April 2019 arXiv papers — page 105

Maria Bras-Amorós

We analyze the set of increasingly enumerable additive submonoids of R, for instance, the set of logarithms of the positive integers with respect to a given base. We call them $ω$-monoids. The $ω$-monoids for which consecutive elements become arbitrarily close are called tempered monoids. This is, in particular, the case for the set of logarithms. We show th

François Roueff, Randal Douc, Ois Roueff, Tepmony Sim

In this contribution we are interested in proving that a given observation-driven model is identifiable. In the case of a GARCH(p, q) model, a simple sufficient condition has been established in [1] for showing the consistency of the quasi-maximum likelihood estimator. It turns out that this condition applies for a much larger class of observation-driven mod

Kou Tanaka, Hirokazu Kameoka, Takuhiro Kaneko, Nobukatsu Hojo

WaveCycleGAN has recently been proposed to bridge the gap between natural and synthesized speech waveforms in statistical parametric speech synthesis and provides fast inference with a moving average model rather than an autoregressive model and high-quality speech synthesis with the adversarial training. However, the human ear can still distinguish the proc

Elliot J. Carr, Christyn J. Wood

We study methods for calculating the thermal diffusivity of solids from laser flash experiments. This experiment involves subjecting the front surface of a small sample of the material to a heat pulse and recording the resulting temperature rise on the opposite (rear) surface. Recently, a method was developed for calculating the thermal diffusivity from the

Katarina Karlova, Jozef Strecka, Taras Verkholyak

The mixed spin-1 and spin-1/2 Heisenberg octahedral chain with regularly alternating monomeric spin-1 sites and square-plaquette spin-1/2 sites is investigated using variational technique, localized-magnon approach, exact diagonalization (ED) and density-matrix renormalization group (DMRG) method. The investigated model has in a magnetic field an extraordina

Stephane Robin, Vincent Miele, Catherine Matias, Stéphane Dray

These tips provide a quick and concentrated guide for beginners in the analysis of network data.

Akira Ono, Jun Xu, Maria Colonna, Pawel Danielewicz

We compare ten transport codes for a system confined in a box, aiming at improved handling of the production of $Δ$ resonances and pions, which is indispensable for constraining high-density symmetry energy from observables such as the $π^-/π^+$ yield ratio in heavy-ion collisions. The system in a box is initialized with nucleons at saturation density and at

Claudio Arancibia-Ibarra, Michael Bode, José Flores, Graeme Pettet

We study a predator-prey model with Holling type I functional response, an alternative food source for the predator, and multiple Allee effects on the prey. We show that the model has at most two equilibrium points in the first quadrant, one is always a saddle point while the other can be a repeller or an attractor. Moreover, there is always a stable equilib

Masaki J. S. Yang

In this paper, we consider a lopsided flavor texture compatible with thermal leptogenesis in partially composite Pati--Salam unification. The Davidson--Ibarra bound $M_{νR1} \gtrsim 10^9$ GeV for the successful thermal leptogenesis can be recast to the Froggatt--Nielsen (FN) charge of the lopsided texture. We found the FN charge $n_{\nu1}$ of the lightest ri

Tomokazu Kashio

Coleman calculated the absolute Frobenius on Fermat curves explicitly. In this paper we show that a kind of $p$-adic continuity implies a large part of his formula. To do this, we study a relation between functional equations of the ($p$-adic) gamma function and monomial relations on ($p$-adic) CM-periods.

A. Zorko, M. Pregelj, M. Klanjšek, M. Gomilšek

One of the key questions concerning frustrated lattices that has lately emerged is the role of disorder in inducing spin-liquid-like properties. In this context, the quantum kagome antiferromagnets YCu$_3$(OH)$_6$Cl$_3$, which has been recently reported as the first geometrically perfect realization of the kagome lattice with negligible magnetic/non-magnetic

Hugh Entwistle, Christopher Lustri, Georgy Sofronov

We consider optimal stopping problems, in which a sequence of independent random variables is drawn from a known continuous density. The objective of such problems is to find a procedure which maximizes the expected reward; this is often known as the "full information" problem. In this analysis, we obtain asymptotic expressions for the expectation an

