July 2022 arXiv papers — page 3

Hongyang Du, Jiacheng Wang, Dusit Niyato, Jiawen Kang

Emerging with the support of computing and communications technologies, Metaverse is expected to bring users unprecedented service experiences. However, the increase in the number of Metaverse users places a heavy demand on network resources, especially for Metaverse services that are based on graphical extended reality and require rendering a plethora of vi

Maosen Li, Siheng Chen, Zijing Zhang, Lingxi Xie

Graph convolutional network based methods that model the body-joints' relations, have recently shown great promise in 3D skeleton-based human motion prediction. However, these methods have two critical issues: first, deep graph convolutions filter features within only limited graph spectrums, losing sufficient information in the full band; second, using a si

L. -W. Huang, J-H. Peng, F. -J. Jiang

The Curie constants $C^{*} = \lim_{T\rightarrow 0}T\chi_{\text{imp}}$ of a spin-1/2 and a spin-1 impurities are calculated using the quantum Monte Carlo simulations. Here the impurity susceptibility $\chi_{\text{imp}}$ is the difference between the uniform susceptibilities with and without the impurity and $T$ is the temperature. Moreover, the two-dimensiona

Lubomíra Dvořáková, Daniela Opočenská, Edita Pelantová

The critical exponent $E(\mathbf u)$ of an infinite sequence $\mathbf u$ over a finite alphabet expresses the maximal repetition of a factor in $\mathbf u$. By the famous Dejean's theorem, $E(\mathbf u) \geq 1+\frac1{d-1}$ for every $d$-ary sequence $\mathbf u$. We define the asymptotic critical exponent $E^*(\mathbf u)$ as the upper limit of the maximal rep

Akshaya Jayashankar, Prabha Mandayam

The quantum computing devices of today have tens to hundreds of qubits that are highly susceptible to noise due to unwanted interactions with their environment. The theory of quantum error correction provides a scheme by which the effects of such noise on quantum states can be mitigated, paving the way for realising robust, scalable quantum computers. In thi

Indra Agustian, Bagus Imam Prayoga, Hendy Santosa, Novalio Daratha

The Nutrient Film Technique (NFT) method is one of the most popular hydroponic cultivation methods. This method has advantages such as easier maintenance, faster and optimal plant growth, better use of fertilizers, and less deposition. The disadvantages of NFT include the consumption of electrical power and the faster spread of disease. Therefore, NFT requir

M. Ya. Sushko, S. D. Balika

We study the role of the electrical double layer (EDL) in the formation of the quasistatic electrical conductivity of suspensions of nanosized particles. A suspension is viewed as a system of hard-core--penetrable-shell particles. The shells are electrically inhomogeneous, with a radially symmetrical conductivity profile. It is assumed that the real microstr

Surjit S. Wadhwa, Ain De Horta, Miroslav D. Filipovic, N. F. H. Tothill

We present photometric analysis of three bright red nova progenitor contact binary systems: ASAS J082151-0612.6, TYC 7281-269-1 and TYC 7275-1968-1. The primary components in all three systems are solar-type low mass stars with radii somewhat larger than their Zero Age Main Sequence counterparts. The secondaries, as in most contact binary systems, have radii

Zhipeng Zhang, Zhimin Wei, Zhongzhen Huang, Rui Niu

Referring Expression Comprehension (REC) is one of the most important tasks in visual reasoning that requires a model to detect the target object referred by a natural language expression. Among the proposed pipelines, the one-stage Referring Expression Comprehension (OSREC) has become the dominant trend since it merges the region proposal and selection stag

André Guerino Castoldi, Emerson L. Monte Carmelo, Lucia Moura, Daniel Panario

This work shows several direct and recursive constructions of ordered covering arrays using projection, fusion, column augmentation, derivation, concatenation and cartesian product. Upper bounds on covering codes in NRT spaces are also obtained by improving a general upper bound. We explore the connection between ordered covering arrays and covering codes in

Fatema Tarannum, Swapneel Danayat, Avinash Nayal, Rajmohan Muthaiah

In this work, we have comprehensively studied the effect of auxiliary intercalating agents on the thermal conductivity of expanded graphite (EG) polymer composites. We report an ultra-high enhancement of 4030% in thermal conductivity of polyetherimide/graphene nanocomposite (k = 9.5 Wm-1K-1) prepared through the use of EG with hydrogen peroxide (H2O2) as an

Ophelia Adams

We introduce an anabelian approach to the study of arboreal Galois representations and apply Tamagawa's anabelian version of the N\'eron-Ogg-Shafarevich criterion to produce a dynamical analogue of this criterion: unramified representations correspond to rational maps satisfying a strong form of good reduction in terms of their critical locus. Subsequently,

