July 2022 arXiv papers — page 39

Zhuohui Zhang

In this paper, a construction to imitate the Bernstein-Zelevinsky derivative for automorphic representations on $GL_n(\mathbb{A})$ is introduced. We will later consider the induced representation \[I(\tau_1,\tau_2;\underline{s}) = \mathrm{Ind}_{P_{[n_1,n_2]}}^{G_n}(\Delta(\tau_1,n_1)|\cdot|^{s_1}\boxtimes \Delta(\tau_2,n_2)|\cdot|^{s_2}).\] from the discrete

Haoran Sun, Etash K. Guha, Hanjun Dai

The hardness of combinatorial optimization (CO) problems hinders collecting solutions for supervised learning. However, learning neural networks for CO problems is notoriously difficult in lack of the labeled data as the training is easily trapped at local optima. In this work, we propose a simple but effective annealed training framework for CO problems. In

Tianle Ni, Jingwei Wang, Yunlong Ma, Shuang Wang

Automated detection of anomalous trajectories is an important problem with considerable applications in intelligent transportation systems. Many existing studies have focused on distinguishing anomalous trajectories from normal trajectories, ignoring the large differences between anomalous trajectories. A recent study has made great progress in identifying a

Christopher Perez, Sayar Karmakar

COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of which leading to negative outcomes in victims. To study cyberbullying specifically, 1 million tweets containing keywords associated with abuse were collected from the beginning of 201

Silvia Mollerach, Esteban Roulet, Oscar Taborda

We study the anisotropies on large angular scales which can be present in the flux of cosmic rays reaching the Earth from a population of extragalactic sources, focusing on the energy range between the second knee and the ankle. In this energy range the particles are significantly affected by the Galactic magnetic field, which then plays a relevant role in s

Ji Liu, Dong Li, Zekun Li, Han Liu

Sample assignment plays a prominent part in modern object detection approaches. However, most existing methods rely on manual design to assign positive / negative samples, which do not explicitly establish the relationships between sample assignment and object detection performance. In this work, we propose a novel dynamic sample assignment scheme based on h

Francesco Tani, Jacob Lampen, Martin Butryn, Michael H. Frosz

We combine soliton dynamics in gas-filled hollow-core photonic crystal fibers with a state-of-the-art fiber laser to realize a turn-key system producing few-fs pulses at 8 MHz repetition rate at pump energies as low as 220 nJ. Furthermore, by exploiting the soliton self-frequency shift in a second hydrogen-filled hollow-core fiber, we efficiently generate pu

Jared Herron, Daniel Lopez, Jarred Jordan, Jillian Rudy

A large number of robotic and human-assisted missions to the Moon and Mars are forecast. NASA's efforts to learn about the geology and makeup of these celestial bodies rely heavily on the use of robotic arms. The safety and redundancy aspects will be crucial when humans will be working alongside the robotic explorers. Additionally, robotic arms are crucial t

Xing Huang, Feng-Yu Wang

The log-Harnack inequality and Bismut formula are established for McKean-Vlasov SDEs with singularities in all (time, space, distribution) variables, where the drift satisfies an integrability condition in time-space, and the continuity in distribution may be weaker than Dini. The main results considerably improve the existing ones for the case where the dri

YingXing Cheng, Toon Verstraelen

A frequency-dependent extension of the polarizable force field ``Atom-Condensed Kohn-Sham density functional theory approximated to the second-order'' (ACKS2) [J. Chem. Phys. 141, 194114 (2014)] is proposed, referred to as ACKS2$\omega$. The method enables theoretical predictions of dynamical response properties of finite systems after a partitioning of the

Joomee Song, Juyoung Hahm, Jisoo Lee, Chae Yeon Lim

Automated segmentation and volumetry of brain magnetic resonance imaging (MRI) scans are essential for the diagnosis of Parkinson's disease (PD) and Parkinson's plus syndromes (P-plus). To enhance the diagnostic performance, we adopt deep learning (DL) models in brain segmentation and compared their performance with the gold-standard non-DL method. We collec

Mohsen Aghajani

In this paper, we consider the N-pure notion. An ideal $I$ of a ring $R$ is said to be N-pure, if for every $a\in I$ there exists $b\in I$ such that $a(1-b)\in N(R)$, where N(R) is nil radical of $R$. We provide new characterizations for N-pure ideals. In addition, N-pure ideals of an arbitrary ring are identified. Also, some other properties of N-pure ideal

