March 2020 arXiv papers — page 142

Wenjie Song, Xiansi Wang, Wenfeng Wang Changjun Jiang, Xiangrong Wang

Propagation of backward magnetostatic surface spin waves (SWs) in exchange coupled Co/FeNi bilayers are studied by using Brillouin light scattering (BLS) technique. Two types of SWs modes were identified in our BLS measurements. They are magnetostatic surface waves (MSSWs) mode and perpendicular standing spin waves (PSSWs) mode. The dispersion relations of M

Lijia Ding, Kai Wang

Let $\mathbb{B}^d$ be the unit ball on the complex space $\mathbb{C}^d$ with normalized Lebesgue measure $dv.$ For $α\in\mathbb{R},$ denote $k_α(z,w)=\frac{1}{(1-\langle z,w\rangle)^α},$ the Bergman-type integral operator $K_α$ on $L^1(\mathbb{B}^d,dv)$ is defined by $$ K_αf(z)=\int_{\mathbb{B}^d}k_α(z,w)f(w)dv(w).$$ It is an important class of operators in

Adrian Hauswirth, Florian Dörfler, Andrew Teel

In this paper we study how high-gain anti-windup schemes can be used to implement projected dynamical systems in control loops that are subject to saturation on a (possibly unknown) set of admissible inputs. This insight is especially useful for the design of autonomous optimization schemes that realize a closed-loop behavior which approximates a particular

Jing Li, Suiyi Ling, Junle Wang, Zhi Li

In the big data era, data labeling can be obtained through crowdsourcing. Nevertheless, the obtained labels are generally noisy, unreliable or even adversarial. In this paper, we propose a probabilistic graphical annotation model to infer the underlying ground truth and annotator's behavior. To accommodate both discrete and continuous application scenari

Yue Xu, Feng Yin, Wenjun Xu, Chia-Han Lee

The marriage of wireless big data and machine learning techniques revolutionizes the wireless system by the data-driven philosophy. However, the ever exploding data volume and model complexity will limit centralized solutions to learn and respond within a reasonable time. Therefore, scalability becomes a critical issue to be solved. In this article, we aim t

Yuri S. Sarkisov, Min Jun Kim, Andre Coelho, Dzmitry Tsetserukou

This paper presents a design of oscillation damping control for the cable-Suspended Aerial Manipulator (SAM). The SAM is modeled as a double pendulum, and it can generate a body wrench as a control action. The main challenge is the fact that there is only one onboard IMU sensor which does not provide full information on the system state. To overcome this dif

Reut Levi, Moti Medina

In this paper we study the problem of testing graph isomorphism (GI) in the CONGEST distributed model. In this setting we test whether the distributive network, $G_U$, is isomorphic to $G_K$ which is given as an input to all the nodes in the network, or alternatively, only to a single node. We first consider the decision variant of the problem in which the a

Benjamin Ward-Cherrier, Nicholas Pestell, Nathan F. Lepora

Developing artificial tactile sensing capabilities that rival human touch is a long-term goal in robotics and prosthetics. Gradually more elaborate biomimetic tactile sensors are being developed and applied to grasping and manipulation tasks to help achieve this goal. Here we present the neuroTac, a novel neuromorphic optical tactile sensor. The neuroTac com

Stefano Longhi, Liang Feng

Multi-mode interference (MMI) and self-imaging are important phenomena of diffractive wave optics with major applications in optical signal processing, beam shaping and optical sensing. Such phenomena generally arise from interference of normal modes in lossless dielectric guiding structures, however the impact of spatially-inhomogeneous optical gain and los

Hamza Ali Imran, Saad Wazir, Ahmed Jamal Ikram, Ataul Aziz Ikram

Applications like Big Data, Machine Learning, Deep Learning and even other Engineering and Scientific research requires a lot of computing power; making High-Performance Computing (HPC) an important field. But access to Supercomputers is out of range from the majority. Nowadays Supercomputers are actually clusters of computers usually made-up of commodity ha

