April 2020 arXiv papers — page 31

A. M. Escobar-Ruiz, R. Linares, P. Winternitz

A study is presented of superintegrable quantum systems in two-dimensional Euclidean space $E_2$ allowing the separation of variables in Cartesian coordinates. In addition to the Hamiltonian $H$ and the second order integral of motion $X$, responsible for the separation of variables, they allow a third integral that is a polynomial of order $N\, (N\geq3)$ in

Chuadhry Mujeeb Ahmed, Jay Prakash, Jianying Zhou

In an Industrial Control System (ICS), its complex network of sensors, actuators and controllers have raised security concerns for critical infrastructures and industrial production units. This opinion paper strives to initiate discussion on the design algorithms which can segregate attacks from faults. Most of the proposed anomaly detection mechanisms are n

Andreas Mihatsch

We prove that, in certain situations, intersection numbers on formal schemes that come in profinite families vary locally constantly in the parameter. To this end, we define the product $S\times M$ of a profinite set $S$ with a locally noetherian formal scheme $M$ and study intersections thereon. Our application is to the Arithmetic Fundamental Lemma of W. Z

Mani A, Sandor Radeleczki

In relational approach to general rough sets, ideas of directed relations are supplemented with additional conditions for multiple algebraic approaches in this research paper. The relations are also specialized to representations of general parthood that are upper-directed, reflexive and antisymmetric for a better behaved groupoidal semantics over the set of

Fatemeh Azimi, Benjamin Bischke, Sebastian Palacio, Federico Raue

Video Object Segmentation (VOS) is an active research area of the visual domain. One of its fundamental sub-tasks is semi-supervised / one-shot learning: given only the segmentation mask for the first frame, the task is to provide pixel-accurate masks for the object over the rest of the sequence. Despite much progress in the last years, we noticed that many

Sheena Panthaplackel, Pengyu Nie, Milos Gligoric, Junyi Jessy Li

We formulate the novel task of automatically updating an existing natural language comment based on changes in the body of code it accompanies. We propose an approach that learns to correlate changes across two distinct language representations, to generate a sequence of edits that are applied to the existing comment to reflect the source code modifications.

Dirk van der Linden

This article introduces a new class of socio-technical systems, interspecies information systems (IIS) by describing several examples of these systems emerging through the use of commercially available data-driven animal-centered technology. When animal-centered technology, such as pet wearables, cow health monitoring, or even wildlife drones captures animal

Nicholas Bender, Alexey Yamilov, Hasan Yilmaz, Hui Cao

Selective excitation of a diffusive system's transmission eigenchannels enables manipulation of its internal energy distribution. The fluctuations and correlations of the eigenchannels' spatial profiles, however, remain unexplored so far. Here we show that the depth profiles of high-transmission eigenchannels exhibit low realization-to-realization fluctuatio

Édouard Bonnet, Stéphan Thomassé, Xuan Thang Tran, Rémi Watrigant

We study the approximability of the Maximum Independent Set (MIS) problem in $H$-free graphs (that is, graphs which do not admit $H$ as an induced subgraph). As one motivation we investigate the following conjecture: for every fixed graph $H$, there exists a constant $\delta > 0$ such that MIS can be $n^{1 - \delta}$-approximated in $H$-free graphs, where $n

Andras Palffy, Jiaao Dong, Julian F. P. Kooij, Dariu M. Gavrila

This letter presents a novel radar based, single-frame, multi-class detection method for moving road users (pedestrian, cyclist, car), which utilizes low-level radar cube data. The method provides class information both on the radar target- and object-level. Radar targets are classified individually after extending the target features with a cropped block of

Xiao Guo, Yixuan Qiu, Hai Zhang, Xiangyu Chang

Directed networks are broadly used to represent asymmetric relationships among units. Co-clustering aims to cluster the senders and receivers of directed networks simultaneously. In particular, the well-known spectral clustering algorithm could be modified as the spectral co-clustering to co-cluster directed networks. However, large-scale networks pose great

Ignasi Reichardt, Jordi Pallares Marta Sales-Pardo, Roger Guimera

Ever since Nikuradse's experiments on turbulent friction in 1933, there have been theoretical attempts to describe his measurements by collapsing the data into single-variable functions. However, this approach, which is common in other areas of physics and in other fields, is limited by the lack of rigorous quantitative methods to compare alternative data co

