November 2019 arXiv papers — page 39

Rui Zhang, Quanyan Zhu

Internet of Things (IoT) is highly vulnerable to emerging Advanced Persistent Threats (APTs) that are often operated by well-resourced adversaries. Achieving perfect security for IoT networks is often cost-prohibitive if not impossible. Cyber insurance is a valuable mechanism to mitigate cyber risks for IoT systems. In this work, we propose a bi-level game-t

Sean Weaver, Marijn Heule

Minimal perfect hash functions (MPHFs) are used to provide efficient access to values of large dictionaries (sets of key-value pairs). Discovering new algorithms for building MPHFs is an area of active research, especially from the perspective of storage efficiency. The information-theoretic limit for MPHFs is 1/(ln 2) or roughly 1.44 bits per key. The curre

Fangyu Liu, Rongtian Ye, Xun Wang, Shuaipeng Li

The hubness problem widely exists in high-dimensional embedding space and is a fundamental source of error for cross-modal matching tasks. In this work, we study the emergence of hubs in Visual Semantic Embeddings (VSE) with application to text-image matching. We analyze the pros and cons of two widely adopted optimization objectives for training VSE and pro

Jaynta Mandi, Emir Demirović, Peter. J Stuckey, Tias Guns

Combinatorial optimization assumes that all parameters of the optimization problem, e.g. the weights in the objective function is fixed. Often, these weights are mere estimates and increasingly machine learning techniques are used to for their estimation. Recently, Smart Predict and Optimize (SPO) has been proposed for problems with a linear objective functi

Filippo Aleotti, Matteo Poggi, Fabio Tosi, Stefano Mattoccia

Scene flow is a challenging task aimed at jointly estimating the 3D structure and motion of the sensed environment. Although deep learning solutions achieve outstanding performance in terms of accuracy, these approaches divide the whole problem into standalone tasks (stereo and optical flow) addressing them with independent networks. Such a strategy dramatic

Mohamed-Salem Ahmed, Lionel Cucala, Michael Genin

Spatial scan statistics are well-known methods for cluster detection and are widely used in epidemiology and medical studies for detecting and evaluating the statistical significance of disease hotspots. For the sake of simplicity, the classical spatial scan statistic assumes that the observations of the outcome variable in different locations are independen

Reka A. Vig, Tamas G. Kovacs

Across the finite temperature transition to the quark-gluon plasma, the QCD topological susceptibility decreases sharply. Thus in the high temperature phase the remaining topological objects (possibly calorons) form a weakly interacting dilute gas. The overlap Dirac operator, through its exact zero modes, allows one to measure the net topological charge. We

Paul S Davids, Erik Anderson, Jared Kirsch, Joshua Shank

Ultrafast photon-assisted tunneling is shown to lead to large nonlinear dynamic currents that can be used to generate dc rectified current as well as higher order harmonic response from a metasurface-coupled tunnel diode. This artificial nonlinear media can have tailored resonances in the infrared around the longitudinal optical phonon modes of various compa

Ferenc Bálint-Benczédi, Jan-Hendrik Worch, Daniel Nyga, Nico Blodow

A pressing question when designing intelligent autonomous systems is how to integrate the various subsystems concerned with complementary tasks. More specifically, robotic vision must provide task-relevant information about the environment and the objects in it to various planning related modules. In most implementations of the traditional Perception-Cogniti

Will Johnson

We give an example of a dense o-minimal structure in which there is a definable quotient that cannot be eliminated, even after naming parameters. Equivalently, there is an interpretable set which cannot be put in parametrically definable bijection with any definable set. This gives a negative answer to a question of Eleftheriou, Peterzil, and Ramakrishnan. A

Hassna Ouassal, Ming Yan, Jeffrey A. Nanzer

A new approach to distributed syntonization (frequency alignment) for the coordination of nodes in open loop coherent distributed antenna arrays to enable distributed beamforming is presented. This approach makes use of the concept of consensus optimization among nodes without requiring a centralized control. Decentralized frequency consensus can be achieved

Ahmed Ayad, Geoff Beck

Axions or more generally axion-like particles (ALPs) are pseudo-scalar particles predicted by many extensions of the Standard Model of particle physics (SM) and considered as highly viable candidates for dark matter (DM) in the universe. If they exist in nature, they are expected to couple with photons in the presence of an external magnetic field through a

