Neural machine translation (NMT) is often heralded as the most effective approach to machine translation due to its success on language pairs with large parallel corpora. However, neural methods produce less than ideal ...
Rasterization and ray tracing are two common techniques used in computer graphics rendering which displays complex 3D scenes containing billions of objects on our computer. Compared to rasterization, ray tracing can generate ...
Many varying analyses and transformations in the field of program optimization rely on an ability to answer counting questions; specifically, how many elements satisfy a set of conditions. Thus, it is indispensable to be ...
In this thesis, we conduct a literature review on the application of two natural language processing techniques, topic modeling and named-entity recognition (character identification), on collections of literary fiction. ...
In this paper, we discuss Shi and Malik's groundbreaking Normalized Cuts approach to image segmentation, and review a number of modified Normalized Cut methods, including Mixed Normalized Cut, Semi-Supervised Normalized ...
Introductory computer science students have trouble building consistent mental models of computer execution. To alleviate this problem, previous work suggests explicitly introducing a consistent and accurate abstraction ...
In recent history, access to biological and genomic data (provided by DNA sequencing) has exponentially increased as more efficient technologies have been developed. Newer, more accurate algorithms for analyzing this data ...
Problems beginners face with understanding Object-Oriented Programming (OOP) concepts have been investigated and reported in a number of studies. In this paper, we present the results of comparing and contrasting the methods ...
Population genetics can be defined as the study of distributions and changes in the genetic data of populations through time. This field relies heavily on simulated data for validation. Simulating a population involves ...
With recent advances in the past decade in the web, websites have grown past being simple pages of content and have evolved to become more interactive with their audiences. The increase in complexity has contributed to ...
Modern software systems are powered by decentralized computing systems. While these distributed systems are generally able to handle a higher throughput with larger clusters of computing nodes running in parallel, they ...
Pure-functional programming is a paradigm of programming closely related to mathematical constructs that can offer great power and expressiveness in terms of how to write and reason about programs. Additional benefits ...
We review new advances in word embeddings and apply them to cross-lingual literary analysis of Latin and English translations of Latin. We introduce word embeddings, summarize the developments to them that allow them to ...
This thesis explores n-grams-based gender classification analyses using various n-grams
types, sizes, and feature sets. This study expanded on previous research by including
a non-binary gender category. First, a ...
Recurrent Neural Networks (RNNs) are successful at modeling languages because of their ability to recognize patterns over an undefined input length using their internal memory. However, the data kept in their memory decays ...
Population genetics is a study of genetic variations in populations and evolutionary forces that explain these variations. Relevant studies are usually based on simulated genomic data in matrix form. Many existing methods, ...
Navigating unfamiliar environments independently is a challenging task for people with visual impairments (PVIs). Navigation Assistive Technologies (NATs) enhance spatial cognition and independent navigation for PVIs through ...
This thesis is about analyzing the different approaches to verb prediction in machine translation, mainly between languages with different grammar structures. We will introduce the importance of verb prediction in translation ...
Machine translation is widely used by people. However, all machine translation models can sometimes make mistakes. I review some previous studies on possible errors in machine translation. Then I elaborate on the problem ...
Convolutional Neural Networks (CNNs) is one of the most efficient approaches to analyze population genetics data and draw conclusions on the species' evolution. Population genetics is one approach people take to learn about ...