November 2019 arXiv papers — page 37

Menatallh Hammad, May Hammad, Mohamed Elshenawy

The task of video captioning, that is, the automatic generation of sentences describing a sequence of actions in a video, has attracted an increasing attention recently. The complex and high-dimensional representation of video data makes it difficult for a typical encoder-decoder architectures to recognize relevant features and encode them in a proper format

Qingxin Meng, Kerrianne Harrington, Julian Stirling, Richard Bowman

As 3D printers become more widely available, researchers are able to rapidly produce components that may have previously taken weeks to have machined. The resulting plastic components, having high surface roughness, are often not suitable for high-precision optomechanics. However, by playing to the strengths of 3D printing---namely the ability to print compl

Rongrong Jiang, Dehua Wen, Houyuan Chen

Similar to the compactness parameter ($\beta=M/R$), the gravitational binding energy (GBE) is also a characteristic parameter which can reflect the internal structure of a neutron star and thus can be used to expressing the universal relations. Scaling by the stellar mass, this investigation demonstrates a perfect universal relation between the GBE and the m

Zeyu Sun, Qihao Zhu, Yingfei Xiong, Yican Sun

A code generation system generates programming language code based on an input natural language description. State-of-the-art approaches rely on neural networks for code generation. However, these code generators suffer from two problems. One is the long dependency problem, where a code element often depends on another far-away code element. A variable refer

M. A. Amirabadi

One of the main problems encountered with Free Space Optical (FSO) Communication system is the atmospheric turbulence. Although many solutions exist for combating this effect, they have either high complexity or low performance. In this paper, a comprehensive investigation is developed, and three new effective Deep Learning (DL) based solutions are proposed.

Jonathan W. Bartlett, Rachael A. Hughes

Multiple imputation has become one of the most popular approaches for handling missing data in statistical analyses. Part of this success is due to Rubin's simple combination rules. These give frequentist valid inferences when the imputation and analysis procedures are so called congenial and the complete data analysis is valid, but otherwise may not. Ro

Jeff Hicks

Biran and Cornea showed that monotone Lagrangian cobordisms give an equivalence of objects in the Fukaya category. However, there are currently no known non-trivial examples of monotone Lagrangian cobordisms with two ends. We look at an extension of their theory to the pearly model of Lagrangian Floer cohomology and unobstructed Lagrangian cobordisms. In par

Alejandro Garcia-Quismondo, Guillermo A. Mena Marugan

We discuss the quantization of vacuum Bianchi I spacetimes in the modified formalism of loop quantum cosmology recently proposed by Dapor and Liegener. This modification is based on a regularization procedure where both the Euclidean and Lorentzian terms of the Hamiltonian are treated independently. Whereas the Euclidean part has already been dealt with in t

Eirini Troullinou, Grigorios Tsagkatakis, Spyridon Chavlis, Gergely Turi

Identification of different neuronal cell types is critical for understanding their contribution to brain functions. Yet, automated and reliable classification of neurons remains a challenge, primarily because of their biological complexity. Typical approaches include laborious and expensive immunohistochemical analysis while feature extraction algorithms ba

Martin Azkarate, Levin Gerdes, Luc Joudrier, Carlos J. Pérez-del-Pulgar

This paper proposes a Guidance, Navigation, and Control (GNC) architecture for planetary rovers targeting the conditions of upcoming Mars exploration missions such as Mars 2020 and the Sample Fetching Rover (SFR). The navigation requirements of these missions demand a control architecture featuring autonomous capabilities to achieve a fast and long traverse.

Raffaella Burioni, Alessandro Vezzani

Rare events in stochastic processes with heavy-tailed distributions are controlled by the big jump principle, which states that a rare large fluctuation is produced by a single event and not by an accumulation of coherent small deviations. The principle has been rigorously proved for sums of independent and identically distributed random variables and it has

Tero Harju

We consider words $w$ over the alphabet $\Sigma=\{0,1,2\}$. It is shown that there are irreducibly square-free words of all lengths $n$ except 4,5,7 and 12. Such a word is square-free (i.e., it has no repetitions $uu$ as factors), but by removing any one internal letter creates a square in the word.

