February 2021 arXiv papers — page 6

Parley Ruogu Yang

This paper proposes a forecast-centric adaptive learning model that engages with the past studies on the order book and high-frequency data, with applications to hypothesis testing. In line with the past literature, we produce brackets of summaries of statistics from the high-frequency bid and ask data in the CSI 300 Index Futures market and aim to forecast

Claudio Mura, Renato Pajarola, Konrad Schindler, Niloy Mitra

Recent years have seen a proliferation of new digital products for the efficient management of indoor spaces, with important applications like emergency management, virtual property showcasing and interior design. These products rely on accurate 3D models of the environments considered, including information on both architectural and non-permanent elements.

Alexander Weber, Alexander Knoll

This paper proposes an algorithmic method to heuristically solve the famous Travelling Salesman Problem (TSP) when the salesman's path evolves in continuous state space and discrete time but with otherwise arbitrary (nonlinear) dynamics. The presented method is based on the framework of Symbolic Control. In this way, our method returns a provably correct

Christine Lang, Lisa Conrad, Dagmar Iber

A common developmental process, called branching morphogenesis, generates the epithelial trees in a variety of organs, including the lungs, kidneys, and glands. How branching morphogenesis can create epithelial architectures of very different shapes and functions remains elusive. In this review, we compare branching morphogenesis and its regulation in lungs

Birgitta Dresp-Langley, John M. Wandeto

Symmetry in biological and physical systems is a product of self organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry based feature extrac-tion or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in reco

David Chaum, Christian Grothoff, Thomas Moser

With the emergence of Bitcoin and recently proposed stablecoins from BigTechs, such as Diem (formerly Libra), central banks face growing competition from private actors offering their own digital alternative to physical cash. We do not address the normative question whether a central bank should issue a central bank digital currency (CBDC) or not. Instead, w

Tokuji Araya, Olgur Celikbas, Jesse Cook, Toshinori Kobayashi

If $M$ is a nonzero finitely generated module over a commutative Noetherian local ring $R$ such that $M$ has finite injective dimension and finite Gorenstein dimension, then it follows from a result of Holm that $M$ has finite projective dimension, and hence a result of Foxby implies that $R$ is Gorenstein. We investigate whether the same conclusion holds fo

Harsh Agarwal, Navyata Sanghvi, Vivek Roy, Kris Kitani

Accurate smartphone localization (< 1-meter error) for indoor navigation using only RSSI received from a set of BLE beacons remains a challenging problem, due to the inherent noise of RSSI measurements. To overcome the large variance in RSSI measurements, we propose a data-driven approach that uses a deep recurrent network, DeepBLE, to localize the smartphon

Rebekah Chua, Jun Zhou, Xiaojiang Yu, Wei Yu

The realization of long-range magnetic ordering in two-dimensional (2D) systems can potentially revolutionize next-generation information technology. Here, we report the successful fabrication of crystalline Cr3Te4 monolayers with room temperature ferromagnetism. Using molecular beam epitaxy, the growth of 2D Cr3Te4 films with monolayer thickness is demonstr

A. E. Baia, G. Di Bari, V. Poggioni

Recent studies have shown that Deep Leaning models are susceptible to adversarial examples, which are data, in general images, intentionally modified to fool a machine learning classifier. In this paper, we present a multi-objective nested evolutionary algorithm to generate universal unrestricted adversarial examples in a black-box scenario. The unrestricted

V. V. Bobylev, A. T. Bajkova, A. S. Rastorguev, M. V. Zabolotskikh

To construct the rotation curve of the Galaxy, classical Cepheids with proper motions, parallaxes and line-of-sight velocities from the Gaia DR2 Catalog are used in large part. The working sample formed from literature data contains about 800 Cepheids with estimates of their age. We determined that the linear rotation velocity of the Galaxy at a solar distan

Matteo Cervetti

In this paper we continue the study of permutations avoiding the vincular pattern $1-32-4$ by constructing a generating tree with a single label for these permutations. This construction finally provides a clearer explanation of why a certain recursive formula found by Callan actually counts these permutations, insofar as this formula was originally obtained

Cleophas Kweyu, Lihong Feng, Matthias Stein, Peter Benner

The Poisson-Boltzmann equation (PBE) is a fundamental implicit solvent continuum model for calculating the electrostatic potential of large ionic solvated biomolecules. However, its numerical solution encounters severe challenges arising from its strong singularity and nonlinearity. In [1,2], the effect of strong singularities was eliminated by applying the

