February 2019 arXiv papers — page 11

Yonghao Yuan, Xintong Wang, Canli Song, Lili Wang

We report high-resolution scanning tunneling microscopy (STM) study of nano-sized Pb islands grown on SrTiO3, where three distinct types of gaps with different energy scales are revealed. At low temperature, an enlarged superconducting gap (Δs) emerges while there is no enhancement in superconducting transition temperature (Tc), giving rise to a larger BCS r

Hao Ouyang

We consider Toda field theories in a classical Euclidean $AdS_2$ background. We compute the four-point functions of boundary operators in the $a_1$, $a_2$ and $b_2$ Toda field theories. They take the same form as the four-point functions of generators in the corresponding $\mathcal{W}$-algebras. Therefore we conjecture that the boundary operators are in one-

C. Hadjidakis, S. J. Brodsky, G. Cavoto, C. Da Silva

By extracting the beam with a bent crystal or by using an internal gas target, the multi-TeV proton and lead LHC beams allow one to perform the most energetic fixed-target experiments ever and to study $pp$, $p$d and $p$A collisions at $\sqrt{s_{NN}}=115$ GeV and Pb$p$ and PbA collisions at $\sqrt{s_{NN}}=72$ GeV with high precision and modern detection tech

Fadhel Ayed, Marco Battiston, Federico Camerlenghi, Stefano Favaro

Feature models are popular in machine learning and they have been recently used to solve many unsupervised learning problems. In these models every observation is endowed with a finite set of features, usually selected from an infinite collection $(F_{j})_{j\geq 1}$. Every observation can display feature $F_{j}$ with an unknown probability $p_{j}$. A statist

Shuzhao Li, Huimin Yu, Wei Huang, Jing Zhang

Person attributes are often exploited as mid-level human semantic information to help promote the performance of person re-identification task. In this paper, unlike most existing methods simply taking attribute learning as a classification problem, we perform it in a different way with the motivation that attributes are related to specific local regions, wh

Patrick Buchfink, Ashish Bhatt, Bernard Haasdonk

Parametric high-fidelity simulations are of interest for a wide range of applications. But the restriction of computational resources renders such models to be inapplicable in a real-time context or in multi-query scenarios. Model order reduction (MOR) is used to tackle this issue. Recently, MOR is extended to preserve specific structures of the model throug

Péter Berkics

A linear operator on a Hilbert space $\mathbb{H}$, in the classical approach of von Neumann, must be symmetric to guarantee self-adjointness. However, it can be shown that the symmetry could be ommited by using a criterion for the graph of the operator and the adjoint of the graph. Namely, S is shown to be densely defined and closed if and only if $\{k + l :

Kristina Rognlien Dahl, Espen Stokkereit

We show how a stochastic version of the Lagrange multiplier method can be combined with the stochastic maximum principle for jump diffusions to solve certain constrained stochastic optimal control problems. Two different terminal constraints are considered; one constraint holds in expectation and the other almost surely. As an application of this method, we

Pietro Ursino

Using the technique of formative processes, I solve the decidability problem of MLS with unordered cartesian product in the positive. Moreover I give a pure combinatorial description of the satisfiable MLS with unordered cartesian product-formulas for a given number of variables.

Jelena Rupčić

This note attempts to study lacunary trigonometric products with values in the matrix group SU(1,1) in analogy with lacunary trigonometric series. The central questions are the characterization of their convergence in an appropriately define $L^p$-metric and the characterization of their convergence almost everywhere. These can be interpreted as nonlinear an

Mathias S. Jørgensen, Henrik L. Mortensen, Søren A. Meldgaard, Esben L. Kolsbjerg

One endeavour of modern physical chemistry is to use bottom-up approaches to design materials and drugs with desired properties. Here we introduce an atomistic structure learning algorithm (ASLA) that utilizes a convolutional neural network to build 2D compounds and layered structures atom by atom. The algorithm takes no prior data or knowledge on atomic int

Maxat Kulmanov, Wang Liu-Wei, Yuan Yan, Robert Hoehndorf

An embedding is a function that maps entities from one algebraic structure into another while preserving certain characteristics. Embeddings are being used successfully for mapping relational data or text into vector spaces where they can be used for machine learning, similarity search, or similar tasks. We address the problem of finding vector space embeddi

Kristina Rognlien Dahl

We consider the pricing problem of a seller with delayed price information. By using Lagrange duality, a dual problem is derived, and it is proved that there is no duality gap. This gives a characterization of the seller's price of a contingent claim. Finally, we analyze the dual problem, and compare the prices offered by two sellers with delayed and ful

