December 2020 arXiv papers — page 90

Sebastian Cristian Lesnic

The article $-$ part of a larger thesis which aims to give a detailed description of the generalisation to the category of groups with operators of the classical theory of semisimplicity for modules $-$ presents a straightforward generalisation to groups with operators of a number of invariants well-known in the theory of modules, having a special bearing on

Prabhu Kaliyammal Thiruvasagam, Vijeth J. Kotagi, C. Siva Ram Murthy

Network Functions Virtualization (NFV) allows flexibility, scalability, agility, and easy manageability of networks by leveraging the features of virtualization and cloud computing technologies. However, softwarization of network functions imposes many challenges. Reliability and latency are major challenges in NFV-enabled 5G networks that can lead to custom

Vincent Lahoche, Mohamed Ouerfelli, Dine Ousmane Samary, Mohamed Tamaazousti

The tensorial principal component analysis is a generalization of ordinary principal component analysis, focusing on data which are suitably described by tensors rather than matrices. This paper aims at giving the nonperturbative renormalization group formalism based on a slight generalization of the covariance matrix, to investigate signal detection for the

Kun Li, Jinsong Zhang, Yebin Liu, Yu-Kun Lai

Human pose transfer, which aims at transferring the appearance of a given person to a target pose, is very challenging and important in many applications. Previous work ignores the guidance of pose features or only uses local attention mechanism, leading to implausible and blurry results. We propose a new human pose transfer method using a generative adversa

Siwei Wang, Haoyun Wang, Longbo Huang

We study the multi-armed bandit (MAB) problem with composite and anonymous feedback. In this model, the reward of pulling an arm spreads over a period of time (we call this period as reward interval) and the player receives partial rewards of the action, convoluted with rewards from pulling other arms, successively. Existing results on this model require pri

Jie Liu, Zhenyu Li, Jinlong Yang

Recently, an adaptive variational algorithm termed Adaptive Derivative-Assembled Pseudo-Trotter ansatz Variational Quantum Eigensolver (ADAPT-VQE) has been proposed by Grimsley et al. (Nat. Commun. 10, 3007) while the number of measurements required to perform this algorithm scales O(N^8). In this work, we present an efficient adaptive variational quantum so

Sunny Katyara, Fanny Ficuciello, Fei Chen, Bruno Siciliano

Humans in contrast to robots are excellent in performing fine manipulation tasks owing to their remarkable dexterity and sensorimotor organization. Enabling robots to acquire such capabilities, necessitates a framework that not only replicates the human behaviour but also integrates the multi-sensory information for autonomous object interaction. To address

Shimry Haviv, Natali Revivo, Nimrod Kruger, Assaf Manor

The challenge in solar energy today is not the cost of photovoltaic (PV) electricity generation, already competing with fossil fuel prices, but rather utility-scale energy storage and flexibility in supply. Low-cost thermal energy storage (TES) exists but relies on expensive heat engines. Here, we introduce the concept of luminescent solar power (LSP), where

Jianfeng Cheng, Lili Du, Qin Zhang

This paper is concerned with the well-posedness theory of the impact of a subsonic axially symmetric jet emerging from a semi-infinitely long nozzle, onto a rigid wall. The fluid motion is described by the steady isentropic Euler system. We showed that there exists a critical value $M_{cr}>0$, if the given mass flux is less than $M_{cr}$, there exists a uniq

Jingxin Zhang, Donghua Zhou, Maoyin Chen

For multimode processes, one generally establishes local monitoring models corresponding to local modes. However, the significant features of previous modes may be catastrophically forgotten when a monitoring model for the current mode is built. It would result in an abrupt performance decrease. It could be an effective manner to make local monitoring model

Wenhui Lei, Wei Xu, Ran Gu, Hao Fu

Deep learning networks have shown promising performance for accurate object localization in medial images, but require large amount of annotated data for supervised training, which is expensive and expertise burdensome. To address this problem, we present a one-shot framework for organ and landmark localization in volumetric medical images, which does not ne

Xiangde Luo, Wenjun Liao, Jieneng Chen, Tao Song

Gross Target Volume (GTV) segmentation plays an irreplaceable role in radiotherapy planning for Nasopharyngeal Carcinoma (NPC). Despite that Convolutional Neural Networks (CNN) have achieved good performance for this task, they rely on a large set of labeled images for training, which is expensive and time-consuming to acquire. In this paper, we propose a no

