March 2023 arXiv papers — page 113

P. Lindner, C. Kuckein, S. J. González Manrique, N. Bello González

While it is being conjectured that a chromospheric canopy plays a role in penumbra formation, it has been difficult to find observational evidence of the connectivity between the photosphere and the chromosphere. We investigate the existence of a chromospheric canopy as a necessary condition for the formation of a penumbra and aim to find the origin of the i

Sanqing Qu, Tianpei Zou, Florian Roehrbein, Cewu Lu

Deep neural networks (DNNs) often perform poorly in the presence of domain shift and category shift. How to upcycle DNNs and adapt them to the target task remains an important open problem. Unsupervised Domain Adaptation (UDA), especially recently proposed Source-free Domain Adaptation (SFDA), has become a promising technology to address this issue. Neverthe

Jan Robine, Marc Höftmann, Tobias Uelwer, Stefan Harmeling

Deep neural networks have been successful in many reinforcement learning settings. However, compared to human learners they are overly data hungry. To build a sample-efficient world model, we apply a transformer to real-world episodes in an autoregressive manner: not only the compact latent states and the taken actions but also the experienced or predicted r

Aditya Saxena, Manpreet Kaur, Vipin Devrari, Mandip Singh

A transparent polarisation sensitive phase pattern exhibits a position and polarisation dependent phase shift of transmitted light and it represents a unitary transformation. A quantum ghost image of this pattern is produced with hyper-entangled photons consisting of Einstein-Podolsky-Rosen (EPR) and polarisation entanglement. In quantum ghost imaging, a sin

Junichiro Sugihara, Takuzumi Nishio, Keisuke Nagato, Masayuki Nakao

In previous research, various types of aerial robots were developed to improve maneuverability or manipulation abilities. However, there was a challenge in achieving both mobility and manipulation capabilities simultaneously. This is because aerial robots with high mobility lack the necessary rotors to perform manipulation tasks, while those with manipulatio

Jesse Milzman, Andre Harrison, Carlos Nieto-Granda, John Rogers

Factor graphs are a ubiquitous tool for multi-source inference in robotics and multi-sensor networks. They allow for heterogeneous measurements from many sources to be concurrently represented as factors in the state posterior distribution, so that inference can be conducted via sparse graphical methods. Adding measurements from many sources can supply robus

Zhiwei Xu, Min Zhou, Xibin Zhao, Yang Chen

The application of deep learning techniques in software engineering becomes increasingly popular. One key problem is developing high-quality and easy-to-use source code representations for code-related tasks. The research community has acquired impressive results in recent years. However, due to the deployment difficulties and performance bottlenecks, seldom

Giulia Piccitto, Angelo Russomanno, Davide Rossini

We explain how to apply a Gaussian-preserving operator to a fermionic Gaussian state. We use this method to study the evolution of the entanglement entropy of an Ising spin chain following a Lindblad dynamics with string measurement operators, focusing on the quantum-jump unraveling of such Lindbladian. We find that the asymptotic entanglement entropy obeys

Junde Xu, Zikai Lin, Donghao Zhou, Yaodong Yang

Masked Image Modeling (MIM) has achieved impressive representative performance with the aim of reconstructing randomly masked images. Despite the empirical success, most previous works have neglected the important fact that it is unreasonable to force the model to reconstruct something beyond recovery, such as those masked objects. In this work, we show that

Ksenia Bestuzheva, Mathieu Besançon, Wei-Kun Chen, Antonia Chmiela

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this paper is on the role of the SCIP Optimization Suite in supporting research. SCIP's main design principles are discussed, followed by a presentation of the latest performance

Florian Bauer

Cameras play a crucial role in modern driver assistance systems and are an essential part of the sensor technology for automated driving. The quality of images captured by in-vehicle cameras highly influences the performance of visual perception systems. This paper presents a feature-based algorithm to detect certain effects that can degrade image quality in

Utkucan Balci, Chen Ling, Emiliano De Cristofaro, Megan Squire

The Internet has been instrumental in connecting under-represented and vulnerable groups of people. Platforms built to foster social interaction and engagement have enabled historically disenfranchised groups to have a voice. One such vulnerable group is women. In this paper, we explore the diversity in online women's ideological spaces using a multi-dimensi

Yan Ke, Minqing Zhang, Jia Liu, Xiaoyuan Yang

With the popularization and application of privacy protection technologies in cloud service and social network, ciphertext has been gradually becoming a common platform for public to exchange data. Under the cover of such a plat-form, we propose steganography in encrypted domain (SIED) in this paper to re-alize a novel method to realize secret communication

