January 2022 arXiv papers — page 106

L. Gordeev, E. H. Haeusler

In [GH1] and [GH2] (see also [GH3]) we presented full proof of the equalities NP = coNP = PSPACE. These results have been obtained by the novel proof theoretic tree-to-dag compressing techniques adapted to Prawitz's Natural Deduction (ND) for propositional minimal logic coupled with the corresponding Hudelmaier's cutfree sequent calculus. In this paper we pr

Priyanka Grover, Sushil Singla

An expression for the subdifferential of the joint numerical radius is obtained. Its applications to the best approximation problems in the joint numerical radius are discussed.

Lam Pham, Dat Ngo, Truong Hoang, Alexander Schindler

In this paper, we evaluate various deep learning frameworks for detecting respiratory anomalies from input audio recordings. To this end, we firstly transform audio respiratory cycles collected from patients into spectrograms where both temporal and spectral features are presented, referred to as the front-end feature extraction. We then feed the spectrogram

Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake

This paper proposes a segmentation method of infection regions in the lung from CT volumes of COVID-19 patients. COVID-19 spread worldwide, causing many infected patients and deaths. CT image-based diagnosis of COVID-19 can provide quick and accurate diagnosis results. An automated segmentation method of infection regions in the lung provides a quantitative

Richard Apaua, Harjinder Singh Lallie

Mobile banking applications have gained popularity and have significantly revolutionised the banking industry. Despite the convenience offered by M-Banking Apps, users are often distrustful of the security of the applications due to an increasing trend of cyber security compromises, cyber-attacks, and data breaches. Considering the upsurge in cyber security

Juan Cruz Viotti, Mital Kinderkhedia

We present a comprehensive benchmark of JSON-compatible binary serialization specifications using the SchemaStore open-source test suite collection of over 400 JSON documents matching their respective schemas and representative of their use across industries. We benchmark a set of schema-driven (ASN.1, Apache Avro, Microsoft Bond, Cap'n Proto, FlatBuffers, P

Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto

This paper proposes an automated segmentation method of infection and normal regions in the lung from CT volumes of COVID-19 patients. From December 2019, novel coronavirus disease 2019 (COVID-19) spreads over the world and giving significant impacts to our economic activities and daily lives. To diagnose the large number of infected patients, diagnosis assi

Igor O. Sokolov, Werner Dobrautz, Hongjun Luo, Ali Alavi

Transcorrelated methods provide an efficient way of partially transferring the description of electronic correlations from the ground state wavefunction directly into the underlying Hamiltonian. In particular, Dobrautz et al. [Phys. Rev. B, 99(7), 075119, (2019)] have demonstrated that the use of momentum-space representation, combined with a non-unitary sim

Fraser Binns, Subhankar Dey

Viewing the BRAID invariant as a generator of link Floer homology we generalise work of Baldwin-Vela-Vick to obtain rank bounds on the next to top grading of knot Floer homology. These allow us to classify links with knot Floer homology of rank at most eight, and prove a variant of a classification of links with Khovanov homology of low rank due to Xie-Zhang

Walter Bridges, Ali Uncu

Recently Corteel and Welsh outlined a technique for finding new sum-product identities by using functional relations between generating functions for cylindric partitions and a theorem of Borodin. Here, we extend this framework to include very general product-sides coming from work of Han and Xiong. In doing so, we are led to consider structures such as weig

Emilio Minichiello, Manuel Rivera, Mahmoud Zeinalian

We establish an explicit comparison between two constructions in homotopy theory: the left adjoint of the homotopy coherent nerve functor, also known as the rigidification functor, and the Kan loop groupoid functor. This is achieved by considering localizations of the rigidification functor, unraveling a construction of Hinich, and using a sequence of operat

Thomas Grubl, Harjinder Singh Lallie

The precise age estimation of child sexual abuse and exploitation (CSAE) victims is one of the most significant digital forensic challenges. Investigators often need to determine the age of victims by looking at images and interpreting the sexual development stages and other human characteristics. The main priority - safeguarding children -- is often negativ

Sergi Elizalde, Bruce Sagan

Associated with any composition beta=(a,b,...) is a corresponding fence poset F(beta) whose covering relations are x_1 < x_2 < ... < x_{a+1} > x_{a+2} > ... > x_{a+b+1} < x_{a+b+2} < ... The distributive lattice L(beta) of all lower order ideals of F(beta) is important in the theory of cluster algebras. In addition, its rank generating function r(q;beta) is

