Numerical Analysis and Scientific Computing Commons^™

Coupled Dynamics Of Spin Qubits In Optical Dipole Microtraps: Application To The Error Analysis Of A Rydberg-Blockade Gate, L. V. Gerasimov, R. R. Yusupov, A. D. Moiseevsky, I. Vybornyi, K. S. Tikhonov, S. P. Kulik, S. S. Straupe, Charles I. Sukenik, D. V. Kupriyanov

Physics Faculty Publications

Single atoms in dipole microtraps or optical tweezers have recently become a promising platform for quantum computing and simulation. Here we report a detailed theoretical analysis of the physics underlying an implementation of a Rydberg two-qubit gate in such a system—a cornerstone protocol in quantum computing with single atoms. We focus on a blockade-type entangling gate and consider various decoherence processes limiting its performance in a real system. We provide numerical estimates for the limits on fidelity of the maximally entangled states and predict the full process matrix corresponding to the noisy two-qubit gate. We consider different excitation geometries and …

High Performance Data Acquisition And Analysis Routines For The Nab Experiment, David Mathews

Theses and Dissertations--Physics and Astronomy

Probes of the Standard Model of particle physics are pushing further and further into the so-called “precision frontier”. In order to reach the precision goals of these experiments, a combination of elegant experimental design and robust data acquisition and analysis is required. Two experiments that embody this philosophy are the Nab and Calcium-45 experiments. These experiments are probing the understanding of the weak interaction by examining the beta decay of the free neutron and Calcium-45 respectively. They both aim to measure correlation parameters in the neutron beta decay alphabet, a and b. The parameter a, the electron-neutrino correlation coefficient, is …

On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang

Research Collection School Of Computing and Information Systems

The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between two trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering similar subtrajectories within a single trajectory or across multiple trajectories. In this paper, we adopt DFD as the similarity measure, and study two representative trajectory analysis problems, namely, motif discovery and frequent pattern discovery. Due to the time complexity of DFD, these tasks are computationally challenging. We address that challenge with a suite of …

Interest Points Analysis For Internet Forum Based On Long-Short Windows Similarity, Xinghai Ju, Jicang Lu, Xiangyang Luo, Gang Zhou, Shiyu Wang, Shunhang Li, Yang Yang

Research Collection School Of Computing and Information Systems

For Internet forum Points of Interest (PoI), existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation, which lead to blindness in method selection. To address this problem, this paper proposed a PoI variation prediction framework based on similarity analysis between long and short windows. Based on the framework, this paper presented 5 PoI analysis algorithms which can be categorized into 2 types, i.e., the traditional sequence analysis methods such as autoregressive integrated moving average model (ARIMA), support vector regressor (SVR), and the deep learning methods such as convolutional neural network (CNN), long-short …

Face To Purchase: Predicting Consumer Choices With Structured Facial And Behavioral Traits Embedding, Zhe Liu, Xianzhi Wang, Lina Yao, Jake An, Lei Bai, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Predicting consumers’ purchasing behaviors is critical for targeted advertisement and sales promotion in e-commerce. Human faces are an invaluable source of information for gaining insights into consumer personality and behavioral traits. However, consumer's faces are largely unexplored in previous research, and the existing face-related studies focus on high-level features such as personality traits while neglecting the business significance of learning from facial data. We propose to predict consumers’ purchases based on their facial features and purchasing histories. We design a semi-supervised model based on a hierarchical embedding network to extract high-level features of consumers and to predict the top-N purchase …

Do Sequels Outperform Or Disappoint? Insights From An Analysis Of Amazon Echo Consumer Reviews, Kyong Jin Shim, Siaw Ling Lo, Su Yee Liew

Research Collection School Of Computing and Information Systems

Rapid technological advances in recent years drastically transformed our world. Amidst modern technological inventions such as smart phones, smart watches and smart home devices, consumers of electronic digital devices experience greatly improved automation, productivity, and efficiency in conducting routine daily tasks, information searching, shopping as well as finding entertainment. In the last few years, the global smart speaker market has undergone significant growth. As technology continues to advance and smart speakers are equipped with innovative features, the adoption of smart speakers will increase and so will consumer expectations. This research paper presents an aspect-specific sentiment analysis of consumer reviews of …

Towards An Instant Structure-Property Prediction Quality Control Tool For Additive Manufactured Steel Using A Crystal Plasticity Trained Deep Learning Surrogate, Yuhui Tu, Zhongzhou Liu, Luiz Carneiro, Caitriona M. Ryan, Andrew C. Parnell, Sean B. Leen

Research Collection School Of Computing and Information Systems

The ability to conduct in-situ real-time process-structure-property checks has the potential to overcome process and material uncertainties, which are key obstacles to improved uptake of metal powder bed fusion in industry. Efforts are underway for live process monitoring such as thermal and image-based data gathering for every layer printed. Current crystal plasticity finite element (CPFE) modelling is capable of predicting the associated strength based on a microstructural image and material data but is computationally expensive. This work utilizes a large database of input–output samples from CPFE modelling to develop a trained deep neural network (DNN) model which instantly estimates the …

Bounded-Degree Plane Geometric Spanners: Connecting The Dots Between Theory And Practice, Matthew Alexander Graham

UNF Graduate Theses and Dissertations

The construction of bounded-degree plane geometric spanners has been a focus of interest since 2002 when Bose, Gudmundsson, and Smid proposed the first algorithm to construct such spanners. To date, eleven algorithms have been designed with various trade-offs in degree and stretch factor. We have implemented these sophisticated algorithms in C++ using the CGAL library and experimented with them using large synthetic and real-world pointsets. Our experiments have revealed their practical behavior and real-world efficacy. We share the implementations via GitHub for broader uses and future research.