Rogemar A. Riffel, Rogério Riffel, Marina Bianchin, Thaisa Storchi-Bergmann

We use optical Integral Field Spectroscopy (IFU) to study the gas emission structure and kinematics in the inner 3.4$\times$4.9 kpc$^2$ region of the galaxy UGC 8782 (3C 293), host of a radio loud Active Galactic Nucleus (AGN). The observations were performed with the GMOS-IFU on the Gemini North telescope, resulting in a spatial resolution of $\sim725$ pc a

J. F. Jardine

The hierarchy associated to clusters in the HDBSCAN algorithm has layers, which are defined by cardinality. The layers define a layer subposet of the HDBSCAN hierarchy, which is a strong deformation retract and admits a stability analysis. That stability analysis is introduced here. Cardinality arguments lead to sharper results for layers than one sees for s

Maximilian Tschuchnig, Petra Tschuchnig, Cornelia Ferner, Michael Gadermayr

Inflation is a major determinant for allocation decisions and its forecast is a fundamental aim of governments and central banks. However, forecasting inflation is not a trivial task, as its prediction relies on low frequency, highly fluctuating data with unclear explanatory variables. While classical models show some possibility of predicting inflation, rel

Chaofan Zheng, Xinyu Lyu, Lianli Gao, Bo Dai

Current Scene Graph Generation (SGG) methods explore contextual information to predict relationships among entity pairs. However, due to the diverse visual appearance of numerous possible subject-object combinations, there is a large intra-class variation within each predicate category, e.g., "man-eating-pizza, giraffe-eating-leaf", and the severe inter-clas

Pantelis Melas, Dimitrios K. Papoulias, Niki Saoulidou

We explore the prospects of constraining general non standard interactions involving light mediators through elastic neutrino-electron scattering events at the DUNE Near Detector (ND). We furthermore consider the special cases of light vector mediators in motivated models such as $U(1)_{B-L}$, $U(1)_{L_\mu - L_\tau}$, $E_6$ and left-right symmetry. The prese

Shahad Hardan, Hussain Alasmawi, Xiangjian Hou, Mohammad Yaqub

Vestibular schwannoma (VS) is a non-cancerous tumor located next to the ear that can cause hearing loss. Most brain MRI images acquired from patients are contrast-enhanced T1 (ceT1), with a growing interest in high-resolution T2 images (hrT2) to replace ceT1, which involves the use of a contrast agent. As hrT2 images are currently scarce, it is less likely t

Simon Murmann, Marcel Schmidt

In this paper we give a version of Harris' criterion for determining $H^{1,p}_0$ within $H^{1,p}$ on discrete spaces. Moreover, we provide a converse via Hardy inequalities involving distances to metric boundaries.

Yiwei Liao, Zhuorui Li, Shi Pu

In the modern paradigm of multi-agent networks, communication has become one of the main bottlenecks for decentralized optimization, where a large number of agents are involved in minimizing the average of the local cost functions. In this paper, we propose a robust compressed push-pull algorithm (RCPP) that combines gradient tracking with communication comp

Tony J. Puthenpurakal

Let $(A,\mathfrak{m})$ be an excellent normal domain of dimension two containing a field $k \cong A/\mathfrak{m}$. An $\mathfrak{m}$-primary ideal $I$ to be a $p_g$-ideal if the Rees algebra $A[It]$ is a Cohen-Macaulay normal domain. If $k$ is algebraically closed then Okuma, Watanabe and Yoshida proved that $A$ has $p_g$-ideals and furthermore product of tw

Andrew Weng, Jason B. Siegel, Anna Stefanopoulou

Voltage-based battery metrics are ubiquitous and essential in battery manufacturing diagnostics. They enable electrochemical "fingerprinting" of batteries at the end of the manufacturing line and are naturally scalable, since voltage data is already collected as part of the formation process which is the last step in battery manufacturing. Yet, despite their

F. Michael Russell, Juan F. R. Archilla, José L. Mas

Tokamak fusion reactors produce energetic He ions that penetrate surfaces less than 20 micron and neutrons that spread throughout the reactor. Experiments with similar swift He ions in heavy metals show that the vibronic coupling of nonlinear lattice excitations creates mobile lattice excitations, called quodons. These are decoupled from phonons, move ballis

Zi-Yue Zheng, Ting-Ting Sun, Huan Chen, Jin-Biao Wei

We investigate non-radial oscillations of pure and hybrid neutron stars, employing equations of state of nuclear matter from Brueckner-Hartree-Fock theory, and of quark matter from the Dyson-Schwinger quark model, performing a Gibbs construction for the mixed phase in hybrid stars. Characteristic differences between neutron-star and hybrid-star $g_1$-mode os