Sneha Chaudhari, Varun Mithal, Gungor Polatkan, Rohan Ramanath

Attention Model has now become an important concept in neural networks that has been researched within diverse application domains. This survey provides a structured and comprehensive overview of the developments in modeling attention. In particular, we propose a taxonomy which groups existing techniques into coherent categories. We review salient neural arc

Ga Wu, Buser Say, Scott Sanner

In many real-world planning problems with factored, mixed discrete and continuous state and action spaces such as Reservoir Control, Heating Ventilation, and Air Conditioning, and Navigation domains, it is difficult to obtain a model of the complex nonlinear dynamics that govern state evolution. However, the ubiquity of modern sensors allows us to collect la

Boah Kim, Jong Chul Ye

Recent state-of-the-art image segmentation algorithms are mostly based on deep neural networks, thanks to their high performance and fast computation time. However, these methods are usually trained in a supervised manner, which requires large number of high quality ground-truth segmentation masks. On the other hand, classical image segmentation approaches s

Parinya Karndumri, Patharadanai Nuchino

We give a large class of supersymmetric domain walls in maximal seven-dimensional gauged supergravity with various types of gauge groups. Gaugings are described by components of the embedding tensor transforming in representations $\mathbf{15}$ and $\overline{\mathbf{40}}$ of the global symmetry $SL(5)$. The embedding tensor in $\mathbf{15}$ representation l

Amirata Ghorbani, James Zou

As data becomes the fuel driving technological and economic growth, a fundamental challenge is how to quantify the value of data in algorithmic predictions and decisions. For example, in healthcare and consumer markets, it has been suggested that individuals should be compensated for the data that they generate, but it is not clear what is an equitable valua

Tatsuo Kobayashi, Hajime Otsuka, Hikaru Uchida

We propose matter wavefunctions on resolutions of $T^2/\mathbb{Z}_N$ singularities with constant magnetic fluxes. In the blow-down limit, the obtained wavefunctions of chiral zero-modes result in those on the magnetized $T^2/\mathbb{Z}_N$ orbifold models, but the wavefunctions of $\mathbb{Z}_N$-invariant zero-modes receive the blow-up effects around fixed po

Sushrut Thorat, Daria Proklova, Marius V. Peelen

The principles underlying the animacy organization of the ventral temporal cortex (VTC) remain hotly debated, with recent evidence pointing to an animacy continuum rather than a dichotomy. What drives this continuum? According to the visual categorization hypothesis, the continuum reflects the degree to which animals contain animal-diagnostic features. By co

Colm Talbot, Rory Smith, Eric Thrane, Gregory B. Poole

Bayesian inference is the workhorse of gravitational-wave astronomy, for example, determining the mass and spins of merging black holes, revealing the neutron star equation of state, and unveiling the population properties of compact binaries. The science enabled by these inferences comes with a computational cost that can limit the questions we are able to

Yule Zhang, Zehao Xiao, Jia Wu, Liwei Zhang

In this paper, we investigate regrets of an online semi-proximal alternating direction method of multiplier (Online-spADMM) for solving online linearly constrained convex composite optimization problems. Under mild conditions, we establish ${\rm O}(\sqrt{N})$ objective regret and ${\rm O}(\sqrt{N})$ constraint violation regret at round $N$ when the dual step

Yaojie Liu, Joel Stehouwer, Amin Jourabloo, Xiaoming Liu

Face anti-spoofing is designed to keep face recognition systems from recognizing fake faces as the genuine users. While advanced face anti-spoofing methods are developed, new types of spoof attacks are also being created and becoming a threat to all existing systems. We define the detection of unknown spoof attacks as Zero-Shot Face Anti-spoofing (ZSFA). Pre

Ellery Ames, Florian Beyer, James Isenberg

We prove an asymptotic stability result for a linear coupled hyperbolic-elliptic system on a large class of singular background spacetimes in CMC gauge on the n-torus. At each spatial point these background spacetimes are perturbations of Kasner-like solutions of the Einstein-scalar field equations which are not required to be close to the homogeneous and is

Atsushi Nobe, Junta Matsukidaira

The one-parameter family of second order nonlinear difference equations each of which is given by $$ x_{n-1}x_nx_{n+1}=x_{n-1}+(x_n)^{β-1}+x_{n+1} \qquad(β\in\mathbb{N}) $$ is explored. Since the equation above is arising from seed mutations of a rank 2 cluster algebra, its solution is periodic only when $β\leq3$. In order to evaluate the dynamics with $β\ge

