October 2022 arXiv papers — page 100

Jay Lawrence, Marcin Markiewicz, Marek Żukowski

In this comment we answer to the recent critique of our article [arXiv:2208.11793] about Relational Quantum Mechanics (RQM) by Aur\'elien Drezet [arXiv:2209.01237]. Here we point out that our critical analysis of RQM was precisely based on the most recent formulation of RQM, and that the theses found in the critique are based on neither RQM assumptions nor o

Gavril Farkas

The classical De Jonquieres and MacDonald formulas describe the virtual number of divisors with prescribed multiplicities in a linear system on an algebraic curve. We establish an essentially optimal result concerning the enumerative validity of these formulas in the case of a general curve of genus g.

Mingjin Zhang, Jiannong Cao, Lei Yang, Liang Zhang

Collaborative edge computing (CEC) is an emerging paradigm enabling sharing of the coupled data, computation, and networking resources among heterogeneous geo-distributed edge nodes. Recently, there has been a trend to orchestrate and schedule containerized application workloads in CEC, while Kubernetes has become the de-facto standard broadly adopted by the

Shanjin Wu, Koichi Murase, Huichao Song

Based on the coalescence model, we analyse the light-nuclei production near the critical point by expanding the phase-space distribution function $f(\mathbf{r},\mathbf{p})$ in terms of the phase-space cumulants $\sim \langle r^m p^m\rangle_c$. We show that the dominant contribution of the phase-space distribution to the yield of light nuclei is determined by

Trisha F. Doyle, Matthew P. Holland, Robert S. Hill, Tahir Yaqoob

XRISM (X-Ray Imaging and Spectroscopy Mission), with the Resolve high-resolution spectrometer and the Xtend wide-field imager on-board, is designed to build on the successes of the abbreviated Hitomi mission to address outstanding astrophysical questions using high resolution X-ray spectroscopy. In preparation for launch, the XRISM Science Data Center (SDC)

Gonzalo Mier, João Valente, Sytze de Bruin

This paper describes Fields2Cover, a novel open source library for coverage path planning (CPP) for agricultural vehicles. While there are several CPP solutions nowadays, there have been limited efforts to unify them into an open source library and provide benchmarking tools to compare their performance. Fields2Cover provides a framework for planning coverag

Randall D. Beer

Garden of Eden (GOE) states in cellular automata are grid configurations which have no precursors, that is, they can only occur as initial conditions. Finding individual configurations that minimize or maximize some criterion of interest (e.g., grid size, density, etc.) has been a popular sport in recreational mathematics, but systematic studies of the set o

Niklas Schmid, Jonas Gruner, Hossam S. Abbas, Philipp Rostalski

Gaussian Process (GP) regressions have proven to be a valuable tool to predict disturbances and model mismatches and incorporate this information into a Model Predictive Control (MPC) prediction. Unfortunately, the computational complexity of inference and learning on classical GPs scales cubically, which is intractable for real-time applications. Thus GPs a

Serafino Cicerone, Gabriele Di Stefano, Sandi Klavžar, Ismael G. Yero

Let $G$ be a graph and $X\subseteq V(G)$. Then $X$ is a mutual-visibility set if each pair of vertices from $X$ is connected by a geodesic with no internal vertex in $X$. The mutual-visibility number $\mu(G)$ of $G$ is the cardinality of a largest mutual-visibility set. In this paper, the mutual-visibility number of strong product graphs is investigated. As

Jouko Väänänen

Anonymity has gained notoriety in modern times as data about our actions and choices accumulates in the internet partly unbeknownst to us and partly by our own choice. Usually people wish some data about themselves were private while some other date may be public or is even wanted to be public for publicity reasons. There are different criteria which charact

Juhi Singh, Robert Zeier, Tommaso Calarco, Felix Motzoi

Predictive design and optimization methods for controlled quantum systems depend on the accuracy of the system model. Any distortion of the input fields in an experimental platform alters the model accuracy and eventually disturbs the predicted dynamics. These distortions can be non-linear with a strong frequency dependence so that the field interacting with

Subaveerapandiyan A, Fakrudhin Ali Ahamed

The Government of India initiated SWAYAM (Study Webs of Active-learning for Young Aspiring Minds), where the objective of the programme is to take the best teaching and learning resources to all with no costs. To find out the awareness and usage of SWAYAM courses among Library and Information science students, survey method of research used. To collect data

Neil Hindman, Maria-Romina Ivan, Imre Leader

Our aim in this paper is to show that, for any $k$, there is a finite colouring of the set of rationals whose denominators contain only the first $k$ primes such that no infinite set has all of its finite sums and products monochromatic. We actually prove a `uniform' form of this: there is a finite colouring of the rationals with the property that no infinit

Rodrigue Lelotte

We prove a conjecture regarding the asymptotic behavior at infinity of the Kantorovich potential for the Multimarginal Optimal Transport with Coulomb and Riesz costs.

Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, Bastian Wandt

Industrial defect detection is commonly addressed with anomaly detection (AD) methods where no or only incomplete data of potentially occurring defects is available. This work discovers previously unknown problems of student-teacher approaches for AD and proposes a solution, where two neural networks are trained to produce the same output for the defect-free

Nils Körber

Visual perception is driven by the focus on relevant aspects in the surrounding world. To transfer this observation to the digital information processing of computers, attention mechanisms have been introduced to highlight salient image regions. Here, we introduce a parameter-free attention mechanism called PfAAM, that is a simple yet effective module. It ca

Yongyong Cai, Lili Ju, Rihui Lan, Jingwei Li

The convective Allen-Cahn equation has been widely used to simulate multi-phase flows in many phase-field models. As a generalized form of the classic Allen-Cahn equation, the convective Allen-Cahn equation still preserves the maximum bound principle (MBP) in the sense that the time-dependent solution of the equation with appropriate initial and boundary con

David Zhang, Gooitzen van der Wal, Saurabh Farkya, Thomas Senko

We present a scalable in-pixel processing architecture that can reduce the data throughput by 10X and consume less than 30 mW per megapixel at the imager frontend. Unlike the state-of-the-art (SOA) analog process-in-pixel (PIP) that modulates the exposure time of photosensors when performing matrix-vector multiplications, we use switched capacitors and pulse

Alexander Fribergh, Tanguy Lions, Carlo Scali

We consider a biased random walk in positive random conductances on $\mathbb{Z}^d$ for $d\geq 5$. In the sub-ballistic regime, we prove the quenched convergence of the properly rescaled random walk towards a Fractional Kinetics.

Anita Mezzetti, Loïc Maréchal, Dimitri Percia David, William Lacube

We introduce TechRank, a recursive algorithm based on a bi-partite graph with weighted nodes. We develop TechRank to link companies and technologies based on the method of reflection. We allow the algorithm to incorporate exogenous variables that reflect an investor's preferences. We calibrate the algorithm in the cybersecurity sector. First, our results hel

Jian Ding, Hang Du, Shuyang Gong

For two independent Erd\H{o}s-R\'enyi graphs $\mathbf G(n,p)$, we study the maximal overlap (i.e., the number of common edges) of these two graphs over all possible vertex correspondence. We present a polynomial-time algorithm which finds a vertex correspondence whose overlap approximates the maximal overlap up to a multiplicative factor that is arbitrarily

Rayhane Pouyan, Hadi Kalamati, Hannane Ebrahimian, Mohammad Karrabi

Movies are a great source of entertainment. However, the problem arises when one is trying to find the desired content within this vast amount of data which is significantly increasing every year. Recommender systems can provide appropriate algorithms to solve this problem. The content_based technique has found popularity due to the lack of available user da

Sebastian Giehl, Carsten Andrich, Michael Schubert, Maximilian Engelhardt

Current and upcoming communication and sensing technologies require ever larger bandwidths. Channel bonding can be utilized to extend a receiver's instantaneous bandwidth beyond a single converter's Nyquist limit. Two potential joint front-end and converter design approaches are theoretically introduced, realized and evaluated in this paper. The Xilinx RFSoC

Marjana Mahdia, James Allred, Zhiyang Yuan, Jared Rovny

Color centers in diamond are widely explored for applications in quantum sensing, computing, and networking. Their optical, spin, and charge properties have been extensively studied, while their interactions with itinerant carriers are relatively unexplored. Here we show that NV centers situated within 10 nm of the diamond surface can be converted to the neu

Cora Uhlemann, Oliver Friedrich, Aoife Boyle, Alex Gough

One-point probability distribution functions (PDFs) of the cosmic matter density are powerful cosmological probes that extract non-Gaussian properties of the matter distribution and complement two-point statistics. Computing the covariance of one-point PDFs is key for building a robust galaxy survey analysis for upcoming surveys like Euclid and the Rubin Obs

