May 2023 arXiv papers — page 182

Lukas Mouton, Florentin Reiter, Ying Chen, Patrick Rebentrost

Partial differential equations frequently appear in the natural sciences and related disciplines. Solving them is often challenging, particularly in high dimensions, due to the "curse of dimensionality". In this work, we explore the potential for enhancing a classical deep learning-based method for solving high-dimensional nonlinear partial different

M. W. AlMasri

The multiple-valued quantum logic is formulated systematically such that the truth values are represented naturally as unique roots of unity placed on the unit circle. Consequently, multi-valued quantum neuron (MVQN) is based on the principles of multiple-valued threshold logic over the field of complex numbers. The training of MVQN is reduced to the movemen

Claudio Cicconetti, Marco Conti, Andrea Passarella

Quantum Key Distribution (QKD) enables secure communications via the exchange of cryptographic keys exploiting the properties of quantum mechanics. Nowadays the related technology is mature enough for production systems, thus field deployments of QKD networks are expected to appear in the near future, starting from local/metropolitan settings, where edge com

Ahmed Salih, Zahra Raisi-Estabragh, Ilaria Boscolo Galazzo, Petia Radeva

eXplainable artificial intelligence (XAI) methods have emerged to convert the black box of machine learning (ML) models into a more digestible form. These methods help to communicate how the model works with the aim of making ML models more transparent and increasing the trust of end-users into their output. SHapley Additive exPlanations (SHAP) and Local Int

Marcus Zibrowius

We study the derived tensor product of the representation rings of subgroups of a given compact Lie group G. That is, given two such subgroups H_1 and H_2, we study the tensor product of the associated representation rings R(H_1) and R(H_2) over the representation ring RG, and prove a vanishing result for the associated higher Tor-groups. This result can be

Mina Alibeigi, William Ljungbergh, Adam Tonderski, Georg Hess

Existing datasets for autonomous driving (AD) often lack diversity and long-range capabilities, focusing instead on 360° perception and temporal reasoning. To address this gap, we introduce Zenseact Open Dataset (ZOD), a large-scale and diverse multimodal dataset collected over two years in various European countries, covering an area 9x that of existing dat

Noah F. Q. Yuan

The critical field behavior of a layered Ising superconductor with finite number of layers is studied. Under in-plane magnetic fields, the finite-momentum superconductivity dubbed as the orbital Fulde- Ferrell-Larkin-Ovchinnikov state is found in the regime of low field and high temperature. Our theory agrees well with the experimental results in Nature 619,

ATLAS Collaboration

A search new phenomena giving rise to pairs of opposite electrically charged muons with impact parameters in the millimetre range is presented, using 139 fb$^{-1}$ of $\sqrt{s} = 13$ TeV $pp$ collision data from the ATLAS detector at the LHC. The search targets the gap in coverage between existing searches targeting final states with leptons with large displ

Saúl Burgos, José Luis Flores, Jónatan Herrera

Inspired by some Lorentzian versions of the notion of metric and length space introduced by Kunzinger and Sämman, and more recently, by Müller, and Minguzzi and Sühr, we revisit the notion of Lorentzian metric space in order to later construct the c-completion of these general objects. We not only prove that this construction is feasible in great generality

Saharon Shelah

The theme of the first two sections, is to prepare the framework of how from a ``complicated'' family of so called index models $I \in K_1$ we build many and/or complicated structures in a class $K_2$. The index models are characteristically linear orders, trees with $κ+1$ levels (possibly with linear order on the set of successors of a member) and l

Yanglin Hu, Marco Tomamichel

The no-cloning theorem is a cornerstone of quantum cryptography. Here we generalize and rederive in a unified framework various upper bounds on the maximum achievable fidelity of probabilistic and deterministic cloning machines. Building on ideas by Gisin [Phys.~Lett.~A, 1998], our result starts from the fact that remote state preparation is possible and the

Ergun Yalcin

In [F. Xu, On the cohomology rings of small categories, J. Pure Appl. Algebra 212 (2008), 2555-2569], Xu constructs a LHS-spectral sequence for target regular extensions of small categories. We extend this construction to ext-groups and construct a similar spectral sequence for source regular extensions (with right module coefficients). As a special case of

Marco Regis, Michael Korsmeier, Gianni Bernardi, Giada Pignataro

Radiative emissions from electrons and positrons generated by dark matter (DM) annihilation or decay are one of the most investigated signals in indirect searches of WIMPs. Ideal targets must have large ratio of DM to baryonic matter. However, such ``dark'' systems have a poorly known level of magnetic turbulence, which determines the residence time