Suhail Masda, J. A. Docobo, A. Hussein, M. Mardini

The precise determination of the physical and dynamical parameters of the HIP 109951 triple star system (WDS J22161-0705AB) which is formed by the A, Ba, and Bb components are presented. The binary nature of component B was recently confirmed by studying the radial velocities. The analysis of the system follows Al-Wardat's complex method for analyzing CVBS w

Felipe Gomez-Cuba, Andrea J. Goldsmith

This paper analyzes the impact of non-Gaussian multipath component (MPC) amplitude distributions on the performance of Compressed Sensing (CS) channel estimators for OFDM systems. The number of dominant MPCs that any CS algorithm needs to estimate in order to accurately represent the channel is characterized. This number relates to a Compressibility Index (C

Meng Chen, Ruixue Liu, Lei Shen, Shaozu Yuan

Human conversations are complicated and building a human-like dialogue agent is an extremely challenging task. With the rapid development of deep learning techniques, data-driven models become more and more prevalent which need a huge amount of real conversation data. In this paper, we construct a large-scale real scenario Chinese E-commerce conversation cor

Yasin Almalioglu, Mehmet Turan, Alp Eren Sari, Muhamad Risqi U. Saputra

In the last decade, numerous supervised deep learning approaches requiring large amounts of labeled data have been proposed for visual-inertial odometry (VIO) and depth map estimation. To overcome the data limitation, self-supervised learning has emerged as a promising alternative, exploiting constraints such as geometric and photometric consistency in the s

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

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

Felipe Gomez-Cuba, Mainak Chowdhury, Alexandros Manolakos, Elza Erkip

The scaling of coherent and non-coherent channel capacity is studied in a single-input multiple-output (SIMO) block Rayleigh fading channel as both the bandwidth and the number of receiver antennas go to infinity jointly with the transmit power fixed. The transmitter has no channel state information (CSI), while the receiver may have genie-provided CSI (cohe

Célestin Matte, Nataliia Bielova, Cristiana Santos

As a result of the GDPR and the ePrivacy Directive, European users encounter cookie banners on almost every website. Many of such banners are implemented by Consent Management Providers (CMPs), who respect the IAB Europe's Transparency and Consent Framework (TCF). Via cookie banners, CMPs collect and disseminate user consent to third parties. In this work, w

Rafael Aoude, Andreas Helset

We find new relations for the non-universal part of the Yang-Mills amplitudes by combining the KLT-relation and the soft behavior of gauge and gravity amplitudes. We also extend the relations to include contributions from effective operators.

Jeremy P. Parker, Colm-cille P. Caulfield, Rich R. Kerswell

The Holmboe wave instability is one of the classic examples of a stratified shear instability, usually explained as the result of a resonance between a gravity wave and a vorticity wave. Historically, it has been studied by linear stability analyses at infinite Reynolds number, $Re$, and by direct numerical simulations at relatively low $Re$ in the regions k

Onur Ayan, H. Murat Gürsu, Arled Papa, Wolfgang Kellerer

Age-of-information (AoI) is a metric quantifying information freshness at the receiver. It captures the delay together with packet loss and packet generation rate. However, the existing literature focuses on average or peak AoI and neglects the complete distribution. In this work, we consider a N-hop network with time-invariant packet loss probabilities on e

Peter Groenhout, Colin D. Reid, George A. Willis

Groups of almost upper triangular infinite matrices with entries indexed by integers are studied. It is shown that, when the matrices are over a finite field, these groups admit a nondiscrete totally disconnected, locally compact group topology and are topologically simple.

Francesco Petocchi, Fredrik Nilsson, Ferdi Aryasetiawan, Philipp Werner

We perform a systematic {\it ab initio} study of the electronic structure of Sr(V,Mo,Mn)O$_3$ perovskites, using the parameter-free $GW$+EDMFT method. This approach self-consistently calculates effective interaction parameters, taking into account screening effects due to nonlocal charge fluctuations. Comparing the results of a 3-band ($t_{2g}$) description

Grigori A. Karagulyan

We give a domination condition implying good-$\lambda$ and exponential inequalities for couples of measurable functions. Those inequalities recover several classical and new estimations involving some operators in Harminic Analysis. Among other corollaries we prove a new exponential estimate for Carleson operators. The main results of the paper are considere

He-Feng Yin, Xiao-Jun Wu

Representation based classification method (RBCM) remains one of the hottest topics in the community of pattern recognition, and the recently proposed non-negative representation based classification (NRC) achieved impressive recognition results in various classification tasks. However, NRC ignores the relationship between the coding and classification stage

Ivan Jakovac, Mladen Horvatić, Eike F. Schwier, Andrey Prokofiev

We report $^{105}$Pd NMR and NQR measurements on a single crystal of Ce$_3$Pd$_{20}$Si$_6$, where antiferroquadrupolar and antiferromagnetic orders develop at low temperature. From the analysis of NQR and NMR spectra, we have determined the electric field gradient (EFG) tensors and the anisotropic Knight shift ($K$) components for both inequivalent Pd sites