D. Schaerer, T. Fragos, Y. Izotov

The origin of nebular HeII emission, which is frequently observed in low-metallicity (O/H) star-forming galaxies, remains largely an unsolved question. Using the observed anticorrelation of the integrated X-ray luminosity per unit of star formation rate ($L_X/{\rm SFR}$) of an X-ray binary population with metallicity and other empirical data from the well-st

Masatake Tsuji, Hidenori Hiramatsu, Hideo Hosono

The ternary nitride CaZn2N2, composed only of earth-abundant elements, is a novel semiconductor with a band gap of 1.8 eV. First-principles calculations predict that continuous Mg substitution at the Zn site will change the optical band gap in a wide range from ~3.3 eV to ~1.9 eV for Ca(Mg1-xZnx)2N2 (x = 0-1). In this study, we demonstrate that a solid-state

Jan Dvořák, Zdeněk Hanzálek

The portfolio of models offered by car manufacturing groups often includes many variants (i.e., different car models and their versions). With such diversity in car models, variant management becomes a formidable task. Thus, there is an effort to keep the variants as close as possible. This simple requirement forms a big challenge in the area of communicatio

Kristina Rognlien Dahl

We consider the pricing problem facing a seller of a contingent claim. We assume that this seller has some general level of partial information, and that he is not allowed to sell short in certain assets. This pricing problem, which is our primal problem, is a constrained stochastic optimization problem. We derive a dual to this problem by using the conjugat

Anisur Rahaman Molla, William K. Moses

We consider cooperation among insects, modeled as cooperation between mobile robots on a graph. Within this setting, we consider the problem of mobile robot dispersion on graphs. The study of mobile robots on a graph is an interesting paradigm with many interesting problems and applications. The problem of dispersion in this context, introduced by Augustine

Jose-Ignacio Izpura

To study resistance noise (DeltaR) by a spectrum analyzer we must convert this noise into a noise voltage (DeltaV) at the reach of such generalized voltmeter. Whenever a current Iconv is set in a resistor to convert its resistance noise into noise voltage by Ohm's Law: DeltaV=DeltaR*Iconv, the converted noise thus obtained does not track DeltaRte (its re

Teresa Montaruli

The focus of this presentation is to go through some of the remarkable observations concerning gamma-ray cosmic accelerators and diffuse emissions. Additionally, I will cover the status of the new generation of gamma-ray groundbased observatories, CTA and LHAASO. To create this new generation of arrays, new technologies have been prepared concerning the phot

Haojie Liu, Tong Chen, Peiyao Guo, Qiu Shen

A deep image compression scheme is proposed in this paper, offering the state-of-the-art compression efficiency, against the traditional JPEG, JPEG2000, BPG and those popular learning based methodologies. This is achieved by a novel conditional probably model with embedded priors which can accurately approximate the entropy rate for rate-distortion optimizat

Joël Kabore, Alexandre Fotue-Tabue, Kenza Guenda, Mohammed E. Charkani

In this paper, the investigation on the algebraic structure of the ring $\frac{\mathbb{F}_q[v]}{\langle\,v^q-v\,\rangle}$ and the description of its automorphism group, enable to study the algebraic structure of codes and their dual over this ring. We explore the algebraic structure of skew-constacyclic codes, by using a linear Gray map and we determine thei

Oliver Moolan-Feroze, Konstantinos Karachalios, Dimitrios N. Nikolaidis, Andrew Calway

We present a novel method of integrating image-based measurements into a drone navigation system for the automated inspection of wind turbines. We take a model-based tracking approach, where a 3D skeleton representation of the turbine is matched to the image data. Matching is based on comparing the projection of the representation to that inferred from image

Joanna Dziadkowiec, Bahareh Zareeipolgardani, Dag Kristian Dysthe, Anja Røyne

Fluid-induced alteration of rocks and mineral-based materials often starts at confined mineral interfaces where nm-thick water films can persist even at high overburden pressures and at low vapor pressures. These films enable transport of reactants and affect forces acting between mineral surfaces. However, the feedback between the surface forces and reactiv

Satoru Takashima, Hirokazu Kobayashi, Katsushi Iwashita

This paper describes an integer multiplier for the orbital angular momentum (OAM) of light through the parallel implementation of multiple circular-sector transformations, whereby the cross-sectional circular shape of the OAM mode is geometrically transformed to the circular-sector shape. Experiments show that the conversion accuracy of both OAM doubler and