David Holtz, Sinan Aral

In an A/B test, the typical objective is to measure the total average treatment effect (TATE), which measures the difference between the average outcome if all users were treated and the average outcome if all users were untreated. However, a simple difference-in-means estimator will give a biased estimate of the TATE when outcomes of control units depend on

Liwei Huang, Yutao Ma, Yanbo Liu, Keqing He

Next (or successive) point-of-interest (POI) recommendation has attracted increasing attention in recent years. Most of the previous studies attempted to incorporate the spatiotemporal information and sequential patterns of user check-ins into recommendation models to predict the target user's next move. However, none of these approaches utilized the social

José C. Bellido, Alejandro Ortega

In this work we introduce volume constraint problems involving the nonlocal operator $(-\Delta)_{\delta}^{s}$, closely related to the fractional Laplacian $(-\Delta)^{s}$, and depending upon a parameter $\delta>0$ called horizon. We study the associated linear and spectral problems and the behavior of these volume constraint problems when $\delta\to0^+$ and

Mike Thelwall, Amalia Mas-Bleda

Current attempts to address the shortfall of female researchers in Science, Technology, Engineering and Mathematics (STEM) have not yet succeeded despite other academic subjects having female majorities. This article investigates the extent to which gender disparities are subject-wide or nation-specific by a first author gender comparison of 30 million artic

Haoxi Zhong, Chaojun Xiao, Cunchao Tu, Tianyang Zhang

Legal Artificial Intelligence (LegalAI) focuses on applying the technology of artificial intelligence, especially natural language processing, to benefit tasks in the legal domain. In recent years, LegalAI has drawn increasing attention rapidly from both AI researchers and legal professionals, as LegalAI is beneficial to the legal system for liberating legal

Roger Guimera, Ignasi Reichardt, Antoni Aguilar-Mogas, Francesco A Massucci

Closed-form, interpretable mathematical models have been instrumental for advancing our understanding of the world; with the data revolution, we may now be in a position to uncover new such models for many systems from physics to the social sciences. However, to deal with increasing amounts of data, we need "machine scientists" that are able to extract these

Cédric Join, Michel Fliess, Frédéric Chaxel

Model-Free Control (MFC), which is easy to implement both from software and hardware viewpoints, permits the introduction of a high level control synthesis for the Industrial Internet of Things (IIoT) and the Industry 4.0. The choice of the User Diagram Protocol (UDP) as the Internet Protocol permits to neglect the latency. In spite of most severe packet los

Shi-Ping He

With the deeper study of Higgs particle, Higgs precision measurements can be served to probe new physics indirectly. In many new physics models, vector-like quarks $T_L,~T_R$ occur naturally. It is important to probe their couplings with standard model particles. In this work, we consider the singlet $T_L,~T_R$ extended models and show how to constrain the $

Keisuke Fujii, Yusuke Nishida

The bulk viscosity of two-component fermions with a zero-range interaction is revisited both in two and three dimensions. We first point out that the "standard" Kubo formula employed in recent studies has flaws to give rise to an unphysical divergent bulk viscosity even in a limit where it is supposed to vanish. The corrected Kubo formula as well as the sum

Huayang Chen, Alan Haynes

In this paper we investigate the problem of how well points in finite dimensional p-adic solenoids can be approximated by rationals. The setting we work in was previously studied by Palmer, who proved analogues of Dirichlet's theorem and the Duffin-Schaeffer theorem. We prove a complementary result, showing that the set of badly approximable points has maxim

Briti Gangopadhyay, Somnath Hazra, Pallab Dasgupta

Human vision is able to compensate imperfections in sensory inputs from the real world by reasoning based on prior knowledge about the world. Machine learning has had a significant impact on computer vision due to its inherent ability in handling imprecision, but the absence of a reasoning framework based on domain knowledge limits its ability to interpret c

Sergio Cobo-Lopez, Antonia Godoy-Lorite, Jordi Duch, Marta Sales-Pardo

Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to evaluate their merit and, thus, to help establish which mechanisms are most plausible. Here, we propose models and deve

Xiaozheng Xie, Jianwei Niu, Xuefeng Liu, Zhengsu Chen

Although deep learning models like CNNs have achieved great success in medical image analysis, the small size of medical datasets remains a major bottleneck in this area. To address this problem, researchers have started looking for external information beyond current available medical datasets. Traditional approaches generally leverage the information from

E. David, S. Madec, P. Sadeghi-Tehran, H. Aasen

Detection of wheat heads is an important task allowing to estimate pertinent traits including head population density and head characteristics such as sanitary state, size, maturity stage and the presence of awns. Several studies developed methods for wheat head detection from high-resolution RGB imagery. They are based on computer vision and machine learnin

Liang Kong, Xiao-Gang Wen

A bosonic topological order on $d$-dimensional closed space $\Sigma^d$ may have degenerate ground states. The space $\Sigma^d$ with different shapes (different metrics) form a moduli space ${\cal M}_{\Sigma^d}$. Thus the degenerate ground states on every point in the moduli space ${\cal M}_{\Sigma^d}$ form a complex vector bundle over ${\cal M}_{\Sigma^d}$.

