November 2018 arXiv papers — page 5

Lin Chen, Nicole Megow, Roman Rischke, Leen Stougie

We consider a natural generalization of classical scheduling problems in which using a time unit for processing a job causes some time-dependent cost which must be paid in addition to the standard scheduling cost. We study the scheduling objectives of minimizing the makespan and the sum of (weighted) completion times. It is not difficult to derive a polynomi

S. Nakamura, N. Kabeya, M. Kobayashi, K. Araki

The magnetization and specific heat measurements have been performed on single-crystalline Gd_3_Ru_4_Al_12_ with a distorted Kagome lattice structure. This spin system is regarded as an antiferromagnetic triangular lattice of XY like Heisenberg model at low temperatures. The magnetic phase diagrams indicate the existence of frustration and Z_2_ degeneracy. T

Kanako Oshiro

Given a shadow biquandle $(B,X)$ composed of a biquandle $B$ and a strongly connected $B$-set $X$, we have a local biquandle structure on $X$. The (co)homology groups of such shadow biquandles are isomorphic to those of the corresponding local biquandles. Moreover, cocycle invariants, of oriented links and oriented surface-links, using such shadow biquandles

Yiling Chen, Shuran Zheng

We study a data analyst's problem of acquiring data from self-interested individuals to obtain an accurate estimation of some statistic of a population, subject to an expected budget constraint. Each data holder incurs a cost, which is unknown to the data analyst, to acquire and report his data. The cost can be arbitrarily correlated with the data. The data

Alex Turzillo

The two dimensional state sum models of Barrett and Tavares are extended to unoriented spacetimes. The input to the construction is an algebraic structure dubbed half twist algebras, a class of examples of which is real separable superalgebras with a continuous parameter. The construction generates pin-minus TQFTs, including the root invertible theory with p

Linghui Hou, Yi-Jian Du

All tree-level amplitudes in Einstein-Yang-Mills (EYM) theory and gravity (GR) can be expanded in terms of color ordered Yang-Mills (YM) ones whose coefficients are polynomial functions of Lorentz inner products and are constructed by a graphic rule. Once the gauge invariance condition of any graviton is imposed, the expansion of a tree level EYM or gravity

Zeeshan Haider, Kiramat Ullah, Tauseef Jamal

Cooperative networking brings performance improvement to most of the issues in wireless networks, such as fading or delay due to slow stations. However, due to cooperation when data is relayed via other nodes, there network is more prone to attacks. Since, channel access is very important for cooperation, most of the attacks happens at MAC. One of the most c

Slavko Rebec, Tao Jia, Hafiz Sohail, Makoto Hashimoto

Oxide materials are important candidates for the next generation of electronics due to a wide array of desired properties which they can exhibit alone or when combined with other materials. While SrTiO$_3$ (STO) is often considered a prototypical oxide, it too hosts a wide array of unusual properties including a two dimensional electron gas (2DEG) which can

Aleksandra Faust, Hao-Tien Lewis Chiang, Lydia Tapia

Robot motion planning often requires finding trajectories that balance different user intents, or preferences. One of these preferences is usually arrival at the goal, while another might be obstacle avoidance. Here, we formalize these, and similar, tasks as preference balancing tasks (PBTs) on acceleration controlled robots, and propose a motion planning so

Marthe Bonamy, Nicolas Bousquet, Guillem Perarnau

Let $G$ be a graph of maximum degree $\Delta$ and $k$ be an integer. The $k$-recolouring graph of $G$ is the graph whose vertices are $k$-colourings of $G$ and where two $k$-colourings are adjacent if they differ at exactly one vertex. It is well-known that the $k$-recolouring graph is connected for $k\geq \Delta+2$. Feghali, Johnson and Paulusma [Journal of

Fei Sun, Jieming Zhou

Systemic risk measures are crucial for the stability of financial markets, yet classical formulations fail to capture the complexity of market volatility. We propose a new framework for systemic risk measurement on the variable-exponent Bochner-Lebesgue space $L^{p(\cdot)}$, where the exponent $p(\cdot)$ is a random variable rather than a deterministic const

Andrew Zhai, Hao-Yu Wu

Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images. Two major applications of metric learning are content-based image retrieval and face verification. For the retrieval tasks, the majority of current state-of-the-art (SOTA) approaches are triplet-based non-parametric traini

Hikmet Çakmak

Sunspots are the most important indicator of the magnetic activity on the solar surface during a cycle. Every sunspot group is formed and shaped by the magnetic field of the Sun. Hence, the magnetic field intensity shows itself as the size of a sunspot group area on the surface. This shows that getting the development or evolution of sunspot groups over time

