January 2022 arXiv papers — page 35

Andrea Bevilacqua, Jerzy Kowalski-Glikman, Wojciech Wislicki

In this paper we revisit the model of $\kappa$-deformed complex scalar field. We find that this model possesses ten conserved Noether charges that form, under commutators, a representation of (undeformed) Poincar\'e algebra. It follows that the theory is relativistic and does not break Lorentz invariance. However the spacetime representation of boosts is not

Emiru Tsunoo, Chaitanya Narisetty, Michael Hentschel, Yosuke Kashiwagi

A streaming style inference of encoder-decoder automatic speech recognition (ASR) system is important for reducing latency, which is essential for interactive use cases. To this end, we propose a novel blockwise synchronous decoding algorithm with a hybrid approach that combines endpoint prediction and endpoint post-determination. In the endpoint prediction,

Michelle Lochner, Bruce A. Bassett

The next generation of telescopes such as the SKA and the Rubin Observatory will produce enormous data sets, requiring automated anomaly detection to enable scientific discovery. Here, we present an overview and friendly user guide to the Astronomaly framework for active anomaly detection in astronomical data. Astronomaly uses active learning to combine the

Zhiyu Tian, Yuan-Yuan Zhao, Hao Wu, Zhao Wang

For many protocols, quantum strategies have advantages compared with their classical counter-partners, and these advantages have attracted many interests and applications. One of the famous examples is the Clauser-Horne-Shimony-Holt (CHSH) game, which recasts Bell's theorem~\cite{2} into the framework of a game. In the CHSH game, two space-like separated pla

Anton Galajinsky

Dynamical realizations of the Lifshitz group are studied within the group-theoretic framework. A generalization of the 1d conformal mechanics is constructed, which involves an arbitrary dynamical exponent z. A similar generalization of the Ermakov-Milne-Pinney equation is proposed. Invariant derivative and field combinations are introduced, which enable one

Alessandro Carfì, Fulvio Mastrogiovanni

The possibility for humans to interact with physical or virtual systems using gestures has been vastly explored by researchers and designers in the last twenty years to provide new and intuitive interaction modalities. Unfortunately, the literature about gestural interaction is not homogeneous, and it is characterised by a lack of shared terminology. This le

Sumrit Gupta, Ushasi Chaudhuri, Biplab Banerjee

The performance of a zero-shot sketch-based image retrieval (ZS-SBIR) task is primarily affected by two challenges. The substantial domain gap between image and sketch features needs to be bridged, while at the same time the side information has to be chosen tactfully. Existing literature has shown that varying the semantic side information greatly affects t

Xiren Zhou, Qiuju Chen, Shengfei Lyu, Huanhuan Chen

Ground Penetrating Radar (GPR) is widely used as a non-destructive approach to estimate buried utilities. When the GPR's detecting direction is perpendicular to a pipeline, a hyperbolic characteristic would be formed on the GPR B-scan image. However, in real-world applications, the direction of pipelines on the existing pipeline map could be inaccurate, and

Benjamin Guiselin, Gilles Tarjus, Ludovic Berthier

We propose and numerically implement a local probe of the static self-induced heterogeneity characterizing glass-forming liquids. The method relies on the equilibrium statistics of the overlap between pairs of configurations measured in mesoscopic cavities with unconstrained boundaries. By systematically changing the location of the probed cavity, we directl

Rahul Goel, Modar Sulaiman, Kimia Noorbakhsh, Mahdi Sharifi

Facial images disclose many hidden personal traits such as age, gender, race, health, emotion, and psychology. Understanding these traits will help to classify the people in different attributes. In this paper, we have presented a novel method for classifying images using a pretrained transformer model. We apply the pretrained transformer for the binary clas

P. -M. Hillenbrand, S. Hagmann, Y. S. Kozhedub, E. P. Benis

We present an experimental and theoretical study of symmetric $\textrm{Xe}^{54+}+\textrm{Xe}$ collisions at 50, 30, and 15 MeV/u, corresponding to strong perturbations with $v_K/v_\text{p}$ = 1.20, 1.55, and 2.20, respectively ($v_K$: classical $K$-shell orbital velocity, $v_\text{p}$: projectile velocity), as well as $\textrm{Xe}^{53+}+\textrm{Xe}$ collisio

Akinori Kamiyama, Masahiro Matsuura, John N. Moore, Takaaki Mano

We present scanning optical stroboscopic confocal microscopy and spectroscopy measurements wherein three degrees of freedom, namely energy, real-space, and real-time, are resolvable. The edge-state propagation is detected as a temporal change in the optical response in the downstream edge. We succeeded in visualizing the excited states of the most fundamenta

