April 2023 arXiv papers — page 54

Florin Ciucu, Sima Mehri

When the arrival processes are Poisson, queueing networks are well-understood in terms of the product-form structure of the number of jobs $N_i$ at the individual queues; much less is known about the waiting time $W$ across the whole network. In turn, for non-Poisson arrivals, little is known about either $N_i$'s or $W$. This paper considers a tandem network

Frédéric Campana, Andreas Höring, Thomas Peternell

In this text we signal a serious gap in the proof of the main theorem of our paper and explain which parts of the statement remain valid. In fact, the main theorem remains valid unless possibly the variety does not admit positive-dimensional subvarieties through a very general point and is not bimeromorphic to a quotient of a torus. This latter case would be

Mohsen Khorasani, Moein Mosleh, Ahmad Sheykhi

We use parameterized post-Friedmann (PPF) description for dark energy and apply ellipsoidal nested sampling to perform the Bayesian model selection method on different time-dependent dark energy models using a combination of $Planck$ and data based on distance measurements, namely baryon acoustic oscillations and supernovae luminosity distance. Models with t

Hao-Yuan Chen, Yen-Jui Chang, Shih-Wei Liao, Ching-Ray Chang

Quantum computing holds great potential for advancing the limitations of machine learning algorithms to handle higher dimensions of data and reduce overall training parameters in deep learning (DL) models. This study uses a trainable variational quantum circuit (VQC) on a gate-based quantum computing model to investigate the potential for quantum benefit in

Verena Blaschke, Hinrich Schütze, Barbara Plank

One of the challenges with finetuning pretrained language models (PLMs) is that their tokenizer is optimized for the language(s) it was pretrained on, but brittle when it comes to previously unseen variations in the data. This can for instance be observed when finetuning PLMs on one language and evaluating them on data in a closely related language variety w

Hang Li, Derong Qiu

In this paper, a new criterion is given to determine the $p-$rationality of some complex cubic number fields in terms of $ p-$divisibility of certain terms of a third-order recurrence sequence, several illustrated examples are constructed,the relations between generalized $ abc-$conjecture and the $p-$rationality are discussed, from which some explicit field

B Kartik, Manimaran P

One of the most important parts of business, especially in the coal mining sector, is industrial safety. Suffocation, gas poisoning, object falls, roof collapses, and gas explosions are among the risks associated with underground mining. Therefore, air quality and the detection of hazardous events are crucial in the mining business. This technology offers a

Sunjin Choi, Seok Kim, Eunwoo Lee, Siyul Lee

We study the cohomology of local BPS operators in $\mathcal{N}=4$ Yang-Mills theory. The finite $N$ cohomologies consist of the graviton part (subject to the stringy exclusion principle) and the rest which may describe black hole microstates in quantum AdS/CFT. We construct an infinite tower of non-graviton cohomologies in the $SU(2)$ theory and study to wha

Abdul Salam Rasmi Asraf Ali, Andrea Fusiello, Claudio Landi, Cristina Sarti

Cone Beam Computed Tomography (CBCT) is widely used in dentistry for diagnostics and treatment planning. CBCT Imaging has a long acquisition time and consequently, the patient is likely to move. This motion causes significant artifacts in the reconstructed data which may lead to misdiagnosis. Existing motion correction algorithms only address this issue part

Laura Cabello, Anna Katrine Jørgensen, Anders Søgaard

The societal impact of pre-trained language models has prompted researchers to probe them for strong associations between protected attributes and value-loaded terms, from slur to prestigious job titles. Such work is said to probe models for bias or fairness-or such probes 'into representational biases' are said to be 'motivated by fairness'-suggesting an in

Quan Zhou, Yicheng Liu, Shu-Lin Wu

We present the Parareal-CG algorithm for time-dependent differential equations in this work. The algorithm is a parallel in time iteration algorithm utilizes Chebyshev-Gauss spectral collocation method for fine propagator F and backward Euler method for coarse propagator G. As far as we know, this is the first time that the spectral method used as the F prop

Philipp Müller

The K Nearest Neighbors (KNN) classifier is widely used in many fields such as fingerprint-based localization or medicine. It determines the class membership of unlabelled sample based on the class memberships of the K labelled samples, the so-called nearest neighbors, that are closest to the unlabelled sample. The choice of K has been the topic of various s

Yan Feng, Dorine C. Duives

This paper proposes a comprehensive approach for modeling pedestrian wayfinding behavior in complex buildings. This study employs two types of discrete choice models (i.e., MNL and PSL) featuring pedestrian route choice behavior, and three multivariate linear regression (MLR) models featuring the overall wayfinding performance and observation behavior (e.g.,

Muzammil Mushtaq, Daniel Ceverino, Ralf S. Klessen, Stefan Reissl

We study the behavior of dust in galaxies at cosmic dawn, z=6-8, by coupling the FirstLight simulations with the radiative transfer code POLARIS. The starburst nature of these galaxies and their complex distribution of dust lead to a large diversity of attenuation curves. These follow the Calzetti model only for relatively massive galaxies, Mstars=10^9Msun.

