however, im

Chenzhong Yin, Mihai Udrescu, Gaurav Gupta, Mingxi Cheng

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. Current COPD diagnosis (i.e., spirometry) could be unreliable because the test depends on an adequate effort from the tester and testee. Moreover, the early diagnosis of COPD is challenging. We address COPD detection by constructing two novel physiological signals d

Robert L. Bassett, Micah Y. Oh

We consider the problem of estimating a signal subspace in the presence of interference that contaminates some proportion of the received observations. Our emphasis is on detecting the contaminated observations so that the signal subspace can be estimated with the contaminated observations discarded. To this end, we employ a signal model which explicitly inc

Saumil Shivdikar, Jagannath Nirmal

With the impact of real-time processing being realized in the recent past, the need for efficient implementations of reinforcement learning algorithms has been on the rise. Albeit the numerous advantages of Bellman equations utilized in RL algorithms, they are not without the large search space of design parameters. This research aims to shed light on the de

Alexandru Hening, Nguyen Trong Hieu, Dang Hai Nguyen, Nhu Ngoc Nguyen

We analyze plankton-nutrient food chain models composed of phytoplankton, herbivorous zooplankton and a limiting nutrient. These models have played a key role in understanding the dynamics of plankton in the oceanic layer. Given the strong environmental and seasonal fluctuations that are present in the oceanic layer, we propose a stochastic model for which w

Subhashini Venugopalan, Jimmy Tobin, Samuel J. Yang, Katie Seaver

We developed dysarthric speech intelligibility classifiers on 551,176 disordered speech samples contributed by a diverse set of 468 speakers, with a range of self-reported speaking disorders and rated for their overall intelligibility on a five-point scale. We trained three models following different deep learning approaches and evaluated them on ~94K uttera

Muslum Emir Avci, Sule Ozev

Due to the need for higher reliability and performance from RF circuits, multi-port reflectometers are increasingly used as low-overhead impedance monitors. In this work, using periodic structures as multi-ports is proposed. Periodic structures impose a new constraint on the multi-port theory and simplify it significantly. This simplification leads to closed

Yaoju Tarn, Mekhola Sinha, Christopher Pasco, Darrell G. Schlom

Plasma discharge lamps are widely utilized in the practice of angle-resolved photoemission spectroscopy (ARPES) experiments as narrow-linewidth ultraviolet photon sources. However, many emission lines such as Ar-I, Ne-I, and Ne-II have closely spaced doublet emission lines, which result in superimposed replica on the measured ARPES spectra. Here, we present

Mst Shapna Akter, Hossain Shahriar

A dataset, collected under an industrial setting, often contains a significant portion of noises. In many cases, using trivial filters is not enough to retrieve useful information i.e., accurate value without the noise. One such data is time-series sensor readings collected from moving vehicles containing fuel information. Due to the noisy dynamics and mobil

David Gray Widder, Richmond Wong

After children were pictured sewing its running shoes in the early 1990s, Nike at first disavowed the "working conditions in its suppliers' factories", before public pressure led them to take responsibility for ethics in their upstream supply chain. In 2023, OpenAI responded to criticism that Kenyan workers were paid less than $2 per hour to filter traumatic

Paolo Cascini, Calum Spicer

We show that termination of flips for $\mathbb Q$-factorial klt pairs in dimension $r$ implies existence of minimal models for algebraically integrable foliations of rank $r$ with log canonical singularities over a $\mathbb Q$-factorial klt projective variety.

Zhenmei Shi, Yifei Ming, Ying Fan, Frederic Sala

The ability to generalize to unseen domains is crucial for machine learning systems deployed in the real world, especially when we only have data from limited training domains. In this paper, we propose a simple and effective regularization method based on the nuclear norm of the learned features for domain generalization. Intuitively, the proposed regulariz

Alois Schiessl

The Basel problem consists in finding the sum of the reciprocals of the squares of the positive integers. It was finally solved in 1735 by Leonhard Euler. In this paper, we propose a simple proof based on the Weierstrass Sine product formula and L'H\^opital's rule.