Vahid Garousi, Ehsan Abbasi, Bedir Tekinerdogan

Development of scientific and engineering software is usually different and could be more challenging than the development of conventional enterprise software. The authors were involved in a technology-transfer project between academia and industry which focused on engineering, development and testing of a software for optimization of pumping energy costs fo

Jianmin Chen, Yanan Lin, Shiquan Ruan, Hongxia Zhang

The string group acts on the category of coherent sheaves over a weighted projective line by degree-shift actions. We study the equivariant equivalence relations induced by degree-shift actions between weighted projective lines. We prove that such an equivariant equivalence is characterized by an admissible homomorphism between the associated string groups.

Armand Wirgin

The problem of the response of a cylindrical protuberance of rectangular shape to a SH seismic plane wave is studied in parametric manner so as to provide answers to the questions: (i) where and how should one measure this response, (ii) is the normal-incidence response a valid indication of response at other incident angles of the seismic plane wave, iii) i

Menghuan Yang, Hong Wu, Qiqi Wang, Yingxin Zhao

The secondary modulation with the NeumannHoffman code increases the possibility of bit sign transition. Unlike other GNSS signals, there is no pilot component for synchronization in BeiDou B1/B3 signals, which increases the complexity in acquisition. A previous study has shown that the delay and multiplication (DAM) method is able to eliminate the bit sign t

Shao-Wen Wei, Yu-Xiao Liu

Recently, black hole thermodynamics and phase transition have been studied in the extended phase space. Besides the VdW-like phase transition, more interesting phase transitions were found. More interestingly, combining with the thermodynamic geometry, the microstructure of black holes was investigated.In this paper, we give a brief review of recent progress

Na Jiang, Siyao Ke, Hengxi Ji, Hao Wang

In the presence of mass anisotropy, anisotropic interaction, or in-plane magnetic field, quantum Hall droplets can exhibit shape deformation and internal geometrical degree of freedom. We characterize the geometry of quantum Hall states by principal component analysis, which is a statistical technique that emphasizes variation in a dataset. We first test the

Gargi Shaw, G. J. Ferland

The gamma-ray burst (GRB) afterglows provide an unique opportunity to study the interstellar medium (ISM) of star-forming galaxies at high-redshift. The GRB-DLAs (damped Lyman-$α$ absorbers) contain a large neutral hydrogen column density, N(H I), and are observed against the GRB afterglow. A large fraction of GRB-DLAs show presence of molecular hydrogen (H$

Fucai Lin, Qianqian Sun, Yujin Lin, Jinjin Li

Let $(U, R)$ be an approximation space with $U$ being non-empty set and $R$ being an equivalence relation on $U$, and let $\overline{G}$ and $\underline{G}$ be the upper approximation and the lower approximation of subset $G$ of $U$. A topological rough group $G$ is a rough group $G=(\underline{G}, \overline{G})$ endowed with a topology, which is induced fro

Arthur-Jozsef Molnar, Simona Motogna

We present a longitudinal study on the long-term evolution of maintainability in open-source software. Quality assessment remains at the forefront of both software research and practice, with many models and assessment methodologies proposed and used over time. Some of them helped create and shape standards such as ISO 9126 and 25010, which are well establis

Franck Assous, Yevgeni Furman

We introduce a new family of paraxial asymptotic models that approximate the Vlasov-Maxwell equations in non-relativistic cases. This formulation is $n$-th order accurate in a parameter $η$, which denotes the ratio between the characteristic velocity of the beam and the speed of light. This family of models is interesting, first because it is simpler than th

Johannes Carmesin, Lyuben Lichev

We construct a simply connected $2-$complex $C$ embeddable in $3-$space such that for any embedding of $C$ in $\mathbb S^3$, any edge contraction forms a minor of the $2-$complex not embeddable in $3-$space. We achieve this by proving that every edge of $C$ forms a nontrivial knot in any of the embeddings of $C$ in $\mathbb S^3$.