Junling Liu, Chao Liu, Peilin Zhou, Renjie Lv

Recommendation systems have witnessed significant advancements and have been widely used over the past decades. However, most traditional recommendation methods are task-specific and therefore lack efficient generalization ability. Recently, the emergence of ChatGPT has significantly advanced NLP tasks by enhancing the capabilities of conversational models.

Daniel Wigger, Johannes Schall, Marielle Deconinck, Nikolai Bart

Semiconductor quantum dot molecules are considered as promising candidates for quantum technological applications due to their wide tunability of optical properties and coverage of different energy scales associated with charge and spin physics. While previous works have studied the tunnel-coupling of the different excitonic charge complexes shared by the tw

Qi Qin, Yankai Rong, Guoshun Nan, Shaokang Wu

Deep learning based semantic communication(DLSC) systems have shown great potential of making wireless networks significantly more efficient by only transmitting the semantics of the data. However, the open nature of wireless channel and fragileness of neural models cause DLSC systems extremely vulnerable to various attacks. Traditional wireless physical lay

Misha Bialy, Daniel Tsodikovich

In this work we consider variational properties of exact symplectic twist maps $T$ that act on the cotangent bundle of a torus, or on a ball bundle over a sphere. An example of such a map is the well-known Birkhoff billiard map corresponding to smooth convex hypersurfaces. In this work we will focus on the important class $\mathcal{M}$ of orbits of $T$ which

Yiming Zhu, Peixian Zhang, Ehsan-Ul Haq, Pan Hui

The release of ChatGPT has uncovered a range of possibilities whereby large language models (LLMs) can substitute human intelligence. In this paper, we seek to understand whether ChatGPT has the potential to reproduce human-generated label annotations in social computing tasks. Such an achievement could significantly reduce the cost and complexity of social

Yoshihiko Nishikawa, Werner Krauth, A. C. Maggs

We study the liquid--hexatic transition of soft disks with massively parallel simulations and determine the equation of state as a function of system size. For systems with interactions decaying as the inverse $m$th power of the separation, the liquid--hexatic phase transition is continuous for $m = 12$ and $m=8$, while it is of first order for $m = 24$. The

Taro Suzuki

A global navigation satellite system (GNSS) is a sensor that can acquire 3D position and velocity in an earth-fixed coordinate system and is widely used for outdoor position estimation of robots and vehicles. Various GNSS/inertial measurement unit (IMU) integration methods have been proposed to improve the accuracy and availability of GNSS positioning. Howev

Sabrine Chebbi, Václav Mácha, Šárka Nečasová

We are concerned with a one dimensional flow of a compressible fluid which may be seen as a simplification of the flow of fluid in a long thin pipe. We assume that the pipe is on one side ended by a spring. The other side of the pipe is let open -- there we assume either inflow or outflow boundary conditions. Such situation can be understood as a toy model f

Wojciech Ciezobka, Maksymilian Wojnar, Katarzyna Kosek-Szott, Szymon Szott

Data rate selection algorithms for Wi-Fi devices are an important area of research because they directly impact performance. Most of the proposals are based on measuring the transmission success probability for a given data rate. In dense scenarios, however, this probing approach will fail because frame collisions are misinterpreted as erroneous data rate se

Róbert Juhász

Motivated by long-range dispersal in ecological systems, we formulate and apply a general strong-disorder renormalization group (SDRG) framework to describe one-dimensional disordered contact processes with heavy-tailed, such as power law, stretched exponential, and log-normal dispersal kernels, widely used in ecology. The focus is on the close-to-critical s

Jayanand Maurya, Y. C. Joshi, Manash Ranjan Samal, Vineet Rawat

We present the dynamical evolution of ten open clusters which were part of our previous studies. These clusters include both young and intermediate-age open clusters with ages ranging from 25$\pm$19 Myr to 1.78$\pm$0.20 Gyr. The total mass of these clusters ranges from 356.18$\pm$142.90 to 1811.75$\pm$901.03 M$_{\odot}$. The Galactocentric distances to the c