Yuqing Liu, Wei Zhang, Weifeng Sun, Zhikai Yu

Deep learning for image super-resolution (SR) has been investigated by numerous researchers in recent years. Most of the works concentrate on effective block designs and improve the network representation but lack interpretation. There are also iterative optimization-inspired networks for image SR, which take the solution step as a whole without giving an ex

Marcos Dajczer, Miguel Ibieta Jimenez

The classical classifications of the locally isometrically deformable Euclidean hypersurfaces obtained by U. Sbrana in 1909 and E. Cartan in 1916 includes four classes, among them the one formed by submanifolds that allow just a single deformation. The question of whether these Sbrana-Cartan hypersurfaces do, in fact, exist was not addressed by either of the

Nandara K. Krishnand, Akshakhi Kumar Pritoonka, Faeze Kiani

Detection of surface defects is one of the most important issues in the field of image processing and machine vision. In this article, a method for detecting surface defects based on energy changes in co-occurrence matrices is presented. The presented method consists of two stages of training and testing. In the training phase, the co-occurrence matrix opera

Dušan Malić, Christian Fruhwirth-Reisinger, Horst Possegger, Horst Bischof

LiDAR 3D object detection models are inevitably biased towards their training dataset. The detector clearly exhibits this bias when employed on a target dataset, particularly towards object sizes. However, object sizes vary heavily between domains due to, for instance, different labeling policies or geographical locations. State-of-the-art unsupervised domai

Xi Chen, Tianyu Shi, Qingpeng Zhao, Yuchen Sun

Recent advances in deep reinforcement learning (RL) have demonstrated complex decision-making capabilities in simulation environments such as Arcade Learning Environment, MuJoCo, and ViZDoom. However, they are hardly extensible to more complicated problems, mainly due to the lack of complexity and variations in the environments they are trained and tested on

Run Wang, Jixing Ren, Boheng Li, Tianyi She

Watermarking has been widely adopted for protecting the intellectual property (IP) of Deep Neural Networks (DNN) to defend the unauthorized distribution. Unfortunately, the popular data-poisoning DNN watermarking scheme relies on target model fine-tuning to embed watermarks, which limits its practical applications in tackling real-world tasks. Specifically,

Luca Canalini, Jan Klein, Nuno Pedrosa de Barros, Diana Maria Sima

In this work, we compare five deep learning solutions to automatically segment the resection cavity in postoperative MRI. The proposed methods are based on the same 3D U-Net architecture. We use a dataset of postoperative MRI volumes, each including four MRI sequences and the ground truth of the corresponding resection cavity. Four solutions are trained with

Leandro Vicente Mauri, Denise de Mattos, Edivaldo Lopes dos Santos

In this paper, we prove a version of the Colored Tverberg Theorem with new constraints on the faces, in which we limit the number of faces with each one of the colors.

Zilun Wang, Wendong Mao, Peixiang Yang, Zhongfeng Wang

Deep learning-based point cloud processing plays an important role in various vision tasks, such as autonomous driving, virtual reality (VR), and augmented reality (AR). The submanifold sparse convolutional network (SSCN) has been widely used for the point cloud due to its unique advantages in terms of visual results. However, existing convolutional neural n

Samrat Mukhopadhyay, Himanshu Bhusan Mishra

We address the problem of sparse recovery using greedy compressed sensing recovery algorithms, without explicit knowledge of the sparsity. Estimating the sparsity order is a crucial problem in many practical scenarios, e.g., wireless communications, where exact value of the sparsity order of the unknown channel may be unavailable a priori. In this paper we h

Thierry Njougouo, Victor Camargo, Patrick Louodop, Fernando F Ferreira

This paper presents the optimal control and synchronization problem of a multilevel network of R\"ossler chaotic oscillators. Using the Hamilton-Jacobi-Bellman (HJB) technique, the optimal control law with three-state variables feedback is designed such that the trajectories of all the R\"ossler oscillators in the network are optimally synchronized in each l

Maximilian Reininghaus

The CORSIKA 8 project is a collaborative effort aiming to develop a versatile C++ framework for the simulation of extensive air showers, intended to eventually succeed the long-standing FORTRAN version. I present an overview of its current capabilities, focusing on aspects concerning the hadronic and muonic shower components. In particular, I demonstrate the

Alan Medlar, Yang Liu, Dorota Glowacka

r/antiwork is a Reddit community that focuses on the discussion of worker exploitation, labour rights and related left-wing political ideas (e.g. universal basic income). In late 2021, r/antiwork became the fastest growing community on Reddit, coinciding with what the mainstream media began referring to as the Great Resignation. This same media coverage was