Jian An, Hanyi Wang, Bing Liu, Kai Hong Luo

The high cost of high-resolution computational fluid/flame dynamics (CFD) has hindered its application in combustion related design, research and optimization. In this study, we propose a new framework for turbulent combustion simulation based on the deep learning approach. An optimized deep convolutional neural network (CNN) inspired from a U-Net architectu

Rashid Ahmad, Safia Bibi, Uzma Sajjad

The evolution of a walker in standard "Discrete-time Quantum Walk (DTQW)" is determined by coin and shift unitary operators. The conditional shift operator shifts the position of the walker to right or left by unit step size while the direction of motion is specified by the coin operator. This scenario can be generalized by choosing the step size ran

Chengjun Li, Yang Li

Differential Evolution (DE) is quite powerful for real parameter single objective optimization. However, the ability of extending or changing search area when falling into a local optimum is still required to be developed in DE for accommodating extremely complicated fitness landscapes with a huge number of local optima. We propose a new flow of DE, termed D

Jacques Bair, Piotr Blaszczyk, Peter Heinig, Vladimir Kanovei

Like his colleagues de Prony, Petit, and Poisson at the Ecole Polytechnique, Cauchy used infinitesimals in the Leibniz-Euler tradition both in his research and teaching. Cauchy applied infinitesimals in an 1826 work in differential geometry where infinitesimals are used neither as variable quantities nor as sequences but rather as numbers. He also applied in

Mira Bivas, Aris Daniilidis, Marc Quincampoix

The ordinary differential equation $\dot{x}(t)=f(x(t)), \; t \geq 0 $, for $f$ measurable, is not sufficiently regular to guarantee existence of solutions. To remedy this we may relax the problem by replacing the function $f$ with its Filippov regularization $F_{f}$ and consider the differential inclusion $\dot{x}(t)\in F_{f}(x(t))$ which always has a soluti

L. P. Horwitz, R. I. Arshansky

We show that in a relativistically covariant formulation of the two-body bound state problem, the bound state spectrum is in agreement, up to relativistic corrections, with the non-relativistic bound state spectrum. The solution is achieved by solving the problem with support of the wave function in an O(2,1) invariant submanifold of the Minkowski spacetime.

Oksana Bezushchak, Bogdana Oliynyk

We introduce an abstract definition of a Hamming space that generalizes standard Hamming spaces $( \mathbb{Z}/ 2 \mathbb{Z})^n $. We classify countable locally standard Hamming spaces and show that each of them can be realized as the Boolean algebra of idempotents of a Cartan subalgebra of a locally matrix algebra.

Kamran Alipour, Jurgen P. Schulze, Yi Yao, Avi Ziskind

Explainability and interpretability of AI models is an essential factor affecting the safety of AI. While various explainable AI (XAI) approaches aim at mitigating the lack of transparency in deep networks, the evidence of the effectiveness of these approaches in improving usability, trust, and understanding of AI systems are still missing. We evaluate multi

Xinwei Chen, Ali Taleb Zadeh Kasgari, Walid Saad

In this paper, the problem of head movement prediction for virtual reality videos is studied. In the considered model, a deep learning network is introduced to leverage position data as well as video frame content to predict future head movement. For optimizing data input into this neural network, data sample rate, reduced data, and long-period prediction le

Jian An, Guo Qiang He, Kai Hong Luo, Fei Qin

To effectively simulate the combustion of hydrocarbon-fueled supersonic engines, such as rocket-based combined cycle (RBCC) engines, a detailed mechanism for chemistry is usually required but computationally prohibitive. In order to accelerate chemistry calculation, an artificial neural network (ANN) based methodology was introduced in this study. This metho

J. A. Kittl, M. Houssa, V. V. Afanasiev, J. -P. Locquet

Analysis of data presented in the paper -- Unveiling the double-well energy landscape in a ferroelectric layer, by M. Hoffmann, et al., Nature 565, 464 (2019) -- suggesting the claims of lack of hysteresis and s-curve trajectory are unfounded.