E. Molnár, I. Prok, J. Szirmai

In our Novi Sad conference paper (1999) we described Dehn type surgeries of the famous Gieseking (1912) hyperbolic ideal simplex manifold $\mathcal{S}$, leading to compact fundamental domain $\mathcal{S}(k)$, $k = 2, 3, \dots$ with singularity geodesics of rotation order $k$, but as later turned out with cone angle $2(k-1)/k$. We computed also the volume of

Daniel Plabst, Francisco Javier García Gómez, Thomas Wiegart, Norbert Hanik

Analytic expressions are derived for the Wiener filter (WF), also known as the linear minimum mean square error (LMMSE) estimator, for an intensity-modulation/direct-detection (IM/DD) short-haul fiber-optic communication system. The link is purely dispersive and the nonlinear square-law detector (SLD) operates at the thermal noise limit. The achievable rates

James E. Smith

A computational paradigm based on neuroscientific concepts is proposed and shown to be capable of online unsupervised clustering. Because it is an online method, it is readily amenable to streaming realtime applications and is capable of dynamically adjusting to macro-level input changes. All operations, both training and inference, are localized and efficie

Jack Saywell, Max Carey, Ilya Kuprov, Tim Freegarde

We present designs for the augmentation 'mirror' pulses of large-momentum-transfer atom interferometers that maintain their fidelity as the wavepacket momentum difference is increased. These bi-selective pulses, tailored using optimal control methods to the evolving bi-modal momentum distribution, should allow greater interferometer areas and hence increased

Yi Liu, Yue Tang, Ziqiao Wang, Chaofei Liu

Intriguing novel phenomena in lead films inspire new understanding of quantum physics, such as quantum size effect and quantum phase transitions etc. The improvement of the sample quality makes it even more promising to explore the intrinsic properties in two-dimensional system. In this paper, we show that the crystalline interfacial striped incommensurate l

Nils C. Geib, Richard Hollinger, Elissa Haddad, Paul Herrmann

In this work, we demonstrate a discrete dispersion scan scheme using a low number of flat windows to vary the dispersion of laser pulses in discrete steps. Monte Carlo simulations indicate that the pulse duration can be retrieved accurately with less than 10 dispersion steps, which we verify experimentally by measuring few-cycle pulses and material dispersio

Thomas Brocken, G. Wessel van der Heijden, Irina Kostitsyna, Lloyd E. Lo-Wong

In the problem of multi-robot motion planning, a group of robots, placed in a polygonal domain with obstacles, must be moved from their starting positions to a set of target positions. We consider the specific case of unlabeled disc robots of two different sizes. That is, within one class of robots, where a class is given by the robots' size, any robot can b

Yishu Wang, Arnaud Mary, Marie-France Sagot, Blerina Sinaimeri

When a problem has more than one solution, it is often important, depending on the underlying context, to enumerate (i.e., to list) them all. Even when the enumeration can be done in polynomial delay, that is, spending no more than polynomial time to go from one solution to the next, this can be costly as the number of solutions themselves may be huge, inclu

Taekyun Kim, Dae San Kim

The aim of this paper is twofold. The first one is to find several relations between the type 2 higher-order degenerate Euler polynomials and the type 2 higher-order Changhee polynomials in connection with the degenerate stirling numbers of both kinds and Jindalrae-stirling numbers of both kinds. The second one is to introduce the discrete harmonic numbers a

Léo Exibard, Emmanuel Filiot, Ayrat Khalimov

In a Church synthesis game, two players, Adam and Eve, alternately pick some element in a finite alphabet, for an infinite number of rounds. The game is won by Eve if the omega-word formed by this infinite interaction belongs to a given language S, called the specification. It is well-known that for omega-regular specifications, it is decidable whether Eve h

