May 2022 arXiv papers — page 44

Zi-wei Wang, Zi-ang Li, Xu-hui Bai, Ting Gong

We establish a theoretical model to analyze the photoassociative (PA) spectroscopy of $(3)^3\Sigma^+$ state of $^{85}$Rb$^{133}$Cs molecule. The term energy, spin-spin coupling constants and hyperfine interaction constant of nine vibrational levels in the $(3)^3\Sigma^+$ state are determined. Based on the fitted term energy and rotation constant, the potenti

Sheng Dai, Timo Kuosmanen, Xun Zhou

Quantile regression and partial frontier are two distinct approaches to nonparametric quantile frontier estimation. In this article, we demonstrate that partial frontiers are not quantiles. Both convex and nonconvex technologies are considered. To this end, we propose convexified order-$\alpha$ as an alternative to convex quantile regression (CQR) and convex

Ryohei Miyadera, Hikaru Manabe, Shunsuke Nakamura

In this study, we investigate three-dimensional chocolate bar games, which are variants of the game of Chomp. A three-dimensional chocolate bar is a three-dimensional array of cubes in which a bitter cubic box is present in some part of the bar. Two players take turns and cut the bar horizontally or vertically along the grooves. The player who manages to lea

Lidia Angeleri Hügel, Ivo Herzog, Rosanna Laking

Every cotilting module over a ring R induces a t-structure with a Grothendieck heart in the derived category D(Mod R). We determine the simple objects in this heart and their injective envelopes, combining torsion-theoretic aspects with methods from the model theory of modules and Auslander-Reiten theory.

K. G Paulson, Subhashish Banerjee

We derive Margolus-Levitin and Mandelstamm-Tamm type bound on the quantum speed limit time for the creation and decay of quantum correlations by an amount in a quantum system evolving under the influence of its ambient environment. The minimum distance of a non-classical state from an appropriate set of classical states is a legitimate measure of the quantum

Zhiyuan Zhao, Mingcheng Yang, Shigeyuki Komura, Ryohei Seto

Prior studies have revealed that nonzero odd viscosity is an essential property for chiral active fluids. Here we report that such an odd viscosity also exists in suspensions of non-active or non-externally-driven but chirally-shaped particles. Computational simulations are carried out for monolayers of dense ratchets in simple shear and planar extensional f

Qian Fu, Linlin Liu, Fei Hou, Ying He

Aiming at developing intuitive and easy-to-use portrait editing tools, we propose a novel vectorization method that can automatically convert raster images into a 3-tier hierarchical representation. The base layer consists of a set of sparse diffusion curves (DC) which characterize salient geometric features and low-frequency colors and provide means for sem

Michal Czakon, Alexander Mitov, Rene Poncelet

Flavour tagging is technically challenging on the experimental side. However, it suffers from a more fundamental problem from the theoretical point of view, in particular when implemented in fixed-order perturbation theory. It turns out that an infrared-safe definition of a flavoured jet is intricate due to the singularities induced by the emission of flavou

Luciano Freitas, Petr Kuznetsov, Andrei Tonkikh

Randomisation is a critical tool in designing distributed systems. The common coin primitive, enabling the system members to agree on an unpredictable random number, has proven to be particularly useful. We observe, however, that it is impossible to implement a truly random common coin protocol in a fault-prone asynchronous system. To circumvent this impossi

Rajeev Bhaskaran

In this paper, following earlier results in [2] we derive the asymptotic distribution as $t \to \infty$, of the excursion of Brownian motion straddling $t$, into an interval $(a,b)$, conditional on the event that there is such an excursion.

Di Wang, Jinyuan Liu, Xin Fan, Risheng Liu

Recent learning-based image fusion methods have marked numerous progress in pre-registered multi-modality data, but suffered serious ghosts dealing with misaligned multi-modality data, due to the spatial deformation and the difficulty narrowing cross-modality discrepancy. To overcome the obstacles, in this paper, we present a robust cross-modality generation

M. Pregelj, A. Zorko, D. Arčon, M. Klanjšek

In frustrated spin-1/2 chains the competition between the nearest- and next-nearest-neighbor exchange interactions leads to a rich phase diagram that becomes even richer in the presence of perturbations in their material realizations. These effects are still largely unexplored, so that new insight into static and dynamic magnetism, in particular by sensitive

Antoine Gonon, Nicolas Brisebarre, Rémi Gribonval, Elisa Riccietti

We deal with two complementary questions about approximation properties of ReLU networks. First, we study how the uniform quantization of ReLU networks with real-valued weights impacts their approximation properties. We establish an upper-bound on the minimal number of bits per coordinate needed for uniformly quantized ReLU networks to keep the same polynomi