George K. Leontaris, Qaisar Shafi

Motivated by the ongoing searches for new physics at the LHC, we explore the low energy consequences of a D-brane inspired $ SU(4)_C\times SU(2)_L \times SU(2)_R$ (4-2-2) model. The Higgs sector consists of an $SU(4)$ adjoint, a pair $H+\bar H$ in $(4,1,2)+(\bar 4,1,2)$, and a bidoublet field in $h(1,2,2)$. With the $SU(4)$ adjoint the symmetry breaks to a l

Jiadong Guo, Paulo V. K. Borges, Chanoh Park, Abel Gawel

Place recognition is a challenging problem in mobile robotics, especially in unstructured environments or under viewpoint and illumination changes. Most LiDAR-based methods rely on geometrical features to overcome such challenges, as generally scene geometry is invariant to these changes, but tend to affect camera-based solutions significantly. Compared to c

Jinseok Choi, Yunseong Cho, Brian L. Evans, Alan Gatherer

In this paper, we investigate learning-based maximum likelihood (ML) detection for uplink massive multiple-input and multiple-output (MIMO) systems with one-bit analog-to-digital converters (ADCs). To overcome the significant dependency of learning-based detection on the training length, we propose two one-bit ML detection methods: a biased-learning method a

Houdun Zeng, Yuliang Xin, Siming Liu

Supernova remnants (SNRs) have been considered as the dominant contributors to Galactic cosmic rays. However, the relation between high-energy particles trapped in SNRs and cosmic rays observed at the Earth remains obscure. In this paper, we fit the spectral energy distributions of 35 SNRs with a simple one-zone emission model and analyze correlations of mod

Ning Dai. Qing-Feng Sun

One of the typical features of Majorana zero mode (MZM) at the end of topological superconductor is a zero-bias peak in the tunneling spectroscopy of the normal lead-superconductor junction. In this paper we study on a model with one phonon mode coupling to the superconductor lead of the normal lead-superconductor junction, which can be viewed as an electron

Tomasz M. Rutkowski, Qibin Zhao, Masao S. Abe, Mihoko Otake

Dementia and especially Alzheimer's disease (AD) are the most common causes of cognitive decline in elderly people. A spread of the above mentioned mental health problems in aging societies is causing a significant medical and economic burden in many countries around the world. According to a recent World Health Organization (WHO) report, it is approximated

Xingxing Wei, Siyuan Liang, Ning Chen, Xiaochun Cao

Adversarial examples have been demonstrated to threaten many computer vision tasks including object detection. However, the existing attacking methods for object detection have two limitations: poor transferability, which denotes that the generated adversarial examples have low success rate to attack other kinds of detection methods, and high computation cos

Sudeshna Roy, Meghana Madhyastha, Sheril Lawrence, Vaibhav Rajan

The Internet has rich and rapidly increasing sources of high quality educational content. Inferring prerequisite relations between educational concepts is required for modern large-scale online educational technology applications such as personalized recommendations and automatic curriculum creation. We present PREREQ, a new supervised learning method for in

Abhijit Roy, Rakesh Kumar Singh, Maruthi M. Brundavanam

A technique based on speckle contrast measurement is proposed and demonstrated to track the polarization rotation of an optical beam behind a scattering layer. It is shown that with the help of a reference speckle pattern with a known linear polarization, it is possible to track the polarization rotation behind a scattering layer in a non-invasive manner by

Jinseok Choi, Gilwon Lee, Brian L. Evans

In this paper, we propose a two-stage analog combining architecture for millimeter wave (mmWave) communications with hybrid analog/digital beamforming and low-resolution analog-to-digital converters (ADCs). We first derive a two-stage combining solution by solving a mutual information (MI) maximization problem without a constant modulus constraint on analog

Keith J. Kasunic

The shift in Aharanov-Bohm electron-interference fringe positions has been previously derived as resulting from phase differences induced by the magnetic vector potential, without being clear on the physical mechanism behind it. In this paper, we show that the de Broglie wavelength of the electron wavefunction is changed locally by its interaction with the v

Jyoti Islam, Yanqing Zhang

Automated segmentation of Lungs plays a crucial role in the computer-aided diagnosis of chest X-Ray (CXR) images. Developing an efficient Lung segmentation model is challenging because of difficulties such as the presence of several edges at the rib cage and clavicle, inconsistent lung shape among different individuals, and the appearance of the lung apex. I

