July 2019 arXiv papers — page 19

Benjamin K. Tapley, Helge I. Andersson, Elena Celledoni, Brynjulf Owren

A geometric numerical method for simulating suspensions of spherical and non-spherical particles with Stokes drag is proposed. The method combines divergence-free matrix-valued radial basis function interpolation of the fluid velocity field with a splitting method integrator that preserves the sum of the Lyapunov spectrum while mimicking the centrifuge effec

Jakub Nalepa, Lukasz Tulczyjew, Michal Myller, Michal Kawulok

Hyperspectral imaging provides detailed information about the scanned objects, as it captures their spectral characteristics within a large number of wavelength bands. Classification of such data has become an active research topic due to its wide applicability in a variety of fields. Deep learning has established the state of the art in the area, and it con

James Meneghello, Nik Thompson, Kevin Lee, Kok Wai Wong

The pervasiveness of Social Media and user-generated content has triggered an exponential increase in global data volumes. However, due to collection and extraction challenges, data in many feeds, embedded comments, reviews and testimonials are inaccessible as a generic data source. This paper incorporates Knowledge Management framework as a paradigm for kno

Hong Cao, Shao-Wu Yao, Li-Xiang Cen

The anomalous dynamical evolution and the crossing of nonadiabatic energy levels are investigated for exactly solvable time-dependent quantum systems through a reverse-engineering scheme. By exploiting a typical driven model, we elucidate the peculiarities of its dynamics with anomalous behavior: the evolution of the adiabatic states and of the nonadiabatic

Di Jin, Zhijing Jin, Joey Tianyi Zhou, Peter Szolovits

Machine learning algorithms are often vulnerable to adversarial examples that have imperceptible alterations from the original counterparts but can fool the state-of-the-art models. It is helpful to evaluate or even improve the robustness of these models by exposing the maliciously crafted adversarial examples. In this paper, we present TextFooler, a simple

Tôru Sakai, Kiyomi Okamoto, Takashi Tonegawa

We investigate the $S=2$ antiferromagnetic quantum spin chain with the exchange and single-ion anisotropies in a magnetic field, using the numerical exact diagonalization of finite-size clusters and the level spectroscopy analysis. It is found that a magnetization plateau possibly appears at a half of the saturation magnetization for some suitable anisotropy

G. K. Goswami, Meena Mishra, Anil Kumar Yadav, Anirudh Pradhan

In this paper, we study a Bianchi type -I model of universe filled with barotropic and dark energy(DE) type fluids. The present values of cosmological parameters such as Hubble constant $H_0$, barotropic, DE and anisotropy energy parameters $(\Omega_{m})_0$, $(\Omega_{de})_0$ and $(\Omega_{\sigma})_0 $ and Equation of State(EoS) parameter for DE ($\omega_{de

Jaba Saha, Sudip Suklabaidya, Jayasree Nath, Arpan Datta Roy

A mercury (II) sensor has been proposed based on Fluorescence Resonance Energy Transfer (FRET) between N,N'-dioctadecyl thiacyanine perchlorate (NK) and Octadecyl rhodamine B chloride (RhB). Out of these two molecules NK is sensitive to Hg2+ ions due to presence of sulfur atom in it. Accordingly, presence of Hg2+ ions affects the NK fluorescence as well as F

Sergio Albeverio, Nicolò Cangiotti, Sonia Mazzucchi

A Feynman path integral formula for the Schr\"odinger equation with magnetic field is rigorously mathematically realized in terms of infinite dimensional oscillatory integrals. We show (by the example of a linear vector potential) that the requirement of the independence of the integral on the approximation procedure forces the introduction of a counterterm

Samuel N. Mellon, Eric E. Mamajek, Remko Stuik, Konstanze Zwintz

Besides monitoring the bright star $\beta$ Pic during the near transit event for its giant exoplanet, the $\beta$ Pictoris b Ring (bRing) observatories at Siding Springs Observatory, Australia and Sutherland, South Africa have monitored the brightnesses of bright stars ($V$ $\simeq$ 4--8 mag) centered on the south celestial pole ($\delta$ $\leq$ -30$^{\circ}

Marco Chianese

Recent analyses of the diffuse TeV-PeV neutrino flux highlight a tension between different Ice-Cube data samples that strongly suggests a two-component scenario rather than a single steep power-law flux. Such a tension is further strengthened once the latest ANTARES data are also taken into account. Remarkably, both experiments show an excess in the same ene

