April 2023 arXiv papers — page 153

Weidong Wang, Jing Yang

In this paper, we develop two variants of Bezout subresultant formulas for several polynomials, i.e., hybrid Bezout subresultant polynomial and non-homogeneous Bezout subresultant polynomial. Rather than simply extending the variants of Bezout subresultant formulas developed by Diaz-Toca and Gonzalez-Vega in 2004 for two polynomials to arbitrary number of po

Christian Mugisho Zagabe, Alexandre Mauroy

We present novel sufficient conditions for the global stability of equilibria in the case of nonlinear dynamics with analytic vector fields. These conditions provide stability criteria that are directly expressed in terms of the Taylor expansion coefficients of the vector field (e.g. in terms of first order coefficients, maximal coefficient, sum of coefficie

Teimour Hosseinalizadeh, Nima Monshizadeh

The data transmitted by cyber-physical systems can be intercepted and exploited by malicious individuals to infer privacy-sensitive information regarding the physical system. This motivates us to study the problem of preserving privacy in data releasing of linear dynamical system using stochastic perturbation. In this study, the privacy sensitive quantity is

Anderson D. S. Duraes

Virtually, every ab-initio electronic structure method (Coupled Cluster, DMRG, etc.) can be viewed as an algorithm to compress the ground-state wavefunction. This compression is usually obtained by exploiting some physical structure of the wavefunction, which leads to issues when the system changes and that structure is lost. Compressions which are efficient

Jaydip Sen, Subhasis Dasgupta

Recent developments in hardware and information technology have enabled the emergence of billions of connected, intelligent devices around the world exchanging information with minimal human involvement. This paradigm, known as the Internet of Things (IoT) is progressing quickly with an estimated 27 billion devices by 2025. This growth in the number of IoT d

Hong Hui Yeoh, Andrea Liew, Raphaël Phan, Fredrik Strand

Breast cancer is a significant public health concern and early detection is critical for triaging high risk patients. Sequential screening mammograms can provide important spatiotemporal information about changes in breast tissue over time. In this study, we propose a deep learning architecture called RADIFUSION that utilizes sequential mammograms and incorp

Suman Chakraborty, Sagar Chakraborty

In this paper, the replicator dynamics of the two-locus two-allele system under weak mutation and weak selection is investigated in a generation-wise non-overlapping unstructured population of individuals mating at random. Our main finding is that the dynamics is gradient-like when the point mutations at the two loci are independent. This is in stark contras

Marilena Crupi, Antonino Ficarra, Ernesto Lax

Let $G$ be a finite simple graph and let $I(G)$ be its edge ideal. In this article, we deeply investigate the squarefree powers of $I(G)$ by means of Betti splittings. When $G$ is a forest, it is shown that the normalized depth function of $I(G)$ is non-increasing. Furthermore, we compute explicitly the regularity function of squarefree powers of $I(G)$ with

Shuning Chang, Pichao Wang, Fan Wang, Jiashi Feng

Localizing people and recognizing their actions from videos is a challenging task towards high-level video understanding. Existing methods are mostly two-stage based, with one stage for person bounding box generation and the other stage for action recognition. However, such two-stage methods are generally with low efficiency. We observe that directly unifyin

Sheng Xu, Yanjing Li, Mingbao Lin, Peng Gao

The recent detection transformer (DETR) has advanced object detection, but its application on resource-constrained devices requires massive computation and memory resources. Quantization stands out as a solution by representing the network in low-bit parameters and operations. However, there is a significant performance drop when performing low-bit quantized

Hao Chen, Chen Gong, Yizhe Wang, Xinwen Hou

A backdoor attack allows a malicious user to manipulate the environment or corrupt the training data, thus inserting a backdoor into the trained agent. Such attacks compromise the RL system's reliability, leading to potentially catastrophic results in various key fields. In contrast, relatively limited research has investigated effective defenses against bac

Ghaith Matalkah, Edward J. Coyle

We propose a novel method for monitoring gas distribution networks (GDNs) using intelligent sensor nodes that can be integrated with existing smart gas meters (intelligent meters). The method aims at detecting and locating gas leaks in GDNs in real time. The intelligent meters leverage wireless connectivity in existing smart meters to collaborate in implemen

