November 2019 arXiv papers — page 6

E. V. Castelani, R. Lopes, W. V. I. Shirabayashi, F. N. C. Sobral

The robust adjustment of nonlinear models to data is considered in this paper. When data comes from real experiments, it is possible that measurement errors cause the appearance of discrepant values, which should be ignored when adjusting models to them. This work presents a Lower Order-value Optimization (LOVO) version of the Levenberg-Marquardt algorithm,

Kazuya Nishimura, Dai Fei Elmer Ker, Ryoma Bise

Cell shape analysis is important in biomedical research. Deep learning methods may perform to segment individual cells if they use sufficient training data that the boundary of each cell is annotated. However, it is very time-consuming for preparing such detailed annotation for many cell culture conditions. In this paper, we propose a weakly supervised metho

C. Wetterich

The great emptiness is a possible beginning of the Universe in the infinite past of physical time. For the epoch of great emptiness particles are extremely rare and effectively massless. Only expectation values of fields and average fluctuations characterize the lightlike vacuum of this empty Universe. The physical content of the early stages of standard inf

Alessandra Bernardi, Martina Iannacito, Duccio Rocchini

We propose a new method to estimate plant biodiversity with R{\'e}nyi and Rao indexes through the so called High Order Singular Value Decomposition (HOSVD) of tensors. Starting from NASA multispectral images we evaluate biodiversity and we compare original biodiversity estimates with those realised via the HOSVD compression methods for big data. Our strategy

Philipp Kniefacz, Franz E. Schuster

A family of sharp $L^p$ Sobolev inequalities is established by averaging the length of $i$-dimensional projections of the gradient of a function. Moreover, it is shown that each of these new inequalities directly implies the classical $L^p$ Sobolev inequality of Aubin and Talenti and that the strongest member of this family is the only affine invariant one a

Danijel Žlaus, Domen Mongus

This paper introduces a fast Central Processing Unit (CPU) implementation of geodesic morphological operations using stream processing. In contrast to the current state-of-the-art, that focuses on achieving insensitivity to the filter sizes with efficient data structures, the proposed approach achieves efficient computation of long chains of elementary $3 \t

Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha

Interpretability is an emerging area of research in trustworthy machine learning. Safe deployment of machine learning system mandates that the prediction and its explanation be reliable and robust. Recently, it has been shown that the explanations could be manipulated easily by adding visually imperceptible perturbations to the input while keeping the model'

Ahmad Sheykhi, Saskia Grunau

We construct some new classes of topological black hole solutions in the context of mimetic gravity. We study the uncharged and charged black holes, separately. In the absence of a potential for the mimetic field, our solutions can address the flat rotation curves of spiral galaxies and alleviate the dark matter problem without invoking any kind of particle

Sebastian Risi, Julian Togelius

Procedural Content Generation (PCG) refers to the practice, in videogames and other games, of generating content such as levels, quests, or characters algorithmically. Motivated by the need to make games replayable, as well as to reduce authoring burden, limit storage space requirements, and enable particular aesthetics, a large number of PCG methods have be

Lianzi Jiang, Mingshang Hu

In this paper, we study the discrete-time approximation schemes for a class of backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) which corresponds to the hedging pricing of European contingent claims. By introducing an auxiliary extended $\widetilde{G}$-expectation space, we propose a class of $\theta$-schemes to discrete $

M. V. Korolkov, I. A. Khodasevich, A. S. Grabchikov, D. Mogilevtsev

Here we report and discuss the avalanche-like up-conversion behavior in absence of the avalanche. We experimentally observed significant changes in the slope of the curve for the intensity dependence of up-conversion luminescence of erbium ions in green band on the pump intensity of the diode laser. Such changes are typical for the photon avalanche. However,

Beibin Li, Nicholas Nuechterlein, Erin Barney, Caitlin Hudac

In genomic analysis, biomarker discovery, image recognition, and other systems involving machine learning, input variables can often be organized into different groups by their source or semantic category. Eliminating some groups of variables can expedite the process of data acquisition and avoid over-fitting. Researchers have used the group lasso to ensure

Swarnajit Chatterjee, Matthieu Mangeat, Raja Paul, Heiko Rieger

We study the active 4-state Potts model (APM) on the square lattice in which active particles have four internal states corresponding to the four directions of motion. A local alignment rule inspired by the ferromagnetic 4-state Potts model and self-propulsion via biased diffusion according to the internal particle states leads to flocking at high densities

