November 2019 arXiv papers — page 65

Denis P. Ilyutko, Vassily O. Manturov

In [3] we constructed the parity-biquandle bracket valued in {\em pictures} (linear combinations of $4$-valent graphs). We gave no example of classical links such that the parity-biquandle bracket of which is not trivial. In the present paper we slightly change the notation of the parity-biquandle bracket and give examples of knots and links having a non-tri

Christian M. Rohwer, Mehran Kardar, Matthias Krüger

Perturbations of fluid media can give rise to non-equilibrium dynamics, which may in turn cause motion of immersed inclusions. We consider perturbations ("activations") that are local in space and time, of a fluid density which is conserved, and study the resulting diffusiophoretic phenomena that emerge at a large distance. Specifically, we consider

Yunhan Huang

In this work, we use a Stackelberg infinite discrete-time dynamic game model to study the optimal supply schedule and the optimal demand response under a market-driven dynamic price. A two-layer optimization framework is established. At the lower layer, for each user, different appliances are scheduled for energy consumption. For enegy provider, different ge

Alessio Bernardo, Emanuele Della Valle, Albert Bifet

Nowadays, every device connected to the Internet generates an ever-growing stream of data (formally, unbounded). Machine Learning on unbounded data streams is a grand challenge due to its resource constraints. In fact, standard machine learning techniques are not able to deal with data whose statistics is subject to gradual or sudden changes without any warn

Helena Ribera, Brian Wetton, Timothy Myers

In this paper we detail the mechanisms that drive substitutional binary diffusion and derive appropriate governing equations. We focus on the one-dimensional case with insulated boundary conditions. Asymptotic expansions are used in order to simplify the problem. We are able to obtain approximate analytical solutions in two distinct cases: the two species di

D. Yu. Khanukaeva

This paper considers membranes of globular structure in the framework of the cell model technique. Coupled micropolar and Brinkman-type equations are used to model the flow of micropolar fluid through a spherical cell, consisting of solid core, porous layer and liquid envelope. The solution is obtained in analytical form. Boundary value problems with differe

Xuemei Chen, Yang Chu, Min Zheng

A frame is an overcomplete set that can represent vectors(signals) faithfully and stably. Two frames are equivalent if signals can be essentially represented in the same way, which means two frames differ by a permutation, sign change or orthogonal transformation. Since these operations are combinatorial in nature, it is infeasible to check whether two frame

A. Santerne, L. Malavolta, M. R. Kosiarek, F. Dai

Transiting extrasolar planets are key objects in the study of the formation, migration, and evolution of planetary systems. In particular, the exploration of the atmospheres of giant planets, through transmission spectroscopy or direct imaging, has revealed a large diversity in their chemical composition and physical properties. Studying these giant planets

Bishakh Chandra Ghosh, Sourav Kanti Addya, Nishant Baranwal Somy, Shubha Brata Nath

Serverless computing has gained a significant traction in recent times because of its simplicity of development, deployment and fine-grained billing. However, while implementing complex services comprising databases, file stores, or more than one serverless function, the performance in terms of latency of serving requests often degrades severely. In this wor

Esma Zouaoui, Noureddine Mebarki

A new model using a general expression of the radiation energy and explaining the dynamics of the afterglows is proposed. It is shown that this model is suitable for the ultra-relativistic and non-relativistic phases as well as the study of radiative and adiabatic fireballs.

Abhinav Jain, Seth Hutchinson, Frank Dellaert

In this paper, we explore the task of robot sculpting. We propose a search based planning algorithm to solve the problem of sculpting by material removal with a multi-axis manipulator. We generate collision free trajectories for a manipulator using best-first search in voxel space. We also show significant speedup of our algorithm by using octrees to decompo

Abhinav Jain, Frank Dellaert

Pose estimation is a vital step in many robotics and perception tasks such as robotic manipulation, autonomous vehicle navigation, etc. Current state-of-the-art pose estimation methods rely on deep neural networks with complicated structures and long inference times. While highly robust, they require computing power often unavailable on mobile robots. We pro

Xue-Mei Li

We introduce strong p-completeness and use them for studying the continuous dependence of solutions of SDE's on non-compact manifolds. We obtain conditions for the existence of global smooth solution flow, and prove their diffeomorphism properties. The criterion is in terms of the growth of the solutions of the linearized equations (i.e. the derivative f

