March 2020 arXiv papers — page 110

Ruiyu Zhang, Fulai Guo

The Fermi bubbles are two giant bubbles in gamma rays lying above and below the Galactic center (GC). Despite numerous studies on the bubbles, their origin and emission mechanism remain elusive. Here we use a suite of hydrodynamic simulations to study the scenario where the cosmic rays (CRs) in the bubbles are mainly accelerated at the forward shocks driven

Laura Cladek, Blair Davey, Krystal Taylor

The Favard length of a subset of the plane is defined as the average of its orthogonal projections. This quantity is related to the probabilistic Buffon needle problem; that is, the Favard length of a set is proportional to the probability that a needle or a line that is dropped at random onto the set will intersect the set. If instead of dropping lines onto

P. P. Malavadkar, Sachin Gunjal, Uday Jagadale

The splitting operation on a $p$-matroid does not necessarily preserve connectivity. It is observed that there exists a single element extension of the splitting matroid which is connected. In this paper, we define the element splitting operation on $p$-matroids which is a splitting operation followed by a single element extension. It is proved that element

Bintoro S. Nugroho, Alexander A. Iskandar, Victor A. Malyshev, Jasper Knoester

Tho-photon absorption holds potential for many practical applications. We theoretically investigate the onset of this phenomenon in a semiconductor quantum dot -- metallic nanoshell composite subjected to a resonant CW excitation. Two-photon absorption in this system may occur in two ways: incoherent -- due to a consecutive ground-to-one-exciton-to-biexciton

Jie Chen, Ziyang Yuan, Jian Peng, Li Chen

Change detection is a basic task of remote sensing image processing. The research objective is to identity the change information of interest and filter out the irrelevant change information as interference factors. Recently, the rise of deep learning has provided new tools for change detection, which have yielded impressive results. However, the available m

Sérgio Esteves, Gianmarco De Francisci Morales, Rodrigo Rodrigues, Marco Serafini

Processing data streams in near real-time is an increasingly important task. In the case of event-timestamped data, the stream processing system must promptly handle late events that arrive after the corresponding window has been processed. To enable this late processing, the window state must be maintained for a long period of time. However, current systems

Shoukai Xu, Haokun Li, Bohan Zhuang, Jing Liu

Neural network quantization is an effective way to compress deep models and improve their execution latency and energy efficiency, so that they can be deployed on mobile or embedded devices. Existing quantization methods require original data for calibration or fine-tuning to get better performance. However, in many real-world scenarios, the data may not be

Wei-Ming Dai, Yin-Zhe Ma, Hong-Jian He

Holographic dark energy (HDE) describes the vacuum energy in a cosmic IR region whose total energy saturates the limit of avoiding the collapse into a black hole. HDE predicts that the dark energy equation of the state transiting from greater than the $-1$ regime to less than $-1$, accelerating the Universe slower at the early stage and faster at the late st

N. Mert Vural, Selim F. Yilmaz, Fatih Ilhan, Suleyman S. Kozat

We investigate online nonlinear regression with continually running recurrent neural network networks (RNNs), i.e., RNN-based online learning. For RNN-based online learning, we introduce an efficient first-order training algorithm that theoretically guarantees to converge to the optimum network parameters. Our algorithm is truly online such that it does not

Nina Mazyavkina, Sergey Sviridov, Sergei Ivanov, Evgeny Burnaev

Many traditional algorithms for solving combinatorial optimization problems involve using hand-crafted heuristics that sequentially construct a solution. Such heuristics are designed by domain experts and may often be suboptimal due to the hard nature of the problems. Reinforcement learning (RL) proposes a good alternative to automate the search of these heu

Armin Pournaki, Felix Gaisbauer, Sven Banisch, Eckehard Olbrich

We present an open-source interface for scientists to explore Twitter data through interactive network visualizations. Combining data collection, transformation and visualization in one easily accessible framework, the twitter explorer connects distant and close reading of Twitter data through the interactive exploration of interaction networks and semantic

K. M. Rajwade, M. B. Mickaliger, B. W. Stappers, V. Morello

The discovery that at least some Fast Radio Bursts (FRBs) repeat has ruled out cataclysmic events as the progenitors of these particular bursts. FRB~121102 is the most well-studied repeating FRB but despite extensive monitoring of the source, no underlying pattern in the repetition has previously been identified. Here, we present the results from a radio mon