Luca Nannini, Agathe Balayn, Adam Leon Smith

Public attention towards explainability of artificial intelligence (AI) systems has been rising in recent years to offer methodologies for human oversight. This has translated into the proliferation of research outputs, such as from Explainable AI, to enhance transparency and control for system debugging and monitoring, and intelligibility of system process

Ahsan Tanveer, Sarvat Mushtaq Ahmad

This article presents the design and real-time implementation of an optimal controller for precise steering control of a remotely operated underwater vehicle (ROV). A PI controller is investigated to achieve the desired steering performance. The gain parameters of the controller are tuned using the genetic algorithm (GA). The experimental response correspond

Zhiyuan Wang, Zeliang Zhang, Siyuan Liang, Xiaosen Wang

Given the great threat of adversarial attacks against Deep Neural Networks (DNNs), numerous works have been proposed to boost transferability to attack real-world applications. However, existing attacks often utilize advanced gradient calculation or input transformation but ignore the white-box model. Inspired by the fact that DNNs are over-parameterized for

Sean Cotner

Let $k$ be a field, let $H \subset G$ be (possibly disconnected) reductive groups over $k$, and let $\Gamma$ be a finitely generated group. Vinberg and Martin have shown that the induced morphism of character varieties \[ \underline{\mathrm{Hom}}_{k\textrm{-gp}}(\Gamma, H)//H \to \underline{\mathrm{Hom}}_{k\textrm{-gp}}(\Gamma, G)//G \] is finite. In this no

Luigi Caputi, Daniele Celoria, Carlo Collari

We prove that the second page of the Mayer-Vietoris spectral sequence, with respect to anti-star covers, can be identified with another homological invariant of simplicial complexes: the $0$-degree \"uberhomology. Consequently, we obtain a combinatorial interpretation of the second page of the Mayer-Vietoris sequence in this context. This interpretation is t

Ram Kumar, S. Rayaprol, A. Hoser, E. V. Sampathkumaran

The Haldane-spin chain compound, Tb2BaNiO5, has been known to be an exotic multiferroic system, exhibiting antiferromagnetic anomalies at T_N1= 63 K and T_N2= 25 K, with ferroelectricity appearing below T_N2 only. Previous reports in addition established that, interestingly, Tb ions play a direct and decisive role to lead to multiferroic properties with a cr

G. Andrini, G. Zanelli, S. Ditalia Tchernij, E. Corte

The recent demonstration of optically active telecom emitters makes silicon a compelling candidate for solid state quantum photonic platforms. Particularly fabrication of the G center has been demonstrated in carbon-rich silicon upon conventional thermal annealing. However, the high-yield controlled fabrication of these emitters at the wafer-scale still requ

Bowen Wang, Liangzhi Li, Yuta Nakashima, Hajime Nagahara

Interpreting and explaining the behavior of deep neural networks is critical for many tasks. Explainable AI provides a way to address this challenge, mostly by providing per-pixel relevance to the decision. Yet, interpreting such explanations may require expert knowledge. Some recent attempts toward interpretability adopt a concept-based framework, giving a

Herbert Gangl, Yue Ren, Ziva Urbancic

This is a guide on how to create 3d printable models of tropical surfaces, curves, and combinations thereof. It uses Polymake to construct bounded models of the tropical objects, and OpenSCAD to thicken and export them to any common 3D printable file format.

Luke Harvey, Kate Maguire, Mark R. Magee, Mattia Bulla

An open question in SN Ia research is where the boundary lies between 'normal' Type Ia supernovae (SNe Ia) that are used in cosmological measurements and those that sit off the Phillips relation. We present the spectroscopic modelling of one such '86G-like' transitional SN Ia, SN 2021rhu, that has recently been employed as a local Hubble Constant calibrator

Dane Cross, Gray Thoron, Tesla Jeltema, Allison Swart

While collisionless cold dark matter models have been largely successful in explaining a wide range of observational data, some tensions still exist, and it remains possible that dark matter possesses a non-negligible level of self interactions. In this paper, we investigate a possible observable consequence of self-interacting dark matter: offsets between t

Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong

Large-scale pre-trained models have achieved remarkable success in many applications, but how to leverage them to improve the prediction reliability of downstream models is undesirably under-explored. Moreover, modern neural networks have been found to be poorly calibrated and make overconfident predictions regardless of inherent sample difficulty and data u

