Databases and Information Systems Commons^™

Comparison Of Major Cloud Providers, Justin Berman

Other Student Works

This paper will compare the following major cloud providers: Microsoft Azure, Amazon AWS, Google Cloud, and IBM Cloud. An introduction to the companies and their history, fundamentals and services, strengths and weaknesses, costs, and their security will be discussed throughout this writing.

High Performance Document Store Implementation In Rust, Ishaan Aggarwal

Master's Projects

Databases are a core part of any application which requires persistence of data. The performance of applications involving the use of database systems is directly proportional to how fast their database read-write operations are. The aim of this project was to build a high- performance document store which can support variety of applications which require data storage and retrieval of some kind. This document store can be used as an independently running backend service which can be utilized by search engines, applications which deal with keeping records, etc. We used Rust to make this document store which is fast, robust, …

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 …

Node.Js Based Document Store For Web Crawling, David Bui

Master's Projects

WARC files are central to internet preservation projects. They contain the raw resources of web crawled data and can be used to create windows into the past of web pages at the time they were accessed. Yet there are few tools that manipulate WARC files outside of basic parsing. The creation of our tool WARC-KIT gives users in the Node.js JavaScript environment, a tool kit to interact with and manipulate WARC files.

Included with WARC-KIT is a WARC parsing tool known as WARCFilter that can be used standalone tool to parse, filter, and create new WARC files. WARCFilter can also, …

Using Parallel Primary Caches To Improve Capacity And Bandwidth, John Rubena Wani

Archived Theses and Dissertations

No abstract provided.

Moment-Preserving Piecewise Approximation For 1-D And 2-D Signals, Soha M. A. A. Seif

Archived Theses and Dissertations

No abstract provided.

Shape Similarity By Deformation Using Polynomial Transformation, Hanan M. Moussa

Archived Theses and Dissertations

No abstract provided.

Messiness: Automating Iot Data Streaming Spatial Analysis, Christopher White, Atilio Barreda Ii

Publications and Research

The spaces we live in go through many transformations over the course of a year, a month, or a day; My room has seen tremendous clutter and pristine order within the span of a few hours. My goal is to discover patterns within my space and formulate an understanding of the changes that occur. This insight will provide actionable direction for maintaining a cleaner environment, as well as provide some information about the optimal times for productivity and energy preservation.

Using a Raspberry Pi, I will set up automated image capture in a room in my home. These images will …

Ready, Willing, And Able, Gerry Boyle

Colby Magazine

So what gives? How, after four years on Mayflower Hill, do these Colby alumni have an outsized impact in a fintech company that is focused on, for example, changing the way municipal bonds are traded? What makes them able to dive in and figure it out? “That’s part of the liberal arts education,” said Associate Professor of History John Turner, who taught Tagg Martin ’13, history major turned MarketAxess go-to analyst. “You’re always learning. … You are always going to be mastering something, as opposed to having mastered.”

Efficient Data Structures For Text Processing Applications, Paniz Abedin

Electronic Theses and Dissertations, 2020-2023

This thesis is devoted to designing and analyzing efficient text indexing data structures and associated algorithms for processing text data. The general problem is to preprocess a given text or a collection of texts into a space-efficient index to quickly answer various queries on this data. Basic queries such as counting/reporting a given pattern's occurrences as substrings of the original text are useful in modeling critical bioinformatics applications. This line of research has witnessed many breakthroughs, such as the suffix trees, suffix arrays, FM-index, etc. In this work, we revisit the following problems: 1. The Heaviest Induced Ancestors problem 2. …

Examining The Effects Of Information And Communication Technologies In The Legal Representation Of Latin American Asylum Seekers, Victor M. Portillo Ochoa

Open Access Theses & Dissertations

The purpose of this thesis was to explore how legal defense nonprofit organizations (NPO) are using Information and Communication Technologies (ICT) to provide legal defense for asylum seekers and improve the conditions of immigrants at detention centers. In addition, this research explored the impact of ICTs on legal defense NPOs, bottlenecks, and security implications when supporting vulnerable communities. ICTs profoundly impacted the way we interact in a post-pandemic world, and it presents new challenges and possibilities for legal defense nonprofit organizations that are helping vulnerable communities. This study consists of staff and volunteers from different legal defense nonprofit organizations NPOs …

Fair And Diverse Group Formation Based On Multidimensional Features, Mohammed Saad A Alqahtani

Graduate Theses and Dissertations

The goal of group formation is to build a team to accomplish a specific task. Algorithms are being developed to improve the team's effectiveness so formed and the efficiency of the group selection process. However, there is concern that team formation algorithms could be biased against minorities due to the algorithms themselves or the data on which they are trained. Hence, it is essential to build fair team formation systems that incorporate demographic information into the process of building the group. Although there has been extensive work on modeling individuals’ expertise for expert recommendation and/or team formation, there has been …

The Power Of Renegotiation And Monitoring In Software Outsourcing: Substitutes Or Complements?, He Huang, Minhui Hu, Robert J. Kauffman, Hongyan Xu