Yavar Kian, Eric Soccorsi, Qi Xue, Masahiro Yamamoto

This paper is concerned with the inverse problem of determining the time and space dependent source term of diffusion equations with constant-order time-fractional derivative in $(0,2)$. We examine two different cases. In the first one, the source is the product of two spatial and temporal terms, and we prove that both of them can be retrieved by knowledge o

Daniel Ahlberg

We consider planar first-passage percolation and show that the time constant can be bounded by multiples of the first and second tertiles of the weight distribution. As a consequence we obtain a counter-example to a problem proposed by Alm and Deijfen.

Assia Benabdallah, Matania Ben-Artzi, Yves Dermenjian

Consider the Dirichlet-Laplacian in $\Omega:= (0,L)\times (0,H)$ and choose another open set $\omega\subset \Omega$. The estimate $0<C_{\omega}\leq R_{\omega}(u):=\frac{\Vert u\Vert^{2}_{L^{2}(\omega)}}{\Vert u\Vert^{2}_{L^{2}(\Omega)}}\leq \frac{vol(\omega)}{vol(\omega)}$, for all the eigenfunctions, is well known. This is no longer true for an inhomogeneou

Mona Buisson-Fenet, Friedrich Solowjow, Sebastian Trimpe

Despite the availability of ever more data enabled through modern sensor and computer technology, it still remains an open problem to learn dynamical systems in a sample-efficient way. We propose active learning strategies that leverage information-theoretical properties arising naturally during Gaussian process regression, while respecting constraints on th

Andreas Lenz, Cyrus Rashtchian, Paul H. Siegel, Eitan Yaakobi

A covering code is a set of codewords with the property that the union of balls, suitably defined, around these codewords covers an entire space. Generally, the goal is to find the covering code with the minimum size codebook. While most prior work on covering codes has focused on the Hamming metric, we consider the problem of designing covering codes define

Guanqi Zhan, Yihao Zhao, Bingchan Zhao, Haoqi Yuan

Recent studies have shown how disentangling images into content and feature spaces can provide controllable image translation/ manipulation. In this paper, we propose a framework to enable utilizing discrete multi-labels to control which features to be disentangled, i.e., disentangling label-specific fine-grained features for image manipulation (dubbed DLGAN

Saadaoui Nejib

In this paper, we classify flnite dimensional multiplicative simple BiHom-Lie algebras by investigating the corresponding semisimple Lie algebras and we give a complete classification of the complex 3-dimensional multiplicative BiHom-Lie algebras.

Alexander Ziller, Julius Hansjakob, Vitalii Rusinov, Daniel Zügner

We release a realistic, diverse, and challenging dataset for object detection on images. The data was recorded at a beer tent in Germany and consists of 15 different categories of food and drink items. We created more than 2,500 object annotations by hand for 1,110 images captured by a video camera above the checkout. We further make available the remaining

Jin Liu, Robert A. Perera, Le Kang, Robert M. Kirkpatrick

The linear spline growth model (LSGM), which approximates complex patterns using at least two linear segments, is a popular tool for examining nonlinear change patterns. Among such models, the linear-linear piecewise change pattern is the most straightforward one. An earlier study has proved that other than the intercept and slopes, the knot (or change-point

Jin Liu, Le Kang, Roy T. Sabo, Robert M. Kirkpatrick

Empirical researchers are usually interested in investigating the impacts of baseline covariates have when uncovering sample heterogeneity and separating samples into more homogeneous groups. However, a considerable number of studies in the structural equation modeling (SEM) framework usually start with vague hypotheses in terms of heterogeneity and possible

Binal Poyyathuruthy Bruno, Robert Schütze, Ruediger Grunwald, Ulrike Wallrabe

We present the design and fabrication of a miniaturized array of piezoelectrically actuated high speed Fresnel mirrors with individual mirror control. These Fresnel mirrors can be used to generate propagation invariant and self-healing interference patterns. The mirrors are actuated using piezobimorph actuators, and the consequent change of the tilting angle

Yuichi Enoki, Taizan Watari

We focus on 4D $\mathcal{N}=2$ string vacua described both by perturbative Heterotic theory and by Type IIA theory; a Calabi--Yau three-fold $X_{\rm IIA}$ in the Type IIA language is further assumed to have a regular K3-fibration. It is well-known that one can assign a modular form $\Phi$ to such a vacuum by counting perturbative BPS states in Heterotic theo

