Physical Sciences and Mathematics Commons^™

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Enabling The Human Perception Of A Working Camera In Web Conferences Via Its Movement, Anish Shrestha

LSU Master's Theses

In recent years, video conferencing has seen a significant increase in its usage due to the COVID-19 pandemic. When casting user’s video to other participants, the videoconference applications (e.g. Zoom, FaceTime, Skype, etc.) mainly leverage 1) webcam’s LED-light indicator, 2) user’s video feedback in the software and 3) the software’s video on/off icons to remind the user whether the camera is being used. However, these methods all impose the responsibility on the user itself to check the camera status, and there have been numerous cases reported when users expose their privacy inadvertently due to not realizing that their camera is …

Computational Imaging For Shape Understanding, Yuqi Ding

LSU Doctoral Dissertations

Geometry is the essential property of real-world scenes. Understanding the shape of the object is critical to many computer vision applications. In this dissertation, we explore using computational imaging approaches to recover the geometry of real-world scenes. Computational imaging is an emerging technique that uses the co-designs of image hardware and computational software to expand the capacity of traditional cameras. To tackle face recognition in the uncontrolled environment, we study 2D color image and 3D shape to deal with body movement and self-occlusion. Especially, we use multiple RGB-D cameras to fuse the varying pose and register the front face in …

2-Dimensional String Problems: Data Structures And Quantum Algorithms, Dhrumilkumar Patel

LSU Master's Theses

The field of stringology studies algorithms and data structures used for processing strings efficiently. The goal of this thesis is to investigate 2-dimensional (2D) variants of some fundamental string problems, including \textit{Exact Pattern Matching} and \textit{Longest Common Substring}.

In the 2D pattern matching problem, we are given a matrix $\M[1\dd n,1\dd n]$ that consists of $N = n \times n$ symbols drawn from an alphabet $\Sigma$ of size $\sigma$. The query consists of a $ m \times m$ square matrix $\PP[1\dd m, 1\dd m]$ drawn from the same alphabet, and the task is to find all the locations of $\PP$ …

Scheduling Many-Task Computing Applications For A Hybrid Cloud, Shifat Perveen Mithila

LSU Doctoral Dissertations

A centralized scheduler can become a bottleneck for placing the tasks of a many-task application on heterogeneous cloud resources. Previously, it was demonstrated that a decentralized vector scheduling approach based on performance measurements can be used successfully for this task placement scenario. In this dissertation, we extend this approach to task placement based on latency measurements. Each node collects performance metrics from its neighbors on an overlay graph, measures the communication latency, and then makes local decisions on where to move tasks. We present a decentralized and a centralized algorithm for configuring the overlay graph based on latency measurements and …

Control And Planning For Mobile Manipulators Used In Large Scale Manufacturing Processes, Joshua T. Nguyen

LSU Master's Theses

Sanding operations in industry is one of the few manufacturing tasks that has yet to achieve automation. Sanding tasks require skilled operators that have developed a sense of when a work piece is sufficiently sanded. In order to achieve automation in sanding with robotic systems, this developed sense, or intelligence, that human operators have needs to be understood and implemented in order to achieve, at the minimum, the same quality of work. The system will also need to have the equivalent reach of a human operator and not be constrained to a single, small workspace. This thesis developed solutions for …

Neutron Interferometry Using A Single Modulated Phase Grating, Ivan J. Hidrovo Giler

LSU Master's Theses

Neutron grating interferometry provides information on phase and small-angle scatter in addition to attenuation. Previously, phase grating moiré interferometers (PGMI) with two or three phase gratings have been developed. These phase-grating systems use the moiré far-field technique to avoid the need for high-aspect absorption gratings used in Talbot-Lau interferometers (TLI) which reduce the neutron flux reaching the detector. We demonstrate through simulations a novel phase grating interferometer system for cold neutrons that requires a single modulated phase grating (MPG) for phase-contrast imaging, as opposed to the two or three phase gratings in previously employed PGMI systems. We compare the MPG …

Optimizing The Performance Of Parallel And Concurrent Applications Based On Asynchronous Many-Task Runtimes, Weile Wei

LSU Doctoral Dissertations

Nowadays, High-performance Computing (HPC) scientific applications often face per- formance challenges when running on heterogeneous supercomputers, so do scalability, portability, and efficiency issues. For years, supercomputer architectures have been rapidly changing and becoming more complex, and this challenge will become even more com- plicated as we enter the exascale era, where computers will exceed one quintillion cal- culations per second. Software adaption and optimization are needed to address these challenges. Asynchronous many-task (AMT) systems show promise against the exascale challenge as they combine advantages of multi-core architectures with light-weight threads, asynchronous executions, smart scheduling, and portability across diverse architectures.

