October 2022 arXiv papers — page 75

Zetian Jiang, Jiaxin Lu, Tianzhe Wang, Junchi Yan

We consider the general setting for partial matching of two or multiple graphs, in the sense that not necessarily all the nodes in one graph can find their correspondences in another graph and vice versa. We take a universe matching perspective to this ubiquitous problem, whereby each node is either matched into an anchor in a virtual universe graph or regar

Subaveerapandiyan A, Ammaji Rajitha

The primary aim of this study intends the perception of students towards online learning in the covid-19 pandemic period. The pandemic has changed the traditional concepts of the education system and broken the functions of the educational institutions. But, they give it an opportunity to change pedagogy. The research paper discussed the students opinions on

Subaveerapandiyan A, Sakthivel N

This article attempts to comprehend the current issues and hurdles that Indian colleges affiliated with Tamil Nadu State Universities encounter when trying to subscribe to a software that detects plagiarism. The study goals are to determine whether colleges employ anti-plagiarism software, whether they ensure that their student-given assignments are free of

Gian Marcello Andolina, Antonella De Pasquale, Francesco Maria Dimitri Pellegrino, Iacopo Torre

Amperean superconductivity is an exotic phenomenon stemming from attractive effective electron-electron interactions (EEEIs) mediated by a transverse gauge field. Originally introduced in the context of quantum spin liquids and high-Tc superconductors, Amperean superconductivity has been recently proposed to occur at temperatures on the order of 1-20 K in tw

Jingxun Liang, Zhihao Gavin Tang, Yixuan Even Xu, Yuhao Zhang

Ranking and Balance are arguably the two most important algorithms in the online matching literature. They achieve the same optimal competitive ratio of $1-1/e$ for the integral version and fractional version of online bipartite matching by Karp, Vazirani, and Vazirani (STOC 1990) respectively. The two algorithms have been generalized to weighted online bipa

Bowen Xing, Ivor W. Tsang

Recent joint multiple intent detection and slot filling models employ label embeddings to achieve the semantics-label interactions. However, they treat all labels and label embeddings as uncorrelated individuals, ignoring the dependencies among them. Besides, they conduct the decoding for the two tasks independently, without leveraging the correlations betwe

Azahara Luna-Triguero, Eduardo Andres-Garcia, Pedro Leo, Willy Rook

In a world where capture and separation processes represent above 10% of global energy consumption, novel porous materials, such as Metal-Organic Frameworks (MOFs) used in adsorption-based processes are a promising alternative to dethrone the high-energy-demanding distillation. Shape and size tailor-made pores in combination with Lewis acidic sites can enhan

Hiroto Arima, Md. Riad Kasem, Yoshikazu Mizuguchi

This study examines the temperature-dependent evolution of the lattice constants for various CuAl2-type compounds, including NiZr2, (Co,Rh,Ir)Zr2, (Fe,Co,Rh,Ir)Zr2, and (Co,Ni,Cu,Rh,Ir)Zr2, in the pursuit of negative or zero thermal expansion. Results reveal that NiZr2 has positive thermal expansion, while the other compounds exhibit uniaxial negative therma

Lande Ma, Zhaokun Ma

We introduce and develop the root locus method in mathematics. And we study the distribution of zeros of meromorphic functions by root locus method.

Daniela Rato, Miguel Oliveira, Vítor Santos, Manuel Gomes

Collaborative robotic industrial cells are workspaces where robots collaborate with human operators. In this context, safety is paramount, and for that a complete perception of the space where the collaborative robot is inserted is necessary. To ensure this, collaborative cells are equipped with a large set of sensors of multiple modalities, covering the ent

Shuai Wang, Wenjun Zhang, Tao Zhang, Shuyao Mei

Defect-free atomic arrays have been demonstrated as a scalable and fully-controllable platform for quantum simulations and quantum computations. To push the qubit size limit of this platform further, we design an integrated measurement and feedback system, based on field programmable gate array (FPGA), to quickly assemble two-dimensional defect-free atomic a

Tristan Bouchet, Sylvain Chaty, Francis Fortin, John A. Tomsick

Since its launch, the INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL) satellite has discovered hundreds of X-ray sources, many of which lack proper classification. This mission also led to the discovery of new categories of high mass X-ray binaries (HMXB). We use the spectra of the X-Shooter instrument at the Very Large Telescope (VLT) of the Euro

Xuehai He, Diji Yang, Weixi Feng, Tsu-Jui Fu

Prompt tuning is a new few-shot transfer learning technique that only tunes the learnable prompt for pre-trained vision and language models such as CLIP. However, existing prompt tuning methods tend to learn spurious or entangled representations, which leads to poor generalization to unseen concepts. Towards non-spurious and efficient prompt learning from li

Kanta Masuki, Hiroyuki Sudo, Masaki Oshikawa, Yuto Ashida

We reply to the comments on our previous paper Physical Review Letters, Vol. 129, 087001 (2022), raised by Th\'eo S\'epulcre, Serge Florens, and Izak Snyman in arXiv:2210.00742.

