October 2020 arXiv papers — page 124

Hao Zhu, Liping Liu, Soha Hassoun

Detecting and quantifying products of cellular metabolism using Mass Spectrometry (MS) has already shown great promise in many biological and biomedical applications. The biggest challenge in metabolomics is annotation, where measured spectra are assigned chemical identities. Despite advances, current methods provide limited annotation for measured spectra.

Reed Milewicz, James Willenbring, Dena Vigil

At Sandia National Laboratories, the Software Engineering and Research Department seeks to provide sustainable career pathways for research software engineers (RSEs). The conceptual model for our organization follows what we call a Research, Develop, and Deploy (RDD) workflow pattern, enabling RSEs to partner with research and deployment specialists. We argu

Shibin Dai, Qiang Liu, Toai Luong, Keith Promislow

The Functionalized Cahn-Hilliard equation has been proposed as a model for the interfacial energy of phase-separated mixtures of amphiphilic molecules. We study the existence of a nonnegative weak solutions of a gradient flow of the Functionalized Cahn-Hilliard equation subject to a degenerate mobility M(u) that is zero for u<=0. Assuming the initial data u0

Wouter Mortelmans, Stefan De Gendt, Marc Heyns, Clement Merckling

The application of new materials in nanotechnology opens new perspectives and enables ground-breaking innovations. Two-dimensional van der Waals materials and more specific, 2D chalcogenides are a promising class of new materials awaiting their usage in the semiconductor industry. However, the integration of van der Waals materials relying on industry-compat

C. G. De Pree, D. J. Wilner, L. E. Kristensen, R. Galván-Madrid

We present new Jansky Very Large Array (VLA) images of the central region of the W49A star-forming region at 3.6~cm and at 7~mm at resolutions of 0\farcs15 (1650 au) and 0\farcs04 (440 au), respectively. The 3.6~cm data reveal new morphological detail in the ultracompact \ion{H}{2} region population, as well as several previously unknown and unresolved sourc

Mary Ellen Foster, Ronald P. A. Petrick

This paper describes a new research project that aims to develop a social robot designed to help children cope with painful and distressing medical procedures in a clinical setting. While robots have previously been trialled for this task, with promising initial results, the systems have tended to be teleoperated, limiting their flexibility and robustness. T

Anabel del Val, Olivier P. Le Maître, Olivier Chazot, Thierry E. Magin

This work deals with the inference of catalytic recombination parameters from plasma wind tunnel experiments for reusable thermal protection materials. One of the critical factors affecting the performance of such materials is the contribution to the heat flux of the exothermic recombination reactions at the vehicle surface. The main objective of this work i

Emmanuel Thomas, Emmanouil Potetsianakis, Thomas Stockhammer, Imed Bouazizi

With the advent of immersive media applications, the requirements for the representation and the consumption of such content has dramatically increased. The ever-increasing size of the media asset combined with the stringent motion-to-photon latency requirement makes the equation of a high quality of experience for XR streaming services difficult to solve. T

K. D. Danov, P. A. Kralchevsky, R. D. Stanimirova, S. D. Stoyanov

Hypotheses: The aggregation number and length of spherocylindrical (rodlike, wormlike) micelles in solutions of an ionic surfactant and salt can be predicted knowing the molecular parameters and the input concentrations of the species. This can be achieved by upgrading the quantitative molecular thermodynamic model from the previous parts of this series with

Thomas Chaton, Nicolas Chaulet, Sofiane Horache, Loic Landrieu

We introduce Torch-Points3D, an open-source framework designed to facilitate the use of deep networks on3D data. Its modular design, efficient implementation, and user-friendly interfaces make it a relevant tool for research and productization alike. Beyond multiple quality-of-life features, our goal is to standardize a higher level of transparency and repro

Zuchao Li, Hai Zhao, Rui Wang, Kevin Parnow

Semantic role labeling is primarily used to identify predicates, arguments, and their semantic relationships. Due to the limitations of modeling methods and the conditions of pre-identified predicates, previous work has focused on the relationships between predicates and arguments and the correlations between arguments at most, while the correlations between

Ahsan Noor, Anoop R. Damodaran, In-Ho Lee, Stefan A. Maier

Plasmonic enhancement of nonlinear optical processes confront severe limitations arising from the strong dispersion of metal susceptibilities and small interaction volumes that hamper desirable phase-matching-like conditions. Maximizing nonlinear interactions in nanoscale systems require simultaneous excitation of resonant modes that spatially and constructi

