March 2020 arXiv papers — page 111

Francesco Becattini, Michael Lisa

The quark-gluon plasma produced by collisions between ultra-relativistic heavy nuclei is well described in the language of hydrodynamics. Non-central collisions are characterized by very large angular momentum, which in a fluid system manifests as flow vorticity. This rotational structure can lead to a spin polarization of the hadrons that eventually emerge

Tom Banks, Willy Fischler

We revisit the construction of models of quantum gravity in d dimensional Minkowski space in terms of random tensor models, and correct some mistakes in our previous treatment of the subject. We find a large class of models in which the large impact parameter scattering scales with energy and impact parameter like Newton`s law. The scattering amplitudes in t

Paula Cutipa, Kirill Yu. Spasibko, Maria V. Chekhova

We present a direct measurement of the spatiotemporal coherence of parametric down-conversion in the range of negative group-velocity dispersion. In this case, the frequency-angular spectra are ring-shaped and temporal coherence is coupled to spatial coherence. Correspondingly, the lack of coherence due to spatial displacement can be compensated with the int

Majed El Helou, Frederike Dümbgen, Sabine Süsstrunk

The large capacity of neural networks enables them to learn complex functions. To avoid overfitting, networks however require a lot of training data that can be expensive and time-consuming to collect. A common practical approach to attenuate overfitting is the use of network regularization techniques. We propose a novel regularization method that progressiv

A. A. Osipov, A. A. Pivovarov, M. K. Volkov, M. M. Khalifa

The rates and spectra of the anomalous $η\toπ^+π^-γ$ and $η' \toπ^+π^-γ$ decays are calculated. The approach is based on the effective meson Lagrangian obtained in the Nambu-Jona-Lasinio model with vector and axial-vector mesons by integrating out quark fields. The resulting action is affected by mixing between members of pseudoscalar $J^{PC}=0^{-+}$ and

Oliver Herbort, Peter Woitke, Christiane Helling, Aubrey Zerkle

Little is known about the interaction between atmospheres and crusts of exoplanets so far, but future space missions and ground-based instruments are expected to detect molecular features in the spectra of hot rocky exoplanets. We aim to understand the composition of the gas in an exoplanet atmosphere which is in equilibrium with a planetary crust. Methods.

David M. Page, Suzanne M. Wendelken, Tyler S. Davis, David T. Kluger

Objective: This paper aims to demonstrate functional discriminability among restored hand sensations with different locations, qualities, and intensities that are evoked by microelectrode stimulation of residual afferent fibers in human amputees. Methods: We implanted a Utah Slanted Electrode Array (USEA) in the median and ulnar residual arm nerves of three

Nghia Tuan Duong, Julien Trébosc, Olivier Lafon, Jean-Paul Amoureux

We demonstrate the possibility to use UDEFT (Uniform Driven Equilibrium Fourier Transform) technique in order to improve the sensitivity and the quantification of one-dimensional ${}^{29}$Si NMR experiments under Magic-Angle Spinning (MAS). We derive an analytical expression of the signal-to-noise ratios of UDEFT and single-pulse (SP) experiments subsuming t

Amit Sheth, Swati Padhee, Amelie Gyrard

Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities. However, for dynamic real-world applications such as social networks, recommender systems, computational biology, relational knowledge representation has emerged as a challenging research problem where there is a need to represent

Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang

This paper presents a method to interpret the success of knowledge distillation by quantifying and analyzing task-relevant and task-irrelevant visual concepts that are encoded in intermediate layers of a deep neural network (DNN). More specifically, three hypotheses are proposed as follows. 1. Knowledge distillation makes the DNN learn more visual concepts t

Moritz Herrmann, Philipp Probst, Roman Hornung, Vindi Jurinovic

Multi-omics data, that is, datasets containing different types of high-dimensional molecular variables (often in addition to classical clinical variables), are increasingly generated for the investigation of various diseases. Nevertheless, questions remain regarding the usefulness of multi-omics data for the prediction of disease outcomes such as survival ti

R. da Rocha, A. A. Tomaz

Exotic spinor fields arise from inequivalent spin structures on non-trivial topological manifolds, $M$. This induces an additional term in the Dirac operator, defined by the cohomology group $H^1(M,\mathbb{Z}_2)$ that rules a Cech cohomology class. This formalism is extended for manifolds of any finite dimension, endowed with a metric of arbitrary signature.