Andrey Mudrov

Tensor product of irreducible modules of highest weight over a semi-simple quantum group is semi-simple if and only if a natural contravariant form is non-degenerate when restricted to the span of singular vectors. We express this restriction through the extremal projector of the quantum group providing a computationally feasible criterion for complete reduc

Christelle Stodel, Marcel Toulemonde, Christoph Fransen, Bertrand Jacquot

High electronic excitations in radiation of metallic targets with swift heavy ion beams at the coulomb barrier play a dominant role in the damaging processes of some metals. The inelastic thermal spike model was developed to describe tracks in materials and is applied in this paper to some systems beams/targets employed recently in some nuclear physics exper

Yann Chaubet, Nguyen Viet Dang

We introduce a new object, the dynamical torsion, which extends the potentially ill-defined value at $0$ of the Ruelle zeta function of a contact Anosov flow twisted by an acyclic representation of the fundamental group. We show important properties of the dynamical torsion: it is invariant under deformations among contact Anosov flows, it is holomorphic in

Yunfei Liu, Yu Li, Shaodi You, Feng Lu

Intrinsic image decomposition, which is an essential task in computer vision, aims to infer the reflectance and shading of the scene. It is challenging since it needs to separate one image into two components. To tackle this, conventional methods introduce various priors to constrain the solution, yet with limited performance. Meanwhile, the problem is typic

Lewei Yao, Hang Xu, Wei Zhang, Xiaodan Liang

The state-of-the-art object detection method is complicated with various modules such as backbone, feature fusion neck, RPN and RCNN head, where each module may have different designs and structures. How to leverage the computational cost and accuracy trade-off for the structural combination as well as the modular selection of multiple modules? Neural archit

Susmita Bhaduri, Anirban Bhaduri, Dipak Ghosh

A deailed knowledge of pp collision is required both as input to comprehensive theoretical models of strong interactions and as baseline to decipher the AA collisions at relativistic and ultrarelativistic energies, which has been of great interest in the area of theoretical and experimental physics. The multiplicity distribution of particles produced in pp c

Sunčica Čanić, Marija Galić, Boris Muha

We consider a nonlinear, moving boundary, fluid-structure interaction problem between a time dependent incompressible, viscous fluid flow, and an elastic structure composed of a cylindrical shell supported by a mesh of elastic rods. The fluid flow is modeled by the time-dependent Navier-Stokes equations in a three-dimensional cylindrical domain, while the la

Hasan Genc, Seah Kim, Alon Amid, Ameer Haj-Ali

DNN accelerators are often developed and evaluated in isolation without considering the cross-stack, system-level effects in real-world environments. This makes it difficult to appreciate the impact of System-on-Chip (SoC) resource contention, OS overheads, and programming-stack inefficiencies on overall performance/energy-efficiency. To address this challen

Cheng Lian, Mathijs Janssen, Honglai Liu, René van Roij

The development of novel electrolytes and electrodes for supercapacitors is hindered by a gap of several orders of magnitude between experimentally measured and theoretically predicted charging timescales. Here, we propose an electrode model, containing many parallel stacked electrodes, that explains the slow charging dynamics of supercapacitors. At low appl

John Erik Fornæss, Nikolai Nikolov

A quantitative version of strong localization of the Kobayashi, Azukawa and Sibony metrics, as well as of the squeezing function, near a plurisubharmonic peak boundary point of a domain in $\Bbb C^n$ is given. As an application, the behavior of these metrics near a strictly pseudoconvex boundary point is studied. A weak localization of the three metrics and

Jonas Richter, Dennis Schubert, Robin Steinigeweg

The real-time dynamics of equal-site correlation functions is studied for one-dimensional spin models with quenched disorder. Focusing on infinite temperature, we present a comparison between the dynamics of models with different quantum numbers $S = 1/2, 1, 3/2$, as well as of chains consisting of classical spins. Based on this comparison as well as by anal

D. Schaerer, Y. Izotov, T. Fragos

Understanding the ionizing spectrum of low-metallicity galaxies is of great importance for modeling and interpreting emission line observations of early/distant galaxies. Although a wide suite of stellar evolution, atmosphere, population synthesis, and photoionization models, taking many physical processes into account now exist, all models face a common pro