J. A. Kittl, J. -P. Locquet, M. Houssa, V. V. Afanasiev

We present a thorough analysis of the foundations of models of stabilization of negative capacitance (NC) in a ferroelectric (FE) layer by capacitance matching to a dielectric layer, which claim that the FE is stabilized in a low polarization state without FE polarization switching (non-switching), showing that the concept is fundamentally flawed and unphysi

Zhu Fuhai, Chen Zhiqi, Liang Ke

Let $G$ be a connected, simply-connected, compact simple Lie group. In this paper, we show that the isometry group of $G$ with a left-invariant pseudo-Riemannan metric is compact. Furthermore, the identity component of the isometry group is compact if $G$ is not simply-connected.

Hong-lin Liao, Tao Tang, Tao Zhou

In this work, we investigate the two-step backward differentiation formula (BDF2) with nonuniform grids for the Allen-Cahn equation. We show that the nonuniform BDF2 scheme is energy stable under the time-step ratio restriction $r_k:=τ_k/τ_{k-1}<(3+\sqrt{17})/2\approx3.561.$ Moreover, by developing a novel kernel recombination and complementary technique, we

Hua-Jian Ding, Jing-Jing Chen, Liang Ji, Xing-Yu Zhou

Quantum digital signature (QDS) guarantee the unforgeability, nonrepudiation and transferability of signature messages with information-theoretical security, and hence has attracted much attention recently. However, most previous implementations of QDS showed relatively low signature rates or/and short transmission distance. In this paper, we report a proof-

Prajwal K R, Rudrabha Mukhopadhyay, Jerin Philip, Abhishek Jha

In light of the recent breakthroughs in automatic machine translation systems, we propose a novel approach that we term as &#34;Face-to-Face Translation&#34;. As today&#39;s digital communication becomes increasingly visual, we argue that there is a need for systems that can automatically translate a video of a person speaking in language A into a target lan

Muhammad Asim, Muaaz Zakria

k-nearest neighbour (kNN) is one of the most prominent, simple and basic algorithm used in machine learning and data mining. However, kNN has limited prediction ability, i.e., kNN cannot predict any instance correctly if it does not belong to any of the predefined classes in the training data set. The purpose of this paper is to suggest an Advanced kNN (A-kN

Yixin Wang, Xiaohong Guan, Youtian Du, Nan Nan

Music tone quality evaluation is generally performed by experts. It could be subjective and short of consistency and fairness as well as time-consuming. In this paper we present a new method for identifying the clarinet reed quality by evaluating tone quality based on the harmonic structure and energy distribution. We first decouple the quality of reed and c

Mahmood A. Khan, Md Zahidul Islam, Mohsin Hafeez

Recent drought and population growth are planting unprecedented demand for the use of available limited water resources. Irrigated agriculture is one of the major consumers of freshwater. A large amount of water in irrigated agriculture is wasted due to poor water management practices. To improve water management in irrigated areas, models for estimation of

Zitian Huang, Yikuan Yu, Jiawen Xu, Feng Ni

In this paper, we propose a Point Fractal Network (PF-Net), a novel learning-based approach for precise and high-fidelity point cloud completion. Unlike existing point cloud completion networks, which generate the overall shape of the point cloud from the incomplete point cloud and always change existing points and encounter noise and geometrical loss, PF-Ne

Sulan Zhai, Shunqiang Liu, Xiao Wang, Jin Tang

Person search is to detect all persons and identify the query persons from detected persons in the image without proposals and bounding boxes, which is different from person re-identification. In this paper, we propose a fusing multi-task convolutional neural network(FMT-CNN) to tackle the correlation and heterogeneity of detection and re-identification with