Evan Bray, David N. Burrows, Sangwook Park, Aravind P. Ravi

We present an analysis of the dispersed spectral data from 11 epochs (March 2011 to September 2018) of supernova remnant (SNR) 1987A observations performed with Chandra. These observations were performed with the High Energy Transmission Grating (HETG) as part of our ongoing Chandra monitoring campaign of SNR 1987A, whose 1st-order dispersed spectrum provide

Boyan Gao, Henry Gouk, Timothy M. Hospedales

We present a &#34;learning to learn&#34; approach for automatically constructing white-box classification loss functions that are robust to label noise in the training data. We parameterize a flexible family of loss functions using Taylor polynomials, and apply evolutionary strategies to search for noise-robust losses in this space. To learn re-usable loss f

Jean Cortissoz, César Reyes

In this paper we investigate the one dimensional (1D) logarithmic diffusion equation with nonlinear Robin boundary conditions, namely, \[ \left\{ \begin{array}{l} \partial_t u=\partial_{xx} \log u\quad \mbox{in}\quad \left[-l,l\right]\times \left(0, \infty\right)\\ \displaystyle \partial_x u\left(\pm l, t\right)=\pm 2γu^{p}\left(\pm l, t\right), \end{array}

Artyom M. Grigoryan, Sos S. Agaian

In this paper, we discuss possible color palletes, prediction and analysis of originality of the colors that Artists used on the Renaissance oil paintings. This framework goal is to help to use the color symbology and image enhancement tools, to predict the historical color palletes of the Renaissance oil artworks. This work is only the start of a developmen

Mete Şeref Ahunbay, Adrian Vetta

We study the performance of the Empirical Revenue Maximizing (ERM) mechanism in a single-item, single-seller, single-buyer setting. We assume the buyer&#39;s valuation is drawn from a regular distribution $F$ and that the seller has access to {\em two} independently drawn samples from $F$. By solving a family of mixed-integer linear programs (MILPs), the ERM

Dan You, Shouguang Wang, Carla Seatzu

Opacity, an information-flow property related to the privacy and security of a system, has been extensively studied in the context of discrete event systems. Although various notions of opacity have been proposed, in all cases the considered secret was constant. This work focuses on current-state opacity, considering a scenario where the secret changes dynam

Eniafe Festus Ayetiran, Petr Sojka, Vít Novotný

Several language applications often require word semantics as a core part of their processing pipeline, either as precise meaning inference or semantic similarity. Multi-sense embeddings (M-SE) can be exploited for this important requirement. M-SE seeks to represent each word by their distinct senses in order to resolve the conflation of meanings of words as

Andry Alamsyah, Fatma Saviera

The rapid growth of the e-commerce market in Indonesia, making various e-commerce companies appear and there has been high competition among them. Marketing intelligence is an important activity to measure competitive position. One element of marketing intelligence is to assess customer satisfaction. Many Indonesian customers express their sense of satisfact

EmadElDin A Mazied, Lingjia Liu, Scott F. Midkiff

To meet the diverse demands for wireless communication, fifth-generation (5G) networks and beyond (B5G) embrace the concept of network slicing by forging virtual instances (slices) of its physical infrastructure. While network slicing constitutes dynamic allocation of core network and radio access network (RAN) resources, this article emphasizes RAN slicing

Tohid Soleymani Aghdam, Seyed Mohammad Mahdi Alavi, Mehrdad Saif

Structural identifiability analysis of fractional-order equivalent circuit models (FO-ECMs), obtained through electrochemical impedance spectroscopy (EIS) is still a challenging problem. No peer-reviewed analytical or numerical proof does exist showing that whether impedance spectroscopy FO-ECMs are structurally identifiable or not, regardless of practical i

Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen

Designing feasible and effective architectures under diverse computation budgets incurred by different applications/devices is essential for deploying deep models in practice. Existing methods often perform an independent architecture search for each target budget, which is very inefficient yet unnecessary. Moreover, the repeated independent search manner wo

Adina Crisan, Cresus Godinho, Ion Vancea

We construct a class of knot solutions of the gravitoelectromagnetic (GEM) equations in vacuum in the linearized gravity approximation by analogy with the Rañada-Hopf fields. For these solutions, the dual metric tensors of the bi-metric geometry of the gravitational vacuum with knot perturbations are given and the geodesic equation as a function of two compl

Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert, Marian Verhelst

Bayesian reasoning is a powerful mechanism for probabilistic inference in smart edge-devices. During such inferences, a low-precision arithmetic representation can enable improved energy efficiency. However, its impact on inference accuracy is not yet understood. Furthermore, general-purpose hardware does not natively support low-precision representation. To

Martin Knor, Riste Skrekovski, Ismael G. Yero

For a given graph $G$, the metric and edge metric dimensions of $G$, $\dim(G)$ and ${\rm edim}(G)$, are the cardinalities of the smallest possible subsets of vertices in $V(G)$ such that they uniquely identify the vertices and the edges of $G$, respectively, by means of distances. It is already known that metric and edge metric dimensions are not in general

V. Prokofev, A. Zabrodin

We consider solutions of the 2D Toda lattice hierarchy which are elliptic functions of the zeroth time t_0=x. It is known that their poles as functions of t_1 move as particles of the elliptic Ruijsenaars-Schneider model. The goal of this paper is to extend this correspondence to the level of hierarchies. We show that the Hamiltonians which govern the dynami

E. S. Egorova, O. V. Egorov, A. V. Moiseev, A. S. Saburova

The low-mass low-surface brightness (LSB) disc galaxy Arakelian 18 (Ark 18) resides in the Eridanus void and because of its isolation represents an ideal case to study the formation and evolution mechanisms of such a galaxy type. Its complex structure consists of an extended blue LSB disc and a bright central elliptically-shaped part hosting a massive off-ce

Lifeng Xie, Xiaowen Cao, Jie Xu, Rui Zhang

Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) has recently emerged as a promising technique to provide sustainable energy supply for widely distributed low-power ground devices (GDs) in large-scale wireless networks. Compared with the energy transmitters (ETs) in conventional WPT systems which are deployed at fixed locations, UAV-mounte

Evgeny Burnaev

The aim of this note is to prove the inversion formula, which can be used to compute the Levi measure of an infinitely divisible distribution from its characteristic function. Obtained formula is similar to the well-known inversion formula [2], which is used to compute the distribution function of a random variable from the corresponding characteristic funct

Harneet Kaur, Shailza Pathania, Amit Goyal, C. N. Kumar

We report theoretical prediction of exact localized solutions for dynamics of surface gravity waves, at the critical point kh=1.363, modelled by higher-order nonlinear Schrodinger equation. The model possess domain walls (kink solitons) and dark solitons modulated through different phase profiles. The parametric domains are delineated for the existence of so

Carla Boix-Constant, Samuel Mañas-Valero, Rosa Córdoba, Eugenio Coronado

Van der Waals heterostructures (vdWHs) allow the assembly of high-crystalline two-dimensional (2D) materials in order to explore dimensionality effects in strongly correlated systems and the emergence of potential new physical scenarios. In this work, it is illustrated the feasibility to integrate 2D materials in-between 2D superconductors. Particularly, it

Giulia Crocioni, Giambattista Gruosso, Danilo Pau, Davide Denaro

Nowadays, Neural Networks represent a major expectation for the realization of powerful Deep Learning algorithms, which can determine several physical systems&#39; behaviors and operations. Computational resources required for model, training, and running are large, especially when related to the amount of data that Neural Networks typically need to generali

Abdul Hameed Azeemi, Adeel Waheed

Understanding the public sentiment and perception in a healthcare crisis is essential for developing appropriate crisis management techniques. While some studies have used Twitter data for predictive modelling during COVID-19, fine-grained sentiment analysis of the opinion of people on social media during this pandemic has not yet been done. In this study, w

Anna Olofsson, Emma Rose Simpson, Neven Ibrakovic, Samuel Bengtsson

Extreme-ultraviolet (XUV) light is notoriously difficult to control due to its strong interaction cross-section with media. We demonstrate a method to overcome this problem by using Opto-Optical Modulation guided by a geometrical model to shape XUV light. A bell-shaped infrared light pulse is shown to imprint a trace of its intensity profile onto the XUV lig

Thomas Preibisch, Stefan Flaischlen, Christiane Göppl, Barbara Ercolano

The Carina Nebula harbors a large population of high-mass stars, including at least 75 O-type and Wolf-Rayet stars, but the current census is not complete since further high-mass stars may be hidden in or behind the dense dark clouds that pervade the association. With the aim of identifying optically obscured O- and early B-type stars in the Carina Nebula, w

