March 2020 arXiv papers — page 104

Jonathan Jedwab, Tabriz Popatia

Mutually orthogonal frequency squares (MOFS) of type $F(mλ;λ)$ generalize the structure of mutually orthogonal Latin squares: rather than each of $m$ symbols appearing exactly once in each row and in each column of each square, the repetition number is $λ\ge 1$. A classical upper bound for the number of such MOFS is $\frac{(mλ-1)^2}{m-1}$. We introduce a new

Sankalp Garg, Navodita Sharma, Woojeong Jin, Xiang Ren

Time series prediction is an important problem in machine learning. Previous methods for time series prediction did not involve additional information. With a lot of dynamic knowledge graphs available, we can use this additional information to predict the time series better. Recently, there has been a focus on the application of deep representation learning

Yuma Rao, Jacob Steeves, Ala Shaabana, Daniel Attevelt

As with other commodities, markets could help us efficiently produce machine intelligence. We propose a market where intelligence is priced by other intelligence systems peer-to-peer across the internet. Peers rank each other by training neural networks which learn the value of their neighbors. Scores accumulate on a digital ledger where high ranking peers a

Josef Dick, Takashi Goda, Hiroya Murata

Motivated mainly by applications to partial differential equations with random coefficients, we introduce a new class of Monte Carlo estimators, called Toeplitz Monte Carlo (TMC) estimator for approximating the integral of a multivariate function with respect to the direct product of an identical univariate probability measure. The TMC estimator generates a

Stephan Plugge, Étienne Lantagne-Hurtubise, Marcel Franz

Quantum effects can stabilize wormhole solutions in general relativity, allowing information and matter to be transported between two connected spacetimes. Here we study the revival dynamics of signals sent between two weakly coupled quantum chaotic systems, represented as identical Sachdev-Ye-Kitaev models, that realize holographically a traversable wormhol

Clarice Poon, Jingwei Liang

First-order operator splitting methods are ubiquitous among many fields through science and engineering, such as inverse problems, signal/image processing, statistics, data science and machine learning, to name a few. In this paper, we study a geometric property of first-order methods when applying to solve non-smooth optimization problems. With the tool of

Axel Barrau, Silvere Bonnabel

To fuse information from inertial measurement units (IMU) with other sensors one needs an accurate model for IMU error propagation in terms of position, velocity and orientation, a triplet we call extended pose. In this paper we leverage a nontrivial result, namely log-linearity of inertial navigation equations based on the recently introduced Lie group $SE_

Alimzhan Amanov, Damir Yeliussizov

We prove Jacobi-Trudi-type determinantal formulas for skew dual Grothendieck polynomials which are $K$-theoretic deformations of Schur polynomials. We also prove a bialternant-type formula analogous to the classical definition of Schur polynomials.

Mariagrazia Bianchi, Cheryl E. Praeger, S. P. Glasby

Let ${\rm cs}(G)$ denote the set of conjugacy class sizes of a group $G$, and let ${\rm cs}^*(G)={\rm cs}(G)\setminus\{1\}$ be the sizes of non-central classes. We prove three results. We classify all finite groups $G$ with ${\rm cs}(G)=\{a, a+d, \dots ,a+rd\}$ an arithmetic progression with $r\geqslant 2$. (We show that ${\rm cs}(G)=\{1,2,3\}$.) Our most su

Satoshi Yamanaka, Akio K. Inoue, Toru Yamada, Erik Zackrisson

Using a sample of galaxies at $z\approx 3$ with detected Lyman Continuum (LyC) leakage in the SSA22 field, we attempt to verify a proposed indirect method for identifying cases with high LyC escape fraction $f_\mathrm{esc}$ based on measurements of the H$β$ equivalent width (EW) and the $β$ slope of the UV continuum. To this end, we present Keck/MOSFIRE H$β$

Nima Arkani-Hamed, Thomas Lam, Marcus Spradlin

We define and study the totally nonnegative part of the Chow quotient of the Grassmannian, or more simply the nonnegative configuration space. This space has a natural stratification by positive Chow cells, and we show that nonnegative configuration space is homeomorphic to a polytope as a stratified space. We establish bijections between positive Chow cells

Andronikos Paliathanasis, Genly Leon

In the context of Einstein-aether scalar field cosmology we solve the field equations and determine exact and analytic solutions. In particular, we consider a model proposed by Kanno and Soda where the aether and the scalar fields interact through the aether coefficient parameters, which are promoted to be functions of the scalar field. For this model, we wr