Michael S. Ferguson, Leon C. Camenzind, Clemens Müller, Daniel E. F. Biesinger

The current revolution in quantum technologies relies on the ability to isolate, coherently control, and measure the state of quantum systems. The act of measurement in quantum mechanics, however, is naturally invasive as the measurement apparatus becomes entangled with the system that it observes. Even for ideal detectors, the measurement outcome always lea

Vibhu Bhatia, Yatender Kumar

In the last few years, several deep learning models, especially Generative Adversarial Networks have received a lot of attention for the task of Single Image Super-Resolution (SISR). These methods focus on building an end-to-end framework, which produce a high resolution(SR) image from a given low resolution(LR) image in a single step to achieve state-of-the

Jin Lan, Jiang Xiao

Spin wave and magnetic texture are two elementary excitations in magnetic systems, and their interaction leads to rich magnetic phenomena. By describing the spin wave and the magnetic texture using their own collective coordinates, we find that they interact as classical particles traveling in mutual electromagnetic fields. Based on this unified collective c

Libor Barto, Diego Battistelli, Kevin M. Berg

The Promise Constraint Satisfaction Problem (PCSP) is a recently introduced vast generalization of the Constraint Satisfaction Problem (CSP). We investigate the computational complexity of a class of PCSPs beyond the most studied cases - approximation variants of satisfiability and graph coloring problems. We give an almost complete classification for the cl

Fengping Jin, Dennis Willsch, Madita Willsch, Hannes Lagemann

We review and extend, in a self-contained way, the mathematical foundations of numerical simulation methods that are based on the use of random states. The power and versatility of this simulation technology is illustrated by calculations of physically relevant properties such as the density of states of large single particle systems, the specific heat, curr

Maryam Amyari, Marzieh Moradian Khibary

We introduce the notion of approximate numerical radius (Birkhoff) orthogonality and investigate its significant properties. Let $T, S\in \mathbb{B}(\mathscr{H})$ and $\varepsilon \in [0, 1)$. We say that $T$ is approximate numerical radius orthogonal to $S$ and we write $T\perp^{\varepsilon}_ω S$ if $$ω^2(T+λS)\geq ω^2(T)-2\varepsilon ω(T) ω(λS)\,\,\, \text

Mario Lezcano-Casado

Adaptive methods do not have a direct generalization to manifolds as the adaptive term is not invariant. Momentum methods on manifolds suffer from efficiency problems stemming from the curvature of the manifold. We introduce a framework to generalize adaptive and momentum methods to arbitrary manifolds by noting that for every differentiable manifold, there

John Holmes, Feride Tiglay, Ryan Thompson

For Besov spaces $B^s_{p,r}(\rr)$ with $s>\max\{ 2 + \frac1p , \frac52\} $, $p \in (1,\infty]$ and $r \in [1 , \infty)$, it is proved that the data-to-solution map for the FORQ equation is not uniformly continuous from $B^s_{p,r}(\rr)$ to $C([0,T]; B^s_{p,r}(\rr))$. The proof of non-uniform dependence is based on approximate solutions and the Littlewood-Pale

Min Zhao, Tiande Gao, Jie Chen, Wei Chen

Nowadays, nonnegative matrix factorization (NMF) based methods have been widely applied to blind spectral unmixing. Introducing proper regularizers to NMF is crucial for mathematically constraining the solutions and physically exploiting spectral and spatial properties of images. Generally, properly handcrafting regularizers and solving the associated comple

Guohou Shan, James Foulds, Shimei Pan

Text features that are correlated with class labels, but do not directly cause them, are sometimesuseful for prediction, but they may not be insightful. As an alternative to traditional correlation-basedfeature selection, causal inference could reveal more principled, meaningful relationships betweentext features and labels. To help researchers gain insight

Gonçalo Mordido, Christoph Meinel

We propose a family of metrics to assess language generation derived from population estimation methods widely used in ecology. More specifically, we use mark-recapture and maximum-likelihood methods that have been applied over the past several decades to estimate the size of closed populations in the wild. We propose three novel metrics: ME$_\text{Petersen}

Ibrahim Gullu, S. Habib Mazharimousavi

The electric and magnetic black hole solutions are found by coupling the recently introduced nonlinear electrodynamics (NED) model, called &#34;double logharitmic nonlinear electrodynamics&#34; with cosmological Einstein gravity. The solutions become Reissner-Nordstrom (RN) black hole in the weak field limit and asymptotically. The electric solution is expre

