November 2019 arXiv papers — page 7

Ansong Ni, Pengcheng Yin, Graham Neubig

A semantic parser maps natural language commands (NLs) from the users to executable meaning representations (MRs), which are later executed in certain environment to obtain user-desired results. The fully-supervised training of such parser requires NL/MR pairs, annotated by domain experts, which makes them expensive to collect. However, weakly-supervised sem

Mengbin Ye, Ji Liu, Brian D. O. Anderson, Ming Cao

This paper focuses on the equilibria and their regions of attraction for continuous-time nonlinear dynamical systems. The classical Poincar\'e--Hopf Theorem from differential topology is used to derive a result on a sufficient condition on the Jacobian for the existence of a unique equilibrium for the system, which is in fact locally exponentially stable. We

Mariana Macedo, Laura Lotero, Alessio Cardillo, Hugo Barbosa

Public stakeholders implement several policies and regulations to tackle gender gaps, fostering the change in the cultural constructs associated with gender. One way to quantify if such changes elicit gender equality is by studying mobility. In this work, we study the daily mobility patterns of women and men occurring in Medell\'in (Colombia) in two years: 2

Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan

Domain adaptation (DA) and domain generalization (DG) have emerged as a solution to the domain shift problem where the distribution of the source and target data is different. The task of DG is more challenging than DA as the target data is totally unseen during the training phase in DG scenarios. The current state-of-the-art employs adversarial techniques,

Xuewen Shi, Heyan Huang, Ping Jian, Yuhang Guo

Recently, Chinese word segmentation (CWS) methods using neural networks have made impressive progress. Most of them regard the CWS as a sequence labeling problem which construct models based on local features rather than considering global information of input sequence. In this paper, we cast the CWS as a sequence translation problem and propose a novel sequ

Yawei Lu, Wei Chen, H. Vincent Poor

Recently coded caching has emerged as a promising means to handle continuously increasing wireless traffic. However, coded caching requires users to cooperate in order to minimize the overall transmission rate. How users with heterogeneous preferences cooperate in coded caching and how to calculate the resulting caching gains are still open problems. In this

Ai Guan, Andrey Lazarev, Yunhe Sheng, Rong Tang

We give a general treatment of deformation theory from the point of view of homotopical algebra following Hinich, Manetti and Pridham. In particular, we show that any deformation functor in characteristic zero is controlled by a certain differential graded Lie algebra defined up to homotopy, and also formulate a noncommutative analogue of this result valid i

İnci Akkaya Oralhan, Raúl Michel, Yonca Karslı, Hikmet Çakmak

The CCD UBV(RI)KC photometry of the poorly studied open clusters Juchert 9 (Juc 9) and Berkeley 97 (Be 97), which are observed with the 0.84 m telescope at the San Pedro M\'artir National Observatory, M\'exico has been analysed. For the likely cluster members, we determined the reddenings, E(B-V)=0.82 +- 0.04 (Juc 9) and E(B-V)=0.87 +- 0.05 (Be 97), from the

Wooyoung Chin

We provide new simple proofs of the Kolmogorov extension theorem and Prokhorovs' theorem. The proof of the Kolmogorov extension theorem is based on the simple observation that $\mathbb{R}$ and the product measurable space $\{0,1\}^\mathbb{N}$ are Borel isomorphic. To show Prokhorov's theorem, we observe that we can assume that the underlying space is $\mathb

Adam G. M. Lewis, Guifré Vidal

We numerically compute renormalized expectation values of quadratic operators in a quantum field theory (QFT) of free Dirac fermions in curved two-dimensional (Lorentzian) spacetime. First, we use a staggered-fermion discretization to generate a sequence of lattice theories yielding the desired QFT in the continuum limit. Numerically-computed lattice correla

Agnibha De Sarkar, Sayan Biswas, Nayantara Gupta

The recently observed data by AMS-02 clearly confirms that the positron flux rises with energy and shows a peak near a few hundred GeV. This rising positron flux cannot be explained by interactions of cosmic rays with interstellar hydrogen gas. In this paper, our goal is to study whether secondary production due to cosmic ray interactions in nearby Galactic

Melkior Ornik, Ufuk Topcu

This paper proposes a formal approach to online learning and planning for agents operating in a priori unknown, time-varying environments. The proposed method computes the maximally likely model of the environment, given the observations about the environment made by an agent earlier in the system run and assuming knowledge of a bound on the maximal rate of

