December 2023 arXiv papers — page 16

Avdhesh Kumar, Philipp Gubler, Di-Lun Yang

Starting with the polarization dependent Wigner function of vector mesons, we derive an expression for the 00-component ($\rho_{00}$) of spin density matrix in terms of the second order gradients of the vector meson distribution functions. We further apply a thermal model to analyze the transverse momentum and the azimuthal angle dependence of $\rho_{00}$ fo

Xi Zhang, Xiuquan Xia, Qiye Liu, Yonggang He

The exchange bias (EB) effect, pivotal in magnetic data storage and sensing devices, has been observed not only in interfacial regions but also in intrinsic ferromagnetic materials. Here, we've uncovered a robust and stable exchange bias effect within the layered van der Waals (vdW) ferromagnet VI3 employing magnetic circular dichroism microscopy. At 10 K, w

Thomas T. Dumitrescu, Po-Shen Hsin

In gauge theories with fundamental matter there is typically no sharp way to distinguish confining and Higgs regimes, e.g. using generalized global symmetries acting on loop order parameters. It is standard lore that these two regimes are continuously connected, as has been explicitly demonstrated in certain lattice and continuum models. We point out that Hi

Kamil Khadiev, Elizaveta Krendeleva

In the paper, we investigate Two Sets Intersection problem. Assume that we have two sets that are subsets of n objects. Sets are presented by two predicates that show which of n objects belong to these sets. We present a quantum algorithm that finds an element from the two sets intersection. It is a modification of the well-known Grover's search algorithm th

Suho Shin, Seyed A. Esmaeili, MohammadTaghi Hajiaghayi

We study the problem of designing replication-proof bandit mechanisms when agents strategically register or replicate their own arms to maximize their payoff. Specifically, we consider Bayesian agents who only know the distribution from which their own arms' mean rewards are sampled, unlike the original setting of by Shin et al. 2022. Interestingly, with Bay

Yuanyuan Duan, Xingchen Liu, Zhiping Yu, Hanming Wu

Chiplet-based systems have gained significant attention in recent years due to their low cost and competitive performance. As the complexity and compactness of a chiplet-based system increase, careful consideration must be given to microbump assignments, interconnect delays, and thermal limitations during the floorplanning stage. This paper introduces RLPlan

Soumya Ranjan Choudhaury, Aditya Narendra, Ashutosh Mishra, Ipsit Misra

The widespread usage of cars and other large, heavy vehicles necessitates the development of an effective parking infrastructure. Additionally, algorithms for detection and recognition of number plates are often used to identify automobiles all around the world where standardized plate sizes and fonts are enforced, making recognition an effortless task. As a

Zhecheng Sheng, Tianhao Zhang, Chen Jiang, Dongyeop Kang

Measuring the coherence of text is a vital aspect of evaluating the quality of written content. Recent advancements in neural coherence modeling have demonstrated their efficacy in capturing entity coreference and discourse relations, thereby enhancing coherence evaluation. However, many existing methods heavily depend on static embeddings or focus narrowly

Huiling Qin, Xianyuan Zhan, Yuanxun Li, Yu Zheng

Semi-supervised learning holds great promise for many real-world applications, due to its ability to leverage both unlabeled and expensive labeled data. However, most semi-supervised learning algorithms still heavily rely on the limited labeled data to infer and utilize the hidden information from unlabeled data. We note that any semi-supervised learning tas

Wei Liu, Jingqi Chen, Wenjie Dou

This study investigates the dynamic behavior of polaritons in an optical cavity containing one million molecules, emphasizing the influence of molecular rotation and level disorder on the coupling between molecules and photons. Through rigorous theoretical simulations and numerical analyses, we systematically explore the formation and spectral characteristic

Yangqin Jiang, Yuhao Yang, Lianghao Xia, Chao Huang

Knowledge Graphs (KGs) have emerged as invaluable resources for enriching recommendation systems by providing a wealth of factual information and capturing semantic relationships among items. Leveraging KGs can significantly enhance recommendation performance. However, not all relations within a KG are equally relevant or beneficial for the target recommenda

Sagar Basak, Anisa Chorwadwala, Sheela Verma

We consider mixed Steklov-Dirichlet eigenvalue problem on smooth bounded domains in Riemannian manifolds. Under certain symmetry assumptions on multiconnected domains in $\mathbb{R}^{n}$ with a spherical hole, we obtain isoperimetric inequalities for $k$-th Steklov-Dirichlet eigenvalues for $2 \leq k \leq n+1$. We extend Theorem 3.1 of \cite{gavitone2023isop