Qiang Du, Zhi Zhou

We study a simple nonlocal-in-time dynamic system proposed for the effective modeling of complex diffusive regimes in heterogeneous media. We present its solutions and their commonly studied statistics such as the mean square distance. This interesting model employs a nonlocal operator to replace the conventional first-order time-derivative. It introduces a

Lenore Cowen, Kapil Devkota, Xiaozhe Hu, James M. Murphy

Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffusion state distance (DSD), which compares points using a data-driven diffusion process. Unlike related diffusion methods, DSDs incorporate information across time scales, which allo

Michael Boldin

We consider a stationary $AR(p)$ model. The autoregression parameters are unknown as well as the distribution of innovations. Based on the residuals from the parameter estimates, an analog of empirical distribution function is defined and the tests of Kolmogorov's and $ω^2$ type is constructed for testing hypotheses on the normality of innovations. We ob

Batuhan Kaplan, İbrahim Kahraman, Ali Görçin, Hakan Ali Çırpan

The applications of the unmanned aerial vehicles (UAVs) increase rapidly in everyday life, thus detecting the UAVs and/or its pilot is a crucial task. Many UAVs adopt frequency hopping spread spectrum (FHSS) technology to efficiently and securely communicate with their radio controllers (RC) where the signal follows a hopping pattern to prevent harmful inter

Rishab Sharma, Rahul Deora, Anirudha Vishvakarma

In this paper, we propose an end to end solution for image matting i.e high-precision extraction of foreground objects from natural images. Image matting and background detection can be achieved easily through chroma keying in a studio setting when the background is either pure green or blue. Nonetheless, image matting in natural scenes with complex and unev

Katherine Van Koevering, Austin R. Benson, Jon Kleinberg

There is inherent information captured in the order in which we write words in a list. The orderings of binomials --- lists of two words separated by `and' or `or' --- has been studied for more than a century. These binomials are common across many areas of speech, in both formal and informal text. In the last century, numerous explanations have been

Radek Ošlejšek, Vít Rusňák, Karolína Burská, Valdemar Švábenský

Hands-on training is an effective way to practice theoretical cybersecurity concepts and increase participants' skills. In this paper, we discuss the application of visual analytics principles to the design, execution, and evaluation of training sessions. We propose a conceptual model employing visual analytics that supports the sensemaking activities of

Zhe Li, Chunhua Sun, Chunli Liu, Xiayu Chen

Outlier detection is an important task in data mining and many technologies have been explored in various applications. However, due to the default assumption that outliers are non-concentrated, unsupervised outlier detection may not correctly detect group anomalies with higher density levels. As for the supervised outlier detection, although high detection

Kai Wang, Zhi Zhou

The aim of this paper is to develop and analyze high-order time stepping schemes for solving semilinear subdiffusion equations. We apply the $k$-step BDF convolution quadrature to discretize the time-fractional derivative with order $α\in (0,1)$, and modify the starting steps in order to achieve optimal convergence rate. This method has already been well-stu

Karishma Bansal, Greg Taylor, Kevin Stovall, Jayce Dowell

PSR B1508+55 is known to have a single component profile above 300 MHz. However, when we study it at frequencies below 100 MHz using the first station of the Long Wavelength Array, it shows multiple components. These include the main pulse, a precursor, a postcursor, and a trailing component. The separation of the trailing component from the main peak evolve

Jaroslav Nešetřil, Patrice Ossona de Mendez, Michał Pilipczuk, Xuding Zhu

We prove that if $G$ is a sparse graph --- it belongs to a fixed class of bounded expansion $\mathcal{C}$ --- and $d\in \mathbb{N}$ is fixed, then the $d$th power of $G$ can be partitioned into cliques so that contracting each of these clique to a single vertex again yields a sparse graph. This result has several graph-theoretic and algorithmic consequences

Rodrigo Banuelos, Michal Brzozowski, Adam Osekowski

Let $X$ be a continuous-path martingale and let $Y$ be a stochastic integral, with respect to $X$, of some predictable process with values in $[-1,1]$. We provide an explicit formula for Burkholder's function associated with the weighted $L^2$ bound $$ \|Y\|_{L^2(W)}\lesssim [w]_{A_2}\|X\|_{L^2(W)}.$$

Antonios Nathanail, Ramandeep Gill, Oliver Porth, Christian M. Fromm

The observations of GW170817/GRB170817A have confirmed that the coalescence of a neutron-star binary is the progenitor of a short gamma-ray burst. In the standard picture of a short gamma-ray burst, a collimated highly relativistic outflow is launched after merger and it successfully breaks out from the surrounding ejected matter. Using initial conditions in