Umair Ahmed, Zubair Khalid

In practice, the finite number of samples of the spherical radiation pattern or antenna gain are taken on the sphere for both the reconstruction of the antenna radiation pattern and the computation of mobile handset performance measures such as directivity and mean effective gain (MEG). The acquisition of samples is time consuming as the measurements are req

Raquel Galazo, Irene Bartolomé, Laura Ares, Alfredo Luis

Two complementary observables can be measured simultaneously so that the exact individual distributions can be recovered by a proper data inversion. We apply this program to the paradigmatic example of the Young interferometer from the classical and quantum points of view. We show complete parallelism between complementarity in the quantum and classical theo

Yongwei Huang, Longtao Zhou

Consider a multiuser downlink beamforming optimization problem for the non-orthogonal multiple access (NOMA) transmission in a multiple-input single-output (MISO) system. The total transmission power minimization problem is formulated subject to both per-antenna power constraints and quality-of-service (QoS) constraints under the NOMA principal. The problem

Sooyeon Lee, Huy Kang Kim

Since with massive data growth, the need for autonomous and generic anomaly detection system is increased. However, developing one stand-alone generic anomaly detection system that is accurate and fast is still a challenge. In this paper, we propose conventional time-series analysis approaches, the Seasonal Autoregressive Integrated Moving Average (SARIMA) m

Yahui Wang, Shaojun Cai, Shi-Jie Li, Yun Liu

We present a real-time feature-based SLAM (Simultaneous Localization and Mapping) system for fisheye cameras featured by a large field-of-view (FoV). Large FoV cameras are beneficial for large-scale outdoor SLAM applications, because they increase visual overlap between consecutive frames and capture more pixels belonging to the static parts of the environme

Tengteng Lu, Zhen Li, Chao Luo, Jun Xu

Previous cryogenic electronics studies are most above 4.2K. In this paper we present the cryogenic characterization of a 0.18{\mu}m standard bulk CMOS technology(1.8V and 5V) at sub-kelvin temperature around 270mK. PMOS and NMOS devices with different width to length ratios(W/L) are tested and characterized under various bias conditions at temperatures from

Xiang Fan

A well-known result of von zur Gathen asserts that a non-exceptional permutation polynomial of degree $n$ over $\mathbb{F}_{q}$ exists only if $q<n^{4}$. With the help of the Weil bound for the number of $\mathbb{F}_{q}$-points on an absolutely irreducible (possibly singular) affine plane curve, Chahal and Ghorpade improved von zur Gathen's proof to replace

Yurui Ming, Chin-Teng Lin, Stephen D. Bartlett, Wei-Wei Zhang

Topologically ordered materials may serve as a platform for new quantum technologies such as fault-tolerant quantum computers. To fulfil this promise, efficient and general methods are needed to discover and classify new topological phases of matter. We demonstrate that deep neural networks augmented with external memory can use the density profiles formed i

Li Huang, Yifeng Yin, Zeng Fu, Shifa Zhang

Intensive care data are valuable for improvement of health care, policy making and many other purposes. Vast amount of such data are stored in different locations, on many different devices and in different data silos. Sharing data among different sources is a big challenge due to regulatory, operational and security reasons. One potential solution is federa

Haifeng Yu, Ivica Nikolic, Ruomu Hou, Prateek Saxena

Many blockchain consensus protocols have been proposed recently to scale the throughput of a blockchain with available bandwidth. However, these protocols are becoming increasingly complex, making it more and more difficult to produce proofs of their security guarantees. We propose a novel permissionless blockchain protocol OHIE which explicitly aims for sim

Hyungu Kahng, Yonghyun Jeong, Yoon Sang Cho, Gonie Ahn

StarCraft, one of the most popular real-time strategy games, is a compelling environment for artificial intelligence research for both micro-level unit control and macro-level strategic decision making. In this study, we address an eminent problem concerning macro-level decision making, known as the 'fog-of-war', which rises naturally from the fact that info

Tsung-Wei Chen, Zhi-Yang Huang, Dah-Wei Chiou

We investigate the spin dynamics in the two-dimensional spin-orbit coupled system subject to an in-plane ($x$-$y$ plane) constant electric field, which is assumed to be turned on at the moment $t=0$. The equation of spin precession in linear response to the switch-on of the electric field is derived in terms of Heisenberg's equation by the perturbation metho

