November 2018 arXiv papers — page 11

Fugen Torunbalci Aydin

In this paper, hyperbolic k-Fibonacci quaternions are defined. Also, some algebraic properties of hyperbolic k-Fibonacci quaternions which are connected with hyperbolic numbers and k-Fibonacci numbers are investigated. Furthermore, D'Ocagne's identity, the Honsberger identity, Binet's formula, Cassini's identity and Catalan's identity for these quaternions a

Jun-Hyuk Kim, Jun-Ho Choi, Manri Cheon, Jong-Seok Lee

In recent years, single image super-resolution (SR) methods based on deep convolutional neural networks (CNNs) have made significant progress. However, due to the non-adaptive nature of the convolution operation, they cannot adapt to various characteristics of images, which limits their representational capability and, consequently, results in unnecessarily

Zhan-Chao Hu, Stephen H. Davis, Xin-Rong Zhang

Near the thermodynamic critical point, the physical properties of binary fluids exhibit large variations in response to small temperature and concentration differences, whose effects on the onset of double-diffusive convection are reported here. The vertical symmetry is broken, irregular penetrative instability occurs, and cat's eye patterns are identified i

F. E. Burstall

We characterise the canonical elements, in the sense of Burstall--Rawnsley \cite{BurRaw90}, of a compact semisimple Lie algebra and discuss the case of $\mathfrak{so}(n)$ in detail. In so doing, we correct two errors in Burstall et al. \cite{BurEscFerTri04}.

Brendan Avent, Yatharth Dubey, Aleksandra Korolova

We explore the power of the hybrid model of differential privacy (DP), in which some users desire the guarantees of the local model of DP and others are content with receiving the trusted-curator model guarantees. In particular, we study the utility of hybrid model estimators that compute the mean of arbitrary real-valued distributions with bounded support.

Iñigo Alonso, Ana C. Murillo

Event cameras, or Dynamic Vision Sensor (DVS), are very promising sensors which have shown several advantages over frame based cameras. However, most recent work on real applications of these cameras is focused on 3D reconstruction and 6-DOF camera tracking. Deep learning based approaches, which are leading the state-of-the-art in visual recognition tasks, c

Hiroaki Ishida, Roman Krutowski, Taras Panov

We describe the basic cohomology ring of the canonical holomorphic foliation on a moment-angle manifold, LVMB-manifold or any complex manifold with a maximal holomorphic torus action. Namely, we show that the basic cohomology has a description similar to the cohomology ring of a complete simplicial toric variety due to Danilov and Jurkiewicz. This settles a

Hayato Takahashi

In this paper we show the distributions of sliding block patterns for Bernoulli processes with finite alphabet, which is not based on the induction on sample size. We show a new inclusion-exclusion formula in multivariate generating function form on partially ordered sets, and show a simpler expression of generating functions of the number of pattern occurre

Takashi Tsukagoshi, Munetake Momose, Yoshimi Kitamura, Masao Saito

We report $0.14"$ resolution observations of the dust continuum at band 7, and the CO(3--2) and HCO$^{+}$(4--3) line emissions toward the transitional disk around Sz 91 with Atacama Large Millimeter/submillimeter Array (ALMA). The dust disk appears to be an axisymmetric ring, peaking a radius of $\sim$95~au from a Gaussian fit. The Gaussian fit widths of the

Siwen Jiang, Wenxuan Wei, Shihao Guo, Hongguang Fu

At present, the great achievements of convolutional neural network(CNN) in feature and metric learning have attracted many researchers. However, the vast majority of deep network architectures have been used to represent based on real values. The research of complex-valued networks is seldom concerned due to the absence of effective models and suitable dista

Valentina Brosco, Massimo Capone

The recent discovery of materials featuring strong Rashba spin-orbit coupling (RSOC) and strong electronic correlation raises questions about the interplay of Mott and Rashba physics. In this work, we employ cluster perturbation theory to investigate the spectral properties of the two-dimensional Hubbard model in the presence of a significant or large RSOC.