C. Itoi, Y. Sakamoto

A new series of correlation inequalities for random field spin systems is proven rigorously. First one corresponds to the well-known Schwartz-Soffer inequality. These are expected to rule out incorrect results calculated in effective theories and numerical studies. The large $N$ expansion with the replica method for random field systems as an example is chec

Can Peng, Kun Zhao, Brian C. Lovell

The human vision and perception system is inherently incremental where new knowledge is continually learned over time whilst existing knowledge is retained. On the other hand, deep learning networks are ill-equipped for incremental learning. When a well-trained network is adapted to new categories, its performance on the old categories will dramatically degr

Aman Sinha, Matthew O'Kelly, Hongrui Zheng, Rahul Mangharam

Balancing performance and safety is crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conservative policies, highlighting the need for robust, adaptive strategies. Current approaches either make simplifying assumptions about other agents or lack robust mechanisms for onl

Li Guo, Yunnan Li, Yunhe Sheng, Guodong Zhou

As an algebraic study of differential equations, differential algebras have been studied for a century and and become an important area of mathematics. In recent years the area has been expended to the noncommutative associative and Lie algebra contexts and to the case when the operator identity has a weight in order to include difference operators and diffe

Fei Shi, Xiande Zhang, Lin Chen

We completely characterize the condition when a tile structure provides an unextendible product basis (UPB), and construct UPBs of different large sizes in $\mathbb{C}^m\otimes\mathbb{C}^n$ for any $n\geq m\geq 3$. This solves an open problem in [S. Halder et al., Phys. Rev. A 99, 062329 (2019)]. As an application, we show that our UPBs of size $(mn-4\lfloor

Tran Thi Phuong, Le Trieu Phong

We show that the convergence proof of a recent algorithm called dist-EF-SGD for distributed stochastic gradient descent with communication efficiency using error-feedback of Zheng et al. (NeurIPS 2019) is problematic mathematically. Concretely, the original error bound for arbitrary sequences of learning rate is unfortunately incorrect, leading to an invalid

Guan-Ying Wang, Man-Yu Duan, En Wang, De-Min Li

We have analyzed the reaction $χ_{c0}\to \bar{p} K^+Λ$ reported by the BESIII Collaboration, taking into account the contributions from the intermediate $K(1830)$, $N(2300)$, and $Λ(1520)$ resonances. Our results are in good agreement with the BESIII measurements, and it is found that the anomalous enhancement near the $\bar{p}Λ$ threshold is mainly due to t

Yihe Dong, Will Sawin

We introduce COPT, a novel distance metric between graphs defined via an optimization routine, computing a coordinated pair of optimal transport maps simultaneously. This gives an unsupervised way to learn general-purpose graph representation, applicable to both graph sketching and graph comparison. COPT involves simultaneously optimizing dual transport plan

Yang Liu, Wendi Ma, Hui-Hui Dai

In this paper, the two-dimensional pure bending of a hyperelastic substrate coated by a nematic liquid crystal elastomer (abbreviated as NLCE) is studied within the framework of nonlinear elasticity. The governing system, arising from the deformational momentum balance, the orientational momentum balance and the mechanical constraint, is formulated, and the

Hendrik Ranocha, Jan Nordström

Since integration by parts is an important tool when deriving energy or entropy estimates for differential equations, one may conjecture that some form of summation by parts (SBP) property is involved in provably stable numerical methods. This article contributes to this topic by proposing a novel class of $A$ stable SBP time integration methods which can al

Yong Liu, Lizhong Ding, Weiping Wang

In this paper, we study the statistical properties of kernel $k$-means and obtain a nearly optimal excess clustering risk bound, substantially improving the state-of-art bounds in the existing clustering risk analyses. We further analyze the statistical effect of computational approximations of the Nyström kernel $k$-means, and prove that it achieves the sam

Oliver M. Cliff, Leonardo Novelli, Ben D. Fulcher, James M. Shine

Inferring linear dependence between time series is central to our understanding of natural and artificial systems. Unfortunately, the hypothesis tests that are used to determine statistically significant directed or multivariate relationships from time-series data often yield spurious associations (Type I errors) or omit causal relationships (Type II errors)

