March 2020 arXiv papers — page 80

Andrea Carracedo Rodriguez, Linus Balicki, Serkan Gugercin

The AAA algorithm has become a popular tool for data-driven rational approximation of single variable functions, such as transfer functions of a linear dynamical system. In the setting of parametric dynamical systems appearing in many prominent applications, the underlying (transfer) function to be modeled is a multivariate function. With this in mind, we de

Bingtao Ma, Hongsen Liu, Liangliang Nan, Yang Cong

The 3D mesh is an important representation of geometric data. In the generation of mesh data, geometric deficiencies (e.g., duplicate elements, degenerate faces, isolated vertices, self-intersection, and inner faces) are unavoidable and may violate the topology structure of an object. In this paper, we propose an effective and efficient geometric deficiency

Junfan Lin, Keze Wang, Ziliang Chen, Xiaodan Liang

Medical diagnosis assistant (MDA) aims to build an interactive diagnostic agent to sequentially inquire about symptoms for discriminating diseases. However, since the dialogue records used to build a patient simulator are collected passively, the data might be deteriorated by some task-unrelated biases, such as the preference of the collectors. These biases

Daniela Calvetti, Monica Pragliola, Erkki Somersalo

The recovery of sparse generative models from few noisy measurements is an important and challenging problem. Many deterministic algorithms rely on some form of $\ell_1$-$\ell_2$ minimization to combine the computational convenience of the $\ell_2$ penalty and the sparsity promotion of the $\ell_1$. It was recently shown within the Bayesian framework that sp

Jung Heon Song, Matthias Maier, Mitchell Luskin

We discuss a quartic eigenvalue problem arising in the context of an optical waveguiding problem involving atomically thick 2D materials. The waveguide configuration we consider consists of a gradient-index (spatially dependent) dielectric equipped with conducting interior interfaces. This leads to a quartic eigenvalue problem with mixed transverse electric

David Pastor-Escuredo

Ethics is an ancient matter for human kind, from the origin of civilizations ethics have been related with the most relevant human concerns and determined cultures. Ethics was initially related to religion, politics and philosophy to then be fragmented into specific communities of practice. The undergoing digital revolution enabled by Artificial Intelligence

Simon Lentner, Svea Nora Mierach, Christoph Schweigert, Yorck Sommerhaeuser

Given a finite modular tensor category, we associate with each compact surface with boundary a cochain complex in such a way that the mapping class group of the surface acts projectively on its cohomology groups. In degree zero, this action coincides with the known projective action of the mapping class group on the space of chiral conformal blocks. In the c

David A. Croydon, Makiko Sasada

We deduce a generalized hydrodynamic limit for the box-ball system, which explains how the densities of solitons of different sizes evolve asymptotically under Euler space-time scaling. To describe the limiting soliton flow, we introduce a continuous state-space analogue of the soliton decomposition of Ferrari, Nguyen, Rolla and Wang (cf. the original work o

Amirhosein Mojavezi, Reza Moazzemi, Mohammad Ebrahim Zomorrodian

$ $In this paper we present a systematic treatment for fundamental renormalization of quantum electrodynamics in real space. Although the standard renormalization is an old school problem in this case, it has not yet been completely done in position space. The most important difference with well-known differential renormalization is that we do the whole proc

Agnieszka Grabska-Barwińska

The ability of to explain neural network decisions goes hand in hand with their safe deployment. Several methods have been proposed to highlight features important for a given network decision. However, there is no consensus on how to measure effectiveness of these methods. We propose a new procedure for evaluating explanations. We use it to investigate visu

Riccardo Marin, Arianna Rampini, Umberto Castellani, Emanuele Rodolà

We introduce the first learning-based method for recovering shapes from Laplacian spectra. Given an auto-encoder, our model takes the form of a cycle-consistent module to map latent vectors to sequences of eigenvalues. This module provides an efficient and effective linkage between spectrum and geometry of a given shape. Our data-driven approach replaces the

Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee, Sarah Cherng

Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data prevent widespread practice of scalable EHR-based stratification analysis. Here we present an unsupervised framework based on deep learning to process heterogeneous EHRs and derive p

Le Anh Vu, Duong Quang Hoa, Nguyen Minh Tri, Ha Van Hieu

In recent decades, we have known some interesting applications of Lie theory in the theory of technological progress. Firstly, we will discuss some results of R. Saito in \cite{rS1980} and \cite{rS1981} about the application modeling of Lie groups in the theory of technical progress. Next, we will describe the result on Romanian economy of G. Zaman and Z. Go