In …

From Equal-Mass To Extreme-Mass-Ratio Binary Inspirals: Simulation Tools For Next Generation Gravitational Wave Detectors, Samuel Douglas Cupp

LSU Doctoral Dissertations

Current numerical codes can successfully evolve similar-mass binary black holes systems, and these numerical waveforms contributed to the success of the LIGO Collaboration's detection of gravitational waves. LIGO requires high resolution numerical waveforms for detection and parameter estimation of the source. Great effort was expended over several decades to produce the numerical methods used today. However, future detectors will require further improvements to numerical techniques to take full advantage of their detection capabilities. For example, the Laser Interferometer Space Antenna (LISA) will require higher resolution simulations of similar-mass-ratio systems than LIGO. LISA will also be able to detect extreme-mass-ratio inspiral …

Improving Kernel Artifact Extraction In Linux Memory Samples Using The Slub Allocator, Daniel A. Donze

LSU Master's Theses

Memory forensics allows an investigator to analyze the volatile memory (RAM) of a computer, providing a view into the system state of the machine as it was running. Examples of items found in memory samples that are of interest to investigators are kernel data structures which can represent processes, files, and sockets. The SLUB allocator is the default small-request memory allocator for modern Linux systems. SLUB allocates “slabs”, which are contiguous sections of pre-allocated memory that are used to efficiently service allocation requests. The predecessor to SLUB, the SLAB allocator, tracked every slab it allocated, allowing extraction of allocated slabs …

Malware And Memory Forensics On M1 Macs, Charles E. Glass

LSU Master's Theses

As malware continues to evolve, infection mechanisms that can only be seen in memory are increasingly commonplace. These techniques evade traditional forensic analysis, requiring the use of memory forensics. Memory forensics allows for the recovery of historical data created by running malware, including information that it tries to hide. Memory analysis capabilities have lagged behind on Apple's new M1 architecture while the number of malicious programs only grows. To make matters worse, Apple has developed Rosetta 2, the translation layer for running x86_64 binaries on an M1 Mac. As a result, all malware compiled for Intel Macs is theoretically functional …

Improving Memory Forensics Capabilities On Apple M1 Computers, Raphaela Santos Mettig Rocha

LSU Master's Theses

Malware threats are rapidly evolving to use more sophisticated attacks. By abusing rich application APIs such as Objective-C’s, they are able to gather information about user activity, launch background processes without the user’s knowledge as well as perform other malicious activities. In some cases, memory forensics is the only way to recover artifacts related to this malicious activity, as is the case with memory-only execution. The introduction of the Rosetta 2 on the Apple M1 introduces a completely new attack surface by allowing binaries of both Intel x86 64 and ARM64 architecture to run in userland. For this reason it …

Rethinking The Design Of Online Professor Reputation Systems, Haley Tatum

LSU Master's Theses

Online Professor Reputation (OPR) systems, such as RateMyProfessors.com (RMP), are frequently used by college students to post and access peer evaluations of their pro- fessors. However, recent evidence has shown that these platforms suffer from major bias problems. Failing to address bias in online professor ratings not only leads to negative expectations and experiences in class, but also poor performance on exams. To address these concerns, in this thesis, we study bias in OPR systems from a software design point of view. At the first phase of our analysis, we conduct a systematic literature review of 23 interdisciplinary studies on …

Practical Considerations And Applications For Autonomous Robot Swarms, Rory Alan Hector

LSU Doctoral Dissertations

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical …

Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines

Honors Theses

No abstract provided.

Performance Analysis And Improvement For Scalable And Distributed Applications Based On Asynchronous Many-Task Systems, Nanmiao Wu

LSU Doctoral Dissertations

As the complexity of recent and future large-scale data and exascale systems architectures grows, so do productivity, portability, software scalability, and efficient utilization of system resources challenges presented to both industry and the research community. Software solutions and applications are expected to scale in performance on such complex systems. Asynchronous many-task (AMT) systems, taking advantage of multi-core architectures with light-weight threads, asynchronous executions, and smart scheduling, are showing promise in addressing these challenges.

In this research, we implement several scalable and distributed applications based on HPX, an exemplar AMT runtime system. First, a distributed HPX implementation for a parameterized benchmark …

Digital Discrimination In The Sharing Economy: Evidence, Policy, And Feature Analysis, Miroslav Tushev

LSU Doctoral Dissertations

Applications (apps) of the Digital Sharing Economy (DSE), such as Uber, Airbnb, and TaskRabbit, have become a main facilitator of economic growth and shared prosperity in modern-day societies. However, recent research has revealed that the participation of minority groups in DSE activities is often hindered by different forms of bias and discrimination. Evidence of such behavior has been documented across almost all domains of DSE, including ridesharing, lodging, and freelancing. However, little is known about the under- lying design decisions of DSE systems which allow certain demographics of the market to gain unfair advantage over others. To bridge this knowledge …

90snet:, Seth Richard

Honors Theses

No abstract provided.

Using Memory Forensics To Analyze Programming Language Runtimes, Modhuparna Manna

LSU Doctoral Dissertations

The continued increase in the use of computer systems in recent times has led to a significant rise in the capabilities of malware and attacker toolkits that target different operating systems and their users. Over the last several years, cybersecurity threat reports have documented numerous instances of users that were targeted by governments, intelligence agencies, and criminal groups, and the result was that the victims ended up having highly sophisticated malware installed on their systems. Unfortunately, the rise of these threats has not been met with equal research and development of defensive mechanisms that can detect and analyze such malware. …

Application Of Gravity Data For Hydrocarbon Exploration Using Machine Learning Assisted Workflow, Oluwafemi Temidayo Alaofin

LSU Master's Theses

Gravity survey has played an essential role in many geoscience fields ever since it was conducted, especially as an early screening tool for subsurface hydrocarbon exploration. With continued improvement in data processing techniques and gravity survey accuracy, in-depth gravity anomaly studies, such as characterization of Bouguer and isostatic residual anomalies, have the potential to delineate prolific regional structures and hydrocarbon basins. In this study, we focus on developing a cost-effective, quick, and computationally efficient screening tool for hydrocarbon exploration using gravity data employing machine learning techniques. Since land-based gravity surveys are often expensive and difficult to obtain in remote places, …