Dawei Zhai, Wang Yao

Periodicity of long wavelength moir\'e patterns is very often destroyed by the inhomogeneous strain introduced in fabrications of van der Waals layered structures. We present a framework to describe massive Dirac fermions in such distorted moir\'e pattern of transition metal dichalcogenides homobilayers, accounting for the dynamics of layer pseudospin. In de

G. Violano, A. Papangelo, M. Ciavarella

Two surfaces are "sticky" if breaking their mutual contact requires a finite tensile force. At low fractal dimensions D, there is consensus stickiness does not depend on the upper truncation frequency of roughness spectrum (or "magnification"). As debate is still open for the case at high D, we exploit BAM theory of Ciavarella and Persson-Tosatti theory, to

Lina Ji, Zenghu Li

We give constructions of age-structured branching processes without or with immigration as pathwise unique solutions to stochastic integral equations. A necessary and sufficient condition for the ergodicity of the model with immigration is also given.

Christina Petschnigg, Juergen Pilz

The digital factory provides undoubtedly a great potential for future production systems in terms of efficiency and effectivity. A key aspect on the way to realize the digital copy of a real factory is the understanding of complex indoor environments on the basis of 3D data. In order to generate an accurate factory model including the major components, i.e.

Michael Beyer, Andrey Morozov, Emil Valiev, Christoph Schorn

Today, Deep Learning (DL) enhances almost every industrial sector, including safety-critical areas. The next generation of safety standards will define appropriate verification techniques for DL-based applications and propose adequate fault tolerance mechanisms. DL-based applications, like any other software, are susceptible to common random hardware faults

Daniel Hexner

The elastic behavior of materials operating in the linear regime is constrained, by definition, to operations that are linear in the imposed deformation. Though the nonlinear regime holds promise for new functionality, the design in this regime is challenging. In this paper we demonstrate that a recent approach based on training [Hexner et al., PNAS 2020, 20

Walaa Elmetenawee

An efficient and precise reconstruction of charged-particle tracks is crucial for the overall performance of the CMS experiment. During Run 2 of LHC, significant upgrades were made to the track reconstruction algorithms in order to accommodate for the high pileup environment and the installation of an upgraded pixel detector in 2017. This paper provides an o

Nemalidinne Siva Mouni, Abhinav Kumar, Prabhat K. Upadhyay

Non-orthogonal multiple access (NOMA) has been recognized as a key driving technology for the fifth generation (5G) and beyond 5G cellular networks. For a practical dowlink NOMA system with imperfect successive interference cancellation (SIC), we derive bounds on channel coefficients and power allocation factors between NOMA users to achieve higher rates tha

Zhengxiong Luo, Zhicheng Wang, Yuanhao Cai, Guanan Wang

In this paper, we propose an efficient human pose estimation network (DANet) by learning deeply aggregated representations. Most existing models explore multi-scale information mainly from features with different spatial sizes. Powerful multi-scale representations usually rely on the cascaded pyramid framework. This framework largely boosts the performance b

Vincent Corlay, Joseph J. Boutros, Philippe Ciblat, Loïc Brunel

We characterize the complexity of the lattice decoding problem from a neural network perspective. The notion of Voronoi-reduced basis is introduced to restrict the space of solutions to a binary set. On the one hand, this problem is shown to be equivalent to computing a continuous piecewise linear (CPWL) function restricted to the fundamental parallelotope.

Claudianor O. Alves, Geovany F. Patricio

This paper concerns the existence of a nontrivial solution for the following problem \begin{equation} \left\{\begin{aligned} -\Delta u + V(x)u & \in \partial_u F(x,u)\;\;\mbox{a.e. in}\;\;\mathbb{R}^{N},\nonumber u \in H^{1}(\mathbb{R}^{N}), \end{aligned} \right.\leqno{(P)} \end{equation} where $F(x,t)=\int_{0}^{t}f(x,s)\,ds$, $f$ is a discontinuous function

Kangda Zhi, Cunhua Pan, Hong Ren, Kezhi Wang

This paper investigates the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems with direct links, and the phase shifts of the RIS are designed based on the statistical channel state information (CSI). We first derive the closed-form expression of the uplink ergodic data rate. Then, based on the

Florentin Rauscher, Oliver Sawodny

Providing smooth reference trajectories can effectively increase performance and accuracy of tracking control applications while overshoot and unwanted vibrations are reduced. Trajectory planning computations can often be simplified significantly by transforming the system dynamics into decoupled integrator chains using methods such as feedback linearization