Xincao Xu, Kai Liu, Qisen Zhang, Hao Jiang

Heterogeneous information fusion is one of the most critical issues for realizing vehicular cyber-physical systems (VCPSs). This work makes the first attempt at quantitatively measuring the quality of heterogeneous information fusion in VCPS by designing a new metric called Age of View (AoV). Specifically, we derive a sensing model based on a multi-class M/G

Libei Sun, Xiucai Huang, Yongduan Song

This paper investigates the decentralized stabilization problem for a class of interconnected systems in the presence of non-triangular structural uncertainties and time-varying parameters, where each subsystem exchanges information only with its neighbors and only intermittent (rather than continuous) states and input are to be utilized. Thus far to our bes

Tiancai Peng, Zhimin Zhu, Siqi Xu, Xiang Liu

We obtain the masses, the electromagnetic properties, and the parton distribution functions (PDFs) of $\Lambda$, $\Lambda_c$, and their isospin triplet baryons, i.e, $\Sigma^0$, $\Sigma^+$, $\Sigma^-$ and $\Sigma_c^0$, $\Sigma_c^+$, $\Sigma_c^{++}$ from a light-front effective Hamiltonian in the leading Fock sector in the basis light-front quantization frame

Lei Huang, Jiawang Nie, Ya-Xiang Yuan

This paper studies generalized truncated moment problems with unbounded sets. First, we study geometric properties of the truncated moment cone and its dual cone of nonnegative polynomials. By the technique of homogenization, we give a convergent hierarchy of Moment-SOS relaxations for approximating these cones. With them, we give a Moment-SOS method for sol

A. Adam Ding, Natalie DelRocco, Samuel Wu

Biomarker is a critically important tool in modern clinical diagnosis, prognosis, and classification/prediction. However, there are fiscal and analytical barriers to biomarker research. Selective Genotyping is an approach to increasing study power and efficiency where individuals with the most extreme phenotype (response) are chosen for genotyping (exposure)

Evan Ehrenberg, Kleovoulos Leo Tsourides, Hossein Nejati, Ngai-Man Cheung

In the domain of face recognition, there exists a puzzling timing discrepancy between results from macaque neurophysiology on the one hand and human electrophysiology on the other. Single unit recordings in macaques have demonstrated face identity specific responses in extra-striate visual cortex within 100 milliseconds of stimulus onset. In EEG and MEG expe

Peng Xia, Yuechi Zhou, Ziyan Zhang, Zecheng Tang

In view of the poor robustness of existing Chinese grammatical error correction models on attack test sets and large model parameters, this paper uses the method of knowledge distillation to compress model parameters and improve the anti-attack ability of the model. In terms of data, the attack test set is constructed by integrating the disturbance into the

Nam H. Nguyen, Quy C. Tran, Thach A. Nguyen, Trung Phan

We show how the electrical field inside the conductor changes as a function of the number of charged-particles. We show that the non-vanishing electrical field is concentrated near the surface of the conductor, at a shallow depth on the same order of magnitude as the separation between charges. Our study has illustrated the effect of charge discretization on

Norihiro Oyama, Shihori Koyama, Takeshi Kawasaki

Glass transitions are widely observed in various types of soft matter systems. However, the physical mechanism of these transitions remains {elusive}, despite years of ambitious research. In particular, an important unanswered question is whether the glass transition is accompanied by a divergence of the correlation lengths of the characteristic static struc

Tiandong Wang, Sidney Resnick

Users of social networks display diversified behavior and online habits. For instance, a user's tendency to reply to a post can depend on the user and the person posting. For convenience, we group users into aggregated behavioral patterns, focusing here on the tendency to reply to or reciprocate messages. The reciprocity feature in social networks reflects t

Siyu Lv, Jie Xiong, Xin Zhang

In this paper, we consider a linear quadratic (LQ) leader-follower stochastic differential game for regime switching diffusions with mean-field interactions. One of the salient features of this paper is that conditional mean-field terms are included in the state equation and cost functionals. Based on stochastic maximum principles (SMPs), the follower's prob

Kang Zhou, Qiao Qiao, Yuepei Li, Qi Li

To reduce human annotations for relation extraction (RE) tasks, distantly supervised approaches have been proposed, while struggling with low performance. In this work, we propose a novel DSRE-NLI framework, which considers both distant supervision from existing knowledge bases and indirect supervision from pretrained language models for other tasks. DSRE-NL

André Guerino Castoldi, Emerson Luiz do Monte Carmelo, Lucia Moura, Daniel Panario

In this work, constructions of ordered covering arrays are discussed and applied to obtain new upper bounds on covering codes in Rosenbloom-Tsfasman spaces (RT spaces), improving or extending some previous results.

