April 2019 arXiv papers — page 100

Łukasz Dusanowski, Soon-Hong Kwon, Christian Schneider, Sven Höfling

Integrated single photon sources are key building blocks for realizing scalable devices for quantum information processing. For such applications highly coherent and indistinguishable single photons on a chip are required. Here we report on a triggered resonance fluorescence single photon source based on In(Ga)As/GaAs quantum dots coupled to single- and mult

Natalie Parde, Rodney D. Nielsen

Artificial intelligence is revolutionizing formal education, fueled by innovations in learning assessment, content generation, and instructional delivery. Informal, lifelong learning settings have been the subject of less attention. We provide a proof-of-concept for an embodied book discussion companion, designed to stimulate conversations with readers about

Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang

Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex components that require a great deal of hand-tuning for specific workloads and datasets. Motivated by this shortcoming and inspired by recent advances in applying machine learning to data m

Dale G. Karr

An example of capillary phenomena commonly seen and often studied is a droplet of water hanging in air from a horizontal surface. A thin capillary surface interface between the liquid and gas develops tangential surface tension, which provides a balance of the internal and external pressures. The Young-Laplace equation has been historically used to establish

Wojciech Kamiński

We will prove in an elementary way that off-diagonal Seeley-DeWitt and Hadamard coefficients are (sesqui-)symmetric for smooth manifolds of arbitrary signature.

J Liu, X. Liu, J. Sun

We consider the inverse elastic scattering problems using the far field data due to one incident plane wave. A simple method is proposed to reconstruct the location and size of the obstacle using different components of the far field pattern. The method sets up linear ill-posed integral equations for sampling points in the domain of interrogation and uses th

Sandy Engelhardt, Simon Sauerzapf, Bernhard Preim, Matthias Karck

Given the multitude of challenges surgeons face during mitral valve repair surgery, they should have a high confidence in handling of instruments and in the application of surgical techniques before they enter the operating room. Unfortunately, opportunities for surgical training of minimally-invasive repair are very limited, leading to a situation where mos

Emanuele Haus, Alberto Maspero

We consider the semiclassical Schrödinger equation on $\mathbb R^d$ given by $$\mathrm{i} \hbar \partial_t ψ= \left(-\frac{\hbar^2}{2} Δ+ W_l(x) \right)ψ+ V(t,x)ψ,$$ where $W_l$ is an anharmonic trapping of the form $W_l(x)= \frac{1}{2l}\sum_{j=1}^d x_j^{2l}$, $l\geq 2$ is an integer and $\hbar$ is a semiclassical small parameter. We construct a smooth poten

Lara Román Castellanos, Ortwin Hess, Johannes Lischner

Hot carriers produced from the decay of localized surface plasmons in metallic nanoparticles are intensely studied because of their optoelectronic, photovoltaic and photocatalytic applications. From a classical perspective, plasmons are coherent oscillations of the electrons in the nanoparticle, but their quantized nature comes to the fore in the novel field

Yanbo Fang

For a projective variety $X$ defined over a non-Archimedean complete non-trivially valued field $k$, and a semipositive metrized line bundle $(L, ϕ)$ over it, we establish a metric extension result for sections of $L^{\otimes n}$ from a sub-variety $Y$ to $X$. We form normed section algebras from $(L, ϕ)$ and study their Berkovich spectra. To compare the sup

Alexander W. Winkler, Carlos Mastalli, Ioannis Havoutis, Michele Focchi

We present a framework for dynamic quadrupedal locomotion over challenging terrain, where the choice of appropriate footholds is crucial for the success of the behaviour. We build a model of the environment on-line and on-board using an efficient occupancy grid representation. We use Any-time-Repairing A* (ARA*) to search over a tree of possible actions, cho

I. García-Bernete, C. Ramos Almeida, A. Alonso-Herrero, M. J. Ward

We characterize for the first time the torus properties of an ultra-hard X-ray (14-195 keV) volume-limited (DL<40 Mpc) sample of 24 Seyfert (Sy) galaxies (BCS40 sample). The sample was selected from the Swift/BAT nine month catalog. We use high angular resolution nuclear infrared (IR) photometry and N-band spectroscopy, the CLUMPY torus models and a Bayesian

Carlos Mastalli, Ioannis Havoutis, Alexander W. Winkler, Darwin G. Caldwell

We present a legged motion planning approach for quadrupedal locomotion over challenging terrain. We decompose the problem into body action planning and footstep planning. We use a lattice representation together with a set of defined body movement primitives for computing a body action plan. The lattice representation allows us to plan versatile movements t