Anthony Suen

We prove uniqueness of weak solutions of the three-dimensional compressible Navier-Stokes equations with potential force. We make use of the Lagrangean framework in comparing the instantaneous states of corresponding fluid particles in two different solutions. The present work provides qualitative results on how the weak solutions depend continuously on init

Xuejian Wang

Different regional reactions to war in 1894 and 1900 can significantly impact Chinese imports in 2001. As international relationship gets tense and China rises, international conflicts could decrease trade.We analyze impact of historic political conflict. We measure regional change of number of people passing imperial exam because of war. War leads to an uns

Luigi Pagano

Let $K$ be a discretely-valued field. Let $X\rightarrow Spec K$ be a surface with trivial canonical bundle. In this paper we construct a weak N\'eron model of the schemes $Hilb^n(X)$ over the ring of integers $R\subseteq K$. We exploit this construction in order to compute the Motivic Zeta Function of $Hilb^n(X)$ in terms of $Z_X$. We determine the poles of

Matteo Salvato, Mattia Scagliotti, Maurizio De Crescenzi, Paola Castrucci

A new fabrication process is developed for growing Bi2Se3 topological insulators in the form of nanowires/nanobelts and ultra-thin films. It consists of two consecutive procedures: first Bi2Se3 nanowires/nanobelts are deposited by standard catalyst free vapour-solid deposition on different substrates positioned inside a quartz tube. Then, the Bi2Se3, stuck o

T. M. Aliev, M. Savci, S. Bilmis

Magnetic dipole moment form factor, $G_M^{(2)}(Q^2)$, describing the radial excitation of decuplet baryons to octet baryons electromagnetic transitions as well as the ratios, $R_{SM} = -\frac{1}{4 m_2^2} \sqrt{4 m_2^2 Q^2 + (m_2^2 - Q^2 -m_1^2)^2} \frac{G_C^{(2)}(Q^2)}{G_M^{(2)}(Q^2)}$ and $R_{EM} = -\frac{G_E^{(2)}(Q^2)}{G_M^{(2)}(Q^2)}$ are calculated in t

Nghi D. Q. Bui, Yijun Yu, Lingxiao Jiang

Building deep learning models on source code has found many successful software engineering applications, such as code search, code comment generation, bug detection, code migration, and so on. Current learning techniques, however, have a major drawback that these models are mostly trained on datasets labeled for particular downstream tasks, and code represe

Zezhou Hu, Zhen Zhong, Peng-Cheng Li, Minyong Guo

In this work, taking the QED effect into account, we investigate the shadows of the static black hole with magnetic monopoles and neutral black holes in magnetic fields through the numerical backward ray-tracing method. For a static black holes with magnetic monopole, we obtain the relation between the shadow radius and the coupling constant. For neutral bla

Jingxin Zhang, Maoyin Chen, Hao Chen, Xia Hong

By integrating two powerful methods of density reduction and intrinsic dimensionality estimation, a new data-driven method, referred to as OLPP-MLE (orthogonal locality preserving projection-maximum likelihood estimation), is introduced for process monitoring. OLPP is utilized for dimensionality reduction, which provides better locality preserving power than

Daniel Steffensen, Andreas Kreisel, P. J. Hirschfeld, Brian M. Andersen

The electronic structure of the enigmatic iron-based superconductor FeSe has puzzled researchers since spectroscopic probes failed to observe the expected electron pocket at the $Y$ point in the 1-Fe Brillouin zone. It has been speculated that this pocket, essential for an understanding of the superconducting state, is either absent or incoherent. Here, we p

Yinuo Guo, Zeqi Lin, Jian-Guang Lou, Dongmei Zhang

Neural semantic parsers usually fail to parse long and complex utterances into correct meaning representations, due to the lack of exploiting the principle of compositionality. To address this issue, we present a novel framework for boosting neural semantic parsers via iterative utterance segmentation. Given an input utterance, our framework iterates between

Andrea Lucchini

For a finite group $G$, we investigate the behaviour of four invariants, $\text{MaxDim}(G),$ $\text{MinDim}(G),$ $\text{MaxInt}(G)$ and $\text{MinInt}(G),$ measuring in some way the width and the height of the lattice $\mathcal M(G)$ consisting of the intersections of the maximal subgroups of $G.$