Mst Shapna Akter, Hossain Shahriar, Zakirul Alam Bhuiya

One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. These flaws are highly likely ex-ploited and lead to system compromise, data leakage, or denial of ser-vice. C and C++ open source code are now available in order to create a large-scale, classical machine-learning and quantum

Manuel Parra-Royón, Jesús Sánchez-Castañeda, Julián Garrido, Susana Sánchez-Expósito

The Square Kilometre Array (SKA) infrastructure will consist of two radio telescopes that will be the most sensitive telescopes on Earth. The SKA community will have to process and manage near exascale data, which will be a technical challenge for the coming years. In this respect, the SKA Global Network of Regional Centres plays a key role in data distribut

Pubudu Wijesooriya, Sheikh Muhammad Farjad, Nikolaos Stergiou, Spyridon Mastorakis

Augmented Reality (AR) based on Head-Mounted Displays (HMDs) has gained significant traction over the recent years. Nevertheless, it remains unclear what AR HMD-based applications have been developed over the years and what their system performance is when they are run on HMDs. In this paper, we aim to shed light into this direction. Our study focuses on the

Chenguang Huang, Oier Mees, Andy Zeng, Wolfram Burgard

While interacting in the world is a multi-sensory experience, many robots continue to predominantly rely on visual perception to map and navigate in their environments. In this work, we propose Audio-Visual-Language Maps (AVLMaps), a unified 3D spatial map representation for storing cross-modal information from audio, visual, and language cues. AVLMaps integ

Sébastien Descotes-Genon, Darius A. Faroughy, Ioannis Plakias, Olcyr Sumensari

In this letter, we use LHC data from the Drell-Yan processes $pp\to\ell_i\ell_j$ (with $i\neq j$) to derive model-independent upper limits on lepton-flavor-violating meson decays. Our analysis is based on an Effective Field Theory (EFT) approach and it does not require a specific assumption regarding the basis of effective operators. We find that current LHC

Mst Shapna Akter, Hossain Shahriar, Sweta Sneha, Alfredo Cuzzocrea

Skin cancer detection is challenging since different types of skin lesions share high similarities. This paper proposes a computer-based deep learning approach that will accurately identify different kinds of skin lesions. Deep learning approaches can detect skin cancer very accurately since the models learn each pixel of an image. Sometimes humans can get c

Theodoros Galanos, Antonios Liapis, Georgios N. Yannakakis

Architectural design is a highly complex practice that involves a wide diversity of disciplines, technologies, proprietary design software, expertise, and an almost infinite number of constraints, across a vast array of design tasks. Enabling intuitive, accessible, and scalable design processes is an important step towards performance-driven and sustainable

Marcelo L. Pereira Junior, José. M. De Sousa, Wjefferson H. S. Brandão, Douglas. S. Galvão

Me-graphene (MeG) is a novel two-dimensional (2D) carbon allotrope. Due to its attractive electronic and structural properties, it is important to study the mechanical behavior of MeG in its monolayer and nanotube topologies. In this work, we conducted fully atomistic reactive molecular dynamics simulations using the Tersoff force field to investigate their

Hanxue Gu, Hongyu He, Roy Colglazier, Jordan Axelrod

Three-dimensional segmentation in magnetic resonance images (MRI), which reflects the true shape of the objects, is challenging since high-resolution isotropic MRIs are rare and typical MRIs are anisotropic, with the out-of-plane dimension having a much lower resolution. A potential remedy to this issue lies in the fact that often multiple sequences are acqu

Payam Parvizi, Runnan Zou, Colin Bellinger, Ross Cheriton

Optical satellite-to-ground communication (OSGC) has the potential to improve access to fast and affordable Internet in remote regions. Atmospheric turbulence, however, distorts the optical beam, eroding the data rate potential when coupling into single-mode fibers. Traditional adaptive optics (AO) systems use a wavefront sensor to improve fiber coupling. Th

Michael Hott

Common proofs of the Gagliardo-Nirenberg-Sobolev (GNS) do not provide explicit bounds on the involved constants, unless a sharp constant is being determined. GNS inequalities naturally occur in error estimates for numerical approximations. In particular, bounds on GNS constants allow us to provide explicit a priori estimates. We provide an algorithm that det

Kislaya Prasad

This paper introduces a space of variable lotteries and proves a constructive version of the expected utility theorem. The word ``constructive'' is used here in two senses. First, as in constructive mathematics, the logic underlying proofs is intuitionistic. In a second sense of the word, ``constructive'' is taken to mean ``built up from smaller components.'