Ungki Lee, Namwoo Kang

Neural network (NN) ensembles can reduce large prediction variance of NN and improve prediction accuracy. For highly nonlinear problems with insufficient data set, the prediction accuracy of NN models becomes unstable, resulting in a decrease in the accuracy of ensembles. Therefore, this study proposes a frequency distribution-based ensemble that identifies

Gang Bao, Yiwen Lin, Xiang Xu

Stability results for the Helmholtz equations in both deterministic and random periodic structures are proved in this paper. Under the assumption of excluding resonances, by a variational method and Fourier analysis in the energy space, the stability estimate for the Helmholtz equation in a deterministic periodic structure is established. For the stochastic

Elisa Sanchez-Bayona, Rodrigo Agerri

The lack of wide coverage datasets annotated with everyday metaphorical expressions for languages other than English is striking. This means that most research on supervised metaphor detection has been published only for that language. In order to address this issue, this work presents the first corpus annotated with naturally occurring metaphors in Spanish

Pooja Jayachandran, Lin Htoo Zaw, Valerio Scarani

We introduce a family of entanglement witnesses for continuous variable systems, which rely on the sole assumption that their dynamics is that of coupled harmonic oscillators at the time of the test. Entanglement is inferred from the Tsirelson nonclassicality test on one of the normal modes, without any knowledge about the state of the other mode. In each ro

V Brunn, A Marcowith, C Sauty, M Padovani

Magnetic reconnection is one of the major particle acceleration processes in space and astrophysical plasmas. Low-energy supra-thermal particles emitted by magnetic reconnection are a source of ionisation for circumstellar discs, influencing their chemical, thermal and dynamical evolution. The aim of this work is to propose a first investigation to evaluate

Seungyeon Shin, Dongju Shin, Namwoo Kang

Topology optimization (TO) is a method of deriving an optimal design that satisfies a given load and boundary conditions within a design domain. This method enables effective design without initial design, but has been limited in use due to high computational costs. At the same time, machine learning (ML) methodology including deep learning has made great pr

Dhruv Pathak, Debarati Chatterjee

The spin-down limit of the continuous gravitational wave strain from pulsars assumed to be triaxial stars rotating about a principal moment of inertia axis depends upon the value of the intrinsic spin frequency derivative of the pulsar, among other parameters. In order to get more accurate intrinsic spin frequency derivative values, dynamical effects contrib

Marco Huber, Philipp Terhörst, Florian Kirchbuchner, Naser Damer

Face Recognition (FR) is increasingly used in critical verification decisions and thus, there is a need for assessing the trustworthiness of such decisions. The confidence of a decision is often based on the overall performance of the model or on the image quality. We propose to propagate model uncertainties to scores and decisions in an effort to increase t

Sanjin Benić, Davor Horvatić, Abhiram Kaushik, Eric Andreas Vivoda

We compute the transverse single spin asymmetry in forward $p^\uparrow p \to hX$ and $p^\uparrow A \to hX$ collisions from the odderon mechanism originally suggested by Kovchegov and Sievert [1]. Working in the hybrid approach of the Color Glass Condensate effective theory we firstly identify the relevant collinear parton distribution function (PDF) of the t

Guodong Ding, Fadime Sener, Angela Yao

Temporal action segmentation (TAS) in videos aims at densely identifying video frames in minutes-long videos with multiple action classes. As a long-range video understanding task, researchers have developed an extended collection of methods and examined their performance using various benchmarks. Despite the rapid growth of TAS techniques in recent years, n

Baiming Zhang, Ying Zhao, Zhixiang Li

Because of their abundance of amino acids, polysaccharides, and many other nutrients that benefit human beings, mushrooms are deservedly popular as dietary cuisine both worldwide and in China. However, if people eat poisonous fungi by mistake, they may suffer from nausea, vomiting, mental disorder, acute anemia, or even death. Each year in China, there are a