Hang Jung Ling, Nathan Painchaud, Pierre-Yves Courand, Pierre-Marc Jodoin

Deep learning-based methods have spearheaded the automatic analysis of echocardiographic images, taking advantage of the publication of multiple open access datasets annotated by experts (CAMUS being one of the largest public databases). However, these models are still considered unreliable by clinicians due to unresolved issues concerning i) the temporal co

Philipp Glaum, Fabian Neumann, Tom Brown

Wind energy has become increasingly important for meeting Europe's energy needs. While onshore wind expansion faces public acceptance problems, for offshore wind the European Commission has introduced ambitious goals to increase capacity from 15GW to 300GW in 2050. Incorporating more offshore wind electricity into the power grid may offer a more widely a

Xiaodan Xing, Yang Nan, Federico Felder, Simon Walsh

Training medical AI algorithms requires large volumes of accurately labeled datasets, which are difficult to obtain in the real world. Synthetic images generated from deep generative models can help alleviate the data scarcity problem, but their effectiveness relies on their fidelity to real-world images. Typically, researchers select synthesis models based

Pedro Portugal, Fredrik Brange, Kalle S. U. Kansanen, Peter Samuelsson

Recent experimental advances have made it possible to detect individual quantum jumps in open quantum systems, such as the tunneling of single electrons in nanoscale conductors or the emission of photons from non-classical light sources. Here, we investigate theoretically the statistics of photons emitted from a microwave cavity that is driven resonantly by

Jakub Bulín, Michael Kompatscher

A first-order formula is called primitive positive (pp) if it only admits the use of existential quantifiers and conjunction. Pp-formulas are a central concept in (fixed-template) constraint satisfaction since CSP($\Gamma$) can be viewed as the problem of deciding the primitive positive theory of $\Gamma$, and pp-definability captures gadget reductions betwe

Anne-Sophie Bonnet-Ben Dhia, Lucas Chesnel, Mahran Rihani

We study a transmission problem for the time harmonic Maxwell's equations between a classical positive material and a so-called negative index material in which both the permittivity $\varepsilon$ and the permeability $\mu$ take negative values. Additionally, we assume that the interface between the two domains is smooth everywhere except at a point where it

Sougata Bose, David Purser, Patrick Totzke

We consider history-determinism, a restricted form of non-determinism, for Vector Addition Systems with States (VASS) when used as acceptors to recognise languages of finite words. History-determinism requires that the non-deterministic choices can be resolved on-the-fly; based on the past and without jeopardising acceptance of any possible continuation of t

Zhixi Cai, Shreya Ghosh, Abhinav Dhall, Tom Gedeon

Most deepfake detection methods focus on detecting spatial and/or spatio-temporal changes in facial attributes and are centered around the binary classification task of detecting whether a video is real or fake. This is because available benchmark datasets contain mostly visual-only modifications present in the entirety of the video. However, a sophisticated

Kenshi Kuroki, Azumi Sakai, Koichi Murase, Tetsufumi Hirano

One of the long-standing problems in the field of high-energy heavy-ion collisions is that the dynamical models based on viscous hydrodynamics fail to describe the experimental elliptic flow $v_2$ and the triangular flow $v_3$ simultaneously in ultra-central collisions. The problem, known as the "ultra-central flow puzzle", is specifically that hydro

Jiahui Geng, Zongxiong Chen, Yuandou Wang, Herbert Woisetschlaeger

Dataset distillation is attracting more attention in machine learning as training sets continue to grow and the cost of training state-of-the-art models becomes increasingly high. By synthesizing datasets with high information density, dataset distillation offers a range of potential applications, including support for continual learning, neural architecture

Satish Narayana Srirama

Recent developments in the Internet of Things (IoT) and real-time applications, have led to the unprecedented growth in the connected devices and their generated data. Traditionally, this sensor data is transferred and processed at the cloud, and the control signals are sent back to the relevant actuators, as part of the IoT applications. This cloud-centric

Bushra Ali, Sweta Singh, Anuj Chandra, Shakeel Ahmad

Event-by-event (ebe) multiplicity \fll and \cor amongst the charged particles emitted in the forward-backward symmetric pseudorapidity (\et) windows of varying widths and positions are investigated by analyzing the experimental data on $^{197}$Au-AgBr collisions at 11.6A GeV/c. The findings are compared with the predictions of relativistic transport model, \