Ryan J. Tibshirani

This paper reviews a class of univariate piecewise polynomial functions known as discrete splines, which share properties analogous to the better-known class of spline functions, but where continuity in derivatives is replaced by (a suitable notion of) continuity in divided differences. As it happens, discrete splines bear connections to a wide array of deve

Jun-Muk Hwang

Nirenberg and Spencer posed the question whether the germ of a compact complex submanifold in a complex manifold is determined by its infinitesimal neighborhood of finite order when the normal bundle is sufficiently positive. To study the problem for a larger class of submanifolds, including free rational curves, we reformulate the question in the setting of

Yong Liu, Lizhong Ding, Weiping Wang

Theoretical analysis of the divide-and-conquer based distributed learning with least square loss in the reproducing kernel Hilbert space (RKHS) have recently been explored within the framework of learning theory. However, the studies on learning theory for general loss functions and hypothesis spaces remain limited. To fill the gap, we study the risk perform

Ben Boukai

Trading option strangles is a highly popular strategy often used by market participants to mitigate volatility risks in their portfolios. In this paper we propose a measure of the relative value of a delta-Symmetric Strangle and compute it under the standard Black-Scholes option pricing model. This new measure accounts for the price of the strangle, relative

Da-Wu Xiao, Wen-Hui Hu, Yunfeng Cai, Nan Zhao

The discovery of magnetic protein provides a new understanding of a biocompass at the molecular level. However, the mechanism by which magnetic protein enables a biocompass is still under debate, mainly because of the absence of permanent magnetism in the magnetic protein at room temperature. Here, based on a widely accepted radical pair model of a biocompas

Éva Czabarka, Trevor Olsen, Stephen Smith, László A. Székely

The Wiener index of a connected graph is the sum of the distances between all unordered pairs of vertices. We provide formulae for the minimum Wiener index of simple triangulations and quadrangulations with connectivity at least $c$, and provide the extremal structures, which attain those values. Our main tool is setting upper bounds for the maximum degree i

Yoji Yamato

In the recent years, systems using FPGAs, GPUs have increased due to their advantages such as power efficiency compared to CPUs. However, use in systems such as FPGAs and GPUs requires understanding hardware-specific technical specifications such as HDL and CUDA, which is a high hurdle. Based on this background, I previously proposed environment adaptive sof

Varun Bhatt, Shalini Shrivastava, Tanmay Chavan, Udayan Ganguly

The in-memory computing paradigm with emerging memory devices has been recently shown to be a promising way to accelerate deep learning. Resistive processing unit (RPU) has been proposed to enable the vector-vector outer product in a crossbar array using a stochastic train of identical pulses to enable one-shot weight update, promising intense speed-up in ma

Syed Muhammad Usman, Shahzad Latif, Arshad Beg

Epilepsy is a disease in which frequent seizures occur due to abnormal activity of neurons. Patients affected by this disease can be treated with the help of medicines or surgical procedures. However, both of these methods are not quite useful. The only method to treat epilepsy patients effectively is to predict the seizure before its onset. It has been obse

Dongbi Bai, Minh Hoa Huynh, David A. Simpson, Philipp Reineck

Diamond containing the negatively charged nitrogen-vacancy (NV) center is emerging as a significant new system for magnetometry. However, most NV sensors require microscopes to collect the fluorescence signals and are therefore limited to laboratory settings. By incorporating micron-scale diamond particles at an annular interface within the cross section of

Victoria H. J. Clark, Alec Owens, Jonathan Tennyson, Sergei N. Yurchenko

A rotation-vibration line list for the electronic ground state ($\tilde{X}^{1}A_{1}$) of SiH$_2$ is presented. The line list, named CATS, is suitable for temperatures up to 2000 K and covers the wavenumber range 0 - 10,000 cm$^{-1}$(wavelengths $>1.0$ $μ$m) for states with rotational excitation up to $J=52$. Over 310 million transitions between 593 804 energ

Alp Öktem, Mirko Plitt, Grace Tang

We report our experiments in building a domain-specific Tigrinya-to-English neural machine translation system. We use transfer learning from other Ge'ez script languages and report an improvement of 1.3 BLEU points over a classic neural baseline. We publish our development pipeline as an open-source library and also provide a demonstration application.

