April 2023 arXiv papers — page 2

Zihan Zhou, Animesh Garg

We propose Structured Exploration with Achievements (SEA), a multi-stage reinforcement learning algorithm designed for achievement-based environments, a particular type of environment with an internal achievement set. SEA first uses offline data to learn a representation of the known achievements with a determinant loss function, then recovers the dependency

Xiaozhu Yu, Xinyang Wang

In this study, we investigate the mass spectrum of $\pi$ and $\sigma$ mesons at finite chemical potential using the self-consistent NJL model and the Fierz-transformed interaction Lagrangian. The model introduces an arbitrary parameter $\alpha$ to reflect the weights of the Fierz-transformed interaction channels. We show that when $\alpha$ exceeds a certain

Emad Alamoudi, Felipe Reck, Nils Bundgaard, Frederik Graw

Approximate Bayesian Computation (ABC) is a widely applicable and popular approach to estimating unknown parameters of mechanistic models. As ABC analyses are computationally expensive, parallelization on high-performance infrastructure is often necessary. However, the existing parallelization strategies leave resources unused at times and thus do not optima

Chaoqun Guo, Jiangping Hu, Jiasheng Hao, Sergej Celikovsky

In this paper, a fixed-time safe control problem is investigated for an uncertain high-order nonlinear pure-feedback system with state constraints. A new nonlinear transformation function is firstly proposed to handle both the constrained and unconstrained cases in a unified way. Further, a radial basis function neural network is constructed to approximate t

Jiali Wang, Yijie Mao, Ting Wang, Yuanming Shi

In this paper, we propose an energy-efficient federated learning (FL) framework for the energy-constrained devices over cloud radio access network (Cloud-RAN), where each device adopts quantized neural networks (QNNs) to train a local FL model and transmits the quantized model parameter to the remote radio heads (RRHs). Each RRH receives the signals from dev

Anna M. Limbach, Martin Winter

The clique graph $kG$ of a graph $G$ has as its vertices the cliques (maximal complete subgraphs) of $G$, two of which are adjacent in $kG$ if they have non-empty intersection in $G$. We say that $G$ is clique convergent if $k^nG\cong k^m G$ for some $n\not= m$, and that $G$ is clique divergent otherwise. We completely characterise the clique convergent grap

D. Radić, L. Y. Gorelik, S. I. Kulinich, R. I. Shekhter

We suggest a nanoelectromechanical setup and corresponding time protocol of its manipulation by which we transduce quantum information from charge qubit to nanomechanical cat state. The setup is based on the AC Josephson effect between bulk superconductors and mechanically vibrating mesoscopic superconducting island in the regime of the Cooper pair box. Star

Stephane Geudens, Alfonso G. Tortorella, Marco Zambon

In the companion paper arXiv:2110.05298, we developed the deformation theory of symplectic foliations, focusing on geometric aspects. Here, we address some algebraic questions that arose naturally. We show that the $L_{\infty}$-algebra constructed there is independent of the choices made, and we prove that the gauge equivalence of Maurer-Cartan elements corr

W. Arendt, I. Chalendar, B. Moletsane

The following version of the Lumer-Phillips is proved: a surjective dissipative operator is m-dissipative and invertible. The result remains true if dissipative linear relations (i.e multivalued operators) are considered. The main purpose of this article is to study relations which generate semigroups. We consider m-dissipative relations and also the holomor

Gabriel Cuomo, J. M. Viana Parente Lopes, José Matos, Júlio Oliveira

We perform Monte-Carlo measurements of two and three point functions of charged operators in the critical O(2) model in 3 dimensions. Our results are compatible with the predictions of the large charge superfluid effective field theory. To obtain reliable measurements for large values of the charge, we improved the Worm algorithm and devised a measurement sc

Qinghu Hou, Haihong He, Xiaoxia Wang

By applying the derivative operator to the known identities from hypergeometric series or WZ pairs, we obtain seven series associated with harmonic numbers. Specifically, six of them are Ramanujan-like formulas for $1/\pi$ and the remaining onecontains harmonic numbers of order $2$. As conclusions, Sun's five conjectural series are proved.

