January 2019 arXiv papers — page 24

Xinlun Cheng, Chao Liu, Shude Mao, Wenyuan Cui

With about 12 000 OB type stars selected from the LAMOST and Gaia survey, we study their 3 dimensional velocity distribution over the range of galactocentric radius from 6 to 15 kpc in the Galactic disk plane. A clear ripple pattern in the radial velocity ($V_R$) map is shown. The median $V_R$ reaches $-8$ km s$^{-1}$ at $R\sim9$ kpc, then increases to $\sim

Zhou-Run Zhu, Sheng-Qin Feng, Ya-Fei Shi, Yang Zhong

We systematically study holographic effects on the magnetic field dependence of the drag force, diffusion coefficient, jet quenching parameter of heavy quarks and the shooting string energy loss of light quarks in the RHIC and LHC energy regions by using the AdS/CFT correspondence in this paper. This study is motivated by the phenomena of strong magnetic fie

Muneya Matsui

Asymptotics of maximum likelihood estimation for $\alpha$-stable law are analytically investigated with a continuous parameterization. The consistency and asymptotic normality are shown on the interior of the whole parameter space. Although these asymptotics have been provided with Zolotarev's $(B)$ parameterization, there are several gaps between. Especiall

R. Carrera, A. Bragaglia, T. Cantat-Gaudin, A. Vallenari

Context: Open clusters are ideal laboratories to investigate a variety of astrophysical topics, from the properties of the Galactic disk to stellar evolutionary models. Knowing their metallicity and possibly detailed chemical abundances is therefore important. However, the number of systems with chemical abundances determined from high resolution spectroscop

Antonio Lei, Bharathwaj Palvannan

The purpose of this paper is to build on results in {\it{higher codimension Iwasawa theory}}. The setting of our results involves Galois representations arising as cyclotomic twist deformations associated to (i) the tensor product of two cuspidal Hida families $F$ and $G$, and (ii) the tensor product of three cuspidal Hida families $F$, $G$ and $H$. On the a

P. Raviteja, Khoa T. Phan, Yi Hong, Emanuele Viterbo

Orthogonal time frequency space (OTFS) modulation was proposed to tackle the destructive Doppler effects in wireless communications, with potential applications to many other areas. In this paper, we investigate its application to radar systems, and propose a novel efficient OTFS-based matched filter algorithm for target range and velocity estimation. The pr

Saviz Saei, Mohsen Mohammadi, Mahsa Fekriseri, Kouroush Jenab

Flexibility in shape and scale of Burr XII distribution can make close approximation of numerous well-known probability density functions. Due to these capabilities, the usages of Burr XII distribution are applied in risk analysis, lifetime data analysis and process capability estimation. In this paper the Cross-Entropy (CE) method is further developed in te

Adam Lipowski, Antonio Luis Ferreira, Dorota Lipowska, Manuel A. Barroso

We show that an intricate relation of cluster properties and optimal bipartitions, which takes place in undirected random graphs, extends to directed and mixed random graphs. In particular, the satisfability threshold coincides with the relative size of the giant OUT component reaching~{1/2}. Moreover, when counting undirected links as two directed ones, the

Houssam Abdul-Rahman, Marius Lemm, Angelo Lucia, Bruno Nachtergaele

The AKLT spin chain is the prototypical example of a frustration-free quantum spin system with a spectral gap above its ground state. Affleck, Kennedy, Lieb, and Tasaki also conjectured that the two-dimensional version of their model on the hexagonal lattice exhibits a spectral gap. In this paper, we introduce a family of variants of the two-dimensional AKLT

Lingpeng Kong, Gabor Melis, Wang Ling, Lei Yu

We present a new theoretical perspective of data noising in recurrent neural network language models (Xie et al., 2017). We show that each variant of data noising is an instance of Bayesian recurrent neural networks with a particular variational distribution (i.e., a mixture of Gaussians whose weights depend on statistics derived from the corpus such as the

Iosif Pinelis

Oftentimes, Stokes' theorem is derived by using, more or less explicitly, the invariance of the curl of the vector field with respect to translations and rotations. However, this invariance -- which is oftentimes described as the curl being a "physical" vector -- does not seem quite easy to verify, especially for undergraduate students. An even bigger proble

Jing Zhang

Anomaly detecting as an important technical in cloud computing is applied to support smooth running of the cloud platform. Traditional detecting methods based on statistic, analysis, etc. lead to the high false-alarm rate due to non-adaptive and sensitive parameters setting. We presented an online model for anomaly detecting using machine learning theory. Ho

Thomas Schmickl, Martin Stefanec

This article describes the conversion of the two-dimensional Primordial Particle System into a threedimensional model that exhibits comparable features. We present the transformed model here in the form of a pseudocode implementation and detail the modifications required for this conversion.