Yingyao Wang, Junwei Bao, Chaoqun Duan, Youzheng Wu

Hybrid question answering (HQA) aims to answer questions over heterogeneous data, including tables and passages linked to table cells. The heterogeneous data can provide different granularity evidence to HQA models, e.t., column, row, cell, and link. Conventional HQA models usually retrieve coarse- or fine-grained evidence to reason the answer. Through compa

Botao Yu, Peiling Lu, Rui Wang, Wei Hu

Symbolic music generation aims to generate music scores automatically. A recent trend is to use Transformer or its variants in music generation, which is, however, suboptimal, because the full attention cannot efficiently model the typically long music sequences (e.g., over 10,000 tokens), and the existing models have shortcomings in generating musical repet

Shuntaro Aoki, Ryotaro Ishikawa, Sergei V. Ketov

We extend the Cecotti-Kallosh model of Starobinsky inflation in supergravity by adding a holomorphic function to the superpotential in order to generate a large peak in the power spectrum of scalar (curvature) perturbations. In our approach, the singular non-canonical kinetic terms are largely responsible for inflation (as an attractor solution), whereas the

Y. Kuang

We discuss a possible generalisation of a conjecture of Bley, Burns and Hahn concerning the relation between the second Adams-operator twisted Galois-Gauss sums of weakly ramified Artin characters and the square root of the inverse different of finite, odd degree, Galois extensions of number fields, to the setting of all finite Galois extensions of number fi

LHCb collaboration

An amplitude analysis of $B^-\to J/\psi\Lambda\bar{p}$ decays is performed using about 4400 signal candidates selected on a data sample of $pp$ collisions recorded at center-of-mass energies of 7, 8 and 13 TeV with the LHCb detector, corresponding to an integrated luminosity of 9 fb$^{-1}$. A narrow resonance in the $J/\psi\Lambda$ system, consistent with a

Borhan Ahmadi, Ricard Ravell Rodríguez, Robert Alicki, Michał Horodecki

Interactions between a source of light and atoms are ubiquitous in nature. The study of them is interesting on the fundamental level as well as for applications. They are in the core of Quantum Information Processing tasks and in Quantum Thermodynamics protocols. However, even for two-level atom interacting with field in rotating wave approximation there exi

Rahul Bhattacharjee, Sonu Saini, Vinay Kumar Gupta, Anirudh S. Rana

Experimental and theoretical studies on millimetre-sized droplets suggest that at low Reynolds number the difference between the drag force on a circulating water droplet and that on a rigid sphere is very small (less than 1 %) (LeClair et al., J. Atmos. Sci., vol. 29, 1972, pp. 728-740). While the drag force on a spherical liquid droplet at high viscosity r

Xuming Hu, Yong Jiang, Aiwei Liu, Zhongqiang Huang

Data augmentation techniques have been used to alleviate the problem of scarce labeled data in various NER tasks (flat, nested, and discontinuous NER tasks). Existing augmentation techniques either manipulate the words in the original text that break the semantic coherence of the text, or exploit generative models that ignore preserving entities in the origi

Kristian Piscicchia, Magdalena Skurzok, Michael Cargnelli, Raffaele Del Grande

We report the first simultaneous and independent measurements of the K$^{-}$p $\rightarrow \Sigma^0 \, \pi^{0}$ and K$^{-}$p $\rightarrow \Lambda \, \pi^{0}$ cross sections around 100 MeV/c kaon momentum. The kaon beam delivered by the DA$\Phi$NE collider was exploited to detect K$^-$ absorptions on Hydrogen atoms, populating the gas mixture of the KLOE drif

Renqian Luo, Liai Sun, Yingce Xia, Tao Qin

Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.e., BERT (and its variants) and GPT (and its variants), the first one has been extensively studied in the

Zhen Qin, XiaoDong Han, Weixuan Sun, Dongxu Li

Linear transformers aim to reduce the quadratic space-time complexity of vanilla transformers. However, they usually suffer from degraded performances on various tasks and corpus. In this paper, we examine existing kernel-based linear transformers and identify two key issues that lead to such performance gaps: 1) unbounded gradients in the attention computat

Manoj K. Rajbhar, Basudeba Maharana, Shyamapada Patra, Shyamal Chatterjee

In this work, we demonstrate the use of tapered optical fibers (TOF) to detect charged particle (ions), irradiated at various energies, fluences and species. The single mode tapered optical fiber has been used in various sensing applications in recent times. Here, tapered optical fibers have been exposed to two different ion species namely Ar+ and N+ at diff

G. Anand, Swarnava Ghosh, Markus Eisenbach

The chemical short-range order (CSRO) in the crystalline materials influences the properties and its effect is particularly important in the context of the multicomponent materials. We propose a scheme for CSRO parameter or $\mathrm{\Delta-}$parameter in terms of number of like and unlike bonds in the multicomponent systems. The OPERA or $\bf{O}$rder $\bf{P}