Tom Weber, Stefan Wermter

Explainable artificial intelligence (XAI) can help foster trust in and acceptance of intelligent and autonomous systems. Moreover, understanding the motivation for an agent&#39;s behavior results in better and more successful collaborations between robots and humans. However, not only can humans benefit from a robot&#39;s explanation but the robot itself can

S Ganga Prasath, Joel Marthelot, Narayanan Menon, Rama Govindarajan

We study the wetting of a thin elastic filament floating on a fluid surface by a droplet of another, immiscible fluid. This quasi-2D experimental system is the lower-dimensional counterpart of the wetting and wrapping of a droplet by an elastic sheet. The simplicity of this system allows us to study the phenomenology of partial wetting and wrapping of the dr

Tong Ma, David Alonso Barajas-Solano, Ramakrishna Tipireddy, Alexandre M. Tartakovsky

Real-time state estimation and forecasting is critical for efficient operation of power grids. In this paper, a physics-informed Gaussian process regression (PhI-GPR) method is presented and used for probabilistic forecasting and estimating the phase angle, angular speed, and wind mechanical power of a three-generator power grid system using sparse measureme

Max Karoubi

The purpose of this short paper is to investigate relations between various real K-theories. In particular, we show how a real projective bundle theorem implies an unexpected relation between Atiyah&#39;s KR-theory and the usual equivariant K-theory of real vector bundles. This relation has been used recently in a new computation of the Witt group of real cu

Xinyu Dong, Jianyuan Deng, Sina Rashidian, Kayley Abell-Hart

The United States is experiencing an opioid epidemic, and there were more than 10 million opioid misusers aged 12 or older each year. Identifying patients at high risk of Opioid Use Disorder (OUD) can help to make early clinical interventions to reduce the risk of OUD. Our goal is to predict OUD patients among opioid prescription users through analyzing elec

Emeline Bolmont, Sylvain N. Breton, Gabriel Tobie, Caroline Dumoulin

With the discovery of TRAPPIST-1 and its seven planets within 0.06 au, the correct treatment of tidal interactions is becoming necessary. The eccentricity, rotation, and obliquity of the planets of TRAPPIST-1 are indeed the result of tidal evolution over the lifetime of the system. Tidal interactions can also lead to tidal heating in the interior of the plan

Shilpa Mayannavar, Uday Wali, V M Aparanji

The paper presents Multi-layer Auto Resonance Networks (ARN), a new neural model, for image recognition. Neurons in ARN, called Nodes, latch on to an incoming pattern and resonate when the input is within its &#39;coverage.&#39; Resonance allows the neuron to be noise tolerant and tunable. Coverage of nodes gives them an ability to approximate the incoming p

K. P. Khemchandani, A. Martinez Torres, H. Nagahiro, A. Hosaka

The nature of nucleon resonances is still being debated, while much experimental data are accumulated. In this work, we focus on the negative parity resonance $N^*(1895)$ which is located in the scattering region of various meson-baryon coupled channels, and such dynamics can be crucial in understanding its properties. To test the relevance of such hadron dy

Wendi Ren, Yinghao Li, Hanting Su, David Kartchner

We study the problem of learning neural text classifiers without using any labeled data, but only easy-to-provide rules as multiple weak supervision sources. This problem is challenging because rule-induced weak labels are often noisy and incomplete. To address these two challenges, we design a label denoiser, which estimates the source reliability using a c

Sang Xie, Jian Liu, Xiugui Liu

In this paper, we show that for finite $CW$-complexes $X$ and two-stage space $Y$ (for example $n$-spheres $S^n$, homogeneous spaces and $F_0$-spaces), the rational homotopy type of $\map(X, Y)$ is determined by the cohomology algebra $H^*(X; \Q)$ and the rational homotopy type of $Y$. From this, we deduce the existence of H-structures on a component of the

Hsin-Yu Chen, Cheng-Te Li

In the computational detection of cyberbullying, existing work largely focused on building generic classifiers that rely exclusively on text analysis of social media sessions. Despite their empirical success, we argue that a critical missing piece is the model explainability, i.e., why a particular piece of media session is detected as cyberbullying. In this

Emmanuel P. Agbo, Chris M. Ekpo, Collins O. Edet

Trend analysis of meteorological parameters (temperature, pressure, and relative humidity) as well as calculated refractivity, equivalent potential temperature (EPT) for a pseudo-adiabatic process, and field strength in Calabar, Southern Nigeria has been analyzed using Mann-Kendall trend test and Sens slope estimator. Data of the meteorological parameters we