Vittorio Fabris

Recent studies pointed out some limitations about classic top-k queries and skyline queries. Ranking queries impose the user to provide a specific scoring function, which can lead to the exclusion of interesting results because of the inaccurate estimation of the assigned weights. The skyline approach makes it difficult to always retrieve an accurate result,

Zhihong Yuan, Pengyu Zheng, Yiran Peng, Rui Liu

The electronic structure, lattice dynamics, and electron-phonon coupling (EPC) of the newly discovered (Ba,K)SbO$_3$ superconductors are investigated by first-principles calculations. The EPC of (Ba,K)SbO$_3$ is significantly enhanced by considering non-local electronic correlation using the Heyd-Scuseria-Ernzerhof hybrid exchange-correlation functional (HSE

Iyad Suleiman, Jens Arnbak Holbøll Nielsen, Xueshi Guo, Nitin Jain

We demonstrate the generation, 40 km fiber transmission, and homodyne detection of single-mode squeezed states of light at 1550 nm using real-time phase control of a locally generated local oscillator, often called a "real local oscillator" or "local local oscillator". The system was able to stably measure up to around 3.7 dB of noise suppression with a phas

Gy. Gyürky, Z. Halász, G. G. Kiss, T. Szücs

14N(p,gamma)15O is one of the key reactions of nuclear astrophysics playing a role in various stellar processes and influencing energy generation of stars, stellar evolution and nucleosynthesis. For a reliable reaction rate calculation the low energy cross section of 14N(p,gamma)15O must be known with high accuracy. Owing to the unmeasurable low cross sectio

Zhi Wu, Dongheng Zhang, Chunyang Xie, Cong Yu

Human silhouette segmentation, which is originally defined in computer vision, has achieved promising results for understanding human activities. However, the physical limitation makes existing systems based on optical cameras suffer from severe performance degradation under low illumination, smoke, and/or opaque obstruction conditions. To overcome such limi

Yu-kuo Zhao, Yu-xin Dong

In the literature of calculating atomic and molecular structures, most Schrodinger equations are described by Coulomb potential. However, there are also a few literatures that discuss some magnetic correction methods, such as Pauli and Shortley's early work. But in fact, the calculation accuracy of these Schrodinger equations is not consistent with Lamb shif

Kyungsub Lee, Byoung Ki Seo

This study proposes a versatile model for the dynamics of the best bid and ask prices using an extended Hawkes process. The model incorporates the zero intensities of the spread-narrowing processes at the minimum bid-ask spread, spread-dependent intensities, possible negative excitement, and nonnegative intensities. We apply the model to high-frequency best

C. E. Kofinas, V. Metaftsis, A. I. Papistas

For a Baumslag-Solitar group $G$ we calculate the intersection $\gamma_w(G)$ of all terms of the lower central sequence of $G$.Using this we are able to show that $[\gamma_w(G),G]=\gamma_w(G)$ thus answering a question of Bardakov and Neschadim. Finally we show that the quotient groups $\gamma_c(G)/\gamma_{c+1}(G)$ of the lower central series of $G$ are fini

Chih Wei Ling, Yanxiao Liu, Cheuk Ting Li

In this paper, we introduce a new class of codes, called weighted parity-check codes, where each parity-check bit has a weight that indicates its likelihood to be one (instead of fixing each parity-check bit to be zero). It is applicable to a wide range of settings, e.g. asymmetric channels, channels with state and/or cost constraints, and the Wyner-Ziv prob

Xiren Zhou, Qiuju Chen, Shengfei Lyu, Huanhuan Chen

With the rapid expansion of urban areas and the increasingly use of electricity, the need for locating buried cables is becoming urgent. In this paper, a noval method to locate underground cables based on Ground Penetrating Radar (GPR) and Gaussian-process regression is proposed. Firstly, the coordinate system of the detected area is conducted, and the input

Sanchar Sharma, Victor A. S. V. Bittencourt, Silvia Viola Kusminskiy

We propose and numerically evaluate a protocol to generate an arbitrary quantum state of the magnetization in a magnet. The protocol involves repeatedly exciting a frequency-tunable superconducting transmon and transferring the excitations to the magnet via a microwave cavity. To avoid decay, the protocol must be much shorter than magnon lifetime. Speeding u

Yinhan Wang, Jiang Wang, Shipeng Fan

An active defense against an incoming missile requires information of it, including a guidance law parameter and a first-order lateral time constant. To this end, assuming that a missile with a proportional navigation (PN) guidance law attempts to attack an aerial target with bang-bang evasive maneuvers, a parameter identification model based on the gated re