Dietmar Pfeifer

After several years of development, the Solvency II-project has finally been set to work in the European Union with the beginning of the year 2016. This has caused massive changes in the regional legislative supervisory acts. One new aspect of regulation is the requirement of an analysis and judgement concerning possible deviations of the company's risk prof

Jake Levinson, Kevin Purbhoo

We prove a generalization of the Shapiro-Shapiro conjecture on Wronskians of polynomials, allowing the Wronskian to have complex conjugate roots. We decompose the real Schubert cell according to the number of real roots of the Wronski map, and define an orientation of each connected component. For each part of this decomposition, we prove that the topologica

Lei Shi, Shu Wang, Tianni Lu, Yuan He

High stability and oxygen permeability are two prominent requirements for the oxygen transport membrane candidates used as industrialization. Herein, we report several composite membranes based on xwt.%Ce0.9Pr0.1O2(CPO)-(100-x)wt.%Pr0.6Sr0.4Fe0.8Al0.2O3(PSFAO) (x = 50, 60 and 75) prepared via a modified Pechini method. Oxygen permeability test reveals that t

Cheng-Han Lee, Ziwei Liu, Lingyun Wu, Ping Luo

Facial image manipulation has achieved great progress in recent years. However, previous methods either operate on a predefined set of face attributes or leave users little freedom to interactively manipulate images. To overcome these drawbacks, we propose a novel framework termed MaskGAN, enabling diverse and interactive face manipulation. Our key insight i

Zitong Yu, Wei Peng, Xiaobai Li, Xiaopeng Hong

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any contact, has great potential in many applications (e.g., remote healthcare). Existing rPPG approaches rely on analyzing very fine details of facial videos, which are prone to be affected by video compression. Here we propose a two-stage, end-to-end method using hidden rP

Daniel Kasprowski, Peter Teichner

We show that two closed, connected $4$-manifolds with finite fundamental groups are $\mathbb{CP}^2$-stably homeomorphic if and only if their quadratic $2$-types are stably isomorphic and their Kirby-Siebenmann invariant agrees.

Zhao Deng, L. L. Lao, V. S. Chan, R. Prater

This paper develops two non-inductive steady state scenarios for larger size configuration of China Fusion Engineering Test Reactor (CFETR) with integrated modeling simulations. A self-consistent core-pedestal coupled workflow for CFETR is developed under integrated modeling framework OMFIT, which allows more accurate evaluation of CFETR performance. The wor

Zhenzhen Feng, Jing Ma

In this paper, we investigate exceptional sets in the Waring-Goldbach problem for unlike powers. For example, estimates are obtained for sufficiently large integers below a parameter subject to the necessary local conditions that do not have a representation as the sum of a square of prime, a cube of prime and a sixth power of prime and a $k$-th power of pri

Seong Hun Lee, Javier Civera

For decades, it has been widely accepted that the gold standard for two-view triangulation is to minimize the cost based on reprojection errors. In this work, we challenge this idea. We propose a novel alternative to the classic midpoint method that leads to significantly lower 2D errors and parallax errors. It provides a numerically stable closed-form solut

Ion Errea, Francesco Belli, Lorenzo Monacelli, Antonio Sanna

The discovery of superconductivity at 200 K in the hydrogen sulfide system at large pressures [1] was a clear demonstration that hydrogen-rich materials can be high-temperature superconductors. The recent synthesis of LaH$_{10}$ with a superconducting critical temperature (T$_{\text{c}}$) of 250 K [2,3] places these materials at the verge of reaching the lon

Allan Borodin, Akash Rakheja

We discuss the problem of setting prices in an electronic market that has more than one buyer. We assume that there are self-interested sellers each selling a distinct item that has an associated cost. Each buyer has a submodular valuation for purchasing any subset of items. The goal of the sellers is to set a price for their item such that their profit from

Ang Li, Xue Yang, Chongyang Zhang

We extend the state-of-the-art Cascade R-CNN with a simple feature sharing mechanism. Our approach focuses on the performance increases on high IoU but decreases on low IoU thresholds--a key problem this detector suffers from. Feature sharing is extremely helpful, our results show that given this mechanism embedded into all stages, we can easily narrow the g

Joseph E. Gaudio, Anuradha M. Annaswamy, Michael A. Bolender, Eugene Lavretsky

Input constraints as well as parametric uncertainties must be accounted for in the design of safe control systems. This paper presents an adaptive controller for multiple-input-multiple-output (MIMO) plants with input magnitude and rate saturation in the presence of parametric uncertainties. A filter is introduced in the control path to accommodate the prese