Andreas Björklund, Petteri Kaski

We show that computing the Tutte polynomial of a linear matroid of dimension $k$ on $k^{O(1)}$ points over a field of $k^{O(1)}$ elements requires $k^{Ω(k)}$ time unless the \#ETH---a counting extension of the Exponential Time Hypothesis of Impagliazzo and Paturi [CCC 1999] due to Dell {\em et al.} [ACM TALG 2014]---is false. This holds also for linear matro

Kunio Tokushuku, Tomonari Mizoguchi, Masafumi Udagawa

We obtain a classical spin liquid (CSL) phase by applying a magnetic field in $J_1$-$J_2$-$J_3$ Ising model on a kagome lattice. As we proved in the previous study [Phys. Rev. Lett. {\bf 119}, 077207 (2017)], this model realizes one species of CSL, the hexamer CSL, at zero magnetic field, which consists of macroscopically degenerate spin configurations with

Changbiao Wang

Minkowski applied Einstein's principle of relativity to moving media and developed electrodynamics of moving media. Like Einstein introduced the EM field-strength tensor $F^{μν}$ for electric field $\mathbf{E}$ and magnetic induction $\mathbf{B}$, Minkowski introduced another EM field-strength tensor $G^{μν}$ for the electric displacement $\mathbf{D}$ an

Ira B Schwartz, Victoria Edwards, Sayomi Kamimoto, Klimka Kasraie

Dynamical emergent patterns of swarms are now fairly well established in nature, and include flocking and rotational states. Recently, there has been great interest in engineering and physics to create artificial self-propelled agents that communicate over a network and operate with simple rules, with the goal of creating emergent self-organizing swarm patte

Michikazu Kobayashi, Philippe Parnaudeau, Francky Luddens, Corentin Lothode

This paper is concerned with the numerical investigation of Quantum Turbulence (QT) described by the Gross-Pitaevskii (GP) equation. Numerical simulations are performed using a parallel (MPI-OpenMP) code based on a pseudo-spectral spatial discretization and second order splitting for the time integration. We start by revisiting (in the framework of high-perf

Sang-Ho Kim, Seung-il Nam

We investigate $ϕ$-meson electroproduction off the proton target, i.e., $γ^* p \to ϕp$, by employing a tree-level effective Lagrangian approach in the kinematical ranges of $Q^2$ = (0$-$4) $\mathrm{GeV}^2$, $W$ = (2$-$5) GeV, and $|t| \leq 2\,\mathrm{GeV}^2$. In addition to the universally accepted Pomeron exchange, we consider various meson exchanges in the

Robert L. Jack, Rosemary J. Harris

We analyse large deviations of time-averaged quantities in stochastic processes with long-range memory, where the dynamics at time t depends itself on the value q_t of the time-averaged quantity. First we consider the elephant random walk and a Gaussian variant of this model, identifying two mechanisms for unusual fluctuation behaviour, which differ from the

V. A. Khodel, J. W. Clark, M. V. Zverev

We address the intervention of classical-like behavior, well documented in experimental studies of strongly correlated electron systems of solids that emerges at temperatures $T$ far below the Debye temperature $T_D$. We attribute this unexpected phenomenon to spontaneous rearrangement of the conventional Landau state beyond a critical point at which the top

Yuri Viazovetskyi, Vladimir Ivashkin, Evgeny Kashin

StyleGAN2 is a state-of-the-art network in generating realistic images. Besides, it was explicitly trained to have disentangled directions in latent space, which allows efficient image manipulation by varying latent factors. Editing existing images requires embedding a given image into the latent space of StyleGAN2. Latent code optimization via backpropagati

Roberto Casadio, Iberê Kuntz

We compute quantum corrections for the gravitational potential obtained by including a derivative self-coupling in its classical dynamics as a toy model for analysing quantum gravity in the strong field regime. In particular, we focus on quantum corrections to the classical solutions in the vacuum outside localised matter sources.

Laura Bozzelli, Aniello Murano, Adriano Peron

In this paper, we investigate the module-checking problem of pushdown multi-agent systems (PMS) against ATL and ATL* specifications. We establish that for ATL, module checking of PMS is 2EXPTIME-complete, which is the same complexity as pushdown module-checking for CTL. On the other hand, we show that ATL* module-checking of PMS turns out to be 4EXPTIME-comp

Murat Sağlam

We show that any co-oriented closed contact manifold of dimension at least five admits a contact form such that the contact volume is arbitrarily small but the Reeb flow admits a global hypersurface of section with the property that the minimal period on the boundary of the hypersurface and the first return time in the interior of the hypersurface are bounde

Jacopo Pegoraro, Francesca Meneghello, Michele Rossi

In this work, we investigate the use of backscattered mm-wave radio signals for the joint tracking and recognition of identities of humans as they move within indoor environments. We build a system that effectively works with multiple persons concurrently sharing and freely moving within the same indoor space. This leads to a complicated setting, which requi