Fuad Noman, Ammar Al-Kahtani, Vassilios Agelidis, Sieh Kiong Tiong

The integration of large-scale wind farms and large-scale charging stations for electric vehicles with the electricity grids necessitate energy storage support for both technologies. Matching the energy variability of the wind farms with the demand variability of the electric vehicles (EVs) off-grid could potentially eliminate the need for expensive energy s

Pavel Surynek

Multi-agent path finding in continuous space and time with geometric agents MAPF$^\mathcal{R}$ is addressed in this paper. The task is to navigate agents that move smoothly between predefined positions to their individual goals so that they do not collide. We introduce a novel solving approach for obtaining makespan optimal solutions called SMT-CBS$^\mathcal

Feyi Olalotiti-Lawal, Shusei Tanaka, Akhil Datta-Gupta

Subsurface sequestration of CO2 has received attention from the global scientific community in response to climate change concerns due to higher concentrations of CO2 in the atmosphere. Mathematical models have thus been developed to aid the understanding of multiphase flow of CO2 and trapping mechanisms during subsurface sequestration. Solutions to these mo

Y. Brihaye, J. Renaux

The Einstein-Maxwell-Klein-Gordon Lagrangian is supplemented by a non-minimal coupling of the real scalar field to the Gauss-Bonnet invariant. The non minimal coupling function is chosen as a general second degree polynomial in the scalar field for which the system is known to admit hairy black holes. The new interaction leads naturally to a violation of the

Abolhassan Mohammadi, Tayeb Golanbari, Salah Nasri, Khaled Saaidi

The scenario of constant-roll inflation in the frame of the RSII brane gravity model is considered. Based on the scenario, the smallness of the second slow-roll parameter is released and it is assumed as a constant which could be of the order of unity. Applying the Hamilton-Jacobi formalism, the constancy of the parameter gives a differential equation for th

Benjamin F. Cooke, Don Pollacco

We set out a simulation to explore the follow-up of exoplanet candidates. We look at comparing photometric (transit method) and spectroscopic (Doppler shift method) techniques using three instruments: NGTS, HARPS and CORALIE. We take into account precision of follow-up and required observing time in attempt to rank each method for a given set of planetary sy

Aradhita Chattopadhyaya

In this paper we compute the gravitational couplings of the heterotic string compactified on $(K3\times T^2)/\mathbb{Z}_N$ and $E_8\times E_8$ and predict the Gopakumar Vafa invariants of the dual Calabi Yau manifold in presence of Wilson lines. Here $\mathbb{Z}_N$ acts as an automorphism on $K3$ associated with the conjugacy classes of $M_{23}$ and a shift

Ning Liu, Zhanchun Tu

The momentum distribution and dynamical structure factor in a weakly interacting Bose gas with a time-dependent periodic modulation in terms of the Bogoliubov treatment are investigated. The evolution equation related to the Bogoliubov weights happens to be a solvable Mathieu equation when the coupling strength is periodically modulated. An exact relation be

Nikolaos G. Antoniou, Nikolaos Davis, Fotios K. Diakonos, Georgios Doultsinos

In a systematic search for the QCD critical point in nuclear collisions, at the CERN SPS, it was found that intermittency measurements in the freeze-out state of central Si+Si collisions, at the maximum SPS energy, provide us with an indication of sizeable critical fluctuations. Also, rather recently, a weaker effect was traced in preliminary data of the Ar+

Robert Williams

With an initial requirement to make observations a minimum of 5-10 years, Hubble Space Telescope (HST) has continued to operate well for 30 years. It has relied upon five servicing missions to repair and replace essential components. Since the final Space Shuttle mission 10 years ago it has avoided major breaks in its operation, with the only serious effects

Moritz Geist, Philipp Petersen, Mones Raslan, Reinhold Schneider

We perform a comprehensive numerical study of the effect of approximation-theoretical results for neural networks on practical learning problems in the context of numerical analysis. As the underlying model, we study the machine-learning-based solution of parametric partial differential equations. Here, approximation theory predicts that the performance of t

Philip Nadler, Shuo Wang, Rossella Arcucci, Xian Yang

The global pandemic of the 2019-nCov requires the evaluation of policy interventions to mitigate future social and economic costs of quarantine measures worldwide. We propose an epidemiological model for forecasting and policy evaluation which incorporates new data in real-time through variational data assimilation. We analyze and discuss infection rates in

