May 2022 arXiv papers — page 81

Chia-Wei Liu, Chao-Qiang Geng

Despite the great success on the mass spectra, the reputation of the bag model has been closely followed by the embarrassment from the center of mass motion. It leads to severe theoretical inconsistencies. For instance, the masses and the decay constants would no longer be independent of the momentum. In this work, we provide a systematical approach to resol

Minglei Yuan, Qian Xu, Chunhao Cai, Yin-Dong Zheng

The transductive inference is an effective technique in the few-shot learning task, where query sets update prototypes to improve themselves. However, these methods optimize the model by considering only the classification scores of the query instances as confidence while ignoring the uncertainty of these classification scores. In this paper, we propose a no

Dimitrios Bachtis

We combine histogram reweighting techniques with the two-lattice matching Monte Carlo renormalization group method to conduct computationally efficient calculations of critical exponents on systems with moderately small lattice sizes. The approach, which relies on the construction of renormalization group mappings between two systems of identical lattice siz

Aiyi Li, Masaki Ogura, Naoki Wakamiya

Swarm guidance addresses a challenging problem considering the navigation and control of a group of passive agents. To solve this problem, shepherding offers a bio-inspired technique of navigating such group of agents by using external steering agents with appropriately designed movement law. Although most shepherding researches are mainly based on the avail

Kerstin Beer

This PhD thesis combines two of the most exciting research areas of the last decades: quantum computing and machine learning. We introduce dissipative quantum neural networks (DQNNs), which are designed for fully quantum learning tasks, are capable of universal quantum computation and have low memory requirements while training. These networks are optimised

Michael Voit

Bessel processes associated with the root systems $A_{N-1}$ and $B_N$ describe interacting particle systems with $N$ particles on $\mathbb R$; they form dynamic versions of the classical $\beta$-Hermite and Laguerre ensembles. In this paper we study corresponding Cauchy processes constructed via some subordination. This leads to $\beta$-Cauchy ensembles in b

Huan Meng

In this paper, a novel dual-mode robust model predictive control (MPC) approach is proposed for solving the tracking control problem of non-holonomoic mobile robots with additive bounded disturbance. To reduce the negative effect of disturbance and drive the state of real system closer to the one of nominal system , a robust reference signal is introduced in

Marvin van Bekkum, Frederik Zuiderveen Borgesius

Organisations can use artificial intelligence to make decisions about people for a variety of reasons, for instance, to select the best candidates from many job applications. However, AI systems can have discriminatory effects when used for decision-making. To illustrate, an AI system could reject applications of people with a certain ethnicity, while the or

Yuanyuan Yang, Delin Feng, Sören Schwertfeger

This paper presents a very compact 16-node cluster that is the core of a future robot for collecting and storing massive amounts of sensor data for research on Simultaneous Localization and Mapping (SLAM). To the best of our knowledge, this is the first time that such a cluster is used in robotics. We first present the requirements and different options for

Tianshu Hou, Peining Zhen, Ngai Wong, Quan Chen

Electromigration (EM) is one of the major concerns in the reliability analysis of very large scale integration (VLSI) systems due to the continuous technology scaling. Accurately predicting the time-to-failure of integrated circuits (IC) becomes increasingly important for modern IC design. However, traditional methods are often not sufficiently accurate, lea

Yiming Tu

High-precision lidar odomety is an essential part of autonomous driving. In recent years, deep learning methods have been widely used in lidar odomety tasks, but most of the current methods only extract the global features of the point clouds. It is impossible to obtain more detailed point-level features in this way. In addition, only the fully connected lay

Thomas Borger, Pablo Mosteiro, Heysem Kaya, Emil Rijcken

Inpatient violence is a common and severe problem within psychiatry. Knowing who might become violent can influence staffing levels and mitigate severity. Predictive machine learning models can assess each patient's likelihood of becoming violent based on clinical notes. Yet, while machine learning models benefit from having more data, data availability is l

Ke Lai, Zilong Liu, Jing Lei, Lei Wen

This work presents a novel K-Repetition based HARQ scheme for LDPC coded uplink SCMA by employing a network coding (NC) principle to encode different packets, where K-Repetition is an emerging technique (recommended in 3GPP Release 15) for enhanced reliability and reduced latency in future massive machine-type communication. Such a scheme is referred to as t