Mahdi Boloursaz Mashhadi, Qianqian Yang, Deniz Gunduz

Massive multiple-input multiple-output (MIMO) systems require downlink channel state information (CSI) at the base station (BS) to achieve spatial diversity and multiplexing gains. In a frequency division duplex (FDD) multiuser massive MIMO network, each user needs to compress and feedback its downlink CSI to the BS. The CSI overhead scales with the number o

Bin Zhu, Qing Song, Lu Yang, Zhihui Wang

In object detection, offset-guided and point-guided regression dominate anchor-based and anchor-free method separately. Recently, point-guided approach is introduced to anchor-based method. However, we observe points predicted by this way are misaligned with matched region of proposals and score of localization, causing a notable gap in performance. In this

Kuntal Deka, Minerva Priyadarsini, Sanjeev Sharma, Baltasar Beferull-Lozano

Non-orthogonal multiple access (NOMA) is a promising technology which meets the demands of massive connectivity in future wireless networks. Sparse code multiple access (SCMA) is a popular code-domain NOMA technique. The effectiveness of SCMA comes from: (1) the multi-dimensional sparse codebooks offering high shaping gain and (2) sophisticated multi-user de

Ze-Chun Hu, Ting Ma, Xiu-Ju Zhu

In this note, convergence of random variables will be revisited. We will give the answers to 5 questions among the 6 open questions introduced in (Convergence rates in the law of large numbers and new kinds of convergence of random variables, {\it Communication in Statistics - Theory and Methods}, DOI: 10.1080/03610926.2020.1716248), and make some related di

ATLAS Collaboration

Azimuthal anisotropies of muons from charm and bottom hadron decays are measured in Pb+Pb collisions at $\sqrt{s_\mathrm{NN}}= 5.02$ TeV. The data were collected with the ATLAS detector at the Large Hadron Collider in 2015 and 2018 with integrated luminosities of $0.5~\mathrm{nb}^{-1}$ and $1.4~\mathrm{nb^{-1}}$, respectively. The kinematic selection for hea

Jinjin Xu, Wenli Du, Ran Cheng, Wangli He

Learning over massive data stored in different locations is essential in many real-world applications. However, sharing data is full of challenges due to the increasing demands of privacy and security with the growing use of smart mobile devices and IoT devices. Federated learning provides a potential solution to privacy-preserving and secure machine learnin

Genly Leon, Esteban González, Alfredo D. Millano, Felipe Orlando Franz Silva

Scalar field cosmologies with a generalized harmonic potential are investigated in flat and negatively curved Friedmann-Lemaître-Robertson-Walker and Bianchi I metrics. An interaction between the scalar field and matter is considered. Asymptotic methods and averaging theory are used to obtain relevant information about the solution space. In this approach, t

Tanji Zhou, Zhongcheng Yu, Zhihan Li, Xuzong Chen

With topologcial semimetal developing, semimetal with nodal-line ring comes into people's vision as a powerful candidate for practical application of topological devices. We propose a method using ultracold atoms in two-dimensional amplitude-shaken bipartite hexagonal optical lattice to simulate nodal-line semimetal, which can be achieved in experiment b

Shiqi Zheng, Peng Shi, Ramesh K. Agarwal, Chee Peng Lim

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have ac

Edith Elkind, Neel Patel, Alan Tsang, Yair Zick

We examine the problem of assigning plots of land to prospective buyers who prefer living next to their friends. They care not only about the plot they receive, but also about their neighbors. This externality results in a highly non-trivial problem structure, as both friendship and land value play a role in determining agent behavior. We examine mechanisms

Ke Ou

In this paper, we determine the modular invariants of finite modular pseudo-reflection subgroups of the finite general linear group $ \text{GL}_n(q) $ acting on the tensor product of the symmetric algebra $ S^{\bullet}(V) $ and the exterior algebra $ \wedge^{\bullet}(V) $ of the natural $ \text{GL}_n(q) $-module $ V $. We are particularly interested in the c

Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

ISO 24617-2, the standard for dialog act annotation, defines a hierarchically organized set of general-purpose communicative functions. The automatic recognition of these functions, although practically unexplored, is relevant for a dialog system, since they provide cues regarding the intention behind the segments and how they should be interpreted. We explo