Antoni Szczurek

We discuss some new aspects of charm production trigerred by recent observations of the LHCb collaboration. The LHCb collaboration measured small asymmetries in production of $D^+ D^-$ mesons as well as $D_s^+ D_s^-$ mesons. Is this related to initial quark/antiquark asymmetries in the proton ? Here we discuss a scenario in which unfavored fragmentations $q/

Jeff J. Andrews, Borja Anguiano, Julio Chanamé, Marcel A. Agüeros

Stars of a common origin are thought to have similar, if not nearly identical, chemistry. Chemical tagging seeks to exploit this fact to identify Milky Way subpopulations through their unique chemical fingerprints. In this work, we compare the chemical abundances of dwarf stars in wide binaries to test the abundance consistency of stars of a common origin. O

Deepak Sarma

In this article, we establish some bounds involving the largest two distance Pareto eigenvalues of a connected graph. Also we characterize all possible values for smallest six distance Pareto eigenvalues of a connected graph.

Xin Lu, Buyu Li, Yuxin Yue, Quanquan Li

This paper proposes a novel object detection framework named Grid R-CNN, which adopts a grid guided localization mechanism for accurate object detection. Different from the traditional regression based methods, the Grid R-CNN captures the spatial information explicitly and enjoys the position sensitive property of fully convolutional architecture. Instead of

Movaffaq Kateb, Egill Jacobsen, Snorri Ingvarsson

We demonstrate anisotropic resistivity measurements using the extended van der Pauw (vdP) method in ferromagnetic Ni80Fe20 (Py) films. We apply it to measure anisotropic magnetoresistance (AMR) and compare the results of the vdP method with the more conventional Hall-bar method along the hard and easy axis of the film and show that the vdP method gives more

Hiromasa Kitai, Jason Paul Cruz, Naoto Yanai, Naohisa Nishida

A privacy-preserving framework in which a computational resource provider receives encrypted data from a client and returns prediction results without decrypting the data, i.e., oblivious neural network or encrypted prediction, has been studied in machine learning that provides prediction services. In this work, we present MOBIUS (Model-Oblivious BInary neUr

Elena Pierro, Francesco Bottiglione, Giuseppe Carbone

We discuss the Brownian thermal noise which affects the cantilever dynamics of a dAFM (dynamic atomic force microscope), both when it works in air and in presence of water. Our scope is to accurately describe the cantilever dynamics, and to get this result we deeply investigate the relationship between the cantilever thermal fluctuations and its interactions

Qing Song, Yingqi Wu, Lu Yang

With the broad use of face recognition, its weakness gradually emerges that it is able to be attacked. So, it is important to study how face recognition networks are subject to attacks. In this paper, we focus on a novel way to do attacks against face recognition network that misleads the network to identify someone as the target person not misclassify incon

Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri, Rituraj Singh

Computational analysis on physiological signals would provide immense impact for enabling automated clinical analytics. However, the class imbalance issue where negative or minority class instances are rare in number impairs the robustness of the practical solution. The key idea of our approach is intelligent augmentation of minority class examples to constr

Atefeh Javadi, Jacco Th. van Loon

The evolution of galaxies is driven by the birth and death of stars. AGB stars are at the end points of their evolution and therefore their luminosities directly reflect their birth mass; this enables us to reconstruct the star formation history. These cool stars also produce dust grains that play an important role in the temperature regulation of the inters

S. M. Troshin, N. E. Tyurin

The reflective scattering mode is supposed to play a significant role in hadron interactions at the LHC energy region and beyond. We discuss connection of this mode to the color conducting medium formation in hadron collisions and its role in centrality determination. The issues of centrality in view of the measurements at the LHC are relevant for enlighteni

Marco Edoardo Rosti, Stefano Olivieri, Arash A. Banaei, Luca Brandt

The flapping states of a flexible fiber fully coupled to a three-dimensional turbulent flow are investigated via state-of-the-art numerical methods. Two distinct flapping regimes are predicted by the phenomenological theory recently proposed by Rosti et al. [Phys. Rev. Lett. 121, 044501, 2018]: the under-damped regime, where the elasticity strongly affects t

M. R. Gafurov, G. V. Mamin, E. I. Baibekov, I. N. Kurkin

We have demonstrated electron-electron and electron-nuclear spin manipulations of Gd3+ ion in CaWO4 crystal. The results suggest that the studied system is perspective for multiqubit implementation in quantum computing.