Sylvestre Twagirayezu, Gregory E. Hall, Trevor J. Sears

Frequency comb-referenced measurements of sub-Doppler laser saturation dip absorption lines in the $v_1+v_3$ band of acetylene near $1.5\,μ\mathrm{m}$ are reported. These measurements include transitions involving higher rotational levels than previously frequency measured in this band. The accuracy of the measured frequencies is typically better than 10 kHz

Manos Athanasakos, Nicholas Kalouptsidis

This paper is concerned with the general multiple access wiretap channel and the existence of codes that accomplish reliability and strong secrecy. Information leakage to the eavesdropper is assessed by the variational distance metric, whereas the average error probability is bounded by modifying Feinsteins Lemma. We derive an achievable strong secrecy rate

A. Galanopoulos, A. G. Tasiopoulos, G. Iosifidis, T. Salonidis

A large number of emerging IoT applications rely on machine learning routines for analyzing data. Executing such tasks at the user devices improves response time and economizes network resources. However, due to power and computing limitations, the devices often cannot support such resource-intensive routines and fail to accurately execute the analytics. In

Fang Wan, Zheng Wang, Brooke Franchuk, Xinyao Hu

We describe a fluidic actuator design that replaces the sealed chamber of a hydraulic cylinder using a soft actuator to provide compliant linear compression with a large force ($\geq$100 N) at a low operation pressure ($\leq$50 kPa) for a lower-limb wearable. The external shells constrain the deformation of the soft actuator under fluidic pressurization. Thi

Pengli Lu, Chen Dong

The rapid expansion of social network provides a suitable platform for users to deliver messages. Through the social network, we can harvest resources and share messages in a very short time. The developing of social network has brought us tremendous conveniences. However, nodes that make up the network have different spreading capability, which are constrai

A. Galanopoulos, V. Valls, G. Iosifidis, D. J. Leith

We develop an edge-assisted object recognition system with the aim of studying the system-level trade-offs between end-to-end latency and object recognition accuracy. We focus on developing techniques that optimize the transmission delay of the system and demonstrate the effect of image encoding rate and neural network size on these two performance metrics.

Pengli Lu, Chen Dong

The safety and robustness of the network have attracted the attention of people from all walks of life, and the damage of several key nodes will lead to extremely serious consequences. In this paper, we proposed the clustering H-index mixing (CHM) centrality based on the H- index of the node itself and the relative distance of its neighbors. Starting from th

Pengli Lu, JingJuan Yu

The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In thi

Benjamin P. Fingerhut, Jakob Schauss, Achintya Kundu, Thomas Elsaesser

The extent of contact and solvent shared ion pairs of phosphate groups with Na$^+$, Ca$^{2+}$ and Mg$^{2+}$ ions in aqueous environment and their relevance for the stability of polyanionic DNA and RNA structures is highly debated. Employing the asymmetric phosphate stretching vibration of dimethyl phosphate (DMP), a model system of the sugar-phosphate backbo

Shantanu Mishra, Xuelin Yao, Qiang Chen, Kristjan Eimre

Nanographenes with zigzag edges are predicted to manifest non-trivial pi-magnetism resulting from the interplay of hybridization of localized frontier states and Coulomb repulsion between valence electrons. This provides a chemically tunable platform to explore quantum magnetism at the nanoscale and opens avenues toward organic spintronics. The magnetic stab

Jussi Hanhirova, Anton Debner, Matias Hyyppä, Vesa Hirvisalo

Autonomous vehicles need safe development and testing environments. Many traffic scenarios are such that they cannot be tested in the real world. We see hybrid photorealistic simulation as a viable tool for developing AI (artificial intelligence) software for autonomous driving. We present a machine learning environment for detecting autonomous vehicle corne

Songyang Zhang

Even real time video telephony services have been pervasively applied, providing satisfactory quality of experience to users is still a challenge task especially in wireless networks. Multipath transmission is a promising solution to improve video quality by aggregating bandwidth. In existing multipath transmission solutions, sender concurrently splits traff

Tianxin Feng, Lifeng Xie, Jianping Yao, Jie Xu

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless sensor network, in which one UAV flies in the sky to collect the data transmitted from a set of sensors via distributed beamforming. We consider the delay-sensitive application scenario, in which the sensors transmit the common/shared messages by using fixed data rates and adaptive transmit