François-Xavier Schmider, Patrick Gaulme, Raúl Morales-Juberías, Jason Jackiewicz

We present three-dimensional (3D) maps of Jupiter's atmospheric circulation at cloud-top level from Doppler-imaging data obtained in the visible domain with JIVE, the second node of the JOVIAL network, which is mounted on the Dunn Solar Telescope at Sunspot, New Mexico. We report on 12 nights of observations between May 4 and May 30, 2018, representing a tot

Arne Bethmann, Marina Aoki, Charlotte Hunsicker, Claudia Weileder

Figure drawing is often used as part of dementia screening protocols. The Survey of Health Aging and Retirement in Europe (SHARE) has adopted three drawing tests from Addenbrooke's Cognitive Examination III as part of its questionnaire module on cognition. While the drawings are usually scored by trained clinicians, SHARE uses the face-to-face interviewers w

Xiangxiang Chu, Limeng Qiao, Xinyang Lin, Shuang Xu

We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted to run on mobile devices. It is an amalgamation of a myriad of architectural designs and techniques that are mobile-oriented, which comprises a set of language models at the scale of 1.4B and 2.7B parameters, trained from scratch, a multimodal vision model that is pre-trained

Pierre-Michel Bousquet, Mickael Rouvier

A new loss function for speaker recognition with deep neural network is proposed, based on Jeffreys Divergence. Adding this divergence to the cross-entropy loss function allows to maximize the target value of the output distribution while smoothing the non-target values. This objective function provides highly discriminative features. Beyond this effect, we

Johann Kay Ann Tan

Binaural recordings are a form of stereophonic recording method that replicates how human ears perceive sound, these types of recordings create a 3D aural image around the listener and are extremely immersive when well recorded and listened to appropriately with headphones. It has wide applications in video, podcast, and gaming formats -- allowing the listen

Cheng Zhang, Yinuo Deng, Hailiang Zhao, Tianlv Chen

In the realm of edge computing, the increasing demand for high Quality of Service (QoS), particularly in dynamic multimedia streaming applications (e.g., Augmented Reality/Virtual Reality and online gaming), has prompted the need for effective solutions. Nevertheless, adopting an edge paradigm grounded in distributed computing has exacerbated the issue of ta

Ashwin Prasad Shivarpatna Venkatesh, Samkutty Sabu, Jiawei Wang, Amir M. Mir

In light of the growing interest in type inference research for Python, both researchers and practitioners require a standardized process to assess the performance of various type inference techniques. This paper introduces TypeEvalPy, a comprehensive micro-benchmarking framework for evaluating type inference tools. TypeEvalPy contains 154 code snippets with

Qianrui Teng, Rui Wang, Xing Cui, Peipei Li

Existing face aging methods often focus on modeling either texture aging or using an entangled shape-texture representation to achieve face aging. However, shape and texture are two distinct factors that mutually affect the human face aging process. In this paper, we propose 3D-STD, a novel 3D-aware Shape-Texture Disentangled face aging network that explicit

Jaydip Sen, Abhiraj Sen, Ananda Chatterjee

The notion of adversarial attacks on image classification models based on convolutional neural networks (CNN) is introduced in this work. To classify images, deep learning models called CNNs are frequently used. However, when the networks are subject to adversarial attacks, extremely potent and previously trained CNN models that perform quite effectively on

Somesh Chamoli, Anmol Mishra, Richa Sharma Kesarkar, B. K. Sahoo

We have employed equation-of-motion coupled-cluster (EOM-CC) method in the four-component relativistic theory framework to understand roles of electron correlation effects in the $\textit{ab initio}$ estimations of electric dipole polarizabilities ($\alpha$) of the states engaged in the clock transition ($^{1}$S$_{0}$$\rightarrow$$^{3}$P$_{0}$) of the zinc a

Dóra Gréta Petróczy, László Csató

The Council of the European Union (EU) is one of the main decision-making bodies of the EU. A number of decisions require a qualified majority, the support of 55% of the member states (currently 15) that represent at least 65% of the total population. We investigate how the power distribution based on the Shapley--Shubik index and the proportion of winning c

Liliia Safina, Kamil Khadieva, Ilnar Zinnatullina, Aliya Khadieva

In this work, we present a quantum circuit for a binary classification prediction algorithm using a random forest model. The quantum prediction algorithm is presented in our previous works. We construct a circuit and implement it using qiskit tools (python module for quantum programming). One of our goals is reducing the number of basic quantum gates (elemen

