December 2023 arXiv papers — page 65

Q. M. Danish Lohani, Ashutosh Tiwari, Mohd Shoaib Khan

The definition of weighted distance measure involves weights. The paper proposes a weighted distance measure without the help of weights. Here, weights are intrinsically added to the measure, and for this, the concept of metric space is generalized based on a novel divided difference operator. The proposed operator is used over a two-dimensional sequence of

Luca Giorgetti, Wei Yuan, XuRui Zhao

Recently, S. Carpi et al. (Comm. Math. Phys., 402:169-212, 2023) proved that every connected (i.e. haploid) Frobenius algebra in a tensor C$^*$-category is unitarizable (i.e. isomorphic to a special C$^*$-Frobenius algebra). Building on this result, we extend it to the non-connected case by showing that an algebra in a multitensor C$^*$-category is unitariza

Gregor Häfner, Marcus Müller

The cellular environment, characterized by its intricate composition and spatial organization, hosts a variety of organelles, ranging from membrane-bound ones to membraneless structures that are formed through liquid-liquid phase separation. Cells show precise control over the position of such condensates. We demonstrate that organelle movement in external c

Dario Lucente, Marco Baldovin, Andrea Puglisi, Angelo Vulpiani

Random exchange kinetic models are widely employed to describe the conservative dynamics of large interacting systems. Due to their simplicity and generality, they are quite popular in several fields, from statistical mechanics to biophysics and economics. Here we study a version where bounds on the individual shares of the globally conserved quantity are in

Md. Rafiul Biswas, Farida Mohsen, Zubair Shah, Wajdi Zaghouani

This study evaluates ChatGPT's performance in annotating vaccine-related Arabic tweets by comparing its annotations with human annotations. A dataset of 2,100 tweets representing various factors contributing to vaccine hesitancy was examined. Two domain experts annotated the data, with a third resolving conflicts. ChatGPT was then employed to annotate the sa

Yibo Wang, Tingui Wang, Ning Jiang, Xiaer Zhang

We re-examined the classification of the optical transient ASASSN-18ap, which was initially identified as a supernova (SNe) upon its discovery. Based on newly emerged phenomena, such as a delayed luminous infrared outburst and the emergence of luminous coronal emission lines, we suggest that ASASSN-18ap is more likely a tidal disruption event (TDE) in a dust

Wouter Groeneveld, Laurens Luyten, Joost Vennekens, Kris Aerts

Creativity is a critical skill that professional software engineers leverage to tackle difficult problems. In higher education, multiple efforts have been made to spark creative skills of engineering students. However, creativity is a vague concept that is open to interpretation. Furthermore, studies have shown that there is a gap in perception and implement

Subhankar Mondal

This paper is concerned with recovering the solution of a final value problem associated with a parabolic equation involving a non linear source and a non-local term, which to the best of our knowledge has not been studied earlier. It is shown that the considered problem is ill-posed, and thus, some regularization method has to be employed in order to obtain

Yuxiang Wang, Yuxiang Zeng, Yi Xu, Zimu Zhou

Federated Trajectory Matching (FTM) is gaining increasing importance in big trajectory data analytics, supporting diverse applications such as public health, law enforcement, and emergency response. FTM retrieves trajectories that match with a query trajectory from a large-scale trajectory database, while safeguarding the privacy of trajectories in both the

Manjil P. Saikia, Abhishek Sarma, James A. Sellers

Recently, Drema and Saikia (2023) proved several congruences modulo powers of 2 and 3 for overpartition triples with odd parts. We extend their list substantially. We prove several congruences modulo powers of 2 for overpartition k-tuples with odd parts, along with a few infinite families of congruences for overpartition triples with odd parts and for overpa

Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano, Mattia Panettiere

Categorization is one of the basic tasks in machine learning and data analysis. Building on formal concept analysis (FCA), the starting point of the present work is that different ways to categorize a given set of objects exist, which depend on the choice of the sets of features used to classify them, and different such sets of features may yield better or w

Wasu Top Piriyakulkij, Volodymyr Kuleshov, Kevin Ellis

Actively inferring user preferences, for example by asking good questions, is important for any human-facing decision-making system. Active inference allows such systems to adapt and personalize themselves to nuanced individual preferences. To enable this ability for instruction-tuned large language models (LLMs), one may prompt them to ask users questions t

Celina K Gehringer, Glen P Martin, Ben Van Calster, Kimme L Hyrich

Multinomial prediction models (MPMs) have a range of potential applications across healthcare where the primary outcome of interest has multiple nominal or ordinal categories. However, the application of MPMs is scarce, which may be due to the added methodological complexities that they bring. This article provides a guide of how to develop, externally valid

