September 2019 arXiv papers — page 16

Soubhik Chakrabarty, Anup Kumar Mandia, Bhaskaran Muralidharan, Seung Cheol Lee

We present a comprehensive investigation of semi-classical transport properties of n-type ternary compound AlGaAs2, using Rode's iterative method. Four scattering mechanisms, have been included in our transport calculation, namely, ionized impurity, piezoelectric, acoustic deformation and polar optical phonon (POP). The scattering rates have been calculated

Coline Larmier, Alain Mazzolo, Andrea Zoia

In a recent article, Krapivsky and Redner (J. Stat. Mech. 093208 (2018)) established that the distribution of the first hitting times for a diffusing particle subject to hitting an absorber is independent of the direction of the external flow field. In the present paper, we build upon this observation and investigate when the conditioning on the diffusion le

Henning Schnoor, Wilhelm Hasselbring

Coupling metrics are an established way to measure software architecture quality with respect to modularity. Static coupling metrics are obtained from the source or compiled code of a program, while dynamic metrics use runtime data gathered e.g., by monitoring a system in production. We study \emph{weighted} dynamic coupling that takes into account how often

Subhrajit Sinha, Sai Pushpak Nandanoori, Enoch Yeung

In this paper, we provide an algorithm for online computation of Koopman operator in real-time using streaming data. In recent years, there has been an increased interest in data-driven analysis of dynamical systems, with operator theoretic techniques being the most popular. Existing algorithms, like Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode

Feng Chen, Jun-Jie Chen, Ling-Na Wu, Yong-Chun Liu

Spin squeezing (SS) is a recognized resource for realizing measurement precision beyond the standard quantum limit $\propto 1/\sqrt{N}$. The rudimentary one-axis twisting (OAT) interaction can facilitate SS and has been realized in diverse experiments, but it cannot achieve extreme SS for precision at Heisenberg limit $\propto 1/{N}$. Aided by deep reinforce

Allan Grønlund, Lior Kamma, Kasper Green Larsen, Alexander Mathiasen

Boosting is one of the most successful ideas in machine learning. The most well-accepted explanations for the low generalization error of boosting algorithms such as AdaBoost stem from margin theory. The study of margins in the context of boosting algorithms was initiated by Schapire, Freund, Bartlett and Lee (1998) and has inspired numerous boosting algorit

Quan-Hoang Vuong, Manh-Tung Ho, Hong-Kong Nguyen, Viet-Phuong La

This research employs the Bayesian network modeling approach, and the Markov chain Monte Carlo technique, to learn about the role of lies and violence in teachings of major religions, using a unique dataset extracted from long-standing Vietnamese folktales. The results indicate that, although lying and violent acts augur negative consequences for those who c

Mincheul Kang, Heechan Shin, Donghyuk Kim, Sung-Eui Yoon

A redundant manipulator has multiple inverse kinematics solutions per end-effector pose. Accordingly, there can be many trajectories for joints that follow a given endeffector path in the Cartesian space. In this paper, we present a trajectory optimization of a redundant manipulator (TORM) to synthesize a trajectory that follows a given end-effector path acc

Lei Pan, Xin Chen, Yu Chen, Hui Zhai

Linear response theory lies at the heart of quantum many-body physics because it builds up connections between the dynamical response to an external probe and correlation functions at equilibrium. Here we consider the dynamical response of a Hermitian system to a non-Hermitian probe, and we develop a non-Hermitian linear response theory that can also relate

Lei Chen

In this paper, we study the action of $\text{Homeo}_0(M)$, the identity component of the group of homeomorphisms of an $n$-dimensional manifold $M$ with an $\mathbb{F}_p$-free action, on another manifold $N$ of dimension $n+k<2n$. We prove that if $M$ is not an $\mathbb{F}_p$-homology sphere, then $N\cong M\times K$ for a homology manifold $K$ such that the

Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li

Clustering uncertain data is an essential task in data mining for the internet of things. Possible world based algorithms seem promising for clustering uncertain data. However, there are two issues in existing possible world based algorithms: (1) They rely on all the possible worlds and treat them equally, but some marginal possible worlds may cause negative

Lin Song, Yanwei Li, Zeming Li, Gang Yu

Learning discriminative global features plays a vital role in semantic segmentation. And most of the existing methods adopt stacks of local convolutions or non-local blocks to capture long-range context. However, due to the absence of spatial structure preservation, these operators ignore the object details when enlarging receptive fields. In this paper, we