Da-Zhu Ma, Dan Zhang, Guoyang Fu, Jian-Pin Wu

By fast Lyapunov indicator (FLI), we study the chaotic dynamics of closed string around charged black brane with hyperscaling violation (HV). The Hawking temperature, Lifshitz dynamical exponent and HV exponent together affect the chaotic dynamics of this system. The temperature plays the role of driving the closed string to escape to infinity. There is a th

Jeff Achter, Sebastian Casalaina-Martin, Charles Vial

Classically, regular homomorphisms have been defined as a replacement for Abel--Jacobi maps for smooth varieties over an algebraically closed field. In this work, we interpret regular homomorphisms as morphisms from the functor of families of algebraically trivial cycles to abelian varieties and thereby define regular homomorphisms in the relative setting, e

Monimoy Bujarbaruah, Akhil Shetty, Kameshwar Poolla, Francesco Borrelli

We propose an approach to design a Model Predictive Controller (MPC) for constrained Linear Time Invariant systems performing an iterative task. The system is subject to an additive disturbance, and the goal is to learn to satisfy state and input constraints robustly. Using disturbance measurements after each iteration, we construct Confidence Support sets,

Desmond C. Ong, Zhengxuan Wu, Tan Zhi-Xuan, Marianne Reddan

Human emotions unfold over time, and more affective computing research has to prioritize capturing this crucial component of real-world affect. Modeling dynamic emotional stimuli requires solving the twin challenges of time-series modeling and of collecting high-quality time-series datasets. We begin by assessing the state-of-the-art in time-series emotion r

Shumpei Iino, Satoshi Morita, Naoki Kawashima

We numerically obtain the conformal spectrum of several classical spin models on a two-dimensional lattice with open boundaries, for every boundary fixed point obtained by the Cardy's derivation [J. L. Cardy, Nucl. Phys. B 324, 581 (1989)]. In order to extract accurate conformal data, we implement the tensor network renormalization algorithm [G. Evenbly and

Weizhu Qian, Fabrice Lauri, Franck Gechter

Predicting smartphone users location with WiFi fingerprints has been a popular research topic recently. In this work, we propose two novel deep learning-based models, the convolutional mixture density recurrent neural network and the VAE-based semi-supervised learning model. The convolutional mixture density recurrent neural network is designed for path pred

De-Xian Wei, Li-Juan Zhou, Xin-Fei Li

We carry out simulations using a multi-phase transport (AMPT) model to describe the response relation between $v_2$ and $\varepsilon_2$ in Pb-Pb and p-Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV, respectively. To simulate such relation, two methods have been introduced in the calculation: one is the directed response (DR) method, which correlates the outgoing

Xiong-Ying Guo, Huai-Fan Li, Li-Chun Zhang, Ren Zhao

Previously, the Maxwell equal-area law has been used to discuss the conditions satisfied by the phase transition of charged AdS black holes with cloud of string and quintessence, and it was concluded that black holes have phase transition similar to that of vdW system. The phase transition depends on the electric potential of the black hole and is not the on

Johan F. Hoorn, Johnny K. W. Ho

In the design of artificially sentient robots, an obstacle always has been that conventional computers cannot really process information in parallel, whereas the human affective system is capable of producing experiences of emotional concurrency (e.g., happy and sad). Another schism that has been in the way is the persistent Cartesian divide between cognitio

Deng Kangkang, Peng Zheng

We consider a nonsmooth optimization problem on Riemannian manifold, whose objective function is the sum of a differentiable component and a nonsmooth convex function. We propose a manifold inexact augmented Lagrangian method (MIALM) for the considered problem. The problem is reformulated to a separable form. By utilizing the Moreau envelope, we get a smooth

Dalian Yuan, Ercai Chen, Zijie Lin

Let $σ_{K}: \sum_{K}\rightarrow \sum_{K}$ be a shift map. For an interval $[p,q]\subset[0,1]$, let $D_{σ_{K}}([p,q])$ denote the set of pairs for which the density spectrum of the $ε$-approach time set equals $[p,q]$ when $ε$ is small and $E_{σ_{K}}([p,q])$ the set of pairs for which the density spectrum of the $ε$-approach time set converges to $[p,q]$ when

Robert D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman

To communicate with new partners in new contexts, humans rapidly form new linguistic conventions. Recent neural language models are able to comprehend and produce the existing conventions present in their training data, but are not able to flexibly and interactively adapt those conventions on the fly as humans do. We introduce an interactive repeated referen