Orhun Buğra Baran, Ramazan Gökberk Cinbiş

Over the last couple of years few-shot learning (FSL) has attracted great attention towards minimizing the dependency on labeled training examples. An inherent difficulty in FSL is the handling of ambiguities resulting from having too few training samples per class. To tackle this fundamental challenge in FSL, we aim to train meta-learner models that can lev

Federico Piazzon

Optimal experimental designs are probability measures with finite support enjoying an optimality property for the computation of least squares estimators. We present an algorithm for computing optimal designs on finite sets based on the long-time asymptotics of the gradient flow of the log-determinant of the so called information matrix. We prove the converg

Douglas Newman

Clifford Unification describes all the observed fundamental fermions in terms of seven commuting elements of the $Cl_{7,7}$ Clifford algebra. The eigenvalues of each commuting element define a binary quantum number, which relates to a fermion property that is conserved in decays and interactions. These include the quantum number descriptions of a hitherto un

Elette Boyle, Itai Dinur, Niv Gilboa, Yuval Ishai

Can we sense our location in an unfamiliar environment by taking a sublinear-size sample of our surroundings? Can we efficiently encrypt a message that only someone physically close to us can decrypt? To solve this kind of problems, we introduce and study a new type of hash functions for finding shifts in sublinear time. A function $h:\{0,1\}^n\to \mathbb{Z}

Zhenjun Dong, Yong Zeng

Extremely large-scale array (XL-array) communications correspond to systems whose antenna sizes are so large that the scatterers and/or users may no longer be located in the far-field region. By discarding the conventional far-field uniform plane wave (UPW) assumption, this letter studies the near-field spatial correlation of XL-array communications, by taki

Rui Qiang Wang, Zhen Qiang yin, Rong Wang, Shuang Wang

Quantum key distribution(QKD) allows two remote parties to share information-theoretic secret keys. Many QKD protocols assume the phase of encoding state can be continuous randomized from 0 to 2 pi, which, however, may be questionable in experiment. This is particularly the case in the recently proposed twin-field(TF) QKD, which has received a lot of attenti

Luiz Vale Silva

The Standard Model Effective Field Theory (SMEFT) is a universal way of parametrizing New Physics (NP) manifesting as new, heavy particle interactions with the Standard Model (SM) degrees of freedom, that respect the SM gauged symmetries. Higher order terms in the NP interactions possibly lead to sizable effects, mandatory for meaningful phenomenological stu

Alastair Fletcher, Jacob Pratscher

We study the mean radius growth function for quasiconformal mappings. We give a new sub-class of quasiconformal mappings in $\mathbb{R}^n$, for $n\geq 2$, called bounded integrable parameterization mappings, or BIP maps for short. These have the property that the restriction of the Zorich transform to each slice has uniformly bounded derivative in $L^{n/(n-1

Yiming Luo, Jialin Wang, Rongkai Shi, Hai-Ning Liang

In recent years, Virtual Reality (VR) Head-Mounted Displays (HMD) have been used to provide an immersive, first-person view in real-time for the remote-control of Unmanned Ground Vehicles (UGV). One critical issue is that it is challenging to perceive the distance of obstacles surrounding the vehicle from 2D views in the HMD, which deteriorates the control o

Yu Jiang, Christian Poellabauer

Medication errors most commonly occur at the ordering or prescribing stage, potentially leading to medical complications and poor health outcomes. While it is possible to catch these errors using different techniques; the focus of this work is on textual and contextual analysis of prescription information to detect and prevent potential medication errors. In

Simone Blumer

The Kurosh theorem for groups provides the structure of any subgroup of a free product of groups and its proof relies on Bass-Serre theory of groups acting on trees. In the case of Lie algebras, such a general theory does not exists and the Kurosh theorem is false in general, as it was first noticed by Shirshov. However, we prove that, for a class of positiv

Guido Buonincontri

Heart failure is a leading cause of mortality in the Western world. The mouse is a widely used model for a number of diseases, induced by genetic modification or surgical intervention. When performing experiments in mice, in vivo magnetic resonance imaging (MRI) can be used to evaluate heart anatomy and function at multiple levels. Volumetric measurements of