Bin Liu, Zhengling Qi, Xinsheng Zhang, Yufeng Liu

We propose a novel approach for detecting change points in high-dimensional linear regression models. Unlike previous research that relied on strict Gaussian/sub-Gaussian error assumptions and had prior knowledge of change points, we propose a tail-adaptive method for change point detection and estimation. We use a weighted combination of composite quantile

Recep Akif Tasci, Fatih Kilinc, Abdulkadir Celik, Asmaa Abdallah

This paper introduces a reconfigurable intelligent surface (RIS)-assisted grant-free non-orthogonal multiple-access (GF-NOMA) scheme. To ensure the power reception disparity required by the power domain NOMA (PD-NOMA), we propose a joint user clustering and RIS assignment/alignment approach that maximizes the network sum rate by judiciously pairing user equi

Tieming Chen, Qijie Song, Xuebo Qiu, Tiantian Zhu

Recently, APT attacks have frequently happened, which are increasingly complicated and more challenging for traditional security detection models. The system logs are vital for cyber security analysis mainly due to their effective reconstruction ability of system behavior. existing log collection tools built on ETW for Windows suffer from working shortages,

Arshdeep Singh, Mark D. Plumbley

This paper presents a low-complexity framework for acoustic scene classification (ASC). Most of the frameworks designed for ASC use convolutional neural networks (CNNs) due to their learning ability and improved performance compared to hand-engineered features. However, CNNs are resource hungry due to their large size and high computational complexity. There

M. Arana-Catania, F. A. Van Lier, Rob Procter

Today's conflicts are becoming increasingly complex, fluid and fragmented, often involving a host of national and international actors with multiple and often divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense of conflict dynamics, such as the range of conflict parties and the evolut

Bheemsehan Gurjar, Dipankar Chakrabarti, Chandan Mondal

We obtain the leading twist T-odd quark transverse momentum dependent parton distribution functions (TMDs) of the proton, namely the Sivers function, $f_{1T}^{\perp q}(x,p_\perp^2)$, and the Boer-Mulders function, $h_1^{\perp q}(x,p_\perp^2)$, in a light-front quark-diquark model constructed with the wave functions predicted by the soft-wall AdS/QCD. The glu

Swarnim Shashank, Shafqat Riaz, Askar B. Abdikamalov, Cosimo Bambi

X-ray reflection spectroscopy is currently one of the leading techniques for studying the inner part of accretion disks around black holes, measuring black hole spins, and even testing fundamental physics in strong gravitational fields. However, the accuracy of these measurements depends on the reflection models employed for the spectral analysis, which are

Tong Wu, Jing Guo

A multiscale simulation method is developed to model a quantum dot (QD) array of germanium (Ge) holes for quantum computing. Guided by three-dimensional numerical quantum device simulations of QD structures, an analytical model of the tunnel coupling between the neighboring hole QDs is obtained. Two-qubit entangling quantum gate operations and quantum circui

Yang Zhou, Jimei Yang, Dingzeyu Li, Jun Saito

Human speech is often accompanied by body gestures including arm and hand gestures. We present a method that reenacts a high-quality video with gestures matching a target speech audio. The key idea of our method is to split and re-assemble clips from a reference video through a novel video motion graph encoding valid transitions between clips. To seamlessly

Prassanna Ganesh Ravishankar, Antonio M. Lopez, Gemma M. Sanchez

Monocular vision based road detection methods are mostly based on machine learning methods, relying on classification and feature extraction accuracy, and suffer from appearance, illumination and weather changes. Traditional methods introduce the predictions into conditional random fields or markov random fields models to improve the intermediate predictions

Li Shen, Yongpeng Wu, Derrick Wing Kwan Ng, Wenjun Zhang

In this letter, we propose a symbol-wise puncturing scheme to support hybrid automatic repeat request (HARQ) integrated probabilistic amplitude shaping (PAS). To prevent the probability distribution distortion caused by the traditional sequential puncturing and realize the promised gain of PAS, we perform symbol-wise puncturing on the label sequence of the s

Gabriel Lindelöf, Talayeh Aledavood, Barbara Keller

Since the onset of the COVID-19 pandemic, vaccines have been an important topic in public discourse. The discussions around vaccines are polarized as some see them as an important measure to end the pandemic, and others are hesitant or find them harmful. This study investigates posts related to COVID-19 vaccines on Twitter and focuses on those which have a n

Eric Bourreau, Gérard Fleury, Philippe Lacomme

This paper concerns quantum heuristics based on Mixer Hamiltonians that allow to restrict investigation on a specific subspace. Mixer Hamiltonian based approaches can be included in QAOA algorithm and we can state that Mixer Hamiltonians are mapping functions from the set of qubit-strings to the set of solutions. Mixer Hamiltonian offers an approach very sim