Valeriy G. Bardakov, Tatyana A. Kozlovskaya, Dmitry V. Talalaev

The principal aim of this article is to introduce and study n-valued quandles and n-corack bialgebras. We elaborate the basic methods of this theory, reproduce the coset construction known in the theory of n-valued groups. We also consider a construction of n-valued quandles using n-multi-quandles. In contrast to the case of n-valued groups this construction

Md. Rafiul Biswas, Ashhadul Islam, Zubair Shah, Wajdi Zaghouani

The advanced large language model (LLM) ChatGPT has shown its potential in different domains and remains unbeaten due to its characteristics compared to other LLMs. This study aims to evaluate the potential of using a fine-tuned ChatGPT model as a personal medical assistant in the Arabic language. To do so, this study uses publicly available online questions

Pramod Bhakuni, Marian Krajčí, Sudipta Roy Barman

Using scanning tunneling microscopy (STM), low energy electron diffraction (LEED), and density functional theory (DFT), we demonstrate the formation of quasicrystalline gallium adlayer on icosahedral ($i$)-Al-Pd-Mn. Quasiperiodic motifs are evident in the STM topography images, including the Ga white flower (GaWF) and $\tau$ inflated GaWF ($\tau$-GaWF), wher

M. Bayar, R. Molina, E. Oset, Ming-Zhu Liu

We address a general problem in the evaluation of triangle loops stemming from the consideration of the range of the interaction involved in some of the vertices, as well as the energy dependence of the width of some unstable particles in the loop. We find sizeable corrections from both effects. We apply that to a loop relevant to the $D_s^+ \to \pi^+ \pi^0

Egide Ndamuzi, Rachel Akimana, Paterne Gahungu, Elie Bimenyimana

Air pollution is a result of multiple sources including both natural and anthropogenic activities. The rapid urbanization of the cities such as Bujumbura economic capital of Burundi, is one of these factors. The very first characterization of the spatio-temporal variability of PM2.5 in Bujumbura and the forecasting of PM2.5 concentration have been conducted

Georgian-Vlad Saioc, Dmitriy Shirchenko, Milind Chabbi

Go is a modern programming language gaining popularity in enterprise microservice systems. Concurrency is a first-class citizen in Go with lightweight ``goroutines'' as the building blocks of concurrent execution. Go advocates message-passing to communicate and synchronize among goroutines. Improper use of message passing in Go can result in ``partial deadlo

Keshav Kumar, Shrawan K. Mishra, Sanjay Singh, Ivan Baev

The magnetic ground state of BaFe12O19 (BFO) was investigated using X-ray absorption at 1.2 K and 1.5 K, respectively. The XMCD measurements on single-crystals of BFO in grazing incidence geometry reveal the canting of the spins away from the c-axis of the hexagonal unit cell. Single-crystal neutron diffraction studies reveal magnetic satellite peaks along t

Leander van den Heuvel, Gertjan Burghouts, David W. Zhang, Gwenn Englebienne

For object detection, it is possible to view the prediction of bounding boxes as a reverse diffusion process. Using a diffusion model, the random bounding boxes are iteratively refined in a denoising step, conditioned on the image. We propose a stochastic accumulator function that starts each run with random bounding boxes and combines the slightly different

Yan-Xi Zhang, Qi Lin, Xiao-Qiang Yan, Ling-Ling Wang

Many applications involve the phenomenon of a material absorbing electromagnetic radiation. By exploiting wave interference, the efficiency of absorption can be significantly enhanced. Here, we propose Friedrich-Wintgen bound states in the continuum (F-W BICs) based on borophene metamaterials to realize coherent perfect absorption with a dual-band absorption

Valentin Boyanov, Vitor Cardoso, Kyriakos Destounis, José Luis Jaramillo

Black holes in anti-de Sitter spacetime provide an important testing ground for both gravitational and field-theoretic phenomena. In particular, the study of perturbations can be useful to further our understanding regarding certain physical processes, such as superradiance, or the dynamics of strongly coupled conformal field theories through the holographic

Zhuowei Zhang, Mengting Hu, Yinhao Bai, Zhen Zhang

Mind-map generation aims to process a document into a hierarchical structure to show its central idea and branches. Such a manner is more conducive to understanding the logic and semantics of the document than plain text. Recently, a state-of-the-art method encodes the sentences of a document sequentially and converts them to a relation graph via sequence-to