Dayan Guan, Xing Luo, Yanpeng Cao, Jiangxin Yang

Multimodal information (e.g., visible and thermal) can generate robust pedestrian detections to facilitate around-the-clock computer vision applications, such as autonomous driving and video surveillance. However, it still remains a crucial challenge to train a reliable detector working well in different multispectral pedestrian datasets without manual annot

Leonel Robert, Luis Santiago

We revise the construction of the augmented Cuntz semigroup functor used by the first author to classify inductive limits of 1-dimensional noncommutative CW complexes. The original construction has good functorial properties when restricted to the class of C*-algebras of stable rank one. The construction proposed here has good properties for all C*-algebras:

Wayne Osborn, Grzegorz Kopacki, Horace A. Smith, Barton J. Pritzl

New CCD photometry has been combined with published and unpublished earlier observations to study the three Cepheid variables in M13: V1, V2 and V6. The light curve characteristics in $B$, $V$ and $I_{\rm C}$ have been determined and the periods updated. A period change analysis shows all three stars have increasing periods but for V1 and V2 the rate of peri

Farhood Rismanchian, Karim Rahimian

Relevance vector machine (RVM) can be seen as a probabilistic version of support vector machines which is able to produce sparse solutions by linearly weighting a small number of basis functions instead using all of them. Regardless of a few merits of RVM such as giving probabilistic predictions and relax of parameter tuning, it has poor prediction for test

Damian Rössler

On montre que le groupe de Selmer d&#39;une isogénie de hauteur un entre deux variétés abéliennes définies sur le corps de fonctions d&#39;une variété quasi-projective et lisse $V$ sur un corps parfait $k_0$ de caractéristique $p>0$ peut être plongé dans le groupe des homomorphismes entre deux fibrés vectoriels naturels sur $V$. / We show that the Selmer gro

Hironori Michihisa

After GGH model was proposed by M. Ghisi, M. Gobbino and A. Haraux (2016), R. Ikehata and S. Iyota (2018) showed decay estimates for the total energy of solutions to GGH equations uniformly in the initial data. However, their results imply that the total energy is bounded when the initial data belong to the energy space. That is, whether it actually decays h

Damian Rössler

We prove a refinement of the Grothendieck-Riemann-Roch theorem in degree one.

Chaitanya Prasad Sishtla, Steven W. D. Chien, Vyacheslav Olshevsky, Erwin Laure

iPIC3D is a widely used massively parallel Particle-in-Cell code for the simulation of space plasmas. However, its current implementation does not support execution on multiple GPUs. In this paper, we describe the porting of iPIC3D particle mover to GPUs and the optimization steps to increase the performance and parallel scaling on multiple GPUs. We analyze

Maria Colombo, Antonio De Rosa, Andrea Marchese

We show in full generality the stability of optimal traffic paths in branched transport: namely we prove that any limit of optimal traffic paths is optimal as well. This solves an open problem in the field (cf. Open problem 1 in the book Optimal transportation networks, by Bernot, Caselles and Morel), which has been addressed up to now only under restrictive

Dietmar Silke Klemm, Lucrezia Ravera

We show that the horizon geometry for supersymmetric black hole solutions of minimal five-dimensional gauged supergravity is that of a particular Einstein-Cartan-Weyl (ECW) structure in three dimensions, involving the trace and traceless part of both torsion and nonmetricity, and obeying some precise constraints. In the limit of zero cosmological constant, t

T. A. Hromakina, I. N. Belskaya, Yu. N. Krugly, V. G. Shevchenko

We studied the rotational properties of the dwarf planet Makemake. The photometric observations were carried out at different telescopes between 2006 and 2017. Most of the measurements were acquired in BVRI broad-band filters of a standard Johnson-Cousins photometric system. We found that Makemake rotates more slowly than was previously reported. A possible

Xing Lu, Kathryn Hinkelman, Yangyang Fu, Jing Wang

Infrastructure in future smart and connected communities is envisioned as an aggregate of public services, including the energy, transportation and communication systems, all intertwined with each other. The intrinsic interdependency among these systems may exert underlying influence on both design and operation of the heterogeneous infrastructures. However,