Muhammad Haroon Shakeel, Asim Karim, Imdadullah Khan

Most studies on text classification are focused on the English language. However, short texts such as SMS are influenced by regional languages. This makes the automatic text classification task challenging due to the multilingual, informal, and noisy nature of language in the text. In this work, we propose a novel multi-cascaded deep learning model called Mc

Fedor Levkovich-Maslyuk

We give an introduction to the Quantum Spectral Curve in AdS/CFT. This is an integrability-based framework which provides the exact spectrum of planar N = 4 super Yang-Mills theory (and of the dual string model) in terms of a solution of a Riemann-Hilbert problem for a finite set of functions. We review the underlying QQ relations starting from simple spin c

Raul Martinez, Francisco Alarcon, Juan Luis Aragones, Chantal Valeriani

Asymmetric obstacles can be exploited to direct the motion and induce sorting of run-and-tumbling particles. In this work, we show that flocking particles which follow the Vicsek model aligning rules experience a collective trapping in the presence of a wall of funnels made of chevrons, concentrating at the opposite side of a wall of funnels than run-and-tum

Jayeeta Bhattacharya, Nathalie Gimenes, Emmanuel Guerre

The paper proposes a parsimonious and flexible semiparametric quantile regression specification for asymmetric bidders within the independent private value framework. Asymmetry is parameterized using powers of a parent private value distribution, which is generated by a quantile regression specification. As noted in Cantillon (2008) , this covers and extends

Wladimir Sidorenko

This thesis explores the ways by how people express their opinions on German Twitter, examines current approaches to automatic mining of these feelings, and proposes novel methods, which outperform state-of-the-art techniques. For this purpose, I introduce a new corpus of German tweets that have been manually annotated with sentiments, their targets and hold

Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony Caterini

One of the most pressing questions in climate science is that of the effect of anthropogenic aerosol on the Earth's energy balance. Aerosols provide the `seeds' on which cloud droplets form, and changes in the amount of aerosol available to a cloud can change its brightness and other physical properties such as optical thickness and spatial extent. Clouds pl

Jan Müller, Reinhard Klein, Michael Weinmann

Wasserstein-GANs have been introduced to address the deficiencies of generative adversarial networks (GANs) regarding the problems of vanishing gradients and mode collapse during the training, leading to improved convergence behaviour and improved image quality. However, Wasserstein-GANs require the discriminator to be Lipschitz continuous. In current state-

Alessandro Neri, Sven Puchinger, Anna-Lena Horlemann-Trautmann

We show that the sequence of dimensions of the linear spaces, generated by a given rank-metric code together with itself under several applications of a field automorphism, is an invariant for the whole equivalence class of the code. The same property is proven for the sequence of dimensions of the intersections of itself under several applications of a fiel

Błażej Nikiel-Wroczyński

In this work, archive 1.4 and 4.86 GHz radio continuum data from the VLA were re-reduced and, together with the 1.4 GHz maps from the NVSS, investigated for the presence of a detectable, non-thermal continuum radio emission that could be associated with the TDG candidates in HCG 26, 91, and 96. Radio emission highly coincident with the optical and $\rm H_{\a

Miguel Onorato, Giovanni Dematteis

Starting from the action-angle variables and using a standard asymptotic expansion, here we present a new derivation of the Wave Kinetic Equation for resonant process of the type $2\leftrightarrow 2$. Despite not offering new physical results and despite not being more rigorous than others, our procedure has the merit of being straightforward; it allows for

Dmitry Akimov

In this paper, we describe NeurIPS 2019 Learning to Move - Walk Around challenge physics-based environment and present our solution to this competition which scored 1303.727 mean reward points and took 3rd place. Our method combines recent advances from both continuous- and discrete-action space reinforcement learning, such as Soft Actor-Critic and Recurrent

Sebastian Cammerer, Fayçal Ait Aoudia, Sebastian Dörner, Maximilian Stark

We consider a trainable point-to-point communication system, where both transmitter and receiver are implemented as neural networks (NNs), and demonstrate that training on the bit-wise mutual information (BMI) allows seamless integration with practical bit-metric decoding (BMD) receivers, as well as joint optimization of constellation shaping and labeling. M