Mariane Maynard, Thibault Duhamel, Froduald Kabanza

The ability to observe the effects of actions performed by others and to infer their intent, most likely goals, or course of action, is known as a plan or intention recognition cognitive capability and has long been one of the fundamental research challenges in AI. Deep learning has recently been making significant inroads on various pattern recognition prob

Abolfazl Asudeh, H. V. Jagadish

Human decision-makers often receive assistance from data-driven algorithmic systems that provide a score for evaluating objects, including individuals. The scores are generated by a function (mechanism) that takes a set of features as input and generates a score.The scoring functions are either machine-learned or human-designed and can be used for different

Siavash Mollaebrahim, Daniel Romero, Baltasar Beferull-Lozano

We study decentralized designing of the graph shift operators to implement linear transformations between graph signals. Since this operator captures the local structure of the graph, the proposed method of this paper gives rise to decentralized linear network operators. Unfortunately, existing decentralized approaches either consider some special instances

Long Zhang, Zhe Zhang, Fengcheng Wu, Danqing Wang

Moiré superlattices formed in van der Waals bilayers have enabled the creation and manipulation of new quantum states, as is exemplified by the discovery of superconducting and correlated insulating states in twisted bilayer graphene near the magic angle. Twisted bilayer semiconductors may lead to tunable exciton lattices and topological states, yet signatur

Hisakazu Minakata, Ivan Martinez-Soler, Kimihiro Okumura

Use of low energy atmospheric neutrinos is considered for precision measurement of neutrino mixing parameters. At around energy $E \simeq$ a few $\times$100 MeV and baseline $L$ of a few $\times$1000 km, CP phase effect is $\sim$10 times larger than that of the conventional LBL accelerator neutrino experiments. We report here a few progresses: (1) To analyze

Artur Avila, Xavier Buff, Arnaud Chéritat

We prove the existence of Siegel disks with smooth boundaries in most families of holomorphic maps fixing the origin. The method can also yield other types of regularity conditions for the boundary. The family is required to have an indifferent fixed point at $0$, to be parameterized by the rotation number $α$, to depend on $α$ in a Lipschitz-continuous way,

Dmitry Gnatyshak, Luis Oliva-Felipe, Sergio Álvarez-Napagao, Julian Padget

Currently, agent-based simulation frameworks force the user to choose between simulations involving a large number of agents (at the expense of limited agent reasoning capability) or simulations including agents with increased reasoning capabilities (at the expense of a limited number of agents per simulation). This paper describes a first attempt at putting

Henri Berestycki, Linfeng Mei, Juncheng Wei

This paper is a continuation of the paper Berestycki, Wei and Winter \cite{Berestycki2014}. In \cite{Berestycki2014}, the existence of multiple symmetric and asymmetric spike solutions of a chemotaxis system modeling crime pattern formation, suggested by Short, Bertozzi, and Brantingham \cite{Short2010}, has been proved in the one-dimensional case. The probl

Santiago Paternain, Manfred Morari, Alejandro Ribeiro

In this work we adapt a prediction-correction algorithm for continuous time-varying convex optimization problems to solve dynamic programs arising from Model Predictive Control. In particular, the prediction step tracks the evolution of the optimal solution of the problem which depends on the current state of the system. The cost of said step is that of inve

E. Seydel, R. Hoffmann-Vogel, M. Marz

Graphite surfaces interact weakly with molecules compared to other conducting surfaces bringing the molecule-molecule interaction to the foreground. C$_{60}$ on highly oriented pyrolytic graphite is a model system for studying the molecular self-assembly on surfaces. Our scanning tunneling microscopy measurements at liquid nitrogen temperatures confirm the p

John Armstrong, Cristin Buescu

In a collectivised pension fund, investors agree that any money remaining in the fund when they die can be shared among the survivors. We compute analytically the optimal investment-consumption strategy for a fund of $n$ identical investors with homogeneous Epstein--Zin preferences, investing in the Black--Scholes market in continuous time but consuming in d

Julian Fernandez Bonder, Zhiwei Cheng, Hayk Mikayelyan

We consider an optimal rearrangement maximization problem involving the fractional Laplace operator $(-Δ)^s$, $0<s<1$, and the Gagliardo-Nirenberg seminorm $[u]_s$. We prove the existence of a maximizer, analyze its properties and show that it satisfies the unstable fractional obstacle problem equation for some $α>0$ $$(-Δ)^s u=χ_{\{u>α\}}.$$

Artyom Gadetsky, Kirill Struminsky, Christopher Robinson, Novi Quadrianto

Learning models with discrete latent variables using stochastic gradient descent remains a challenge due to the high variance of gradient estimates. Modern variance reduction techniques mostly consider categorical distributions and have limited applicability when the number of possible outcomes becomes large. In this work, we consider models with latent perm