Tom Britton, Pieter Trapman, Frank Ball

The COVID-19 pandemic has hit different parts of the world differently: some regions are still in the rise of the first wave, other regions are now facing a decline after a first wave, and yet other regions have started to see a second wave. The current immunity level $\hat i$ in a region is closely related to the cumulative fraction infected, which primaril

Anastasia Bolotnikova, Pierre Gergondet, Arnaud Tanguy, Sébastien Courtois

We present an open-source software interface, called mc_naoqi, that allows to perform whole-body task-space Quadratic Programming based control, implemented in mc_rtc framework, on the SoftBank Robotics Europe humanoid robots. We describe the control interface, associated robot description packages, robot modules and sample whole-body controllers. We demonst

Jiani Fei, Chia-Nan Yeh, Emanuel Gull

Simulations of finite temperature quantum systems provide imaginary frequency Green&#39;s functions that correspond one-to-one to experimentally measurable real-frequency spectral functions. However, due to the bad conditioning of the continuation transform from imaginary to real frequencies, established methods tend to either wash out spectral features at h

Jinsong Yang, Cong Zhang, Yongge Ma

The scheme of using the Chern-Simons action to regularize the gravitational Hamiltonian constraint is extended to including the Lorentzian term in the $k=0$ cosmological model. The Euclidean term and the Lorenzian term are thus regularized separately mimicking the treatment of full loop quantum gravity. The new quantum dynamics for the spatially flat Friedma

Daniel Hernández García, Yanchao Yu, Weronika Sieińska, Jose L. Part

In this paper, we propose a minimum set of concepts and signals needed to track the social state during Human-Robot Interaction. We look into the problem of complex continuous interactions in a social context with multiple humans and robots, and discuss the creation of an explainable and tractable representation/model of their social interaction. We discuss

Henry Bosch, Tyler Gonzales, Kamryn Spinelli, Gabe Udell

We compute the leading coefficient in the asymptotic expansion of the eigenvalue counting function for the Kohn Laplacian on the spheres. We express the coefficient as an infinite sum and as an integral.

Hayate Okuhara, Ahmed Elnaqib, Davide Rossi, Alfio Di Mauro

As the Internet-of-Things (IoT) applications become more and more pervasive, IoT end nodes are requiring more and more computational power within a few mW of power envelope, coupled with high-speed and energy-efficient inter-chip communication to deal with the growing input/output and memory bandwidth for emerging near-sensor analytics applications. While tr

Sachin Raja, Ajoy Mondal, C. V. Jawahar

Tables are information-rich structured objects in document images. While significant work has been done in localizing tables as graphic objects in document images, only limited attempts exist on table structure recognition. Most existing literature on structure recognition depends on extraction of meta-features from the PDF document or on the optical charact

Sweta Kumari, Amlan Dutta

Deformation twinning, which occurs in fcc metals only under particular conditions of intrinsic material properties, microstructure, and loading conditions, occupies an indispensable place in their deformation mechanism maps. Nonetheless, dedicated studies have seldom been carried out to explore the fundamental properties of twinning dislocations mediating th

Daniel M. A. Silva, Rute C. Sofia

This paper debates on notions of context-awareness as a relevant asset of networking and computing architectures for an Internet of Things (IoT), in particular in regards to a smoother support of the the networking operation between Cloud and Edge. Specifically, the paper debates on notions of context-awareness and goes over different types of context-awaren

Danny Lathouwers, Zoltan Perko

In a previous paper (Lathouwers and Perkó, 2019) we have developed an efficient angular multigrid preconditioner for the Boltzmann transport equation with forward-peaked scatter modeled by the Fokker-Planck approximation. The discretization was based on a completely discontinuous Galerkin finite element scheme both for space and angle. The scheme was found t

Devanshu Arya, Deepak K. Gupta, Stevan Rudinac, Marcel Worring

Graphs are the most ubiquitous form of structured data representation used in machine learning. They model, however, only pairwise relations between nodes and are not designed for encoding the higher-order relations found in many real-world datasets. To model such complex relations, hypergraphs have proven to be a natural representation. Learning the node re

Alan Savushkin, Nikita Benkovich, Dmitry Golubev

In this paper, we propose a novel approach for implicit data representation to evaluate similarity of input data using a trained neural network. In contrast to the previous approach, which uses gradients for representation, we utilize only the outputs from the last hidden layer of a neural network and do not use a backward step. The proposed technique explic