Takuto Yamaguchi, Yasutomo Ota, Ryota Katsumi, Katsuyuki Watanabe

We report a valley photonic crystal (VPhC) waveguide in a GaAs slab with InAs quantum dots (QDs) as an internal light source exploited for experimental characterization of the waveguide. A topological interface state formed at the interface between two topologically-distinct VPhCs is used as the waveguide mode. We demonstrate robust propagation for near-infr

Shujaat Khan, Jaeyoung Huh, Jong Chul Ye

In ultrasound (US) imaging, individual channel RF measurements are back-propagated and accumulated to form an image after applying specific delays. While this time reversal is usually implemented using a hardware- or software-based delay-and-sum (DAS) beamformer, the performance of DAS decreases rapidly in situations where data acquisition is not ideal. Here

Fatemeh Sheikholeslami, Swayambhoo Jain, Georgios B. Giannakis

Despite their unprecedented performance in various domains, utilization of Deep Neural Networks (DNNs) in safety-critical environments is severely limited in the presence of even small adversarial perturbations. The present work develops a randomized approach to detecting such perturbations based on minimum uncertainty metrics that rely on sampling at the hi

Faeza Hafiz, Celia Shahnaz

The aim of this paper is to propose a new approach for the pattern recognition of power quality (PQ) disturbances based on Empirical mode decomposition (EMD) and $k$ Nearest Neighbor ($k$-NN) classifier. Since EMD decomposes a signal into intrinsic mode functions (IMF) in time-domain with same length of the original signal, it preserves the information that

Esraa Abdel-Ghani, Said Ghoul

Background. Feature Model (FM) is the most important technique used to manage the variability through products in Software Product Lines (SPLs). Often, the SPLs requirements variability is by using variable use case model which is a real challenge in actual approaches: large gap between their concepts and those of real world leading to bad quality, poor supp

Urmimala Dey, Archisman Ghosh, Syed Abbas, A Taraphder

Chronic exposure to inorganic arsenic is a potential cause of carcinogenesis. It elicits its potential by generation of ROS, leading to DNA, protein and lipid damage. Therefore, the deleterious effect of arsenic can be mitigated by quenching ROS using antioxidants. There is a homology between the protein coding regions of mice and human. Effect of these alte

Lucas Gren

Agility implies a set of principles that need to be followed in order to have the proposed responsiveness to change. This paper presents how the Agile Adoption Framework can be used to assess agility and pinpoint focus areas for companies that want to improve. Management found it useful in general to get data on possible focus points for improvement in their

Lucas Gren

This note highlights the importance of investigating diversity aspects in combination in empirical research. It draws on the psychological discourse and suggests why and how software engineering scholars can use the aspect of diversity in all their research endeavors.

Lucas Gren

The purpose of this paper is to review research on attitudes and social norms and connect it to the agile software development context. Furthermore, I propose additional theories from social psychology (mainly the theory of planned behavior and using the degree of internalization of social norms) that would most certainly be useful for further sense-making o

Maja von Cube, Martin Schumacher, Hein Putter, Jean-Francois Timsit

The public health impact of a harmful exposure can be quantified by the population-attributable fraction (PAF). The PAF describes the attributable risk due to an exposure and is often interpreted as the proportion of preventable cases if the exposure could be extinct. Difficulties in the definition and interpretation of the PAF arise when the exposure of int

Francesca Pelusi, Mauro Sbragaglia, Roberto Benzi

We study the coarsening dynamics of a two dimensional system via lattice Boltzmann numerical simulations. The system under consideration is a biphasic system consisting of domains of a dispersed phase closely packed together in a continuous phase and separated by thin interfaces. Such system is elastic and typically out of equilibrium. The equilibrium state

Oryna Ivashtenko, Polina Kofman, Oleksiy Golubov, Zakhar Maizelis

The article studies the elastic and locomotive properties of Miura-ori-type paper origami. The mechanics of a single paper crease is studied experimentally, and its non-elastic properties turn out to be crucial. The entire origami construction is then described as a collection of individual creases, its capability to launch small objects is evaluated, and th