S. Navarro-Obregón, L. M. Nieto, J. M. Queiruga

We present an effective Lagrangian for the $\phi^4$ model that includes radiation modes as collective coordinates. The coupling between these modes to the discrete part of the spectrum, i.e., the zero mode and the shape mode, gives rise to different phenomena which can be understood in a simple way in our approach. In particular, the energy transfer between

Y. B. Shi, Z. Song

Exact solutions for non-Hermitian quantum many-body systems are rare but may provide valuable insights into the interplay between Hermitian and non-Hermitian components. We report our investigation of a non-Hermitian variant of a p-wave Kitaev chain by introducing staggered imbalanced pair creation and annihilation terms. We find that there exists a fixed li

Olena Atlasiuk, Vladimir Mikhailets

We study linear systems of ordinary differential equations of an arbitrary order on a finite interval with the most general (generic) inhomogeneous boundary conditions in Sobolev spaces. We investigate the character of solvability of inhomogeneous boundary-value problems, prove their Fredholm properties, and find the indices, the dimensions of the kernel, an

Zhenan Sui, Wei Sun

In this paper, we study the interior gradient estimates for admissible solutions to prescribed curvature equations in hyperbolic space.

Dipankar Basak, Kalyan Dey

The deep learning technique has been applied for the first time to investigate the possibility of centrality determination in terms of the number of participants ($N_{\mathrm{part}}$) in high-energy heavy-ion collisions. For this purpose, supervised learning using both deep neural network (DNN) and convolutional neural network (CNN) is performed with labeled

Onur Mutlu, Can Firtina

High-throughput sequencing (HTS) technologies have revolutionized the field of genomics, enabling rapid and cost-effective genome analysis for various applications. However, the increasing volume of genomic data generated by HTS technologies presents significant challenges for computational techniques to effectively analyze genomes. To address these challeng

Kristoffer Reinholt Thomsen, Steen Rasmussen

In recent years, studies in epigenetic inheritance in biological systems as well as studies on evolution in non-biological systems e.g., machine learning and robotics, have reopened the discussion of non-Darwinian methods of evolutionary optimization. In this paper, the three most prominent classical evolutionary strategies Lamarckian, Darwinian, and Baldwin

Everton Cavalcante, Jean Spinelly

In this paper, we investigate a rotating fullerene molecule with Ih symmetry within the framework of non-inertial spacetimes. We use a low-energy geometric theory to describe the molecule as a two-dimensional spherical space of G\"odel type. Using the well-known fictitious `t Hooft Polyakov monopole to decouple the doublet associated with the lattice, we emp

Kedeng Tong, Xin Jin, Yuqing Yang, Chen Wang

Focused plenoptic cameras can record spatial and angular information of the light field (LF) simultaneously with higher spatial resolution relative to traditional plenoptic cameras, which facilitate various applications in computer vision. However, the existing plenoptic image compression methods present ineffectiveness to the captured images due to the comp

Yifan Sun, Pedro Parra-Rivas, Mario Ferraro, Fabio Mangini

By means of a modified Lugiato-Lefever equation model, we investigate the nonlinear dynamics of dissipative wave structures in coherently-driven Kerr cavities with a parabolic potential. The potential stabilizes system dynamics, leading to the generation of robust dissipative solitons in the positive detuning regime, and of higher-order solitons in the negat

G. Nandakumar, N. Ryde, L. Casagrande, G. Mace

Cool stars, such as M giants, can only be analysed in the near-infrared (NIR) regime due to the ubiquitous TiO features in optical spectra of stars with Teff < 4000 K. In dust obscured regions, like the inner bulge and Galactic Center, the intrinsically bright M giants observed in the NIR is an optimal option to determine their stellar abundances. Due to unc

John Urschel

We prove that every element of the special linear group can be represented as the product of at most six block unitriangular matrices, and that there exist matrices for which six products are necessary, independent of indexing. We present an analogous result for the general linear group. These results serve as general statements regarding the representationa

Hamza Ruzayqat, Alexandros Beskos, Dan Crisan, Ajay Jasra

We consider a class of high-dimensional spatial filtering problems, where the spatial locations of observations are unknown and driven by the partially observed hidden signal. This problem is exceptionally challenging as not only is high-dimensional, but the model for the signal yields longer-range time dependencies through the observation locations. Motivat

Teng Xiang, Xiao-Dong Shi, Da-Yong Wang, Xiao-Rong Zhou

A sensitivity study for the search for the charged lepton flavor violating process $\tau \to \gamma\mu$ at the Super $\tau$-Charm Facility is performed with a fast simulation. With the expected performance of the current detector design and an integrated luminosity of \SI{1}{ab^{-1}} corresponding to one-year of data taking, the sensitivity on the branching