Sijie Li, Cheuk Ting Li

We consider a network coding problem where the destination wants to recover the sum of the signals (Gaussian random variables or random finite field elements) at all the source nodes, but the sum must be kept secret from an eavesdropper that can wiretap on a subset of edges. This setting arises naturally in sensor networks and federated learning, where the s

Yixin Guo, Hiroyuki Tajima, Haozhao Liang

We theoretically study the ground-state properties and the condensations of exciton-like Cooper pairs and biexciton-like Cooper quartets in an electron-hole system. Applying the variational approach associated based on the quartet Bardeen-Cooper-Schrieffer (BCS) model to the four-component fermionic system consisting of spin-1/2 electrons and spin-1/2 holes,

Nourelhouda Groun, Maria Villalba-Orero, Enrique Lara-Pezzi, Eusebio Valero

In this work, we study in detail the performance of Higher Order Dynamic Mode Decomposition (HODMD) technique when applied to echocardiography images. HODMD is a data-driven method generally used in fluid dynamics and in the analysis of complex non-linear dynamical systems modeling several complex industrial applications. In this paper we apply HODMD, for th

Abhishek Gupta, Himanshu Soni, Raunak Joshi, Ronald Melwin Laban

A lot of prognostication methodologies have been formulated for early detection of Polycystic Ovary Syndrome also known as PCOS using Machine Learning. PCOS is a binary classification problem. Dimensionality Reduction methods impact the performance of Machine Learning to a greater extent and using a Supervised Dimensionality Reduction method can give us a ne

Maryam Daneshi, Reza Taghavi Fard, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Solar shading design should be done for the desired Indoor Environmental Quality (IEQ) in the early design stages. This field can be very challenging and time-consuming also requires experts, sophisticated software, and a large amount of money. The primary purpose of this research is to design a simple tool to study various models of solar shadings and make

Satoshi Nato, Yiqiang Sheng

Identifying anomaly multimedia traffic in cyberspace is a big challenge in distributed service systems, multiple generation networks and future internet of everything. This letter explores meta-generalization for a multiparty privacy learning model in graynet to improve the performance of anomaly multimedia traffic identification. The multiparty privacy lear

Prashant Sharma, Hadeel Saadany, Leonardo Zilio, Diptesh Kanojia

Acronyms are abbreviated units of a phrase constructed by using initial components of the phrase in a text. Automatic extraction of acronyms from a text can help various Natural Language Processing tasks like machine translation, information retrieval, and text summarisation. This paper discusses an ensemble approach for the task of Acronym Extraction, which

Liqin Zhou, Yuting Qian, Changming Yue, Zhong Fang

Based on the first-principles calculations within local density approximation and model analysis, we propose that the iso-structural compounds Cu2SnS3 and Cu2SnSe3 are both the simplest nodal line semimetals with only one nodal line in their crystal momentum space when spin-orbit coupling (SOC) is ignored. The including of SOC drives Cu2SnS3 into a Weyl semi

Rebecca G. Martin, Stephen H. Lubow

A highly misaligned gas disk around one component of a binary star system can undergo global Kozai-Lidov (KL) oscillations for which the disk inclination and eccentricity are exchanged. With hydrodynamical simulations of a gas and dust disk we explore the effects of these oscillations on the dust density distribution. For dust that is marginally coupled to t

Tatsuya Hayashi, Fumitaka Yura, Jun Mada, Hiroki Kurihara

A two-dimensional mathematical model for dynamics of endothelial cells in angiogenesis is investigated. Angiogenesis is a morphogenic process in which new blood vessels emerge from an existing vascular network. Recently a one-dimensional discrete dynamical model has been proposed to reproduce elongation, bifurcation, and cell motility such as cell-mixing dur

Hiraku Nozawa, Subaru Nomoto

We introduce and study generalized Bishop frames on regular curves, which are generalizations of the Frenet and Bishop frames for regular curves on higher dimensional spaces. There are four types of generalized Bishop frames on regular curves on $\mathbb{E}^{4}$ up to the change of the order of vectors fixing the first one which is the tangent vector. One of

Wen Li, Mert Okyay, Rafael I. Nepomechie

A probabilistic algorithm for preparing Bethe eigenstates of the spin-1/2 Heisenberg spin chain on a quantum computer has recently been found. We derive an exact formula for the success probability of this algorithm in terms of the Gaudin determinant, and we study its large-length limit. We demonstrate the feasibility of computing antiferromagnetic ground-st

