September 2019 arXiv papers — page 28

M. Euler, C. Petit

Quasi-subfield polynomials were introduced by Huang et al. together with a new algorithm to solve the Elliptic Curve Discrete Logarithm Problem (ECDLP) over finite fields of small characteristic. In this paper we provide both new quasi-subfield polynomial families and a new theorem limiting their existence. Our results do not allow to derive any speedup for

Dragana Božović, Iztok Peterin

The packing chromatic number $\chi_{\rho}(G)$ of a graph $G$ is the smallest integer $k$ such that there exists a $k$-vertex coloring of $G$ in which any two vertices receiving color $i$ are at distance at least $i+1$. In this short note we present upper and lower bound for the packing chromatic number of the lexicographic product $G\circ H$ of graphs $G$ an

Xinchun Yu, Shuangqin Wei, Yuan Luo

This paper considers the achievability and converse bounds on the maximal channel coding rate at a given blocklength and error probability over AWGN channels. The problem stems from covert communication with Gaussian codewords. By re-visiting [18], we first present new and more general achievability bounds for random coding schemes under maximal or average p

Elena Cristina Canepa, Dragos-Patru Covei, Traian A. Pirvu

Stochastic production planning problems were studied in several works; the model with one production good was discussed in [3]. The extension to several economic goods is not a trivial issue as one can see from the recent works [4], [5] and [6]. The following qualitative aspects of the problem are analyzed in [5]; the existence of a solution and its characte

Malin Palö Forsström, Jeffrey E. Steif

Using formulas for certain quantities involving stable vectors, due to I. Molchanov, and in some cases utilizing the so-called divide and color model, we prove that certain families of integrals which, ostensibly, depend on a parameter are in fact independent of this parameter.

Jun-Gi Jang, Chun Quan, Hyun Dong Lee, U Kang

How can we efficiently compress Convolutional Neural Network (CNN) while retaining their accuracy on classification tasks? Depthwise Separable Convolution (DSConv), which replaces a standard convolution with a depthwise convolution and a pointwise convolution, has been used for building lightweight architectures. However, previous works based on depthwise se

Youngsoo Choi, Geoffrey Oxberry, Daniel White, Trenton Kirchdoerfer

Although design optimization has shown its great power of automatizing the whole design process and providing an optimal design, using sophisticated computational models, its process can be formidable due to a computationally expensive large-scale linear system of equations to solve, associated with underlying physics models. We introduce a general reduced o

Kazuhiro Ichihara, In Dae Jong, Hidetoshi Masai

We give a list of hyperbolic two-bridge links which includes all such links with complete exceptional surgeries, i.e., Dehn surgeries on both components which yield non-hyperbolic manifolds but whose all the proper sub-fillings give hyperbolic manifolds. Also all the candidate slopes of complete exceptional surgeries for them are enumerated in our lists.

Cédric Lorcé

We review some of the recent developments regarding mass, angular momentum and pressure forces inside hadrons. These properties are all encoded in the energy-momentum tensor of the system, which is described at the non-perturbative level in terms of gravitational form factors. Similarly to electromagnetic form factors, Fourier transforms of gravitational for

Ayse Peker Dobie, Ali Demirci, Ayse Humeyra Bilge, Semra Ahmetolan

In the standard Susceptible-Infected-Removed (SIR) and Susceptible-Exposed-Infected-Removed (SEIR) models, the peak of infected individuals coincides with the in ection point of removed individuals. Nevertheless, a survey based on the data of the 2009 H1N1 epidemic in Istanbul, Turkey [19] displayed an unexpected time shift between the hospital referrals and

T M Feroz Ali, Subhasis Chaudhuri

Person re-identification is the task of matching pedestrian images across non-overlapping cameras. In this paper, we propose a non-linear cross-view similarity metric learning for handling small size training data in practical re-ID systems. The method employs non-linear mappings combined with cross-view discriminative subspace learning and cross-view distan

Mostafa Zaman Chowdhury, Md. Shahjalal, Shakil Ahmed, Yeong Min Jang

Fifth-generation (5G) communication, which has many more features than fourth-generation communication, will be officially launched very soon. A new paradigm of wireless communication, the sixth-generation (6G) system, with the full support of artificial intelligence is expected to be deployed between 2027 and 2030. In beyond 5G, there are some fundamental i