Godwill Mbiti Kanyolo, Titus Masese, Nami Matsubara, Chih-Yao Chen

The advent of nanotechnology has hurtled the discovery and development of nanostructured materials with stellar chemical and physical functionalities in a bid to address issues in energy, environment, telecommunications and healthcare. In this quest, a class of two-dimensional layered materials consisting of alkali or coinage metal atoms sandwiched between s

Klaas Landsman

The aim of this paper is to argue that the (alleged) indeterminism of quantum mechanics, claimed by adherents of the Copenhagen interpretation since Born (1926), can be proved from Chaitin's follow-up to Goedel's (first) incompleteness theorem. In comparison, Bell's (1964) theorem as well as the so-called free will theorem-originally due to Heywo

Marc Noy, Vonjy Rasendrahasina, Vlady Ravelomanana, Juanjo Rué

Let $L$ be subset of $\{3,4,\dots\}$ and let $X_{n,M}^{(L)}$ be the number of cycles belonging to unicyclic components whose length is in $L$ in the random graph $G(n,M)$. We find the limiting distribution of $X_{n,M}^{(L)}$ in the subcritical regime $M=cn$ with $c<1/2$ and the critical regime $M=\frac{n}{2}\left(1+μn^{-1/3}\right)$ with $μ=O(1)$. Depending

David Rios Insua, Roi Naveiro, Victor Gallego, Jason Poulos

Adversarial Machine Learning (AML) is emerging as a major field aimed at protecting machine learning (ML) systems against security threats: in certain scenarios there may be adversaries that actively manipulate input data to fool learning systems. This creates a new class of security vulnerabilities that ML systems may face, and a new desirable property call

Gioele Zardini, Nicolas Lanzetti, Mauro Salazar, Andrea Censi

The design of autonomous vehicles (AVs) and the design of AV-enabled mobility systems are closely coupled. Indeed, knowledge about the intended service of AVs would impact their design and deployment process, whilst insights about their technological development could significantly affect transportation management decisions. This calls for tools to study suc

Jay Gupta, Swaprava Nath

Skill verification is a central problem in workforce hiring. Companies and academia often face the difficulty of ascertaining the skills of an applicant since the certifications of the skills claimed by a candidate are generally not immediately verifiable and costly to test. Blockchains have been proposed in the literature for skill verification and tamper-p

Mikhail Alfimov, Nikolay Gromov, Vladimir Kazakov

We review the applications of the Quantum Spectral Curve (QSC) method to the Regge (BFKL) limit in N=4 supersymmetric Yang-Mills theory. QSC, based on quantum integrability of the AdS$_5$/CFT$_4$ duality, was initially developed as a tool for the study of the spectrum of anomalous dimensions of local operators in the N=4 SYM in the planar, $N_c\to\infty$ lim

Axel Laborieux, Maxence Ernoult, Tifenn Hirtzlin, Damien Querlioz

While deep neural networks have surpassed human performance in multiple situations, they are prone to catastrophic forgetting: upon training a new task, they rapidly forget previously learned ones. Neuroscience studies, based on idealized tasks, suggest that in the brain, synapses overcome this issue by adjusting their plasticity depending on their past hist

C. Wang, R. L. Huang, J. G. Bao

We study the solvability of the second boundary value problem of the Lagrangian mean curvature equation arising from special Lagrangian geometry. By the parabolic method we obtain the existence and uniqueness of the smooth uniformly convex solution, which generalizes the Brendle-Warren&#39;s theorem about minimal Lagrangian diffeomorphism in Euclidean metric

Yonghee Kim, Emiko Hiyama, Makoto Oka, Kei Suzuki

The mass spectra of singly charmed and bottom baryons, $Λ_{c/b}(1/2^\pm,3/2^-)$ and $Ξ_{c/b}(1/2^\pm,3/2^-)$, are investigated using a nonrelativistic potential model with a heavy quark and a light diquark. The masses of the scalar and pseudoscalar diquarks are taken from a chiral effective theory. The effect of $U_A(1)$ anomaly induces an inverse hierarchy

Baruch Rosenstein, B. Ya. Shapiro

Microscopic theory of a high Tc cuprate BiSCO based on main pairing channel of electrons in CuO planes due to 40meV lateral vibrations of the apical oxygen atoms in adjacent the SrO ionic insulator layer is proposed. The separation between the vibrating charged atoms and the 2D electron gas creates the forward scattering peak leading in turn to the d-wave pa

Balaji Ganesan, Srinivas Parkala, Neeraj R Singh, Sumit Bhatia

Learning graph representations of n-ary relational data has a number of real world applications like anti-money laundering, fraud detection, and customer due diligence. Contact tracing of COVID19 positive persons could also be posed as a Link Prediction problem. Predicting links between people using Graph Neural Networks requires careful ethical and privacy