Nikolai Gorbushin, Lev Truskinovsky

Peristalsis by actively generated waves of muscle contraction is one of the most fundamental ways of producing motion in living systems. We show that peristalsis can be modeled by a train of rectangular-shaped solitary waves of localized activity propagating through otherwise passive matter. Our analysis is based on the FPU-type discrete model accounting for

Giovanni Abbiendi

The MUonE experiment aims at an independent and very precise determination of the leading hadronic contribution to the muon magnetic moment, based on an alternative method, complementary to the existing ones. This can be achieved by measuring with unprecedented precision the shape of the differential cross section of $\mu e$ elastic scattering, using the int

Huibin Chen, Zhiqi Chen, Fuhai Zhu

In this paper, we focus on homogeneous spaces which are constructed from two strongly isotropy irreducible spaces, and prove that any geodesic orbit metric on these spaces is naturally reductive.

Hailing Liu, Yusen Wu, Linchun Wan, Shijie Pan

The Poisson equation has wide applications in many areas of science and engineering. Although there are some quantum algorithms that can efficiently solve the Poisson equation, they generally require a fault-tolerant quantum computer which is beyond the current technology. In this paper, we propose a Variational Quantum Algorithm (VQA) to solve the Poisson e

Sriram Nagaraj

Nonlocal models have recently had a major impact in nonlinear continuum mechanics and are used to describe physical systems/processes which cannot be accurately described by classical, calculus based "local" approaches. In part, this is due to their multiscale nature that enables aggregation of micro-level behavior to obtain a macro-level description of sing

T. E. Gureyev, H. M. Quiney, A. Kozlov, D. M. Paganin

It has been argued that in atomic-resolution transmission electron microscopy (TEM) of sparse weakly scattering structures, such as small biological molecules, multiple electron scattering usually has only a small effect, while the in-molecule Fresnel diffraction can be significant due to the intrinsically shallow depth of focus. These facts suggest that the

Yasuhito Tanaka

The existence of involuntary unemployment advocated by J. M. Keynes is a very important problem of the modern economic theory. Using a three-generations overlapping generations model, we show that the existence of involuntary unemployment is due to the instability of the economy. Instability of the economy is the instability of the difference equation about

Ziyue Qiao, Zhiyuan Ning, Yi Du, Yuanchun Zhou

Most researches for knowledge graph completion learn representations of entities and relations to predict missing links in incomplete knowledge graphs. However, these methods fail to take full advantage of both the contextual information of entity and relation. Here, we extract contexts of entities and relations from the triplets which they compose. We propo

Kacper Koteras, Jakub Gawraczynski, Mariana Derzsi, Zoran Mazej

Theoretical DFT calculations using GGA+U and HSE06 frameworks enabled vibrational mode assignment and partial (atomic) phonon DOS determination in KAgF3 perovskite, a low-dimensional magnetic fluoroargentate(II). Twelve bands in the spectra of KAgF3 were assigned to either IR active or Raman active modes, reaching very good correlation with experimental valu

Yanqi Liu, Zhigang Li, Wei Wei, Jiehui Zheng

The dispatchable region of volatile renewable power generation (RPG) quantifies how much uncertainty the power system can handle at a given operating point. State-of-the-art dispatchable region (DR) research has studied how system operational constraints influence the DR but has seldom considered the effect of the uncertainty features of RPG outputs. The tra

Xuejian Wang

Industries can enter one country first, and then enter its neighbors' markets. Firms in the industry can expand trade network through the export behavior of other firms in the industry. If a firm is dependent on a few foreign markets, the political risks of the markets will hurt the firm. The frequent trade disputes reflect the importance of the choice of ex

Danko D. Georgiev

The brain is composed of electrically excitable neuronal networks regulated by the activity of voltage-gated ion channels. Further portraying the molecular composition of the brain, however, will not reveal anything remotely reminiscent of a feeling, a sensation or a conscious experience. In classical physics, addressing the mind-brain problem is a formidabl

Xiaodong Cun, Chi-Man Pun

Digital watermark is a commonly used technique to protect the copyright of medias. Simultaneously, to increase the robustness of watermark, attacking technique, such as watermark removal, also gets the attention from the community. Previous watermark removal methods require to gain the watermark location from users or train a multi-task network to recover th

Han Qiu, Yi Zeng, Shangwei Guo, Tianwei Zhang

Public resources and services (e.g., datasets, training platforms, pre-trained models) have been widely adopted to ease the development of Deep Learning-based applications. However, if the third-party providers are untrusted, they can inject poisoned samples into the datasets or embed backdoors in those models. Such an integrity breach can cause severe conse