Tiannan Wang, Wangchunshu Zhou, Yan Zeng, Xinsong Zhang

Pre-trained vision-language models (VLMs) have achieved impressive results in a range of vision-language tasks. However, popular VLMs usually consist of hundreds of millions of parameters which brings challenges for fine-tuning and deployment in real-world applications due to space, memory, and latency constraints. In this work, we introduce a distilling the

Frederick Maes, Karel Van Bockstal

In this article, we study the existence and uniqueness of a weak solution to the fractional single-phase lag heat equation. This model contains the terms $\cal{D}_t^\alpha(u_t)$ and $\cal{D}_t^\alpha u $ (with $\alpha \in(0,1)$), where $\cal{D}_t^\alpha$ denotes the Caputo fractional derivative in time of constant order $\alpha\in(0,1)$. We consider homogene

Yotam Gafni, Aviv Yaish

Cryptocurrencies employ auction-esque transaction fee mechanisms (TFMs) to allocate transactions to blocks, and to determine how much fees miners can collect from transactions. Several impossibility results show that TFMs that satisfy a standard set of "good" properties obtain low revenue, and in certain cases, no revenue at all. In this work, we circumvent

Louis Castricato, Alexander Havrilla, Shahbuland Matiana, Michael Pieler

Controlled automated story generation seeks to generate natural language stories satisfying constraints from natural language critiques or preferences. Existing methods to control for story preference utilize prompt engineering which is labor intensive and often inconsistent. They may also use logit-manipulation methods which require annotated datasets to ex

Camille Noûs, Sylvain Rubenthaler

We are interested in a fragmentation process. We observe fragments frozen when their sizes are less than {\epsilon} ({\epsilon} > 0). It is known ([BM05]) that the empirical measure of these fragments converges in law, under some renormalization. In [HK11], the authors show a bound for the rate of convergence. Here, we show a central-limit theorem, under som

George D Tsibidis, Emmanuel Stratakis

The employment of ultrashort laser sources at the mid-IR spectral region for transparent materials is designed to open new routes for laser patterning and a wealth of exciting applications in optics and photonics. To elucidate the material response to irradiation with mid-IR laser sources, a consistent analysis of the interaction of long wavelength femtoseco

Peter J. Cameron, Michael Kagan

We consider all spanning trees of a complete simple graph $\Gamma$ on $n$ vertices that contain a given $m-$forest $F$. We show that the number of such spanning trees, $\tau(F)$, doesn't depend on the structure of $F$ and is completely determined by the number of vertices $q_i \, (i=1, ..., m)$ in each connected component of $F$. Specifically, $\tau(F) = q_1

Pezhman Nasirifard, Hans-Arno Jacobsen

With the ongoing integration of Renewable Energy Sources (RES), the complexity of power grids is increasing. Due to the fluctuating nature of RES, ensuring the reliability of power grids can be challenging. One possible approach for addressing these challenges is Demand Response (DR) which is described as matching the demand for electrical energy according t

Ashmita, Payel Sarkar, Prasanta Kumar Das

We investigate inflation in modified gravity framework by introducing a direct coupling term between a scalar field $\phi$ and the trace of the energy momentum tensor $T$ as $f(\phi,T) = 2 \phi( \kappa^{1/2} \alpha T + \kappa^{5/2} \beta T^2) $ to the Einstein-Hilbert action. We consider a class of inflaton potentials (i) $V_0 \phi^p e^{-\lambda\phi}$, (ii)

Ngoc Duc Le, Thierry Jolicoeur

We study the fractional quantum Hall effect in the central Landau level of bilayer graphene. By tuning the external applied magnetic field and the electric bias between the two layers one can access a regime where there is a degeneracy between Landau levels with orbital characters corresponding to N=0 and N=1 Galilean Landau levels. While the Laughlin state

I. S. Proshina, A. V. Moiseev, O. K. Sil'chenko

We present the results of our study of starforming regions in the lenticular galaxy NGC 4324. During a complex analysis of multiwavelength observational data -- the narrow-band emission-line images obtained with the 2.5-m telescope at the Caucasus Mountain Observatory of the Sternberg Astronomical Institute of the Moscow State University and the archival ima

Michal Jex, Mathieu Lewin, Peter S. Madsen

We provide upper and lower bounds on the lowest free energy of a classical system at given one-particle density $\rho(x)$. We study both the canonical and grand-canonical cases, assuming the particles interact with a pair potential which decays fast enough at infinity.