Monther Aldwairi, Yahya Flaifel, Khaldoon Mhaidat

Network intrusion detection systems and antivirus software are essential in detecting malicious network traffic and attacks such as denial-of-service and malwares. Each attack, worm or virus has its own distinctive signature. Signature-based intrusion detection and antivirus systems depend on pattern matching to look for possible attack signatures. Pattern m

Justin D. Glover, Jonathan T. Pham

Small scale contact between a soft, liquid-coated layer and a stiff surface is common in many situations, from synovial fluid on articular cartilage to adhesives in humid environments. Moreover, many model studies on soft adhesive contacts are conducted with soft silicone elastomers, which possess uncrosslinked liquid molecules (i.e. silicone oil) when the m

Zhenfang Chen, Peng Wang, Lin Ma, Kwan-Yee K. Wong

Referring expression comprehension (REF) aims at identifying a particular object in a scene by a natural language expression. It requires joint reasoning over the textual and visual domains to solve the problem. Some popular referring expression datasets, however, fail to provide an ideal test bed for evaluating the reasoning ability of the models, mainly be

Hugo Tremblay, Fabio Petrillo

Reduce and control complexity is an essential practice in software design. Cyclomatic complexity (CC) is one of the most popular software metrics, applied for more than 40 years. Despite CC is an interesting metric to highlight the number of branches in a program, it clearly not sufficient to represent the complexity in a piece of software. In this paper, we

Taekyun Kim, Dae san Kim

Recently, the degenerate gamma functions are introduced as a degenerate version of the usual gamma function by Kim-Kim. In this paper, we investigate several properties of them. Namely, we obtain an analytic continuation as a meromorphic function on the whole complex plane,the difference formula, the values at positive integers, some expressions following fr

Qi Chen, Qi Wu, Rui Tang, Yuhan Wang

Home design is a complex task that normally requires architects to finish with their professional skills and tools. It will be fascinating that if one can produce a house plan intuitively without knowing much knowledge about home design and experience of using complex designing tools, for example, via natural language. In this paper, we formulate it as a lan

Abdullah Al-Noman Patwary, Anmin Fu, Ranesh Kumar Naha, Sudheer Kumar Battula

Fog computing is an emerging computing paradigm that has come into consideration for the deployment of IoT applications amongst researchers and technology industries over the last few years. Fog is highly distributed and consists of a wide number of autonomous end devices, which contribute to the processing. However, the variety of devices offered across dif

Stefano Favaro, Sandra Fortini, Stefano Peluchetti

We consider fully connected feed-forward deep neural networks (NNs) where weights and biases are independent and identically distributed as symmetric centered stable distributions. Then, we show that the infinite wide limit of the NN, under suitable scaling on the weights, is a stochastic process whose finite-dimensional distributions are multivariate stable

Denis Gudovskiy, Alec Hodgkinson, Takuya Yamaguchi, Sotaro Tsukizawa

Active learning (AL) aims to minimize labeling efforts for data-demanding deep neural networks (DNNs) by selecting the most representative data points for annotation. However, currently used methods are ill-equipped to deal with biased data. The main motivation of this paper is to consider a realistic setting for pool-based semi-supervised AL, where the unla

Shizhe Chen, Yida Zhao, Qin Jin, Qi Wu

Cross-modal retrieval between videos and texts has attracted growing attentions due to the rapid emergence of videos on the web. The current dominant approach for this problem is to learn a joint embedding space to measure cross-modal similarities. However, simple joint embeddings are insufficient to represent complicated visual and textual details, such as

Mengjie Yi, Xijun Wang, Juan Liu, Yan Zhang

Due to the flexibility and low operational cost, dispatching unmanned aerial vehicles (UAVs) to collect information from distributed sensors is expected to be a promising solution in Internet of Things (IoT), especially for time-critical applications. How to maintain the information freshness is a challenging issue. In this paper, we investigate the fresh da

