May 2020 arXiv papers — page 40

Mayank Sharma, A. Bhattacharyay

The paper discusses the natural emergence of directed motion in a dimer system due to a structural symmetry breaking. A generalised solution is obtained for the transport of such a system which is driven entirely by bath fluctuations. The result shows the existence of possibility of ratcheting driven by bath fluctuations. If this component of energy conversi

Sorawit Saengkyongam, Ricardo Silva

We propose an approach to estimate the effect of multiple simultaneous interventions in the presence of hidden confounders. To overcome the problem of hidden confounding, we consider the setting where we have access to not only the observational data but also sets of single-variable interventions in which each of the treatment variables is intervened on sepa

Daoyuan Wu, Debin Gao, Robert H. Deng, Rocky K. C. Chang

Widely-used Android static program analysis tools, e.g., Amandroid and FlowDroid, perform the whole-app inter-procedural analysis that is comprehensive but fundamentally difficult to handle modern (large) apps. The average app size has increased three to four times over five years. In this paper, we explore a new paradigm of targeted inter-procedural analysi

J. Y. Süngü, A. Türkan, E. Sertbakan, E. Veli Veliev

The mass and decay constant of the axial-tensor meson nonets $\rho_2,~\omega_2$ and a missing member and also their first excited states are analyzed by the Thermal QCD sum rules model including QCD condensates up to dimension five. Mass and decay constant values in terms of variations of temperature are very well stable from $T=0$ up to ~$T \cong 120 ~\math

Javier Fresán, Claude Sabbah, Jeng-Daw Yu

We prove the existence of quadratic relations between periods of meromorphic flat bundles on complex manifolds with poles along a divisor with normal crossings under the assumption of "goodness". In dimension one, for which goodness is always satisfied, we provide methods to compute the various pairings involved. In an appendix, we give details on the classi

Anas Tahir, Yazan Qiblawey, Amith Khandakar, Tawsifur Rahman

Novel Coronavirus disease (COVID-19) is an extremely contagious and quickly spreading Coronavirus infestation. Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), which outbreak in 2002 and 2011, and the current COVID-19 pandemic are all from the same family of coronavirus. This work aims to classify COVID-19, SARS, and MERS

Domenico Cotroneo, Antonio Ken Iannillo, Roberto Natella, Roberto Pietrantuono

This paper analyzes the phenomenon of software aging - namely, the gradual performance degradation and resource exhaustion in the long run - in the Android OS. The study intends to highlight if, and to what extent, devices from different vendors, under various usage conditions and configurations, are affected by software aging and which parts of the system a

Anastassia M. Makarieva, Andrei V. Nefiodov, Douglas Sheil, Antonio Donato Nobre

In a recent paper Rousseau-Rizzi and Emanuel (2019) presented a derivation of an upper limit on maximum hurricane velocity at the surface. This derivation was based on a consideration of an infinitely narrow (differential) Carnot cycle with the warmer isotherm at the point of the maximum wind velocity. Here we show that this derivation neglected a significan

Bin Chen, Shao-Ming Fei

We investigate the total variance of a quantum state with respect to a complete set of mutually complementary measurements and its relation to the Brukner-Zeilinger invariant information. By summing the variances over any complete set of mutually unbiased measurements and general symmetric informationally complete measurements respectively, we show that the

Adriano A. Batista, A. A. Lisboa de Souza

Here we present a one-degree-of-freedom model of a nonlinear parametrically-driven resonator in the presence of a small added ac signal that has spectral responses similar to a frequency comb. The proposed nonlinear resonator has a spread spectrum response with a series of narrow peaks that are equally spaced in frequency. The system displays this behavior m

Abuzer Alp Yetisgin, Hazal Sakar, Hakan Bermek, Levent Trabzon

Polydimethylsiloxane (PDMS) is an insulator and it is commonly used in fabrication of micro-structures but there is a need of electrical conductive PDMS. Therefore, this research is mainly focused on producing PDMS nanocomposites with high electrical conductivity. Thus, we produced highly conductive PDMS nanocomposites which were filled with multiwalled carb

Mikhail V. Bondarko, Sergei V. Vostokov

In this note we prove that additive categories that occur as hearts of weight structures are precisely the weakly idempotent completecategories, that is, the categories where all split monomorphisms give direct sum decompositions. We also give several other conditions equivalent to weak idempotent completeness (some of them are completely new), and discuss w