Victor Volfson

The summation arithmetic functions with asymptotically independent summands are studied in the paper. We prove statements about the condition under which the summation arithmetic functions have asymptotically independent summands. It is also prove that the limiting distribution of the summation arithmetic function with asymptotically independent summands is

Yan Li, Xiaohua Zhu

In this paper, we compute Tian's $\alpha_{m,k}^{K\times K}$-invariant on a polarized $G$-group compactification, where $K$ denotes a maximal compact subgroup of a connected complex reductive group $G$. We prove that Tian's conjecture (see Conjecture 1.1 below) is true for $\alpha_{m,k}^{K\times K}$-invariant on such manifolds when $k=1$, but it fails in gene

Frank Göhmann, Salvish Goomanee, Karol K. Kozlowski, Junji Suzuki

This work develops a rigorous setting allowing one to prove several features related to the behaviour of the Heisenberg-Ising (or XXZ) spin-$1/2$ chain at finite temperature $T$. Within the quantum inverse scattering method the physically pertinent observables at finite $T$, such as the \textit{per}-site free energy or the correlation length, have been argue

Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse

Large-scale distributed training of deep neural networks suffer from the generalization gap caused by the increase in the effective mini-batch size. Previous approaches try to solve this problem by varying the learning rate and batch size over epochs and layers, or some ad hoc modification of the batch normalization. We propose an alternative approach using

P. Schuck

A comparison of pairing properties in cuprates and nuclear matter is briefly discussed. Quartet (alpha-particle) condensation is a very important aspect of nuclear physics. The physics of the Hoyle state in 12 C will be outlined and its crucial role for the existence of life on earth explained.

Daniil Polykovskiy, Alexander Zhebrak, Benjamin Sanchez-Lengeling, Sergey Golovanov

Generative models are becoming a tool of choice for exploring the molecular space. These models learn on a large training dataset and produce novel molecular structures with similar properties. Generated structures can be utilized for virtual screening or training semi-supervised predictive models in the downstream tasks. While there are plenty of generative

Lijie Chen, Ryan Williams

The Orthogonal Vectors problem ($\textsf{OV}$) asks: given $n$ vectors in $\{0,1\}^{O(\log n)}$, are two of them orthogonal? $\textsf{OV}$ is easily solved in $O(n^2 \log n)$ time, and it is a central problem in fine-grained complexity: dozens of conditional lower bounds are based on the popular hypothesis that $\textsf{OV}$ cannot be solved in (say) $n^{1.9

Yi-Lun Liao, Yao-Cheng Yang, Yu-Chiang Frank Wang

Aiming at inferring 3D shapes from 2D images, 3D shape reconstruction has drawn huge attention from researchers in computer vision and deep learning communities. However, it is not practical to assume that 2D input images and their associated ground truth 3D shapes are always available during training. In this paper, we propose a framework for semi-supervise

Clementine Cottineau, Maarten Vanhoof

Thanks to the use of geolocated big data in computational social science research, the spatial and temporal heterogeneity of human activities are increasingly being revealed. Paired with smaller and more traditional data, this opens new ways of understanding how people act and move, and how these movements crystallise into the structural patterns observed by

Zhihua Liu, Pierre Magal

In this article we study a class of delay differential equations with infinite delay in weighted spaces of uniformly continuous functions. We focus on the integrated semigroup formulation of the problem and so doing we provide an spectral theory. As a consequence we obtain a local stability result and a Hopf bifurcation theorem for the semiflow generated by

Xiang Gao, Wei Hu, Jiaxiang Tang, Jiaying Liu

With the prevalence of accessible depth sensors, dynamic human body skeletons have attracted much attention as a robust modality for action recognition. Previous methods model skeletons based on RNN or CNN, which has limited expressive power for irregular skeleton joints. While graph convolutional networks (GCN) have been proposed to address irregular graph-

Jarosław Grytczuk, Xuding Zhu

This paper proves that every planar graph $G$ contains a matching $M$ such that the Alon-Tarsi number of $G-M$ is at most $4$. As a consequence, $G-M$ is $4$-paintable, and hence $G$ itself is $1$-defective $4$-paintable. This improves a result of Cushing and Kierstead [Planar Graphs are 1-relaxed, 4-choosable, {\em European Journal of Combinatorics} 31(2010

Robert A. Neiss, Peter Pickl

The derivation of effective equations for interacting many body systems has seen a lot of progress in the recent years. While dealing with classical systems, singular potentials are quite challenging, comparably strong results are known to hold for quantum systems. In this paper, we wish to show how techniques developed for the derivation of effective descri