Raphaela Löbel, Michael Luttenberger, Helmut Seidl

A language over an alphabet $B = A \cup \overline{A}$ of opening ($A$) and closing ($\overline{A}$) brackets, is balanced if it is a subset of the Dyck language $D_B$ over $B$, and it is well-formed if all words are prefixes of words in $D_B$. We show that well-formedness of a context-free language is decidable in polynomial time, and that the longest common

Changlin Li, Jiefeng Peng, Liuchun Yuan, Guangrun Wang

Neural Architecture Search (NAS), aiming at automatically designing network architectures by machines, is hoped and expected to bring about a new revolution in machine learning. Despite these high expectation, the effectiveness and efficiency of existing NAS solutions are unclear, with some recent works going so far as to suggest that many existing NAS solut

Fabio Podestà, Alberto Raffero

We provide the complete classification of seven-dimensional manifolds endowed with a closed non-parallel G$_2$-structure and admitting a transitive reductive group G of automorphisms. In particular, we show that the center of G is one-dimensional and the manifold is the Riemannian product of a flat factor and a non-compact homogeneous six-dimensional manifol

Avner Kiro, Alon Nishry

We study fluctuations in the number of zeros of random analytic functions given by a Taylor series whose coefficients are independent complex Gaussians. When the functions are entire, we find sharp bounds for the asymptotic growth rate of the variance of the number of zeros in large disks centered at the origin. To obtain a result that holds under no assumpt

Hong Ren, Cunhua Pan, Yansha Deng, Maged Elkashlan

In URLLC, short packet transmission is adopted to reduce latency, such that conventional Shannon's capacity formula is no longer applicable, and the achievable data rate in finite blocklength becomes a complex expression with respect to the decoding error probability and the blocklength. To provide URLLC service in a factory automation scenario, we consider

J. Hanuš, P. Vernazza, M. Viikinkoski, M. Ferrais

With an estimated diameter in the 320 to 350 km range, (704) Interamnia is the fifth largest main belt asteroid and one of the few bodies that fills the gap in size between the four largest bodies with $D$ > 400 km (Ceres, Vesta, Pallas and Hygiea) and the numerous smaller bodies with $D$ $\lesssim$ 200 km. However, despite its large size, little is known ab

Krzysztof Malarz, Janusz A. Hołyst

A critical temperature for a complete signed graph of $N$ agents where time-dependent links polarization tends towards the Heider (structural) balance is found analytically using the heat-bath approach and the mean-field approximation as $T^c=(N-2)/a^c$, where $a^c\approx 1.71649$. The result is in perfect agreement with numerical simulations starting from t

Jiashan Zheng

We consider the spatially $3$-D version of the following Keller-Segel-Navier-Stokes system with rotational flux $$\left\{\begin{array}{l} n_t+u\cdot\nabla n=\Delta n-\nabla\cdot(nS(x,n,c)\nabla c),\quad x\in \Omega, t>0, c_t+u\cdot\nabla c=\Delta c-c+n,\quad x\in \Omega, t>0,\\ u_t+\kappa(u \cdot \nabla)u+\nabla P=\Delta u+n\nabla \phi,\quad x\in \Omega, t>0

Anuma Garg, Satyabrata Adhikari

We derive a criteria for the detection of $d\otimes d$ dimensional negative partial transpose (NPT) entangled state useful for teleportation. The newly derived criteria are based on the maximum eigenvalue of the NPT entangled state, which is easier to determine experimentally than to completely reconstruct the state via tomography. We then illustrate our cri

Joachim Escher, Patrik Knopf, Christina Lienstromberg, Bogdan-Vasile Matioc

We consider Euler's equations for free surface waves traveling on a body of density stratified water in the scenario when gravity and surface tension act as restoring forces. The flow is continuously stratified, and the water layer is bounded from below by an impermeable horizontal bed. For this problem we establish three equivalent classical formulations in

Bingchuan Liu, Xiaoshan Huang, Yijun Wang, Xiaogang Chen

Brain-computer interface (BCI) provides an alternative means to communicate and it has sparked growing interest in the past two decades. Specifically, for Steady-State Visual Evoked Potential based BCI, marked improvement has been made in the frequency recognition method and data sharing. However, the number of pubic database is still limited in this field.