Justin Ziegenbein, Manuel Schrick, Marko Thiel, Johannes Hinckeldeyn

A key aspect of the precision of a mobile robots localization is the quality and aptness of the map it is using. A variety of mapping approaches are available that can be employed to create such maps with varying degrees of effort, hardware requirements and quality of the resulting maps. To create a better understanding of the applicability of these differen

Kaiyuan Chen, Weiwei Xu, Linhua Jiang

We present MMT spectroscopic observations of two massive galaxy cluster candidates at redshift $z\sim0.07$ that show extended and diffuse X-ray emission in the ROSAT All Sky Survey (RASS) images. The targets were selected from a previous catalog of 303 newly-identified cluster candidates with the similar properties using the intra-cluster medium emission. Us

Kangyu Lin, Toshiyuki Ohtsuka

In this study, we focus on the numerical solution method for the optimal control problem with equilibrium constraints (OCPEC).It is extremely challenging to solve OCPEC owing to the absence of constraint regularity and strictly feasible interior points. To solve OCPEC efficiently, we first relax the discretized OCPEC to recover the constraint regularity and

Jihye Back, Seungkwon Kim, Namhyuk Ahn

Full-body portrait stylization, which aims to translate portrait photography into a cartoon style, has drawn attention recently. However, most methods have focused only on converting face regions, restraining the feasibility of use in real-world applications. A recently proposed two-stage method expands the rendering area to full bodies, but the outputs are

Jörg-Uwe Löbus

For a class of piecewise deterministic Markov processes we introduce a stochastic calculus which is a certain non-Gaussian counterpart to the classical Malliavin calculus. As an application we investigate the regularity of densities of $N$-particle Boltzmann type processes at time $t>0$.

Josh Shelton, Philippe H. Trinh

There has been significant recent interest in the study of water waves coupled with non-zero vorticity. We derive analytical approximations for the exponentially-small free-surface waves generated in two-dimensions by one or several submerged point vortices when driven at low Froude numbers. The vortices are fixed in place, and a boundary-integral formulatio

Felix Friedrich, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting

Current transformer language models (LM) are large-scale models with billions of parameters. They have been shown to provide high performances on a variety of tasks but are also prone to shortcut learning and bias. Addressing such incorrect model behavior via parameter adjustments is very costly. This is particularly problematic for updating dynamic concepts

Quoc Lap Trieu, Bahman Javadi, Jim Basilakis, Adel N. Toosi

Next generation technologies such as smart healthcare, self-driving cars, and smart cities require new approaches to deal with the network traffic generated by the Internet of Things (IoT) devices, as well as efficient programming models to deploy machine learning techniques. Serverless edge computing is an emerging computing paradigm from the integration of

Vignesh V Menon, Hadi Amirpour, Prajit T Rajendran, Mohammad Ghanbari

In live streaming applications, a fixed set of bitrate-resolution pairs (known as bitrate ladder) is generally used to avoid additional pre-processing run-time to analyze the complexity of every video content and determine the optimized bitrate ladder. Furthermore, live encoders use the fastest available preset for encoding to ensure the minimum possible lat

Jin Myung Kwak, Minseon Kim, Sung Ju Hwang

Transformer-based Language Models (LMs) have achieved impressive results on natural language understanding tasks, but they can also generate toxic text such as insults, threats, and profanity, limiting their real-world applications. To overcome this issue, a few text generation approaches aim to detoxify toxic texts using additional LMs or perturbations. How

Domenico Trotta, Laura Vuorinen, Heli Hietala, Timothy Horbury

Spacecraft missions provide the unique opportunity to study the properties of collisionless shocks utilising in situ measurements. In the past years, several diagnostics have been developed to address key shock parameters using time series of magnetic field (and plasma) data collected by a single spacecraft crossing a shock front. A critical aspect of such d

Arvin Ravanpak, Golnaz Farpour Fadakar

In this article we study a constant-roll inflationary model in the context of the DGP brane-world cosmology caused by a quintessence scalar field. We determine an analytical solution for the Friedman equation coupled to the equation of motion of the scaler field. The evolution of the primordial scalar and tensor perturbations is also studied. To check the vi

Edan Lerner, Eran Bouchbinder

A hallmark of structural glasses and other disordered solids is the emergence of excess low-frequency vibrations, on top of the Debye spectrum $D_{\rm Debye}(\omega)$ of phonons ($\omega$ denotes the vibrational frequency), which exist in any solid whose Hamiltonian is translationally invariant. These excess vibrations -- a signature of which is a THz peak i