Hongyuan Zhang, Yanan Zhu, Xuelong Li

Graph neural networks (GNN) suffer from severe inefficiency. It is mainly caused by the exponential growth of node dependency with the increase of layers. It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming. To address this problem, we propose to decouple a multi-layer GNN as multipl

K. É. Gabányi, K. Smith, S. Frey, Z. Paragi

X-ray binaries are known to show state transitions related to accretion rate changes which are often accompanied with dramatic changes in the jet emission. However, it is not clear whether this characteristics of stellar-mass black hole systems can be scaled up to the accretion disk of active galactic nuclei. The Seyfert 1 galaxy, KUG 1141+371 has been showi

Chenglu Sun, Yichi Zhang, Yu Zhang, Ziling Lu

Asymmetrical multiplayer (AMP) game is a popular game genre which involves multiple types of agents competing or collaborating with each other in the game. It is difficult to train powerful agents that can defeat top human players in AMP games by typical self-play training method because of unbalancing characteristics in their asymmetrical environments. We p

Halyun Jeong, Deanna Needell

The Kaczmarz method (KZ) and its variants, which are types of stochastic gradient descent (SGD) methods, have been extensively studied due to their simplicity and efficiency in solving linear equation systems. The iterative thresholding (IHT) method has gained popularity in various research fields, including compressed sensing or sparse linear regression, ma

K. K. Iyer, S. Matteppanavar, S. Dodamani, K. Maiti

We have investigated for the first time the magnetic behaviour of an intermetallic compound, Dy4RhAl, crystallizing in Gd4RhIn type cubic structure containing 3 sites for rare-earth (R), by several bulk measurements down to 1.8 K. This work is motivated by the fact that the isostructural Dy compound in the R4PtAl family surprisingly orders ferromagnetically

Kartik K. Iyer, Sudhindra Rayaprol, Ram Kumar, Shidaling Matteppanavar

We report the electronic properties of R4PtAl (R = Ho, and Er), which contains 3 sites for R, by the measurements of magnetization (ac and dc), heat-capacity, transport, and magnetoresistance (MR). Dc magnetization data reveal antiferromagnetic order below 19 K and 12 K in Ho and Er compounds, respectively. Additional features observed at lower temperatures

Magdalena Gawęda, Magdalena Wilczopolska, Kinga Suchorab, Małgorzata Frelek-Kozak

4th Generation high-temperature gas-cooled nuclear reactors (HTGR) are regarded as possible sources of industrial heat in Poland and Europe, allowing for a substantial reduction of the dependency on gas and coal import. It is mainly due to their safety of use, reliability and economy in a current energetic crisis. In this work, graphite, as a primary constru

Wei Zhang

In this paper, we consider the general divisor functions over Piatetski-Shapiro sequences. We can give some general results which contain some special divisor functions. Precisely, we extend the divisor problem over Piatetski-Shapiro sequences to the function $f(n),$ where $f(n)\ll n^{\varepsilon},$ $$f(n)=\sum_{n=n_{1}n_{2}} \tau(n_{1})g(n_{2}),$$ $\tau(n)$

Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana, André Röhm

Quantum walks (QWs) have a property that classical random walks (RWs) do not possess -- the coexistence of linear spreading and localization -- and this property is utilized to implement various kinds of applications. This paper proposes RW- and QW-based algorithms for multi-armed-bandit (MAB) problems. We show that, under some settings, the QW-based model r

Chao-Wan-Zhen Wang, Jin-Bao Zhu, Guo-Qing Huang, Fu-Wen Shu

The successful observation of gravitational waves has provided humanity with an additional method to explore the universe, particularly black holes. In this study, we utilize data from LIGO and Virgo gravitational wave observations to test the first law of black hole mechanics, employing two different approaches. We consider the secondary compact object as a

Richard Paluch, Tanja Aal, Katerina Cerna, Dave Randall

Technological development continues to advance, with consequences for the use of robots in health care. For this reason, this workshop contribution aims at consideration of how socially assistive robots can be integrated into care and what tasks they can take on. This also touches on the degree of autonomy of these robots and the balance of decision support

Magdalena Gawęda, Piotr Jeleń, Maciej Bik, Magdalena Szumera

Vibrational spectroscopy is the most effective, efficient and informative method of structural analysis of amorphous materials with silica matrix and, therefore, an indispensable tool for examining silicon oxycarbide-based amorphous materials (SiOC). The subject of this work is a description of the modification process of SiOC glasses with phosphate ions bas