Jiaqi Zhang, Beilun Wang

Because tensor data appear more and more frequently in various scientific researches and real-world applications, analyzing the relationship between tensor features and the univariate outcome becomes an elementary task in many fields. To solve this task, we propose \underline{Fa}st \underline{S}parse \underline{T}ensor \underline{R}egression model (FasTR) ba

Anirban Kundu, Hyunsoo Yang, M. B. A. Jalil

Weyl semimetals (WSM) exhibit chiral anomaly in their magnetotransport due to broken conservation laws. Here, we analyze the magnetotransport of WSM in the presence of the time-reversal symmetry-breaking tilt parameter. The analytical expression for the magnetoconductivity is derived in the small tilt limit using the semiclassical Boltzmann equation. We pred

Amit Kumar Prasad, Jitendra Kumar, Ashok Kumar

In present work, we have studied a new stellar distribution model with spherically symmetric matter and an uncharged isotropic distribution in general relativity. In this model, we have considered a particular metric potential. The model is capable to represents some known compact stars like Her X-1,4U 1538-52 and SAX J1808.4-3658.The model satisfy the energ

Roman Cherniha, Vasyl' Davydovych

Q-conditional (nonclassical) symmetries of the known three-component reaction-diffusion system [K. Aoki et al Theor. Pop. Biol. 50(1) (1996)] modeling interaction between farmers and hunter-gatherers are constructed for the first time. A wide variety of Q-conditional symmetries are found in an explicit form and it is shown that these symmetries are not equiv

Rishikesh Yadav, Ramakanta Meher, Vishnu Narayan Mishra

This paper deals with the approximations of Durrmeyer type generalization of Szasz-Mirakjan operators. We establish the direct results, quantitative Voronovskaya type theorem, Gruss type theorem, A-statistical convergence, rate of convergence in terms of the function with derivative of bounded variation. At last, the graphical analysis, comparison study and

Yong-Su Kim, Young-Wook Cho, Hyang-Tag Lim, Sang-Wook Han

Entanglement among multiple particles is a keystone for not only fundamental research on quantum information but also various practical quantum information applications. In particular, W state has attracted a lot of attention due to the robustness against particle loss and the applications in multiparty quantum communication. However, it is challenging to ge

Mikhail Y. Shalaginov, Sensong An, Yifei Zhang, Fan Yang

Active metasurfaces, whose optical properties can be modulated post-fabrication, have emerged as an intensively explored field in recent years. The efforts to date, however, still face major performance limitations in tuning range, optical quality, and efficiency especially for non mechanical actuation mechanisms. In this paper, we introduce an active metasu

Ulrich Horst, Wei Xu

We provide a general probabilistic framework within which we establish scaling limits for a class of continuous-time stochastic volatility models with self-exciting jump dynamics. In the scaling limit, the joint dynamics of asset returns and volatility is driven by independent Gaussian white noises and two independent Poisson random measures that capture the

A. J. Santos

With blockchain technology, information is recorded in a permanent distributed ledger that is maintained by multiple computers in a peer-to-peer network. There is no central authority that can alter records or change network consensus rules. Such technology could be utilized for voting, title transfers, issuance of company shares, document notarization, but

M. T. Huynh, N. Seymour, R. P. Norris, T. J. Galvin

We present a new image of the 9.0 GHz radio emission from the extended Chandra Deep Field South. A total of 181 hours of integration with the Australia Telescope Compact Array has resulted in a 0.276 square degree image with a median sensitivity of $\sim$20 $\mu$Jy/beam rms, for a synthesised beam of 4.0 $\times$ 1.3 arcsec. We present a catalogue of the 9.0

Axel Pérez-Obiol, Taksu Cheon

We consider the solution of the quantum Coulomb problem in one dimension with the most general connection condition at the origin. The divergence of the derivative of the wave function at the origin invalidates the standard current conservation approach. We explore two approaches, Wronskian self-adjoint extension method and cutoff regularization method, and

Jiaqi Zhang, Yinghao Cai, Zhaoyang Wang, Beilun Wang

Recently, tensor data (or multidimensional array) have been generated in many modern applications, such as functional magnetic resonance imaging (fMRI) in neuroscience and videos in video analysis. Many efforts are made in recent years to predict the relationship between tensor features and univariate responses. However, previously proposed methods either lo

Hikaru Hirano

Minhyong Kim introduced arithmetic Chern-Simons invariants for totally imaginary number fields as arithmetic analogues of the Chern-Simons invariants for 3-manifolds. In this paper, we extend Kim's definition for any number field, by using the modified \'etale cohomology groups and fundamental groups which take real places into account. We then show explicit

Liang Fang, Jian Wang

We present a visual interpretation of fiber mode degeneracy lifting as SOI (Imbert-Fedorov shift) of OAM modes in a ray picture, and the analytical results are verified by comparing them with eigen equation solutions.