Chris Gustin, Łukasz Dusanowski, Sven Höfling, Stephen Hughes

We describe how a coherent optical drive that is near-resonant with the upper rungs of a three-level ladder system, in conjunction with a short pulse excitation, can be used to provide a frequency-tunable source of on-demand single photons. Using an intuitive master equation model, we identify two distinct regimes of device operation: (i) for a resonant driv

Kuluhan Binici, Shivam Aggarwal, Nam Trung Pham, Karianto Leman

Data-Free Knowledge Distillation (KD) allows knowledge transfer from a trained neural network (teacher) to a more compact one (student) in the absence of original training data. Existing works use a validation set to monitor the accuracy of the student over real data and report the highest performance throughout the entire process. However, validation data m

Meng-Shiun Tsai, Pei-Ze Chiang, Yi-Hsuan Tsai, Wei-Chen Chiu

Self-supervised learning on point clouds has gained a lot of attention recently, since it addresses the label-efficiency and domain-gap problems on point cloud tasks. In this paper, we propose a novel self-supervised framework to learn informative representations from partial point clouds. We leverage partial point clouds scanned by LiDAR that contain both c

Simon Lupart, Benoit Favre, Vassilina Nikoulina, Salah Ait-Mokhtar

MeSH (Medical Subject Headings) is a large thesaurus created by the National Library of Medicine and used for fine-grained indexing of publications in the biomedical domain. In the context of the COVID-19 pandemic, MeSH descriptors have emerged in relation to articles published on the corresponding topic. Zero-shot classification is an adequate response for

Nikolaos Ioannis Bountos, Dimitrios Michail, Ioannis Papoutsis

The detection of early signs of volcanic unrest preceding an eruption, in the form of ground deformation in Interferometric Synthetic Aperture Radar (InSAR) data is critical for assessing volcanic hazard. In this work we treat this as a binary classification problem of InSAR images, and propose a novel deep learning methodology that exploits a rich source of

Darlison Nyirenda, Beaullah Mugwangwavari

In this paper, we consider various theorems of P.A. MacMahon and M.V. Subbarao. For a non-negative integer $n$, MacMahon proved that the number of partitions of $n$ wherein parts have multiplicity greater than 1 is equal to the number of partitions of $n$ in which odd parts are congruent to 3 modulo 6. We give a new bijective proof for this theorem and its g

Gao Huang, Yulin Wang, Kangchen Lv, Haojun Jiang

Spatial redundancy widely exists in visual recognition tasks, i.e., discriminative features in an image or video frame usually correspond to only a subset of pixels, while the remaining regions are irrelevant to the task at hand. Therefore, static models which process all the pixels with an equal amount of computation result in considerable redundancy in ter

Rui-Yang Ju, Ting-Yu Lin, Jia-Hao Jian, Jen-Shiun Chiang

With the continuous development of neural networks for computer vision tasks, more and more network architectures have achieved outstanding success. As one of the most advanced neural network architectures, DenseNet shortcuts all feature maps to solve the model depth problem. Although this network architecture has excellent accuracy with low parameters, it r

Diego Tapias, Peter Sollich

Inspired by works on the Anderson model on sparse graphs, we devise a method to analyze the localization properties of sparse systems that may be solved using cavity theory. We apply this method to study the properties of the eigenvectors of the master operator of the sparse Barrat-M\'ezard trap model, with an emphasis on the extended phase. As probes for lo

Arpan Das

We discuss the quantum statistical fluctuations of energy in subsystems of hot relativistic gas for both spin-zero and spin half particles. We explicitly show the system size dependence of the quantum statistical fluctuation of energy. Our results show that with decreasing system size quantum statistical fluctuations increase substantially. As the consistenc

Gamal Elkoumy, Alisa Pankova, Marlon Dumas

The applicability of process mining techniques hinges on the availability of event logs capturing the execution of a business process. In some use cases, particularly those involving customer-facing processes, these event logs may contain private information. Data protection regulations restrict the use of such event logs for analysis purposes. One way of ci

María J. Martín

We review the relation between the classical formulas of the pre-Schwarzian and Schwarzian derivatives of locally univalent analytic functions and the derivatives of the generating functions of the methods due to Newton and Halley, respectively, for approximating zeros. We extend these relations to the cases when the functions considered are harmonic.

Francisco Mota

In this paper we show an alternative way of defining Fourier Series and Transform by using the concept of convolution with exponential signals. This approach has the advantage of simplifying proofs of transforms properties and, in our view, may be interesting for educational purposes.