Tatsuyuki Hikita

Lusztig defined certain involutions on the equivariant K-theory of Slodowy varieties and gave a characterization of certain bases called canonical bases. In this paper, we give a conjectural generalization of these involutions and K-theoretic canonical bases to conical symplectic resolutions which have good Hamiltonian torus actions and state several conject

Thirunavukarasu Balasubramaniam, Richi Nayak, Chau Yuen

With the advancements in computing technology and web-based applications, data is increasingly generated in multi-dimensional form. This data is usually sparse due to the presence of a large number of users and fewer user interactions. To deal with this, the Nonnegative Tensor Factorization (NTF) based methods have been widely used. However existing factoriz

Shasha Li

For a graph $G=(V,E)$ and a set $S\subseteq V(G)$ of size at least $2$, an $S$-Steiner tree $T$ is a subgraph of $G$ that is a tree with $S\subseteq V(T)$. Two $S$-Steiner trees $T$ and $T'$ are internally disjoint (resp. edge-disjoint) if $E(T)\cap E(T')=\emptyset$ and $V(T)\cap V(T')=S$ (resp. if $E(T)\cap E(T')=\emptyset$). Let $κ_G (S)$ (

Lluis Puig

Let p be a prime, P a finite p-group, F a Frobenius P-category and F^sc the full subcategory of F over the set of F-selfcentralizing subgroups of P. Recently, we have understood an easy way to obtain the perfect F^sc-locality P^sc from the basic F^sc-locality L^b: it depends on a suitable filtration of the basic F-locality L^b and on a vanishing cohomology r

Denis Borisov, Matthias Täufer, Ivan Veselic

We consider multi-dimensional Schrödinger operators with a weak random perturbation distributed in the cells of some periodic lattice. In every cell the perturbation is described by the translate of a fixed abstract operator depending on a random variable. The random variables, indexed by the lattice, are assumed to be independent and identically distributed

Xiaodong Cheng, Lanlin Yu, Dingchao Ren, Jacquelien M. A. Scherpen

This paper studies reduced-order modeling of dynamic networks with strongly connected topology. Given a graph clustering of an original complex network, we construct a quotient graph with less number of vertices, where the edge weights are parameters to be determined. The model of the reduced network is thereby obtained with parameterized system matrices, an

Xiongwei Cai, Zhangju Liu, Maosong Xiang

We study representations of hemistrict Lie 2-algebras and give a functorial construction of their cohomology. We prove that both the cohomology of an injective hemistrict Lie 2-algebra $L$ and the cohomology of the semistrict Lie 2-algebra obtained from skew-symmetrization of $L$ are isomorphic to the Chevalley-Eilenberg cohomology of the induced Lie algebra

Aihua Mao, Canglan Dai, Lin Gao, Ying He

3D reconstruction from a single view image is a long-standing prob-lem in computer vision. Various methods based on different shape representations(such as point cloud or volumetric representations) have been proposed. However,the 3D shape reconstruction with fine details and complex structures are still chal-lenging and have not yet be solved. Thanks to the

Mehmet Akif Akyol, Selahattin Beyendi

The main purpose of the present paper is to define and study the notion of quasi bi-slant submanifolds of almost contact metric manifolds. We mainly concerned with quasi bi-slant submanifolds of cosymplectic manifolds as a generalization of slant, semi-slant, hemi-slant, bi-slant and quasi hemi-slant submanifolds. First, we give non-trivial examples in order

T. Ichii, Y. Hazama, N. Naka, K. Tanaka

A fundamental understanding of the photoexcited carrier system in diamond is crucial to facilitate its application in photonic and electronic devices. Here, we studied the detailed balance between free carriers and excitons in pristine diamond by using a deep-ultraviolet (DUV) pump in combination with terahertz (THz) probe spectroscopy. We investigated the t

Benjamin Crinquand, Benoît Cerutti, Alexander Philippov, Kyle Parfrey

Black holes are known to launch powerful relativistic jets and emit highly variable gamma radiation. How these jets are loaded with plasma remains poorly understood. Spark gaps are thought to drive particle acceleration and pair creation in the black-hole magnetosphere. In this paper, we perform 2D axisymmetric general-relativistic particle-in-cell simulatio

Toijam Sunder Meetei, Meerasha Mubarak Ali, Shanmugam Boomadevi, Krishnamoorthy Pandiyan

Domain-engineered quasi-phase-matching (QPM) devices are known for its versatility and ability to tune the nonlinear optical frequency conversion process. In this paper, a simple approach is presented to generate multiple quasi-phase-matched second-harmonic generation (SHG) in the phase reversal optical superlattice (PROS) structure. Theoretical studies are