Nanzhe Wang, Haibin Chang, Dongxiao Zhang

Subsurface flow problems usually involve some degree of uncertainty. Consequently, uncertainty quantification is commonly necessary for subsurface flow prediction. In this work, we propose a methodology for efficient uncertainty quantification for dynamic subsurface flow with a surrogate constructed by the Theory-guided Neural Network (TgNN). The TgNN here i

Abel Brodeur, Andrew E. Clark, Sarah Fleche, Nattavudh Powdthavee

The COVID-19 pandemic has led many governments to implement lockdowns. While lockdowns may help to contain the spread of the virus, it is possible that substantial damage to population well-being will result. This study relies on Google Trends data and tests whether the lockdowns implemented in Europe and America led to changes in well-being related topic se

Yu-Xin Xin, Jin-Ming Bai, Bao-Li Lun, Yu-Feng Fan

We installed two sets of Astronomical Site Monitoring System(ASMS) at Lijiang Observatory(GMG), for the running of the 2.4-meter Lijiang optical telescope(LJT) and the 1.6-meter Multi-channel Photometric Survey Telescope (Mephisto). The Mephistro is under construction. ASMS has been running on robotic mode since 2017. The core instruments: Cloud Sensor, All-

Meng-Xue Guan, En Wang, Pei-Wei You, Jia-Tao Sun

Optical control of structural and electronic properties of Weyl semimetals allows development of switchable and dissipationless topological devices at the ultrafast scale. An unexpected orbitial-selective photoexcitation in type-II Weyl material WTe2 is reported under linearly polarized light (LPL), inducing striking transitions among several topologically-d

Hongyu Lin, Yaojie Lu, Jialong Tang, Xianpei Han

Fine-tuning pretrained model has achieved promising performance on standard NER benchmarks. Generally, these benchmarks are blessed with strong name regularity, high mention coverage and sufficient context diversity. Unfortunately, when scaling NER to open situations, these advantages may no longer exist. And therefore it raises a critical question of whethe

Triparna Mondal, Pragya Shukla

The statistics of chiral matrix ensembles with uncorrelated but multivariate Gaussian distributed elements is intuitively expected to be driven by many parameters. Contrary to intuition, however, our theoretical analysis reveals the existence of a single parameter, a function of all ensemble parameters, which governs the dynamics of spectral statistics. The

Milad Radiom, Jean-Franccois Berret

The discovery of SARS-CoV-2, the responsible virus for the Covid-19 epidemic, has sparked a global health concern with many countries affected. Developing models that can interpret the epidemic and give common trend parameters are useful for prediction purposes by other countries that are at an earlier phase of the epidemic; it is also useful for future plan

Davide Ninni, Miguel A. Mendez

In the era of the Big Data revolution, methods for the automatic discovery of regularities in large datasets are becoming essential tools in applied sciences. This article presents an open software package, named MODULO (MODal mULtiscale pOd), to perform the Multiscale Proper Orthogonal Decomposition (mPOD) of numerical and experimental data. This novel deco

Walid Kehila

In the present paper, we determine the sums $\sum_{j=1}^{p-1}\frac{H_j^{(s_1)}H_j^{(s_3)}}{j^{s_2}}$ and $\sum_{j=1}^{p-1}\frac{H_j^{(s_1)}H_j^{(s_3)}H_j^{(s_4)}}{j^{s_2}}$ modulo $p$ and modulo $p^2$ in certain cases. This is done by using multiple harmonic sums of length three and four, as well as, many other results. In addition, We recover three congruen

Noboru Ito

This paper demonstrates an approach for developing a framework to produce invariants of base-point-free generic spherical curves under some chosen local moves from Reidemeister moves using based chord diagrams. Our invariants not only contain Arnold's classical generic spherical curve invariant but also new invariants.

Xin-Yang Wang, Jie Jiang

The new version of the gedanken experiment proposed by Sorce and Wald has been used to examine the weak cosmic censorship conjecture (WCCC) for black holes at the second-order approximation of the matter fields perturbation. However, only considering the perturbation until the second-order approximation is incomplete because there is an optimal option such t

Phila Rembold, Nimba Oshnik, Matthias M. Müller, Simone Montangero

Diamond based quantum technology is a fast emerging field with both scientific and technological importance. With the growing knowledge and experience concerning diamond based quantum systems, comes an increased demand for performance. Quantum optimal control (QOC) provides a direct solution to a number of existing challenges as well as a basis for proposed