Xiaoyi Gu, Santanu S. Dey, Jean-Philippe P. Richard

Recently, we proposed a class of inequalities called lifted bilinear cover inequalities, which are second-order cone representable convex inequalities, and are valid for a set described by a separable bilinear constraint together with bounds on variables. In this paper, we study the computational potential of these inequalities for separable bilinear optimiz

Leena Mathur, Ralph Adolphs, Maja J Matarić

In our multicultural world, affect-aware AI systems that support humans need the ability to perceive affect across variations in emotion expression patterns across cultures. These systems must perform well in cultural contexts without annotated affect datasets available for training models. A standard assumption in affective computing is that affect recognit

Youqian Zhang, Kasper Rasmussen

Differential signaling is a method of data transmission that uses two complementary electrical signals to encode information. This allows a receiver to reject any noise by looking at the difference between the two signals, assuming the noise affects both signals in the same way. Many protocols such as USB, Ethernet, and HDMI use differential signaling to ach

Romesh Kumar, Rajat Singh

In this paper, we investigate Li-Yorke composition operators and some of their variations on Lorentz spaces. Further, we also study expansive composition operators on these spaces. The work of the paper is essentially based on the work in [1], [9], [11], and [13].

Kenju Otsuka, Seiichi Sudo

Formation of a peculiar lasing pattern leading to a TEM00-like mode accompanied by a nonzero bright outer-ring emission (namely, a modified TEM00 mode) was observed in a 300-\mu m-thick LiNdP4O12 (LNP) laser with reflective flat end mirrors that was pumped with a laser diode whose focused spot size was larger than the lasing beam spot size determined by the

Weichao Guo, Guoping Zhao

Inspired by a recent article \cite[JFAA, 28(2):1-34, (2022)]{Skrettingland2022JoFAaA}, this paper is devoted to the study of suitable window class in the framework of bounded linear operators on $L^2(\rd)$. We establish a natural and complete characterization for the window class such that the corresponding STFT leads to equivalent norms of modulation spaces

Jiang Li, Xiaoping Wang, Guoqing Lv, Zhigang Zeng

Multimodal machine learning is an emerging area of research, which has received a great deal of scholarly attention in recent years. Up to now, there are few studies on multimodal Emotion Recognition in Conversation (ERC). Since Graph Neural Networks (GNNs) possess the powerful capacity of relational modeling, they have an inherent advantage in the field of

Sein Park, Yeongsang Jang, Eunhyeok Park

Robust quantization improves the tolerance of networks for various implementations, allowing reliable output in different bit-widths or fragmented low-precision arithmetic. In this work, we perform extensive analyses to identify the sources of quantization error and present three insights to robustify a network against quantization: reduction of error propag

Tian Tan, Yue Li

Static analysis is a mature field with applications to bug detection, security analysis, and code optimization, etc. To facilitate these applications, static analysis frameworks play an essential role by providing a series of fundamental services such as program abstraction, control flow graph construction, and points-to/alias information computation, etc. H

Noah Swimmer, Thayne Currie, Sarah Steiger, Gregory Mirek Brandt

We present the direct imaging discovery of a low-mass companion to the nearby accelerating F star, HIP 5319, using SCExAO coupled with the CHARIS, VAMPIRES, and MEC instruments in addition to Keck/NIRC2 imaging. CHARIS $JHK$ (1.1-2.4 $\mu$m) spectroscopic data combined with VAMPIRES 750 nm, MEC $Y$, and NIRC2 $L_{\rm p}$ photometry is best matched by an M3--

André Guerino Castoldi, Lucia Moura, Daniel Panario, Brett Stevens

We present a new construction of ordered orthogonal arrays (OOA) of strength $t$ with $(q + 1)t$ columns over a finite field $\mathbb{F}_{q}$ using linear feedback shift register sequences (LFSRs). OOAs are naturally related to $(t, m, s)$-nets, linear codes, and MDS codes. Our construction selects suitable columns from the array formed by all subintervals o

Sk Golam Saroar, Waseefa Ahmed, Maleknaz Nayebi

Marketplaces for distributing software products and services have been getting increasing popularity. GitHub, which is most known for its version control functionality through Git, launched its own marketplace in 2017. GitHub Marketplace hosts third party apps and actions to automate workflows in software teams. Currently, this marketplace hosts 440 Apps and