Xingpeng Li, Qianxue Xia

Transmission expansion planning (TEP) is critical for the power grid to meet fast growing demand in the future. Traditional TEP model does not utilize the flexibility in the transmission network that is considered as static assets. However, as the load profile may have different seasonal patterns, the optimal network configuration could be very different for

Xingpeng Li, Qianxue Xia

There has been a significant growth of variable renewable generation in the power grid today. However, the industry still uses deterministic optimization to model and solve the optimal power flow (OPF) problem for real-time generation dispatch that ignores the uncertainty associated with intermittent renewable power. Thus, it is necessary to study stochastic

Vladimir N. Potapov

A pair of orthogonal latin cubes of order $q$ is equivalent to an MDS code with distance $3$ or to an ${\rm OA}_1(3,5,q)$ orthogonal array. We construct pairs of orthogonal latin cubes for a sequence of previously unknown orders $q_i=16(18i-1)+4$ and $q'_i=16(18i+5)+4$. The minimal new obtained parameters of orthogonal arrays are ${\rm OA}_1(3,5,84)$. Keywor

Naor Alaluf, Alina Ene, Moran Feldman, Huy L. Nguyen

We study the problem of maximizing a non-monotone submodular function subject to a cardinality constraint in the streaming model. Our main contribution is a single-pass (semi-)streaming algorithm that uses roughly $O(k / \varepsilon^2)$ memory, where $k$ is the size constraint. At the end of the stream, our algorithm post-processes its data structure using a

Chien-Ying Yang, Yi-Chi Chang, Hung-Hsiang Liang, Che-Yen Chu

Instruments flown on CubeSats are small. Meaningful applications of CubeSats in astronomical observations rely on the choice of a particular subject that is feasible for CubeSats. Here we report the result of a feasibility study for observing gamma-ray polarization from Cygnus X-1 using a small Compton polarimeter on board a 3U CubeSat. Silicon detectors and

Shiyuan Li

Spike-timing dependent plasticity (STDP) which observed in the brain has proven to be important in biological learning. On the other hand, artificial neural networks use a different way to learn, such as Back-Propagation or Contrastive Hebbian Learning. In this work, we propose a new framework called mstdp that learn almost the same way biological learning u

Himangsu Bhaumik, Giuseppe Foffi, Srikanth Sastry

Yielding behavior in amorphous solids has been investigated in computer simulations employing uniform and cyclic shear deformation. Recent results characterise yielding as a discontinuous transition, with the degree of annealing of glasses being a significant parameter. Under uniform shear, discontinuous changes in stresses at yielding occur in the high anne

Jihn E. Kim

The chirality is the key for our world. In this scheme, I present a solution of the long standing gauge hierarchy problem with a hidden sector SU(5)$'$ with representations $\overline{\bf 10}\oplus \overline{\bf 5}\oplus 2\cdot{\bf 5}$. Sideway remarks are on {\it NATURAL HILLTOP} inflation and a bound on the QCD angle $\bar\theta$.

Novak Boskov, Mihailo Isakov, Michel A. Kinsy

Binary analysis is traditionally used in the realm of malware detection. However, the same technique may be employed by an attacker to analyze the original binaries in order to reverse engineer them and extract exploitable weaknesses. When a binary is distributed to end users, it becomes a common remotely exploitable attack point. Code obfuscation is used to

Edmund Heng, Kie Seng Nge

We construct a finite dimensional quiver algebra from the non-simply laced type $B$ Dynkin diagram, which we call the type $B$ zigzag algebra. This leads to a faithful categorical action of the type $B$ braid group $\mathcal{A}(B)$, acting on the homotopy category of its projective modules. This categorical action is also closely related to the topological a

Shinichiro Akiyama, Yoshinobu Kuramashi, Takumi Yamashita, Yusuke Yoshimura

We investigate the phase transition of the four-dimensional Ising model with two types of tensor network scheme, one is the higher-order tensor renormalization group and the other is the anisotropic tensor renormalization group. The results for the internal energy and magnetization obtained by the former algorithm with the impure tensor method, enlarging the

Kai Sheng Lee, Zhao Zhuo, Christophe Couteau, David Wilkowski

Canonical quantum formalism predicts that the interference pattern registered in multi-slit experiments should be a simple combination of patterns observed in two-slit experiments. This has been linked to the validity of Born's rule and verified in precise experiments with photons as well as molecules via nuclear magnetic resonance. Due to the expected unive

Haruka Miyazaki, Takanori Sugimoto, Katsuhiro Morita, Takami Tohyama

Recent experimental study on Tsai-type quasicrystalline approximant Au-Al-Gd has revealed the presence of magnetic orders and phase transitions with changing the Au/Al concentration. Motivated by the experiment, we theoretically investigate whether a successive change of magnetic orders occurs in a minimal magnetic model including the RKKY interaction only.