Feng Liu, Weiwen Liu, Xutao Li, Yunming Ye

Modeling the sequential correlation of users' historical interactions is essential in sequential recommendation. However, the majority of the approaches mainly focus on modeling the \emph{intra-sequence} item correlation within each individual sequence but neglect the \emph{inter-sequence} item correlation across different user interaction sequences. Though

Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak

This paper proposes a Deep Reinforcement Learning (DRL) approach for solving knapsack problem. The proposed method consists of a state aggregation step based on tabular reinforcement learning to extract features and construct states. The state aggregation policy is applied to each problem instance of the knapsack problem, which is used with Advantage Actor C

Aiden Peakman, Robert Gregg

There is a strong motivation to develop high-power output nuclear fission reactors (around 1 MWe) for space applications, such as high-payload missions and long-duration missions beyond Mars, where the reduced solar flux makes using alternative energy sources challenging. Many published gas-cooled reactor designs for space applications deliver outputs in the

Junxiao Feng, Eva Grimaldi, Can Onur Avci, Manuel Baumgartner

Oxidation strongly influences the properties of magnetic layers employed in spintronic devices. We study the effect of oxidation on the structural, magnetic, and electrical properties as well as current-induced spin-orbit torques (SOTs) in Pt/Co/AlOx, Pt/CoOx/Co/AlOx, and PtOx/Co/AlOx layers. We show how the saturation magnetization, perpendicular magnetic a

Vahram L. Grigoryan, Ke Xia

We propose a quantum state readout mechanism of a weakly coupled qubit in dispersive regime. The hybrid system consists of ferromagnetic insulator and a superconducting qubit in a microwave cavity. The enhancement of the measurement sensitivity is achieved by exerting torque on the ferromagnetic insulator magnetization, which compensates the damping of the s

Samir Karaa

We derive optimal $L^2$-error estimates for semilinear time-fractional subdiffusion problems involving Caputo derivatives in time of order $\alpha\in (0,1)$, for cases with smooth and nonsmooth initial data. A general framework is introduced allowing a unified error analysis of Galerkin type space approximation methods. The analysis is based on a semigroup t

Anthony Bagnall, Paul Southam, James Large, Richard Harvey

The aviation and transport security industries face the challenge of screening high volumes of baggage for threats and contraband in the minimum time possible. Automation and semi-automation of this procedure offers the potential to increase security by detecting more threats and improve the customer experience by speeding up the process. Traditional 2D x-ra

Yu-Kun Yan, Shao-Feng Wu, Xian-Hui Ge, Yu Tian

Based on AdS/CFT correspondence, we build a deep neural network to learn black hole metrics from the complex frequency-dependent shear viscosity. The network architecture provides a discretized representation of the holographic renormalization group flow of the shear viscosity and can be applied to a large class of strongly coupled field theories. Given the

Hari Krishna Vydana, Martin Karafi'at, Katerina Zmolikova, Luk'as Burget

Conventional spoken language translation (SLT) systems are pipeline based systems, where we have an Automatic Speech Recognition (ASR) system to convert the modality of source from speech to text and a Machine Translation (MT) systems to translate source text to text in target language. Recent progress in the sequence-sequence architectures have reduced the

Ripan Saha, David A. Towers

This paper is primarily concerned with studying finite-dimensional anti-commutative nonassociative algebras in which every centralizer is an ideal. These are shown to be anti-associative and are classified over a general field $F$; in particular, they are nilpotent of class at most $3$ and metabelian. These results are then applied to show that a Leibniz alg

Edoardo Fossati

Symplectic fillings of standard tight contact structures on lens spaces are understood and classified. The situation is different if one considers non-standard tight structures (i.e. those that are virtually overtwisted), for which a classification scheme is still missing. In this work we use different approaches and employ various techniques to improve our

M. A. P. Chamikara, P. Bertok, I. Khalil, D. Liu

Edge computing and distributed machine learning have advanced to a level that can revolutionize a particular organization. Distributed devices such as the Internet of Things (IoT) often produce a large amount of data, eventually resulting in big data that can be vital in uncovering hidden patterns, and other insights in numerous fields such as healthcare, ba

Wyman Kwok

An indeterministic interpretation of classical physics has been proposed recently, in which the argument relies on attacking an alleged unwarranted metaphysical hidden assumption of the standard deterministic interpretation. This short paper aims at showing that it is arguably a strawman attack.