Mohammad Azzeh, Ali Bou Nassif, Imtinan Attili

Context: Predicting software project effort from Use Case Points (UCP) method is increasingly used among researchers and practitioners. However, unlike other effort estimation domains, this area of interest has not been systematically reviewed. Aims: There is a need for a systemic literature review to provide directions and supports for this research area of

Yutai Hou, Sanyuan Chen, Wanxiang Che, Cheng Chen

Slot filling, a fundamental module of spoken language understanding, often suffers from insufficient quantity and diversity of training data. To remedy this, we propose a novel Cluster-to-Cluster generation framework for Data Augmentation (DA), named C2C-GenDA. It enlarges the training set by reconstructing existing utterances into alternative expressions wh

Cǎlin-Şerban Bǎrbat

In this work I show that in each rectangle formed by the parameter curves on a Liouville surface the energies of the main diagonals are equal. This result extends naturally to n-dimensional Liouville manifolds.

Hongwei Yu, Zhihai Wang, Jin-Hui Wu

We investigate the dynamics of giant atom(s) in a waveguide QED scenario, where the atom couples to the coupled resonator waveguide via two sites. For a single giant atom setup, we find that the atomic dissipation rate can be adjusted by tuning its size. For the two giant atoms system, the waveguide will induce the controllable individual and collective diss

Yanlin Ma, Jihua Zhu, Zhongyu Li, Zhiqiang Tian

Recently, Expectation-maximization (EM) algorithm has been introduced as an effective means to solve multi-view registration problem. Most of the previous methods assume that each data point is drawn from the Gaussian Mixture Model (GMM), which is difficult to deal with the noise with heavy-tail or outliers. Accordingly, this paper proposed an effective regi

Xianqi Tong, Yeming Meng, Xunda Jiang, Chaohong Lee

We investigate the nonequilibrium dynamics of the one-dimension Aubry-Andr\'{e}-Harper model with $p$-wave superconductivity by changing the potential strength with slow and sudden quench. Firstly, we study the slow quench dynamics from localized phase to critical phase by linearly decreasing the potential strength $V$. The localization length is finite and

Dandan Song, Siyi Ma, Zhanchen Sun, Sicheng Yang

Reasoning is a critical ability towards complete visual understanding. To develop machine with cognition-level visual understanding and reasoning abilities, the visual commonsense reasoning (VCR) task has been introduced. In VCR, given a challenging question about an image, a machine must answer correctly and then provide a rationale justifying its answer. T

Vladimir Filinov, Pavel Levashov, Alexander Larkin

The new {\em ab initio} quantum path integral Monte Carlo approach has been developed and applied for the entropy difference calculations for the strongly coupled degenerated uniform electron gas (UEG), a well--known model of simple metals. Calculations have been carried out at finite temperature in canonical ensemble over the wide density and temperature ra

Olivier Le Gal, Mickaël Matusinski, Fernando Sanz Sánchez

We introduce a notion of regular separation for solutions of systems of ODEs $y'=F(x,y)$, where F is definable in a polynomially bounded o-minimal structure and $y = (y_1,y_2)$. Given a pair of solutions with flat contact, we prove that, if one of them has the property of regular separation, the pair is either interlaced or generates a Hardy field. We adapt

Yu Liu, Panyue Zhou

Let $\mathcal B$ be an extriangulated category with enough projectives and enough injectives. We define a proper $m$-term subcategory $\mathcal G$ on $\mathcal B$, which is an extriangulated subcategory. Then we give a correspondence between cotorsion pairs on $\mathcal G$, support $\tau$-tilting subcategories on an abelian quotient of $\mathcal G$ when $m=2

M. Ünzelmann, H. Bentmann, T. Figgemeier, P. Eck

Since the early days of Dirac flux quantization, magnetic monopoles have been sought after as a potential corollary of quantized electric charge. As opposed to magnetic monopoles embedded into the theory of electromagnetism, Weyl crystals exhibit Berry flux monopoles in reciprocal parameter space. As a function of crystal momentum, such monopoles locate at t

Shuang Li, Fangrui Lv, Binhui Xie, Chi Harold Liu

Unsupervised domain adaptation challenges the problem of transferring knowledge from a well-labelled source domain to an unlabelled target domain. Recently,adversarial learning with bi-classifier has been proven effective in pushing cross-domain distributions close. Prior approaches typically leverage the disagreement between bi-classifier to learn transfera