Najwa Kouka, Raja Fdhila, Adel M. Alimi

This paper investigates a new hybridization of multi-objective particle swarm optimization (MOPSO) and cooperative agents (MOPSO-CA) to handle the problem of stagnation encounters in MOPSO, which leads solutions to trap in local optima. The proposed approach involves a new distribution strategy based on the idea of having a set of a sub-population, each of w

Julien Roussel, Gabriel Stoltz

We propose a general variance reduction strategy for diffusion processes. Our approach does not require the knowledge of the measure that is sampled, which may indeed be unknown as for nonequilibrium dynamics in statistical physics. We show by a perturbative argument that a control variate computed for a simplified version of the model can provide an efficie

Saman Jahani, Li-Ping Yang, Adrian Buganza Tepole, Joseph C. Bardin

Superconducting nanowire single-photon detectors have emerged as a promising technology for quantum metrology from the mid-infrared to ultra-violet frequencies. Despite the recent experimental successes, a predictive model to describe the detection event in these detectors is needed to optimize the detection metrics. Here, we propose a probabilistic criterio

Soheila Sadeghiram, Hui Ma, Gang Chen

Web Service Composition (WSC) is a particularly promising application of Web services, where multiple individual services with specific functionalities are composed to accomplish a more complex task, which must fulfil functional requirements and optimise Quality of Service (QoS) attributes, simultaneously. Additionally, large quantities of data, produced by

Sangkug Lym, Esha Choukse, Siavash Zangeneh, Wei Wen

State-of-the-art convolutional neural networks (CNNs) used in vision applications have large models with numerous weights. Training these models is very compute- and memory-resource intensive. Much research has been done on pruning or compressing these models to reduce the cost of inference, but little work has addressed the costs of training. We focus preci

Andrea Mantile, Andrea Posilicano

We provide a general scheme, in the combined frameworks of Mathematical Scattering Theory and Factorization Method, for inverse scattering for the couple of self-adjoint operators $(\widetilde\Delta,\Delta)$, where $\Delta$ is the free Laplacian in $L^{2}({\mathbb R}^{3})$ and $\widetilde\Delta$ is one of its singular perturbations, i.e., such that the set $

Sara Mazzonetto, Diyora Salimova

In this paper we propose an all-in-one statement which includes existence, uniqueness, regularity, and numerical approximations of mild solutions for a class of stochastic partial differential equations (SPDEs) with non-globally monotone nonlinearities. The proof of this result exploits the properties of an existent fully explicit space-time discrete approxi

Rony Gelman

Deep learning has been successfully applied to a variety of image classification tasks. There has been keen interest to apply deep learning in the medical domain, particularly specialties that heavily utilize imaging, such as ophthalmology. One issue that may hinder application of deep learning to the medical domain is the vast amount of data necessary to tr

Abby Stylianou, Hong Xuan, Maya Shende, Jonathan Brandt

Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have been trafficked, and where their traffickers might move them or others in the future. Recognizing the hotel from images is challenging because of low image quality, uncommon camera

Wesley Taylor, Faisal Z. Qureshi

We present a method for creating video summaries in real-time on commodity hardware. Real-time here refers to the fact that the time required for video summarization is less than the duration of the input video. First, low-level features are use to discard undesirable frames. Next, video is divided into segments, and segment-level features are extracted for

Alan T. Sherman, Linda Oliva, Enis Golaszewski, Dhananjay Phatak

For two days in February 2018, 17 cybersecurity educators and professionals from government and industry met in a "hackathon" to refine existing draft multiple-choice test items, and to create new ones, for a Cybersecurity Concept Inventory (CCI) and Cybersecurity Curriculum Assessment (CCA) being developed as part of the Cybersecurity Assessment Tools (CATS

Faraz Dadgostari

This thesis introduces stochastic generalized routing problem model and proposes exact and heuristic algorithms to solve it efficiently, in a wide range of problem sizes. At first, the classic routing problem with its common variations in deterministic form is reviewed. Its mathematical models are demonstrated and exact and heuristic algorithms are described

Liqun Lu, Yanfeng Ouyang

Opposition to vaccination has long been a non-negligible public health phenomenon resulted from people's varied perceptions toward vaccination (e.g., vaccine-phobia). This paper investigates the voluntary vaccination behavior of a heterogeneous population during an epidemic outbreak, where each individual makes its own vaccination decision to minimize its ex