Georgii Mikriukov, Gesina Schwalbe, Christian Hellert, Korinna Bade

Safety-critical applications require transparency in artificial intelligence (AI) components, but widely used convolutional neural networks (CNNs) widely used for perception tasks lack inherent interpretability. Hence, insights into what CNNs have learned are primarily based on performance metrics, because these allow, e.g., for cross-architecture CNN compar

Zhonghua Li, Shukun Wang

As Hopf truss analogues of Rota-Baxter Hopf algebras, the notion of Rota-Baxter systems of Hopf algebras is proposed. We study the relatiohship between Rota-Baxter systems of Hopf algebras and Rota-Baxter Hopf algebras, show that there is a Rota-Baxter system structure on the group algebra if the group has a Rota-Baxter system structure, investigate the desc

Alexandros Banis, Andrea Gomez, Vitaliy Bliznuk, Aniruddha Dutta

This study focuses on the microstructure's evolution upon different aging conditions of a high-strength low-density steel with a composition of Fe-28Mn-9Al-1C. The steel is hot-rolled, subsequently quenched without any solution treatment, and then aged under different conditions. The microstructure of the samples was studied by means of Scanning Electron Mic

Arijit Manna, Sabyasachi Pal

In the interstellar medium (ISM), the complex organic molecules that contain the thiol group ($-$SH) play an important role in the polymerization of amino acids. We look for SH-bearing molecules in the chemically rich solar-type protostar IRAS 16293-2422. After the extensive spectral analysis using the local thermodynamic equilibrium (LTE) model, we have det

Dylan Langharst, Eli Putterman, Michael Roysdon, Deping Ye

For a convex body $K$ in $\mathbb R^n$, the inequalities of Rogers-Shephard and Zhang, written succinctly, are $$\text{vol}_n(DK)\leq \binom{2n}{n} \text{vol}_n(K) \leq \text{vol}_n(n\text{vol}_n(K)\Pi^\circ K).$$ Here, $DK=\{x\in\mathbb R^n:K\cap(K+x)\neq \emptyset\}$ is the difference body of $K$, and $\Pi^\circ K$ is the polar projection body of $K$. Ther

Ning Liu, Siavash Jafarzadeh, Yue Yu

Fourier neural operators (FNOs) can learn highly nonlinear mappings between function spaces, and have recently become a popular tool for learning responses of complex physical systems. However, to achieve good accuracy and efficiency, FNOs rely on the Fast Fourier transform (FFT), which is restricted to modeling problems on rectangular domains. To lift such

Giovanni Parmigiani

In this article I propose an approach for defining replicability for prediction rules. Motivated by a recent NAS report, I start from the perspective that replicability is obtaining consistent results across studies suitable to address the same prediction question, each of which has obtained its own data. I then discuss concept and issues in defining key ele

Remo Sasso, Michelangelo Conserva, Paulo Rauber

Despite remarkable successes, deep reinforcement learning algorithms remain sample inefficient: they require an enormous amount of trial and error to find good policies. Model-based algorithms promise sample efficiency by building an environment model that can be used for planning. Posterior Sampling for Reinforcement Learning is such a model-based algorithm

Yang Chen, Zhaolei Cui, Yuebao Wang

For two nonstandard renewal risk models, we investigate the precise large deviations of the finite-time ruin probability and a random sum of the net-loss process, and the asymptotics of the random-time ruin probability. Notably, in one of these models, claim sizes series and claim interval time series are allowed to be arbitrarily dependent. Subsequently, we

E. Sokolova-Lapa, J. Stierhof, T. Dauser, J. Wilms

It is a common belief that for magnetic fields typical for accreting neutron stars in High-Mass X-ray Binaries vacuum polarization only affects the propagation of polarized emission in the neutron star magnetosphere. We show that vacuum resonances can significantly alter the emission from the poles of accreting neutron stars. The effect is similar to vacuum

Daron Acemoglu, Asuman Ozdaglar, Sarath Pattathil

Adaptation to dynamic conditions requires a certain degree of diversity. If all agents take the best current action, learning that the underlying state has changed and behavior should adapt will be slower. Diversity is harder to maintain when there is fast communication between agents, because they tend to find out and pursue the best action rapidly. We expl

Ángel López Oriona, Pablo Montero Manso, José Antonio Vilar Fernández

In this paper, a novel method to perform model-based clustering of time series is proposed. The procedure relies on two iterative steps: (i) K global forecasting models are fitted via pooling by considering the series pertaining to each cluster and (ii) each series is assigned to the group associated with the model producing the best forecasts according to a