Hongyu Li, Rang Liu, Ming Li, Qian Liu

Intelligent reflecting surface (IRS) is considered as an enabling technology for future wireless communication systems since it can intelligently change the wireless environment to improve the communication performance. In this paper, an IRS-enhanced wideband multiuser multi-input single-output orthogonal frequency division multiplexing (MU-MISO-OFDM) system

Bo Tranberg, Kasper Koops Kratmann, Jason Stege

The installation process of offshore wind turbines requires the use of expensive jack-up vessels. These vessels regularly report their position via the Automatic Identification System (AIS). This paper introduces a novel approach of applying machine learning to AIS data from jack-up vessels. We apply the new method to 13 offshore wind farms in Danish, German

Maxim Goncharov

We study possible connections between Rota-Baxter operators of non-zero weight and non-skew-symmetric solutions of the classical Yang-Baxter equation on finite-dimensional quadratic Lie algebras. The particular attention is made to the case when for a solution $r$ the element $r+\tau(r)$ is $L$-invariant.

Zhuo-Zhi Zhang, Xiang-Xiang Song, Gang Luo, Zi-Jia Su

Vibrational modes in mechanical resonators provide a promising candidate to interface and manipulate classical and quantum information. The observation of coherent dynamics between distant mechanical resonators can be a key step towards scalable phonon-based applications. Here we report tunable coherent phonon dynamics with an architecture comprising three g

Chongshuang Chen, Jun Zhao

The INFORMS RAS 2019 Problem Solving Competition is focused on the integrated train blocking and shipment path (TBSP) optimization for tonnage-based operating railways. In nature, the TBSP problem could be viewed as a multi-commodity network design problem with a double-layer network structure. By introducing a directed physical railway network and a directe

Xue Zhou, Zeyu Jiang, Kenan Zhang, Wei Yao

Atomically thin transition metal dichalcogenide films with distorted trigonal (1T$^\prime$) phase have been predicted to be candidates for realizing quantum spin Hall effect. Growth of 1T$^\prime$ film and experimental investigation of its electronic structure are critical. Here we report the electronic structure of 1T$^\prime$-MoTe$_2$ films grown by molecu

Chunpeng Wu, Wei Wen, Yiran Chen, Hai Li

Generative adversarial network (GAN) has greatly improved the quality of unsupervised image generation. Previous GAN-based methods often require a large amount of high-quality training data while producing a small number (e.g., tens) of classes. This work aims to scale up GANs to thousands of classes meanwhile reducing the use of high-quality data in trainin

G. Sivaganesh, A. Arulgnanam, A. N. Seethalakshmi

A novel explicit analytical solution is reported for the transmission and recovery of information signals using a simple communication scheme. Analytical solutions are obtained for the normalized state equations of coupled second-order chaotic transmitter and receiver systems embedding the information signal. The analytical solution of the difference system

Yuanqiang Cai, Dawei Du, Libo Zhang, Longyin Wen

Object detection and counting are related but challenging problems, especially for drone based scenes with small objects and cluttered background. In this paper, we propose a new Guided Attention Network (GANet) to deal with both object detection and counting tasks based on the feature pyramid. Different from the previous methods relying on unsupervised atte

Dingchuan Xue, Yichao Zhu, Shaoshuai Li, Chang Liu

Gradient porous structured materials possess significant potential of being applied in many engineering fields. To accelerate the design process of infill graded microstructures, a novel asymptotic homogenisation topology optimisation method was proposed by Zhu et al.(2019), aiming for 1) significantly enriching the pool of representable graded microstructur

Yu Liu, Fanggang Wang

This paper investigates a complete blind receiver approach in an unknown multipath fading channel, which has multiple tasks including blind channel estimation, noise power estimation, modulation classification, channel coding recognition, and data detection. Each of these tasks has been sufficiently studied in the literature. However, to the best of our know

Ali A. Esswie, Klaus I. Pedersen

The ultra-reliable and low-latency communication (URLLC) is the key driver of the current 5G new radio standardization. URLLC encompasses sporadic and small-payload transmissions that should be delivered within extremely tight radio latency and reliability bounds, i.e., a radio latency of 1 ms with 99.999% success probability. However, such URLLC targets are

Ethan Dyer, Guy Gur-Ari

Understanding the asymptotic behavior of wide networks is of considerable interest. In this work, we present a general method for analyzing this large width behavior. The method is an adaptation of Feynman diagrams, a standard tool for computing multivariate Gaussian integrals. We apply our method to study training dynamics, improving existing bounds and der