Yunfei Liu, Yu Li, Shaodi You, Feng Lu

Reflection is common in images capturing scenes behind a glass window, which is not only a disturbance visually but also influence the performance of other computer vision algorithms. Single image reflection removal is an ill-posed problem because the color at each pixel needs to be separated into two values, i.e., the desired clear background and the reflec

Cheng Qian, Amin Emad, Nicholas D. Sidiropoulos

The biological processes involved in a drug's mechanisms of action are oftentimes dynamic, complex and difficult to discern. Time-course gene expression data is a rich source of information that can be used to unravel these complex processes, identify biomarkers of drug sensitivity and predict the response to a drug. However, the majority of previous work ha

Vlad-Ioan Lupoaie, Ivona-Alexandra Chili, Mihaela Elena Breaban, Madalina Raschip

Multiple-TSP, also abbreviated in the literature as mTSP, is an extension of the Traveling Salesman Problem that lies at the core of many variants of the Vehicle Routing problem of great practical importance. The current paper develops and experiments with Self Organizing Maps, Evolutionary Algorithms and Ant Colony Systems to tackle the MinMax formulation o

Zixiang Xu, Tao Zhang, Gennian Ge

Recently, several hypergraph Tur\'{a}n problems were solved by the powerful random algebraic method. However, the random algebraic method usually requires some parameters to be very large, hence we are concerned about how these Tur\'{a}n numbers depend on such large parameters of the forbidden hypergraphs. In this paper, we determine the dependence on such s

Björn Bebensee

In the past decade analysis of big data has proven to be extremely valuable in many contexts. Local Differential Privacy (LDP) is a state-of-the-art approach which allows statistical computations while protecting each individual user's privacy. Unlike Differential Privacy no trust in a central authority is necessary as noise is added to user inputs locally.

Svanhvít Lilja Ingólfsdóttir, Hrafn Loftsson, Jón Friðrik Daðason, Kristín Bjarnadóttir

Lemmatization, finding the basic morphological form of a word in a corpus, is an important step in many natural language processing tasks when working with morphologically rich languages. We describe and evaluate Nefnir, a new open source lemmatizer for Icelandic. Nefnir uses suffix substitution rules, derived from a large morphological database, to lemmatiz

Ahmad Gazar, Gabriele Nava, Francisco Javier Andrade Chavez, Daniele Pucci

Nonlinear controllers for floating base systems in contact with the environment are often framed as quadratic programming (QP) optimization problems. Common drawbacks of such QP based controllers are: the control input often experiences discontinuities; no force feedback from Force/Torque (FT) sensors installed on the robot is taken into account. This paper

Vasimuddin Md, Sanchit Misra, Heng Li, Srinivas Aluru

Innovations in Next-Generation Sequencing are enabling generation of DNA sequence data at ever faster rates and at very low cost. Large sequencing centers typically employ hundreds of such systems. Such high-throughput and low-cost generation of data underscores the need for commensurate acceleration in downstream computational analysis of the sequencing dat

Frédéric Maffray, Irena Penev, Kristina Vušković

A ring is a graph $R$ whose vertex set can be partitioned into $k \geq 4$ nonempty sets, $X_1, \dots, X_k$, such that for all $i \in \{1,\dots,k\}$, the set $X_i$ can be ordered as $X_i = \{u_i^1, \dots, u_i^{|X_i|}\}$ so that $X_i \subseteq N_R[u_i^{|X_i|}] \subseteq \dots \subseteq N_R[u_i^1] = X_{i-1} \cup X_i \cup X_{i+1}$. A hyperhole is a ring $R$ such

Cheng Qian, Xiao Fu, Nicholas D. Sidiropoulos

This letter revisits the channel estimation problem for MIMO systems with one-bit analog-to-digital converters (ADCs) through a novel algorithm--Amplitude Retrieval (AR). Unlike the state-of-the-art methods such as those based on one-bit compressive sensing, AR takes a different approach. It accounts for the lost amplitudes of the one-bit quantized measureme

Sherif Abdulkader Tawfik

This work introduces a generalization of the form of the spin-orbit interaction, the generalized spin-orbit interaction (GSOI). It expresses the magnetic field induced by two charged particles moving with a non-zero relative velocity as a field defined at all points in space, and exists in the reference frames of both particles. This is in contrast to spin-o

Gennady Eremin

In number theory, we know Legendre's formula $ v_p(n!) = \sum_{k \ge 1} \lfloor \frac{n}{p^k} \rfloor $, which calculates the $p$-adic valuation of the factorial, i.e. the exponent of the greatest power of a prime $p$ that divides $n!$. There is also the second (or alternative) equality $ v_p (n!) = \frac{n-s_p(n)}{p-1} $ where $s_p(n)$ is the $p$-adic weigh