Mst Shapna Akter, Hossain Shahriar, Alfredo Cuzzocrea, Nova Ahmed

A handwritten word recognition system comes with issues such as lack of large and diverse datasets. It is necessary to resolve such issues since millions of official documents can be digitized by training deep learning models using a large and diverse dataset. Due to the lack of data availability, the trained model does not give the expected result. Thus, it

Yoshinobu Fudamoto, Akio K. Inoue, Dan Coe, Brian Welch

We present results of [CII]$\,158\,\rm{\mu m}$ emission line observations, and report the spectroscopic redshift confirmation of a strongly lensed ($\mu\sim20$) star-forming galaxy, MACS0308-zD1 at $z=6.2078\pm0.0002$. The [CII] emission line is detected with a signal-to-noise ratio $>6$ within the rest-frame UV bright clump of the lensed galaxy (zD1.1) and

Julian B. Carlin, Andrew Melatos, Michael S. Wheatland

Solar flares result from the sudden release of energy deposited by sub-photospheric motions into the magnetic field of the corona. The deposited energy accumulates secularly between events. One may interpret the observed event statistics as resulting from a state-dependent Poisson process, in which the instantaneous flare rate is a function of the stress in

Masoome Haghani, Behrouz Mohammadkari, Rima Fayaz

This paper evaluates the energy performance of a new daylighting system, patented by the author, in a regular closed office space. The advantage of this new system as opposed to conventional venetian blinds is its rotating capability, which improves the energy efficiency of the space. Computer simulation method has been conducted to examine the performance o

Hannah Kirkland, Sanjeev J. Koppal

Privacy-preserving vision must overcome the dual challenge of utility and privacy. Too much anonymity renders the images useless, but too little privacy does not protect sensitive data. We propose a novel design for privacy preservation, where the imagery is stored in quantum states. In the future, this will be enabled by quantum imaging cameras, and, curren

Soroush Sadeghnejad, Farshad Khadivar, Mojtaba Esfandiari, Golchehr Amirkhani

In this paper, a modified robust model predictive control scheme is proposed for linear parametric variable (LPV) and hybrid systems based on a quasi-min-max algorithm. Using a new cost function resulted in reduced unwanted disturbances during switching. In addition, the effects of uncertainties are reduced in the prediction dynamics, and robust stability of

Hoang M. Ngo, My T. Thai, Tamer Kahveci

Target Identification by Enzymes (TIE) problem aims to identify the set of enzymes in a given metabolic network, such that their inhibition eliminates a given set of target compounds associated with a disease while incurring minimum damage to the rest of the compounds. This is an NP-complete problem, and thus optimal solutions using classical computers fail

Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White

The ability to learn continually is essential in a complex and changing world. In this paper, we characterize the behavior of canonical value-based deep reinforcement learning (RL) approaches under varying degrees of non-stationarity. In particular, we demonstrate that deep RL agents lose their ability to learn good policies when they cycle through a sequenc

Ulrich Schwickerath, Andrii Verbytskyi

We present a revived version of CERNLIB, the basis for software ecosystems of most of the pre-LHC HEP experiments. The efforts to consolidate CERNLIB are part of the activities of the Data Preservation for High Energy Physics collaboration to preserve data and software of the past HEP experiments. The presented version is based on CERNLIB version 2006 with n

T. M. Aliev, S. Bilmis, M. Savci

In this study, we analyzed the weak decays induced by $J^P = \frac{1}{2}^{+} \to \frac{3}{2}^{-} $ transitions within the light-cone sum rules. Specifically, semileptonic decays of the bottom baryons into the P-wave baryons $\Lambda_b \to \Lambda_c(2625) \ell \nu_l$ and $\Xi_b \to \Xi_c(2815) \ell \nu_l$ as well as nonleptonic $\Lambda_b \to \Lambda_c(2625)

A. Tehranchi, S. Zhang, A. Zendegani, C. Scheu

Thermodynamic bulk phase diagrams have become the roadmap used by researchers to identify alloy compositions and process conditions that result in novel materials with tailored microstructures. Recent experimental studies show that changes in the alloy composition can drive not only transitions in the bulk phases present in a material, but also in the concen

Rafid Mahbub, Swagat S. Mishra

We investigate the possibility of oscillon formation during the preheating phase of asymmetric inflationary potentials. We analytically establish the existence of oscillon-like solutions for the Klein-Gordon equation for a polynomial potential of the form $V(\phi)=\frac{1}{2}\phi^2+A\phi^3+B\phi^4$ using the small amplitude analysis, which naturally arises a