Yusuke Hirota, Yuta Nakashima, Noa Garcia

Vision-and-language tasks have increasingly drawn more attention as a means to evaluate human-like reasoning in machine learning models. A popular task in the field is visual question answering (VQA), which aims to answer questions about images. However, VQA models have been shown to exploit language bias by learning the statistical correlations between ques

Zhang Yue, Zheng Xiangtao, Lu Xiaoqiang

Remote sensing scene classification aims to assign a specific semantic label to a remote sensing image. Recently, convolutional neural networks have greatly improved the performance of remote sensing scene classification. However, some confused images may be easily recognized as the incorrect category, which generally degrade the performance. The differences

Anna Stramaglia, Jeroen J. A. Keiren

Low-code development platforms are gaining popularity. Essentially, such platforms allow to shift from coding to graphical modeling, helping to improve quality and reduce development time. The Cordis SUITE is a low-code development platform that adopts the Unified Modeling Language (UML) to design complex machine-control applications. In this paper we introd

Lara Beßmann

A universal group is a subgroup of the group of type preserving automorphisms of a right-angled building and hence associated to this building. A question is then if this universal group can act chamber-transitively and with compact open stabilisers on a different right-angled building of the same type. We answer this question and define two universal groups

Mario Beraha, Bruno Guindani, Matteo Gianella, Alessandra Guglielmi

We describe BayesMix, a C++ library for MCMC posterior simulation for general Bayesian mixture models. The goal of BayesMix is to provide a self-contained ecosystem to perform inference for mixture models to computer scientists, statisticians and practitioners. The key idea of this library is extensibility, as we wish the users to easily adapt our software t

Yu Wang, Binbin Zhu, Lingsi Kong, Jianlin Wang

Ultrasound-guided nerve block anesthesia (UGNB) is a high-tech visual nerve block anesthesia method that can observe the target nerve and its surrounding structures, the puncture needle's advancement, and local anesthetics spread in real-time. The key in UGNB is nerve identification. With the help of deep learning methods, the automatic identification or seg

Hai-Han Sun, Yee Hui Lee, Wenhao Luo, Lai Fern Ow

Detecting a shallowly buried and elongated object and estimating its orientation using a commonly adopted co-polarized GPR system is challenging due to the presence of strong ground clutter that masks the target reflection. A cross-polarized configuration can be used to suppress ground clutter and reveal the object reflection, but it suffers from inconsisten

Florian Domingo, Herbi K. Dreiner

We study the phenomenology associated with a light bino-like neutralino with mass under the tau mass in the context of the R-parity violating Minimal Supersymmetric Standard Model. This is a well-motivated example of scenarios producing potentially light and long-lived exotic particles, which might be testable in far-detector experiments, such as the FASER e

Candy Sonveaux, Joseph J. Winkin

An age-dependent SIR model is considered with the aim to develop a state-feedback vaccination law in order to eradicate a disease. A dynamical analysis of the system is performed using the principle of linearized stability and shows that, if the basic reproduction number is larger than 1, the disease free equilibrium is unstable. This result justifies the de

Peng Pan, Jaafar Najafi Rad, Philippe Roncin

We describe a UHV setup for grazing incidence fast atom diffraction (GIFAD) experiments. The overall geometry is simply a source of keV atoms facing an imaging detector. Therefore, It is very similar to the geometry of RHEED experiments, reflection high energy electron diffraction used to monitor growth at surfaces. Several custom instrumental developments a

Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi, Noboru Harada

Many application studies rely on audio DNN models pre-trained on a large-scale dataset as essential feature extractors, and they extract features from the last layers. In this study, we focus on our finding that the middle layer features of existing supervised pre-trained models are more effective than the late layer features for some tasks. We propose a sim

Xiaoliang Li, Cong Wang

We treat the exterior Dirichlet problem for a class of fully nonlinear elliptic equations of the form $$f(\lambda(D^2u))=g(x),$$ with prescribed asymptotic behavior at infinity. The equations of this type had been studied extensively by Caffarelli--Nirenberg--Spruck \cite{Caffarelli1985}, Trudinger \cite{Trudinger1995} and many others, and there had been sig

Qianqian Yu, Siqi Liu, Chunqi Yuan, Dong Sheng

Detection dead zones and heading errors induced by light shifts are two important problems in optically pumped scalar magnetometry. We introduce an atomic orientation based single-beam magnetometry scheme to simultaneously solve these problems, using a polarization-reversing and path-bending Herriott cavity. Here, a reflection mirror is inserted into the cav