Robin Kooistra, Khee-Gan Lee, Benjamin Horowitz

The fluctuating Gunn-Peterson approximation (FGPA) is a commonly-used method to generate mock Lyman-$\alpha$ (Ly$\alpha$) forest absorption skewers at Cosmic Noon ($z\gtrsim 2$) from the matter-density field of $N$-body simulations without running expensive hydrodynamical simulations. Motivated by recent developments in 3D IGM tomography observations as well

Sangmin Woo, Jinyoung Park, Inyong Koo, Sumin Lee

Natural Language Video Grounding (NLVG) aims to localize time segments in an untrimmed video according to sentence queries. In this work, we present a new paradigm named Explore-And-Match for NLVG that seamlessly unifies the strengths of two streams of NLVG methods: proposal-free and proposal-based; the former explores the search space to find time segments

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellán Beteta

A search for the decay $B^0\to\phi\mu^+\mu^-$ is performed using proton-proton collisions at centre-of-mass energies of 7, 8, and 13 TeV collected by the LHCb experiment and corresponding to an integrated luminosity of 9 fb$^{-1}$. No evidence for the $B^0\to \phi \mu^+ \mu^-$ decay is found and an upper limit on the branching fraction, excluding the $\phi$

Gautam Rajendrakumar Gare, Andrew Schoenling, Vipin Philip, Hai V Tran

We propose using a pre-trained segmentation model to perform diagnostic classification in order to achieve better generalization and interpretability, terming the technique reverse-transfer learning. We present an architecture to convert segmentation models to classification models. We compare and contrast dense vs sparse segmentation labeling and study its

Grigory Korolev, Aleksey Kureev, Evgeny Khorov, Andrey Lyakhov

Non-Orthogonal Multiple Access (NOMA) is a promising technology for future Wi-Fi. In uplink NOMA, stations with different channel conditions transmit simultaneously at the same frequency by splitting the signal by power level. Since Wi-Fi uses random access, the implementation of uplink NOMA in Wi- Fi faces many challenges. The paper presents a data transmis

Kazuya Horibe, Yuanxiang Fan, Yutaka Nakamura, Hiroshi Ishiguro

Humans communicate non-verbally by sharing physical rhythms, such as nodding and gestures, to involve each other. This sharing of physicality creates a sense of unity and makes humans feel involved with others. In this paper, we developed a new body motion generation system based on the free-energy principle (FEP), which not only responds passively but also

Michael Ponds

This thesis is devoted to the construction of theories describing the consistent propagation of (super)conformal higher-spin fields on curved three- and four-dimensional (super)spaces. In the first half of this thesis we systematically derive models for conformal fields of arbitrary rank on various types of curved spacetimes. On generic conformally-flat back

Xin Jin, Ruoyu Feng, Simeng Sun, Runsen Feng

Traditional media coding schemes typically encode image/video into a semantic-unknown binary stream, which fails to directly support downstream intelligent tasks at the bitstream level. Semantically Structured Image Coding (SSIC) framework makes the first attempt to enable decoding-free or partial-decoding image intelligent task analysis via a Semantically S

Damjan Škulj

Credal sets are one of the most important models for describing probabilistic uncertainty. They usually arise as convex sets of probabilistic models compatible with judgments provided in terms of coherent lower previsions or more specific models such as coherent lower probabilities or probability intervals. In finite spaces, credal sets usually take the form

Enrico Viganò, Oscar Cornejo, Fabrizio Pastore, Lionel Briand

Cyber-physical systems (CPSs) typically consist of a wide set of integrated, heterogeneous components; consequently, most of their critical failures relate to the interoperability of such components.Unfortunately, most CPS test automation techniques are preliminary and industry still heavily relies on manual testing. With potentially incomplete, manually-gen

Yeong Gyun Kim, Kang Young Lee, Jungil Lee, Soo-hyeon Nam

We discuss vacuum structure and vacuum stability in classically scale-invariant renormalizable models with a scalar dark matter multiplet of global O(N) symmetry together with an electroweak singlet scalar mediator. Our conformally invariant scalar potential generates the electroweak symmetry breaking via the Coleman-Weinberg mechanism, and the new scalar si

Xiaolong Zhang, Xicheng Zhang

Let $\alpha\in(0,2)$ and $d\in\mathbb{N}$. Consider the following stochastic differential equation (SDE) driven by $\alpha$-stable process in $\mathbb{R}^d$: $$ dX_t=b(X_t)dt+\sigma(X_{t-})d L^{\alpha}_t, \quad X_0=x\in\mathbb{R}^d, $$ where $b:\mathbb{R}^d\to\mathbb{R}^d$ and $\sigma:\mathbb{R}^d\to\mathbb{R}^d\otimes\mathbb{R}^d$ are locally $\gamma$-H\"ol