Jiasong Wu, Fuzhi Wu, Qihan Yang, Youyong Kong

One of the key challenges in the area of signal processing on graphs is to design transforms and dictionaries methods to identify and exploit structure in signals on weighted graphs. In this paper, we first generalize graph Fourier transform (GFT) to graph fractional Fourier transform (GFRFT), which is then used to define a novel transform named spectral gra

Gerard t Hooft

Getting the mathematical rules for quantised black holes correctly is far from straightforward. Many earlier treatises got it not quite correctly. The general relativistic transformation linking the distant observer (who only detects particles outside the hole) with the observations of a local observer (who falls into a black hole) must map the quantum state

Yanlin Qian, Song Yan, Joni-Kristian Kämäräinen, Jiri Matas

In the real world, a scene is usually cast by multiple illuminants and herein we address the problem of spatial illumination estimation. Our solution is based on detecting gray pixels with the help of flash photography. We show that flash photography significantly improves the performance of gray pixel detection without illuminant prior, training data or cal

Gauri Devi, Mridusmita Buragohain, Amit Pathak

This work reports a 'Density Functional Theory' (DFT) calculation of PAH molecules with a five-member ring to determine the expected region of infrared features. It is highly possible that fullerene molecule might be originated from five-membered ring PAH molecules in the ISM. Effect of ionization and protonation on five-membered ring PAH molecule is

Mario Stipčić

This paper studies dyadic singular integral forms associated with $r$-partite $r$-uniform hypergraphs such that all their connected components are complete. We characterize their $L^p$ boundedness by T(1)-type conditions in two different ways. We also dominate these forms by positive sparse forms and prove weighted estimates with multilinear Muckenhoupt weig

Jinpeng Xia, Jiasong Wu, Youyong Kong, Pinzheng Zhang

Although Convolutional Neural Networks (CNNs) achieve effectiveness in various computer vision tasks, the significant requirement of storage of such networks hinders the deployment on computationally limited devices. In this paper, we propose a new compact and portable deep learning network named Modulated Binary Cliquenet (MBCliqueNet) aiming to improve the

Àngel Calsina, József Z. Farkas

In this work we establish conditions which guarantee the existence of (strictly) positive steady states of a nonlinear structured population model. In our framework the steady state formulation amounts to recasting the nonlinear problem as a family of eigenvalue problems combined with a fixed point problem. Amongst other things our formulation requires us to

M. A. Shevchenko, L. L. Chaikov, M. N. Kirichenko, A. D. Kudryavtseva

Stimulated low-frequency Raman scattering can give essential information about the elastic properties of different nanoparticles systems, in particular, biological nanostructures. In the present study, low-frequency vibrational modes in human and bovine serum albumin were for the first time investigated using stimulated low-frequency Raman scattering. Stimul

KJ Edmunds, H Petersen, M Hassan, S Yassine

Maintaining upright posture is a complex task governed by the integration of afferent sensorimotor and visual information with compensatory neuromuscular reactions. The objective of this work was to characterize the visual dependency and functional dynamics of cortical activation during postural control. Proprioceptic vibratory stimulation of calf muscles at

Erki Metsanurk, Mattias Klintenberg

Effective harmonic methods allow for calculating temperature dependent phonon frequencies by incorporating the anharmonic contributions into an effective harmonic Hamiltonian. The systematic errors arising from such an approximation are explained theoretically and quantified by density functional theory based numerical simulations. Two techniques with differ

S. Reschke, V. Tsurkan, S. -H. Do, K. -Y. Choi

Spin liquids may host emergent quasiparticles, collective excitations of the spin degrees of freedom with characteristic features of Majorana fermions, which experimentally are detectable by broad excitation continua due to spin fractionalization. The latter is predicted for the Kitaev spin liquid, an exactly solvable model with bond-dependent interactions o

Rupak Majumdar, Joël Ouaknine, Amaury Pouly, James Worrell

We exhibit an algorithm to compute the strongest algebraic (or polynomial) invariants that hold at each location of a given unguarded linear hybrid automaton (i.e., a hybrid automaton having only unguarded transitions, all of whose assignments are given by affine expressions, and all of whose continuous dynamics are given by linear differential equations). O

Bartosz Malman

We prove that the nearly invariant subspaces of a de Branges space which have no common zeros are precisely of the form an exponential function times a de Branges space.

