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Full-Text Articles in Engineering

Efficient Machine Learning: Models And Accelerations, Zhe Li Dec 2018

Efficient Machine Learning: Models And Accelerations, Zhe Li

Dissertations - ALL

One of the key enablers of the recent unprecedented success of machine learning is the adoption of very large models. Modern machine learning models typically consist of multiple cascaded layers such as deep neural networks, and at least millions to hundreds of millions of parameters (i.e., weights) for the entire model. The larger-scale model tend to enable the extraction of more complex high-level features, and therefore, lead to a significant improvement of the overall accuracy. On the other side, the layered deep structure and large model sizes also demand to increase computational capability and memory requirements. In order to achieve …


Amplifying The Prediction Of Team Performance Through Swarm Intelligence And Machine Learning, Erick Michael Harris Dec 2018

Amplifying The Prediction Of Team Performance Through Swarm Intelligence And Machine Learning, Erick Michael Harris

Master's Theses

Modern companies are increasingly relying on groups of individuals to reach organizational goals and objectives, however many organizations struggle to cultivate optimal teams that can maximize performance. Fortunately, existing research has established that group personality composition (GPC), across five dimensions of personality, is a promising indicator of team effectiveness. Additionally, recent advances in technology have enabled groups of humans to form real-time, closed-loop systems that are modeled after natural swarms, like flocks of birds and colonies of bees. These Artificial Swarm Intelligences (ASI) have been shown to amplify performance in a wide range of tasks, from forecasting financial markets to …


Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li Nov 2018

Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li

Doctoral Dissertations

In the past decades, the computing capability has shown an exponential growth trend, which is observed as Moore’s law. However, this growth speed is slowing down in recent years mostly because the down-scaled size of transistors is approaching their physical limit. On the other hand, recent advances in software, especially in big data analysis and artificial intelligence, call for a break-through in computing hardware. The memristor, or the resistive switching device, is believed to be a potential building block of the future generation of integrated circuits. The underlying mechanism of this device is different from that of complementary metal-oxide-semiconductor (CMOS) …


Leveraging Eye Structure And Motion To Build A Low-Power Wearable Gaze Tracking System, Addison Mayberry Oct 2018

Leveraging Eye Structure And Motion To Build A Low-Power Wearable Gaze Tracking System, Addison Mayberry

Doctoral Dissertations

Clinical studies have shown that features of a person's eyes can function as an effective proxy for cognitive state and neurological function. Technological advances in recent decades have allowed us to deepen this understanding and discover that the actions of the eyes are in fact very tightly coupled to the operation of the brain. Researchers have used camera-based eye monitoring technology to exploit this connection and analyze mental state across across many different metrics of interest. These range from simple things like attention and scene processing, to impairments such as a fatigue or substance use, and even significant mental disorders …


Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan Jul 2018

Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan

Mechanical & Aerospace Engineering Theses & Dissertations

Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system …


Neural Network On Virtualization System, As A Way To Manage Failure Events Occurrence On Cloud Computing, Khoi Minh Pham Jun 2018

Neural Network On Virtualization System, As A Way To Manage Failure Events Occurrence On Cloud Computing, Khoi Minh Pham

Electronic Theses, Projects, and Dissertations

Cloud computing is one important direction of current advanced technology trends, which is dominating the industry in many aspects. These days Cloud computing has become an intense battlefield of many big technology companies, whoever can win this war can have a very high potential to rule the next generation of technologies. From a technical point of view, Cloud computing is classified into three different categories, each can provide different crucial services to users: Infrastructure (Hardware) as a Service (IaaS), Software as a Service (SaaS), and Platform as a Service (PaaS). Normally, the standard measurements for cloud computing reliability level is …


An Investigation Of The Cortical Learning Algorithm, Anthony C. Samaritano May 2018

An Investigation Of The Cortical Learning Algorithm, Anthony C. Samaritano

Theses and Dissertations

Pattern recognition and machine learning fields have revolutionized countless industries and applications from biometric security to modern industrial assembly lines. The fields continue to accelerate as faster, more efficient processing hardware becomes commercially available. Despite the accelerated growth of the pattern recognition and machine learning fields, computers still are unable to learn, reason, and perform rudimentary tasks that humans and animals find routine. Animals are able to move fluidly, understand their environment, and maximize their chances of survival through adaptation - animals demonstrate intelligence. A primary argument in this thesis that we have not yet achieved a level of intelligence …


Comparison Of Google Image Search And Resnet Image Classification Using Image Similarity Metrics, David Smith May 2018

Comparison Of Google Image Search And Resnet Image Classification Using Image Similarity Metrics, David Smith

Computer Science and Computer Engineering Undergraduate Honors Theses

In this paper, we compare the results of ResNet image classification with the results of Google Image search. We created a collection of 1,000 images by performing ten Google Image searches with a variety of search terms. We classified each of these images using ResNet and inspected the results. The ResNet classifier predicted the category that matched the search term of the image 77.5% of the time. In our best case, with the search term “forklift”, the classifier categorized 92 of the 100 images as forklifts. In the worst case, for the category “hammer”, the classifier matched the search term …


Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan Jan 2018

Developing A Recurrent Neural Network With High Accuracy For Binary Sentiment Analysis, Kevin Cunanan

CMC Senior Theses

Sentiment analysis has taken on various machine learning approaches in order to optimize accuracy, precision, and recall. However, Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) account for the context of a sentence by using previous predictions as additional input for future sentence predictions. Our approach focused on developing an LSTM RNN that could perform binary sentiment analysis for positively and negatively labeled sentences. In collaboration with Mariam Salloum, I developed a collection of programs to classify individual sentences as either positive or negative. This paper additionally looks into machine learning, neural networks, data preprocessing, implementation, and resulting comparisons.