Digital Commons Network^™

Retail Store Ranking Recommender System, Fatmah Ahmed Ali Alkhzami

Theses

Companies have been changing and developing their marketing tools and techniques in order to follow the rapid growth of e-commerce in many aspects, and they specifically try to target customers by offering them the products and services they need using recommender engines. Moreover, the rapid growth in e-commerce resulted in people placing the web as the source of information to buy or sell from. Therefore, other than normal stores, many online shops exist, in different forms, from websites with private domain to thread in online forums. This has advantages which is that people have more options to shop from, but …

Using Classification For Analysis Of Multi-Modal Video Summarization, Brendan Wells

Theses

Video Summarization refers to taking the important contents of a video and condensing it down to an easily consumable piece of data without having to watch the entire video. Currently, Millions of Videos are being recorded and shared every day. These videos range from the consumer level, such as a birthday party or wedding video, all the way up to industry such as film and television. We have constructed a model that seeks to address the problem of not being able to consume all the media that is being presented to you because of time constraints. To do this, we …

Accessibility In User Reviews For Mobile Apps: An Automated Detection Approach, Murtaza Tamjeed

Theses

In recent years, mobile accessibility has become an important trend with the goal of allowing all users the possibility of using any app without many restrictions. Recent work demonstrated that user reviews include insights that are useful for app evolution. However, with the increase in the amount of received reviews, manually analyzing them is tedious and time-consuming, especially when searching for accessibility reviews. The goal of this thesis is to support the automated identification of accessibility in user reviews, to help practitioners in prioritizing their handling, and thus, creating more inclusive apps. Particularly, we design a model that takes as …

Application Of Thermal And Ultraviolet Sensors In Remote Sensing Of Upland Ducks, Matthew W. Helvey

Theses

Detection, mapping, and monitoring of wildlife populations can provide significant insight into the health and trajectory of the ecosystems they rely on. In fact, it was not until recently that the benefits of wetland ecosystems were fully understood. Unfortunately, by that point, the United States had removed more than 50% of its native wetlands. The Prairie Pothole Region in North America is the premier breeding location for ducks; responsible for producing more than 50% of the North American ducks annually. The current survey methods for obtaining duck population counts are accomplished primarily using manned flights with observers manually identifying and …

Neural Network Architectures And Ensembles For Packet Classification: Addressing Visibility, Security And Quality Of Service Challenges In Communication Networks, Bruce Hartpence

Theses

Increasingly researchers are turning to machine learning techniques such as artificial neural networks (ANN) to address communication network research challenges in the areas of enhanced security, quality of service, visibility and control. Central to each is the need to classify packets. Determining an effective architecture for the artificial neural network is more difficult because traditional techniques such as principal component analysis (PCA) show reduced effectiveness. Presented are the techniques for preprocessing datasets and selecting input traffic features for the multi-layer perceptron (MLP) architecture. This methodology achieves classification accuracy above 99%.

An investigation into neural network architectures revealed the optimal structure …

Self-Supervised Learning For Segmentation Using Image Reconstruction, Srivallabha Karnam

Theses

Deep learning is the engine that is piloting tremendous growth in various segments of the industry by consuming valuable fuel called data. We are witnessing many businesses adopting this technology be it healthcare, transportation, defense, semiconductor, or retail. But most of the accomplishments that we see now rely on supervised learning. Supervised learning needs a substantial volume of labeled data which are usually annotated by humans- an arduous and expensive task often leading to datasets that are insufficient in size or human labeling errors. The performance of deep learning models is only as good as the data. Self-supervised learning minimizes …