January 2022 arXiv papers — page 113

Pengxiang Su, Zhenguang Liu, Shuang Wu, Lei Zhu

Motion prediction is a classic problem in computer vision, which aims at forecasting future motion given the observed pose sequence. Various deep learning models have been proposed, achieving state-of-the-art performance on motion prediction. However, existing methods typically focus on modeling temporal dynamics in the pose space. Unfortunately, the complic

Kenta Tsukuura

We construct a model with a saturated ideal $I$ over $\mathcal{P}_{\kappa}\lambda$ and study the extent of saturation of $I$.

Sourish Ganguly

With quadrotors becoming immensely popular in applications such as relief operations, infrastructure maintenance etc., a key control design challenge arises when the quadrotor has to manoeuvre through constrained spaces during various operational scenarios: for example, inspecting a pipeline within predefined velocity and space, dropping relief material at a

Alain Blaustein, Francis Filbet

We consider a spatially extended mesoscopic FitzHugh-Nagumo model with strong local interactions and prove that its asymptotic limit converges towards the classical nonlocal reaction-diffusion FitzHugh-Nagumo system. As the local interactions strongly dominate, the weak solution to the mesoscopic equation under consideration converges to the local equilibriu

Anna Minguzzi, Patrizia Vignolo

Quantum correlations can be used as a resource for quantum computing, eg for quantum state manipulation, and for quantum sensing, eg for creating non-classical states which allow to achieve the quantum advantage regime. This review collects the predictions coming from a family of exact solutions which allows to describe the many-body wavefunction of strongly

Jean Fresnel, Michel Matignon

The existence of certain Fq-spaces of differential forms of the projective line over a field K containing Fq leads us to prove an identity linking the determinant of the Moore matrix of n indeterminates with the determinant of the Moore matrix of the cofactors of its first row. These same spaces give an interpretation of Elkies pairing in terms of residues o

Xianjing Dong, Shuangshuang Yang

This paper re-develops the Nevanlinna theory for meromorphic functions on $\mathbb C$ in the viewpoint of holomorphic forms. According to our observation, Nevanlinna's functions can be formulated by a holomorphic form. Applying this thought to Riemann surfaces, one then extends the definition of Nevanlinna's functions using a holomorphic form $\mathscr S$. W

Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun

Motivated by potential financial gain, companies may hire fraudster groups to write fake reviews to either demote competitors or promote their own businesses. Such groups are considerably more successful in misleading customers, as people are more likely to be influenced by the opinion of a large group. To detect such groups, a common model is to represent f

Yasuhiro Ohta, Bao-Feng Feng

In the present paper, we attempt to construct both the general rogue wave solutions to the fully discrete nonlinear Schr\"odinger (fd-NLS) equation via the KP-Toda reduction method. First, we deduce the general breather solution of the fd-NLS equation starting from a pair of bilinear equations. We then derive the general rogue wave solution by taking a limit

Yinjie Zhao, Xin Kang, Tieyan Li, Cheng-Kang Chu

With the rapid development of blockchain technology in recent years, all kinds of blockchain-based applications have emerged. Among them, the decentralized finance (DeFi) is one of the most successful applications, which is regarded as the future of finance. The great success of DeFi relies on the real-world data which is not directly available on the blockc

Mingzhe Li, Zhihao Li, Haomin Rao

In this paper we consider the parity violating gravity model within the framework of teleparallel gravity. The parity violations are caused by the couplings of a scalar field to the scalar invariants which are parity-odd and quadratic in the torsion tensor. Totally there are two such type independent invariants, and one of them is the Nieh-Yan density. Throu

Dingwen Zhang, Guohai Huang, Qiang Zhang, Jungong Han

Recent advances in machine learning and prevalence of digital medical images have opened up an opportunity to address the challenging brain tumor segmentation (BTS) task by using deep convolutional neural networks. However, different from the RGB image data that are very widespread, the medical image data used in brain tumor segmentation are relatively scarc

Francesco Caravelli, Fabio L. Traversa, Michele Bonnin, Fabrizio Bonani

We study embeddings of continuous dynamical systems in larger dimensions via projector operators. We call this technique PEDS, projective embedding of dynamical systems, as the stable fixed point of the dynamics are recovered via projection from the higher dimensional space. In this paper we provide a general definition and prove that for a particular type o

