January 2022 arXiv papers — page 62

Rui Hu, Zhen-Hua Zhang

An analysis of the Forward-Backward Asymmetry (FBA) in the decay $B^\pm \to K^\pm K^\mp K^\pm$ is carried out based on the LHCb data. It is found that the large FBA observed for the invariant mass of the $K^+ K^-$ pair around 1.5 GeV can be explained by the interference of the amplitudes between the resonances with even and odd spins, where the former can be

Yo Tokunaga, Hironori Sakai, Shinsaku Kambe, Yoshinori Haga

$^{125}$Te NMR experiments in field ($H$) applied along the easy magnetization axis (the $a$-axis) revealed slow electronic dynamics developing in the paramagnetic state of UTe$_2$. The observed slow fluctuations are concerned with a successive growth of long-range electronic correlations below 30$-$40 K, where the spin susceptibility along the hard magnetiz

Yixuan Liu, Yuhan Tang, Yati Liu

As the shared micromobility becomes a part of our daily life and environment, we expect the number of low-speed modes for first-and-last mile trips to grow rapidly. The shared micomobility is expected to serve billions of humans, bringing us considerable advantages. With this growth, shared micromobility simulation such as docked stations based shared bikes,

Bei Ding, Jun Liu, Hang Li, Jinjing Liang

The search for materials exhibiting nanoscale spiral order continues to be fuelled by the promise of emergent inductors. Although such spin textures have been reported in many materials, most of them exhibit long periods or are limited to operate far below room temperature. Here, we present the real-space observation of an ordered helical spin order with a p

Christian Lienen, Marco Platzner

Many applications from the robotics domain can benefit from FPGA acceleration. A corresponding key question is how to integrate hardware accelerators into software-centric robotics programming environments. Recently, several approaches have demonstrated hardware acceleration for the robot operating system (ROS), the dominant programming environment in roboti

Zhuo Chen, Xue-Ning Bai

The final stage of gas giant formation involves accreting gas from the parent protoplanetary disk. In general, the infalling gas likely approaches a free-fall velocity, creating an accretion shock, leading to strong shock heating and radiation. We investigate the kinematics and energetics of such accretion shocks using 1D radiation hydrodynamic simulations.

Seth Karten, Mycal Tucker, Huao Li, Siva Kailas

Learning interpretable communication is essential for multi-agent and human-agent teams (HATs). In multi-agent reinforcement learning for partially-observable environments, agents may convey information to others via learned communication, allowing the team to complete its task. Inspired by human languages, recent works study discrete (using only a finite se

Linhao Qu, Shaolei Liu, Manning Wang, Shiman Li

Image fusion is a technique to integrate information from multiple source images with complementary information to improve the richness of a single image. Due to insufficient task-specific training data and corresponding ground truth, most existing end-to-end image fusion methods easily fall into overfitting or tedious parameter optimization processes. Two-s

A. I. Milstein, S. G. Salnikov

We show that the final-state interaction explains the nontrivial near-threshold energy dependence of the cross section of the process $e^{+}e^{-}\rightarrow\Lambda_{c}\bar{\Lambda}_{c}$ observed by the Belle and BESIII collaborations. This energy dependence is the result of the mixture of $S$-wave and $D$-wave components of the $\Lambda_{c}\bar{\Lambda}_{c}$

Veronika Arefieva, Roman Egger

The Bidirectional Encoder Representations from Transformers (BERT) is currently one of the most important and state-of-the-art models for natural language. However, it has also been shown that for domain-specific tasks it is helpful to pretrain BERT on a domain-specific corpus. In this paper, we present TourBERT, a pretrained language model for tourism. We d

Xu Huang

This article explores a generic framework of well-typed and well-scoped syntaxes, with a signature-axiom approach resembling traditional abstract algebra. The boilerplate code needed in defining operations on syntaxes is identified and abstracted away. Some of the frequent boilerplate proofs are also generalized.

