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2024

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Articles 61 - 67 of 67

Full-Text Articles in Programming Languages and Compilers

Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala Jan 2024

Bert-Based Detection Of Ai-Generated Text For Content Verification, Soham Biren Katlariwala

2024 REYES Proceedings

With advancements in AI-driven natural language generation, distinguishing between AI-generated and human-written text has become imperative for ensuring content authenticity across industries. This study explores the effectiveness of Bidirectional Encoder Representations from Transformers (BERT) in addressing this classification challenge. Utilizing a diverse dataset and robust preprocessing techniques, BERT achieved a peak F1-score of 0.94364, outperforming traditional models such as Logistic Regression and Support Vector Machines. The results underscore the potential of transformer-based models in addressing real-world con- tent verification problems. Future enhancements include fine-tuning and expanding datasets for greater generalizability.


Statically Controlled Synchronized Lane Architectures, Scott K. Pomerville Jan 2024

Statically Controlled Synchronized Lane Architectures, Scott K. Pomerville

Dissertations, Master's Theses and Master's Reports

Modern superscalar processors dominate the field of computing. While dynamic execution allows for versatility in code, these processors are complex. Statically scheduled code has historically enabled simpler processor designs, but static scheduling cannot account for variables that are unknown at compile time. Furthermore, static scheduling has many inefficiencies, such as the need to insert a large number of nops for code in traditional Very Long Instruction Word (VLIW) processors. In this dissertation, we explore a novel architectural approach for statically scheduled code by breaking the code into several synchronous instruction streams. By representing code in a fundamentally new way, we …


The Computational Search For Unidentified Central Configurations Of The Newtonian N-Body Problem, Hannah G. Havel Jan 2024

The Computational Search For Unidentified Central Configurations Of The Newtonian N-Body Problem, Hannah G. Havel

CURE Proceedings

The N-body problem is a field of study in mathematics and physics that involves predicting the motion of particles moving under their mutual gravitational attraction. It is vital in celestial mechanics, such as planning collision-free satellite orbit trajectories. When beginning to understand the N-body problem, we can start by looking at equal masses of these particles or celestial bodies. As particles move, their position and velocity change, both energy and angular momentum are conserved. Sets of constant energy and angular momentum, known as integral manifolds, are higher-dimensional figures that represent constraints of movement to a system. Integral manifolds are described …


Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers Jan 2024

Adaptive Neh With Constrained Nearest Neighbor Subtours For The Electric Vehicle Routing Problem With Time Windows, Andrew Struthers

All Master's Theses

The development of electric vehicles is currently considered one of the most innovative areas in manufacturing. Largely driven by the desire to reduce greenhouse emissions, electric vehicles are seen as a viable alternative to internal combustion engine cars. Starting from consumer cars, a dedicated effort is being made to translate this into commercial vehicles for freight and delivery. This research introduces a novel adaptive Nawaz, Enscore, Ham (NEH) algorithm with constrained nearest neighbor subtour (NEH-NN). This algorithm is tested on the standard benchmark problems in literature and used as a seed solution for the Genetic Algorithm (GA). The performance and …


Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman Jan 2024

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

College of Graduate Studies: Theses & Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …


The Amethyst Compiler, David Britton Jan 2024

The Amethyst Compiler, David Britton

Williams Honors College, Honors Research Projects

Amethyst is a custom programming language, whose compiler translates Amethyst source code into textual LLVM IR, which can, in turn, be compiled by LLVM back-ends to produce executable binaries. This paper explores compiler concepts and implementation details for the Amethyst compiler, describes the LLVM architecture, and provides an overview of some Amethyst language features.


Ung: A Diagnostic Standard C Library, Jakob Knute Kaivo Jan 2024

Ung: A Diagnostic Standard C Library, Jakob Knute Kaivo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Undefined behavior in C programs is a major source of unreliable software. Many of the most common exploitable software vulnerabilities can be traced directly to undefined behavior. In the increasingly connected world, a successful attack can cost the victim millions of dollars to recover from. While static program analysis aids in identifying undefined behavior, testing indicates that even the best static analysis tools correctly identifies about 35% of these defects. This dissertation introduces UNG’s Not GNU (UNG), a standard C library designed to mitigate undefined behavior. Where others have seen opportunities for optimization, UNG makes every effort to identify undefined …