Taewoo Kim, Joo-Haeng Lee

Motion retargeting between heterogeneous polymorphs with different sizes and kinematic configurations requires a comprehensive knowledge of (inverse) kinematics. Moreover, it is non-trivial to provide a kinematic independent general solution. In this study, we developed a cyclic three-phase optimization method based on deep reinforcement learning for human-r

Tahira Iqbal, Norbert Seyff, Daniel Mendez Fernández

App store mining has proven to be a promising technique for requirements elicitation as companies can gain valuable knowledge to maintain and evolve existing apps. However, despite first advancements in using mining techniques for requirements elicitation, little is yet known how to distill requirements for new apps based on existing (similar) solutions and

Stephen L. Adler, Angelo Bassi, Luca Ferialdi

The CSL model predicts a progressive breakdown of the quantum superposition principle, with a noise randomly driving the state of the system towards a localized one, thus accounting for the emergence of a classical world within a quantum framework. In the original model the noise is supposed to be white, but since white noises do not exist in nature, it beco

Lajos Molnár

In this paper we consider power means of positive Hilbert space operators both in the conventional and in the Kubo-Ando senses. We describe the corresponding isomorphisms (bijective transformations respecting those means as binary operations) on positive definite cones and on positive semidefinite cones in operator algebras. We also investigate the question

Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang

In natural language processing, it has been observed recently that generalization could be greatly improved by finetuning a large-scale language model pretrained on a large unlabeled corpus. Despite its recent success and wide adoption, finetuning a large pretrained language model on a downstream task is prone to degenerate performance when there are only a

Xiuyuan Cheng, Alexander Cloninger

The recent success of generative adversarial networks and variational learning suggests training a classifier network may work well in addressing the classical two-sample problem. Network-based tests have the computational advantage that the algorithm scales to large samples. This paper proposes a two-sample statistic which is the difference of the logit fun

Mengting Hu, Shiwan Zhao, Honglei Guo, Renhong Cheng

Aspect-based sentiment analysis (ABSA) is to predict the sentiment polarity towards a particular aspect in a sentence. Recently, this task has been widely addressed by the neural attention mechanism, which computes attention weights to softly select words for generating aspect-specific sentence representations. The attention is expected to concentrate on opi

R. S. Raja Durai, Ashwini Kumar

A code $\mathcal{C}(n, k, d)$ defined over $\texttt{GF}(q^{n})$ is conventionally designed to encode a $k$-symbol user data into a codeword of length $n$, resulting in a fixed-rate coding. This paper proposes a coding procedure to derive a multiple-rate code from existing channel codes defined over a composite field $\texttt{GF}(q^{n})$. Formally, by viewing

Kenji Bekki, Takuji Tsujimoto

We investigate the formation processes of the Galactic globular cluster (GC) omega Cen with multiple stellar populations based on our original hydrodynamical simulations with chemical enrichment by Type II supernovae (SNe II), asymptotic giant branch (AGB) stars, and neutron star mergers (NSMs). The principal results are as follows. Multiple stellar populati

Simon Luo, Lamiae Azizi, Mahito Sugiyama

We present a novel blind source separation (BSS) method, called information geometric blind source separation (IGBSS). Our formulation is based on the log-linear model equipped with a hierarchically structured sample space, which has theoretical guarantees to uniquely recover a set of source signals by minimizing the KL divergence from a set of mixed signals

Jian Li, Zhihong Jeff Xia, Liyong Zhou

We aim to determine the relative angle between the total angular momentum of the minor planets and that of the Sun-planets system, and to improve the orientation of the invariable plane of the solar system. By utilizing physical parameters available in public domain archives, we assigned reasonable masses to 718041 minor planets throughout the solar system,

Viktor Könye, Masao Ogata

We study the thermoelectric transport properties of a three-dimensional massive relativistic fermion gas with screened Coulomb impurities in high magnetic fields where only the lowest Landau levels contribute to the transport. Our results can be applied to experimental results of gapless and gapped Dirac materials. We focus on the effects of the mass term an

Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor

Recent years have seen a dramatic expansion of tasks and datasets posed as question answering, from reading comprehension, semantic role labeling, and even machine translation, to image and video understanding. With this expansion, there are many differing views on the utility and definition of "question answering" itself. Some argue that its scope should be