Jonathan. M. Wheeler, Jacob N. Chamoun, Vinayak Dangui, Michel J. F. Digonnet

The noise and drift requirements for a navigation-grade gyroscope are widely known, yet there is no simple analytic model of how the noise and drift of a gyroscope influence the fix displacement error (FDE) of an inertial navigation system (INS). This work derives simple analytical expressions for the cross-track and along-track errors of an aircraft whose I

Xiaozhen Ge, Re-Bing Wu, Herschel Rabitz

This review investigates the landscapes of prevalent hybrid quantum-classical optimization algorithms in many rapidly developing quantum technologies, where the objective function is either computed by a natural quantum system or a quantum ansatz that is engineered, but the optimizer is classical. In any particular case, the nature of the underlying control

Fabian Denner, Berend van Wachem

The majority of available numerical algorithms for interfacial two-phase flows either treat both fluid phases as incompressible (constant density) or treat both phases as compressible (variable density). This presents a limitation for the prediction of many two-phase flows, such as subsonic fuel injection, as treating both phases as compressible is computati

Yan Huang, Derong Kong

For $\lambda\in(0,1/3]$ let $C_\lambda$ be the middle-$(1-2\lambda)$ Cantor set in $\mathbb R$. Given $t\in[-1,1]$, excluding the trivial case we show that \[ \Lambda(t):=\left\{\lambda\in(0,1/3]: C_\lambda\cap(C_\lambda+t)\ne\emptyset\right\} \] is a topological Cantor set with zero Lebesgue measure and full Hausdorff dimension. In particular, we calculate

Emil Žagar

In this paper interpolation of two planar points, corresponding tangent directions and curvatures with Pythagorean-hodograph (PH) curves of degree seven preserving an arc length is considered. A general approach using complex representation of PH curves is presented and a detailed analysis of the problem for data arising from a circular arc is provided. In t

Yanzhen Ren, Ting Liu, Liming Zhai, Lina Wang

Deep image steganography is a data hiding technology that conceal data in digital images via deep neural networks. However, existing deep image steganography methods only consider the visual similarity of container images to host images, and neglect the statistical security (stealthiness) of container images. Besides, they usually hides data limited to image

Lin Xiao

We consider infinite-horizon discounted Markov decision problems with finite state and action spaces and study the convergence rates of the projected policy gradient method and a general class of policy mirror descent methods, all with direct parametrization in the policy space. First, we develop a theory of weak gradient-mapping dominance and use it to prov

Bidesh Biswas, Sourjyadeep Chakraborty, Anjana Joseph, Shashidhara Acharya

Chromium nitride (CrN) is a well-known hard coating material that has found applications in abrasion and wear-resistant cutting tools, bearings, and tribology applications due to its high hardness, high-temperature stability, and corrosion-resistant properties. In recent years, CrN has also attracted significant interest due to its high thermoelectric power

Sudhanwa Patra, Utkarsh Patel, Purushottam Sahu

The presence of small neutrino masses and flavour mixings can be accounted for naturally in various models about extensions of the standard model, particularly in the seesaw mechanism models. In this work, we present a minimally extended seesaw framework with two right-handed neutrinos, where the active neutrino masses are derived in the radiative regime. Us

Satoshi Tomita, DaPeng Yao, Hiroki Tsuchiura, Kentaro Nomura

We study the electronic state of an inverse spinel compound MnMg$_{2}$O$_{4}$ based on first-principles calculations. The high-spin state is realized in Mn ions on the diamond lattice, resulting in that this material is found to be a half-metallic semimetal with the minority spin-gap about 3eV, and also with line nodes in the Brillouin zone. The intrinsic an

Zhanqiang Bai, Zheng-an Chen

Let $\mathfrak{g}$ be the Lie algebra $\mathfrak{sl}(n,\mathbb{C})$. Its Weyl group is the symmetric group $S_n$. In this paper, we want to describe some Kazhdan-Lusztig right cells containing smooth elements which parameterize the smooth Schubert varieties. These elements are closely related to the study of associated varieties of highest weight modules of

Dabiao Ma, Yitong Zhang, Meng Li, Feng Ye

Neural network based end-to-end Text-to-Speech (TTS) has greatly improved the quality of synthesized speech. While how to use massive spontaneous speech without transcription efficiently still remains an open problem. In this paper, we propose MHTTS, a fast multi-speaker TTS system that is robust to transcription errors and speaking style speech data. Specif

Nikolaos I. Miridakis, Zheng Shi, Theodoros A. Tsiftsis, Guanghua Yang

The extreme or maximum age of information (AoI) is analytically studied for wireless communication systems. In particular, a wireless powered single-antenna source node and a receiver (connected to the power grid) equipped with multiple antennas are considered when operated under independent Rayleigh-faded channels. Via the extreme value theory and its corre