Harald Hanselmann, Hermann Ney

The task of fine-grained visual classification (FGVC) deals with classification problems that display a small inter-class variance such as distinguishing between different bird species or car models. State-of-the-art approaches typically tackle this problem by integrating an elaborate attention mechanism or (part-) localization method into a standard convolu

Xiongquan Yao, Lei Li, Andrey Komarov, Mariusz Klimczak

Due to the weak birefringence of single mode fibers, solitons generated in fiber lasers are indeed vector pulses and exhibit periodic parameter change including polarization evolution even when there is a polarizer inside the cavity. Period doubling eigenstates of solitons generated in a fiber laser mode-locked by the nonlinear polarization rotation, i.e., p

Nao Fukagawa

Studying the evolution of dwarf galaxies can provide insights into the characteristics of systems that can act as building blocks of massive galaxies. This paper discusses the history of star formation and gas flows (inflow and outflow) of a dwarf irregular galaxy in the Local Group, NGC 6822, from the viewpoint of gas-phase and stellar chemical abundance. G

Scott A. Cameron, Hans C. Eggers, Steve Kroon

We consider estimating the marginal likelihood in settings with independent and identically distributed (i.i.d.) data. We propose estimating the predictive distributions in a sequential factorization of the marginal likelihood in such settings by using stochastic gradient Markov Chain Monte Carlo techniques. This approach is far more efficient than tradition

Shin'ichi Nojiri, S. D. Odintsov, V. K. Oikonomou

In this work we shall study ghost-free non-local $F(R)$ gravity models. Firstly we shall demonstrate how the ghost degrees of freedom may occur in the non-local $F(R)$ gravity models, and accordingly we shall modify appropriately the gravitational action of non-local $F(R)$ gravity models in order to eliminate the ghosts. Also we shall investigate how the (a

Christine Bauer

The task of a music recommender system is to predict what music item a particular user would like to listen to next. This position paper discusses the main challenges of the music preference prediction task: the lack of information on the many contextual factors influencing a user's music preferences in existing open datasets, the lack of clarity of what

Lars Diening, Franz Gmeineder

We establish a Riesz potential criterion for Lebesgue continuity points of functions of bounded $\mathbb{A}$-variation, where $\mathbb{A}$ is a $\mathbb{C}$-elliptic differential operator of arbitrary order. This result might even be of interest for classical functions of bounded variation.

David W. Kribs, Jeremy Levick, Mike Nelson, Rajesh Pereira

We show that the approximate quasiorthogonality of two operator algebras is equivalent to the algebras being approximately private relative to their conditional expectation quantum channels. Our analysis is based on a characterization of the measure of orthogonality in terms of Choi matrices and Kraus operators for completely positive maps. We present exampl

Xue-Mei Li

Let $M$ be a compact Riemannian manifold and $h$ a smooth function on $M$. Let $ρ^h(x)=\inf_{|v|=1}\left(Ric_x(v,v)-2Hess(h)_x(v,v) \right)$. Here $Ric_x$ denotes the Ricci curvature at $x$ and $Hess(h)$ is the Hessian of $h$. Then $M$ has finite fundamental group if $Δ^h-ρ^h<0$. Here $Δ^h=: Δ+2L_{\nabla h}$ is the Bismut-Witten Laplacian. This leads to a qu

Maryam Aliakbarpour, Sandeep Silwal

We propose a new setting for testing properties of distributions while receiving samples from several distributions, but few samples per distribution. Given samples from $s$ distributions, $p_1, p_2, \ldots, p_s$, we design testers for the following problems: (1) Uniformity Testing: Testing whether all the $p_i$&#39;s are uniform or $ε$-far from being unifor

Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang

Graph convolutional networks (GCNs) have recently received wide attentions, due to their successful applications in different graph tasks and different domains. Training GCNs for a large graph, however, is still a challenge. Original full-batch GCN training requires calculating the representation of all the nodes in the graph per GCN layer, which brings in h

Issaka Haruna, Oluwole Daniel Makinde, David Mwangi Theuri

In this paper we provide a model to describe the dynamics of the species of the ecosystem after it has been raided by a bad competing specie. The competing specie invades the native plants for nutrition, carbon dioxide and space. This affects the population of the native species of the ecosystem. The effect of the bad biomass on the ecosystem is examined by

E. N. Kabachkov, E. N. Kurkin, N. N. Vershinin, I. L. Balikhin

Catalysts of carbon monoxide oxidation were synthesized by deposition of platinum on titanium nitride (TiN). Two substrates with an average particle size of 18 and 36 nm were obtained by hydrogen reduction of titanium tetrachloride in a stream of microwave plasma of nitrogen. The surface of the catalysts was studied by X-ray photoelectron spectroscopy (XPS).