Gaoyang Pang, Wanchun Liu, Yonghui Li, Branka Vucetic

Remote state estimation, where sensors send their measurements of distributed dynamic plants to a remote estimator over shared wireless resources, is essential for mission-critical applications of Industry 4.0. Existing algorithms on dynamic radio resource allocation for remote estimation systems assumed oversimplified wireless communications models and can

Sophie Chauvet, Florence Hubert, Fanny Mann, Mathieu Mezache

The nervous system is today recognized to play an important role in the development of cancer. Indeed, neurons extend long processes (axons) that grow and infiltrate tumors in order to regulate the progression of the disease in a positive or negative way, depending on the type of neuron considered. Mathematical modelling of this biological process allows to

Athanasios C. Tzemos, George Contopoulos

We consider the Bohmian trajectories in a 2-d quantum harmonic oscillator with non commensurable frequencies whose wavefunction is of the form $\Psi=a\Psi_{m_1,n_1}(x,y)+b\Psi_{m_2,n_2}(x,y)+c\Psi_{m_3,n_3}(x,y)$. We first find the trajectories of the nodal points for different combinations of the quantum numbers $m,n$. Then we study, in detail, a case with

François Rivière, Timothée de Guillebon, Léo Maumet, Gabriel Hétet

Using the spin properties of nitrogen-vacancy (NV) centers in levitated diamond, we characterize the absorption of single nanodiamonds. We first calibrate the thermometry response of the NV centers embedded in our nanodiamonds. Then, using this calibration, we estimate the absorption cross-section of single levitated nanodiamonds. We show that this absorptio

Anqi Huang, Akihiro Mizutani, Hoi-Kwong Lo, Vadim Makarov

To achieve secure quantum key distribution, all imperfections in the source unit must be incorporated in a security proof and measured in the lab. Here we perform a proof-of-principle demonstration of the experimental techniques for characterising the source phase and intensity fluctuation in commercial quantum key distribution systems. When we apply the mea

Yishan Xu, Jinshuang Jin, Shikuan Wang, YiJing Yan

Within the second-order non-Markovian master equation description, we develop an efficient method for calculating the noise spectrum of transport current through interacting mesoscopic systems. By introducing proper current-related density operators, we propose a practical and very efficient time-local approach to compute the noise spectrum, including the as

Jérémy Martin

In this paper, new spectral inequalities for finite combinations of eigenfunctions of anisotropic Shubin operators are presented. Given a subset $\omega$ and an energy level, we provide an explicit control of the ratio of the L 2 (R d)-norm over the L 2 ($\omega$)-norm with respect to the energy level. The proofs are based on recent uncertainty principles ho

Tatsuya Ide, Daisuke Kawahara

In communication, a human would recognize the emotion of an interlocutor and respond with an appropriate emotion, such as empathy and comfort. Toward developing a dialogue system with such a human-like ability, we propose a method to build a dialogue corpus annotated with two kinds of emotions. We collect dialogues from Twitter and annotate each utterance wi

Zhi-Bo Yang, Wei-Jiang Wu, Jie Li, Yi-Pu Wang

For solid-state spin systems, the collective spin motion in a single crystal embodies multiple magnetostatic modes. Recently, it was found that the cross-Kerr interaction between the higher-order magnetostatic mode and the Kittel mode introduces a new operable degree of freedom. In this work, we propose a scheme to entangle two magnon modes via the cross-Ker

Barbara Jung, Anna-Maria von Pippich

Let $\mathcal{A}_g$ denote the moduli stack of principally polarized abelian varieties of dimension $g$. The arithmetic height, or arithmetic volume, of $\overline{\mathcal{A}}_g$, is defined to be the arithmetic degree of the metrized Hodge bundle $\overline{\omega}_g$ on $\overline{\mathcal{A}}_g$. In 1999, K\"uhn proved a formula for the arithmetic volume

Jennifer D'Souza

We are faced with an unprecedented production in scholarly publications worldwide. Stakeholders in the digital libraries posit that the document-based publishing paradigm has reached the limits of adequacy. Instead, structured, machine-interpretable, fine-grained scholarly knowledge publishing as Knowledge Graphs (KG) is strongly advocated. In this work, we

Quentin Vila

We study the long-time behaviour of axisymmetric solutions without swirl for the threedimensional Navier-Stokes equations in the whole space. Assuming that the initial vorticity is sufficiently localised, we compute explicitly the leading terms in the asymptotic expansion of the solution, both for the vorticity and the velocity field. In particular, we ident