I. M. Suslov

The correct definition of the conductance of finite systems implies a connection to the system of the massive ideal leads. Influence of the latter on the properties of the system appears to be rather essential and is studied below on the simplest example of the 1D case. In the log-normal regime this influence is reduced to the change of the absolute scale of

Leonel Merino, Mario Hess, Alexandre Bergel, Oscar Nierstrasz

Developers are usually unaware of the impact of code changes to the performance of software systems. Although developers can analyze the performance of a system by executing, for instance, a performance test to compare the performance of two consecutive versions of the system, changing from a programming task to a testing task would disrupt the development f

Lucas Gren, Per Lenberg

Today, software companies usually organize their work in teams. Social science research on team development has shown that for a team to reach a productive and autonomous stage, it has to be able to manage internal conflicts and disagreements efficiently. To better facilitate the team development process, we argue that software engineers' needs additiona

Lucas Gren

An agile change effort in an organization needs to be understood in relation to human processes. Such theory and accompanying tools already existed almost 50 years ago in applied psychology. The core ideas of Agile Process Consultation are that a client initiating a change toward more agility often does not know what is wrong and the consultant needs to diag

Khaled Al-Sabbagh, Lucas Gren

Empirical evidence regarding the connection between group development (maturity) and the success of software development teams is lacking. The purpose of this research is to gain a qualitative and quantitative understanding of how velocity and planning effectiveness of software teams connect to a group development model. The Group Development Questionnaire w

Lucas Gren

Agile processes explicitly focus more on team-work than more traditional management techniques when building software. With high velocity and responsiveness on team-level come the risk of interpersonal conflict in the agile organizations. Through a survey with 68 software developers from three large Swedish companies, I found that the presence of interperson

Maoying Qiao, Jun Yu, Wei Bian, Qiang Li

Stochastic block models (SBMs) have been playing an important role in modeling clusters or community structures of network data. But, it is incapable of handling several complex features ubiquitously exhibited in real-world networks, one of which is the power-law degree characteristic. To this end, we propose a new variant of SBM, termed power-law degree SBM

Paul A. Reiser

This paper presents a simple physical model for self-similar (gnomonic, or first-order) seashell growth which is expressed in coordinate-free terms. The shell is expressed as the solution of a differential equation which expresses the growth dynamics, and may be used to investigate shell growth from both the local viewpoint of the organism building it and mo

Kyongmin Yeo

The behavior of recurrent neural network for the data-driven simulation of noisy dynamical systems is studied by training a set of Long Short-Term Memory Networks (LSTM) on the Mackey-Glass time series with a wide range of noise level. It is found that, as the training noise becomes larger, LSTM learns to depend more on its autonomous dynamics than the noisy

Lucas Gren

Scholars have tried to explain how organizations can build agile teams by only looking at one level of analysis. We argue in this short paper that lessons can be learned from organizational science results explaining variance on three different abstraction levels of organizations. We suggest agility needs to be explained from organizational (macro), the team

Lucas Gren

Agile requirements engineering implies more complex communication patterns since even the developers are supposed to have direct contact with customers. With more face-to-face communication comes social-psychological factors influencing the requirements. Studies have pointed at the importance of negotiation training, but I argue that more basic human traits

Lucas Gren, Vard Antinyan

Unit testing has been considered as having a key role in building high quality software, and therefore it has been widely used in practice. However, data on the relationship between unit testing and aspects of software quality remain scarce. A survey study with 235 survey responses from seven organizations was conducted in order to understand the correlation

Fulvio Melia

The Universe has a gravitational horizon with a radius R_h=c/H coincident with that of the Hubble sphere. This surface separates null geodesics approaching us from those receding, and as free-falling observers within the Friedmann-Lemaitre-Robertson-Walker spacetime, we see it retreating at proper speed c, giving rise to the eponymously named cosmological mo

Patrick A. K. Reinbold, Roman O. Grigoriev

In spatially extended systems, it is common to find latent variables that are hard, or even impossible, to measure with acceptable precision, but are crucially important for the proper description of the dynamics. This substantially complicates construction of an accurate model for such systems using data-driven approaches. The present paper illustrates how