Audace A. V. Dossou-Olory, Stephan Wagner

The quantity that captures the asymptotic value of the maximum number of appearances of a given topological tree (a rooted tree with no vertices of outdegree $1$) $S$ with $k$ leaves in an arbitrary tree with sufficiently large number of leaves is called the inducibility of $S$. Its precise value is known only for some specific families of trees, most of the

Prasad Perlekar

We conduct direct numerical simulation (DNS) of the Cahn-Hilliard-Navier-Stokes (CHNS) equations to investigate the statistical properties of the turbulent phase-separating symmetric binary-fluid mixture. Turbulence causes an arrest of the phase-separation which leads to the formation of a statistically steady emulsion. We characterize turbulent velocity flu

Timo Sämann, Karl Amende, Stefan Milz, Christian Witt

The ability to perform semantic segmentation in real-time capable applications with limited hardware is of great importance. One such application is the interpretation of the visual bird's-eye view, which requires the semantic segmentation of the four omnidirectional camera images. In this paper, we present an efficient semantic segmentation that sets new st

Olivier Guédon, A. E. Litvak, K. Tatarko

Let $\Gamma$ be an $N\times n$ random matrix with independent entries and such that in each row entries are i.i.d. Assume also that the entries are symmetric, have unit variances, and satisfy a small ball probabilistic estimate uniformly. We investigate properties of the corresponding random polytope $\Gamma^* B_1^N$ in $\mathbb{R}$ (the absolute convex hull

Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li

Deep Convolutional Networks (ConvNets) are fundamental to, besides large-scale visual recognition, a lot of vision tasks. As the primary goal of the ConvNets is to characterize complex boundaries of thousands of classes in a high-dimensional space, it is critical to learn higher-order representations for enhancing non-linear modeling capability. Recently, Gl

Siddhartha Mukherjee, Jayabrata Dhar, Sunando DasGupta, Suman Chakraborty

The performances of lubricated systems widely used in natural, biological, and artificial settings are traditionally dictated by their load bearing capacities. Here we unveil that, by exploiting a unique coupling between interfacial electro-mechanics, hydrodynamics and substrate compliance, it is plausible to realize a massive augmentation in the load bearin

Daniil Osokin

In this work we adapt multi-person pose estimation architecture to use it on edge devices. We follow the bottom-up approach from OpenPose, the winner of COCO 2016 Keypoints Challenge, because of its decent quality and robustness to number of people inside the frame. With proposed network design and optimized post-processing code the full solution runs at 28

Sumit Kumar, Pawan Kumar, Sunando DasGupta, Suman Chakraborty

The wetting of solid surfaces can be manoeuvred by altering the energy balance at the interfacial region. While electric field acts favourably to spread a droplet on a rigid surface, this tendency may be significantly suppressed over soft surfaces, considering a part of the interfacial energy being utilized to deform the solid elastically by capillary forces

Huseyin Coskun

This article develops a new mathematical method for holistic analysis of nonlinear dynamic compartmental systems through the system decomposition theory. The method is based on the novel dynamic system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. The dynamic system and subsystem partitioning

Y. H. Zhang, Yu. A. Litvinov, T. Uesaka, H. S. Xu

In the last two and a half decades ion storage rings have proven to be powerful tools for precision experiments with unstable nuclides in realm of nuclear structure and astrophysics. There are presently three storage ring facilities in the world at which experiments with stored radioactive ions are possible. These are the ESR in GSI, Darmstadt/Germany, the C

Aous Karoui, Iza Marfisi-Schottman, Sébastien George

Mobile Learning Games (MLGs) show great potential for increasing engagement, creativity and authentic learning. Yet, despite their great potential for education, the use of MLGs by teachers, remains limited. This is partly due to the fact that MLGs are often designed to match a specific learning context, and thus cannot be reusable for other contexts. Theref

H. Ebrahim, M. Asadi, M. Ali-Akbari

The holographic complexity has been studied in a background which includes a critical point in the dual field theory. We have examined how the complexity rate and the saturation time of dynamical variables in the theory behave as one moves towards the critical point. Two significant results of our analysis are that (i) it takes more time for the complexity i

A. G. Karapetyan, A. A. Hakobyan, L. V. Barkhudaryan, G. A. Mamon

We present an analysis of the impact of spiral density waves (DWs) on the radial and surface density distributions of core-collapse (CC) supernovae (SNe) in host galaxies with different arm classes. For the first time, we show that the corotation radius normalized surface density distribution of CC SNe (tracers of massive star formation) indicates a dip at c

Yann Traonmilin, Jean-François Aujol

The sparse spike estimation problem consists in estimating a number of off-the-grid impulsive sources from under-determined linear measurements. Information theoretic results ensure that the minimization of a non-convex functional is able to recover the spikes for adequately chosen measurements (deterministic or random). To solve this problem, methods inspir

Oleg N. German

In this paper we give a survey of what is currently known about Diophantine exponents of lattices and propose several problems.