Ying Yang, Tim Dwyer, Michael Wybrow, Benjamin Lee

When collaborating face-to-face, people commonly use the surfaces and spaces around them to perform sensemaking tasks, such as spatially organising documents, notes or images. However, when people collaborate remotely using desktop interfaces they no longer feel like they are sharing the same space. This limitation may be overcome through collaboration in im

Yingxiu Zhao, Yinhe Zheng, Zhiliang Tian, Chang Gao

Lifelong learning (LL) is vital for advanced task-oriented dialogue (ToD) systems. To address the catastrophic forgetting issue of LL, generative replay methods are widely employed to consolidate past knowledge with generated pseudo samples. However, most existing generative replay methods use only a single task-specific token to control their models. This s

Baohong Guo, Jannis Teunissen

We study the energy efficiency of species production by streamer discharges with a single voltage pulse in atmospheric dry air, using a 2D axisymmetric fluid model. Sixty different positive streamers are simulated by varying the electrode length, the pulse duration and the applied voltage. Between these cases, the streamer radius and velocity vary by about a

Dhruv Manchanda, Will Sutherland, Charalambos Pittordis

Recent studies have shown that velocity differences of very wide binary stars, measured to high precision with GAIA, can provide an interesting test for modified-gravity theories which emulate dark matter; in essence, MOND-like theories (with external field effect included) predict that wide binaries (wider than ~ 7 kAU) should orbit ~ 15% faster than Newton

Zhirui Chen, P. N. Karthik, Vincent Y. F. Tan, Yeow Meng Chee

We study best arm identification in a federated multi-armed bandit setting with a central server and multiple clients, when each client has access to a {\em subset} of arms and each arm yields independent Gaussian observations. The goal is to identify the best arm of each client subject to an upper bound on the error probability; here, the best arm is one th

Ruth A. Daly

The rotational properties of astrophysical black holes are fundamental quantities that characterization the black holes. A new method to empirically determine the spin mass-energy characteristics of astrophysical black holes is presented and applied here. Results are obtained for a sample of 100 supermassive black holes with collimated dual outflows and reds

C. Fromentin, T. Silva, T. C. Dias, A. S. Morillo-Candas

This work explores the effect of O2 addition on CO2 dissociation and on the vibrational kinetics of CO2 and CO under various non-equilibrium plasma conditions. A self-consistent model, previously validated for pure CO2 discharges, is further extended by adding the vibrational kinetics of CO, including electron impact excitation and de-excitation (e-V), vibra

Anthony Sicilia, Malihe Alikhani

Algorithms for text-generation in dialogue can be misguided. For example, in task-oriented settings, reinforcement learning that optimizes only task-success can lead to abysmal lexical diversity. We hypothesize this is due to poor theoretical understanding of the objectives in text-generation and their relation to the learning process (i.e., model training).

Martino Calzavara, Yevhenii Kuriatnikov, Andreas Deutschmann-Olek, Felix Motzoi

We present our new experimental and theoretical framework which combines a broadband superluminescent diode (SLED/SLD) with fast learning algorithms to provide speed and accuracy improvements for the optimization of 1D optical dipole potentials, here generated with a Digital Micromirror Device (DMD). To characterize the setup and potential speckle patterns a

Fabian Märkert, Martin Sunkel, Anselm Haselhoff, Stefan Rudolph

Complete depth information and efficient estimators have become vital ingredients in scene understanding for automated driving tasks. A major problem for LiDAR-based depth completion is the inefficient utilization of convolutions due to the lack of coherent information as provided by the sparse nature of uncorrelated LiDAR point clouds, which often leads to

Jakob Poncelet, Hugo Van hamme

TV subtitles are a rich source of transcriptions of many types of speech, ranging from read speech in news reports to conversational and spontaneous speech in talk shows and soaps. However, subtitles are not verbatim (i.e. exact) transcriptions of speech, so they cannot be used directly to improve an Automatic Speech Recognition (ASR) model. We propose a mul

Chao Zhang, Liang Zheng, Shusu Shi, Zi-Wei Lin

It has been a challenge to understand the experimental data on both the nuclear modification factor and elliptic flow of $D^0$ mesons in $p-$Pb collisions at LHC energies. In this work, we study these collisions with an improved multi-phase transport model. By including the Cronin effect (i.e., transverse momentum broadening) and independent fragmentation fo