Aruna Kumar Nayak, Jnanadeva Maharana

The Froissart bound on the total cross section is subjected to test against very high energy data. We have found no clear evidence for its violation. The scaling property of differential cross section in the diffraction region is investigated. It exhibits scaling in the ISR, SPS, Tevatron and LHC energy domain which had hitherto remained unexplored. The slop

Ivan Puddu, Moritz Schneider, Miro Haller, Srdjan Čapkun

We introduce a new timing side-channel attack on Intel CPU processors. Our Frontal attack exploits timing differences that arise from how the CPU frontend fetches and processes instructions while being interrupted. In particular, we observe that in modern Intel CPUs, some instructions' execution times will depend on which operations precede and succeed them,

Léo Grinsztajn, Elizaveta Semenova, Charles C. Margossian, Julien Riou

This tutorial shows how to build, fit, and criticize disease transmission models in Stan, and should be useful to researchers interested in modeling the SARS-CoV-2 pandemic and other infectious diseases in a Bayesian framework. Bayesian modeling provides a principled way to quantify uncertainty and incorporate both data and prior knowledge into the model est

S. Thorwirth, M. E. Harding, O. Asvany, S. Brünken

The carbon chain ions HC$_3$O$^+$ and HC$_3$S$^+$ - longer variants of the famous "X-ogen" line carrier HCO$^+$ - have been observed for the first time using two cryogenic 22-pole ion trap apparatus (FELion, Coltrap) and two different light sources: the Free Electron Laser for Infrared eXperiments (FELIX), which was operated between 500 and 2500 cm$^{-1}$ an

Alfredo Iorio

The work of our group on reproducing scenarios of high energy theoretical physics on Dirac materials, like graphene, is illustrated. The main goal of this paper is to explain how versatile these systems are, and how far and wide into the hep-th territory we can explore with them. I first review why these materials lend themselves to the emergence of special

A. E. Antony, V. Z. Thomas

If $p$ is an odd prime, then we prove that $\e(H_2(G,\mathbb{Z})) \mid p\ \e(G)$ for $p$ groups of class 7. We prove the same for $p$ groups of class at most $p+1$ with $\e(Z(G))=p$. We also prove Schurs conjecture if $\e(G/Z(G))$ is $2,3$ or $6$. Furthermore we prove that if $G$ is a solvable group of derived length $d$ and $\e(G)=p$, then $\e(H_2(G,\mathbb

Simra Shahid, Tanmay Singh, Yash Sharma, Kapil Sharma

With the increasing number of cybersecurity threats, it becomes more difficult for researchers to skim through the security reports for malware analysis. There is a need to be able to extract highly relevant sentences without having to read through the entire malware reports. In this paper, we are finding relevant malware behavior mentions from Advanced Pers

Mike Thelwall, Ruth Fairclough

Within academia, mature researchers tend to be more senior, but do they also tend to write higher impact articles? This article assesses long-term publishing (16+ years) United States (US) researchers, contrasting them with shorter-term publishing researchers (1, 6 or 10 years). A long-term US researcher is operationalised as having a first Scopus-indexed jo

Arghya Das, Abhishek Dhar, Srashti Goyal, Anupam Kundu

The Susceptible-Exposed-Infected-Recovered (SEIR) epidemiological model is one of the standard models of disease spreading. Here we analyse an extended SEIR model that accounts for asymptomatic carriers, believed to play an important role in COVID-19 transmission. For this model we derive a number of analytic results for important quantities such as the peak

Ionas Erb, Nihat Ay

Information geometry uses the formal tools of differential geometry to describe the space of probability distributions as a Riemannian manifold with an additional dual structure. The formal equivalence of compositional data with discrete probability distributions makes it possible to apply the same description to the sample space of Compositional Data Analys

A. Gutiérrez-Rodríguez, M. A. Hernández-Ruíz, E. Gurkanli, V. Ari

In this paper, a study is carried out on the $e^-p \to e^-\gamma^* p \to p W^+\gamma \nu_e$ production to probe quartic $W^+W^-\gamma\gamma$ couplings using 10, 100 ${\rm fb^{-1}}$ of $e^-p$ collisions data at $\sqrt{s}$= 1.30, 1.98 GeV at the Large Hadron electron Collider (LHeC) and 100, 1000 ${\rm fb^{-1}}$ with $\sqrt{s}$= 3.46, 5.29 GeV at the Future Ci