Kingshuk Majumder, Uday Bondhugula

The emergence of machine learning, image and audio processing on edge devices has motivated research towards power efficient custom hardware accelerators. Though FPGAs are an ideal target for energy efficient custom accelerators, the difficulty of hardware design and the lack of vendor agnostic, standardized hardware compilation infrastructure has hindered t

Peng Song, Zhufeng Hou, Pedro Baptista de Castro, Kousuke Nakano

The search for hydride compounds that exhibit high $T_c$ superconductivity has been extensively studied. Within the range of binary hydride compounds, the studies have been developed well including data-driven searches as a topic of interest. Toward the search for the ternary systems, the number of possible combinations grows rapidly, and hence the power of

Taito Tauchi, Tsuyoshi Yoneda

In this article, we investigate the geometry of a central extension $\widehat{\mathcal D}_μ(S^{2})$ of the group of volume-preserving diffeomorphisms of the 2-sphere equipped with the $L^{2}$-metric, whose geodesics correspond solutions of the incompressible Euler equation with Coriolis force. In particular, we calculate the Misiolek curvature of this group.

Mengxi Liu, Qian Shi, Andrea Marinoni, Da He

Change detection, which aims to distinguish surface changes based on bi-temporal images, plays a vital role in ecological protection and urban planning. Since high resolution (HR) images cannot be typically acquired continuously over time, bi-temporal images with different resolutions are often adopted for change detection in practical applications. Traditio

Ji Zhou, Chengkun Yang, Dawei Wang, Qi Sui

In this paper, we present a field-trial C-band 72Gbit/s optical on-off keying (OOK) system over 18.8km dispersion-uncompensated submarine optical cable in the South China Sea. Chromatic dispersion (CD) of 18.8km submarine optical cable causes four spectral nulls on the 36GHz bandwidth of 72Gbit/s OOK signal, which is the main obstacle for achieving an accept

Cristina Curreli, Francesco Pappalardo, Giulia Russo, Marzio Pennisi

Agent-Based Models are a powerful class of computational models widely used to simulate complex phenomena in many different application areas. However, one of the most critical aspects, poorly investigated in the literature, regards an important step of the model credibility assessment: solution verification. This study overcomes this limitation by proposing

Lorenzo Zino, Ming Cao

During the ongoing COVID-19 pandemic, mathematical models of epidemic spreading have emerged as powerful tools to produce valuable predictions of the evolution of the pandemic, helping public health authorities decide which intervention policies should be implemented. The study of these models -- grounded in the systems theory and often analyzed using contro

Kostas Kolomvatsos, Christos Anagnostopoulos

The combination of the Internet of Things and the Edge Computing gives many opportunities to support innovative applications close to end users. Numerous devices present in both infrastructures can collect data upon which various processing activities can be performed. However, the quality of the outcomes may be jeopardized by the presence of outliers. In th

K. Jayaprakash, Prince Alex, A. Saravanan, M. Perumal

The Floating Potential Fluctuations (FPF) observed in a dc glow discharge plasma powered with two sources is modeled using an anharmonic oscillator with two forcing terms. In the discharge system, one of the electrode is biased to a negative voltage source (i.e. cathode), and the second electrode is biased to a positive voltage source (i.e. anode), while the

Dhong Yeon Cheong, Sung Mook Lee, Seong Chan Park

We review the recent progress in Higgs inflation focusing on Higgs-$R^2$ inflation, primordial black hole production and the $R^3$ term.

Mayank Gokarna

There are many sectors which have moved to Cloud and are planning aggressively to move their workloads to Cloud since the world entered Covid-19 pandemic. There are various reasons why Cloud is an essential irresistible technology and serves as an ultimate solution to access IT software and systems. It has become a new essential catalyst for Enterprise Organ

Kimitoshi Tsutaya, Yuta Wakasugi

Consider a nonlinear wave equation for a massless scalar field with self-interaction in the spatially flat Friedmann-Lemaître-Robertson-Walker spacetimes. We treat the so-called heatlike case where the critical exponent is affected by the Fujita exponent. We show upper bounds of the lifespan of blow-up solutions by distinguishing subcritical and critical cas

Song JuAe

For a rational map $ϕ$ from a metric graph $\varGamma$ to a tropical projective space $\boldsymbol{TP^n}$ defined by a ratio of rational functions $f_1, \ldots, f_{n + 1}$, an automorphism $σ$ of $\varGamma$ induces a permutation of the coordinates of $\boldsymbol{TP^n}$ if $\{ f_1, \ldots, f_{n + 1} \}$ is $\langle σ\rangle$-invariant. Through this descript