Sergey Ivanov, Irina Demina, Sergey Merkuryev

The purpose of this work is to compare kinematics of small-scale current vortices located near the core-mantle boundary with high-speed anomalies of seismic wave velocity in the lowest mantle asso-ciated with the subduction zones. The small-scale vortex paths were early obtained by the authors in the frame of the macro model of the main geomagnetic field sou

Tarik C. Gouhier, Pradeep Pillai

We demonstrate that the conclusions drawn by Bernhard et al. (2018) regarding the ability of nonlinear averaging to accurately predict organismal performance under fluctuating temperatures are flawed because of a series of experimental and statistical issues that include the presence of a hidden treatment effect, the use of a single low frequency temperature

Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot, Christophe Sintes

The motivation of this paper is to address the problem of registering airborne LiDAR data and optical aerial or satellite imagery acquired from different platforms, at different times, with different points of view and levels of detail. In this paper, we present a robust registration method based on building regions, which are extracted from optical images u

John H Zhang

Based on the observed absorption spectral band shifts, the growth process of the semiconductor clusters was divided into two phenomenological regimes: The &#34;molecular regime&#34; that is associated with the band blue shift as the size of cluster increases and the &#34;crystallite regime&#34; that is associated with the band red shift as the size of cluste

Dieter Büchler, Roberto Calandra, Jan Peters

High-speed and high-acceleration movements are inherently hard to control. Applying learning to the control of such motions on anthropomorphic robot arms can improve the accuracy of the control but might damage the system. The inherent exploration of learning approaches can lead to instabilities and the robot reaching joint limits at high speeds. Having hard

Xinxing Wu, Xu Zhang

In this paper, we show that there exists a monoid, on which neither the syndetic property nor the dual syndetic property holds, and there exists a strongly mixing semi-flow with this monoid action which does not have thick sensitivity, syndetic sensitivity, thickly syndetic sensitivity, or thickly periodical sensitivity. Meanwhile, we show that there exists

Roman Romanov, Harald Woracek

We study spectral properties of two-dimensional canonical systems $y&#39;(t)=zJH(t)y(t)$, $t\in[a,b)$, where the Hamiltonian $H$ is locally integrable on $[a,b)$, positive semidefinite, and Weyl&#39;s limit point case takes place at $b$. We answer the following questions explicitly in terms of $H$: Is the spectrum of the associated selfadjoint operator discr

Dr Sudhira Panda

Satanandacharya the astronomer and mathematician of 11th century was born in 1068 C.E. at Purusottamdham Puri of Odisha wrote the scripture Bhasvati in 1099 C.E.. The scripture has significant contribution to world of Astronomy and Mathematics. Satananda has adopted centisimal system for the calculation of position and motion of heavenly bodies, which is sim

Keisuke Takano, Hiroshi Yokoyama, Akira Ichii, Isao Morimoto

Wire-grid polarizer sheets in the terahertz region have been fabricated on flexible substrates by nanoimprint technology. They show ideal polarization property in the terahertz frequency region whereas the cost is very low. Since the wire pitch is far smaller than the wavelength, the effective medium theory agrees well with experimental results. The effectiv

Weina Jin, Alissa N. Antle, Diane Gromala

Music plays a crucial role in young children&#39;s development. Current research lacks the design of an interactive system for younger children that could generate dynamic music change in response to the children&#39;s body movement. In this paper, we present the design of bike as an embodied musical instrument for young children 2-5 years old to improve the

Eugene Serebryany, Rostam Razban, Eugene I Shakhnovich

Most known proteins in nature consist of multiple domains. Interactions between domains may lead to unexpected folding and misfolding phenomena. This study of human γD-crystallin, a two-domain protein in the eye lens, revealed one such surprise: conformational catalysis of misfolding via intermolecular domain interface &#39;&#39;stealing&#39;&#39;. An interm

Tifenn Hirtzlin, Marc Bocquet, Jacques-Olivier Klein, Etienne Nowak

Resistive random access memories (RRAM) are novel nonvolatile memory technologies, which can be embedded at the core of CMOS, and which could be ideal for the in-memory implementation of deep neural networks. A particularly exciting vision is using them for implementing Binarized Neural Networks (BNNs), a class of deep neural networks with a highly reduced m

Tamara Bottazzi, Alejandro Varela

We study the unitary orbit of a compact Hermitian diagonal operator with spectral multiplicity one under the action of the unitary group U_(K+C) of the unitization of the compact operators K(H)+C, or equivalently, the quotient U_(K+C)/ U_Diag(K+C). We relate this and the action of different unitary subgroups to describe metric geodesics (using a natural dist