Sandi Klavžar, Elif Tan

A set of edges $X\subseteq E(G)$ of a graph $G$ is an edge general position set if no three edges from $X$ lie on a common shortest path in $G$. The cardinality of a largest edge general position set of $G$ is the edge general position number of $G$. In this paper edge general position sets are investigated in partial cubes. In particular it is proved that t

Goirik Chakrabarty, Manogna Sreenivas, Soma Biswas

Adapting a trained model to perform satisfactorily on continually changing testing domains/environments is an important and challenging task. In this work, we propose a novel framework, SATA, which aims to satisfy the following characteristics required for online adaptation: 1) can work seamlessly with different (preferably small) batch sizes to reduce laten

K. Sato, T. Fukui

The periodic Toda lattice is solved by exploiting the spectral properties of the Lax operator, in which the boundary states play an important role. We show that these boundary states have a topological origin similar to that of the edge states in topological insulators, and consequently, that the bulk wave functions of the Lax operator yield nontrivial Chern

Kenta Otsubo, Takaki Kiyozumi, Kohei Noda, Kentaro Nakamura

We show that the systematic error unique to Brillouin optical correlation-domain reflectometry (BOCDR) can be effectively suppressed by use of low-coherence light, and demonstrate distributed strain measurement with ~3 cm spatial resolution.

Jun Yin, Amilcare Porporato, Lamberto Rondoni

While the warming trends of the Earth's mean temperature are evident at climatological scales, the local temperature at shorter timescales are highly fluctuating. In this letter we show that the probabilities of such fluctuations are characterized by a special symmetry typical of systems out of equilibrium. Their nearly universal properties are linked to the

Chen Qian, Shicheng Jiang, Tong Wu, Hongming Weng

The solid-state harmonic generation (SSHG) derives from photocurrent coherence. The crystal symmetry, including point-group symmetry and time-reversal symmetry, constrains the amplitude and phase of the photocurrent, thus manipulates the coherent processes in SSHG. We revisit the expression of photocurrent under the electric dipole approximation and give an

Hoang-Giang Cao, Weihao Zeng, I-Chen Wu

Picking cluttered general objects is a challenging task due to the complex geometries and various stacking configurations. Many prior works utilize pose estimation for picking, but pose estimation is difficult on cluttered objects. In this paper, we propose Cluttered Objects Descriptors (CODs), a dense cluttered objects descriptor that can represent rich obj

Peiliu Li, Xianfu Huang, Ya-Pu Zhao

Thin films being a universal functional material have attracted much interest in academic and industrial applications, such as flexible electronics, soft robotics, and micro-nano devices. With thin films becoming micro/nanoscale, developing a simple and nondestructive peeling method for transferring and reusing remains a big challenge. Here, we present an in

Roy Gotlib, Tali Kaufman

"No Where to go but in" is a well known statement of Osho. Osho meant to say that the answers to all our questions should be obtained by looking into ourselves. In a paraphrase to Osho's statement we say "No Where to go but high". This meant to demonstrate that for various seemingly unrelated topics and questions the only way to get significant progress is v

Jin Bai, Tong Qiu

Although procurement fraud is always a critical problem in almost every free market, audit departments still have a strong reliance on reporting from informed sources when detecting them. With our generous cooperator, SF Express, sharing the access to the database related with procurements took place from 2015 to 2017 in their company, our team studies how m

Mohammad R. Garousi

This paper investigates the $\beta$-symmetry of the heterotic string theory at order $\alpha'$ in the context of open spacetime manifolds. Our analysis reveals that the parity-odd component of the effective action at this order remains invariant under $\beta$-transformations. Furthermore, we demonstrate that the corresponding $\beta$-transformations leave th

Libo Huang, Yan Zeng, Chuanguang Yang, Zhulin An

Class-Incremental Learning (CIL) aims to solve the neural networks' catastrophic forgetting problem, which refers to the fact that once the network updates on a new task, its performance on previously-learned tasks drops dramatically. Most successful CIL methods incrementally train a feature extractor with the aid of stored exemplars, or estimate the feature

Iulian D. Toader

The paper offers an argument against an intuitive reading of the Stone-von Neumann theorem as a categoricity result, thereby pointing out that, against what is usually taken to be the case, this theorem does not entail any model-theoretical difference between the theories that validate it and those that don't.