Ke Chen, Qin Li, Kit Newton, Steve Wright

For an overdetermined system $\mathsf{A}\mathsf{x} \approx \mathsf{b}$ with $\mathsf{A}$ and $\mathsf{b}$ given, the least-square (LS) formulation $\min_x \, \|\mathsf{A}\mathsf{x}-\mathsf{b}\|_2$ is often used to find an acceptable solution $\mathsf{x}$. The cost of solving this problem depends on the dimensions of $\mathsf{A}$, which are large in many prac

Morgan Heisler, Forson Chan, Zaid Mammo, Chandrakumar Balaratnasingam

Automatic quantification of perifoveal vessel densities in optical coherence tomography angiography (OCT-A) images face challenges such as variable intra- and inter-image signal to noise ratios, projection artefacts from outer vasculature layers, and motion artefacts. This study demonstrates the utility of deep neural networks for automatic quantification of

Nway Nway Han, Aye Thida

Reference corpus for word alignment is an important resource for developing and evaluating word alignment methods. For Myanmar-English language pairs, there is no reference corpus to evaluate the word alignment tasks. Therefore, we created the guidelines for Myanmar-English word alignment annotation between two languages over contrastive learning and built t

Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen

How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans. To handle this problem, memory networks are usually a great choice and a promising way. However, existing memory networks do not perform well when leveraging heterogeneous information from different sources. In this pape

Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu

While generative adversarial networks (GANs) have revolutionized machine learning, a number of open questions remain to fully understand them and exploit their power. One of these questions is how to efficiently achieve proper diversity and sampling of the multi-mode data space. To address this, we introduce BasisGAN, a stochastic conditional multi-mode imag

Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu

In this paper, we consider domain-invariant deep learning by explicitly modeling domain shifts with only a small amount of domain-specific parameters in a Convolutional Neural Network (CNN). By exploiting the observation that a convolutional filter can be well approximated as a linear combination of a small set of dictionary atoms, we show for the first time

Peter V. Pikhitsa

The stability of floating drops on the liquid surface of the same liquid is considered in terms of viscous drainage theory. We have expressed the minimal thickness of the air film, separating the drop from the liquid surface, and the lifetime of the drop through the Hamaker constant, characterizing the intensity of van-der-Waals forces which make the air fil

Ushnish Ray, Garnet Kin-Lic Chan

We present a strategy to construct guiding distribution functions (GDFs) based on variance minimization. Auxiliary dynamics via GDFs mitigates the exponential growth of variance as a function of bias in Monte Carlo estimators of large deviation functions. The variance minimization technique exploits the exact properties of eigenstates of the tilted operator

Mohamed Raessa, Jimmy Chi Yin Chen, Weiwei Wan, Kensuke Harada

This paper develops a robotic manipulation planner for human-robot collaborative assembly. Unlike previous methods which study an independent and fully AI-equipped autonomous system, this paper explores the subtask distribution between a robot and a human and studies a human-in-the-loop robotic system for collaborative assembly. The system distributes the su

Caio E. Stringari, Hannah E. Power

Bore-bore capture occurs when a faster moving bore captures a slower moving bore whilst both are propagating shoreward in the surf or swash zones. This phenomenon occurs frequently on natural beaches, but has not yet been quantified in the literature. Novel application of wave tracking methods allowed for investigation of this phenomenon at seven sandy, micr

N. Christopher Phillips

Let G be a discrete group. Suppose that the reduced group C*-algebra of G is simple. We use results of Kalantar-Kennedy and Haagerup, and Banach space interpolation, to prove that, for p in (1,infinity), the reduced group L^p operator algebra F^p_r(G) and its *-analog B^{p,*}_r(G) are simple. If G is countable, we prove that the Banach algebras generated by

Irwandi Hipiny, Hamimah Ujir, Aazani Mujahid, Nurhartini Kamalia Yahya

Passive biometric identification enables wildlife monitoring with minimal disturbance. Using a motion-activated camera placed at an elevated position and facing downwards, we collected images of sea turtle carapace, each belonging to one of sixteen Chelonia mydas juveniles. We then learned co-variant and robust image descriptors from these images, enabling i

Shengyang Zhou, Enrique P. Blair

Models of quantum disentanglement are developed for nanometer-scale molecular charge qubits (MCQs). Two MCQs, $A$ and $B$, are prepared in a Bell state and separated for negligible $A$-$B$ interactions. Interactions between the local environment and each MCQ unravels $A$-$B$ entanglement during coherent system+environment evolution. Three models are used for