Ondrej Novotny, Oldrich Plchot, Ondrej Glembek, Lukas Burget

In this work, we continue in our research on i-vector extractor for speaker verification (SV) and we optimize its architecture for fast and effective discriminative training. We were motivated by computational and memory requirements caused by the large number of parameters of the original generative i-vector model. Our aim is to preserve the power of the or

S. M. Cherniavsky, E. V. Lychagin, A. Yu. Muzychka, G. V. Nekhaev

We measured the temperature dependence of the probability of small heating and total losses of UCNs on the PFPE Fomblin Y surface with various molecular masses Mw=2800, 3300, 6500 amu in the temperature range of 100-300 K. The probability of small heating sharply decreases with increasing Mw and decreasing temperature. The probability of total loss weakly de

G. Schepers, A. Ali, A. Belias, R. Dzhygadlo

The Barrel DIRC of the PANDA experiment at FAIR will cleanly separate pions from kaons for the physics program of PANDA. Innovative solutions for key components of the detector sitting in the strong magnetic field of the compact PANDA target spectrometer as well as two reconstruction methods were developed in an extensive prototype program. The technical des

Michał Eckstein, Paweł Horodecki

Modern physics is founded on two mainstays: mathematical modelling and empirical verification. These two assumptions are prerequisite for the objectivity of scientific discourse. Here we show, however, that they are contradictory, leading to the `experiment paradox'. We reveal that any experiment performed on a physical system is - by necessity - invasiv

V. I. Yukalov, E. P. Yukalova

Self-similar approximation theory is shown to be a powerful tool for describing phase transitions in quantum field theory. Self-similar approximants present the extrapolation of asymptotic series in powers of small variables to the arbitrary values of the latter, including the variables tending to infinity. The approach is illustrated by considering three pr

Masakatsu Kenmoku

Bargmann-Wigner equations and their solutions are studied in (3+1)-dimensional curved spacetime. Fermion-Boson correspondence for bi-spinor case is studied through the Bargmann-Wigner equations and solutions over curved spacetime. As an application to scattering phenomena of massive Fermions and Bosons on the rotating black holes, the superradiance with nega

Pushkar Mishra, Marco Del Tredici, Helen Yannakoudakis, Ekaterina Shutova

Abuse on the Internet represents a significant societal problem of our time. Previous research on automated abusive language detection in Twitter has shown that community-based profiling of users is a promising technique for this task. However, existing approaches only capture shallow properties of online communities by modeling follower-following relationsh

Riccardo Fantoni

The simplest statistical mechanics model of a Coulomb plasma in two spatial dimensions admits an exact analytic solution at some special temperature in several (curved) surfaces. We present in a unifying perspective these solutions for the (non-quantum) plasma, made of point particles carrying an absolute charge $e$, in thermal equilibrium at a temperature $

Murat Kirişci

We define the Pythagorean fuzzy parameterized soft set and investigate some properties of the new set. Further, we propose to the solution of decision-making application for the Pythagorean fuzzy parameterized soft set and other related concepts.

Afra Alishahi, Grzegorz Chrupała, Tal Linzen

The EMNLP 2018 workshop BlackboxNLP was dedicated to resources and techniques specifically developed for analyzing and understanding the inner-workings and representations acquired by neural models of language. Approaches included: systematic manipulation of input to neural networks and investigating the impact on their performance, testing whether interpret

Tran Tri Dang, Tran Khanh Dang

This paper proposes a novel visual model for web applications security monitoring. Although an automated intrusion detection system can shield a web application from common attacks, it usually cannot detect more complicated break-ins. So, a human-assisted monitoring system is an indispensable complement, following the "Defense in depth" strategy. To

Axel Saenz

These notes are based on a talk given at the 2018 Arizona School of Analysis and Mathematical Physics. We give a comprehensive introduction to the KPZ universality class, a conjectured class of stochastic process with local interactions related to random growth processes in $1+1$ dimensions. We describe some of the characteristic properties of the KPZ univer

Usama Choudhry, Shengying Yue, Bolin Liao

Coherent wave effects of thermal phonons hold promise of transformative opportunities in thermal transport control but remain largely unexplored due to the small wavelength of thermal phonons, typically below a few nanometers. This small length scale indicates that, instead of artificial phononic crystals, a more promising direction is to examine the coheren