Ankit Aggarwal, Alejandra Castro, Stéphane Detournay, Beatrix Mühlmann

A holographic description of three-dimensional warped black holes suffers from ambiguities due to a seemingly harmless choice of coordinate system. This gives rise to the notion of ensembles in warped black holes, and we focus on two of them: the canonical and quadratic ensemble. Our aim is to quantify the imprint of these ensembles in the near-extremal limi

Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir

Federated learning has attracted increasing attention due to the promise of balancing privacy and large-scale learning; numerous approaches have been proposed. However, most existing approaches focus on problems with balanced data, and prediction performance is far from satisfactory for many real-world applications where the number of samples in different cl

Masahiro Kawasaki, Tsutomu T. Yanagida

When we impose the discrete symmetry in the standard model we have Dai-Freed global anomalies. However, interestingly if we introduce three right-handed neutrinos we can have an anomaly-free discrete $Z_4$ gauge symmetry. This $Z_4$ symmetry should be spontaneously broken down to the $Z_2$ symmetry to generate the heavy Majorana masses for the right-handed n

Yi Xuan

In this paper, we study weighted fractional Sobolev-Poincar\'e inequalities for irregular domains. The weights considered here are distances to the boundary to certain powers, and the domains are the so-called $s$-John domains and $\beta$-H\"older domains. Our main results extend that of Hajlasz-Koskela [J. Lond. Math. Soc. 1998] from the classical weighted

Zhao Yang, Thomas. M. Moerland, Mike Preuss, Aske Plaat

While deep reinforcement learning has shown important empirical success, it tends to learn relatively slow due to slow propagation of rewards information and slow update of parametric neural networks. Non-parametric episodic memory, on the other hand, provides a faster learning alternative that does not require representation learning and uses maximum episod

Tonghua Su, Fuxiang Yang, Xiang Zhou, Donglin Di

In this work, we propose a task called "Scene Style Text Editing (SSTE)", changing the text content as well as the text style of the source image while keeping the original text scene. Existing methods neglect to fine-grained adjust the style of the foreground text, such as its rotation angle, color, and font type. To tackle this task, we propose a quadruple

Gi-Chol Cho, Chikako Idegawa

We investigate a suppression mechanism of dark matter and quark scattering amplitudes in a complex singlet extension of the Standard Model. It has been pointed out that, in a some variant of the model, the scattering amplitudes cancel each other in the limit in which two mediator scalars degenerate in their masses. We study the origin of such the cancellatio

Chao Zhou, Bin Lyu, Youhong Feng, Dinh Thai Hoang

In this paper, we propose a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) empowered transmission scheme for symbiotic radio (SR) systems to make more flexibility for network deployment and enhance system performance. The STAR-RIS is utilized to not only beam the primary signals from the base station (BS) towards mul

Payal Vasoya, Devsi Bantva

A radio labeling of a graph $G$ is a function $f : V(G) \rightarrow \{0,1,2,\ldots\}$ such that $|f(u)-f(v)| \geq diam(G) + 1 - d(u,v)$ for every pair of distinct vertices $u,v$ of $G$. The radio number of $G$, denoted by $rn(G)$, is the smallest number $k$ such that $G$ has radio labeling $f$ with max$\{f(v):v \in V(G)\} = k$. In this paper, we give a lower

Jinxiang Lai, Siqian Yang, Junhong Zhou, Wenlong Wu

Weak feature representation problem has influenced the performance of few-shot classification task for a long time. To alleviate this problem, recent researchers build connections between support and query instances through embedding patch features to generate discriminative representations. However, we observe that there exists semantic mismatches (foregrou

Tianyun Tang, Kim-Chuan Toh, Nachuan Xiao, Yinyu Ye

In this paper, we propose a cubic-regularized Riemannian optimization method (RDRSOM), which partially exploits the second order information and achieves the iteration complexity of $\mathcal{O}(1/\epsilon^{3/2})$. In order to reduce the per-iteration computational cost, we further propose a practical version of (RDRSOM), which is an extension of the well kn

Jun Zhu, Jiandong Jin, Zihan Yang, Xiaohao Wu

Existing pedestrian attribute recognition (PAR) algorithms are mainly developed based on a static image. However, the performance is not reliable for images with challenging factors, such as heavy occlusion, motion blur, etc. In this work, we propose to understand human attributes using video frames that can make full use of temporal information. Specificall

Qianhui Sun, Qingyu Yang, Chongyi Li, Shangchen Zhou

Developing and integrating advanced image sensors with novel algorithms in camera systems are prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for an in-depth exchange of views from industry and academia constrain the development of