Eva Thelisson, Grzegorz Mika, Quentin Schneiter, Kirtan Padh

As AI/ML models, including Large Language Models, continue to scale with massive datasets, so does their consumption of undeniably limited natural resources, and impact on society. In this collaboration between AI, Sustainability, HCI and legal researchers, we aim to enable a transition to sustainable AI development by enabling stakeholders across the AI val

Haojie Xu, Xia Wu, Wei Lu, Xiwang Cao

In this paper, the sufficient and necessary condition for the minimum distance of the BCH codes over $\mathbb{F}_q$ with length $q+1$ and designed distance 3 to be 3 and 4 are provided. Let $d$ be the minimum distance of the BCH code $\mathcal{C}_{(q,q+1,3,h)}$. We prove that (1) for any $q$, $d=3$ if and only if $\gcd(2h+1,q+1)>1$; (2) for $q$ odd, $d=4$ if

Korrawe Karunratanakul, Konpat Preechakul, Emre Aksan, Thabo Beeler

We propose Diffusion Noise Optimization (DNO), a new method that effectively leverages existing motion diffusion models as motion priors for a wide range of motion-related tasks. Instead of training a task-specific diffusion model for each new task, DNO operates by optimizing the diffusion latent noise of an existing pre-trained text-to-motion model. Given t

R. Molina, Zhi-Wei Liu, Li-Sheng Geng, E. Oset

We have conducted a model independent analysis of the $K^+ \bar{K}^0$ pair correlation function obtained from ultra high energy $pp$ collisions, with the aim of extracting the information encoded in it related to the $K\bar{K}$ interaction and the coupled channel $\pi^+ \eta$. With the present large errors at small relative $K^+\bar{K}^0$ momenta, we find th

Juan Carlos Gonzalez-Rosillo, Maxim Guc, Maciej Oskar Liedke, Maik Butterling

LiMn2O4 (LMO), cathodes present large stability when cycled in aqueous electrolytes, contrasting its behavior in conventional organic electrolytes in Lithium-ion batteries (LIBs). To elucidate the mechanisms underlying this distinctive behavior, we employ unconventional characterization techniques, including Variable Energy Positron Annihilation Lifetime Spe

Stefanie von Felten, Chiara Vanetta, Christoph M. Rüegger, Sven Wellmann

Continuous outcome measurements truncated by death present a challenge for the estimation of unbiased treatment effects in randomized controlled trials (RCTs). One way to deal with such situations is to estimate the survivor average causal effect (SACE), but this requires making non-testable assumptions. Motivated by an ongoing RCT in very preterm infants wi

Keshav Kumar, Shrawan Kumar Mishra, Ivan Baev, Michael Martins

We present here the results of low-temperature magnetization and X-ray magnetic circular dichroism studies on single crystals of BaFe12O19 which reveal for the first time the emergence of a spin glass phase, in coexistence with the long-range ordered ferrimagnetic phase, due to the freezing of the basal plane spin component.

Tomas Stolker, Jens Kammerer, Myriam Benisty, Dori Blakely

Transition disks have large central cavities that have been spatially resolved during recent years. Cavities and other substructures in circumstellar disks are often interpreted as signposts to massive companions. We aim to search for stellar and substellar companions in the central regions of transition disks. We want to determine if these disks might be ci

Ruixin Ding, Bowei Chen, James M. Wilson, Zhi Yan

The automotive industry plays a critical role in the global economy, and particularly important is the expanding Chinese automobile market due to its immense scale and influence. However, existing automotive sector datasets are limited in their coverage, failing to adequately consider the growing demand for more and diverse variables. This paper aims to brid

Yuxuan Jiang, Chaoyun Zhang, Shilin He, Zhihao Yang

Large-scale cloud systems play a pivotal role in modern IT infrastructure. However, incidents occurring within these systems can lead to service disruptions and adversely affect user experience. To swiftly resolve such incidents, on-call engineers depend on crafting domain-specific language (DSL) queries to analyze telemetry data. However, writing these quer

Ting-Hsiang Hsu

A search is presented for new Higgs bosons, targeting proton-proton (pp) collision events with a same-sign top quark pair associated with an extra jet via the processes pp$\rightarrow tH/A \rightarrow tt\bar{c}$ and pp$\rightarrow tH/A \rightarrow tt\bar{u}$, where H and A represent exotic scalar and pseudoscalar bosons, respectively. The study is based on d

Hugo Roussille, David Langlois, Karim Noui

We present a novel approach to the numerical computation of quasi-normal modes, based on the first-order (in radial derivative) formulation of the equations of motion and using a matrix version of the continued fraction method. This numerical method is particularly suited to the study of static black holes in modified gravity, where the traditional second-or