Bitan De, Bhaskaran Muralidharan

The anomalous behavior of electron induced phonon transport is investigated using an Anderson-Holstein based dissipative quantum dot setup under two relevant bias situations: (a) a voltage bias in the absence of an electronic temperature gradient and (b) an electronic temperature gradient at zero voltage. It is shown that the direction of phonon transport in

K. Manikandan, Ayush Patidar, Pallav Walia, Aneek Barman Roy

The hand gestures are one of the typical methods used in sign language. It is very difficult for the hearing-impaired people to communicate with the world. This project presents a solution that will not only automatically recognize the hand gestures but will also convert it into speech and text output so that impaired person can easily communicate with norma

Luna M. Zhang

Convolutional Neural Networks (CNNs) usually use the same activation function, such as RELU, for all convolutional layers. There are performance limitations of just using RELU. In order to achieve better classification performance, reduce training and testing times, and reduce power consumption and memory usage, a new "Compressed Multi-function CNN" is devel

Eriko Kaminishi, Takashi Mori

Quantum systems exhibit recurrence phenomena after equilibration, but it is a difficult task to evaluate the recurrence time of a quantum system because it drastically increases as the system size increases (usually double-exponential in the number of particles) and strongly depends on the initial state. Here, we analytically derive the recurrence times of t

B. -Q. Liu, P. Čermák, C. Franz, C. Pfleiderer

We report first principles calculations of the structural parameters and phonon dispersion of the tetragonal non-centrosymmetric heavy fermion compound CeAuAl$_3$. Taking into account weak magnetoelastic interactions of the rare-earth (RE) ions with the spectrum of phonons, we obtain an analytical expression for the hybridization of quadrupole excitations an

Juni-ichi Inoguchi, Marian Ioan Munteanu

We investigate contact magnetic curves in the real special linear group of degree 2. They are geodesics of the Hopf tubes over the projection curve. We prove that periodic contact magnetic curves in SL(2,R) can be quantized in the set of rational numbers. Finally, we study contact homogeneous magnetic trajectories in SL(2,R) and show that they project to hor

Ruijian He, Bo Yang, Hui Liu, Zhangxin Chen

As a competitive recovery method for heavy oil, In-Situ Combustion (ISC) shows its great potential accompanied by technological advances in recent years. Reservoir simulation will play an indispensable role in the prediction of the implementation of ISC projects. With the computational complexity, it is imperative to develop an effective and robust parallel

Yahui Sun

The Steiner tree problems are well-known NP-hard problems that have diverse applications. Duin et al. (2004) have intuitively proposed the widely-used transformation from the classical group Steiner tree problem to the classical Steiner tree problem in graphs. This transformation has not been rigorously proven so far. Specifically, the large M value that is

Yutaro Miyauchi, Yusuke Sugano, Yasuyuki Matsushita

Conditional image generation is effective for diverse tasks including training data synthesis for learning-based computer vision. However, despite the recent advances in generative adversarial networks (GANs), it is still a challenging task to generate images with detailed conditioning on object shapes. Existing methods for conditional image generation use c

V. A. Khokhlov, N. A. Inogamov, V. V. Zhakhovsky, Yu. V. Petrov

Laser ablation in liquid (LAL) is important technique used for formation of nanoparticles (NP). The LAL processes cover logarithmically wide range of spatiotemporal scales and is not fully understood. The NP produced by LAL are rather expensive, thus optimization of involved processes is valuable. As the first step to such optimizations more deep understandi

Dongruo Zhou, Pan Xu, Quanquan Gu

We propose a sample efficient stochastic variance-reduced cubic regularization (Lite-SVRC) algorithm for finding the local minimum efficiently in nonconvex optimization. The proposed algorithm achieves a lower sample complexity of Hessian matrix computation than existing cubic regularization based methods. At the heart of our analysis is the choice of a cons