Hai-Han Sun, Weixia Cheng, Zheng Fan

The clutter in the ground-penetrating radar (GPR) radargram disguises or distorts subsurface target responses, which severely affects the accuracy of target detection and identification. Existing clutter removal methods either leave residual clutter or deform target responses when facing complex and irregular clutter in the real-world radargram. To tackle th

Sibel Baskal, Sinan Celik

The introduction of extra dimensions is an invaluable strategy for the unification of gravity with other physical fields. Nevertheless, the matter in hand is to be eventually reduced to the actual 4D spacetime. The Kaluza-Klein theory is no exception to this well-known scheme. There are two procedures to obtain the field equations from a higher dimensional a

Hossein Teimoori Faal

The ordinary generating function of the number of complete subgraphs (cliques) of $G$, denoted by $C(G,x)$, is called the The clique polynomial of the graph $G$. In this paper, we first introduce some \emph{clique} incidence matrices associated by a simple graph $G$ as a generalization of the classical vertex-edge incidence matrix of $G$. Then, using these c

Joachim Schaeffer, Richard Braatz

The ever-increasing quantity of multivariate process data is driving a need for skilled engineers to analyze, interpret, and build models from such data. Multivariate data analytics relies heavily on linear algebra, optimization, and statistics and can be challenging for students to understand given that most curricula do not have strong coverage in the latt

S. Zarrin, S. Dadfar

We present the effects of nonlinear corrections to the single differential cross section d\sigma/dQ^2 and the reduced cross section \sigma_r (x,Q^2) for the neutral current (NC) e-p scattering at the leading order (LO) and the next-to-leading order (NLO) approximations in perturbative quantum chromo dynamics (QCD). Technically, based on the double Laplace tr

S. Rosswog, P. Diener, F. Torsello

To date, essentially all simulation codes that solve the full set of Einstein's equations are performed in the framework of Eulerian hydrodynamics. The exception is our recently developed Numerical Relativity code SPHINCS_BSSN which solves the commonly used BSSN formulation of the Einstein equations on a structured mesh and the matter equations via Lagrangia

Kuan Fang, Patrick Yin, Ashvin Nair, Sergey Levine

General-purpose robots require diverse repertoires of behaviors to complete challenging tasks in real-world unstructured environments. To address this issue, goal-conditioned reinforcement learning aims to acquire policies that can reach configurable goals for a wide range of tasks on command. However, such goal-conditioned policies are notoriously difficult

Marco Milanese, Francesco Ranzato

Local Completeness Logic (LCL) has been put forward as a program logic for proving both the correctness and incorrectness of program specifications. LCL is an abstract logic, parameterized by an abstract domain that allows combining over- and under-approximations of program behaviors. It turns out that LCL instantiated to the trivial singleton abstraction bo

Simona Perotto, Gloria Bellini, Francesco Ballarin, Karol Calò

Microfluidics proved to be a key technology in various applications, allowing to reproduce large-scale laboratory settings at a more sustainable small-scale. The current effort is focused on enhancing the mixing process of different passive species at the micro-scale, where a laminar flow regime damps turbulence effects. Chaotic advection is often used to im

Petr Gregor, Arturo Merino, Torsten Mütze

We say that a Hamilton cycle $C=(x_1,\ldots,x_n)$ in a graph $G$ is $k$-symmetric, if the mapping $x_i\mapsto x_{i+n/k}$ for all $i=1,\ldots,n$, where indices are considered modulo $n$, is an automorphism of $G$. In other words, if we lay out the vertices $x_1,\ldots,x_n$ equidistantly on a circle and draw the edges of $G$ as straight lines, then the drawing

Ignatios Antoniadis, Spiros Cotsakis, John Miritzis

We study the problem of evolution of bulk 5-fluids having an embedded braneworld with a flat, de Sitter, or anti-de Sitter geometry. We introduce new variables to express the Einstein equations as a dynamical system that depends on the equation of state parameter $\gamma$ and exponent $\lambda$. For linear fluids (i.e., $\lambda=1$), our formulation leads to

Orion Weller, Kevin Seppi, Matt Gardner

Transfer learning (TL) in natural language processing (NLP) has seen a surge of interest in recent years, as pre-trained models have shown an impressive ability to transfer to novel tasks. Three main strategies have emerged for making use of multiple supervised datasets during fine-tuning: training on an intermediate task before training on the target task (