Xixi Zhou, Chengxi Li, Jiajun Bu, Chengwei Yao

Text matching is a core natural language processing research problem. How to retain sufficient information on both content and structure information is one important challenge. In this paper, we present a neural approach for general-purpose text matching with deep mutual information estimation incorporated. Our approach, Text matching with Deep Info Max (TIM

Radomir Popović, Florian Lemmerich, Markus Strohmaier

Bias in Word Embeddings has been a subject of recent interest, along with efforts for its reduction. Current approaches show promising progress towards debiasing single bias dimensions such as gender or race. In this paper, we present a joint multiclass debiasing approach that is capable of debiasing multiple bias dimensions simultaneously. In that direction

Gal Levy-Fix, Jason Zucker, Konstantin Stojanovic, Noémie Elhadad

Identifying a patient's key problems over time is a common task for providers at the point care, yet a complex and time-consuming activity given current electric health records. To enable a problem-oriented summarizer to identify a patient's comprehensive list of problems and their salience, we propose an unsupervised phenotyping approach that jointl

Hyunji Chung, Jungheum Park, Sangjin Lee

In recent years, as electronic files include personal records and business activities, these files can be used as important evidences in a digital forensic investigation process. In general, the data that can be verified using its own application programs is largely used in the investigation of document files. However, in the case of the PDF file that has be

Laura Rieger, Lars Kai Hansen

The adoption of machine learning in health care hinges on the transparency of the used algorithms, necessitating the need for explanation methods. However, despite a growing literature on explaining neural networks, no consensus has been reached on how to evaluate those explanation methods. We propose IROF, a new approach to evaluating explanation methods th

Dom Huh, Sai Gurrapu, Frederick Olson, Huzefa Rangwala

With advancements in deep model architectures, tasks in computer vision can reach optimal convergence provided proper data preprocessing and model parameter initialization. However, training on datasets with low feature-richness for complex applications limit and detriment optimal convergence below human performance. In past works, researchers have provided

Diogo Lopes, António Ramires Fernandes, Stéphane Clain

There are several numerical models that describe real phenomena being used to solve complex problems. For example, an accurate numerical breast model can provide assistance to surgeons with visual information of the breast as a result of a surgery simulation. The process of finding the model parameters requires numeric inputs, either based in medical imaging

Sumeet Kumar, M. Gunaseelan, Rahul Vaippully, Amrendra Kumar

3D pitch rotation of microparticles and cells assumes importance in a wide variety of applications in biology, physics, chemistry and medicine. Applications such as cell imaging and injection benefit from pitch-rotational manipulation. Generation of such motion in single beam optical tweezers has remained elusive due to complicacies of generating high enough

Nikolai Kubochkin, Joachim Venzmer, Tatiana Gambaryan-Roisman

Nanofluids hold promise for a wide range of areas of industry. However, understanding of wetting behavior and deposition formation in course of drying and spreading of nanofluids, particularly containing surfactants, is still poor. In this paper, the evaporation dynamics of quantum dot-based nanofluids and evaporation-driven self-assembly in nanocolloidal su

Christopher Roth

Modeling quantum many-body systems is enormously challenging due to the exponential scaling of Hilbert dimension with system size. Finding efficient compressions of the wavefunction is key to building scalable models. Here, we introduce iterative retraining, an approach for simulating bulk quantum systems that uses recurrent neural networks (RNNs). By mappin

Ting-Yao Hu, Ashish Shrivastava, Oncel Tuzel, Chandra Dhir

We present a method to generate speech from input text and a style vector that is extracted from a reference speech signal in an unsupervised manner, i.e., no style annotation, such as speaker information, is required. Existing unsupervised methods, during training, generate speech by computing style from the corresponding ground truth sample and use a decod

Nathan Hagen

Textbooks in physics use science history to humanize the subject and motivate students for learning, but they deal exclusively with the heroes of the field and ignore the vast majority of scientists who have not found their way into history. What is the role of these invisible scientists --- are they merely the worker ants in the colony of science, whose mai

Jan Portisch, Michael Hladik, Heiko Paulheim

In this paper, we present KGvec2go, a Web API for accessing and consuming graph embeddings in a light-weight fashion in downstream applications. Currently, we serve pre-trained embeddings for four knowledge graphs. We introduce the service and its usage, and we show further that the trained models have semantic value by evaluating them on multiple semantic b

V. Krasnoselskikh, A. Larosa, O. Agapitov, T. Dudok de Wit

One of the discoveries made by Parker Solar Probe during first encounters with the Sun is the ubiquitous presence of relatively small-scale structures standing out as sudden deflections of the magnetic field. They were called switchbacks as some of them show up the full reversal of the radial component of the magnetic field and then return to regular conditi