Rishiraj Bhattacharyya, Avradip Mandal

ASIC hash engines are specifically optimized for parallel computations of cryptographic hashes and thus a natural environment for mounting brute-force attacks on hash functions. Two fundamental advantages of ASICs over general purpose computers are the area advantage and the energy efficiency. The memory-hard functions approach the problem by reducing the ar

Chuanguang Yang, Zhulin An, Helong Zhou, Fuzhen Zhuang

The teacher-free online Knowledge Distillation (KD) aims to train an ensemble of multiple student models collaboratively and distill knowledge from each other. Although existing online KD methods achieve desirable performance, they often focus on class probabilities as the core knowledge type, ignoring the valuable feature representational information. We pr

Kun Lu, Rongpeng Li, Honggang Zhang

Continuous one-to-many mapping is a less investigated yet important task in both low-level visions and neural image translation. In this paper, we present a new formulation called MonoPix, an unsupervised and contrastive continuous modulation model, and take a step further to enable a pixel-level spatial control which is critical but can not be properly hand

Weichao Yao, Yicheng Wang, Sergei Tomilov, Martin Hoffmann

We report on an in-band pumped SESAM mode-locked Ho:CALGO bulk laser with a record-high average power of 8.7 W and an optical-to-optical efficiency of 38.2% at a central wavelength of 2.1 um. At this power level, the bulk laser generates pulses with a duration of 369 fs at 84.4-MHz repetition rate, corresponding to a pulse energy of 103 nJ and a peak power o

Jiaxin Zhang, Canjie Luo, Lianwen Jin, Fengjun Guo

Camera-captured document images usually suffer from perspective and geometric deformations. It is of great value to rectify them when considering poor visual aesthetics and the deteriorated performance of OCR systems. Recent learning-based methods intensively focus on the accurately cropped document image. However, this might not be sufficient for overcoming

Huy Ha, Shuran Song

We study open-world 3D scene understanding, a family of tasks that require agents to reason about their 3D environment with an open-set vocabulary and out-of-domain visual inputs - a critical skill for robots to operate in the unstructured 3D world. Towards this end, we propose Semantic Abstraction (SemAbs), a framework that equips 2D Vision-Language Models

Olesia Zavarzina

It is known that if any function acting from precompact metric space to itself increases the distance between some pair of points then it must decrease distance between some other pair of points. We show that this is not the case for quasi-metric spaces. After that, we present some sufficient conditions under which the previous property holds true for heredi

Wentao Liu, Weijin Xu, Songlin Yan, Lemeng Wang

Abdominal organ segmentation has many important clinical applications, such as organ quantification, surgical planning, and disease diagnosis. However, manually annotating organs from CT scans is time-consuming and labor-intensive. Semi-supervised learning has shown the potential to alleviate this challenge by learning from a large set of unlabeled images an

Ho Man Kwan, Shenghui Song

Downsampling is widely adopted to achieve a good trade-off between accuracy and latency for visual recognition. Unfortunately, the commonly used pooling layers are not learned, and thus cannot preserve important information. As another dimension reduction method, adaptive sampling weights and processes regions that are relevant to the task, and is thus able

Zeina Ghazo Hanna, Amine El Sahili

We construct a combinatorial function F which computes the number of oriented Hamiltonian paths of any given type, in a transitive tournament. We also study many properties of F that arise, and reach some observations.

Annabelle M. Brown, Evan Bolyen, Isaiah Raspet, John A. Altin

PepSIRF is a command-line, module-based open-source software package that facilitates the analysis of data from highly-multiplexed serology assays (e.g., PepSeq or PhIP-Seq). It has nine separate modules in its current release (v1.5.0): demux, info, subjoin, norm, bin, zscore, enrich, link, and deconv. These modules can be used together to conduct analyses r

J. A. Rebouças, P. A. Brandão

Perturbation theory is applied to one-dimensional scattering systems consisting of a general class of inhomogeneous and isotropic slabs having size $L$ described by the relative permittivity $\varepsilon(z) = 1 + \alpha \chi(z)$, where $\chi(z)$ is the electric susceptibility and $\alpha$ the perturbation parameter. The transmitted and reflected amplitudes a

Paolo Bartesaghi

Synchronization and resonance on networks are some of the most remarkable collective dynamical phenomena. The network topology, or the nature and distribution of the connections within an ensemble of coupled oscillators, plays a crucial role in shaping the local and global evolution of the two phenomena. This article further explores this relationship within