Kun Hu, Matthew G. Baring, Zorawar Wadiasingh, Alice K. Harding

Over the last four decades, persistent and flaring emission of magnetars observed by various telescopes has provided us with a suite of light curves and spectra in soft and hard X-rays, with no emission yet detected above around 1 MeV. Attenuation of such high-energy photons by magnetic pair creation and photon splitting is expected to be active in the magne

Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell

In this paper, we quantify, analyze and mitigate gender bias exhibited in ELMo's contextualized word vectors. First, we conduct several intrinsic analyses and find that (1) training data for ELMo contains significantly more male than female entities, (2) the trained ELMo embeddings systematically encode gender information and (3) ELMo unequally encodes g

Sina Mokhtarzadeh Azar, Mina Ghadimi Atigh, Ahmad Nickabadi, Alexandre Alahi

We present an end-to-end deep Convolutional Neural Network called Convolutional Relational Machine (CRM) for recognizing group activities that utilizes the information in spatial relations between individual persons in image or video. It learns to produce an intermediate spatial representation (activity map) based on individual and group activities. A multi-

Matteo D'Andrea

ATHENA is a large-class ESA mission selected for launch in 2031. It is designed to address the science theme "The Hot and Energetic Universe", performing X-ray observations (0.2-12 keV) at the L2 Sun-Earth Lagrangian point. The X-IFU is one of the two instruments of the payload. It is a cryogenic spectrometer providing spatially resolved high-resolut

Ivon Dorado, Ricardo Torres

We formulate and prove a criterion for reducibility of a quadratic polynomial over the integers. The main theorem was suggested by the teaching experience with the concrete material called "the polynomial box". Through the corollaries we relate our theorem and the use of concrete material with some well know factoring methods for quadratic polynomial

Francesco Pittaluga, Sanjeev J. Koppal, Sing Bing Kang, Sudipta N. Sinha

Many 3D vision systems localize cameras within a scene using 3D point clouds. Such point clouds are often obtained using structure from motion (SfM), after which the images are discarded to preserve privacy. In this paper, we show, for the first time, that such point clouds retain enough information to reveal scene appearance and compromise privacy. We prese

Urmish Thakker, Ganesh Dasika, Jesse Beu, Matthew Mattina

Recurrent neural networks (RNNs) have shown state of the art results for speech recognition, natural language processing, image captioning and video summarizing applications. Many of these applications run on low-power platforms, so their energy efficiency is extremely important. We observed that cache-oblivious RNN scheduling during inference typically resu

Kiran Garimella, Robert West

Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media, where impact is usually defined as the reach of a user's content as captured by metrics such as the number of views, likes, retweets, or shares. In this paper, we study entir

John Doroshewitz, Christopher Oakley, Vincens Gjokaj, Jeffrey Nanzer

A unique three-band patch antenna for high accuracy ranging between nodes in open-loop coherent distributed antenna arrays is presented. Open-loop coherent distributed operations require accurate relative position knowledge between nodes to enable distributed beamforming operations. For the highest accuracy, the inter-node ranging will typically occur at fre

Randa A. T. Alani, Taisir E. H. El-Gorashi, Jaafar M. H. Elmirghani

In this study, we investigate the embedding of various cloud applications in PON AWGR and Server Based Data Centres.

Jinho Choi

For the Internet of Things (IoT), there might be a large number of devices to be connected to the Internet through wireless technologies. In general, IoT devices would have various constraints due to limited processing capability, memory, energy source, and so on, and it is desirable to employ efficient wireless transmission schemes, especially for uplink tr

Yi Luan, Dave Wadden, Luheng He, Amy Shah

We introduce a general framework for several information extraction tasks that share span representations using dynamically constructed span graphs. The graphs are constructed by selecting the most confident entity spans and linking these nodes with confidence-weighted relation types and coreferences. The dynamic span graph allows coreference and relation ty

Ishan Durugkar, Matthew Hausknecht, Adith Swaminathan, Patrick MacAlpine

Policy gradient algorithms typically combine discounted future rewards with an estimated value function, to compute the direction and magnitude of parameter updates. However, for most Reinforcement Learning tasks, humans can provide additional insight to constrain the policy learning. We introduce a general method to incorporate multiple different feedback c