Hongyin Zhu, Prayag Tiwari

Climate change poses grave challenges, demanding widespread understanding and low-carbon lifestyle awareness. Large language models (LLMs) offer a powerful tool to address this crisis, yet comprehensive evaluations of their climate-crisis knowledge are lacking. This paper proposes an automated evaluation framework to assess climate-crisis knowledge within LL

Shunshun Cao, Jinchen Jiang, Jaroslaw Dyks, Longfei Hao

As one of the paradigm examples to probe into pulsar magnetospheric dynamics, PSR B0943+10 (J0946+0951) manifests representatively, showing mode switch, orthogonal polarization and subpulse drifting, frequently studied below 600 MHz. Here both integrated and single pulses are studied at a high frequency (1.25 GHz) with FAST. The mode switch is studied using

Yongqi An, Xu Zhao, Tao Yu, Ming Tang

Network Pruning is a promising way to address the huge computing resource demands of the deployment and inference of Large Language Models (LLMs). Retraining-free is important for LLMs' pruning methods. However, almost all of the existing retraining-free pruning approaches for LLMs focus on unstructured pruning, which requires specific hardware support for a

Hai-Long Huang, Yun-Song Piao

The bubbles that nucleated during slow-roll inflation can be supercritical, i.e. their radii are larger than the Hubble horizon of de Sitter spacetime inside the bubble (an inflating baby universe inside it), and thus naturally develop to the supermassive primordial black holes (SMPBHs) with a multi-peaks mass function. In this paper, we further investigate

Karl Kunisch, Donato Vásquez-Varas

In this work the synthesis of approximate optimal and smooth feedback laws for infinite horizon optimal control problems is addressed. In this regards, $L^{p}$ type error bounds of the approximating smooth feedback laws are derived, depending on either the $C^1$ norm of the value function or its semi-concavity. These error bounds combined with the existence

Jadupati Nag, Bishal Das, Sayantika Bhowal, Yukimi Nishioka

Spintronics has emerged as a viable alternative to traditional electronics based technologies in the past few decades. While on one hand, the discovery of topological phases of matter with protected spin-polarized states has opened up exciting prospects, recent revelation of intriguing non-relativistic spin splitting in collinear antiferromagnetic materials

William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu

Sparse recovery is ubiquitous in machine learning and signal processing. Due to the NP-hard nature of sparse recovery, existing methods are known to suffer either from restrictive (or even unknown) applicability conditions, or high computational cost. Recently, iterative regularization methods have emerged as a promising fast approach because they can achiev

Kwangrae Kim, Hyun-Woo J. Kim, Seunghyeok Ha, Hoon Kim

Chirality is a ubiquitous phenomenon in which a symmetry between left- and right-handed objects is broken, examples in nature ranging from subatomic particles and molecules to living organisms. In particle physics, the weak force is responsible for the symmetry breaking and parity violation in beta decay, but in condensed matter systems interactions that lea

Ole Christensen, Marzieh Hasannasab, Friedrich Philipp, Diana Stoeva

In 2016 Aldroubi et al. constructed the first class of frames having the form $\{T^k\varphi \}_{k=0}^\infty$ for a bounded linear operator on the underlying Hilbert space. In this paper we show that a subclass of these frames has a number of additional remarkable features that have not been identified for any other frames in the literature. Most importantly,

Sougata Biswas, Arunava Chakrabarti

We study quantum dynamics of a wave packet on a class of one dimensional decorated aperiodic lattices, described within a tight binding formalism. We look for the possibility of finding extended single particle states even in the absence of any translational periodicity. The chosen lattices are stubbed with one or more atoms, tunnel coupled to the backbone,

Dongmin Kim, Sunghyun Park, Jaegul Choo

Time-series anomaly detection deals with the problem of detecting anomalous timesteps by learning normality from the sequence of observations. However, the concept of normality evolves over time, leading to a "new normal problem", where the distribution of normality can be changed due to the distribution shifts between training and test data. This paper high

Xinyu Wang, Vinod K. Mishra, C. -C. Jay Kuo

AI algorithms at the edge demand smaller model sizes and lower computational complexity. To achieve these objectives, we adopt a green learning (GL) paradigm rather than the deep learning paradigm. GL has three modules: 1) unsupervised representation learning, 2) supervised feature learning, and 3) supervised decision learning. We focus on the second module

J. Pawlowski, M. Panfil, J. Herbrych, M. Mierzejewski

Relaxation rates in nearly integrable systems usually increase quadratically with the strength of the perturbation that breaks integrability. We show that the relaxation rates can be significantly smaller in systems that are integrable along two intersecting lines in the parameter space. In the vicinity of the intersection point, the relaxation rates of cert