Sunder Ali Khowaja, Kapal Dev, Parus Khuwaja, Paolo Bellavista

The provision of communication services via portable and mobile devices, such as aerial base stations, is a crucial concept to be realized in 5G/6G networks. Conventionally, IoT/edge devices need to transmit the data directly to the base station for training the model using machine learning techniques. The data transmission introduces privacy issues that mig

Doyeon Kim, Woonghyun Ka, Pyungwhan Ahn, Donggyu Joo

Depth estimation from a single image is an important task that can be applied to various fields in computer vision, and has grown rapidly with the development of convolutional neural networks. In this paper, we propose a novel structure and training strategy for monocular depth estimation to further improve the prediction accuracy of the network. We deploy a

Rafael Ferreira da Silva, Kyle Chard, Henri Casanova, Dan Laney

The importance of workflows is highlighted by the fact that they have underpinned some of the most significant discoveries of the past decades. Many of these workflows have significant computational, storage, and communication demands, and thus must execute on a range of large-scale computer systems, from local clusters to public clouds and upcoming exascale

Junchen Zhao, Yurun Song, Junlin Wang, Ian G. Harris

Automatic code generation from natural language descriptions can be highly beneficial during the process of software development. In this work, we propose GAP-Gen, a Guided Automatic Python Code Generation method based on Python syntactic constraints and semantic constraints. We first introduce Python syntactic constraints in the form of Syntax-Flow, which i

Ahmed Abdelali, Nadir Durrani, Fahim Dalvi, Hassan Sajjad

Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While these models have been compared with respect to downstream NLP tasks, no evaluation has been carried out to directly compare the internal representations. We

Mohammad Mousavi, Meng Wu

In this paper, a framework is proposed to coordinate the operation of the independent system operator (ISO) and distribution system operator (DSO) to leverage the wholesale market participation of distributed energy resources (DERs) aggregators while ensuring secure operation of distribution grids. The proposed coordination framework is based on parametric p

Zhipeng Yu, Yuchen Song, Tianting Zhong, Huanhao Li

Optical logic gates are fundamental blocks of optical computing to accelerate information processing. While significant progress has been achieved in recent years, existing implementations typically rely on dedicated structures that are predesigned to modulate the phases and intensities of optical beams accurately for specific logic functions. Thus, these op

Taekyun Kim, Dae san Kim

The aim of this paper is by using generating functions to further study some identities and properties on the degenerate Stirling numbers of the second kind, the degenerate $r$-Stirling numbers of the second kind, the degenerate Stirling numbers of the first kind and the unsigned degenerate Stirling numbers of the first kind.

Jin-Feng Wang, Qing-Xin Dong, Zhao-Peng Guo, Meng Lv

Magnetic Weyl semimetals (MWSM) have attracted significant attention due to their intriguing physical properties and potential applications in spin-electronic devices. Here we report the characterization of NdAlSi including transport, magnetization, and heat capacity on single crystals, as well as band structure calculation. It is a newly proposed MWSM candi

Yu Wang, Xinsheng Wang, Pengcheng Zhu, Jie Wu

This paper introduces Opencpop, a publicly available high-quality Mandarin singing corpus designed for singing voice synthesis (SVS). The corpus consists of 100 popular Mandarin songs performed by a female professional singer. Audio files are recorded with studio quality at a sampling rate of 44,100 Hz and the corresponding lyrics and musical scores are prov

Xianghao Liao, Shanshan Wang, Lanlan Tu, Yuhao Wang

A large number of coils are able to provide enhanced signal-to-noise ratio and improve imaging performance in parallel imaging. Nevertheless, the increasing growth of coil number simultaneously aggravates the drawbacks of data storage and reconstruction speed, especially in some iterative reconstructions. Coil compression addresses these issues by generating

Kiran Koshy Thekumparampil, Niao He, Sewoong Oh

We study the bilinearly coupled minimax problem: $\min_{x} \max_{y} f(x) + y^\top A x - h(y)$, where $f$ and $h$ are both strongly convex smooth functions and admit first-order gradient oracles. Surprisingly, no known first-order algorithms have hitherto achieved the lower complexity bound of $\Omega((\sqrt{\frac{L_x}{\mu_x}} + \frac{\|A\|}{\sqrt{\mu_x \mu_y

Amir Caspi, M. Barthelemy, C. D. Bussy-Virat, I. J. Cohen

Recent advances in miniaturization and commercial availability of critical satellite subsystems and detector technology have made small satellites (SmallSats, including CubeSats) an attractive, low-cost potential solution for space weather research and operational needs. Motivated by the 1st International Workshop on SmallSats for Space Weather Research and