We present a simple practical algorithm, named AppxStretchFactor, that can estimate stretch factors …

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …

Deep Convolutional Neural Networks For Accurate Diagnosis Of Covid-19 Patients Using Chest X-Ray Image Databases From Italy, Canada, And The Usa, Amgad A. Salama, Samy H. Darwish, Samir M. Abdel-Mageed, Radwa A. Meshref, Ehab I. Mohamed

The University of Louisville Journal of Respiratory Infections

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), famously known as COVID-19, has quickly become a global pandemic. Chest X-ray (CXR) imaging has proven reliable, fast, and cost-effective for identifying COVID-19 infections, which proceeds to display atypical unilateral patchy infiltration in the lungs like typical pneumonia. We employed the deep convolutional neural network (DCNN) ResNet-34 to detect and classify CXR images from patients with COVID-19 and Viral Pneumonia and Normal Controls.

Methods: We created a single database containing 781 source CXR images from four different international sub-databases: the Società Italiana di Radiologia Medica e Interventistica (SIRM), the GitHub Database, the …

A Framework For Phrase Based Smt In The Technical Translation Domain, Hisham Farouk Khodeir

Archived Theses and Dissertations

No abstract provided.

Error Correction In Quantum Cryptography, Mohamed Salah El Ashmawy

Archived Theses and Dissertations

No abstract provided.

Analyze And Examine Wildfire Events In California, Aleena Hoodith, Sakim Zaman, Safoan Hossain, Jiehao Huang

Publications and Research

•A wildfire is an unplanned, unwanted, uncontrolled fire in an area of combustible vegetation starting in rural areas and urban areas. •Recent studies have shown that the effect of anthropogenic climate change has fueled the wildfire events, leading to an increase in the annual burned areas and number of events. •California is one of the places having the most deadliest and destructive wildfire seasons. With the global warming effect of 1°C since 1850, the 20 largest wildfires events that have occurred in California, 8 of them were in 2017. (Center For Climate And Energy Solutions) •Climate change is primarily caused …

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.14 was released on 27 October, 2021. It is compatible with R 4.1.0 and consists of 2083 software packages, 408 experiment data packages, 904 up-to-date annotation packages, and 29 workflows.

Changes In R, Tomas Kalibera, Sebastian Meyer, Kurt Hornik, Gennadiy Starostin, Luke Tierney

The R Journal

We present important changes in the development version of R (referred to as R-devel, to become R 4.2) and give a summary of the new search engine interfaced by RSiteSearch(). Some statistics on bug tracking activities in 2021 are also provided.

Rpese: Risk And Performance Estimators Standard Errors With Serially Dependent Data, Anthony-Alexander Christidis, R Douglas Martin

The R Journal

The R package RPESE (Risk and Performance Estimators Standard Errors) implements a new method for computing accurate standard errors of risk and performance estimators when returns are serially dependent. The new method makes use of the representation of a risk or performance estimator as a summation of a time series of influence-function (IF) transformed returns, and computes estimator standard errors using a sophisticated method of estimating the spectral density at frequency zero of the time series of IF-transformed returns. Two additional packages used by RPESE are introduced, namely RPEIF which computes and provides graphical displays of the IF of risk …

The Vote Package: Single Transferable Vote And Other Electoral Systems In R, Adrian E. Raftery, Hana ŠevčÍková, Bernard W. Silverman

The R Journal

We describe the vote package in R, which implements the plurality (or first-past-the-post), two-round runoff, score, approval, and Single Transferable Vote (STV) electoral systems, as well as methods for selecting the Condorcet winner and loser. We emphasize the STV system, which we have found to work well in practice for multi-winner elections with small electorates, such as committee and council elections, and the selection of multiple job candidates. For single-winner elections, STV is also called Instant Runoff Voting (IRV), Ranked Choice Voting (RCV), or the alternative vote (AV) system. The package also implements the STV system with equal preferences, for …

Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos

The R Journal

Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language

Bssm: Bayesian Inference Of Non-Linear And Non-Gaussian State Space Models In R, Jouni Helske, Matti Vihola

The R Journal

We present an R package bssm for Bayesian non-linear/non-Gaussian state space modeling. Unlike the existing packages, bssm allows for easy-to-use approximate inference based on Gaussian approximations such as the Laplace approximation and the extended Kalman filter. The package also accommodates discretely observed latent diffusion processes. The inference is based on fully automatic, adaptive Markov chain Monte Carlo (MCMC) on the hyperparameters, with optional importance sampling post-correction to eliminate any approximation bias. The package also implements a direct pseudo-marginal MCMC and a delayed acceptance pseudo-marginal MCMC using intermediate approximations. The package offers an easy-to-use interface to define models with linear-Gaussian state …

Openskies - Integration Of Aviation Data Into The R Ecosystem, Rafael Ayala, Daniel Ayala, Lara Sellés Vidal, David Ruiz

The R Journal

Aviation data has become increasingly more accessible to the public thanks to the adoption of technologies such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Mode S, which provide aircraft information over publicly accessible radio channels. Furthermore, the OpenSky Network provides multiple public resources to access such air traffic data from a large network of ADS-B receivers. Here, we present openSkies, the first R package for processing public air traffic data. The package provides an interface to the OpenSky Network resources, standardized data structures to represent the different entities involved in air traffic data, and functionalities to analyze and visualize such …