Xincao Xu, Kai Liu, Ke Xiao, Liang Feng

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such

Sonali Agarwal, Narinder Singh Punn, Sanjay Kumar Sonbhadra, M. Tanveer

The unprecedented outbreak of the novel coronavirus (COVID-19), during early December 2019 in Wuhan, China, has quickly evolved into a global pandemic, became a matter of grave concern, and placed government agencies worldwide in a precarious position. The scarcity of resources and lack of experiences to endure the COVID-19 pandemic, combined with the fear o

Zdzislaw Burda, Michalina Kotwica, Krzysztof Malarz

Many real-world complex networks arise as a result of a competition between growth and rewiring processes. Usually the initial part of the evolution is dominated by growth while the later one rather by rewiring. The initial growth allows the network to reach a certain size while rewiring to optimise its function and topology. As a model example we consider t

Ishfaq Ahmad Bhat, T. Mithun, B. A. Malomed, K. Porsezian

We study modulation instability (MI) of flat states in two-component spin-orbit-coupled (SOC) Bose-Einstein condensates (BECs) in the framework of coupled Gross-Pitaevskii equations for two components of the pseudospinor wave function. The analysis is performed for equal densities of the components. Effects of the interaction parameters, Rabi coupling, and S

Cornelius Ihle, Moritz Schubotz, Norman Meuschke, Bela Gipp

Plagiarism detection systems are essential tools for safeguarding academic and educational integrity. However, today's systems require disclosing the full content of the input documents and the document collection to which the input documents are compared. Moreover, the systems are centralized and under the control of individual, typically commercial provide

Michael Ruzhansky, Nurgissa Yessirkegenov

In this paper we present a comparison principle for higher order nonlinear hypoelliptic heat operators on graded Lie groups. Moreover, using the comparison principle we obtain blow-up type results and global in $t$-boundedness of solutions of nonlinear equations for the heat $p$-sub-Laplacian on stratified Lie groups. In particular, this paper generalises an

Sepideh Ghasemi, Hamid Rajabalipanah, Majid Tayarani, Ali Abdolali

This paper explores the time-modulated waveguide setups for unique and accurate permittivity and permeability extraction of lossy dispersive samples with phase-less measurements. We theoretically demonstrate that when the position of the short-circuit termination is dynamically modulated in a predefined way, the phase information of the reflection S-paramete

Qiong Liu, Dongyu Li, Shuzhi Sam Ge, Zhong Ouyang

Composite adaptive radial basis function neural network (RBFNN) control with a lattice distribution of hidden nodes has three inherent demerits: 1) the approximation domain of adaptive RBFNNs is difficult to be determined a priori; 2) only a partial persistence of excitation (PE) condition can be guaranteed; and 3) in general, the required number of hidden n

Neha Deopa, Daniele Rinaldo

We study the stochastic dynamics of natural resources under the threat of ecological regime shifts. We establish a Pareto optimal framework of regime shift detection under uncertainty that minimizes the delay with which economic agents become aware of the shift. We integrate ecosystem surveillance in the formation of optimal resource extraction policies. We

Shinji Kakinaka, Ken Umeno

Stable distribution is one of the attractive models that well describes fat-tail behaviors and scaling phenomena in various scientific fields. The approach based upon the method of moments yields a simple procedure for estimating stable law parameters with the requirement of using momental points for the characteristic function, but the selection of points i

Vaggelis Atlidakis, Roxana Geambasu, Patrice Godefroid, Marina Polishchuk

This paper introduces Pythia, the first fuzzer that augments grammar-based fuzzing with coverage-guided feedback and a learning-based mutation strategy for stateful REST API fuzzing. Pythia uses a statistical model to learn common usage patterns of a target REST API from structurally valid seed inputs. It then generates learning-based mutations by injecting

Julio A. López-Saldívar, Margarita A. Man'ko, Vladimir I. Man'ko

In a differential approach elaborated, we study the evolution of the parameters of Gaussian, mixed, continuous variable density matrices, whose dynamics are given by Hermitian Hamiltonians expressed as quadratic forms of the position and momentum operators or quadrature components. Specifically, we obtain in generic form the differential equations for the co

Oleg Zubelevich

It is shown that some class of differential inclusions has solutions that are defined and bounded for all real values of independent variable. Applications to dynamics are considered.