Gaoyang Pang, Wanchun Liu, Yonghui Li, Branka Vucetic

Remote state estimation, where many sensors send their measurements of distributed dynamic plants to a remote estimator over shared wireless resources, is essential for mission-critical applications of Industry 4.0. Most of the existing works on remote state estimation assumed orthogonal multiple access and the proposed dynamic radio resource allocation algo

Phelan Yu, Adrian Lopez, William A. Goddard, Nicholas R. Hutzler

Optical control of polyatomic molecules promises new opportunities in precision metrology, fundamental chemistry, quantum information, and many-body science. Contemporary experimental and theoretical efforts have mostly focused on cycling photons via excitation of a single electron localized to an alkaline earth (group 2)-like metal center. In this manuscrip

Julian Berberich, Johannes Köhler, Matthias A. Müller, Frank Allgöwer

Data-driven model predictive control (DD-MPC) based on Willems' Fundamental Lemma has received much attention in recent years, allowing to control systems directly based on an implicit data-dependent system description. The literature contains many successful practical applications as well as theoretical results on closed-loop stability and robustness. In th

Inácio Bó, Chiu Yu Ko

We consider the problem of designing prices for public transport where payment enforcing is done through random inspection of passengers' tickets as opposed to physically blocking their access. Passengers are fully strategic such that they may choose different routes or buy partial tickets in their optimizing decision. We derive expressions for the prices th

Shijie Zhang, Wei Yuan, Hongzhi Yin

In recent years, recommender systems are crucially important for the delivery of personalized services that satisfy users' preferences. With personalized recommendation services, users can enjoy a variety of recommendations such as movies, books, ads, restaurants, and more. Despite the great benefits, personalized recommendations typically require the collec

S. H. Chiu, T. K. Kuo

The eigenvector-eigenvalue identities are expanded to include general mixing parameters. Some simple relations are obtained and they reveal an intricate texture of connections between the eigenvalues and the mixing parameters. Permutation symmetry ($S_{3}\times S_{3}$) plays an indispensable role in our analysis. It is the guiding principle for the understan

Ajit Kumar Gupta, Saikat Mukherjee

A generalization of the Lebesgue number lemma is obtained. It is proved that, if each countably infinite locally finite open cover of a chainable metric space $X$ has a Lebesgue number, then $X$ is totally bounded. A property of metric spaces which is a generalization of connectedness and Menger convexity is introduced. It is observed that Atsujiness and com

Zhiwei Hao, Guanyu Xu, Yong Luo, Han Hu

Recently, deploying deep neural network (DNN) models via collaborative inference, which splits a pre-trained model into two parts and executes them on user equipment (UE) and edge server respectively, becomes attractive. However, the large intermediate feature of DNN impedes flexible decoupling, and existing approaches either focus on the single UE scenario

Anat Ninio

Language sciences rely less and less on formal syntax as their base. The reason is probably its lack of psychological reality, knowingly avoided. Philosophers of science call for a paradigm shift in which explanations are by mechanisms, as in biology. We turned to programming languages as heuristic models for a process-based syntax of English. The combinatio

Cheng Jie, Chen Yingbing, Zhang Qingwen, Gan Lu

Real-time kinodynamic trajectory planning in dynamic environments is critical yet challenging for autonomous driving. In this letter, we propose an efficient trajectory planning system for autonomous driving in complex dynamic scenarios through iterative and incremental path-speed optimization. Exploiting the decoupled structure of the planning problem, a pa

E. Keihanen, V. Lindholm, P. Monaco, L. Blot

We present a method for fast evaluation of the covariance matrix for a two-point galaxy correlation function (2PCF) measured with the Landy-Szalay estimator. The standard way of evaluating the covariance matrix consists in running the estimator on a large number of mock catalogs, and evaluating their sample covariance. With large random catalog sizes (data-t

Ryohei Miyadera, Hikaru Manabe

This paper presents a study of restricted Nim with a pass. In the restricted Nim considered in this study, two players take turns and remove stones from the piles. In each turn, when the number of stones is m, each player is allowed to remove at least one stone and at most the ceiling of m/2 stones from a pile of m stones. The standard rules of the game are

Zifan Wang, Yuhang Yao, Chaoran Zhang, Han Zhang

This paper studies faithful explanations for Graph Neural Networks (GNNs). First, we provide a new and general method for formally characterizing the faithfulness of explanations for GNNs. It applies to existing explanation methods, including feature attributions and subgraph explanations. Second, our analytical and empirical results demonstrate that feature