Hassan Gharoun, Fereshteh Momenifar, Fang Chen, Amir H. Gandomi

Despite its astounding success in learning deeper multi-dimensional data, the performance of deep learning declines on new unseen tasks mainly due to its focus on same-distribution prediction. Moreover, deep learning is notorious for poor generalization from few samples. Meta-learning is a promising approach that addresses these issues by adapting to new tas

Bo Huang, Ke Wang, Josep Miquel Girart, Wenyu Jiao

In order to study the initial conditions of massive star formation, we have previously built a sample of 463 high-mass starless clumps (HMSCs) across the inner Galactic plane covered by multiple continuum surveys. Here, we use $^{13}$ CO(2-1) line data from the SEDIGISM survey, which covers 78$^{\circ}$ in longitude ($-60^{\circ}<l<18^{\circ}$, $\vert b\vert

Jeffrey Barrett, Isaac Goldbring

Using the tools of nonstandard analysis, we develop and present an alternative formulation of Bohmian mechanics. This approach allows one to describe a broader assortment of physical systems than the standard formulation of the theory. It also allows one to make predictions in more situations. We motivate the nonstandard formulation with a Bohmian example sy

Azer Akhmedov, James Thorne

We construct examples of non-bi-orderable one-relator groups without generalized torsion. This answers a question asked in [2].

Shan Tang, Shanjun Mao, Yangyang Chen, Falong Tan

Many diseases are considered to be closely related to the changes in the gut microbial community, including colorectal cancer (CRC), which is one of the most common cancers in the world. The diagnostic classification and etiological analysis of CRC are two critical issues worthy of attention. Many methods adopt gut microbiota to solve it, but few of them sim

J. Brock, S. Covrig Dusa, J. Dunne, C. Keith

A high-power liquid hydrogen target was built for the Jefferson Lab Qweak experiment, which measured the tiny parity-violating asymmetry in $\vec{e}$p scattering at an incident energy of 1.16 GeV, and a Q$^2 = 0.025$ GeV$^{2}$. To achieve the luminosity of $1.7 \times 10^{39}$ cm$^{-2}$ s$^{-1}$, a 34.5 cm-long target was used with a beam current of 180 $\mu

Keita Nishii, Deborah A. Levin

Gridded ion thrusters are tested in ground vacuum chambers to verify their performance when deployed in space. However, the presence of high background pressure and conductive walls in the chamber leads to facility effects that increase uncertainty in the performance of the thruster in space. To address this issue, this study utilizes a fully kinetic simulat

Jamie M. Karthein

Fluctuations provide a powerful tool for elucidating the nature of strongly-interacting matter in the QCD phase diagram. In heavy-ion-collision systems, the net-particle number fluctuations are captured at the moment of chemical freeze-out. Studies of the chemical freeze-out via susceptibilities from lattice QCD and the Hadron Resonance Gas model contribute

David Miyamoto

A singular foliation is a partition of a manifold into leaves of perhaps varying dimension. Stefan and Sussmann carried out fundamental work on singular foliations in the 1970s. We survey their contributions, show how diffeological objects and ideas arise naturally in this setting, and highlight some consequences within diffeology. We then introduce a defini

Moisés Bravo-Gaete, Luis Guajardo, Fabiano F. Santos

The well known shear viscosity to entropy density ratio ($\eta /s$) cannot be computed when the black hole space-time has zero thermodynamic entropy. This is the case, for example, when General Relativity in four dimensions is complemented with Critical Gravity, or in particular scenarios within the Four-dimensional-scalar-Gauss-Bonnet theories. Recently, it

Yuri Nesterenko

The following hypothesis was put forward by Goreinov, Tyrtyshnikov and Zamarashkin in \cite{GTZ1997}. For arbitrary real $n \times k$ matrix with orthonormal columns a sufficiently "good" $k \times k$ submatrix exists. "Good" in the sense of having a bounded spectral norm of its inverse. The hypothesis says that for arbitrary $k = 1, \ldots, n-1$ the upper b

Alex Gurevich

Performance of superconducting resonators, particularly cavities for particle accelerators and micro cavities and thin film resonators for quantum computations and photon detectors has been improved substantially by recent materials treatments and technological advances. As a result, the niobium cavities have reached the quality factors $Q\sim 10^{11}$ at 1-