Yucheng Lin, Huiting Hong, Xiaoqing Yang, Xiaodi Yang

Graph neural networks have become an important tool for modeling structured data. In many real-world systems, intricate hidden information may exist, e.g., heterogeneity in nodes/edges, static node/edge attributes, and spatiotemporal node/edge features. However, most existing methods only take part of the information into consideration. In this paper, we pre

Artur Frankiewicz, Adam Glos, Krzysztof Grochla, Zbigniew Łaskarzewski

The LP WAN networks use gateways or base stations to communicate with devices distributed on large distances, up to tens of kilometres. The selection of optimal gateway locations in wireless networks should allow providing the complete coverage for a given set of nodes, taking into account the limitations, such as the number of nodes served per access point

Jialin Liu, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi

Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based methods have been applied to various content types such as levels, maps, character models, and textures. A research field centered on content generation in games has existed for more

Yu Zhou, Zhengshuo Li

This paper suggests leveraging reactive power potential (RPP) embedded in wind farms to improve power system operational safety and optimality. First, three typical RPP provision approaches are analyzed and a two-stage robust linear optimization based RPP evaluation method is proposed. This approach yields an RPP range that ensures the security of wind farm

Jaume Meseguer-Sanchez, Dina Abdul Wahab, Hubertus Luetkens, Grigol Taniashvili

Magnetic phase transitions often occur spontaneously at specific critical temperatures. The presence of more than one critical temperature (Tc) has been observed in several compounds where the coexistence of competing magnetic orders highlights the importance of phase separation driven by different factors such as pressure, temperature and chemical compositi

João A. Leite, Diego F. Silva, Kalina Bontcheva, Carolina Scarton

Hate speech and toxic comments are a common concern of social media platform users. Although these comments are, fortunately, the minority in these platforms, they are still capable of causing harm. Therefore, identifying these comments is an important task for studying and preventing the proliferation of toxicity in social media. Previous work in automatica

F. M. Abdelmalek, Esther Vander Meulen, Kevin N. Vander Meulen, Adam Van Tuyl

The $k$-token graph $T_k(G)$ is the graph whose vertices are the $k$-subsets of vertices of a graph $G$, with two vertices of $T_k(G)$ adjacent if their symmetric difference is an edge of $G$. We explore when $T_k(G)$ is a well-covered graph, that is, when all of its maximal independent sets have the same cardinality. For bipartite graphs $G$, we classify wh

Antoine Legat, Julien M. Hendrickx

This work focuses on the identifiability of dynamical networks with partial excitation and measurement: a set of nodes are interconnected by unknown transfer functions according to a known topology, some nodes are subject to external excitation, and some nodes are measured. The goal is to determine which transfer functions in the network can be recovered bas

Xingyu Zhao, Tian Lin, Yu Zhu, Jun Zhang

Hybrid beamforming (HBF) is an attractive technology for practical massive multiple-input and multiple-output (MIMO) millimeter wave (mmWave) systems. Compared with the fully-connected HBF architecture, the partially-connected one can further reduce the hardware cost and power consumption. However, the special block diagonal structure of its analog beamformi

Zhou Fang, Ying Jin, Tianren Yang

Deep learning applications in shaping ad hoc planning proposals are limited by the difficulty in integrating professional knowledge about cities with artificial intelligence. We propose a novel, complementary use of deep neural networks and planning guidance to automate street network generation that can be context-aware, example-based and user-guided. The m

Frederik Hahn, Jarn de Jong, Anna Pappa

Conference Key Agreement (CKA) is a cryptographic effort of multiple parties to establish a shared secret key. In future quantum networks, generating secret keys in an anonymous way is of tremendous importance for parties that want to keep their shared key secret and at the same time protect their own identity. We provide a definition of anonymity for genera

Carolina Scarton, Diego F. Silva, Kalina Bontcheva

Stance classification can be a powerful tool for understanding whether and which users believe in online rumours. The task aims to automatically predict the stance of replies towards a given rumour, namely support, deny, question, or comment. Numerous methods have been proposed and their performance compared in the RumourEval shared tasks in 2017 and 2019. R

Martin Schmidhammer, Christian Gentner, Stephan Sand, Uwe-Carsten Fiebig

State-of-the-art device-free localization systems infer presence and location of users based on received signal strength measurements of line-of-sight links in wireless networks. In this letter, we propose to enhance device-free localization systems by exploiting multipath propagation between the individual network nodes. Particularly indoors, wireless propa

Concettina Guerra, Pietro Hiram Guzzi

Aligning protein interaction networks (PPI) of two or more organisms consists of finding a mapping of the nodes (proteins) of the networks that captures important structural and functional associations (similarity). It is a well studied but difficult problem. It is provably NP-hard in some instances thus computationally very demanding. The problem comes in s