Lingfeng Tao, Michael Bowman, Xu Zhou, Jiucai Zhang

Enabling robots to provide effective assistance yet still accommodating the operator's commands for telemanipulation of an object is very challenging because robot's assistive action is not always intuitive for human operators and human behaviors and preferences are sometimes ambiguous for the robot to interpret. Although various assistance approaches are be

Qisheng Wang, Mingsheng Ying

Random access machines (RAMs) and random access stored-program machines (RASPs) are models of computing that are closer to the architecture of real-world computers than Turing machines (TMs). They are also convenient in complexity analysis of algorithms. The relationships between RAMs, RASPs and TMs are well-studied. However, clear relationships between thei

Hiroyuki Abe, Tatsuo Kobayashi, Shohei Uemura, Junji Yamamoto

We study Fayet-Iliopoulos (FI) terms of six-dimensional supersymmetric Abelian gauge theory compactified on a $T^2/Z_2$ orbifold. Such orbifold compactifications can lead to localized FI-terms and instability of bulk zero modes. We study 1-loop correction to FI-terms in more general geometry than the previous works. We find induced FI-terms depend on the com

Gabriel Angelini-Knoll, Andrew Salch

This paper provides conditions for Morava $K$-theory to commute with certain homotopy limits. These conditions extend previous work on this question by allowing for homotopy limits of sequences of spectra that are not uniformly bounded below. As an application, we prove the $K(n)$-local triviality (for sufficiently large $n$) of the algebraic $K$-theory of a

Chia Zargeh

In this paper we introduce the notion of existentially closed Leibniz algebras. Then we use HNN-extensions of Leibniz algebras in order to prove an embedding theorem.

Yuki Koyano, Hiroyuki Kitahata, Koji Hasegawa, Satoshi Matsumoto

Recent experimental results indicate that mixing is enhanced by a reciprocal flow induced inside a levitated droplet with an oscillatory deformation [T. Watanabe et al. Sci. Rep. 8, 10221 (2018)]. Generally, reciprocal flow cannot convect the solutes in time average, and agitation cannot take place. In the present paper, we focus on the diffusion process cou

Nico Vervliet, Andreas Themelis, Panagiotis Patrinos, Lieven De Lathauwer

The decomposition of tensors into simple rank-1 terms is key in a variety of applications in signal processing, data analysis and machine learning. While this canonical polyadic decomposition (CPD) is unique under mild conditions, including prior knowledge such as nonnegativity can facilitate interpretation of the components. Inspired by the effectiveness an

Palash Goyal, Saurabh Sahu, Shalini Ghosh, Chul Lee

Multi-modal machine learning (ML) models can process data in multiple modalities (e.g., video, audio, text) and are useful for video content analysis in a variety of problems (e.g., object detection, scene understanding, activity recognition). In this paper, we focus on the problem of video categorization using a multi-modal ML technique. In particular, we h

Xiaojie Qi

It is a consensus that feature maps in the shallow layer are more related to image attributes such as texture and shape, whereas abstract semantic representation exists in the deep layer. Meanwhile, some image information will be lost in the process of the convolution operation. Naturally, the direct method is combining them together to gain lost detailed in

Andrew Clark

Control Barrier Functions (CBFs) aim to ensure safety by constraining the control input at each time step so that the system state remains within a desired safe region. This paper presents a framework for CBFs in stochastic systems in the presence of Gaussian process and measurement noise. We first consider the case where the system state is known at each ti

Yan Hong, Li Niu, Jianfu Zhang, Liqing Zhang

To generate new images for a given category, most deep generative models require abundant training images from this category, which are often too expensive to acquire. To achieve the goal of generation based on only a few images, we propose matching-based Generative Adversarial Network (GAN) for few-shot generation, which includes a matching generator and a

Futao Sun, Jiulin Du

We study the collision frequency of electron-neutral-particle in the weakly ionized plasma with the power-law velocity q-distribution and derive the formulation of the average collision frequency. We find that the average collision frequency in the q-distributed plasma also depends strongly on the q-parameter and thus is generally different from that in the

Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe

We revisit the problem of online learning with sleeping experts/bandits: in each time step, only a subset of the actions are available for the algorithm to choose from (and learn about). The work of Kleinberg et al. (2010) showed that there exist no-regret algorithms which perform no worse than the best ranking of actions asymptotically. Unfortunately, achie