Mauro Patti, Giuliana Fiorentino

Astrometry was not a science case of the Gemini Multiconjugate adaptive optics System (GeMS) at its design stage. However, since GeMS has been in regular science operation with the Gemini South Adaptive Optics Imager (GSAOI), their astrometric performances have been deeply analysed. The non-linear component of the distortion map model shows a characteristic

Janina Löffler, Christophe Ballif, Nicolas Wyrsch

With their fast response time and a spatial resolution in the range of a few microns, microchannel plates (MCPs) are a prominent choice for the development of detectors with highest resolution standards. Amorphous silicon-based microchannel plates (AMCPs) aim at overcoming the fabrication drawbacks of conventional MCPs and the long dead time of their individ

Nadja Klein, Manuel Carlan, Thomas Kneib, Stefan Lang

We propose a novel spike and slab prior specification with scaled beta prime marginals for the importance parameters of regression coefficients to allow for general effect selection within the class of structured additive distributional regression. This enables us to model effects on all distributional parameters for arbitrary parametric distributions, and t

Kerstin Beer, Dmytro Bondarenko, Terry Farrelly, Tobias J. Osborne

Neural networks enjoy widespread success in both research and industry and, with the imminent advent of quantum technology, it is now a crucial challenge to design quantum neural networks for fully quantum learning tasks. Here we propose the use of quantum neurons as a building block for quantum feed-forward neural networks capable of universal quantum compu

Anna Belova, Igors Gorbovickis

The multiplier $λ_n$ of a periodic orbit of period $n$ can be viewed as a (multiple-valued) algebraic function on the space of all complex quadratic polynomials $p_c(z)=z^2+c$. We provide a numerical algorithm for computing critical points of this function (i.e., points where the derivative of the multiplier with respect to the complex parameter $c$ vanishes

Olga I. Borodina, Anton F. Seleznev, Giovanni Carraro, Vladimir M. Danilov

Binary stars are present in all stellar systems, yet their role is far from being fully understood. We investigate the effect of unresolved binaries in the derivation of open clusters' mass by star counts. We start from the luminosity functions of five open clusters: IC 2714, NGC 1912, NGC 2099, NGC 6834 and NGC 7142. Luminosity functions are obtained vi

R. Eder

A formulation of the Kondo lattice Hamiltonian in terms of bond particles is derived and solved in two different approximations. The bond particles correspond to the eigenstates of a single unit cell and are bosons for states with even electron number and fermions for states with an odd electron number. A s a check various physical quantities are calculated

Su Yang, Yuqing Zhang, Chensi Wu

With the developing of the attack and defense technology, the cyber environment has been more and more sophisticated. We failed to give an accurate evaluation of network security situation, as we lack a more accurate quantitative evaluation of attack-defense behaviors. In response to this situation, we proposed an attack-defense stochastic game model (ADSGM)

D. Bisschoff, M. S. Potgieter, O. P. M. Aslam

The local interstellar spectra (LIS's) for galactic cosmic rays (CR's) cannot be directly observed at the Earth below certain energies, because of solar modulation in the heliosphere. With Voyager 1 crossing the heliopause in 2012, in situ experimental LIS data below 100 MeV/nuc can now constrain computed galactic CR spectra. Using galactic propagati

Emma Lepri, Marco Manetti

In this paper we study classical deformations of diagrams of commutative algebras over a field of characteristic 0. In particular we determine several homotopy classes of DG-Lie algebras, each one of them controlling this above deformation problem: the first homotopy type is described in terms of the projective model structure on the category of diagrams of

Simone Finizio, Katharina Zeissler, Sebastian Wintz, Sina Mayr

Magnetic skyrmions are topological solitons that exhibit an increased stability against annihilation, and can be displaced with low current densities, making them a promising candidate as an information carrier. In order to demonstrate a viable skyrmion-based memory device, it is necessary to reliably and reproducibly nucleate, displace, detect, and delete t

R. Eder, P. Wrobel

We discuss the quasiparticle band structure of the antiferromagnetic phase of the planar Kondo lattice model with a half-filled conduction band, the so-called Kondo insulator. The band structure is obtained by bond fermion technique and good agreement is obtained with the single particle spectral function obtained by Dynamical Cluster Approximation. In parti

Joanna Dziadkowiec, Shaghayegh Javadi, Jon E. Bratvold, Ola Nilsen

Nm-range forces acting between calcite surfaces in water affect macroscopic properties of carbonate rocks and calcite-based granular materials, and are significantly influenced by calcite surface recrystallization. We suggest that the repulsive mechanical effects related to nm-scale surface recrystallization of calcite in water could be partially responsible