Vladimir Bashmakov, Hrachya Khachatryan

We study the infrared phases of $\mathcal{N}\,=\,1$ QCD$_3$ with gauge group $SU(N_c)$ and with the superpotential containing the mass term and the baryon operator. We restrict ourselves to the cases, when the number of flavors is equal to the number of colours, such that baryon operator is neutral under the global $SU(N_F)$. We also focus on the cases with

Adrian Lopez Rodriguez, Krystian Mikolajczyk

We propose a domain adaptation approach for object detection. We introduce a two-step method: the first step makes the detector robust to low-level differences and the second step adapts the classifiers to changes in the high-level features. For the first step, we use a style transfer method for pixel-adaptation of source images to the target domain. We find

Tristan Kraft, Marco Piani

Quantum coherence plays an important role in quantum information protocols that provide an advantage over classical information processing. The amount of coherence that can exist between two orthogonal subspaces is limited by the positivity constraint on the density matrix. On the level of multipartite systems, this gives rise to what is known as monogamy of

Stefano Vincenzi, Angelo Porrello, Pietro Buzzega, Annamaria Conte

Nowadays, Vector-Borne Diseases (VBDs) raise a severe threat for public health, accounting for a considerable amount of human illnesses. Recently, several surveillance plans have been put in place for limiting the spread of such diseases, typically involving on-field measurements. Such a systematic and effective plan still misses, due to the high costs and e

Friso G. Heslinga, Josien P. W. Pluim, A. J. H. M. Houben, Miranda T. Schram

Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to blindness and cardiovascular disease. Information about early stage T2D might be present in retinal fundus images, but to what extent these images can be used for a screening setting is still unknown. In this study, deep neural networks were employed to differentiate between fundus images

Christian Walther Andersen, John Bulava, Ben Hörz, Colin Morningstar

Calculations of the elastic $I=\frac{3}{2}$ nucleon-pion scattering phase shifts on two lattice QCD ensembles with $m_π=200\mathrm{MeV}$ and $280\mathrm{MeV}$ are presented. The ensembles both employ $N_\mathrm{f} = 2+1$ Wilson clover fermions. We determine the $Δ(1232)$ resonance parameters from a finite volume scattering analysis. In one study the single p

Mahendra K. Verma

In this paper, I discuss the challenges in porting hydrodynamic codes to futuristic exascale HPC systems. In particular, we describe the computational complexities of finite difference method, pseudo-spectral method, and Fast Fourier Transform (FFT). We show how global data communication among the processors brings down the efficiency of pseudo-spectral code

Lingling Wang, Shaobin Liu, Xiangkun Kong, Haifeng Zhang

In this paper, we combine the design of band-pass frequency selective surfaces (FSSs) with polarization converters to realize a broadband frequency-selective polarization converter (FSPC) with lowbackward scattering, which consists of the top polarization conversion layer backed by a multi-layer bandpass FSS. It is numerically demonstrated that the 1 dB tran

Pritam Borah, V. Venugopal, Jai Sukhatme, Pranesh Muddebihal

The forecast of Indian monsoon droughts has been predicated on the notion of a season-long rainfall deficit linked to warm anomalies in the equatorial Pacific. Here, we show that in fact nearly half of all droughts over the past century were sub-seasonal, and characterized by an abrupt decline in late-season rainfall. Furthermore, the potential driver of thi

Sambuddha Saha, Aashish Kumar, Pratyush Sahay, George Jose

Deep Learning based AI systems have shown great promise in various domains such as vision, audio, autonomous systems (vehicles, drones), etc. Recent research on neural networks has shown the susceptibility of deep networks to adversarial attacks - a technique of adding small perturbations to the inputs which can fool a deep network into misclassifying them.

Nurul Huda Mahmood, Hirley Alves

Multi-connectivity (MC) with packet duplication, where the same data packet is duplicated and transmitted from multiple transmitters, is proposed in 5G New Radio as a reliability enhancement feature. However, it is found to be resource inefficient, since radio resources from more than one transmitters are required to serve a single user. Improving the perfor

He-Feng Yin, Xiao-Jun Wu, Su-Gen Chen

Discriminative dictionary learning (DDL) has recently gained significant attention due to its impressive performance in various pattern classification tasks. However, the locality of atoms is not fully explored in conventional DDL approaches which hampers their classification performance. In this paper, we propose a locality constraint dictionary learning wi

N. Nikitin, K. Toms

In the framework of non-relativistic quantum mechanics we present a proposal for a gedunken experimental setup of a quantum system allowing information exchange. We discuss the compatibility of the procedure with a few no-go theorems.