Mats Persson, Adam Wang, Norbert J. Pelc

Purpose: Developing photon-counting CT detectors requires understanding the impact of parameters such as converter material, absorption length and pixel size. We apply a novel linear-systems framework, incorporating spatial and energy resolution, to study realistic silicon (Si) and cadmium telluride (CdTe) detectors at low count rate. Approach: We compared C

JieZhang Cao, Langyuan Mo, Qing Du, Yong Guo

Joint distribution matching (JDM) problem, which aims to learn bidirectional mappings to match joint distributions of two domains, occurs in many machine learning and computer vision applications. This problem, however, is very difficult due to two critical challenges: (i) it is often difficult to exploit sufficient information from the joint distribution to

Angel Garcia-Chung

In this paper we provide the representation of the symplectic group $Sp(2n, \mathbb{R})$ in polymer quantum mechanics. We derive the propagator of the polymer free particle and the polymer harmonic oscillator without considering a polymer scale. The polymer scale is then introduced to reconcile our results with those expressions for the polymer free particle

Shizhe Chen, Qin Jin, Peng Wang, Qi Wu

Humans are able to describe image contents with coarse to fine details as they wish. However, most image captioning models are intention-agnostic which can not generate diverse descriptions according to different user intentions initiatively. In this work, we propose the Abstract Scene Graph (ASG) structure to represent user intention in fine-grained level a

William E. Gerhard, Pratap Tokekar

We present the design of a radio antenna system for obtaining instantaneous bearing measurements towards a radio emitter. Our work is motivated by applications where robots are used for localizing and tracking radio-tagged wildlife. The traditional method is to use directional antennas that need to be rotated in order find the bearing which is time consuming

Zhixin Jia, Mengxiang Lin, Zhixin Chen, Shibo Jian

Vision-based learning methods provide promise for robots to learn complex manipulation tasks. However, how to generalize the learned manipulation skills to real-world interactions remains an open question. In this work, we study robotic manipulation skill learning from a single third-person view demonstration by using activity recognition and object detectio

Wenrui Lin, Xijun Wang, Chao Xu, Xinghua Sun

The freshness of status updates is imperative in mission-critical Internet of things (IoT) applications. Recently, Age of Information (AoI) has been proposed to measure the freshness of updates at the receiver. However, AoI only characterizes the freshness over time, but ignores the freshness in the content. In this paper, we introduce a new performance metr

Chao Xu, Xijun Wang, Howard H. Yang, Hongguang Sun

Caching has been regarded as a promising technique to alleviate energy consumption of sensors in Internet of Things (IoT) networks by responding to users&#39; requests with the data packets stored in the edge caching node (ECN). For real-time applications in caching enabled IoT networks, it is essential to develop dynamic status update strategies to strike a

Momchil Minkov, Ian A. D. Williamson, Lucio C. Andreani, Dario Gerace

Gradient-based inverse design in photonics has already achieved remarkable results in designing small-footprint, high-performance optical devices. The adjoint variable method, which allows for the efficient computation of gradients, has played a major role in this success. However, gradient-based optimization has not yet been applied to the mode-expansion me

Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans

Starting with Gilmer et al. (2018), several works have demonstrated the inevitability of adversarial examples based on different assumptions about the underlying input probability space. It remains unclear, however, whether these results apply to natural image distributions. In this work, we assume the underlying data distribution is captured by some conditi

Yang Li, Jinqiao Duan, Xianbin Liu, Yanxia Zhang

The emergence of the exit events from a bounded domain containing a stable fixed point induced by non-Gaussian Lévy fluctuations plays a pivotal role in practical physical systems. In the limit of weak noise, we develop a Hamiltonian formalism under the Lévy fluctuations with exponentially light jumps for one- and two-dimensional stochastic dynamical systems