Subin Lin, Vasantha Ramani, Miguel Martin, Pandarasamy Arjunan

The paper describes a dataset that was collected by infrared thermography, which is a non-contact, non-intrusive technique to collect data and analyze the built environment in various aspects. While most studies focus on the city and building scales, the rooftop observatory provides high temporal and spatial resolution observations with dynamic interactions

Yacine Chitour, Hoai-Minh Nguyen, Christophe Roman

We establish the exponential decay of the solutions of the damped wave equations in one-dimensional space where the damping coefficient is a nowhere-vanishing function of space. The considered PDE is associated with several dynamic boundary conditions, also referred to as Wentzell/Ventzel boundary conditions in the literature. The analysis is based on the de

Jiannan Tang, Weihao Wu, Liang Li, Peng Miao

TRIDENT (The tRopIcal DEep-sea Neutrino Telescope) is a proposed next-generation neutrino telescope to be constructed in the South China Sea. In September 2021, the TRIDENT Pathfinder experiment (TRIDENT EXplorer, T-REX for short) was conducted to evaluate the in-situ optical properties of seawater. The T-REX experiment deployed three digital optical modules

Cesar Bonilla, A. E. Cárcamo Hernández, João Gonçalves, Vishnudath K. N.

We propose a framework to account for neutrino masses at the two-loop level. This mechanism introduces new scalars and Majorana fermions to the Standard Model. It is assumed the existence of a global $\mathrm{U(1)\times \mathcal{Z}_2}$ symmetry which after partial breaking provides the stability of the dark matter candidates of the theory. The rich structure

Luisa Herrmann, Vincent Peth, Sebastian Rudolph

We propose $ω$MSO$\Join$BAPA, an expressive logic for describing countable structures, which subsumes and transcends both Counting Monadic Second-Order Logic (CMSO) and Boolean Algebra with Presburger Arithmetic (BAPA). We show that satisfiability of $ω$MSO$\Join$BAPA is decidable over the class of labeled infinite binary trees, whereas it becomes undecidabl

Axel Maas

There is an odd tension in electroweak physics. Perturbation theory is extremely successful. At the same time, fundamental field theory gives manifold reasons why this should not be the case. This tension is resolved by the Fr\"ohlich-Morchio-Strocchi mechanism. However, the legacy of this work goes far beyond the resolution of this tension, and may usher in

Areski Cousin, Jérôme Lelong, Tom Picard

This paper studies the multi-period mean-variance portfolio allocation problem with transaction costs. Many methods have been proposed these last years to challenge the famous uni-period Markowitz strategy.But these methods cannot integrate transaction costs or become computationally heavy and hardly applicable. In this paper, we try to tackle this allocatio

Anwesh Ray

Let $\ell\geq 5$ be a prime number and $\mathbb{F}_\ell$ denote the finite field with $\ell$ elements. We show that the number of Galois extensions of the rationals with Galois group isomorphic to $GL_2(\mathbb{F}_\ell)$ and absolute discriminant bounded above by $X$ is asymptotically at least $\frac{X^{\frac{\ell}{12(\ell-1)\# GL_2(\mathbb{F}_\ell)}}}{\log

Chi Seng Cheang, Hou Pong Chan, Derek F. Wong, Xuebo Liu

Recent pre-trained language models (PLMs) achieve promising results in existing abstractive summarization datasets. However, existing summarization benchmarks overlap in time with the standard pre-training corpora and finetuning datasets. Hence, the strong performance of PLMs may rely on the parametric knowledge that is memorized during pre-training and fine

Mariano G. Beiró, Ning Ning Chung, Lock Yue Chew, Yérali Gandica

The success of an on-line movement could be defined in terms of the shift to large-scale and the later off-line massive street actions of protests. The role of social media in this process is to facilitate the transformation from small or local feelings of disagreement into large-scale social actions. The way how social media achieves that effect is by growi

Stephen Appleby, Motonari Tonegawa, Changbom Park, Sungwook E. Hong

We extract the galaxy density and momentum power spectra from a subset of early-type galaxies in the SDSS DR7 main galaxy catalog. Using galaxy distance information inferred from the improved fundamental plane described in \citet{Yoon_2020}, we reconstruct the peculiar velocities of the galaxies and generate number density and density-weighted velocity field

Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang

This study aims to prove the emergence of symbolic concepts (or more precisely, sparse primitive inference patterns) in well-trained deep neural networks (DNNs). Specifically, we prove the following three conditions for the emergence. (i) The high-order derivatives of the network output with respect to the input variables are all zero. (ii) The DNN can be us

Fengbin Zhu, Chao Wang, Fuli Feng, Zifeng Ren

Discrete reasoning over table-text documents (e.g., financial reports) gains increasing attention in recent two years. Existing works mostly simplify this challenge by manually selecting and transforming document pages to structured tables and paragraphs, hindering their practical application. In this work, we explore a more realistic problem setting in the

Harold Berjamin, Michel Destrade

We present and review several models of fractional viscous stresses from the literature, which generalise classical viscosity theories to fractional orders by replacing total strain derivatives in time with fractional time derivatives. We also briefly introduce Prony-type approximations of these theories. Here we investigate the issues of material frame-indi

Tobias Ladner, Matthias Althoff

Formal verification of neural networks is essential before their deployment in safety-critical applications. However, existing methods for formally verifying neural networks are not yet scalable enough to handle practical problems under strict time constraints. We address this challenge by introducing a fully automatic and sound reduction of neural networks

A. O. Korotkevich, S. V. Nazarenko, Y. Pan, J. Shatah

We develop a theory of turbulence of weak random gravity waves on surface of deep water in which the main nonlinear process at high-frequency part of the spectrum is a nonlocal interaction with a strong low-frequency component. The latter component, which we call ``condensate", may appear in the system due to, e.g., the finite size effects which lead to an e

Wanqing Cui, Xin Hong, Yanyan Lan, Liang Pang

Humans can naturally reason from superficial state differences (e.g. ground wetness) to transformations descriptions (e.g. raining) according to their life experience. In this paper, we propose a new visual reasoning task to test this transformation reasoning ability in real-world scenarios, called \textbf{V}isual \textbf{T}ransformation \textbf{T}elling (VT

Andrew Perkis, Mattia Bellini, Valentina Nisi, Maria Cecilia Reyes

This white paper was written by the members of the Work Group focusing on design practices of the COST Action 18230 - Interactive Narrative Design for Complexity Representation (INDCOR, WG1). It presents an overview of Interactive Digital Narratives (IDNs) design for complexity representations through IDN workflows and methodologies, IDN authoring tools and

Qiaoyan Peng, Qingqing Wu, Guangji Chen, Ruiqi Liu

Deploying active reflecting elements at the intelligent reflecting surface (IRS) increases signal amplification capability but incurs higher power consumption. Therefore, it remains a challenging and open problem to determine the optimal number of active/passive elements for maximizing energy efficiency (EE). To answer this question, we consider a hybrid act

Marius de Leeuw, Chiara Paletta, Balázs Pozsgay, Eric Vernier

We consider spin-1/2 chains with external driving that breaks the continuous symmetries of the Hamiltonian. We introduce a family of models described by the Lindblad equation with local jump operators. The models have hidden strong symmetries in the form of quasi-local charges, leading to multiple non-equilibrium steady states. We compute them exactly in the

Kiyohiro Nakayama, Mikaela Angelina Uy, Jiahui Huang, Shi-Min Hu

While the community of 3D point cloud generation has witnessed a big growth in recent years, there still lacks an effective way to enable intuitive user control in the generation process, hence limiting the general utility of such methods. Since an intuitive way of decomposing a shape is through its parts, we propose to tackle the task of controllable part-b

Wanli Li, Tieyun Qian, Yi Song, Zeyu Zhang

Zero-shot Relation Triplet Extraction (ZeroRTE) aims to extract relation triplets from texts containing unseen relation types. This capability benefits various downstream information retrieval (IR) tasks. The primary challenge lies in enabling models to generalize effectively to unseen relation categories. Existing approaches typically leverage the knowledge

Qinyuan Cheng, Xiaogui Yang, Tianxiang Sun, Linyang Li

Contrastive learning has become a popular approach in natural language processing, particularly for the learning of sentence embeddings. However, the discrete nature of natural language makes it difficult to ensure the quality of positive and negative sample pairs generated through data augmentation methods. Although supervised contrastive learning can produ

Kevin Aguyar Brix, Alexander Mundey, Adam Rennie

We present an extension of the notion of in-splits from symbolic dynamics to topological graphs and, more generally, to C*-correspondences. We demonstrate that in-splits provide examples of strong shift equivalences of C*-correspondences. Furthermore, we provide a streamlined treatment of Muhly, Pask, and Tomforde's proof that any strong shift equivalence of