Junhua Liu, Yung Chuen Ng, Kwan Hui Lim

There has been growing interest in utilizing occupational data mining and analysis. In today's job market, occupational data mining and analysis is growing in importance as it enables companies to predict employee turnover, model career trajectories, screen through resumes and perform other human resource tasks. A key requirement to facilitate these tasks is

S. H. Shabbeer Basha, Sravan Kumar Vinakota, Viswanath Pulabaigari, Snehasis Mukherjee

Transfer learning enables solving a specific task having limited data by using the pre-trained deep networks trained on large-scale datasets. Typically, while transferring the learned knowledge from source task to the target task, the last few layers are fine-tuned (re-trained) over the target dataset. However, these layers are originally designed for the so

Samaneh Nasiri, Christian Greff, Kai Wang, Mingjun Yang

We report results of a multiscale simulation study of multilayer structures consisting of graphene sheets with embedded Pt nanoparticles. Density functional theory is used to understand the energetics of Pt-graphene interfaces and provide reference data for the parameterization of a Pt-graphene interaction potential. Molecular dynamics simulations then provi

Junhua Liu, Lionell Loh, Ernest Ng, Yijia Chen

Primary and secondary education is a crucial stage to build a strong foundation before diving deep into specialised subjects in colleges and universities. To excel in the current education system, students are required to have a deep understanding of knowledge according to standardized curriculums and syllabus, and exam-related problem solving skills. In cur

Yury Kochetkov

Let $P=A_1\ldots A_n$ be a generic polygon in three-dimensional space and let $v_1,v_2,\ldots,v_n$ be vectors $\overline{A_1A_2},\overline{A_2A_3},\ldots,\overline{A_nA_1}$, respectively. $P$ will be called \emph{regular}, if there exist vectors $u_1,\ldots,u_n$ such that cross products $[u_1,u_2],[u_2,u_3],\ldots,[u_n,u_1]$ are equal to vectors $v_2,v_3,\ld

Cihan Bayindir, Azmi Ali Altintas, Fatih Ozaydin

Beyond a pure mathematical interest, q-deformation is promising for the modeling and interpretation of various physical phenomena. In this paper, we numerically investigate the existence and properties of the self-localized soliton solutions of the nonlinear Schr\"{o}dinger equation (NLSE) with a q-deformed Rosen-Morse potential. By implementing a Petviashvi

Bruce G. Elmegreen, Debra M. Elmegreen

To study the vertical distribution of the earliest stages of star formation in galaxies, three edge-on spirals, NGC 891, NGC 3628, and IC 5052 observed by the Spitzer Space Telescope InfraRed Array Camera (IRAC) were examined for compact 8 micron cores using an unsharp mask technique; 173, 267, and 60 cores were distinguished, respectively. Color-color distr

Deniz Engin, Alperen Kantarcı, Seçil Arslan, Hazım Kemal Ekenel

Research on offline signature verification has explored a large variety of methods on multiple signature datasets, which are collected under controlled conditions. However, these datasets may not fully reflect the characteristics of the signatures in some practical use cases. Real-world signatures extracted from the formal documents may contain different typ

Suyash Shandilya, Waris Quamer

Face reading is the most intuitive aspect of emotion recognition. Unfortunately, digital analysis of facial expression requires digitally recording personal faces. As emotional analysis is particularly required in a more poised scenario, capturing faces becomes a gross violation of privacy. In this paper, we use the concept of compressive analysis to concept

Antoni Musolas, Estelle Massart, Julien M. Hendrickx, P. -A. Absil

We propose a differential geometric construction for families of low-rank covariance matrices, via interpolation on low-rank matrix manifolds. In contrast with standard parametric covariance classes, these families offer significant flexibility for problem-specific tailoring via the choice of "anchor" matrices for the interpolation. Moreover, their low-rank

Szilvia Homolya, Jeno Szigeti

We show, how the combination of the Cayley-Hamilton theorem and a certain companion matrix construction can be used to derive Z2-graded trace identities in M_{n}(E).