Chenghao Yang, Xuezhe Ma

Fine-tuning over large pretrained language models (PLMs) has established many state-of-the-art results. Despite its superior performance, such fine-tuning can be unstable, resulting in significant variance in performance and potential risks for practical applications. Previous works have attributed such instability to the catastrophic forgetting problem in t

Maoli Ma, Guifre Molera Calves, Giuseppe Cimo, Ming Xiong

Probing the solar corona is crucial to study the coronal heating and solar wind acceleration. However, the transient and inhomogeneous solar wind flows carry large-amplitude inherent Alfven waves and turbulence, which make detection more difficult. We report the oscillation and propagation of the solar wind at 2.6 solar radii (Rs) by observation of China Tia

Anna D. Skitnevskaya, Kirill Gokhberg, Alexander B. Trofimov, Emma K. Grigoricheva

After ionization of an inner-valence electron of molecules, the resulting cation-radicals store substantial internal energy which, if sufficient, can trigger ejection of an additional electron in an Auger decay usually followed by molecule fragmentation. In the environment, intermolecular Coulombic decay (ICD) and electron-transfer mediated decay (ETMD) are

Kunal Gautam

Jet-flavour identification algorithms are of paramount importance to maximise the physics potential of the Future Circular Collider (FCC). Out of the extensive FCC-ee physics program, flavour tagging is crucial for the Higgs physics program, given the dominance of hadronic decays of the Higgs boson. Highly efficient discrimination of $b$-, $c$-, $s$-, and gl

Zongwei Wang, Min Gao, Wentao Li, Junliang Yu

The acquisition of explicit user feedback (e.g., ratings) in real-world recommender systems is often hindered by the need for active user involvement. To mitigate this issue, implicit feedback (e.g., clicks) generated during user browsing is exploited as a viable substitute. However, implicit feedback possesses a high degree of noise, which significantly und

Yinghui Li, Shirong Ma, Qingyu Zhou, Zhongli Li

Chinese Spell Checking (CSC) aims to detect and correct Chinese spelling errors. Recent researches start from the pretrained knowledge of language models and take multimodal information into CSC models to improve the performance. However, they overlook the rich knowledge in the dictionary, the reference book where one can learn how one character should be pr

Rodrigo S. Mitishita, Gwynn J. Elfring, Ian A. Frigaard

We present an experimental investigation of turbulent drag reduction with flexible and rigid polymer solutions. The flexible polymer is partially hydrolyzed polyacrylamide (HPAM) and the rigid polymer is xanthan gum (XG). The experiments are carried out at low drag reduction ($\%DR < 40$), high drag reduction ($\%DR > 40$) and maximum drag reduction (where t

Renjie Liao, Simon Kornblith, Mengye Ren, David J. Fleet

We revisit the challenging problem of training Gaussian-Bernoulli restricted Boltzmann machines (GRBMs), introducing two innovations. We propose a novel Gibbs-Langevin sampling algorithm that outperforms existing methods like Gibbs sampling. We propose a modified contrastive divergence (CD) algorithm so that one can generate images with GRBMs starting from n

Islam Nassar, Munawar Hayat, Ehsan Abbasnejad, Hamid Rezatofighi

We present LAVA, a simple yet effective method for multi-domain visual transfer learning with limited data. LAVA builds on a few recent innovations to enable adapting to partially labelled datasets with class and domain shifts. First, LAVA learns self-supervised visual representations on the source dataset and ground them using class label semantics to overc

Qi Ma

The Kirchhoff index is defined as the sum of resistance distances between all pairs of vertices in a graph. This index is a critical parameter for measuring graph structures. In this paper, we characterize polygonal chains with the minimum Kirchhoff index, and characterize even (odd) polygonal chains with the maximum Kirchhoff index, which extends the result

Konstantin Aleshkin, Chiu-Chu Melissa Liu

We study K-theoretic GLSM invariants with one-dimensional gauge group and introduce elliptic central charges that depend on an elliptic cohomology class called an elliptic brane and a choice of level structure. These central charges have an integral representation related to an interpolation problem for the elliptic brane and satisfy natural q-difference equ

Ding Ma, Lester Phillip Violeta, Kazuhiro Kobayashi, Tomoki Toda

Sequence-to-sequence (seq2seq) voice conversion (VC) models have greater potential in converting electrolaryngeal (EL) speech to normal speech (EL2SP) compared to conventional VC models. However, EL2SP based on seq2seq VC requires a sufficiently large amount of parallel data for the model training and it suffers from significant performance degradation when