Junyong Wang, Yuan Zeng, Yi Gong

Accurate detection of objects in 3D point clouds is a key problem in autonomous driving systems. Collaborative perception can incorporate information from spatially diverse sensors and provide significant benefits for improving the perception accuracy of autonomous driving systems. In this work, we consider that the autonomous vehicle uses local point cloud

Yukiyasu Moriya, Taiki Matsushita, Masahiko G. Yamada, Takeshi Mizushima

We investigate the intrinsic anomalous thermal Hall effect as an effective probe of the order parameters of non-unitary pairing states of the putative spin-triplet superconductor UTe$_2$. We consider all symmetry-allowed non-unitary states under magnetic fields comprehensively, and calculate the anomalous Hall conductivity arising from time-reversal symmetry

Idriss Mazari-Fouquer, Grégoire Nadin

We propose a fine analysis of second order optimality conditions for the optimal control of semi-linear parabolic equations with respect to the initial condition. More precisely, we investigate the following problem: maximise with respect to $y\in L^\infty({(0;T)\times \Omega})$ the cost functional $J(y)=\iint_{(0;T)\times \Omega}j_1(t,x,u)+\int_\Omega j_2(x

Ang Liu, Feng-Lan Shao, Zhi-Long Han, Yi Jin

In this paper, we propose the sterile neutrino portal dark matter in $\nu$THDM. This model can naturally generate tiny neutrino mass with the neutrinophilic scalar doublet $\Phi_{\nu}$ and sterile neutrinos $N$ around TeV scale. Charged under a $Z_2$ symmetry, one Dirac fermion singlet $\chi$ and one scalar singlet $\phi$ are further introduced in the dark s

Zhiwei Hao, Yong Luo, Zhi Wang, Han Hu

Recently, the compression and deployment of powerful deep neural networks (DNNs) on resource-limited edge devices to provide intelligent services have become attractive tasks. Although knowledge distillation (KD) is a feasible solution for compression, its requirement on the original dataset raises privacy concerns. In addition, it is common to integrate mul

Raveena Khan, K. Nagaraju

The diagnostic capabilities of spectral lines in far ultraviolet (FUV) and extreme ultraviolet (EUV) wavelength range are explored in terms of their Hanle and Zeeman sensitivity to probe vector magnetic field in the solar corona. The temperature range covered is log$_{10}(T)=5.5-6.3$. The circular polarization signal due to longitudinal Zeeman effect is esti

Anay Ajit Deshpande, Roberto Pereira, Federico Chiariotti, Adriano Pastore

Routing is a crucial component in the design of Flying Ad-Hoc Networks (FANETs). State of the art routing solutions exploit the position of Unmanned Aerial Vehicles (UAVs) and their mobility information to determine the existence of links between them, but this information is often unreliable, as the topology of FANETs can change quickly and unpredictably. I

Ajit Kumar Gupta, Saikat Mukherjee

Given uniformly homeomorphic metric spaces $X$ and $Y$, it is proved that the hyperspaces $C(X)$ and $C(Y)$ are uniformly homeomorphic, where $C(X)$ denotes the collection of all nonempty closed subsets of $X$, and is endowed with Hausdorff distance. Gerald Beer has proved that the hyperspace $C(X)$ is Atsuji when $X$ is either compact or uniformly discrete.

Xulong Zhang, Jianzong Wang, Ning Cheng, Jing Xiao

Singing voice synthesis is a generative task that involves multi-dimensional control of the singing model, including lyrics, pitch, and duration, and includes the timbre of the singer and singing skills such as vibrato. In this paper, we proposed SU-net for singing voice synthesis named SUSing. Synthesizing singing voice is treated as a translation task betw

Tiago Timponi Torrent, Arthur Lorenzi, Ely Edison da Silva Matos, Frederico Belcavello

This paper presents Lutma, a collaborative, semi-constrained, tutorial-based tool for contributing frames and lexical units to the Global FrameNet initiative. The tool parameterizes the process of frame creation, avoiding consistency violations and promoting the integration of frames contributed by the community with existing frames. Lutma is structured in a

Pinchen Xie, Yixiao Chen, Xinyu Xu, Zhi Yao

We report a systematic and accurate approach for deriving the bulk free energy surface (FES), a function of temperature, polarization, and strain, from the first-principles density functional theory (DFT) of proper ferroelectrics. The core of our approach is the metadynamics algorithm that extracts the polarization dependence of the FES from all-atom molecul