Nicola Franco, Tom Wollschläger, Benedikt Poggel, Stephan Günnemann

Emerging quantum computing technologies, such as Noisy Intermediate-Scale Quantum (NISQ) devices, offer potential advancements in solving mathematical optimization problems. However, limitations in qubit availability, noise, and errors pose challenges for practical implementation. In this study, we examine two decomposition methods for Mixed-Integer Linear P

Bouzid Mosbahi, Ahmed Zahari, Imed Basdouri

In the current research work, our basic objective is to investigate the stucture of Hom-associative trialgebras. Next, we build up one important class of Hom-associative trialgebras and provide properties of right, left and meddle operations in Hom-associative trialgebras. Furthermore, we describe the classification of $n$-dimensional Hom-associative trialge

Maria Laura Battagliola, Helle Sørensen, Anders Tolver, Ana-Maria Staicu

This article focuses on the study of lactating sows, where the main interest is the influence of temperature, measured throughout the day, on the lower quantiles of the daily feed intake. We outline a model framework and estimation methodology for quantile regression in scenarios with longitudinal data and functional covariates. The quantile regression model

Peter K. F. Kuhfittig

This paper extends several previous studies of wormholes supported by two non-interacting fluids beginning with a combined model of ordinary matter and phantom dark energy with an anisotropic matter distribution. After noting that such wormholes could only exist on very large scales, the two-fluid model is extended to neutron stars, previously treated only f

Mahir Bilen Can, Pinaki Saha

This article explores the relationship between Schubert varieties and equivariant embeddings, using the framework of homogeneous fiber bundles over flag varieties. We show that the homogenous fiber bundles obtained from Bott-Samelson-Demazure-Hansen varieties are always toroidal. Furthermore, we identify the wonderful varieties among them. We give a short pr

Julio Araujo, Mitre C. Dourado, Fábio Protti, Rudini Sampaio

In this paper, we study two graph convexity parameters: iteration time and general position number. The iteration time was defined in 1981 in the geodesic convexity, but its computational complexity was so far open. The general position number was defined in the geodesic convexity and proved NP-hard in 2018. We extend these parameters to any graph convexity

Ngoc Cuong Nguyen, Jaime Peraire

We present a model reduction approach that extends the original empirical interpolation method to enable accurate and efficient reduced basis approximation of parametrized nonlinear partial differential equations (PDEs). In the presence of nonlinearity, the Galerkin reduced basis approximation remains computationally expensive due to the high complexity of e

Ángel López-Oriona, José Antonio Vilar Fernández, Pierpaolo D'Urso

The problem of testing the equality of the generating processes of two categorical time series is addressed in this work. To this aim, we propose three tests relying on a dissimilarity measure between categorical processes. Particular versions of these tests are constructed by considering three specific distances evaluating discrepancy between the marginal d

Ge Bu-Feng, Gao Ming-Yuan, Dong Hao

The complicated mesoscopic configurations of composite plate and shell structures requires a huge amount of computational overhead for directly simulating their mechanical problems. In this paper, a unified high-order multi-scale method, which can effectively simulate the mechanical behavior and predict yield strength of composite plates and shells, is devel

Amélie Loher

We derive Schauder estimates using ideas from Campanato's approach for a general class of local hypoelliptic operators and non-local kinetic equations. The method covers equations in divergence and non-divergence form. In particular our results are applicable to the inhomogeneous Landau and to the non-cutoff Boltzmann equation. The paper is self-contained.

Yu Zhu, Boning Li, Santiago Segarra

We propose a flexible framework for defining the 1-Laplacian of a hypergraph that incorporates edge-dependent vertex weights. These weights are able to reflect varying importance of vertices within a hyperedge, thus conferring the hypergraph model higher expressivity than homogeneous hypergraphs. We then utilize the eigenvector associated with the second sma

Ngoc Cuong Nguyen, Jordi Vila-Perez, Jaime Peraire

We introduce an adaptive viscosity regularization approach for the numerical solution of systems of nonlinear conservation laws with shock waves. The approach seeks to solve a sequence of regularized problems consisting of the system of conservation laws and an additional Helmholtz equation for the artificial viscosity. We propose a homotopy continuation of

Xue-Na Zhu, Jing Wang, Gui Bao, Ming Li

We study the separability of bipartite quantum systems in arbitrary dimensions based on the Bloch representation of density matrices. We present two separability criteria for quantum states in terms of the matrices $T_{\alpha\beta}(\rho)$ and $W_{ab,\alpha\beta}(\rho)$ constructed from the correlation tensors in the Bloch representation. These separability c