Jy-yong Sohn, Liang Shang, Hongxu Chen, Jaekyun Moon

Mixup is a data augmentation method that generates new data points by mixing a pair of input data. While mixup generally improves the prediction performance, it sometimes degrades the performance. In this paper, we first identify the main causes of this phenomenon by theoretically and empirically analyzing the mixup algorithm. To resolve this, we propose Gen

Xingru Chen, Feng Fu

The COVID-19, the disease caused by the novel coronavirus 2019 (SARS-CoV-2), has caused graving woes across the globe since first reported in the epicenter Wuhan, Hubei, China, December 2019. The spread of COVID-19 in China has been successfully curtailed by massive travel restrictions that put more than 900 million people housebound for more than two months

Rajashekhar V S, Debasish Ghose

Mobility, which is a basic property for a mechanism has to be analyzed to find the degrees of freedom. A quick method for calculation of degrees of freedom in a mechanism is proposed in this work. The mechanism is represented in a way that resembles a zebra crossing. An algorithm is proposed which is used to determine the mobility from the zebra crossing dia

Hampei Sasahara, Henrik Sandberg

This paper addresses the question whether model knowledge can guide a defender to appropriate decisions, or not, when an attacker intrudes into control systems. The model-based defense scheme considered in this study, namely Bayesian defense mechanism, chooses reasonable reactions through observation of the system's behavior using models of the system's stoc

Debvrat Varshney, Claudio Persello, Prasun Kumar Gupta, Bhaskar Ramachandra Nikam

Clouds and snow have similar spectral features in the visible and near-infrared (VNIR) range and are thus difficult to distinguish from each other in high resolution VNIR images. We address this issue by introducing a shortwave-infrared (SWIR) band where clouds are highly reflective, and snow is absorptive. As SWIR is typically of a lower resolution compared

H. -T. Ding, S. -T. Li, J. -H. Liu, X. -D. Wang

We point out that chiral condensates at nonzero temperature and magnetic fields are in strict connection to the space-time integral of corresponding two-point neutral meson correlation functions in the pseudoscalar channel via the Ward-Takahashi identity. Screening masses of neutral pseudoscalar mesons, which are defined as the exponential decay of the corre

Md Riajul Haque, Debaprasad Maity

Our present understanding of the reheating phase is incomplete due to a lack of observations. Apart from its cosmological implications, the reheating should play a vital role in particle physics and inflation model building. Conventionally reheating dynamics are modeled by invoking arbitrary coupling among the inflaton and daughter fields. Such an approach l

Surasree Sadhukhan, Banasree Sadhukhan, Sudipta Kanungo

Recently topologically non-trivial phases have been identified in few time-reversal invariant systems that lack of inversion symmetry. Using density functional theory based first-principles calculations, we report a strong topologically non-trivial phase in chalchopyrite ZnGeSb$_2$, which can act as a model system of strained HgTe. The calculations reveal th

Huanyu Wang, Junjie Liu, Xin Ma, Yang Yong

Few-sample compression aims to compress a big redundant model into a small compact one with only few samples. If we fine-tune models with these limited few samples directly, models will be vulnerable to overfit and learn almost nothing. Hence, previous methods optimize the compressed model layer-by-layer and try to make every layer have the same outputs as t

Barkha Baloda, Jitender Kumar

The intersection ideal graph $\Gamma(S)$ of a semigroup $S$ is a simple undirected graph whose vertices are all nontrivial left ideals of $S$ and two distinct left ideals $I, J$ are adjacent if and only if their intersection is nontrivial. In this paper, we investigate the connectedness of $\Gamma(S)$. We show that if $\Gamma(S)$ is connected then $diam(\Gam

Jitender Kumar, Barkha Baloda, Sanjeet Malhotra

The left-ideal relation graph on a ring $R$, denoted by $\overrightarrow{\Gamma_{l-i}}(R)$, is a directed graph whose vertex set is all the elements of $R$ and there is a directed edge from $x$ to a distinct $y$ if and only if the left ideal generated by $x$, written as $[x]$, is properly contained in the left ideal generated by $y$. In this paper, the autom

Zhiyuan Chen, Soon Boon Lee, Shazia Paras Shaikh, Mirza Rayana Sanzana

Comparing with lecturer marked assessments, peer assessment is a more comprehensive learning process and many of the associated problems have occurred. In this research work, we study the peer-assessment impact on group learning activities in order to provide a complete and systematic review, increase the practice and quality of the peer assessment process.