Zechun Liu, Zhiqiang Shen, Marios Savvides, Kwang-Ting Cheng

In this paper, we propose several ideas for enhancing a binary network to close its accuracy gap from real-valued networks without incurring any additional computational cost. We first construct a baseline network by modifying and binarizing a compact real-valued network with parameter-free shortcuts, bypassing all the intermediate convolutional layers inclu

João Henrique Andrade, João Marcos do Ó

We study the asymptotic behavior for singular solutions to a critical fourth order system generalizing the constant $Q$-curvature equation. Our main result extends to the case of strongly coupled systems, the celebrated asymptotic classification due to [L. A. Caffarelli, B. Gidas and J. Spruck, Comm. Pure Appl. Math. (1989)] and [N. Korevaar, R. Mazzeo, F. P

Md. Habibur Rahman Sifat, Chowdhury Rafeed Rahman, Mohammad Rafsan, Md. Hasibur Rahman

While writing Bengali using English keyboard, users often make spelling mistakes. The accuracy of any Bengali spell checker or paragraph correction module largely depends on the kind of error dataset it is based on. Manual generation of such error dataset is a cumbersome process. In this research, We present an algorithm for automatic misspelled Bengali word

Li Songlin, Deng Yangdong, Wang Zhihua

Grid cells are believed to play an important role in both spatial and non-spatial cognition tasks. A recent study observed the emergence of grid cells in an LSTM for path integration. The connection between biological and artificial neural networks underlying the seemingly similarity, as well as the application domain of grid cells in deep neural networks (D

Sam M. Werner, Paul J. Pritz, Daniel Perez

In the Ethereum network, miners are incentivized to include transactions in a block depending on the gas price specified by the sender. The sender of a transaction therefore faces a trade-off between timely inclusion and cost of his transaction. Existing recommendation mechanisms aggregate recent gas price data on a per-block basis to suggest a gas price. We

Qinqing Zheng, Bor-Yiing Su, Jiyan Yang, Alisson Azzolini

Recommendation systems are often trained with a tremendous amount of data, and distributed training is the workhorse to shorten the training time. While the training throughput can be increased by simply adding more workers, it is also increasingly challenging to preserve the model quality. In this paper, we present \shadowsync, a distributed framework speci

Shashank Tripathi, Siddhant Ranade, Ambrish Tyagi, Amit Agrawal

Recovering 3D human pose from 2D joints is a highly unconstrained problem. We propose a novel neural network framework, PoseNet3D, that takes 2D joints as input and outputs 3D skeletons and SMPL body model parameters. By casting our learning approach in a student-teacher framework, we avoid using any 3D data such as paired/unpaired 3D data, motion capture se

Jingpei Lu, Ambareesh Jayakumari, Florian Richter, Yang Li

Robotic automation in surgery requires precise tracking of surgical tools and mapping of deformable tissue. Previous works on surgical perception frameworks require significant effort in developing features for surgical tool and tissue tracking. In this work, we overcome the challenge by exploiting deep learning methods for surgical perception. We integrated

Samer Henry, Ahmed Alsohaily, Elvino Sousa

The 3rd Generation Partnership Project (3GPP) submitted the 5G New Radio (NR) system specifications to International Telecommunication Union (ITU) as a candidate fifth generation (5G) mobile communication system (formally denoted as IMT-2020 systems). As part of the submission, 3GPP provided a self-evaluation for the compliance of 5G NR systems with the ITU

Haoyu Zhang, Yaochu Jin, Ran Cheng, Kuangrong Hao

The performance of a deep neural network is heavily dependent on its architecture and various neural architecture search strategies have been developed for automated network architecture design. Recently, evolutionary neural architecture search (ENAS) has received increasing attention due to the attractive global optimization capability of evolutionary algor

Xuehai He, Yichen Zhang, Luntian Mou, Eric Xing

Is it possible to develop an &#34;AI Pathologist&#34; to pass the board-certified examination of the American Board of Pathology? To achieve this goal, the first step is to create a visual question answering (VQA) dataset where the AI agent is presented with a pathology image together with a question and is asked to give the correct answer. Our work makes th

S. Son

A new mechanism for the THz light amplification is identified ina non-resonant Raman scattering between the THz light and a visible light lasers. The non-resonant scattering normally does not exchange the energy between E \&M fields, but the presence of the plasma density gradientcreates an condition in which a visible light laser could transfer its energy i

Xiang Li, Chao Wang, Jiwei Tan, Xiaoyi Zeng

For better user experience and business effectiveness, Click-Through Rate (CTR) prediction has been one of the most important tasks in E-commerce. Although extensive CTR prediction models have been proposed, learning good representation of items from multimodal features is still less investigated, considering an item in E-commerce usually contains multiple h