Yehuda Pinchover, Idan Versano

We construct families of optimal Hardy-weights for a subcritical linear second-order elliptic operator using a one-dimensional reduction. More precisely, we first characterise all optimal Hardy-weights with respect to one-dimensional subcritical Sturm-Liouville operators on a given interval, and then apply this result to obtain families of optimal Hardy ineq

Kenneth F. Caluya, Abhishek Halder

In this paper, we study the feedback synthesis problem for steering the joint state density or ensemble subject to multi-input state feedback linearizable dynamics. This problem is of interest to many practical applications including that of dynamically shaping a robotic swarm. Our results here show that it is possible to exploit the structural nonlinearitie

Satomi Nakahara, Akihiro Doi, Yasuhiro Murata, Masanori Nakamura

We investigated the jet width profile with distance along the jet in the nearby radio galaxy NGC 1052 at radial distances between $\sim300$ to $4 \times 10^7$ Schwarzschild Radii($R_{\rm S}$) from the central engine on both their approaching and receding jet sides. The width of jets was measured in images obtained with the VLBI Space Observatory Programme (V

Hong-Wei Ke, Mei Li, Xiao-Hai Liu, Xue-Qian Li

$P_c(4312)$ observed by the LHCb collaboration is confirmed as a pentaquark and its structure, production, and decay behaviors attract great attention from theorists and experimentalists. Since its mass is very close to sum of $\Sigma_c$ and $\bar D$ masses, it is naturally tempted to be considered as a molecular state composed of $\Sigma_c$ and $\bar D$. Mo

B. P. Mahapatra

We introduce a non perturbative general approximation scheme (NGAS) that can handle interactions of any strength in quantum theory. This approach starts with an input Hamiltonian that can be solved exactly. The interaction effects are then built into this Hamiltonian through nonlinear feedback enforced by self consistency conditions. While the method itself

Mir Muntasir Hossain, Satyendra N. Biswas

Comparators have multifarious applications in various fields, especially used in analog to digital converters. Over the years, we have seen many different designs of single stage, dynamic latch type and double tail type comparators based on CMOS technology, and all of them had to make the tradeoff between power consumption and delay time. Meanwhile, to mitig

Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang

Recently deep neutral networks have achieved promising performance for filling large missing regions in image inpainting tasks. They usually adopted the standard convolutional architecture over the corrupted image, leading to meaningless contents, such as color discrepancy, blur and artifacts. Moreover, most inpainting approaches cannot well handle the large

Venkatraman Renganathan, Navid Hashemi, Justin Ruths, Tyler H. Summers

Designing resilient control strategies for mitigating stealthy attacks is a crucial task in emerging cyber-physical systems. In the design of anomaly detectors, it is common to assume Gaussian noise models to maintain tractability; however, this assumption can lead the actual false alarm rate to be significantly higher than expected. We propose a distributio

R. Wang, K. L. Zhang, Z. Song

Uncorrelated disorder potential in one-dimensional lattice definitely induces Anderson localization, while quasiperiodic potential can lead to both localized and extended phases, depending on the potential strength. We investigate the Anderson localization in one-dimensional lattice with nonHermitian complex disorder and quasiperiodic potential. We present a

Upendra Kumar, Sanjay Nayak, Soubhik Chakrabarty, Satadeep Bhattacharjee

Using machine learning (ML) approach, we unearthed a new III-V semiconducting material having an optimal bandgap for high efficient photovoltaics with the chemical composition of Gallium-Boron-Phosphide(GaBP$_2$, space group: Pna2$_1$). ML predictions are further validated by state of the art ab-initio density functional theory (DFT) simulations. The stoichi

Jürgen Röhler

The characteristic hole concentrations x_opt = 0.16 and x_c = 0.19 in the under- to overdoped transition regime of cuprate superconductors are shown to be intimately interrelated by mesoscale organization of bond-like RVB arrays extending over 3 x 4 copper sites and comprising 2 holes spaced by 3a_0. Columnar organization maximizes T_c but reduces the superf

James Stephens Cavenaugh

Cross-validation assesses the predictive ability of a model, allowing one to rank models accordingly. Although the nonparametric bootstrap is almost always used to assess the variability of a parameter, it can be used as the basis for cross-validation if one keeps track of which items were not selected in a given bootstrap iteration. The items which were sel

