July 2023 arXiv papers — page 71

Shankar Bhamidi, Dhruv Patel, Vladas Pipiras, Guorong Wu

A dynamic factor model with a mixture distribution of the loadings is introduced and studied for multivariate, possibly high-dimensional time series. The correlation matrix of the model exhibits a block structure, reminiscent of correlation patterns for many real multivariate time series. A standard $k$-means algorithm on the loadings estimated through princ

Remy Cazabet, Catherine Annen, Jean-Francois Moyen, Roberto Weinberg

Magmas form at depth, move upwards and evolve chemically through a combination of processes. Magmatic processes are investigated by means of fieldwork combined with geophysics, geochemistry, analog and numerical models, and many other approaches. However, scientists in the field still struggle to understand how the variety of magmatic products arises, and th

Fatemeh Najafi, Masoud Kaveh, Mohammad Reza Mosavi, Alessandro Brighente

Physical unclonable functions (PUFs) are hardware-oriented primitives that exploit manufacturing variations to generate a unique identity for a physical system. Recent advancements showed how DRAM can be exploited to implement PUFs. DRAM PUFs require no additional circuits for PUF operations and can be used in most of the applications with resource-constrain

Jean-François Paquet

I present an overview of photon and dilepton production in heavy-ion collisions, highlighting recent progress and ongoing challenges, with focus on hard initial scatterings, pre-equilibrium electromagnetic emission, as well as thermal and hadronic production. The potential of photons and dileptons to probe low-energy collisions is discussed briefly.

Timothy H. Boyer

A charged particle which is allowed to accelerate must have relativistic behavior because it is coupled to electromagnetic radiation which propagates at the speed of light. We treat the simple steady-state situation of a charged particle moving in a circular orbit with counter-propagating plane waves providing the power which balances the energy radiated awa

Henrique Musseli Cezar, Caetano Rodrigues Miranda

Silica (SiO$_2$) nanotubes (NTs) are used in a wide range of applications that go from sensors to nanofluidics. Currently, these NTs can be grown with diameters as small as 3 nm, with walls 1.5 nm thick. Recent experimental advances combined with first-principles calculations suggest that silica NTs could be obtained from a single silica sheet. In this work,

Silverio Martínez-Fernández, Xavier Franch, Francisco Durán

Nowadays, AI-based systems have achieved outstanding results and have outperformed humans in different domains. However, the processes of training AI models and inferring from them require high computational resources, which pose a significant challenge in the current energy efficiency societal demand. To cope with this challenge, this research project paper

Paula Gherghinescu, Payel Das, Robert J. J. Grand, Matthew D. A. Orkney

In this work, we present an action-based dynamical equilibrium model to constrain the phase-space distribution of stars in the stellar halo, present-day dark matter distribution, and the total mass distribution in M31-like galaxies. The model comprises a three-component gravitational potential (stellar bulge, stellar disk, and a dark matter halo), and a doub

Zur Izhakian, Manfred Knebusch

Summand absorbing submodules are common in modules over (additively) idempotent semirings, for example, in tropical algebra. A submodule $W$ of $V$ is summand absorbing, if $x + y \in W$ implies $x \in W, \; y \in W $ for any $x, y \in V$. This paper proceeds the study of these submodules, and more generally of additive monoids, with emphasis on their archim

Jan van den Brand, Sebastian Forster, Yasamin Nazari, Adam Polak

We study dynamic algorithms in the model of algorithms with predictions. We assume the algorithm is given imperfect predictions regarding future updates, and we ask how such predictions can be used to improve the running time. This can be seen as a model interpolating between classic online and offline dynamic algorithms. Our results give smooth tradeoffs be

Gaëlle Bigeard, Alessandro Cresti

We investigate the effect of a magnetic field on the band structure of bilayer graphene with a magic twist angle of 1.08{\deg}. The coupling of a tight-binding model and the Peierls phase allows the calculation of the energy bands of periodic two-dimensional systems. For an orthogonal magnetic field, the Landau levels are dispersive, particularly for magneti

Nils Freyer, Dustin Thewes, Matthias Meinecke

Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized pr

Pavlos Sermpezis, Lars Prehn, Sofia Kostoglou, Marcel Flores

Network operators and researchers frequently use Internet measurement platforms (IMPs), such as RIPE Atlas, RIPE RIS, or RouteViews for, e.g., monitoring network performance, detecting routing events, topology discovery, or route optimization. To interpret the results of their measurements and avoid pitfalls or wrong generalizations, users must understand a