Varad Deshmukh, Elizabeth Bradley, Joshua Garland, James D. Meiss

We propose a curvature-based approach for choosing good values for the time-delay parameter $τ$ in delay reconstructions. The idea is based on the effects of the delay on the geometry of the reconstructions. If the delay is chosen too small, the reconstructed dynamics are flattened along the main diagonal of the embedding space; too-large delays, on the othe

Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das, Mandira Saha

We report a model to predict patient&#39;s radiological response to curative radiation therapy (RT) for non-small-cell lung cancer (NSCLC). Cone-Beam Computed Tomography images acquired weekly during the six-week course of RT were contoured with the Gross Tumor Volume (GTV) by senior radiation oncologists for 53 patients (7 images per patient). Deformable re

Pengli Lu, JingJuan Yu

Essential protein plays a crucial role in the process of cell life. The identification of essential proteins can not only promote the development of drug target technology, but also contribute to the mechanism of biological evolution. There are plenty of scholars who pay attention to discovering essential proteins according to the topological structure of pr

Gautam Krishna, Co Tran, Mason Carnahan, Ahmed Tewfik

In this paper we explore speaker identification using electroencephalography (EEG) signals. The performance of speaker identification systems degrades in presence of background noise, this paper demonstrates that EEG features can be used to enhance the performance of speaker identification systems operating in presence and absence of background noise. The pa

Raphaël Berthon, Bastien Maubert, Aniello Murano, Sasha Rubin

We introduce an extension of Strategy Logic for the imperfect-information setting, called SLii, and study its model-checking problem. As this logic naturally captures multi-player games with imperfect information, this problem is undecidable; but we introduce a syntactical class of &#34;hierarchical instances&#34; for which, intuitively, as one goes down the

Rosana Veroneze, Fernando J. Von Zuben

This paper further extends RIn-Close_CVC, a biclustering algorithm capable of performing an efficient, complete, correct and non-redundant enumeration of maximal biclusters with constant values on columns in numerical datasets. By avoiding a priori partitioning and itemization of the dataset, RIn-Close_CVC implements an online partitioning, which is demonstr

Trevor P. Searight

A complete set of wave solutions is given for the weak field in a Kaluza-Klein theory with degenerate metric. In the five-dimensional version of this theory electromagnetism is described by two vector fields, and there is a reflection symmetry between them which unifies them with gravitation; wave behaviour in the extra dimension has been interpreted as dark

Arianna Giunti, Richard M. Höfer

We consider the homogenization to the Brinkman equations for the incompressible Stokes equations in a bounded domain which is perforated by a random collection of small spherical holes. This problem has been studied by the same authors in [A. Giunti and R.M. Höfer, Homogenization for the Stokes equations in randomly perforated domains under almost minimal as

Wanpeng Tan

In light of Gödel&#39;s undecidability results (incomplete theorems) for math, quantum indeterminism indicates that physics and the Universe may be indeterministic, incomplete, and open in nature, and therefore demand no single unification theory of everything. The Universe is dynamic and so are the underlying physical models and spacetime. As the 4-d spacet

Xin-Yun Hu, Ke-Jian He, Zhong-Hua Li, Guo-Ping Li

Treating the cosmological constant as a dynamical variable, we investigate the thermodynamics and weak cosmic censorship conjecture (WCCC) of a charged AdS black hole (BH) in the Rastall gravity. We determine the energy momentum relation of charged fermion at the horizon of the BH by using the Dirac equation. Based on this relation, we show that the first la

Stefano Maria Iacus, Fabrizio Natale, Michele Vespe

This short note provides estimates of the number of passengers that travel from China to all world airports in the period October 2019 - March 2020 on the basis of historical data. From this baseline we subtract the expected reduction in the number of passengers taking into account the temporary ban of some routes which was put in place since 23 January 2020

Carina Geldhauser, Christian Kuehn

Many physical, chemical and biological systems have an inherent discrete spatial structure that strongly influences their dynamical behaviour. Similar remarks apply to internal or external noise, as well as to nonlocal coupling. In this paper we study the combined effect of nonlocal spatial discretization and stochastic perturbations on travelling waves in t

Yoshikazu Hagiwara, Yoshitaka Hatta, Roman Pasechnik, Jian Zhou

We introduce a new model of near-forward elastic proton-(anti)proton scattering at high energy based on the modern formulation of Pomeron and Odderon in terms of Wilson lines and generalized TMDs (GTMDs). We compute the helicity-dependent elastic amplitudes $ϕ_{1,2,3,4,5}$ in this model and study their energy dependence from the nonlinear small-$x$ evolution