Patrick J. Fox, Julia Gehrlein, Seyda Ipek

We study the LHC constraints on an $R$-symmetric SUSY model, where the neutrino masses are generated through higher dimensional operators involving the pseudo-Dirac bino, named bi$\nu$o. We consider a particle spectrum where the squarks are heavier than the lightest neutralino, which is a pure bi$\nu$o. The bi$\nu$o is produced through squark decays and it s

Charles B. Delahunt, Courosh Mehanian, J. Nathan Kutz

Softmax is a standard final layer used in Neural Nets (NNs) to summarize information encoded in the trained NN and return a prediction. However, Softmax leverages only a subset of the class-specific structure encoded in the trained model and ignores potentially valuable information: During training, models encode an array $D$ of class response distributions,

J. Nsofini, D. Sarenac, D. G. Cory, D. A. Pushin

A zero-area four-blade perfect crystal neutron interferometer (NI) possess a decoherence-free subspace (DFS) for low-frequency mechanical vibrations and thus is easier to site. %has the potential to broaden the application of crystal-based neutron interferometry to a higher number of neutron sources. However, unlike the standard three-blade Mach-Zehnder NI t

Mohamed Nassar

Privacy-preserving machine learning is learning from sensitive datasets that are typically distributed across multiple data owners. Private machine learning is a remarkable challenge in a large number of realistic scenarios where no trusted third party can play the role of a mediator. The strong decentralization aspect of these scenarios requires tools from

Stefan Milz, Martin Simon, Kai Fischer, Maximillian Pöpperl

We present the first approach for 3D point-cloud to image translation based on conditional Generative Adversarial Networks (cGAN). The model handles multi-modal information sources from different domains, i.e. raw point-sets and images. The generator is capable of processing three conditions, whereas the point-cloud is encoded as raw point-set and camera pro

Samuel M. Corson, Ilya Kazachkov

A group $G$ is called automatically continuous if any homomorphism from a completely metrizable or locally compact Hausdorff group to $G$ has open kernel. In this paper, we study preservation of automatic continuity under group-theoretic constructions, focusing mainly on groups of size less than continuum. In particular, we consider group extensions and grap

Peter Frankl, Andrey Kupavskii

A family $\mathcal F\subset {[n]\choose k}$ is $U(s,q)$ of for any $F_1,\ldots, F_s\in \mathcal F$ we have $|F_1\cup\ldots\cup F_s|\le q$. This notion generalizes the property of a family to be $t$-intersecting and to have matching number smaller than $s$. In this paper, we find the maximum $|\mathcal F|$ for $\mathcal F$ that are $U(s,q)$, provided $n>C(s,q

Tianyu Wang, Weicheng Ye, Dawei Geng, Cynthia Rudin

Stochastic Lipschitz bandit algorithms balance exploration and exploitation, and have been used for a variety of important task domains. In this paper, we present a framework for Lipschitz bandit methods that adaptively learns partitions of context- and arm-space. Due to this flexibility, the algorithm is able to efficiently optimize rewards and minimize reg

Andrei Novikov, Zohreh Eskandarian, Zamira Kholmatova

In this article we propose a conception of mixed limits of functional spaces as the case, when the upper limit (projective limit of inductive limits) and the lower limit (inductive limit of projective limits) coincide as topological spaces, which are generalization of inductive and projective limits of functional spaces. We show a cases where these mixed lim

Filip P. Adamus

We consider a long-wave transversely isotropic (TI) medium equivalent to a series of finely parallel-layered isotropic layers, obtained using the \citet{Backus} average. In such a TI equivalent medium, we verify the \citet{Berrymanetal} method of indicating fluids and the author's method \citep{Adamus}, using anisotropy parameter $\varphi$. Both methods are

A. Yu. Okulov

Spatial chaos as a phenomenon of ultimate complexity requires the efficient numerical algorithms. For this purpose iterative low-dimensional maps have demonstrated high efficiency. Natural generalization of Feigenbaum and Ikeda maps may include convolution integrals with kernel in a form of Green function of a relevant linear physical system. It is shown tha

Damiano Anselmi

Under certain assumptions, it is possible to make sense of higher derivative theories by quantizing the unwanted degrees of freedom as fakeons, which are later projected away. Then the true classical limit is obtained by classicizing the quantum theory. Since quantum field theory is formulated perturbatively, the classicization is also perturbative. After de