M. Cheng, F. Fang, C. C. Pain, I. M. Navon

Considering the high computation cost produced in conventional computation fluid dynamic simulations, machine learning methods have been introduced to flow dynamic simulations in recent years. However, most of studies focus mainly on existing fluid fields learning, the prediction of spatio-temporal nonlinear fluid flows in varying parameterized space has bee

Mojtaba Noghabaei, Kevin Han

Unmanaged hazards in dangerous construction environments proved to be one of the main sources of injuries and accidents. Hazard recognition is crucial to achieve effective safety management and reduce injuries and fatalities in hazardous job sites. Still, there has been lack of effort that can efficiently assist workers in improving their hazard recognition

Mengjiao Hu, Kang Sim, Juan Helen Zhou, Xudong Jiang

Convolutional Neural Network (CNN) has been successfully applied on classification of both natural images and medical images but not yet been applied to differentiating patients with schizophrenia from healthy controls. Given the subtle, mixed, and sparsely distributed brain atrophy patterns of schizophrenia, the capability of automatic feature learning make

Stanislav Katina, Liberty Vittert, Adrian W. Bowman

The advent of high resolution imaging has made data on surface shape widespread. Methods for the analysis of shape based on landmarks are well established but high resolution data require a functional approach. The starting point is a systematic and consistent description of each surface shape. Three innovative forms of analysis are then introduced. The firs

Poorna Chandra Tejasvi, Vasanth Rajaraman, Arun Babu Puthuparambil, Akhil Pankaj

With the massive increase in the number of IoT devices being deployed in smart cities, it becomes paramount for middlewares to be able to handle very high loads and support demanding use-cases. In order to do so, middlewares must scale horizontally while providing a commensurate increase in availability and throughput. Currently, most open-source IoT middlew

Yong-Liang Xiao, Rongguang Liang, Jianxin Zhong, Xianyu Su

Realization of deep learning with coherent optical field has attracted remarkably attentions presently, which benefits on the fact that optical matrix manipulation can be executed at speed of light with inherent parallel computation as well as low latency. Photonic neural network has a significant potential for prediction-oriented tasks. Yet, real-value Back

Saheb Soroushfar, Sudhaker Upadhyay

We provide a description of a thin accretion disc for a static spherically symmetric black holes in $f(R)$ gravity. In this regard, we first study the horizons of black holes in $f(R)$ gravity. The equation of motion and effective potential are also computed which eventually leads to possible existence of innermost circular orbits of accretion disc. We deriv

A. M. Ishkhanyan, G. Lévai

We examine the conditions under which the solution of the radial stationary Schrödinger equation for the sextic anharmonic oscillator can be expanded in terms of Hermite functions. We find that this is possible for an infinite hierarchy of potentials discriminated by the parameter setting the strength of the centrifugal barrier. The $N$'th member of the

Riccardo Fazio

In a transformation method, the numerical solution of a given boundary value problem is obtained by solving one or more related initial value problems. Therefore, a transformation method, like a shooting method, is an initial value method. The main difference between a transformation and a shooting method is that the former is conceived and derive its formul

Riccardo Fazio

The Blasius flow is the idealized flow of a viscous fluid past an infinitesimally thick, semi-infinite flat plate. The definition of a non-iterative transformation method for the celebrated Blasius problem is due to T{ö}pfer and dates more than a century ago. Here we define a non-iterative transformation method for Blasius equation with a moving wall, a slip

Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar

This paper demonstrates that false data injection (FDI) attacks are extremely limited in their ability to cause physical consequences on $N-1$ reliable power systems operating with real-time contingency analysis (RTCA) and security constrained economic dispatch (SCED). Prior work has shown that FDI attacks can be designed via an attacker-defender bi-level li

Eric G. Blackman

How well do current combat helmets protect against Traumatic Brain Injury? To answer this question it is necessary to evaluate both the measures and standards of protection. We define measure as a physical test that the helmet must be subject to and the standard as the quantitative threshold of performance in this test that the helmet must satisfy to be acce

Ognjen Milatovic, Hemanth Saratchandran

We give sufficient conditions for the essential self-adjointness of perturbed biharmonic operators acting on sections of a Hermitian vector bundle over a Riemannian manifold with additional assumptions, such as lower semi-bounded Ricci curvature or bounded sectional curvature. In the case of lower semi-bounded Ricci curvature, we formulate our results in ter