Lech Szymanski, Brendan McCane, Craig Atkinson

We introduce switched linear projections for expressing the activity of a neuron in a deep neural network in terms of a single linear projection in the input space. The method works by isolating the active subnetwork, a series of linear transformations, that determine the entire computation of the network for a given input instance. With these projections we

Taiji Suzuki, Hiroshi Abe, Tomoaki Nishimura

One of the biggest issues in deep learning theory is the generalization ability of networks with huge model size. The classical learning theory suggests that overparameterized models cause overfitting. However, practically used large deep models avoid overfitting, which is not well explained by the classical approaches. To resolve this issue, several attempt

Yangyang Cheng, Guanghui Wang, Yi Zhao

Let $G_1,...,G_n$ be graphs on the same vertex set of size $n$, each graph with minimum degree $\delta(G_i)\ge n/2$. A recent conjecture of Aharoni asserts that there exists a rainbow Hamiltonian cycle i.e. a cycle with edge set $\{e_1,...,e_n\}$ such that $e_i\in E(G_i)$ for $1\leq i \leq n$. This can be viewed as a rainbow version of the well-known Dirac t

Zijian Wang, Christopher Potts

Condescending language use is caustic; it can bring dialogues to an end and bifurcate communities. Thus, systems for condescension detection could have a large positive impact. A challenge here is that condescension is often impossible to detect from isolated utterances, as it depends on the discourse and social context. To address this, we present TalkDown,

Jose F. Nieves, Sarira Sahu

We consider the decoherence effects in the propagation of neutrinos in a background composed of a scalar particle and a fermion due to the non-forward neutrino scattering processes. Using a simple model for the coupling of the form $\bar f_R\nu_L\phi$ we calculate the contribution to the imaginary part of the neutrino self-energy arising from the non-forward

Paul Sánchez, Daniel J. Scheeres

The migration of cohesive regolith on the surface of an otherwise monolithic or strong asteroid is studied using theoretical and simulation models. The theory and simulations show that under an increasing spin rate (such as due to the YORP effect), the regolith covering is preferentially lost across certain regions of the body. For regolith with little or no

Si-Baek Seong, Hae-Jeong Park

The advancement of the neuroscientific imaging techniques has produced an unprecedented size of neural cell imaging data, which calls for automated processing. In particular, identification of cells from two photon images demands segmentation of neural cells out of various materials and classification of the segmented cells according to their cell types. To

Maciej Halber, Yifei Shi, Kai Xu, Thomas Funkhouser

In depth-sensing applications ranging from home robotics to AR/VR, it will be common to acquire 3D scans of interior spaces repeatedly at sparse time intervals (e.g., as part of regular daily use). We propose an algorithm that analyzes these "rescans" to infer a temporal model of a scene with semantic instance information. Our algorithm operates inductively

Ling Sun, Richard Brito, Maximiliano Isi

Ultralight scalars, if they exist as theorized, could form clouds around rapidly rotating black holes. Such clouds are expected to emit continuous, quasimonochromatic gravitational waves that could be detected by LIGO and Virgo. Here we present results of a directed search for such signals from the Cygnus X-1 binary, using data from Advanced LIGO's second ob

Xinyang Zhou, Zhiyuan Liu, Yi Guo, Changhong Zhao

The increasing distributed and renewable energy resources and controllable devices in distribution systems make fast distribution system state estimation (DSSE) crucial in system monitoring and control. We consider a large multi-phase distribution system and formulate DSSE as a weighted least squares (WLS) problem. We divide the large distribution system int

Nils Paz, Steven Silverman, John Harmon

Distributed Ledger Technology (DLT) is a shared, synchronized and replicated data spread spatially and temporally with no centralized administration and/or storage. Each node has a complete and identical set of records. All participants contribute to building and maintaining the distributed ledger. Current DLT technologies fall into two broad categories. Tho

Scott E. Kruger

It is shown that the Galilean limit (V << c, or L/T <<c)) of the Maxwell equations admits three different limits: the magneto-quasi-static, electro-quasi-static, and electromagnetic-quasi-static limits, in addition to the two obvious static limits. The first two quasi-static limits have been previously identified as Galilean Electromagnetics, while the latte

Jin-Jie Yang, Shou-Fu Tian

We study systematically a matrix Riemann-Hilbert problem for the modified Landau-Lifshitz (mLL) equation with nonzero boundary conditions at infinity. Unlike the zero boundary conditions case, there occur double-valued functions during the process of the direct scattering. In order to establish the Riemann-Hilbert (RH) problem, it is necessary to make approp