Fenglei Zhang, Kui Liu, Zongyang Li, Xiaohua Feng

Large-scale high sensitivity laser gyroscopes have important applications for ground-based and space-based gravitational wave detection. We report on the development of a 3 m$\times$3 m heterolithic passive resonant gyroscope (HUST-1) which is installed on the ground of a cave laboratory. We operate the HUST-1 on different longitudinal cavity modes and the r

Svetlin G. Georgiev, Goverdan Khadekar, Praveen Kumar

In this paper, we formulate and prove Wendroff's inequalities on time scales. Next, we deduct some of Pachpatte's inequalities.

Marek Berezowski

In the paper the distribution of prime numbers and digits of $π$ were presented as chaotic.

Chi-Chun Zhou, Ping Zhang, Wu-Sheng Dai

A Brownian particle in an ideal quantum gas is considered. The mean square displacement (MSD) is derived. The Bose-Einstein or Fermi-Dirac distribution, other than the Maxwell-Boltzmann distribution, provides a different stochastic force compared with the classical Brownian motion. The MSD, which depends on the thermal wavelength and the density of medium pa

Tom F. H. Runia, Kirill Gavrilyuk, Cees G. M. Snoek, Arnold W. M. Smeulders

For many of the physical phenomena around us, we have developed sophisticated models explaining their behavior. Nevertheless, measuring physical properties from visual observations is challenging due to the high number of causally underlying physical parameters -- including material properties and external forces. In this paper, we propose to measure latent

Maria Bortos, Joe Gildea, Abidin Kaya, Adrian Korban

Many generator matrices for constructing extremal binary self-dual codes of different lengths have the form G=(I|A), where I is the n by n identity matrix and A is the n by n matrix fully determined by the first row. In this work, we define a generator matrix in which A is a block matrix, where the blocks come from group rings and also, A is not fully determ

Sara Morsy, George Karypis

Grade prediction for future courses not yet taken by students is important as it can help them and their advisers during the process of course selection as well as for designing personalized degree plans and modifying them based on their performance. One of the successful approaches for accurately predicting a student's grades in future courses is Cumula

Cs. Vincze, M. Oláh, L. M. Alabdulsada

In the paper we consider Riemannian surfaces admitting a global expression of the Gauss curvature as the divergence of a vector field. It is equivalent to the existence of a metric linear connection of zero curvature. Such a linear connection $\nabla$ plays an important role in the differential geometry of non-Riemannian surfaces in the sense that the Rieman

Shahariar Sarkar, Pawan Kumar, Kanhaiya Jha, P. K. Raina

In the present work, we examine the role of central (C), spin-orbit (SO) and tensor (T) components of two-nucleon interaction in the nuclear matrix elements (NMEs) of the two-neutrino double beta decay ($2νββ$) and the light neutrino-exchange mechanism of neutrinoless double beta decay ($0νββ$) of $^{48}$Ca in closure approximation and nonclosure approach. T

A M Ishtiaque Mahbub, Andreas A. Malikopoulos, Liuhui Zhao

Connected and automated vehicles (CAVs) provide the most intriguing opportunity to optimize energy consumption and travel time. Several approaches have been proposed in the literature that allow CAVs to coordinate in situations where there is a potential conflict, for example, in signalized intersections, merging at roadways and roundabouts, to reduce energy

Nitish Mital, Deniz Gunduz, Cong Ling

Cache-aided content delivery is studied in a multi-server system with $P$ servers and $K$ users, each equipped with a local cache memory. In the delivery phase, each user connects randomly to any $ρ$ out of $P$ servers. Thanks to the availability of multiple servers, which model small-cell base stations (SBSs), demands can be satisfied with reduced storage c

Jean-Paul Caltagirone, Stephane Vincent

Discrete mechanics makes it possible to formulate any problem of fluid mechanics or fluid-structure interaction in velocity and potentials of acceleration; the equation system consists of a single vector equation and potentials updates. The scalar potential of the acceleration represents the pressure stress and the vector potential is related to the rotation

Yatin A. Manerkar, Daniel Lustig, Margaret Martonosi

Modern SoCs are heterogeneous parallel systems comprised of components developed by distinct teams and possibly even different vendors. The memory consistency model (MCM) of processors in such SoCs specifies the ordering rules which constrain the values that can be read by load instructions in parallel programs running on such systems. The implementation of