Erik Butz

The era of High-Luminosity Large Hadron Collider will pose unprecedented challenges for detector design and operation. The planned luminosity of the upgraded machine is 5-7.5 x 10$^{34}$ cm$^{-2}$ s$^{-1}$, reaching an integrated luminosity of 3000-4000 fb$^{-1}$ by the end of 2039. The CMS Tracker detector will have to be replaced in order to fully exploit

Yihong Tang, Junlin He, Zhan Zhao

Human mobility prediction is a fundamental task essential for various applications in urban planning, location-based services and intelligent transportation systems. Existing methods often ignore activity information crucial for reasoning human preferences and routines, or adopt a simplified representation of the dependencies between time, activities and loc

Kyle Min

This report describes our approach for the Audio-Visual Diarization (AVD) task of the Ego4D Challenge 2022. Specifically, we present multiple technical improvements over the official baselines. First, we improve the detection performance of the camera wearer's voice activity by modifying the training scheme of its model. Second, we discover that an off-the-s

Tuan-Phong Nguyen, Simon Razniewski, Aparna Varde, Gerhard Weikum

Structured knowledge is important for many AI applications. Commonsense knowledge, which is crucial for robust human-centric AI, is covered by a small number of structured knowledge projects. However, they lack knowledge about human traits and behaviors conditioned on socio-cultural contexts, which is crucial for situative AI. This paper presents CANDLE, an

Sunwoo Kim, Youngjo Min, Younghun Jung, Seungryong Kim

We propose a controllable style transfer framework based on Implicit Neural Representation that pixel-wisely controls the stylized output via test-time training. Unlike traditional image optimization methods that often suffer from unstable convergence and learning-based methods that require intensive training and have limited generalization ability, we prese

Sepideh Amiri, Bulat Ibragimov

Numerous oncology indications have extensively quantified metabolically active tumors using positron emission tomography (PET) and computed tomography (CT). F-fluorodeoxyglucose-positron emission tomography (FDG-PET) is frequently utilized in clinical practice and clinical drug research to detect and measure metabolically active malignancies. The assessment

Wesley Joon-Wie Tann, Akhil Vuputuri, Ee-Chien Chang

Non-fungible tokens (NFTs) are digital assets stored on a blockchain representing real-world objects such as art or collectibles. An NFT collection comprises numerous tokens; each token can be transacted multiple times. It is a multibillion-dollar market where the number of collections has more than doubled in 2022. In this paper, we want to obtain a generat

Donggeun Yoon, Jinsun Park, Donghyeon Cho

Recently, alpha matting has received a lot of attention because of its usefulness in mobile applications such as selfies. Therefore, there has been a demand for a lightweight alpha matting model due to the limited computational resources of commercial portable devices. To this end, we suggest a distillation-based channel pruning method for the alpha matting

Rebekka Garreis, Jonas Daniel Gerber, Veronika Stará, Chuyao Tong

We measure telegraph noise of current fluctuations in an electrostatically defined quantum dot in bilayer graphene by real-time detection of single electron tunneling with a capacitively coupled neighboring quantum dot. Suppression of the second and third cumulant (related to shot noise) in a tunable graphene quantum dot is demonstrated experimentally. With

Subaveerapandiyan, Supriya Pradhan

The purpose of this study is to analyze the research article publishing with special reference to preparing to publish and peer reviewing. Peer reviewing is the process required for standardizing any publications. Manuscript writing is an art. Though it appears to be simple there is a lot of effort required. Peer reviewing is the process that eliminates arti

P. G. de Oliveira, A. S. T. Pires

We studied a two-band magnon insulating model whose geometry is that of a modified Lieb lattice in which one of the sites was removed. Anisotropic ferromagnetic exchange interactions exist between the three nearest neighbors, and the anisotropy opens a gap in the magnon energy band structure. A non-vanishing Berry curvature is induced by a Dzyaloshinskii-Mor

Lorenzo Nespoli, Nina Wiedemann, Esra Suel, Yanan Xin

Deploying real-time control on large-scale fleets of electric vehicles (EVs) is becoming pivotal as the share of EVs over internal combustion engine vehicles increases. In this paper, we present a Vehicle-to-Grid (V2G) algorithm to simultaneously schedule thousands of EVs charging and discharging operations, that can be used to provide ancillary services. To