Jinglei Cheng, Haoqing Deng, Xuehai Qian

In the last decades, we have witnessed the rapid growth of Quantum Computing. In the current Noisy Intermediate-Scale Quantum (NISQ) era, the capability of a quantum machine is limited by the decoherence time, gate fidelity and the number of Qubits. Current quantum computing applications are far from the real &#34;quantum supremacy&#34; due to the fragile ph

Chuan-Tao Ma, Yan-Xiang Gong, Xiao-Mei Wu, Jianghui Ji

The inclination distribution of circumbinary planets (CBPs) is an important scientific issue. It is of great significance in estimating the occurrence rate of CBPs and studying their formation and evolution. Although the CBPs currently discovered by the transit method are nearly coplanar, the true inclination distribution of CBPs is still unknown. Previous r

Rahul Trivedi, Guillermo Angeris, Logan Su, Stephen Boyd

The ability to design the scattering properties of electromagnetic structures is of fundamental interest in optical science and engineering. While there has been great practical success applying local optimization methods to electromagnetic device design, it is unclear whether the performance of resulting designs is close to that of the best possible design.

Gian Paolo Vacca

We consider a functional relation between a given Wilsonian RG flow, which has to be related to a specific coarse-graining procedure, and an infinite family of (UV cutoff) scale dependent field redefinitions. Within this framework one can define a family of Wilsonian proper-time exact RG equations associated to an arbitrary regulator function. New applicatio

Bahman Kalantari

Newton&#39;s method for polynomial root finding is one of mathematics&#39; most well-known algorithms. The method also has its shortcomings: it is undefined at critical points, it could exhibit chaotic behavior and is only guaranteed to converge locally. Based on the {\it Geometric Modulus Principle} for a complex polynomial $p(z)$, together with a {\it Modu

Bradley S. Price, Aaron J. Molstad, Ben Sherwood

We propose a penalized likelihood framework for estimating multiple precision matrices from different classes. Most existing methods either incorporate no information on relationships between the precision matrices, or require this information be known a priori. The framework proposed in this article allows for simultaneous estimation of the precision matric

Masashi Okada, Norio Kosaka, Tadahiro Taniguchi

In the present paper, we propose an extension of the Deep Planning Network (PlaNet), also referred to as PlaNet of the Bayesians (PlaNet-Bayes). There has been a growing demand in model predictive control (MPC) in partially observable environments in which complete information is unavailable because of, for example, lack of expensive sensors. PlaNet is a pro

Daniel Freer, Guang-Zhong Yang

With increasing global age and disability assistive robots are becoming more necessary, and brain computer interfaces (BCI) are often proposed as a solution to understanding the intent of a disabled person that needs assistance. Most frameworks for electroencephalography (EEG)-based motor imagery (MI) BCI control rely on the direct control of the robot in Ca

S. Bhandari, G. -H. Lee, K. Watanabe, T. Taniguchi

Coherent charge transport along ballistic paths can be introduced into graphene by Andreev reflection, for which an electron reflects from a superconducting contact as a hole, while a Cooper pair is transmitted. We use a liquid-helium cooled scanning gate microscope (SGM) to image Andreev reflection in graphene in the magnetic focusing regime, where carriers

Zhize Li, Jian Li

Anderson acceleration (or Anderson mixing) is an efficient acceleration method for fixed point iterations $x_{t+1}=G(x_t)$, e.g., gradient descent can be viewed as iteratively applying the operation $G(x) \triangleq x-α\nabla f(x)$. It is known that Anderson acceleration is quite efficient in practice and can be viewed as an extension of Krylov subspace meth

Sejun Park, Deepjyoti Deka, Scott Backhaus, Michael Chertkov

Efficient operation of distribution grids in the smart-grid era is hindered by the limited presence of real-time nodal and line meters. In particular, this prevents the easy estimation of grid topology and associated line parameters that are necessary for control and optimization efforts in the grid. This paper studies the problems of topology and parameter