G. K. Singh, G. Purwar, R. Patel, V. L. Tanna

In cryogenic two phase flow, it is always challenging to measure the quality and void fraction. In this regard, an effort has been made to indigenously develop an electronic circuit to measure the void fraction by measuring the capacitance of the order of picofarads accurately depending upon the dielectric constant of nitrogen in vapor and liquid phase. The

Laurent Boué

The goal of this document is to provide a pedagogical introduction to the main concepts underpinning the training of deep neural networks using gradient descent; a process known as backpropagation. Although we focus on a very influential class of architectures called "convolutional neural networks" (CNNs) the approach is generic and useful to the machine lea

Manik Singhal, Tolunay Seyfi, Aly El Gamal

We study information theoretic models of interference networks that consist of K Base Station (BS) - Mobile Terminal (MT) pairs. Each BS is connected to the MT carrying the same index as well as L following MTs. We fix the value of L and study the per user Degrees of Freedom (puDoF) in large networks. We assume that each MT can be associated with N BSs, and

Ken Sakurada, Mikiya Shibuya, Weimin Wang

This paper presents a novel semantic scene change detection scheme with only weak supervision. A straightforward approach for this task is to train a semantic change detection network directly from a large-scale dataset in an end-to-end manner. However, a specific dataset for this task, which is usually labor-intensive and time-consuming, becomes indispensab

Tetsuyuki Ochiai

A network model that can describe light propagation in one-dimensional ring-resonator arrays with a dimer structure is studied as a Su-Schrieffer-Heeger-type Floquet network. The model can be regarded as a Floquet system without periodic driving and exhibits quasienergy band structures of the ring propagation phase. Resulting band gaps support deterministic

Anas Bilal, Aimal Rextin, Ahmad Kakakhail, Mehwish Nasim

While users in the developed world can choose to adopt the technology that suits their needs, the emergent users cannot afford this luxury, hence, they adapt themselves to the technology that is readily available. When technology is designed, such as the mobile-phone technology, it is an implicit assumption that it would be adopted by the emergent users in d

Tomokage Yoneyama, Kiyoshi Hayashida, Hiroshi Nakajima, Hironori Matsumoto

Strongly magnetized isolated neutron stars (NSs) are categorized into two families, according mainly to their magnetic field strength. The one with a higher magnetic field of $10^{14}$ - $10^{15}$ G is called magnetar, characterized with repeated short bursts, and the other is X-ray isolated neutron star (XINS) with $10^{13}$ G. Both magnetars and XINSs show

Tiantian Mao, Bin Wang, Ruodu Wang

In this paper, we analyze the set of all possible aggregate distributions of the sum of standard uniform random variables, a simply stated yet challenging problem in the literature of distributions with given margins. Our main results are obtained for two distinct cases. In the case of dimension two, we obtain four partial characterization results. An analyt

Alexey E. Rastegin

We accomplish studies of properly quantifying eavesdropper's information gain in individual attacks on the BB84 system of quantum key distribution. A noticeable sensitivity of conclusions to the choice of information measures is brightly revealed, when generalized state discrimination is used at the last stage. To realize her aims, Eve intrudes into the comm

Hadi Kazemi, Sobhan Soleymani, Fariborz Taherkhani, Seyed Mehdi Iranmanesh

Unsupervised image-to-image translation is a class of computer vision problems which aims at modeling conditional distribution of images in the target domain, given a set of unpaired images in the source and target domains. An image in the source domain might have multiple representations in the target domain. Therefore, ambiguity in modeling of the conditio

Shreshth Tuli, Redowan Mahmud, Shikhar Tuli, Rajkumar Buyya

The requirement of supporting both latency sensitive and computing intensive Internet of Things (IoT) applications is consistently boosting the necessity for integrating Edge, Fog and Cloud infrastructure. Although there are a number of real-world frameworks attempt to support such integration, they have many limitations from various perspectives including p

Shang-Ta Yang, Fu-En Wang, Chi-Han Peng, Peter Wonka

We present a deep learning framework, called DuLa-Net, to predict Manhattan-world 3D room layouts from a single RGB panorama. To achieve better prediction accuracy, our method leverages two projections of the panorama at once, namely the equirectangular panorama-view and the perspective ceiling-view, that each contains different clues about the room layouts.