Igor N. Karnaukhov

The Kondo insulator (KI) is studyed in the frameworrk of one dimensional models of Kondo and symmentic Anderson lattices at half filling. The consistent application of the mean field approach and the solution using the Bethe ansatz made it possible to come close to solving the problem of the ground state of KI. It is shown, that in ${Z}_2$-field electrons an

Moritz Schäfer, Peter Heidrich, Thomas Götz

In this study, we present an integro-differential model to simulate the local spread of infections. The model incorporates a standard susceptible-infected-recovered (\textit{SIR}-) model enhanced by an integral kernel, allowing for non-homogeneous mixing between susceptibles and infectives. We define requirements for the kernel function and derive analytical

Mengda Xu, Zhenjia Xu, Cheng Chi, Manuela Veloso

Human demonstration videos are a widely available data source for robot learning and an intuitive user interface for expressing desired behavior. However, directly extracting reusable robot manipulation skills from unstructured human videos is challenging due to the big embodiment difference and unobserved action parameters. To bridge this embodiment gap, th

Shridhar Velhal, Suresh Sundaram, Narasimhan Sundararajan

In this paper, a Priority-based Dynamic REsource Allocation with decentralized Multi-task assignment (P-DREAM) approach is presented to protect a territory from highly manoeuvring intruders. In the first part, static optimization problems are formulated to compute the following parameters of the perimeter defense problem; the number of reserve stations, thei

Sarthak Satapathy

In this work we have presented the one-loop calculation of the bulk viscosity of a system of rotating, hot and dense spin 1/2 fermions within the framework of Kubo formalism calculated from correlation functions of fields which in turn is used to calculate the spectral function of energy-momentum tensors. The calculation has been done in curved space by the

Sioree Ansar, Sandeep K Kataria, Mousumi Das

Dark matter (DM) halo angular momentum is very challenging to determine from observations of galaxies. In this study, we present a new hybrid method of estimating the dimensionless halo angular momentum, halo spin of a gas-rich dwarf barred galaxy UGC5288 using N-Body/SPH simulations. We forward model the galaxy disk properties: stellar and gas mass, surface

Erik Voogd, Einar Broch Johnsen, Alexandra Silva, Zachary J. Susag

We present a new symbolic execution semantics of probabilistic programs that include observe statements and sampling from continuous distributions. Building on Kozen's seminal work, this symbolic semantics consists of a countable collection of measurable functions, along with a partition of the state space. We use the new semantics to provide a full correctn

Junjielong Xu, Ruichun Yang, Yintong Huo, Chengyu Zhang

Log parsing, which involves log template extraction from semi-structured logs to produce structured logs, is the first and the most critical step in automated log analysis. However, current log parsers suffer from limited effectiveness for two reasons. First, traditional data-driven log parsers solely rely on heuristics or handcrafted features designed by do

Balázs Gerencsér, Julien M. Hendrickx

We analyze the absolute spectral gap of Markov chains on graphs obtained from a cycle of $n$ vertices and perturbed only at approximately $n^{1/\rho}$ random locations with an appropriate, possibly sparse, interconnection structure. Together with a strong asymmetry along the cycle, the gap of the resulting chain can be bounded inversely proportionally by the

Gayatri Ghosh

We predict the low energy signatures of a Flipped $SU(5) \times U(1)_{\chi}$ effective local model , constructed within the framework of F$-$theory based on $ A_{4} $ symmetry. The Flipped SU(5) model from F Theory in the field of particle physics is prominent due to its ability to construct realistic four$-$dimensional theories from higher$-$dimensional com

Steven Landgraf, Markus Hillemann, Kira Wursthorn, Markus Ulrich

Deep neural networks have shown exceptional performance in various tasks, but their lack of robustness, reliability, and tendency to be overconfident pose challenges for their deployment in safety-critical applications like autonomous driving. In this regard, quantifying the uncertainty inherent to a model's prediction is a promising endeavour to address the

M. A. Cusentino, E. L. Sikorski, M. J. McCarthy, A. P. Thompson

A series of MD and DFT simulations were performed to investigate hydrogen self-clustering and retention in tungsten. Using a newly develop machine learned interatomic potential, spontaneous formation of hydrogen platelets was observed after implanting low-energy hydrogen into tungsten at high fluxes and temperatures. The platelets formed along low miller ind