Muhammad Abdullah Hanif, Giuseppe Maria Sarda, Alberto Marchisio, Guido Masera

In today's era of smart cyber-physical systems, Deep Neural Networks (DNNs) have become ubiquitous due to their state-of-the-art performance in complex real-world applications. The high computational complexity of these networks, which translates to increased energy consumption, is the foremost obstacle towards deploying large DNNs in resource-constrained sy

Kelli Francis-Staite

This paper studies Stochastic Shortest Path (SSP) problems in known and unknown environments from the perspective of convex optimisation. It first recalls results in the known parameter case, and develops understanding through different proofs. It then focuses on the unknown parameter case, where it studies extended value iteration (EVI) operators. This incl

Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen, Francis Ferraro

The events in a narrative are understood as a coherent whole via the underlying states of their participants. Often, these participant states are not explicitly mentioned, instead left to be inferred by the reader. A model that understands narratives should likewise infer these implicit states, and even reason about the impact of changes to these states on t

Alessio Colucci, Andreas Steininger, Muhammad Shafique

Research on Deep Neural Networks (DNNs) has focused on improving performance and accuracy for real-world deployments, leading to new models, such as Spiking Neural Networks (SNNs), and optimization techniques, e.g., quantization and pruning for compressed networks. However, the deployment of these innovative models and optimization techniques introduces poss

Ulysse Chabaud, Abhinav Deshpande, Saeed Mehraban

The permanent is pivotal to both complexity theory and combinatorics. In quantum computing, the permanent appears in the expression of output amplitudes of linear optical computations, such as in the Boson Sampling model. Taking advantage of this connection, we give quantum-inspired proofs of many existing as well as new remarkable permanent identities. Most

L. F. Melo, Thiago Melo, Fernando Parisio

Whenever a physical quantity becomes essential to the realization of useful tasks, it is desirable to define proper measures or monotones to quantify it. In quantum mechanics, coherence, entanglement, and Bell nonlocality are examples of such quantities. Given a quantum state $\varrho$ and a quantifier ${\cal E}(\varrho)$, both arbitrary, it is a hard task t

Dustin Padilla

Brucellosis is a zoonotic bacterial infectious disease that affects livestock and wildlife. The Greater Yellowstone Ecosystem is the last area in the United States where cattle are regularly infected with brucellosis. Even though livestock are vaccinated, interactions with reservoir species still result in spill-over cases to cattle. The National Academy of

Hopein Christofen Tang, Djoko Suprijanto

We obtain all possible parameters of Plotkin-optimal two-Lee weight projective codes over $\mathbb{Z}_4,$ together with their weight distributions. We show the existence of codes with these parameters as well as their weight distributions by constructing an infinite family of two-weight codes. Previously known codes constructed by Shi et al. (\emph{Des Codes

Jae-Won Choi, Dae-Yong Hong, Chan Jung, Eugene Hwang

The performances of commonly used electrocardiogram (ECG) diagnosis models have recently improved with the introduction of deep learning (DL). However, the impact of various combinations of multiple DL components and/or the role of data augmentation techniques on the diagnosis have not been sufficiently investigated. This study proposes an ensemble-based mul

Sharmita Dey, David Fan, Robin Schmid, Anushri Dixit

Legged robots can traverse a wide variety of terrains, some of which may be challenging for wheeled robots, such as stairs or highly uneven surfaces. However, quadruped robots face stability challenges on slippery surfaces. This can be resolved by adjusting the robot's locomotion by switching to more conservative and stable locomotion modes, such as crawl mo

Nai-Bo Zhang, Bao-An Li

Using a meta model for nuclear Equation of State (EOS) with its parameters constrained by astrophysical observations and terrestrial nuclear experiments, we examine effects of nuclear EOS especially its symmetry energy \esym term on the speed of sound squared $C^2_s(\rho)$ and the critical density $\rho_t$ where $C^2_s(\rho_t)$ vanishes (indicating the onset

Ron Shnapp, Stefano Brizzolara, Marius M. Neamtu-Halic, Alessandro Gambino

Countless processes in nature and industry, from rain droplet nucleation to plankton interaction in the ocean, are intimately related to turbulent fluctuations of local concentrations of advected matter. These fluctuations can be described by considering the change of the separation between particle pairs, known as pair dispersion, which is believed to obey

Rachel Holladay, Tomás Lozano-Pérez, Alberto Rodriguez

Multi-step forceful manipulation tasks, such as opening a push-and-twist childproof bottle, require a robot to make various planning choices that are substantially impacted by the requirement to exert force during the task. The robot must reason over discrete and continuous choices relating to the sequence of actions, such as whether to pick up an object, an