Jessica P. Kunke, Ian Laga, Xiaoyue Niu, Tyler H. McCormick

The network scale-up method (NSUM) is a cost-effective approach to estimating the size or prevalence of a group of people that is hard to reach through a standard survey. The basic NSUM involves two steps: estimating respondents' degrees by one of various methods (in this paper we focus on the probe group method which uses the number of people a respondent k

Junjie Ke, Tianhao Zhang, Yilin Wang, Peyman Milanfar

No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience. Unlike video recognition tasks, VQA tasks are sensitive to changes in input resolution. Since large amounts of UGC videos nowadays are 720p or above, the fixed and relatively small input used in conventional NR-VQA met

Stéphane Gonzalez, Nikolaos Pnevmatikos

The axiomatic foundations of Bentham and Rawls solutions are discussed within the broader domain of cardinal preferences. It is unveiled that both solution concepts share all four of the following axioms: Nonemptiness, Anonymity, Unanimity, and Continuity. In order to fully characterize the Bentham and Rawls solutions, three variations of a consistency crite

Daniel G. Edelberg, Roy R. Lederman

Variational autoencoders (VAEs) are a popular generative model used to approximate distributions. The encoder part of the VAE is used in amortized learning of latent variables, producing a latent representation for data samples. Recently, VAEs have been used to characterize physical and biological systems. In this case study, we qualitatively examine the amo

Yang Yang, Shao-Fu Shih, Hakan Erdogan, Jamie Menjay Lin

High quality speech capture has been widely studied for both voice communication and human computer interface reasons. To improve the capture performance, we can often find multi-microphone speech enhancement techniques deployed on various devices. Multi-microphone speech enhancement problem is often decomposed into two decoupled steps: a beamformer that pro

Yi Wang, Yihui Wei, Victor Dolores-Calzadilla, Daoxin Dai

Semiconductor optical amplifiers (SOA) are a fundamental building block for many photonic systems. However, their power inefficiency has been setting back operational cost reduction, and the resulting thermal losses constrain miniaturization, and the realization of more complex photonic functions such as large-scale switches and optical phased arrays. In thi

Mst Shapna Akter, Hossain Shahriar, Nova Ahmed, Alfredo Cuzzocrea

Aggressive comments on social media negatively impact human life. Such offensive contents are responsible for depression and suicidal-related activities. Since online social networking is increasing day by day, the hate content is also increasing. Several investigations have been done on the domain of cyberbullying, cyberaggression, hate speech, etc. The maj

Flavien Bureau, Justine Robin, Arthur Le Ber, William Lambert

Matrix imaging paves the way towards a next revolution in wave physics. Based on the response matrix recorded between a set of sensors, it enables an optimized compensation of aberration phenomena and multiple scattering events that usually drastically hinder the focusing process in heterogeneous media. Although it gave rise to spectacular results in optical

Bo-hyun Kwon, Jung Hoon Lee

In this paper, we define the \textit{normal form} of collections of disjoint three \textit{bridge arcs} for a given rational $3$-tangle. We show that there is a sequence of \textit{normal jump moves} which leads one to the other for two normal forms of the same rational 3-tangle.

Hardy Chan

In a bounded domain, we consider a variable range nonlocal operator, which is maximally isotropic in the sense that its radius of interaction equals the distance to the boundary. We establish $C^{1,\alpha}$ boundary regularity and existence results for the Dirichlet problem.

Gabriel Tellez

The bare Coulomb interaction between two like-charges is repulsive. When these charges are immersed in an electrolyte, the thermal fluctuations of the ions turn the bare Coulomb interaction into an effective interaction between the two charges. An interesting question arises: is it possible that the effective interaction becomes attractive for like-charges?