Jing Han, Shaofan Li, Haicheng Yu, Jun Li

In this work, we developed a bond-based cohesive peridynamics model (CPDM) and apply it to simulate inelastic fracture by using the meso-scale Xu-Needleman cohesive potential . By doing so, we have successfully developed a bond-based cohesive continuum mechanics model with intrinsic stress/strain measures as well as consistent and built-in macro-scale consti

Chunhui Zhang, Guanjie Huang, Li Liu, Shan Huang

Unmanned aerial vehicle (UAV) tracking is of great significance for a wide range of applications, such as delivery and agriculture. Previous benchmarks in this area mainly focused on small-scale tracking problems while ignoring the amounts of data, types of data modalities, diversities of target categories and scenarios, and evaluation protocols involved, gr

Hadi Hosseini, Andrew Searns, Erel Segal-Halevi

We study the problem of fairly allocating a set of m indivisible chores (items with non-positive value) to n agents. We consider the desirable fairness notion of 1-out-of-d maximin share (MMS) -- the minimum value that an agent can guarantee by partitioning items into d bundles and receiving the least valued bundle -- and focus on ordinal approximation of MM

Yueyi Jiang, Yunfan Jiang, Liu Leqi, Piotr Winkielman

Loneliness has been associated with negative outcomes for physical and mental health. Understanding how people express and cope with various forms of loneliness is critical for early screening and targeted interventions to reduce loneliness, particularly among vulnerable groups such as young adults. To examine how different forms of loneliness and coping str

Haoran Bai, Jinshan Pan

Existing deep learning-based video super-resolution (SR) methods usually depend on the supervised learning approach, where the training data is usually generated by the blurring operation with known or predefined kernels (e.g., Bicubic kernel) followed by a decimation operation. However, this does not hold for real applications as the degradation process is

Juncheng Wang, Ben Liang, Min Dong, Gary Boudreau

We consider online wireless network virtualization (WNV) in a multi-cell multiple-input multiple output (MIMO) system with delayed feedback of channel state information (CSI). Multiple service providers (SPs) simultaneously share the base station resources of an infrastructure provider (InP). We aim at minimizing the accumulated precoding deviation of the In

Yi Gui, Yao Wan, Hongyu Zhang, Huifang Huang

Binary-source code matching plays an important role in many security and software engineering related tasks such as malware detection, reverse engineering and vulnerability assessment. Currently, several approaches have been proposed for binary-source code matching by jointly learning the embeddings of binary code and source code in a common vector space. De

Siddharth Barman, Anand Krishna, Y. Narahari, Soumyarup Sadhukhan

We study the problem of allocating indivisible goods among agents in a fair manner. While envy-free allocations of indivisible goods are not guaranteed to exist, envy-freeness can be achieved by additionally providing some subsidy to the agents. These subsidies can be alternatively viewed as a divisible good (money) that is fractionally assigned among the ag

Junko Ueda, Tomonari Michiyama, Daisuke Iono, Yusuke Miyamoto

We present $\sim$0."3 (114 pc) resolution maps of [CI] $^{3}P_{1}$-$^{3}P_{0}$ (hereafter [CI] (1-0)) and $^{12}$CO (1-0) obtained toward Arp 220 with the Atacama Large Millimeter/submillimeter Array. The overall distribution of the [CI] (1-0) emission is consistent with the CO (1-0). While the [CI] (1-0) and CO (1-0) luminosities of the system follow the em

Nan Sun, Chang-Tsun Li, Hin Chan, Ba Dung Le

Advances of emerging Information and Communications Technology (ICT) technologies push the boundaries of what is possible and open up new markets for innovative ICT products and services. The adoption of ICT products and systems with security properties depends on consumers' confidence and markets' trust in the security functionalities and whether the assura

Maria Gillespie, Sean T. Griffin, Jake Levinson

We consider products of $\psi$ classes and products of $\omega$ classes on $\overline{M}_{0,n+3}$. For each product, we construct a flat family of subschemes of $\overline{M}_{0,n+3}$ whose general fiber is a complete intersection representing the product, and whose special fiber is a generically reduced union of boundary strata. Our construction is built up

Yuhang Liu, Yunchu Dai

We study rotational hypersurfaces with constant Gauss-Kronecker curvature. We solve the ODE for the generating curves of such hypersurfaces and analyze several geometric properties of such hypersurfaces. In particular, we discover a class of non-compact rotational hypersurfaces with constant and negative Gauss-Kronecker curvature and finite volume, which can