Wei-Ting Yeh, Misaki Ozawa, Kunimasa Miyazaki, Takeshi Kawasaki

We perform molecular dynamics simulations to investigate the effect of a glass preparation on its yielding transition under oscillatory shear. We use swap Monte Carlo to investigate a broad range of glass stabilities from poorly annealed to highly stable systems. We observe a qualitative change in the nature of yielding, which evolves from ductile to brittle

C P Anil Kumar

For a Dedekind domain $\mathcal{O}$ and a rank two co-torsion module $M\subseteq \mathcal{O}^2$ with invariant factor ideals $\mathcal{L}\supseteq \mathcal{K}$ in $\mathcal{O}$, that is, $\frac{\mathcal{O}^2}{M}\cong \frac{\mathcal{O}}{\mathcal{L}}\oplus \frac{\mathcal{O}}{\mathcal{K}}$ we associate a new projective space invariant element in $\mathbb{PF}^1_

Kaihua Zhang, Jin Chen, Bo Liu, Qingshan Liu

Object co-segmentation is to segment the shared objects in multiple relevant images, which has numerous applications in computer vision. This paper presents a spatial and semantic modulated deep network framework for object co-segmentation. A backbone network is adopted to extract multi-resolution image features. With the multi-resolution features of the rel

Zhanhao Xiao, Hai Wan, Hankui Hankz Zhuo, Andreas Herzig

Hierarchical Task Network (HTN) planning is showing its power in real-world planning. Although domain experts have partial hierarchical domain knowledge, it is time-consuming to specify all HTN methods, leaving them incomplete. On the other hand, traditional HTN learning approaches focus only on declarative goals, omitting the hierarchical domain knowledge.

Jing Xiao, Hualin Zhan, Zaiquan Xu, Xiao Wang

Multilayered graphene-based nanoporous membranes with electrolyte incorporated between individual sheets is a unique nano-heterostructure system in which nanoconfined electrons in graphene and ions confined in between sheets are intimately coupled throughout the entire membrane. In contrast to the general notion that the electrolyte gating is unlikely to app

Zhao-Xu Ji, Pei-Ru Fan, Huan-Guo Zhang, Hou-Zhen Wang

Recently, Wu et al. [Int. J. Theor. Phys. 58, 1854, (2019)] found a serious information leakage problem in Ye and Ji's quantum private comparison protocol [Int. J. Theor. Phys. 56, 1517, (2017)], that is, a malicious participant can steal another's secret data without being detected through an active attack means. In this paper, we show that Wu et al.'s atta

Jianping Wang, Mingxin Wang

We investigate the higher-dimensional forager-exploiter model with homogeneous Neumann boundary condition. The existence and uniqueness of global bounded classical solution is established for the high dimension.

Alexey Svyatkovskiy, Ying Zhao, Shengyu Fu, Neel Sundaresan

In this paper, we propose a novel end-to-end approach for AI-assisted code completion called Pythia. It generates ranked lists of method and API recommendations which can be used by software developers at edit time. The system is currently deployed as part of Intellicode extension in Visual Studio Code IDE. Pythia exploits state-of-the-art large-scale deep l

Nguyen T. Thao, Dominik Rzepka

We propose an entirely redesigned framework of bandlimited signal reconstruction for the time encoding machine (TEM) introduced by Lazar and T\'oth. As the encoding part of TEM consists in obtaining integral values of a bandlimited input over known time intervals, it theoretically amounts to applying a known linear operator on the input. We then approach the

Hong-Hao Ma, Kai Lin, Wei-Liang Qian, Bin Wang

As one of the possible signals for the whereabouts of the critical point on the QCD phase diagram, recently, the multiplicity fluctuations in heavy-ion collisions have aroused much attention. It is a crucial observable of the Beam Energy Scan program of the Relativistic Heavy Ion Collider. In this work, we investigate the centrality dependence of the multipl

Haoran Zhu

In this paper, we will answer one of the questions proposed by Bodur, Del~Pia, Dey, Molinaro and Pokutta in 2017. Specifically, we show that the k-aggregation closure of a covering set is a polyhedron. The proof technique is based on an equivalent condition for the closure of any particular family of cutting-planes to be polyhedral, from the perspective of c