Nongnuch Artrith, Alexander Urban, Yan Wang, Gerbrand Ceder

Nanostructured Si is the most promising high-capacity anode material to substantially increase the energy density of Li-ion batteries. Among the remaining challenges is its low rate capability as compared to conventional materials. To understand better what controls the diffusion of Li in the amorphous Li-Si alloy, we use a novel machine-learning potential t

Ikram Fatima Zohra Bensaid, Souheyb Dehimi, Bent Fuglede, Mohammed Hichem Mortad

In this paper, we show a new and classic version of the celebrated Fuglede Theorem in an unbounded setting. A related counterexample is equally presented. In the second strand of the paper, we give a pair of a closed and self-adjoint (unbounded) operators which is not intertwined by any (bounded or closed) operator except the zero operator.

Michal Uricar, David Hurych, Pavel Krizek, Senthil Yogamani

Autonomous driving is getting a lot of attention in the last decade and will be the hot topic at least until the first successful certification of a car with Level 5 autonomy. There are many public datasets in the academic community. However, they are far away from what a robust industrial production system needs. There is a large gap between academic and in

Konstantin Mishchenko, Eduard Gorbunov, Martin Takáč, Peter Richtárik

Training large machine learning models requires a distributed computing approach, with communication of the model updates being the bottleneck. For this reason, several methods based on the compression (e.g., sparsification and/or quantization) of updates were recently proposed, including QSGD (Alistarh et al., 2017), TernGrad (Wen et al., 2017), SignSGD (Be

Pavao Mardesic, Dmitry Novikov, Laura Ortiz-Bobadilla, Jessie Pontigo-Herrera

We consider foliations given by deformations $dF+\epsilon\omega$ of exact forms $dF$ in $\mathbb{C}^2$ in a neighborhood of a family of cycles $\gamma(t)\subset F^{-1}(t)$. In 1996 Francoise gave an algorithm for calculating the first nonzero term of the displacement function $\Delta$ along $\gamma$ of such deformations. This algorithm recalls the well-known

Sankarshan Sahu

Here a special case of perturbation in quantum harmonic oscillator is studied. Here we assume the perturbed potential to be a Harmonic Oscillator that has been shifted in the position space.We construct the new creation and annihilation operators for the new Hamiltonian to find out its energy eigenstates. What is interesting about the solution of this system

Wei Ma, Zhen, Qian

Dynamic origin-destination (OD) demand is central to transportation system modeling and analysis. The dynamic OD demand estimation problem (DODE) has been studied for decades, most of which solve the DODE problem on a typical day or several typical hours. There is a lack of methods that estimate high-resolution dynamic OD demand for a sequence of many consec

Vineesha Srivastava, Ankita Niranjan, Rejish Nath

We study the population dynamics in a two-atom setup in which each atom is driven independently by different light fields, but coupling the same Rydberg state. In particular, we look at how an offset in the Rabi frequencies between two atoms influences the dynamics. We find novel features such as amplifying the Rabi frequency of one atom, together with stron

Eddy Maddalena, Luis-Daniel Ibáñez, Elena Simperl

The use of volunteers has emerged as low-cost alternative to generate accurate geographical information, an approach known as Volunteered Geographic Information (VGI). However, VGI is limited by the number and availability of volunteers in the area to be mapped, hindering scalability for large areas and making difficult to map within a time-frame. Fortunatel

Eytan Kats, Jacob Goldberger, Hayit Greenspan

This paper explores the use of a soft ground-truth mask ("soft mask'') to train a Fully Convolutional Neural Network (FCNN) for segmentation of Multiple Sclerosis (MS) lesions. Detection and segmentation of MS lesions is a complex task largely due to the extreme unbalanced data, with very small number of lesion pixels that can be used for training. Utilizing

Michael P. Frank

We review the physical foundations of Landauer's Principle, which relates the loss of information from a computational process to an increase in thermodynamic entropy. Despite the long history of the Principle, its fundamental rationale and proper interpretation remain frequently misunderstood. Contrary to some misinterpretations of the Principle, the mere t

Dale E. Gary

The solar burst of 2006 December 06 reached a radio flux density of more than 1 million solar flux units (1 sfu = $10^{-22}$ W/m$^2$/Hz), as much as 10 times the previous record, and caused widespread loss of satellite tracking by GPS receivers. The event was well observed by NJITs Owens Valley Solar Array (OVSA). This work concentrates on an accurate determ