Jia-Ming Xie, Jun-Xu Lu, Li-Sheng Geng, Bing-Song Zou

Two-pole structures refer to the fact that two dynamically generated states are located close to each other between two coupled channels and have a mass difference smaller than the sum of their widths. Thus, the two poles overlap in the invariant mass distribution of their decay products, creating the impression that only one state exists. This phenomenon wa

Michal Dobrski

Nonlinear action of the group of spatial rotations on commuting components of a position operator of a massless particle of arbitrary helicity is studied. It is shown that linearization of this action necessarily leads to the Pryce operator with non-commuting components. The problem is also analyzed from a geometric perspective using Callan, Coleman, Wess an

Tamas Veres, Mark Kerestely, Borbala M. Kovacs, David Keresztes

Recent findings show that single, non-neuronal cells are also able to learn signalling responses developing cellular memory. In cellular learning nodes of signalling networks strengthen their interactions e.g. by the conformational memory of intrinsically disordered proteins, protein translocation, miRNAs, lncRNAs, chromatin memory and signalling cascades. T

Ertugrul Basar, George C. Alexandropoulos, Yuanwei Liu, Qingqing Wu

Reconfigurable intelligent surfaces (RISs) are rapidly gaining prominence in the realm of fifth generation (5G)-Advanced, and predominantly, sixth generation (6G) mobile networks, offering a revolutionary approach to optimizing wireless communications. This article delves into the intricate world of the RIS technology, exploring its diverse hardware architec

Leonardo Puggioni, Stefano Musacchio

The relationship between the polymer orientation and the chaotic flow, in a dilute solution of rigid rodlike polymers at low Reynolds number, is investigated by means of direct numerical simulations. It is found that the rods tend to align with the velocity field in order to minimize the friction with the solvent fluid, while regions of rotational disorder a

Hamid Mofidi

In this research, we explore how permanent charges affect the movement of ionic currents through ion channels. We use a quasi-one-dimensional classical Poisson-Nernst-Planck (PNP) model to study two types of ions, one positively charged and the other negatively charged. The distribution of permanent charges is simple, with zero values at both ends and a cons

Gurvan Mével

In 2022, Brugall{\'e} and Jaramillo-Puentes showed that the coefficients of small codegree of the tropical refined invariant are polynomial in the Newton polygon. This raised the question of the existence of universal polynomials giving these coefficients, i.e. polynomials depending only on the genus and the codegree, and with variables the combinatorial dat

Burak Can Sahin, Abdulrezzak Zekiye, Oznur Ozkasap

For the purpose of enabling, democratizing, and reducing the fees of peer-to-peer energy trading for battery-powered devices, we propose ANKA as a fully decentralized energy marketplace for peers with battery-powered devices. ANKA utilizes state-of-the-art technologies, namely blockchain, smart contracts, and decentralized applications. Within this marketpla

Qingyou He, Hai-Liang Li, Benoît Perthame

We revisit the problem of proving the incompressible limit for the compressible porous media equation with Newtonian drift and growth. The question is motivated by models of living tissues development including chemotaxis. We extend the problem, already treated by the authors and several other contributions, in using a simplified approach, in treating dimens

Violaine Courrier, Christophe Biernacki, Cristian Preda, Benjamin Vittrant

In healthcare, patient data is often collected as multivariate time series, providing a comprehensive view of a patient's health status over time. While this data can be sparse, connected devices may enhance its frequency. The goal is to create patient profiles from these time series. In the absence of labels, a predictive model can be used to predict future

Jipeng Jin, Zhaoxiang Zhang, Zhiheng Li, Xiaofeng Gao

Recommender systems with cascading architecture play an increasingly significant role in online recommendation platforms, where the approach to dealing with negative feedback is a vital issue. For instance, in short video platforms, users tend to quickly slip away from candidates that they feel aversive, and recommender systems are expected to receive these

Yu Chen, Shuai Zheng, Menglong Jin, Yan Chang

Fluid motion can be considered as a point cloud transformation when using the SPH method. Compared to traditional numerical analysis methods, using machine learning techniques to learn physics simulations can achieve near-accurate results, while significantly increasing efficiency. In this paper, we propose an innovative approach for 3D fluid simulations uti

Hiroki Sukeno, Takuya Okuda

The digital quantum simulation of lattice gauge theories is expected to become a major application of quantum computers. Measurement-based quantum computation is a widely studied competitor of the standard circuit-based approach. We formulate a measurement-based scheme to perform the quantum simulation of Abelian lattice gauge theories in general dimensions.