Daisuke Yoshida, Mayuka Ichihara, Takeshi Kondo, Feng-Lei Hong

Frequency-multiplexed quantum communication usually requires a single-shot identification of the frequency mode of a single photon . In this paper, we propose a scheme that can identify the frequency mode with high-resolution even for spontaneously emitted photons whose generation time is unknown, by combining the time-to-space and frequency-to-time mode map

Huai-Xiang Huang, Yu-Qian Cao, Xin Wan

In europium-based iron pnictides superconducting Fe-planes can be influenced by a Zeeman field originated from the neighboring Eu-planes. The field tends to induce spin-density waves with a ferromagnetic average which coexists with the superconducting order by forming complementary patterns of the superconducting and magnetic order parameters in a Fulde-Ferr

Liangkun Yu, Xiang Sun, Rana Albelaihi, Chen Yi

Federated learning (FL) is a collaborative machine learning framework that requires different clients (e.g., Internet of Things devices) to participate in the machine learning model training process by training and uploading their local models to an FL server in each global iteration. Upon receiving the local models from all the clients, the FL server genera

Michihiro Takami, Hans Moritz Guenther, P. Christian Schneider, Tracy L. Beck

We present Gemini-NIFS, VLT-SINFONI and Keck-OSIRIS observations of near-infrared [Fe II] emission associated with the well-studied jets from three active T Tauri stars; RW Aur A, RY Tau and DG Tau taken from 2012-2021. We primarily covered the redshifted jet from RW Aur A, and the blueshifted jets from RY Tau and DG Tau, to investigate long-term time variab

Dietmar Jannach

Recommender systems can be characterized as software solutions that provide users convenient access to relevant content. Traditionally, recommender systems research predominantly focuses on developing machine learning algorithms that aim to predict which content is relevant for individual users. In real-world applications, however, optimizing the accuracy of

Sally Collins

The $0$-surgeries of two knots $K_1$ and $K_2$ are homology cobordant rel meridians if there exists a $\mathbb{Z}$-homology cobordism $X$ between them such that the two knot meridians are in the same homology class in $H_{1}(X,\mathbb{Z})$. In this paper, we give a pair of rationally slice knots which are not smoothly concordant but whose $0$-surgeries are h

Kensuke Akita, Masahide Yamaguchi

We review the distortions of spectra of relic neutrinos due to the interactions with electrons, positrons, and neutrinos in the early universe. We solve integro-differential kinetic equations for the neutrino density matrix, including vacuum three-flavor neutrino oscillations, oscillations in electron and positron background, a collision term and finite temp

Zuozhi Wang, Shengquan Ni, Avinash Kumar, Chen Li

A computing job in a big data system can take a long time to run, especially for pipelined executions on data streams. Developers often need to change the computing logic of the job such as fixing a loophole in an operator or changing the machine learning model in an operator with a cheaper model to handle a sudden increase of the data-ingestion rate. Recent

Wenbiao Li, Ziyang Wang, Yunfang Wu

For readability assessment, traditional methods mainly employ machine learning classifiers with hundreds of linguistic features. Although the deep learning model has become the prominent approach for almost all NLP tasks, it is less explored for readability assessment. In this paper, we propose a BERT-based model with feature projection and length-balanced l

Apurva Badithela, Josefine B. Graebener, Wyatt Ubellacker, Eric V. Mazumdar

We study automated test generation for verifying discrete decision-making modules in autonomous systems. We utilize linear temporal logic to encode the requirements on the system under test in the system specification and the behavior that we want to observe during the test is given as the test specification which is unknown to the system. First, we use the

Naoki Kitazawa

We show that manifolds admitting special generic maps also admit nice generalized multisections. Special generic maps are natural generalized versions of Morse functions with exactly two singular points on closed manifolds, characterizing spheres whose dimensions are not $4$ topologically and the $4$-dimensional unit sphere, and canonical projections of unit

Menghuai Xu, Jiang Zhu, Jun Fang, Ning Zhang

The line spectrum estimation problem is considered in this paper. We propose a CFAR-based Newtonized OMP (NOMP-CFAR) method which can maintain a desired false alarm rate without the knowledge of the noise variance. The NOMP-CFAR consists of two steps, namely, an initialization step and a detection step. In the initialization step, NOMP is employed to obtain