Md Arif Iqbal, Naveen Kumar Macha, Bhavana Tejaswini Repalle, Mostafizur Rahman

Crosstalk computing, involving engineered interference between nanoscale metal lines, offers a fresh perspective to scaling through co-existence with CMOS. Through capacitive manipulations and innovative circuit style, not only primitive gates can be implemented, but custom logic cells such as an Adder, Subtractor can be implemented with huge gains. Our simu

Naoki Ishizu, Jiro Kitagawa

High-entropy alloys are a new class of alloys, and attract much attention due to their unique properties. Since the discovery of a superconducting high-entropy alloy (HEA) in 2014, the materials research on HEA superconductor is a hot topic. We have found that Hf$_{21}$Nb$_{25}$Ti$_{15}$V$_{15}$Zr$_{24}$ body-centered-cubic (BCC) HEA is a new superconductor

Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta, Gerard Pons-Moll

Convolutional Neural Network based approaches for monocular 3D human pose estimation usually require a large amount of training images with 3D pose annotations. While it is feasible to provide 2D joint annotations for large corpora of in-the-wild images with humans, providing accurate 3D annotations to such in-the-wild corpora is hardly feasible in practice.

C. A. Brown, C. S. Carrillo Vazquez, R. Goswami, S. Heil

The study of sorting permutations by block interchanges has recently been stimulated by a phenomenon observed in the genome maintenance of certain ciliate species. The result was the identification of a block interchange operation that applies only under certain constraints. Interestingly, this constrained block interchange operation can be generalized natur

Tridib Kumar Sinha, Jinho Lee, Jin Kuk Kim, Samit K. Ray

CaxCoO2 thin films can be promising for widespread flexible thermoelectric applications in a wide temperature range from room-temperature self-powered wearable applications (by harvesting power from body heat) to energy harvesting from hot surfaces (e.g., hot pipes) if a cost-effective and facile growth technique is developed. Here, we demonstrate a time res

Jaehong Park, Stepan S. Bulanov, Jianhui Bin, Qing Ji

Magnetic Vortex Acceleration (MVA) from near critical density targets is one of the promising schemes of laser-driven ion acceleration. 3D particle-in-cell simulations are used to explore a more extensive laser-target parameter space than previously reported on in the literature as well as to study the laser pulse coupling to the target, the structure of the

Jianren Wang, Yihui He, Xiaobo Wang, Xinjia Yu

We introduce a prediction driven method for visual tracking and segmentation in videos. Instead of solely relying on matching with appearance cues for tracking, we build a predictive model which guides finding more accurate tracking regions efficiently. With the proposed prediction mechanism, we improve the model robustness against distractions and occlusion

Naureen Mahmood, Nima Ghorbani, Nikolaus F. Troje, Gerard Pons-Moll

Large datasets are the cornerstone of recent advances in computer vision using deep learning. In contrast, existing human motion capture (mocap) datasets are small and the motions limited, hampering progress on learning models of human motion. While there are many different datasets available, they each use a different parameterization of the body, making it

Stephen Hughes, Sebastian Franke, Chris Gustin, Mohsen Kamandar Dezfouli

Quantum emitters coupled to plasmonic resonators are known to allow enhanced broadband Purcell factors, and such systems have been recently suggested as possible candidates for on-demand single photon sources, with fast operation speeds. However, a true single photon source has strict requirements of high efficiency (brightness) and quantum indistinguishabil

Tyler Maunu, Gilad Lerman

We study the problem of robust subspace recovery (RSR) in the presence of adversarial outliers. That is, we seek a subspace that contains a large portion of a dataset when some fraction of the data points are arbitrarily corrupted. We first examine a theoretical estimator that is intractable to calculate and use it to derive information-theoretic bounds of e

Takuya Kanazawa, Mario Kieburg, Jacobus J. M. Verbaarschot

We propose a random matrix theory for QCD in three dimensions with a Chern-Simons term at level $k$ which spontaneously breaks the flavor symmetry according to U($2N_{\rm f}$) $\to $ U($N_{\rm f}+k$)$\times$U($N_{\rm f}-k$). This random matrix model is obtained by adding a complex part to the action for the $k=0$ random matrix model. We derive the pattern of