Chul-Ung Woo, Jae Dong Noh

We introduce a Brownian $p$-state clock model in two dimensions and investigate the nature of phase transitions numerically. As a nonequilibrium extension of the equilibrium lattice model, the Brownian $p$-state clock model allows spins to diffuse randomly in the two-dimensional space of area $L^2$ under periodic boundary conditions. We find three distinct p

Miles Everett, Mingjun Zhong, Georgios Leontidis

Capsule Networks have emerged as a powerful class of deep learning architectures, known for robust performance with relatively few parameters compared to Convolutional Neural Networks (CNNs). However, their inherent efficiency is often overshadowed by their slow, iterative routing mechanisms which establish connections between Capsule layers, posing computat

Mayank Pandey, Maksym Radziwiłł

We show that the $L^1$ norm of an exponential sum of length $X$ and with coefficients equal to the Liouville or M\"{o}bius function is at least $\gg_{\varepsilon} X^{1/4 - \varepsilon}$ for any given $\varepsilon$. For the Liouville function this improves on the lower bound $\gg X^{c/\log\log X}$ due to Balog and Perelli (1998). For the M\"{o}bius function t

Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo

Recommender systems are a ubiquitous feature of online platforms. Increasingly, they are explicitly tasked with increasing users' long-term satisfaction. In this context, we study a content exploration task, which we formalize as a multi-armed bandit problem with delayed rewards. We observe that there is an apparent trade-off in choosing the learning signal:

Brandon Theodorou, Cao Xiao, Jimeng Sun

Clinical trials are critical for drug development but often suffer from expensive and inefficient patient recruitment. In recent years, machine learning models have been proposed for speeding up patient recruitment via automatically matching patients with clinical trials based on longitudinal patient electronic health records (EHR) data and eligibility crite

Giovanni Pierobon, Javier Redondo, Ken'ichi Saikawa, Alejandro Vaquero

The properties of axion miniclusters and of the voids between them can have very strong implications for the discovery of axions and the dark matter of the Universe. These properties can be strongly affected by axion dynamics in the early Universe, such as the axion string network and the non-linear dynamics around the QCD phase transition. Recently, improve

Luiz Renato Fontes, Fabio P. Machado, Rinaldo B. Schinazi

We introduce the following model for the evolution of a population. At every discrete time $j\geq 0$ exactly one individual is introduced in the population and is assigned a death probability $c_j$ sampled from $C$, a fixed probability distribution. We think of $c_j$ as a genetic marker of this individual. At every time $n\geq 1$ every individual in the popu

Jaume Alonso, Yuri B. Suris, Kangning Wei

The goal of this paper is the exact computation of the degrees $\text{deg}(f^n)$ of the iterates of birational maps $f: \mathbb{P}^N \dashrightarrow \mathbb{P}^N$. In the preceding companion paper, a new method has been proposed based on the use of indices of polynomials associated to the local blow-ups used to resolve contractions of hypersurfaces by $f$, a

Harsha M., Gurpreet Singh, Vinod Kumar, Arun Balaji Buduru

With the sustained rise in satellite deployment in Low Earth Orbits, the collision risk from untracked space debris is also increasing. Often small-sized space debris (below 10 cm) are hard to track using the existing state-of-the-art methods. However, knowing such space debris' trajectory is crucial to avoid future collisions. We present a Physics Informed

Gabriele Pasquale, Edoardo Lopriore, Zhe Sun, Kristiāns Čerņevičs

Two-dimensional flat-band systems have recently attracted considerable interest due to the rich physics unveiled by emergent phenomena and correlated electronic states at van Hove singularities. However, the difficulties in electrically detecting the flat band position in field-effect structures are slowing down the investigation of their properties. In this

Pedro Gomes, Silvia Rossi, Laura Toni

This paper focuses on motion prediction for point cloud sequences in the challenging case of deformable 3D objects, such as human body motion. First, we investigate the challenges caused by deformable shapes and complex motions present in this type of representation, with the ultimate goal of understanding the technical limitations of state-of-the-art models

Lukas Grunwald, Giacomo Passetti, Dante M. Kennes

We investigate the dynamical onset of superconductivity in the exactly solvable Yukawa-Sachdev-Ye-Kitaev model. It hosts an unconventional superconducting phase that emerges out of a non-Fermi liquid normal state, providing a toy model for superconductivity in a strongly correlated system. Analyzing dynamical protocols motivated by theoretical mechanisms pro