Lucia Ameis, Oliver Kuß, Annika Hoyer, Kathrin Möllenhoff

Time-to-event analysis often relies on prior parametric assumptions, or, if a non-parametric approach is chosen, Cox's model. This is inherently tied to the assumption of proportional hazards, with the analysis potentially invalidated if this assumption is not fulfilled. In addition, most interpretations focus on the hazard ratio, that is often misinterprete

Martin C. Korzeczek, Laurynas Dagys, Christoph Müller, Benedikt Tratzmiller

Nuclear spin hyperpolarization techniques, such as dynamic nuclear polarization (DNP) and parahydrogen-induced polarization (PHIP), have revolutionized nuclear magnetic resonance and magnetic resonance imaging. In these methods, a readily available source of high spin order, either electron spins in DNP or singlet states in hydrogen for PHIP, is brought into

Li Yang, Sen Lin, Fan Zhang, Junshan Zhang

Inspired by the success of Self-supervised learning (SSL) in learning visual representations from unlabeled data, a few recent works have studied SSL in the context of continual learning (CL), where multiple tasks are learned sequentially, giving rise to a new paradigm, namely self-supervised continual learning (SSCL). It has been shown that the SSCL outperf

Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel

Many engineering organizations are reimplementing and extending deep neural networks from the research community. We describe this process as deep learning model reengineering. Deep learning model reengineering - reusing, reproducing, adapting, and enhancing state-of-the-art deep learning approaches - is challenging for reasons including under-documented ref

Kuo-Wei Lai, Vidya Muthukumar

We provide a unified framework that applies to a general family of convex losses across binary and multiclass settings in the overparameterized regime to approximately characterize the implicit bias of gradient descent in closed form. Specifically, we show that the implicit bias is approximated (but not exactly equal to) the minimum-norm interpolation in hig

Yuguang Yao, Jiancheng Liu, Yifan Gong, Xiaoming Liu

Numerous adversarial attack methods have been developed to generate imperceptible image perturbations that can cause erroneous predictions of state-of-the-art machine learning (ML) models, in particular, deep neural networks (DNNs). Despite intense research on adversarial attacks, little effort was made to uncover 'arcana' carried in adversarial attacks. In

Sambatra Andrianomena, Sultan Hassan, Francisco Villaescusa-Navarro

We build a bijective mapping between different physical fields from hydrodynamic CAMELS simulations. We train a CycleGAN on three different setups: translating dark matter to neutral hydrogen (Mcdm-HI), mapping between dark matter and magnetic fields magnitude (Mcdm-B), and finally predicting magnetic fields magnitude from neutral hydrogen (HI-B). We assess

Marius Peters, Kristin Kliemt, Michelle Ocker, Bernd Wolf

EuPd$_2$Si$_2$ is a valence-fluctuating system undergoing a temperature-induced valence crossover at $T'_V\approx160\,$K. We present the successful single crystal growth using the Czochralski method for the substitution series EuPd$_2$(Si$_{1-x}$Ge$_x$)$_2$, with substitution levels $x\leq 0.15$. A careful determination of the germanium content revealed that

Ian Ball

This note presents a unified theorem of the alternative that explicitly allows for any combination of equality, componentwise inequality, weak dominance, strict dominance, and nonnegativity relations. The theorem nests 60 special cases, some of which have been stated as separate theorems.

Shrihari Sridharan, Jacob R. Stevens, Kaushik Roy, Anand Raghunathan

Transformers have achieved great success in a wide variety of natural language processing (NLP) tasks due to the attention mechanism, which assigns an importance score for every word relative to other words in a sequence. However, these models are very large, often reaching hundreds of billions of parameters, and therefore require a large number of DRAM acce

Ronald Fagin, Phokion G. Kolaitis, Domenico Lembo, Lucian Popa

We propose a new framework for combining entity resolution and query answering in knowledge bases (KBs) with tuple-generating dependencies (tgds) and equality-generating dependencies (egds) as rules. We define the semantics of the KB in terms of special instances that involve equivalence classes of entities and sets of values. Intuitively, the former collect

Peter Zhang

We propose a distributionally robust principal agent formulation, which generalizes some common variants of worst-case and Bayesian principal agent problems. We construct a theoretical framework to certify whether any surjective contract family is optimal, and bound its sub-optimality. We then apply the framework to study the optimality of affine contracts.