Ming Yu, Varun Gupta, Mladen Kolar

In typical high dimensional statistical inference problems, confidence intervals and hypothesis tests are performed for a low dimensional subset of model parameters under the assumption that the parameters of interest are unconstrained. However, in many problems, there are natural constraints on model parameters and one is interested in whether the parameter

Michael Cashmore, Alessandro Cimatti, Daniele Magazzeni, Andrea Micheli

One of the major limitations for the employment of model-based planning and scheduling in practical applications is the need of costly re-planning when an incongruence between the observed reality and the formal model is encountered during execution. Robustness Envelopes characterize the set of possible contingencies that a plan is able to address without re

Philippe Mulhem, Lorraine Goeuriot, Massih-Reza Amini, Nayanika Dogra

We describe here an experimental framework and the results obtained on microblogs retrieval. We study the contribution one popular approach, i.e., words embeddings, and investigate the impact of the training set on the learned embedding. We focus on query expansion for the retrieval of tweets on the CLEF CMC 2016 corpus. Our results show that using embedding

Daniel Ritter

As impressively shown by the financial crisis in 2007/08, contagion effects in financial networks harbor a great threat for the stability of the entire system. Without sufficient capital requirements for banks and other financial institutions, shocks that are locally confined at first can spread through the entire system and be significantly amplified by var

Behnam Akbari, Farhad Pourtahmasbi, Hossein Mokhtari

High percentage of voltage harmonics has been observed in transmission networks due to harmonic currents penetrated from the load side amplified by resonant conditions. This requires the use of suitable harmonic filters in transmission networks. However, filter placement in a transmission system for harmonic mitigation is a planning procedure of high complex

Penelope Taylor, Amy Longstreth, Maria-Teresa Herd

Speed of sound and attenuation as a function of frequency between 2 and 18 MHz were measured and compared for a cancerous prostate cell line and a healthy prostate cell line. Speed of sound for the cancerous cells line was found to be 1521.4 $\pm$ 0.8~m/s, which was equivalent to the speed of sound for the healthy cell line of 1521.5 $\pm$ 0.6~m/s. The avera

Senthil Mani, Anush Sankaran, Srikanth Tamilselvam, Akshay Sethi

Deep Neural Networks (DNNs), with its promising performance, are being increasingly used in safety critical applications such as autonomous driving, cancer detection, and secure authentication. With growing importance in deep learning, there is a requirement for a more standardized framework to evaluate and test deep learning models. The primary challenge in

Sanal Shivaprasad

We study the convergence of volume forms on a degenerating holomorphic family of log-Calabi-Yau varieties to a non-Archimedean measure, extending a result of Boucksom and Jonsson. More precisely, let $(X,B)$ be a holomorphic family of sub log canonical, log-Calabi-Yau complex varieties parameterized by the punctured unit disk. Let $η$ be a meromorphic volume

Maria Borralho

Elements $a,b$ of a semigroup $S$ are said to be \emph{primarily conjugate} or just \emph{p-conjugate}, if there exist $x,y\in S^1$ such that $a=xy$ and $b=yx$. The p-conjugacy relation generalizes conjugacy in groups, but for general semigroups, it is not transitive. Finding the classes of semigroups in which this notion is transitive is an open problem. Th

Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu

Deep learning based medical image diagnosis has shown great potential in clinical medicine. However, it often suffers two major difficulties in practice: 1) only limited labeled samples are available due to expensive annotation costs over medical images; 2) labeled images may contain considerable label noises (e.g., mislabeling labels) due to diagnostic diff

Akshay Raman, Kimberly Chou, Spyridon Mastorakis

Peer-to-peer file sharing envisions a data-centric dissemination model, where files consisting of multiple data pieces can be shared from any peer that can offer the data or from multiple peers simultaneously. This aim, implemented at the application layer of the network architecture, matches with the objective of Named Data Networking (NDN), a proposed Inte

Lim Tze Yee, Tony She, Kezia Irene

This paper analyses the Chinese Sovereign bond yield to find out the principal factors affecting the term structure of interest rate changes. We apply Principal Component Analysis (PCA) on our data consisting of the Chinese Sovereign bond from January 2002 till May 2018 with the different yield to maturity. Then we will discuss the multi-factor immunization