Zheng Ge, Zhi-Yuan Zhou, Jing-Xin Ceng, Li Chen

We present a scheme for estimating the noise-equivalent temperature difference (NETD) of frequency upconversion detectors (UCDs) that detect mid-infrared (MIR) light. In particular, this letter investigates the frequency upconversion of a periodically polarized crystal based on lithium niobate, where a mid-infrared conversion bandwidth of 220 nm can be achie

Fritz Günther, Marco Marelli, Marco Alessandro Petilli

Over the last years, advancements in deep learning models for computer vision have led to a dramatic improvement in their image classification accuracy. However, models with a higher accuracy in the task they were trained on do not necessarily develop better image representations that allow them to also perform better in other tasks they were not trained on.

Axel Gagge, Th. K. Mavrogordatos, Jonas Larson

With the objective of simulating the physical behavior of electrons in a dynamic background, we investigate a cold atomic Bose-Fermi mixture confined in an optical lattice potential solely affecting the bosons. The bosons, residing in the deep superfluid regime, inherit the periodicity of the optical lattice, subsequently serving as a dynamic potential for t

Katsuhiro Endo, Yuki Sato, Rudy Raymond, Kaito Wada

Variational Quantum Eigensolver (VQE) is a hybrid algorithm for finding the minimum eigenvalue/vector of a given Hamiltonian by optimizing a parametrized quantum circuit (PQC) using a classical computer. Sequential optimization methods, which are often used in quantum circuit tensor networks, are popular for optimizing the parametrized gates of PQCs. This pa

Grzegorz Głuch, Rudiger Urbanke

We introduce a new notion of complexity of functions and we show that it has the following properties: (i) it governs a PAC Bayes-like generalization bound, (ii) for neural networks it relates to natural notions of complexity of functions (such as the variation), and (iii) it explains the generalization gap between neural networks and linear schemes. While t

Elmer V. H. Doggen, Yuval Gefen, Igor V. Gornyi, Alexander D. Mirlin

Measurement-induced phase transitions are the subject of intense current research, both from an experimental and a theoretical perspective. We explore the concept of implementing quantum measurements by coupling a many-body lattice system to an ancillary degree of freedom (implemented using two additional sites), on which projective measurements are performe

Jie Hu, Mengze Zeng, Enhua Wu

Deep neural networks have been proven effective in a wide range of tasks. However, their high computational and memory costs make them impractical to deploy on resource-constrained devices. To address this issue, quantization schemes have been proposed to reduce the memory footprint and improve inference speed. While numerous quantization methods have been p

Yikun Li, Mohamed Soliman, Paris Avgeriou

Self-Admitted Technical Debt or SATD can be found in various sources, such as source code comments, commit messages, issue tracking systems, and pull requests. Previous research has established the existence of relations between SATD items in different sources; such relations can be useful for investigating and improving SATD management. However, there is cu

Yutian Chi, Chenglong Shen, Long Cheng, Bingkun Yu

Tianwen-1 spacecraft (Wan et al. 2020) is China's first Mars exploration mission. The Mars Orbiter Magnetometer (MOMAG) is a scientific instrument aboard the Tianwen-1 mission that is designed to study magnetic fields at Mars, including the solar wind to the magnetosheath and the ionosphere. Using the first Tianwen-1/MOMAG data that is publicly available, we

Zihao Lin, Jinrong Li, Fan Yang, Shuangping Huang

Offline Handwritten Mathematical Expression Recognition (HMER) has been dramatically advanced recently by employing tree decoders as part of the encoder-decoder method. Despite the tree decoder-based methods regard the expressions as a tree and parse 2D spatial structure to the tree nodes sequence, the performance of existing works is still poor due to the i

G. Bargiacchi, M. G. Dainotti, S. Nagataki, S. Capozziello

The recent $\sim 4 \, \sigma$ Hubble constant, $H_{0}$, tension is observed between the value of $H_{0}$ from the Cosmic Microwave Background (CMB) and Type Ia Supernovae (SNe Ia). It is a decade since this tension is excruciating the modern astrophysical community. To shed light on this problem is key to consider probes at intermediate redshifts between SNe

Elena Stoykova, Blaga Blagoeva, Natalya Berberova-Buhova, Mikhail Levchenko

Statistical processing of speckle data enables observation of speed of processes. In intensity-based pointwise dynamic speckle analysis, a map related to speed's spatial distribution is extracted from a sequence of speckle patterns formed on an object under coherent light. Monitoring of time evolution of a process needs storage, transfer and processing of a