Hendra I. Nurdin

This brief article gives an overview of quantum mechanics as a {\em quantum probability theory}. It begins with a review of the basic operator-algebraic elements that connect probability theory with quantum probability theory. Then quantum stochastic processes is formulated as a generalization of stochastic processes within the framework of quantum probabili

Simon Wiedemann, Heiner Kirchoffer, Stefan Matlage, Paul Haase

The field of video compression has developed some of the most sophisticated and efficient compression algorithms known in the literature, enabling very high compressibility for little loss of information. Whilst some of these techniques are domain specific, many of their underlying principles are universal in that they can be adapted and applied for compress

Cian M. Scannell, Piet van den Bosch, Amedeo Chiribiri, Jack Lee

The quantification of myocardial perfusion MRI has the potential to provide a fast, automated and user-independent assessment of myocardial ischaemia. However, due to the relatively high noise level and low temporal resolution of the acquired data and the complexity of the tracer-kinetic models, the model fitting can yield unreliable parameter estimates. A s

Wen-Chin Huang, Yi-Chiao Wu, Kazuhiro Kobayashi, Yu-Huai Peng

We present a modification to the spectrum differential based direct waveform modification for voice conversion (DIFFVC) so that it can be directly applied as a waveform generation module to voice conversion models. The recently proposed DIFFVC avoids the use of a vocoder, meanwhile preserves rich spectral details hence capable of generating high quality conv

Amareshwara Sainadh Chamarthi, Hiroaki Nishikawa, Kimiya Komurasaki

In this paper, we present a high order finite difference solver for anisotropic diffusion problems based on the first-order hyperbolic system method. In particular, we demonstrate that the construction of a uniformly accurate fifth-order scheme that is independent of the degree of anisotropy is made straightforward by the hyperbolic method with an optimal le

Yizhou Lu, Yungui Gong, Zhu Yi, Fengge Zhang

Primordial black holes and secondary gravitational waves can be used to probe the small scale physics at very early time. For secondary gravitational waves produced after the horizon reentry, we derive an analytical formula for the time integral of the source and analytical behavior of the time dependence of the energy density of induced gravitational waves

Igor Buzhinsky, Valeriy Vyatkin

Model checking is an established technique to formally verify automation systems which are required to be trusted. However, for sufficiently complex systems model checking becomes computationally infeasible. On the other hand, testing, which offers less reliability, often does not present a serious computational challenge. Searching for synergies between the

Javier Villarroel, Juan A. Vega, Miquel Montero

We consider the problem of determining escape probabilities from an interval of a general compound renewal process with drift. This problem is reduced to the solution of a certain integral equation. In an actuarial situation where only negative jumps arise we give a general solution for escape and survival probabilities under Erlang$(n)$ and hypo-exponential

Sabah Al-Fedaghi

Behavior modeling and software architecture specification are attracting more attention in software engineering. Describing both of them in integrated models yields numerous advantages for coping with complexity since the models are platform independent. They can be decomposed to be developed independently by experts of the respective fields, and they are hi

Anupam Singh

This is an exercise based approach to matrix groups. The idea is to collect a bunch of exercises at one place which anyone with basic knowledge of linear algebra can attempt to solve and learn matrix groups and algebraic groups.

Mingtian Zhang, Thomas Bird, Raza Habib, Tianlin Xu

Probabilistic models are often trained by maximum likelihood, which corresponds to minimizing a specific f-divergence between the model and data distribution. In light of recent successes in training Generative Adversarial Networks, alternative non-likelihood training criteria have been proposed. Whilst not necessarily statistically efficient, these alternat

Francesco Catino, Ilaria Colazzo, Paola Stefanelli

We investigate the matched product of solutions associated with right and left shelves. First, we prove that the requirements to provide the matched product of solutions that come from shelves can be simplified. Then we give conditions for left non-degeneracy of the matched product. Later, we compute the structure shelf of the matched product of solutions. F

Tamar Lavee, Matan Orbach, Lili Kotlerman, Yoav Kantor

Engaging in a live debate requires, among other things, the ability to effectively rebut arguments claimed by your opponent. In particular, this requires identifying these arguments. Here, we suggest doing so by automatically mining claims from a corpus of news articles containing billions of sentences, and searching for them in a given speech. This raises t

Zihan Jiang, Wanling Gao, Lei Wang, Xingwang Xiong

In recent years, with the trend of applying deep learning (DL) in high performance scientific computing, the unique characteristics of emerging DL workloads in HPC raise great challenges in designing, implementing HPC AI systems. The community needs a new yard stick for evaluating the future HPC systems. In this paper, we propose HPC AI500 --- a benchmark su