Xu Yuan

For the 5D energy-critical wave equation, we construct excited $N$-solitons with collinear speeds, i.e. solutions $u$ of the equation such that \begin{equation*} \lim_{t\to+\infty}\bigg\|\nabla_{t,x}u(t)-\nabla_{t,x}\bigg(\sum_{n=1}^{N}Q_{n}(t)\bigg)\bigg\|_{L^{2}}=0, \end{equation*} where for $n=1,\ldots,N$, $Q_n(t,x)$ is the Lorentz transform of a non-dege

ALICE Collaboration

One of the key challenges for nuclear physics today is to understand from first principles the effective interaction between hadrons with different quark content. First successes have been achieved using techniques that solve the dynamics of quarks and gluons on discrete space-time lattices. Experimentally, the dynamics of the strong interaction have been st

Shijun Li, Wenqiang Lei, Qingyun Wu, Xiangnan He

Static recommendation methods like collaborative filtering suffer from the inherent limitation of performing real-time personalization for cold-start users. Online recommendation, e.g., multi-armed bandit approach, addresses this limitation by interactively exploring user preference online and pursuing the exploration-exploitation (EE) trade-off. However, ex

Laura Seiffe, Oliver Marten, Michael Mikhailov, Sven Schmeier

Many people share information in social media or forums, like food they eat, sports activities they do or events which have been visited. This also applies to information about a person's health status. Information we share online unveils directly or indirectly information about our lifestyle and health situation and thus provides a valuable data resource. I

S. S. Acharya, V. R. R. Medicherla, Komal Bapna, Khadiza Ali

We investigate the ground state properties of Invar alloys via detailed study of the electronic structure of Fe$_{1-x}$Ni$_x$ alloys ($x$ = 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.9) employing $x$-ray photoelectron spectroscopy (XPS). While all the alloys exhibit soft ferromagnetic behavior with Curie temperature much higher than the room temperature, the results fo

Kanghong Shi, Igor G. Vladimirov, Ian R. Petersen

A robust output feedback consensus problem for networked identical nonlinear negative-imaginary (NI) systems is investigated in this paper. Output consensus is achieved by applying identical linear output strictly negative-imaginary (OSNI) controllers to all the nonlinear NI plants in positive feedback through the network topology. First, we extend the defin

Varik Hoang, Ling-Hong Hung, David Perez, Huazeng Deng

This paper presents the Container Profiler, a software tool that measures and records the resource usage of any containerized task. Our tool profiles the CPU, memory, disk, and network utilization of containerized tasks collecting over fifty Linux operating system metrics at the virtual machine, container, and process levels. The Container Profiler supports

Shuo Zhang, Zhuyun Dai, Krisztian Balog, Jamie Callan

Tabular data provide answers to a significant portion of search queries. However, reciting an entire result table is impractical in conversational search systems. We propose to generate natural language summaries as answers to describe the complex information contained in a table. Through crowdsourcing experiments, we build a new conversation-oriented, open-

Shizuo Kaji, Takeki Sudo, Kazushi Ahara

We introduce Cubical Ripser for computing persistent homology of image and volume data (more precisely, weighted cubical complexes). To our best knowledge, Cubical Ripser is currently the fastest and the most memory-efficient program for computing persistent homology of weighted cubical complexes. We demonstrate our software with an example of image analysis

Mohamed Loukili, Kamila Kotrasova, Denys Dutykh

The simulation of natural convection problem based on the Galerkin finite-element method, with the penalty finite-element formulation of the momentum balance equation, is exploited for accurate solutions of equations describing the problem of H-Form cavity differentially heated side walls. The cavity is occupied by the air whose Prandtl number is Pr=0.71, th

Eiji Yamamura., Yoshiro Tsutsui

During the COVID-19 epidemic in Japan between March and April 2020, Internet surveys were conducted to construct panel data to investigate changes at the individual level regarding preventive behaviors and mental conditions by surveying the same respondents at different times. Specifically, the difference-in-difference (DID) method was used to explore the im

Maryam Sadat Mirzaei, Kourosh Meshgi, Etienne Frigo, Toyoaki Nishida

Producing realistic character animations is one of the essential tasks in human-AI interactions. Considered as a sequence of poses of a humanoid, the task can be considered as a sequence generation problem with spatiotemporal smoothness and realism constraints. Additionally, we wish to control the behavior of AI agents by giving them what to do and, more spe

Jiadong Dan, Xiaoxu Zhao, Shoucong Ning, Jiong Lu

Progress in functional materials discovery has been accelerated by advances in high throughput materials synthesis and by the development of high-throughput computation. However, a complementary robust and high throughput structural characterization framework is still lacking. New methods and tools in the field of machine learning suggest that a highly autom