Xiutao Zhu, Yaojun Chen

The Tur\'an number $ex(n,H)$ is the maximum number of edges in an $H$-free graph on $n$ vertices. Let $T$ be any tree. The odd-ballooning of $T$, denoted by $T_o$, is a graph obtained by replacing each edge of $T$ with an odd cycle containing the edge, and all new vertices of the odd cycles are distinct. In this paper, we determine the exact value of $ex(n,T

Jonas Sjöstrand

A locally uniform random permutation is generated by sampling $n$ points independently from some absolutely continuous distribution $\rho$ on the plane and interpreting them as a permutation by the rule that $i$ maps to $j$ if the $i$th point from the left is the $j$th point from below. As $n$ tends to infinity, decreasing subsequences in the permutation wil

Arslan Syed, Eman A. Aldhahri, Muhammad Munawar Iqbal, Abid Ali

In videos, the human's actions are of three-dimensional (3D) signals. These videos investigate the spatiotemporal knowledge of human behavior. The promising ability is investigated using 3D convolution neural networks (CNNs). The 3D CNNs have not yet achieved high output for their well-established two-dimensional (2D) equivalents in still photographs. Board

Peng Kang, Srutarshi Banerjee, Henry Chopp, Aggelos Katsaggelos

The sense of touch is essential for a variety of daily tasks. New advances in event-based tactile sensors and Spiking Neural Networks (SNNs) spur the research in event-driven tactile learning. However, SNN-enabled event-driven tactile learning is still in its infancy due to the limited representative abilities of existing spiking neurons and high spatio-temp

Nikita A. Ignatyuk, Daniel Skliannyi

Dualities between quantum field theories have proven to be a powerful tool in various areas of physics. In this paper, we introduce a new perspective for obtaining strong coupling expansions based on a well-known technique -- the Field-space Fourier transform. We discuss the advantages of this approach for a class of Euclidean quantum field theories on a gen

Lucien Heurtier, Ahmad Moursy, Lucien Wacquez

In supergravity, the dynamics of the sgoldstino -- superpartner of the goldstino superfield associated with the breaking of supersymmetry at low energy -- can substantially modify the dynamics of inflation in the primordial Universe. So-called sgoldstinoless models assume the existence of a nilpotency constraint $S^2=0$ that effectively removes the sgoldstin

Xuan Li, Yuan-Chun Jing, Fu-Zhong Yang

In this paper, we study the open topological string amplitudes on Calabi-Yau threefolds by the extended holomorphic anomaly equation. The disk two-point function determined by the domainwall tension, together with the Yukawa couplings, solves the amplitudes with high genus and boundaries recursively. The BPS invariants encoded in the amplitudes are extracted

Dilara Dogan, Bahadir Altun, Muhammed Said Zengin, Mucahid Kutlu

The recent advances in natural language processing have yielded many exciting developments in text analysis and language understanding models; however, these models can also be used to track people, bringing severe privacy concerns. In this work, we investigate what individuals can do to avoid being detected by those models while using social media platforms

Xuan Li, Yuan-Chun Jing, Fu-Zhong Yang

Open topological string partition function on compact Calabi-Yau threefolds satisfies the extended holomorphic anomaly equation. By direct integration, we solve these equations and obtain partition functions for first several genus and boundaries on complete intersection Calabi-Yau threefolds. Complemented by the unoriented worldsheet contribution, the annul

Mohammad Javad Latifi, Doug Pickrell

In this paper we discuss two items which in one way or another originated from conversations with Hermann Flaschka and his students. The first is an application of the Toda lattice to the question of whether there exists a complex Lie group (with certain properties) associated to an indefinite type Kac-Moody Lie algebra. The second concerns a new example of

Utku Umur Acikalin, Mucahid Kutlu

In this paper, we propose a novel method for the prior-art search task. We fine-tune SciBERT transformer model using Triplet Network approach, allowing us to represent each patent with a fixed-size vector. This also enables us to conduct efficient vector similarity computations to rank patents in query time. In our experiments, we show that our proposed meth

Mathew Francis, Drimit Pattanayak

A $p$-centered coloring of a graph $G$, where $p$ is a positive integer, is a coloring of the vertices of $G$ in such a way that every connected subgraph of $G$ either contains a vertex with a unique color or contains more than $p$ different colors. We give an explicit construction of a $p$-centered coloring using $O(p)$ colors for the planar grid.