Paolo Bartesaghi, Gian Paolo Clemente, Rosanna Grassi

We propose a new paradigm to design a network-based self-adaptive epidemic model that relies on the interplay between the network and its line graph. We implement this proposal on a Susceptible-Infected-Susceptible model in which both nodes and edges are considered susceptible and their respective probabilities of being infected result in a real-time re-modu

Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica

To avoid failures on out-of-distribution data, recent works have sought to extract features that have an invariant or stable relationship with the label across domains, discarding "spurious" or unstable features whose relationship with the label changes across domains. However, unstable features often carry complementary information that could boost performa

Tetsu Mizumachi

The KP-II equation was derived by Kadomtsev and Petviashvili to explain stability of line solitary waves of shallow water. Using the Darboux transformations, we study linear stability of 2-line solitons whose line solitons interact elastically each other. Time evolution of resonant continuous eigenfunctions is described by a damped wave equation in the trans

Matteo Ronchetti, Wolfgang Wein, Nassir Navab, Oliver Zettinig

Multimodal image registration is a challenging but essential step for numerous image-guided procedures. Most registration algorithms rely on the computation of complex, frequently non-differentiable similarity metrics to deal with the appearance discrepancy of anatomical structures between imaging modalities. Recent Machine Learning based approaches are limi

N. Krane, E. Turco, A. Bernhardt, D. Jacob

Phenalenyl is a radical nanographene with triangular shape that hosts an unpaired electron with spin S = 1/2. The open-shell nature of phenalenyl is expected to be retained in covalently bonded networks. Here, we study a first step in that direction and report the synthesis of the phenalenyl dimer by combining in-solution synthesis and on-surface activation

Mochu Xiang, Jing Zhang, Nick Barnes, Yuchao Dai

Effectively measuring and modeling the reliability of a trained model is essential to the real-world deployment of monocular depth estimation (MDE) models. However, the intrinsic ill-posedness and ordinal-sensitive nature of MDE pose major challenges to the estimation of uncertainty degree of the trained models. On the one hand, utilizing current uncertainty

Qiao-Qiao Lv, Jin-Min Liang, Zhi-Xi Wang, Shao-Ming Fei

The recycling of quantum correlations has attracted widespread attention both theoretically and experimentally. Previous works show that bilateral sharing of nonlocality is impossible under mild measurement strategy and 2-qubit entangled state can be used to witness entanglement arbitrary many times by sequential and independent pairs of observers. However,

I. S. Rakhimov

A complete classifications, up to isomorphism, of two-dimensional associative and diassociative algebras over any basic field are given.

A. Bouzenada, A. Boumali, O. Mustafa, RLL. Vetoria

In this contribution, the relativistic quantum motions of the position-dependent mass (PDM) oscillator field with a scalar potential in the context of the Kaluza-Klein theory is investigated. Through a purely analytical analysis, the eigensolutions of this system have been obtained. The results showed that the KGO is influenced not only by curvature, torsion

William T. Dugan, Maura Hegarty, Alejandro H. Morales, Annie Raymond

In 1999, Pitman and Stanley introduced the polytope bearing their name along with a study of its faces, lattice points, and volume. The Pitman-Stanley polytope is well-studied due to its connections to probability, parking functions, the generalized permutahedra, and flow polytopes. Its lattice points correspond to plane partitions of skew shape with entries

Youssef Diouane, Vyacheslav Kungurtsev, Francesco Rinaldi, Damiano Zeffiro

In this work, we introduce new direct search schemes for the solution of bilevel optimization (BO) problems. Our methods rely on a fixed accuracy black box oracle for the lower-level problem, and deal both with smooth and potentially nonsmooth true objectives. We thus analyze for the first time in the literature direct search schemes in these settings, givin

Michael Grohs, Luka Abb, Nourhan Elsayed, Jana-Rebecca Rehse

Business Process Management (BPM) aims to improve organizational activities and their outcomes by managing the underlying processes. To achieve this, it is often necessary to consider information from various sources, including unstructured textual documents. Therefore, researchers have developed several BPM-specific solutions that extract information from t