Lluís Alsedà, José Tomás Lázaro, Ricard Solé, Blai Vidiella

Ecological systems are complex dynamical systems. Modelling efforts on ecosystems' dynamical stability have revealed that population dynamics, being highly nonlinear, can be governed by complex fluctuations. Indeed, experimental and field research has provided mounting evidence of chaos in species' abundances, especially for discrete-time systems. Discrete-t

Weihao Wu, Lei Zhao, Erlei Chen, Shubin Liu

BPM (Beam Position Measurement) system is one of the most important beam diagnostic instruments in accelerators. A fully digital BPM (DBPM) has been designed for SSRF (Shanghai Synchrotron Radiation Facility). As Analog-to-Digital Converter (ADC) is one crucial part in the DBPM system, the sampling methods should be studied to achieve optimum performance. We

Mohamadreza Ahmadi, Masahiro Ono, Michel D. Ingham, Richard M. Murray

We consider the problem of designing policies for partially observable Markov decision processes (POMDPs) with dynamic coherent risk objectives. Synthesizing risk-averse optimal policies for POMDPs requires infinite memory and thus undecidable. To overcome this difficulty, we propose a method based on bounded policy iteration for designing stochastic but fin

Shadi Haddad, Abhishek Halder

We study the convex geometry of the forward reach sets for integrator dynamics in finite dimensions with bounded control. We derive closed-form expressions for the volume and the diameter (i.e., maximal width) of these sets in terms of the state space dimension, control bound, and time. These results are novel, and use convex analysis to give an analytical h

Jenish C. Mehta, Leonard J. Schulman

The classic graphical Cheeger inequalities state that if $M$ is an $n\times n$ symmetric doubly stochastic matrix, then \[ \frac{1-\lambda_{2}(M)}{2}\leq\phi(M)\leq\sqrt{2\cdot(1-\lambda_{2}(M))} \] where $\phi(M)=\min_{S\subseteq[n],|S|\leq n/2}\left(\frac{1}{|S|}\sum_{i\in S,j\not\in S}M_{i,j}\right)$ is the edge expansion of $M$, and $\lambda_{2}(M)$ is t

Xuan Wen, Qiong Li, Haokun Mao, Yi Luo

Reconciliation is a crucial procedure in post-processing of continuous variable quantum key distribution (CV-QKD) system, which is used to make two distant legitimate parties share identical corrected keys. The adaptive reconciliation is necessary and important for practical systems to cope with the variable channel. Many researchers adopt the punctured LDPC

Mohammadhadi Azari, George Kirczenow

We present electronic structure and quantum transport calculations that predict conducting channels induced in graphene quantum dots by lines of adsorbed hydrogen atoms to function as highly efficient, experimentally realizable valley filters, accumulators and switches. The underlying physics is a novel property of graphene Dirac point resonances (DPRs) that

Tomoki Anzai, Kuniyuki Takahashi

For in-hand manipulation, estimation of the object pose inside the hand is one of the important functions to manipulate objects to the target pose. Since in-hand manipulation tends to cause occlusions by the hand or the object itself, image information only is not sufficient for in-hand object pose estimation. Multiple modalities can be used in this case, th

Kuniyuki Takahashi, Kenta Yonekura

We propose a method to annotate segmentation masks accurately and automatically using invisible marker for object manipulation. Invisible marker is invisible under visible (regular) light conditions, but becomes visible under invisible light, such as ultraviolet (UV) light. By painting objects with the invisible marker, and by capturing images while alternat

F. Chegini, F. Kheirandish, M. R. Setare

In the first part of the present work, the correction to photon emission rate of an oscillating two-level atom in the presence of electromagnetic quantum vacuum field has been investigated for two different configurations: (i) Atom is trapped in the vicinity of a perfect conductor (ii) Atom is trapped between two perfect conductors. In the second part, the c

Cathryn M. Trott, Jonathan C. Pober

Interferometric experiments of the reionization era offer the advantages of measuring power in spatial modes with increased sensitivity afforded by multiple independent sky measurements. Here we review early work to measure this signal, current experiments, and future opportunities, highlighting the lessons learned along the way that have shaped the research

Shuanglin Sun, Yun-An Yan

The key difficulty to develop efficient high-order methods for integrating stochastic differential equations lies in the calculations of the multiple stochastic integrals. This letter suggests a scheme to compute the stochastic integrals for the colored noises based on the white noise representation. The multiple stochastic integrals involving one and two st

Uttam Paudel, Marta Luengo-Kovac, Jacob Pilawa, T. Justin Shaw

Reservoir computing is a recurrent machine learning framework that expands the dimensionality of a problem by mapping an input signal into a higher-dimension reservoir space that can capture and predict features of complex, non-linear temporal dynamics. Here, we report on a bulk optical demonstration of an analog reservoir computer using speckles generated b