Lin Tian, Lorenzo Di Mario, Aswathi K Sivan, Daniele Catone

We present femtosecond transient transmission (or absorbance) measurements in silicon nanowires in the energy range 1.1-3.5 eV, from below the indirect band-gap to above the direct band-gap. Our pump-probe measurements allow us to give a complete picture of the carrier dynamics in silicon. In this way we perform an experimental study with a spectral complete

Takayuki Hibi, Hiroju Kanno, Kazunori Matsuda

Let $G$ be a finite simple graph on the vertex set $V(G) = \{x_1, \ldots, x_n\}$ and $I(G) \subset K[V(G)]$ its edge ideal, where $K[V(G)]$ is the polynomial ring in $x_1, \ldots, x_n$ over a field $K$ with each ${\rm deg} x_i = 1$ and where $I(G)$ is generated by those squarefree quadratic monomials $x_ix_j$ for which $\{x_i, x_j\}$ is an edge of $G$. In th

Yasutaka Taniguchi

Coupling of cluster and deformed structures are important for dynamics of nuclear structure. Threshold energy has been discussed to explain cluster structures coupling to deformed states but relation between threshold energy and excitation energy has open problems. Negative-parity superdeformed (SD) states were observed by a $γ$-spectroscopy experiment in $^

R. Juhász, J. Kelling, G. Ódor

We consider the Kuramoto model on sparse random networks such as the Erdős-Rényi graph or its combination with a regular two-dimensional lattice and study the dynamical scaling behavior of the model at the synchronization transition by large-scale, massively parallel numerical integration. By this method, we obtain an estimate of critical coupling strength m

Naixie Zhou, Sicong Jiang, Timothy Huang, Mingde Qin

High-entropy intermetallic compounds (HEICs) were fabricated by mechanical alloying and spark plasma sintering to fill a knowledge gap between the traditional high-entropy alloys (HEAs) and emerging high-entropy ceramics (HECs). Notably, several four- or five-component equimolar aluminides, such as the B2-phase (Fe1/5Co1/5Ni1/5Mn1/5Cu1/5)Al, have been made i

Bang Liu, Mingjun Zhao, Di Niu, Kunfeng Lai

Automatic question generation is an important technique that can improve the training of question answering, help chatbots to start or continue a conversation with humans, and provide assessment materials for educational purposes. Existing neural question generation models are not sufficient mainly due to their inability to properly model the process of how

Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou

Modern neural networks are over-parametrized. In particular, each rectified linear hidden unit can be modified by a multiplicative factor by adjusting input and output weights, without changing the rest of the network. Inspired by the Sinkhorn-Knopp algorithm, we introduce a fast iterative method for minimizing the L2 norm of the weights, equivalently the we

Leon Bungert, Martin Burger, Daniel Tenbrinck

In this work we investigate the computation of nonlinear eigenfunctions via the extinction profiles of gradient flows. We analyze a scheme that recursively subtracts such eigenfunctions from given data and show that this procedure yields a decomposition of the data into eigenfunctions in some cases as the 1-dimensional total variation, for instance. We discu

I. S. Ciuperca, E. Feireisl, M. Jai, A. Petrov

The existence of weak solutions to the Navier-Stokes-Fourier system describing the stationary states of a compressible, viscous, and heat conducting fluid in bounded 2D-domains is shown under fairly general and physically relevant constitutive relations. The equation of state of a real fluid is considered, where the admissible range of density is confined to

K. Moraitis, E. Pariat, G. Valori, K. Dalmasse

Context. Magnetic helicity is an important quantity in studies of magnetized plasmas as it provides a measure of the geometrical complexity of the magnetic field in a given volume. A more detailed description of the spatial distribution of magnetic helicity is given by the field line helicity that expresses the amount of helicity associated to individual fie

Yusuf A. Yilmaz, Ahmet M. Alpkilic, Aydan Yeltik, Hamza Kurt

Previously proposed designs of integrated photonic devices have used the intuitive brute force approach or optimization methods that employ parameter search algorithms. However, a small parameter space and poor exploitation of the underlying physics have limited device performance, functionality, and footprint. In this paper, we propose efficient and compact

Ibrahim Jubran, David Cohn, Dan Feldman

The $\ell_p$ linear regression problem is to minimize $f(x)=||Ax-b||_p$ over $x\in\mathbb{R}^d$, where $A\in\mathbb{R}^{n\times d}$, $b\in \mathbb{R}^n$, and $p>0$. To avoid overfitting and bound $||x||_2$, the constrained $\ell_p$ regression minimizes $f(x)$ over every unit vector $x\in\mathbb{R}^d$. This makes the problem non-convex even for the simplest c