Todor Davchev, Michael Burke, Subramanian Ramamoorthy

Context plays a significant role in the generation of motion for dynamic agents in interactive environments. This work proposes a modular method that utilises a learned model of the environment for motion prediction. This modularity explicitly allows for unsupervised adaptation of trajectory prediction models to unseen environments and new tasks by relying o

M. C. Rodriguez

In this lectures, we give a review about the Minimal Supersymmetric Standard Model (MSSM) and the General Singlet Extensions of the MSSM (GSEMSSM). We, first introduce the minimal set of fields to built both models. Then we introduce their superfields and using them we build the lagrangian of those models in the superspace formalism. We show how to get the m

Julien Monteil, Anton Dekusar, Claudio Gambella, Yassine Lassoued

The transport literature is dense regarding short-term traffic predictions, up to the scale of 1 hour, yet less dense for long-term traffic predictions. The transport literature is also sparse when it comes to city-scale traffic predictions, mainly because of low data availability. In this work, we report an effort to investigate whether deep learning models

Giuseppina Pace, Ilaria Bargigia, Yong-Young Noh, Carlos Silva

It is still a matter of controversy whether the relative difference in hole and electron transport in solution-processed organic semiconductors is either due to intrinsic properties linked to chemical and solid-state structure or to extrinsic factors, as device architecture. We here isolate the intrinsic factors affecting either electron or hole transport wi

Kai Leong Chong, Yanshen Li, Chong Shen Ng, Roberto Verzicco

We numerically investigate both single and multiple droplet dissolution with droplets consisting of lighter liquid dissolving in a denser host liquid. The significance of buoyancy is quantified by the Rayleigh number Ra which is the buoyancy force over the viscous damping force. In this study, Ra spans almost four decades from 0.1 to 400. We focus on how the

Aksel Kobiałka, Przemysław Piekarz, Andrzej M. Oleś, Andrzej Ptok

Recent experiments have shown the signatures of Majorana bound states at the ends of magnetic chains deposited on a superconducting substrate. Here, we employ first principles calculations to directly investigate the topological properties of $3d$ transition metal nanochains (i.e., Mn, Cr, Fe and Co). In contrast to the previous studies [Nadj-Perge et al. Sc

Krishna Kanth Nakka, Mathieu Salzmann

Recently, deep networks have achieved impressive semantic segmentation performance, in particular thanks to their use of larger contextual information. In this paper, we show that the resulting networks are sensitive not only to global attacks, where perturbations affect the entire input image, but also to indirect local attacks where perturbations are confi

J Antonio Rivero Ostoic

\pkg{multiplex} is a computer program that provides algebraic tools for the analysis of multiple network structures within the \proglang{R} environment. Apart from the possibility to create and manipulate multivariate data representing multiplex, signed, and two-mode networks, this package offers a collection of functions that deal with algebraic systems ---

Luc Giffon, Stéphane Ayache, Thierry Artières, Hachem Kadri

Recent work has focused on combining kernel methods and deep learning to exploit the best of the two approaches. Here, we introduce a new architecture of neural networks in which we replace the top dense layers of standard convolutional architectures with an approximation of a kernel function by relying on the Nystr{\"o}m approximation. Our approach is easy

A. Nieto, J. Escribano, F. Spill, J. M. Garcia-Aznar

Cell extravasation is a crucial step of the metastatic cascade. In this process, the circulating tumor cells inside the blood vessels adhere to the cell monolayer of the blood vessel wall and passes through it, which allows them to invade different organs and complete metastasis. In this process, it is relevant to understand how the adhesions between cells t

Yao Wang, Rui-Xue Xu, YiJing Yan

Dissipaton-equation-of-motion (DEOM) theory [Y. J. Yan, J. Chem. Phys. 140, 054105 (2014)] is an exact and nonperturbative many-particle method for open quantum systems. The existing dissipaton algebra treats also the dynamics of hybrid bath solvation coordinates. The dynamics of conjugate momentums remain to be addressed within the DEOM framework. In this w

Niclas Schneider, Gerhard Wurm

In laboratory experiments, we study the motion of levitated, sedimenting clouds of sub-mm grains at low ambient pressure and at high solid-to-gas ratios $\epsilon$. The experiments show a collective behavior of particles, i.e. grains in clouds settle faster than an isolated grain. In collective particle clouds, the sedimentation velocity linearly depends on

Marco Forgione, Dario Piga

This paper focuses on the identification of dynamical systems with tailor-made model structures, where neural networks are used to approximate uncertain components and domain knowledge is retained, if available. These model structures are fitted to measured data using different criteria including a computationally efficient approach minimizing a regularized