Jaeman Song, Mikyung Lim, Seung S. Lee, Bong Jae Lee

Numerous studies have reported performance enhancement of a thermophotovoltaic (TPV) system when an emitter is separated by nanoscale gaps from a TPV cell. Although a $p$-$n$-junction-based TPV cell has been widely used for the near-field TPV system, a Schottky-junction-based near-field TPV system has drawn attention recently with the advantage of the easy f

Sanghyun Ha, Junshin Park, Donghyun You

A new flow solver scalable on multiple Graphics Processing Units (GPUs) for direct numerical simulation of wall-bounded incompressible flow is presented. This solver utilizes a previously reported work (J. Comp. Physics, vol. 352 (2018), pp.246-264) which proposes a semi-implicit fractional-step method on a single GPU. Extension of this work to accommodate m

Guoqing Pu, Lilin Yi, Li Zhang, Weisheng Hu

Nonlinear polarized evolution-based passively mode-locked fiber lasers with ultrafast and high peak power pulses are a powerful tool for engineering applications and research. However, their sensitivity to polarization limits their widespread application. To address this, automatic mode-locking immune to environmental disturbances is attracting more concerns

Elham J. Barezi, Peyman Momeni, Pascale Fung

We propose a novel method, Modality-based Redundancy Reduction Fusion (MRRF), for understanding and modulating the relative contribution of each modality in multimodal inference tasks. This is achieved by obtaining an $(M+1)$-way tensor to consider the high-order relationships between $M$ modalities and the output layer of a neural network model. Applying a

Daniele Pinna, George Bourianoff, Karin Everschor-Sitte

The Reservoir Computing (RC) paradigm posits that sufficiently complex physical systems can be used to massively simplify pattern recognition tasks and nonlinear signal prediction. This work demonstrates how random topological magnetic textures present sufficiently complex resistance responses for the implementation of RC as applied to A/C current pulses. In

Miguel Munoz Rojo, Zuanyi Li, Charles Sievers, Alex C. Bornstein

Step junctions are often present in layered materials, i.e. where single-layer regions meet multi-layer regions, yet their effect on thermal transport is not understood to date. Here, we measure heat flow across graphene junctions (GJs) from monolayer to bilayer graphene, as well as bilayer to four-layer graphene for the first time, in both heat flow directi

Mohamad Gharib, John Mylopoulos

Nowadays, most companies need to collect, store, and manage personal information in order to deliver their services. Accordingly, privacy has emerged as a key concern for these companies since they need to comply with privacy laws and regulations. To deal with them properly, such privacy concerns should be considered since the early phases of system design.

Gurcan Comert, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury

Connected vehicle (CV) systems are cognizant of potential cyber attacks because of increasing connectivity between its different components such as vehicles, roadside infrastructure and traffic management centers. However, it is a challenge to detect security threats in real-time and develop appropriate/effective countermeasures for a CV system because of th

Hyunseok Kim, Hyunwoo Kwon

We consider the Dirichlet and Neumann problems for second-order linear elliptic equations: \[ -\triangle u +\mathrm{div}(u\mathbf{b}) =f \quad\text{ and }\quad -\triangle v -\mathbf{b} \cdot \nabla v =g \] in a bounded Lipschitz domain $\Omega$ in $\mathbb{R}^n$ $(n\geq 3)$, where $\mathbf{b}:\Omega \rightarrow \mathbb{R}^n$ is a given vector field. Under th

Tanja Kling, Felix Kling, Davide Donadio

We characterized the structural and dynamical properties of the quasi-liquid layer (QLL) at the surface of ice by molecular dynamics simulations with a thermodynamically consistent water model. Our simulations show that for three low-index ice surfaces only the outermost molecular layer presents short-range and mid-range disorder and is diffusive. The onset

Yu-Ki Lee, Zhonghua Xi, Young-Joo Lee, Yun-Hyeong Kim

This study starts from the counter-intuitive question of how we can render a conventional stiff, non-stretchable and even brittle material conformable so that it can fully wrap around a curved surface, such as a sphere, without failure. Here, we answer this conundrum by extending geometrical design in computational kirigami (paper cutting and folding) to pap

Mingyuan Ma, Sen Na, Hongyu Wang, Congzhou Chen

Interactive news recommendation has been launched and attracted much attention recently. In this scenario, user's behavior evolves from single click behavior to multiple behaviors including like, comment, share etc. However, most of the existing methods still use single click behavior as the unique criterion of judging user's preferences. Further, although h