Shun Shimomura

For a general solution of the degenerate third Painlev\'e equation we show the Boutroux ansatz near the point at infinity. It admits an asymptotic representation in terms of the Weierstrass pe-function in cheese-like strips along generic directions. The expression is obtained by using isomonodromy deformation of a linear system governed by the degenerate thi

Aleksander Szpakiewicz Szatan, Sylwester J. Rzoska, Aleksandra Drozd-Rzoska

Melting/freezing are canonical examples of discontinuous phase transitions, for which no pretransitional effects in the liquid phase are expected.For the solid phase, weak premelting effects are evidenced. This report shows long-range, critical-like, pretransitional effect in liquid thymol detected in Electrooptic Kerr effect (EKE) studies. Notable is the ne

Chufeng Tang, Lingxi Xie, Gang Zhang, Xiaopeng Zhang

The requirement of expensive annotations is a major burden for training a well-performed instance segmentation model. In this paper, we present an economic active learning setting, named active pointly-supervised instance segmentation (APIS), which starts with box-level annotations and iteratively samples a point within the box and asks if it falls on the ob

Constantin Aniculaesei, Thanh Ha, Samuel Yoffe, Edward McCary

In an electron wakefield accelerator, an intense laser pulse or charged particle beam excites plasma waves. Under proper conditions, electrons from the background plasma are trapped in the plasma wave and accelerated to ultra-relativistic velocities. We present recent results from a proof-of-principle wakefield acceleration experiment that reveal a unique sy

Daniel F. O. Onah, Elaine L. L. Pang, Mahmoud El-Haj

With the advent and popularity of big data mining and huge text analysis in modern times, automated text summarization became prominent for extracting and retrieving important information from documents. This research investigates aspects of automatic text summarization from the perspectives of single and multiple documents. Summarization is a task of conden

Viswanatha V, Chandana R K, Ramachandra A. C.

The field of artificial intelligence is built on object detection techniques. YOU ONLY LOOK ONCE (YOLO) algorithm and it's more evolved versions are briefly described in this research survey. This survey is all about YOLO and convolution neural networks (CNN)in the direction of real time object detection.YOLO does generalized object representation more effec

Viswanatha V, Ramachandra A. C, Raghavendra Prasanna, Prem Chowdary Kakarla

In this article gesture recognition and speech recognition applications are implemented on embedded systems with Tiny Machine Learning (TinyML). It features 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. The gesture recognition,provides an innovative approach nonverbal communication. It has wide applications in human-computer interaction and

Gianmarco Ricciardi, Guido Montagna, Guido Caldarelli, Giulio Cimini

Modelling systems with networks has been a powerful approach to tame the complexity of several phenomena. Unfortunately, such an approach is often made difficult by the large number of variables to take into consideration. Methods of dimensional reduction are useful tools to rescale a complex dynamical network down to a low-dimensional effective system and t

Athira A B, S D Madhu Kumar, Anu Mary Chacko

People now see social media sites as their sole source of information due to their popularity. The Majority of people get their news through social media. At the same time, fake news has grown exponentially on social media platforms in recent years. Several artificial intelligence-based solutions for detecting fake news have shown promising results. On the o

Ittai Rubinstein

The {\em insertion-deletion channel} takes as input a binary string $x \in\{0, 1\}^n$, and outputs a string $\widetilde{x}$ where some of the bits have been deleted and others inserted independently at random. In the {\em trace reconstruction problem}, one is given many outputs (called {\em traces}) of the insertion-deletion channel on the same input message

Jian Wang, Hao Yang, Jianliang Zhai, Tusheng Zhang

The irreducibility is fundamental for the study of ergodicity of stochastic dynamical systems. The existing methods on the irreducibility of stochastic partial differential equations (SPDEs) and stochastic differential equations (SDEs) driven by pure jump noise are basically along the same lines as that for the Gaussian case, which are not particularly suita

Dat Thai Van

This note establishes convergence in mean of order $p$, $0<p\le 1$ for $d$-dimensional arrays of random vectors in Hilbert spaces under the Ces\`{a}ro uniform integrability conditions. In the case where $0<p<1$, our $L_p$ convergence is valid irrespective of any dependence structure. In the case where $p=1$, the underlying random vectors are supposed to be p

Stefanos Bennett, Jase Clarkson

Time series prediction is often complicated by distribution shift which demands adaptive models to accommodate time-varying distributions. We frame time series prediction under distribution shift as a weighted empirical risk minimisation problem. The weighting of previous observations in the empirical risk is determined by a forgetting mechanism which contro