Peng-Li Du, Yao Wang, Rui-Xue Xu, Hou-Dao Zhang

In this work, we establish a so-called "system-bath entanglement theorem", for arbitrary systems coupled with Gaussian environments. This theorem connects the entangled system-bath response functions in the total composite space to those of local systems, as long as the interacting bath spectral densities are given. We validate the theorem with the direct ev

Axel Schild

Quantum hydrodynamics is a formulation of quantum mechanics based on the probability density and flux (current) density of a quantum system. It can be used to define trajectories which allow for a particle-based interpretation of quantum mechanics, commonly known as Bohmian mechanics. However, quantum hydrodynamics rests on the usual time-dependent formulati

Maurício Sousa, Daniel Mendes, Joaquim Jorge

New technologies allow ordinary people to access Virtual Reality at affordable prices in their homes. One of the most important tasks when interacting with immersive Virtual Reality is to navigate the virtual environments (VEs). Arguably, the best methods to accomplish this use of direct control interfaces. Among those, natural walking (NW) makes for enjoyab

Adrien Bourgoin

When dealing with highly accurate modeling of time and frequency transfers into arbitrarily moving dielectrics medium, it may be convenient to work with Gordon's optical spacetime metric rather than the usual physical spacetime metric. Additionally, an accurate modeling of the geodesic evolution of observable quantities (e.g., the range and the Doppler) requ

Björn Augner, Dieter Bothe

Every mathematical model describing physical phenomena is an approximation to model reality, hence has its limitations. Depending on characteristic values of the variables in the model, different aspects of the model and, e.g., thermodynamic mechanisms have to be emphasised, or may be neglected in a reduced limit model. Within this paper, a heterogeneous cat

Fufang Wen, Jiaqi Jiang, Jonathan A. Fan

Generative adversarial networks, which can generate metasurfaces based on a training set of high performance device layouts, have the potential to significantly reduce the computational cost of the metasurface design process. However, basic GAN architectures are unable to fully capture the detailed features of topologically complex metasurfaces, and generate

Lingzhen Guo, Anton Frisk Kockum, Florian Marquardt, Göran Johansson

We investigate the relaxation dynamics of a single artificial atom interacting, via multiple coupling points, with a continuum of bosonic modes (photons or phonons) in a one-dimensional waveguide. In the non-Markovian regime, where the travelling time of a photon or phonon between the coupling points is sufficiently large compared to the inverse of the bare

Robert Speck, Michael Knobloch, Sebastian Lührs, Andreas Gocht

While many ideas and proofs of concept for parallel-in-time integration methods exists, the number of large-scale, accessible time-parallel codes is rather small. This is often due to the apparent or subtle complexity of the algorithms and the many pitfalls awaiting developers of parallel numerical software. One example of such a time-parallel code is pySDC,

B. Golli

Our recently proposed model of the $\Delta(1600)$ resonance, in which the dominant component is a quasi-bound state of the $\Delta(1232)$ and the pion, is confronted with a similar model of the $N^*(1440)$ resonance as its counterpart in the P11 partial wave. We stress an essentially different mechanism responsible for generating the two resonances.

Qingyin Ma, John Stachurski

We propose a new approach to solving dynamic decision problems with rewards that are unbounded below. The approach involves transforming the Bellman equation in order to convert an unbounded problem into a bounded one. The major advantage is that, when the conditions stated below are satisfied, the transformed problem can be solved by iterating with a contra

Timotheus Kampik, Juan Carlos Nieves

Abstract argumentation has emerged as a method for non-monotonic reasoning that has gained popularity in the symbolic artificial intelligence community. In the literature, the different approaches to abstract argumentation that were refined over the years are typically evaluated from a formal logics perspective; an analysis that is based on models of economi

Mattia Dalla Brida, Leonardo Giusti, Michele Pepe

We present a new theoretical and practical strategy to renormalize non-perturbatively the energy-momentum tensor in lattice QCD based on the framework of shifted boundary conditions. As a preparatory step for the fully non-perturbative calculation, we apply the strategy at 1-loop order in perturbation theory determining the renormalization constants of both

Yiwen Ding

We study the adjunction property of the Jacquet-Emerton functor in certain neighborhoods of critical points in the eigencurve. As an application, we construct two-variable $p$-adic $L$-functions around critical points via Emerton's representation theoretic approach.