Sayyed Mohsen Vazirizade, Ali Bakhshi, Omid Bahar

Civil structures are on the verge of changing which leads energy dissipation capacity to decline. Structural Health Monitoring (SHM) as a process in order to implement a damage detection strategy and assess the condition of structure plays a key role in structural reliability. Earthquake is a recognized factor in variation of structures condition, inasmuch a

Koji Hashimoto, Shunichiro Kinoshita, Keiju Murata

Thermal states in some quantum field theories (QFTs) correspond to black holes in asymptotically AdS spacetime in the AdS/CFT correspondence. We propose a direct procedure to construct holographic images of the black hole in the bulk from a given response function of the QFT on the boundary. The response function with respect to an external source correspond

O. V. Bogdanov, P. O. Kazinski

The effect of a finite width of a particle bunch on radiation of twisted photons is studied. The general formulas connecting the radiation probability distribution of twisted photons produced by bunches of identical particles with the radiation probability distribution of twisted photons generated by one particle are obtained for axially symmetric bunches. T

Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik

We propose a possible solution to a public challenge posed by the Fair Isaac Corporation (FICO), which is to provide an explainable model for credit risk assessment. Rather than present a black box model and explain it afterwards, we provide a globally interpretable model that is as accurate as other neural networks. Our "two-layer additive risk model" is de

Dinesh Kumar, Abhishek Kumar, Rajiv Prakash, Akhilesh Kumar Singh

The nanoparticles (NPs) of Zn1-xCuxFe2O4 (ZCFO) spinels with x = 0, 0.2, 0.4, 0.6 and 0.8 were synthesized by a sol-gel combustion method using acetate precursor. The NPs of ZCFO were prepared by following calcination process at 600C for 8hrs. The synthesized NPs of ZCFO were characterized by X-ray diffraction (XRD) analysis using Rietveld refinement. The Ri

H. H. Jen

We theoretically investigate the flow of the atomic excitations in a driven chiral-coupled atomic chain with nonreciprocal decay channels. This one-dimensional system allows infinite-range dipole-dipole interaction, and enables directional guided modes of scattered light. Under a weakly driven condition, we are able to simulate the transport properties of at

Tao Zhu, Qiang Wu, Anzhong Wang

Field amplification and particle production due to parametric resonance are highly nontrivial predictions of quantum fields that couple to an oscillating source during inflation and reheating. Understanding this two effects is crucial for the connection between the resonance phenomenon and precise observational data. In this paper, we give a general and anal

Binghui Chen, Weihong Deng, Haifeng Shen

Recently, learning discriminative features to improve the recognition performances gradually becomes the primary goal of deep learning, and numerous remarkable works have emerged. In this paper, we propose a novel yet extremely simple method \textbf{Virtual Softmax} to enhance the discriminative property of learned features by injecting a dynamic virtual neg

Vishal Sharma

The blockchain is a safe, reliable and innovative mechanism for managing numerous vehicles seeking connectivity. However, following the principles of the blockchain, the number of transactions required to update ledgers pose serious issues for vehicles as these may consume the maximum available energy. To resolve this, an efficient model is presented in this

Farhang Momeni, Jun Ni

4D printing is a new manufacturing paradigm that combines stimuli-responsive materials, mathematics, and multi-material additive manufacturing to yield encoded multi-material structures with intelligent behavior over time. This emerging field has received growing interests from various disciplines such as space exploration, renewable energy, bioengineering,

Yukang Wang, Yongchao Xu, Stavros Tsogkas, Xiang Bai

Computing object skeletons in natural images is challenging, owing to large variations in object appearance and scale, and the complexity of handling background clutter. Many recent methods frame object skeleton detection as a binary pixel classification problem, which is similar in spirit to learning-based edge detection, as well as to semantic segmentation

Christopher Funk, Savinay Nagendra, Jesse Scott, Bharadwaj Ravichandran

Pose stability analysis is the key to understanding locomotion and control of body equilibrium, with applications in numerous fields such as kinesiology, medicine, and robotics. In biomechanics, Center of Pressure (CoP) is used in studies of human postural control and gait. We propose and validate a novel approach to learn CoP from pose of a human body to ai

Lou Zhao

This thesis considers channel estimation and multiuser (MU) data transmission for massive MIMO systems with fully digital/hybrid structures in mmWave channels. It contains three main contributions. In this thesis, we first propose a tone-based linear search algorithm to facilitate the estimation of angle-of-arrivals of the strongest components as well as sca