Wonjoon Chang, Dahee Kwon, Jaesik Choi

Understanding intermediate representations of the concepts learned by deep learning classifiers is indispensable for interpreting general model behaviors. Existing approaches to reveal learned concepts often rely on human supervision, such as pre-defined concept sets or segmentation processes. In this paper, we propose a novel unsupervised method for discove

G. Mustafa, Allah Ditta, Saadia Mumtaz, S. K. Maurya

The primary objective of this work is to study the dynamical characteristics of an anisotropic compact star model with spherical symmetry. This investigation is conducted in the framework of $f(Q)$ modified gravity. To simplify the calculations, we employ the Karmarkar condition and derive a differential equation that establishes a relationship between two c

Emilie Huffman

Typical fermion algorithms require the computation (or sampling) of the fermion determinant. We focus instead on cluster algorithms which do not involve the determinant and involve a more physically relevant sampling of the configuration space. We develop new cluster algorithms and design classes of models for fermions coupled to $\mathbb{Z}_2$ and $U(1)$ ga

Mingtao Yang, See-Kiong Ng, Jinlan Fu

Pre-trained conversation models (PCMs) have demonstrated remarkable results in task-oriented dialogue (TOD) systems. Many PCMs focus predominantly on dialogue management tasks like dialogue state tracking, dialogue generation tasks like response generation, or both. However, the existing PCMs seldom consider dialogue comprehension tasks, such as dialogue que

Junjie Miao, Hongbo Zhao

In this paper, we study the spectrality of infinite convolutions generated by infinitely many admissible pairs which may not be compactly supported, where the spectrality means the corresponding square integrable function space admits a family of exponential functions as an orthonormal basis. First, we prove that the infinite convolution exists and is a spec

Zhengqing Yuan, Zhaoxu Li, Weiran Huang, Yanfang Ye

In recent years, multimodal large language models (MLLMs) such as GPT-4V have demonstrated remarkable advancements, excelling in a variety of vision-language tasks. Despite their prowess, the closed-source nature and computational demands of such models limit their accessibility and applicability. This study introduces TinyGPT-V, a novel open-source MLLM, de

Y. Fujikawa, T. Kawabata, S. Adachi, S. Enyo

We searched for the 6$\alpha$-condensed state in $^{24}$Mg by measuring the $^{12}\rm{C}+{}^{12}\rm{C}$ scattering with the SAKRA Si detector array at $E_\rm{cm}$ = 17.5-25.0 MeV. By using the invariant-mass method for the detected 3$\alpha$ particles, the inclusive cross sections for the $^{12}\rm{C}+{}^{12}\rm{C}\to{}^{12}\rm{C}(0^+_2)+X$ and $^{12}\rm{C}(

Yichen Li, Chicheng Zhang

We study interactive imitation learning, where a learner interactively queries a demonstrating expert for action annotations, aiming to learn a policy that has performance competitive with the expert, using as few annotations as possible. We focus on the general agnostic setting where the expert demonstration policy may not be contained in the policy class u

Elham Nazari, Samik Mitra, Shahram Abbassi, Santabrata Das

We present the structure of a low angular momentum accretion flows around rotating compact objects incorporating relativistic corrections up to the leading post-Newtonian order. To begin with, we formulate the governing post-Newtonian hydrodynamic equations for the mass and energy-momentum flux without imposing any symmetries. However, for the sake of simpli

Ryo Ohashi, Momonari Kudo

In algebraic geometry, enumerating or finding superspecial curves in positive characteristic $p$ is important both in theory and in computation. In this paper, we propose feasible algorithms to enumerate or find superspecial hyperelliptic curves of genus $4$ with automorphism group properly containing the Klein $4$-group. Executing the algorithms on Magma, w

G. Mustafa, A. Ditta, Faisal Javed, S. K. Maurya

This study deals with astrophysical accretion onto the charged black hole solution, which is sourced by the dilation, spin, and shear charge of matter in metric affine gravity. The metric affine gravity defines the link between torsion and nonmetricity in space-time geometry. In the current analysis, we study the accretion process of various perfect fluids t

Takeo Kojima

The deformed $W$-algebra is a quantum deformation of the $W$-algebra ${\cal W}_\beta(\mathfrak{g})$ in conformal field theory. Using the free field construction, we obtain a closed set of quadratic relations of the $W$-currents of the deformed $W$-algebra. This allows us to define the deformed $W$-algebra by generators and relations. In this review, we study