Luca Vismara, Vee-Liem Saw, Lock Yue Chew

Bus bunching is ostensibly regarded as a detrimental phenomenon in bus systems. We study a bus loop with two bus stops, one regular and one spike bus stop, where bunched buses can outperform staggered buses. The spike bus stop models a bus stop connected to a train or metro service, where passengers arrive in groups at periodic intervals (spikes). We introdu

Shengbing Deng, Xingliang Tian

This paper deals with the existence and multiplicity of solutions for a class of Kirchhoff type elliptic system involving the Trudinger-Moser exponential growth nonlinearities. We first study the existence of solutions for the following system \begin{eqnarray*} \left\{ \arraycolsep=1.5pt \begin{array}{ll} -\big(a_1+b_1\|u\|^{2(\theta_1-1)}\big)\Delta u= \lam

M. D. I. Bhuyan, Rana Hossain, Ferdous Ara, M. A. Basith

Here, the first-principles predictions on the structural stability, magnetic behavior and electronic structure of B-site ordered double perovskite Nd$_{2}$FeCrO$_{6}$ have been reported. Initially, the ground state of the parent single perovskites NdCrO$_{3}$ and NdFeO$_{3}$ have been studied to determine the relevant Hubbard U parameter to investigate the p

Shikuang Deng, Jingwei Li, B. T. Thomas Yeo, Shi Gu

The brain's functional connectivity fluctuates over time instead of remaining steady in a stationary mode even during the resting state. This fluctuation establishes the dynamical functional connectivity that transitions in a non-random order between multiple modes. Yet it remains unexplored how the transition facilitates the entire brain network as a dynami

Christian Otto, Markus Rokicki, Georg Pardi, Wolfgang Gritz

The emerging research field Search as Learning investigates how the Web facilitates learning through modern information retrieval systems. SAL research requires significant amounts of data that capture both search behavior of users and their acquired knowledge in order to obtain conclusive insights or train supervised machine learning models. However, the cr

Shengbing Deng, Xingliang Tian

The aim of this paper is to study the multiplicity of solutions for the following Kirchhoff type elliptic systems \begin{eqnarray*} \left\{ \arraycolsep=1.5pt \begin{array}{ll} -m\left(\sum^k_{j=1}\|u_j\|^2\right)\Delta u_i=\frac{f_i(x,u_1,\ldots,u_k)}{|x|^\beta}+\varepsilon h_i(x),\ \ & \mbox{in}\ \ \Omega, \ \ i=1,\ldots,k ,\\[2mm] u_1=u_2=\cdots=u_k=0,\ \

Hiroshi Miki, Satoshi Tsujimoto, Luc Vinet

Classical and quantum walks on some finite paths are introduced. It is shown that these walks have explicit solutions given in terms of exceptional Krawtchouk polynomials and their properties are explored. In particular, fractional revival is shown to take place in the corresponding quantum walks.

Mo Liu

Over increasing domain interpretations, \exists\Box and \forall\Box bundled fragments are decidable and over constant domain interpretations, \exists\Box bundled fragment is decidable while \forall\Box bundled fragment is undecidable. Based on the existing results,we show that over increasing domain interpretations, \Box\exists and \Box\forall bundled fragme

Magda H. Barecka, Joel W. Ager

The transition towards carbon-neutral chemical production is challenging due to the fundamental reliance of the chemical sector on petrochemical feedstocks. Electrolysis-based manufacturing, powered by renewables, is a rapidly evolving technology that might be capable of drastically reducing CO2 emissions from the chemical sector. However, will it be possibl

Hajime Tanaka

The liquid state is one of the fundamental and essential states of matter, but its physical understanding is far behind the other states, such as the gas and solid states, due to the difficulties associated with the high density causing many-body correlations and the lack of long-range order. Significant open problems in liquid science include glass transiti

Byounghyo Lee, Dongyeon Kim, Seungjae Lee, Chun Chen

Holography is a promising approach to implement the three-dimensional (3D) projection beyond the present two-dimensional technology. True 3D holography requires abilities of arbitrary 3D volume projection with high-axial resolution and independent control of all 3D voxels. However, it has been challenging to implement the true 3D holography with high-reconst

Shu-Min Wu, Hao-Sheng Zeng

We study the genuine tripartite nonlocality (GTN) and the genuine tripartite entanglement (GTE) of Dirac fields in the background of a Schwarzschild black hole. We find that the Hawking radiation degrades both the physically accessible GTN and the physically accessible GTE. The former suffers from "sudden death" at some critical Hawking temperature, and the