Dandan Huang, Leyang Cui, Sen Yang, Guangsheng Bao

Deep learning has led to significant improvement in text summarization with various methods investigated and improved ROUGE scores reported over the years. However, gaps still exist between summaries produced by automatic summarizers and human professionals. Aiming to gain more understanding of summarization systems with respect to their strengths and limits

Brian C. Sawyer, Kenton R. Brown

We propose an optical scheme for generating entanglement between co-trapped identical or dissimilar alkaline earth atomic ions ($^{40}\text{Ca}^+$, $^{88}\text{Sr}^+$, $^{138}\text{Ba}^+$, $^{226}\text{Ra}^+$) which exhibits fundamental error rates below $10^{-4}$ and can be implemented with a broad range of laser wavelengths spanning from ultraviolet to inf

Loris Arnold

In this article we study bounded operators $T$ on Banach space $X$ which satisfy the discrete Gomilko Shi-Feng condition $$\int_{0}^{2π}|\langle R(re^{it},T)^{2}x,x^*\rangle |dt \leq \frac{C}{(r^2-1)}\norme{x}\norme{x^*},\quad r>1, x\in X, x^* \in X^*. $$ We show that it is equivalent to a certain derivative bounded functional calculus and also to a bounded

Mathias Sonnleitner, Friedrich Pillichshammer

This paper is a follow-up to the recent paper &#34;A note on isotropic discrepancy and spectral test of lattice point sets&#34; [J. Complexity, 58:101441, 2020]. We show that the isotropic discrepancy of a lattice point set is at most $d \, 2^{2(d+1)}$ times its spectral test, thereby correcting the dependence on the dimension $d$ and an inaccuracy in the pr

Xuefeng Bai, Linfeng Song, Yue Zhang

AMR-to-text generation aims to recover a text containing the same meaning as an input AMR graph. Current research develops increasingly powerful graph encoders to better represent AMR graphs, with decoders based on standard language modeling being used to generate outputs. We propose a decoder that back predicts projected AMR graphs on the target sentence du

Rohith Pudari, Sunil Bhutada, Sai Pavan Mudavath

Face Recognition is one of the process of identifying people using their face, it has various applications like authentication systems, surveillance systems and law enforcement. Convolutional Neural Networks are proved to be best for facial recognition. Detecting faces using core-ml api and processing the extracted face through a coreML model, which is train

Mahdi Ghorbani, Fahimeh Fooladgar, Shohreh Kasaei

Deep neural network architectures have attained remarkable improvements in scene understanding tasks. Utilizing an efficient model is one of the most important constraints for limited-resource devices. Recently, several compression methods have been proposed to diminish the heavy computational burden and memory consumption. Among them, the pruning and quanti

Raanju R. Sundararajan

Dimension reduction techniques for multivariate time series decompose the observed series into a few useful independent/orthogonal univariate components. We develop a spectral domain method for multivariate second-order stationary time series that linearly transforms the observed series into several groups of lower-dimensional multivariate subseries. These m

Weihao Xia, Yujiu Yang, Jing-Hao Xue, Wensen Feng

In this work, we present interpGaze, a novel framework for controllable gaze redirection that achieves both precise redirection and continuous interpolation. Given two gaze images with different attributes, our goal is to redirect the eye gaze of one person into any gaze direction depicted in the reference image or to generate continuous intermediate results

Namid Stillman, Igor Balazs, Sabine Hauert

We present an extension to active learning routines in which non-constant costs are explicitly considered. This work considers both known and unknown costs and introduces the term ε-frugal for learners that do not only consider minimizing total costs but are also able to explore high cost regions of the sample space. We demonstrate our extension on a well-kn

Nataša Petrović, Gabriel Moyà-Alcover, Antoni Jaume-i-Capó, Manuel González-Hidalgo

In this work we propose an approach to select the classification method and features, based on the state-of-the-art, with best performance for diagnostic support through peripheral blood smear images of red blood cells. In our case we used samples of patients with sickle-cell disease which can be generalized for other study cases. To trust the behavior of th

Haochen Tian, Fei Meng, Baike Lin, Shiying Cao

In this letter, we derive a fully-stabilized narrow-linewidth optical frequency comb (OFC) reference to a kilometer-long fiber delay line for the first time, to the best of our knowledge. The 1537-nm comb modes and 1566-nm comb modes in the OFC are phase-locked to the fiber delay line with 40-kHz locking bandwidth. From out-of-loop measurement, the 1542-nm c