Christoph Saulder, Steffen Mieske, Eelco van Kampen, Werner W. Zeilinger

Context. Backreactions from large-scale inhomogeneities may provide an elegant explanation for the observed accelerated expansion of the universe without the need to introduce dark energy. Aims. We propose a cosmological test for a specific model of inhomogeneous cosmology, called timescape cosmology. Using large-scale galaxy surveys such as SDSS and 2MRS, w

Yaadhav Raaj, Haroon Idrees, Gines Hidalgo, Yaser Sheikh

We present an online approach to efficiently and simultaneously detect and track the 2D pose of multiple people in a video sequence. We build upon Part Affinity Field (PAF) representation designed for static images, and propose an architecture that can encode and predict Spatio-Temporal Affinity Fields (STAF) across a video sequence. In particular, we propos

Rafael N. Alexander, Amr Ahmadain, Zhao Zhang, Israel Klich

We present bulk tensor networks that exactly represent the ground states of a continuous family of one-dimensional frustration-free Hamiltonians. These states, which are known as area-deformed Motzkin and Fredkin states, exhibit a novel quantum phase transition. By tuning a single parameter, they go from a phase obeying an area law to a highly entangled rain

Yi-Chen Zhang, Ziyang Chen, Christian Weedbrook, Song Yu

The continuous-variable quantum key distribution with entanglement in the middle, a semi-device-independent protocol, places the source at the untrusted third party between Alice and Bob, and thus has the advantage of high levels of security with the purpose of eliminating the assumptions about the source device. However, previous works considered the collec

Koichi Oyanagi, Saburo Takahashi, Ludo J. Cornelissen, Juan Shan

The discovery of new materials that efficiently transmit spin currents has been important for spintronics and material science. The electric insulator $\mathrm{Gd}_3\mathrm{Ga}_5\mathrm{O}_{12}$ (GGG) is a superior substrate for growing magnetic films, but has never been considered as a conduit for spin currents. Here we report spin current propagation in pa

Xinhang Zhang, Haoyuan Hu, Longfei Wang, Zhijun Sun

Packing cost accounts for a large part of the e-commerce logistics cost. Mining the patterns of customer orders and designing suitable packing bins help to reduce operating cost. In the classical bin packing problem, a given set of cuboid-shaped items should be packed into bins with given and fixed-sizes (length, width and height) to minimize the number of b

Shujian Yu, Jose C. Principe

Feature selection aims to select the smallest feature subset that yields the minimum generalization error. In the rich literature in feature selection, information theory-based approaches seek a subset of features such that the mutual information between the selected features and the class labels is maximized. Despite the simplicity of this objective, there

Antoine Deza, Kai Huang, Michael R. Metel

This work focuses on finding optimal locations for charging stations for one-way electric car sharing programs. The relocation of vehicles by a service staff is generally required in vehicle sharing programs in order to correct imbalances in the network. We seek to limit the need for vehicle relocation by strategically locating charging stations given estima

Lijun Yu, Dawei Zhang, Xiangqun Chen, Alexander Hauptmann

We propose a traffic danger recognition model that works with arbitrary traffic surveillance cameras to identify and predict car crashes. There are too many cameras to monitor manually. Therefore, we developed a model to predict and identify car crashes from surveillance cameras based on a 3D reconstruction of the road plane and prediction of trajectories. F

Ning Liu, Yongchao Long, Changqing Zou, Qun Niu

We propose an attention-injective deformable convolutional network called ADCrowdNet for crowd understanding that can address the accuracy degradation problem of highly congested noisy scenes. ADCrowdNet contains two concatenated networks. An attention-aware network called Attention Map Generator (AMG) first detects crowd regions in images and computes the c

Nahomi Kan, Kiyoshi Shiraishi, Mai Yashiki

We present a gravitational action with a modified higher order term of a combination of scalar curvature and Lagrangian density of a scalar field. This type of models has been considered first by Cruz-Dombriz et al. The classical and quantum cosmologies governed by the modified action are studied. Models described by a positive-definite action and a pure arb

Laiachi El Kaoutit, Leonardo Spinosa

We explore the category of internal categories in the usual category of (right) group-sets, whose objects are referred to as categorified group-sets. More precisely, we develop a new Burnside theory, where the equivalence relation between two categorified group-sets is given by a particular equivalence between the underlying categories. We also exhibit some

K. A. Marsh, A. P. Whitworth

We present resolution-enhanced images of warm dust at multiple temperatures and opacity index values in the star-forming bubble/HII region, RCW 120. The image set, representing a 4D hypercube of differential column density, was obtained using our Bayesian procedure, ppmap. The cool peripheral material ($\sim16$-22 K) exhibits ragged clumpy structure as noted

Saudamini Nayak, Rudra Narayan Padhan, Kishor Chandra Pati

Isoclinism of Lie superalgebras has been defined and studied currently. In this article it is shown that for finite dimensional Lie superalgebras of same dimension, the notation of isoclinism and isomorphism are equivalent. Furthermore we show that covers of finite dimensional Lie superalgebras are isomorphic using isoclinism concept.