Nima Salek Gilani, Mohammad Tavakoli Bina, Fatemeh Rahmani, Mahmood Hosseini Imani

In this study, the problem of fault zone detection of distance relaying in FACTS-based transmission lines is analyzed. Existence of FACTS devices on the transmission line, when they are included in the fault zone, from the distance relay point of view, causes different problems in determining the exact location of the fault by changing the impedance seen by

Giuseppe De Vito, Paola Parlanti, Roberta Cecchi, Stefano Luin

When live imaging is not feasible, sample fixation allows preserving the ultrastructure of biological samples for subsequent microscopy analysis. This process could be performed with various methods, each one affecting differently the biological structure of the sample. While these alterations were well-characterized using traditional microscopy, little info

Eren Simsek

This paper will attempt to show that the Doppler principle was of major relevance to Einstein for the genesis of the special theory of relativity.

Hatoon S. AlSagri, Mourad Ykhlef

Social media channels, such as Facebook, Twitter, and Instagram, have altered our world forever. People are now increasingly connected than ever and reveal a sort of digital persona. Although social media certainly has several remarkable features, the demerits are undeniable as well. Recent studies have indicated a correlation between high usage of social me

Vladimir García-Morales, Javier Cervera, José A. Manzanares

The binary radix expansion of a real number can be used to code the outcome of any series of coin tosses, a fact that provides an intriguing link between number theory, measure theory and statistical physics. Inspired by this fact, a general result is established for the definite integral of a differentiable function of a single variable that allows any such

Xiaobo Zhang, Donghai Zhai, Yan Yang, Yiling Zhang

In recent years, there are many research cases for the diagnosis of Parkinson's disease (PD) with the brain magnetic resonance imaging (MRI) by utilizing the traditional unsupervised machine learning methods and the supervised deep learning models. However, unsupervised learning methods are not good at extracting accurate features among MRIs and it is di

Mouktar Bello, Wenjuan Yu, Arsenia Chorti, Leila Musavian

In the fifth generation and beyond (B5G), delayconstraints emerge as a topic of particular interest, e.g. forultra-reliable low latency communications (URLLC) such asautonomous vehicles and enhanced reality. In this paper, westudythe performance of a two-user uplink NOMA network understatistical quality of service (QoS) delay constraints, capturedthrough eac

Jailton Coelho, Marco Tulio Valente, Luciano Milen, Luciana L. Silva

Context: GitHub hosts an impressive number of high-quality OSS projects. However, selecting "the right tool for the job" is a challenging task, because we do not have precise information about those high-quality projects. Objective: In this paper, we propose a data-driven approach to measure the level of maintenance activity of GitHub projects. Our g

S. M. Ghoreyshi, M. Shadmehri

Observational evidence and theoretical arguments postulate that outflows may play a significant role in the advection-dominated accretion discs (ADAFs). While the azimuthal viscosity is the main focus of most previous studies in this context, recent studies indicated that disc structure can also be affected by the radial viscosity. In this work, we incorpora

Rodica Dinu, Martin Vodička

We study the Gorenstein property for phylogenetic group-based models. We prove that for the groups $\mathbb Z_3$ and $\mathbb Z_2\times \mathbb Z_2$ and trivalent trees the associated polytopes are always Gorenstein extending the results of Buczyńska and Wiśniewski for the group $\mathbb Z_2$.

Davoud Mougouei

The existing software requirement selection methods have mainly focused on optimizing the economic value of a software product while ignoring its social values and their long-term impacts on the society. Social values however, are also important and need to be taken into account in software requirement selection. Moreover, social values of software requireme

Alessandro Oltramari, Jonathan Francis, Cory Henson, Kaixin Ma

Computational context understanding refers to an agent's ability to fuse disparate sources of information for decision-making and is, therefore, generally regarded as a prerequisite for sophisticated machine reasoning capabilities, such as in artificial intelligence (AI). Data-driven and knowledge-driven methods are two classical techniques in the pursui

Dong-Hun Chae, Mun-Seog Kim, Wan-Seop Kim, Takehiko Oe

Accurate measurement of the electric current requires a stable and calculable resistor for an ideal current to voltage conversion. However, the temporal resistance drift of a physical resistor is unavoidable, unlike the quantum Hall resistance directly linked to the Planck constant h and the elementary charge e. Lack of an invariant high resistance leads to

Sarah Bird, Vikas Mishra, Steven Englehardt, Rob Willoughby

As online tracking continues to grow, existing anti-tracking and fingerprinting detection techniques that require significant manual input must be augmented. Heuristic approaches to fingerprinting detection are precise but must be carefully curated. Supervised machine learning techniques proposed for detecting tracking require manually generated label-sets.