Ivan Lau, Jonathan Scarlett, Yang Sun

The goal of the group testing problem is to identify a set of defective items within a larger set of items, using suitably-designed tests whose outcomes indicate whether any defective item is present. In this paper, we study how the number of tests can be significantly decreased by leveraging the structural dependencies between the items, i.e., by incorporat

Nathalie Revol, Luis Benet, Luca Ferranti, Sergei Zhilin

As developers of libraries implementing interval arithmetic, we faced the same difficulties when it came to testing our libraries. What must be tested? How can we devise relevant test cases for unit testing? How can we ensure a high (and possibly 100%) test coverage? In this paper we list the different aspects that, in our opinion, must be tested, giving ind

Frederico Belcavello, Marcelo Viridiano, Ely Edison Matos, Tiago Timponi Torrent

This paper presents Charon, a web tool for annotating multimodal corpora with FrameNet categories. Annotation can be made for corpora containing both static images and video sequences paired - or not - with text sequences. The pipeline features, besides the annotation interface, corpus import and pre-processing tools.

Fatma Sevinç Kurnaz, Peter Filzmoser

A robust and sparse estimator for multinomial regression is proposed for high dimensional data. Robustness of the estimator is achieved by trimming the observations, and sparsity of the estimator is obtained by the elastic net penalty, which is a mixture of $L_1$ and $L_2$ penalties. From this point of view, the proposed estimator is an extension of the enet

Cyril Bénézet, Stéphane Crépey

In this paper we revisit Burnett (2021) \& Burnett and Williams (2021)'s notion of hedging valuation adjustment (HVA), originally intended to deal with dynamic hedging frictions such as transaction costs, in the direction of model risk. The corresponding HVA reconciles a global fair valuation model with the local models used by the different desks of the ban

Sosuke Kobayashi, Shun Kiyono, Jun Suzuki, Kentaro Inui

Ensembling is a popular method used to improve performance as a last resort. However, ensembling multiple models finetuned from a single pretrained model has been not very effective; this could be due to the lack of diversity among ensemble members. This paper proposes Multi-Ticket Ensemble, which finetunes different subnetworks of a single pretrained model

Berken Utku Demirel, Luke Chen, Mohammad Abdullah Al Faruque

Providing health monitoring devices with machine intelligence is important for enabling automatic mobile healthcare applications. However, this brings additional challenges due to the resource scarcity of these devices. This work introduces a neural contextual bandits based dynamic sensor selection methodology for high-performance and resource-efficient body

Eloïse Berthier, Ziad Kobeissi, Francis Bach

Temporal-difference learning is a popular algorithm for policy evaluation. In this paper, we study the convergence of the regularized non-parametric TD(0) algorithm, in both the independent and Markovian observation settings. In particular, when TD is performed in a universal reproducing kernel Hilbert space (RKHS), we prove convergence of the averaged itera

Iason Katsamenis, Eleni Eirini Karolou, Agapi Davradou, Eftychios Protopapadakis

Substantial progress has been made in the field of object detection in road scenes. However, it is mainly focused on vehicles and pedestrians. To this end, we investigate traffic cone detection, an object category crucial for road effects and maintenance. In this work, the YOLOv5 algorithm is employed, in order to find a solution for the efficient and fast d

Yu-Xuan Chen, Dagan Feng, Hong-Bin Shen

Rigid image alignment is a fundamental task in computer vision, while the traditional algorithms are either too sensitive to noise or time-consuming. Recent unsupervised image alignment methods developed based on spatial transformer networks show an improved performance on clean images but will not achieve satisfactory performance on noisy images due to its

Priya Chakraborty, Sayantari Ghosh

Living cells need a constant availability of certain resources to have a sustained gene expression process. Limited availability of cellular resources for gene expression, like ribosomes, along with a variation of resource affinity, significantly modifies the system dynamics. Factors like the variation in rate of binding, or variation in efficiency of the re

Xavier Guidetti, Alisa Rupenyan, Lutz Fassl, Majid Nabavi

We propose a framework for the configuration and operation of expensive-to-evaluate advanced manufacturing methods, based on Bayesian optimization. The framework unifies a tailored acquisition function, a parallel acquisition procedure, and the integration of process information providing context to the optimization procedure. \cmtb{The novel acquisition fun

Jaehyo Yoo, Jaewoo Kang

Many machine translation models are trained on bilingual corpus, which consist of aligned sentence pairs from two different languages with same semantic. However, there is a qualitative discrepancy between train and test set in bilingual corpus. While the most train sentences are created via automatic techniques such as crawling and sentence-alignment method