G. Cosentino, I. Jiménez-Serra, J. C. Tan, J. D. Henshaw

Supernova remnants (SNRs) contribute to regulate the star formation efficiency and evolution of galaxies. As they expand into the interstellar medium (ISM), they transfer vast amounts of energy and momentum that displace, compress and heat the surrounding material. Despite the extensive work in galaxy evolution models, it remains to be observationally valida

Pragnya Das, Elisa Palezzato, Simona Settepanella

In 1989 Manin and Schechtman defined the discriminantal arrangement $\mathcal{B}(n, k,\mathcal{A})$ associated to a generic arrangement $\mathcal{A}$ of $n$ hyperplanes in a $k$-dimensional space. An equivalent notion was already introduced by Crapo in 1985 with the name of geometry of circuits. While both those papers were mainly focused on the case in whic

Nguyen T. Thao, Dominik Rzepka, Marek Miśkowicz

Leaky integrate-and-fire (LIF) encoding is a model of neuron transfer function in biology that has recently attracted the attention of the signal processing and neuromorphic computing communities as a technique of event-based sampling for data acquisition. While LIF enables the implementation of analog-circuit signal samplers of lower complexity and higher a

Bo Tan, Bo Sun

The idea of exploiting the Wi-Fi bursts as the medium for sensing purposes, particularly for the human targets in the indoor environment, was cultivated in both radar and computer science communities and it has became a noticeable research genre with cross-disciplinary impact in security, healthcare, human-machine interaction etc.This article comparatively i

Omid Rohanian, Samaneh Kouchaki, Andrew Soltan, Jenny Yang

Early detection of COVID-19 is an ongoing area of research that can help with triage, monitoring and general health assessment of potential patients and may reduce operational strain on hospitals that cope with the coronavirus pandemic. Different machine learning techniques have been used in the literature to detect coronavirus using routine clinical data (b

Jon Bohlin

A model is presented relating the evolution of genomic GC content over time to AT$\rightarrow$GC and GC$\rightarrow$AT mutation rates. By employing It\^o calculus it is shown that if mutation rates in asexually reproducing organisms are subject to random perturbations that can vary over time several implications follow. For instance, an extra Brownian motion

Prerana Mukherjee, Vinay Kaushik, Ronak Gupta, Ritika Jha

Predicting attributes in the landmark free facial images is itself a challenging task which gets further complicated when the face gets occluded due to the usage of masks. Smart access control gates which utilize identity verification or the secure login to personal electronic gadgets may utilize face as a biometric trait. Particularly, the Covid-19 pandemic

Victor J. W. Guo

Employing a quadratic transformation formula of Rahman and the method of `creative microscoping' (introduced by the author and Zudilin in 2019), we provide some new $q$-supercongruences for truncated basic hypergeometric series. In particular, we confirm two recent conjectures of Liu and Wang. We also propose some related conjectures on supercongruences and

Ding Wang, Yueheng Lan

Searching recurrent patterns in complex systems with high-dimensional phase spaces is an important task in diverse fields. In the current work, an improved scheme is proposed to accelerate the recently designed variational approach for finding periodic orbits in systems with chaotic dynamics based on the existence of inertial manifold widely observed in vari

Keren Censor-Hillel, Orr Fischer, François Le Gall, Dean Leitersdorf

The possibilities offered by quantum computing have drawn attention in the distributed computing community recently, with several breakthrough results showing quantum distributed algorithms that run faster than the fastest known classical counterparts, and even separations between the two models. A prime example is the result by Izumi, Le Gall, and Magniez [

P. F. Rohde, S. Walch, D. Seifried, A. P. Whitworth

During the early phases of low-mass star formation, episodic accretion causes the ejection of high-velocity outflow bullets, which carry a fossil record of the driving protostar's accretion history. We present 44 SPH simulations of $1\,\mathrm{M}_{\odot}$ cores, covering a wide range of initial conditions, and follow the cores for five free-fall times. Indiv

V. G. Bornyakov, V. A. Goy, E. A. Kozlovsky, V. K. Mitrjushkin

In the Landau-gauge lattice gluodynamics we find that, both in the SU(2) and SU(3) theory, a correlation of the Polyakov loop with the asymmetry of the $A^2$ gluon condensate as well as with the longitudinal propagator makes it possible to determine the critical behavior of these quantities. We discuss finite-volume corrections and reveal that they can be re