Neus Penalva, Jonathan M. Flynn, Eliecer Hernández, Juan Nieves

We benefit from the lattice QCD determination by the HPQCD of the Standard Model (SM) form factors for the $\bar B_s\to D_s$ [Phys. Rev. D 101, 074513 (2020)] and the SM and tensor ones for the $\bar B_s\to D_s^{*}$ (arXiv:2304.03137 [hep-lat]) semileptonic decays, and the heavy quark effective theory (HQET) relations for the analogous $B\to D^{(*)}$ decays

Longwen Zhang, Qiwei Qiu, Hongyang Lin, Qixuan Zhang

Emerging Metaverse applications demand accessible, accurate, and easy-to-use tools for 3D digital human creations in order to depict different cultures and societies as if in the physical world. Recent large-scale vision-language advances pave the way to for novices to conveniently customize 3D content. However, the generated CG-friendly assets still cannot

Leila Ismail, Huned Materwala

Stroke is the second leading cause of death worldwide. Machine learning classification algorithms have been widely adopted for stroke prediction. However, these algorithms were evaluated using different datasets and evaluation metrics. Moreover, there is no comprehensive framework for stroke data analytics. This paper proposes an intelligent stroke predictio

Yu Tang, Li Jin, Kaan Ozbay

Routing control is one of important traffic management strategies against urban congestion. However, it could be compromised by heterogeneous driver non-compliance with routing instructions. In this article we model the compliance in a stochastic manner and investigate its impacts on routing control. We consider traffic routing for two parallel links. Partic

Soumyadip Sarkar

Portfolio management is an essential component of investment strategy that aims to maximize returns while minimizing risk. This paper explores several portfolio management strategies, including asset allocation, diversification, active management, and risk management, and their importance in optimizing portfolio performance. These strategies are examined ind

Takahiro Tsumura, Seiji Yamada

One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. In this study, we focused on a task between an agent and a human in which the agent makes a mistake. To investigate significant factors for designing a robotic agent that can promote humans empathy, we experimentally examined the hypothe

Toshiyasu Arai

This is a lecture notes for a mini-course in Department of Mathematics, Ghent University, 14 Mar.-25 Mar. 2023.

Binhang Qi, Hailong Sun, Xiang Gao, Hongyu Zhang

Training deep neural network (DNN) models, which has become an important task in today's software development, is often costly in terms of computational resources and time. With the inspiration of software reuse, building DNN models through reusing existing ones has gained increasing attention recently. Prior approaches to DNN model reuse have two main limit

Xuyu Chen, Xudong Li, Yangfeng Su

This paper studies the convex isotonic regression with generalized order restrictions induced by a directed tree. The proposed model covers various intriguing optimization problems with shape or order restrictions, including the generalized nearly isotonic optimization and the total variation on a tree. Inspired by the success of the pool-adjacent-violator a

Shailesh B. Bhagat, Milind B. Naik, Satheesha S. Poojary, Harshit Shah

The TIFR Near Infrared Imaging Camera-II (TIRCAM2) is being used at the 3.6 m Devasthal Optical Telescope (DOT) operated by Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital, Uttarakhand, India. Earlier, the TIRCAM2 was used at the main port of the DOT on time shared basis. It has now been installed at the side port of the telescope.

Jiahao Nie, Zhiwei He, Yuxiang Yang, Xudong Lv

Siamese trackers based on 3D region proposal network (RPN) have shown remarkable success with deep Hough voting. However, using a single seed point feature as the cue for voting fails to produce high-quality 3D proposals. Additionally, the equal treatment of seed points in the voting process, regardless of their significance, exacerbates this limitation. To

Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King

Searching on bipartite graphs is basal and versatile to many real-world Web applications, e.g., online recommendation, database retrieval, and query-document searching. Given a query node, the conventional approaches rely on the similarity matching with the vectorized node embeddings in the continuous Euclidean space. To efficiently manage intensive similari

Bishnupada Ghosh, Mrinmay Sahu, Pinku Saha, Nico Giordano

We have synthesized an orthorhombic phase of nickel and silicon doped Fe$_{7}$C$_{3}$ at high-pressure and high temperature using a laser-heated diamond anvil cell. The synthesized material is characterized using X-ray diffraction (XRD), Raman spectroscopy, and Transmission Electron Microscopy (TEM) measurements. High-pressure XRD measurement at room tempera

François Bacher

Consider a Brody hyperbolic foliation with non-degenerate singularities on a compact complex manifold. We show that the leafwise heat diffusions and the abstract heat diffusions coincide. In particular, this will imply that the abstract heat diffusions are unique.