Mengbo Li, Yuanzhong Zheng, Dichucheng Li, Yulun Wu

Speech Emotion Recognition (SER) has become a growing focus of research in human-computer interaction. Spatiotemporal features play a crucial role in SER, yet current research lacks comprehensive spatiotemporal feature learning. This paper focuses on addressing this gap by proposing a novel approach. In this paper, we employ Convolutional Neural Network (CNN

Haeyong Kang, Jaehong Yoon, Sung Ju Hwang, Chang D. Yoo

Inspired by the Lottery Ticket Hypothesis (LTH), which highlights the existence of efficient subnetworks within larger, dense networks, a high-performing Winning Subnetwork (WSN) in terms of task performance under appropriate sparsity conditions is considered for various continual learning tasks. It leverages pre-existing weights from dense networks to achie

Pengxiang Ding, Qiongjie Cui, Min Zhang, Mengyuan Liu

Human motion forecasting, with the goal of estimating future human behavior over a period of time, is a fundamental task in many real-world applications. However, existing works typically concentrate on predicting the major joints of the human body without considering the delicate movements of the human hands. In practical applications, hand gesture plays an

William Borrelli, Michele Correggi, Davide Fermi

We study a two-dimensional Pauli operator describing a charged quantum particle with spin $1/2$ moving on a plane in presence of an orthogonal Aharonov-Bohm magnetic flux. We classify all the admissible self-adjont realizations and give a complete picture of their spectral and scattering properties. Symmetries of the resulting Hamiltonians are also discussed

Chen Gao, Xiaochong Lan, Nian Li, Yuan Yuan

Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Integrating large language models into agent-based modeling and simulation presents a promising avenue for enhancing simulation capabilities. This paper surveys the landscape of util

Anubha Pandey, Aditi Rai, Maneet Singh, Deepak Bhatt

Recent research has identified discriminatory behavior of automated prediction algorithms towards groups identified on specific protected attributes (e.g., gender, ethnicity, age group, etc.). When deployed in real-world scenarios, such techniques may demonstrate biased predictions resulting in unfair outcomes. Recent literature has witnessed algorithms for

Ru-Ting Sun, Mei-Yu Peng, Tian-Xiang Lu, Ya-Feng Jiao

We propose to achieve a multi-color nonreciprocal optical amplifier, a crucial device in optical communication and information processing, by spinning an active resonator. We show that in such a device, due to the interplay of the Sagnac effect and the optical gain, nonreciprocal signal {amplification} can be realized, accompanied by a giant enhancement of o

Wei Tang, Liang Li, Xuejing Liu, Lu Jin

Visual grounding (VG) aims to locate a specific target in an image based on a given language query. The discriminative information from context is important for distinguishing the target from other objects, particularly for the targets that have the same category as others. However, most previous methods underestimate such information. Moreover, they are usu

Alberto Carpentieri, Doris Folini, Jussi Leinonen, Angela Meyer

Surface solar irradiance (SSI) plays a crucial role in tackling climate change - as an abundant, non-fossil energy source, exploited primarily via photovoltaic (PV) energy production. With the growing contribution of SSI to total energy production, the stability of the latter is challenged by the intermittent character of the former, arising primarily from c

Takuya Agemura, Yukinari Sumino

For the heavy quarkonium system we examine ${\cal O}(\Lambda_{\rm QCD}^2/m)$ renormalons, which are expected to be included in the perturbative series of the pole mass and $1/(mr^2)$ interquark potential. We find indications of existence and cancellation of these renormalons, from examinations of stability and convergence properties of the perturbative serie

Anthony Gauvan

Given a sequence of random variables $\left\{ X_k : k \geq 1\right\}$ uniformly distributed in $(0,1)$ and independent, we consider the following random sets of directions $$\Omega_{\text{rand},\text{lin}} := \left\{ \frac{\pi X_k}{k}: k \geq 1\right\}$$ and $$\Omega_{\text{rand},\text{lac}} := \left\{ \frac{ \pi X_k}{2^k} : k\geq 1 \right\}.$$ We prove that

Zhidan Feng, Henning Fernau, Kevin Mann

In this paper, we study the task of enumerating (and counting) locally and globally minimal defensive alliances in graphs. We consider general graphs as well as special graph classes. From an input-sensitive perspective, our presented algorithms are mostly optimal.

