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- Creators: Computer Science and Engineering Program
Description
Cyber threats are growing in number and sophistication making it important to continually study and improve all dimensions of digital forensics. Teamwork in forensic analysis has been overlooked in systems even though forensics relies on collaboration. Forensic analysis lacks a system that is flexible and available on different electronic devices which are being used and incorporated into everyday life. For instance, cellphones or tablets that are easy to bring on-the-go to sites where the first steps of forensic analysis is done. Due to the present day conversion to online accessibility, most electronic devices connect to the internet. Squeegee is a proof of concept that forensic analysis can be done on the web. The forensic analysis expansion to the web opens many doors to collaboration and accessibility.
ContributorsJuntiff, Samantha Maria (Author) / Ahn, Gail-Joon (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Getting to the Core of Services: Considering the Arizona State University Library as a Core Facility
Description
As academic libraries focus on delivering new services in such areas as research data, digital preservation, and data curation, they have begun to explore alternative funding models and approaches to research. The Arizona State University (ASU) Library in Tempe works with the university's Office of Knowledge Enterprise Development to collaborate and support ASU's researchers at scale. The library's ongoing collaboration and its specialized services, consultations, and training have led it to consider becoming a core facility, a centralized service that would provide consultation and other help to the university's researchers. As a core facility, the library would gain the ability to fund new initiatives and functions that would expand its reach and improve its support for research.
ContributorsOgborn, Matt (Author) / Harp, Matthew (Author) / Kurtz, Debra Hanken (Author)
Created2019-10
Description
This thesis dives into the world of artificial intelligence by exploring the functionality of a single layer artificial neural network through a simple housing price classification example while simultaneously considering its impact from a data management perspective on both the software and hardware level. To begin this study, the universally accepted model of an artificial neuron is broken down into its key components and then analyzed for functionality by relating back to its biological counterpart. The role of a neuron is then described in the context of a neural network, with equal emphasis placed on how it individually undergoes training and then for an entire network. Using the technique of supervised learning, the neural network is trained with three main factors for housing price classification, including its total number of rooms, bathrooms, and square footage. Once trained with most of the generated data set, it is tested for accuracy by introducing the remainder of the data-set and observing how closely its computed output for each set of inputs compares to the target value. From a programming perspective, the artificial neuron is implemented in C so that it would be more closely tied to the operating system and therefore make the collected profiler data more precise during the program's execution. The program is designed to break down each stage of the neuron's training process into distinct functions. In addition to utilizing more functional code, the struct data type is used as the underlying data structure for this project to not only represent the neuron but for implementing the neuron's training and test data. Once fully trained, the neuron's test results are then graphed to visually depict how well the neuron learned from its sample training set. Finally, the profiler data is analyzed to describe how the program operated from a data management perspective on the software and hardware level.
ContributorsRichards, Nicholas Giovanni (Author) / Miller, Phillip (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05