Jung-Chao Ban, Chih-Hung Chang, Wen-Guei Hu, Guan-Yu Lai

Motivated from the study of multiple ergodic average, the investigation of multiplicative shift spaces has drawn much of interest among researchers. This paper focuses on the relation of topologically mixing properties between multiplicative shift spaces and traditional shift spaces. Suppose that $\mathsf{X}_Ω^{(l)}$ is the multiplicative subshift derived fr

Priya Sharma

I discuss heat and momentum transport in a mesoscopic film of $^3$He, confined by rough walls in the normal Fermi liquid state. Inelastic binary quasiparticle scattering mediated by elastic scattering from the surface roughness gives rise to a coherent &#34;mixed&#34;scattering channel that drives anomalous transport over a range of temperature. I calculate

Michele Coti Zelati, Theodore D. Drivas

We provide examples of initial data which saturate the enhanced diffusion rates proved for general shear flows which are Hölder regular or Lipschitz continuous with critical points, and for regular circular flows, establishing the sharpness of those results. Our proof makes use of a probabilistic interpretation of the dissipation of solutions to the advectio

Vinay Annam, Nikhil Koditala, Radhika Mamidi

Anaphora resolution is a challenging task which has been the interest of NLP researchers for a long time. Traditional resolution techniques like eliminative constraints and weighted preferences were successful in many languages. However, they are ineffective in free word order languages like most SouthAsian languages.Heuristic and rule-based techniques were

Moshe Babaioff, Noam Nisan, Inbal Talgam-Cohen

We study competitive equilibrium in the canonical Fisher market model, but with indivisible goods. In this model, every agent has a budget of artificial currency with which to purchase bundles of goods. Equilibrium prices match between demand and supply---at such prices, all agents simultaneously get their favorite within-budget bundle, and the market clears

Pablo D. Brubeck, Yuji Nakatsukasa, Lloyd N. Trefethen

Vandermonde matrices are exponentially ill-conditioned, rendering the familiar &#34;polyval(polyfit)&#34; algorithm for polynomial interpolation and least-squares fitting ineffective at higher degrees. We show that Arnoldi orthogonalization fixes the problem.

Chong Wang, Feng Wu, Ping Ju, Shunbo Lei

The increasing extreme weather events poses unprecedented challenges on power system operation because of their uncertain and sequential impacts on power systems. This paper proposes the concept of an extended steady-state security region (ESSR), and resilience enhancement for transmission systems based on ESSR in consideration of uncertain varying topology

Aastha M. Sathe, N. S. Upadhye

In this article, we first propose the modified Hannan-Rissanen Method for estimating the parameters of the autoregressive moving average (ARMA) process with symmetric stable noise and symmetric stable generalized autoregressive conditional heteroskedastic (GARCH) noise. Next, we propose the modified empirical characteristic function method for the estimation

A. A. Kamashev, N. N. Garif&#39;yanov, A. A. Validov, J. Schumann

We report a comparative analysis and theoretical description of the superconducting properties of two spin-valve-valve structures containing the Heusler alloy Co$_2$Cr$_{1-x}$Fe$_x$Al$_{y}$ as one of two ferromagnetic (F1 or F2) layers of the F1/F2/S structure, where S stands for the superconducting Pb layer. In our experiments we used the Heusler alloy laye

Ling Luo, Dingyu Xue, Xinglong Feng

A large number of retinal vessel analysis methods based on image segmentation have emerged in recent years. However, existing methods depend on cumbersome backbones, such as VGG16 and ResNet-50, benefiting from their powerful feature extraction capabilities but suffering from high computational costs. In this paper, we propose a novel neural network (HybridN

M. A. Korolev

We obtain a new estimate for Kloosterman sum with primes $p\leqslant X$ to composite modulo $q$, that is, for the exponential sum of the type \[ \sum\limits_{p\leqslant X,\;p\,\nmid q}\exp{\biggl(\frac{2πi}{q}\bigl(a\overline{p}+bp\bigr)\,\biggr)},\quad (ab,q)=1,\quad p\overline{p}\equiv 1\pmod{q}, \] which is non-trivial in the case when $q^{\,3/4+\varepsil