Marco Forgione, Dario Piga, Alberto Bemporad

Model Predictive Control (MPC) is a powerful and flexible design tool of high-performance controllers for physical systems in the presence of input and output constraints. A challenge for the practitioner applying MPC is the need of tuning a large number of parameters such as prediction and control horizons, weight matrices of the MPC cost function, and obse

Maxim Goncharov, Vsevolod Gubarev

We classify all Rota-Baxter operators of nonzero weight on the matrix algebra of order three over an algebraically closed field of characteristic zero which are not arisen from the decompositions of the entire algebra into a direct vector space sum of two subalgebras.

Minsoo Kang, Jonghwan Mun, Bohyung Han

We present a novel framework of knowledge distillation that is capable of learning powerful and efficient student models from ensemble teacher networks. Our approach addresses the inherent model capacity issue between teacher and student and aims to maximize benefit from teacher models during distillation by reducing their capacity gap. Specifically, we empl

Antonio Quintero-Rincón, Catalina Carenzo, Joaquín Ems, Lourdes Hirschson

Epilepsy is an important public health issue. An appropriate epileptiform discharge pattern detection of this neurological disease is a typical problem in biomedical engineering. In this paper, a new method is proposed for spike-and-wave discharge pattern detection based on Kendall's Tau-b coefficient. The proposed approach is demonstrated on a real dataset

Seongjoong Kim, Sanemichi Takahashi, Hideko Nomura, Takashi Tsukagoshi

We observe the dust continuum at 225 GHz and CO isotopologue (12CO, 13CO, and C18O) J=2-1 emission lines toward the CR Cha protoplanetary disk using the Atacama Large Millimeter/Submillimeter Array (ALMA). The dust continuum image shows a dust gap-ring structure in the outer region of the dust disk. A faint dust ring is also detected around 120 au beyond the

L. Tolos, J. Nieves, R. Pavao

Recently five $\Omega_c$ excited states have been reported by the LHCb Collaboration, four of them corroborated by Belle. The Belle Collaboration has also discovered in 2017 one excited $\Xi_c$ with mass of 2930 MeV. In view of these recent detections, we analyze the possible molecular description of these states, using a unitarized baryon-meson model that i

Weina Wu, Jianliang Zhai

In this paper, we establish the large deviation principles for stochastic porous media equations driven by time-dependent multiplicative noise on $\sigma$-finite measure space $(E,\mathcal{B}(E),\mu)$, and the Laplacian replaced by a negative definite self-adjoint operator. The coefficient is only assumed to satisfy the increasing Lipschitz nonlinearity assu

Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian

A groundswell of recent work has focused on improving data management systems with learned components. Specifically, work on learned index structures has proposed replacing traditional index structures, such as B-trees, with learned models. Given the decades of research committed to improving index structures, there is significant skepticism about whether le

K. Manes, I. Tasoulas, A. Sapounakis, P. Tsikouras

In this paper, a natural bijection between multichains of binary paths and shifted tableaux is presented, and it is used for the enumeration of the chains with maximum length from a given path $P$ to the maximum path $\mathbf{1}_{|P|}$. By mapping chains to shifted tableaux, the main formulas given in a recent paper by the authors for the enumeration of the

Gionni Marchetti, Marco Patriarca, Els Heinsalu

We present a novel Bayesian approach to semiotic dynamics, which is a cognitive analogue of the naming game model restricted to two conventions. The one-shot learning that characterizes the agent dynamics in the basic naming game is replaced by a word-learning process, in which agents learn a new word by generalizing from the evidence garnered through pairwi

Bryar A. Hassan, Tarik A. Rashid

The experiments conducted in previous studies demonstrated the successful performance of BSA and its non-sensitivity toward the several types of optimisation problems. This success of BSA motivated researchers to work on expanding it, e.g., developing its improved versions or employing it for different applications and problem domains. However, there is a la

Minseok Choi, Andreas F. Molisch, Joongheon Kim

In wireless caching networks, the design of the content delivery method must consider random user requests, caching states, network topology, and interference management. In this paper, we establish a general framework for content delivery in wireless caching networks without stringent assumptions that restrict the network structure, delivery link, and inter

Giulio Baù, Javier Roa

We present a new method for computing orbits in the perturbed two-body problem: the position and velocity vectors of the propagated object in Cartesian coordinates are replaced by eight orbital elements, i.e., constants of the unperturbed motion. The proposed elements are uniformly valid for any value of the total energy. Their definition stems from the idea