Thomas Anthony, Robert Nishihara, Philipp Moritz, Tim Salimans

Monte Carlo Tree Search (MCTS) algorithms perform simulation-based search to improve policies online. During search, the simulation policy is adapted to explore the most promising lines of play. MCTS has been used by state-of-the-art programs for many problems, however a disadvantage to MCTS is that it estimates the values of states with Monte Carlo averages

M. H. N. Assadi, H. Katayama-Yoshida

We have systematically investigated the $Na_xCoO_2$ system doped with Cu, Y, Sn, W, Au and Bi for $x$ = 0:5; 0:75 and 1.00 using density functional theory. Sn, W, and Bi always substitute a Co while Au always substitutes a Na regardless of Na concentration. However, for Cu and Y, the substitution site depends on Na concentration. When compared to the availab

Donghoh Kim, Guebin Choi, Hee-Seok Oh

This paper considers the problem of signal decomposition and data visualization. For this purpose, we introduce a new multiscale transform, termed `ensemble patch transformation&#39; that enhances identification of local characteristics embedded in a signal and provides multiscale visualization according to different levels; hence, it is useful for data anal

Daniel Azagra, Carlos Mudarra

Let $X$ denote $\mathbb{R}^n$ or, more generally, a Hilbert space. Given an arbitrary subset $C$ of $X$ and a collection $\mathcal{H}$ of affine hyperplanes of $X$ such that every $H\in\mathcal{H}$ passes through some point $x_{H}\in C$, and $C=\{x_H : H\in\mathcal{H}\}$, what conditions are necessary and sufficient for the existence of a $C^{1,1}$ convex hy

Aleksandr Maksimenko

We give a complete enumeration of all 2-neighborly 0/1-polytopes of dimension 7. There are 13 959 358 918 different 0/1-equivalence classes of such polytopes. They form 5 850 402 014 combinatorial classes and 1 274 089 different f-vectors. It enables us to list some of their combinatorial properties. In particular, we have found a 2-neighborly polytope with

P. W. Adriaans

We present the concept of the \emph{information efficiency of functions} as a technique to understand the interaction between information and computation. Based on these results we identify a new class of objects that we call \emph{Semi-Countable Sets}. As the name suggests these sets form a separate class of objects between countable and uncountable sets. I

Quentin Betti, Raphaël Khoury, Sylvain Hallé, Benoît Montreuil

The Physical Internet and hyperconnected logistics concepts promise an open, more efficient and environmentally friendly supply chain for goods. Blockchain and Internet of Things technologies are increasingly regarded as main enablers of improvements in this domain. We describe how blockchain and smart contracts present the potential of being applied to hype

Wei-Hong Li, Fa-Ting Hong, Wei-Shi Zheng

Humans can easily recognize the importance of people in social event images, and they always focus on the most important individuals. However, learning to learn the relation between people in an image, and inferring the most important person based on this relation, remains undeveloped. In this work, we propose a deep imPOrtance relatIon NeTwork (POINT) that

James F. Lutsko

Recent advances in classical density functional theory are combined with stochastic process theory and rare event techniques to formulate a theoretical description of nucleation, including crystallization, that can predict nonclassical nucleation pathways based on no input other than the interaction potential of the particles making up the system. The theory

Songtao Liu, Di Huang, Yunhong Wang

Pedestrian detection in a crowd is a very challenging issue. This paper addresses this problem by a novel Non-Maximum Suppression (NMS) algorithm to better refine the bounding boxes given by detectors. The contributions are threefold: (1) we propose adaptive-NMS, which applies a dynamic suppression threshold to an instance, according to the target density; (

F. Fuerst, P. Kretschmar, V. Grinberg, K. Pottschmidt

Strongly magnetized, accreting neutron stars show periodic and aperiodic variability over a wide range of time scales. By obtaining spectral and timing information on these different time scales, we can have a closer look into the physics of accretion close to the neutron star and the properties of the accreted material. One of the most prominent time scales

Lu Yu, Vacit Oguz Yazici, Xialei Liu, Joost van de Weijer

Metric learning networks are used to compute image embeddings, which are widely used in many applications such as image retrieval and face recognition. In this paper, we propose to use network distillation to efficiently compute image embeddings with small networks. Network distillation has been successfully applied to improve image classification, but has h