Farzaneh Tatari, Aquib Mustafa, Majid Mazouchi, Hamidreza Modares

This work presents a rigorous analysis of the adverse effects of cyber-physical attacks on the performance of multi-agent consensus with event-triggered control protocols. It is shown how a strategic malicious attack on sensors and actuators can deceive the triggering condition of both state-based event-triggered mechanism and combinational state-based event

A. P. Misra, Animesh Roy, Debjani Chatterjee, T. D. Kaladze

The theory of low-frequency internal gravity waves (IGWs) is readdressed in the stable stratified weakly ionized Earth's ionosphere. The formation of dipolar vortex structures and their dynamical evolution, as well as, the emergence of chaos in the wave-wave interactions are studied both in presence and absence of the Pedersen conductivity. The latter is sho

Kelvin L. T. Fung, Simon T. Perrault, Michael T. Gastner

A contiguous area cartogram is a geographic map in which the area of each region is proportional to numerical data (e.g., population size) while keeping neighboring regions connected. In this study, we investigated whether value-to-area legends (square symbols next to the values represented by the squares' areas) and grid lines aid map readers in making bett

Ali Bou Nassif, Ismail Shahin, Ashraf Elnagar, Divya Velayudhan

Speaker recognition systems are widely used in various applications to identify a person by their voice; however, the high degree of variability in speech signals makes this a challenging task. Dealing with emotional variations is very difficult because emotions alter the voice characteristics of a person; thus, the acoustic features differ from those used t

Lingfeng Shen, Haiyun Jiang, Lemao Liu, Shuming Shi

It has been shown that natural language processing (NLP) models are vulnerable to a kind of security threat called the Backdoor Attack, which utilizes a `backdoor trigger' paradigm to mislead the models. The most threatening backdoor attack is the stealthy backdoor, which defines the triggers as text style or syntactic. Although they have achieved an incredi

Tianhan Zhang, Yuxiao Yi, Yifan Xu, Zhi X. Chen

Machine learning has long been considered as a black box for predicting combustion chemical kinetics due to the extremely large number of parameters and the lack of evaluation standards and reproducibility. The current work aims to understand two basic questions regarding the deep neural network (DNN) method: what data the DNN needs and how general the DNN m

Xiaoliang Wang, Andrew Harrison

How patterns and structures undergo symmetry breaking and self-organize within biological systems from initially homogeneous states is a key issue for biological development. The activator-inhibitor (AI) mechanism, derived from reaction-diffusion (RD) models, has been widely believed to be the elementary mechanism for biological pattern formation. This mecha

Jash Dalvi, Sanket Bafna, Devansh Bagaria, Shyamal Virnodkar

Face Recognition has proven to be one of the most successful technology and has impacted heterogeneous domains. Deep learning has proven to be the most successful at computer vision tasks because of its convolution-based architecture. Since the advent of deep learning, face recognition technology has had a substantial increase in its accuracy. In this paper,

Ana Carpio, Rafael Gonzalez-Albaladejo

We propose a computational framework to study the growth and spread of bacterial biofilms on interfaces, as well as the action of antibiotics on them. Bacterial membranes are represented by boundaries immersed in a fluid matrix and subject to interaction forces. Growth, division and death of bacterial cells follow dynamic energy budget rules, in response to

Qing-Hong Cao, Kun Cheng, Changlong Xu

Using a geometric description of 2HDM, we classify CP invariants into three independent sectors such as scalar potential, Yukawa interaction and CKM matrix. Thermal effective potential of 2HDM is calculated in a basis invariant way. It is shown that the CP violation in Yukawa interactions can contribute to effective potential at one loop level but the CP pha

Long Yang, Jiangtao Wang, Xuan Xue, Jia Shi

In this paper, we investigate the secure beamforming design in an intelligent reflection surface (IRS) assisted millimeter wave (mmWave) system, where the hybrid beamforming (HB) and the passive beamforming (PB) are employed by the transmitter and the IRS, respectively. To maximize the secrecy capacity, the joint optimization of HB and PB is formulated as a

Jinping Zhang, Keming Zhang

Risk management is very important for individual investors or companies. There are many ways to measure the risk of investment. Prices of risky assets vary rapidly and randomly due to the complexity of finance market. Random interval is a good tool to describe uncertainty with both randomness and imprecision. Considering the uncertainty of financial market,