Qingyu Liu, Haibo Zeng, Minghua Chen

We consider the scenario where a sender periodically sends a batch of data to a receiver over a multi-hop network, possibly using multiple paths. Our objective is to minimize peak/average Age-of-Information (AoI) subject to throughput requirements. The consideration of batch generation and multi-path communication differentiates our AoI study from existing o

Wei Chen, Xiaopeng Zheng, Jingyao Ke, Na Lei

This work proposes a novel metric based algorithm for quadrilateral mesh generating. Each quad-mesh induces a Riemannian metric satisfying special conditions: the metric is a flat metric with cone signualrites conformal to the original metric, the total curvature satisfies the Gauss-Bonnet condition, the holonomy group is a subgroup of the rotation group $\{

Allen Gehret, Travis Nell

In this note, we construct a distal expansion for the structure $(\mathbb{R}; +,<,H)$, where $H\subseteq \mathbb{R}$ is a dense $\mathbb{Q}$-vector space basis of $\mathbb{R}$ (a so-called Hamel basis). Our construction is also an expansion of the dense pair $(\mathbb{R}; +,<,\mathbb{Q})$ and has full quantifier elimination in a natural language.

Hossein Keshavarz, XuanLong Nguyen, Clayton Scott

Maximizing the likelihood has been widely used for estimating the unknown covariance parameters of spatial Gaussian processes. However, evaluating and optimizing the likelihood function can be computationally intractable, particularly for large number of (possibly) irregularly spaced observations, due to the need to handle the inverse of ill-conditioned and

Angus Galloway, Anna Golubeva, Graham W. Taylor

We analyze the adversarial examples problem in terms of a model's fault tolerance with respect to its input. Whereas previous work focuses on arbitrarily strict threat models, i.e., $\epsilon$-perturbations, we consider arbitrary valid inputs and propose an information-based characteristic for evaluating tolerance to diverse input faults.

R. Y. Umetsu, H. Fujiwara, K. Nagai, Y. Nakatani

Detailed information on the electronic states of both V and Mn 3d electrons in the ferrimagnet Mn2VAl is obtained by the bulk sensitive resonant inelastic soft x-ray scattering (SX-RIXS) excited with the circularly polarized light under an external magnetic field for the first time. The results under the V L-edge excitation have revealed the negligible parti

Chuanfeng Hu, Hongwei Lin

In isogeometric analysis, it is frequently required to handle the geometric models enclosed by four-sided or non-four-sided boundary patches, such as trimmed surfaces. In this paper, we develop a Gregory solid based method to parameterize those models. First, we extend the Gregory patch representation to the trivariate Gregory solid representation. Second, t

Kyle Vedder, Joydeep Biswas

Real-world multi-agent systems such as warehouse robots operate under significant time constraints -- in such settings, rather than spending significant amounts of time solving for optimal paths, it is instead preferable to find valid collision-free paths quickly, even if suboptimal, and given additional time, to iteratively refine such paths to improve thei

Hongwei Lin, Hao Huang, Chuanfeng Hu

The advent of isogeometric analysis has prompted a need for methods to generate Trivariate B-spline Solids (TBS) with positive Jacobian. However, it is difficult to guarantee a positive Jacobian of a TBS since the geometric pre-condition for ensuring the positive Jacobian is very complicated. In this paper, we propose a method for generating TBSs with guaran

Lu Yang, Qing Song, Zhihui Wang, Ming Jiang

Instance-level human analysis is common in real-life scenarios and has multiple manifestations, such as human part segmentation, dense pose estimation, human-object interactions, etc. Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance. In this paper, we present an end-to-e

W. W. Ge, Y. J. Yuan, J. C. Yang, R. J. Chen

The Isochronous Mass Spectrometry (IMS) based on storage rings is a powerful technique for mass measurement of short-lived exotic nuclei. The transition energy $\gamma_t$ of the storage ring is a vital parameter of the IMS technique. It is difficult to measure the $\gamma_t$ and its relation to momentum spread or circulating length, especially to monitor the

Christoph Böhm, Ramiro A. Lafuente

We show that homogeneous Einstein metrics on Euclidean spaces are Einstein solvmanifolds, using that they admit periodic, integrally minimal foliations by homogeneous hypersurfaces. For the geometric flow induced by the orbit-Einstein condition, we construct a Lyapunov function based on curvature estimates which come from real GIT.