A. Michael Stock, Sergio López-Ureña

In computed tomography, the approximation quality of a scan of a physical object is typically limited by the acquisition modalities, especially the hardware including X-ray detectors. To improve upon this, we experiment with a three-dimensional subdivision scheme to increase the resolution of the reconstructed voxel data. Subdivision schemes are often used t

Renato Vizuete, Paolo Frasca, Elena Panteley

In this paper, we provide a formulation of an open Hegselmann-Krause (HK) dynamics where agents can join and leave the system during the interactions. We consider a stochastic framework where the time instants corresponding to arrivals and departures are determined by homogeneous Poisson processes. Then, we provide a survey of Lyapunov functions based on glo

Wanying Ge, Hemlata Tak, Massimiliano Todisco, Nicholas Evans

Spoofing countermeasure (CM) and automatic speaker verification (ASV) sub-systems can be used in tandem with a backend classifier as a solution to the spoofing aware speaker verification (SASV) task. The two sub-systems are typically trained independently to solve different tasks. While our previous work demonstrated the potential of joint optimisation, it a

Aviad Eisenberg, Sharon Gannot, Shlomo E. Chazan

In this work, we present a two-stage method for speaker extraction under reverberant and noisy conditions. Given a reference signal of the desired speaker, the clean, but the still reverberant, desired speaker is first extracted from the noisy-mixed signal. In the second stage, the extracted signal is further enhanced by joint dereverberation and residual no

Norman Peitek, Annabelle Bergum, Maurice Rekrut, Jonas Mucke

Background: Despite similar education and background, programmers can exhibit vast differences in efficacy. While research has identified some potential factors, such as programming experience and domain knowledge, the effect of these factors on programmers' efficacy is not well understood. Aims: We aim at unraveling the relationship between efficacy (speed

Alejandro Cros Carrillo de Albornoz, Dominic C. Rose, Arijeet Pal

Existence of Anderson localization is considered a manifestation of coherence of classical and quantum waves in disordered systems. Signatures of localization have been observed in condensed matter and cold atomic systems where the coupling to the environment can be significantly suppressed but not eliminated. In this work we explore the phenomena of localiz

Damien Sileo, Kanimozhi Uma, Marie-Francine Moens

Medical multiple-choice question answering (MCQA) is particularly difficult. Questions may describe patient symptoms and ask for the correct diagnosis, which requires domain knowledge and complex reasoning. Standard language modeling pretraining alone is not sufficient to achieve the best results. \citet{jin2020disease} showed that focusing masked language m

Saviz Mowlavi, Ken Kamrin

Most noninvasive imaging techniques utilize electromagnetic or acoustic waves originating from multiple locations and directions to identify hidden geometrical structures. Surprisingly, it is also possible to image hidden voids and inclusions buried within an object using a single static thermal or mechanical loading experiment by observing the response of t

Lakshmi Mandal, Shalabh Bhatnagar

We consider the problem of finding the optimal value of n in the n-step temporal difference (TD) learning algorithm. Our objective function for the optimization problem is the average root mean squared error (RMSE). We find the optimal n by resorting to a model-free optimization technique involving a one-simulation simultaneous perturbation stochastic approx

Tong Xia, Jing Han, Abhirup Ghosh, Cecilia Mascolo

Federated learning (FL) aided health diagnostic models can incorporate data from a large number of personal edge devices (e.g., mobile phones) while keeping the data local to the originating devices, largely ensuring privacy. However, such a cross-device FL approach for health diagnostics still imposes many challenges due to both local data imbalance (as ext

David Afonso Delgado, Tanausú del Pino Alemán, Javier Trujillo Bueno

This paper presents a theoretical investigation on the polarization and magnetic sensitivity of the near-ultraviolet (near-UV) solar spectral lines of Fe II between 250 and 278 nm. In recent years, UV spectropolarimetry has become key to uncover the magnetism of the upper layers of the solar chromosphere. The unprecedented data obtained by the CLASP2 suborbi

Jianyang Gu, Kai Wang, Hao Luo, Chen Chen

Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the retrieval performance. Previous works explore new optimizing targets and search spaces for NAS ReID, yet they neglect the difference of training schemes between image classification

Leichao Cui, Xiuxian Li, Min Meng, Xiaoyu Mo

LiDAR point clouds have become the most common data source in autonomous driving. However, due to the sparsity of point clouds, accurate and reliable detection cannot be achieved in specific scenarios. Because of their complementarity with point clouds, images are getting increasing attention. Although with some success, existing fusion methods either perfor

Jonas Rønning, Julian Renaud, Amin Doostmohammadi, Luiza angheluta

Polar active matter of self-propelled particles sustain spontaneous flows through the full-integer topological defects. We study theoretically the effect of both polar and dipolar active forces on the flow profile around $\pm 1$ defects and their interaction in the presence of both viscosity and frictional dissipation. The vorticity induced by the active str