Masaki Kashiwara, Myungho Kim, Se-jin Oh, Euiyong Park

In this paper we establish affinizations and R-matrices in the language of pro-objects, and as an application, we construct reflection functors over the localizations of quiver Hecke algebras of arbitrary finite types. This reflection functor categorifies the braid group action on the half of a quantum group and the Saito reflection.

Amjad Sohail, Rizwan Ahmed, Jia-Xin Peng, Aamir Shahzad

We analytically investigate the Fano-type optical response and four-wave mixing (FWM) process by exploiting the magnetoelasticity of a ferromagnetic material. The deformation of the ferromagnetic material plays the role of mechanical displacement, which is simultaneously coupled to both optical and magnon modes. We report that the magnetostrictively induced

Deep Kumar Kirtania

The main objective of this paper is to identify the major research areas of ChatGPT through term and keyword co-occurrence network mapping techniques. For conducting the present study, total of 577 publications were retrieved from the Lens database for the network visualization. The findings of the study showed that chatgpt occurrence in maximum number of ti

Jason Holmes, Zhengliang Liu, Lian Zhang, Yuzhen Ding

We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have large test-taker populations and ample test preparation resources in circulation, they may not allow for accurately assessing the true potential of LLMs. This paper proposes evalua

Yi Zheng, Mu Yang, Yu-Wei Liao, Jin-Shi Xu

The quantum wave function of multiple particles provides additional information which is inaccessible to detectors working alone. Here, we introduce the coincidence wavefront sensing (CWS) method to reconstruct the phase of the multiphoton transverse spatial wave function. The spatially resolved coincidence photon counting is involved. Numerical simulations

Suman Adhya, Debarshi Kumar Sanyal

The TCPD-IPD dataset is a collection of questions and answers discussed in the Lower House of the Parliament of India during the Question Hour between 1999 and 2019. Although it is difficult to analyze such a huge collection manually, modern text analysis tools can provide a powerful means to navigate it. In this paper, we perform an exploratory analysis of

Junwei Liu, Zikai Ouyang, Jiahui Yang, Hua Chen

In this paper, we present a dual-layer online optimization strategy for defender robots operating in multiplayer reach-avoid games within general convex environments. Our goal is to intercept as many attacker robots as possible without prior knowledge of their strategies. To balance optimality and efficiency, our approach alternates between coordinating defe

Pengliang Yang

This paper delivers a software -- libEMM -- for 3D controlled-source electromagnetics (CSEM) modelling in fictitious wave domain, based on the newly developed high-order finite-difference time-domain (FDTD) method on non-uniform grid. The numerical simulation can be carried out over a number of parallel processors using MPI-based high performance computing a

Reda Alami, Mohammed Mahfoud, Eric Moulines

We consider the problem of learning in a non-stationary reinforcement learning (RL) environment, where the setting can be fully described by a piecewise stationary discrete-time Markov decision process (MDP). We introduce a variant of the Restarted Bayesian Online Change-Point Detection algorithm (R-BOCPD) that operates on input streams originating from the

Zhiqiang Cao, Lama Ghazi, Claudia Mastrogiacomo, Laura Forastiere

While the inverse probability of treatment weighting (IPTW) is a commonly used approach for treatment comparisons in observational data, the resulting estimates may be subject to bias and excessively large variance when there is lack of overlap in the propensity score distributions. By smoothly down-weighting the units with extreme propensity scores, overlap

Zenon B. Batang

We show that the Fermat equation $x^p + y^p = z^p$ has no solutions in coprime positive integers $x, y, z$ for any odd prime $p$.