Mohammad Hekmatnejad, Bardh Hoxha, Georgios Fainekos

The safety of Automated Vehicles (AV) as Cyber-Physical Systems (CPS) depends on the safety of their consisting modules (software and hardware) and their rigorous integration. Deep Learning is one of the dominant techniques used for perception, prediction, and decision making in AVs. The accuracy of predictions and decision-making is highly dependant on the

Thomas H. Jørgensen

A common approach to estimation of economic models is to calibrate a sub-set of model parameters and keep them fixed when estimating the remaining parameters. Calibrated parameters likely affect conclusions based on the model but estimation time often makes a systematic investigation of the sensitivity to calibrated parameters infeasible. I propose a simple

Chung-Han Hsieh

In this paper, we consider a discrete-time portfolio with $m \geq 2$ assets optimization problem which includes the rebalancing~frequency as an additional parameter in the maximization. The so-called Kelly Criterion is used as the performance metric; i.e., maximizing the expected logarithmic growth of a trader's account, and the portfolio obtained is called

Elden Elmanto, Marc Hoyois, Ryomei Iwasa, Shane Kelly

We prove that the $\infty$-category of motivic spectra satisfies Milnor excision: if $A\to B$ is a morphism of commutative rings sending an ideal $I\subset A$ isomorphically onto an ideal of $B$, then a motivic spectrum over $A$ is equivalent to a pair of motivic spectra over $B$ and $A/I$ that are identified over $B/IB$. Consequently, any cohomology theory

David Navarro-Alarcon, Jiaming Qi, Jihong Zhu, Andrea Cherubini

In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialise in a loc

Chang Liu, Lijing Shao, Junjie Zhao, Yong Gao

The Advanced LIGO and Virgo detectors opened a new era to study black holes (BHs) in our Universe. A population of stellar-mass binary BHs (BBHs) are discovered to be heavier than previously expected. These heavy BBHs provide us an opportunity to achieve multiband observation with ground-based and space-based gravitational-wave (GW) detectors. In this work,

Lin Zhang, Ying-Chang Liang

We consider a typical heterogeneous network (HetNet), in which multiple access points (APs) are deployed to serve users by reusing the same spectrum band. Since different APs and users may cause severe interference to each other, advanced power control techniques are needed to manage the interference and enhance the sum-rate of the whole network. Conventiona

Mingyang Zhang, Tong Li, Yue Yu, Yong Li

Urban anomalies may result in loss of life or property if not handled properly. Automatically alerting anomalies in their early stage or even predicting anomalies before happening are of great value for populations. Recently, data-driven urban anomaly analysis frameworks have been forming, which utilize urban big data and machine learning algorithms to detec

Zhenwei Liu, Donya Nojavanzadeh, Ali Saberi, Anton A. Stoorvogel

This paper studies global regulated state synchronization of homogeneous networks of non-introspective agents in presence of input saturation. We identify three classes of agent models which are neutrally stable, double-integrator, and mixed of double-integrator, single-integrator and neutrally stable dynamics. A \textit{scale-free linear observer-based} pro

Matjaž Konvalinka, Robin Sulzgruber, Vasu Tewari

Berget and Rhoades asked whether the permutation representation obtained by the action of $S_{n-1}$ on parking functions of length $n-1$ can be extended to a permutation action of $S_{n}$. We answer this question in the affirmative. We realize our module in two different ways. The first description involves binary Lyndon words and the second involves the act

Kasun Bandara, Christoph Bergmeir, Sam Campbell, Deborah Scott

Emergency Medical Services (EMS) demand load has become a considerable burden for many government authorities, and EMS demand is often an early indicator for stress in communities, a warning sign of emerging problems. In this paper, we introduce Deep Planning and Policy Making Net (DeepPPMNet), a Long Short-Term Memory network based, global forecasting and i

Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson, Matthew C. Valenti

In recent years, due to the emergence of deep learning, face recognition has achieved exceptional success. However, many of these deep face recognition models perform relatively poorly in handling profile faces compared to frontal faces. The major reason for this poor performance is that it is inherently difficult to learn large pose invariant deep represent

Onur Günlü, Peter Trifonov, Muah Kim, Rafael F. Schaefer

We consider polar subcodes (PSCs), which are polar codes (PCs) with dynamically-frozen symbols, to increase the minimum distance as compared to corresponding PCs. A randomized nested PSC construction with a low-rate PSC and a high-rate PC, is proposed for list and sequential successive cancellation decoders. This code construction aims to perform lossy compr

Robert Laterveer

Fatighenti and Mongardi have defined Fano varieties of type S6 as zero loci of a certain vector bundle on the Grassmannian $\hbox{Gr}(2,10)$. These varieties have 3 Hodge structures of K3 type in their cohomology. We show that the Chow ring of these varieties also displays "K3 type" behaviour.

Robert Laterveer

We prove that certain Fano fourfolds of K3 type constructed by Fatighenti-Mongardi have a multiplicative Chow-K\"unneth decomposition. We present some consequences for the Chow ring of these fourfolds.