Manuel Lopes, Francisco Melo

In this paper we propose the first machine teaching algorithm for multiple inverse reinforcement learners. Specifically, our contributions are: (i) we formally introduce the problem of teaching a sequential task to a heterogeneous group of learners; (ii) we identify conditions under which it is possible to conduct such teaching using the same demonstration f

Wenpeng Li, Yongli Sun, Jinjun Wang, Han Xu

Jointly utilizing global and local features to improve model accuracy is becoming a popular approach for the person re-identification (ReID) problem, because previous works using global features alone have very limited capacity at extracting discriminative local patterns in the obtained feature representation. Existing works that attempt to collect local pat

Petteri Harjulehto, Jonne Juusti

We study minimizers of the Dirichlet phi-energy integral with generalized Orlicz growth. We prove the Kellogg property, the set of irregular points has zero capacity, and give characterizations of semiregular boundary points. The results are new ever for the special cases double phase and Orlicz growth.

Aleksei F. Ber, Matthijs J. Borst, Fedor A. Sukochev

In [7], Kwapie\'{n} announced that every mean zero function $f\in L_\infty[0,1]$ can be written as a coboundary $f = g\circ T -g$ for some $g\in L_\infty[0,1]$ and some measure preserving transformation $T$ of $[0,1]$. Whereas the original proof in [7] holds for continuous functions, there is a serious gap in the proof for functions with discontinuities. In

K. Altwegg, H. Balsiger, J. -J. Berthelier, C. Briois

Cometary comae are generally depleted in nitrogen. The main carriers for volatile nitrogen in comets are NH3 and HCN. It is known that ammonia readily combines with many acids like e.g. HCN, HNCO, HCOOH, etc. encountered in the interstellar medium as well as in cometary ice to form ammonium salts (NH4+X-) at low temperatures. Ammonium salts, which can play a

Maksim Jenihhin, Said Hamdioui, Matteo Sonza Reorda, Milos Krstic

The recent trends for nanoelectronic computing systems include machine-to-machine communication in the era of Internet-of-Things (IoT) and autonomous systems, complex safety-critical applications, extreme miniaturization of implementation technologies and intensive interaction with the physical world. These set tough requirements on mutually dependent extra-

Wei Wang, Lihong Qiu, Jianguo Qian, Wei Wang

A mixed graph $G$ is a graph obtained from a simple undirected graph by orientating a subset of edges. $G$ is self-converse if it is isomorphic to the graph obtained from $G$ by reversing each directed edge. For two mixed graphs $G$ and $H$ with Hermitian adjacency matrices $A(G)$ and $A(H)$, we say $G$ is $\mathbb{R}$\emph{-cospectral} to $H$ if, for any $y

Laurent Baratchart, Sébastien Fueyo, Gilles Lebeau, Jean-Baptiste Pomet

We give a sufficient condition for exponential stability of a network of lossless telegrapher's equations, coupled by linear time-varying boundary conditions. The sufficient conditions is in terms of dissipativity of the couplings, which is natural for instance in the context of microwave circuits. Exponential stability is with respect to any $L^p$-norm, $1\

Shaoli Wang, Xiyan Bai, Fei Xu

In this paper, we consider a SIRS model with general nonmonotone and saturated incidence rate and perform stability and bifurcation analysis. We show that the system has saddle-node bifurcation and displays bistable behavior. We obtain the critical thresholds that characterize the dynamical behaviors of the model. We find with surprise that the system always

J. Kluson

We study T-duality with non-zero components of NSNS two form field along directions we dualize with the help of canonical formalism. As a result of this procedure we determine generalized Buscher's rules. We also apply the same procedure to the case of non-relativistic string.

Daniel Räde

Inspired by Gromov's work on 'Metric inequalities with scalar curvature' we establish band width inequalities for Riemannian bands of the form $(V=M\times[0,1],g)$, where $M^{n-1}$ is a closed manifold. We introduce a new class of orientable manifolds we call filling enlargeable and prove: If $M$ is filling enlargeable and all unit balls in the universal cov

Ayumu Kuwahara, Hiroyuki Kurokawa

The pebble accretion model has the potential to explain the formation of various types of planets. A growing planet embedded in a disk induces three-dimensional (3D) gas flow, which may influence pebble accretion. In this study, we investigate the influence of the 3D planet-induced gas flow on pebble accretion. Assuming a non-isothermal, inviscid gas disk, w