John W. Simpson-Porco

Distributed consensus-based controllers for optimal secondary frequency regulation of microgrids and power systems have received substantial attention in recent years. This paper provides a Lyapunov-based proof that, under a time-scale separation, these control schemes are stabilizing for a wide class of nonlinear power system models, and under weak assumpti

Mark Wagner, Yongsung Park, Peter Gerstoft

The problem of gridless direction of arrival (DOA) estimation is addressed in the non-uniform array (NUA) case. Traditionally, gridless DOA estimation and root-MUSIC are only applicable for measurements from a uniform linear array (ULA). This is because the sample covariance matrix of ULA measurements has Toeplitz structure, and both algorithms are based on

Yong Sun, Zhi-Gang Wang, Antti Rasila, Janusz Sokol

In this paper, we consider a subclass of starlike functions associated with a vertical strip domain. Several results concerned with integral representations, convolutions, and coefficient inequalities for functions belonging to this class are obtained. Furthermore, we consider radius problems and inclusion relations involving certain classes of strongly star

Zhi-Gang Wang, Lei Shi, Yue-Ping Jiang

In the present paper, we derive several conditions of linear combinations and convolutions of harmonic mappings to be univalent and convex in one direction, one of them gives a partial answer to an open problem proposed by Dorff. The results presented here provide extensions and improvements of those given in some earlier works. Several examples of univalent

Hyunjun Eun, Daeyeong Kim, Chanho Jung, Changick Kim

Background and Objective: In pulmonary nodule detection, the first stage, candidate detection, aims to detect suspicious pulmonary nodules. However, detected candidates include many false positives and thus in the following stage, false positive reduction, such false positives are reliably reduced. Note that this task is challenging due to 1) the imbalance b

Chuanqi Xiao, Gyula O. H. Katona

By the theorem of Mantel $[5]$ it is known that a graph with $n$ vertices and $\lfloor \frac{n^{2}}{4} \rfloor+1$ edges must contain a triangle. A theorem of Erdős gives a strengthening: there are not only one, but at least $\lfloor\frac{n}{2}\rfloor$ triangles. We give a further improvement: if there is no vertex contained by all triangles then there are at

Manuel Cortés-Izurdiaga, Pedro A. Guil Asensio, Berke Kalebogaz, Ashish K. Srivastava

We develop a general theory of partial morphisms in additive exact categories which extends the model theoretic notion introduced by Ziegler in the particular case of pure-exact sequences in the category of modules over a ring. We relate partial morphisms with (co-)phantom morphisms and injective approximations and study the existence of such approximations

Shivam Gautam, Gregory P. Meyer, Carlos Vallespi-Gonzalez, Brian C. Becker

Accurate motion state estimation of Vulnerable Road Users (VRUs), is a critical requirement for autonomous vehicles that navigate in urban environments. Due to their computational efficiency, many traditional autonomy systems perform multi-object tracking using Kalman Filters which frequently rely on hand-engineered association. However, such methods fail to

Yves Achdou, Mathieu Laurière

The theory of mean field games aims at studying deterministic or stochastic differential games (Nash equilibria) as the number of agents tends to infinity. Since very few mean field games have explicit or semi-explicit solutions, numerical simulations play a crucial role in obtaining quantitative information from this class of models. They may lead to system

Tatsuya Miyazaki, Masato Takei

We consider a minimal model of one-dimensional discrete-time random walk with step-reinforcement, introduced by Harbola, Kumar, and Lindenberg (2014): The walker can move forward (never backward), or remain at rest. For each $n=1,2,\cdots$, a random time $U_n$ between $1$ and $n$ is chosen uniformly, and if the walker moved forward [resp. remained at rest] a

Federico Giaimo, Hugo Andrade, Christian Berger

Recently, an increasingly growing number of companies is focusing on achieving self-driving systems towards SAE level 3 and higher. Such systems will have much more complex capabilities than today's advanced driver assistance systems (ADAS) like adaptive cruise control and lane-keeping assistance. For complex software systems in the Web-application domai