Zhi Zhang, Decheng Chen, Jiahao Qi, Yueqiang Cheng

Rowhammer has drawn much attention from both academia and industry in the past years as rowhammer exploitation poses severe consequences to system security. Since the first comprehensive study of rowhammer in 2014, a number of rowhammer attacks have been demonstrated against dynamic random access memory (DRAM)-based commodity systems to break software confid

Dong Quan Vu, Kimon Antonakopoulos, Panayotis Mertikopoulos

We consider the traffic assignment problem in nonatomic routing games where the players' cost functions may be subject to random fluctuations (e.g., weather disturbances, perturbations in the underlying network, etc.). We tackle this problem from the viewpoint of a control interface that makes routing recommendations based solely on observed costs and withou

Alexander Vishik

We study the conjecture claiming that, over a flexible field, isotropic Chow groups coincide with numerical Chow groups (with ${\Bbb{F}}_p$-coefficients). This conjecture is essential for understanding the structure of the isotropic motivic category and that of the tensor triangulated spectrum of Voevodsky category of motives. We prove the conjecture for the

Youxi Wu, Qian Hu, Yan Li, Lei Guo

A time series is a collection of measurements in chronological order. Discovering patterns from time series is useful in many domains, such as stock analysis, disease detection, and weather forecast. To discover patterns, existing methods often convert time series data into another form, such as nominal/symbolic format, to reduce dimensionality, which inevit

Oleh Danyliv

The article is an empirical study of market impact through order book events. It describes a mechanism of extracting an average participation rate and a market impact of small orders which represent individual slices of large metaorders. The study is based on tick data for futures contracts. It is shown that the impact could be either linear or a concave fun

Alessandra Faggionato, Vittoria Silvestri

We consider a Markov jump process on a general state space to which we apply a time-dependent weak perturbation over a finite time interval. By martingale-based stochastic calculus, under a suitable exponential moment bound for the perturbation we show that the perturbed process does not explode almost surely and we study the linear response (LR) of observab

Haibo Liu, Qunying Liao

Recently, minimal linear codes have been extensively studied due to their applications in secret sharing schemes, secure two-party computations, and so on. Constructing minimal linear codes violating the Ashikhmin-Barg condition and then determining their weight distributions have been interesting in coding theory and cryptography. In this paper, a generic c

Mohammad Shifat E Rabbi, Yan Zhuang, Shiying Li, Abu Hasnat Mohammad Rubaiyat

Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform when training data are limited and thus require data augmentation strategies that render the method computationally expensive and not always effective. Rather than using a data augmen

Congpei An, Hao-Ning Wu, Xiaoming Yuan

The total variation (TV) regularization has phenomenally boosted various variational models for image processing tasks. We propose to combine the backward diffusion process in the earlier literature of image enhancement with the TV regularization, and show that the resulting enhanced TV minimization model is particularly effective for reducing the loss of co

Run-kun Lu, Jian-wei Liu, Yuan-fang Wang, Hao-jie Xie

Multi-view learning is a learning problem that utilizes the various representations of an object to mine valuable knowledge and improve the performance of learning algorithm, and one of the significant directions of multi-view learning is sub-space learning. As we known, auto-encoder is a method of deep learning, which can learn the latent feature of raw dat

Diptesh Kanojia, Kevin Patel, Pushpak Bhattacharyya

Wordnets are rich lexico-semantic resources. Linked wordnets are extensions of wordnets, which link similar concepts in wordnets of different languages. Such resources are extremely useful in many Natural Language Processing (NLP) applications, primarily those based on knowledge-based approaches. In such approaches, these resources are considered as gold sta

Stephan Loveless, Dina Prialnik, Morris Podolak

The interest in the structure of ice-rich planetary bodies, in particular the differentiation between ice and rock, has grown due to the discovery of Kuiper belt objects and exoplanets. We thus carry out a parameter study for a range of planetary masses $M$, yielding radii $50 \aplt R \aplt 3000$~km, and for rock/ice mass ratios between 0.25 and 4, evolving

Wei Xu

This paper provides a detailed description for the asymptotics of exponential functionals of random walks with light/heavy tails. We give the convergence rate based on the key observation that the asymptotics depends on the sample paths with either slowly decreasing local minimum or final value below a low level. Also, our thoughtful analysis of the interrel