Oleksandr V. Pylypovskyi, Yelyzaveta A. Borysenko, Jürgen Fassbender, Denis D. Sheka

Chiral antiferromagnets are currently considered for broad range of applications in spintronics, spin-orbitronics and magnonics. In contrast to the established approach relying on materials screening, the anisotropic and chiral responses of low-dimensional antifferromagnets can be tailored relying on the geometrical curvature. Here, we consider an achiral, a

Mazhar Ali, Elena Gryazina, Anatoly Dymarsky, Petr Vorobev

Modern power systems face a grand challenge in grid management due to increased electricity demand, imminent disturbances, and uncertainties associated with renewable generation, which can compromise grid security. The security assessment is directly connected to the robustness of the operating condition and is evaluated by analyzing proximity to the power f

Yuya Tanaka, Giuseppe Viglialoro, Tomomi Yokota

These notes aim to provide a deeper insight on the specifics of two articles dealing with chemotaxis models with nonlinear production. More precisely, we are referring to the papers &#34;Boundedness of solutions to a quasilinear parabolic-parabolic chemotaxis model with nonlinear signal production&#34; by X. Tao, S. Zhou and M. Ding [J. Math. Anal. Appl. 474

Renzhe Yu, John Scott, Zachary A. Pardos

In online collaborative learning environments, students create content and construct their own knowledge through complex interactions over time. To facilitate effective social learning and inclusive participation in this context, insights are needed into the correspondence between student-contributed artifacts and their subsequent popularity among peers. In

N. Asger Mortensen, P. A. D. Gonçalves, Fedor A. Shuklin, Joel D. Cox

Surface-response functions are one of the most promising routes for bridging the gap between fully quantum-mechanical calculations and phenomenological models in quantum nanoplasmonics. Within all the currently available recipes for obtaining such response functions, \emph{ab initio} calculations remain one of the most predominant, wherein the surface-respon

Le Thi Ngoc Bao, Duong Dinh Phuoc, Le Thi Dieu Hien, Dinh Nhu Thao

In this paper, we study the exciton absorption spectra in InGaAs prolate ellipsoidal quantum dots when a strong pump laser resonant with electron quantized levels is active. Our obtained results by renormalized wavefunction theory show that, under suitable conditions, the initial exciton absorption peak is split into two new peaks as the evidence of the exis

Hirokazu Saito

The aim of this paper is to show time-decay estimates of solutions to linearized two-phase Navier-Stokes equations with surface tension and gravity. The original two-phase Navier-Stokes equations describe the two-phase incompressible viscous flow with a sharp interface that is close to the hyperplane $x_N=0$ in the $N$-dimensional Euclidean space, $N \geq 2$

Kan Hatakeyama-Sato, Kenichi Oyaizu

We report a deep generative model for regression tasks in materials informatics. The model is introduced as a component of a data imputer, and predicts more than 20 diverse experimental properties of organic molecules. The imputer is designed to predict material properties by &#34;imagining&#34; the missing data in the database, enabling the use of incomplet

Yanjie Jiang, Hui Liu, Nan Niu, Lu Zhang

High-quality and large-scale repositories of real bugs and their concise patches collected from real-world applications are critical for research in software engineering community. In such a repository, each real bug is explicitly associated with its fix. Therefore, on one side, the real bugs and their fixes} may inspire novel approaches for finding, locatin

B. D. M. De Zoysa, Y. A. M. M. A. Ali, M. D. I. Maduranga, Indika Perera

The problem of finding dense components of a graph is a widely explored area in data analysis, with diverse applications in fields and branches of study including community mining, spam detection, computer security and bioinformatics. This research project explores previously available algorithms in order to study them and identify potential modifications th

Peng Gao

We study the $2k$-th moment of central values of the family of Dirichlet $L$-functions to a fixed prime modulus. We establish sharp lower bounds for all real $k \geq 0$ and sharp upper bounds for $k$ in the range $0 \leq k \leq 1$.