Lorenz Graf-Vlachy

Software engineering capabilities are increasingly important to the success of economic and political blocs. This paper analyzes quantity and quality of software engineering research output originating from the US, Europe, and China over time. The results indicate that the quantity of research is increasing across the board with Europe leading the field. Dep

Justin McMillen, Gokhan Mumcu, Yasin Yilmaz

Radio frequency (RF) fingerprinting is a tool which allows for authentication by utilizing distinct and random distortions in a received signal based on characteristics of the transmitter. We introduce a deep learning-based authentication method for a novel RF fingerprinting system called Physically Unclonable Wireless Systems (PUWS). An element of PUWS is b

Yanyan Liang, Matous Mrovec, Yury Lysogorskiy, Miquel Vega-Paredes

Insight into structural and thermodynamic properties of nanoparticles is crucial for designing optimal catalysts with enhanced activity and stability. We present a semi-automated workflow for parameterizing the atomic cluster expansion (ACE) from ab initio data. The main steps of the workflow are the generation of training data from accurate electronic struc

Anirban Guha, Akanksha Gupta

By providing mathematical estimates, this paper answers a fundamental question -- "what leads to Stokes drift"? Although overwhelmingly understood for water waves, Stokes drift is a generic mechanism that stems from kinematics and occurs in any non-transverse wave in fluids. To showcase its generality, we undertake a comparative study of the pathline equatio

Jan Bohn, Willy Dörfler, Michael Feischl, Stefan Karch

We propose a new adaptive algorithm for the approximation of the Landau-Lifshitz-Gilbert equation via a higher-order tangent plane scheme. We show that the adaptive approximation satisfies an energy inequality and demonstrate numerically, that the adaptive algorithm outperforms uniform approaches.

Minkyu Shin, Jin Kim, Bas van Opheusden, Thomas L. Griffiths

How will superhuman artificial intelligence (AI) affect human decision making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI already exceeds human performance, analyzing more than 5.8 million move decisions made by professional Go players over the past 71 years (1950-2021). To address the first question,

Ken R. Duffy, Moritz Grundei, Muriel Medard

To meet the Ultra Reliable Low Latency Communication (URLLC) needs of modern applications, there have been significant advances in the development of short error correction codes and corresponding soft detection decoders. A substantial hindrance to delivering low-latency is, however, the reliance on interleaving to break up omnipresent channel correlations t

Alban Jean-Marie Seguinard, Amélie Piveteau, Piotr Mironowicz, Mohamed Bourennane

One of the striking properties of quantum mechanics is the occurrence of the Bell-type non-locality. They are a fundamental feature of the theory that allows two parties that share an entangled quantum system to observe correlations stronger than possible in classical physics. In addition to their theoretical significance, non-local correlations have practic

Roberto Feola, Jessica Elisa Massetti

We consider a completely resonant nonlinear Schr\"odinger equation on the $d$-dimensional torus, for any $d\geq 1$, with polynomial nonlinearity of any degree $2p+1$, $p\geq1$, which is gauge and translation invariant. We study the behaviour of high Sobolev $H^{s}$-norms of solutions, $s\geq s_1+1 > d/2 + 2$, whose initial datum $u_0\in H^{s}$ satisfies an a

Cong Han, Nima Mesgarani

Binaural speech separation in real-world scenarios often involves moving speakers. Most current speech separation methods use utterance-level permutation invariant training (u-PIT) for training. In inference time, however, the order of outputs can be inconsistent over time particularly in long-form speech separation. This situation which is referred to as th

Yisheng Xiao, Ruiyang Xu, Lijun Wu, Juntao Li

Transformer-based autoregressive (AR) methods have achieved appealing performance for varied sequence-to-sequence generation tasks, e.g., neural machine translation, summarization, and code generation, but suffer from low inference efficiency. To speed up the inference stage, many non-autoregressive (NAR) strategies have been proposed in the past few years.

Wanshi Chen, Xingqin Lin, Juho Lee, Antti Toskala

Since the start of 5G work in 3GPP in early 2016, tremendous progress has been made in both standardization and commercial deployments. 3GPP is now entering the second phase of 5G standardization, known as 5G-Advanced, built on the 5G baseline in 3GPP Releases 15, 16, and 17. 3GPP Release 18, the start of 5G-Advanced, includes a diverse set of features that

Richard Lieu, Chun-Hui Shi

With tantalizing evidence of the recent e-Rosita mission, re-discovering very soft X-rays and EUV radiation from a cluster of galaxies or its environment, the question of the origin of cluster EUV excess is revisited in this work. It will be shown that the gas temperature, density, and frozen-in magnetic field of the intracluster medium, collectively support