Xinshao Wang, Elyor Kodirov, Yang Hua, Neil Robertson

Loss functions play a crucial role in deep metric learning thus a variety of them have been proposed. Some supervise the learning process by pairwise or tripletwise similarity constraints while others take advantage of structured similarity information among multiple data points. In this work, we approach deep metric learning from a novel perspective. We pro

Lutz Prechelt

Background: The state of the art in software engineering consists of a myriad of contributions and the gaps between them; it is difficult to characterize. Questions: In order to help understanding the state of the art, can we identify gaps in our knowledge that are at a very general, widely relevant level? Which research directions do these gaps suggest? Met

G. C. Jones, R. Maiolino, P. Caselli, S. Carniani

We report the discovery of a high-redshift, massive molecular outflow in the starburst galaxy SPT0346-52 ($z=5.656$) via the detected absorption of high-excitation water transitions (H$_2$O $4_{2,3}-4_{1,4}$ and H$_2$O $3_{3,0}-3_{2,1}$) with the Atacama Large Millimeter/submillimeter Array (ALMA). The host galaxy is one of the most powerful starburst galaxi

Mayukh Nilay Khan

We study quantum mechanics in the phase space associated with the coherent state (CS) manifold of Lie groups. Eigenstates of generators of the group are constructed as one dimensional integral superpositions of CS along their orbits. We distinguish certain privileged orbits where the superposition is in phase. Interestingly, for closed in phase orbits, the g

Pilhyeon Lee, Youngjung Uh, Hyeran Byun

Weakly-supervised temporal action localization is a very challenging problem because frame-wise labels are not given in the training stage while the only hint is video-level labels: whether each video contains action frames of interest. Previous methods aggregate frame-level class scores to produce video-level prediction and learn from video-level action lab

Barak Itkin, Lior Wolf, Nachum Dershowitz

Field archeologists are called upon to identify potsherds, for which purpose they rely on their experience and on reference works. We have developed two complementary machine-learning tools to propose identifications based on images captured on site. One method relies on the shape of the fracture outline of a sherd; the other is based on decorative features.

Sarra Ghanjeti

PPI network alignment aims to find topological and functional similarities between networks of different species. Several alignment approaches have been proposed. Each of these approaches relies on a different alignment method and uses different biological information during the alignment process such as the topological structure of the networks and the sequ

Slawomir Konrad Tadeja, Wojciech Rydlewicz, Yupu Lu, Per Ola Kristensson

Photogrammetry is a science dealing with obtaining reliable information about physical objects using their imagery description. Recent advancements in the development of Virtual Reality (VR) can help to unlock the full potential offered by the digital 3D-reality models generated using the state-of-art photogrammetric technologies. These models are becoming a

Johannes Müller, Thomas Griebel, Michael Gabb, Michael Buchholz

A reliable estimation of the communication chan-nel which connects automated vehicles is an important steptowards the safety of connected and automated vehicles. The communication channel is usually modeled as Markov chain with slowly time-varying transition rates and is identifiedthrough statistics on the observed state transitions. However, the classical i

Dominique Béroule, Pascale Gisquet-Verrier

A computational architecture is presented, in which &#34;swift and fuzzy&#34; emotional channels guide a &#34;slow and precise&#34; decision-making channel. Reported neurobiological studies first provide hints on the representation of both emotional and cognitive dimensions across brain structures, mediated by the neuromodulation system. The related model is

Chaitanya Joshi, David Rios Insua, Jesus Rios

Insider threats entail major security issues in geopolitics, cyber risk management and business organization. The game theoretic models proposed so far do not take into account some important factors such as the organisational culture and whether the attacker was detected or not. They also fail to model the defensive mechanisms already put in place by an org

K. E. Nagaev

This is a detailed derivation of the equation for the voltage noise of a resistively shunted Josephson junction with non-sinusoidal current-phase relation, which was presented in Sov. Phys. JETP {\bf 67}, 579 (1988).