Bharti Bharti, Andreas Carlson, Tak Shing Chan, Thomas Salez

We theoretically study the Plateau-Rayleigh instability of a thin viscous film covering a fiber consisting of a rigid cylindrical core coated with a thin compressible elastic layer. We develop a soft-lubrication model, combining the capillary-driven flow in the viscous film to the elastic deformation of the soft coating, within the Winkler-foundation framewo

Qian Xiao, Oleg Janson, Sonia Francoual, Qingzheng Qiu

Chiral phases of matter, characterized by a definite handedness, abound in nature, ranging from the crystal structure of quartz to spiraling spin states in helical magnets. In $1T$-TiSe$_2$ a source of chirality has been proposed that stands apart from these classical examples as it arises from combined electronic charge and quantum orbital fluctuations. Thi

Zhidan Feng, Henning Fernau, Kevin Mann, Xingqin Qi

Signed graphs have been introduced to enrich graph structures expressing relationships between persons or general social entities, introducing edge signs to reflect the nature of the relationship, e.g., friendship or enmity. Independently, offensive alliances have been defined and studied for undirected, unsigned graphs. We join both lines of research and de

Kewei Sun, Lauri Kurki, Orlando J. Silveira, Tomohiko Nishiuchi

Sila-cyclic rings are a class of organosilicon cyclic compounds and have abundant application in organic chemistry and materials science. However, it is still challenging to synthesize compounds with sila-cyclic rings in solution chemistry due to their low solubility and high reactivity. Recently, on-surface synthesis was introduced into organosilicon chemis

Ndolane Diouf, Cesar Vargas Anamuro, Cédric Gueguen, Massa Ndong

Energy is a major expense issue for mobile operators. In the case of wireless networks, base stations have been identified as the main source of energy consumption. In this paper, we study the energy consumption reduction problem based on real measurements for a commercial multi-band LTE network. Specifically, we are interested in sleep modes to turn off cer

Cesar Augusto Ipanaque Zapata, Daciberg Lima Gonçalves

Let $G$ be a finite group with order $|G|=\ell$ and $2\leq q\leq \ell$. For a free $G$-space $X$, we introduce a notion of $q$-th index of $(X,G)$, denoted by $\text{ind}_q(X,G)$. Our concept is relevant in the Borsuk-Ulam theory. We draw general estimates for the $q$-th index in terms of the sectional category of the quotient map $X\to X/G$, denoted by $\te

Fan Zhang, Shaodi You, Yu Li, Ying Fu

Monocular depth estimation has experienced significant progress on terrestrial images in recent years, largely due to deep learning advancements. However, it remains inadequate for underwater scenes, primarily because of data scarcity. Given the inherent challenges of light attenuation and backscattering in water, acquiring clear underwater images or precise

Kana Sakaguri, Masaya Hasegawa, Yuki Sakurai, Junna Sugiyama

We developed a broadband two-layer anti-reflection (AR) coating for use on a sapphire half-wave plate (HWP) and an alumina infrared (IR) filter for the cosmic microwave background (CMB) polarimetry. Measuring the faint CMB B-mode signals requires maximizing the number of photons reaching the detectors and minimizing spurious polarization due to reflection wi

Nan Jiang, Md Nasim, Yexiang Xue

Automating scientific discovery has been a grand goal of Artificial Intelligence (AI) and will bring tremendous societal impact. Learning symbolic expressions from experimental data is a vital step in AI-driven scientific discovery. Despite exciting progress, most endeavors have focused on the horizontal discovery paths, i.e., they directly search for the be

Huafeng Qin, Xin Jin, Yun Jiang, Mounim A. El-Yacoubi

Data mixing augmentation has been widely applied to improve the generalization ability of deep neural networks. Recently, offline data mixing augmentation, e.g. handcrafted and saliency information-based mixup, has been gradually replaced by automatic mixing approaches. Through minimizing two sub-tasks, namely, mixed sample generation and mixup classificatio

Xiaotie Deng, Hangxin Gan, Ningyuan Li, Weian Li

We investigate a two-stage competitive model involving multiple contests. In this model, each contest designer chooses two participants from a pool of candidate contestants and determines the biases. Contestants strategically distribute their efforts across various contests within their budget. We first show the existence of a pure strategy Nash equilibrium

Collin Leiber, Dominik Mautz, Claudia Plant, Christian Böhm

High-dimensional datasets often contain multiple meaningful clusterings in different subspaces. For example, objects can be clustered either by color, weight, or size, revealing different interpretations of the given dataset. A variety of approaches are able to identify such non-redundant clusterings. However, most of these methods require the user to specif