S. S. Das, G. Kopnov, A. Gerber

Palladium satisfies most of the requirements for an effective hydrogen storage material with two major drawbacks: it has a relatively low gravimetric hydrogen density and is prohibitively expensive for large-scale applications. Pd-based alloys should be considered as possible alternatives to a pure Pd. The question is how much one can dilute the Pd concentra

Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang

Recent progress on Transformers and multi-layer perceptron (MLP) models provide new network architectural designs for computer vision tasks. Although these models proved to be effective in many vision tasks such as image recognition, there remain challenges in adapting them for low-level vision. The inflexibility to support high-resolution images and limitat

Jean-Marie Frère

While Left-Right symmetry (space parity) breaking historically appeared as a surprise, we argue that the real wonder is its restoration in long-distance interactions (at least until we find electric dipole moments!).

Meng Liu, Minglei Yang, Huifang Li, Kun Zeng

To mitigate the radar and communication frequency overlapping caused by massive devices access, we propose a novel joint communication and sensing (JCS) system in this paper, where a micro base station (MiBS) can realize target sensing and cooperative communication simultaneously. Concretely, the MiBS, as the sensing equipment, can also serve as a full-duple

Yang Guo, Chen Lan, Yan-Gang Miao

Gravitational lensing in the weak field limit, quasinormal spectra, and gray-body factors are investigated in the Reissner-Nordstr\"om spacetime corrected by bounce parameters. Using the Gauss-Bonnet theorem, we analyze the effects of bounce corrections to the weak gravitational deflection angle and find that the divergence of the deflection angle can be sup

Asaf Cohen Antonir

Building on the techniques from the breakthrough paper of Harel, Mousset and Samotij, which solved the upper tail problem for cliques, we compute the asymptotics of the upper tail for the number of induced copies of the 4-cycle in the binomial random graph $G_{n,p}$. We observe a new phenomenon in the theory of large deviations of subgraph counts. This pheno

H. C. Fan, X. Y. Liu, X. F. Li, J. F. Qu

Electron beam polarization in the bubble regime of the interaction between a high-intensity laser and a longitudinally pre-polarized plasma is investigated by means of the Thomas-Bargmann-Michel-Telegdi equation. Using a test-particle model, the dependence of the accelerated electron polarization on the bubble geometry is analyzed in detail. Tracking the pol

Tao Niu, Yinglei Teng, Zhu Han, Panpan Zou

Recently, the applications of deep neural network (DNN) have been very prominent in many fields such as computer vision (CV) and natural language processing (NLP) due to its superior feature extraction performance. However, the high-dimension parameter model and large-scale mathematical calculation restrict the execution efficiency, especially for Internet o

Pierre Houdouin, Frédéric Pascal, Matthieu Jonckheere, Andrew Wang

Linear and Quadratic Discriminant Analysis are well-known classical methods but can heavily suffer from non-Gaussian distributions and/or contaminated datasets, mainly because of the underlying Gaussian assumption that is not robust. To fill this gap, this paper presents a new robust discriminant analysis where each data point is drawn by its own arbitrary E

Akira Ono

A known limitation of time-dependent mean-field approaches is a lack of quantum tunneling for collective motions such as in sub-barrier fusion reactions. As a first step toward a solution, a time-dependent model is considered using a superposition of Gaussian wave packets, to describe the relative motion between two colliding nuclei, which may be simplified

V. I. Bondarenko, M. H. Urin

The basic version of the semi-microscopic particle-hole dispersive optical model is implemented to describe main properties of the Gamow-Teller and charge-exchange giant spin-monopole resonances in medium-heavy closed-shell parent nuclei. Calculation results obtained for $^{48}Ca$, $^{90}Zr$, $^{132}Sn$, and $^{208}Pb$ are compared with available experimenta

Shu Xu, Jörg Schmiedmayer, Barry C. Sanders

Quantum interferometry and quantum information processing have been proposed for Bose-Einstein condensates (BECs), but BECs are described in complicated ways such as using quantum field theory or using a nonlinear differential equation. Nonlinear quantum mechanics does not mesh well with the superposition principle at the heart of interferometry and quantum

Yan Liu, Qingyong Hu, Yinjie Lei, Kai Xu

Learning dense point-wise semantics from unstructured 3D point clouds with fewer labels, although a realistic problem, has been under-explored in literature. While existing weakly supervised methods can effectively learn semantics with only a small fraction of point-level annotations, we find that the vanilla bounding box-level annotation is also informative