Yudi Chen, Wei Wang, Yu Zhou, Fei Yang

Though deep learning based scene text detection has achieved great progress, well-trained detectors suffer from severe performance degradation for different domains. In general, a tremendous amount of data is indispensable to train the detector in the target domain. However, data collection and annotation are expensive and time-consuming. To address this pro

Stephan Ramon Garcia

We present a detailed proof of the prime number theorem suitable for a typical undergraduate- or graduate-level complex analysis course. Our presentation is particularly useful for any instructor who seeks to use the prime number theorem for a series of capstone lectures, a scaffold for a series of guided exercises, or as a framework for an inquiry-based cou

Oana Brandibur, Eva Kaslik

Necessary and sufficient stability and instability conditions are obtained for multi-term homogeneous linear fractional differential equations with three Caputo derivatives and constant coefficients. In both cases, fractional-order-dependent as well as fractional-order-independent characterisations of stability and instability properties are obtained, in ter

Yumiharu Nakano

We study an inverse problem of the stochastic optimal control of general diffusions with performance index having the quadratic penalty term of the control process. Under mild conditions on the system dynamics, the cost functions, and the optimal control process, we show that our inverse problem is well-posed using a stochastic maximum principle. Then, with

Samira Hosseinzadeh Alikhalaji, Mojtaba Sedaghatjoo, Mohammad Roueentan

In this paper we investigate right uniform notion on some classes of semigroups. The main objective of this paper is realizing the structure of regular right uniform semigroups which can be applied as a cornerstone of characterizing regular right subdirectly irreducible semigroups.

Shahin Absar, Sanjib Ghoshal, Anisur Rahaman

We consider the gauged model of Siegel type chiral boson with a Lorentz non-covariant mass-like term for the gauge fields which is found to be equivalent to the chiral Schwinger model with Faddeevian anomaly when it is described in terms of Floreanini-Jackiw type chiral boson. We carry out the quantization of gauge non-invariant version this model in both th

Eyke Hüllermeier

Principles of analogical reasoning have recently been applied in the context of machine learning, for example to develop new methods for classification and preference learning. In this paper, we argue that, while analogical reasoning is certainly useful for constructing new learning algorithms with high predictive accuracy, is is arguably not less interestin

Moonseop Kim, Guang Lin

This paper uses the peridynamic theory, which is well-suited to crack studies, to predict the crack patterns in a moving disk and classify them according to the modes and finally perform regression analysis. In that way, the crack patterns are obtained according to each mode by Molecular Dynamic (MD) simulation using the peridynamics. Image classification an

Ali Ibnun Nurhadi, Guntur Petrus B. K., Muhammad Firdaus, Raditya Muhammad

A reliable network is an absolute requirement for telecommunication networks at this time. This is in line with the growing number of users who need a reliable and uninterrupted connection to the server. Link Aggregation is one of the techniques that can be used to provide a reliable network. Link Aggregation System combines two or more links into one logica

Myeonggi Kwon, Takahiro Oba

We study embeddability of rational ruled surfaces as symplectic hyperplane sections into closed integral symplectic manifolds. From this we obtain results on Stein fillability of Boothby--Wang bundles over rational ruled surfaces.

Muhammad Firdaus, Raditya Muhammad, Rifqy Hakimi

The development of cellular technology will be directly proportional to the increasing requirement in various aspects, such as the speed of data transmission (velocity), data variations (variety), and data storage media (volume). The increase in various aspects will have a direct impact on the growth of internet users worldwide. In relation to that, the dema

Ludovic Goudenège, Luigi Manca

We consider a stochastic perturbation of the $\alpha$-Navier-Stokes model. The stochastic perturbation is an additive space-time noise of trace class. Under a natural condition about the trace of operator $Q$ in front of the noise, we prove the existence and uniqueness of strong solution, continuous in time in classical spaces of $L^{2}$ functions with estim

Ricardo Gallego Torromé

We argue that in a framework for emergent quantum mechanics, the weak equivalence principle is a consequence of concentration of measure in large dimensional spaces of $1$-Lipshitz functions. Furthermore, as a consequence of the emergent framework and the properties that we assume for the fundamental dynamics, it is argued that gravity must be a classical, e

Chen-Te Ma

We obtain a Seiberg-Witten map for the gauge sector of multiple D$p$-branes in a large R-R $(p-1)$-form field background up to the first-order in the inverse R-R field background. By applying the Seiberg-Witten map and then electromagnetic duality on the non-commutative D3-brane theory in the large R-R 2-form background, we find the expected commutative diag