Taotao Wang, Soung Chang Liew, Shengli Zhang

This work applies reinforcement learning (RL) from the AI machine learning field to derive an optimal Bitcoin-like blockchain mining strategy without knowing the details of the blockchain network model. Previously, the most profitable mining strategy was believed to be honest mining encoded in the default blockchain protocol. It was shown later that it is po

Khépani Raya, Lei Chang, Minghui Ding, Daniele Binosi

A valuable approach to the analysis of hadron physics observables is provided by QCD's equations-of-motion; namely, the Dyson-Schwinger equations. Drawing from a diverse collection of predictions, we revisit: $\gamma \gamma^* \to$ neutral pseudoscalar transition form factors, their corresponding valence-quark distribution amplitudes and a recent result on th

Fucai Lin, Rongxin Shen, Chuan Liu

We study the heredity of the classes of generalized metric spaces (for example, spaces with a $\sigma$-hereditarily closure-preserving $k$-network, spaces with a point-countable base, spaces with a base of countable order, spaces with a point-regular base, Nagata-spaces, $c$-semi-stratifiable spaces, $\gamma$-spaces, semi-metrizable spaces) to the hyperspace

Haruki Watanabe, Masaki Oshikawa, Tohru Koma

We address the question whether time translation symmetry can be spontaneously broken in a quantum many-body system. One way of detecting such a symmetry breaking is to examine the time-dependence of a correlation function. If the large-distance behavior of the correlation function exhibits a nontrivial time-dependence in the thermodynamic limit, the system

Meng Bao, Fucai Lin

Topological gyrogroups, with a weaker algebraic structure than groups, have been investigated recently. In this paper, we prove that every feathered strongly topological gyrogroup is paracompact, which implies that every feathered strongly topological gyrogroup is a $D$-space and gives partial answers to two questions posed by A.V.Arhangel' ski\v\i ~(2010) i

Yilong Zhu, Dong Han, Bohuan Xue, Jianhao Jiao

Road curb detection is very important and necessary for autonomous driving because it can improve the safety and robustness of robot navigation in the outdoor environment. In this paper, a novel road curb detection method based on tensor voting is presented. The proposed method processes the dense point cloud acquired using a 3D LiDAR. Firstly, we utilize a

Chaoli Yang, Yan Gao, Chengbing Qin, Xilong Liang

Monolayer transition metal dichalcogenides (TMDs) are direct gap semiconductors emerging promising applications in diverse optoelectronic devices. To improve performance, recent investigations have been systematically focused on the tuning of their optical properties. However, an all-optical approach with the reversible feature is still a challenge. Here we

Yongxing Wu, Fucai Lin

In this paper, we discuss some properties of of $G$-hull, $G$-kernel and $G$-connectedness, and extend some results of \cite{life34}. In particular, we prove that the $G$-connectedness are preserved by countable product. Moreover, we introduce the concept of $G$-topological group, and prove that a $G$-topological group is a $G$-topology under the assumption

Atsutoshi Ikeda, Shun Koibuchi, Shinji Kitao, Mohamed Oudah

We report the temperature variation of the $^{119}$Sn-M\"{o}ssbauer spectra of the antiperovskite (inverse perovskite) oxide superconductor Sr$_{3-x}$SnO. Both superconductive (Sr-deficient) and non-superconductive (nearly stoichiometric) samples exhibit major $\gamma$-ray absorption with isomer shift similar to that of Mg$_2$Sn. This fact shows that Sr$_{3-

Batya Kenig, Pranay Mundra, Guna Prasad, Babak Salimi

Acyclic schemes have numerous applications in databases and in machine learning, such as improved design, more efficient storage, and increased performance for queries and machine learning algorithms. Multivalued dependencies (MVDs) are the building blocks of acyclic schemes. The discovery from data of both MVDs and acyclic schemes is more challenging than o

Caleb Helbling, Samuel Z Guyer

This paper presents the design and implementation of Juniper: a functional reactive programming language (FRP) targeting the Arduino and related microcontroller systems. Juniper provides a number of high level features, including parametric polymorphic functions, anonymous functions, automatic memory management, and immutable data structures. Also included i

Wenjuan Li, Huiju Wang

In this paper, we consider the pointwise convergence for a class of generalized Schr\"{o}dinger operators with suitable perturbations, and convergence rate for a class of generalized Schr\"{o}dinger operators with polynomial growth. We show that the pointwise convergence results remain valid for a class of generalized Schr\"{o}dinger operators under small pe