Tommi Keski-Filppula, Marko Nikki, Marianne Haapea, Naglis Ramanauskas

Objectives: To assess the use of artificial intelligence-based software in ruling out chest X-ray cases, with no significant findings in a primary health care setting. Methods: In this retrospective study, a commercially available artificial intelligence (AI) software was used to analyse 10 000 chest X-rays of Finnish primary health care patients. In studies

V. Tiwari, M. Morita T. Inoue, S. Ando S. Kuroda, H. Boukari

We study the dynamics of the spin system that consist of a positively charged II-VI semiconductor quantum dot doped with a single Cr$^+$ ion. The resonant photoluminescence (PL) of the positively charged exciton coupled with the Cr$^+$ spin is used to analyze the main spin relaxation channels. The intensity of the resonant PL is reduced by an optical pumping

Jia Zhan, Francis C. M. Lau

In this paper, we propose using a generic protograph to design joint source-channel codes (JSCCs). We present a generalized algorithm, called protograph extrinsic information transfer for JSCC algorithm (PEXIT-JSCC algorithm), for analyzing the channel threshold of the proposed JSCC. We also propose a source generic protograph EXIT (SGP-EXIT) algorithm, whic

M. Rezaei, K. Javidan, M. Abdi

The main challenge in deterministic quantum state transfer between remote mechanical resonators is the local decoherence and the transmission losses in the communication channel. In the path of overcoming this limitation, here we employ a shortcut to adiabatic passage protocol to devise a fast and reliable evolution path between two remote mechanical modes i

Haoran You, Baopu Li, Huihong Shi, Yonggan Fu

Neural networks (NNs) with intensive multiplications (e.g., convolutions and transformers) are capable yet power hungry, impeding their more extensive deployment into resource-constrained devices. As such, multiplication-free networks, which follow a common practice in energy-efficient hardware implementation to parameterize NNs with more efficient operators

Xinze Qiu, Tianli Gao, Yu Yang, Ankang Luo

Bike-sharing systems have been regarded as a critical component of solutions towards the transition to greener and more sustainable transportation, with the benefits of reducing carbon emissions, improving public health, and mitigating congestion by replacing short-distance motorized trips. Due to better accessibility and usage flexibility, newly emergent do

Michel Brion, Stefan Schröer

We show that each connected group scheme of finite type over an arbitrary ground field is isomorphic to the component of the identity inside the automorphism group scheme of some projective, geometrically integral scheme. The main ingredients are embeddings into smooth group schemes, equivariant completions, blow-ups of orbit closures, Fitting ideals for K\"

Ayano Ikegami, Raula Gaikovina Kula, Bodin Chinthanet, Vittunyuta Maeprasart

Third-party library dependencies are commonplace in today's software development. With the growing threat of security vulnerabilities, applying security fixes in a timely manner is important to protect software systems. As such, the community developed a list of software and hardware weakness known as Common Weakness Enumeration (CWE) to assess vulnerabiliti

Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu

In this paper, we study the design and analysis of a class of efficient algorithms for computing the Gromov-Wasserstein (GW) distance tailored to large-scale graph learning tasks. Armed with the Luo-Tseng error bound condition~\citep{luo1992error}, two proposed algorithms, called Bregman Alternating Projected Gradient (BAPG) and hybrid Bregman Proximal Gradi

Wei-Ming Huang, Wei-Min Zhang

By solving the exact master equation of open quantum systems, we formulate the quantum thermodynamics from weak to strong couplings. The open quantum systems exchange matters, energies and information with their reservoirs through quantum particles tunnelings that are described by the generalized Fano-Anderson Hamiltonians. We find that the exact solution of

Mehdi Shaffei Aporvari, Agnese Callegari, Emine Ulku Saritas

In many physical and biological systems, particles and microorganisms move in the proximity of an interface. Understanding the dynamics of a particle suspended close to an interface is not only important conceptually but is crucial for practical applications ranging from the treatment of waste waters to industrial applications of self-assemblies. In this wor

Laurence Barry, Arthur Charpentier

Since the beginning of their history, insurers have been known to use data to classify and price risks. As such, they were confronted early on with the problem of fairness and discrimination associated with data. This issue is becoming increasingly important with access to more granular and behavioural data, and is evolving to reflect current technologies an

Daisuke Shimamoto, Miho Yanagisawa

We introduce a model for particles that are extremely polydisperse in size compared to monodisperse and bidisperse systems. In two dimensions (2D), size polydispersity inhibits crystallization and increases packing fraction at jamming points. However, no packing pattern common to diverse polydisperse particles has been reported. We focused on polydisperse pa