David H. Wu, Victor V. Albert

The Rabi model describes the simplest nontrivial interaction between a few-level system and a bosonic mode, featuring in multiple seemingly unrelated systems of importance to quantum science and technology. While exact expressions for the energies of this model and its few-mode extensions have been obtained, they involve roots of transcendental functions and

Xinying Ma, Zhi Chen, Longfei Yan, Chong Han

Terahertz (THz) communications have been envisioned as a promising enabler to provide ultra-high data transmission for sixth generation (6G) wireless networks. To tackle the blockage vulnerability brought by severe path attenuation and poor diffraction of THz waves, an intelligent reflecting surface (IRS) is put forward to smartly control the incident THz wa

Bo Yang, Xuelin Cao, Kai Xiong, Chau Yuen

In a level-5 autonomous driving system, the autonomous driving vehicles (AVs) are expected to sense the surroundings via analyzing a large amount of data captured by a variety of onboard sensors in near-real-time. As a result, enormous computing costs will be introduced to the AVs for processing the tasks with the deployed machine learning (ML) model, while

Maitrayee Saha, Samudra Roy, Shailendra K. Varshney

Understanding the intra-cavity field dynamics in passive microresonator systems has already been intriguing. It becomes fascinating when the system is complex, such as a concentric dual microring resonator that exhibit avoided mode crossing (AMC). In this work, we present a systematic study of intra-cavity oscillatory field dynamics near AMC in a concentric

Siya Goel, Clark Gedney, Jean Honorio

Pancreatic cancer (PC) is the fourth leading cause of cancer death in the United States due to its five-year survival rate of 10%. Late diagnosis, affiliated with the asymptomatic nature in early stages and the location of the cancer with respect to the pancreas, makes current widely-accepted screening methods unavailable. Prior studies have achieved low (70

Anees Al-Najjar, Furqan Hameed Khan, Marius Portmann

Software Defined Networking (SDN) is an emerging technology of efficiently controlling and managing computer networks, such as in data centres, Wide Area Networks (WANs), as well as in ubiquitous communication. In this paper, we explore the idea of embedding the SDN components, represented by SDN controller and virtual switch, in end-hosts to improve network

Jafar Majidpour, Hiwa Hasanzadeh

Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks were studied in this paper. The identification of attacks in computer networks is divided in to two categories of intrusion detection and anomaly detection in terms of the information used in the learning phase. Intrusion detection uses both routine traffi

Jinping Zhang, Kouji Yano

Martingale representation theorem for set-valued martingales was proposed by M. Kisielewicz [J. Math. Anal. Appl. 2014]. We shall prove that the result holds only for very special case: the set-valued martingale degenerates to the point-valued one. A revised representation theorem for a special kind of non-degenerate set-valued martingales is presented.

Sepanta Zeighami, Cyrus Shahabi, John Krumm

Physical contacts result in the spread of various phenomena such as viruses, gossips, ideas, packages and marketing pamphlets across a population. The spread depends on how people move and co-locate with each other, or their mobility patterns. How far such phenomena spread has significance for both policy making and personal decision making, e.g., studying t

Ilyas Haouam

In this paper, we investigated the Pauli equation in a two-dimensional noncommutative phase-space by considering a constant magnetic field perpendicular to the plane. We mapped the noncommutative problem to the equivalent commutative one through a set of two-dimensional Bopp-shift transformation. The energy spectrum and the wave function of the two-dimension

Xiangyun Zhao, Raviteja Vemulapalli, Philip Mansfield, Boqing Gong

Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Network (CNN) based semantic segmentation approaches have achieved impressive results by using large amounts of labeled training data, their performance drops significantly as the amoun

Peter Nekrasov, Jessica Freeze, Victor Batista

Precise physical descriptions of molecules can be obtained by solving the Schrodinger equation; however, these calculations are intractable and even approximations can be cumbersome. Force fields, which estimate interatomic potentials based on empirical data, are also time-consuming. This paper proposes a new methodology for modeling a set of physical parame

Yi Zhang, Hu Chen, Wenjun Xia, Yang Chen

Compressed sensing (CS) computed tomography has been proven to be important for several clinical applications, such as sparse-view computed tomography (CT), digital tomosynthesis and interior tomography. Traditional compressed sensing focuses on the design of handcrafted prior regularizers, which are usually image-dependent and time-consuming. Inspired by re