Marcel Fang, Pierre-Alexandre Bliman

We consider in this paper a general SEIRS model describing the dynamics of an infectious disease including latency, waning immunity and infection-induced mortality. We derive an infinite system of differential equations that provides an image of the same infection process, but counting also the reinfections. Existence and uniqueness of the corresponding Cauc

Josh Southerland

Following Beck-Chen, we say a flow $\phi_t$ on a metric space $(X, d)$ is superdense if there is a $c > 0$ such that for every $x \in X$, and every $T>0$, the trajectory $\{\phi_t x\}_{0 \le t \le cT}$ is $1/T$-dense in $X$. We show that a linear flow on a translation surface is superdense if the associated Teichm\"uller geodesic is bounded. Conversely, if t

Ashay Aswale, Antonio Lopez, Aukkawut Ammartayakun, Carlo Pinciroli

Ants have evolved to seek and retrieve food by leaving trails of pheromones. This mechanism has inspired several approaches to decentralized multi-robot coordination. However, in this paper, we show that pheromone trails are a fragile mechanism for coordination, and can be sabotaged to starve the colony. We introduce detractors: malicious agents that leave a

Guanxiong Qu, Gen Tatara

We study the inverse Faraday effect (IFE) in a Dirac Hamiltonian with random impurities using Keldysh formalism and diagrammatic perturbation theory. The mass term in the Dirac Hamiltonian is essential for IFE, where the spin magnetic moment induced by circularly polarized light is proportional to the frequency of the incident light within the THz regime. Fo

Jiang Zhang, Kaiwei Liu

The classic studies of causal emergence have revealed that in some Markovian dynamical systems, far stronger causal connections can be found on the higher-level descriptions than the lower-level of the same systems if we coarse-grain the system states in an appropriate way. However, identifying this emergent causality from the data is still a hard problem th

Jung Hoon Lee

A bridge position of a knot is said to be perturbed if there exists a cancelling pair of bridge disks. Motivated by the examples of knots admitting unperturbed strongly irreducible non-minimal bridge positions due to Jang-Kobayashi-Ozawa-Takao, we derive examples of unperturbed weakly reducible non-minimal bridge positions. Also, a bridge version of Gordon's

Dongyu Rao, Xiao-Jun Wu, Tianyang Xu, Guoyang Chen

Deep learning-based image fusion approaches have obtained wide attention in recent years, achieving promising performance in terms of visual perception. However, the fusion module in the current deep learning-based methods suffers from two limitations, \textit{i.e.}, manually designed fusion function, and input-independent network learning. In this paper, we

Nicolas Champagnat, Denis Villemonais

We study quasi-stationary distributions and quasi-limiting behavior of Markov chains in general reducible state spaces with absorption. We propose a set of assumptions dealing with particular situations where the state space can be decomposed into three subsets between which communication is only possible in a single direction. These assumptions allow us to

Hongyu Song, Jincheng Yu, Jiantao Qiu, Zhixiao Sun

For scenes such as floods and earthquakes, the disaster area is large, and rescue time is tight. Multi-UAV exploration is more efficient than a single UAV. Existing UAV exploration work is modeled as a Coverage Path Planning (CPP) task to achieve full coverage of the area in the presence of obstacles. However, the endurance capability of UAV is limited, and

Thierry Bodineau, Isabelle Gallagher, Laure Saint-Raymond, Sergio Simonella

The evolution of a gas can be described by different models depending on the observation scale. A natural question, raised by Hilbert in his sixth problem, is whether these models provide consistent predictions. In particular, for rarefied gases, it is expected that continuum laws of kinetic theory can be obtained directly from molecular dynamics governed by

Satoko Ito, Ruck Thawonmas, Pujana Paliyawan

This paper proposes a Minecraft-based system for early detection of Alzheimer's disease in young adults. Early detection, where spatial navigation is a crucial key, is regarded as an important way to prevent the disease. The proposed system is compared with a recent existing and thoroughly studied system using a game called Sea Hero Quest (SHQ), by analyzing

Dongyu Rao, Xiao-Jun Wu, Tianyang Xu

The end-to-end image fusion framework has achieved promising performance, with dedicated convolutional networks aggregating the multi-modal local appearance. However, long-range dependencies are directly neglected in existing CNN fusion approaches, impeding balancing the entire image-level perception for complex scenario fusion. In this paper, therefore, we

Nicolas Vanspranghe, Lucas Brivadis

This paper deals with the problem of robust output regulation of systems governed by nonlinear contraction semigroups. After adding an integral action to the system, we design a feedback law based on the so-called forwarding approach. For small constant perturbations, we give sufficient conditions for the existence of a locally exponentially stable equilibri