Yihan Jiang, Jakub Konečný, Keith Rush, Sreeram Kannan

Federated Learning (FL) refers to learning a high quality global model based on decentralized data storage, without ever copying the raw data. A natural scenario arises with data created on mobile phones by the activity of their users. Given the typical data heterogeneity in such situations, it is natural to ask how can the global model be personalized for e

Anthony D. Rice, Abhishek Sharan, Nathaniel S. Wilson, Sean D. Harrington

As progress is made on thin-film synthesis of Heusler compounds, a more complete understanding of the surface will be required to control their properties, especially as functional heterostructures are explored. Here, the surface reconstructions of semiconducting half-Heusler NiTiSn(001), and Ni1+xTiSn(001) (x=0.0-1.0) are explored as a way to optimize growt

Fu-Ming Guo, Sijia Liu, Finlay S. Mungall, Xue Lin

Recently, pre-trained language representation flourishes as the mainstay of the natural language understanding community, e.g., BERT. These pre-trained language representations can create state-of-the-art results on a wide range of downstream tasks. Along with continuous significant performance improvement, the size and complexity of these pre-trained neural

Jingwei Ma, Jiahui Wen, Mingyang Zhong, Liangchen Liu

In recommender systems, the user-item interaction data is usually sparse and not sufficient for learning comprehensive user/item representations for recommendation. To address this problem, we propose a novel dual-bridging recommendation model (DBRec). DBRec performs latent user/item group discovery simultaneously with collaborative filtering, and interacts

François Gay-Balmaz, Cornelia Vizman

We describe the coadjoint orbits of the group of volume preserving diffeomorphisms of $\mathbb{R}^3$ associated to the motion of closed vortex sheets in ideal 3D fluids. We show that these coadjoint orbits can be identified with nonlinear Grassmannians of compact surfaces enclosing a given volume and endowed with a closed 1-form describing the vorticity dens

Xiting Zhao, Zhijie Yang, Sören Schwertfeger

This paper presents a method to detect reflection of 3D light detection and ranging (Lidar) scans and uses it to classify the points and also map objects outside the line of sight. Our software uses several approaches to analyze the point cloud, including intensity peak detection, dual return detection, plane fitting, and finding the boundaries. These approa

Mingjie Sun, Jimin Xiao, Eng Gee Lim, Yanchu Xie

In this paper, we aim to tackle the task of semi-supervised video object segmentation across a sequence of frames where only the ground-truth segmentation of the first frame is provided. The challenges lie in how to online update the segmentation model initialized from the first frame adaptively and accurately, even in presence of multiple confusing instance

Jun-Feng Wang, Fei-Fei Yan, Qiang Li, Zheng-Hao Liu

Solid-state color centers with manipulatable spin qubits and telecom-ranged fluorescence are ideal platforms for quantum communications and distributed quantum computations. In this work, we coherently control the nitrogen-vacancy (NV) center spins in silicon carbide at room temperature, in which telecom-wavelength emission is detected. We increase the NV co

Weiwei Ding, Hiroshi Matano

This paper is concerned with the Cauchy problem $$u_t=u_{xx} +f(t,u), \,\,\, x\in\mathbb{R},\,t>0, $$ $$u(0,x)= u_0(x), \,\,\, x\in\mathbb{R},$$ where $f$ is a rather general nonlinearity that is periodic in $t$, and satisfies $f(\cdot,0)\equiv 0$ and that the corresponding ODE has a positive periodic solution $p(t)$. Assuming that $u_0$ is front-like, that

Samuel Bladwell

Monolayer Graphene contains two inequivalent local minimum, valleys, located at $K$ and $K'$ in the Brillouin zone. There has been considerable interest in the use of these two valleys as a doublet for information processing. Herein I propose a method to resolve valley currents spatially, using only a weak magnetic field. Due to the trigonal warping of the v

M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed

We report a study of the $e^{+}e^{-} \to D^{+} D^{-} \pi^{+} \pi^{-}$ process using $e^{+}e^{-}$ collision data samples with an integrated luminosity of $2.5\,\rm{fb}^{-1}$ at center-of-mass energies from 4.36 to $4.60 \rm{GeV}$, collected with the BESIII detector at the BEPCII storage ring. The $D_{1}(2420)^+$ is observed in the $D^{+} \pi^{+} \pi^{-}$ mass

Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán

Arbitrary style transfer is an important problem in computer vision that aims to transfer style patterns from an arbitrary style image to a given content image. However, current methods either rely on slow iterative optimization or fast pre-determined feature transformation, but at the cost of compromised visual quality of the styled image; especially, disto

Shaoyu Dai, Yang Liu, Yifei Pan

In this note, we prove the existence of weak solutions of a Poisson type equation in the weighted Hilbert space $L^2(\mathbb{R}^n,e^{-|x|^2})$.