Varshaneya V, S Balasubramanian, Vineeth N Balasubramanian

Sketching is more fundamental to human cognition than speech. Deep Neural Networks (DNNs) have achieved the state-of-the-art in speech-related tasks but have not made significant development in generating stroke-based sketches a.k.a sketches in vector format. Though there are Variational Auto Encoders (VAEs) for generating sketches in vector format, there is

Yu. T. Tsap, A. V. Stepanov, Yu. G. Kopylova

Two approaches are used for description of linear transverse (kink) modes excited in a vertical thin magnetic flux tube. First one is based on the elastic thread model (Spruit, 1981). The second one follows from the the Taylor and Laurent series expansions of wave variables with respect to the tube radius inside and outside of the magnetic flux tube (Lopin a

Z. X. Wen, Q. Li, Y. Yu, Kai. H. Luo

In this paper, an improved three-dimensional color-gradient lattice Boltzmann (LB) model is proposed for simulating immiscible multiphase flows. Compared with the previous three-dimensional color-gradient LB models, which suffer from the lack of Galilean invariance and considerable numerical errors in many cases owing to the error terms in the recovered macr

Yang Zhang, Lantian Li, Dong Wang

Deep speaker embedding has achieved state-of-the-art performance in speaker recognition. A potential problem of these embedded vectors (called `x-vectors&#39;) are not Gaussian, causing performance degradation with the famous PLDA back-end scoring. In this paper, we propose a regularization approach based on Variational Auto-Encoder (VAE). This model transfo

Beibin Li, Sachin Mehta, Deepali Aneja, Claire Foster

In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, arousal, and valence. Our system classifies ASD using representations of different facial attributes from convolutional neural networks, which are trained on images in the wild. Our

Fatemeh Shiri, Xin Yu, Fatih Porikli, Richard Hartley

Recovering a photorealistic face from an artistic portrait is a challenging task since crucial facial details are often distorted or completely lost in artistic compositions. To handle this loss, we propose an Attribute-guided Face Recovery from Portraits (AFRP) that utilizes a Face Recovery Network (FRN) and a Discriminative Network (DN). FRN consists of an

Lee-Ad Gottlieb, Yair Bartal

We give an algorithm that computes a $(1+ε)$-approximate Steiner forest in near-linear time $n \cdot 2^{(1/ε)^{O(ddim^2)} (\log \log n)^2}$. This is a dramatic improvement upon the best previous result due to Chan et al., who gave a runtime of $n^{2^{O(ddim)}} \cdot 2^{(ddim/ε)^{O(ddim)} \sqrt{\log n}}$. For Steiner tree our methods achieve an even better ru

Yongpan Huang

Boundary differentiability is shown for solutions of nondivergence elliptic equations with unbounded drift

Vladislav G. Polnikov

In the Navier-Stokes equations, a current is decomposed into four constituents: the mean flow, wave-orbital motion, wave-induced-turbulent and background-turbulent currents. Under certain statistical assumptions, this allows to separate the wave-induced Reynolds stress from the background one. To close the wave-induced Reynolds stress, the Prandtl approach f

Tiexin Guo, Erxin Zhang, Yachao Wang, George Yuan

Let $(B,\|\cdot\|)$ be a Banach space, $(Ω,\mathcal{F},P)$ a probability space and $L^0(\mathcal{F},B)$ the set of equivalence classes of strong random elements (or strongly measurable functions) from $(Ω,\mathcal{F},P)$ to $(B,\|\cdot\|)$. It is well known that $L^0(\mathcal{F},B)$ becomes a complete random normed module, which has played an important role

Mohannad Babli, Eva Onaindia, Eliseo Marzal

Approaches to goal-directed behaviour including online planning and opportunistic planning tackle a change in the environment by generating alternative goals to avoid failures or seize opportunities. However, current approaches only address unanticipated changes related to objects or object types already defined in the planning task that is being solved. Thi

Dominik Wrazidlo

By a theorem of Banagl-Chriestenson, intersection spaces of depth one pseudomanifolds exhibit generalized Poincaré duality of Betti numbers, provided that certain characteristic classes of the link bundles vanish. In this paper, we show that the middle-perversity intersection space of a depth one Witt space can be completed to a rational Poincaré duality spa

Shuhao Zhang, Jiong He, Amelie Chi Zhou, Bingsheng He

We introduce BriskStream, an in-memory data stream processing system (DSPSs) specifically designed for modern shared-memory multicore architectures. BriskStream&#39;s key contribution is an execution plan optimization paradigm, namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair of producer-consumer operators into consideration. We