Ziheng Chen, Tianyang Xu, Xiao-Jun Wu, Rui Wang

The Symmetric Positive Definite (SPD) matrices have received wide attention for data representation in many scientific areas. Although there are many different attempts to develop effective deep architectures for data processing on the Riemannian manifold of SPD matrices, very few solutions explicitly mine the local geometrical information in deep SPD featur

C Cuny, J Dedecker, F Merlevède

We obtain large and moderate deviation estimates, as well as concentration inequalities, for a class of nonuniformly expanding maps with stretched exponential decay of correlations. In the large deviation regime, we also exhibit examples showing that the obtained upper bounds are essentially optimal.

Vincent Huin, Giulia Coarelli, Clément Guemy, Susana Boluda

CANVAS caused by RFC1 biallelic expansions is a major cause of inherited sensory neuronopathy. Detection of RFC1 expansion is challenging and CANVAS can be associated with atypical features. We clinically and genetically characterized 50 patients, selected based on the presence of sensory neuronopathy confirmed by EMG. We screened RFC1 expansion by PCR, repe

Yunlong Hou, Vincent Y. F. Tan, Zixin Zhong

We design and analyze VA-LUCB, a parameter-free algorithm, for identifying the best arm under the fixed-confidence setup and under a stringent constraint that the variance of the chosen arm is strictly smaller than a given threshold. An upper bound on VA-LUCB's sample complexity is shown to be characterized by a fundamental variance-aware hardness quantity $

Joseph Y. Halpern, Yuval Heller, Eyal Winter

We study the strategic advantages of coarsening one's utility by clustering nearby payoffs together (i.e., classifying them the same way). Our solution concept, coarse-utility equilibrium (CUE) requires that (1) each player maximizes her coarse utility, given the opponent's strategy, and (2) the classifications form best replies to one another. We characteri

Yuan RuiFeng, Wu Lei

A kinetic model called the $\nu$-model is proposed to replace the complicated Boltzmann collision operator in the simulation of rarefied flows of monatomic gas. The model follows the relaxation-time approximation, but the collision frequency (i.e, inverse relaxation time) is a function of the molecular velocity to reflect part of the collision details of the

Tong Yang

It has been a fascinating topic in the study of boundary layer theory about the well-posedness of Prandtl equation that was derived in 1904. Recently, new ideas about cancellation to overcome the loss of tangential derivatives were obtained so that Prandtl equation can be shown to be well-posed in Sobolev spaces to avoid the use of Crocco transformation as i

Soumitri Chattopadhyay, Siladittya Manna, Saumik Bhattacharya, Umapada Pal

Offline Signature Verification (OSV) is a fundamental biometric task across various forensic, commercial and legal applications. The underlying task at hand is to carefully model fine-grained features of the signatures to distinguish between genuine and forged ones, which differ only in minute deformities. This makes OSV more challenging compared to other ve

Md Nadim, Debajyoti Mondal, Chanchal K. Roy

The most common use of data visualization is to minimize the complexity for proper understanding. A graph is one of the most commonly used representations for understanding relational data. It produces a simplified representation of data that is challenging to comprehend if kept in a textual format. In this study, we propose a methodology to utilize the rela

Hui Gao

Let $K$ be a mixed characteristic complete discrete valuation field with perfect residue field, and let $K_\infty/K$ be a Kummer tower extension by adjoining a compatible system of $p$-power roots of a chosen uniformizer. We use this Kummer tower to reconstruct Sen theory which classically is obtained using the cyclotomic tower. Using this Sen theory over th

Mengxiang Zhang, Xinxing Yuan, Xi-Wang Luo, Chang Liu

Triply degenerate points (TDPs), which correspond to new types of topological semimetals, can support novel quasiparticles possessing effective integer spins while preserving Fermi statistics. Here by mapping the momentum space to the parameter space of a three-level system in a trapped ion, we experimentally explore the transitions between different types o

A. Chilingarian, G. Hovsepyan, T. Karapetyan, B. Sargsyan

Aragats solar neutron telescope (ASNT) is a unique instrument allowing to measure the energy spectra of electrons accelerated and multiplied in the strong electric fields of the atmosphere. We describe the instrument setup, its operation condition, software, and hardware triggers. We present energy spectra of a very large thunderstorm ground enhancement (TGE

Oussama Saoudi, Ishwar Singh, Hamidreza Mahyar

Autonomous vehicles are the culmination of advances in many areas such as sensor technologies, artificial intelligence (AI), networking, and more. This paper will introduce the reader to the technologies that build autonomous vehicles. It will focus on open-source tools and libraries for autonomous vehicle development, making it cheaper and easier for develo