Dinusha Vatsalan, Peter Christen, Erhard Rahm

Privacy-Preserving Record Linkage (PPRL) supports the integration of sensitive information from multiple datasets, in particular the privacy-preserving matching of records referring to the same entity. PPRL has gained much attention in many application areas, with the most prominent ones in the healthcare domain. PPRL techniques tackle this problem by conduc

YongJie Ye, Jingjing Zhang, Weigang Wu, Xiapu Luo

The payment channel, which allows two parties to perform micropayments without involving the blockchain, has become a promising proposal to improve the scalability of decentralized ledgers such as Bitcoin and Ethereum. Payment channels have been extended to the payment network, through which users can utilize existing channels as intermediary links to route

Naoya Takahashi, Mayank Kumar Singh, Sakya Basak, Parthasaarathy Sudarsanam

Despite recent advances in voice separation methods, many challenges remain in realistic scenarios such as noisy recording and the limits of available data. In this work, we propose to explicitly incorporate the phonetic and linguistic nature of speech by taking a transfer learning approach using an end-to-end automatic speech recognition (E2EASR) system. Th

Russell Tsuchida, Fred Roosta, Marcus Gallagher

It is well-known that the distribution over functions induced through a zero-mean iid prior distribution over the parameters of a multi-layer perceptron (MLP) converges to a Gaussian process (GP), under mild conditions. We extend this result firstly to independent priors with general zero or non-zero means, and secondly to a family of partially exchangeable

Bo-Wen Chen, Yen-Min Hsu, Hung-Yi Lee

Several results in the computer vision literature have shown the potential of randomly weighted neural networks. While they perform fairly well as feature extractors for discriminative tasks, a positive correlation exists between their performance and their fully trained counterparts. According to these discoveries, we pose two questions: what is the value o

Jheng-Jie Chen

We show that the set of threefold canonical thresholds satisfies the ascending chain condition. Moreover, we derive that threefold canonical thresholds in the interval $ (\frac{1}{2}, 1)$ consists of $ \{ \frac{1}{2}+\frac{1}{n}\}_{n \ge 3} \cup \{ \frac{4}{5}\}$.

Nicolas Privault, Liang Wang

This paper considers a general stochastic SIR epidemic model driven by a multidimensional Levy jump process with heavy tailed increments and possible correlation between noise components. In this framework, we derive new sufficient conditions for disease extinction and persistence in the mean. Our method differs from previous approaches by the use of Kunita'

Xinting Yu, Sarah M. Horst, Chao He, Patricia McGuiggan

Sand electrification is important for aeolian sediment transportation on terrestrial bodies with silicate sand as the main sediment composition. However, it has not been thoroughly studied for icy bodies such as Titan with organic sand as the main dune-forming material. We used the colloidal probe atomic force microscopy (AFM) technique to study triboelectri

Georgios Smyrnis, Petros Maragos

In this work, we examine the process of Tropical Polynomial Division, a geometric method which seeks to emulate the division of regular polynomials, when applied to those of the max-plus semiring. This is done via the approximation of the Newton Polytope of the dividend polynomial by that of the divisor. This process is afterwards generalized and applied in

Inho Kwak, Min-Cheol Lee, Byung Cheol Park, Choong H. Kim

We investigate the ultrafast dynamics of Cd$_2$Os$_2$O$_7$, a prototype material showing a Lifshitz-type transition as a function of temperature. In the paramagnetic metallic state, the photo-reflectivity shows a sub-picosecond relaxation, followed by a featureless small offset. In the antiferromagnetic state slightly below $T_N$, however, the photo-reflecti

Inho Kwak, Jaeseok Son, Bumjoo Lee, Thomas Wolf

Electronic nematicity have attracted a great deal of interest in the unconventional superconductivity research. We present an experimental method to investigate reflectivity anisotropy by the electronic nematicity and its non-equilibrium dynamics. Our experimental results on Ba(Fe$_{0.955}$Co$_{0.045}$)$_{2}$As$_{2}$ single crystal clearly feature the broken

Van-Duc Le, Tien-Cuong Bui, Sang Kyun Cha

Recently, air pollution is one of the most concerns for big cities. Predicting air quality for any regions and at any time is a critical requirement of urban citizens. However, air pollution prediction for the whole city is a challenging problem. The reason is, there are many spatiotemporal factors affecting air pollution throughout the city. Collecting as m