Ang Li, Yixiao Duan, Huanrui Yang, Yiran Chen

The success of deep learning partially benefits from the availability of various large-scale datasets. These datasets are often crowdsourced from individual users and contain private information like gender, age, etc. The emerging privacy concerns from users on data sharing hinder the generation or use of crowdsourcing datasets and lead to hunger of training

L. Lin, C. F. Zhang, P. Wang, H. Gao

Fast radio bursts (FRBs) are mysterious millisecond-duration radio transients of unknown origin observed at extragalactic distances. It has been long speculated that magnetars are the engine powering repeating bursts from FRB sources, but no convincing evidence has been collected so far\cite{sun19}. Recently, the Galactic magnetar SGR J1935+2154 entered an a

Yuexin Zhang, Jiahong Wang

A deep-learning-based hybrid strategy for short-term load forecasting is presented. The strategy proposes a novel tree-based ensemble method Warm-start Gradient Tree Boosting (WGTB). Current strategies either ensemble submodels of a single type, which fail to take advantage of the statistical strengths of different inference models. Or they simply sum the ou

Jun Han

This paper studies the issues about tensors. Three typical kinds of tensor decomposition are mentioned. Among these decompositions, the t-SVD is proposed in this decade. Different definitions of rank derive from tensor decompositions. Based on the research about higher order tensor t-product and tensor products with invertible transform, this paper introduce

Maria Alessandra Ragusa, Atsushi Tachikawa

We prove regularity properties in the vector valued case for minimizers of variational integrals of the form $$A(u) = \int_\Omega A(x,u,Du) dx$$ where the integrand $A(x,u,Du)$ is not necessarily continuous respect to the variable $x,$ grows polinomially like $|\xi|^p,$ $p \geq 2.$

Junxu Cao, Qi Chen, Jun Guo, Ruichao Shi

For object detection, how to address the contradictory requirement between feature map resolution and receptive field on high-resolution inputs still remains an open question. In this paper, to tackle this issue, we build a novel architecture, called Attention-guided Context Feature Pyramid Network (AC-FPN), that exploits discriminative information from vari

Emad Aghayi, Aaron Massey, Thomas LaToza

When working in large and complex codebases, developers face challenges using \textit{Find Usages} to understand how to reuse classes and methods. To better understand these challenges, we conducted a small exploratory study with 4 participants. We found that developers often wasted time reading long lists of similar usages or prematurely focused on a single

W. Jaskólski, G. Sarbicki

Gated trilayer graphene exhibits energy gap in its most stable ABC stacking. Here we show that when the stacking order changes from ABC to CBA, three gapless states appear in each valley. The states are topologically protected and their number is related to the change of the valley Chern number across the stacking boundary. The stacking change is achieved by

Zheng Ge, Zequn Jie, Xin Huang, Chengzheng Li

Imbalance issue is a major yet unsolved bottleneck for the current object detection models. In this work, we observe two crucial yet never discussed imbalance issues. The first imbalance lies in the large number of low-quality RPN proposals, which makes the R-CNN module (i.e., post-classification layers) become highly biased towards the negative proposals in

Sha-Sha Zheng, Feng-Xiao Sun, Huai-Yang Yuan, Zbigniew Ficek

The generation and manipulation of strong entanglement and Einstein-Podolsky-Rosen (EPR) steering in macroscopic systems are outstanding challenges in modern physics. Especially, the observation of asymmetric EPR steering is important for both its fundamental role in interpreting the nature of quantum mechanics and its application as resource for the tasks w

Donghao Xu, Zhezhang Ding, Xu He, Huijing Zhao

Driving in a human-like manner is important for an autonomous vehicle to be a smart and predictable traffic participant. To achieve this goal, parameters of the motion planning module should be carefully tuned, which needs great effort and expert knowledge. In this study, a method of learning cost parameters of a motion planner from naturalistic driving data

Taizo Okabe, Masamune Oguri, Sébastien Peirani, Yasushi Suto

We study shapes and alignments of 45 dark matter (DM) haloes and their brightest cluster galaxies (BCGs) using a sample of 39 massive clusters from Hubble Frontier Field (HFF), Cluster Lensing And Supernova survey with Hubble (CLASH), and Reionization Lensing Cluster Survey (RELICS). We measure shapes of the DM haloes by strong gravitational lensing, whereas