Vinay Shankar, Suneel Singh, P. Anantha Lakshmi

A detailed analysis highlighting the effect of optomechanical non-linearity on the dynamical evolution of a hybrid electro-optomechanical system (EOMS) is presented. The study, conducted over a wide range of parameter regime reveals that the quadratic coupling term significantly alters the dynamics of the system and thus cannot be ignored for any potential a

Qian Hu, Jianhua Sun, Qian Zhao, Yonggang Meng

The experimentally demonstration of Casimir force transition from attraction to repulsion is still challenging. Herein, the Casimir forces for a sphere above a plate immersed in different liquids were precisely measured using Atomic force microscope, and the long-range repulsive Casimir force in the gold-cyclohexane-PTFE system is observed for the first time

Jiang Zhu, Zhennan Liu, Qi Zhang, Chunyi Song

The recovery of a low rank matrix from a subset of noisy low-precision quantized samples arises in several applications such as collaborative filtering, intelligent recommendation and millimeter wave channel estimation with few bit ADCs. In this paper, a generalized sparse Bayesian learning (Gr-SBL) combining expectation propagation (EP) is proposed to solve

Sergey Gorchinskiy

We describe the orthogonal to the group of principal ideles with respect to the global tame symbol pairing on the group of ideles of a smooth projective algebraic curve over a field.

Claudia S. Bianchini, Fabrizio Borgia, Maria de Marsico

SWift (SignWriting improved fast transcriber) is an advanced editor for SignWriting (SW). At present, SW is a promising alternative to provide documents in an easy-to-grasp written form of (any) Sign Language, the gestural way of communication which is widely adopted by the deaf community. SWift was developed SW users, either deaf or not, to support collabor

E. W. Guenther, D. Woeckel, P. Muheki

Using the Kepler K2 data, we studied the flare-activity of young K-and M-stars in the Upper Sco region and found that they have 10000 to 80000 times as many super-flares with E> 5E34 erg than solar like stars. The power-law index for flares is $N/dE~E^-1.2 for K stars, N/dE~E^-1.4 for early M-star and dN/dE~E^-1.3 for late M stars, which is about the same as

Dounia Arcens, Etienne Grau, Stéphane Grelier, Henri Cramail

Fatty acid sugar esters represent an important class of non-ionic bio-based surfactants. They can be synthesized from vinyl fatty acids and sugars with enzyme as a catalyst. Herein, the influence of the solvent, the lipase and the temperature on a model reaction between vinyl palmitate and glucose via enzymatic catalysis has been investigated and the reactio

Fabrizio Borgia, Claudia S. Bianchini, Patrice Dalle, Maria de Marsico

The SignWriting improved fast transcriber (SWift), presented in this paper, is an advanced editor for computer-aided writing and transcribing of any Sign Language (SL) using SignWriting (SW). The application is an editor which allows composing and saving desired signs using the SW elementary components, called &#34;glyphs&#34;. These make up a sort of alphab

R. Q. Wang, Z. Q. Yuan, G. H. Chen

In order to improve the precision of multi-robot SLAM multi-view target tracking process, a improved multi-robot SLAM multi-view target tracking algorithm based on panoramic vision in irregular environment was put forward, adding an correction factor to renew the existing Extended Kalman Filter (EKF) model, obtaining new coordinates X and Y after twice itera

Eike W. Guenther, Kristina G. Kislyakova

HD3167b is a transiting super-Earth that has a density which is consistent with a rocky composition. The planet is exposed to strong radiation, intense stellar wind, and likely strong tidal forces and induction heating. According to theory, planets that are so close to the star should have an atmosphere like Mercury but much more extended and denser. Other t

Zhengyuan Liu

The morphological attributes of retinal vessels, such as length, width, tortuosity and branching pattern and angles, play an important role in diagnosis, screening, treatment, and evaluation of various cardiovascular and ophthalmologic diseases such as diabetes, hypertension and arteriosclerosis. The crucial step before extracting these morphological charact

Yong Wang, Longyue Wang, Shuming Shi, Victor O. K. Li

The key challenge of multi-domain translation lies in simultaneously encoding both the general knowledge shared across domains and the particular knowledge distinctive to each domain in a unified model. Previous work shows that the standard neural machine translation (NMT) model, trained on mixed-domain data, generally captures the general knowledge, but mis

Julien Bensmail, Sandip Das, Soumen Nandi, Théo Pierron

Pushable homomorphisms and the pushable chromatic number $χ_p$ of oriented graphs were introduced by Klostermeyer and MacGillivray in 2004. They notably observed that, for any oriented graph $\overrightarrow{G}$, we have $χ_p(\overrightarrow{G}) \leq χ_o(\overrightarrow{G}) \leq 2 χ_p(\overrightarrow{G})$, where $χ_o(\overrightarrow{G})$ denotes the oriented

Matthias A. Müller

This chapter provides a concise survey on different dissipativity conditions that have appeared in the literature on economic model predictive control and discusses their decisive role in this context.