Fangyu Shen, Wei Gao

Video-based point cloud compression (V-PCC) has been an emerging compression technology that projects the 3D point cloud into a 2D plane and uses high efficiency video coding (HEVC) to encode the projected 2D videos (geometry video and color video). In this work, we propose a rate control algorithm for the all-intra (AI) configuration of V-PCC. Specifically,

Xulong Zhang, Jianzong Wang, Ning Cheng, Jing Xiao

Recently, synthesizing personalized speech by text-to-speech (TTS) application is highly demanded. But the previous TTS models require a mass of target speaker speeches for training. It is a high-cost task, and hard to record lots of utterances from the target speaker. Data augmentation of the speeches is a solution but leads to the low-quality synthesis spe

Yifeng Zhou, Xing Xu, Shuaicheng Liu, Guoqing Wang

To achieve promising results on removing noise from real-world images, most of existing denoising networks are formulated with complex network structure, making them impractical for deployment. Some attempts focused on reducing the number of filters and feature channels but suffered from large performance loss, and a more practical and lightweight denoising

Jaehun Jung, Lianhui Qin, Sean Welleck, Faeze Brahman

Despite their impressive capabilities, large pre-trained language models (LMs) struggle with consistent reasoning; recently, prompting LMs to generate explanations that self-guide the inference has emerged as a promising direction to amend this. However, these approaches are fundamentally bounded by the correctness of explanations, which themselves are often

Xulong Zhang, Jianzong Wang, Ning Cheng, Jing Xiao

Metaverse has stretched the real world into unlimited space. There will be more live concerts in Metaverse. The task of singer identification is to identify the song belongs to which singer. However, there has been a tough problem in singer identification, which is the different live effects. The studio version is different from the live version, the data di

Ryo Namiki

We analyze the security against collective attacks for a homodyne-based continuous-variable quantum key distribution protocol using binary coherent states and postselection. We derive a lower bound of the secret key rate in an asymptotic scenario, and numerically optimize it for the case of a symmetric Gaussian channel.

Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang

Trojan attacks threaten deep neural networks (DNNs) by poisoning them to behave normally on most samples, yet to produce manipulated results for inputs attached with a particular trigger. Several works attempt to detect whether a given DNN has been injected with a specific trigger during the training. In a parallel line of research, the lottery ticket hypoth

Shiwei Shen, Tian Qin, Jingjing Gao, Chenhaoping Wen

Realization of Kondo lattice in superconducting van der Waals materials not only provides a unique opportunity for tuning the Kondo lattice behavior by electrical gating or intercalation, but also is helpful for further understanding the heavy fermion superconductivity. Here we report a low-temperature and vector-magnetic-field scanning tunneling microscopy

Xulong Zhang, Jianzong Wang, Ning Cheng, Jing Xiao

Metaverse is an interactive world that combines reality and virtuality, where participants can be virtual avatars. Anyone can hold a concert in a virtual concert hall, and users can quickly identify the real singer behind the virtual idol through the singer identification. Most singer identification methods are processed using the frame-level features. Howev

Arjun Berera, Jaime Calderón-Figueroa

The possibility of achieving quantum communication using photons across interstellar distances is examined. For this, different factors are considered that could induce decoherence of photons, including the gravitational field of astrophysical bodies, the particle content in the interstellar medium, and the more local environment of the Solar System. The X-r

Sarath Chandra Varma, Debayan Dasgupta, Aloke Kumar

Recent investigations on the coalescence of polymeric droplets on a solid substrate have reported strong disagreements; the heart of the issue is whether coalescence of polymeric drops is similar to that of Newtonian fluid and is independent of molecular relaxation, or whether the role of entanglement of polymeric chains leads to a transition kinetics differ

Linrui Zhang, Li Shen, Long Yang, Shixiang Chen

Safe reinforcement learning aims to learn the optimal policy while satisfying safety constraints, which is essential in real-world applications. However, current algorithms still struggle for efficient policy updates with hard constraint satisfaction. In this paper, we propose Penalized Proximal Policy Optimization (P3O), which solves the cumbersome constrai

Diego Arcis, Camilo González, Sebastián Márquez

We study in detail the Hopf algebra of noncommutative symmetric functions in superspace sNSym, introduced by Fishel, Lapointe and Pinto. We introduce a family of primitive elements of sNSym and extend the noncommutative elementary and power sum functions to superspace. Then, we give formulas relating these families of functions. Also, we introduce noncommuta