Lu Liu, Ke Yang, Guangyu Wang, Di Lu

The spin-orbital entangled states are of great interest as they hold exotic phases and intriguing properties. Here we use first-principles calculations to investigate the electronic and magnetic properties of RuI$_{3}$ and RuCl$_{3}$ in both bulk and monolayer cases. Our results show that RuI$_{3}$ bulk is a paramagnetic metal, which is in agreement with rec

Qianhui Sun, Qingyu Yang, Chongyi Li, Shangchen Zhou

Developing and integrating advanced image sensors with novel algorithms in camera systems are prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for an in-depth exchange of views from industry and academia constrain the development of

Feng Guo, Zheng Sun, Yuxuan Chen, Lei Ju

Recently, studies show that deep learning-based automatic speech recognition (ASR) systems are vulnerable to adversarial examples (AEs), which add a small amount of noise to the original audio examples. These AE attacks pose new challenges to deep learning security and have raised significant concerns about deploying ASR systems and devices. The existing def

Md Sadman Sakib Rahman, Tianyi Gan, Emir Arda Deger, Cagatay Isil

Free-space optical systems are emerging for high data rate communication and transfer of information in indoor and outdoor settings. However, free-space optical communication becomes challenging when an occlusion blocks the light path. Here, we demonstrate, for the first time, a direct communication scheme, passing optical information around a fully opaque,

Minh Nhat Ly, Takayoshi Sano, Youichi Sakawa, Yasuhiko Sentoku

Collisionless shock acceleration, which transfers localized particle energies to non-thermal energetic particles via electromagnetic potential, is ubiquitous in space plasma. We investigate dynamics of collisionless electrostatic shocks that appear at interface of two plasma slabs with different pressures using one-dimensional particle-in-cell (PIC) simulati

Phat K. Huynh, Dang Nguyen, Grace Binder, Sharad Ambardar

Recent advances in high-resolution biomedical imaging focusing on morphological, electrical, and biochemical properties of cells and tissues, scaling from cell clusters down to the molecular level, have improved cancer diagnosis. Multiscale imaging revealed high complexity that requires advanced data processing methods of multifractal analysis. We performed

Jan Tristram Acuña, Po-Yan Tseng

In this work, we assess the sensitivity reach of pulsar timing array (PTA) measurements to probe pointlike primordial black holes (PBHs), with an extended mass distribution, which originate from collapsed Fermi balls that are formed through the aggregation of asymmetric U(1) dark fermions trapped within false vacuum bubbles during a dark first order phase tr

Young-Ho Seo, Jonghyun Lee, Aly I. El-Kadi, Niels Grobbe

Estimating subsurface properties like hydraulic conductivity using hydrogeological data alone is challenging in field sites with sparse wells. Geophysical data, including Self-potential (SP) and Magnetotelluric (MT), can improve understanding of hydrogeological structures and interpolate data between wells. However, determining hydraulic conductivity require

Weiwei Su, Yuki Izumida, Hiroshi Kori

Most bacteria are driven by the cilia or flagella, consisting of a long filament and a rotary molecular motor through a short flexible hook. The beating pattern of these filaments shows synchronization properties from hydrodynamic interactions, especially in low Reynolds number fluids. Here, we introduce a model based on simple spherical oscillators which ex

Guangping Li, Tingting Xu, Liping Li, Xianjun Gao

The classification of galaxy morphology is a hot issue in astronomical research. Although significant progress has been made in the last decade in classifying galaxy morphology using deep learning technology, there are still some deficiencies in spatial feature representation and classification accuracy. In this study, we present a multi-scale convolutional

Yu-Tao Liu, Li Wang, Jie yang, Weikai Chen

Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in neural implicit surface rendering. However, existing methods based on signed distance function (SDF) are limited to closed surfaces, failing to reconstruct a wide range of real-world objects that contain open-surface structures. In this work, we introduce a ne

Yingqi Wang, Zhongqin Wang, J. Andrew Zhang, Haimin Zhang

Contact-free vital sign monitoring, which uses wireless signals for recognizing human vital signs (i.e, breath and heartbeat), is an attractive solution to health and security. However, the subject's body movement and the change in actual environments can result in inaccurate frequency estimation of heartbeat and respiratory. In this paper, we propose a robu

Shengxiang Hu, Guobing Zou, Song Yang, Shiyi Lin

Dynamic graph representation learning has emerged as a crucial research area, driven by the growing need for analyzing time-evolving graph data in real-world applications. While recent approaches leveraging recurrent neural networks (RNNs) and graph neural networks (GNNs) have shown promise, they often fail to adequately capture the impact of temporal edge s