Jagjit Singh, W. Horiuchi, L. Fortunato, A. Vitturi

We study the two-neutron correlations in the ground state of the weakly-bound two-neutron halo nucleus $^{22}$C sitting at the edge of the neutron-drip line and also in the unbound nucleus $^{26}$O sitting beyond the neutron dripline. For the present study, we employ a three-body (core$+n+n$) structure model designed for describing the two-neutron halo syste

Himanshu Goyal, Pramit Saha, Bryan Gick, Sidney Fels

The fundamental frequency (F0) of human voice is generally controlled by changing the vocal fold parameters (including tension, length and mass), which in turn is manipulated by the muscle exciters, activated by the neural synergies. In order to begin investigating the neuromuscular F0 control pathway, we simulate a simple biomechanical arm prototype (instea

Lei Yang, Xuechao Wang, Vivek Bagaria, Gerui Wang

Bitcoin is the first fully-decentralized permissionless blockchain protocol to achieve a high level of security, but at the expense of poor throughput and latency. Scaling the performance of Bitcoin has a been a major recent direction of research. One successful direction of work has involved replacing proof of work (PoW) by proof of stake (PoS). Proposals t

Shifeng Zhang, Yiliang Xie, Jun Wan, Hansheng Xia

Pedestrian detection has achieved significant progress with the availability of existing benchmark datasets. However, there is a gap in the diversity and density between real world requirements and current pedestrian detection benchmarks: 1) most of existing datasets are taken from a vehicle driving through the regular traffic scenario, usually leading to in

Hong Soo Park, Dae-Sik Moon, Dennis Zaritsky, Sang Chul Kim

We present our discovery and analysis of dwarf galaxies in the NGC 3585 galaxy group by the KMTNet Supernova Program. Using deep stack images reaching $\simeq$ 28 mag arcsec$^{-2}$ in $BVI$, we discovered 46 dwarf galaxy candidates distributed in a 7 square degree field. The dwarf galaxy candidates exhibit central surface brightness as faint as $\mu_{0,V} =

Patrick Irvin, Hyungwoo Lee, Jung-Woo Lee, Megan Briggeman

We report Aharonov-Bohm (AB)-type quantum interference in simply-connected devices created at the LaAlO$_3$/SrTiO$_3$ interface using conductive-atomic force microscope (c-AFM) lithography. The oscillations are multi-periodic functions of magnetic field strength, and they exhibit a substantial magnetic hysteresis with frequencies that depends on the magnetic

Omer Anjum, Hongyu Gong, Suma Bhat, Wen-Mei Hwu

Finding the right reviewers to assess the quality of conference submissions is a time consuming process for conference organizers. Given the importance of this step, various automated reviewer-paper matching solutions have been proposed to alleviate the burden. Prior approaches, including bag-of-words models and probabilistic topic models have been inadequat

Ryan Thomas, Niels Kjærgaard

Magnetic Feshbach resonances are a key tool in the field of ultracold quantum gases, but their full exploitation requires the generation of large, stable magnetic fields up to 1000 G with fractional stabilities of better than $10^{-4}$. Design considerations for electromagnets producing these fields, such as optical access and fast dynamical response, mean t

Feng Ding, Xueyuan Hu

Masking information is a protocol that encodes quantum information into a bipartite entangled state while the information is completely unknown to local systems. This paper explicitly studies the structure of the set of maskable states and its relation to hyperdisks. We prove that although the qubit states which can be masked must locate on a single hyperdis

R. B. Torbert, I. Dors, M. R. Argall, K. J. Genestreti

A method is described to model the magnetic field in the vicinity of constellations of multiple satellites using field and plasma current measurements. This quadratic model has the properties that the divergence is zero everywhere and matches the measured values of the magnetic field and its curl (current) at each spacecraft, and thus extends the linear curl

Young Sun Lee, Timothy C. Beers, Young Kwang Kim

We present an analysis of the kinematic properties of stellar populations in the Galactic halo, making use of over 100,000 main sequence turnoff (MSTO) stars observed in the Sloan Digital Sky Survey. After dividing the Galactic halo into an inner-halo region (IHR) and outer-halo region (OHR), based on the spatial variation of carbon-to-iron ratios in the sam