Kai Ren

This paper presents an empirical analysis of the capital asset pricing model using trading data for the Chinese A-share market from 2000 to 2019. Firstly, the standard CAPM is tested using a Fama-MacBetch regression and although the results successfully test the three core hypotheses, the resulting beta risk does not have a significant impact on returns. Sec

Yi Xing, Zhongxiang Wang

We report on the detection of a gamma-ray source at the position of the nearby star-forming galaxy (SFG) M83, which is found from our analysis of 14 years of the data obtained with the Large Area Telescope (LAT) on-board {\it Fermi Gamma-ray Space Telescope (Fermi)}. The source is weakly detected, with a significance of $\sim 5\sigma$, and its emission can b

Kai-Cheng Yang, Filippo Menczer

Search engines increasingly leverage large language models (LLMs) to generate direct answers, and AI chatbots now access the Internet for fresh data. As information curators for billions of users, LLMs must assess the accuracy and reliability of different sources. This paper audits nine widely used LLMs from three leading providers -- OpenAI, Google, and Met

Daichi Saito, Eri Nagatomo, Jefferson Pardomuan, Hideki Koike

To adopt the soft hand exoskeleton to support activities of daily livings, it is necessary to control finger joints precisely with the exoskeleton. The problem of controlling joints to follow a given trajectory is called the tracking control problem. In this study, we focus on the tracking control problem of a human finger attached with thin McKibben muscles

Ming Feng Qin, Yu Zhang, Jinzhong Liu, Fangfang Song

Context. In the Gaia era, the precision of astrometric data is unprecedented. High-quality data make it easier to find more cluster aggregates and support further confirmation of these open clusters. Aims. We use Gaia DR3 to redetermine the open clusters surrounding Pismis 5 in the Vela Molecular Ridge. We also investigate the basic properties of these clust

Behnaz Hadi, Alireza Khosravi, Pouria Sarhadi

Creating safe paths in unknown and uncertain environments is a challenging aspect of leader-follower formation control. In this architecture, the leader moves toward the target by taking optimal actions, and followers should also avoid obstacles while maintaining their desired formation shape. Most of the studies in this field have inspected formation contro

A. Bello-García, V. M. Passegger, J. Ordieres-Meré, A. Schweitzer

The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promising higher accuracy in the derived data products, with information from one domain being transferred to improve the accuracy of a neural network model in another domain. In this wo

Xin Zhang, Shenghui Song, Khaled B. Letaief

The classical Rician Weichselberger channel and the emerging holographic multiple-input multiple-output (MIMO) channel share a common characteristic of non-separable correlation, which captures the interdependence between transmit and receiver antennas. However, this correlation structure makes it very challenging to characterize the fundamental limits of no

Yuhei Iwata, Tomoharu Oka, Shunya Takekawa, Shiho Tsujimoto

We report the results of observations toward the center of the molecular cloud CO 0.02-0.02 made using the Atacama Large Millimeter/Submillimeter Array. The successfully obtained 1 arcsec resolution images of CO $J$=3-2, H$^{13}$CN $J$=4-3, H$^{13}$CO$^{+}$ $J$=4-3, SiO $J$=8-7, CH$_3$OH $J_{K_a, K_c}$ = 7$_{1, 7}$-6$_{1, 6}$ A$^{+}$ lines, and 900 $\mu$m co

Mang Tik Chiu, Xuaner Zhang, Zijun Wei, Yuqian Zhou

Wires and powerlines are common visual distractions that often undermine the aesthetics of photographs. The manual process of precisely segmenting and removing them is extremely tedious and may take up hours, especially on high-resolution photos where wires may span the entire space. In this paper, we present an automatic wire clean-up system that eases the

Ryan Dorrill, Jiffy Felis

A key axiom of equilibrium statistical physics is that all microstates are equally probably in a thermally isolated system. Coupled with the laws of Newtonian mechanics, quantum mechanics, chemistry, and thermal physics, one can build from this axiom both complex and satisfactory models for macroscopic phenomena. Here, we apply the precepts of statistical ph

Chunyu Lei, C. L. Philip Chen, Jifeng Guo, Tong Zhang

Deep learning generally suffers from enormous computational resources and time-consuming training processes. Broad Learning System (BLS) and its convolutional variants have been proposed to mitigate these issues and have achieved superb performance in image classification. However, the existing convolutional-based broad learning system (C-BLS) either lacks a

Fenggang Liu, Yangguang Li, Feng Liang, Jilan Xu

This paper shows that Masking the Deep hierarchical features is an efficient self-supervised method, denoted as MaskDeep. MaskDeep treats each patch in the representation space as an independent instance. We mask part of patches in the representation space and then utilize sparse visible patches to reconstruct high semantic image representation. The intuitio