Shailesh Kalal, Sanjay Nayak, Akhil Tayal, Jens Birch

Rock-salt type niobium nitride ($δ$-NbN) is a well-known superconductor having superconducting transition temperature (Tc) $\approx$ 18\,K and a large superconducting gap $\approx$3\,meV. The Tc of $δ$-NbN thin film exhibits a large scattering irrespective of the growth conditions and lattice parameter. In this work, we investigate the atomic origin of suppr

Seng Huat Ong, Subrata Chakraborty, Aniket Biswas

The skewing mechanism of Azzalini for continuous distributions is used for the first time to derive a new generalization of the geometric distribution. Various structural properties of the proposed distribution are investigated. Characterizations, including a new result for the geometric distribution, in terms of the proposed model are established. Extensive

Shichao Hu, Bin Zhang, Beici Liang, Ethan Zhao

Audio super-resolution is a challenging task of recovering the missing high-resolution features from a low-resolution signal. To address this, generative adversarial networks (GAN) have been used to achieve promising results by training the mappings between magnitudes of the low and high-frequency components. However, phase information is not well-considered

Aviv Gibali, Shoham Sabach, Sergey Voldman

In this paper, we propose a catalog of iterative methods for solving the Split Feasibility Problem in the non-convex setting. We study four different optimization formulations of the problem, where each model has advantageous in different settings of the problem. For each model, we study relevant iterative algorithms, some of which are well-known in this are

Ye Zheng, Ruoran Huang, Chuanqi Han, Xi Huang

Zero-shot detection (ZSD) is crucial to large-scale object detection with the aim of simultaneously localizing and recognizing unseen objects. There remain several challenges for ZSD, including reducing the ambiguity between background and unseen objects as well as improving the alignment between visual and semantic concept. In this work, we propose a novel

Jens Weise, Sanaz Mostaghim

Route planning also known as pathfinding is one of the key elements in logistics, mobile robotics and other applications, where engineers face many conflicting objectives. However, most of the current route planning algorithms consider only up to three objectives. In this paper, we propose a scalable many-objective benchmark problem covering most of the impo

Lawrence E. Bilton, Kevin A. Pimbblet, Yjan A. Gordon

We produce a kinematic analysis of AGN-hosting cluster galaxies from a sample 33 galaxy clusters selected using the X-ray Clusters Database (BAX) and populated with galaxies from the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). The 33 galaxy clusters are delimited by their relative intensity of member galaxy substructuring as a proxy to core merging

Mayank Vashistha, Chinmoy Samanta, Aniruddha Chakraborty

We propose a simple method to calculate transition time in a two-state scattering problem, where two constant potentials are coupled by a delta function potential $V_{12}=V_{21}=k_0 δ(x)$. The exact analytical expression for the time of transition $τ$ is derived. We notice $τ$ explicitly depends on the second state&#39;s potential energy along with the incid

Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu

Continual (sequential) training and multitask (simultaneous) training are often attempting to solve the same overall objective: to find a solution that performs well on all considered tasks. The main difference is in the training regimes, where continual learning can only have access to one task at a time, which for neural networks typically leads to catastr

Nguyen Minh Tri, Masahiro Shibata, Masato Tsuru

With the prevalence of cloud computing and contents delivery networking, OpenFlow-based centrally-managed networks with flexible and dynamic traffic engineering are demanded. To maintain a high quality of service of the network, detecting and locating high-loss links is essential. Therefore, in this paper, a measurement framework is proposed to promptly loca

Kelvin Elphick, Kenta Yoshida, Tufan Roy, Tomohiro Ichinose

In spintronics, one of the long standing questions is why the MgO-based magnetic tunnel junction (MTJ) is almost the only option to achieve a large tunnelling magnetoresistance (TMR) ratio at room temperature (RT) but not as large as the theoretical prediction. This study focuses on the development of an almost strain-free MTJ using metastable bcc CoxMn100-x

Aliaksei Semchankau

We consider the problem of determining the maximum cardinality of a subset containing no arithmetic progressions of length $k$ in a given set of size $n$. It is proved that it is sufficient, in a certain sense, to consider the interval $[1,\dots, n]$. The study continues the work of Komlós, Sulyok, and Szemerédi.