Fei Li, Shiwei Fan, Pengzhen Chen, Xiangxu Li

Traffic violation and the flexible and changeable nature of pedestrians make it more difficult to predict pedestrian behavior or intention, which might be a potential safety hazard on the road. Pedestrian motion state (such as walking and standing) directly affects or reflects its intention. In combination with pedestrian motion state and other influencing f

Ralf-Dieter Scholz

There are 88 stars which lack colours, but have measured parallaxes in \textit{Gaia} EDR3 that place them within 20\,pc from the sun. Among them we found two new common parallax and proper motion (CPPM) companions separated from their primaries by about 3\,arcsec. The CPPM companion of a nearby ($d=14.98$\,pc) F1 star, \object{HD 105452 B}, was already image

Yuanrui Fan, Xin Xia, David Lo, Ahmed E. Hassan

Abstract syntax tree (AST) mapping algorithms are widely used to analyze changes in source code. Despite the foundational role of AST mapping algorithms, little effort has been made to evaluate the accuracy of AST mapping algorithms, i.e., the extent to which an algorihtm captures the evolution of code. We observe that a program element often has only one be

Yu-Yang Songsheng, Yan-Rong Li, Pu Du, Jian-Min Wang

Recently, GRAVITY onboard the Very Large Telescope Interferometer (VLTI) first spatially resolved the structure of the quasar 3C 273 with an unprecedented resolution of $\sim 10μ$as. A new method of measuring parallax distances has been successfully applied to the quasar through joint analysis of spectroastrometry (SA) and reverberation mapping (RM) observat

Anran Wang, Yuhan Wang, Jianfei Li, Ning Xu

Transition metal dichalcogenides (TMDs) are known to support complex excitonic states. Revealing the differences in relaxation dynamics among different excitonic species and elucidating the transition dynamics between them may provide important guidelines for designing TMD-based excitonic devices. Combining photoluminescence (PL) and reflectance contrast mea

Lei Wang, Pengcheng Xu, Zhaoyang Qu, Xiaoyong Bo

Existing coordinated cyber-attack detection methods have low detection accuracy and efficiency and poor generalization ability due to difficulties dealing with unbalanced attack data samples, high data dimensionality, and noisy data sets. This paper proposes a model for cyber and physical data fusion using a data link for detecting attacks on a Cyber-Physica

Osman Akdag, Yigit Akkus, Barbaros Cetin, Zafer Dursunkaya

Droplet evaporation has been intensively investigated in past decades owing to its emerging applications in diverse fields of science and technology. Yet the role transport mechanisms has been the subject of a heated debate, especially the presence of Marangoni flow in water droplets. This work aims to draw a clear picture of the switching transport mechanis

Isayiyas Nigatu Tiba, Quan Zhang, Jing Jiang, Yongchao Wang

An alternate direction method of multipliers (ADMM)-based detectors can achieve good performance in both small and large-scale multiple-input multiple-output (MIMO) systems. However, due to the difficulty of choosing the optimal penalty parameters, their performance is limited. This paper presents a deep neural network (DNN)-based massive MIMO detection meth

Sihuan Li, Jianyu Huang, Ping Tak Peter Tang, Daya Khudia

Soft error, namely silent corruption of signal or datum in a computer system, cannot be caverlierly ignored as compute and communication density grow exponentially. Soft error detection has been studied in the context of enterprise computing, high-performance computing and more recently in convolutional neural networks related to autonomous driving. Deep lea

Swaroop Panda, S. T. Roy

Music Genres, as a popular meta-data of music, are very useful to organize, explore or search music datasets. Soft music genres are weighted multiple-genre annotations to songs. In this initial work, we propose horizontally stacked bar charts to represent a music dataset annotated by these soft music genres. For this purpose, we take an example of a toy data

Swaroop Panda, V. Namboodiri, S. T. Roy

Music Genres serve as an important meta-data in the field of music information retrieval and have been widely used for music classification and analysis tasks. Visualizing these music genres can thus be helpful for music exploration, archival and recommendation. Probabilistic topic models have been very successful in modelling text documents. In this work, w

Yuyang Wang, Nitin Jonathan Myers, Nuria González-Prelcic, Robert W. Heath

Millimeter wave vehicular channels exhibit structure that can be exploited for beam alignment with fewer channel measurements compared to exhaustive beam search. With fixed layouts of roadside buildings and regular vehicular moving trajectory, the dominant path directions of channels will likely be among a subset of beam directions instead of distributing ra

Muhammad Usman, Yannic Noller, Corina Pasareanu, Youcheng Sun

This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and translates them into a Java representation that is amenable for analysis using the Symbolic PathFinder symbolic execution tool. Notably, NEUROSPF encodes specialized peer classes

Debayan Chakraborty, Mauro Lorenzo Mugnai, D. Thirumalai

The beautiful structures of single and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instance