Paul Hoyer

A perturbative expansion for QED and QCD bound states is formulated in $A^0=0$ gauge. The constituents of each Fock state are bound by their instantaneous interaction. In QCD an O($α_s^0$) confining potential arises from a homogeneous solution of Gauss&#39; constraint. The potential is uniquely determined by the QCD action, up to a universal scale. The Corne

Brice Bastian, Stefan Hohenegger

We continue our study of symmetries of a class of little string theories of A-type, which are engineered by $N$ parallel M5-branes probing a flat transverse space. Extending the analysis of the companion paper, we discuss the part of the free energy that is sensitive to the details of the $\mathfrak{a}_{N-1}$ gauge structure, by computing explicit series exp

Alessio Rosatelli, Ekin Gedik, Hayley Hung

In this paper, we investigate the use of proxemics and dynamics for automatically identifying conversing groups, or so-called F-formations. More formally we aim to automatically identify whether wearable sensor data coming from 2 people is indicative of F-formation membership. We also explore the problem of jointly detecting membership and more descriptive i

Yulei Han, Yafei Ren, Xinlong Dong, Junjie Zeng

We numerically investigate the electronic transport properties between two mesoscopic graphene disks with a twist by employing the density functional theory coupled with non-equilibrium Green&#39;s function technique. By attaching two graphene leads to upper and lower graphene layers separately, we explore systematically the dependence of electronic transpor

Brice Bastian, Stefan Hohenegger

We analyse the symmetries of a class of A-type little string theories that are engineered by $N$ parallel M5-branes with M2-branes stretched between them. This paper deals with the so-called reduced free energy, which only receives contributions from the subset of the BPS states that carry the same charges under all the Cartan generators of the underlying ga

Peyton D. Murray, Dustin A. Gilbert, Alexander J. Grutter, Brian J. Kirby

Solid state ionic approaches for modifying ion distributions in getter/oxide heterostructures offer exciting potentials to control material properties. Here we report a simple, scalable approach allowing for total control of the superconducting transition in optimally doped YBa$_{2}$Cu$_{3}$O$_{7-δ}$ (YBCO) films via a chemically-driven ionic migration mecha

Zhigang Chang, Qin Zhou, Mingyang Yu, Shibao Zheng

To learn the optimal similarity function between probe and gallery images in Person re-identification, effective deep metric learning methods have been extensively explored to obtain discriminative feature embedding. However, existing metric loss like triplet loss and its variants always emphasize pair-wise relations but ignore the distribution context in fe

S. -F. Wu, A. Almoalem, I. Feldman, A. Lee

We study Fe$_{1+y}$Te$_{0.6}$Se$_{0.4}$ multi-band superconductor with $T_c=14$K by polarization-resolved Raman spectroscopy. Deep in the superconducting state, we detect pair-breaking excitation at 45cm$^{-1}$ ($2Δ=5.6$meV) in the $XY$($B_{2g}$) scattering geometry, consistent with twice of the superconducting gap energy (3 meV) revealed by ARPES on the hol

Peter Clifford, David Stirzaker

We consider random processes that are history-dependent, in the sense that the distribution of the next step of the process at any time depends upon the entire past history of the process. In general, therefore, the Markov property cannot hold, but it is shown that a suitable sub-class of such processes can be seen as directed Markov processes, subordinate t

Tine Colman, Romain Teyssier

Classical theories for the stellar initial mass function (IMF) predict a peak mass which scales with the properties of the molecular cloud. In this work, we explore a new theory proposed by Lee & Hennebelle (2018). The idea is that the tidal field around first Larson cores prevents the formation of other collapsing clumps within a certain radius. The protost

Renjiao Yi, Ping Tan, Stephen Lin

We present an unsupervised approach for factorizing object appearance into highlight, shading, and albedo layers, trained by multi-view real images. To do so, we construct a multi-view dataset by collecting numerous customer product photos online, which exhibit large illumination variations that make them suitable for training of reflectance separation and c

M. Sumetsky

The optical microresonators reviewed in this paper are called bottle microresonators because their profile often resembles an elongated spheroid or a microscopic bottle. These resonators are commonly fabricated from an optical fiber by variation of its radius. Generally, variation of the bottle microresonator (BMR) radius along the fiber axis can be quite co

Hao-Yun Chen, Li-Huang Tsai, Shih-Chieh Chang, Jia-Yu Pan

Label hierarchies widely exist in many vision-related problems, ranging from explicit label hierarchies existed in image classification to latent label hierarchies existed in semantic segmentation. Nevertheless, state-of-the-art methods often deploy cross-entropy loss that implicitly assumes class labels to be exclusive and thus independence from each other.