Josh A. Taylor

The converters in an AC/DC grid form actuated boundaries between the AC and DC subgrids. We show how in both simple linear and balanced dq-frame models, the states on either side of these boundaries are coupled only by control inputs. This topological property imparts all AC/DC grids with poset-causal information structures. A practical benefit is that certa

A. Ya. Muratidi, F. S. Stonyakin

The paper considers approaches to saddle point problems with a two-sided variant of the Polyak-Lojasievich condition based on the gradient method with inexact information and proposes a stopping rule based on the smallness of the norm of the inexact gradient of the external subproblem. Achieving this rule in combination with a suitable accuracy of solving th

Lucien Hennecart

In this paper, we complete the nonabelian Hodge theory (NAHT) triangle of isomorphisms for stacks between the Borel-Moore homologies of the Dolbeault, Betti, and de Rham moduli stacks. We first explain how to realise the category of connections on a smooth projective curve as a subcategory of a $2$-Calabi-Yau dg-category satisfying some appropriate geometric

Borbala Gerhat, David Krejcirik, Frantisek Stampach

We study the criticality and subcriticality of powers $(-\Delta)^\alpha$ with $\alpha>0$ of the discrete Laplacian $-\Delta$ acting on $\ell^2(\mathbb{N})$. We prove that these positive powers of the Laplacian are critical if and only if $\alpha \ge 3/2$. We complement our analysis with Hardy type inequalities for $(-\Delta)^\alpha$ in the subcritical regime

Peter Jose, Said Jawad Saidi, Oliver Gasser

Users and businesses are increasingly deploying Internet of Things (IoT) devices at home, at work, and in factories. At the same time, we see an increase in the use of IPv6 for Internet connectivity. Even though the IoT ecosystem has been the focus of recent studies, there is no comprehensive analysis of IoT end-hosts in the IPv6 Internet to date. In this pa

G. Angloher, S. Banik, G. Benato, A. Bento

Using CaWO$_4$ crystals as cryogenic calorimeters, the CRESST experiment searches for nuclear recoils caused by the scattering of potential Dark Matter particles. A reliable identification of a potential signal crucially depends on an accurate background model. In this work we introduce an improved normalisation method for CRESST's model of the electromagnet

Long Li, Shu-Qing Zhong, Zi-Gao Dai

Whether binary neutron star mergers are the only astrophysical site of rapid neutron-capture process ($r$-process) nucleosynthesis remains unknown. Collapsars associated with long gamma-ray bursts (GRBs) and hypernovae are promising candidates. Simulations have shown that outflows from collapsar accretion disks can produce enough $r$-process materials to exp

Jianing Hao, Qing Shi, Yilin Ye, Wei Zeng

Deep learning (DL) approaches are being increasingly used for time-series forecasting, with many efforts devoted to designing complex DL models. Recent studies have shown that the DL success is often attributed to effective data representations, fostering the fields of feature engineering and representation learning. However, automated approaches for feature

Zijie Song, Zhenzhen Hu, Yuanen Zhou, Ye Zhao

Cross-lingual image captioning is a challenging task that requires addressing both cross-lingual and cross-modal obstacles in multimedia analysis. The crucial issue in this task is to model the global and the local matching between the image and different languages. Existing cross-modal embedding methods based on the transformer architecture oversee the loca

Uwe Hohm, Christoph Schiller

Experimental and theoretical results about entropy limits for macroscopic and single-particle systems are reviewed. It is clarified when it is possible to speak about a quantum of entropy, given by the Boltzmann constant k, and about a lower entropy limit $S \geq k \ln 2$. Conceptual tensions with the third law of thermodynamics and the additivity of entropy

Bartosz Bednarczyk

We investigate the impact of non-regular path expressions on the decidability of satisfiability checking and querying in description logics extending ALC. Our primary objects of interest are ALCreg and ALCvpl, the extensions of with path expressions employing, respectively, regular and visibly-pushdown languages. The first one, ALCreg, is a notational varian

Abubakr S. Issa, Yossra H. Ali, Tarik A. Rashid

A lately created metaheuristic algorithm called Child Drawing Development Optimization (CDDO) has proven to be effective in a number of benchmark tests. A Binary Child Drawing Development Optimization (BCDDO) is suggested for choosing the wrapper features in this study. To achieve the best classification accuracy, a subset of crucial features is selected usi