Nan Bi, Hyunseung Kang, Jonathan Taylor

A common practice in IV studies is to check for instrument strength, i.e. its association to the treatment, with an F-test from regression. If the F-statistic is above some threshold, usually 10, the instrument is deemed to satisfy one of the three core IV assumptions and used to test for the treatment effect. However, in many cases, the inference on the tre

Mohsen Kheirandishfard, Fariba Zohrizadeh, Farhad Kamangar

Adversarial adaptation models have demonstrated significant progress towards transferring knowledge from a labeled source dataset to an unlabeled target dataset. Partial domain adaptation (PDA) investigates the scenarios in which the source domain is large and diverse, and the target label space is a subset of the source label space. The main purpose of PDA

U. van Kolck

Ever since quantum field theory was first applied to the derivation of nuclear forces in the mid-20th century, the renormalization of pion exchange with realistic couplings has presented a challenge. The implementation of effective field theories (EFTs) in the 1990s promised a solution to this problem but unexpected obstacles were encountered. The response o

Ashesh Ghosh, Kenneth S. Schweizer

We theoretically study thermally activated elementary dynamical processes that precede full structural relaxation in ultra-dense particle liquids interacting via strong short range attractive forces. Our approach is based on a microscopic theory formulated at the particle trajectory level built on the dynamic free energy concept and an explicit treatment of

Wentao Cai, Haosen Wen, H. Alan Beadle, Chris Kjellqvist

The proliferation of fast, dense, byte-addressable nonvolatile memory suggests that data might be kept in pointer-rich "in-memory" format across program runs and even process and system crashes. For full generality, such data requires dynamic memory allocation, and while the allocator could in principle "rolled into" each data structure, it i

Saheb Soroushfar, Sudhaker Upadhyay

In order to study the phase transition through thermodynamic geometry, we consider the charged AdS black hole with global monopole. We first introduce thermodynamics of charged AdS black hole with global monopole by discussing the dependence of Hawking temperature, specific heat and P-v curve on horizon radius and monopole parameter. By implementing various

Rodrigo Nogueira, Zhiying Jiang, Jimmy Lin

This work proposes a novel adaptation of a pretrained sequence-to-sequence model to the task of document ranking. Our approach is fundamentally different from a commonly-adopted classification-based formulation of ranking, based on encoder-only pretrained transformer architectures such as BERT. We show how a sequence-to-sequence model can be trained to gener

Arman Nedjatia, Béla Vizvárib

This study investigates the problem of traveling salesman problem with circular neighborhood (TSPCN). Instead of cities there are circles and each point on circle can be a potential visiting node. The problem is to find the minimum length Hamiltonian cycle connecting the circles. Among the various real life applications of the problem, this paper concentrate

Georgios Karagiannis, Mohammed Saeed, Paolo Papotti, Immanuel Trummer

Organizations such as the International Energy Agency (IEA) spend significant amounts of time and money to manually fact check text documents summarizing data. The goal of the Scrutinizer system is to reduce verification overheads by supporting human fact checkers in translating text claims into SQL queries on an associated database. Scrutinizer coordinates

Djordje Batic, Dubravko Culibrk

We present the results of an initial study focused on developing a visual AI solution able to recognize individual dogs in unconstrained (wild) images occurring on social media. The work described here is part of joint project done with Pet2Net, a social network focused on pets and their owners. In order to detect and recognize individual dogs we combine tra

S. Ostadnezhad, Gh. Forozani, M. Ghanaatian

New V-band CCD observations of variable star V2455 Cyg were performed during two nights in September 2017. According to all times of maximum light and new maxima, the O-C curve was analyzed. The period changes of V2455 Cyg were investigated and the rate of increasing period was obtained to be(1/p* dp/dt) = 1.99 *10^(-7) yr^(-1). Frequency analysis indicated

Siluvai Antony Selvan, Sukhendu Ghosh, Harekrushna Behera, Michael H. Meylan

Hydrodynamic instability of a gravity-driven flow down an inclined plane is investigated in the presence of a floating elastic plate which rests on the top surface of the flow. Linear instability of the system with respect to infinitesimal disturbances is captured using normal-mode analysis. The critical conditions for instability are obtained analytically u

Cristiana De Filippis, Francesco Leonetti

Fix any two numbers $p$ and $q$, with $1<p<q$; we give an example of an integral functional enjoying uniform ellipticity and $p$-$q$ growth.