Michael Plantholt, Hamidreza Habibi, Benjamin Mussell

Let $f: \{1, ..., n\} \rightarrow \{1, ..., n\}$ be a function (not necessarily one-to-one). An $f-derangement$ is a permutation $ g:\{1,...,n\} \rightarrow \{1,...,n\}$ such that $g(i) \neq f(i)$ for each $ i = 1, ..., n$. When $f$ is itself a permutation, this is a standard derangement. We examine properties of f-derangements, and show that when we fix the

Ramneet Kaur, Susmit Jha, Anirban Roy, Sangdon Park

Machine learning methods such as deep neural networks (DNNs), despite their success across different domains, are known to often generate incorrect predictions with high confidence on inputs outside their training distribution. The deployment of DNNs in safety-critical domains requires detection of out-of-distribution (OOD) data so that DNNs can abstain from

Dileep Singh, Jaskaran Singh, Kavita Dorai, Arvind

We develop a theoretical framework based on a graph theoretic approach to analyze monogamous relationships of entropic non-contextuality (ENC) inequalities. While ENC inequalities are important in quantum information theory and are well studied, theoretical as well as experimental demonstration of their monogamous nature is still elusive. We provide conditio

Mitra Koley, A. J. Parameswaran

In this article we study asymptotic slopes of strongly semistable vector bundles on a smooth projective surface. A connection between asymptotic slopes and strong restriction theorem of a strongly semistable vector bundle is shown. We also give an equivalent criterion of strong semistability of a vector bundle in terms of its asymptotic slopes under some ass

Ankit Sahay, Abhishek Kushwaha, Samadhan A. Pawar, Midhun P. R.

We report the occurrence of amplitude death (AD) of limit cycle oscillations in a bluff body stabilized turbulent combustor through delayed acoustic self-feedback. Such feedback control is achieved by coupling the acoustic field of the combustor to itself through a single coupling tube attached near the anti-node position of the acoustic standing wave. We ob

Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen

The learning objective plays a fundamental role to build a recommender system. Most methods routinely adopt either pointwise or pairwise loss to train the model parameters, while rarely pay attention to softmax loss due to its computational complexity when scaling up to large datasets or intractability for streaming data. The sampled softmax (SSM) loss emerg

Satoru Hayami

A skyrmion crystal (SkX) expressed as a multiple number of spiral modulations manifests itself not only in its peculiar magnetic texture but also in nontrivial transport properties originating from an emergent magnetic field. We here report our numerical results for multiple SkXs in a centrosymmetric tetragonal crystal system. By performing simulated anneali

Ginga Yoshizawa

In time series data analysis, detecting change points on a real-time basis (online) is of great interest in many areas, such as finance, environmental monitoring, and medicine. One promising means to achieve this is the Bayesian online change point detection (BOCPD) algorithm, which has been successfully adopted in particular cases in which the time series o

Zhengxuan Wei, Ruobing Bai

Photoactive liquid crystal elastomers are polymer networks of liquid crystal mesogens embedded with chromophores like azobenzene. They undergo large deformation when illuminated by light of a certain wavelength through photochemical reaction, inspiring exciting new applications. However, despite the recent progresses in both the experiment and theory of thes

Duong Thuy Anh Nguyen, Duong Tung Nguyen, Angelia Nedić

This paper proposes a distributed algorithm to find the Nash equilibrium in a class of non-cooperative convex games with partial-decision information. Our method employs a distributed projected gradient play approach alongside consensus dynamics, with individual agents minimizing their local costs through gradient steps and local information exchange with ne

Kenta Tsukuura

It is known that the set of possible cofinalities $\mathrm{pcf}(A)$ has good properties if $A$ is a progressive interval of regular cardinals. In this paper, we give an interval of regular cardinals $A$ such that $\mathrm{pcf}(A)$ has no good properties in the presense of a measurable cardinal, or in generic extensions by Prikry-type forcing.