Jamie Laird, Sandheep Ravishankar, Askhkat Jumabekov, Kevin Rietwyk

In this report, we describe a large-area Laser Beam Induced Current (LBIC) microscope that has been adapted to perform Intensity Modulated Photocurrent Spectroscopy in an imaging mode combined with automated J-V electrical characterization. Henceforth we refer to the method as either Intensity Modulated Photocurrent Micro-spectroscopy or simply IMPS microsco

Shiwani Singh, Ganesh Subramanian, Santosh Ansumali

We provide a Boltzmann-type kinetic description for dilute polymer solutions based on two-fluid theory. This Boltzmann-type description uses a quasi-equilibrium based relaxation mechanism to model collisions between a polymer dumbbell and a solvent molecule. The model reproduces the desired macroscopic equations for the polymer-solvent mixture. The proposed

Harshavardhan R. Kalluru, Jaydeep K. Basu

Light emitters in vicinity of a hyperbolic metamaterial (HMM) show a range of quantum optical phenomena from spontaneous decay rate enhancement to strong coupling. In this study, we integrate monolayer Molybdenum disulfide (MoS$_2$) emitter in near field region of HMM. The MoS$_2$ monolayer has A and B excitons, which emit in the red region of visible spectr

Haohan Guo, Zhiping Zhou, Fanbo Meng, Kai Liu

Adversarial waveform generation has been a popular approach as the backend of singing voice conversion (SVC) to generate high-quality singing audio. However, the instability of GAN also leads to other problems, such as pitch jitters and U/V errors. It affects the smoothness and continuity of harmonics, hence degrades the conversion quality seriously. This pa

Chen Cai, Yusu Wang

Although theoretical properties such as expressive power and over-smoothing of graph neural networks (GNN) have been extensively studied recently, its convergence property is a relatively new direction. In this paper, we investigate the convergence of one powerful GNN, Invariant Graph Network (IGN) over graphs sampled from graphons. We first prove the stabil

José Madrid, Barry Simon, Daniel R. Wells

We study comparison of correlation functions for ferromagnetic generalized Ising models with two different apriori measures. One purpose of this note is to publicize some unpublished 45 year old work of Daniel Wells on the issue. We then prove results for the apriori measures associated to one component of D-vectors uniformly distributed on the unit sphere a

Sanjay Chandlekar, Easwar Subramanian, Sanjay Bhat, Praveen Paruchuri

Periodic double auctions (PDA) have applications in many areas such as in e-commerce, intra-day equity markets, and day-ahead energy markets in smart-grids. While the trades accomplished using PDAs are worth trillions of dollars, finding a reliable bidding strategy in such auctions is still a challenge as it requires the consideration of future auctions. A p

Kyohei Shimozato, Michihiro Shintani, Takashi Sato

Outlier detection of semiconductor devices is important since manufacturing variation is inherently inevitable. In order to properly detect outliers, it is necessary to consider the discrepancy from underlying trend. Conventional methods are insufficient as they cannot track spatial changes of the trend}}. This study proposes an adaptive outlier detection us

Yunlang Guo, Chengyuan Wu, Bo Wang

Context. Classical novae are powered by thermonuclear runaways occurring on the surface of accreting white dwarfs (WDs). In the observations, the enrichments of heavy elements in nova ejecta have been detected, indicating a mixing process between the accreted matter and the matter from the outer layers of the underlying WDs prior to nova outbursts. However,

Masanori Katsurada, Takumi Noda

For a class of generalized holomorphic Eisenstein series, we establish complete asymptotic expansions (Theorems~1~and~2), which together with the explicit expression of the latter remainder (Theorem~3), naturally transfer to several new variants of the celebrated formulae of Euler and of Ramanujan for specific values of the Riemann zeta-function (Theorem~4 a

Rutvij Wamanse, Tushuli Patil

Climate change in India is one of the most alarming problems faced by our community. Due to adverse and sudden changes in climate in past few years, mankind is at threat. Various impacts of climate change include extreme heat, changing rainfall patterns, droughts, groundwater, glacier melt, sea-level rise, and many more. Machine Learning can be used to analy

Yongxu Jin, Yushan Han, Zhenglin Geng, Joseph Teran

We present a novel paradigm for modeling certain types of dynamic simulation in real-time with the aid of neural networks. In order to significantly reduce the requirements on data (especially time-dependent data), as well as decrease generalization error, our approach utilizes a data-driven neural network only to capture quasistatic information (instead of