Bangjian Zhou, Pan Jieming, Maheswari Sivan, Aaron Voon-Yew Thean

With high device integration density and evolving sophisticated device structures in semiconductor chips, detecting defects becomes elusive and complex. Conventionally, machine learning (ML)-guided failure analysis is performed with offline batch mode training. However, the occurrence of new types of failures or changes in the data distribution demands retra

Tom Bridgeland

We argued in [Proc. Sympos. Pure Math., Vol. 103, American Mathematical Society, Providence, RI, 2021, 1-66, arXiv:1912.06504] that, when a certain sub-exponential growth property holds, the Donaldson-Thomas invariants of a 3-Calabi-Yau triangulated category should give rise to a geometric structure on its space of stability conditions called a Joyce structu

Till Massing

Tempered stable distributions are frequently used in financial applications (e.g., for option pricing) in which the tails of stable distributions would be too heavy. Given the non-explicit form of the probability density function, estimation relies on numerical algorithms which typically are time-consuming. We compare several parametric estimation methods su

Ishan Prasad, Abhiram Reddy, Gregory M. Grason

Chirality transfer from the level of molecular structure up to mesoscopic lengthscales of supramolecular morphologies is a broad and persistent theme in self-assembled soft materials, from biological to synthetic matter. Here, we analyze the mechanism of chirality transfer in a prototypical self-assembly system, block copolymers (BCPs), in particular, its im

D. Rodgers-Lee, P. B. Rimmer, A. A. Vidotto, A. J. Louca

A key first step to constrain the impact of energetic particles in exoplanet atmospheres is to detect the chemical signature of ionisation due to stellar energetic particles and Galactic cosmic rays. We focus on GJ$\,$436, a well-studied M dwarf with a warm Neptune-like exoplanet. We demonstrate how the maximum stellar energetic particle momentum can be esti

Hsu Chew Lee, Peng Dai, Minping Wan, Vladimir A. Sabelnikov

Recent complex-chemistry direct numerical simulations of lean hydrogen-air flames propagating in forced turbulence in a box were continued by switching-off the turbulence forcing. Results show that a decrease in burning velocity U_T(t), caused by the turbulence decay, is reversed when the turbulence becomes weak and a peak of U_T(t) appears, with the peak ma

Benedikt Barthel, Themistoklis Sapsis

This work addresses the data-driven forecasting of extreme events in the airfoil flow. These events may be seen as examples of the kind of unsteady and intermittent dynamics relevant to the flow around airfoils and wings in a variety of laboratory and real-world applications. W investigate the instability mechanisms at the heart of these extreme events, and

Sergej Faletic, Philipp Bitzenbauer, Maria Bondani, Marilu Chiofalo

The GIREP community on teaching and learning quantum physics and the Education section of the Quantum flagship project of the European Union (QTEdu) have brought together different stakeholders in the field of teaching quantum physics on all levels, including outreach. The goal of QTEdu is to pave the way for the training of the future quantum workforce. To

Anupam Mondal, Sajal Mukherjee, Kuldeep Saha

We denote the matching complex of the complete graph with $n$ vertices by $M_n$. Bouc first studied the topological properties of $M_n$ in connection with the Quillen complex. Later Bj\"{o}rner, Lov\'{a}sz, Vre\'{c}ica, and \v{Z}ivaljevi\'{c} showed that $M_n$ is homotopically $(\nu_n-1)$-connected, where $\nu_n=\lfloor{\frac{n+1}{3}}\rfloor-1$, but in gener

Gi-Soo Kim, Young Suh Hong, Tae Hoon Lee, Myunghee Cho Paik

Long-term care service for old people is in great demand in most of the aging societies. The number of nursing homes residents is increasing while the number of care providers is limited. Due to the care worker shortage, care to vulnerable older residents cannot be fully tailored to the unique needs and preference of each individual. This may bring negative

Divya D. Joshi, Sachin Bhalekar, Prashant M. Gade

One of the most popular methods of controlling dynamical systems is feedback. It can be used without acquiring detailed knowledge of the underlying system. In this work, we study the stability of fractional-order linear difference equations under feedback. The stability results are derived for an arbitrary feedback time $\tau$. We study the cases of $\tau=1$

Ritam Banerjee, Ananthakrishna Gopal, Soham Bhandary, Pavitra Batra

Achieving chemical accuracy for strongly correlated molecules is a defining milestone for first-generation, fault-tolerant quantum computers, yet the factorial growth of three, four, and six-index tensor contractions in coupled-cluster CCSD(T), full configuration interaction (FCI), and multireference CI (MRCI) makes current classical and quantum approaches p