Hirotaka Yoshino, Keisuke Izumi, Tetsuya Shiromizu, Yoshimune Tomikawa

A dynamically transversely trapping surface (DTTS) is a new concept of an extension of a photon sphere that appropriately represents a strong gravity region and has close analogy with a trapped surface. We study formation of a marginally DTTS in time-symmetric, conformally flat initial data with two black holes, with a spindle-shaped source, and with a ring-

Przemyslaw Malkiewicz, Patrick Peter, S. D. P. Vitenti

We discuss the question of time in a Bianchi I quantum cosmology in the framework of singularity avoidance. We show that time parameters fall into two distinct classes, that are such that the time development of the wave function either always leads to the appearance of a singularity (fast-gauge time) or that always prevents it from occurring (slow-gauge tim

Kristóf Bérczi, André Berger, Matthias Mnich, Roland Vincze

In the Bounded Degree Matroid Basis Problem, we are given a matroid and a hypergraph on the same ground set, together with costs for the elements of that set as well as lower and upper bounds $f(\varepsilon)$ and $g(\varepsilon)$ for each hyperedge $\varepsilon$. The objective is to find a minimum-cost basis $B$ such that $f(\varepsilon) \leq |B \cap \vareps

Ding-qiang Su, Hua Bai, Xiangqun Cui

FAST, the largest single-dish radio telescope in the world, has a 500-meter diameter main reflector and a 300-meter diameter illumination area. It has a shape variable main reflector, which changes the shape of the illuminated area in the main reflector into a paraboloid continuously. In this article, we propose a quasi Cassegrain system to FAST. The detaile

Yuntian Wang, Xiaobo Zhou, Zhihong Zhuang, Linlin Sun

In the finite blocklength scenario, which is suitable for practical applications, a method of maximizing the average effective secrecy rate (AESR) is proposed for a UAV-enabled secure communication by optimizing the UAV's trajectory and transmit power subject to the UAV's mobility constraints and transmit power constraints. To address the formulated non-conv

Bo Han, Chen Yang, Xiaolong Xu, Yuehui Li

Contact interface properties are important in determining the performances of devices based on atomically thin two-dimensional (2D) materials, especially those with short channels. Understanding the contact interface is therefore quite important to design better devices. Herein, we use scanning transmission electron microscopy, electron energy loss spectrosc

Rishabh Agnihotri, Kalyan Chakraborty, Mohit Mishra

Let $H= \mathbb{Q}(\zeta_{n} + {\zeta_{n}}^{-1})$ and $\ell$ be an odd prime such that $q \equiv 1 \pmod \ell$ for some prime factor $q$ of $n$. We get a bound on the $\ell$-rank of the class group of $H$(under some conditions) in terms of the $\ell$-rank of the class group of real quadratic subfield contained in $H$. This is an extension of a recent work of

Mohammad Mahmudur Rahman Khan, Md. Abu Bakr Siddique, Shadman Sakib

Non-Intrusive Load Monitoring (NILM) is the method of detecting an individual device's energy signal from an aggregated energy consumption signature [1]. As existing energy meters provide very little to no information regarding the energy consumption of individual appliances apart from the aggregated power rating, the spotting of individual appliances' energ

Paul T. Brown, Chaitanya Joshi, Stephen Joe, Haavard Rue

Recently, it has been shown that approximations to marginal posterior distributions obtained using a low discrepancy sequence (LDS) can outperform standard grid-based methods with respect to both accuracy and computational efficiency. This recent method, which we will refer to as LDS-StM, can also produce good approximations to multimodal posteriors. However

Saurabh Khanna, Vincent Y. F. Tan

Granger causality is a widely-used criterion for analyzing interactions in large-scale networks. As most physical interactions are inherently nonlinear, we consider the problem of inferring the existence of pairwise Granger causality between nonlinearly interacting stochastic processes from their time series measurements. Our proposed approach relies on mode

Fereshte Khani, Percy Liang

The performance of standard learning procedures has been observed to differ widely across groups. Recent studies usually attribute this loss discrepancy to an information deficiency for one group (e.g., one group has less data). In this work, we point to a more subtle source of loss discrepancy---feature noise. Our main result is that even when there is no i

Zhaoxu Ji, Peiru Fan, Huanguo Zhang

We introduce a class of two-level multi-particle Greenberger-Horne-Zeilinger (GHZ) states, and study entanglement swapping between two systems for Bell states and the class of GHZ states in qubit systems, respectively. We give the formulas for the entanglement swapping of Bell states and GHZ states in any number of qubit systems. We further consider entangle

Carlos Daniel Tamayo Castro, Ricardo Abreu Blaya, Juan Bory Reyes

In this paper, we mainly consider the Riemann boundary value problems for lower dimensional non-commutative Clifford algebras valued monogenic functions. The solutions are given in an explicit way and concrete examples are presented to illustrate the results.