Maria T. Nyamukuru, Kofi M. Odame

There is a growing interest in low power highly efficient wearable devices for automatic dietary monitoring (ADM) [1]. The success of deep neural networks in audio event classification problems makes them ideal for this task. Deep neural networks are, however, not only computationally intensive and energy inefficient but also require a large amount of memory

Carsten Habenicht, Jochen Simon, Manuel Richter, Roman Schuster

We have studied potassium-intercalated bulk HfS$_2$ and HfSe$_2$ by combining transmission electron energy loss spectroscopy, angle-resolved photoemission spectroscopy and density functional theory calculations. Calculations of the formation energies and the evolution of the energies of the charge carrier plasmons as a function of the potassium content show

Gilmarie O&#39;Neill, Matthew Ball, Yujing Liu, Mojtaba Noghabaei

To adhere to the stringent time and budget requirements of construction projects, contractors are utilizing prefabricated construction methods to expedite the construction process. Prefabricated construction methods require an adequate schedule and understanding by the contractors and constructors to be successful. The specificity of prefabricated constructi

Trisha Mittal, Pooja Guhan, Uttaran Bhattacharya, Rohan Chandra

We present EmotiCon, a learning-based algorithm for context-aware perceived human emotion recognition from videos and images. Motivated by Frege&#39;s Context Principle from psychology, our approach combines three interpretations of context for emotion recognition. Our first interpretation is based on using multiple modalities(e.g. faces and gaits) for emoti

Paweł Gawrychowski, Wojciech Janczewski, Jakub Łopuszański

A routing labeling scheme assigns a binary string, called a label, to each node in a network, and chooses a distinct port number from $\{1,\ldots,d\}$ for every edge outgoing from a node of degree $d$. Then, given the labels of $u$ and $w$ and no other information about the network, it should be possible to determine the port number corresponding to the firs

Yanglin Zhu, Bahadur Singh, Yu Wang, Cheng-Yi Huang

We have investigated magnetotransport properties and the topological electronic structure of the half-Heusler compound TbPtBi. Our experiments reveal an exceptionally large anomalous Hall effect (AHE) in the canted antiferromagnetic state of TbPtBi with the anomalous Hall angle (AHA) reaching ~0.68-0.76, which is a few times larger than the previously report

Carlo Rovelli

I study the physical nature of traces (or memories). Surprisingly, (i) systems separation with (ii) temperature differences and (iii) long thermalization times, are sufficient conditions to produce macroscopic traces. Traces of the past are ubiquitous because these conditions are largely satisfied in our universe. I quantify these thermodynamical conditions

Zack Hodari, Catherine Lai, Simon King

In English, prosody adds a broad range of information to segment sequences, from information structure (e.g. contrast) to stylistic variation (e.g. expression of emotion). However, when learning to control prosody in text-to-speech voices, it is not clear what exactly the control is modifying. Existing research on discrete representation learning for prosody

Mahsa Torfeh, Amir Arbabi

Metasurfaces are arrays of subwavelength meta-atoms that shape waves in a compact and planar form factor. Analysis and design of metasurfaces require methods for modeling their interactions with waves. Conventional modeling techniques assume that metasurfaces are locally periodic structures excited by plane waves, restricting their applicability to gradually

Wenjie Dou, Jakob Bätge, Amikam Levy, Michael Thoss

We present an approach based on a density matrix expansion to study thermodynamic properties of a quantum system strongly coupled to two or more baths. For slow external driving of the system, we identify the adiabatic and nonadiabatic contributions to thermodynamic quantities, and we show how the first and second laws of thermodynamics are manifested in the

Santosh Devasia

How a network gets to the goal (a consensus value) can be as important as reaching the consensus value. While prior methods focus on rapidly getting to a new consensus value, maintaining cohesion, during the transition between consensus values or during tracking, remains challenging and has not been addressed. The main contributions of this work are to addre

Xiaohuan Xue

Hedges&#39; unbiased estimator g* has been broadly used in statistics. We propose a sequence of polynomials to better approximate the multiplicative correction factor of g* by incorporating analytic estimations to the ratio of gamma functions.