Benjamin Doerr, Andrei Lissovoi, Pietro S. Oliveto

Recently it has been proven that simple GP systems can efficiently evolve a conjunction of $n$ variables if they are equipped with the minimal required components. In this paper, we make a considerable step forward by analysing the behaviour and performance of a GP system for evolving a Boolean conjunction or disjunction of $n$ variables using a complete fun

Luca Bolzonello, Niek F van Hulst, Andreas Jakobsson

Spectroscopy detected in the time domain entails many techniques, such as FTIR, pump-probe, FT-Raman, and 2DES, and applications, such as molecule characterization, excited state dynamics studies, or spectra classifications. Surprisingly, all these techniques use sampling schemes that rarely exploit the a priori knowledge the scientist has before the experim

Koosha Pourtahmasi Roshandeh, Mostafa Mohammadkarimi, Masoud Ardakani

The discussion on using zero padding (ZP) instead of a cyclic prefix (CP) for enhancing channel estimation and equalization performance is a recurring topic in waveform design for future wireless systems that high spectral efficiency and location awareness are the key factors. This is particularly true for orthogonal signals, such as orthogonal frequency-div

Jingtao Li, Adnan Siraj Rakin, Xing Chen, Li Yang

Federated Learning (FL) is a popular collaborative learning scheme involving multiple clients and a server. FL focuses on protecting clients' data but turns out to be highly vulnerable to Intellectual Property (IP) threats. Since FL periodically collects and distributes the model parameters, a free-rider can download the latest model and thus steal model IP.

William Marfo, Deepak K. Tosh, Shirley V. Moore

Due to the veracity and heterogeneity in network traffic, detecting anomalous events is challenging. The computational load on global servers is a significant challenge in terms of efficiency, accuracy, and scalability. Our primary motivation is to introduce a robust and scalable framework that enables efficient network anomaly detection. We address the issu

Malay Joshi, Aditi Shukla, Jayesh Srivastava, Manya Rastogi

In today's society, where independent living is becoming increasingly important, it can be extremely constricting for those who are blind. Blind and visually impaired (BVI) people face challenges because they need manual support to prompt information about their environment. In this work, we took our first step towards developing an affordable and high-perfo

Alessio Maritan, Luca Schenato

In this work we address the problem of convex optimization in a multi-agent setting where the objective is to minimize the mean of local cost functions whose derivatives are not available (e.g. black-box models). Moreover agents can only communicate with local neighbors according to a connected network topology. Zeroth-order (ZO) optimization has recently ga

Christopher Ick, Adib Mehrabi, Wenyu Jin

Modeling room acoustics in a field setting involves some degree of blind parameter estimation from noisy and reverberant audio. Modern approaches leverage convolutional neural networks (CNNs) in tandem with time-frequency representation. Using short-time Fourier transforms to develop these spectrogram-like features has shown promising results, but this metho

Serena Perrotta, Alison L. Coil, David S. N. Rupke, Christy A. Tremonti

We present results on the properties of extreme gas outflows in massive ($\rm M_* \sim$10$^{11} \ \rm M_{\odot}$), compact, starburst ($\rm SFR \sim$$200 \, \rm M_{\odot} \ yr^{-1}$) galaxies at z = $0.4-0.7$ with very high star formation surface densities ($\rm \Sigma_{SFR} \sim$$2000 \,\rm M_{\odot} \ yr^{-1} \ kpc^{-2}$). Using optical Keck/HIRES spectros

V. A. Zakharov, A. Mert Bozkurt, A. R. Akhmerov, D. O. Oriekhov

We develop a theory of magnetic breakdown (MB) near high-order saddle points in the dispersions of two-dimensional materials, where two or more semiclassical cyclotron orbits approach each other. MB occurs due to quantum tunneling between several trajectories, which leads to non-trivial scattering amplitudes and phases. We show that for any saddle point this

Lea Gassab, Ali Pedram, Özgür E. Müstecaplıoğlu

This paper explores the sensitivity of the human visual system to quantum entangled light. We examine the possibility of human subjects perceiving multipartite entangled state through psychophysical experiments. Our focus begins with a bipartite entangled state to make a comparative study with the literature by taking into account additive noise for false po

Hasan Hassan

DRAM is the primary technology used for main memory in modern systems. Unfortunately, as DRAM scales down to smaller technology nodes, it faces key challenges in both data integrity and latency, which strongly affect overall system reliability, security, and performance. To develop reliable, secure, and high-performance DRAM-based main memory for future syst