Kensuke Akita, Shin'ichiro Ando

The elastic scattering between dark matter (DM) and radiation can potentially explain small-scale observations that the cold dark matter faces as a challenge, as damping density fluctuations via dark acoustic oscillations in the early universe erases small-scale structure. We study a semi-analytical subhalo model for interacting dark matter with radiation, b

Jin Sun

The Ramsey's theorem says that a graph with sufficiently many vertices contains a clique or stable set with many vertices. Now we attach some parameter to every vertex, such as degree. Consider the case a graph with sufficiently many vertices of large degree, we can get the realted Ramsey-type result. The Ramsey's theorem of connected version says th

Yooshin Cho, Hanbyel Cho, Hyeong Gwon Hong, Jaesung Ahn

Since the beginning of world-wide COVID-19 pandemic, facial masks have been recommended to limit the spread of the disease. However, these masks hide certain facial attributes. Hence, it has become difficult for existing face recognition systems to perform identity verification on masked faces. In this context, it is necessary to develop masked Face Recognit

KiYoon Yoo, Wonhyuk Ahn, Jiho Jang, Nojun Kwak

Recent years have witnessed a proliferation of valuable original natural language contents found in subscription-based media outlets, web novel platforms, and outputs of large language models. However, these contents are susceptible to illegal piracy and potential misuse without proper security measures. This calls for a secure watermarking system to guarant

Sang-ik An, Dongheui Lee, Gyunghoon Park

We propose an extension of the input-output feedback linearization for a class of multivariate systems that are not input-output linearizable in a classical manner. The key observation is that the usual input-output linearization problem can be interpreted as the problem of solving simultaneous linear equations associated with the input gain matrix: thus, ev

Yubo Ma, Zehao Wang, Yixin Cao, Aixin Sun

Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e.g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress.This paper presents a thorough empirical study, a unified view of ED models, and a better unified baseline. For fair evaluation, we compare

Tanmoy Chattopadhyay, Sven Herrmann, Peter Orel, Kevan Donlon

We demonstrate so-called repetitive non-destructive readout (RNDR) for the first time on a Single electron Sensitive Readout (SiSeRO) device. SiSeRO is a novel on-chip charge detector output stage for charge-coupled device (CCD) image sensors, developed at MIT Lincoln Laboratory. This technology uses a p-MOSFET transistor with a depleted internal gate beneat

Tao Chen, Liang Lv, Di Wang, Jing Zhang

With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages. Recently, artificial intelligence (AI) techniques such as deep learning (DL) have demonstrated their strong abilities in various areas, including language, vision, remote sens

Tian Zhang, Wenshan Guan, Hao Miao, Xiujie Huang

The field of intelligent connected in modern vehicles continues to expand, and the functions of vehicles become more and more complex with the development of the times. This has also led to an increasing number of vehicle vulnerabilities and many safety issues. Therefore, it is particularly important to identify high-risk vehicle intelligent connected system

Huibo Hong, Runai Quan, Xiao Xiang, Yuting Liu

As a new approach to realizing high-precision time synchronization between remote time scales, quantum two-way time transfer via laboratory fiber link has shown significant enhancement of the transfer stability to several tens of femtoseconds. To verify its great potential in practical systems, the field test in long-haul installed fiber optic infrastructure

Aohua Cheng, Yunhui Xu, Pei Sun, Yang Tian

Modern theories of phase transitions and scale-invariance are rooted in path integral formulation and renormalization group (RG). Despite the applicability of these approaches on simple systems with only pairwise interactions, they are less effective on complex systems with un-decomposable high-order interactions (i.e., interactions among arbitrary sets of u

Preeti Bhall, Meenakshi Batra, Alka Upadhyay

An operator formalism is used on the wavefunction of baryons to compute their charge radii and quadrupole moments. Total anti-symmetric wavefunction in spin, color and flavor space is framed for $J^P=\frac{1}{2}^+$ nucleons and $J^P=\frac{3}{2}^+$ hyperons. To understand the importance of sea, statistical model is used in conjugation with the detailed balanc