Dongyu Gong, Xingchen Wan, Dingmin Wang

Working memory is a critical aspect of both human intelligence and artificial intelligence, serving as a workspace for the temporary storage and manipulation of information. In this paper, we systematically assess the working memory capacity of ChatGPT, a large language model developed by OpenAI, by examining its performance in verbal and spatial n-back task

Petarpa Boonserm, Sattha Phalungsongsathit, Kunlapat Sansuk, Pitayuth Wongjun

Greybody factors are transmission probabilities of the Hawking radiation, which are emitted from black holes and can be obtained from the gravitational potential of black holes. The de Rham, Gabadadze, and Tolly (dRGT) massive gravity is one of the gravity theories that modified general relativity. In this paper, we investigate the greybody factor from the m

Kareem T. Elgindy

In [1], we inaugurated a new area of optimal control (OC) theory that we called "periodic fractional OC theory," which was developed to find optimal ways to periodically control a fractional dynamic system. The typical mathematical formulation in this area includes the class of periodic fractional OC problems (PFOCPs), which can be accurately solved numerica

Jing Wang, Xu Xu, Jiangong You, Qi Zhou

We establish the absolute continuity of the integrated density of states (IDS) for quasi-periodic Schr\"odinger operators with a large trigonometric potential and Diophantine frequency. This partially solves Eliasson's open problem in 2002. Furthermore, this result can be extended to a class of quasi-periodic long-range operators on $\ell^2(\Z^d)$. Our proof

Qian Chang, Xia Lia, Patrick S. W. Fong

With the proliferation of social media, the detection of fake news has become a critical issue that poses a significant threat to society. The dissemination of fake information can lead to social harm and damage the credibility of information. To address this issue, deep learning has emerged as a promising approach, especially with the development of natural

Jia-Hong Huang, Chao-Han Huck Yang, Pin-Yu Chen, Min-Hung Chen

The goal of video summarization is to automatically shorten videos such that it conveys the overall story without losing relevant information. In many application scenarios, improper video summarization can have a large impact. For example in forensics, the quality of the generated video summary will affect an investigator's judgment while in journalism it m

Sai Yang, Fan Liu, Delong Chen, Jun Zhou

Transfer learning has been widely adopted for few-shot classification. Recent studies reveal that obtaining good generalization representation of images on novel classes is the key to improving the few-shot classification accuracy. To address this need, we prove theoretically that leveraging ensemble learning on the base classes can correspondingly reduce th

Jinrong Hu, Yong Huang, Jian Lu, Sinan Wang

In this paper, the $L_{p}$ chord Minkowski problem is concerned. Based on the results showed in \cite{HJ23}, we obtain a new existence result of solutions to this problem in terms of smooth measures by using a nonlocal Gauss curvature flow for $p>-n$ with $p\neq 0$.

Rolf Schneider

Pseudo-cones are a class of unbounded closed convex sets, not containing the origin. They admit a kind of polarity, called copolarity. With this, they can be considered as a counterpart to convex bodies containing the origin in the interior. The purpose of the following is to study this analogy in greater detail. We supplement the investigation of copolarity

I. A. Strakhov, B. S. Safonov, D. V. Cheryasov

In 2022 we carried out an upgrade of the speckle polarimeter (SPP) -- the facility instrument of the 2.5-m telescope of the Caucasian Observatory of the SAI MSU. During the overhaul, CMOS Hamamatsu ORCA-Quest qCMOS C15550-20UP was installed as the main detector, some drawback of the previous version of the instrument were eliminated. In this paper, we presen

Huachuan Qiu, Hongliang He, Shuai Zhang, Anqi Li

Developing specialized dialogue systems for mental health support requires multi-turn conversation data, which has recently garnered increasing attention. However, gathering and releasing large-scale, real-life multi-turn conversations that could facilitate advancements in mental health support presents challenges in data privacy protection and the time and

Yunbo Dong

This thesis designs a prediction system based on matrix factorization to predict the classification accuracy of a specific model on a particular dataset. In this thesis, we conduct comprehensive empirical research on more than fifty datasets that we collected from the openml website. We study the performance prediction of three fundamental machine learning a

Hyeongseop Kim, Chang-geun Oh, Jun-Won Rhim

A singular flat band(SFB), a distinct class of the flat band, has been shown to exhibit various intriguing material properties characterized by a geometric quantity of the Bloch wave function called the quantum distance. We present a general construction scheme for a tight-binding model hosting an SFB, where the quantum distance profile can be controlled. We

Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang

Large Language Models (LLMs) have demonstrated remarkable performance across diverse domains, thereby prompting researchers to explore their potential for use in recommendation systems. Initial attempts have leveraged the exceptional capabilities of LLMs, such as rich knowledge and strong generalization through In-context Learning, which involves phrasing th

Hiuchung Hung, Andreas Maier, Thorsten Piske

This paper introduces a non-native speech corpus consisting of narratives from fifty 5- to 6-year-old Chinese-English children. Transcripts totaling 6.5 hours of children taking a narrative comprehension test in English (L2) are presented, along with human-rated scores and annotations of grammatical and pronunciation errors. The children also completed the p

K. Asnaashari, R. V. Krems, T. V. Tscherbul

Owing to their rich internal structure and significant long-range interactions, ultracold molecules have been widely explored as carriers of quantum information. Several different schemes for encoding qubits into molecular states, both bare and field-dressed, have been proposed. At the same time, the rich internal structure of molecules leaves many unexplore

Chun-Mei Hao, Xing Li, Artem R. Oganov, Jingyu Hou

The discovery of superconductivity in CaC6 with a critical temperature (Tc) of 11.5 K reignites much interest in exploring high-temperature superconductivity in graphite intercalation compounds (GICs). Here we identify a GIC NaC4, discovered by ab initio evolutionary structure search, as a superconductor with a computed Tc of 41.2 K at 5 GPa. This value is e

Jonathan A. Hillman

We characterize the groups of branched twist spins of classical knots in terms of 3-manifold groups, and also give a purely algebraic, conjectural characterization in terms of $PD_3$-groups. We show also that each group is the group of at most finitely many branched twist spins.

Rodrigo Matos

Localization results for a class of random Schr\"odinger operators within the Hartree-Fock approximation are proved in two regimes: large disorder and weak disorder/extreme energies. A large disorder threshold $\lambda_{\mathrm{HF}}$ analogous to the threshold $\lambda_{\mathrm{And}}$ obtained by Schenker in \cite{Schenkl} is provided. We also show certain s

Naresh Kumar Gurulingan, Bahram Zonooz, Elahe Arani

Multi-task learning has the potential to improve generalization by maximizing positive transfer between tasks while reducing task interference. Fully achieving this potential is hindered by manually designed architectures that remain static throughout training. On the contrary, learning in the brain occurs through structural changes that are in tandem with c

A. Bókon, Sz. Kálmán, I. B. Bíró, M. Gy. Szabó

Asymmetric features in exoplanet transit light curves are often interpreted as a gravity darkening effect especially if there is spectroscopic evidence of a spin-orbit misalignment. Since other processes can also lead to light curve asymmetries this may lead to inaccurate gravity darkening parameters. Here we investigate the case of non-radial pulsations as

Mingchen Zheng, Yi Qiao, Yupeng Wang, Junpeng Cao

A one-dimensional Bose Hubbard model with unidirectional hopping is shown to be exactly solvable. Applying the algebraic Bethe ansatz method, we prove the integrability of the model and derive the Bethe ansatz equations. The exact eigenvalue spectrum can be obtained by solving these equations. The distribution of Bethe roots reveals the presence of a superfl

Riccardo Busetto, Valentina Breschi, Simone Formentin

When solving global optimization problems in practice, one often ends up repeatedly solving problems that are similar to each others. By providing a rigorous definition of similarity, in this work we propose to incorporate the META-learning rationale into SMGO-$\Delta$, a global optimization approach recently proposed in the literature, to exploit priors obt

Nan Zhang, Xianyong Ding, Fangyang Zhan, Houpu Li

The coupling between band structure and magnetism can lead to intricate Fermi surface modifications. Here we report on the comprehensive study of the Shubnikov-de Haas (SdH) effect in two rare-earth-based magnetic Weyl semimetals, NdAlSi and CeAlSi$_{0.8}$Ge$_{0.2}$. The results show that the temperature evolution of topologically nontrivial Fermi surfaces s

Rogardt Heldal, Ngoc-Thanh Nguyen, Ana Moreira, Patricia Lago

Achieving the UN Sustainable Development Goals (SDGs) demands adequate levels of awareness and actions to address sustainability challenges. Software systems will play an important role in moving towards these targets. Sustainability skills are necessary to support the development of software systems and to provide sustainable IT-supported services for citiz