Nurettin Turan, Wolfgang Utschick

We present a neural network based predictor which is derived by starting from the linear minimum mean squared error (LMMSE) predictor and by further making two key assumptions. With these assumptions, we first derive a weighted sum of LMMSE predictors which is motivated by the structure of the optimal MMSE predictor. This predictor provides an initialization

Suping Zhou, Jia Jia, Yufeng Yin, Xiang Li

Teaching style plays an influential role in helping students to achieve academic success. In this paper, we explore a new problem of effectively understanding teachers&#39; teaching styles. Specifically, we study 1) how to quantitatively characterize various teachers&#39; teaching styles for various teachers and 2) how to model the subtle relationship betwee

Xiaoze Jiang, Jing Yu, Zengchang Qin, Yingying Zhuang

Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue involves multiple questions which cover a broad range of visual content that could be related to any objects, relationships or semantics. The key challenge in Visual Dialogue task is thus to learn a more comprehensive and semantic-rich imag

Chi Chang, Thomas Jaki, Muhammad Saad Sadiq, Alena A. Kuhlemeier

One size fits all approaches to medicine have become a thing of the past as the understanding of individual differences grows. The paper introduces a test for the presence of heterogeneity in treatment effects in a clinical trial. Heterogeneity is assessed on the basis of the predicted individual treatment effects (PITE) framework and a permutation test is u

Peter L. Bartlett, Jonathan Baxter

In this paper, we derive a new model of synaptic plasticity, based on recent algorithms for reinforcement learning (in which an agent attempts to learn appropriate actions to maximize its long-term average reward). We show that these direct reinforcement learning algorithms also give locally optimal performance for the problem of reinforcement learning with

Youngwoon Lee, Edward S. Hu, Zhengyu Yang, Alex Yin

The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and accelerating the automation of complex manipulation tasks. The environment is designed to advance reinforcement learning from simple toy tasks to complex tasks requiring both long-term planning and sophisticated low-level control. Our environment supports over 80 different

Krisztian Buza

A common assumption about neural networks is that they can learn an appropriate internal representations on their own, see e.g. end-to-end learning. In this work we challenge this assumption. We consider two simple tasks and show that the state-of-the-art training algorithm fails, although the model itself is able to represent an appropriate solution. We wil

S. Wang, R. H. Xu, W. Y. Li, X. Liu

We study double ionization (DI) dynamics of vibrating HeH$^+$ versus its isotopic variant HeT$^+$ in strong laser fields numerically. Our simulations show that for both cases, these two electrons in DI prefer to release together along the H(T) side. At the same time, however, the single ionization (SI) is preferred when the first electron escapes along the H

Jeppe Christiansen, Joakim Vester-Petersen, Søren Roesgaard, Søren H. Møller

Upconversion of sub-band-gap photons constitutes a promising way for improving the efficiency of silicon-based solar cells beyond the Shockley-Queisser limit. 1500 to 980 nm upconversion by trivalent erbium ions is well-suited for this purpose, but the small absorption cross section hinders real-world applications. We employ tailored gold nanostructures to v

D. Fargion, P. G. De Sanctis Lucentini, M. Yu. Khlopov, P. Oliva

Last two years high energy neutrino data are studied. The two recent tau neutrino double bang candidate are discussed within their detectability, noise and expected rate. The neutrino flavor distribution mainly favoring equal electron and muon presence, is reminded. The angular distribution of highest muon neutrino tracks is analyzed. Their horizontal strong

Yangyang Cao, Mohammad A. Ghazizadeh, Philippe G. LeFloch

We study the cosmological Burgers model, as we call it, which is a nonlinear hyperbolic balance law (in one and two spatial variables) posed on an expanding or contracting background. We design a finite volume scheme that is fourth-order in time and second-order in space, and allows us to compute weak solutions containing shock waves. Our main contribution i

Amanda Welch

We classify cocovers and covers of a given element of the double affine Weyl semigroup W with respect to the Bruhat order, specifically when W is associated to a finite root system that is irreducible and simply laced. We show two approaches: one extending the work of Lam and Shimozono, and its strengthening by Milicevic, where cocovers are characterized in

Ali Çivril

The classical algorithm of Agrawal, Klein and Ravi [SIAM J. Comput., 24 (1995), pp. 440-456], stated in the setting of the primal-dual schema by Goemans and Williamson [SIAM J. Comput., 24 (1995), pp. 296-317] uses the undirected cut relaxation for the Steiner forest problem. Its approximation ratio is $2-\frac{1}{k}$, where $k$ is the number of terminal pai