Boyu Li, Meng Wang, John E. Hopcroft, Kun He

Local community detection has attracted much research attention recently, and many methods have been proposed for the single local community detection that finds a community containing the given set of query nodes. However, nodes may belong to several communities in the network, and detecting all the communities for the query node set, termed as the multiple

Federica Naccarata, Giulio Maria Bianco, Gaetano Marrocco

Radiofrequency finger augmentation devices (R-FADs) are a recently introduced class of epidermal radiofrequency identification (RFID) sensor-tags attached to the fingers, communicating with a body-worn reader. These devices are promising candidates to enable Tactile Internet (TI) applications in the short term. R-FAD based on auto-tuning RFID microchips can

D. Ibadullayev, Yu. S. Tsyganov

A new wide-range formula $T_\alpha =f (Q_\alpha)$ to operate with the new DGFRS2 analog spectrometer installed at the DC-280 cyclotron facility is presented. The main goal of this formula application algorithm is to search the optimal time correlation recoil-alpha parameter directly during the execution of the C++ acquisition code. Note that the spectrometer

Jinhwi Lee, Jungtaek Kim, Hyunsoo Chung, Jaesik Park

Assembling parts into an object is a combinatorial problem that arises in a variety of contexts in the real world and involves numerous applications in science and engineering. Previous related work tackles limited cases with identical unit parts or jigsaw-style parts of textured shapes, which greatly mitigate combinatorial challenges of the problem. In this

Adrian Schumacher, Ruben Merz, Andreas Burg

Modern trains act as Faraday cages making it challenging to provide high cellular data capacities to passengers. A solution is the deployment of linear cells along railway tracks, forming a cellular corridor. To provide a sufficiently high data capacity, many cell sites need to be installed at regular distances. However, such cellular corridors with high pow

Shangyu Wu, Yufei Cui, Jinghuan Yu, Xuan Sun

Recent works on learned index open a new direction for the indexing field. The key insight of the learned index is to approximate the mapping between keys and positions with piece-wise linear functions. Such methods require partitioning key space for a better approximation. Although lots of heuristics are proposed to improve the approximation quality, the bo

Meng-Ru Wu, Projjwal Banerjee

Although the multimessenger detection of the neutron star merger event GW170817 confirmed that mergers are promising sites producing the majority of nature's heavy elements via the rapid neutron-capture process ($r$-process), a number of issues related to the production of translead nuclei -- the actinides -- remain to be answered. In this short review paper

George P. Harabin, Morad Behandish

Hybrid manufacturing (HM) technologies combine additive and subtractive manufacturing (AM/SM) capabilities in multi-modal process plans that leverage the strengths of each. Despite the growing interest in HM technologies, software tools for process planning have not caught up with advances in hardware and typically impose restrictions that limit the design a

Hung-Min Hsu, Xinyu Yuan, Baohua Zhu, Zhongwei Cheng

Package theft detection has been a challenging task mainly due to lack of training data and a wide variety of package theft cases in reality. In this paper, we propose a new Global and Local Fusion Package Theft Detection Embedding (GLF-PTDE) framework to generate package theft scores for each segment within a video to fulfill the real-world requirements on

Lesheng Jin, Zihan Wang, Jingbo Shang

Existing backdoor defense methods are only effective for limited trigger types. To defend different trigger types at once, we start from the class-irrelevant nature of the poisoning process and propose a novel weakly supervised backdoor defense framework WeDef. Recent advances in weak supervision make it possible to train a reasonably accurate text classifie

Alexander V. Osipov

A topological space $X$ is Baire if the Baire Category Theorem holds for $X$, i.e., the intersection of any sequence of open dense subsets of $X$ is dense in $X$. In this paper, we have obtained that the space $B^{st}_1(X)$ of pointwise stabilizing Baire-one functions is Baire if the space $B_1(X)$ of Baire-one functions is so. This answers a question posed

Aritra Bhattacharya

Haglund's conjecture states that $\dfrac{\langle J_{\lambda}(q,q^k),s_\mu \rangle}{(1-q)^{|\lambda|}} \in \mathbb{Z}_{\geq 0}[q]$ for all partitions $\lambda,\mu$ and all non-negative integers $k$, where $J_{\lambda}$ is the integral form Macdonald symmetric function and $s_\mu$ is the Schur function. This paper proves Haglund's conjecture in the cases when

Divya Kothandaraman, Sumit Shekhar, Abhilasha Sancheti, Manoj Ghuhan

We present a novel method, SALAD, for the challenging vision task of adapting a pre-trained "source" domain network to a "target" domain, with a small budget for annotation in the "target" domain and a shift in the label space. Further, the task assumes that the source data is not available for adaptation, due to privacy concerns or otherwise. We postulate t