Pisheng Ding, Sunil K. Chebolu

Generalized sine and cosine functions, $\sin_{n}$ and $\cos_{n}$, that parametrize the generalized unit circle $x^n+y^n=1$ are, much like their classical circular counterparts, extendable as complex analytic functions. In this article, we identify the natural domain on which $\sin_{n}$ is a conformal equivalence from a polygon to the complex plane with $n$ s

Pooya Farokhi

Shape dynamics is an alternative background-independent approach to classical dynamics that implements Leibnizian philosophy and Mach's Principles. It is a formulation of the dynamics of the universe in terms of the intrinsic and relational degrees of freedom which are objectively observable and not properties defined with respect to an external frame of ref

Samuel Judson, Joan Feigenbaum

Insightful interdisciplinary collaboration is essential to the principled governance of technology. When such efforts address the interaction between computation and society, they often focus on modeling, the process by which computer scientists formally define problems in order to enable algorithmic solutions. But modeling is a multifaceted and inherently i

Weian Mao, Yongtao Ge, Chunhua Shen, Zhi Tian

We propose a direct, regression-based approach to 2D human pose estimation from single images. We formulate the problem as a sequence prediction task, which we solve using a Transformer network. This network directly learns a regression mapping from images to the keypoint coordinates, without resorting to intermediate representations such as heatmaps. This a

Zheng Lyu, Thomas Goossens, Brian Wandell, Joyce Farrell

We assess the accuracy of a smartphone camera simulation. The simulation is an end-to-end analysis that begins with a physical description of a high dynamic range 3D scene and includes a specification of the optics and the image sensor. The simulation is compared to measurements of a physical version of the scene. The image system simulation accurately match

Sourav Mukhopadhyay, Vinay B. Chandratre, Sanjib Muhuri, Rama N. Singaraju

A wide swing charge sensitive amplifier (CSA) has been developed, as a part of a front-end electronics (FEE) readout ASIC, for a prototype silicon tungsten (Si-W) based electromagnetic (EM) calorimeter. The CSA, designed in 0.35 $\mu$m N-well CMOS technology using 5V MOS transistors, has a wide linear operating range of 2.6 pC w.r.t the input charge with a p

Mohammadreza Iman, Khaled Rasheed, Hamid R. Arabnia

Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two major constraints: dependency on extensive labeled data and training costs. Transfer learning in deep learning, known as Deep Transfer Learning (DTL), attempts to reduce such dependency and costs by reusing an obtained knowledge from a

Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li

Unsupervised graph representation learning has emerged as a powerful tool to address real-world problems and achieves huge success in the graph learning domain. Graph contrastive learning is one of the unsupervised graph representation learning methods, which recently attracts attention from researchers and has achieved state-of-the-art performances on vario

Emil Y. Sidky, Per Christian Hansen, Jakob S. Jørgensen, Xiaochuan Pan

The generalized minimal residual (GMRES) algorithm is applied to image reconstruction using linear computed tomography (CT) models. The GMRES algorithm iteratively solves square, non-symmetric linear systems and it has practical application to CT when using unmatched back-projector/projector pairs and when applying preconditioning. The GMRES algorithm is dem

Frédéric Ouimet

In this paper, we prove a local limit theorem for the chi-square distribution with $r > 0$ degrees of freedom and noncentrality parameter $\lambda \geq 0$. We use it to develop refined normal approximations for the survival function. Our maximal errors go down to an order of $r^{-2}$, which is significantly smaller than the maximal error bounds of order $r^{

Stella Biderman, Edward Raff

As artificial intelligence (AI) technologies become increasingly powerful and prominent in society, their misuse is a growing concern. In educational settings, AI technologies could be used by students to cheat on assignments and exams. In this paper we explore whether transformers can be used to solve introductory level programming assignments while bypassi

Yunfeng Shi

In this paper we develop a Nash-Moser iteration type reducibility approach to prove the (inverse) localization for some $d$-dimensional discrete almost-periodic operators with power-law long-range hopping. We also provide a quantitative lower bound on the regularity of the hopping. As an application, some results of \cite{Sar82, Pos83, Cra83, BLS83} are gene

Shancong Mou, Jianjun Shi

Image-based anomaly detection systems are of vital importance in various manufacturing applications. The resolution and acquisition rate of such systems is increasing significantly in recent years under the fast development of image sensing technology. This enables the detection of tiny defects in real-time. However, such a high resolution and acquisition ra