Yezheng Li, Hongzhe Li

Suppose two networks are observed for the same set of nodes, where each network is assumed to be generated from a weighted stochastic block model. This paper considers the problem of testing whether the community memberships of the two networks are the same. A test statistic based on singular subspace distance is developed. Under the weighted stochastic bloc

Timur E. Gureyev, Alexander Kozlov, Yakov I. Nesterets, David M. Paganin

It is proved that the width of a function and the width of the distribution of its values cannot be made arbitrarily small simultaneously. In the case of ergodic stochastic processes, an ensuing uncertainty relationship is demonstrated for the product of correlation length and variance. A closely related uncertainty principle is also established for the aver

Yuheng Bu, Kevin Small

While recommendation systems generally observe user behavior passively, there has been an increased interest in directly querying users to learn their specific preferences. In such settings, considering queries at different levels of granularity to optimize user information acquisition is crucial to efficiently providing a good user experience. In this work,

Beau Norgeot, Dmytro Lituiev, Benjamin S. Glicksberg, Atul J. Butte

Clinical data for ambulatory care, which accounts for 90% of the nations healthcare spending, is characterized by relatively small sample sizes of longitudinal data, unequal spacing between visits for each patient, with unequal numbers of data points collected across patients. While deep learning has become state-of-the-art for sequence modeling, it is unkno

Panyue Zhou, Bin Zhu

Let $\mathcal{C}$ be a triangulated category with shift functor $[1]$ and $\mathcal{R}$ a rigid subcategory of $\mathcal{C}$. We introduce the notions of two-term $\mathcal{R}[1]$-rigid subcategories, two-term (weak) $\mathcal{R}[1]$-cluster tilting subcategories and two-term maximal $\mathcal{R}[1]$-rigid subcategories, and discuss relationship between them

Yuuki Yokoyama, Tomu Katsumata, Muneki Yasuda

Generalization is one of the most important issues in machine learning problems. In this study, we consider generalization in restricted Boltzmann machines (RBMs). We propose an RBM with multivalued hidden variables, which is a simple extension of conventional RBMs. We demonstrate that the proposed model is better than the conventional model via numerical ex

Dmitry Golovaty, Michael Novack, Peter Sternberg, Raghavendra Venkatraman

We analyze a model problem based on highly disparate elastic constants that we propose in order to understand corners and cusps that form on the boundary between the nematic and isotropic phases in a liquid crystal. For a bounded planar domain $\Omega$ we investigate the $\varepsilon \to 0$ asymptotics of the variational problem \[\inf \frac{1}{2}\int_\Omega

Marco M. Dias e Costa, J. M. Toledo, V. B. Bezerra

We obtain the solution corresponding to a static and spherically symmetric black hole with a cloud of strings (Letelier spacetime) immersed in a quintessential fluid. We discuss some aspects of its thermodynamics. We also present a discussion about Hawking radiation of particles, in the background under consideration.

Lars Martin Sektnan

We prove a version of the Arezzo-Pacard-Singer blow-up theorem in the setting of Poincar\'e type metrics. We apply this to give new examples of extremal Poincar\'e type metrics. A key feature is an additional obstruction which has no analogue in the compact case. This condition is conjecturally related to ensuring the metrics remain of Poincar\'e type.

Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann

Machine learning for healthcare often trains models on de-identified datasets with randomly-shifted calendar dates, ignoring the fact that data were generated under hospital operation practices that change over time. These changing practices induce definitive changes in observed data which confound evaluations which do not account for dates and limit the gen

Harleigh C. Marsh, Mark Karpenko, Qi Gong

Historically, solving optimal control problems with high index differential algebraic equations (DAEs) has been considered extremely hard. Computational experience with Runge-Kutta (RK) methods confirms the difficulties. High index DAE problems occur quite naturally in many practical engineering applications. Over the last two decades, a vast number of real-

Nicholas R. Beaton, Jeremy W. Eng, Christine E. Soteros

We study several related models of self-avoiding polygons in a tubular subgraph of the simple cubic lattice, with a particular interest in the asymptotics of the knotting statistics. Polygons in a tube can be characterised by a finite transfer matrix, and this allows for the derivation of pattern theorems, calculation of growth rates and exact enumeration. W

Heping Dong, Jun Lai, Peijun Li

This paper concerns an inverse elastic scattering problem which is to determine the location and the shape of a rigid obstacle from the phased or phaseless far-field data for a single incident plane wave. By introducing the Helmholtz decomposition, the model problem is reduced to a coupled boundary value problem of the Helmholtz equations. The relation is es

Devlin Mallory

We give an answer in the "geometric" setting to a question of de Fernex, Ein, and Ishii, asking when local isomorphisms of $k$-schemes can be detected on the associated maps of local arc or jet schemes. In particular, we show that their ideal-closure operation $\mathfrak a\mapsto \mathfrak a^{\mathrm{ac}}$ (the arc-closure) on a local $k$-algebra $(R,\mathfr