S. Gratton, E. Simon, Ph. L. Toint

An adaptive regularization algorithm using inexact function and derivatives evaluations is proposed for the solution of composite nonsmooth nonconvex optimization. It is shown that this algorithm needs at most $O(|\log(ε)|\,ε^{-2})$ evaluations of the problem's functions and their derivatives for finding an $ε$-approximate first-order stationary point. T

Yingting Liu, Yinghui Ye, Haiyang Ding, Jianmei Shen

This letter proposes a dynamic power splitting scheme (DPSS) for decode-and-forward (DF) based cooperative simultaneous wireless information and power transfer (SWIPT) networks with direct link. The relay node adopts an optimal dynamic power splitting factor determined by instantaneous channel state information (CSI) to harvest energy and process information

Bilal Abu-Salih, Bushra Bremie, Pornpit Wongthongtham, Kevin Duan

The wealth of Social Big Data (SBD) represents a unique opportunity for organisations to obtain the excessive use of such data abundance to increase their revenues. Hence, there is an imperative need to capture, load, store, process, analyse, transform, interpret, and visualise such manifold social datasets to develop meaningful insights that are specific to

Ondřej Černotík, Aurélien Dantan, Claudiu Genes

We present a general framework for cavity quantum electrodynamics with strongly frequency-dependent mirrors. The method is applicable to a variety of reflectors exhibiting sharp internal resonances as can be realized, for example, with photonic-crystal mirrors or with two-dimensional atomic arrays around subradiant points. Our approach is based on a modifica

G. Buldgen

The theory of stellar evolution plays a central role in astrophysics as stellar models are used to infer properties for Galactic and Extragalactic stellar populations as well as exoplanetary systems. However, despite decades of experience, stellar models still face major issues linked to transport processes of chemicals and angular momentum. This review will

Song Jiaoyan, Zhao Jing, Li Yimin, Li Bo

Absorbing materials in ultra-high frequency (UHF) band has constantly been a major challenge. The size of the absorber in UHF band is large, whereas the resonant frequency band is narrow. According to Rozanov's theory, two kinds of composite metamaterial absorbers are designed to realize the requirements of low-frequency broadband metamaterial microwave

Joachim Neu

Applications of massive machine-type communications, such as sensor networks, smart metering, 'internet-of-things', or process and factory automation, are forecast to have great economic impact in the next five to ten years. Low-complexity energy- and cost-efficient communication schemes are essential to enable large-scale deployments. To target thes

Liming Zhao, Zhikuan Zhao, Patrick Rebentrost, Joseph Fitzsimons

Efficiently processing basic linear algebra subroutines is of great importance for a wide range of computational problems. In this paper, we consider techniques to implement matrix functions on a quantum computer, which are composed of basic matrix operations on a set of matrices. These matrix operations include addition, multiplication, Kronecker sum, tenso

Rongqian Wang, Jincheng Lu, Jian-Hua Jiang

Graphene---hexagonal-boron-nitride---InSb near-field structures are designed and optimized to enhance the output power and energy efficiency of the thermophotovoltaic systems working in the temperature range of common industrial waste heat, $400~\rm K \sim 800~\rm K$, which is also the working temperature range for conventional thermoelectric devices. We sho

G. Buldgen, S. J. A. J. Salmon, A. Noels, V. A. Baturin

The Sun is the most studied of stars and a laboratory of fundamental physics. However, the understanding of our star is stained by the solar modelling problem which can stem from various causes. We combine inversions of sound speed, an entropy proxy and the Ledoux discriminant with the position of the base of the convective zone and the photospheric helium a

Y. Zhao, L. Rezac, P. Hartogh, J. Ji

Our aim is to investigate early activity (July 2014) of 67P/CG with 3D coma and radiative transfer modeling of MIRO measurements, accounting for nucleus shape, illumination, and orientation of the comet. We investigate MIRO line shape information for spatial distribution of water activity on the nucleus during the onset of activity. During this period we sho

Itsikiantsoa Randrianantenaina, Megumi Kaneko, Hayssam Dahrouj, Hesham ElSawy

Non-Orthogonal Multiple Access (NOMA) and Fog Radio Access Networks (FRAN) are promising candidates within the 5G and beyond systems. This work examines the benefit of adopting NOMA in an FRAN architecture with constrained capacity fronthaul. The paper proposes methods for optimizing joint scheduling and power adaptation in the downlink of a NOMA-based FRAN