G. R. Boroun, B. Rezaei, F. Abdi

An analytical study with respect to the nonlinear corrections for the nuclear gluon distribution function in the next-to-leading order approximation at small $x$ is presented. We consider the nonlinear corrections to the nuclear gluon distribution functions at low values of $x$ and $Q^{2}$ using the parametrization $F_{2}(x,Q^{2})$ and using the nuclear modi

Shupeng Hu, Fei Li, Xiumei Li

The weight distribution and weight hierarchy of a linear code are two important research topics in coding theory. In this paper, choosing $ D=\Big\{(x,y)\in \Big(\F_{p^{s_1}}\times\F_{p^{s_2}}\Big)\Big\backslash\{(0,0)\}: f(x)+\Tr_1^{s_2}(αy)=0\Big\}$ as a defining set , where $α\in\mathbb{F}_{p^{s_2}}^*$ and $f(x)$ is a quadratic form over $\mathbb{F}_{p^{s

Minseop Jung, Jaeseung Lee, Jibum Kim

Several studies have attempted to solve traveling salesman problems (TSPs) using various deep learning techniques. Among them, Transformer-based models show state-of-the-art performance even for large-scale Traveling Salesman Problems (TSPs). However, they are based on fully-connected attention models and suffer from large computational complexity and GPU me

Peifeng Wang, Zhengyang Wang, Zheng Li, Yifan Gao

Large language models (LMs) beyond a certain scale, demonstrate the emergent capability of generating free-text rationales for their predictions via chain-of-thought (CoT) prompting. While CoT can yield dramatically improved performance, such gains are only observed for sufficiently large LMs. Even more concerning, there is little guarantee that the generate

Daniel Hader, Matthew J. Patitz

Algorithmic self-assembly occurs when disorganized components autonomously combine to form structures and, by their design and the dynamics of the system, are forced to follow the execution of algorithms. Motivated by applications in DNA-nanotechnology, investigations in algorithmic tile-based self-assembly have blossomed into a mature theory with research l

Siyu Yuan, Deqing Yang, Jinxi Liu, Shuyu Tian

Concepts benefit natural language understanding but are far from complete in existing knowledge graphs (KGs). Recently, pre-trained language models (PLMs) have been widely used in text-based concept extraction (CE). However, PLMs tend to mine the co-occurrence associations from massive corpus as pre-trained knowledge rather than the real causal effect betwee

Raymond Leung

This article is a sequel to "GPU implementation of a ray-surface intersection algorithm in CUDA" (arXiv:2209.02878) [1]. Its main focus is PyCUDA which represents a Python scripting approach to GPU run-time code generation in the Compute Unified Device Architecture (CUDA) framework. It accompanies the open-source code distributed in GitHub which prov

Hanzhen Ma, Susanne F. Yelin

Finding a comprehensive and general description of the collective Lamb shift and cooperative broadening in a radiatively interacting system is a long-standing open question. Both energy levels and linewidth of individual atoms are modified by the exchange of real and virtual photons making up the dipole-dipole interaction. We introduce a method to theoretica

Zhepei Wang, Cem Subakan, Krishna Subramani, Junkai Wu

Recent advances in using language models to obtain cross-modal audio-text representations have overcome the limitations of conventional training approaches that use predefined labels. This has allowed the community to make progress in tasks like zero-shot classification, which would otherwise not be possible. However, learning such representations requires a

Eason Chen, Ray Huang, Han-Shin Chen, Yuen-Hsien Tseng

Learning new programming skills requires tailored guidance. With the emergence of advanced Natural Language Generation models like the ChatGPT API, there is now a possibility of creating a convenient and personalized tutoring system with AI for computer science education. This paper presents GPTutor, a ChatGPT-powered programming tool, which is a Visual Stud

Runze Han, Jiazhou Chen, Mengyue Zhang, Jinze Gao

Here, the magnetic susceptibility of a triangular-graphene-quantum-dot-like system was examined by using the determinant quantum Monte Carlo method. We focused on three zigzag edge quantum dots or rings, namely, the triangular graphene quantum ring, bilayer triangular graphene quantum dot, and bilayer triangular graphene quantum ring. The triangular-graphene

Kuei-Nuan Lin, Yi-Huang Shen

In this paper, we study the algebra of Veronese type. We show that the presentation ideal of this algebra has an initial ideal whose Alexander dual has linear quotients. As an application, we explicitly obtain the Castelnuovo-Mumford regularity of the Veronese type algebra. Furthermore, we give an effective upper bound on the multiplicity of this algebra.