Zhangxing Bian, Muhan Shao, Aaron Carass, Jerry L. Prince

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imaging (EPI) with high gradient fields, which could introduce severe geometric distortions that interfere with further analyses. Most tools for correcting distortion require two minima

Ruining Deng, Can Cui, Lucas W. Remedios, Shunxing Bao

Analyzing high resolution whole slide images (WSIs) with regard to information across multiple scales poses a significant challenge in digital pathology. Multi-instance learning (MIL) is a common solution for working with high resolution images by classifying bags of objects (i.e. sets of smaller image patches). However, such processing is typically performe

Jiaang Li, Quan Wang, Zhendong Mao

Relation prediction on knowledge graphs (KGs) is a key research topic. Dominant embedding-based methods mainly focus on the transductive setting and lack the inductive ability to generalize to new entities for inference. Existing methods for inductive reasoning mostly mine the connections between entities, i.e., relational paths, without considering the natu

Tao Wang, Wonjae Lee, Mark Limes, Tom Kornack

We introduce a vector atomic magnetometer that employs a fast-rotating magnetic field applied to a pulsed $^{87}$Rb scalar atomic magnetometer. This approach enables simultaneous measurements of the total magnetic field and its two polar angles relative to the rotation plane. Operating in gradiometer mode, the magnetometer achieves a total field gradient sen

Botao Zhao, Mojtaba Esfandiari, David E. Usevitch, Peter Gehlbach

Cooperative robots for intraocular surgery allow surgeons to perform vitreoretinal surgery with high precision and stability. Several robot structural designs have shown capabilities to perform these surgeries. This research investigates the comparative performance of a serial and parallel cooperative-controlled robot in completing a retinal vessel-following

Mingze Yuan, Yingda Xia, Hexin Dong, Zifan Chen

Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically significant. A trustworthy medical AI algorithm should demonstrate its effectiveness on tail conditions to avoid clinically dangerous damage in these out-of-distribution (OOD) cases. In

Mao Sun

Approximately half of the existing winged-insect species are of very small size (wing length about 0.3-4 mm); they are referred to as miniature insects. Yet until recently, much of what we know about the mechanics of insect flight was derived from studies on relatively large insects, such as hoverflies, honey bees and hawkmoths. Because of their very small s

Hans Riess, Michael Munger, Michael M. Zavlanos

We introduce a decentralized mechanism for pricing and exchanging alternatives constrained by transaction costs. We characterize the time-invariant solutions of a heat equation involving a (weighted) Tarski Laplacian operator, defined for max-plus matrix-weighted graphs, as approximate equilibria of the trading system. We study algebraic properties of the so

Zheng Zhang, Boris Epel, Buxin Chen, Dan Xia

Objective: We investigate and develop optimization-based algorithms for accurate reconstruction of four-dimensional (4D)-spectral-spatial (SS) images directly from data collected over limited angular ranges (LARs) in continuous-wave (CW) electron paramagnetic resonance imaging (EPRI). Methods: Basing on a discrete-to-discrete data model devised in CW EPRI em

Jinning Liang, Eda Gjergo, Xilong Fan

One-zone Galactic Chemical Evolution (GCE) models have provided useful insights on a great wealth of average abundance patterns in many environments, especially for the Milky Way and its satellites. However, the scatter of such abundance patterns is still a challenging aspect to reproduce. The leading hypothesis is that dynamics is a likely major source of t

Ramesh Kannan Kandasami, Charalampos Konstantinou, Giovanna Biscontin

Understanding and controlling fracture propagation is one of the most challenging engineering problems, especially in the oil and gas sector, groundwater hydrology and geothermal energy applications. Predicting the fracture orientation while also possessing a non-linear material response becomes more complex when the medium is non-homogeneous and anisotropic

Sriram Radhakrishna, Adithya Balasubramanyam

Road accidents involving autonomous vehicles commonly occur in situations where a (pedestrian) obstacle presents itself in the path of the moving vehicle at very sudden time intervals, leaving the robot even lesser time to react to the change in scene. In order to tackle this issue, we propose a novel algorithmic implementation that classifies the intent of