Swapnil Ghodke, Omprakash Muthusamy, Kevin Delime Codrin, Seongho Choi

The efficiency of energy conversion in thermoelectric generators (TEGs) is directly proportional to electrical conductivity and Seebeck coefficient while inversely to thermal conductivity. The challenge is to optimize these interdependent parameters simultaneously. In this work, the problem is addressed with a novel approach of nanostructuring and constructi

Luke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro, Christopher Ré

Machine learning models for medical image analysis often suffer from poor performance on important subsets of a population that are not identified during training or testing. For example, overall performance of a cancer detection model may be high, but the model still consistently misses a rare but aggressive cancer subtype. We refer to this problem as hidde

Yossi Bokor, Daniel Grixti-Cheng, Markus Hegland, Stephen Roberts

Many data-rich industries are interested in the efficient discovery and modelling of structures underlying large data sets, as it allows for the fast triage and dimension reduction of large volumes of data embedded in high dimensional spaces. The modelling of these underlying structures is also beneficial for the creation of simulated data that better repres

Tianshu Ouyang, Jiahong Cai, Yuxuan Gao, Xinyan He

Electric vehicles (EVs) are increasingly used in transportation. Worldwide use of EVs, for their limited battery capacity, calls for effective planning of EVs charging stations to enhance the efficiency of using EVs. This paper provides a methodology of describing EV detouring behavior for recharging, and based on this, we adopt the extra driving length caus

Serang Park, Zackery Z. Clark, Yanzeng Li, Michael McLamb

Additive manufactured THz optics have been introduced as an efficient alternative to their commercial counterparts. Among various additive manufacturing methods, stereolithography provides superior spatial resolution and surface finish. However, examples of stereolithographically fabricated components for THz applications are still scarce. In this paper, we

Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin

We study the problem of training machine learning models incrementally with batches of samples annotated with noisy oracles. We select each batch of samples that are important and also diverse via clustering and importance sampling. More importantly, we incorporate model uncertainty into the sampling probability to compensate for poor estimation of the impor

Ruisen Luo, Tao Hu, Zuodong Tang, Chen Wang

To solve the problem of inaccurate recognition of types of communication signal modulation, a RNN neural network recognition algorithm combining residual block network with attention mechanism is proposed. In this method, 10 kinds of communication signals with Gaussian white noise are generated from standard data sets, such as MASK, MPSK, MFSK, OFDM, 16QAM,

Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong

In this paper, we propose the differentiable mask-matching network (DMM-Net) for solving the video object segmentation problem where the initial object masks are provided. Relying on the Mask R-CNN backbone, we extract mask proposals per frame and formulate the matching between object templates and proposals at one time step as a linear assignment problem wh

Ernie Croot, Hamed Mousavi

Following attempts at an analytic proof of the Pentagonal Number Theorem, we report on the discovery of a general principle leading to an unexpected cancellation of oscillating sums. After stating the motivation, and our theorem, we apply it to prove several results on the Prouhet-Tarry-Escott Problem, integer partitions, and the distribution of prime number

Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán

With the recent success of deep neural networks in computer vision, it is important to understand the internal working of these networks. What does a given neuron represent? The concepts captured by a neuron may be hard to understand or express in simple terms. The approach we propose in this paper is to characterize the region of input space that excites a

Jaqueline J. Brito, Thiago Mosqueiro, Jeremy Rotman, Victor Xue

In today's world of big data, computational analysis has become a key driver of biomedical research. Recent exponential growth in the volume of available omics data has reshaped the landscape of contemporary biology, creating demand for a continuous feedback loop that seamlessly integrates experimental biology techniques and bioinformatics tools. High-perfor

Li-Feng Xi, Jun Jie Miao, Ying Xiong

We obtain a necessary and sufficient condition for Lalley-Gatzouras sets to be uniform disconnected. This enable us to find all Lalley-Gatzouras sets which are quasisymmetrically equivalent to the Cantor ternary set. As another application, we also study the limit behavior of the gap sequence of Lalley-Gatzouras sets.