Mehdi Zarea, Hikaru Ueki, J. A. Sauls

We report results for the superconducting transition temperature and anisotropic energy gap for pure Niobium based on Eliashberg's equations and electron and phonon band structures computed from density functional theory. The electronic band structure is used to construct the Fermi surface and calculate the Fermi velocity at each point on the Fermi surface.T

Francesco Malandrino, Carla Fabiana Chiasserini

Traditionally, distributed machine learning takes the guise of (i) different nodes training the same model (as in federated learning), or (ii) one model being split among multiple nodes (as in distributed stochastic gradient descent). In this work, we highlight how fog- and IoT-based scenarios often require combining both approaches, and we present a framewo

Jiaxin Hu, Miaoyan Wang

We consider the problem of multiway clustering in the presence of unknown degree heterogeneity. Such data problems arise commonly in applications such as recommendation system, neuroimaging, community detection, and hypergraph partitions in social networks. The allowance of degree heterogeneity provides great flexibility in clustering models, but the extra c

C. D. Rodríguez-Camargo, A. Saldivar, N. F. Svaiter

Critical fluctuations of some order parameter describing a fluid generates long-range forces between boundaries. Here, we discuss fluctuation-induced forces associated to a disordered Landau-Ginzburg model defined in a $d$-dimensional slab geometry $\mathbb R^{d-1}\times[0,L]$. In the model the strength of the disordered field is defined by a non-thermal con

Yinghui He, Yunlong Cai, Hao Mao, Guanding Yu

Integrated sensing and communication (ISAC) has been regarded as one of the most promising technologies for future wireless communications. However, the mutual interference in the communication radar coexistence system cannot be ignored. Inspired by the studies of reconfigurable intelligent surface (RIS), we propose a double-RIS-assisted coexistence system w

Xi Li, Yan Luo, Minfu Feng

In this paper, we propose an efficient proper orthogonal decomposition based reduced-order model(POD-ROM) for nonstationary Stokes equations, which combines the classical projection method with POD technique. This new scheme mainly owns two advantages: the first one is low computational costs since the classical projection method decouples the reduced-order

Shuntaro Sumita, Kazuaki Takasan

We show that Weyl superconductivity can be induced by finite supercurrent in noncentrosymmetric spin-orbit-coupled superconductors with line nodes. We introduce a three-dimensional tight-binding model of a tetragonal superconductor in a $D+p$-wave pairing state with a finite center-of-mass momentum, and elucidate that a line-nodal to point-nodal spectral tra

Yang Ni, Bani Mallick

Causal discovery for purely observational, categorical data is a long-standing challenging problem. Unlike continuous data, the vast majority of existing methods for categorical data focus on inferring the Markov equivalence class only, which leaves the direction of some causal relationships undetermined. This paper proposes an identifiable ordinal causal di

Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo

Understanding deep learning is increasingly emergent as it penetrates more and more into industry and science. In recent years, a research line from Fourier analysis sheds lights on this magical "black box" by showing a Frequency Principle (F-Principle or spectral bias) of the training behavior of deep neural networks (DNNs) -- DNNs often fit functions from

Chingis Oinar, Binh M. Le, Simon S. Woo

Feature learning is a widely used method employed for large-scale face recognition. Recently, large-margin softmax loss methods have demonstrated significant enhancements on deep face recognition. These methods propose fixed positive margins in order to enforce intra-class compactness and inter-class diversity. However, the majority of the proposed methods d

Michael T. Jury, Robert T. W. Martin, Edward J. Timko

We extend results on analytic complex measures on the complex unit circle to a non-commutative multivariate setting. Identifying continuous linear functionals on a certain self-adjoint subspace of the Cuntz--Toeplitz $C^*-$algebra, the free disk operator system, with non-commutative (NC) analogues of complex measures, we refine a previously developed Lebesgu

Noah Arbesfeld

We study the holomorphic Euler characteristics of tautological sheaves on Hilbert schemes of points on surfaces. In particular, we establish the rationality of K-theoretic descendent series. Our approach is to control equivariant holomorphic Euler characteristics over the Hilbert scheme of points on the affine plane. To do so, we slightly modify a Macdonald

Xudong Pan, Yifan Yan, Mi Zhang, Min Yang

For model piracy forensics, previous model fingerprinting schemes are commonly based on adversarial examples constructed for the owner's model as the \textit{fingerprint}, and verify whether a suspect model is indeed pirated from the original model by matching the behavioral pattern on the fingerprint examples between one another. However, these methods heav