Sebastiaan Koning, Caspar Greeven, Eric Postma

Despite their successes in the field of self-learning AI, Convolutional Neural Networks (CNNs) suffer from having too many trainable parameters, impacting computational performance. Several approaches have been proposed to reduce the number of parameters in the visual domain, the Inception architecture [Szegedy et al., 2016] being a prominent example. This r

Haggai Roitman, Avigdor Gal, Louiqa Raschid

Advances in Web technology enable personalization proxies that assist users in satisfying their complex information monitoring and aggregation needs through the repeated querying of multiple volatile data sources. Such proxies face a scalability challenge when trying to maximize the number of clients served while at the same time fully satisfying clients&#39

Jonathan Mayzel, Victor Steinberg, Atul Varshney

Electron transport in two-dimensional conducting materials such as graphene, with dominant electron-electron interaction, exhibits unusual vortex flow that leads to a nonlocal current-field relation (negative resistance), distinct from the classical Ohm's law. The transport behavior of these materials is best described by low Reynolds number hydrodynamic

James H. Matthews, Anthony R. Bell, Anabella T. Araudo, Katherine M. Blundell

The origin of ultrahigh energy cosmic rays (UHECRs) is an open question. In this proceeding, we first review the general physical requirements that a source must meet for acceleration to 10-100 EeV, including the consideration that the shock is not highly relativistic. We show that shocks in the backflows of radio galaxies can meet these requirements. We dis

Rainer Dahlhaus, Stefan Richter

Two adaptive bandwidth selection methods for nonparametric estimators in locally stationary processes are proposed. We investigate a cross validation approach and a method based on contrast minimization and derive asymptotic properties of both methods. The results are applicable for different statistics under a broad setting of locally stationarity including

Nikola Tomasevic, Dejan Paunovic, Sanja Vranes

A content recommender system or a recommendation system represents a subclass of information filtering systems which seeks to predict the user preferences, i.e. the content that would be most likely positively "rated" by the user. Nowadays, the recommender systems of OpenCourseWare (OCW) platforms typically generate a list of recommendations in one o

Hao Zhou, Minlie Huang, Yishun Mao, Changlei Zhu

Advertising (ad for short) keyword suggestion is important for sponsored search to improve online advertising and increase search revenue. There are two common challenges in this task. First, the keyword bidding problem: hot ad keywords are very expensive for most of the advertisers because more advertisers are bidding on more popular keywords, while unpopul

K. Dajani, M. R. de Lepper, E. A. Robinson

We introduce the concept of Minkowski normality, a different type of normality for the regular continued fraction expansion. We use the ordering \[ \frac{1}{2},\quad \frac{1}{3}, \frac{2}{3},\quad \frac{1}{4}, \frac{3}{4},\frac{2}{5}, \frac{3}{5},\quad \frac{1}{5}, \cdots \] of rationals obtained from the Kepler tree to give a concrete construction of an inf

Detchat Samart

The congruent number elliptic curves are defined by $E_d: y^2=x^3-d^2x$, where $d\in \mathbb{N}.$ We give a simple proof of a formula for $L(\mathrm{Sym}^2(E_d),3)$ in terms of the determinant of the elliptic trilogarithm evaluated at some degree zero divisors supported on the torsion points on $E_d(\overline{\mathbb{Q}})$.

Haggai Roitman

This work presents a general query term weighting approach based on query performance prediction (QPP). To this end, a given term is weighed according to its predicted effect on query performance. Such an effect is assumed to be manifested in the responses made by the underlying retrieval method for the original query and its (simple) variants in the form of

Yiming Hu, Jianquan Li, Xianlei Long, Shenhua Hu

Deep neural networks (DNNs) have achieved great success in a wide range of computer vision areas, but the applications to mobile devices is limited due to their high storage and computational cost. Much efforts have been devoted to compress DNNs. In this paper, we propose a simple yet effective method for deep networks compression, named Cluster Regularized

S. N. Kudryavtsev

The article examines Nikolskii and Besov spaces with norms defined using "$L_p$-averaged" mixed moduli of continuity of functions of appropriate orders, instead of mixed moduli of continuity of known orders for certain mixed derivative functions. The author builds continuous linear mappings of such spaces of functions defined on cube $ I^d, $ to ordi