Nikolai Vogler, Songlin Li, Yujie Xu, Yujian Mi

We show that a simple unsupervised masking objective can approach near supervised performance on abstractive multi-document news summarization. Our method trains a state-of-the-art neural summarization model to predict the masked out source document with highest lexical centrality relative to the multi-document group. In experiments on the Multi-News dataset

Masaaki Tomii, Thomas Blum, Daniel Hoying, Taku Izubuchi

We calculate $K\to\pi\pi$ matrix elements using periodic boundary conditions as an independent calculation from our previous study with G-parity boundary conditions. We present our preliminary results for $K\to\pi\pi$ three-point functions and matrix elements on a $24^3, a^{-1} = 1$~GeV, $2+1$-flavor M\"obius DWF ensemble at physical pion and kaon masses gen

Raluca M. Balan, Wangjun Yuan

In this article, we study the asymptotic behavior of the spatial integral of the solution to the hyperbolic Anderson model in dimension $d\leq 2$, as the domain of the integral gets large (for fixed time $t$). This equation is driven by a spatially homogeneous Gaussian noise, whose covariance function is either integrable, or is given by the Riesz kernel. Th

Guo-Li Wang, Tianghong Wang, Qiang Li, Chao-Hsi Chang

The spectrum and relativistic wave functions of $B_c$ system are investigated via solving the complete Salpeter equation. Emphases are put on the study of the partial waves of each $J^P$ state. Our study shows that there are three categories of $J^P$ states. The first category contains $0^-$ and $0^+$ states, which are ${}^1S_0$ dominant state with a small a

P. Klose, M. Laine, S. Procacci

A pseudoscalar inflaton $\varphi$, coupled to the topological charge density $F\tilde{F}$ of a non-Abelian sector, can decay to gauge bosons ($\varphi\to g g $), which may thermalize rapidly. The friction felt by $\varphi$ is then increased by non-Abelian "strong sphalerons", leading to a self-amplifying process that can efficiently heat up the medium. We de

Chao Zhang, Peng Yang, Feng Liu, Biao Tu

The global spin alignment of vector mesons is a powerful probe to study the vorticity field of the system produced in non-central relativistic heavy-ion collisions. Since the experimental observables of global spin alignment are sensitive to many factors, proper corrections are need to be taken care of when measuring the global spin alignment of vector meson

Man Ho Chan, Chak Man Lee

Celestial objects such as stars and planets might be able to capture a large amount of dark matter particles through dark matter-nucleon scattering. Many previous studies have considered different celestial objects such as the Sun and the Earth as natural dark matter detectors and obtained some stringent bounds of the dark matter-nucleon scattering cross sec

Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi

Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images. However, most of these algorithms assume the degradation is fixed and known a priori. When the real degradation is unknown or differs from assumption, both the pre-processing module and the consequent high-level task su

Killian Wood, Emiliano Dall'Anese

This paper focuses on stochastic saddle point problems with decision-dependent distributions. These are problems whose objective is the expected value of a stochastic payoff function and whose data distribution drifts in response to decision variables--a phenomenon represented by a distributional map. A common approach to accommodating distributional shift i

Irene Li, Thomas George, Alexander Fabbri, Tammy Liao

Effective human learning depends on a wide selection of educational materials that align with the learner's current understanding of the topic. While the Internet has revolutionized human learning or education, a substantial resource accessibility barrier still exists. Namely, the excess of online information can make it challenging to navigate and discover

Canqi Yao, Shibo Chen, Mauro Salazar, Zaiyue Yang

This paper investigates the scheduling problem of a fleet of electric vehicles, providing mobility as a service to a set of time-specified customers, where the operator needs to solve the routing and charging problem jointly for each EV. Hereby we consider incentive-aware customers and propose that the operator offers monetary incentives to customers in exch

Santosh Kumar Radha, Casey Jao

The similarity between objects is significant in a broad range of areas. While similarity can be measured using off-the-shelf distance functions, they may fail to capture the inherent meaning of similarity, which tends to depend on the underlying data and task. Moreover, conventional distance functions limit the space of similarity measures to be symmetric a

Chi-Ho Chan, Tsvi Piran, Julian H. Krolik

The magnetorotational instability (MRI) has been extensively studied in circular magnetized disks, and its ability to drive accretion has been demonstrated in a multitude of scenarios. There are reasons to expect eccentric magnetized disks to also exist, but the behavior of the MRI in these disks remains largely uncharted territory. Here we present the first

Wei Wang, Xiang-Gen Xia, Chuanjiang He, Zemin Ren

In this paper, we propose a new GPU implementation of the Katsevich algorithm for helical CT reconstruction. Our implementation divides the sinograms and reconstructs the CT images pitch by pitch. By utilizing the periodic properties of the parameters of the Katsevich algorithm, our method only needs to calculate these parameters once for all the pitches and

Victor Guba

Let $R=K[G]$ be a group ring of a group $G$ over a field $K$. It is known that if $G$ is amenable then $R$ satisfies the Ore condition: for any $a,b\in R$ there exist $u,v\in R$ such that $au=bv$, where $u\ne0$ or $v\ne0$. It is also true for amenable groups that a non-zero solution exists for any finite system of linear equations over $R$, where the number