A. V. Ivanov, D. V. Vassilevich

We consider the index of a Dirac operator on a compact even dimensional manifold with a domain wall. The latter is defined as a co-dimension one submanifold where the connection jumps. We formulate and prove an analog of the Atiyah-Patodi-Singer theorem that relates the index to the bulk integral of Pontryagin density and $η$-invariants of auxiliary Dirac op

S. D. Odintsov, V. K. Oikonomou

We provide a compact review on recent developments on axion $F(R)$ gravity. The axion field is a string theory originating theoretical particle that is a perfect candidate for low-mass particle dark matter. In this review we present how a viable inflationary phenomenology and a viable late-time evolution can be described by an axion $F(R)$ gravity theory, in

Moshe Lichtenstein, Prasanna Sattigeri, Rogerio Feris, Raja Giryes

The field of Few-Shot Learning (FSL), or learning from very few (typically $1$ or $5$) examples per novel class (unseen during training), has received a lot of attention and significant performance advances in the recent literature. While number of techniques have been proposed for FSL, several factors have emerged as most important for FSL performance, awar

Vasily Klimov

The exact analytical solution of Maxwell equations for a Bessel light beam scattered by a sphere is found. Scattered power, stored energy and a generalized Q factor as a function of frequency, the sphere radius, permittivity, and the Bessel beam angle are found. On the base of this solution, modes and pseudo-modes of a dielectric sphere are extracted by calc

Daisuke Ida

The equation of motion for comohogeneity-one Nambu-Goto strings in flat space $\mathbb{R}^{n,1}$ has been investigated. We first classify possible forms of the Killing vector fields in $\mathbb{R}^{n,1}$ after appropriate action of the Poincaré group. Then, all possible forms of the Hamiltonian for the cohomogeneity-one Nambu-Goto strings are determined. It

Raphaël Raynaud, Jérôme Guilet, Hans-Thomas Janka, Thomas Gastine

The release of spin-down energy by a magnetar is a promising scenario to power several classes of extreme explosive transients. However, it lacks a firm basis because magnetar formation still represents a theoretical challenge. Using the first three-dimensional simulations of a convective dynamo based on a protoneutron star interior model, we demonstrate tha

Thomas Kerdreux, Louis Thiry, Erwan Kerdreux

We present interactive painting processes in which a painter and various neural style transfer algorithms interact on a real canvas. Understanding what these algorithms&#39; outputs achieve is then paramount to describe the creative agency in our interactive experiments. We gather a set of paired painting-pictures images and present a new evaluation methodol

Davide Berghi, Hanne Stenzel, Marco Volino, Adrian Hilton

Immersive audio-visual perception relies on the spatial integration of both auditory and visual information which are heterogeneous sensing modalities with different fields of reception and spatial resolution. This study investigates the perceived coherence of audiovisual object events presented either centrally or peripherally with horizontally aligned/misa

Varvara Logacheva, Denis Teslenko, Artem Shelmanov, Steffen Remus

Disambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed to solve this task. However, (i) the inherent Zipfian distribution of supervised training instances for a given word and/or (ii) the quality of linguistic knowledge representations

Subhajit Chaudhury, Toshihiko Yamasaki

In this paper, we study the generalization properties of neural networks under input perturbations and show that minimal training data corruption by a few pixel modifications can cause drastic overfitting. We propose an evolutionary algorithm to search for optimal pixel perturbations using novel cost function inspired from literature in domain adaptation tha

Yulan Gao, Chao Yong, Zehui Xiong, Dusit Niyato

It is known that the capacity of the intelligent reflecting surface (IRS) aided cellular network can be effectively improved by reflecting the incident signals from the transmitter in a low-cost passive reflecting way. In this paper, we study the adoption of an IRS for downlink multi-user communication from a multi-antenna base station (BS). Nevertheless, in

Matthias F. Stallmann, Yang Ho, Timothy D. Goodrich

Akiba and Iwata [TCS, 2016] demonstrated that a branch and reduce (B&R) solver for the vertex cover problem can compete favorably with integer linear programming solvers (e.g., CPLEX). Our research question is are there graph characteristics that determine which reductions will be most effective? Not only is the answer affirmative, but relevant characteristi

Benoît Mahault, Ramin Golestanian

A generic class of scalar active matter, characterized at the mean field level by the diffusivity vanishing above some threshold density, was recently introduced [Golestanian R 2019 Phys. Rev. E 100 010601(R)]. In the presence of harmonic confinement, such &#39;diffusivity edge&#39; was shown to lead to condensation in the ground state, with the associated t