Teresa Munoz-Ecija, Benjamin Vargas-Quesada, Zaida Chinchilla-Rodriguez

Proper field delineation plays an important role in scientometric studies, although it is a tough task. Based on an emerging and interdisciplinary field, nanoscience and nanotechnology, this paper highlights the problem of field delineation. First, we review the related literature. Then, three different approaches to delineate a field of knowledge were appli

Hongxia Zhong, Jin Yu, Kaixiang Huang, Shengjun Yuan

A parameterized tight-binding (TB) model based on the first-principles GW calculations is developed for single layer tin diselenide (SnSe$_2$) and used to study its electronic and optical properties under external magnetic field. The truncated model is derived from six maximally localized wannier orbitals on Se site, which accurately describes the quasi-part

Trung V. Phan, T M Rayhan Gias, Syed Tasnimul Islam, Truong Thu Huong

Software Defined Networking (SDN) enables flexible and scalable network control and management. However, it also introduces new vulnerabilities that can be exploited by attackers. In particular, low-rate and slow or stealthy Denial-of-Service (DoS) attacks are recently attracting attention from researchers because of their detection challenges. In this paper

Saar Beck, Betzalel Bazak, Nir Barnea

The Wigner bound, setting an upper limit on the scattering effective range, is examined at different orders of contact effective field theory. Using cutoff regulator we show that the bound loosens when higher orders of the theory are considered. For a sharp and a Gaussian regulators, we conjecture an analytic formula for the dependence of the Wigner bound on

Kai Qiao, Chi Zhang, Jian Chen, Linyuan Wang

Recently, visual encoding based on functional magnetic resonance imaging (fMRI) have realized many achievements with the rapid development of deep network computation. Visual encoding model is aimed at predicting brain activity in response to presented image stimuli. Currently, visual encoding is accomplished mainly by firstly extracting image features throu

Colin Cotter, Dan Crisan, Darryl D. Holm, Wei Pan

In this work, we combine a stochastic model reduction with a particle filter augmented with tempering and jittering, and apply the combined algorithm to a damped and forced incompressible 2D Euler dynamics defined on a simply connected bounded domain. We show that using the combined algorithm, we are able to assimilate data from a reference system state (the

Taeho Ryu, Julian Krolik, Tsvi Piran, Scott Noble

This is the second in a series of papers presenting the results of fully general relativistic simulations of stellar tidal disruptions in which the stars' initial states are realistic main-sequence models. We consider eight different stellar masses, from $0.15~{\rm M}_\odot$ to $10~{\rm M}_\odot$. In the first paper (Ryu et al. 2019a), we gave an overview of

Luong Trung Nguyen, Junhan Kim, Byonghyo Shim

As a paradigm to recover unknown entries of a matrix from partial observations, low-rank matrix completion (LRMC) has generated a great deal of interest. Over the years, there have been lots of works on this topic but it might not be easy to grasp the essential knowledge from these studies. This is mainly because many of these works are highly theoretical or

Baoluo Sun, Yifan Cui, Eric Tchetgen Tchetgen

Instrumental variable methods have been widely used to identify causal effects in the presence of unmeasured confounding. A key identification condition known as the exclusion restriction states that the instrument cannot have a direct effect on the outcome which is not mediated by the exposure in view. In the health and social sciences, such an assumption i

Satyajit Neogi, Michael Hoy, Kang Dang, Hang Yu

Smooth handling of pedestrian interactions is a key requirement for Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS). Such systems call for early and accurate prediction of a pedestrian's crossing/not-crossing behaviour in front of the vehicle. Existing approaches to pedestrian behaviour prediction make use of pedestrian motion, his/her

Manoj Kumar Lenka, Anubha Pandey, Anurag Mittal

Deblurring is the task of restoring a blurred image to a sharp one, retrieving the information lost due to the blur. In blind deblurring we have no information regarding the blur kernel. As deblurring can be considered as an image to image translation task, deep learning based solutions, including the ones which use GAN (Generative Adversarial Network), have

Aaqib Saeed, Tanir Ozcelebi, Johan Lukkien

Deep learning methods are successfully used in applications pertaining to ubiquitous computing, health, and well-being. Specifically, the area of human activity recognition (HAR) is primarily transformed by the convolutional and recurrent neural networks, thanks to their ability to learn semantic representations from raw input. However, to extract generaliza