Arash Moradzadeh, Kazem Pourhossein, Behnam Mohammadi-Ivatloo, Tohid Khalili

A power transformer winding is usually subject to mechanical stress and tension because of improper transportation or operation. Radial deformation (RD) is an example of mechanical stress that can impact power transformer operation through short circuit faults and insulation damages. Frequency response analysis (FRA) is a well-known method to diagnose mechan

Stephen Macke, Hongpu Gong, Doris Jung-Lin Lee, Andrew Head

Computational notebooks have emerged as the platform of choice for data science and analytical workflows, enabling rapid iteration and exploration. By keeping intermediate program state in memory and segmenting units of execution into so-called "cells", notebooks allow users to execute their workflows interactively and enjoy particularly tight feedback. Howe

Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr

In this paper, we propose a geometric neural network with edge-aware refinement (GeoNet++) to jointly predict both depth and surface normal maps from a single image. Building on top of two-stream CNNs, GeoNet++ captures the geometric relationships between depth and surface normals with the proposed depth-to-normal and normal-to-depth modules. In particular,

Shachar Schnapp, Sivan Sabato

We study active feature selection, a novel feature selection setting in which unlabeled data is available, but the budget for labels is limited, and the examples to label can be actively selected by the algorithm. We focus on feature selection using the classical mutual information criterion, which selects the $k$ features with the largest mutual information

Taekang Eom, Seungjun Lee, Hee-Kap Ahn

Given a convex polygon $P$ with $k$ vertices and a polygonal domain $Q$ consisting of polygonal obstacles with total size $n$ in the plane, we study the optimization problem of finding a largest similar copy of $P$ that can be placed in $Q$ without intersecting the obstacles. We improve the time complexity for solving the problem to $O(k^2n^2\lambda_4(k)\log

Wenhao Wu, Dongliang He, Tianwei Lin, Fu Li

Conventionally, spatiotemporal modeling network and its complexity are the two most concentrated research topics in video action recognition. Existing state-of-the-art methods have achieved excellent accuracy regardless of the complexity meanwhile efficient spatiotemporal modeling solutions are slightly inferior in performance. In this paper, we attempt to a

G. Jhang, J. Estee, J. Barney, G. Cerizza

In the past two decades, pions created in the high density regions of heavy ion collisions have been predicted to be sensitive at high densities to the symmetry energy term in the nuclear equation of state, a property that is key to our understanding of neutron stars. In a new experiment designed to study the symmetry energy, the multiplicities of negatively

Luke A. Barnes, Geraint F. Lewis

Curiously, our Universe was born in a low entropy state, with abundant free energy to power stars and life. The form that this free energy takes is usually thought to be gravitational: the Universe is almost perfectly smooth, and so can produce sources of energy as matter collapses under gravity. It has recently been argued that a more important source of lo

Noor Ali Al-Athba Al-Marri, Bekir Sait Ciftler, Mohamed Abdallah

Internet of things (IoT) devices are prone to attacks due to the limitation of their privacy and security components. These attacks vary from exploiting backdoors to disrupting the communication network of the devices. Intrusion Detection Systems (IDS) play an essential role in ensuring information privacy and security of IoT devices against these attacks. R

H. Moradpour, A. H. Ziaie, C. Corda

It has been recently shown that the Bekenstein entropy bound is not respected by the systems satisfying modified forms of Heisenberg uncertainty principle (HUP) including the generalized and extended uncertainty principles, or even their combinations. On the other, the use of generalized entropies, which differ from Bekenstein entropy, in describing gravity

Chirag Kyal

One of the key research areas in computer vision addressed by a vast number of publications is the processing and understanding of images containing human faces. The most often addressed tasks include face detection, facial landmark localization, face recognition and facial expression analysis. Other, more specialized tasks such as affective computing, the e

Anand A. Joshi, Soyoung Choi, Haleh Akrami, Richard M. Leahy

Due to the spontaneous nature of resting-state fMRI (rs-fMRI) signals, cross-subject comparison and therefore, group studies of rs-fMRI are challenging. Most existing group comparison methods use features extracted from the fMRI time series, such as connectivity features, independent component analysis (ICA), and functional connectivity density (FCD) methods

Changhe Song, Jingbei Li, Yixuan Zhou, Zhiyong Wu

Syntactic structure of a sentence text is correlated with the prosodic structure of the speech that is crucial for improving the prosody and naturalness of a text-to-speech (TTS) system. Nowadays TTS systems usually try to incorporate syntactic structure information with manually designed features based on expert knowledge. In this paper, we propose a syntac