Nantheera Anantrasirichai, Majid Geravand, David Braendler, David R. Bull

Disparity/depth estimation from sequences of stereo images is an important element in 3D vision. Owing to occlusions, imperfect settings and homogeneous luminance, accurate estimate of depth remains a challenging problem. Targetting view synthesis, we propose a novel learning-based framework making use of dilated convolution, densely connected convolutional

Guansong Lu, Zhiming Zhou, Jian Shen, Cheng Chen

Recent advances in large-scale optimal transport have greatly extended its application scenarios in machine learning. However, existing methods either not explicitly learn the transport map or do not support general cost function. In this paper, we propose an end-to-end approach for large-scale optimal transport, which directly solves the transport map and i

Caio Almeida, Débora Santos

Fake news is a growing problem in the last years, especially during elections. It&#39;s hard work to identify what is true and what is false among all the user generated content that circulates every day. Technology can help with that work and optimize the fact-checking process. In this work, we address the challenge of finding similar content in order to be

Shoichi Okaba, Deshui Yu, Luca Vincetti, Fetah Benabid

Unravelling superradiance, also known as superfluorescence, relies on an ensemble of phase-matched dipole oscillators and the suppression of inhomogeneous broadening. Here we report on a novel superradiance platform that combines an optical lattice free from the ac Stark shift and a hollow-core photonic crystal fibre, enabling an extended atom-light interact

Chao Huang, Ruihui Li, Xianzhi Li, Chi-Wing Fu

This paper presents a novel non-local part-aware deep neural network to denoise point clouds by exploring the inherent non-local self-similarity in 3D objects and scenes. Different from existing works that explore small local patches, we design the non-local learning unit (NLU) customized with a graph attention module to adaptively capture non-local semantic

Qiang Li, Xianming Liu, Kaige Han, Cheng Guo

Whole slide imaging (WSI) is an emerging technology for digital pathology. The process of autofocusing is the main influence of the performance of WSI. Traditional autofocusing methods either are time-consuming due to repetitive mechanical motions, or require additional hardware and thus are not compatible to current WSI systems. In this paper, we propose th

Hua Y. Geng, Q. Wu, Miriam Marqués, Graeme J. Ackland

The properties of hydrogen at high pressure have wide implications in astrophysics and high-pressure physics. Its phase change in the liquid is variously described as a metallization, H2-dissociation, density discontinuity or plasma phase transition. It has been tacitly assumed that these phenomena coincide at a first-order liquid-liquid transition (LLT). In

Arbaz Khan, Catherine E. Powell

Linear poroelasticity models have a number of important applications in biology and geophysics. In particular, Biot&#39;s consolidation model is a well-known model that describes the coupled interaction between the linear response of a porous elastic medium and a diffusive fluid flow within it, assuming small deformations. Although deterministic linear poroe

Y. X. Wang, Hua Y. Geng, Q. Wu, Xiang R. Chen

It is believed that the density functional theory (DFT) describes most elements with s, p and d orbitals very well, except some materials that having strongly localized and correlated valence electrons. In this work, we find that the widely employed exchange-correlation (xc) functionals, including LDA, GGA and meta-GGA, underestimate the shear modulus and ph

Xiao Z. Yan, Yang M. Chen, Hua Y. Geng

Pressure significantly modifies the microscopic interactions in condense phase, leading to new patterns of bonding and unconventional chemistry. Both argon and xenon possess closed-shell electronic structures, which renders them chemically unreactive. Using unbiased structure searching techniques combined with first-principles calculations, we demonstrate th

Asieh Sattari, Majid Arezoomand, Mohammad A. Iranmanesh

Let $G$ be a finite group and $S$ be a subset of $G.$ A bi-Cayley graph $\BCay(G,S)$ is a simple and an undirected graph with vertex-set $G\times\{1,2\}$ and edge-set $\{\{(g,1),(sg,2)\}\mid g\in G, s\in S\}$. A bi-Cayley graph $\BCay(G,S)$ is called a $\BCI$-graph if for any bi-Cayley graph $\BCay(G,T)$, whenever $\BCay(G,S)\cong\BCay(G,T)$ we have $T=gS^σ$

Nikolaos Melissinos, Aris Pagourtzis, Theofilos Triommatis

We consider the Subset Sum Ratio Problem ($SSR$), in which given a set of integers the goal is to find two subsets such that the ratio of their sums is as close to~1 as possible, and introduce a family of variations that capture additional meaningful requirements. Our main contribution is a generic framework that yields fully polynomial time approximation sc