Sergey N. Filippov, Kamil Yu. Magadov

We introduce a spin polarization-scaling map for spin-$j$ particles, whose physical meaning is the decrease of spin polarization along three mutually orthogonal axes. We find conditions on three scaling parameters under which the map is positive, completely positive, entanglement breaking, 2-tensor-stable positive, and 2-locally entanglement annihilating. Th

Paolo Leonetti, Carlo Sanna

For every integer $k \geq 2$ and every $A \subseteq \mathbb{N}$, we define the \emph{$k$-directions sets} of $A$ as $D^k(A) := \{{\bf a} / \|{\bf a}\| : {\bf a} \in A^k\}$ and $D^{\underline{k}}(A) := \{{\bf a} / \|{\bf a}\| : {\bf a} \in A^{\underline{k}}\}$, where $\|\cdot\|$ is the Euclidean norm and $A^{\underline{k}} := \{{\bf a} \in A^k : a_i \neq a_j

Robert B. Stone, Gordon T. Richards

This work provides evidence that a large fraction of \ion{C}{IV} narrow absorption lines (NALs) seen along the line of sight to distant quasars are due to accretion disk winds, while also seeking to understand the relationship between NALs and certain quasar-intrinsic properties. We extend the results from past work in the literature using $\sim105,000$ NALs

Amang Song-Kyoo Kim, Chan Yeob Yeun, Paul D. Yoo

This paper is targeted in the area of biometric data enabled security system based on the machine learning for the digital health. The disadvantages of traditional authentication systems include the risks of forgetfulness, loss, and theft. Biometric authentication is therefore rapidly replacing traditional authentication methods and is becoming an everyday p

A. Liashyk

We consider quantum integrable models solvable by the algebraic Bethe ansatz and possessing $\mathfrak{gl}(2)$-invariant $R$-matrix. We study the models of both periodic boundary conditions and boundary conditions based on reflection algebra. We present a new method to calculate the scalar products based on formula of an action of transfer matrix of a model

Alireza Abdollahi, Niloufar Zakeri

The following problem has been proposed in [Research problems from the Aveiro workshop on graph spectra, {\em Linear Algebra and its Applications}, {\bf 423} (2007) 172-181.]:\\ (Problem AWGS.4) Let $G_n$ and $G'_n$ be two nonisomorphic graphs on $n$ vertices with spectra $$\lambda_1 \geq \lambda_2 \geq \cdots \geq \lambda_n \;\;\;\text{and}\;\;\; \lambda'_1

Bo-Yong Chen, Yuanpu Xiong

Let $M$ be a closed complex submanifold in ${\mathbb C}^N$ with the complete K\"ahler metric induced by the Euclidean metric. Several finiteness theorems on the $L^p$ Bergman space of holomorphic sections of a given Hermitian line bundle $L$ over $M$ and the associated $L^2$ cohomology groups are obtained. Some infiniteness theorems are also given in order t

Mohsen Nejad-Asghar

Thermal instability (TI) is a trigger mechanism, which can explain formation of condensations through some regions of the interstellar clouds. Our goal here is to investigate some conditions for occurrence of TI and formation of pre-condensations through the outer half a quasi-static spherical molecular clump or core. The inner half is nearly singular and am

Jungkwon Kim, Yoonjung Lee, Ihyeok Seo

In this paper we study the well-posedness for the inhomogeneous nonlinear Schr\"odinger equation $i\partial_{t}u+\Delta u=\lambda|x|^{-\alpha}|u|^{\beta}u$ in Sobolev spaces $H^s$, $s\geq0$. The well-posedness theory for this model has been intensively studied in recent years, but much less is understood compared to the classical NLS model where $\alpha=0$.

Yubo Ma, Yang Zhang, Ren Zhao, Shuo Cao

In this paper, we investigate the combined effects of the cloud of strings and quintessence on the thermodynamics of a Reissner-Nordstr\"om-de Sitter black hole. Based on the equivalent thermodynamic quantities considering the correlation between the black hole horizon and the cosmological horizon, we extensively discuss the phase transitions of the space-ti

Jianbo Cui, Jialin Hong

In this article, we develop and analyze a full discretization, based on the spatial spectral Galerkin method and the temporal drift implicit Euler scheme, for the stochastic Cahn--Hilliard equation driven by multiplicative space-time white noise. By introducing an appropriate decomposition of the numerical approximation, we first use the factorization method

Hamideh. S Fazael Ardakani, Sajad Daei, Farzan Haddadi

Matrix recovery is the problem of recovering a low-rank matrix from a few linear measurements. Recently, this problem has gained a lot of attention as it is employed in many applications such as Netflix prize problem, seismic data interpolation and collaborative filtering. In these applications, one might access to additional prior information about the colu