Sara M. Clifton, Rachel J. Whitaker, Zoi Rapti

The canonical bacteriophage is obligately lytic: the virus infects a bacterium and hijacks cell functions to produce large numbers of new viruses which burst from the cell. These viruses are well-studied, but there exist a wide range of coexisting virus lifestyles that are less understood. Temperate viruses exhibit both a lytic cycle and a latent (lysogenic)

Leen Alawieh, Jonathan Goodman, John B. Bell

A new algorithm is developed to tackle the issue of sampling non-Gaussian model parameter posterior probability distributions that arise from solutions to Bayesian inverse problems. The algorithm aims to mitigate some of the hurdles faced by traditional Markov Chain Monte Carlo (MCMC) samplers, through constructing proposal probability densities that are bot

Alexandr Savinov

We describe a new logical data model, called the concept-oriented model (COM). It uses mathematical functions as first-class constructs for data representation and data processing as opposed to using exclusively sets in conventional set-oriented models. Functions and function composition are used as primary semantic units for describing data connectivity ins

Phu X. V. Nguyen, Tham T. T. Hong, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen

Student&#39;s feedback is an important source of collecting students&#39; opinions to improve the quality of training activities. Implementing sentiment analysis into student feedback data, we can determine sentiments polarities which express all problems in the institution since changes necessary will be applied to improve the quality of teaching and learni

Alexander Pfeiffer, Robert M. Reeve, Kelvin Elphick, Atsufumi Hirohata

Spin transport phenomena underpin an extensive range of spintronic effects. In particular spin transport across interfaces occurs in most device concepts, but is so far poorly understood. As interface properties strongly impact spin transport, one needs to characterize and correlate them to the fabrication method. Here we investigate pure spin current transp

Marco Cantarini, Alessandro Gambini, Alessandro Zaccagnini

We consider weighted averages of the number of representations of an even integer as a sum of two prime numbers, where each summand lies in a given arithmetic progression modulo a common integer $q$. Our result is uniform in a suitable range for $q$.

Onur Beker, Congyu Liao, Jaejin Cho, Zijing Zhang

We propose a convolutional neural network (CNN) approach that works synergistically with physics-based reconstruction methods to reduce artifacts in accelerated MRI. Given reconstructed coil k-spaces, our network predicts a k-space correction term for each coil. This is done by matching the difference between the acquired autocalibration lines and their erro

Haiyang Si, Zhiqiang Zhang, Feifan Lv, Gang Yu

Real-time semantic segmentation plays a significant role in industry applications, such as autonomous driving, robotics and so on. It is a challenging task as both efficiency and performance need to be considered simultaneously. To address such a complex task, this paper proposes an efficient CNN called Multiply Spatial Fusion Network (MSFNet) to achieve fas

Jacob M. Gold, Jeremy L. England

We consider a glassy system of interacting spins driven by continual switching amongst a finite set of nonuniform external fields. We find that the system evolves over time towards configurations that minimize the work absorbed from this external drive. The configurations which achieve this are specific to the details of the external fields used to drive the

Tatiana Latychevskaia

This paper provides a tutorial of iterative phase retrieval algorithms based on the Gerchberg-Saxton (GS) algorithm applied in digital holography. In addition, a novel GS-based algorithm that allows reconstruction of 3D samples is demonstrated. The GS-based algorithms recover complex-valued wavefront by wavefront back-and forth propagation between two planes

Filippo Fabiani, Sergio Grammatico

We present semi-decentralized and distributed algorithms, designed via a preconditioned forward-backward operator splitting, for solving large-scale, decomposable semidefinite programs (SDPs). We exploit a chordal aggregate sparsity pattern assumption on the original SDP to obtain a set of mutually coupled SDPs defined on positive semidefinite (PSD) cones of

Lucky Galvez, Jon-Lark Kim

Practically good error-correcting codes should have good parameters and efficient decoding algorithms. Some algebraically defined good codes such as cyclic codes, Reed-Solomon codes, and Reed-Muller codes have nice decoding algorithms. However, many optimal linear codes do not have an efficient decoding algorithm except for the general syndrome decoding whic

Hideyuki Mizuno, Masanari Shimada, Atsushi Ikeda

Understanding the vibrational and thermal properties of amorphous solids is one of the most discussed and long-standing issues in condensed matter physics. Recent works have made significant steps towards understanding harmonic vibrational states. In particular, it has been established that quasi-localized vibrational modes emerge in addition to phonon-like