Zhijun Song, Yang Yu, Bin Cheng, Jing Lv

An asteroid spun up to its critical limit has unique surface mechanical properties that its gravity and the centrifugal force largely balance, creating a relaxation environment where low-energy events such as mass shedding may trigger subsequent long complex motion of an asteroid's regolith grains. Exploring such an evolution process may provide key clues fo

Gui-Long Jiang, Wen-Qiang Liu, Hai-Rui Wei

Hyperentanglement, defined as the simultaneous entanglement in several independent degrees of freedom (DOFs) of a quantum system, is a fascinating resource in quantum information processing with its outstanding merits. Here we propose heralded hyperentanglement concentration protocols (hyper-ECPs) to concentrate an unknown partially less polarization-spatial

M. E. Raikh

The origin of magnetoresistance is bipolar organic materials is the influence of magnetic field on the dynamics of recombination within localized electron-hole pairs. Recombination from the $S$ spin-state of the pair in preceded by the beatings between the states $S$ and $T_0$. Period of the beating is set by the the random hyperfine field. For the case when

Xiaojun Jia, Yong Zhang, Xingxing Wei, Baoyuan Wu

Fast adversarial training (FAT) is an efficient method to improve robustness. However, the original FAT suffers from catastrophic overfitting, which dramatically and suddenly reduces robustness after a few training epochs. Although various FAT variants have been proposed to prevent overfitting, they require high training costs. In this paper, we investigate

Rui Sun, Chen Wang, An-An Lu, Xiqi Gao

We investigate the weighted sum-rate (WSR) maximization linear precoder design for massive multiple-input multiple-output (MIMO) downlink. We consider a single-cell system with multiple users and propose a unified matrix manifold optimization framework applicable to total power constraint (TPC), per-user power constraint (PUPC) and per-antenna power constrai

Fengyi Li, Youssef Marzouk

We propose a novel diffusion map particle system (DMPS) for generative modeling, based on diffusion maps and Laplacian-adjusted Wasserstein gradient descent (LAWGD). Diffusion maps are used to approximate the generator of the corresponding Langevin diffusion process from samples, and hence to learn the underlying data-generating manifold. On the other hand,

Elisa Negrini, Levon Nurbekyan

In this work, we investigate applications of no-collision transportation maps introduced in [Nurbekyan et. al., 2020] in manifold learning for image data. Recently, there has been a surge in applying transportation-based distances and features for data representing motion-like or deformation-like phenomena. Indeed, comparing intensities at fixed locations of

Debdipta Goswami

This paper explores the problem of training a recurrent neural network from noisy data. While neural network based dynamic predictors perform well with noise-free training data, prediction with noisy inputs during training phase poses a significant challenge. Here a sequential training algorithm is developed for an echo-state network (ESN) by incorporating n

A. Morozov

A sketchy review of the "island" paradigm in black hole evaporation theory, which actually brings us back to the old idea that interior of black hole decouples from our universe after Page time, so that Hawking radiation is entangled with emerging new universe, thus leaving no room for the information paradox. Instead this provides a self-consistent descript

Fei Yu Chen

In this paper, we prove that the deformation theory of an object in an $n$-category is controlled by the its $n$-fold endomorphism algebra. This recovers Lurie's results on deforming objects and categories. We also generalize a previous result by Blanc et al. on deforming a category and an object simultaneously to the case of $n$-categories.

Awni Altabaa, Taylor Webb, Jonathan Cohen, John Lafferty

An extension of Transformers is proposed that enables explicit relational reasoning through a novel module called the Abstractor. At the core of the Abstractor is a variant of attention called relational cross-attention. The approach is motivated by an architectural inductive bias for relational learning that disentangles relational information from object-l

Shuo Yang, George J. Pappas, Rahul Mangharam, Lars Lindemann

We consider perception-based control using state estimates that are obtained from high-dimensional sensor measurements via learning-enabled perception maps. However, these perception maps are not perfect and result in state estimation errors that can lead to unsafe system behavior. Stochastic sensor noise can make matters worse and result in estimation error

Lidan Xu, Hao Lu, JianLiang Wang, Xianggui Guo

This article studies the collaborative transportation of a cable-suspended pipe by two quadrotors. A force-coordination control scheme is proposed, where a force-consensus term is introduced to average the load distribution between the quadrotors. Since thrust uncertainty and cable force are coupled together in the acceleration channel, disturbance observer