V. J. Dowling, V. A. Slipko, Y. V. Pershin

The modeling of conventional (deterministic) electronic circuits - ones consisting of transistors, resistors, capacitors, inductors, and other traditional electronic components - is a well-established subject. The cycle-to-cycle variability of emerging electronic devices, in particular, certain ReRAM cells, has led to the concept of stochastic circuits. Unfo

V. V. Obukhov

The algebras of the symmetry operators for the Hamilton-Jacobi and Klein-Gordon-Fock equations are found for a charged test particle moving in an external electromagnetic field in a spacetime manifold, on the isotropic (null) hypersurface of which a three-parameter groups of motions act transitively.on the isotropic (null) hypersurface of which a three-param

Yuya Haraguchi, Akira Matsuo, Koichi Kindo, Hiroko Aruga Katori

A polycrystalline sample of the hyperhoneycomb iridate $\beta$-ZnIrO$_3$ was synthesized via a topochemical reaction, and its structural, magnetic, and thermodynamic properties were investigated. The magnetization and heat capacity data show the absence of long-range magnetic order at least down to 2 K. A positive Curie-Weiss temperature $\theta_W \sim 45$ K

Janosch Rieger

The Kaczmarz method is an iterative numerical method for solving large and sparse rectangular systems of linear equations. Gearhart, Koshy and Tam have developed an acceleration technique for the Kaczmarz method that minimizes the distance to the desired solution in the direction of a full Kaczmarz step. The present paper generalizes this technique to an acc

S. Z. Eweis, Zeinab S. I. Mansour

In this paper, we introduce the polynomials $B^{(k)}_{n,\alpha}(x;q)$ generated by a function including Jackson $q$-Bessel functions $J^{(k)}_{\alpha}(x;q)$ $ (k=1,2,3),\,\alpha>-1$. The cases $\alpha=\pm\frac{1}{2}$ are the $q$-analogs of Bernoulli and Euler$^{,}$s polynomials introduced by Ismail and Mansour for $(k=1,2)$, Mansour and Al-Towalib for $(k=3)

Giuseppe A. D'Agostino, Sarah R. Langley

Parcellations are fundamental tools in neuroanatomy, allowing researchers to place functional imaging and molecular data within a structural context in the brain. Visualizing these parcellations is critical to guide biological understanding of clinical and experimental datasets in humans and model organisms. However, software used to visualize parcellations

Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck

In structured prediction, the goal is to jointly predict many output variables that together encode a structured object -- a path in a graph, an entity-relation triple, or an ordering of objects. Such a large output space makes learning hard and requires vast amounts of labeled data. Different approaches leverage alternate sources of supervision. One approac

Suat Evren, Praneeth Vepakomma

Social choice functions help aggregate individual preferences while differentially private mechanisms provide formal privacy guarantees to release answers of queries operating on sensitive data. However, preserving differential privacy requires introducing noise to the system, and therefore may lead to undesired byproducts. Does an increase in the level of d

Zhe Lin, Zike Yuan, Jieru Zhao, Wei Zhang

Power estimation is the basis of many hardware optimization strategies. However, it is still challenging to offer accurate power estimation at an early stage such as high-level synthesis (HLS). In this paper, we propose PowerGear, a graph-learning-assisted power estimation approach for FPGA HLS, which features high accuracy, efficiency and transferability. P

Sicen Liu, Xiaolong Wang, Yongshuai Hou, Ge Li

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain. Most existing EHR-oriented studies, however, either focus on a particular modality or integrate data from different modalities in a straight

Alessandro Palmieri, Hiroyuki Takamura

In this work we derive some blow-up results for semilinear wave equations both in de Sitter and anti-de Sitter spacetimes. By requiring suitable conditions on a time-dependent factor in the nonlinear term, we prove the blow-up in finite time of the spatial averages of local in time solutions. In particular, we derive a sequence of lower bound estimates for t

Weiqian Tan, Binwei Wu, Shuo Wang, Tao Huang

IEEE 802.1Qbv (TAS) is the most widely used technique in Time-Sensitive Networking (TSN) which aims to provide bounded transmission delays and ultra-low jitters in industrial local area networks. With the development of emerging technologies (e.g., cloud computing), many wide-range time-sensitive network services emerge, such as factory automation, connected

Anh-Dzung Doan, Michele Sasdelli, David Suter, Tat-Jun Chin

Fitting geometric models onto outlier contaminated data is provably intractable. Many computer vision systems rely on random sampling heuristics to solve robust fitting, which do not provide optimality guarantees and error bounds. It is therefore critical to develop novel approaches that can bridge the gap between exact solutions that are costly, and fast he