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai

Many previous studies aim to augment collaborative filtering with deep neural network techniques, so as to achieve better recommendation performance. However, most existing deep learning-based recommender systems are designed for modeling singular type of user-item interaction behavior, which can hardly distill the heterogeneous relations between user and it

Lokahith Agasthya, Patricio Clark Di Leoni, Luca Biferale

Nudging is a data assimilation technique that has proved to be capable of reconstructing several highly turbulent flows from a set of partial spatiotemporal measurements. In this study we apply the nudging protocol on the temperature field in a Rayleigh-B\'enard Convection system at varying levels of turbulence. We assess the global, as well as scale by scal

Quan Feng, Songcan Chen

Multi-task learning is to improve the performance of the model by transferring and exploiting common knowledge among tasks. Existing MTL works mainly focus on the scenario where label sets among multiple tasks (MTs) are usually the same, thus they can be utilized for learning across the tasks. While almost rare works explore the scenario where each task only

Shipeng Yan, Songyang Zhang, Xuming He

This paper tackles the problem of few-shot learning, which aims to learn new visual concepts from a few examples. A common problem setting in few-shot classification assumes random sampling strategy in acquiring data labels, which is inefficient in practical applications. In this work, we introduce a new budget-aware few-shot learning problem that not only a

Tianhua Zhu

Since the birth of artificial intelligence 70 years ago, attempts at literary "creation" with computers are present in the course of technological development, creating what one might call "artificial intelligence literature" (AI literature). Evolving from "textual experiments" conducted by technologists to "experimental texts" that explore the possibilities

Sachin Konan, Kevin J Liang, Li Yin

In many applications, such as autonomous driving, hand manipulation, or robot navigation, object detection methods must be able to detect objects unseen in the training set. Open World Detection(OWD) seeks to tackle this problem by generalizing detection performance to seen and unseen class categories. Recent works have seen success in the generation of clas

Junwei Shen, Shirin Golchi, Erica E. M. Moodie, David Benrimoh

Adaptive approaches, allowing for more flexible trial design, have been proposed for individually randomized trials to save time or reduce sample size. However, adaptive designs for cluster-randomized trials in which groups of participants rather than individuals are randomized to treatment arms are less common. Motivated by a cluster-randomized trial design

Kohei Miyaguchi

We are concerned with the problem of hyperparameter selection for the fitted Q-evaluation (FQE). FQE is one of the state-of-the-art method for offline policy evaluation (OPE), which is essential to the reinforcement learning without environment simulators. However, like other OPE methods, FQE is not hyperparameter-free itself and that undermines the utility

Hillel Sanhedrai, Shlomo Havlin

Epidemics on complex networks is a widely investigated topic in the last few years, mainly due to the last pandemic events. Usually, real contact networks are dynamic, hence much effort has been invested in studying epidemics on evolving networks. Here we propose and study a model for evolving networks based on varying degrees, where at each time step a node

Shuang Li, Qiuwei Li

Tensor optimization is crucial to massive machine learning and signal processing tasks. In this paper, we consider tensor optimization with a convex and well-conditioned objective function and reformulate it into a nonconvex optimization using the Burer-Monteiro type parameterization. We analyze the local convergence of applying vanilla gradient descent to t

Omid Orang, Petrônio Cândido de Lima e Silva, Frederico Gadelha Guimarães

Among various soft computing approaches for time series forecasting, Fuzzy Cognitive Maps (FCM) have shown remarkable results as a tool to model and analyze the dynamics of complex systems. FCM have similarities to recurrent neural networks and can be classified as a neuro-fuzzy method. In other words, FCMs are a mixture of fuzzy logic, neural network, and e

Yan Wang, Moussa Gueye, Steven J. Greybush, Helen Greatrex

Rainfall is an important variable to be able to monitor and forecast across Africa, due to its impact on agriculture, food security, climate related diseases and public health. Numerical Weather Models (NWM) are an important component of this work, due to their complete spatial coverage, high resolution, and ability to forecast into the future. In this study

Aras Asaad, Dashti Ali, Taban Majeed, Rasber Rashid

An Important tool in the field topological data analysis is known as persistent Homology (PH) which is used to encode abstract representation of the homology of data at different resolutions in the form of persistence diagram (PD). In this work we build more than one PD representation of a single image based on a landmark selection method, known as local bin