Chunming Tang, Yan Qiu, Qunying Liao, Zhengchun Zhou

In this paper, we first study in detail the relationship between minimal linear codes and cutting blocking sets, which were recently introduced by Bonini and Borello, and then completely characterize minimal linear codes as cutting blocking sets. As a direct result, minimal projective codes of dimension $3$ and $t$-fold blocking sets with $t\ge 2$ in project

Sadia Noureen, Akbar Ali, Akhlaq Ahmad Bhatti

Let $\mathcal{CT}_{n,k}$ and $\mathcal{CT}^*_{n,b}$ be the classes of all $n$-vertex chemical trees with $k$ segments and $b$ branching vertices, respectively, where $3\le k\le n-1$ and $1\le b< \frac{n}{2}-1$. The solution of the problem of finding trees from the class $\mathcal{CT}_{n,k}$ or $\mathcal{CT}^*_{n,b}$, with the minimum first Zagreb index or mi

Bing Zhang

Cosmic explosions called $\gamma$-ray bursts are the most energetic bursting events in the universe. Observations of extremely high-energy emission from two $\gamma$-ray bursts provide a new way to study these gigantic explosions.

Tushar Nagar, Lorenzo Spina, Amanda I. Karakas

Planetary engulfment events involve the chemical assimilation of a planet into a star&#39;s external layer. This can cause a change in the chemical pattern of the stellar atmosphere in a way that mirrors the composition of the rocky object engulfed, with the refractory elements being more abundant than the volatiles. Due to these stellar chemical changes, pl

Bo Chen, Decai Li, Yuqing He, Chunsheng Hua

Technologies to predict human actions are extremely important for applications such as human robot cooperation and autonomous driving. However, a majority of the existing algorithms focus on exploiting visual features of the videos and do not consider the mining of relationships, which include spatial relationships between human and scene elements as well as

Elliot G Mitchell, Esteban G Tabak, Matthew E Levine, Lena Mamykina

Decision-making related to health is complex. Machine learning (ML) and patient generated data can identify patterns and insights at the individual level, where human cognition falls short, but not all ML-generated information is of equal utility for making health-related decisions. We develop and apply attributable components analysis (ACA), a method inspir

Akash K Mishra, Sumanta Chakraborty

Deterministic nature of general relativity is ensured by the strong cosmic censorship conjecture, which asserts that spacetime cannot be extended beyond Cauchy horizon with square integrable connection. Although this conjecture holds true for asymptotically flat black hole spacetimes in general relativity, a potential violation of this conjecture occurs in c

Sheikh Rabiul Islam, William Eberle, Sheikh K. Ghafoor, Ambareen Siraj

Artificial Intelligence (AI) has become an integral part of modern-day security solutions for its ability to learn very complex functions and handling "Big Data". However, the lack of explainability and interpretability of successful AI models is a key stumbling block when trust in a model's prediction is critical. This leads to human intervention, which in

Haris Aziz

Fairness is becoming an increasingly important concern when designing markets, allocation procedures, and computer systems. I survey some recent developments in the field of multi-agent fair allocation.

Muhammad Ejaz, Chaitanya Joshi, Stephen Joe

Adversarial Risk Analysis (ARA) is an upcoming methodology that is considered to have advantages over the traditional decision theoretic and game theoretic approaches. ARA solutions for first-price sealed-bid (FPSB) auctions have been found but only under strong assumptions which make the model somewhat unrealistic. In this paper, we use ARA methodology to m

So Chigusa, Takeo Moroi, Kazunori Nakayama

We consider the search for axion-like particles (ALPs) by using time series data of the polarization angle of the light. If the condensation of an ALP plays the role of dark matter, the polarization plane of the light oscillates as a function of time and we may be able to detect the signal of the ALP by continuously observing the polarization. In particular,

Cheng Yu, Kuo-Hsuan Hung, Syu-Siang Wang, Szu-Wei Fu

Previous studies have proven that integrating video signals, as a complementary modality, can facilitate improved performance for speech enhancement (SE). However, video clips usually contain large amounts of data and pose a high cost in terms of computational resources and thus may complicate the SE system. As an alternative source, a bone-conducted speech