Binwei Wu, Shuo Wang, Jiasen Wang, Weiqian Tan

Deterministic IP (DIP) networking is a promising technique that can provide delay-bounded transmission in large-scale networks. Nevertheless, DIP faces several challenges in the mixed traffic scenarios, including (i) the capability of ultra-low latency communications, (ii) the simultaneous satisfaction of diverse QoS requirements, and (iii) the network effic

Sterling G. Baird, Marianne Liu, Hasan M. Sayeed, Taylor D. Sparks

Experimentally [1-38] and computationally [39-50] validated machine learning (ML) articles are sorted based on the size of the training data: 1-100, 101-10000, and 10000+ in a comprehensive set summarizing legacy and recent advances in the field. The review emphasizes the interrelated fields of synthesis, characterization, and prediction. Size range 1-100 co

Huizi Wu, Shiyi Wang, Hui Fang

With the rapid information explosion on online social network sites (SNSs), it becomes difficult for users to seek new friends or broaden their social networks in an efficient way. Link prediction, which can effectively conquer this problem, has thus attracted wide attention. Previous methods on link prediction fail to comprehensively capture the factors lea

Quan Nguyen Minh, Bang Le Van, Can Nguyen, Anh Le

People detection in top-view, fish-eye images is challenging as people in fish-eye images often appear in arbitrary directions and are distorted differently. Due to this unique radial geometry, axis-aligned people detectors often work poorly on fish-eye frames. Recent works account for this variability by modifying existing anchor-based detectors or relying

Ziao Wang, Ning Zhang, Weina Wang, Lele Wang

Graph alignment aims at finding the vertex correspondence between two correlated graphs, a task that frequently occurs in graph mining applications such as social network analysis. Attributed graph alignment is a variant of graph alignment, in which publicly available side information or attributes are exploited to assist graph alignment. Existing studies on

An-Dan Nguyen, Duc-Thinh Pham, Nimrod Lilith, Sameer Alam

General real-time runway occupancy time prediction modelling for multiple airports is a current research gap. An attempt to generalize a real-time prediction model for Arrival Runway Occupancy Time (AROT) is presented in this paper by substituting categorical features by their numerical equivalences. Three days of data, collected from Saab Sensis' Aerobahn s

Ethan Grooby, Chiranjibi Sitaula, Kenneth Tan, Lindsay Zhou

Neonatal respiratory distress is a common condition that if left untreated, can lead to short- and long-term complications. This paper investigates the usage of digital stethoscope recorded chest sounds taken within 1min post-delivery, to enable early detection and prediction of neonatal respiratory distress. Fifty-one term newborns were included in this stu

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, R. Abbott

Results are presented for a semi-coherent search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1, using a hidden Markov model (HMM) to allow for spin wandering. This search improves on previous HMM-based searches of Laser Interferometer Gravitational-wave Observatory (LIGO) data by including the orbital period in the search tem

Keqi Deng, Zehui Yang, Shinji Watanabe, Yosuke Higuchi

While Transformers have achieved promising results in end-to-end (E2E) automatic speech recognition (ASR), their autoregressive (AR) structure becomes a bottleneck for speeding up the decoding process. For real-world deployment, ASR systems are desired to be highly accurate while achieving fast inference. Non-autoregressive (NAR) models have become a popular

Jin Hyun Park

From the point of view of the human brain, continual learning can perform various tasks without mutual interference. An effective way to reduce mutual interference can be found in sparsity and selectivity of neurons. According to Aljundi et al. and Hadsell et al., imposing sparsity at the representational level is advantageous for continual learning because

Md. Ferdous Wahid, Md. Fahim Shahriar, Md. Shohanur Islam Sobuj

Bangla Handwritten Digit recognition is a significant step forward in the development of Bangla OCR. However, intricate shape, structural likeness and distinctive composition style of Bangla digits makes it relatively challenging to distinguish. Thus, in this paper, we benchmarked four rigorous classifiers to recognize Bangla Handwritten Digit: K-Nearest Nei

Hongliang Zhang, Boya Di, Kaigui Bian, Zhu Han

In future cellular systems, wireless localization and sensing functions will be built-in for specific applications, e.g., navigation, transportation, and healthcare, and to support flexible and seamless connectivity. Driven by this trend, the need rises for fine-resolution sensing solutions and cm-level localization accuracy, while the accuracy of current wi

Nikolaos Kalntis

This work is based on a cosmological scenario of a universe dominated by phantom energy with equation of state parameter $w<-1$ and the analysis of its asymptotic behaviour in the far-future. The author discusses whether a Big Rip singularity could be reached in the future. Working in the context of general relativity, it is argued that the Big Rip singulari