Christopher Sun

Since frequent severe droughts are lengthening the dry season in the Amazon Rainforest, it is important to detect wildfires promptly and forecast possible spread for effective suppression response. Current wildfire detection models are not versatile enough for the low-technology conditions of South American hot spots. This deep learning study first trains a

Keigo Matsuda, Satoru Komori, Naohisa Takagaki, Ryo Onishi

Effect of surface tension reduction on wind-wave growth is investigated using direct numerical simulation (DNS) of air-water two-phase turbulent flow. The incompressible Navier-Stokes equations for air and water sides are solved using an arbitrary Lagrangian-Eulerian method with boundary-fitted moving grids. The wave growth of finite-amplitude and non-breaki

Q. M. Zhang, J. L. Chen, S. T. Li, L. Lu

We investigate the transverse coronal-loop oscillations induced by the eruption of a prominence-carrying flux rope on 7 December 2012. The flux rope originating from NOAA Active Region (AR) 11621 was observed in EUV wavelengths by the SDO/AIA and in H$\alpha$ line center by the ground-based telescope at the BBSO. The early evolution of the flux rope is divid

Lingzhi Zhao, Ying Cui, Sheng Yang, Shlomo Shamai

Immersive video, such as virtual reality (VR) and multi-view videos, is growing in popularity. Its wireless streaming is an instance of general multicast, extending conventional unicast and multicast, whose effective design is still open. This paper investigates the optimization of general rate splitting with linear beamforming for general multicast. Specifi

Ni Ding

Pufferfish privacy achieves $\epsilon$-indistinguishability over a set of secret pairs in the disclosed data. This paper studies how to attain $\epsilon$-pufferfish privacy by exponential mechanism, an additive noise scheme that generalizes the Laplace noise. It is shown that the disclosed data is $\epsilon$-pufferfish private if the noise is calibrated to t

Mina Razghandi, Hao Zhou, Melike Erol-Kantarci, Damla Turgut

Data is the fuel of data science and machine learning techniques for smart grid applications, similar to many other fields. However, the availability of data can be an issue due to privacy concerns, data size, data quality, and so on. To this end, in this paper, we propose a Variational AutoEncoder Generative Adversarial Network (VAE-GAN) as a smart grid dat

Lingzhi Zhao, Ying Cui, Sheng Yang, Shlomo Shamai

Immersive video, such as virtual reality (VR) and multi-view videos, is growing in popularity. Its wireless streaming is an instance of general multicast, extending conventional unicast and multicast, whose effective design is still open. This paper investigates general rate splitting for general multicast. Specifically, we consider a multi-carrier single-ce

Han Zhang, Hao Zhou, Melike Erol-Kantarci

Recently, the concept of open radio access network (O-RAN) has been proposed, which aims to adopt intelligence and openness in the next generation radio access networks (RAN). It provides standardized interfaces and the ability to host network applications from third-party vendors by x-applications (xAPPs), which enables higher flexibility for network manage

Zinan Xiong, Chenxi Wang, Ying Li, Yan Luo

Convolutional neural networks (CNNs) have been widely utilized in many computer vision tasks. However, CNNs have a fixed reception field and lack the ability of long-range perception, which is crucial to human pose estimation. Due to its capability to capture long-range dependencies between pixels, transformer architecture has been adopted to computer vision

Si-si Zhang, Jian-wei Liu, Xin Zuo, Run-kun Lu

Online learning is an important technical means for sketching massive real-time and high-speed data. Although this direction has attracted intensive attention, most of the literature in this area ignore the following three issues: (1) they think little of the underlying abstract hierarchical latent information existing in examples, even if extracting these a

Phil Attard

Bose-Einstein condensation and the $\lambda$-transition are described in molecular detail for bosons interacting with a pair potential. New phenomena are identified that are absent in the usual ideal gas treatment. Monte Carlo simulations of Lennard-Jones helium-4 neglecting ground momentum state bosons give a diverging heat capacity approaching the transiti

Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du

Deep learning has introduced significant improvements in many software analysis tasks. Although the Large Language Models (LLMs) based neural code models demonstrate commendable performance when trained and tested within the intra-project independent and identically distributed (IID) setting, they often struggle to generalize effectively to real-world inter-

Anna Haensch, Natasa Dragovic, Christoph Börgers, Bruce Boghosian

Covid-19 vaccines are widely available in the United States, yet our Covid-19 vaccination rates have remained far below 100%. Not only that, but CDC data shows that even in places where vaccine acceptance was proportionally high at the outset of the Covid-19 vaccination effort, that willingness has not necessarily translated into high rates of vaccination ov

Gabriel Santana, Maira Valera-López

This research aimed to introduce the concept of harmonically m-convex set-valued functions, which is obtained from the combination of two definitions: harmonically m-convex functions and set-valued functions. In this work some properties and characteristics are developed, as well as a inequality of the Hermite-Hadamard type for such functions.