X. Y. Zhu, H. Zhang, D. J. Gawryluk, Z. X. Zhen

We report on systematic muon-spin rotation and relaxation ($\mu$SR) studies of the magnetic properties of EuAl$_4$ and EuGa$_4$ single crystals at a microscopic level. Transverse-field $\mu$SR measurements, spanning a wide temperature range (from 1.5 to 50 K), show clear bulk AFM transitions, with an almost 100% magnetic volume fraction in both cases. Zero-f

Xiangliang Kong, Jing Ye, Bin Chen, Fan Guo

A number of double coronal X-ray sources have been observed during solar flares by RHESSI, where the two sources reside at different sides of the inferred reconnection site. However, where and how are these X-ray-emitting electrons accelerated remains unclear. Here we present the first model of the double coronal hard X-ray (HXR) sources, where electrons are

Julian Martinez-Iriarte, Gabriel Montes-Rojas, Yixiao Sun

This paper studies the unconditional effects of a general policy intervention, which includes location-scale shifts and simultaneous shifts as special cases. The location-scale shift is intended to study a counterfactual policy aimed at changing not only the mean or location of a covariate but also its dispersion or scale. The simultaneous shift refers to th

Haiquan Lu, Yong Zeng

This paper proposes a novel broadband transmission technology, termed delay alignment modulation (DAM), which enables the low-complexity equalization-free single-carrier communication, yet without suffering from inter-symbol interference (ISI). The key idea of DAM is to deliberately introduce appropriate delays for information-bearing symbols at the transmit

Dongwei Zhao, Mehdi Jafari, Audun Botterud, Apurba Sakti

Arbitrage is one important revenue source for energy storage in electricity markets. However, a large amount of storage in the market will impact the energy price and reduce potential revenues. This can lead to strategic behaviors of profit-seeking storage investors. To study the investors' strategic storage investments, we formulate a non-cooperative game b

Joel Kamnitzer

In order to give a combinatorial descriptions of tensor product multiplicites for semisimple groups, it is useful to find bases for representations which are compatible with the actions of Chevalley generators of the Lie algebra. There are three known examples of such bases, each of which flows from geometric or algebraic mountain. Remarkably, each mountain

Yu. G. Peisakhovich, A. A. Shtygashev

A numerical-analytical simulation of scattering by a three-barrier heterostructure of an electronic Gaussian wave packet, the spectral width of which is on the order of the distance between the levels of the doublet of quasi-stationary states, is carried out. It is shown that as a result of scattering, damped waves of electron charge and current densities ar

Mariana Lira, Juan Carlos Degollado, Claudia Moreno, Darío Núñez

Modelling as a dipole the magnetic interaction of a binary system of neutron stars, we are able to include the magnetic effects in the Newtonian and in the inspiral dynamics of the system using an equivalent one-body description. Furthermore, in the inspiral stage we determine the role of the magnetic interaction in the waveforms generated by the system and

Liang Li, Ruipeng Shen, Chenhui Wang, Lijuan Wei

In this work we consider weakly non-radiative solutions to both linear and non-linear wave equations. We first characterize all weakly non-radiative free waves, without the radial assumption. Then in dimension 3 we show that the initial data of non-radiative solutions to a wide range of nonlinear wave equations are similar to those of non-radiative free wave

Reza Mahroo, Amin Kargarian

This paper proposes a hybrid quantum-classical algorithm to solve a fundamental power system problem called unit commitment (UC). The UC problem is decomposed into a quadratic subproblem, a quadratic unconstrained binary optimization (QUBO) subproblem, and an unconstrained quadratic subproblem. A classical optimization solver solves the first and third subpr

Michael A. Allen, Kenneth Edwards

The number of ways to tile an $n$-board (an $n\times1$ rectangular board) with $(\frac12,\frac12;1)$-, $(\frac12,\frac12;2)$-, and $(\frac12,\frac12;3)$-combs is $T_{n+2}^2$ where $T_n$ is the $n$th tribonacci number. A $(\frac12,\frac12;m)$-comb is a tile composed of $m$ sub-tiles of dimensions $\frac12\times1$ (with the shorter sides always horizontal) sep

Liang Li, Ruipeng Shen, Chenhui Wang

In this work we consider the operator \[ (\mathbf{T} G) (x)= \int_{\mathbb{S}^2} G(x\cdot \omega, \omega) d\omega, \quad x\in \mathbb{R}^3, \; G\in L^2(\mathbb{R}\times \mathbb{S}^2). \] This is the adjoint operator of the Radon transform. We manage to give an optimal $L^6$ decay estimate of $\mathbf{T} G$ near the infinity by a geometric method, if the func