Linyan Rong, Zhencheng Mu, Zhexin Xie, Bo Wang

The China spallation neutron source (CSNS) linac is designed with beam energy of 81MeV and a peak current of 15mA in the first phase. The RF power system for the 81 MeV Linac requires 8 units of RF power sources, each unit has one independent digital low level RF (LLRF) control system which is used to stabilize the amplitude and phase of the RF accelerating

Yang Lv, Liangsheng Zhuang, Pengyu Luo

Session based recommendation has become one of the research hotpots in the field of recommendation systems due to its highly practical value.Previous deep learning methods mostly focus on the sequential characteristics within the current session,and neglect the context similarity and temporal similarity between sessions which contain abundant collaborative i

Chang How Tan, Vincent CS Lee, Mahsa Salehi

Concept drift is formally defined as the change in joint distribution of a set of input variables X and a target variable y. The two types of drift that are extensively studied are real drift and virtual drift where the former is the change in posterior probabilities p(y|X) while the latter is the change in distribution of X without affecting the posterior p

Young Kwang Kim, Young Sun Lee, Timothy C. Beers

We explore differences in Galactic halo kinematic properties derived from two commonly employed Galactic potentials: the St$\ddot{a}$ckel potential and the default Milky Way-like potential used in the "Galpy" package (MWPotential2014), making use of stars with available metallicities, radial velocities, and proper motions from Sloan Digital Sky Survey Data R

Ori Henderson-Sapir, Nathaniel Bawden, Matthew R. Majewski, Robert I. Woodward

We report on a mid-infrared mode-locked fiber laser that uses an acousto-optic tunable filter to achieve frequency-shifted feedback pulse generation with frequency tuning over a 215 nm range. The laser operates on the 3.5 ${\mu}$m transition in erbium-doped zirconium fluoride-based fiber and utilizes the dual-wavelength pumping scheme. Stable, self-starting

John Gideon, Katie Matton, Steve Anderau, Melvin G McInnis

Bipolar disorder (BPD) is a chronic mental illness characterized by extreme mood and energy changes from mania to depression. These changes drive behaviors that often lead to devastating personal or social consequences. BPD is managed clinically with regular interactions with care providers, who assess mood, energy levels, and the form and content of speech.

Hugh Morton, Peter Samuelson

We give a skein-theoretic realization of the $\mathfrak{gl}_n$ double affine Hecke algebra of Cherednik using braids and tangles in the punctured torus. We use this to provide evidence of a relationship we conjecture between the classical skein algebra of the punctured torus and the elliptic Hall algebra of Burban and Schiffmann.

Karin I. Oberg, Robin Wordsworth

Jupiter's atmosphere is enriched in C, N, S, P, Ar, Kr and Xe with respect to solar abundances by a factor of ~3. Gas Giant envelopes are mainly enriched through the dissolution of solids in the atmosphere, and this constant enrichment factor is puzzling since several of the above elements are not expected to have been in the solid phase in Jupiter's feeding

Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou

Constructions of locally decodable codes (LDCs) have one of two undesirable properties: low rate or high locality (polynomial in the length of the message). In settings where the encoder/decoder have already exchanged cryptographic keys and the channel is a probabilistic polynomial time (PPT) algorithm, it is possible to circumvent these barriers and design

Xiao-Bin Liang, Bo Li, Shao-Ming Fei

We study the problem of information masking through nonzero linear operators that distribute information encoded in single qubits to the correlations between two qubits. It is shown that a nonzero linear operator cannot mask any nonzero measure set of qubit states. We prove that the maximal maskable set of states on the Bloch sphere with respect to any maske

Lihwai Lin, Hsi-An Pan, Sara L. Ellison, Francesco Belfiore

The origin of the star forming main sequence ( i.e., the relation between star formation rate and stellar mass, globally or on kpc-scales; hereafter SFMS) remains a hotly debated topic in galaxy evolution. Using the ALMA-MaNGA QUEnching and STar formation (ALMaQUEST) survey, we show that for star forming spaxels in the main sequence galaxies, the three local

Avital Dery, Yosef Nir

The recent measurement of $\Delta A_{CP}$ by the LHCb collaboration requires an ${\cal O}(10)$ enhancement coming from hadronic physics in order to be explained within the SM. We examine to what extent can NP models explain $\Delta A_{CP}$ without such enhancements. We discuss the implications in terms of a low energy effective theory as well as in the conte