I. Yu. Mogilnykh

Let L be a Desarguesian 2-spread in the Grassmann graph $J_q(n,2)$. We prove that the collection of the 4-subspaces, which do not contain subspaces from L is a completely regular code in $J_q(n,4)$. Similarly, we construct a completely regular code in the Johnson graph $J(n,6)$ from the Steiner quadruple system of the extended Hamming code. We obtain several

Abhejit Rajagopal, Vamshi C. Madala, Shivkumar Chandrasekaran, Peder E. Z. Larson

We study generalization in deep learning by appealing to complexity measures originally developed in approximation and information theory. While these concepts are challenged by the high-dimensional and data-defined nature of deep learning, we show that simple vector quantization approaches such as PCA, GMMs, and SVMs capture their spirit when applied layer-

Kai Zhang, Hao Qian, Qing Cui, Qi Liu

In the Click-Through Rate (CTR) prediction scenario, user's sequential behaviors are well utilized to capture the user interest in the recent literature. However, despite being extensively studied, these sequential methods still suffer from three limitations. First, existing methods mostly utilize attention on the behavior of users, which is not always suita

Hao Li, Bo-Qiang Ma

Recent studies on the high-energy photons from gamma-ray bursts~(GRBs) suggested a light speed variation $v(E)=c(1-E/E_{\mathrm{LV}})$ with $E_\mathrm{LV}=3.6\times 10^{17}$ GeV. We check this speed variation from previous observations on light curves of three active galactic nuclei (AGNs), namely Markarian 421 (Mrk 421), Markarian 501 (Mrk 501) and PKS 2155

Zhixin Qi, Hongzhi Wang, Haoran Zhang

To effectively manage increasing knowledge graphs in various domains, a hot research topic, knowledge graph storage management, has emerged. Existing methods are classified to relational stores and native graph stores. Relational stores are able to store large-scale knowledge graphs and convenient in updating knowledge, but the query performance weakens obvi

Sabirat Rubya, Joseph Numainville, Svetlana Yarosh

Targeting the right group of workers for crowdsourcing often achieves better quality results. One unique example of targeted crowdsourcing is seeking community-situated workers whose familiarity with the background and the norms of a particular group can help produce better outcome or accuracy. These community-situated crowd workers can be recruited in diffe

Bolin Lai, Yuhsuan Wu, Xiaoyu Bai, Xiao-Yun Zhou

Using radiological scans to identify liver tumors is crucial for proper patient treatment. This is highly challenging, as top radiologists only achieve F1 scores of roughly 80% (hepatocellular carcinoma (HCC) vs. others) with only moderate inter-rater agreement, even when using multi-phase magnetic resonance (MR) imagery. Thus, there is great impetus for com

Joel L. Schiff

The Arithmetic Fourier Transform is a numerical formulation for computing Fourier series and Taylor series coefficients. It competes with the Fast Fourier Transform in terms of speed and efficiency, requiring only addition operations and can be performed by parallel processing. The AFT has some deep connections with the Prime Number Theorem and its rich hist

Jia Meng, Jae Bem You, Gilmar F. Arends, Hao Hao

In situ observation of precipitation or phase separation induced by solvent addition is important in studying its dynamics. Combined with optical and fluorescence microscopy, microfluidic devices have been leveraged in studying the phase separation in various materials including biominerals, nanoparticles, and inorganic crystals. However, strong scattering f

Jiashuo Jiang, Xiaocheng Li, Jiawei Zhang

We consider a general online stochastic optimization problem with multiple budget constraints over a horizon of finite time periods. In each time period, a reward function and multiple cost functions are revealed, and the decision maker needs to specify an action from a convex and compact action set to collect the reward and consume the budget. Each cost fun

Fengge Zhang, Yungui Gong, Jiong Lin, Yizhou Lu

Enormous information about interactions is contained in the non-Gaussianities of the primordial curvature perturbations, which are essential to break the degeneracy of inflationary models. We study the primordial bispectra for G-inflation models predicting both sharp and broad peaks in the primordial scalar power spectrum. We calculate the non-Gaussianity pa

Chenhao Xie, Jieyang Chen, Jesun S Firoz, Jiajia Li

Designing efficient and scalable sparse linear algebra kernels on modern multi-GPU based HPC systems is a daunting task due to significant irregular memory references and workload imbalance across the GPUs. This is particularly the case for Sparse Triangular Solver (SpTRSV) which introduces additional two-dimensional computation dependencies among subsequent