Shogo Suzuki, Hideaki Okada, Kai Yabumoto, Seiju Matsuda

To develop a high-density and long-life lithium-ion battery, a technology is needed that allows non-destructive visualization of the spatial distribution of deteriorated parts after cycle test. In the present study, we measured the distribution of the magnetic field leaking from the lithium-ion battery during its operation. Based on the measurement results,

Ricarda Winkelmann, Jonathan F. Donges, E. Keith Smith, Manjana Milkoreit

Societal transformations are necessary to address critical global challenges, such as mitigation of anthropogenic climate change and reaching UN sustainable development goals. Recently, social tipping processes have received increased attention, as they present a form of social change whereby a small change can shift a sensitive social system into a qualitat

Pierangelo Lombardo, Alessio Boiardi, Luca Colombo, Angelo Schiavone

The growth of domain-specific applications of semantic models, boosted by the recent achievements of unsupervised embedding learning algorithms, demands domain-specific evaluation datasets. In many cases, content-based recommenders being a prime example, these models are required to rank words or texts according to their semantic relatedness to a given conce

Daniel Nevo, Malka Gorfine

An emerging challenge for time-to-event data is studying semi-competing risks, namely when two event times are of interest: a non-terminal event time (e.g. age at disease diagnosis), and a terminal event time (e.g. age at death). The non-terminal event is observed only if it precedes the terminal event, which may occur before or after the non-terminal event.

Wayne Xin Zhao, Junhua Chen, Pengfei Wang, Qi Gu

Top-N item recommendation has been a widely studied task from implicit feedback. Although much progress has been made with neural methods, there is increasing concern on appropriate evaluation of recommendation algorithms. In this paper, we revisit alternative experimental settings for evaluating top-N recommendation algorithms, considering three important f

Gangming Zhao, Chaowei Fang, Guanbin Li, Licheng Jiao

Identifying and locating diseases in chest X-rays are very challenging, due to the low visual contrast between normal and abnormal regions, and distortions caused by other overlapping tissues. An interesting phenomenon is that there exist many similar structures in the left and right parts of the chest, such as ribs, lung fields and bronchial tubes. This kin

Sunil Gundapu, Radhika Mamidi

In a multilingual or sociolingual configuration Intra-sentential Code Switching (ICS) or Code Mixing (CM) is frequently observed nowadays. In the world, most of the people know more than one language. CM usage is especially apparent in social media platforms. Moreover, ICS is particularly significant in the context of technology, health, and law where convey

Rachan Rangdee, Patcha Chatraphorn

\emph{Wolf-Villain (WV) model} is a simple model used to study \emph{ideal} molecular beam epitaxy (MBE) growth by using computer simulations. In this model, an adatom diffuses instantaneously within a finite diffusion length to maximize its coordination number. We study statistical properties of thin films grown by this model. The morphology of the WV model

Nadège Lagarde, Céline Reylé

The cornerstone mission of the European Space Agency, Gaia, has revealed properties of 260 000 white dwarfs in the Galaxy, allowing us for the first time to constrain the evolution of white dwarfs with a large sample. Complementary surveys (CoRoT,Kepler, K2, APOGEE andGaia-ESO), will revolutionize our understanding of the formation and history of our Galaxy,

Jean-Michel Coron, Armand Koenig, Hoai-Minh Nguyen

This paper is devoted to the local null-controllability of the nonlinear KdV equation equipped the Dirichlet boundary conditions using the Neumann boundary control on the right. Rosier proved that this KdV system is small-time locally controllable for all non-critical lengths and that the uncontrollable space of the linearized system is of finite dimension w

E. I. Jafarov, S. M. Nagiyev, R. Oste, J. Van der Jeugt

We present an exact solution of a confined model of the non-relativistic quantum harmonic oscillator, where the effective mass and the angular frequency are dependent on the position. The free Hamiltonian of the proposed model has the form of the BenDaniel--Duke kinetic energy operator. The position-dependency of the mass and the angular frequency is such th

Dominik Helm, Florian Kübler, Michael Reif, Michael Eichberg

Current approaches combining multiple static analyses deriving different, independent properties focus either on modularity or performance. Whereas declarative approaches facilitate modularity and automated, analysis-independent optimizations, imperative approaches foster manual, analysis-specific optimizations. In this paper, we present a novel approach to

Shirali Kadyrov, Ardak Kashkynbayev, Piotr Skrzypacz, Konstantinos Kaloudis

We study periodic solutions of a one-degree of freedom micro-electro-mechanical system (MEMS) with a parallel-plate capacitor under $T$--periodic electrostatic forcing. We obtain analytical results concerning the existence of $T-$ periodic solutions of the problem in the case of arbitrary nonlinear restoring force, as well as when the moving plate is attache