Nick McKenna, Tianyi Li, Mark Johnson, Mark Steedman

The diversity and Zipfian frequency distribution of natural language predicates in corpora leads to sparsity in Entailment Graphs (EGs) built by Open Relation Extraction (ORE). EGs are computationally efficient and explainable models of natural language inference, but as symbolic models, they fail if a novel premise or hypothesis vertex is missing at test-ti

Chaitali Joshi, Wenyuan Chen, Henry G. LeDuc, Peter K. Day

Thin films of disordered superconductors such as titanium nitride (TiN) exhibit large kinetic inductance (KI), high critical temperature, and large quality factors at the single-photon level. KI nonlinearity can be exploited as an alternative to Josephson junctions for creating novel nonlinear quantum devices with the potential to operate at higher frequenci

Guilherme Paulino-Passos, Francesca Toni

Recent work shows issues of consistency with explanations, with methods generating local explanations that seem reasonable instance-wise, but that are inconsistent across instances. This suggests not only that instance-wise explanations can be unreliable, but mainly that, when interacting with a system via multiple inputs, a user may actually lose confidence

Sadegh Dalvandi, Brijesh Dongol

Transactional memory (TM) is an intensively studied synchronisation paradigm with many proposed implementations in software and hardware, and combinations thereof. However, TM under relaxed memory, e.g., C11 (the 2011 C/C++ standard) is still poorly understood, lacking rigorous foundations that support verifiable implementations. This paper addresses this ga

Eduardo J. Dubuc, Jaqueline Girabel

In this paper we study a 2-dimensional version of Quillen's homotopy category construction. Given a category $\mathscr{A}$ and a class of morphisms $\Sigma \subset \mathscr{A}$ containing the identities, we construct a 2-category $\mathcal{H}o(\mathscr{A})$ obtained by the addition of 2-cells determined by homotopies. A salient feature here is the use of a n

Ryland T. Giebelhaus, Michael D. Sorochan Armstrong, A. Paulina de la Mata, James J. Harynuk

There are many challenges associated with analysing gas chromatography - mass spectrometry (GC-MS) data. Many of these challenges stem from the fact that electron ionisation can make it difficult to recover molecular information due to the high degree of fragmentation with concomitant loss of molecular ion signal. With GC-MS data there are often many common

Kevin Y. Chen

Finding the shortest path between two points in a graph is a fundamental problem that has been well-studied over the past several decades. Shortest path algorithms are commonly applied to modern navigation systems, so our study aims to improve the efficiency of an existing algorithm on large-scale Euclidean networks. The current literature lacks a deep under

Zixuan Jiang, Jiaqi Gu, Mingjie Liu, David Z. Pan

As deep learning models and datasets rapidly scale up, network training is extremely time-consuming and resource-costly. Instead of training on the entire dataset, learning with a small synthetic dataset becomes an efficient solution. Extensive research has been explored in the direction of dataset condensation, among which gradient matching achieves state-o

Huan-Bo Luo, B. A. Malomed, Wu-Ming Liu, Lu Li

We present an analysis of stationary solutions for two-dimensional (2D) Bose-Einstein condensates (BECs) with the Rashba spin-orbit (SO) coupling and Zeeman splitting. By introducing the generalized momentum operator, the linear version of the system can be solved exactly. The solutions are semi-vortices of the Bessel-vortex (BV) and modified Bessel-vortex (

Eric R. Hoglund, De-Liang Bao, Andrew O'Hara, Thomas W. Pfeifer

Grain boundaries (GBs) are a prolific microstructural feature that dominates the functionality of a wide class of materials. The change in functionality at a GB is a direct result of unique local atomic arrangements, different from those in the grain, that have driven extensive experimental and theoretical studies correlating atomic-scale GB structures to ma

Johan Linåker, Hussan Munir, Krzysztof Wnuk, Carl-Eric Mols

Open Source Software (OSS) ecosystems have reshaped the ways how software-intensive firms develop products and deliver value to customers. However, firms still need support for strategic product planning in terms of what to develop internally and what to share as OSS. Existing models accurately capture commoditization in software business, but lack operation

Zhuqing Li, Roberto Guglielmi

We deduce a sufficient condition of the exponential (integral) turnpike property for infinite dimensional generalized linear-quadratic optimal control problems in terms of structural properties of the control system, such as exponential stabilizability and detectability. The proof relies on the analysis of the exponential convergence of solutions to the diff

Rémi Lefèvre, Krissia Zawadzki, Grégoire Ithier

The modeling of out-of-equilibrium many-body systems requires to go beyond the low-energy physics and local densities of states. Many-body localization, presence or lack of thermalization and quantum chaos are examples of phenomena in which states at different energy scales, including the highly excited ones, contribute to the dynamics and therefore affect t