Jean-Christophe Aval

Complete non-ambiguous trees (CNATs) are combinatorial objects which appear in various contexts.Recently, Chen and Ohlig studied the notion of permutations associated to these objects, and proposed a series of nice conjectures.Most of them were proved by Selig and Zhu, through a connection with the abelian sandpile model.But one conjecture remained open, abo

Boumediène Chentouf, Aissa Guesmia, Mauricio A Sepulveda Cortes, Rodrigo Véjar

This article is intended to present a qualitative and numerical analysis of well-posedness and boundary stabilization problems of the well-known Korteweg-de Vries-Burgers equation. Assuming that the boundary control is of memory type, the history approach is adopted in order to deal with the memory term. Under sufficient conditions on the physical parameters

DaEun Choi, Sumin Hong, Jeongeon Park, John Joon Young Chung

Graphic designers often get inspiration through the recombination of references. Our formative study (N=6) reveals that graphic designers focus on conceptual keywords during this process, and want support for discovering the keywords, expanding them, and exploring diverse recombination options of them, while still having room for designers' creativity. We pr

Ernesto Lopez Fune

In this article we offer a comprehensive analysis of the Urysohn's classifier in a binary classification context. It utilizes Urysohn's Lemma of Topology to construct separating functions, providing rigorous and adaptable solutions. Numerical experiments demonstrated exceptional performance, with scores ranging from 95% to 100%. Notably, the Urysohn's classi

Rui Liu, Yifan Hu, Yi Ren, Xiang Yin

Conversational Speech Synthesis (CSS) aims to accurately express an utterance with the appropriate prosody and emotional inflection within a conversational setting. While recognising the significance of CSS task, the prior studies have not thoroughly investigated the emotional expressiveness problems due to the scarcity of emotional conversational datasets a

Blake C. Stacey

I review some recent technical developments in quantum information theory by rephrasing them in the form of exercises.

Haowei Du, Dinghao Zhang, Chen Li, Yang Li

Recent approaches in Incomplete Utterance Rewriting (IUR) fail to capture the source of important words, which is crucial to edit the incomplete utterance, and introduce words from irrelevant utterances. We propose a novel and effective multi-task information interaction framework including context selection, edit matrix construction, and relevance merging t

Huairui Chu, Bingkai Lin

Treewidth is a useful tool in designing graph algorithms. Although many NP-hard graph problems can be solved in linear time when the input graphs have small treewidth, there are problems which remain hard on graphs of bounded treewidth. In this paper, we consider three vertex selection problems that are W[1]-hard when parameterized by the treewidth of the in

Aamal Hussain, Francesco Belardinelli

The behaviour of multi-agent learning in competitive network games is often studied within the context of zero-sum games, in which convergence guarantees may be obtained. However, outside of this class the behaviour of learning is known to display complex behaviours and convergence cannot be always guaranteed. Nonetheless, in order to develop a complete pict

Matthew Bone, Eugenia Ehlinger, Fabian Stephany

Emerging professions in fields like Artificial Intelligence (AI) and sustainability (green jobs) are experiencing labour shortages as industry demand outpaces labour supply. In this context, our study aims to understand whether employers have begun focusing more on individual skills rather than formal qualifications in their recruitment processes. We analyse

Giacomo Passetti, Dante M. Kennes

Despite the huge theoretical potential of neural quantum states, their use in describing generic, highly-correlated quantum many-body systems still often poses practical difficulties. Customized network architectures are under active investigation to address these issues. For a guided search of suited network architectures a deepened understanding of the lin

Yukino Mori, Yota Nakayama, Kazuhiro Yamamoto, Takafumi Ushiba

We measured the mechanical loss of a dielectric multilayer reflective coating (ion-beam-sputtered SiO2 and Ta2O5) with and without TiO2 on sapphire disks between 6 and 77 K. The measured loss angle exhibited a temperature dependence, and the local maximum was found at approximately 20 K. This maximum was 7.0*10^(-4) (with TiO2) and 7.7*10^(-4) (without TiO2)

Xiyuan Jin, Jing Wang, Lei Liu, Youfang Lin

As an exemplary self-supervised approach for representation learning, time-series contrastive learning has exhibited remarkable advancements in contemporary research. While recent contrastive learning strategies have focused on how to construct appropriate positives and negatives, in this study, we conduct theoretical analysis and find they have overlooked t

Yuang Liu, Jing Wang, Qiang Zhou, Fan Wang

Numerous self-supervised learning paradigms, such as contrastive learning and masked image modeling, have been proposed to acquire powerful and general representations from unlabeled data. However, these models are commonly pretrained within their specific framework alone, failing to consider the complementary nature of visual representations. To tackle this

Len Brandes, Wolfram Weise

Recent inference results of the sound velocity in the cores of neutron stars are summarized. Implications for the equation of state and the phase structure of highly compressed baryonic matter are discussed. In view of the strong constraints imposed by the heaviest known pulsars, the equation of state must be very stiff in order to ensure the stability of th

Jessie Galasso-Carbonnel, Chico Sundermann

This is the proceedings of the Sixth International Workshop on Languages for Modelling Variability (MODEVAR 2024) which was held at Bern, Switzerland, February 06th 2024.