Ping Li, Weijie Zhao

We develop the "generalized consistent weighted sampling" (GCWS) for hashing the "powered-GMM" (pGMM) kernel (with a tuning parameter $p$). It turns out that GCWS provides a numerically stable scheme for applying power transformation on the original data, regardless of the magnitude of $p$ and the data. The power transformation is often effective for boostin

Ali Abdollahi, Jianwei Li, Xiaojun Li, Trevor Jones

A voltage-based method is proposed to correct battery pack state of charge (SOC) estimation at the charge-end. Two main characteristics make the charge-end time span a good opportunity to correct SOC estimation: first, it is easy to detect when the battery is at the last stage of charging because the charging profile is known to the BMS designer and also dur

Eitan Tadmor

We provide a bird's eye view on developments in analyzing the long time, large crowd behavior of Cucker-Smale alignment dynamics. We consider a class of (fully-)discrete models, paying particular attention to general alignment protocols in which agents, with possibly time-dependent masses, are driven by a large class of heavy-tailed communication kernels. Th

Nora Horanyi, Kedi Xia, Kwang Moo Yi, Abhishake Kumar Bojja

We propose a novel optimization framework that crops a given image based on user description and aesthetics. Unlike existing image cropping methods, where one typically trains a deep network to regress to crop parameters or cropping actions, we propose to directly optimize for the cropping parameters by repurposing pre-trained networks on image captioning an

Daniel Simons, Erik Gustafson, Yannick Meurice

We examine the decay rate of the particle decay $B^0 \rightarrow D^- \ell^+ \nu_{\ell}$ using data collected from the Belle Collaboration. We studied three parameterizations of the form factor which describe the differential decay rate, the Caprini, Lellouch, and Neubert (CLN) parametrization, the Boyd, Grinstein, and Lebed (BGL) parametrization, and the Bou

Kiprian Berbatov, Pieter D. Boom, Andrew L. Hazel, Andrey P. Jivkov

The formulation of combinatorial differential forms, proposed by Forman for analysis of topological properties of discrete complexes, is extended by defining the operators required for analysis of physical processes dependent on scalar variables. The resulting description is intrinsic, different from the approach known as Discrete Exterior Calculus, because

Martin Cooney, Eric Järpe, Alexey Vinel

Robots are being designed to communicate with people in various public and domestic venues in a helpful, discreet way. Here, we use a speculative approach to shine light on a new concept of robot steganography (RS), that a robot could seek to help vulnerable populations by discreetly warning of potential threats. We first identify some potentially useful sce

Felix Wimbauer, Shangzhe Wu, Christian Rupprecht

With increasing focus on augmented and virtual reality applications (XR) comes the demand for algorithms that can lift objects from images and videos into representations that are suitable for a wide variety of related 3D tasks. Large-scale deployment of XR devices and applications means that we cannot solely rely on supervised learning, as collecting and an

Hongyu Zhu, Jan Schuemann, Qixian Zhang, Leo E Gerweck

FLASH radiation has been reported to efficiently suppress tumor growth while sparing normal tissue, however, the mechanism of the differential tissue sparing effect is still not known. Oxygen has long been known to profoundly impact radiobiological responses, and radiolytic oxygen depletion has been considered to be a possible cause or contributor to the FLA

Marvin Pohl, Sebastian Malerz, Florian Trinter, Chin Lee

We present an experimental X-ray photoelectron circular dichroism (PECD) study of liquid fenchone at the C 1s edge. A novel setup to enable PECD measurements on a liquid microjet [Malerz et al., Rev. Sci. Instrum., 2022, 93, 015101] was used. For the C 1s line assigned to fenchone's carbonyl carbon, a non-vanishing asymmetry is found in the intensity of phot

Chandralekha Singh

This article describes reflections on the Fifth International Conference on Women in Physics which was a conference attended by 215 female physicists and a few male physicists from 49 different countries. The article focuses on the barriers that women face in their professional advancement in physics and the extent to which the situation is different in vari

Edwin K. P. Chong

Linear minimum mean square error (LMMSE) estimation is often ill-conditioned, suggesting that unconstrained minimization of the mean square error is an inadequate approach to filter design. To address this, we first develop a unifying framework for studying constrained LMMSE estimation problems. Using this framework, we explore an important structural proper