Robert Griffiths, Kais Hamza

For a given set of random variables $X_1,\ldots,X_d$ we seek as large a family as possible of random variables $Y_1,\ldots,Y_d$ such that the marginal laws and the laws of the sums match: $Y_i\,{\buildrel d \over =}\,X_i$ and $\sum_iY_i\,{\buildrel d \over =}\,\sum_iX_i$. Under the assumption that $X_1,\ldots,X_d$ are independent and belong to any of the Mei

Abhishek Banerjee, Ananthesh Sundaresh, R. Ganesan, P. S. Anil Kumar

The combination of superconductivity and spin-momentum locking at the interface between an s-wave superconductor and a three-dimensional topological insulator (3D-TI) is predicted to generate exotic p-wave topological superconducting phases that can host Majorana fermions. However, large bulk conductivities of previously investigated 3D-TI samples and Fermi

Jicheng Sun, Xinliang Gao, Yangguang Ke, Quanming Lu

The expansion of hot electrons in flaring magnetic loops is crucial to understanding the dynamics of solar flares. In this paper we investigate, for the first time, the transport of hot electrons in a magnetic mirror field based on a 1-D particle-in-cell (PIC) simulation. The hot electrons with small pitch angle transport into the cold plasma, which leads to

Diarmuid Crowley, Xing Gu, Christian Haesemeyer

We establish upper bounds of the indices of topological Brauer classes over a closed orientable 8-manifolds. In particular, we verify the Topological Period-Index Conjecture (TPIC) for topological Brauer classes over closed orientable 8-manifolds of order not congruent to 2 mod 4. In addition, we provide a counter-example which shows that the TPIC fails in g

Aman Apte, Aritra Bandyopadhyay, K Akhilesh Shenoy, Jason Peter Andrews

Google&#39;s Vision API analyses images and provides a variety of output predictions, one such type is context-based labelling. In this paper, it is shown that adversarial examples that cause incorrect label prediction and spoofing can be generated by rotating the images. Due to the black-boxed nature of the API, a modular context-based pre-processing pipeli

Manish Agnihotri, Adiyta Rathod, Aditya Jajodia, Chethan Sharma

In today&#39;s world of growing number of songs, the need of finding apposite music content according to a user&#39;s interest is crucial. Furthermore, recommendations suitable to one user may be irrelevant to another. In this paper, we propose a recommendation system for users with common-artist music listening patterns. We use &#34;random walk with restart

Quanzhi Li, Qiong Zhang, Luo Si, Yingchi Liu

Social media platforms have been used for information and news gathering, and they are very valuable in many applications. However, they also lead to the spreading of rumors and fake news. Many efforts have been taken to detect and debunk rumors on social media by analyzing their content and social context using machine learning techniques. This paper gives

T. N. Dao, L. Fritz, M. Krause, M. Muhlleitner

In this paper we compute the electroweak corrections to the charged Higgs boson decay into a $W$ boson and a neutral Higgs boson in the CP-conserving NMSSM. We calculate the process in a general $R_ξ$ gauge and investigate the dependence of the loop-corrected decay width on the gauge parameter $ξ$. The gauge dependence arises from the mixing of different loo

H. Garcilazo, A. Valcarce, J. Vijande

We study the coupled $ΛΛnn-Ξ^- pnn$ system to check whether the inclusion of channel coupling is able to bind the $ΛΛnn$ system. We use a separable potential three-body model of the coupled $ΛΛnn - Ξ^- pnn$ system as well as a variational four-body calculation with realistic interactions. Our results exclude the possibility of a $ΛΛnn$ bound state by a large

Mehyar Najla, Zdenek Becvar, Pavel Mach, David Gesbert

Device-to-device (D2D) communication, which enables a direct connection between users while bypassing the cellular channels to base stations (BSs), is a promising way to offload the traffic from conventional cellular networks. In D2D communication, one recurring problem is that, in order to optimally allocate resources across D2D and cellular users, the know

Giuseppe Di Giulio, Erik Tonni

We study the continuum limit of the entanglement hamiltonians of a block of consecutive sites in massless harmonic chains. This block is either in the chain on the infinite line or at the beginning of a chain on the semi-infinite line with Dirichlet boundary conditions imposed at its origin. The entanglement hamiltonians of the interval predicted by Conforma

