Matching Items (512)
Filtering by
- Creators: Computer Science and Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
Description
While not officially recognized as an addictive activity by the Diagnostic and Statistical Manual of Mental Disorders, video game addiction has well-documented resources pointing to its effects on physiological and mental health for both addict and those close to the addict. With the rise of eSports, treating video game addiction has become trickier as a passionate and growing fan base begins to act as a culture not unlike traditional sporting. These concerns call for a better understanding of what constitutes a harmful addiction to video games as its heavy practice becomes more financially viable and accepted into mainstream culture.
ContributorsGohil, Abhishek Bhagirathsinh (Author) / Kashiwagi, Dean (Thesis director) / Kashiwagi, Jacob (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Investment real estate is unique among similar financial instruments by nature of each property's internal complexities and interaction with the external economy. Where a majority of tradable assets are static goods within a dynamic market, real estate investments are dynamic goods within a dynamic market. Furthermore, investment real estate, particularly commercial properties, not only interacts with the surrounding economy, it reflects it. Alive with tenancy, each and every commercial investment property provides a microeconomic view of businesses that make up the local economy. Management of commercial investment real estate captures this economic snapshot in a unique abundance of untapped statistical data. While analysis of such data is undeniably valuable, the efforts involved with this process are time consuming. Given this unutilized potential our team has develop proprietary software to analyze this data and communicate the results automatically though and easy to use interface. We have worked with a local real estate property management and ownership firm, Reliance Management, to develop this system through the use of their current, historical, and future data. Our team has also built a relationship with the executives of Reliance Management to review functionality and pertinence of the system we have dubbed, Reliance Dashboard.
ContributorsBurton, Daryl (Co-author) / Workman, Jack (Co-author) / LePine, Marcie (Thesis director) / Atkinson, Robert (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Management (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
MeetPoint is a project derived from Computer Science with a focus upon applications to mobile. The application is created to provide users with the ability to meet up with certain individuals to accomplish a specific task, in this case studying. The project idea came from the creator wanting to meet up with a friend in order to converse about an upcoming exam. The creator knew where the person lived, but could not easily come up with a location for the two to meet that would be a reasonable distance from both of them. Hence came the idea for a mobile application to complete those actions for the user. The project focuses upon implementation in a school setting in which the meetings would actually take place. For means of this project, the locations were fixed to on campus at Arizona State University. The committee felt that this would scope the project correctly for its two-semester creation while still demonstrating how to fulfill the task at hand. Android is the operating system of choice for the mobile application due to it being Java, which was the most familiar language to the student. MeetPoint provides users with an easy to navigate and familiar front-end while harnessing the power of a database in the back-end. The application hides the intricacies of the back-end from the user in order to better provide a comfortable user experience. A lot of the project was designed around providing a comfortable user experience by keeping the application familiar to the user in that it maintains similarities with other popular mobile applications.
ContributorsWallace, Tyler L (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
CourseKarma is a web application that engages students in their own learning through peer-driven social networking. The influence of technology on students is advancing faster than the school system, and a major gap still lingers between traditional learning techniques and the fast-paced, online culture of today's generation. CourseKarma enriches the educational experience of today's student by creating a space for collaborative inquiry as well as illuminating the opportunities of self and group learning through online collaboration. The features of CourseKarma foster this student-driven environment. The main focus is on a news-feed and Question and Answer component that provides a space for students to share instant updates as well ask and answer questions of the community. The community can be as broad as the entire ASU student body, as specific as students in BIO155, or even more targeted via specific subjects and or skills. CourseKarma also provides reputation points, which are the sum of all of their votes received, identifying the individual's level and or ranking in each subject or class. This not only gamifies the usual day-to-day learning environment, but it also provides an in-depth analysis of the individual's skills, accomplishments, and knowledge. The community is also able to input and utilize course and professor descriptions/feedback. This will be in a review format providing the students an opportunity to share and give feedback on their experience as well as providing incoming students the opportunity to be prepared for their future classes. All of the student's contributions and collaborative activity within CourseKarma is displayed on their personal profile creating a timeline of their academic achievements. The application was created using modern web programming technologies such as AngualrJS, Javascript, jQuery, Bootstrap, HTML5, CSS3 for the styling and front-end development, Mustache.js for client side templating, and Firebase AngularFire as the back-end and NoSQL database. Other technologies such as Pivitol Tracker was used for project management and user story generation, as well as, Github for version control management and repository creation. Object-oreinted programming concepts were heavily present in the creation of the various data structures, as well as, a voting algorithm was used to manage voting of specific posts. Down the road, CourseKarma could even be a necessary add-on within LinkedIn or Facebook that provides a quick yet extremely in-depth look at an individuals' education, skills, and potential to learn \u2014 based all on their actual contribution to their academic community rather than just a text they wrote up.