Miguel Angel Barja, Lidia Stoppino

We prove $f$-positivity of $\mathcal{O}_X(1)$ for arbitrary dimension fibrations over curves $f\colon X\to B$ whose general fibre is a complete intersection. In the special case where the family is a global complete intersection, we prove numerical sufficient and necessary conditions for $f$-positivity of powers of $\mathcal{O}_X(1)$ and for the relative can

Keqiang Li, Mingyang Zhao, Huaiyu Wu, Dong-Ming Yan

We propose a precise and efficient normal estimation method that can deal with noise and nonuniform density for unstructured 3D point clouds. Unlike existing approaches that directly take patches and ignore the local neighborhood relationships, which make them susceptible to challenging regions such as sharp edges, we propose to learn graph convolutional fea

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $4.5~\mathrm{fb}^{-1}$ of $e^+e^-$ annihilation data samples collected at the center-of-mass energies ranging from 4.600~GeV to 4.699~GeV with the BESIII detector at the BEPCII collider, a first study of the semileptonic decays $\Lambda_c^+\rightarrow pK^-e^+\nu_e$, $\Lambda_c^+\rightarrow \Lambda(1520) e^+\nu_e$ and $\Lambda_c^+\rightarrow \Lambda(140

Riccardo Franceschini, Enrico Fini, Cigdem Beyan, Alessandro Conti

Emotion recognition is involved in several real-world applications. With an increase in available modalities, automatic understanding of emotions is being performed more accurately. The success in Multimodal Emotion Recognition (MER), primarily relies on the supervised learning paradigm. However, data annotation is expensive, time-consuming, and as emotion e

Mukesh K. Vyas, Asaf Pe'er

A high energy power law is a common feature in the spectra of many astrophysical objects. We show that the photons in a relativistic plasma with a variable Lorentz factor go through repeated scattering with electrons to gain energy. The escaped population of photons naturally produces a power-law-shaped spectrum making it an anisotropic analogue to the conve

Congwei Lu, Mei Zhang, Haibo Wang, Qing Ai

We investigate a second-order topological quantum transition of a modified Kane-Mele model driven by electron-phonon interaction. The results show that the system parameters of the bare modified Kane-Mele model are renormalized by the electron-phonon interaction. Starting from the second-order topological phase for the bare model, the increasing electron-pho

John Rachwan, Charbel Zalaket

Training and testing supervised object detection models require a large collection of images with ground truth labels. Labels define object classes in the image, as well as their locations, shape, and possibly other information such as pose. The labeling process has proven extremely time consuming, even with the presence of manpower. We introduce a novel lab

Noboru Osawa, Fabian Göttsch, Issei Kanno, Takeo Ohseki

The pilot contamination in cell-free massive multiple-input-multiple-output (CF-mMIMO) must be addressed for accommodating a large number of users. In previous works, we have investigated a decontamination method called subspace projection (SP). The SP separates interference from co-pilot users by using the orthogonality of the principal components of the us

Hamza Kheddar, Soufiane Ouldkhaoua, Riadh Bouguerra

The telecommunication field has seen unprecedented growth in the last decade that has led to the release of several generations that have been committed to satisfy users by increasing the data rate and reducing the latency, especially in the 5G network. With fully commercialized 5G networks that is already launched in many country, Software-defined network (

Marc Wolf, François Wolf

We study the factorization of the numbers $N = X^2+c$, where $c$ is a fixed constant, and this independently of the value of gcd$(X,c)$. We prove the existence of a family of sequences with arithmetic difference $(U_n, Z_n)$ generating factorizations, i.e. such that: $(U_n)^2+c = Z_nZ_{n+1}$. The different properties demonstrated allow us to establish new fa

Á. Torregrosa, J. J. Rodes-Roca, J. M. Torrejón, G. Sanjurjo-Ferrín

The aim of this work is to study both light curve and orbital phase spectroscopy of this source taking advantage of the MAXI/GSC observation strategy. We have investigated the spectral and light curve properties of the X-ray emission from Cen X-3 along the binary orbit. These studies allow delimiting the stellar wind properties and its interactions with the

M. Beccaria, G. P. Korchemsky, A. A. Tseytlin

We consider strong 't Hooft coupling expansion in special four-dimensional $\mathcal N=2$ superconformal models that are planar-equivalent to $\mathcal N=4$ super Yang-Mills theory. Various observables in these models that admit localization matrix model representation can be expressed at large $N$ in terms of a Fredholm determinant of a Bessel operator. The