Mozhdeh Rouhsedaghat, Masoud Monajatipoor, Zohreh Azizi, C. -C. Jay Kuo

Successive Subspace Learning (SSL) offers a light-weight unsupervised feature learning method based on inherent statistical properties of data units (e.g. image pixels and points in point cloud sets). It has shown promising results, especially on small datasets. In this paper, we intuitively explain this method, provide an overview of its development, and po

Takahiro Mizusaki, Peter Schuck

A new method for calculating the symmetry-projected energy of coupled-cluster singles and doubles (CCSD) wave function through the Monte Carlo method is proposed. We present benchmark calculations in considering the three-level Lipkin model which is a simple and minimal model with two phases: spherical and deformed ones. It is demonstrated that this new meth

Yang Yan, Qiuyan Wang

In recent years, Graph Neural Networks has received enormous attention from academia for its huge potential of modeling the network traits such as macrostructure and single node attributes. However, prior mainstream works mainly focus on homogeneous network and lack the capacity to characterize the network heterogeneous property. Besides, most previous liter

Christoph Persch, Maximilian J. Müller, Aakash Yadav, Julian Pries

Controlling a state of material between its crystalline and glassy phase has fostered many real-world applications. Nevertheless, design rules for crystallization and vitrification kinetics still lack predictive power. Here, we identify stoichiometry trends for these processes in phase change materials, i.e. along the GeTe-GeSe, GeTe-SnTe, and GeTe-Sb2Te3 ps

Bihai Sun, Muhammad Shehzad, Daniel Jovic, Christophe Cuvier

In the past decade, advances in electronics technology have made larger imaging sensors available to the experimental fluid mechanics community. These advancements have enabled the measurement of 2-component 2-dimensional (2C-2D) velocity fields using particle image velocimetry (PIV) with much higher spatial resolution than previously possible. However, due

Vu Thi Ngoc Anh, Nguyen Thi Thanh Hien, Lê Vǎn Thành, Vo Thi Hong Van

This paper establishes complete convergence for weighted sums and the Marcinkiewicz--Zygmund-type strong law of large numbers for sequences of negatively associated and identically distributed random variables $\{X,X_n,n\ge1\}$ with general normalizing constants under a moment condition that $ER(X)<\infty$, where $R(\cdot)$ is a regularly varying function. T

Yichong Leng, Xu Tan, Sheng Zhao, Frank Soong

Mean opinion score (MOS) is a popular subjective metric to assess the quality of synthesized speech, and usually involves multiple human judges to evaluate each speech utterance. To reduce the labor cost in MOS test, multiple methods have been proposed to automatically predict MOS scores. To our knowledge, for a speech utterance, all previous works only used

Daniela Pérez, Santiago E. Perez Bergliaffa, Gustavo E. Romero

We analyze the causal structure of McVittie spacetime for a classical bouncing cosmological model. In particular, we compute the trapping horizons of the metric and integrate the trajectories of radial null geodesics before, during, and after the bounce takes place. In the contracting phase up to the occurrence of the bounce, a dynamical black hole is presen

Tadashi Kozuno, Yunhao Tang, Mark Rowland, Rémi Munos

Off-policy multi-step reinforcement learning algorithms consist of conservative and non-conservative algorithms: the former actively cut traces, whereas the latter do not. Recently, Munos et al. (2016) proved the convergence of conservative algorithms to an optimal Q-function. In contrast, non-conservative algorithms are thought to be unsafe and have a limit

Lie Qian

In this paper, we prove that for suitably chosen Dwork motives, the local Galois representation arising from middle cohomology of fibers over a point with $p$-adic valuation $<0$ on the base is regular and ordinary. The result will be crucial in the forthcoming work Potential Automorphy for $GL_n$. The proof consists of the construction of a semistable blowu

A. Sakurai, V. M. Bastidas, W. J. Munro, Kae Nemoto

Symmetries are well known to have had a profound role in our understanding of nature and are a critical design concept for the realization of advanced technologies. In fact, many symmetry-broken states associated with different phases of matter appear in a variety of quantum technology applications. Such symmetries are normally broken in spatial dimension, h

Z. Shao, L. Landau, R. de Lamare

In this work, we investigate dynamic oversampling techniques for large-scale multiple-antenna systems equipped with low-cost and low-power 1-bit analog-to-digital converters at the base stations. To compensate for the performance loss caused by the coarse quantization, oversampling is applied at the receiver. Unlike existing works that use uniform oversampli