Vladislav Kibkalo

Topology of Liouville foliations for an analogue of the Kovalevskaya integrable case on Lie algebra so(4) is discussed. Fomenko-Zieschang invariants (i.e. marked molecules) were calculated for these foliations on every regular isoenergy submanifold. The corresponding stratification of the three-dimensional space of parameters of these manifolds is described

Aljosa Osep, Paul Voigtlaender, Mark Weber, Jonathon Luiten

Many high-level video understanding methods require input in the form of object proposals. Currently, such proposals are predominantly generated with the help of networks that were trained for detecting and segmenting a set of known object classes, which limits their applicability to cases where all objects of interest are represented in the training set. Th

Tetsuya Ishiwata, Takeshi Ohtsuka

In this paper, the evolution of a polygonal spiral curve by the crystalline curvature flow with a pinned center is considered with two view points, discrete model consist of an ODE system of facet lengths and a level set method. We investigate the difference of these models numerically by calculating the area of the region enclosed by these spiral curves. Th

Sascha Kissel, Christof Kuelske, Utkir A. Rozikov

We consider both Hard-Core and Soft-Core Widom-Rowlinson models with spin values $-1,0,1$ on a Cayley tree of order $k\geq 2$ and we are interested in the Gibbs measures of the models. The models depend on 3 parameters: the order $k$ of the tree, $\theta$ describing the strength of the (ferromagnetic or antiferromagnetic) interaction, and $\lambda$ describin

Jose Angel Sanchez Gomez, Victor Amaya Carvajal

A known result in random matrix theory states the following: Given a random Wigner matrix $X$ which belongs to the Gaussian Orthogonal Ensemble (GOE), then such matrix $X$ has an invariant distribution under orthogonal conjugations. The goal of this work is to prove the converse, that is, if $X$ is a symmetric random matrix such that it is invariant under or

Xueying Zhang, Nicolas Vernier, Laurent Vila, Shaohua Yan1

CoFeB is a very soft material, in which Domain Wall (DW) can be moved easily under a weak magnetic field. However, it is very difficult to move DWs in Ta\CoFeB\MgO nanowires with interfacial perpendicular magnetic anisotropy through a spin-polarized current, and this limits the perspectives of racetrack memory driven by the current-in-plane mechanism. To inv

N. Gill, L. Pyber, E. Szabó

We prove that if $G$ is a finite simple group of Lie type and $S_1,\dots, S_k$ are subsets of $G$ satisfying $\prod_{i=1}^k|S_i|\geq|G|^c$ for some $c$ depending only on the rank of $G$, then there exist elements $g_1,\dots, g_k$ such that $G=(S_1)^{g_1}\cdots (S_k)^{g_k}$. This theorem generalizes an earlier theorem of the authors and Short. We also propose

Sanne ter Horst, Miek Messerschmidt, Andre C. M. Ran, Mark Roelands

In 1994 H. Bart and V.\'{E}. Tsekanovskii posed the question whether the Banach space operator relations matricial coupling (MC), equivalence after extension (EAE) and Schur coupling (SC) coincide, leaving only the implication EAE/MC $\Rightarrow$ SC open. Despite several affirmative results, in this paper we show that the answer in general is no. This follo

Huijie Tian, Srinivas Rangarajan

In this paper, we apply multi-task Gaussian Process (MT-GP) to show that the adsorption energy of small adsorbates on transition metal surfaces can be modeled to a high level of fidelity using data from multiple sources, taking advantage of the relatively abundant ''low fidelity" data (such as from density functional theory computations) and small amounts of

Nicola Bastianello, Ruggero Carli, Luca Schenato, Marco Todescato

In this work we focus on the problem of minimizing the sum of convex cost functions in a distributed fashion over a peer-to-peer network. In particular, we are interested in the case in which communications between nodes are prone to failures and the agents are not synchronized among themselves. We address the problem proposing a modified version of the rela

Oguzhan Bahadir, Mukut Mani Tripathi

Lightlike hypersurfaces of a statistical manifold are studied. It is shown that a lightlike hypersurface of a statistical manifold is not a statistical manifold with respect to the induced connections, but the screen distribution has a canonical statistical structure. Some relations between induced geometric objects with respect to dual connections in a ligh

Wolfgang Lueck

We formulate and prove a version of the Segal Conjecture for infinite groups. For finite groups it reduces to the original version. The condition that G is finite is replaced in our setting by the assumption that there exists a finite model for the classifying space underline{E}G for proper actions. This assumption is satisfied for instance for word hyperbol

Tyler Roick, Dimitris Karlis, Paul D. McNicholas

There is a need for the development of models that are able to account for discreteness in data, along with its time series properties and correlation. Our focus falls on INteger-valued AutoRegressive (INAR) type models. The INAR type models can be used in conjunction with existing model-based clustering techniques to cluster discrete-valued time series data