Aditi Agarwal

The Fermi fourth catalog of active galactic nuclei (AGNs) data release 3 (4LAC-DR3) contains 3407 AGNs, out of which 755 are flat spectrum radio quasars (FSRQs), 1379 are BL Lacertae objects (BL Lacs), 1208 are blazars of unknown (BCUs) type, while 65 are non AGNs. Accurate categorization of many unassociated blazars still remains a challenge due to the lack

Yee Lam Elim Thompson, Gary M Levine, Weijie Chen, Berkman Sahiner

In the past decade, Artificial Intelligence (AI) algorithms have made promising impacts to transform healthcare in all aspects. One application is to triage patients' radiological medical images based on the algorithm's binary outputs. Such AI-based prioritization software is known as computer-aided triage and notification (CADt). Their main benefit is to sp

Ya Wang, Qingmin Zhang, Zhenxiang Hong, Jinhua Shen

Solar jets are well-collimated plasma ejections in the solar atmosphere. They are prevalent in active regions, the quiet Sun, and even coronal holes. They display a range of temperatures, yet the nature of the cool components has not been fully investigated. In this paper, we show the existence of the precursors and quasi-periodic properties for two chromosp

Borui Cai, Shuiqiao Yang, Longxiang Gao, Yong Xiang

Variational autoencoders (VAE) are powerful generative models that learn the latent representations of input data as random variables. Recent studies show that VAE can flexibly learn the complex temporal dynamics of time series and achieve more promising forecasting results than deterministic models. However, a major limitation of existing works is that they

Tim Puphal, Malte Probst, Yiyang Li, Yosuke Sakamoto

We consider the problem of correct motion planning for T-intersection merge-ins of arbitrary geometry and vehicle density. A merge-in support system has to estimate the chances that a gap between two consecutive vehicles can be taken successfully. In contrast to previous models based on heuristic gap size rules, we present an approach which optimizes the int

Ziniu Li, Ke Xu, Liu Liu, Lanqing Li

Reinforcement learning (RL) has shown promise for decision-making tasks in real-world applications. One practical framework involves training parameterized policy models from an offline dataset and subsequently deploying them in an online environment. However, this approach can be risky since the offline training may not be perfect, leading to poor performan

Liya Gaynutdinova, Ondřej Rokoš, Jan Havelka, Ivana Pultarová

Materials with heterogeneous structures exhibit complex physical processes such as delamination, cracks, and plasticity, which require micromechanical parameters for understanding. However, identifying these parameters is challenging due to micro-macro length scale differences, ambiguity in boundary conditions, and required high resolution, among others. Whi

Oleksandr Rossolov, Yusak O. Susilo

This paper presents the behavioral study's results on willingness-to-pay the extra money by the customers for e-groceries deliveries based on crowd-shipping. The proposed methodology was tested for Ukraine, i.e., a developing country where the crowd-shipping services are under development conditions. To account for the behavior complexity of the consumers wh

Ben Willetts

This paper conveys the theoretical sensing capability of a Joint Communication and Sensing (JCAS) system that utilizes a True-Time-Delay (TTD) array configuration. The TTD beamformer separates subcarrier beams into different angular locations for wide-beam coverage. The bistatic sensing performance of a TTD array configuration is modeled as a function of the

Raksi Kopo, Charalampos P. Bechlioulis, Kostas J. Kyriakopoulos

This work presents an safe and efficient methodology for autonomous indoor exploration with aerial robots using Harmonic Potential Fields (HPF). The challenge of applying HPF in complex 3D environments rests on high computational load involved in solving the Laplace equation. To address this issue, the proposed solution utilizes the Fast Multiple accelerated

Andrei Buciulea, Antonio G. Marques

Graphs have become pervasive tools to represent information and datasets with irregular support. However, in many cases, the underlying graph is either unavailable or naively obtained, calling for more advanced methods to its estimation. Indeed, graph topology inference methods that estimate the network structure from a set of signal observations have a long

Esperanza Maya-Barbecho, José-Enrique García-Ramos

In this contribution we study the even-even Sr isotopes considering the influence of particle-hole intruder states. We find that the rapid onset of deformation at A $=98$ and onwards can be explained by the crossing of regular and intruder states. We compare the systematics of Sr with the ones of Zr, Pt, and Hg nuclei

Hamed Haghshenas, Anders Hansson, Mikael Norrlöf

This paper studies the time-optimal path tracking problem for a team of cooperating robotic manipulators carrying an object. Considering the problem for rigidly grasped objects, we show that it can be cast as a convex optimization problem and solved efficiently with a guarantee of optimality. When formulating the problem, we avoid using a particular wrench d