Jiahui Zhu, Zdzisław Brzeźniak, Wei Liu

We present remarkably simple proofs of Burkholder-Davis-Gundy inequalities for stochastic integrals and maximal inequalities for stochastic convolutions in Banach spaces driven by L\'{e}vy-type processes. Exponential estimates for stochastic convolutions are obtained and two versions of It\^{o}'s formula in Banach spaces are also derived. Based on the obtain

Wenyuan Ma, Wei Wang, Tao Jiang

Wirelessly powered backscatter communication (WPBC) has been identified as a promising technology for low-power communication systems, which can reap the benefits of energy beamforming to improve energy transfer efficiency. Existing studies on energy beamforming fail to simultaneously take energy supply and information transfer in WPBC into account. This pap

Jiahui Zhu, Zdzisław Brzeźniak, Wei Liu

We study the existence and uniqueness of solutions of 2D Stochastic Navier-Stokes equation with space irregular jump noise for initial data in certain Sobolev spaces of negative order. Comparing with the Galerkin approximation method, the main advantage of this work is to use an $\mathbb{L}^p$-setting to obtain the solution under much weaker assumptions on t

Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro

We introduce a new, rigorously-formulated Bayesian meta-learning algorithm that learns a probability distribution of model parameter prior for few-shot learning. The proposed algorithm employs a gradient-based variational inference to infer the posterior of model parameters to a new task. Our algorithm can be applied to any model architecture and can be impl

Cory A. Krause

In the study of asymptotic geometry in Banach spaces, a basic sequence which gives rise to a spreading model has been called a good sequence. It is well known that every normalized basic sequence in a Banach space has a subsequence which is good. We investigate the assumption that every normalized block tree relative to a basis has a branch which is good. Th

San-Jiang Yang, Yong-Bo Tang, Yong-Hua Zhao, Ting-Yun Shi

In this work, we report an application of Hylleraas-$B$-spline basis set to the nonrelativistic Bethe logarithm calculation of helium. The Bethe logarithm for $n\ ^1S$, $n$ up to 10, states of helium are calculated with a precision of 7-9 significant digits in two gauges, which greatly improves the accuracy of the traditional $B$-spline basis set. In additio

Richard Du, Peng Cao, Lujun Han, Qiyong Ai

Nasopharyngeal Carcinoma (NPC) is endemic cancer in the south-east Asia. With the advent of intensity-modulated radiotherapy excellent locoregional control are being achieved. Consequently, this had led to pretreatment clinical staging classification to be less prognostic of outcomes such as recurrence after treatment. Alternative pretreatment strategies for

Mickael Tardy, Bruno Scheffer, Diana Mateus

This work focuses on the automatic quantification of the breast density from digital mammography imaging. Using only categorical image-wise labels we train a model capable of predicting continuous density percentage as well as providing a pixel wise support frit for the dense region. In particular we propose a weakly supervised loss linking the density perce

Tamara Grava, Alexader Minakov

We study the long time asymptotic behaviour of the solution $q(x,t) $, to the modified Korteweg de Vries equation (MKDV) $q_t+6q^2q_x+q_{xxx}=0$ with step-like initial datum q(x,t=0)->c_- for x->-infinity and q(x,t=0)->c_+ for x-> +infinity. For the exact shock initial data q(x,t=0)=c_- for x<0 and q(x,t=0)=c_+ for x>0 the solution develops an oscillatory re

Ruoqin Yan, Tao Wang, Xiaoyun Jiang, Qingfang Zhong

The use of relatively simple structures to achieve high performance refractive index sensors has always been urgently needed. In this work, we propose a lithography-free sensing platform based on metal-dielectric cavity, the sensitivity of our device can reach 1456700 nm/RIU for solution and 1596700 nm/RIU for solid material, and the FOM can be up to 1234500

Yi Zhang, Cheng Zeng, Hao Cheng, Chongjun Wang

With the emergence of diverse data collection techniques, objects in real applications can be represented as multi-modal features. What's more, objects may have multiple semantic meanings. Multi-modal and Multi-label (MMML) problem becomes a universal phenomenon. The quality of data collected from different channels are inconsistent and some of them may not

Chun-Hung Chen, Hing-Tong Cho, Alan S. Cornell, Gerhard E. Harmsen

In this work we consider spin-3/2 fields in Schwarzschild (A)dS black hole spacetimes. As this spacetime is different from the Ricci-flat cases, it is necessary to modify the covariant derivative to the supercovariant derivative in order to maintain the gauge symmetry, as noted in our earlier works, where this is done here by including terms related to the c