Mohimenul Kabir, Supratik Chakraborty, Kuldeep S Meel

Answer Set Programming (ASP) has emerged as a promising paradigm in knowledge representation and automated reasoning owing to its ability to model hard combinatorial problems from diverse domains in a natural way. Building on advances in propositional SAT solving, the past two decades have witnessed the emergence of well-engineered systems for solving the an

Yuyang Xia, Shuncheng Liu, Quanlin Yu, Liwei Deng

Autonomous driving is an emerging technology that has advanced rapidly over the last decade. Modern transportation is expected to benefit greatly from a wise decision-making framework of autonomous vehicles, including the improvement of mobility and the minimization of risks and travel time. However, existing methods either ignore the complexity of environme

Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao

Causal discovery with latent variables is a crucial but challenging task. Despite the emergence of numerous methods aimed at addressing this challenge, they are not fully identified to the structure that two observed variables are influenced by one latent variable and there might be a directed edge in between. Interestingly, we notice that this structure can

Yujie Li, Zezhi Shao, Yongjun Xu, Qiang Qiu

Complex spatial dependencies in transportation networks make traffic prediction extremely challenging. Much existing work is devoted to learning dynamic graph structures among sensors, and the strategy of mining spatial dependencies from traffic data, known as data-driven, tends to be an intuitive and effective approach. However, Time-Shift of traffic patter

Giannis Tyrovolas, Andrei Constantinescu, Edith Elkind

We consider binary group decision-making under a rich model of liquid democracy recently proposed by Colley, Grandi, and Novaro (2022): agents submit ranked delegation options, where each option may be a function of multiple agents' votes; e.g., "I vote yes if a majority of my friends vote yes." Such ballots are unravelled into a profile of direct votes by s

Fernand Pelletier, Patrick Cabau

Let $p_E : E \to M$ be a fibre bundle over the $m$-dimensional manifold $M$ whose typical fibre is the vector space $\R^e$ and let $p_F : F \to N$ be a fibre bundle over the $n$-dimensional manifold $N$ whose typical fibre is the vector space $\R^f$. We are interested in the structure of the set $\Morph(E,F)$ of smooth linear bundle morphisms $\Phi : E \to F

Xiaodong Shao, Bin Zhang, Hui Zhi, Jose Guadalupe Romero

In this article, we propose a novel approach, called InPTC (Integrated Planning and Tube-Following Control), for prescribed-time collision-free navigation of wheeled mobile robots in a compact convex workspace cluttered with static, sufficiently separated, and convex obstacles. A path planner with prescribed-time convergence is presented based upon Bouligand

Hamza Mukhtar, Muhammad Usman Ghani Khan

Multi-object tracking (MOT) has profound applications in a variety of fields, including surveillance, sports analytics, self-driving, and cooperative robotics. Despite considerable advancements, existing MOT methodologies tend to falter when faced with non-uniform movements, occlusions, and appearance-reappearance scenarios of the objects. Recognizing this i

Sihan Liu, Yiwei Ma, Xiaoqing Zhang, Haowei Wang

Referring Remote Sensing Image Segmentation (RRSIS) is a new challenge that combines computer vision and natural language processing, delineating specific regions in aerial images as described by textual queries. Traditional Referring Image Segmentation (RIS) approaches have been impeded by the complex spatial scales and orientations found in aerial imagery,

Alexandru Dimca, Gabriel Sticlaru

G\"unter Ziegler has shown in 1989 that some homological invariants associated with the free resolutions of Jacobian ideals of line arrangements are not determined by combinatorics. His classical example involves hexagons inscribed in conics. Independently, Sergey Yuzvinsky has arrived in 1993 at the same type of line arrangements in order to show that forma

Pengwei Yan, Kaisong Song, Zhuoren Jiang, Yangyang Kang

While self-supervised graph pretraining techniques have shown promising results in various domains, their application still experiences challenges of limited topology learning, human knowledge dependency, and incompetent multi-level interactions. To address these issues, we propose a novel solution, Dual-level Graph self-supervised Pretraining with Motif dis