Xiaojun Dong, Yunshu Wu, Zhongqi Wang, Laxman Dhulipala

Semisort is a fundamental algorithmic primitive widely used in the design and analysis of efficient parallel algorithms. It takes input as an array of records and a function extracting a \emph{key} per record, and reorders them so that records with equal keys are contiguous. Since many applications only require collecting equal values, but not fully sorting

M. Asorey, A. P. Balachandran, Arshad Momen, B. Qureshi

Lorentz symmetry forbids decays of massive spin-1 particle like the $Z^0$ into two massless photons, a result known as the Landau-Yang theorem. But it is known that infrared effects can break Lorentz invariance. Employing the construction of Mund et. al. \cite{MRS} which incorporated this Lorentz violation, we propose an interaction leading to the decay $Z^0

Vuong Bui

While the number of polyominoes is known to be supermultiplicative by a simple concatenation argument, it is still unknown whether the same applies to polyiamonds. This article proves that if $\ell,m$ are not both $1$, then $T(\ell+m)\ge T(\ell)T(m)$, for which one can say that the number of polyiamonds $T(n)$ is supermultiplicative. The method is, however,

Amir Ghasemian, Nicholas A. Christakis

The "friendship paradox" of social networks states that, on average, "your friends have more friends than you do." Here, we theoretically and empirically explore a related and overlooked paradox we refer to as the "enmity paradox." We use empirical data from 24,687 people living in 176 villages in rural Honduras. We show that, for a real negative undirected

Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu

The rendering scheme in neural radiance field (NeRF) is effective in rendering a pixel by casting a ray into the scene. However, NeRF yields blurred rendering results when the training images are captured at non-uniform scales, and produces aliasing artifacts if the test images are taken in distant views. To address this issue, Mip-NeRF proposes a multiscale

Xiyuan Wang, Pan Li, Muhan Zhang

In this paper, we study using graph neural networks (GNNs) for \textit{multi-node representation learning}, where a representation for a set of more than one node (such as a link) is to be learned. Existing GNNs are mainly designed to learn single-node representations. When used for multi-node representation learning, a common practice is to directly aggrega

Mindi Ruan, Xiangxu Yu, Na Zhang, Chuanbo Hu

How can we teach a computer to recognize 10,000 different actions? Deep learning has evolved from supervised and unsupervised to self-supervised approaches. In this paper, we present a new contrastive learning-based framework for decision tree-based classification of actions, including human-human interactions (HHI) and human-object interactions (HOI). The k

Masanari Shimada, Pegah Behrad, Eric De Giuli

Understanding the emergent behavior of chemical reaction networks (CRNs) is a fundamental aspect of biology and its origin from inanimate matter. A closed CRN monotonically tends to thermal equilibrium, but when it is opened to external reservoirs, a range of behaviors is possible, including transition to a new equilibrium state, a non-equilibrium state, or

Arshed Nabeel, Vivek Jadhav, Danny Raj M, Clément Sire

Coarse-grained descriptions of collective motion of flocking systems are often derived for the macroscopic or the thermodynamic limit. However, many real flocks are small sized (10 to 100 individuals), called the mesoscopic scales, where stochasticity arising from the finite flock sizes is important. Developing mesoscopic scale equations, typically in the fo

Dongge Liu, Jonathan Metzman, Marcel Böhme, Oliver Chang

This report outlines the objectives, methodology, challenges, and results of the first Fuzzing Competition held at SBFT 2023. The competition utilized FuzzBench to assess the code-coverage performance and bug-finding efficacy of eight participating fuzzers over 23 hours. The competition was organized in three phases. In the first phase, participants were ask

K. Iwata, A. Koshiba, Y. Kawasugi, R. Kato

We investigated the magnetoresistance and the Hall effect in an organic massless Dirac fermion system $\alpha$-(BETS)$_2$I$_3$ under pressure. The Fermi energy of this system is slightly far away from the Dirac points, and thus the $\nu =1$ quantum Hall state is realized in a low magnetic field at low temperatures. Moreover, the experimental formula for chem

Joel Janek Dabrowski, Ashfaqur Rahman

In this paper we present a novel application of detecting fruit picker activities based on time series data generated from wearable sensors. During harvesting, fruit pickers pick fruit into wearable bags and empty these bags into harvesting bins located in the orchard. Once full, these bins are quickly transported to a cooled pack house to improve the shelf