Florian Gallwitz, Michael Kreil

The idea that social media platforms like Twitter are inhabited by vast numbers of social bots has become widely accepted in recent years. Social bots are assumed to be automated social media accounts operated by malicious actors with the goal of manipulating public opinion. They are credited with the ability to produce content autonomously and to interact w

Gwo Dong Lin, Jordan M. Stoyanov

Available in the literature are properties which characterize the gamma distribution via independence of two appropriately chosen statistics. Well-known is the classical result when one of the statistics is the sample mean and the other one the sample coefficient of variation. In this paper, we elaborate on a version of Anosov's theorem which allows to estab

Jie Zhan, Jiangxu Li, Wujun Shi, Xing-Qiu Chen

Antiferromagnets (AFMs) with anomalous quantum responses have lead to new progress for the understanding of their magnetic and electronic structures from symmetry and topology points of view. Two typical topological states are the collinear antiferromagnetic Weyl semimetal (WSM) and Weyl nodal loop semimetal (WNLSM). In comparison with the counterparts in fe

Suman Chakraborty, Kjell Raaijmakers, Remco van der Hofstad

In this note, we investigate fundamental relations between exploration processes in random graphs, and branching processes. We formulate a class of models that we call {\em rank-$k$ random graphs}, and that are special in that their neighborhood explorations can be obtained by a {\em thinning} of multi-type branching processes. We show that any rank-2 random

Malte Misfeldt, Vitali Müller, Laura Müller, Henry Wegener

The GRACE Follow-On satellites carry the very first inter-spacecraft Laser Ranging Interferometer (LRI). After more than four years in orbit, the LRI outperforms the sensitivity of the conventional Microwave Instrument (MWI). However, in the current data processing scheme, the LRI product still needs the MWI data to determine the unknown absolute laser frequ

Xiangcheng Du, Zhao Zhou, Yingbin Zheng, Xingjiao Wu

Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data. Although data synthetic engines can provide vast amounts of annotated training samples, there are differences between synthetic and real-world data. In this paper, we employ self-supervision for feature

Zhengzhi Wu, Yi-ming Wu, Fengcheng Wu

We theoretically show that in the presence of conventional or higher order van Hove singularities(VHS), the bare finite momentum pairing, also known as the pair density wave (PDW), susceptibility can be promoted to the same order of the most divergent bare BCS susceptibility through a valley-contrasting flux 3$\phi$ in each triangular plaquette at $\phi=\fra

Zuoyue Li, Tianxing Fan, Zhenqiang Li, Zhaopeng Cui

We introduce a scalable framework for novel view synthesis from RGB-D images with largely incomplete scene coverage. While generative neural approaches have demonstrated spectacular results on 2D images, they have not yet achieved similar photorealistic results in combination with scene completion where a spatial 3D scene understanding is essential. To this

Eran Kaufman, Andrey Iaremenko

Since the inception of Bitcoin in 2009, the market of cryptocurrencies has grown beyond initial expectations as daily trades exceed $10 billion. As industries become automated, the need for an automated fraud detector becomes very apparent. Detecting anomalies in real time prevents potential accidents and economic losses. Anomaly detection in multivariate ti

Ognjen Kundacina, Mirsad Cosovic, Dragisa Miskovic, Dejan Vukobratovic

Nonlinear state estimation (SE), with the goal of estimating complex bus voltages based on all types of measurements available in the power system, is usually solved using the iterative Gauss-Newton method. The nonlinear SE presents some difficulties when considering inputs from both phasor measurement units and supervisory control and data acquisition syste

Siyuan Zhou, Liu Liu, Li Niu, Liqing Zhang

Object placement aims to place a foreground object over a background image with a suitable location and size. In this work, we treat object placement as a graph completion problem and propose a novel graph completion module (GCM). The background scene is represented by a graph with multiple nodes at different spatial locations with various receptive fields.

Bohan Li, Ye Yuan, Dingkang Liang, Xiao Liu

Recently, most handwritten mathematical expression recognition (HMER) methods adopt the encoder-decoder networks, which directly predict the markup sequences from formula images with the attention mechanism. However, such methods may fail to accurately read formulas with complicated structure or generate long markup sequences, as the attention results are of

T. J. Volkoff, Michael J. Martin

We show that the lowest quantum Cram\'{e}r-Rao bound achievable in interferometry with a one-axis twisted spin coherent state is saturated by the asymptotic method of moments error of a protocol that uses one call to the one-axis twisting, one call to time-reversed one-axis twisting, and a final total spin measurement (i.e., a twist-untwist protocol). The re