Alexander Polishchuk

We study the de Rham cohomology and the Hodge to de Rham spectral sequence for supervarieties.

Roman Haak

An Eggert-operad is a variant of Mac Lane's notion of a PROP, for which not only bijective maps, but all maps between standard finite sets, are part of the structure. We construct the free Eggert-operad and prove the universal property it satisfies. Further we use the free Eggert-operad to define the Eggert-operad $\mathrm{GROUP}_0^{\mathrm{fp}}$ via gen

Youngmin Lim, Bhuwan Nepal, David A. Smith, Shuang Wu

An electrically conductive metal typically transmits or absorbs a spin current. Here, we report on evidence that interfacing two metal thin films can suppress spin transmission and absorption. We examine spin pumping in ferromagnet/spacer/ferromagnet heterostructures, in which the spacer -- consisting of metallic Cu and Cr thin films -- separates the ferroma

Lora Bailey, Heather Smith Blake, Garner Cochran, Nathan Fox

In this paper, we examine the computational complexity of enumeration in certain genome rearrangement models. We first show that the Pairwise Rearrangement problem in the Single Cut-and-Join model (Bergeron, Medvedev, & Stoye, J. Comput. Biol. 2010) is $\#\textsf{P}$-complete under polynomial-time Turing reductions. Next, we show that in the Single Cut or Jo

David B. McCoy, Alan E. Hubbard, Alejandro Schuler, Mark J. van der Laan

This study introduces a nonparametric definition of interaction and provides an approach to both interaction discovery and efficient estimation of this parameter. Using stochastic shift interventions and ensemble machine learning, our approach identifies and quantifies interaction effects through a model-independent target parameter, estimated via targeted m

Armin Kianfar, Mahmoud I. Hussein

Local phonon motion underneath a surface interacting with a flow may cause the flow to passively stabilize, or destabilize, as desired within the region adjacent to the subsurface motion. This mechanism has been extensively analyzed over only a spatial region on the order of the instability wavelength along the fluid-structure interface. Here we uncover fund

Gabriel San Martin Silva, Enrique Lopez Droguett

Over the last decade, concepts such as industry 4.0 and the Internet of Things (IoT) have contributed to the increase in the availability and affordability of sensing technology. In this context, Structural Health Monitoring (SHM) arises as an especially interesting field to integrate and develop these new sensing capabilities, given the criticality of struc

Kevin Vanslette

This article expands the framework of Bayesian inference and provides direct probabilistic methods for approaching inference tasks that are typically handled with information theory. We treat Bayesian probability updating as a random process and uncover intrinsic quantitative features of joint probability distributions called inferential moments. Inferential

Nived J M

The Fibonomial coefficients are well-known analogues of the classical binomial coefficients. In 2009, Sagan and Savage introduced a combinatorial interpretation for these coefficients, based on tiling a rectangular grid. More recently, Bergeron extended this work by providing a similar interpretation for the q-Fibonomial coefficients, using weighted tilings

Uyiosa Philip Amadasun, Patrick McNamee, Zahra Nili Ahmadabadi, Peiman Naseradinmousavi

In recent years, advancements have been made towards the goal of using chaotic coverage path planners for autonomous search and traversal of spaces with limited environmental cues. However, the state of this field is still in its infancy as there has been little experimental work done. The existing experimental works have not developed robust methods to sati

Tao Liu, Jing Ren, Chen Zhang

High-frequency gravitational waves (HFGWs) carry a wealth of information on the early Universe with a tiny comoving horizon and astronomical objects of small scale but with dense energy. We demonstrate that the nearby planets, such as Earth and Jupiter, can be utilized as a laboratory for detecting the HFGWs. These GWs are then expected to convert to signal

Varun Shankar, Shivam Barwey, Zico Kolter, Romit Maulik

Graph neural networks (GNNs) have shown promise in learning unstructured mesh-based simulations of physical systems, including fluid dynamics. In tandem, geometric deep learning principles have informed the development of equivariant architectures respecting underlying physical symmetries. However, the effect of rotational equivariance in modeling fluids rem

Fumihide Takeda

A megathrust earthquake genesis of 15 months with its tsunami genesis of the last 3 months provides a real-time disaster prevention warning and hazard mitigation measures leading up to the events.