Asta Heinesen, Chris Blake, Yong-Zhuang Li, David L. Wiltshire

We develop methods for investigating baryon acoustic oscillation (BAO) features in cosmological models with non-trivial (but slowly varying) averaged spatial curvature: models that are not necessarily flat, close to flat, nor with constant spatial curvature. The class of models to which our methods apply include Lemaitre-Tolman-Bondi models, modified gravity

Jeffrey M. Hokanson, Caleb C. Magruder

In many applications throughout science and engineering, model reduction plays an important role replacing expensive large-scale linear dynamical systems by inexpensive reduced order models that capture key features of the original, full order model. One approach to model reduction finds reduced order models that are locally optimal approximations in the $\m

Denis Firsov, Larry Diehl, Christopher Jenkins, Aaron Stump

In the categorical setting, histomorphisms model a course-of-value recursion scheme that allows functions to be defined using arbitrary previously computed values. In this paper, we use the Calculus of Dependent Lambda Eliminations (CDLE) to derive a lambda-encoding of inductive datatypes that admits course-of-value induction. Similar to course-of-value recu

Leanne Dong

Building upon the well-posedness results in \cite{snse1}, in this note we prove the existence of invariant measures for the stochastic Navier-Stokes equations with stable L\'evy noise. The crux of our proof relies on the assumption of finite dimensional L\'evy noise.

Felix G. Hamza-Lup, Jannick P. Rolland, Charles Hughes

Augmented Reality (AR) systems describe the class of systems that use computers to overlay virtual information on the real world. AR environments allow the development of promising tools in several application domains. In medical training and simulation the learning potential of AR is significantly amplified by the capability of the system to present 3D medi

Gaurav Sheni, Benjamin Schreck, Roy Wedge, James Max Kanter

In this paper, we present a data science automation system called Prediction Factory. The system uses several key automation algorithms to enable data scientists to rapidly develop predictive models and share them with domain experts. To assess the system's impact, we implemented 3 different interfaces for creating predictive modeling projects: baseline auto

A. Fang, K. Kroenlein, A. Smolyanitsky

We use all-atom molecular dynamics simulations informed by density functional theory calculations to investigate aqueous ion transport across sub-nanoporous monolayer molybdenum disulfide (MoS$_2$) membranes subject to varying tensile strains. Driven by a transmembrane electric field, highly mechanosensitive permeation of both anions and cations is demonstra

Yuhui Zhang, Allen Nie, James Zou

Supervised learning is limited both by the quantity and quality of the labeled data. In the field of medical record tagging, writing styles between hospitals vary drastically. The knowledge learned from one hospital might not transfer well to another. This problem is amplified in veterinary medicine domain because veterinary clinics rarely apply medical code

Brendan J. Orenstein, Jordan D. Collier, Ray P. Norris

Infrared-Faint Radio Sources (IFRSs) are an important class of high-redshift active galaxy, and potentially important as a means of discovering more high-redshift radio sources, but only 25 IFRSs had redshifts prior to this paper. Here we increase the number of IFRSs with known spectroscopic redshifts by a factor of about 5 to 131, with redshifts up to z=4.3

Souradeep Majumder, Ronnie Sebastian

Let $C$ be a smooth, projective, geometrically irreducible curve defined over $\mathbb{R}$ such that $C(\mathbb{R}) = \emptyset$. Let $r>0$ and $d$ be integers which are coprime. Let $L$ be a line bundle on $C$ which corresponds to an $\mathbb{R}$ point of ${\rm Pic}^d_{C/\mathbb{R}}$. Let $\mathcal{M}_{r,L}$ be the moduli space of stable bundles on the comp

Felix G. Hamza-Lup, Charles Hughes, Jannick P. Rolland

With the advances in sensors and computer networks an increased number of Mixed Reality (MR) applications require large amounts of information from the real world. Such information is collected through sensors (e.g. position and orientation tracking sensors). These sensors collect data from the physical environment in real-time at different locations and a d