Zhitong Xiong, Haopeng Li, Xiao Xiang Zhu

Training semantic segmentation models with few annotated samples has great potential in various real-world applications. For the few-shot segmentation task, the main challenge is how to accurately measure the semantic correspondence between the support and query samples with limited training data. To address this problem, we propose to aggregate the learnabl

Johan Linåker, Per Runeson

Objective: Our objective is to explore how public entities in the role of platform providers can address this issue by enabling collaboration within their OGD ecosystems, both in terms of the OGD published on the underpinning platform, as well as any related Open Source Software (OSS) and standards. Method: We conducted an exploratory multiple-case study of

Sabah Al-Fedaghi

In this paper, we concentrate on object-related analysis in the field of general ontology of reality as related to software engineering (e.g., UML classes). Such a venture is similar to many studies in which researchers have enhanced modeling through ontological analysis of the underlying paradigm of UML models. We attempt to develop a conceptual model that

Md. Taufiqul Haque Khan Tusar, Roban Khan Anik

An estimated 300,000 new cases of leukemia are diagnosed each year which is 2.8 percent of all new cancer cases and the prevalence is rising day by day. The most dangerous and deadly type of leukemia is acute lymphoblastic leukemia (ALL), which affects people of all age groups, including children and adults. In this study, we propose an automated system to d

Naomi Boulware, Naihuan Jing, Kailash C. Misra

In this paper, we investigate $q$-Varchenko matrices for some hyperplane arrangements with symmetry in two and three dimensions, and prove that they have a Smith normal form over $\mathbb Z[q]$. In particular, we examine the hyperplane arrangement for the regular $n$-gon in the plane and the dihedral model in the space and Platonic polyhedra. In each case, w

Soheil Nazar Shahsavani, Arash Fayyazi, Mahdi Nazemi, Massoud Pedram

Recent efforts for improving the performance of neural network (NN) accelerators that meet today's application requirements have given rise to a new trend of logic-based NN inference relying on fixed function combinational logic. Mapping such large Boolean functions with many input variables and product terms to digital signal processors (DSPs) on Field-prog

Yichen Han, Christopher Bo Han, Chen Chen, Peng Wei Lee

Population aging is an increasingly important consideration for health care in the 21th century, and continuing to have access and interact with digital health information is a key challenge for aging populations. Voice-based Intelligent Virtual Assistants (IVAs) are promising to improve the Quality of Life (QoL) of older adults, and coupled with Ecological

Magnus Bakke Botnan, Steffen Oppermann, Steve Oudot, Luis Scoccola

A significant part of modern topological data analysis is concerned with the design and study of algebraic invariants of poset representations -- often referred to as multi-parameter persistence modules. One such invariant is the minimal rank decomposition, which encodes the ranks of all the structure morphisms of the persistence module by a single ordered p

Fatma Altunbulak Aksu, Roghayeh Hafezieh, İpek Tuvay

We investigate the properties of binary linear codes of even length whose permutation automorphism group is a cyclic group generated by an involution. Up to dimension or co-dimension $4$, we show that there is no quasi group code whose permutation automorphism group is isomorphic to $C_2$. By generalizing the method we use to prove this result, we obtain res

Mrudang Mathur, Josef M. Brozovich, Manuel K. Rausch

Augmented reality (AR) has revolutionized the video game industry by providing interactive, three-dimensional visualization. Interestingly, AR technology has only been sparsely used in scientific visualization. This is, at least in part, due to the significant technical challenges previously associated with creating and accessing such models. To ease access

M. I. Belishev, D. V. Korikov

As is known, the Dirichlet-to-Neumann operator $\Lambda$ of a Riemannian surface $(M,g)$ determines the surface up to conformal equivalence class $[(M,g)]$. Such classes constitute the Teichm\"uller space with the distance ${\rm d}_T$. We show that the determination is continuous: $\|\Lambda-\Lambda'\|_{H^1(\partial M)\to L_2(\partial M)}\to 0$ implies ${\rm

Seyedeh Bahereh Hassanpour, Ahmad Khonsari, Masoumeh Moradian, Seyed Pooya Shariatpanahi

Edge caching (EC) decreases the average access delay of the end-users through caching popular content at the edge network, however, it increases the leakage probability of valuable information such as users preferences. Most of the existing privacy-preserving approaches focus on adding layers of encryption, which confronts the network with more challenges su

Mohammed Nowshad Ruhani Chowdhury, Wandong Zhang, Thangarajah Akilan

Studies show that Studies that cardiovascular diseases (CVDs) are malignant for human health. Thus, it is important to have an efficient way of CVD prognosis. In response to this, the healthcare industry has adopted machine learning-based smart solutions to alleviate the manual process of CVD prognosis. Thus, this work proposes an information fusion techniqu

Vincent Knibbeler, Sara Lombardo, Casper Oelen

We classify embeddings of the finite groups $A_4$, $S_4$ and $A_5$ in the Lie group $G_2(\mathbb{C})$ up to conjugation.