Songyan Xin, Sethu Vijayakumar

Wheeled-legged robots combine the efficiency of wheeled robots when driving on suitably flat surfaces and versatility of legged robots when stepping over or around obstacles. This paper introduces a planning and control framework to realise dynamic locomotion for wheeled biped robots. We propose the Cart-Linear Inverted Pendulum Model (Cart-LIPM) as a templa

Rami Puzis, Polina Zilberman, Yuval Elovici

Attackers rapidly change their attacks to evade detection. Even the most sophisticated Intrusion Detection Systems that are based on artificial intelligence and advanced data analytic cannot keep pace with the rapid development of new attacks. When standard detection mechanisms fail or do not provide sufficient forensic information to investigate and mitigat

Shivam Barwey, Venkat Raman, Adam Steinberg

Simultaneous measurements, such as the combination of particle image velocimetry (PIV) for velocity fields with planar laser induced fluorescence (PLIF) for species fields, are widely used in experimental turbulent combustion applications for the analysis of a plethora of complex physical processes. Such physical analyses are driven by the interpretation of

Daniel A. Goldston, Sidney W. Graham, Apoorva Panidapu, Janos Pintz

This paper is intended as a sequel to a paper arXiv:0803.2636 written by four of the coauthors here. In the paper, they proved a stronger form of the Erdős-Mirksy conjecture which states that there are infinitely many positive integers $x$ such that $d(x)=d(x+1)$ where $d(x)$ denotes the number of divisors of $x$. This conjecture was first proven by Heath-Br

M. Tahir Patel, Ramachandran A. Vijayan, Reza Asadpour, M. Varadharajaperumal

Bifacial solar panels are perceived to be the technology of choice for next generation solar farms for their increased energy yield at marginally increased cost. As the bifacial farms proliferate around the world, it is important to investigate the role of temperature-dependent energy-yield and levelized cost of energy (LCOE) of bifacial solar farms relative

Noel Kennedy, Imogen Schofield, Dave C. Brodbelt, David B. Church

We experiment with new methods for learning how related words are positioned relative to each other in word embedding spaces. Previous approaches learned constant vector offsets: vectors that point from source tokens to target tokens with an assumption that these offsets were parallel to each other. We show that the offsets between related tokens are closer

Radosh Bakich

We study distribution of zeros of a complex polynomial whose coefficients has been modified. We give a new proof of the theorem of Rubinstein, and with similar method we prove a new theorem that is not generalization of the previous theorem, but is more efficient in the most number of cases.

Maryam Ashrafi, M. H. Naderi

An investigation is reported of the collective effects and the dynamics of atom atom entanglement in a system of two distant two level atoms which are coupled via an optical element. In the system under consideration, the two atoms, which are trapped in the foci of a lens, are coupled to a common environment being in the vacuum state and they emit photons sp

Pierre-Henri Chavanis

We compute the quantum tunneling rate of dilute axion stars close to the maximum mass [P.H. Chavanis, Phys. Rev. D {\bf 84}, 043531 (2011)] using the theory of instantons. We confirm that the lifetime of metastable states is extremely long, scaling as $t_{\rm life}\sim e^N\, t_D$ (except close to the critical point), where $N$ is the number of axions in the

Jetlir Duraj, Kilian Raschel, Pierre Tarrago, Vitali Wachtel

We determine the asymptotic behavior of the Green function for zero-drift random walks confined to multidimensional convex cones. As a consequence, we prove that there is a unique positive discrete harmonic function for these processes (up to a multiplicative constant); in other words, the Martin boundary reduces to a singleton.

Massimo Grossi, Peng Luo

In this paper we study the following problem \begin{equation} \begin{cases} -Δu=f(u)~&\mbox{in}\ Ω_\varepsilon,\\ u>0~&\mbox{in}\ Ω_\varepsilon,\\ u=0~&\mbox{on}\ \partialΩ_\varepsilon, \end{cases} \end{equation} where $Ω_\varepsilon=Ω\backslash B(P,\varepsilon)$, $Ω\subset R^N$ with $N\geq 2$ is a smooth bounded domain, $B(P,\varepsilon)$ is the ball center

Alex E. Bernardini, Victor A. S. V. Bittencourt, Massimo Blasone

The quantum concurrence of $SU(2) \otimes SU(2)$ spin-parity states is shown to be invariant under $SO(1,3)$ Lorentz boosts and $O(3)$ rotations when the density matrices are constructed in consonance with the covariant probabilistic distribution of Dirac massive particles. Similar invariance properties are obtained for the quantum purity and for the trace o