Vladimir R. Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici

We consider the general class of time-homogeneous stochastic dynamical systems, both discrete and continuous, and study the problem of learning a representation of the state that faithfully captures its dynamics. This is instrumental to learning the transfer operator or the generator of the system, which in turn can be used for numerous tasks, such as foreca

Remco van der Hofstad

We study competition on scale-free random graphs, where the degree distribution satisfies an asymptotic power-law with infinite variance. Our competition process is such that the two types attempt at occupying vertices incident to the presently occupied sets, and the passage times are independent and identically distributed, possibly with different distribut

Alessandra Aimi, Giulia Di Credico, Heiko Gimperlein

This article proposes a boundary element method for the dynamic contact between a linearly elastic body and a rigid obstacle. The Signorini contact problem is formulated as a variational inequality for the Poincar\'{e}-Steklov operator for the elastodynamic equations on the boundary, which is solved in a mixed formulation using boundary elements in the time

Urszula Jessen, Michal Sroka, Dirk Fahland

This research investigates the application of Large Language Models (LLMs) to augment conversational agents in process mining, aiming to tackle its inherent complexity and diverse skill requirements. While LLM advancements present novel opportunities for conversational process mining, generating efficient outputs is still a hurdle. We propose an innovative a

Mahmood Yashar, Tarik A. Rashid

This study presents the vectorization of metaheuristic algorithms as the first stage of vectorized optimization implementation. Vectorization is a technique for converting an algorithm, which operates on a single value at a time to one that operates on a collection of values at a time to execute rapidly. The vectorization technique also operates by replacing

Saikat Santra, Prashant Singh, Anupam Kundu

We investigate the dynamics of tracer particles in the random average process (RAP), a single-file system in one dimension. In addition to the position, every particle possesses an internal spin variable $\sigma (t)$ that can alternate between two values, $\pm 1$, at a constant rate $\gamma$. Physically, the value of $\sigma (t)$ dictates the direction of mo

G. Valori, D. Calchetti, A. Moreno Vacas, É. Pariat

Spectropolarimetric reconstructions of the photospheric vector magnetic field are intrinsically limited by the 180$^\circ$-ambiguity in the orientation of the transverse component. So far, the removal of such an ambiguity has required assumptions about the properties of the photospheric field, which makes disambiguation methods model-dependent. The basic ide

Fa-Ting Hong, Dan Xu

Talking head video generation aims to animate a human face in a still image with dynamic poses and expressions using motion information derived from a target-driving video, while maintaining the person's identity in the source image. However, dramatic and complex motions in the driving video cause ambiguous generation, because the still source image cannot p

Martin Balla, George E. M. Long, Dominik Jeurissen, James Goodman

In recent years, Game AI research has made important breakthroughs using Reinforcement Learning (RL). Despite this, RL for modern tabletop games has gained little to no attention, even when they offer a range of unique challenges compared to video games. To bridge this gap, we introduce PyTAG, a Python API for interacting with the Tabletop Games framework (T

Christine Ruey Shan Lee

We show the $n$ colored Jones polynomials of a highly twisted link approach the Kauffman bracket of an $n$ colored skein element. This is in the sense that the corresponding categorifications of the colored Jones polynomials approach the categorification of the Kauffman bracket of the skein element in a direct limit, as the number of full twists of each twis

Nahid Binandeh Dehaghani, A. Pedro Aguiar, Rafal Wisniewski

This chapter provides an in-depth analysis of the properties and phenomena associated with neutral K-mesons. Kaons are quantum systems illustrating strange behaviours. We begin by examining the significance of strangeness and charge parity violation in understanding these particles. The concept of strangeness oscillations is then introduced, explaining oscil

Tianping Chen

In this short paper, we explore relationship between various models of complex networks with pinning controllers.

Dibyajyoti Mallick, Priya Chakraborty, Sayantari Ghosh

With the advancement of information technology, more people, especially young adults, are getting addicted to the use of different social media platforms. Despite immense useful applications in communication and interactions, the habit of spending excessive time on these social media platforms is becoming addictive, causing different consequences, like anxie

Vinicius Mariano Goncalves, Prashanth Krishnamurthy, Anthony Tzes, Farshad Khorrami

Control Barrier Functions and Quadratic Programming are increasingly used for designing controllers that consider critical safety constraints. However, like Artificial Potential Fields, they can suffer from the stable spurious equilibrium point problem, which can result in the controller failing to reach the goal. To address this issue, we propose introducin