Jack N. Engdahl, Aydin Cem Keser, Oleg P. Sushkov

The hydrodynamic behavior of electron fluids in a certain range of temperatures and densities is well established in graphene and in 2D semiconductor heterostructures. The hydrodynamic regime is intrinsically based on electron-electron interactions, and therefore it provides a unique opportunity to study electron correlations. Unfortunately, in all existing

Soham Vyas, Yuvraj Goyal, Neel Bhatt, Sanskar Bhuwania

Solar energy forecasting has seen tremendous growth in the last decade using historical time series collected from a weather station, such as weather variables wind speed and direction, solar radiance, and temperature. It helps in the overall management of solar power plants. However, the solar power plant regularly requires preventive and corrective mainten

Zhicheng Yang, Jinghui Qin, Jiaqi Chen, Xiaodan Liang

In this paper, we revisit the solving bias when evaluating models on current Math Word Problem (MWP) benchmarks. However, current solvers exist solving bias which consists of data bias and learning bias due to biased dataset and improper training strategy. Our experiments verify MWP solvers are easy to be biased by the biased training datasets which do not c

Dimitrios Betsakos, Alexander Solynin, Matti Vuorinen

In this paper we discuss problems concerning the conformal condenser capacity of "hedgehogs", which are compact sets $E$ in the unit disk $\mathbb{D}=\{z:\,|z|<1\}$ consisting of a central body $E_0$ that is typically a smaller disk $\overline{\mathbb{D}}_r=\{z:\,|z|\le r\}$, $0<r<1$, and several spikes $E_k$ that are compact sets lying on radial intervals $

Syo Kamata, Jakub Jankowski, Mauricio Martinez

In this work we investigate the impact of conformal symmetry breaking on hydrodynamization of a far-from-equilibrium fluid. We find a new kind of transseries solutions for the non-conformal hydrodynamic equations of a longitudinal boost invariant expanding plasma. The new transseries solutions unveil a rich physical structure which arises due to the interpla

Chia-Hung Yang, Yun-Chien Cheng, Chin Kuo

The purpose of this research is to develop a system that generates simulated computed tomography pulmonary angiography (CTPA) images clinically for pulmonary embolism diagnoses. Nowadays, CTPA images are the gold standard computerized detection method to determine and identify the symptoms of pulmonary embolism (PE), although performing CTPA is harmful for p

Peter Kunkel, Volker Mehrmann

Discretization methods for differential-algebraic equations (DAEs) are considered that are based on the integration of an associated inherent ordinary differential equation (ODE). This allows to make use of any discretization scheme suitable for the numerical integration of ODEs. For DAEs with symmetries it is shown that the inherent ODE can be constructed i

Fupeng Sun, Yanwei Sun, Chiwei Yan, Li Jin

We study an all-pay contest in which players with low abilities are filtered out before competing for prizes. We consider a setting where the designer admits a certain number of top players. The admitted players update their beliefs based on the signal that their abilities are among the top, which leads to posterior beliefs that, even under i.i.d. priors, ar

Leslie Ching Ow Tiong, Gunjick Lee, Seok Su Sohn, Donghun Kim

Accurate predictions of the failure progression of structural materials is critical for preventing failure-induced accidents. Despite considerable mechanics modeling-based efforts, accurate prediction remains a challenging task in real-world environments due to unexpected damage factors and defect evolutions. Here, we report a novel method for predicting mat

Zhiyi Huang, Hanwen Zhang

The deterministic $k$-server conjecture states that there is a $k$-competitive deterministic algorithm for the $k$-server problem for any metric space. We show that the work function algorithm is $3$-competitive for the $3$-server problem on circle metrics, a case left open by Coester and Koutsoupias (2021). Our analysis follows the existing framework but in

Saugata Chatterjee

Galileons are stable null energy condition (NEC) violating perturbations. If these NEC violating modes are coupled to Einstein gravity, they can cause violation of the second law of black hole thermodynamics. We demonstrate that galileons can only be coupled to quadratic gravity since they are generated by consistent Kaluza-Klein reduction of the Einstein-Hi

Shuo Kong

Recently, a collision-induced magnetic reconnection (CMR) mechanism was proposed to explain a dense filament formation in the Orion A giant molecular cloud. A natural question is that whether CMR works elsewhere in the Galaxy. As an initial attempt to answer the question, this paper investigates the triggering of CMR and the production of dense gas in a flat