Flavien Prost, Ben Packer, Jilin Chen, Li Wei

There has been a flurry of research in recent years on notions of fairness in ranking and recommender systems, particularly on how to evaluate if a recommender allocates exposure equally across groups of relevant items (also known as provider fairness). While this research has laid an important foundation, it gave rise to different approaches depending on wh

Nicolas Resch, Chen Yuan, Yihan Zhang

In this work we consider the list-decodability and list-recoverability of arbitrary $q$-ary codes, for all integer values of $q\geq 2$. A code is called $(p,L)_q$-list-decodable if every radius $pn$ Hamming ball contains less than $L$ codewords; $(p,\ell,L)_q$-list-recoverability is a generalization where we place radius $pn$ Hamming balls on every point of

Hoang Kim Nguyen

We prove properness of (co)Cartesian fibrations as well as a straightening and unstraightening equivalence, which is compatible with cartesian products, when the base is the nerve of a small category.

Igor Rakhno, Nikolai Mokhov, Igor Tropin, Sergei Striganov

The Deep Underground Neutrino Experiment and Long-Baseline Neutrino Facility (DUNE-LBNF) are under development at Fermilab since early 2010s [1]. At present, the work is being performed towards a comprehensive review conducted by US Department of Energy (DOE)-the Critical Decision 2 (CD-2)-that is planned to take place in the middle of 2022. The primary scie

Hanlin Wu, Ning Ni, Shan Wang, Libao Zhang

Remote sensing images (RSIs) in real scenes may be disturbed by multiple factors such as optical blur, undersampling, and additional noise, resulting in complex and diverse degradation models. At present, the mainstream SR algorithms only consider a single and fixed degradation (such as bicubic interpolation) and cannot flexibly handle complex degradations i

Thomas Strypsteen, Alexander Bertrand

In this paper, we describe a conceptual design methodology to design distributed neural network architectures that can perform efficient inference within sensor networks with communication bandwidth constraints. The different sensor channels are distributed across multiple sensor devices, which have to exchange data over bandwidth-limited communication chann

Yan Jia, Mi Hong, Jingyu Hou, Kailong Ren

This paper describes LeVoice automatic speech recognition systems to track2 of intelligent cockpit speech recognition challenge 2022. Track2 is a speech recognition task without limits on the scope of model size. Our main points include deep learning based speech enhancement, text-to-speech based speech generation, training data augmentation via various tech

Kilian Fraboulet, Jean-Paul Ebran

The present paper is the second of a series of publications that aim at investigating relevant directions to turn the nuclear energy density functional (EDF) method as an effective field theory (EFT). The EDF approach has known numerous successes in nuclear theory over the past decades and is currently the only microscopic technique that can be applied to al

S. Krishnendu, B. N. Bharath, Vimal Bhatia

An efficient caching can be achieved by predicting the popularity of the files accurately. It is well known that the popularity of a file can be nudged by using recommendation, and hence it can be estimated accurately leading to an efficient caching strategy. Motivated by this, in this paper, we consider the problem of joint caching and recommendation in a 5

Patrick Massot, Floris van Doorn, Oliver Nash

In differential topology and geometry, the h-principle is a property enjoyed by certain construction problems. Roughly speaking, it states that the only obstructions to the existence of a solution come from algebraic topology. We describe a formalisation in Lean of the local h-principle for first-order, open, ample partial differential relations. This is a s

Abdel Aziz Taha, Leonhard Hennig, Petr Knoth

One of the most common problems preventing the application of prediction models in the real world is lack of generalization: The accuracy of models, measured in the benchmark does repeat itself on future data, e.g. in the settings of real business. There is relatively little methods exist that estimate the confidence of prediction models. In this paper, we p

Manit Paul, Rishideep Roy, Soudeep Deb

In this article, we study the effect of vector-valued interventions in votes under a binary voter model, where each voter expresses their vote as a $0-1$ valued random variable to choose between two candidates. We assume that the outcome is determined by the majority function, which is true for a democratic system. The term intervention includes cases of cou

Manuel Hauke

Given a badly approximable number $\alpha$, we study the asymptotic behaviour of the Sudler product defined by $P_N(\alpha) = \prod_{r=1}^N 2 | \sin \pi r \alpha |$. We show that $\liminf_{N \to \infty} P_N(\alpha) = 0$ and $\limsup_{N \to \infty} P_N(\alpha)/N = \infty$ whenever the sequence of partial quotients in the continued fraction expansion of $\alph