Jun Wang, Wan-Ting He, Hai-Bo Wang, Qing Ai

The nonadiabatic holonomic quantum computation based on the geometric phase is robust against the built-in noise and decoherence. In this work, we theoretically propose a scheme to realize nonadiabatic holonomic quantum gates in a surface electron system, which is a promising two-dimensional platform for quantum computation. The holonomic gate is realized by

Mario Hubert

This paper investigates the historical origin and ancestors of typicality, which is now a central concept in Boltzmannian Statistical Mechanics and Bohmian Mechanics. Although Ludwig Boltzmann did not use the word typicality, its main idea, namely, that something happens almost always or is valid for almost all cases, plays a crucial role for his explanation

Adriana Stan, Johannah O'Mahony

In this paper we introduce a first attempt on understanding how a non-autoregressive factorised multi-speaker speech synthesis architecture exploits the information present in different speaker embedding sets. We analyse if jointly learning the representations, and initialising them from pretrained models determine any quality improvements for target speaker

Gianluca Cassese

We obtain an elementary characterization of expected utility based on a representation of choice in terms of psychological gambles, which requires no assumption other than coherence between ex-ante and ex-post preferences. Weaker version of coherence are associated with various attitudes towards complexity and lead to a characterization of minimax or Choquet

Metodi P. Yankov, Ognjen Jovanovic, Darko Zibar, Francesco Da Ros

A many-to-one mapping geometric constellation shaping scheme is proposed with a fixed modulation format, fixed FEC engine and rate adaptation with an arbitrarily small step. An autoencoder is used to optimize the labelings and constellation points' positions.

Hüseyin Afşer, László Györfi, Harro Walk

We study the problem nonparametric classification with repeated observations. Let $\bX$ be the $d$ dimensional feature vector and let $Y$ denote the label taking values in $\{1,\dots ,M\}$. In contrast to usual setup with large sample size $n$ and relatively low dimension $d$, this paper deals with the situation, when instead of observing a single feature ve

S. Arati, P. Devaraj

In this paper, we analyse the circumstances in which the adjoint Gabor system is an R-dual of a given Gabor frame in the context of separable uniform time-frequency lattices in locally compact abelian groups. In this regard, we also prove a necessary condition for a Gabor Bessel sequence in this setting to be complete.

Saad Manzur, Wayne Hayes

Existing 2D-to-3D pose lifting networks suffer from poor performance in cross-dataset benchmarks. Although the use of 2D keypoints joined by "stick-figure" limbs has shown promise as an intermediate step, stick-figures do not account for occlusion information that is often inherent in an image. In this paper, we propose a novel representation using opaque 3D

Hao Su, Xuefeng Liu, Jianwei Niu, Ji Wan

We propose 3Deformer, a general-purpose framework for interactive 3D shape editing. Given a source 3D mesh with semantic materials, and a user-specified semantic image, 3Deformer can accurately edit the source mesh following the shape guidance of the semantic image, while preserving the source topology as rigid as possible. Recent studies of 3D shape editing

Antti Keurulainen, Isak Westerlund, Oskar Keurulainen, Andrew Howes

Item Response Theory (IRT) is a well known method for assessing responses from humans in education and psychology. In education, IRT is used to infer student abilities and characteristics of test items from student responses. Interactions with students are expensive, calling for methods that efficiently gather information for inferring student abilities. Met

David T. S. Perkins, Aires Ferreira

We propose how to create, control, and read-out real-space localized spin qubits in proximitized finite graphene nanoribbon (GNR) systems using purely electrical methods. Our proposed nano-qubits are formed of in-gap singlet-triplet states that emerge through the interplay of Coulomb and relativistic spin-dependent interactions in GNRs placed on a magnetic s

P G Romeo, Riya Jose

In this paper we illustrate the rule for finding number of idempotents in the doubly stochastic matrix $D_n$ and also locate the idempotents for the semigroups $D_3$ and $D_4$. Further describe idempotent generated ideals of these semigroups and it is shown that these idempotent generated ideals form lattices.