Moni Kumari, Jyoti Sengupta

Let $f$ and $g$ be two Hecke-Maass cusp forms of weight zero for $SL_2(\mathbb Z)$ with Laplacian eigenvalues $\frac{1}{4}+u^2$ and $\frac{1}{4}+v^2$, respectively. Then both have real Fourier coefficients say, $λ_f(n)$ and $λ_g(n)$, and we may normalize $f$ and $g$ so that $λ_f(1)=1=λ_g(1)$. In this article, we first prove that the sequence $\{λ_f(n)λ_g(n)\

Ivars Dzalbs, Tatiana Kalganova, Ian Dear

The multidimensional knapsack problem is a well-known constrained optimization problem with many real-world engineering applications. In order to solve this NP-hard problem, a new modified Imperialist Competitive Algorithm with Constrained Assimilation (ICAwICA) is presented. The proposed algorithm introduces the concept of colony independence, a free will t

Sakshi Patel, Bharath K P, Rajesh Kumar Muthu

In this paper we have proposed a method that uses chaotic logistic mapping and DNA encoding to encrypt the image. A 32 bit ASCII private key is used to diffuse the image. The results demonstrated clearly show that encryption algorithm based on chaotic logistic mapping and DNA encoding gives better result than encrypting only with chaotic logistic mapping. Th

Sakshi Patel, Bharath K P, Rajesh Kumar Muthu

MRI (Magnetic Resonance Imaging) is a technique used to analyze and diagnose the problem defined by images like cancer or tumor in a brain. Physicians require good contrast images for better treatment purpose as it contains maximum information of the disease. MRI images are low contrast images which make diagnoses difficult; hence better localization of imag

Fotis Savva, Christos Anagnostopoulos, Peter Triantafillou

As more and more organizations rely on data-driven decision making, large-scale analytics become increasingly important. However, an analyst is often stuck waiting for an exact result. As such, organizations turn to Cloud providers that have infrastructure for efficiently analyzing large quantities of data. But, with increasing costs, organizations have to o

Suraj Singh, Sheetal, Bandhana Devi, R. R. Koner

A new mononuclear Dysprosium based Coordination Polymer {Dy-CP} was investigated magnetically using dc and ac magnetic susceptibility. The dc magnetic susceptibility does not exhibit any long-range ordering down to 1.8 K and the negative value of Curie Constant (~ - 4 K) indicate the dominance of antiferromagnetic interactions between the Dy (III) spins. Ac

Canjie Luo, Yuanzhi Zhu, Lianwen Jin, Yongpan Wang

Handwritten text and scene text suffer from various shapes and distorted patterns. Thus training a robust recognition model requires a large amount of data to cover diversity as much as possible. In contrast to data collection and annotation, data augmentation is a low cost way. In this paper, we propose a new method for text image augmentation. Different fr

Galia Nakova

We introduce a class of half lightlike submanifolds of almost contact B-metric manifolds and prove that such submanifolds are semi-Riemannian with respect to the associated B-metric. Object of investigations are also minimal of the considered submanifolds and a non-trivial example for them is given.

Jingnan Guo, Cary Zeitlin, Robert Wimmer-Schweingruber, Donald M. Hassler

The Radiation Assessment Detector (RAD), onboard the Mars Science Laboratory (MSL) rover Curiosity, has been measuring the energetic charged and neutral particles and the radiation dose rate on the surface of Mars since the landing of the rover in August 2012. In contrast to charged particles, neutral particles (neutrons and gamma-rays) are measured indirect

Jingnan Guo, Robert F. Wimmer-Schweingruber, Yuming Wang, Manuel Grande

Space radiation is a major risk for humans, especially on long-duration missions to outer space, e.g., a manned mission to Mars. Galactic cosmic rays (GCR) contribute a predictable radiation background, the main risk is due to the highly variable and currently unpredictable flux of solar energetic particles (SEPs). Such sporadic SEP events may induce acute h

Brian Sutcliffe, R. Guy Woolley

The relationship between the chemical picture of an isolated molecule and that arising from the eiegenfunctions of the Schrodinger Coulomb Hamiltonian ror the isolated molecule are examined and discussed.