Ramy Hussein, Mohamed Osama Ahmed, Rabab Ward, Z. Jane Wang

Objective: The aim of this study is to develop an efficient and reliable epileptic seizure prediction system using intracranial EEG (iEEG) data, especially for people with drug-resistant epilepsy. The prediction procedure should yield accurate results in a fast enough fashion to alert patients of impending seizures. Methods: We quantitatively analyze the hum

Amit Daniely, Yishay Mansour

We consider online algorithms under both the competitive ratio criteria and the regret minimization one. Our main goal is to build a unified methodology that would be able to guarantee both criteria simultaneously. For a general class of online algorithms, namely any Metrical Task System (MTS), we show that one can simultaneously guarantee the best known com

Narendra Kumar, Abhay Kumar Singh

For odd length $n$, the cyclic codes construction over $\Re= \Z_4[v]/ \langle v^2-v \rangle$ is provided. The hulls of cyclic codes over $\Re$ are studied. The average $2$-dimension $E(n)$ of the hulls of cyclic codes over $\Re$ is also conferred. Among these, the various examples of generators of hulls of cyclic codes over $\Re$ are provided, whose $\Z_4$-i

Anthony Genevois, Olga Varghese

An automorphism of a graph product of groups is conjugating if it sends each factor to a conjugate of a factor (possibly different). In this article, we determine precisely when the group of conjugating automorphisms of a graph product satisfies Kazhdan&#39;s property (T) and when it satisfies some vastness properties including SQ-universality.

Quan-Lin Li, Jing-Yu Ma, Yan-Xia Chang, Fan-Qi Ma

In this paper, we develop a more general framework of block-structured Markov processes in the queueing study of blockchain systems, which can provide analysis both for the stationary performance measures and for the sojourn times of any transaction and block. Note that an original aim of this paper is to generalize the two-stage batch-service queueing model

Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He

We address the problem of video representation learning without human-annotated labels. While previous efforts address the problem by designing novel self-supervised tasks using video data, the learned features are merely on a frame-by-frame basis, which are not applicable to many video analytic tasks where spatio-temporal features are prevailing. In this pa

Sara Meftah, Youssef Tamaazousti, Nasredine Semmar, Hassane Essafi

Fine-tuning neural networks is widely used to transfer valuable knowledge from high-resource to low-resource domains. In a standard fine-tuning scheme, source and target problems are trained using the same architecture. Although capable of adapting to new domains, pre-trained units struggle with learning uncommon target-specific patterns. In this paper, we p

Mahdi Eshghi, Ramazan Sever, Sameer M. Ikhdair

We solve the Schrödinger wave equation for the generalized Morse and Cusp molecular potential models. In the limit of high temperature, at first, we need to calculate the canonical partition function which is basically used to study the behavior of the thermodynamic functions. Based on this, we further calculate the thermodynamic quantities such as the free

Mirek Giersz, Abbas Askar, Jakub Klencki, Jakub Morawski

We briefly describe and discuss the set-up of the project MOCCA Survey Database I. The database contains more than 2000 Monte Carlo models of evolution of real star cluster performed with the MOCCA code. Then, we very briefly discuss results of analysis of the database regarding the following projects: formation of intermediate mass black holes, abrupt clust

Wolfgang Bentz, Ian C. Cloet

We present a study of the skewness of nuclear matter, which is proportional to the third derivative of the energy per nucleon with respect to the baryon density at the saturation point, in the framework of the Landau-Migdal theory. We derive an exact relation between the skewness, the nucleon effective mass, and two-particle and three-particle interaction pa

Yongli Zhu, Lingpeng Shi, Renchang Dai, Guangyi Liu

In this study, a graph-computing based grid splitting detection algorithm is proposed for contingency analysis in a graph-based EMS (Energy Management System). The graph model of a power system is established by storing its bus-branch information into the corresponding vertex objects and edge objects of the graph database. Numerical comparison to an up-to-da

Parviz Sahandi, Tirdad Sharif, Siamak Yassemi

We introduce new homological dimensions, namely the Cohen-Macaulay projective, injective and flat dimensions for homologically bounded complexes. Among other things we show that (a) these invariants characterize the Cohen-Macaulay property for local rings, (b) Cohen-Macaulay flat dimension fits between the Gorenstein flat dimension and the large restricted f