Zhikang Zou, Yifan Liu, Shuangjie Xu, Wei Wei

The task of crowd counting is extremely challenging due to complicated difficulties, especially the huge variation in vision scale. Previous works tend to adopt a naive concatenation of multi-scale information to tackle it, while the scale shifts between the feature maps are ignored. In this paper, we propose a novel Hierarchical Scale Recalibration Network

Swarup Deb, Pritam Bhattacharyya, Poulab Chakrabarti, Himadri Chakraborti

Electric and thermoelectric properties of strictly monolayer MoS$_2$ films, which are grown using a novel micro-cavity based CVD growth technique, have been studied under diverse environmental and annealing conditions. Resistance of a thermoelectric device that is fabricated on a continuous monolayer MoS$_2$ layer using photolithography technique has been fo

Eric Heiden, Luigi Palmieri, Kai O. Arras, Gaurav S. Sukhatme

Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, a wide variety of motion planners, steer functions and path-improvement techniques have been proposed for such non-holonomic systems. With the objective of comp

J. Terasaki

A new method has been proposed to determine the strength of the isoscalar proton-neutron pairing interaction applicable to many nuclei. The principle is the equivalence between the double charge change and the double transfer of like-particle pair, and a constraint is derived to the effective interactions used in approximations. This method was applied to th

Devansh Saxena, Karla Badillo-Urquiola, Pamela J. Wisniewski, Shion Guha

The U.S. Child Welfare System (CWS) is charged with improving outcomes for foster youth; yet, they are overburdened and underfunded. To overcome this limitation, several states have turned towards algorithmic decision-making systems to reduce costs and determine better processes for improving CWS outcomes. Using a human-centered algorithmic design approach,

Avrajit Bandyopadhyay, Sivarani Thirupathi, Timothy C. Beers, A. Susmitha

The stars SDSS J064655.6+411620.5 and SDSS J193712.01+502455.5 are relatively bright stars that were initially observed as part of the SDSS/MARVELS pre-survey. They were selected, on the basis of their weak CH $G$-bands, along with a total of 60 others, in the range of halo globular cluster metallicities for high-resolution spectroscopic follow-up as a part

Jacek Chmieliński, Moshe Goldberg

In this paper we extend our findings in [3] and answer further questions regarding continuity and discontinuity of seminorms on infinite-dimensional vector spaces.

Bijju Kranthi Veduruparthi, Jayanta Mukherjee, Partha Pratim Das, Moses Arunsingh

Prediction of survivability in a patient for tumor progression is useful to estimate the effectiveness of a treatment protocol. In our work, we present a model to take into account the heterogeneous nature of a tumor to predict survival. The tumor heterogeneity is measured in terms of its mass by combining information regarding the radiodensity obtained in i

Minhua Zhou, Minfeng Gu

The reason for the difference in the composite X-ray spectrum between radio-loud quasars (RLQs) and radio-quiet quasars (RQQs) is still unclear. To study this difference, we built a new composite X-ray spectrum of RLQs by using Chandra X-ray data and Sloan Digital Sky Survey (SDSS) optical data for the sample of 3CRR quasars. We find the X-ray spectra of all

Wansheng Wang, Mengli Mao, Zheng Wang

In this paper stability and error estimates for time discretizations of linear and semilinear parabolic equations by the two-step backward differentiation formula (BDF2) method with variable step-sizes are derived. An affirmative answer is provided to the question: whether the upper bound of step-size ratios for the $l^\infty(0,T;H)$-stability of the BDF2 me

Xiang Zhou, Huizhuo Yuan, Chris Junchi Li, Qingyun Sun

Stochastic version of alternating direction method of multiplier (ADMM) and its variants (linearized ADMM, gradient-based ADMM) plays a key role for modern large scale machine learning problems. One example is the regularized empirical risk minimization problem. In this work, we put different variants of stochastic ADMM into a unified form, which includes st

Ali Choumane, Zein Al Abidin Ibrahim

Social networks include millions of users constantly looking for new relationships for personal or professional purposes. Social network sites recommend friends based on relationship features and content information. A significant part of information shared every day is spread in Hashtags. None of the existing content-based recommender systems uses the seman

Wen Wang, Xiaojiang Peng, Yanzhou Su, Yu Qiao

Video action anticipation aims to predict future action categories from observed frames. Current state-of-the-art approaches mainly resort to recurrent neural networks to encode history information into hidden states, and predict future actions from the hidden representations. It is well known that the recurrent pipeline is inefficient in capturing long-term