Yuxuan Zhao, Xinyan Cao, Jinlong Lin, Dunshan Yu

There has been an encouraging progress in the affective states recognition models based on the single-modality signals as electroencephalogram (EEG) signals or peripheral physiological signals in recent years. However, multimodal physiological signals-based affective states recognition methods have not been thoroughly exploited yet. Here we propose Multiscal

Peng Chen, Ivan Nourdin, Lihu Xu, Xiaochuan Yang

By a delicate analysis for the Stein's equation associated to the $\alpha$-stable law approximation with $\alpha \in (0,2)$, we prove a quantitative stable central limit theorem in Wasserstein type distance, which generalizes the results in the series of work \cite{Xu19, CNX19+,CNXYZ19+} from the univariate case to the multiple variate case. From an explicit

Masashi Wakaiki, Hideki Sano

This paper addresses the following question: "Suppose that a state-feedback controller stabilizes an infinite-dimensional linear continuous-time system. If we choose the parameters of an event/self-triggering mechanism appropriately, is the event/self-triggered control system stable under all sufficiently small nonlinear Lipschitz perturbations?" We assume t

Mohammad Sababheh, Hamid Reza Moradi, Ibrahim Halil Gümüş, Shigeru Furuichi

The main goal of this exposition is to present further analysis of the Kantorovich and Ando operator inequalities. In particular, a new proof of Ando's inequality is given, a new non-trivial refinement of Kantorovich inequality is shown, and some equivalent forms of Kantorovich inequality are presented with a Minkowski-type application.

Junghyup Lee, Dohyung Kim, Wonkyung Lee, Jean Ponce

We address the problem of semantic correspondence, that is, establishing a dense flow field between images depicting different instances of the same object or scene category. We propose to use images annotated with binary foreground masks and subjected to synthetic geometric deformations to train a convolutional neural network (CNN) for this task. Using thes

Xinmeng Chen, Zhenhua Chai, Huili Wang, Baochang Shi

In this paper, a kind of finite-difference lattice Boltzmann method with the second-order accuracy of time and space (T2S2-FDLBM) is proposed. In this method, a new simplified two-stage fourth order time-accurate discretization approach is applied to construct time marching scheme, and the spatial gradient operator is discretized by a mixed difference scheme

J. H. Xu, A. X. Chen, W. Yang, G. R. Jin1

Performing homodyne detection at one port of squeezed-state light interferometer and then binarzing measurement data are important to achieve super-resolving and super-sensitive phase measurements. Here we propose a new data-processing technique by dividing the measurement quadrature into three bins (equivalent to a multi-outcome measurement), which leads to

Ziqi Pang, Zhiyuan Hu, Pavel Tokmakov, Yu-Xiong Wang

Virtually all of deep learning literature relies on the assumption of large amounts of available training data. Indeed, even the majority of few-shot learning methods rely on a large set of "base classes" for pretraining. This assumption, however, does not always hold. For some tasks, annotating a large number of classes can be infeasible, and even collectin

Seidon Alsaody, Vladimir Chernousov, Arturo Pianzola

Any group of type ${\rm F}_4$ is obtained as the automorphism group of an Albert algebra. We prove that such a group is $R$-trivial whenever the Albert algebra is obtained from the first Tits construction. Our proof uses cohomological techniques and the corresponding result on the structure group of such Albert algebras.

Xiaojun Cai, Ruidong Li, Changcheng Sheng, Yifeng Tao

Background:Diverse tacrolimus population pharmacokinetic models in adult liver transplant recipients have been established to describe the PK characteristics of tacrolimus in the last two decades. However, their extrapolated predictive performance remains unclear.Therefore,in this study,we aimed to evaluate their external predictability and identify their po

Seidon Alsaody, Vladimir Chernousov, Arturo Pianzola

We prove that the structure group of any Albert algebra over an arbitrary field is $R$-trivial. This implies the Tits-Weiss conjecture for Albert algebras and the Kneser-Tits conjecture for isotropic groups of type $\mathrm{E}_{7,1}^{78}, \mathrm{E}_{8,2}^{78}$. As a further corollary, we show that some standard conjectures on the groups of $R$-equivalence c

Fabian Krinner

Modern hadron-spectroscopy experiments such as COMPASS collect data samples of unprecedented size, so that novel analysis techniques become possible and necessary. One such technique is the freed-isobar partial-wave analysis (PWA). In this approach, fixed parametrizations for the amplitudes of intermediate states commonly modeled using Breit-Wigner shapes ar