Hyung Ju Hwang, Jin Woo Jang, Hyeontae Jo, Jae Yong Lee

The issue of the relaxation to equilibrium has been at the core of the kinetic theory of rarefied gas dynamics. In the paper, we introduce the Deep Neural Network (DNN) approximated solutions to the kinetic Fokker-Planck equation in a bounded interval and study the large-time asymptotic behavior of the solutions and other physically relevant macroscopic quan

Fiona M. Audcent-Ross, Gerhardt R. Meurer, James R. Audcent, Stuart D. Ryder

Given the limited availability of direct evidence (pre-explosion observations) for supernova (SN) progenitors, the location of supernovae (SNe) within their host galaxies can be used to set limits on one of their most fundamental characteristics, their initial progenitor mass. We present our constraints on SN progenitors derived by comparing the radial distr

Xin Wang, Tucker A. Jones, Tommaso Treu, Emanuele Daddi

We present hitherto the largest sample of gas-phase metallicity radial gradients measured at sub-kiloparsec resolution in star-forming galaxies in the redshift range of $z\in[1.2, 2.3]$. These measurements are enabled by the synergy of slitless spectroscopy from the Hubble Space Telescope near-infrared channels and the lensing magnification from foreground g

M. Hamed Mozaffari, Won-Sook Lee

Despite renewed awareness of the importance of articulation, it remains a challenge for instructors to handle the pronunciation needs of language learners. There are relatively scarce pedagogical tools for pronunciation teaching and learning. Unlike inefficient, traditional pronunciation instructions like listening and repeating, electronic visual feedback (

Navjeet Ahalawat, Satyabrata Bandyopadhyay, Jagannath Mondal

Solvent often manifests itself as the key determinant of the kinetic aspect of molecular recognition process. While the solvent is often depicted as a source of barrier in the ligand recognition process by polar cavity, the nature of solvent's role in the recognition process involving hydrophobic cavity and hydrophobic ligand remains to be addressed. In this

Jianyu Su, Peter A. Beling, Rui Guo, Kyungtae Han

The ability to model and predict ego-vehicle's surrounding traffic is crucial for autonomous pilots and intelligent driver-assistance systems. Acceleration prediction is important as one of the major components of traffic prediction. This paper proposes novel approaches to the acceleration prediction problem. By representing spatial relationships between veh

Jian-Guo Liu, Wen-Hui Zhu

In this paper, a modified symbolic computation approach is proposed. The multiple rogue wave solutions of a generalized (2+1)-dimensional Boussinesq equation are obtained by using the modified symbolic computation approach. Dynamics features of these obtained multiple rogue wave solutions are displayed in 3D and contour plots. Compared with the original symb

Govind Paneru, Sandipan Dutta, Tsvi Tlusty, Hyuk Kyu Pak

Thermodynamic uncertainty relations (TURs) set fundamental bounds on the fluctuation and dissipation of stochastic systems. Here, we examine these bounds, in experiment and theory, by exploring the entire phase space of a cyclic information engine operating in a non-equilibrium steady state. Close to its maximal efficiency, we find that the engine violates t

Taichiro Kugo, Naoki Yamatsu

It is recently shown that in 4D $SU(N)$ Nambu--Jona-Lasinio (NJL) type models, the $SU(N)$ symmetry breaking into its special subgroups is not special but much more common than that into the regular subgroups, where the fermions belong to complex representations of $SU(N)$. We perform the same analysis for $SO(N)$ NJL model for various $N$ with fermions belo

Govind Paneru, Sandipan Dutta, Takahiro Sagawa, Tsvi Tlusty

Understanding noisy information engines is a fundamental problem of non-equilibrium physics, particularly in biomolecular systems agitated by thermal and active fluctuations in the cell. By the generalized second law of thermodynamics, the efficiency of these engines is bounded by the mutual information passing through their noisy feedback loop. Yet, direct

Xin-Chang Cai, Yan-Gang Miao

We obtain the solution of a static spherically symmetric black hole surrounded by a cloud of strings in Rastall gravity and study the influence of the parameter $a$ associated with strings on the event horizon and the Hawking temperature. Through analyzing the black hole metric, we find that the static spherically symmetric black hole solution surrounded by

B. C. Canas, E. A. Garces, O. G. Miranda, A. Parada

New measurements of the coherent elastic neutrino-nucleus scattering (CEvNS) are expected to be achieved in the near future by using two neutrino production channels with different energy distributions: the very low energy electron antineutrinos from reactor sources and the muon and electron neutrinos from spallation neutron sources (SNS) with a relatively h