Shyam Pratap Singh, Arshad Ali Khan, Riad Souissi, Syed Adnan Yusuf

Traffic congestion has been a major challenge in many urban road networks. Extensive research studies have been conducted to highlight traffic-related congestion and address the issue using data-driven approaches. Currently, most traffic congestion analyses are done using simulation software that offers limited insight due to the limitations in the tools and

Wesley G. Lautenschlaeger, Thaísa Tamusiunas

We introduce partial representation of a finite groupoid $G$ on an algebra $A$ and show that the partial groupoid representations of $G$ are in one-to-one correspondence with the representations of the algebra generated by the Birget-Rhodes expansion $G^{BR}$ of $G$.

J. E. Hirsch

The resistive transition width of a recently discovered room temperature near-ambient-pressure superconductor [1] changes by more than three orders of magnitude between different samples, with the transition temperature nearly unchanged. For the narrowest transitions, the transition width relative to $T_c$ is only $0.014 \%$. The voltage-current characterist

A. Ait Ben Mennana, M. Oulne

The isovector giant dipole resonance (IVGDR) in the chain of even-even Mo isotopes is investigated within the time-dependent Hartree-Fock (TDHF) using the Skyrme force Sly6. The GDR calculated in $ ^{92-108}\text{Mo}$ are presented, and compared with the available experimental data. An overall agreement between them is obtained. Moreover, the dipole strength

Grégoire Sergeant-Perthuis, Nils Ruet, David Rudrauf, Dimitri Ognibene

In human spatial awareness, 3-D projective geometry structures information integration and action planning through perspective taking within an internal representation space. The way different perspectives are related and transform a world model defines a specific perception and imagination scheme. In mathematics, such collection of transformations correspon

Zhan Gao, Yan He

We study the time evolution of geometric phases of one dimensional topological models under the quench dynamics. Taking the Creutz ladder model as an example, it is found that the Berry phase is fixed as the parameter is suddenly tuned across the topological phase boundary, given that the chiral symmetry of the model is preserved. At finite temperature, the

Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz

Recent text-to-image generation models like DreamBooth have made remarkable progress in generating highly customized images of a target subject, by fine-tuning an ``expert model'' for a given subject from a few examples. However, this process is expensive, since a new expert model must be learned for each subject. In this paper, we present SuTI, a Subject-dr

Alec Helbling, Christopher J. Rozell, Matthew O'Shaughnessy, Kion Fallah

Deep generative models have the capacity to render high fidelity images of content like human faces. Recently, there has been substantial progress in conditionally generating images with specific quantitative attributes, like the emotion conveyed by one's face. These methods typically require a user to explicitly quantify the desired intensity of a visual at

Ernest Ma

If dark matter is light, it may be due to a seesaw mechanism just as neutrinos are. It is postulated that both originate from the same type of heavy fermion anchors, either singlets or triplets. In the latter case, a shift of the $W$ mass is predicted, as suggested by the $CDF$ precision measurement. A spontaneously broken dark $U(1)$ gauge symmetry is assum

Gaetano Lambiase, Reggie C. Pantig, Dhruba Jyoti Gogoi, Ali Övgün

The links between the deformation parameter $\beta$ of the generalized uncertainty principle (GUP) to the two free parameters $\hat{\omega}$ and $\gamma$ of the running Newtonian coupling constant of the Asymptotic Safe gravity (ASG) program, has been conducted recently in [Phys.Rev.D 105 (2022) 12, 124054]. In this paper, we test these findings by calculati

Li Zhang

This paper takes into account the estimation for the two unknown parameters of the Chen distribution with bathtub-shape hazard rate function under the improved adaptive Type-II progressive censored data. Maximum likelihood estimation for two parameters are proposed and the approximate confidence intervals are established using the asymptotic normality. Bayes

Alexander Bors, Daniel Panario, Qiang Wang

The functional graph of a function $g:X\rightarrow X$ is the directed graph with vertex set $X$ the edges of which are of the form $x\rightarrow g(x)$ for $x\in X$. Functional graphs are heavily studied because they allow one to understand the behavior of $g$ under iteration (i.e., to understand the discrete dynamical system $(X,g)$), which has various appli