Steven Atkinson, Waad Subber, Liping Wang, Genghis Khan

We present a method of discovering governing differential equations from data without the need to specify a priori the terms to appear in the equation. The input to our method is a dataset (or ensemble of datasets) corresponding to a particular solution (or ensemble of particular solutions) of a differential equation. The output is a human-readable different

Mohammad Hamghalam, Baiying Lei, Tianfu Wang

The magnetic resonance (MR) analysis of brain tumors is widely used for diagnosis and examination of tumor subregions. The overlapping area among the intensity distribution of healthy, enhancing, non-enhancing, and edema regions makes the automatic segmentation a challenging task. Here, we show that a convolutional neural network trained on high-contrast ima

Ke-ke Shang, Michael Small, Yan Wang, Di Yin

Research into detection of dense communities has recently attracted increasing attention within network science, various metrics for detection of such communities have been proposed. The most popular metric -- Modularity -- is based on the so-called rule that the links within communities are denser than external links among communities, has become the defaul

Luqi Yuan, Avik Dutt, Mingpu Qin, Shanhui Fan

The recent emerging field of synthetic dimension in photonics offers a variety of opportunities for manipulating different internal degrees of freedom of photons such as the spectrum of light. While nonlinear optical effects can be incorporated into these photonic systems with synthetic dimensions, these nonlinear effects typically result in long-range inter

Hua Huang, Adrian Barbu

Human beings are particularly good at reasoning and inference from just a few examples. When facing new tasks, humans will leverage knowledge and skills learned before, and quickly integrate them with the new task. In addition to learning by experimentation, human also learn socio-culturally through instructions and learning by example. In this way humans ca

Y. V. Pershin, M. Di Ventra

Wang et al. claim [J. Appl. Phys. 125, 054504 (2019)] that a current-carrying wire interacting with a magnetic core represents a memristor. Here, we demonstrate that this claim is false. We first show that such memristor "discovery" is based on incorrect physics, which does not even capture basic properties of magnetic core materials, such as their magnetic

Xiaozhi Lin, Guanwen Fang, Zhen-Yi Cai, Tao Wang

We present a measurement of the spatial clustering of rest-frame UV-selected massive galaxies at $0.5\le z \le 2.5$ in the COSMOS/UltraVISTA field. Considering four separate redshift bins with $\Delta z=0.5$, we construct three galaxy populations, i.e., red sequence (RS), blue cloud (BC), and green valley (GV) galaxies, according to their rest-frame extincti

Yifei Zhao

Suppose $X$ is a smooth, proper, geometrically connected curve over $\mathbb F_q$ with an $\mathbb F_q$-rational point $x_0$. For any $\mathbb F_q^{\times}$-character $\sigma$ of $\pi_1(X)$ trivial on $x_0$, we construct a functor $\mathbb L_n^{\sigma}$ from the derived category of coherent sheaves on the moduli space of deformations of $\sigma$ over the Wit

Siu Wun Cheung, Eric T. Chung, Wing Tat Leung

Numerical simulation of flow problems and wave propagation in heterogeneous media has important applications in many engineering areas. However, numerical solutions on the fine grid are often prohibitively expensive, and multiscale model reduction techniques are introduced to efficiently solve for an accurate approximation on the coarse grid. In this paper,

Kevin Zhang, Mohit Sharma, Manuela Veloso, Oliver Kroemer

Cutting is a common form of manipulation when working with divisible objects such as food, rope, or clay. Cooking in particular relies heavily on cutting to divide food items into desired shapes. However, cutting food is a challenging task due to the wide range of material properties exhibited by food items. Due to this variability, the same cutting motions

Yajing Liu, April Sagan, Andrey Bernstein, Rui Yang

This paper examines the problem of state estimation in power distribution systems under low-observability conditions. The recently proposed constrained matrix completion method which combines the standard matrix completion method and power flow constraints has been shown to be effective in estimating voltage phasors under low-observability conditions using s

Frank Preiswerk, Spencer T. Brinker, Nathan J. McDannold, Timothy Y. Mariano

In recent years, non-invasive neuro-modulation methods such as Focused Ultrasound (FUS) have gained popularity. The aim of this work is to introduce the use of existing open-source technology for surgical navigation to the field of multimodal non-invasive brain stimulation. Unlike homegrown and commercial systems, the use of well-documented, well maintained,