Adrian Clingher, Thomas Hill, Andreas Malmendier

We construct non-geometric string compactifications by using the F-theory dual of the heterotic string compactified on a two-torus with two Wilson line parameters, together with a close connection between modular forms and the equations for certain K3 surfaces of Picard rank $16$. We construct explicit Weierstrass models for all inequivalent Jacobian ellipti

Paul Wimmer, Jens Mehnert, Alexandru Paul Condurache

State-of-the-art deep learning models have a parameter count that reaches into the billions. Training, storing and transferring such models is energy and time consuming, thus costly. A big part of these costs is caused by training the network. Model compression lowers storage and transfer costs, and can further make training more efficient by decreasing the

Yi Chen, Jing Dong, Xin T. Tong

Many organizations have access to abundant data but lack the computational power to process the data. While they can outsource the computational task to other facilities, there are various constraints on the amount of data that can be shared. It is natural to ask what can data outsourcing accomplish under such constraints. We address this question from a mac

Linh Truong

In this note, we give a short proof that knot Floer thickness is a lower bound on the dealternating number of a knot. The result is originally due to work of Abe and Kishimoto, Lowrance, and Turaev. Our proof is a modification of the Stipsicz-Szabo approach using Kauffman states to show that thickness bounds the minimal number of bad domains in a knot diagra

Gonzalo Maximiliano Lopez, Juan Pablo Aparicio

In this work we present a general framework for the modeling of the transmission dynamics of macroparasites which do not reproduce within the host like Ascaris lumbricoides, Trichuris trichiura, Necator americanus y Ancylostoma duodenale. The basic models are derived from general probabilistic models for the parasite density-dependent mating probability. Her

Vikram S Chundawat, Ayush K Tarun, Murari Mandal, Mohan Kankanhalli

Machine unlearning has become an important area of research due to an increasing need for machine learning (ML) applications to comply with the emerging data privacy regulations. It facilitates the provision for removal of certain set or class of data from an already trained ML model without requiring retraining from scratch. Recently, several efforts have b

Ying Sheng, Andres Nötzli, Andrew Reynolds, Yoni Zohar

Dynamic arrays, also referred to as vectors, are fundamental data structures used in many programs. Modeling their semantics efficiently is crucial when reasoning about such programs. The theory of arrays is widely supported but is not ideal, because the number of elements is fixed (determined by its index sort) and cannot be adjusted, which is a problem, gi

Thomas Delteil, Edouard Belval, Lei Chen, Luis Goncalves

We present MATrIX - a Modality-Aware Transformer for Information eXtraction in the Visual Document Understanding (VDU) domain. VDU covers information extraction from visually rich documents such as forms, invoices, receipts, tables, graphs, presentations, or advertisements. In these, text semantics and visual information supplement each other to provide a gl

Yi-Jun Chang, Hsin-Hao Su

Many combinatorial optimization problems can be approximated within $(1 \pm \epsilon)$ factors in $\text{poly}(\log n, 1/\epsilon)$ rounds in the LOCAL model via network decompositions [Ghaffari, Kuhn, and Maus, STOC 2018]. These approaches require sending messages of unlimited size, so they do not extend to the CONGEST model, which restricts the message siz

Amitesh Omar

The Odd Radio Circles are newly identified diffuse radio sources at ~1 GHz frequency, with edge-brightened nearly circular morphology, which is remarkably similar to supernova remnants although a physical association with previous population of Galactic supernova remnants is challenging due to detections of the Odd Radio Circles at high Galactic latitudes. H

Somnath Roy, Debapriya Das, Dhruba Banerjee

In this article, we explore the possibility of a sub-harmonic $(1{:}2)$ entrainment and supercritical Hopf bifurcation in a van der Pol-Duffing oscillator that has been excited by two frequencies, comprising a slow parametric drive and a fast external forcing, through the variation of the amplitude of the external fast signal. We also deduce the condition fo

Ziwei Wang, Dingran Yuan, Yonhon Ng, Robert Mahony

Event cameras are bio-inspired sensors that capture per-pixel asynchronous intensity change rather than the synchronous absolute intensity frames captured by a classical camera sensor. Such cameras are ideal for robotics applications since they have high temporal resolution, high dynamic range and low latency. However, due to their high temporal resolution,