Xue-Jian Jiang, Thomas R. Greve, Yu Gao, Zhi-Yu Zhang

To study the high-transition dense-gas tracers and their relationships to the star formation of the inner $\sim$ 2 kpc circumnuclear region of NGC253, we present HCN $J=4-3$ and HCO$^+ J=4-3$ maps obtained with the James Clerk Maxwell Telescope (JCMT). With the spatially resolved data, we compute the concentration indices $r_{90}/r_{50}$ for the different tr

Yue Hu, Siheng Chen, Ya Zhang, Xiao Gu

Motion prediction is essential and challenging for autonomous vehicles and social robots. One challenge of motion prediction is to model the interaction among traffic actors, which could cooperate with each other to avoid collisions or form groups. To address this challenge, we propose neural motion message passing (NMMP) to explicitly model the interaction

Ercument H. Ortacgil

We show that the theory of geometric structures proposed in the recent book &#34;An Alternative Approach to Lie Groups and Geometric Structures&#34; can be developed independently of connections.

Vladimir Ivashkin

Looking back at the history of calculators, one can see that they become less functional and more computationally expensive over time. A modern calculator runs on a personal computer and is drawn at 60 fps only to help us click a few digits with a mouse pointer. A search engine is often used as a calculator, which means that nowadays we need the Internet jus

V. I. Afanasyev

A Galton-Watson branching process with immigration evolving in a random environment is considered. Its associated random walk is assumed to be oscillating. We prove a functional limit theorem in which the process under consideration is normalized by a random coefficient depending on the random environment only. The distribution of the limiting process is des

Alexander Chesnokov, Valery Liapidevskii

A plane turbulent mixing in a shear flow of an ideal homogeneous fluid confined between two relatively close rigid walls is considered. The character of the flow is determined by interaction of vortices arising at the nonlinear stage of the Kelvin--Helmholtz instability development and by turbulent friction. In the framework of the shallow water theory and a

Mingzhou Yin, Q. P. Chu, Y. Zhang, Michael A. Niestroy

This paper proposes a novel and practical framework for safe flight envelope estimation and protection, in order to prevent loss-of-control-related accidents. Conventional analytical envelope estimation methods fail to function efficiently for systems with high dimensionality and complex dynamics, which is often the case for high-fidelity aircraft models. In

James Matthews, Anthony Bell, Katherine Blundell

In this chapter, we review some features of particle acceleration in astrophysical jets. We begin by describing four observational results relating to the topic, with particular emphasis on jets in active galactic nuclei and parallels between different sources. We then discuss the ways in which particles can be accelerated to high energies in magnetised plas

Jing Li, J. Y. Ni, X. Y. Li, H. -J. Koo

The layered magnetic topological insulator MnBi$_2$Te$_4$ is a promising platform to realize the quantum anomalous Hall effect because its layers possess intrinsic ferromagnetism. However, it is not well understood why the high-spin $d^5$ magnetic ions Mn$^{2+}$ forming the Mn-Te-Mn spin exchange paths prefer ferromagnetic (FM) coupling, contrary to the pred

Bin Hou, Qingjie Liu, Heng Wang, Yunhong Wang

Traditional change detection methods usually follow the image differencing, change feature extraction and classification framework, and their performance is limited by such simple image domain differencing and also the hand-crafted features. Recently, the success of deep convolutional neural networks (CNNs) has widely spread across the whole field of compute

Bo-Kyeong Kim, Sungjin Park, Geonmin Kim, Soo-Young Lee

We aim to separate the generative factors of data into two latent vectors in a variational autoencoder. One vector captures class factors relevant to target classification tasks, while the other vector captures style factors relevant to the remaining information. To learn the discrete class features, we introduce supervision using a small amount of labeled d

Zongpeng Ding, Zhangdong Ouyang, Yuanqiu Huang, Fengming Dong

A graph $G$ is {$k$-crossing-critical} if $cr(G)\ge k$, but $cr(G\setminus e)<k$ for each edge $e\in E(G)$, where $cr(G)$ is the crossing number of $G$. It is known that for any $k$-crossing-critical graph $G$, $cr(G)\le 2.5k+16$ holds, and in particular, if $δ(G)\ge 4$, then $cr(G)\le 2k+35$ holds, where $δ(G)$ is the minimum degree of $G$. In this paper, w

Joonas Herranen

Rigorous statistical numerical analysis of the response of a nonspherical dust particle ensemble composed of aggregates of astronomical silicate is presented. It is found that the rotational disruption mechanism is not only likely to occur but to be a key element in explaining many separate observations of cometary dust. Namely, radiative torques are shown t