Hiroki Oshima

Submodularity is one of the most important properties in combinatorial optimization, and $k$-submodularity is a generalization of submodularity. Maximization of a $k$-submodular function requires an exponential number of value oracle queries, and approximation algorithms have been studied. For unconstrained $k$-submodular maximization, Iwata et al. gave rand

Oscar Correa, Jeffrey Chan, Vinh Nguyen

Many approaches have been proposed to discover clusters within networks. Community finding field encompasses approaches which try to discover clusters where nodes are tightly related within them but loosely related with nodes of other clusters. However, a community network configuration is not the only possible latent structure in a graph. Core-periphery and

Wentao Hu

To find a trade-off between profitability and prudence, financial practitioners need to choose appropriate risk measures. Two key points are: Firstly, investors' risk attitudes under uncertainty conditions should be an important reference for risk measures. Secondly, risk attitudes are not absolute. For different market performance, investors have different

Byungsoo Ko, Minchul Shin, Geonmo Gu, HeeJae Jun

Many studies have been performed on metric learning, which has become a key ingredient in top-performing methods of instance-level image retrieval. Meanwhile, less attention has been paid to pre-processing and post-processing tricks that can significantly boost performance. Furthermore, we found that most previous studies used small scale datasets to simplif

Panchi Li, Changjian Xie, Rui Du, Jingrun Chen

In this paper, we present two improved Gauss-Seidel projection methods with unconditional stability. The first method updates the gyromagnetic term and the damping term simultaneously and follows by a projection step. The second method introduces two sets of approximate solutions, where we update the gyromagnetic term and the damping term simultaneously for

Hyeontae Jo, Hwijae Son, Hyung Ju Hwang, Eunheui Kim

In this paper, we construct approximated solutions of Differential Equations (DEs) using the Deep Neural Network (DNN). Furthermore, we present an architecture that includes the process of finding model parameters through experimental data, the inverse problem. That is, we provide a unified framework of DNN architecture that approximates an analytic solution

Li Ma, Weidong Bao, Xiaomin Zhu, Meng Wu

Flocking model has been widely used to control robotic swarm. However, with the increasing scalability, there exist complex conflicts for robotic swarm in autonomous navigation, brought by internal pattern maintenance, external environment changes, and target area orientation, which results in poor stability and adaptability. Hence, optimizing the flocking m

Thotsaporn "Aek'' Thanatipanonda

We give an excellent approximation of the average number of spins of a simplified version of a two-player version of the game Dreidel. We also make a conjecture on the average number of spins of the full version of the game.

Daniel W. Meyer, Artur Gomolinski

This work is concerned with the intricate interplay between node or pore pressures and connection or throat conductivities in flow or pore networks. A setting similar to pore networks is given by fracture networks. Recently, a non-local generalization of Darcy's law for flow and transport in porous media was presented in the context of unbounded or periodic

Hunter Park, Connor Monahan

Convolutional neural networks (CNNs) have shown great promise in improving computer aided detection (CADe). From classifying tumors found via mammography as benign or malignant to automated detection of colorectal polyps in CT colonography, these advances have helped reduce the need for further evaluation with invasive testing and prevent errors from missed

Jianlei Zhang, Binil Starly

Data-driven approaches to automated machine condition monitoring are gaining popularity due to advancements made in sensing technologies and computing algorithms. This paper proposes the use of a deep learning model, based on Long Short-Term Memory (LSTM) architecture for a recurrent neural network (RNN) which captures long term dependencies for modeling seq

Zhongwu Li, Yinghua Qiu, Yan Zhang, Min Yue

Ion transport in highly-confined space is important to various applications, such as biosensing and seawater desalination with nanopores. All-atom molecular dynamics simulations are conducted to investigate the transport of Na$^+$ and Cl$^-$ ions through nanopores with the diameter below 6 nm. It is found that the formation of the contact ion pair plays a cr

Adam Coogan, Logan Morrison, Stefano Profumo

With several proposed MeV gamma-ray telescopes on the horizon, it is of paramount importance to perform accurate calculations of gamma-ray spectra expected from sub-GeV dark matter annihilation and decay. We present hazma, a python package for reliably computing these spectra, determining the resulting constraints from existing gamma-ray data, and prospects

Bo Ji, Tianyi Chen

Generative adversarial networks (GANs) have proven hugely successful in variety of applications of image processing. However, generative adversarial networks for handwriting is relatively rare somehow because of difficulty of handling sequential handwriting data by Convolutional Neural Network (CNN). In this paper, we propose a handwriting generative adversa