Weide Liu, Huijing Zhan

Multimodal sentiment analysis aims to identify the emotions expressed by individuals through visual, language, and acoustic cues. However, most existing research assume that all modalities are available during both training and testing, which makes their algorithms susceptible to the missing-modality scenarios. In this paper, we propose a novel knowledge-tra

Bangyi Zhao, Weixia Xu, Jihong Guan, Shuigeng Zhou

Molecular property prediction (MPP) is a fundamental but challenging task in the computer-aided drug discovery process. More and more recent works employ different graph-based models for MPP, which have made considerable progress in improving prediction performance. However, current models often ignore relationships between molecules, which could be also hel

Hui Gao, Hongyu Kuang, Wesley K. G. Assunção, Christoph Mayr-Dorn

Traceability allows stakeholders to extract and comprehend the trace links among software artifacts introduced across the software life cycle, to provide significant support for software engineering tasks. Despite its proven benefits, software traceability is challenging to recover and maintain manually. Hence, plenty of approaches for automated traceability

Youjie Wang, Qian Gao, Zhenpeng Hu

Carbon allotropes have vast potential in various applications, including superconductivity, energy storage, catalysis, and photoelectric semiconductor devices. Recently, there has been significant research interest in exploring new carbon materials that exhibit unique electronic structures. Here, we propose a novel two-dimensional (2D) carbon allotrope calle

Kai Tanaka, Mineichi Kudo, Keigo Kimura

With the increase of the number of elderly people living alone around the world, there is a growing demand for sensor-based detection of anomalous behaviors. Although smart homes with ambient sensors could be useful for detecting such anomalies, there is a problem of lack of sufficient real data for developing detection algorithms. For coping with this probl

Ayman Shehata

Recently, Shehata et al. [37] introduced the $_{r+1}R_{s,k}(B,C,z)$ matrix function and established some properties. The aim of this study established to devote and derive certain basic properties including analytic properties, recurrence matrix relations, differential properties, new integral representations, $k$-Beta transform, Laplace transform, fractiona

Xiaoshui Lin, Zeyu Rao, Ming Gong

The bosonic Josephson junction, one of the maximally simple models for periodic-driven many-body systems, has been intensively studied in the past two decades. Here, we revisit this problem with five different methods, all of which have solid theoretical reasoning. We find that to the order of $\omega^{-2}$ ($\omega$ is the modulating frequency), these appro

Linhan Ma, Yongmao Zhang, Xinfa Zhu, Yi Lei

Accent transfer aims to transfer an accent from a source speaker to synthetic speech in the target speaker's voice. The main challenge is how to effectively disentangle speaker timbre and accent which are entangled in speech. This paper presents a VITS-based end-to-end accent transfer model named Accent-VITS.Based on the main structure of VITS, Accent-VITS m

Vyacheslav Ivanovich Dokuchaev

We describe quantum correction to the accreting hot plasma onto black holes. This quantum correction is related with the Hawking radiation, which heats the accreting plasma. The hot accreting gas is heated additionally by the quantum Hawking radiation. It is demonstrated that Hawking radiation prevails over the Compton scattering of hot electrons in the accr

Kuang-Ru Wu

The goal of the paper is to extend results about ample or Griffiths positive vector bundles to Kobayashi positive vector bundles. In particular, we show that the quotient bundle of a Kobayashi positive vector bundle is Kobayashi positive, and the tensor product of two Kobayashi positive vector bundles is Kobayashi positive. These results strengthen the conje

Tong-Jie Zhang, Bo-Lun Huang, Jian-Kang Li, Zhen-Zhao Tao

Since the commencement of the first SETI observation in 2019, China's Search for Extraterrestrial Intelligence program has garnered momentum through domestic support and international collaborations. Several observations targeting exoplanets and nearby stars have been conducted with the FAST. In 2023, the introduction of the Far Neighbour Project(FNP) marks

Elizabeth Amona, Indranil Sahoo, Edward Boone, Ryad Ghanam

Qatar has undergone distinct waves of COVID-19 infections, compounded by the emergence of variants, posing additional complexities. This research uniquely delves into the varied efficacy of existing vaccines and the pivotal role of vaccination timing in the context of COVID-19. Departing from conventional modeling, we introduce two models that account for th