Agnieszka Bodzenta, Will Donovan

For an effective Cartier divisor D on a scheme X we may form an nth root stack. Its derived category is known to have a semiorthogonal decomposition with components given by D and X. We show that this decomposition is 2n-periodic. For n=2 this gives a purely triangulated proof of the existence of a known spherical functor, namely the pushforward along the em

Haotian Xue, Youssef Michel, Dongheui Lee

In this paper, we present a novel learning-based shared control framework. This framework deploys first-order Dynamical Systems (DS) as motion generators providing the desired reference motion, and a Variable Stiffness Dynamical Systems (VSDS) \cite{chen2021closed} for haptic guidance. We show how to shape several features of our controller in order to achie

Tatiana Fountoukidou, Raphael Sznitman

Recent advances in machine learning models have greatly increased the performance of automated methods in medical image analysis. However, the internal functioning of such models is largely hidden, which hinders their integration in clinical practice. Explainability and trust are viewed as important aspects of modern methods, for the latter's widespread use

Dawen Zhang, Thong Hoang, Shidong Pan, Yongquan Hu

Language tests measure a person's ability to use a language in terms of listening, speaking, reading, or writing. Such tests play an integral role in academic, professional, and immigration domains, with entities such as educational institutions, professional accreditation bodies, and governments using them to assess candidate language proficiency. Recent ad

Yu. B. Kudasov

Two theorems on electron states in helimagnets are proved. They reveal a Kramers-like degeneracy in helical magnetic field. Since a commensurate helical magnetic system is transitionally invariant with two multiple periods (ordinary translations and generalized ones with rotations), the band structure turns out to be topologically nontrivial. Together with t

Boris Flach, Dmitrij Schlesinger, Alexander Shekhovtsov

We view variational autoencoders (VAE) as decoder-encoder pairs, which map distributions in the data space to distributions in the latent space and vice versa. The standard learning approach for VAEs is the maximisation of the evidence lower bound (ELBO). It is asymmetric in that it aims at learning a latent variable model while using the encoder as an auxil

Omri Ben-Dov, Pravir Singh Gupta, Victoria Abrevaya, Michael J. Black

Generative Adversarial Networks (GANs) can produce high-quality samples, but do not provide an estimate of the probability density around the samples. However, it has been noted that maximizing the log-likelihood within an energy-based setting can lead to an adversarial framework where the discriminator provides unnormalized density (often called energy). We

Sergey K. Ivanov, Yaroslav V. Kartashov

We study the existence and stability of $\pi$-solitons on a ring of periodically oscillating waveguides. The array is arranged into Su-Schrieffer-Heeger structure placed on a ring, with additional spacing between two ends of the array. Due to longitudinal oscillations of waveguides, this Floquet structure spends half of the longitudinal period in topological

Liekang Zeng, Haowei Chen, Daipeng Feng, Xiaoxi Zhang

Accurate navigation is of paramount importance to ensure flight safety and efficiency for autonomous drones. Recent research starts to use Deep Neural Networks to enhance drone navigation given their remarkable predictive capability for visual perception. However, existing solutions either run DNN inference tasks on drones in situ, impeded by the limited onb

Haifeng Zou, Xiaowen Xu, Chen-Song Zhang, Zeyao Mo

Algebraic Multigrid (AMG) is one of the most used iterative algorithms for solving large sparse linear equations $Ax=b$. In AMG, the coarse grid is a key component that affects the efficiency of the algorithm, the construction of which relies on the strong threshold parameter $\theta$. This parameter is generally chosen empirically, with a default value in m

Antti Keurulainen, Isak Westerlund, Oskar Keurulainen, Andrew Howes

User models play an important role in interaction design, supporting automation of interaction design choices. In order to do so, model parameters must be estimated from user data. While very large amounts of user data are sometimes required, recent research has shown how experiments can be designed so as to gather data and infer parameters as efficiently as

Paul G Morris, Joseph D. Taylor, Julian F. R. Paton, Alain Nogaret

Many neurological diseases originate in the dysfunction of cellular ion channels. Their diagnosis presents a challenge especially when alterations in the complement of ion channels are a priori unknown. Current approaches based on voltage clamps lack the throughput necessary to identify the mutations causing changes in electrical activity. Here, we introduce

Tarun Tummuru, Anffany Chen, Patrick M. Lenggenhager, Titus Neupert

We extend the notion of topologically protected semi-metallic band crossings to hyperbolic lattices in a negatively curved plane. Because of their distinct translation group structure, such lattices are associated with a high-dimensional reciprocal space. In addition, they support non-Abelian Bloch states which, unlike conventional Bloch states, acquire a ma