Behnam Khaleghi, Sahand Salamat, Mohsen Imani, Tajana Rosing

Cutting edge FPGAs are not energy efficient as conventionally presumed to be, and therefore, aggressive power-saving techniques have become imperative. The clock rate of an FPGA-mapped design is set based on worst-case conditions to ensure reliable operation under all circumstances. This usually leaves a considerable timing margin that can be exploited to re

Gianluca Passarelli, Ka-Wa Yip, Daniel A. Lidar, Hidetoshi Nishimori

In reverse quantum annealing, the initial state is an eigenstate of the final problem Hamiltonian and the transverse field is cycled rather than strictly decreased as in standard (forward) quantum annealing. We present a numerical study of the reverse quantum annealing protocol applied to the $p$-spin model ($p=3$), including pausing, in an open system setti

Qianwei Zhou, Chen Zhou, Haigen Hu, Yuhang Chen

Single image inverse problem is a notoriously challenging ill-posed problem that aims to restore the original image from one of its corrupted versions. Recently, this field has been immensely influenced by the emergence of deep-learning techniques. Deep Image Prior (DIP) offers a new approach that forces the recovered image to be synthesized from a given dee

Fandong Meng, Jinchao Zhang, Yang Liu, Jie Zhou

Recurrent neural networks (RNNs) have been widely used to deal with sequence learning problems. The input-dependent transition function, which folds new observations into hidden states to sequentially construct fixed-length representations of arbitrary-length sequences, plays a critical role in RNNs. Based on single space composition, transition functions in

Kunjin Chen, Yu Zhang, Qin Wang, Jun Hu

Non-intrusive load monitoring addresses the challenging task of decomposing the aggregate signal of a household&#39;s electricity consumption into appliance-level data without installing dedicated meters. By detecting load malfunction and recommending energy reduction programs, cost-effective non-intrusive load monitoring provides intelligent demand-side man

Nour El Houda Lamsakhar, Mohammed Hadouchi, Mohammed Zriouil, Abderrazzak Assani

A novel alluaudite type vanadate has been successfully synthesized in its single crystal and polycrystalline forms. Its crystal structure was determined by means of X ray diffraction measurements. This new vanadate crystallizes in monoclinic system. The crystal structure of this vanadate displays an open transition metals based framework enclosing two kind o

Fanqin Meng, Xiaojing Shen, Zhiguo Wang, Haiqi Liu

In this paper, the multiple-source ellipsoidal localization problem based on acoustic energy measurements is investigated via set-membership estimation theory. When the probability density function of measurement noise is unknown-but-bounded, multiple-source localization is a difficult problem since not only the acoustic energy measurements are complicated n

Mohammed Hadouchi, Abderrazzak Assani, Mohamed Saadi, Abdelilah Lahmar

The magnetic properties of a novel cobalt-based hydrogen vanadate, Co13.5(OH)6(H0.5VO3.5)2(VO4)6, are reported. This new magnetic material was synthesized in single-crystal form using a conventional hydrothermal method. Its crystal structure was determined from single-crystal X-ray diffraction data and was also characterized by scanning electron microscopy.

Yiyao Shi, Jian Wang, Xiangyang Xue

In this paper, a learning-free color constancy algorithm called the Patch-wise Bright Pixels (PBP) is proposed. In this algorithm, an input image is first downsampled and then cut equally into a few patches. After that, according to the modified brightness of each patch, a proper fraction of brightest pixels in the patch is selected. Finally, Gray World (GW)

Mohammed Hadouchi, Abderrazzak Assani, Mohamed Saadi, Yakov Kopelevich

Single crystals of a new silver and-cobalt based vanadate AgCo2V3O10 were grown from a melted mixture. The crystal structure determination reveals that this new vanadate crystallizes in triclinic system with space group P-1. The structure of the titled compound is constructed from CoO6octahedra and VO4 tetrahedra sharing edges and vertices leading to an open

Chencheng Cai, Rong Chen

Many high dimensional optimization problems can be reformulated into a problem of finding theoptimal state path under an equivalent state space model setting. In this article, we present a general emulation strategy for developing a state space model whose likelihood function (or posterior distribution) shares the same general landscape as the objective func

Ruoyu Guo, Cheng Cui, Yuning Du, Xianglong Meng

We present an object detection framework based on PaddlePaddle. We put all the strategies together (multi-scale training, FPN, Cascade, Dcnv2, Non-local, libra loss) based on ResNet200-vd backbone. Our model score on public leaderboard comes to 0.6269 with single scale test. We proposed a new voting method called top-k voting-nms, based on the SoftNMS detect