Research Collection School Of Computing and Information Systems

Monitoring and contract renegotiation are two common solutions for addressing information asymmetry and uncertainty between a client and a vendor of software outsourcing services. Monitoring is mostly applied in time-and-materials contracts, as a basis for inspecting and reimbursing the vendor’s efforts in system development. Renegotiation, by contrast, is deployed in fixed-price and time-and-materials contracts to mitigate the loss of surplus from uncertainty after system development. We investigate the interaction between monitoring and renegotiation and examine the corresponding contract choice problem. We find that the client benefits from renegotiation based on two effects: an uncertainty-resolution effect and a post-development incentive effect, …

Empirical Evaluation Of Minority Oversampling Techniques In The Context Of Android Malware Detection, Lwin Khin Shar, Nguyen Binh Duong Ta, David Lo

Research Collection School Of Computing and Information Systems

In Android malware classification, the distribution of training data among classes is often imbalanced. This causes the learning algorithm to bias towards the dominant classes, resulting in mis-classification of minority classes. One effective way to improve the performance of classifiers is the synthetic generation of minority instances. One pioneer technique in this area is Synthetic Minority Oversampling Technique (SMOTE) and since its publication in 2002, several variants of SMOTE have been proposed and evaluated on various imbalanced datasets. However, these techniques have not been evaluated in the context of Android malware detection. Studies have shown that the performance of SMOTE …

Learning To Iteratively Solve Routing Problems With Dual-Aspect Collaborative Transformer, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang

Research Collection School Of Computing and Information Systems

Recently, Transformer has become a prevailing deep architecture for solving vehicle routing problems (VRPs). However, it is less effective in learning improvement models for VRP because its positional encoding (PE) method is not suitable in representing VRP solutions. This paper presents a novel Dual-Aspect Collaborative Transformer (DACT) to learn embeddings for the node and positional features separately, instead of fusing them together as done in existing ones, so as to avoid potential noises and incompatible correlations. Moreover, the positional features are embedded through a novel cyclic positional encoding (CPE) method to allow Transformer to effectively capture the circularity and symmetry …

Microservices Orchestration Vs. Choreography: A Decision Framework, Alan @ Ali Madjelisi Megargel, Christopher M. Poskitt, Shankararaman, Venky

Research Collection School Of Computing and Information Systems

Microservices-based applications consist of loosely coupled, independently deployable services that encapsulate units of functionality. To implement larger application processes, these microservices must communicate and collaborate. Typically, this follows one of two patterns: (1) choreography, in which communication is done via asynchronous message-passing; or (2) orchestration, in which a controller is used to synchronously manage the process flow. Choosing the right pattern requires the resolution of some trade-offs concerning coupling, chattiness, visibility, and design. To address this problem, we propose a decision framework for microservices collaboration patterns that helps solution architects to crystallize their goals, compare the key factors, and then …

Data Of The Constructivist Practices In The Learning Environment Survey From Engineering Undergraduates: An Exploratory Factor Analysis, Chengcheng Li, Shaoan Zhang, Tiberio Garza, Yingtao Jiang

Teaching and Learning Faculty Research

This paper presents the dataset of a questionnaire on first-year engineering undergraduates’ perceptions of constructivist practices in the learning environment. The questionnaire with a 5-Likert scale was adapted from previous research. The sample consisted of 293 first-year engineering undergraduates in the southwest region of the United States. The online questionnaire was sent to participants who completed it voluntarily at the end of Fall 2019. A total of 274 of 293 participants completed the questionnaire with a response rate of 93.515%. Exploratory factor analysis was conducted to test the underlying factor structure of the questionnaire, which serves as a good reference …

Methods And Applications Of Synthetic Data Generation, Jason Anderson

All Dissertations

The advent of data mining and machine learning has highlighted the value of large and varied sources of data, while increasing the demand for synthetic data captures the structural and statistical characteristics of the original data without revealing personal or proprietary information contained in the original dataset.

In this dissertation, we use examples from original research to show that, using appropriate models and input parameters, synthetic data that mimics the characteristics of real data can be generated with sufficient rate and quality to address the volume, structural complexity, and statistical variation requirements of research and development of digital information processing …

Early Prediction Of Hate Speech Propagation, Ken-Yu Lin, Roy Ka-Wei Lee, Wei Gao, Wen-Chih Peng

Research Collection School Of Computing and Information Systems

Online hate speech has disrupted the social connectedness in online communities and raises public safety concerns in our societies. Motivated by this rising issue, researchers have developed many machine learning and deep learning methods to detect hate speech in social media automatically. However, most of the existing automated solutions have focused on detecting hate speech in a single post, neglecting the network and information propagation effects of social media platforms. Ideally, the content moderators would want to identify the hateful posts and monitor posts and threads that are likely to induce hate. This paper aims to address this research gap …

Fine-Grained Generalization Analysis Of Inductive Matrix Completion, Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft

Research Collection School Of Computing and Information Systems

In this paper, we bridge the gap between the state-of-the-art theoretical results for matrix completion with the nuclear norm and their equivalent in \textit{inductive matrix completion}: (1) In the distribution-free setting, we prove bounds improving the previously best scaling of \widetilde{O}(rd2) to \widetilde{O}(d3/2√r), where d is the dimension of the side information and rr is the rank. (2) We introduce the (smoothed) \textit{adjusted trace-norm minimization} strategy, an inductive analogue of the weighted trace norm, for which we show guarantees of the order \widetilde{O}(dr) under arbitrary sampling. In the inductive case, a similar rate was previously achieved only under uniform sampling …