Shahar Lutati, Eliya Nachmani, Lior Wolf

We present an upper bound for the Single Channel Speech Separation task, which is based on an assumption regarding the nature of short segments of speech. Using the bound, we are able to show that while the recent methods have made significant progress for a few speakers, there is room for improvement for five and ten speakers. We then introduce a Deep neura

STAR Collaboration, M. S. Abdallah, B. E. Aboona, J. Adam

The STAR Collaboration reports measurements of the transverse single-spin asymmetries, $A_N$, for inclusive jets and identified `hadrons within jets' production at midrapidity from transversely polarized $pp$ collisions at $\sqrt{s}$ = 200 GeV, based on data recorded in 2012 and 2015. The inclusive jet asymmetry measurements include $A_N$ for inclusive jets

Zihan Wang, Kewen Zhao, Zilong Wang, Jingbo Shang

Fine-tuning pre-trained language models has recently become a common practice in building NLP models for various tasks, especially few-shot tasks. We argue that under the few-shot setting, formulating fine-tuning closer to the pre-training objectives shall be able to unleash more benefits from the pre-trained language models. In this work, we take few-shot n

Jiachen Li, Ye Yuan, Hong-Bin Shen

Symbolic Regression (SR) is a type of regression analysis to automatically find the mathematical expression that best fits the data. Currently, SR still basically relies on various searching strategies so that a sample-specific model is required to be optimized for every expression, which significantly limits the model's generalization and efficiency. Inspir

Ngoc Hoang Anh Mai

Let $f,g_1,\dots,g_m$ be polynomials of degree at most $d$ with real coefficients in a vector of variables $x=(x_1,\dots,x_n)$. Assume that $f$ is non-negative on a basic semi-algebraic set $S$ defined by polynomial inequalities $g_j(x)\ge 0$, for $j=1,\dots,m$. Our previous work [arXiv:2205.04254 (2022)] has stated several representations of $f$ based on th

Liping Hou, Ke Lu, Xue Yang, Yuqiu Li

Typical representations for arbitrary-oriented object detection tasks include oriented bounding box (OBB), quadrilateral bounding box (QBB), and point set (PointSet). Each representation encounters problems that correspond to its characteristics, such as the boundary discontinuity, square-like problem, representation ambiguity, and isolated points, which lea

Jihang Wang, Dongcheng Zhao, Guobin Shen, Qian Zhang

Privacy protection is a crucial issue in machine learning algorithms, and the current privacy protection is combined with traditional artificial neural networks based on real values. Spiking neural network (SNN), the new generation of artificial neural networks, plays a crucial role in many fields. Therefore, research on the privacy protection of SNN is urge

Chenlin Hang, Tetsuo Ono, Seiji Yamada

Perspective taking, which allows people to imagine another's thinking and goals, is known to be an effective method for promoting prosocial behaviors in human-computer interactions. However, most of the previous studies have focused on simulating human-human interactions in the real world by offering participants experiences related to various moral tasks th

Zhaoyue Chen, Yifan Sun

The Frank-Wolfe method is a popular method in sparse constrained optimization, due to its fast per-iteration complexity. However, the tradeoff is that its worst case global convergence is comparatively slow, and importantly, is fundamentally slower than its flow rate--that is to say, the convergence rate is throttled by discretization error. In this work, we

L. T. Nguyen, Y. L Chang, C. C Hu, J. S Chen

In this article, we introduce the interval optimization problems (IOPs) on Hadamard manifolds as well as study the relationship between them and the interval variational inequalities. To achieve the theoretical results, we build up some new concepts about $gH$-directional derivative and $gH$-G\^ateaux differentiability of interval valued functions and their

Martin Bays, Omer Ben-Neria, Itay Kaplan, Pierre Simon

We study cofinal systems of finite subsets of $\omega_1$. We show that while such systems can be NIP, they cannot be defined in an NIP structure. We deduce a positive answer to a question of Chernikov and Simon from 2013: in an NIP theory, any uncountable externally definable set contains an infinite definable subset. A similar result holds for larger cardin

Anita Arora, Arvind Ayyer

The monopole-dimer model is a signed variant of the monomer-dimer model which has determinantal structure. We extend the monopole-dimer model for planar graphs (Math. Phys. Anal. Geom., 2015) to Cartesian products thereof and show that the partition function of this model can be expressed as a determinant of a generalised signed adjacency matrix. We then sho