Étienne André, Benoît Delahaye, Paulin Fournier, Didier Lime

In this paper we consider state reachability in networks composed of many identical processes running a parametric timed broadcast protocol (PTBP). PTBP are a new model extending both broadcast protocols and parametric timed automata. This work is, up to our knowledge, the first to consider the combination of both a parametric network size and timing paramet

Richard Cleve, Benoit Collins, Li Liu, Vern Paulsen

We consider a bipartite transformation that we call self-embezzlement and use it to prove a constant gap between the capabilities of two models of quantum information: the conventional model, where bipartite systems are represented by tensor products of Hilbert spaces; and a natural model of quantum information processing for abstract states on C*-algebras,

Kai Du, Rui Peng, Ningkui Sun

It is known that a species dies out in the long run for small initial data if its evolution obeys a reaction of bistable nonlinearity. Such a phenomenon, which is termed as the strong Allee effect, is well supported by numerous evidence from ecosystems, mainly due to the environmental pollution as well as unregulated harvesting and hunting. To save an endang

Quan Z. Sheng, Jian Yu, Hanchuan Xu, Wei Emma Zhang

In the era of Web of Things and Services, Context-aware Web Services (CASs) are emerging as an important technology for building innovative context-aware applications. CASs enable the information integration from both the physical and virtual world, which affects human living. However, it is challenging to build CASs, due to the lack of context provisioning

Xiunan Yang, Hua Tong, Weihua Wang, Ke Chen

We rejuvenate well-aged quasi-2D binary colloidal glasses by thermal cycling, and systematically measure both the statistical responses and particle-level structural evolutions during rejuvenation. While the moduli and boson peak are continuously rejuvenated with increasing number of cycles, the mean square displacement (MSD) fluctuates significantly between

Siye Wu

Kapustin and Witten showed that a twisted version of N=4 gauge theory in four dimensions compactifies to a two-dimensional sigma-model whose target space is the Hitchin moduli space. In this talk, I consider the reduction of the gauge theory on a four dimensional orientable spacetime manifold which is not a global product of two surfaces but contains embedde

C. J. Glaser, D. Pocanic, L. P. Alonzi, V. A. Baranov

With few open channels and uncomplicated theoretical description, charged pion decays are uniquely sensitive to certain standard model (SM) symmetries, the universality of weak fermion couplings, and to aspects of pion structure and chiral dynamics. We review the current knowledge of the pion electronic decay $\pi^+ \to e^+ \nu_e({\gamma})$, or $\pi_{e2({\ga

Amruta Mishra, Ankit Kumar, Pallabi Parui, Sourodeep De

The mass modifications of the light vector mesons ($\omega$, $\rho$ and $\phi$) are investigated in asymmetric nuclear matter in the presence of strong magnetic fields, using a QCD sum rule approach. These are computed from the medium modifications of the non-strange and strange light quark condensates as well as scalar gluon condensate. The quark and gluon

Kailas Vodrahalli, Ke Li, Jitendra Malik

Modern computer vision algorithms often rely on very large training datasets. However, it is conceivable that a carefully selected subsample of the dataset is sufficient for training. In this paper, we propose a gradient-based importance measure that we use to empirically analyze relative importance of training images in four datasets of varying complexity.

Chandra Chekuri, Kent Quanrud

We consider parallel, or low adaptivity, algorithms for submodular function maximization. This line of work was recently initiated by Balkanski and Singer and has already led to several interesting results on the cardinality constraint and explicit packing constraints. An important open problem is the classical setting of matroid constraint, which has been i

Tsung-Hsi Wu, Chien-Chih Chen

In this paper, we propose a stochastic dynamic model for earthquake rupture and suggest that the Langevin equation of frictions may be used for interpreting the slip distributions of rupture processes in earthquakes. The steady-state solution of the derived Langevin equation analytically attains the truncated exponential (TEX) distribution that is empiricall

Marianna Chatzakou, Julio Delgado, Michael Ruzhansky

In this work we study a class of anharmonic oscillators within the framework of the Weyl-H\"ormander calculus. The anharmonic oscillators arise from several applications in mathematical physics as natural extensions of the harmonic oscillator. A prototype is an operator on $\mathbb{R}^n$ of the form $(-\Delta)^{\ell}+|x|^{2k}$ for $k,\ell$ integers $\geq 1$.