Yuming Qin, Bin Yang

In this paper, we study the asymptotic behavior of solution to a non-autonomous diffusion equations with delay containing some hereditary characteristics and nonlocal diffusion in time-dependent space $C_{\mathcal{H}_{t}(\Omega)}$. When the nonlinear function $f$ satisfies the polynomial growth of arbitrary order $p-1$ $(p \ge 2)$ and the external force $h \

Jihyeon Lee, Wooyoung Kang, Eun-Sol Kim

It is well known that most of the conventional video question answering (VideoQA) datasets consist of easy questions requiring simple reasoning processes. However, long videos inevitably contain complex and compositional semantic structures along with the spatio-temporal axis, which requires a model to understand the compositional structures inherent in the

Sho Higashi, Hajime Susa, Gen Chiaki

We investigate the physical mechanism that decides the saturation level of turbulence in collapsing gas clouds. We perform a suite of high-resolution numerical simulations following the collapse of turbulent gas clouds with various effective polytropic exponents $\gamma_{\rm eff}$, initial Mach numbers $\mathcal{M}_0$, and initial turbulent seeds. Equating t

Apurva Badithela, Tichakorn Wongpiromsarn, Richard M. Murray

This paper studies the evaluation of learning-based object detection models in conjunction with model-checking of formal specifications defined on an abstract model of an autonomous system and its environment. In particular, we define two metrics -- \emph{proposition-labeled} and \emph{class-labeled} confusion matrices -- for evaluating object detection, and

Haibo Li, Guangming Tan, Tong Zhao

The $k$-step Lanczos bidiagonalization reduces a matrix $A\in\mathbb{R}^{m\times n}$ into a bidiagonal form $B_k\in\mathbb{R}^{(k+1)\times k}$ while generates two orthonormal matrices $U_{k+1}\in\mathbb{R}^{m\times (k+1)}$ and $V_{k+1}\in\mathbb{R}^{n\times {(k+1)}}$. However, any practical implementation of the algorithm suffers from loss of orthogonality o

Haotian Wu, Zhou Zhang

We improve the understanding of both finite time and infinite time singularities of the modified K\"ahler-Ricci flow as initiated by the second author of this paper in [26]. This is done by relating the modified K\"ahler-Ricci flow with the recent studies on the classic K\"ahler-Ricci flow and the degenerate complex Monge-Amp\`ere equation.

N. Dimakis, M. Roumeliotis, A. Paliathanasis, P. S. Apostolopoulos

The existence of self-similar solutions is discussed in symmetric teleparallel $f(Q)$-theory for a Friedmann-Lema\^itre-Robertson-Walker background geometry with zero and non-zero spatial curvature. For the four distinct families of connections which describe the specific cosmology in symmetric teleparallel gravity, the functional form of $f(Q)$ is reconstru

Yue Xiao, Peng Zhang, Yuhong Liu

Digital signature is a major component of transactions on Blockchain platforms, especially in enterprise Blockchain platforms, where multiple signatures from a set of peers need to be produced to endorse a transaction. However, such process is often complex and time-consuming. Multi-signature, which can improve transaction efficiency by having a set of signe

Hongqiu Wu, Ruixue Ding, Hai Zhao, Boli Chen

Multiple pre-training objectives fill the vacancy of the understanding capability of single-objective language modeling, which serves the ultimate purpose of pre-trained language models (PrLMs), generalizing well on a mass of scenarios. However, learning multiple training objectives in a single model is challenging due to the unknown relative significance as

Mohamed Azouz Mrad, Kristóf Csorba, Dorián László Galata, Zsombor Kristóf Nagy

Dissolution testing is part of the target product quality that is essential in approving new products in the pharmaceutical industry. The prediction of the dissolution profile based on spectroscopic data is an alternative to the current destructive and time-consuming method. Raman and near-infrared (NIR) spectroscopies are two fast and complementary methods

Harish Krishnakumar, J. Bryce Kalmbach

Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as manual analysis takes months to accumulate an appreciable sample of rings. This paper presents a convolutional neural netwo

Mengting Hu, Yike Wu, Hang Gao, Yinhao Bai

Recently, aspect sentiment quad prediction (ASQP) has become a popular task in the field of aspect-level sentiment analysis. Previous work utilizes a predefined template to paraphrase the original sentence into a structure target sequence, which can be easily decoded as quadruplets of the form (aspect category, aspect term, opinion term, sentiment polarity).