Chen Li, Huilong Zhu, Yongkui Zhang, Xiaogen Yin

A digital etching method was proposed to achieve excellent control of etching depth. The digital etching characteristics of p+ Si and Si0.7Ge0.3 using the combinations of HNO3 oxidation and BOE oxide removal processes were studied. Experiments showed that oxidation saturates with time due to low activation energy. A physical model was presented to describe t

Andreea Peca, Adriana Tapus, Amir Aly, Cristina Pop

This paper presents an exploratory study designed for children with Autism Spectrum Disorders (ASD) that investigates children's awareness of being imitated by a robot in a play/game scenario. The Nao robot imitates all the arm movement behaviors of the child in real-time in dyadic and triadic interactions. Different behavioral criteria (i.e., eye gaze,

Xinwei Yue, Yuanwei Liu, Yuanyuan Yao, Tian Li

This paper investigates the application of non-orthogonal multiple access (NOMA) to satellite communication network over Shadowed-Rician fading channels. The impact of imperfect successive interference cancellation (ipSIC) on NOMA-based satellite network is taken into consideration from the perspective of practical scenarios. We first derive new exact expres

Konatsu Miyamoto, Masaya Suzuki, Yuma Kigami, Kodai Satake

In this paper, as a study of reinforcement learning, we converge the Q function to unbounded rewards such as Gaussian distribution. From the central limit theorem, in some real-world applications it is natural to assume that rewards follow a Gaussian distribution , but existing proofs cannot guarantee convergence of the Q-function. Furthermore, in the distri

Vincenzo Crescimanna, Bruce Graham

Bayesian Inference and Information Bottleneck are the two most popular objectives for neural networks, but they can be optimised only via a variational lower bound: the Variational Information Bottleneck (VIB). In this manuscript we show that the two objectives are actually equivalent to the InfoMax: maximise the information between the data and the labels.

Ankit Goel, Adam L. Bruce, Dennis S. Bernstein

Learning depends on the ability to acquire and assimilate new information. This ability depends---somewhat counterintuitively---on the ability to forget. In particular, effective forgetting requires the ability to recognize and utilize new information to order to update a system model. This article is a tutorial on forgetting within the context of recursive

Tingbo Hou, Adel Ahmadyan, Liangkai Zhang, Jianing Wei

In this paper, we address the problem of detecting unseen objects from RGB images and estimating their poses in 3D. We propose two mobile friendly networks: MobilePose-Base and MobilePose-Shape. The former is used when there is only pose supervision, and the latter is for the case when shape supervision is available, even a weak one. We revisit shape feature

Y. Wan, R. Jördens, S. D. Erickson, J. J. Wu

Scaling quantum information processors is a challenging task, requiring manipulation of a large number of qubits with high fidelity and a high degree of connectivity. For trapped ions, this could be realized in a two-dimensional array of interconnected traps in which ions are separated, transported and recombined to carry out quantum operations on small subs

Hanting Chen, Yunhe Wang, Han Shu, Changyuan Wen

Despite Generative Adversarial Networks (GANs) have been widely used in various image-to-image translation tasks, they can be hardly applied on mobile devices due to their heavy computation and storage cost. Traditional network compression methods focus on visually recognition tasks, but never deal with generation tasks. Inspired by knowledge distillation, a

Bowen Wen, Chaitanya Mitash, Sruthi Soorian, Andrew Kimmel

Many manipulation tasks, such as placement or within-hand manipulation, require the object's pose relative to a robot hand. The task is difficult when the hand significantly occludes the object. It is especially hard for adaptive hands, for which it is not easy to detect the finger's configuration. In addition, RGB-only approaches face issues with te

Gary R. Marple, David Gorsich, Paramsothy Jayakumar, Shravan Veerapaneni

A mobility map, which provides maximum achievable speed on a given terrain, is essential for path planning of autonomous ground vehicles in off-road settings. While physics-based simulations play a central role in creating next-generation, high-fidelity mobility maps, they are cumbersome and expensive. For instance, a typical simulation can take weeks to run

Jun Han

Approximate inference in probability models is a fundamental task in machine learning. Approximate inference provides powerful tools to Bayesian reasoning, decision making, and Bayesian deep learning. The main goal is to estimate the expectation of interested functions w.r.t. a target distribution. When it comes to high dimensional probability models and lar