Sudip Adhikari, Alan Sayre, Abhilash J Chandy

Detailed analysis of efficiency and pollutant emission characteristics of practical turbulent combustion devices using complex combustion kinetics often depend on the interactions between the combustion chemistry involving both gasses species and soot, and turbulent flow characteristics. Modeling of such combustion system often requires the use of chemical k

Xiang-Fei Yang, Yuan-Hai Shao, Chun-Na Li, Li-Ming Liu

Classical principal component analysis (PCA) may suffer from the sensitivity to outliers and noise. Therefore PCA based on $\ell_1$-norm and $\ell_p$-norm ($0 < p < 1$) have been studied. Among them, the ones based on $\ell_p$-norm seem to be most interesting from the robustness point of view. However, their numerical performance is not satisfactory. Note th

Tingting Liang, Congying Xia, Yuyu Yin, Philip S. Yu

This paper proposes a novel neural network, joint training capsule network (JTCN), for the cold start recommendation task. We propose to mimic the high-level user preference other than the raw interaction history based on the side information for the fresh users. Specifically, an attentive capsule layer is proposed to aggregate high-level user preference fro

Dimitrios Fraggedakis, Mohammad Mirzadeh, Tingtao Zhou, Martin Z. Bazant

The control of the dielectric and conductive properties of device-level systems is important for increasing the efficiency of energy- and information-related technologies. In some cases, such as neuromorphic computing, it is desirable to increase the conductivity of an initially insulating medium by several orders of magnitude, resulting in effective dielect

Qiang Du, Lili Ju, Xiao Li, Zhonghua Qiao

The ubiquity of semilinear parabolic equations has been illustrated in their numerous applications ranging from physics, biology, to materials and social sciences. In this paper, we consider a practically desirable property for a class of semilinear parabolic equations of the abstract form $u_t=\mathcal{L}u+f[u]$ with $\mathcal{L}$ being a linear dissipative

Deniz Mengu, Yifan Zhao, Nezih T. Yardimci, Yair Rivenson

As an optical machine learning framework, Diffractive Deep Neural Networks (D2NN) take advantage of data-driven training methods used in deep learning to devise light-matter interaction in 3D for performing a desired statistical inference task. Multi-layer optical object recognition platforms designed with this diffractive framework have been shown to genera

Argenta Price, Candice Kim, Eric Burkholder, Amy Fritz

A primary goal of science and engineering (S & E) education is to produce good problem solvers, but how to best teach and measure the quality of problem-solving remains unclear. The process is complex, multifaceted, and not fully characterized. Here we present a theoretical framework of the S & E problem-solving process as a set of specific interlinked decis

Hai-Yang Jin, Zhi-An Wang

The paper is concerned with the following chemotaxis system with nonlinear motility functions \begin{equation}\label{0-1}\tag{$\ast$} \begin{cases} u_t=\nabla \cdot (\gamma(v)\nabla u- u\chi(v)\nabla v)+\mu u(1-u), &x\in \Omega, ~~t>0, 0=\Delta v+ u-v,& x\in \Omega, ~~t>0,\\ u(x,0)=u_0(x), & x\in \Omega, \end{cases} \end{equation} with homogeneous Neumann bo

Guanyu Hu, HaiYing Wang

Markov Chain Monte Carlo (MCMC) requires to evaluate the full data likelihood at different parameter values iteratively and is often computationally infeasible for large data sets. In this paper, we propose to approximate the log-likelihood with subsamples taken according to nonuniform subsampling probabilities, and derive the most likely optimal (MLO) subsa

Hai-Yang Jin, Shijie Shi, Zhi-An Wang

We consider the initial-boundary value problem of a system of reaction-diffusion equations with density-dependent motility \begin{equation*}\label{e1}\tag{$\ast$} \begin{cases} u_t=\Delta(\gamma(v)u)+\alpha u F(w) -\theta u, &x\in \Omega, ~~t>0,\\ v_t=D\Delta v+u-v,& x\in \Omega, ~~t>0,\\ w_t=\Delta w-uF(w),& x\in \Omega, ~~t>0, \frac{\partial u}{\partial \n

Yuzhuo Liu, Hangting Chen, Pengyuan Zhang

In recent years, the involvement of synthetic strongly labeled data,weakly labeled data and unlabeled data has drawn much research attentionin semi-supervised sound event detection (SSED). Self-training models carry out predictions without strong annotations and then take predictions with high probabilities as pseudo-labels for retraining. Such models have s

Ziqiang Li, Rentuo Tao, Hongjing Niu, Bin Li

Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution and drug discovery, etc., by now, the inner process of GANs is far from been understood. To get deeper insight of the intrinsic mechanism of GANs, in this paper, a method for interpreting the latent space of GANs by analyzing t

Yixian Zhang, Jieren Chen, Boyi Liu, Yifan Yang

With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Ch

Karunesh Kumar Singh, Asha Ram Gairola

In this paper, we define B\'{e}zier variant of generalized Bernstein-Durrmeyer type operators of second order, introduced by Ana et al. Then, we find an error estimate in terms of terms of Ditzian Totik modulus of smoothness. Next, we study the rate of approximation for a larger class of functions of bounded variation.