Bozhou Chen, Hongzhi Wang, Chenmin Ba

Learning rate adaptation is a popular topic in machine learning. Gradient Descent trains neural nerwork with a fixed learning rate. Learning rate adaptation is proposed to accelerate the training process through adjusting the step size in the training session. Famous works include Momentum, Adam and Hypergradient. Hypergradient is the most special one. Hyper

Hao Zhang

Pre-trained language models (LMs), such as BERT (Devlin et al., 2018) and its variants, have led to significant improvements on various NLP tasks in past years. However, a theoretical framework for studying their relationships is still missing. In this paper, we fill this gap by investigating the linear dependency between pre-trained LMs. The linear dependen

Rolando Magnanini, Giorgio Poggesi

We consider a mixed boundary value problem in a domain $\Omega$ contained in a half-ball $B_+$ and having a portion $\bar{T}$ of its boundary in common with the curved part of $\partial B_+$. The problem has to do with some sort of constrained torsional rigidity. In this situation, the relevant solution $u$ satisfies a Steklov condition on $T$ and a homogene

Alexander Brudnyi

The paper investigates the algebraic properties of Banach algebras of complex-valued functions of bounded variation on a finite interval. It is proved that such algebras have Bass stable rank one and are projective free if they do not contain nontrivial idempotents. These properties are derived from a new result on the vanishing of the second \v{C}ech cohomo

George Xianzhi Yuan

The goal of this paper is to develop some fundamental and important nonlinear analysis for single-valued mappings under the framework of p-vector spaces, in particular, for locally p-convex spaces for p in (0, 1]. More precisely, based on the fixed point theorem of single-valued continuous condensing mapping in locally p-convex spaces as the starting point,

Janaki Raman Babu, Prosenjit Das, Swapnil A. Lokhande

In this exposition, we propose a notion of rank and rigidity of locally nilpotent derivations of affine fibrations. We show that the concept is analogous to the perception of rank and rigidity of locally nilpotent derivations of polynomial algebras. Our results characterize locally nilpotent derivations of $\mathbb{A}^3$-fibrations having slice by classifyin

M. Klasen, P. Duwentäster, T. Jezo, K. Kovarik

We discuss the two most recent global analyses of nuclear parton distribution functions within the nCTEQ approach. LHC data on $W/Z$-boson, single-inclusive hadron and heavy quark/quarkonium production are shown to not only significantly reduce the gluon uncertainty down to $x\geq10^{-5}$, but to also influence the strange quark density. The latter is furthe

Matthew J. Bryan, Linxing Preston Jiang, Rajesh P N Rao

Objective: A major challenge in designing closed-loop brain-computer interfaces is finding optimal stimulation patterns as a function of ongoing neural activity for different subjects and objectives. Approach: To achieve goal-directed closed-loop neurostimulation, we propose "neural co-processors" which use artificial neural networks and deep learning to lea

Min Jun Jo, Junha Kim, Jihoon Lee

We prove the global well-posedness of the 2D incompressible non-resistive MHD equations with a velocity damping term near the non-zero constant background magnetic field. To this end, we newly design a normal mode method of effectively leveraging the anisotropy of the linear propagator that encodes both the partially dissipative nature of the non-resistive M

Megumi Sano, Futoshi Takahashi

We consider the two-dimensional eigenvalue problem for the Laplacian with the Neumann boundary condition involving the critical Hardy potential. We prove the existence of the second eigenfunction and study its asymptotic behavior around the origin. A key tool is the Sobolev type inequality with a logarithmic weight, which is shown in this paper as an applica

Emanuele M. Ventura, Alessandro Trinca, Raffaella Schneider, Luca Graziani

Modeling the 21cm global signal from the Cosmic Dawn is challenging due to the many poorly constrained physical processes that come into play. We address this problem using the semi-analytical code "Cosmic Archaeology Tool" (CAT). CAT follows the evolution of dark matter halos tracking their merger history and provides an ab initio description of their baryo

Vaibhava Srivastava, Eric M. Takyi, Rana D. Parshad

Non-consumptive effects such as fear of depredation, can strongly influence predator-prey dynamics. These effects have not been as well studied in the case of purely competitive systems, despite ecological and social motivations for the same. In this work we consider the classic two species ODE and PDE Lokta-Volterra competition models, where \emph{one} of t

Ying Ma, Toshiaki Shoji, Zhiping Zhou

Let ${\mathbf U}^-_q$ be the negative half of the quantum group associated to a Kac-Moody algebra ${\mathfrak g}$, and $\underline{\mathbf U}^-_q$ the quantum group obtained by a folding of ${\mathfrak g}$. Let ${\mathbf A} = {\mathbf Z}[q,q^{-1}]$. McNamara showed that $\underline{\mathbf U}^-_q$ is categorified over a certain extenion ring $\widetilde{\mat