Neea Palojärvi

In this article, we study the Euler's factorial series $F_p(t)=\sum_{n=0}^\infty n!t^n$ in $p$-adic domain under the Generalized Riemann Hypothesis. First, we show that if we consider primes in $k\varphi(m)/(k+1)$ residue classes in the reduced residue system modulo $m$, then under certain explicit extra conditions we must have $\lambda_0+\lambda_1F_p(\alpha

Jun Li, Thangarajah Akilan

Temperature monitoring is critical for electrical motors to determine if device protection measures should be executed. However, the complexity of the internal structure of Permanent Magnet Synchronous Motors (PMSM) makes the direct temperature measurement of the internal components difficult. This work pragmatically develops three deep learning models to es

Paolo Victor Redondo, Raphael Huser, Hernando Ombao

To study the neurophysiological basis of attention deficit hyperactivity disorder (ADHD), clinicians use electroencephalography (EEG) which record neuronal electrical activity on the cortex. Instead of focusing on single-channel spectral power, a novel framework for investigating interactions (dependence) between channels in the entire network is proposed. A

Tiago Cruz

Important connections in representation theory arise from resolving a finite-dimensional algebra by an endomorphism algebra of a generator-cogenerator with finite global dimension; for instance, Auslander's correspondence, classical Schur--Weyl duality and Soergel's Struktursatz. Here, the module category of the resolution and the module category of the alge

Akash Mondal, Prashanth L. A., Shalabh Bhatnagar

In this paper, we present a stochastic gradient algorithm for minimizing a smooth objective function that is an expectation over noisy cost samples, and only the latter are observed for any given parameter. Our algorithm employs a gradient estimation scheme with random perturbations, which are formed using the truncated Cauchy distribution from the delta sph

Yaozhong Hu, Juan Li, Chao Mi

This paper is concerned with the backward stochastic differential equations whose generator is a weighted fractional Brownian field: $Y_t=\xi+\int_t^T Y_s W (ds,B_s) -\int_t^T Z_sdB_s$, $0\le t\le T$, where $W$ is a $(d+1)$-parameter weighted fractional Brownian field of Hurst parameter $H=(H_0, H_1, \cdots, H_d)$, which provide probabilistic interpretations

Tushar K. Saha, Jannik Ehrich, Momčilo Gavrilov, Susanne Still

Information engines can convert thermal fluctuations of a bath at temperature $T$ into work at rates of order $k_\mathrm{B}T$ per relaxation time of the system. We show experimentally that such engines, when in contact with a bath that is out of equilibrium, can extract much more work. We place a heavy, micron-scale bead in a harmonic potential that ratchets

Florent Chiaroni, Malik Boudiaf, Amar Mitiche, Ismail Ben Ayed

We explore clustering the softmax predictions of deep neural networks and introduce a novel probabilistic clustering method, referred to as k-sBetas. In the general context of clustering discrete distributions, the existing methods focused on exploring distortion measures tailored to simplex data, such as the KL divergence, as alternatives to the standard Eu

Alexandru Buium, Adrian Vasiu

Let $p$ be a prime, let $N\geq 3$ be an integer prime to $p$, let $R$ be the ring of $p$-typical Witt vectors with coefficients in an algebraic closure of $\mathbb F_p$, and consider the correspondence $\mathcal A'_{g,1,N,R}\rightrightarrows \mathcal A_{g,1,N,R}$ obtained by taking the union of all prime to $p$ Hecke correspondences on Mumford's moduli schem

Sanjana Singh, Divyanjali Sharma, Ishita Jaju, Subodh Sharma

The C/C++11 (C11) standard offers a spectrum of ordering guarantees on memory access operations. The combinations of such orderings pose a challenge in developing correct and efficient weak memory programs. A common solution to preclude those program outcomes that violate the correctness specification is using C11 synchronization-fences, which establish orde

S. Bellucci, A. A. Saharian, V. Kh. Kotanjyan

For a massive scalar field with general curvature coupling we evaluate the Wightman function in the geometry of two parallel branes perpendicular to the AdS boundary. On the separate branes, the field operator is constrained by Robin boundary conditions, in general, with different coefficients. In the region between the branes their contribution to the Wight

Aydin Abadi, Steven J. Murdoch, Thomas Zacharias

Fair exchange protocols let two mutually distrustful parties exchange digital data in a way that neither party can cheat. They have various applications such as the exchange of digital items, or the exchange of digital coins and digital services between a buyer/client and seller/server. In this work, we formally define and propose a generic blockchain-based