Thoan Pham Duc, Tuyen Nguyen Dang, Vangty Noulorvang

The purpose of this paper is to prove the finiteness theorems for meromorphic mappings of a complete connected Kähler manifold into projective space sharing few hyperplanes in subgeneral position without counting multiplicity, where all zeros with multiplicities more than a certain number are omitted. Our results are extensions and generalizations of some re

Naoki Seto, Kazumi Kashiyama

We discuss the prospects of high precision pointing of our transmitter to habitable planets around Galactic main sequence stars. For an efficient signal delivery, the future sky positions of the host stars should be appropriately extrapolated with accuracy better than the beam opening angle $Θ$ of the transmitter. Using the latest data release (DR2) of Gaia,

Marnus Stoltz, Gene Stoltz, Kazushige Obara, Ting Wang

Hidden Markov models (HMMs) are general purpose models for time-series data widely used across the sciences because of their flexibility and elegance. However fitting HMMs can often be computationally demanding and time consuming, particularly when the the number of hidden states is large or the Markov chain itself is long. Here we introduce a new Graphical

Hongliang Bi, Pengyuan Liu

Emotion cause analysis such as emotion cause extraction (ECE) and emotion-cause pair extraction (ECPE) have gradually attracted the attention of many researchers. However, there are still two shortcomings in the existing research: 1) In most cases, emotion expression and cause are not the whole clause, but the span in the clause, so extracting the clause-pai

Thirunavukarasu Balasubramaniam, Richi Nayak, Chau Yuen

Coupled Matrix Tensor Factorization (CMTF) facilitates the integration and analysis of multiple data sources and helps discover meaningful information. Nonnegative CMTF (N-CMTF) has been employed in many applications for identifying latent patterns, prediction, and recommendation. However, due to the added complexity with coupling between tensor and matrix d

Wenwei Xue, Hungkeng Pung, Wenlong Ng, Tao Gu

We envisage future context-aware applications will dynamically adapt their behaviors to various context data from sources in wide-area networks, such as the Internet. Facing the changing context and the sheer number of context sources, a data management system that supports effective source organization and efficient data lookup becomes crucial to the easy d

Ting-En Lin, Hua Xu

With the maturity and popularity of dialogue systems, detecting user's unknown intent in dialogue systems has become an important task. It is also one of the most challenging tasks since we can hardly get examples, prior knowledge or the exact numbers of unknown intents. In this paper, we propose SofterMax and deep novelty detection (SMDN), a simple yet

Steve Ertel, Denis Defrère, Philip M. Hinz, Bertrand Mennesson

The Large Binocular Telescope Interferometer (LBTI) enables nulling interferometric observations across the N band (8 to 13 um) to suppress a star's bright light and probe for faint circumstellar emission. We present and statistically analyze the results from the LBTI/HOSTS (Hunt for Observable Signatures of Terrestrial Systems) survey for exozodiacal du

Fan Zhang, Vincent K. N. Lau, Gong Zhang

In this paper, we consider a MIMO networked control system (NCS) in which a sensor amplifies and forwards the observed MIMO plant state to a remote controller via a MIMO fading channel. We focus on the MIMO amplify-and-forward (AF) precoding design at the sensor to minimize a weighted average state estimation error at the remote controller subject to an aver

Ryota Nakano, Masatoshi Hirabayashi

Asteroid (3200) Phaethon, a B-type asteroid, has been active during its perihelion passages. This asteroid is considered to be a source of the Geminid meteor stream. It is reported that this asteroid is spinning at a rotation period of $3.60 \ hr$ and has a top shape (an oblate body with an equatorial ridge) with a mean equatorial diameter of $6.25 \ km$. He

Fatih Erden, Chethan K. Anjinappa, Ender Ozturk, Ismail Guvenc

Base station (BS) placement in mobile networks is critical to the efficient use of resources in any communication system and one of the main factors that determines the quality of communication. Although there is ample literature on the optimum placement of BSs for sub-6 GHz bands, channel propagation characteristics, such as penetration loss, are notably di

Simon Macourt, Giorgis Petridis, Ilya D. Shkredov, Igor E. Shparlinski

We prove, for a sufficiently small subset $\mathcal{A}$ of a prime residue field, an estimate on the number of solutions to the equation $(a_1-a_2)(a_3-a_4) = (a_5-a_6)(a_7-a_8)$ with all variables in $\mathcal{A}$. We then derive new bounds on trilinear exponential sums and on the total number of residues equaling the product of two differences of elements