Sabir Hossain, Xianke Lin

Perception and localization are essential for autonomous delivery vehicles, mostly estimated from 3D LiDAR sensors due to their precise distance measurement capability. This paper presents a strategy to obtain the real-time pseudo point cloud instead of the laser sensor from the image sensor. We propose an approach to use different depth estimators to obtain

Dan Kondo, Robert McGehee, Tom Melia, Hitoshi Murayama

We present a model of self-interacting dark matter based on QCD-like theories and inspired by the proximity of $a_0(980\pm 20)$ to the $K\bar{K}(990)$ threshold. Dark matter is comprised of dark pions which self-scatter via the $\sigma$ resonance close to the $\pi\pi$ threshold. While the linear sigma model serves as a qualitative guide, a fully unitary desc

Ajoy Das, Gias Uddin, Guenther Ruhe

Blockchain is a distributed ledger technique that guarantees the traceability of transactions. Blockchain is adopted in multiple domains like finance (e.g., cryptocurrency), healthcare, security, and supply chain. In the open-source software (OSS) portal GitHub, we observe a growing adoption of Blockchain-based solutions. Given the rapid emergence of Blockch

Ravo Tokiniaina Ranaivoson, Voriraza Séraphin Hejesoa, Raoelina Andriambololona, Nirina Gilbert Rasolofoson

Wave-particle duality is often considered as the modern answer to the problem of the nature of light after more than 2000 years of questioning. It is also the answer given by quantum physics concerning the nature of matter particles and any other radiations. The main objective of this work is to analyze the relations that are existing between this concept of

Huang Zonghao, Quinn Wu, David Howard, Cynthia Sung

We study the effects of injecting human-generated designs into the initial population of an evolutionary robotics experiment, where subsequent population of robots are optimised via a Genetic Algorithm and MAP-Elites. First, human participants interact via a graphical front-end to explore a directly-parameterised legged robot design space and attempt to prod

Md Sarowar Morshed

In this work, we shed light on the so-called Kaczmarz method for solving Linear System (LS) and Linear Feasibility (LF) problems from a optimization point of view. We introduce well-known optimization approaches such as Lagrangian penalty and Augmented Lagrangian in the Randomized Kaczmarz (RK) method. In doing so, we propose two variants of the RK method na

Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou

Industrial recommender systems have been growing increasingly complex, may involve \emph{diverse domains} such as e-commerce products and user-generated contents, and can comprise \emph{a myriad of tasks} such as retrieval, ranking, explanation generation, and even AI-assisted content production. The mainstream approach so far is to develop individual algori

Hexin Dong, Zifan Chen, Mingze Yuan, Yutong Xie

As one of the most challenging and practical segmentation tasks, open-world semantic segmentation requires the model to segment the anomaly regions in the images and incrementally learn to segment out-of-distribution (OOD) objects, especially under a few-shot condition. The current state-of-the-art (SOTA) method, Deep Metric Learning Network (DMLNet), relies

Satoshi Takashima, Hirokazu Odaka, Hiroki Yoneda, Yuto Ichinohe

We have developed a neural network model to perform event reconstruction of Compton telescopes. This model reconstructs events that consist of three or more interactions in a detector. It is essential for Compton telescopes to determine the time order of the gamma-ray interactions and whether the incident photon deposits all energy in a detector or it escape

Chan-Ho Kim, Matteo Longo

The aim of this paper is to prove the two-variable anticyclotomic Iwasawa main conjecture for Hida families and a definite version of the horizontal non-vanishing conjecture, which are formulated in Longo-Vigni. Our approach is based on the two-variable anticyclotomic control theorem for Selmer groups for Hida families and the relation between the two-variab

Chan-Ho Kim, Matteo Longo

The aim of this note is to compare several anticyclotomic $p$-adic $L$-functions for modular forms and $p$-adic families of ordinary modular forms, which have been defined and studied from different perspectives by Skinner-Urban, Hida, Perin-Riou, Bertolini-Darmon, Vatsal, Chida-Hsieh, Longo-Vigni, Castella-Longo and Castella-Kim-Longo. The main result of th

Hidemasa Ishii, Nariaki Nishino

The literature on centralized matching markets often assumes that a true preference of each player is known to herself and fixed, but empirical evidence casts doubt on its plausibility. To circumvent the problem, we consider evolutionary dynamics of preference revelation games in marriage problems. We formulate the asymptotic stability of a matching, indicat