Anoosheh Heidarzadeh, Fatemeh Kazemi, Alex Sprintson

We study the problem of single-server single-message Private Information Retrieval with Private Coded Side Information (PIR-PCSI). In this problem, there is a server that stores a database, and a user who knows a random linear combination of a random subset of messages in the database. The number of messages contributing to the user's side information is kno

Yi Shi, Tugba Erpek, Yalin E. Sagduyu, Jason H. Li

Machine learning has been widely applied in wireless communications. However, the security aspects of machine learning in wireless applications have not been well understood yet. We consider the case that a cognitive transmitter senses the spectrum and transmits on idle channels determined by a machine learning algorithm. We present an adversarial machine le

Bashir Ahmad, Ahmed Alsaedi, Mokhtar Kirane, Berikbol T. Torebek

This paper is devoted to the study of initial-boundary value problems for time-fractional analogues of Korteweg-de Vries, Benjamin-Bona-Mahony, Burgers, Rosenau, Camassa-Holm, Degasperis-Procesi, Ostrovsky and time-fractional modified Korteweg-de Vries-Burgers equations on a bounded domain. Sufficient conditions for the blowing-up of solutions in finite time

K. A. Modic, Ross D. McDonald, J. P. C. Ruff, Maja D. Bachmann

In RuCl$_3$, inelastic neutron scattering and Raman spectroscopy reveal a continuum of non-spin-wave excitations that persists to high temperature, suggesting the presence of a spin liquid state on a honeycomb lattice. In the context of the Kitaev model, magnetic fields introduce finite interactions between the elementary excitations, and thus the effects of

Rohit Girdhar, Du Tran, Lorenzo Torresani, Deva Ramanan

Video recognition models have progressed significantly over the past few years, evolving from shallow classifiers trained on hand-crafted features to deep spatiotemporal networks. However, labeled video data required to train such models have not been able to keep up with the ever-increasing depth and sophistication of these networks. In this work, we propos

Pavel Solomatin

Given a number field $K$ one associates to it the set $\Lambda_K$ of Dedekind zeta-functions of finite abelian extensions of $K$. In this short note we present a proof of the following Theorem: for any number field $K$ the set $\Lambda_K$ determines the isomorphism class of $K$. This means that if for any number field $K'$ the two sets $\Lambda_K$ and $\Lamb

Atanu Nandy, Amrita Mukherjee

The origin of non-dispersive flat band modes for a quasi-one dimensional square-kagome ladder network is explored analytically by virtue of the real space renormalization group (RSRG) technique. A section of the eigenstates is non-diffusive i.e., localized within a cluster of sub-lattice sites partly by the destructive type of quantum interference and partly

Jose Carlos Marinello, Cristiano Panazio, Taufik Abrao, Stefano Tomasin

This paper proposes a detailed investigation on the uplink (UL) performance of massive multiple-input-multiple-output (maMIMO) systems employing maximum-ratio combining at the receiver. While most papers in maMIMO literature assume orthogonal frequency-division multiplexing (OFDM), current standards like LTE employ single-carrier (SC) waveform in the UL due

Abdul Karim, Avinash Mishra, M A Hakim Newton, Abdul Sattar

Toxicity prediction of chemical compounds is a grand challenge. Lately, it achieved significant progress in accuracy but using a huge set of features, implementing a complex blackbox technique such as a deep neural network, and exploiting enormous computational resources. In this paper, we strongly argue for the models and methods that are simple in machine

Mohammad Jobayer Hossain

A high photon to electricity conversion efficiency of 47.2082% was achieved by a novel combination of In0.51Ga0.49P, GaAs, In0.24Ga0.76As and In0.19Ga0.81Sb subcell layers in a quadruple junction solar cell design. The electronic bandgap of these materials are 1.9 eV, 1.42 eV, 1.08 eV and 0.55 eV respectively. This novel III-V arrangement enables the cell to

Hanumant Singh Shekhawat

Multirate digital signal processing and model reduction applications require computation of the frequency truncated norm of a discrete-time system. This paper explains how to compute the frequency truncated norm of a discrete-time system. To this end, a much-generalized problem of integrating a transfer function of a discrete-time system given in the descrip

Y. V. Kalyuzhnyi, J. Rescic, M. Holovko, P. T. Cummings

We propose several versions of primitive models of room temperature ionic liquids (RTILs) and develop a mean spherical approximation (MSA)-type theory for their description. RTIL is modeled as a two-component mixture of hard-sphere anions and flexible linear chain cations, represented by tangentially bonded hard spheres with the charge located on one of the