Amit K. Verma, Mandeep Singh, Ravi P. Agarwal

The regions of existence are established for a class of two point nonlinear diffusion type boundary value problems (NDBVP) \begin{eqnarray*} &&\label{abst-intr-1} -s&#39;&#39;(x)-ns&#39;(x)-\frac{m}{x}s&#39;(x)=f(x,s), \qquad m>0,~n\in \mathbb{R},\qquad x\in(0,1),\\ &&\label{abst-intr-2} s&#39;(0)=0, \qquad a_{1}s(1)+a_{2}s&#39;(1)=C, \end{eqnarray*} where $

Hungchong Kim

In this talk, we summarize our recent works on the tetraquark mixing framework for the two light-meson nonets in the $J^{PC} = 0^{++}$ channel, the light nonet [$a_0(980)$, $K_0^*(700)$, $f_0(500)$, $f_0(980)$] and the heavy nonet [$a_0(1450)$, $K_0^*(1430)$, $f_0(1370)$, $f_0(1500)$]. We briefly explain this mixing framework and present various phenomenolog

Rumeysa Bulut, Alperen Kantarcı, Safa Keskin, Şerif Bahtiyar

Traditional elections satisfy neither citizens nor political authorities in recent years. They are not fully secure since it is easy to attack votes. It threatens also privacy and transparency of voters. Additionally, it takes too much time to count the votes. This paper proposes a solution using Blockchain to eliminate all the disadvantages of conventional

Feng Cheng, Chao-Jiang Xu

In this paper, we study the problem of analyticity of smooth solutions of the inviscid Boussinesq equations. If the initial datum is real-analytic, the solution remains real-analytic on the existence interval. By an inductive method we can obtain lower bounds on the radius of spatial analyticity of the smooth solution.

Hilmi Bahadır Temur, Ahmet Serdar Yılmaz, Mehmet Tekerek

Knowledge networks can be defined as social networks that enable the transfer of the knowledge, which is defined as the intellectual product formed as a result of the work of human intelligence, to be transferred to any other means of communication. A knowledge network represents a large number of people, resources and relationships between them, to create t

Gaoqing Cao, Toru Kojo

We study the string tension $σ$ of quantum chromodynamics (QCD) in external magnetic fields $B$ by combining the quasi-particle treatments for quarks with the collective treatments for gluons. We utilize the 1/Nc-expansion (Nc: number of colors) and the framework of Wilson&#39;s strong coupling expansion at long distance, and compare the resulting string ten

Mohammed Haroon Dupty, Zhen Zhang, Wee Sun Lee

We address the problem of Visual Relationship Detection (VRD) which aims to describe the relationships between pairs of objects in the form of triplets of (subject, predicate, object). We observe that given a pair of bounding box proposals, objects often participate in multiple relations implying the distribution of triplets is multimodal. We leverage the st

Sudarshan Saha, Saptarshi Mandal

We construct and study a time reversal broken tight binding model on diamond lattice with complex next-nearest-neighbour hopping which can be thought of as a generalisation of two dimensional Haldane model in three dimension. The model also breaks inversion symmetry owing to sub-lattice dependent chemical potential. We calculate the spectrum of the model and

Nikki Lijing Kuang, Clement H. C. Leung

In the search and retrieval of multimedia objects, it is impractical to either manually or automatically extract the contents for indexing since most of the multimedia contents are not machine extractable, while manual extraction tends to be highly laborious and time-consuming. However, by systematically capturing and analyzing the feedback patterns of human

Michael Hibbard, Yagis Savas, Zhe Xu, Ufuk Topcu

We consider a scenario in which an autonomous agent carries out a mission in a stochastic environment while passively observed by an adversary. For the agent, minimizing the information leaked to the adversary regarding its high-level specification is critical in creating an informational advantage. We express the specification of the agent as a parametric l

Tapas Nayak, Hwee Tou Ng

A relation tuple consists of two entities and the relation between them, and often such tuples are found in unstructured text. There may be multiple relation tuples present in a text and they may share one or both entities among them. Extracting such relation tuples from a sentence is a difficult task and sharing of entities or overlapping entities among the

Son Doan, Nguyen Thi Ngoc Vinh, Tu Minh Phuong

Text classification is an important field of research from mid 90s up to now. It has many applications, one of them is in Web-based biosurveillance systems which identify and summarize online disease outbreak reports. In this paper we focus on classifying Vietnamese disease outbreak reports. We investigate important properties of disease outbreak reports, e.