Kenichiro Tanaka, Yasuhiro Mukaigawa, Achuta Kadambi

This paper presents a method of passive non-line-of-sight (NLOS) imaging using polarization cues. A key observation is that the oblique light has a different polarimetric signal. It turns out this effect is due to the polarization axis rotation, a phenomena which can be used to better condition the light transport matrix for non-line-of-sight imaging. Our an

Błażej Osiński, Adam Jakubowski, Piotr Miłoś, Paweł Zięcina

We use reinforcement learning in simulation to obtain a driving system controlling a full-size real-world vehicle. The driving policy takes RGB images from a single camera and their semantic segmentation as input. We use mostly synthetic data, with labelled real-world data appearing only in the training of the segmentation network. Using reinforcement learni

Stanley C. Solomon1, Laila Andersson, Alan G. Burns, Richard W. Eastes

The NASA Global-scale Observations of the Limb and Disk (GOLD) ultraviolet imaging spectrograph performs observations of upper-atmosphere airglow from the sunlit disk and limb of the Earth, in order to infer quantities such as the composition and temperature of the thermosphere. To interpret the measurements, the observational and solar illumination geometry

Atreyee Kundu

We propose matrix commutator based stability characterization for discrete-time switched linear systems under restricted switching. Given an admissible minimum dwell time, we identify sufficient conditions on subsystems such that a switched system is stable under all switching signals that obey the given restriction. The primary tool for our analysis is comm

Xingpeng Li, Kory W. Hedman

State estimation estimates the system condition in real-time and provides a base case for other energy management system (EMS) applications including real-time contingency analysis and security-constrained economic dispatch. Recent work in the literature shows malicious cyber-attack can inject false measurements that bypass traditional bad data detection in

Masashi Wakaiki, Hideki Sano

This paper addresses the problem of event-triggered control for infinite-dimensional systems. We employ event-triggering mechanisms that compare the plant state and the error of the control input induced by the event-triggered implementation. Under the assumption that feedback operators are compact, a strictly positive lower bound on the inter-event times ca

Zinovy Diskin

Delta lenses are an established mathematical framework for modelling and designing bidirectional model transformations. Following the recent observations by Fong et al, the paper extends the delta lens framework with a a new ingredient: learning over a parameterized space of model transformations seen as functors. We define a notion of an asymmetric learning

Renee Su, Rong Chen

This paper presents a change detection method that identifies land cover changes from aerial imagery, using semantic segmentation, a machine learning approach. We present a land cover classification training pipeline with Deeplab v3+, state-of-the-art semantic segmentation technology, including data preparation, model training for seven land cover types, and

Pavel Sultanich

In this note we prove that the explicit realization of arbitrary complex powers of generators of quantum group $U_{q}(\mathfrak{sl}(2))$ satisfies all the commutation relations of the algebra of complex powers, including the generalized Kac's identity which was announced in our previous paper. It turns out that the latter identity in this realization is equi

Michal Zajaček, Andreas Eckart, Silke Britzen, Bozena Czerny

For about 500 intermediate-redshift sources ($0.04<z<0.4$), whose radio flux densities at $1.4\,{\rm GHz}$ are larger than 10 mJy, we performed additional observations at 4.85 GHz and 10.45 GHz using 100-m Effelsberg telescope. Our radio-optical galaxies are located preferentially in the composite and AGN spectral classes in the narrow line optical diagnosti

Amanuel Tamirat

This paper proposes a quantum circuit for computing the mean value from a given set of quantum states. The circuit consults a Quantum Random Access Memory to get the values of the set, and by using superposition, interference and entanglement phenomena, it can estimate the mean value in $\mathcal{O}(\frac{1}{\epsilon}\log{Nd})$ complexity. The proposed quant

Tianzhe Bao, Syed Ali Raza Zaidi, Shengquan Xie, Pengfei Yang

Convolutional neural network (CNN) has been widely exploited for simultaneous and proportional myoelectric control due to its capability of deriving informative, representative and transferable features from surface electromyography (sEMG). However, muscle contractions have strong temporal dependencies but conventional CNN can only exploit spatial correlatio

Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock

We propose an efficient distributed online learning protocol for low-latency real-time services. It extends a previously presented protocol to kernelized online learners that represent their models by a support vector expansion. While such learners often achieve higher predictive performance than their linear counterparts, communicating the support vector ex

Mounia Bouabdellah, Faissal El Bouanani, Mohamed-Slim Alouini

In this paper, the physical layer security of a dual-hop underlay uplink cognitive radio network is investigated over Nakagami-m fading channels. Specifically, multiple secondary sources are taking turns in accessing the licensed spectrum of the primary users and communicating with a multiantenna secondary base station D through the aid of a multiantenna rel