Sabino Miranda, Obdulia Pichardo-Lagunas, Bella Martínez-Seis, Pierre Baldi

This study evaluates the performance of large language models, specifically GPT-3.5 and BARD (supported by Gemini Pro model), in undergraduate admissions exams proposed by the National Polytechnic Institute in Mexico. The exams cover Engineering/Mathematical and Physical Sciences, Biological and Medical Sciences, and Social and Administrative Sciences. Both

Daniel Massatt, Stephen P. Shipman, Ilya Vekhter, Justin H. Wilson

We analyze a class of bound defect states in the continuum electronic spectrum of bilayer materials, which emerge independent of symmetry protection or additional degrees of freedom. Taking graphene as a prototypical example, our comparative analysis of AA- and AB-stacked bilayer graphene demonstrates that these states originate from the intrinsic algebraic

Ramin Giahi, Cameron A. MacKenzie, Reyhaneh Bijari

Engineering system design, viewed as a decision-making process, faces challenges due to complexity and uncertainty. In this paper, we present a framework proposing the use of the Deep Q-learning algorithm to optimize the design of engineering systems. We outline a step-by-step framework for optimizing engineering system designs. The goal is to find policies

Xuhao Wu, Peng-Cheng Chu, Min Ju, He Liu

We investigate the properties of hybrid star and the mixed phase core to explore the radius ratio of the mixed phase in hybrid star. In the context of observed massive neutron stars (NSs), we examine the internal structure, phase transitions, and the impacts of the equation of state (EOS) in maximum hybrid star. We investigate the stiffness changes in the EO

Hansol Lee, Junuk Cha, Yunhoe Ku, Jae Shin Yoon

The appearance of a human in clothing is driven not only by the pose but also by its temporal context, i.e., motion. However, such context has been largely neglected by existing monocular human modeling methods whose neural networks often struggle to learn a video of a person with large dynamics due to the motion ambiguity, i.e., there exist numerous geometr

Ramakrishna Nanduri, Tapas Kumar Roy

In this work, we classify the circuit binomials of any weighted oriented graph $D$ and we explicitly compute the circuit binomials of $D$ in terms of the minors of the incidence matrix of $D$. We show that the circuit binomials of any weighted oriented graph $D$ are the primitive binomials corresponding to one of the classes: (i) a balanced cycle, (ii) two u

Leela Raj-Sankar, S. Raj Rajagopalan

Covert communication (also known as steganography) is the practice of concealing a secret inside an innocuous-looking public object (cover) so that the modified public object (covert code) makes sense to everyone but only someone who knows the code can extract the secret (message). Linguistic steganography is the practice of encoding a secret message in natu

Hyungtae Lim, Minho Oh, Seungjae Lee, Seunguk Ahn

With the increasing demand for mobile robots and autonomous vehicles, several approaches for long-term robot navigation have been proposed. Among these techniques, ground segmentation and traversability estimation play important roles in perception and path planning, respectively. Even though these two techniques appear similar, their objectives are differen

Lau Loi So

Describing the gravitational energy-momentum, the super-energy Bel-Robinson tensor is the best candidate. In the past, people seems only explore the lowest order: the electric part $E_{ab}$ and magnetic part $B_{ab}$ for the Riemann tensor. These two components are related with the static case, however, for the energy transfer situation, one may need to cons

Biwen Lei, Kai Yu, Mengyang Feng, Miaomiao Cui

Text-guided domain adaptation and generation of 3D-aware portraits find many applications in various fields. However, due to the lack of training data and the challenges in handling the high variety of geometry and appearance, the existing methods for these tasks suffer from issues like inflexibility, instability, and low fidelity. In this paper, we propose

Li Li, Shogo Seki

This paper proposes Remixed2Remixed, a domain adaptation method for speech enhancement, which adopts Noise2Noise (N2N) learning to adapt models trained on artificially generated (out-of-domain: OOD) noisy-clean pair data to better separate real-world recorded (in-domain) noisy data. The proposed method uses a teacher model trained on OOD data to acquire pseu

Jinwei Zhang, Thanh D. Nguyen, Renjiu Hu, Susan A. Gauthier

Background: Rim+ lesions in multiple sclerosis (MS), detectable via Quantitative Susceptibility Mapping (QSM), correlate with increased disability. Existing literature lacks quantitative analysis of these lesions. We introduce RimSet for quantitative identification and characterization of rim+ lesions on QSM. Methods: RimSet combines RimSeg, an unsupervised