Tomona Kinugawa, Tetsuo Hyodo

The compositeness of weakly bound states is discussed using the effective field theory from the viewpoint of the low-energy universality. We introduce a model with coupling of the single-channel scattering to the bare state, and study the compositeness of the bound state by varying the bare state energy. In contrast to the naive expectation that the near-thr

Rainis Haller, Johann Langemets, Yoël Perreau, Triinu Veeorg

We introduce a new diametral notion for points of the unit sphere of Banach spaces, that naturally complements the notion of Delta-points, but is weaker than the notion of Daugavet points. We prove that this notion can be used to provide a new geometric characterization of the Daugavet property, as well as to recover -- and even to provide new -- results abo

Vivek Kumar Singh, Sachin Chauhan, Aditya Dwivedi, P. Ramadevi

We obtain a quiver representation for a family of knots called double twist knots $K(p,-m)$. Particularly, we exploit the reverse engineering of Melvin-Morton-Rozansky(MMR) formalism to deduce the pattern of the charge matrix for these quivers.

Shuchang Shen, Sachith Seneviratne, Xinye Wanyan, Michael Kirley

In recent decades, wildfires, as widespread and extremely destructive natural disasters, have caused tremendous property losses and fatalities, as well as extensive damage to forest ecosystems. Many fire risk assessment projects have been proposed to prevent wildfires, but GIS-based methods are inherently challenging to scale to different geographic areas du

Christos Matsoukas, Johan Fredin Haslum, Moein Sorkhei, Magnus Söderberg

Convolutional Neural Networks (CNNs) have reigned for a decade as the de facto approach to automated medical image diagnosis, pushing the state-of-the-art in classification, detection and segmentation tasks. Over the last years, vision transformers (ViTs) have appeared as a competitive alternative to CNNs, yielding impressive levels of performance in the nat

Cong Wang, Jinshan Pan, Wanyu Lin, Jiangxin Dong

This work presents an effective depth-consistency self-prompt Transformer for image dehazing. It is motivated by an observation that the estimated depths of an image with haze residuals and its clear counterpart vary. Enforcing the depth consistency of dehazed images with clear ones, therefore, is essential for dehazing. For this purpose, we develop a prompt

Chanaprom Cholsuk, Siavash Davani, Lorcan O. Conlon, Tobias Vogl

Quantum algorithms can potentially overcome the boundary of computationally hard problems. One of the cornerstones in modern optics is the beam propagation algorithm, facilitating the calculation of how waves with a particular dispersion relation propagate in time and space. This algorithm solves the wave propagation equation by Fourier transformation, multi

H. Lu, O. Holderer, A. Ioffe, S. Pasini

We report the first results from a new approach for measuring the $^3$He neutron incoherent scattering length $b_{i}$. $b_{i}$ is directly proportional to the difference $\Delta b=b_{+}-b_{-}$ in the two low-energy s-wave neutron-nucleus scattering amplitudes $b_{+}$ and $b_{-}$, corresponding to the singlet $J=0$ and triplet $J=1$ states of the neutron-$^3$

Amir Shaikhha, Mathieu Huot, Shideh Hashemian

Sparse tensors are prevalent in many data-intensive applications, yet existing differentiable programming frameworks are tailored towards dense tensors. This presents a significant challenge for efficiently computing gradients through sparse tensor operations, as their irregular sparsity patterns can result in substantial memory and computational overheads.

A. Maia, R. Vilarinho, C. Kadlec, M. Lebeda

We report a comprehensive study of the low-level substitution of Mn$^{3+}$ by Fe$^{3+}$ effect on the static and dynamic magnetoelectric coupling in TbMn$_{1-x}$Fe$_x$O$_3$ ($x=0$, 0.02 and 0.04). The cationic substitution has a large impact on the balance between competitive magnetic interactions and, as a result, on the stabilization of the magnetic struct

Meinolf Geck

Let $q$ be a prime power and $F_4(q)$ be the Chevalley group of type $F_4$ over a finite field with $q$ elements. Marcelo--Shinoda (1995) determined the values of the unipotent characters of $F_4(q)$ on all unipotent elements, extending earlier work by Kawanaka and Lusztig to small characteristics. Assuming that $q$ is a power of~$2$, we explain how to const

Henri Gode, Simon Doclo

Interfering sources, background noise and reverberation degrade speech quality and intelligibility in hearing aid applications. In this paper, we present an adaptive algorithm aiming at dereverberation, noise and interferer reduction and preservation of binaural cues based on the wBLCMP beamformer. The wBLCMP beamformer unifies the multi-channel weighted pre