Jie Ren, Wenya Yu, Jiapan Guo, Weichuan Zhang

Interest point detection methods have received increasing attention and are widely used in computer vision tasks such as image retrieval and 3D reconstruction. In this work, second-order anisotropic Gaussian directional derivative filters with multiple scales are used to smooth the input image and a novel blob detection method is proposed. Extensive experime

Burak Ercan, Onur Eker, Aykut Erdem, Erkut Erdem

Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic range and minimal motion blur. However, their output is not easily understandable by humans, making the reconstruction of intensity images from event streams a fundamental task in e

Gábor Hegedüs

Let $\mbox{$\cal F$}\subseteq 2^{[n]}$ be a fixed family of subsets. Let $D(\mbox{$\cal F$})$ stand for the following set of Hamming distances: $$ D(\mbox{$\cal F$}):=\{d_H(F,G):~ F, G\in \mbox{$\cal F$},\ F\neq G\}. $$ $\mbox{$\cal F$}$ is said to be a Hamming symmetric family, if $d\in D(\mbox{$\cal F$})$ implies $n-d\in D(\mbox{$\cal F$})$ for each $d\in

Elia Bonetto, Aamir Ahmad

Nowadays, there is a wide availability of datasets that enable the training of common object detectors or human detectors. These come in the form of labelled real-world images and require either a significant amount of human effort, with a high probability of errors such as missing labels, or very constrained scenarios, e.g. VICON systems. On the other hand,

L. Verra, G. Zevi Della Porta, E. Gschwendtner, M. Bergamaschi

The Advanced Wakefield Experiment (AWAKE) at CERN relies on the seeded Self-Modulation (SM) of a long relativistic proton bunch in plasma to accelerate an externally injected MeV witness electron bunch to GeV energies. During AWAKE Run 1 (2016-2018) and Run 2a (2021-2022), two seeding methods were investigated experimentally: relativistic ionization front se

Christian Schellenberger, Christopher Hobelsberger, Bastian Kolb-Grunder, Florian Herrmann

In this paper an autonomous system to detect and combat Rumex obtusifolius leveraging autonomous unmanned aerial vehicles (UAV), small autonomous sprayer robots and 5G SA connectivity is presented. Rumex obtusifolius is a plant found on grassland that drains nutrients from surrounding plants and has lower nutritive value than the surrounding grass. High conc

Rathindra Nath Dutta, Subhojit Sarkar, Sasthi C. Ghosh

Stringent line-of-sight demands necessitated by the fast attenuating nature of millimeter waves (mmWaves) through obstacles pose one of the central problems of next generation wireless networks. These mmWave links are easily disrupted due to obstacles, including vehicles and pedestrians, which cause degradation in link quality and even link failure. Dynamic

Zhenrong Liu, Zongze Li, Miaowen Wen, Yi Gong

In this paper, simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS) is investigated in the multi-user mobile edge computing (MEC) system to improve the computation rate. Compared with traditional RIS-aided MEC, STAR-RIS extends the service coverage from half-space to full-space and provides new flexibility for improving

Renke Huang, Jiachi Chen, Yanlin Wang, Tingting Bi

Web3, the next generation of the Internet, represents a decentralized and democratized web. Although it has garnered significant public interest and found numerous real-world applications, there is a limited understanding of people's perceptions and experiences with Web3. In this study, we conducted an empirical study to investigate the categories of Web3 ap

Michał Leś, Michał Woźniak

Automatic music transcription (AMT) is one of the most challenging tasks in the music information retrieval domain. It is the process of converting an audio recording of music into a symbolic representation containing information about the notes, chords, and rhythm. Current research in this domain focuses on developing new models based on transformer archite

Yi-Jun Chang

An orthogonal drawing is an embedding of a plane graph into a grid. In a seminal work of Tamassia (SIAM Journal on Computing 1987), a simple combinatorial characterization of angle assignments that can be realized as bend-free orthogonal drawings was established, thereby allowing an orthogonal drawing to be described combinatorially by listing the angles of

Na Li, Xun Li, Zuo Quan Xu

This paper employs a policy iteration reinforcement learning (RL) method to study continuous-time linear-quadratic mean-field control problems in infinite horizon. The drift and diffusion terms in the dynamics involve the states, the controls, and their conditional expectations. We investigate the stabilizability and convergence of the RL algorithm using a L

Andrey Losev, Vyacheslav Lysov

We describe the tropical mirror for complex toric surfaces. In particular we provide an explicit expression for the mirror states and show that they can be written in enumerative form. Their holomorphic germs give an explicit form of good section for Landau-Ginzburg-Saito theory. We use an explicit form of holomorphic germs to derive the divisor relation for

David Ayotte, Xavier Caruso, Antoine Leudière, Joseph Musleh

We present the first implementation of Drinfeld modules fully integrated in the SageMath ecosystem. First features will be released with SageMath 10.0.