Kamel Abdous, Nairouz Mrabah, Mohamed Bouguessa

We investigate the problem of multiplex graph embedding, that is, graphs in which nodes interact through multiple types of relations (dimensions). In recent years, several methods have been developed to address this problem. However, the need for more effective and specialized approaches grows with the production of graph data with diverse characteristics. I

Ryota Watanabe

We consider the double scaling limit of a model of Pauli spin operators recently studied in Hanada et al. [1] and evaluate the moments of the Hamiltonian by the chord diagrams. We find that they coincide with those of the double scaled SYK model, which makes it more likely that this model may play an important role in the study of holography. We compare the

Nickolay D. Malyutin, Artush A. Arutyunyan, Anton G. Loschilov, George A. Malyutin

The elements of the metamaterial made in the form of wave-guiding coplanar strip line type strip structures, the current-carrying strip of which is located on the upper surface of the substrate, have been experimentally investigated. On the same surface, side screens, connected to the lower grounded base, through metallized holes are made. A volumetric lithi

Jiaqi Zhu, Shaofeng Cai, Fang Deng, Beng Chin Ooi

Real-time analytics and decision-making require online anomaly detection (OAD) to handle drifts in data streams efficiently and effectively. Unfortunately, existing approaches are often constrained by their limited detection capacity and slow adaptation to evolving data streams, inhibiting their efficacy and efficiency in handling concept drift, which is a m

Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini

Variational Graph Auto-Encoders (VGAEs) have been widely used to solve the node clustering task. However, the state-of-the-art methods have numerous challenges. First, existing VGAEs do not account for the discrepancy between the inference and generative models after incorporating the clustering inductive bias. Second, current models are prone to degenerate

Tao Hu, Xiaoqing Sun, Mingkai Bai, Xinpei Jia

In this work, we demonstrate the enlargement of the memory window of Si channel FeFET with ferroelectric Hf0.5Zr0.5O2 by gate-side dielectric interlayer engineering. By inserting an Al2O3 dielectric interlayer between TiN gate metal and ferroelectric Hf0.5Zr0.5O2, we achieve a memory window of 3.2 V with endurance of ~105 cycles and retention over 10 years.

Weijie Zhao, Shulong Tan, Ping Li

With the continuous popularity of deep learning and representation learning, fast vector search becomes a vital task in various ranking/retrieval based applications, say recommendation, ads ranking and question answering. Neural network based ranking is widely adopted due to its powerful capacity in modeling complex relationships, such as between users and i

Jesús Guillera

We derive, using a heuristic method, a $p$-adic mate of bilateral Ramanujan series. It has (among other consequences) the Zudiln's supercongruences for rational Ramanujan series.

Hongyu Wang, Hui Li, Bo Li

Speaker verification is to judge the similarity between two unknown voices in an open set, where the ideal speaker embedding should be able to condense discriminant information into a compact utterance-level representation that has small intra-speaker distances and large inter-speaker distances. We propose Voice Transformer (VOT), a novel model for speaker v

Sita Kandel, Godfrey Gumbs, Antonios Balassis, Andrii Iurov

It is now well established that a high-frequency electromagnetic dressing field within the off-resonance regime significantly modifies the electronic transport and optical properties on Dirac materials. Here, using light with circular polarization, we investigate its effect on the energy spectrum of tilted monolayer 1T$^\prime$MoS$_2$ which acquires two ener

Menghao Qu, Guoce Xin

Haglund, Morse, and Zabrocki introduced a family of creation operators of Hall-Littlewood polynomials, $\{C_{a}\}$ for any $a\in \mathbb{Z}$, in their compositional refinement of the shuffle (ex-)conjecture. For any $\alpha\vDash n$, the combinatorial formula for $\nabla C_{\alpha}$ is a weighted sum of parking functions. These summations can be converted to

Hyunjune Kim, Sangyong Lee, Simon S. Woo

Recently, serious concerns have been raised about the privacy issues related to training datasets in machine learning algorithms when including personal data. Various regulations in different countries, including the GDPR grant individuals to have personal data erased, known as 'the right to be forgotten' or 'the right to erasure'. However, there has been le

Jingran Shi, Yipeng Liu, Baocheng Zhang

We investigate the transition behavior of the two-level atom as the Unruh-DeWitt detector outside a noncommutative black hole. When the mass of the black hole is small enough, the difference between the commutative and noncommutative black hole can be distinguished. In particular, an evident fluctuation appearing at a far distance from the horizon by calcula