Yiming Hu, Siyang Sun, Jianquan Li, Jiagang Zhu

Channel pruning, which seeks to reduce the model size by removing redundant channels, is a popular solution for deep networks compression. Existing channel pruning methods usually conduct layer-wise channel selection by directly minimizing the reconstruction error of feature maps between the baseline model and the pruned one. However, they ignore the feature

Benjamin J. Meyer, Tom Drummond

State-of-the-art deep neural network recognition systems are designed for a static and closed world. It is usually assumed that the distribution at test time will be the same as the distribution during training. As a result, classifiers are forced to categorise observations into one out of a set of predefined semantic classes. Robotic problems are dynamic an

Edward Moroshko, Guy Feigenblat, Haggai Roitman, David Konopnicki

We suggest a new idea of Editorial Network - a mixed extractive-abstractive summarization approach, which is applied as a post-processing step over a given sequence of extracted sentences. Our network tries to imitate the decision process of a human editor during summarization. Within such a process, each extracted sentence may be either kept untouched, reph

Seo-Jin Kim, K. -W. Lee

Using ab initio calculations based on the correlated band theory, we have investigated the quasi-one-dimensional chain system $β$-V$_2$O(PO$_4$), showing both charge and spin orderings. Even in the uncorrelated region, the pure transition from the tetragonal to the monoclinic structure leads to a sizable charge difference between the two types of V ions, reg

Michael Haythorpe, Alex Newcombe

The exact crossing number is only known for a small number of families of graphs. Many of the families for which crossing numbers have been determined correspond to cartesian products of two graphs. Here, the cartesian product of the Sunlet graph, denoted $\mathcal{S}_n$, and the Star graph, denoted $K_{1,m}$, is considered for the first time. It is proved t

Vladimir Ejov, Jerzy A Filar, Michael Haythorpe, John F Roddick

An instance of Hamiltonian cycle problem can be solved by converting it to an instance of Travelling salesman problem, assigning any choice of weights to edges of the underlying graph. In this note we demonstrate that, for difficult instances, choosing the edge weights to be the resistance distance between its two incident vertices is often a good choice. We

Zlatko K. Minev

A quantum system driven by a weak deterministic force while under strong continuous energy measurement exhibits quantum jumps between its energy levels (Nagourney et al., 1986, Sauter et al., 1986, Bergquist et al., 1986). This celebrated phenomenon is emblematic of the special nature of randomness in quantum physics. The times at which the jumps occur are r

Michael Haythorpe, Jerzy Filar

We consider a direct conversion of the, classical, set splitting problem to the directed Hamiltonian cycle problem. A constructive procedure for such a conversion is given, and it is shown that the input size of the converted instance is a linear function of the input size of the original instance. A proof that the two instances are equivalent is given, and

Chong Yu, Qiong Liu, Cong Chen, Jin Wang

Heterogeneity is ubiquitous in stem cells (SC), cancer cells (CS), and cancer stem cells (CSC). SC and CSC heterogeneity is manifested as diverse sub-populations with self-renewing and unique regeneration capacity. Moreover, the CSC progeny possesses multiple plasticity and cancerous characteristics. Many studies have demonstrated that cancer heterogeneity i

Michael Haythorpe

The FHCP Challenge Set, comprising of 1001 instances of Hamiltonian cycle problem, is introduced. This set is the first to contain instances of Hamiltonian cycle problem for which the primary difficulty is the underlying graph structure, rather than simply size. A summary of the kinds of graphs contained in the FHCP Challenge Set is given. A discussion of th

Michael Haythorpe

A constructive method is provided that outputs a directed graph which is named a broken crown graph, containing $5n-9$ vertices and $k$ Hamiltonian cycles for any choice of integers $n \geq k \geq 4$. The construction is not designed to be minimal in any sense, but rather to ensure that the graphs produced remain non-trivial instances of the Hamiltonian cycl

Evgenii Tsymbalov, Sergei Makarychev, Alexander Shapeev, Maxim Panov

Active learning methods for neural networks are usually based on greedy criteria which ultimately give a single new design point for the evaluation. Such an approach requires either some heuristics to sample a batch of design points at one active learning iteration, or retraining the neural network after adding each data point, which is computationally ineff

Jerzy A Filar, Michael Haythorpe, Richard Taylor

We address the question of whether it may be worthwhile to convert certain, now classical, NP-complete problems to one of a smaller number of kernel NP-complete problems. In particular, we show that Karp's classical set of 21 NP-complete problems contains a kernel subset of six problems with the property that each problem in the larger set can be convert