Haining Fan, Zhaosheng Feng, Xingjie Yan

In this paper, we study a class of fractional Schrödinger equations involving logarithmic and critical nonlinearities on an unbounded domain, and show that such an equation with positive or sign-changing weight potentials admits at least one positive ground state solution and the associated energy is positive (or negative). By applying the Nehari manifold me

Hongchang Zhang, Jianzhun Shao, Yuhang Jiang, Shuncheng He

In offline reinforcement learning, a policy learns to maximize cumulative rewards with a fixed collection of data. Towards conservative strategy, current methods choose to regularize the behavior policy or learn a lower bound of the value function. However, exorbitant conservation tends to impair the policy&#39;s generalization ability and degrade its perfor

Parth Sane

It&#39;s long been accepted that continuous integration (CI) in software engineering increases the code quality of enterprise projects when adhered to by it&#39;s practitioners. But is any of that effort to increase code quality and velocity directed towards improving software accessibility accommodations? What are the potential benefits quoted in literature

Bin Sun, Benjamin Richstein, Patrick Liebisch, Thorben Frahm

We investigate the operation of dual-gate reconfigurable field-effect transistor (RFET) in the programgate at drain (PGAD) and program-gate at source (PGAS) configurations. To this end, dual-gate silicon nanowire (SiNW) FETs are fabricated based on anisotropic wet chemical silicon etching and nickel silicidation yielding silicide-SiNW Schottky junctions at s

Maria Eugenia Ibarraran, Romeo A. Saldana-Vazquez, Tamara Perez-Garcia

The Atoyac River is among the two most polluted in Mexico. Water quality in the Upper Atoyac River Basin (UARB) has been devastated by industrial and municipal wastewater, as well as from effluents from local dwellers, that go through little to no treatment, affecting health, production, ecosystems and property value. We did a systematic review and mapping o

Haowei Xu, Hua Wang, Jian Zhou, Yunfan Guo

Nonlinear optical properties, such as bulk photovoltaic effects, possess great potential in energy harvesting, photodetection, rectification, etc. To enable efficient light-current conversion, materials with strong photo-responsivity are highly desirable. In this work, we predict that monolayer Janus transition metal dichalcogenides (JTMDs) in the 1T&#39; ph

Andre Merzky, Matteo Turilli, Mikhail Titov, Aymen Al-Saadi

Many extreme scale scientific applications have workloads comprised of a large number of individual high-performance tasks. The Pilot abstraction decouples workload specification, resource management, and task execution via job placeholders and late-binding. As such, suitable implementations of the Pilot abstraction can support the collective execution of la

Flash Sheridan

Two types of approximation to the paradoxical Russell Set are presented, one approximating it from below, one from above. It is shown that any lower approximation gives rise to a better approximation containing it, and that any upper approximation contains a distinct better approximation. The Russell Paradox is then seen to be the claim that two of these pro

Latévi Mohamed Lawson

More recently in [J. Phys. A: Math. Theor. 53, 115303 (2020)], we have introduced a set of noncommutative algebra that describes the space-time at the Planck scale. The interesting significant result we found is that the generalized uncertainty principle induced a maximal length of quantum gravity which has different physical implications to the one of gener

Alexander R. Pruss

Scoring rules measure the deviation between a probabilistic forecast and reality. Strictly proper scoring rules have the property that for any forecast, the mathematical expectation of the score of a forecast p by the lights of p is strictly better than the mathematical expectation of any other forecast q by the lights of p. Probabilistic forecasts need not

Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola

Quantile regression is a fundamental problem in statistical learning motivated by a need to quantify uncertainty in predictions, or to model a diverse population without being overly reductive. For instance, epidemiological forecasts, cost estimates, and revenue predictions all benefit from being able to quantify the range of possible values accurately. As s

C. Sinan Güntürk, Weilin Li

We show that the method of distributed noise-shaping beta-quantization offers superior performance for the problem of spectral super-resolution with quantization whenever there is redundancy in the number of measurements. More precisely, we define the oversampling ratio $λ$ as the largest integer such that $\lfloor M/λ\rfloor - 1\geq 4/Δ$, where $M$ denotes

Anne Canteaut, Alain Couvreur, Léo Perrin

Extended Affine (EA) equivalence is the equivalence relation between two vectorial Boolean functions $F$ and $G$ such that there exist two affine permutations $A$, $B$, and an affine function $C$ satisfying $G = A \circ F \circ B + C$. While the problem has a simple formulation, it is very difficult in practice to test whether two functions are EA-equivalent