Franco M. Luque

In this article we describe our participation in TASS 2019, a shared task aimed at the detection of sentiment polarity of Spanish tweets. We combined different representations such as bag-of-words, bag-of-characters, and tweet embeddings. In particular, we trained robust subword-aware word embeddings and computed tweet representations using a weighted-averag

Siddharth Venkatesh

In this article, we prove that the category of affine group schemes of finite type in the Verlinde category is equivalent to the category of Harish-Chandra pairs in the Verlinde category. Subsequently, we extend this equivalence to an equivalence between corresponding representation categories and then study some consequences of this equivalence to the repre

P. -F. Léget, E. Gangler, F. Mondon, G. Aldering

Type Ia Supernovae (SNe Ia) are widely used to measure the expansion of the Universe. Improving distance measurements of SNe Ia is one technique to better constrain the acceleration of expansion and determine its physical nature. This document develops a new SNe Ia spectral energy distribution (SED) model, called the SUpernova Generator And Reconstructor (SU

Jingyu He, Yao Xiao, Corina Bogdan, Shahin Nazarian

In this paper, we present a load-balancing approach to analyze and partition the UAV perception and navigation intelligence (PNI) code for parallel execution, as well as assigning each parallel computational task to a processing element in an Network-on-chip (NoC) architecture such that the total communication energy is minimized and congestion is reduced. F

Sifei Liu, Xueting Li, Varun Jampani, Shalini De Mello

Processing an input signal that contains arbitrary structures, e.g., superpixels and point clouds, remains a big challenge in computer vision. Linear diffusion, an effective model for image processing, has been recently integrated with deep learning algorithms. In this paper, we propose to learn pairwise relations among data points in a global fashion to imp

Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury

We present fully autonomous source seeking onboard a highly constrained nano quadcopter, by contributing application-specific system and observation feature design to enable inference of a deep-RL policy onboard a nano quadcopter. Our deep-RL algorithm finds a high-performance solution to a challenging problem, even in presence of high noise levels and gener

Haoyan Zhai, Magnus Egerstedt, Haomin Zhou

This paper introduces a graph-based, potential-guided method for path planning problems in unknown environments, where obstacles are unknown until the robots are in close proximity to the obstacle locations. Inspired by optimal transport theory, the proposed method generates a graph connecting the initial and target configurations, and then finds a path over

Shenghong Ju, Ryo Yoshida, Chang Liu, Kenta Hongo

Ultrahigh lattice thermal conductivity materials hold great importance since they play a critical role in the thermal management of electronic and optical devices. Models using machine learning can search for materials with outstanding higher-order properties like thermal conductivity. However, the lack of sufficient data to train a model is a serious hurdle

Yash Bhalgat, Zhe Liu, Pritam Gundecha, Jalal Mahmud

Given that labeled data is expensive to obtain in real-world scenarios, many semi-supervised algorithms have explored the task of exploitation of unlabeled data. Traditional tri-training algorithm and tri-training with disagreement have shown promise in tasks where labeled data is limited. In this work, we introduce a new paradigm for tri-training, mimicking

E. J. J. Smeur, M. Bronz, G. C. H. E. de Croon

Hybrid unmanned aircraft can significantly increase the potential of micro air vehicles, because they combine hovering capability with a wing for fast and efficient forward flight. However, these vehicles are very difficult to control, because their aerodynamics are hard to model and they are susceptible to wind gusts. This often leads to composite and compl

Kyeong Soo Kim, Sanghyuk Lee, Tiew On Ting, Xin-She Yang

The current formulation of the optimal scheduling of appliance energy consumption uses as optimization variables the vectors of appliances&#39; scheduled energy consumption over equally-divided time slots of a day, which does not take into account the atomicity of appliances&#39; operations (i.e., the unsplittable nature of appliances&#39; operations and res

Al Amin Hosain, Panneer Selvam Santhalingam, Parth Pathak, Jana Kosecka

Voice-controlled personal and home assistants (such as the Amazon Echo and Apple Siri) are becoming increasingly popular for a variety of applications. However, the benefits of these technologies are not readily accessible to Deaf or Hard-ofHearing (DHH) users. The objective of this study is to develop and evaluate a sign recognition system using multiple mo

Ian Aberbach, Thomas Polstra

We find sufficient conditions which imply equality of the finitistic test ideal and test ideal in rings of prime characteristic. Utilizing recent progress from the prime characteristic minimal model program we equate the notions of $F$-regular and strongly $F$-regular for 4-dimensional rings essentially of finite type over a field of prime characteristic $p>