Ziqing Yin, Renjie Xie, Wei Xu, Zhaohui Yang

Deep learning (DL)-based channel state information (CSI) feedback methods compressed the CSI matrix by exploiting its delay and angle features straightforwardly, while the measure in terms of information contained in the CSI matrix has rarely been considered. Based on this observation, we introduce self-information as an informative CSI representation from t

Marc Jofre, Jordi Romeu, Luis Jofre-Roca

Quantum sensors provide unprecedented magnetic field detection sensitivities, enabling these to extend the common magnetometry range of applications and environments of operation. In this framework, many applications also require high spatial resolution magnetic measurements for biomedical research, environmental monitoring and industrial production. In this

Supriya Upadhyay, K. Muralidhar

Electrically actuated continuous motion of a water droplet over PDMS-coated single active electrode is analyzed from detailed modeling and experiments. In an experiment, continuous motion of the droplet is achieved when it is located over an active electrode with a horizontal ground wire placed just above in an open EWOD configuration. Using a CCD camera, th

Ela Liberman-Pincu, Oliver Korn, Jonas Grund, Elmer D. van Grondelle

Socially assistive robots (SARs) are becoming more prevalent in everyday life, emphasizing the need to make them socially acceptable and aligned with users' expectations. Robots' appearance impacts users' behaviors and attitudes towards them. Therefore, product designers choose visual qualities to give the robot a character and to imply its functionality and

Mohammed Latif Siddiq, Joanna C. S. Santos, Ridwanul Hasan Tanvir, Noshin Ulfat

A code generation model generates code by taking a prompt from a code comment, existing code, or a combination of both. Although code generation models (e.g., GitHub Copilot) are increasingly being adopted in practice, it is unclear whether they can successfully be used for unit test generation without fine-tuning for a strongly typed language like Java. To

C. S. Sonali, Chinmayi B S, Ahana Balasubramanian

Audio classification is vital in areas such as speech and music recognition. Feature extraction from the audio signal, such as Mel-Spectrograms and MFCCs, is a critical step in audio classification. These features are transformed into spectrograms for classification. Researchers have explored various techniques, including traditional machine and deep learnin

Jifei Miao, Kit Ian Kou, Liqiao Yang, Juan Han

The use of quaternions as a novel tool for color image representation has yielded impressive results in color image processing. By considering the color image as a unified entity rather than separate color space components, quaternions can effectively exploit the strong correlation among the RGB channels, leading to enhanced performance. Especially, color im

Siamak Akhshabi, Saboura Zamani

We analyze the measurement of cosmological distances in the presence of torsion in both Einstein-Cartan and Poincare gauge theory of gravity. Using the modified cosmological distance measurements, we use the observed time delays in gravitational lensing systems to determine the Hubble parameter. The results show the measured Hubble parameter from a lensing s

Rui-Xin Yang, Fei Xie, Dao-Jun Liu

As a possible alternative to black holes, horizonless compact objects have significant implications for gravitational-wave physics. In this work, we utilize the standard linearized theory of general relativity to calculate the quadrupolar tidal Love numbers of a nonexotic compact object with a thin shell proposed by Rosa and Pi\c{c}arra. It is found that bot

Sedrick Scott Keh, Zheyuan Ryan Shi, David J. Patterson, Nirmal Bhagabati

Non-governmental organizations for environmental conservation have a significant interest in monitoring conservation-related media and getting timely updates about infrastructure construction projects as they may cause massive impact to key conservation areas. Such monitoring, however, is difficult and time-consuming. We introduce NewsPanda, a toolkit which

Khalid Ajran, Felix Gotti

Given a join semilattice $S$ with a minimum $\hat{0}$, the quarks (also called atoms in order theory) are the elements that cover $\hat{0}$, and for each $x \in S \setminus \{\hat{0}\}$ a factorization (into quarks) of $x$ is a minimal set of quarks whose join is $x$. If every element $x \in S \setminus \{\hat{0}\}$ has a factorization, then $S$ is called fa