Wensheng Cheng, Yan Zhang, Xu Lei, Wen Yang

Change detection is an important problem in vision field, especially for aerial images. However, most works focus on traditional change detection, i.e., where changes happen, without considering the change type information, i.e., what changes happen. Although a few works have tried to apply semantic information to traditional change detection, they either on

Zilong Chen, Hong Ming Lim, Chang Huang, Rainer Dumke

Traditionally, measuring the center-of-mass (c.m.) velocity of an atomic ensemble relies on measuring the Doppler shift of the absorption spectrum of single atoms in the ensemble. Mapping out the velocity distribution of the ensemble is indispensable when determining the c.m. velocity using this technique. As a result, highly sensitive measurements require p

Yuxin Zhang, Zuquan Zheng, Roland Hu

Convolutional Neural Network (CNN) is intensively implemented to solve super resolution (SR) tasks because of its superior performance. However, the problem of super resolution is still challenging due to the lack of prior knowledge and small receptive field of CNN. We propose the Segmentation-Piror Self-Attention Generative Adversarial Network (SPSAGAN) to

A. Flores, R. C. de Lamare, B. Clerckx

This paper develops stream combining techniques for rate-splitting (RS) multiple-antenna systems with multiple users to enhance the common rate. We propose linear combining techniques based on the Min-Max, the maximum ratio and the minimum mean-square error criteria along with Regularized Block Diagonalization (RBD) precoders for RS-based multiuser multiple-

Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu

The classical development of neural networks has been primarily for mappings between a finite-dimensional Euclidean space and a set of classes, or between two finite-dimensional Euclidean spaces. The purpose of this work is to generalize neural networks so that they can learn mappings between infinite-dimensional spaces (operators). The key innovation in our

Minghua Pan, Daowen Qiu, Shenggen Zheng

Entanglement is considered to be one of the primary reasons for why quantum algorithms are more efficient than their classical counterparts for certain computational tasks. The global multipartite entanglement of the multiqubit states in Grover's search algorithm can be quantified using the geometric measure of entanglement (GME). Rossi {\em et al.} (Phy

Evan Campbell, Jason Chang, Angkoon Phinyomark, Erik Scheme

Despite decades of research and development of pattern recognition approaches, the clinical usability of myoelectriccontrolled prostheses is still limited. One of the main issues is the high inter-subject variability that necessitates long and frequent user-specific training. Cross-user models present an opportunity to improve clinical viability of myoelectr

Huimin Zhang, Yafei Wang, Junjia Liu, Chengwei Li

Precise trajectory prediction of surrounding vehicles is critical for decision-making of autonomous vehicles and learning-based approaches are well recognized for the robustness. However, state-of-the-art learning-based methods ignore 1) the feasibility of the vehicle's multi-modal state information for prediction and 2) the mutual exclusive relationship

Chongsheng Cao, Yanqiu Guo, Edriss S. Titi

We analyze a three-dimensional rapidly rotating convection model of tall columnar structure in the limit of infinite Prandtl number, i.e., when the momentum diffusivity is much more dominant than the thermal diffusivity. Consequently, the dynamics of the velocity field takes place at a much faster time scale than the temperature fluctuation, and at the limit

D. J. Priour

For 3D geometries, we consider stones (modeled as convex polyhedra) subject to weathering with planar slices of random orientation and depth successively removing material, ultimately yielding smooth and round (i.e. spherical) shapes. An exponentially decaying acceptance probability in the area exposed by a prospective slice provides a stochastically driven

Rajan Puri

For the one dimensional Schrödinger operator in the case of Dirichlet boundary condition, we show that $β_{cr}$ is positive and zero for the case of Neumann and Robin boundary condition considering the potential energy of the form $V(x)=-βδ(x-a)$ where, $β\geq 0, \ a > 0.$ We prove that the $β_{cr}$ goes to infinity when the delta potential moves towards the

Jordan Lam, Robert Abbas

Protecting the networks of tomorrow is set to be a challenging domain due to increasing cyber security threats and widening attack surfaces created by the Internet of Things (IoT), increased network heterogeneity, increased use of virtualisation technologies and distributed architectures. This paper proposes SDS (Software Defined Security) as a means to prov

Sharib Ali, Noha Ghatwary, Barbara Braden, Dominique Lamarque

Whilst many technologies are built around endoscopy, there is a need to have a comprehensive dataset collected from multiple centers to address the generalization issues with most deep learning frameworks. What could be more important than disease detection and localization? Through our extensive network of clinical and computational experts, we have collect