Arda Sahiner, Tolga Ergen, Batu Ozturkler, John Pauly

Vision transformers using self-attention or its proposed alternatives have demonstrated promising results in many image related tasks. However, the underpinning inductive bias of attention is not well understood. To address this issue, this paper analyzes attention through the lens of convex duality. For the non-linear dot-product self-attention, and alterna

Minghan Chen, Yiting Li, Timothy D. Brandt, Trent J. Dupuy

We report individual dynamical masses of $66.92 \pm 0.36 \; M_{Jup}$ and $53.25 \pm 0.29 \; M_{Jup}$ for the binary brown dwarfs $\varepsilon$ Indi Ba and Bb, measured from long term ($\approx 10$ yr) relative orbit monitoring and absolute astrometry monitoring data on the VLT. Relative astrometry with NACO fully constrains the Keplerian orbit of the binary

Jaeyoun You, Daemin Park, Joo-yeong Song, Bongwon Suh

Studies on supervised machine learning (ML) recommend involving workers from various backgrounds in training dataset labeling to reduce algorithmic bias. Moreover, sophisticated tasks for categorizing objects in images are necessary to improve ML performance, further complicating micro-tasks. This study aims to develop a task design incorporating the fair pa

Zhixing Huang, Junli Zha, Fei Xie, Yuwei Zheng

Semi-supervised video object segmentation is a fundamental yet Challenging task in computer vision. Embedding matching based CFBI series networks have achieved promising results by foreground-background integration approach. Despite its superior performance, these works exhibit distinct shortcomings, especially the false predictions caused by little appearan

Febin Sunny, Mahdi Nikdast, Sudeep Pasricha

Parameter quantization in convolutional neural networks (CNNs) can help generate efficient models with lower memory footprint and computational complexity. But, homogeneous quantization can result in significant degradation of CNN model accuracy. In contrast, heterogeneous quantization represents a promising approach to realize compact, quantized models with

Sudeep Pasricha

Embedded computing systems are pervasive in our everyday lives, imparting digital intelligence to a variety of electronic platforms used in our vehicles, smart appliances, wearables, mobile devices, and computers. The need to train the next generation of embedded systems designers and engineers with relevant skills across hardware, software, and their co-des

A. Fix, I. Dementjev

The discrete ambiguities appearing in the complete experiment problem for single pseudoscalar meson photoproduction within truncated partial-wave analysis are discussed. It is shown that, in addition to the double ambiguity known from previous works, it is always necessary to take into account another ambiguity arising when truncation in total angular moment

Jahrul Alam

The transfer of turbulence kinetic energy from large to small scales occurs through vortex stretching. Also, statistical properties of the subgrid-scale energy fluxes depend on the alignment of the vorticity vector with the principal strain axis. A heuristic analysis of the present study indicates that vortex-stretching and the second invariant of the veloci

Ninad Hogade, Sudeep Pasricha

Cloud workloads today are typically managed in a distributed environment and processed across geographically distributed data centers. Cloud service providers have been distributing data centers globally to reduce operating costs while also improving quality of service by using intelligent workload and resource management strategies. Such large scale and com

Michal Kepkowski, Lucjan Hanzlik, Ian Wood, Mohamed Ali Kaafar

This paper presents a timing attack on the FIDO2 (Fast IDentity Online) authentication protocol that allows attackers to link user accounts stored in vulnerable authenticators, a serious privacy concern. FIDO2 is a new standard specified by the FIDO industry alliance for secure token online authentication. It complements the W3C WebAuthn specification by pro

Zhihuan Zhou, Gang Liu, Yuhao Mu, Lixin Xu

In this work, we explore the phenomenology of generalized dark matter (GDM) which interacts with photons ($\gamma$). We assume that DM establishes elastic scattering with $\gamma$ when it has already become nonrelativistic, otherwise the abundance of DM today is disfavored by current observations. Within this scenario, the equation of state (EoS) of DM is de

Saideep Tiku, Danish Gufran, Sudeep Pasricha

Smartphones together with RSSI fingerprinting serve as an efficient approach for delivering a low-cost and high-accuracy indoor localization solution. However, a few critical challenges have prevented the wide-spread proliferation of this technology in the public domain. One such critical challenge is device heterogeneity, i.e., the variation in the RSSI sig

Liping Wang, Sudeep Pasricha

Modern indoor localization techniques are essential to overcome the weak GPS coverage in indoor environments. Recently, considerable progress has been made in Channel State Information (CSI) based indoor localization with signal fingerprints. However, CSI signal patterns can be complicated in the large and highly dynamic indoor spaces with complex interiors,