Anubhav Jain, Richa Singh, Mayank Vatsa

Digitally retouching images has become a popular trend, with people posting altered images on social media and even magazines posting flawless facial images of celebrities. Further, with advancements in Generative Adversarial Networks (GANs), now changing attributes and retouching have become very easy. Such synthetic alterations have adverse effect on face

Vishnu Vardhan Chetlur, Harpreet S. Dhillon

In this paper, we present the downlink coverage and rate analysis of a cellular vehicle-to-everything (C-V2X) communication network where the locations of vehicular nodes and road side units (RSUs) are modeled as Cox processes driven by a Poisson line process (PLP) and the locations of cellular macro base stations (MBSs) are modeled as a 2D Poisson point pro

Thomas Moreau, Alexandre Gramfort

Convolutional dictionary learning (CDL) estimates shift invariant basis adapted to multidimensional data. CDL has proven useful for image denoising or inpainting, as well as for pattern discovery on multivariate signals. As estimated patterns can be positioned anywhere in signals or images, optimization techniques face the difficulty of working in extremely

Felipe Cucker, Alperen A. Ergür, Josue Tonelli-Cueto

We exhibit a condition-based analysis of the adaptive subdivision algorithm due to Plantinga and Vegter. The first complexity analysis of the PV Algorithm is due to Burr, Gao and Tsigaridas who proved a $O\big(2^{\tau d^{4}\log d}\big)$ worst-case cost bound for degree $d$ plane curves with maximum coefficient bit-size $\tau$. This exponential bound, it was

Vitaly Malyshev

Within the model of social dynamics determined by collective decisions in a stochastic environment (the ViSE model), we consider the case of a homogeneous society consisting of classically rational economic agents. We obtain analytical expressions for the optimal majority threshold as a function of the parameters of the environment, assuming that the proposa

Yang Lu, Ke Xiong, Pingyi Fan, Zhangdui Zhong

This paper investigates the age of information (AoI) for a radio frequency (RF) energy harvesting (EH) enabled network, where a sensor first scavenges energy from a wireless power station and then transmits the collected status update to a sink node. To capture the thirst for the fresh update becoming more and more urgent as time elapsing, urgency-aware AoI

Disheng Chen, Zhao Mu, Yu Zhou, Johannes Froech

Scalable quantum photonic networks require coherent excitation of quantum emitters. However, many solid-state systems can undergo a transition to a dark shelving state that inhibits the fluorescence. Here we demonstrate that a controlled gating using a weak non-resonant laser, the resonant excitation can be recovered and amplified for single germanium vacanc

Daniela N. Rim, Pablo Cremades, Pablo Kaluza

We present a simple low-cost electronic circuit that is able to show two different dynamical regimens with oscillations of voltages and with constant values of them. This device is designed as a negative feedback three-node network inspired in the genetic repressilator. The circuit's behavior is modeled by a system of differential equations which is studied

Yoichi Takeda

Spectroscopically determined Li abundances of metal-poor turn-off dwarfs are known to be nearly constant (Spite plateau), but lower than the primordial value expected from the standard cosmological model. However, abundance determination by using conventional model atmospheres may not necessarily be correct since the existence of high-temperature chromospher

Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao

Transfer learning through fine-tuning a pre-trained neural network with an extremely large dataset, such as ImageNet, can significantly accelerate training while the accuracy is frequently bottlenecked by the limited dataset size of the new target task. To solve the problem, some regularization methods, constraining the outer layer weights of the target netw

Chunming Tang, Cunsheng Ding, Maosheng Xiong

Coding theory and $t$-designs have close connections and interesting interplay. In this paper, we first introduce a class of ternary linear codes and study their parameters. We then focus on their three-weight subcodes with a special weight distribution. We determine the weight distributions of some shortened codes and punctured codes of these three-weight s

R. Peyton, V. Guarepi, G. A. Torchia

In this work, for the first time of our knowledge, we present a well-supported procedure to fabricate ridge optical waveguides onto thin films of PLZT by femtosecond laser ablation. In order to achieve smooth guiding structures to guarantee good optical performance, we have studied the ablation threshold characteristics for different kinematic conditions of