M. Arthur Munson, Jason Kichen, Dustin Hillard, Ashley Fidler

We describe the motivation and design for esINSIDER, an automated tool that detects potential persistent and insider threats in a network. esINSIDER aggregates clues from log data, over extended time periods, and proposes a small number of cases for human experts to review. The proposed cases package together related information so the analyst can see a bigg

Zhao-Min Chen, Xiu-Shen Wei, Peng Wang, Yanwen Guo

The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model the label dependencies to improve the recognition performance. To capture and explore such important dependencies, we propose a multi-label classification model based on Graph Convolutiona

Guangrun Wang, Keze Wang, Liang Lin

This paper presents a novel adaptively connected neural network (ACNet) to improve the traditional convolutional neural networks (CNNs) {in} two aspects. First, ACNet employs a flexible way to switch global and local inference in processing the internal feature representations by adaptively determining the connection status among the feature nodes (e.g., pix

Zeyuan Sun, Yangfan Yi, Tiancheng Song, Genevieve Clark

Layered antiferromagnetism is the spatial arrangement of ferromagnetic layers with antiferromagnetic interlayer coupling. Recently, the van der Waals magnet, chromium triiodide (CrI3), emerged as the first layered antiferromagnetic insulator in its few-layer form, opening up ample opportunities for novel device functionalities. Here, we discovered an emergen

Difan Zou, Zhengyuan Xu, Chen Gong

Consider a ultraviolet (UV) scattering communication system where the position of the transmitter is fixed and the receiver can move around on the ground. To obtain the link gain effectively and economically, we propose an algorithm based on one-dimensional (1D) numerical integration and an off-line data library. Moreover, we analyze the 2D scattering intens

Nguyen Ngoc Hung, Pham Huu Tiep

The classical Itô-Michler theorem states that the degree of every ordinary irreducible character of a finite group $G$ is coprime to a prime $p$ if and only if the Sylow $p$-subgroups of $G$ are abelian and normal. In an earlier paper, we used the notion of average character degree to prove an improvement of this theorem for the prime $p=2$. In this follow-u

Yu Cao, Jian Huang, Dongrui Wu, Mengshi Zhang

This paper presents an integration of nonlinear disturbance observer within proxy-based sliding mode control (IDO-PSMC) approach for Pneumatic Muscle Actuators (PMAs). Due to the nonlinearities, uncertainties, hysteresis, and time-varying characteristics of the PMA, the model parameters are difficult to be identified accurately, which results in unmeasurable

Feng Shu, Zaoyu Lu, Shuo Zhang, Jin Wang

This paper make an investigation of a secure unmanned aerial vehicle (UAV)-aided communication network based on directional modulation(DM), in which one ground base station (Alice), one legitimate full-duplex (FD) user (Bob) and one illegal receiver (Eve) are involved. In this network, Alice acts as a control center to transmit confidential message and artif

Kazumasa Iida, Taito Omura, Takuya Matsumoto, Takafumi Hatano

We have systematically investigated the grain boundary (GB) angle dependence of transport properties for NdFeAs(O,F) fabricated on [001]-tilt symmetric MgO bicrystal substrates. In our previous study, NdFeAs(O,F) bicrystal films showed a weak-link behaviour even at a GB angle of 6°. However, this was caused by an extrinsic effect originating from the damage

Abram M. Kagan, Paul J. Smith

The basic properties of the Fisher information allow to reveal the statistical meaning of classical inequalities between mean functions. The properties applied to scale mixtures of Gaussian distributions lead to a new mean function of purely statistical origin, unrelated to the classical arithmetic, geometric, and harmonic means. We call it the informational

Henning Koehler

A transitive graph is 2-dimensional if it can be represented as the intersection of two linear orders. Such representations make answering of reachability queries trivial, and allow many problems that are NP-hard on arbitrary graphs to be solved in polynomial time. One may therefore be interested in finding 2-dimensional graphs that closely approximate a giv

Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao

Learning-based hashing algorithms are ``hot topics&#34; because they can greatly increase the scale at which existing methods operate. In this paper, we propose a new learning-based hashing method called ``fast supervised discrete hashing&#34; (FSDH) based on ``supervised discrete hashing&#34; (SDH). Regressing the training examples (or hash code) to the cor

Yamaguchi Kousuke, Tanaka Kanji, Sugimoto Takuma, Ide Rino

Image change detection (ICD) to detect changed objects in front of a vehicle with respect to a place-specific background model using an on-board monocular vision system is a fundamental problem in intelligent vehicle (IV). From the perspective of recent large-scale IV applications, it can be impractical in terms of space/time efficiency to train place-specif