Nikki Lijing Kuang, Clement H. C. Leung

The diversity of intrinsic qualities of multimedia entities tends to impede their effective retrieval. In a SelfLearning Search Engine architecture, the subtle nuances of human perceptions and deep knowledge are taught and captured through unsupervised reinforcement learning, where the degree of reinforcement may be suitably calibrated. Such architectural pa

Marcel Kneib, Oleg Schell, Christopher Huth

Vehicles become more vulnerable to remote attackers in modern days due to their increasing connectivity and range of functionality. Such increased attack vectors enable adversaries to access a vehicle Electronic Control Unit (ECU). As of today in-vehicle access can cause drastic consequences, because the most commonly used in-vehicle bus technology, the Cont

Arpit Bansal, Sankaraganesh Jonna, Rajiv R. Sahay

In this paper, we propose a novel method for the challenging problem of guided depth map super-resolution, called PAGNet. It is based on residual dense networks and involves the attention mechanism to suppress the texture copying problem arises due to improper guidance by RGB images. The attention module mainly involves providing the spatial attention to gui

Jian Li, Xing Wang, Baosong Yang, Shuming Shi

Recent NLP studies reveal that substantial linguistic information can be attributed to single neurons, i.e., individual dimensions of the representation vectors. We hypothesize that modeling strong interactions among neurons helps to better capture complex information by composing the linguistic properties embedded in individual neurons. Starting from this i

Evgeny Tsykunov, Ruslan Agishev, Roman Ibrahimov, Luiza Labazanova

We propose a novel system SwarmCloak for landing of a fleet of four flying robots on the human arms using light-sensitive landing pads with vibrotactile feedback. We developed two types of wearable tactile displays with vibromotors which are activated by the light emitted from the LED array at the bottom of quadcopters. In a user study, participants were ask

Amit Daniely

Many results in recent years established polynomial time learnability of various models via neural networks algorithms. However, unless the model is linear separable, or the activation is a polynomial, these results require very large networks -- much more than what is needed for the mere existence of a good predictor. In this paper we prove that SGD on dept

Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari

Recommendation is one of the critical applications that helps users find information relevant to their interests. However, a malicious attacker can infer users&#39; private information via recommendations. Prior work obfuscates user-item data before sharing it with recommendation system. This approach does not explicitly address the quality of recommendation

Wojciech Bielas, Andrzej Kucharski, Szymon Plewik

We try to explain the differences between the concepts of stratifiable space and $\varkappa$-metrizable space. In particular, we give a characterization of $\varkappa$-metrizable spaces which is modelled on Chigogidze&#39;s characterization. Moreover, we present a $\varkappa$-metric for the Niemytzki plane, using the properties of the Euclidean metric.

Kyung Ho Park, Huy Kang Kim

As a car becomes more connected, a countermeasure against automobile theft has become a significant task in the real world. To respond to automobile theft, data mining, biometrics, and additional authentication methods are proposed. Among current countermeasures, data mining method is one of the efficient ways to capture the owner driver&#39;s unique charact

Janne Heittokangas, Zinelaabidine Latreuch, Jun Wang, Mohamed Amine Zemirni

Meromorphic solutions of non-linear differential equations of the form $f^n+P(z,f)=h$ are investigated, where $n\geq 2$ is an integer, $h$ is a meromorphic function, and $P(z,f)$ is differential polynomial in $f$ and its derivatives with small functions as its coefficients. In the existing literature this equation has been studied in the case when $h$ has th

Jürgen Herzog, Takayuki Hibi

Let $K[G]$ denote the edge ring of a finite connected simple graph $G$ on $[d]$ and $\mat(G)$ the matching number of $G$. It is shown that $\reg(K[G]) \leq \mat(G)$ if $G$ is non-bipartite and $K[G]$ is normal, and that $\reg(K[G]) \leq \mat(G) - 1$ if $G$ is bipartite.

Yuji Komatsu

We study $c$-preprojective roots for a Coxeter element $c$ of infinite Coxeter group $W$. In particular, we consider the case when any positive root is $c$-preprojective for some Coxeter element $c$. In this paper, by assuming that the Coxeter graph of $W$ is cyclic, we establish that any positive root is $c$-preprojective for some Coxeter element $c$ if and

Di Deng, Wei Jing, Yuhe Fu, Ziyin Huang

There is a strong demand for covering a large area autonomously by multiple UAVs (Unmanned Aerial Vehicles) supported by a ground vehicle. Limited by UAVs&#39; battery life and communication distance, complete coverage of large areas typically involves multiple take-offs and landings to recharge batteries, and the transportation of UAVs between operation are