Armen Sargsyan, Ara Tonoyan, Aram Papoyan, David Sarkisyan

Dark resonances were formed via electromagnetically induced transparency for the first time involving magnetically-induced $\Delta F = \pm2$ atomic transitions of alkali metal atom, which are forbidden at zero magnetic field. The probability of these transitions undergoes rapid growth when $300 - 3000$~G magnetic field is applied, allowing formation of dark

Qing Lin

How to implement a computation task efficiently is the central problem in quantum computation science. For a quantum circuit, the multi-control unitary operations are the very important components. We present an extremely efficient approach to implement multiple multi-control unitary operations directly without any decompositions to CNOT gates and single-pho

Qianqian Tong, Xiaosa Li, Kai Lin, Zhiyong Yuan

Haptic feedback is essential to acquire immersive experience when interacting in virtual or augmented reality. Although the existing promising magnetic levitation (maglev) haptic system has advantages of none mechanical friction, its performance is limited by its navigation method, which mainly results from the challenge that it is difficult to obtain high p

Ruben J. Tomlin, Susana N. Gomes

We consider the application of feedback control strategies with point actuators to stabilise desired interface shapes. We take a multidimensional Kuramoto--Sivashinsky equation as a test case; this equation arises in the study of thin liquid films, exhibiting a wide range of dynamics in different parameter regimes, including unbounded growth and full spatiot

ChenYang Xia, YouZhe Fan, Chi-Ying Tsui

Polar codes achieve outstanding error correction performance when using successive cancellation list (SCL) decoding with cyclic redundancy check. A larger list size brings better decoding performance and is essential for practical applications such as 5G communication networks. However, the decoding speed of SCL decreases with increased list size. Adaptive S

Dongwei Ren, Wangmeng Zuo, Qinghua Hu, Pengfei Zhu

Along with the deraining performance improvement of deep networks, their structures and learning become more and more complicated and diverse, making it difficult to analyze the contribution of various network modules when developing new deraining networks. To handle this issue, this paper provides a better and simpler baseline deraining network by consideri

Nidhal Guessoum, Hannachi Zitouni, Robert Mochkovitch

Short gamma-ray bursts result from mergers of two neutron stars or from collapsars, but probably at a smaller rate. In the first case, a kilonova occurs while in the second case a Type Ic supernova is expected. } {Even if future observations of kilonovae in association with gravitational wave events provide better data, detecting a kilonova during an aftergl

Victor Makarenkov, Ido Guy, Niva Hazon, Tamar Meisels

In the process of online storytelling, individual users create and consume highly diverse content that contains a great deal of implicit beliefs and not plainly expressed narrative. It is hard to manually detect these implicit beliefs, intentions and moral foundations of the writers. We study and investigate two different tasks, each of which reflect the dif

Jurgen Mifsud, Carsten van de Bruck

After the first nearly simultaneous joint observations of gravitational-waves and electromagnetic emission produced by the coalescence of a binary neutron star system, another probe of the cosmic expansion which is independent from the cosmic distance ladder, became available. We perform a global analysis in order to constrain an interacting dark energy mode

Edith Elkind, Piotr Faliszewski, Jean-Francois Laslier, Piotr Skowron

We visualize aggregate outputs of popular multiwinner voting rules--SNTV, STV, Bloc, k-Borda, Monroe, Chamberlin--Courant, and HarmonicBorda--for elections generated according to the two-dimensional Euclidean model. We consider three applications of multiwinner voting, namely, parliamentary elections, portfolio/movie selection, and shortlisting, and use our

Ying Wen, Yaodong Yang, Rui Luo, Jun Wang

Though limited in real-world decision making, most multi-agent reinforcement learning (MARL) models assume perfectly rational agents -- a property hardly met due to individual's cognitive limitation and/or the tractability of the decision problem. In this paper, we introduce generalized recursive reasoning (GR2) as a novel framework to model agents with diff

Yuki Shimizu, Yasuhiro Yamaguchi, Masayasu Harada

We study the heavy quark spin (HQS) multiplet structure of P-wave $Q\bar{Q}qqq$-type pentaquarks treated as molecules of a heavy meson and a heavy baryon. We define the light-cloud spin (LCS) basis decomposing the meson-baryon spin wavefunction into the LCS and HQS parts. Introducing the LCS basis, we find HQS multiplets classified by the LCS; five HQS singl

Francisco Louzada, Pedro Luiz Ramos, Hayala C. C. Souza, Lawal Oyeneyin

This paper proposes a unified version of survival models that accounts for both zero-adjustment and cure proportions in various latent competing causes, useful in data where survival times may be zero or cure proportions are present. These models are particularly relevant in scenarios like childbirth duration in sub-Saharan Africa. Different competing cause