Morris Podolak, Nader Haghighipour, Peter Bodenheimer, Ravit Helled

We present results of a detailed study of the rate of the accretion of planetesimals by a growing proto-Jupiter in the core-accretion model. Using a newly developed code, we accurately combine a detailed three-body trajectory calculation with gas drag experienced during the passage of planetesimals in the protoplanet's envelope. We find that the motion of pl

Fernando H. C. Dias, Hassan Hijazi, David Rey

We address the aircraft conflict resolution problem in air traffic control. We introduce new mixed-integer programming formulations for aircraft conflict resolution with speed, heading and altitude control which are based on disjunctive linear separation conditions. We first examine the two-dimensional aircraft conflict resolution problem with speed and head

Hoger Ghahramani, Wania Khodakarami, Esmaeil Feizi

Let A be a Banach algebra and I be a closed ideal of A. We say that A is amenable relative to I, if A/I is an amenable Banach algebra. We study the relative amenability of Banach algebras and investigate the relative amenability of triangular Banach algebras and Banach algebras associated to locally compact groups. We generalize some of the previous known re

Robert Ganian, Neha Lodha, Sebastian Ordyniak, Stefan Szeider

In this paper we propose, implement, and test the first practical decomposition algorithms for the width parameters treecut width and treedepth. These two parameters have recently gained a lot of attention in the theoretical research community as they offer the algorithmic advantage over treewidth by supporting so-called fixed-parameter algorithms for certai

Khaled Masoumifard

In this paper, we investigate stochastic comparisons of parallel systems, and obtain two characterization results in this regard. First, we compare a parallel system with independent heterogeneous components to a parallel system with homogeneous components, and establish some certain assumptions under which the hazard rate and usual stochastic orders between

Ivan Beschastnyi, Ugo Boscain, Mario Sigalotti

In this article we discuss which controllability properties of classical Hamiltonian systems are preserved after quantization. We discuss some necessary and some sufficient conditions for small-time controllability of classical systems and quantum systems using the WKB method. In particular, we investigate the conjecture that if the classical system is not s

Sethu Hareesh Kolluru

In this work, the task of pixel-wise semantic segmentation in the context of self-driving with a goal to reduce the inference time is explored. Fully Convolutional Network (FCN-8s, FCN-16s, and FCN-32s) with a VGG16 encoder architecture and skip connections is trained and validated on the Cityscapes dataset. Numerical investigations are carried out for sever

Ł. Pawelec

We show a new method of estimating the Hausdorff measure (of the proper dimension) of a fractal set from below. The method requires computing the subsequent closest return times of a point to itself.

Dmitrii E. Vavilov

This paper presents a robust linear method for impact probability estimation of near-Earth asteroids with the Earth. This method is a significantly modified and improved method, which uses a special curvilinear coordinate system associated with the nominal orbit of an asteroid. One of the coordinates of this system is the mean anomaly in the osculating orbit

Jung Hyun Lee, Jihun Yun, Sung Ju Hwang, Eunho Yang

Network quantization, which aims to reduce the bit-lengths of the network weights and activations, has emerged as one of the key ingredients to reduce the size of neural networks for their deployments to resource-limited devices. In order to overcome the nature of transforming continuous activations and weights to discrete ones, recent study called Relaxed Q

Junpeng Zhang, Xiuping Jia, Jiankun Hu, Jocelyn Chanussot

Inspired by the recent developments in computer vision, low-rank and structured sparse matrix decomposition can be potentially be used for extract moving objects in satellite videos. This set of approaches seeks for rank minimization on the background that typically requires batch-based optimization over a sequence of frames, which causes delays in processin

Sang Won Bae, Sang Duk Yoon

This paper studies empty squares in arbitrary orientation among a set $P$ of $n$ points in the plane. We prove that the number of empty squares with four contact pairs is between $\Omega(n)$ and $O(n^2)$, and that these bounds are tight, provided $P$ is in a certain general position. A contact pair of a square is a pair of a point $p\in P$ and a side $\ell$

Tao Zeng, Hu Wang, Mengzhu Yang, Joe Alexandersen

With the increasing power density of electronics components, the heat dissipation capacity of heat sinks gradually becomes a bottleneck. Many structural optimization methods, including topology optimization, have been widely used for heat sinks. Due to its high design freedom, topology optimization is suggested for the design of heat sinks using a transient