Cihan Acar, Kuluhan Binici, Alp Tekirdağ, Yan Wu

The use of multi-camera views simultaneously has been shown to improve the generalization capabilities and performance of visual policies. However, the hardware cost and design constraints in real-world scenarios can potentially make it challenging to use multiple cameras. In this study, we present a novel approach to enhance the generalization performance o

Sayani Pal, Soumik Aon, Subhadip Manna, Sambhu G Nath

We have studied ferromagnetic metal/topological insulator bilayer system to understand magnetization dynamics of ferromagnetic metal (FM) in contact with a topological insulator (TI). At magnetic resonance condition, the precessing magnetization in the metallic ferromagnet ($Ni_{80}Fe_{20}$) injects spin current into the topological insulator ($BiSbTe_{1.5}S

Shaina Raza, Syed Raza Bashir, Sneha, Urooj Qamar

The concept of fairness is gaining popularity in academia and industry. Social media is especially vulnerable to media biases and toxic language and comments. We propose a fair ML pipeline that takes a text as input and determines whether it contains biases and toxic content. Then, based on pre-trained word embeddings, it suggests a set of new words by subst

Anna Gallo, Diego Garlaschelli, Renaud Lambiotte, Fabio Saracco

The abundance of data about social relationships allows the human behavior to be analyzed as any other natural phenomenon. Here we focus on balance theory, stating that social actors tend to avoid establishing cycles with an odd number of negative links. This statement, however, can be supported only after a comparison with a benchmark. Since the existing on

Gang Liu, Saminathan Ponnusamy, Victor V. Starkov

Let $\mathcal{H}_0$ denote the set of all sense-preserving harmonic mappings $f=h+\overline{g}$ in the unit disk $\ID$, normalized with $h(0)=g(0)=g'(0)=0$ and $h'(0)=1$. In this paper, we investigate some properties of certain subclasses of $\mathcal{H}_0$, including inclusion relations and stability analysis by precise examples, coefficient bounds, growth,

Amitesh S. Jayaraman, Jikai Ye, Gregory S. Chirikjian

This article reports the modeling of inertial rotational Brownian motion as an Ornstein-Uhlenbeck process evolving on the cotangent bundle of the rotation group, SO(3). The benefit of this approach and the use of a different parameterization of rotations allows the handling of particles with arbitrary shapes, without requiring any simplifying assumptions on

Kiichi Tokuyama, Tatsuaki Kimura, Naoto Miyoshi

Handover (HO) management is one of the most crucial tasks in dense cellular networks with mobile users. A problem in the HO management is to deal with increasing HOs due to network densification in the 5G evolution and various HO skipping techniques have so far been studied in the literature to suppress excessive HOs. In this paper, we propose yet another HO

Enrico Di Lucente, Michele Simoncelli, Nicola Marzari

Skutterudites are crystals with a cage-like structure that can be augmented with filler atoms ("rattlers"), usually leading to a reduction in thermal conductivity that can be exploited for thermoelectric applications. Here, we leverage the recently introduced Wigner formulation of thermal transport to elucidate the microscopic physics underlying heat conduct

Xinrui Chen, Bingquan Zhang

As fatigue is normally revealed in the eyes and mouth of a person's face, this paper tried to construct a XGBoost Algorithm-Based fatigue recognition model using the two indicators, EAR (Eye Aspect Ratio) and MAR(Mouth Aspect Ratio). With an accuracy rate of 87.37% and sensitivity rate of 89.14%, the model was proved to be efficient and valid for further app

N. Crescini, E. G. Kelly, G. Salis, A. Fuhrer

The accuracy of microwave measurements is not only critical for applications in telecommunication and radar, but also for future quantum computers. Qubit technologies such as superconducting qubits or spin qubits require detecting minuscule signals, typically achieved by reflecting a microwave tone off a resonator that is coupled to the qubit. Noise from cab

Camilla Felisetti, Franco Giovenzana, Annalisa Grossi

We give a lattice-theoretic characterization for a manifold of $\mathrm{OG}10$ type to be birational to some moduli space of (twisted) sheaves on a K3 surface. We apply it to the Li-Pertusi-Zhao variety of $\mathrm{OG}10$ type associated to any smooth cubic fourfold. Moreover we determine when a birational transformation is induced by an automorphism of the

Paul Streli, Rayan Armani, Yi Fei Cheng, Christian Holz

Current Virtual Reality systems are designed for interaction under visual control. Using built-in cameras, headsets track the user's hands or hand-held controllers while they are inside the field of view. Current systems thus ignore the user's interaction with off-screen content -- virtual objects that the user could quickly access through proprioception wit