Gerardo Aquino, Weisi Guo, Alan Wilson

The risk of conflict is exasperated by a multitude of internal and external factors. Current multivariate analysis paints diverse causal risk profiles that vary with time. However, these profiles evolve and a universal model to understand that evolution remains absent. Most of the current conflict analysis is data-driven and conducted at the individual count

Jingru Yi, Pengxiang Wu, Dimitris N. Metaxas

This paper proposes a new deep neural network for object detection. The proposed network, termed ASSD, builds feature relations in the spatial space of the feature map. With the global relation information, ASSD learns to highlight useful regions on the feature maps while suppressing the irrelevant information, thereby providing reliable guidance for object

Ivonne Guevara, Howard M. Wiseman

Here, we are concerned with comparing estimation schemes for the quantum state under continuous measurement (quantum trajectories), namely quantum state filtering and, as introduced by us [Phys. Rev. Lett. 115, 180407 (2015)], quantum state smoothing. Unfortunately, the cumulative errors in the most typical simulations of quantum trajectories with a total ti

Scott Ruoti, Ben Kaiser, Arkady Yerukhimovich, Jeremy Clark

Bitcoin's success has led to significant interest in its underlying components, particularly Blockchain technology. Over 10 years after Bitcoin's initial release, the community still suffers from a lack of clarity regarding what properties defines Blockchain technology, its relationship to similar technologies, and which of its proposed use-cases are tenable

Abdulgani Annaberdiyev, Cody A. Melton, M. Chandler Bennett, Guangming Wang

Very recently, we introduced a set of correlation consistent effective core potentials (ccECPs) constructed within full many-body approaches. By employing significantly more accurate correlated approaches we were able to reach a new level of accuracy for the resulting effective core Hamiltonians. We also strived for simplicity of use and easy transferability

Navid Hashemi, Justin Ruths

We present a convex optimization to reduce the impact of sensor falsification attacks in linear time invariant systems controlled by observer-based feedback. We accomplish this by finding optimal observer and controller gain matrices that minimize the size of the reachable set of attack-induced states. To avoid trivial solutions, we integrate a covariance-ba

Taoran Li

An effort towards understanding of the stray light problems for the Xinglong 2.16-m telescope was presented to estimate the stray light performance of the telescope itself and provide a method for improving the stray light suppression. The stray light analysis for 2.16-m telescope model, which consists the onion shaped dome, telescope structure, equatorial m

Per Sebastian Skardal

We study the dynamics of nonlinear random walks on complex networks. We investigate the role and effect of directed network topologies on long-term dynamics. While a period-doubling bifurcation to alternating patterns occurs at a critical bias parameter value, we find that some directed structures give rise to a different kind of bifurcation that gives rise

Pilhwa Lee

We investigate calcium signaling feedback through calcium-activated potassium channels of a dendritic spine by applying the immersed boundary method with electrodiffusion. We simulate the stochastic gating of such ion channels and the resulting spatial distribution of concentration, current, and membrane voltage within the dendritic spine. In this simulation

Hao Wang, Mohammad Reza Amini, Ziyou Song, Jing Sun

In this paper, we propose a combined energy and comfort optimization (CECO) strategy for the air conditioning (A/C) system of the connected and automated vehicles (CAVs). By leveraging the weather and traffic predictions enabled by the emerging CAV technologies, the proposed strategy is able to minimize the A/C system energy consumption while maintaining the

Carl Dunlea, Chijin Xiao, Akira Hirose

Injection of relatively high density spheromaks with significant helicity-content into a tokamak has been proposed as a means for fueling and current drive. The CHI (Co-axial Helicity Injection) device was devised to inject current to the STOR-M tokamak. Various circuit modifications were made to the CHI controls, enabling testing of various injection config

Sin-Han Kang, Hong-Gyu Jung, Seong-Whan Lee

In an effort to interpret black-box models, researches for developing explanation methods have proceeded in recent years. Most studies have tried to identify input pixels that are crucial to the prediction of a classifier. While this approach is meaningful to analyse the characteristic of blackbox models, it is also important to investigate pixels that inter

Bassim Arkook, Christopher Safranski, Rodolfo Rodriguez, Ilya N. Krivorotov

Next-generation spintronic applications require material properties that can be hardly met by one material candidate. Here we demonstrate that by combining insulating and metallic magnets, enhanced spin-charge conversion and energy-efficient thermal spin currents can be realized. We develop a nanowire device consisting of an yttrium iron garnet and permalloy