Nazanin Mehrasa, Akash Abdu Jyothi, Thibaut Durand, Jiawei He

We propose a novel probabilistic generative model for action sequences. The model is termed the Action Point Process VAE (APP-VAE), a variational auto-encoder that can capture the distribution over the times and categories of action sequences. Modeling the variety of possible action sequences is a challenge, which we show can be addressed via the APP-VAE&#39

Polina Bombina, Brendan Ames

We consider the densest $k$-subgraph problem, which seeks to identify the $k$-node subgraph of a given input graph with maximum number of edges. This problem is well-known to be NP-hard, by reduction to the maximum clique problem. We propose a new convex relaxation for the densest $k$-subgraph problem, based on a nuclear norm relaxation of a low-rank plus sp

Kenneth L. Baker, Neil R. Hoffman, Joan E. Licata

This paper describes a Dehn surgery approach to generating asymmetric hyperbolic manifolds with two distinct lens space fillings. Such manifolds were first identified in work of Dunfield-Hoffman-Licata as the result of a computer search of the SnapPy census, but the current work establishes a topological framework for constructing vastly many more such examp

Sepehr Janghorbani, Ashutosh Modi, Jakob Buhmann, Mubbasir Kapadia

Developing intelligent virtual characters has attracted a lot of attention in the recent years. The process of creating such characters often involves a team of creative authors who describe different aspects of the characters in natural language, and planning experts that translate this description into a planning domain. This can be quite challenging as th

Igor G. Vladimirov, Ian R. Petersen, Matthew R. James

This paper extends the Karhunen-Loeve representation from classical Gaussian random processes to quantum Wiener processes which model external bosonic fields for open quantum systems. The resulting expansion of the quantum Wiener process in the vacuum state is organised as a series of sinusoidal functions on a bounded time interval with statistically indepen

Chen Avin, Stefan Schmid

This paper studies the design of self-adjusting networks whose topology dynamically adapts to the workload, in an online and demand-aware manner. This problem is motivated by emerging optical technologies which allow to reconfigure the datacenter topology at runtime. Our main contribution is ReNet, a self-adjusting network which maintains a balance between t

Yufang Hou, Debasis Ganguly, Lea A. Deleris, Francesca Bonin

Population age information is an essential characteristic of clinical trials. In this paper, we focus on extracting minimum and maximum (min/max) age values for the study samples from clinical research articles. Specifically, we investigate the use of a neural network model for question answering to address this information extraction task. The min/max age Q

Tarik Tosun, Eric Mitchell, Ben Eisner, Jinwook Huh

We present a novel method enabling robots to quickly learn to manipulate objects by leveraging a motion planner to generate "expert" training trajectories from a small amount of human-labeled data. In contrast to the traditional sense-plan-act cycle, we propose a deep learning architecture and training regimen called PtPNet that can estimate effectiv

Stephen G. Odaibo

Is all of machine learning supervised to some degree? The field of machine learning has traditionally been categorized pedagogically into $supervised~vs~unsupervised~learning$; where supervised learning has typically referred to learning from labeled data, while unsupervised learning has typically referred to learning from unlabeled data. In this paper, we a

Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab

We describe a transfer method based on annotation projection to develop a dependency-based semantic role labeling system for languages for which no supervised linguistic information other than parallel data is available. Unlike previous work that presumes the availability of supervised features such as lemmas, part-of-speech tags, and dependency parse trees,

Lawrence J. Trautman, Mason J. Molesky

Much has been written about the likely impact of blockchain technology. Early scholarship on this topic has focused on the legal and financial implications of virtual currencies which is based on blockchain technology. Rapid introduction and diffusion of technological changes throughout society, such as blockchain, continue to exceed the ability of law and r

Brian Harbourne, Juan Migliore, Halszka Tutaj-Gasińska

In the paper we present new examples of unexpected varieties. The research on unexpected varieties started with a paper of Cook II, Harbourne, Migliore and Nagel and was continued in the paper of Harbourne, Migliore, Nagel and Teitler. Here we present three ways of producing unexpected varieties that expand on what was previously known. In the paper of Harbo

Takako Tomizawa, Ko Okumura

It has long been known for elastomers that the velocity of crack propagation jumps as a function of strain. On the other hand, such a jump has not been reported in the literature for polymers which do not exhibit a rubbery plateau in the storage-modulus plot. Here, we report observation of jumps in crack propagation for semi-crystalline polymer sheets withou