S. Shallcross, C. v. Korff Schmising, P. Elliott, S. Eisebitt

Encoded in the transient x-ray absorption (XAS) and magnetic circular (MCD) response functions resides a wealth of information of the microscopic processes of ultrafast demagnetisation. Employing state of the art first principles dynamical simulations we show that the experimentally observed energy shift of the L3 XAS peak in Ni, and the absence of a corresp

Valentin Duruisseaux, Melvin Leok

Geometric numerical integration has recently been exploited to design symplectic accelerated optimization algorithms by simulating the Lagrangian and Hamiltonian systems from the variational framework introduced in Wibisono et al. In this paper, we discuss practical considerations which can significantly boost the computational performance of these optimizat

Divyansh Shrimali, Swapnil Bhowmick, Vivek Pandey, Arun Kumar Pati

The notion of capacity of entanglement is the quantum information theoretic counterpart of the heat capacity which is defined as the second cumulant of the entanglement spectrum. Given any bipartite pure state, we can define the capacity of entanglement as the variance of the modular Hamiltonian in the reduced state of any of the subsystems. Here, we study t

Ahmad Adnan Qidan, Khulood Alazwary, Taisir El-Gorashi, Majid Safari

Optical wireless communication (OWC) has recently received massive interest as a new technology that can support the enormous data traffic increasing on daily basis. Laser-based OWC networks can provide terabits per second (Tbps) aggregate data rates. However, the emerging OWC networks require clusters of optical transmitters to provide uniform coverage for

Harry Bevins, Will Handley, Pablo Lemos, Peter Sims

Cosmological experiments often employ Bayesian workflows to derive constraints on cosmological and astrophysical parameters from their data. It has been shown that these constraints can be combined across different probes such as Planck and the Dark Energy Survey and that this can be a valuable exercise to improve our understanding of the universe and quanti

Dongqi Cai, Tao Fan, Yan Kang, Lixin Fan

Privacy, security and data governance constraints rule out a brute force process in the integration of cross-silo data, which inherits the development of the Internet of Things. Federated learning is proposed to ensure that all parties can collaboratively complete the training task while the data is not out of the local. Vertical federated learning is a spec

Zhiheng Wu, Yue Lu, Xingyu Chen, Zhengxing Wu

Open World Object Detection (OWOD) is a challenging computer vision problem that requires detecting unknown objects and gradually learning the identified unknown classes. However, it cannot distinguish unknown instances as multiple unknown classes. In this work, we propose a novel OWOD problem called Unknown-Classified Open World Object Detection (UC-OWOD).

Ashutosh Singh, Anirudh Pradhan

In this article, we explore the homogeneous and isotropic flat Friedmann-Robertson-Walker (FRW) model in Chameleon cosmology. By considering a non-minimal coupling between the scalar field and matter, we present a non-singular bouncing cosmological scenario of the universe. The universe initially exhibits the ekpyrotic phase during the contracting era, under

Zhengyang Zhang

In order to improve the least mean squares (LMS) adaptation algorithm to accommodate the nonlinear transfer function, and to adjust the coefficients of adaptive filter during the actual implement of bias voltage and signal amplitude, methods are proposed and simulated to develop a nonlinear adaptive filter. The inputs to LMS are replaced by the derivatives o

Farrukh Chishtie, Rizwan Bulbul, Panka Babukova, Johannes Scholz

While platial representations are being developed for sedentary entities, a parallel and useful endeavour would be to consider time in so-called "platio-temporal" representations that would also expand notions of mobility in GIScience, that are solely dependent on Euclidean space and time. Besides enhancing such aspects of place and mobility via spatio-tempo

Haris Moazam Sheikh, Tess A. Callan, Kealan J. Hennessy, Philip S. Marcus

Finding the optimal design of a hydrodynamic or aerodynamic surface is often impossible due to the expense of evaluating the cost functions (say, with computational fluid dynamics) needed to determine the performances of the flows that the surface controls. In addition, inherent limitations of the design space itself due to imposed geometric constraints, con

Zi-Long Li, Xing-Yue Tan, Zhu-Feng Zhang, Zhen-Yang Wang

In this work, we systematically investigate the two-pseudoscalar meson systems with the Bethe-Salpeter equation in the ladder and instantaneous approximations. By solving the Bethe-Salpeter equation numerically with the kernel containing the one-particle exchange diagrams, we find that the $K\bar{K}$, $DK$, $B\bar{K}$, $D\bar{D}$, $B\bar{B}$, $BD$, $D\bar{K}