Gorkem Secer, Ali Levent Cinar

A long-standing argument in model-based control of locomotion is about the level of complexity that a model should have to define a behavior such as running. Even though goldilocks model based on biomechanical evidence is often sought, it is unclear what complexity level qualifies to be such a model. This dilemma deepens further for bipedal robotic running w

Yu-Nung Su, Sheng-Yuan Liu, Zhi-Yun Li, Chin-Fei Lee

We report ALMA observations of NGC 1333 IRAS 4A, a young low-mass protostellar binary, referred as 4A1 and 4A2. With multiple H$_2$CO transitions and HNC (4$-$3) observed at a resolution of 0.25" ($\sim$70 au), we investigate the gas kinematics of 4A1 and 4A2. Our results show that, on the large angular scale ($\sim$10"), 4A1 and 4A2 each display a well-coll

Erico S. P. Lopes, Lukas T. N. Landau

MIMO systems are considered as most promising for wireless communications. However, with an increasing number of radio front ends the corresponding energy consumption and costs become an issue, which can be relieved by the utilization of low-resolution quantizers. In this study we propose an optimal precoding algorithm constrained to constant envelope signal

Huaian Diao, Zhao Song, David P. Woodruff, Xin Yang

In the total least squares problem, one is given an $m \times n$ matrix $A$, and an $m \times d$ matrix $B$, and one seeks to "correct" both $A$ and $B$, obtaining matrices $\hat{A}$ and $\hat{B}$, so that there exists an $X$ satisfying the equation $\hat{A}X = \hat{B}$. Typically the problem is overconstrained, meaning that $m \gg \max(n,d)$. The cost of th

Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang

Bioprocesses have received a lot of attention to produce clean and sustainable alternatives to fossil-based materials. However, they are generally difficult to optimize due to their unsteady-state operation modes and stochastic behaviours. Furthermore, biological systems are highly complex, therefore plant-model mismatch is often present. To address the afor

Xi Xiong, Erdong Xiao, Li Jin

Platooning of heavy-duty vehicles (HDVs) is a key component of smart and connected highways and is expected to bring remarkable fuel savings and emission reduction. In this paper, we study the coordination of HDV platooning on a highway section. We model the arrival of HDVs as a Poisson process. Multiple HDVs are merged into one platoon if their headways are

Hai Wang, Dian Yu, Kai Sun, Janshu Chen

Recently, pre-trained language models have achieved remarkable success in a broad range of natural language processing tasks. However, in multilingual setting, it is extremely resource-consuming to pre-train a deep language model over large-scale corpora for each language. Instead of exhaustively pre-training monolingual language models independently, an alt

Yoji Michishita

We determine the general form of the first order linear symmetry operators for the linearized field equation of metric perturbations in the spacetimes of dimension D>=4. Apart from the part derived easily from the invariance under general coordinate transformations, we find a part consisting of a Killing-Yano 3-form.

Mohamed Ousbika, Zakaria El Allali, Lingju Kong

Using the variational approach and the critical point theory, we established several criteria for the existence of at least one nontrivial solution for a discrete elliptic boundary value problem with a weight $p(\cdot, \cdot)$ and depending on a real parameter $\lambda$.

H. Nassar, Y. Y. Chen, G. L. Huang

Rotationally resonant metamaterials are leveraged to answer a longstanding question regarding the existence of transformation-invariant elastic materials and the ad-hoc possibility of transformationbased passive cloaking in full plane elastodynamics. Combined with tailored lattice geometries, rotational resonance is found to induce a polar and chiral behavio

Ali Marjaninejad, Jie Tan, Francisco J. Valero-Cuevas

Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also add dynamical complexity which makes them more challenging to model and control. The impact of this added complexity to autonomous learning has not been thoroughly explored. This is especially relevant to tendon-

Vishaal Kapoor

In his paper Almost-Primes Represented by Quadratic Polynomials, Iwaniec proved that the polynomial n^2 + 1 takes on values with at most two prime factors (counted with multiplicity) infinitely often. He states that "in order to avoid technical complications, we shall restrict our proof to the polynomial n^2 + 1.". In this exposition, we follow Iwaniec's pro

Joshua T. Margolis, Yongjia Song, Scott J. Mason

The multi-vehicle covering tour problem with time windows (MCTPTW) aims to construct a set of maximal coverage routes for a fleet of vehicles that serve (observe) a secondary set of sites given a fixed time schedule, coverage requirements, and energy restrictions. The problem is formulated as a mixed-integer second-order cone programming (MISOCP) model and i