Markus Löchtefeld

Great user experience is killing us (more or less)! My argument in this provocation is that the excessive focus on user experience (UX) by the tech industry and academic community has a negative impact on the sustainability of ICT devices. I will argue based on two examples, that we need new metrics or extend current UX metrics to also include third order ef

Paweł Niszczota, Paul Conway

The introduction of ChatGPT has fuelled a public debate on the use of generative AI (large language models; LLMs), including its use by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust and devalue researchers and scientific output. Participants (N=402) considered a researcher who dele

Masaki Isono, Hideyoshi Yanagisawa

Action-feedback delay during operation reduces both task performance and sense of agency (SoA). In this study, using information-theoretic free energy, we formalized a novel mathematical model for explaining the influence of delay on both task performance and SoA in continuous operations. Based on the mathematical model, we propose a novel interface design c

Malith Gallage, Rafaela Scaciota, Sumudu Samarakoon, Mehdi Bennis

This work presents a harmonic design of autonomous guided vehicle (AGV) control, edge intelligence, and human input to enable autonomous transportation in industrial environments. The AGV has the capability to navigate between a source and destinations and pick/place objects. The human input implicitly provides preferences of the destination and exact drop p

Ákos G. Horváth

In this paper, we investigate the configuration theorems of Desargues and Pappus in a synthetic geometric way. We provide a bridge between the two configurations with a third one that can be considered a specification for both. We do not use the theory of collineations or the analytic description of the plane over a ternary ring.

Zhenyu Piao, Miseul Kim, Hyungchan Yoon, Hong-Goo Kang

This report describes our submission to Task 2 of the Auditory EEG Decoding Challenge at ICASSP 2023 Signal Processing Grand Challenge (SPGC). Task 2 is a regression problem that focuses on reconstructing a speech envelope from an EEG signal. For the task, we propose a pre-layer normalized feed-forward transformer (FFT) architecture. For within-subjects gene

Ercan atam

For fair academic recruitment at universities and research institutions, determination of the right measure based on globally accepted academic quality features is a highly delicate, challenging, but quite important problem to be addressed. In a series of two papers, we consider the modeling part for academic quality quantification in the first paper, in thi

Daniel C. Hinck, Jonas J. Schöttler, Maria Krantz, Katharina-Sophie Isleif

The protection of non-combatants in times of (fully) autonomous warfare raises the question of the timeliness of the international protective emblem. Incidents in the recent past indicate that it is becoming necessary to transfer the protective emblem to other dimensions of transmission and representation. (Fully) Autonomous weapon systems are often launched

Samin Batra, Varun Sharma, Yurou Sun, Xinyao Wang

We aim to leverage the interactions between users and items in the Steam community to build a game recommendation system that makes personalized suggestions to players in order to boost Steam's revenue as well as improve the users' gaming experience. The whole project is built on Apache Spark and deals with Big Data. The final output of the project i

Xiong-Hui Chen, Bowei He, Yang Yu, Qingyang Li

Long-term user engagement (LTE) optimization in sequential recommender systems (SRS) is shown to be suited by reinforcement learning (RL) which finds a policy to maximize long-term rewards. Meanwhile, RL has its shortcomings, particularly requiring a large number of online samples for exploration, which is risky in real-world applications. One of the appeali

Vanitha Patnala, Salla Gangi Reddy, Shashi Prabhakar, R. P. Singh

Extracting the grain size from the microscopic images is a rigorous task involving much human expertise and manual effort. While calculating the grain size, we will be utilizing a finite number of particles which may lead to an uncertainty in the measurement. To avoid this difficulty, we utilize a simple mathematical tool, the auto-correlation function, to d

Mann Khatri, Pritish Wadhwa, Gitansh Satija, Reshma Sheik

In legal document writing, one of the key elements is properly citing the case laws and other sources to substantiate claims and arguments. Understanding the legal domain and identifying appropriate citation context or cite-worthy sentences are challenging tasks that demand expensive manual annotation. The presence of jargon, language semantics, and high dom

Beibei Liu, Yuanfang Zhang, Shiyu Zhang

We adopt the distribution and expectation of guessing times in game Wordle as metrics to predict the difficulty of words and explore their influence factors. In order to predictthe difficulty distribution, we use Monte Carlo to simulate the guessing process of players and then narrow the gap between raw and actual distribution of guessing times for each word

Davut Emre Tasar, Ceren Ocal Tasar

With the increasing use of cloud-based services for training and deploying machine learning models, data privacy has become a major concern. This is particularly important for natural language processing (NLP) models, which often process sensitive information such as personal communications and confidential documents. In this study, we propose a method for t