Johannes Schleischitz

For $m\ge 2$, consider $K$ the $m$-fold Cartesian product of the limit set of an IFS of two affine maps with rational coefficients. If the contraction rates of the IFS are reciprocals of integers, and $K$ does not degenerate to singleton, we construct vectors in $K$ that lie within the ``folklore set'' as defined by Beresnevich et al., meaning they are Diric

Subaveerapandiyan A, Ammaji Rajitha, Mohd Amin Dar, Natarajan R

E-resources are inevitable, technology has grown and libraries are also adopting the technologies although adopting have many challenges to the library professionals. Whenever something new comes they need to update themselves. A study investigated E-Resources management and management issues of Indian library professional perspectives. For this study, data

Nobuaki Aoki, Yasumasa Namba

This paper presents the 3rd place solution to the Google Universal Image Embedding Competition on Kaggle. We use ViT-H/14 from OpenCLIP for the backbone of ArcFace, and trained in 2 stage. 1st stage is done with freezed backbone, and 2nd stage is whole model training. We achieve 0.692 mean Precision @5 on private leaderboard. Code available at https://github

Tatsuto Hatanaka, Takuya Nomoto, Ryotaro Arita

Transition metal dichalcogenides (TMDs) are known to have a wide variety of magnetic structures by hosting other transition metal atoms in the van der Waals gaps. To understand the chemical trend of the magnetic properties of the intercalated TMDs, we perform a systematic first-principles study for 48 compounds with different hosts, guests, and composition r

Basabendu Barman, P. S. Bhupal Dev, Anish Ghoshal

We explore the possibility of probing freeze-in dark matter (DM) produced via the right-handed neutrino (RHN) portal using the RHN search experiments. We focus on a simplified framework of minimally-extended type-I seesaw model consisting of only four free parameters, namely the RHN mass, the fermionic DM mass, the Yukawa coupling between the DM and the RHN,

A. Subaveerapandiyan, Dharmavarapu Sindhu

In any kind of educational institute and organization, libraries are playing a crucial role. For the development of library services, skillful library professionals are indispensable. Without knowledge management skills, no one can provide essential services to the users. Library is a growing organism by S.R. Ranganathan 1931, based on his law, as library pr

Danel Ahman

We explore type systems and programming abstractions for the safe use of resources. In particular, we investigate how to use types to modularly specify and check when programs are allowed to use their resources, e.g., when programming a robot arm on a production line, it is crucial that painted parts are given enough time to dry before assembly. We capture s

Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh

Driven by significant improvements in architectural design and training pipelines, computer vision has recently experienced dramatic progress in terms of accuracy on classic benchmarks such as ImageNet. These highly-accurate models are challenging to deploy, as they appear harder to compress using standard techniques such as pruning. We address this issue by

Fabian Brand, Jürgen Seiler, André Kaup

The rise of variational autoencoders for image and video compression has opened the door to many elaborate coding techniques. One example here is the possibility of conditional interframe coding. Here, instead of transmitting the residual between the original frame and the predicted frame (often obtained by motion compensation), the current frame is transmit

Angana Mondal, Benedikt Waser, Tadas Balciunas, Ofer Neufeld

High-harmonic generation (HHG) in liquids is opening new opportunities for attosecond light sources and attosecond time-resolved studies of dynamics in the liquid phase. In gas-phase HHG, few-cycle pulses are routinely used to create isolated attosecond pulses and to extend the cut-off energy. Here, we study the properties of HHG in liquids, including water

Prudhvi N. Bhattiprolu, Stephen P. Martin, James D. Wells

We study the statistical significances for exclusion and discovery of proton decay at current and future neutrino detectors. Various counterintuitive flaws associated with frequentist and modified frequentist statistical measures of significance for multi-channel counting experiments are discussed in a general context and illustrated with examples. We argue

V. V. Ryazanov

An analogy is drawn between version of non-equilibrium thermodynamics a distribution-based containing an additional thermodynamic first-passage time parameter, nonequilibrium statistical operator method and extended irreversible thermodynamics with flows as an additional thermodynamic parameter. Thermodynamics containing an additional thermodynamic first-pas

Wenbin An, Feng Tian, Ping Chen, Siliang Tang

Novel category discovery aims at adapting models trained on known categories to novel categories. Previous works only focus on the scenario where known and novel categories are of the same granularity. In this paper, we investigate a new practical scenario called Fine-grained Category Discovery under Coarse-grained supervision (FCDC). FCDC aims at discoverin