Hao Wen, Yunze Liu, Jingwei Huang, Bo Duan

This paper proposes a 4D backbone for long-term point cloud video understanding. A typical way to capture spatial-temporal context is using 4Dconv or transformer without hierarchy. However, those methods are neither effective nor efficient enough due to camera motion, scene changes, sampling patterns, and the complexity of 4D data. To address those issues, w

Moritz Platt, Stephen Ojeka, Andreea-Elena Drăgnoiu, Oserere Ejemen Ibelegbu

Decentralized cryptocurrency networks, notably those with high energy demand, have faced significant criticism and subsequent regulatory scrutiny. Despite these concerns, policy interventions targeting cryptocurrency operations in the pursuit of sustainability have largely been ineffective. Some were abandoned for fear of jeopardizing innovation, whereas oth

Zubin Shaikh, A. D. Patel, Meenakshee Sharma, H. H. Joshi

This paper presents the detailed study of the controlled experimental observation and characterization of Ion Acoustic soliton in the quiescent argon plasma produced by filamentary discharge and confined in a multi-pole line cusp magnetic field device named Multi-pole line Cusp Plasma Device (MPD). In this system, the electrostatic fluctuations are found to

Stylianos Piperakis, Michael Maravgakis, Dimitrios Kanoulas, Panos Trahanias

In this article, we propose a deep learning framework that provides a unified approach to the problem of leg contact detection in humanoid robot walking gaits. Our formulation accomplishes to accurately and robustly estimate the contact state probability for each leg (i.e., stable or slip/no contact). The proposed framework employs solely proprioceptive sens

Zhiqin Chen, Thomas Funkhouser, Peter Hedman, Andrea Tagliasacchi

Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synthesize images of 3D scenes from novel views. However, they rely upon specialized volumetric rendering algorithms based on ray marching that are mismatched to the capabilities of widely deployed graphics hardware. This paper introduces a new NeRF representation based on textured polygons

Mustafa Ismail, Ahmed Gaber, M. Anwar

Let $\left\lbrace P_{k}\right\rbrace_{k\geq0}$ be the Padovan sequence defined by $P_{k}=P_{k-2}+P_{k-3}$ with initial values are $P_{0}=P_{1}=P_{2}=1$. Let $\left\lbrace R_{k}\right\rbrace_{k\geq0}$ be the Perrin sequence defined by $R_{k}=R_{k-2}+R_{k-3}$ with initial values are $R_{0}=3$, $R_{1}=0$, $R_{2}=2$. And let $\left\lbrace J_{n}\right\rbrace_{n\g

Junqiang Huang, Xiangwen Kong, Xiangyu Zhang

We focus on better understanding the critical factors of augmentation-invariant representation learning. We revisit MoCo v2 and BYOL and try to prove the authenticity of the following assumption: different frameworks bring about representations of different characteristics even with the same pretext task. We establish the first benchmark for fair comparisons

Fereshteh Yousefirizi, Natalia Dubljevic, Shadab Ahamed, Ingrid Bloise

Segmentation of lymphoma lesions is challenging due to their varied sizes and locations in whole-body PET scans. This work presents a fully-automated segmentation technique using a multi-center dataset of diffuse large B-cell lymphoma (DLBCL) with heterogeneous characteristics. We utilized a dataset of [18F]FDG-PET scans (n=194) from two different imaging ce

Mohammadreza Robaei, Robert Akl

The optimum subspace decomposition of the infinite-dimensional compressible random processes in the locally convex Hausdorff space has been propose and its dimension has been measured. We conduct topological analysis of finite- and infinite-dimensional compressible vector spaces. We prove that if there are a sufficient number of separating points in compress

Khaled Ammar, Siddhartha Sahu, Semih Salihoglu, M. Tamer Ozsu

Differential computation (DC) is a highly general incremental computation/view maintenance technique that can maintain the output of an arbitrary and possibly recursive dataflow computation upon changes to its base inputs. As such, it is a promising technique for graph database management systems (GDBMS) that support continuous recursive queries over dynamic

Da Huo, Shuo Hua, Xue-Dong Tian, Yi-Mou Liu

We propose a theoretical scheme in a cold Rubidium-87 ($^{87}$Rb) atomic ensemble with a non-Hermitian optical structure, in which a lopsided optical diffraction grating can be realized just with the combination of single spatially periodic modulation and loop-phase.~Parity-time ($\mathcal{PT}$) symmetric and parity-time antisymmetric ($\mathcal{APT}$) modul