Omid Abbasi, Halim Yanikomeroglu

In this paper, we propose a cell-free scheme for unmanned aerial vehicle (UAV) base stations (BSs) to manage the severe intercell interference between terrestrial users and UAV-BSs of neighboring cells. Since the cell-free scheme requires enormous bandwidth for backhauling, we propose to use the sub-terahertz (sub-THz) band for the backhaul links between UAV

Sara Farazi, Davood Rafiei

A large volume of content generated by online users is geo-tagged and this provides a rich source for querying in various location-based services. An important class of queries within such services involves the association between content and locations. In this paper, we study two types of queries on streaming geo-tagged data: 1) "Top-k reverse frequent spat

Dafa Li

In [Science 340:1205, (2013)], via entanglement polytopes Michael Walter et al. obtained a finite yet systematic classification of multi-particle entanglement. It is well known that under SLOCC, pure states of three (four) qubits are partitioned into six (nine) families. In this paper,we present a LU invariant and an entanglement measures for the GHZ SLOCC c

Hao Ding, Adam Deller, Marcus Lower, Ryan Shannon

Boasting supreme magnetic strengths, magnetars are among the prime candidates to generate fast radio bursts. Several theories have been proposed for the formation mechanism of magnetars, but have not yet been fully tested. As different magnetar formation theories expect distinct magnetar space velocity distributions, high-precision astrometry of Galactic mag

Archisman Ghosh, J. M. B. Mera, Angshuman Karmakar, Debayan Das

National Institute of Standard & Technology (NIST) is currently running a multi-year-long standardization procedure to select quantum-safe or post-quantum cryptographic schemes to be used in the future. Saber is the only LWR based algorithm to be in the final of Round 3. This work presents a Saber ASIC which provides 1.37X power-efficient, 1.75x lower area,

Lingfeng Li, Manqi Ruan, Yudong Wang, Yuexin Wang

The rare $b\to s\nu\bar{\nu}$ decays are sensitive to contributions of new physics (NP) and helpful to resolve the puzzle of multiple $B$ flavor anomalies. In this work, we propose to study the $b\to s\nu\bar{\nu}$ transition at a future lepton collider operating at the $Z$ pole through the $B_s \to \phi\nu\bar{\nu}$ decay. Using the $B_s\to\phi$ decay form

Robert E. Kent

The first-order logical environment FOLE [5] provides a rigorous and principled approach to distributed interoperable first-order information systems. FOLE has been developed in two forms: a classification form and an interpretation form. Two papers represent FOLE in a classification form corresponding to ideas of the Information Flow Framework [11],[12],[13

Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler

Learning is a process which can update decision rules, based on past experience, such that future performance improves. Traditionally, machine learning is often evaluated under the assumption that the future will be identical to the past in distribution or change adversarially. But these assumptions can be either too optimistic or pessimistic for many proble

Shubin Fu, Eric Chung, Lina Zhao

In this paper, we study the generalized multiscale finite element method (GMsFEM) for single phase compressible flow in highly heterogeneous porous media. We follow the major steps of the GMsFEM to construct permeability dependent offline basis for fast coarse-grid simulation. The offline coarse space is efficiently constructed only once based on the initial

Yao Yao, Zhuolun Wang, Peng Luo, Hanyu Yin

Human activity analysis based on sensor data plays a significant role in behavior sensing, human-machine interaction, health care, and so on. The current research focused on recognizing human activity and posture at the activity pattern level, neglecting the effective fusion of multi-sensor data and assessing different movement styles at the individual level

S. R. Wu, B. Q. Wang, Dong Liu, Z. W. Long

In present work, the evolution of scalar field and electromagnetic field under the background of the charged black-bounce spacetimes are investigated, and we obtain an obvious echoes signal which appropriately reports the properties of the charged black-bounce spacetimes and disclose the physical reasons behind such phenomena. Furthermore, by studying the qu