J. O. Cunha, H. H. Kramer, R. A. Melo

Production and inventory planning have become crucial and challenging in nowadays competitive industrial and commercial sectors, especially when multiple plants or warehouses are involved. In this context, this paper addresses the complexity of uncapacitated multi-plant lot-sizing problems. We consider a multi-item uncapacitated multi-plant lot-sizing proble

Yani Zhao, Manjesh K. Singh, Kurt Kremer, Robinson Cortes-Huerto

The solvent quality determines the collapsed or the expanded state of a polymer. For example, a polymer dissolved in a poor solvent collapses, whereas in a good solvent it opens up. While this standard understanding is generally valid, there are examples when a polymer collapses even in a mixture of two good solvents. This phenomenon, commonly known as co-no

Pieter B. Smit, Isabel A. Houghton, Kalina Jordanova, Thomas Portwood

In-situ ocean wave observations are critical to improve model skill and validate remote sensing wave measurements. Historically, such observations are extremely sparse due to the large costs and complexity of traditional wave buoys and sensors. In this work, we present a recently deployed network of free-drifting satellite-connected surface weather buoys tha

K. R. Goodearl, M. T. Yakimov

We prove a general theorem for constructing integral quantum cluster algebras over ${\mathbb{Z}}[q^{\pm 1/2}]$, namely that under mild conditions the integral forms of quantum nilpotent algebras always possess integral quantum cluster algebra structures. These algebras are then shown to be isomorphic to the corresponding upper quantum cluster algebras, again

Francesco Fanelli, Eduard Feireisl

We introduce a new concept of statistical solution in the framework of weak solutions to the barotropic Navier--Stokes system with inhomogeneous boundary conditions. Statistical solution is a family $\{ M_t \}_{t \geq 0}$ of Markov operators on the set of probability measures $\mathfrak{P}[\mathcal{D}]$ on the data space $\mathcal{D}$ containing the initial

Yan Zhang, Michael M. Zavlanos

In this paper, we study a transfer reinforcement learning problem where the state transitions and rewards are affected by the environmental context. Specifically, we consider a demonstrator agent that has access to a context-aware policy and can generate transition and reward data based on that policy. These data constitute the experience of the demonstrator

Christos Karapapas, Iakovos Pittaras, Nikos Fotiou, George C. Polyzos

Decentralized systems, such as distributed ledgers and the InterPlanetary File System (IPFS), are designed to offer more open and robust services. However, they also create opportunities for illegal activities. We demonstrate how these technologies can be used to launch a ransomware as a service campaign. We show that criminals can transact with affiliates a

Umut Çetin, Henri Waelbroeck

We propose a static equilibrium model for limit order book where profit-maximizing investors receive an information signal regarding the liquidation value of the asset and execute via a competitive dealer with random initial inventory, who trades against a competitive limit order book populated by liquidity suppliers. We show that an equilibrium exists for b

Andrew T. Barker, Stephan V. Gelever, Chak S. Lee, Sarah V. Osborn

We extend previously developed two-level coarsening procedures for graph Laplacian problems written in a mixed saddle point form to the fully recursive multilevel case. The resulting hierarchy of discretizations gives rise to a hierarchy of upscaled models, in the sense that they provide approximation in the natural norms (in the mixed setting). This propert

Zhao-Qian Yao, Daniele Binosi, Zhu-Fang Cui, Craig D. Roberts

A symmetry-preserving continuum approach to meson bound-states in quantum field theory, employed elsewhere to describe numerous $π$- and $K$-meson electroweak processes, is used to analyse leptonic and semileptonic decays of $D_{(s)}$ mesons. Each semileptonic transition is conventionally characterised by the value of the dominant form factor at $t=0$ and th

Joel Merker, Jean-Jacques Szczeciniarz

The statement of the Gauss-Bonnet theorem brings up an unexpected form of reflexivity (major concept of philosophy of mathematics), so that geometry contemplates itself in it. It is therefore the revolutionary and multifaceted concept of Gaussian curvature that triggers a new conceptuality above Euclidean geometry. Here, the equality between integral of tota

Fernando Nieto-Guadarrama, Jorge Villavicencio

We explore the dynamics of relativistic quantum waves in a potential step by using an exact solution to the Klein-Gordon equation with a point source initial condition. We show that in both the propagation, and Klein-tunneling regimes, the Zitterbewegung effect manifests itself as a series of quantum beats of the particle density in the long-time limit. We d