Haifeng Li, Mo Hai, Dong Tang

Ranker and retriever are two important components in dense passage retrieval. The retriever typically adopts a dual-encoder model, where queries and documents are separately input into two pre-trained models, and the vectors generated by the models are used for similarity calculation. The ranker often uses a cross-encoder model, where the concatenated query-

Huy Quang Ngo, Mingyu Guo, Hung Nguyen

We study a Stackelberg game between an attacker and a defender on large Active Directory (AD) attack graphs where the defender employs a set of honeypots to stop the attacker from reaching high-value targets. Contrary to existing works that focus on small and static attack graphs, AD graphs typically contain hundreds of thousands of nodes and edges and const

Yossi Arjevani

We consider the optimization problem associated with training two-layer ReLU networks with \(d\) inputs under the squared loss, where the labels are generated by a target network. Recent work has identified two distinct classes of infinite families of minima: one whose training loss vanishes in the high-dimensional limit, and another whose loss remains bound

Yejun Kim, Kwangsoo Cho, Seungjoo Kim

With the advancement of Internet of Things (IoT) technology, its applications span various sectors such as public, industrial, private and military. In particular, the drone sector has gained significant attention for both commercial and military purposes. As a result, there has been a surge in research focused on vulnerability analysis of drones. However, m

Ashwani Kumar Pal, Kirti Chandra Sahu, Santanu De, Gautam Biswas

The collision dynamics of two drops of the same liquid moving in the same direction has been studied numerically. A wide range of radius ratios of trailing drop and leading drop ($R_r$) and the velocity ratios ($U_r$) have been deployed to understand the collision outcomes. A volume of fluid (VOF) based open-source fluid flow solver, Basilisk, has been used

Martin Miglioli

In this article we prove that the Harish-Chandra-Itzykson-Zuber (HCIZ) integral formula is equivalent to the unitarity of a canonical map between invariant subspaces of Segal-Bargmann spaces. As a consequence, we provide two new proofs of the HCIZ integral formula and alternative proofs of related results.

Bing Yuan, Zhang Jiang, Aobo Lyu, Jiayun Wu

Emergence and causality are two fundamental concepts for understanding complex systems. They are interconnected. On one hand, emergence refers to the phenomenon where macroscopic properties cannot be solely attributed to the cause of individual properties. On the other hand, causality can exhibit emergence, meaning that new causal laws may arise as we increa

Wei Shi, Jindan Xu, Wei Xu, Chau Yuen

Reconfigurable intelligent surface (RIS) technology is emerging as a promising technique for performance enhancement for next-generation wireless networks. This paper investigates the physical layer security of an RIS-assisted multiple-antenna communication system in the presence of random spatially distributed eavesdroppers. The RIS-to-ground channels are a

R Vallabh Ramakanth, Vishrant Tripathi, Eytan Modiano

We study the design of scheduling policies to minimize monitoring error for a collection of correlated sources, where only one source can be observed at any given time. We model correlated sources as a discrete-time Wiener process, where the increments are multivariate normal random variables, with a general covariance matrix that captures the correlation st

Zhan Li, Zhang Chen, Zhong Li, Yi Xu

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results, real-time rendering, and compact storage remains a formidable task. To address these challenges, we propose Spacetime Gaussian Feature Splatting as a novel dynamic scene represent

Artur Kawalec

In this article, we develop a square-free zeta series associated with the M\"obius function into a power series, and prove a Stieltjes like formula for these expansion coefficients. We also investigate another analytical continuation of these series and develop a formula for $\zeta(\tfrac{1}{2})$ in terms of the M\"obius function, and in the last part, we ex

Hanqi Su, Jay Lee

In the field of Prognostics and Health Management (PHM), recent years have witnessed a significant surge in the application of machine learning (ML). Despite this growth, the field grapples with a lack of unified guidelines and systematic approaches for effectively implementing these ML techniques and comprehensive analysis regarding industrial open-source d

Javad Zahedi Moghaddam, Hamidreza Momeni, Mojtaba Danesh

Blind System Identification (BSI) is used to extract a system model whenever input data is not attainable. Therefore, the input data and system model should be estimated simultaneously. Because of nonlinearities in a large number of systems, BSI problem is usually challenging to solve. In this paper, an innovative solution is proposed to deal with the BSI pr

Guandong Li, Xian Yang

In the industrial e-commerce landscape, creative designs such as banners and posters are ubiquitous. Extracting structured semantic information from creative e-commerce design materials (manuscripts crafted by designers) to obtain design semantics represents a core challenge in the realm of intelligent design. In this paper, we propose a comprehensive automa