Hosseinali Jamal, David W. Matolak

In this paper, we investigate an algorithm to attain additive white Gaussian noise (AWGN) performance in spectrally non-white channels, using multicarrier communications, i.e., orthogonal frequency division multiplexing (OFDM) and filterbank multicarrier (FBMC). The non-white channel can be from non-white noise, or more commonly, interference. Our algorithm

Hosseinali Jamal, David W. Matolak

Due to the rapidly increasing number of flights and high usage of VHF channels, the VHF spectrum is becoming much more crowded, and use of analog waveforms will likely not maintain the required performance. Therefore, digital communications have been considered due to larger spectral efficiency. Notably, VHF data link modes 2 and 3 (VDL2 and 3) using D8PSK m

Manuel Lopez Galvan

The aim of this paper is to investigate the use of the Factor Analysis in order to identify the role of the relevant macroeconomic variables in driving the inflation. The Macroeconomic predictors that usually affect the inflation are summarized using a small number of factors constructed by the principal components. This allows us to identify the crucial rol

Calvin Brown, Derek Tseng, Paige M. K. Larkin, Susan Realegeno

Antimicrobial susceptibility testing (AST) is a standard clinical procedure used to quantify antimicrobial resistance (AMR). Currently, the gold standard method requires incubation for 18-24 h and subsequent inspection for growth by a trained medical technologist. We demonstrate an automated, cost-effective optical system that delivers early AST results, min

A. A. Araújo Filho, J. A. A. S. Reis

In this work, we study the interaction of quantum gases in Lorentz-violating scenarios considering both boson and fermion sectors. In the latter case, we investigate the consequences of a system governed by scalar, vector, pseudovector and tensor operators. Besides, we examine the implications of $\left( \hat{k}_{a}\right) ^{\kappa }$ and $\left( \hat{k}_{c}

Haozhe Yi, Kiwon Oh, Rui Kou, Yu Qiao

Currently, most of the waste plastics cannot be recycled, causing serious environmental concerns. In this research, we investigated a compaction formation technology to fabricate structural materials with thermoplastic binders. When the compaction pressure was 70~100 MPa, with only ~10 wt% polyethylene binder, the flexural strength was greater than that of t

Yunfeng Zhang

In this article, we obtain new results for Fourier restriction type problems on compact Lie groups. We first provide a sharp form of $L^p$ estimates of irreducible characters in terms of their Laplace-Beltrami eigenvalue and as a consequence provide some sharp $L^p$ estimates of joint eigenfunctions for the ring of conjugate-invariant differential operators.

Bijan Haney, Alexander Lavin

Prototypical networks have been shown to perform well at few-shot learning tasks in computer vision. Yet these networks struggle when classes are very similar to each other (fine-grain classification) and currently have no way of taking into account prior knowledge (through the use of tabular data). Using a spherical latent space to encode prototypes, we can

M. Echeveste, M. L. Novarino, O. G. Benvenuto, M. A. De Vito

We study the evolution of close binary systems in order to account for the existence of the recently observed binary system containing the most massive millisecond pulsar ever detected, PSR J0740+6620, and its ultra-cool helium white dwarf companion. In order to find a progenitor for this object we compute the evolution of several binary systems composed by

Mustapha Raïssouli, Shigeru Furuichi

In \cite{PSMA}, Pal et al. introduced some weighted means and gave some related inequalities by using an approach for operator monotone functions. This paper discusses the construction of these weighted means in a simple and nice setting that immediately leads to the inequalities established there. The related operator version is here immediately deduced as

Sanjay Kumar

We use purely topological tools to construct several infinite families of hyperbolic links in the 3-sphere that satisfy the Turaev-Viro invariant volume conjecture posed by Chen and Yang. To show that our links satisfy the volume conjecture, we prove that each has complement homeomorphic to the complement of a fundamental shadow link. These are links in conn