Kojima Yusuke, Tanaka Kanji, Yang Naiming, Hirota Yuji

We present a novel scalable framework for image change detection (ICD) from an on-board 3D imagery system. We argue that existing ICD systems are constrained by the time required to align a given query image with individual reference image coordinates. We utilize an invariant coordinate system (ICS) to replace the time-consuming image alignment with an offli

Hiroki Tomoe, Tanaka Kanji

Most of the current state-of-the-art frameworks for cross-season visual place recognition (CS-VPR) focus on domain adaptation (DA) to a single specific season. From the viewpoint of long-term CS-VPR, such frameworks do not scale well to sequential multiple domains (e.g., spring - summer - autumn - winter - ... ). The goal of this study is to develop a novel

Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao

Data-dependent hashing has recently attracted attention due to being able to support efficient retrieval and storage of high-dimensional data such as documents, images, and videos. In this paper, we propose a novel learning-based hashing method called &#34;Supervised Discrete Hashing with Relaxation&#34; (SDHR) based on &#34;Supervised Discrete Hashing&#34;

Roger Fan, Byoungwook Jang, Yuekai Sun, Shuheng Zhou

Estimating conditional dependence graphs and precision matrices are some of the most common problems in modern statistics and machine learning. When data are fully observed, penalized maximum likelihood-type estimators have become standard tools for estimating graphical models under sparsity conditions. Extensions of these methods to more complex settings wh

Aakash Yadav, PC Deshmukh, Ken Roberts, NM Jisrawi

Advances in optimizing thermoelectric material efficiency have seen a parallel activity in theoretical and computational advances. In the current work, it is shown that the calculation of exact Fermi-Dirac integrals enables the generalization of the Wiedemann-Franz law (WF) to optimize the dimensionless thermoelectric figure of merit ZT. This is done by opti

Harish K. Venkataraman, Peter J. Seiler

Reinforcement learning (RL) is used to directly design a control policy using data collected from the system. This paper considers the robustness of controllers trained via model-free RL. The discussion focuses on the standard model-based linear quadratic Gaussian (LQG) problem as a special instance of RL. A simple example, originally formulated for LQG prob

Mario Teixeira Parente

This paper develops a comprehensive probabilistic setup to compute approximating functions in active subspaces. Constantine et al. proposed the active subspace method in (Constantine et al., 2014) to reduce the dimension of computational problems. It can be seen as an attempt to approximate a high-dimensional function of interest $f$ by a low-dimensional one

Ioannis S Stamatiou

We consider mean-reverting CIR/CEV processes with delay and jumps used as models on the financial markets. These processes are solutions of stochastic differential equations with jumps, which have no explicit solutions. We prove the non-negativity property of the solution of the above models and propose an explicit positivity preserving numerical scheme,usin

Hongchao Zhang, Lixin Xu

A self-consistent model which can unify Starobinsky inflation and the $Λ$CDM model in the framework of Poincaré gauge cosmology (PGC) is studied in this work, without extra inflaton and ``dark energy&#39;&#39;. We start from the general nine-parameter PGC Lagrangian and get two Friedmann-like analytical solutions with the certain ghost- and tachyon-free cond

Zhang-Zhu Han, Jun Xu

The elliptic flow splitting $Δv_2$ between $\bar{u}$ and $u$ quarks as well as between $π^-$ and $π^+$ in midcentral Au+Au collisions at $\sqrt{s_{NN}}=200$ GeV has been studied, based on the framework of an extended multiphase transport model with the partonic evolution described by the chiral kinetic equations of motion. Within the available statistics, th

Huy Phan, Oliver Y. Chén, Lam Pham, Philipp Koch

Acoustic scenes are rich and redundant in their content. In this work, we present a spatio-temporal attention pooling layer coupled with a convolutional recurrent neural network to learn from patterns that are discriminative while suppressing those that are irrelevant for acoustic scene classification. The convolutional layers in this network learn invariant

Yizheng Chen, Shiqi Wang, Dongdong She, Suman Jana

Although state-of-the-art PDF malware classifiers can be trained with almost perfect test accuracy (99%) and extremely low false positive rate (under 0.1%), it has been shown that even a simple adversary can evade them. A practically useful malware classifier must be robust against evasion attacks. However, achieving such robustness is an extremely challengi