ContributorsCho, Sungjae (Author) / Mayron, Liam (Thesis director) / Lobock, Alan (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Arts, Media and Engineering (Contributor)
Created2015-05
Description
The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques to align natural language sentences to the linearized parses of their associated knowledge representations in order to learn the meanings of individual words. The work includes proposing and analyzing an approach that can be used to learn some of the initial lexicon.
ContributorsBaldwin, Amy Lynn (Author) / Baral, Chitta (Thesis director) / Vo, Nguyen (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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
Description
Keyboard input biometric authentication systems are software systems which record keystroke information and use it to identify a typist. The primary statistics used to determine the accuracy of a keyboard biometric authentication system are the false acceptance rate (FAR) and false rejection rate (FRR), which are aimed to be as low as possible [1]. However, even if a system has a low FAR and FRR, there is nothing stopping an attacker from also monitoring an individual's typing habits in the same way a legitimate authentication system would, and using its knowledge of their habits to recreate virtual keyboard events for typing arbitrary text, with precise timing mimicking those habits, which would theoretically spoof a legitimate keyboard biometric authentication system into thinking it is the intended user doing the typing. A proof of concept of this very attack, called keyboard input biometric authentication spoofing, is the focus of this paper, with the purpose being to show that even if a biometric authentication system is reasonably accurate, with a low FAR and FRR, it can still potentially be very vulnerable to a well-crafted spoofing system. A rudimentary keyboard input biometric authentication system was written in C and C++ which drew influence from already existing methods and attempted new methods of authentication as well. A spoofing system was then built which exploited the authentication system's statistical representation of a user's typing habits to recreate keyboard events as described above. This proof of concept is aimed at raising doubts about the idea of relying too heavily upon keyboard input based biometric authentication systems since the user's typing input can demonstrably be spoofed in this way if an attacker has full access to the system, even if the system itself is accurate. The results are that the authentication system built for this study, when ran on a database of typing event logs recorded from 15 users in 4 sessions, had a 0% FAR and FRR (more detailed analysis of FAR and FRR is also presented), yet it was still very susceptible to being spoofed, with a 44% to 71% spoofing rate in some instances.
ContributorsJohnson, Peter Thomas (Author) / Nelson, Brian (Thesis director) / Amresh, Ashish (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This paper explores how US Cold War nuclear testing in the Pacific Islands has been approached in three different regions \u2014affected Pacific Islands, the US, and Japan. Because the US has failed to adequately address its nuclear past in the Pacific Islands, and Pacific Islander narratives struggle to reach the international community on their own, my study considers the possibility of Pacific Islanders finding greater outlet for their perspectives within dominant Japanese narratives, which also feature nuclear memory. Whereas the US government has remained largely evasive and aloof about the consequences of its nuclear testing in the Pacific, Japan encourages active, anti-nuclear war memory that could be congruent with Pacific Islander interests. After examining historical events, surrounding context, and prevailing sentiments surrounding this issue in each region however, my study finds that even within Japanese narratives, Pacific Islander narratives can only go so far because of Japan's own nuclear power industry, its hierarchical relationship with the Pacific Islands, and Japan's strong ties to the US in what can be interpreted as enduring Cold War politics.
ContributorsHinze, Rie Victoria (Author) / Benkert, Volker (Thesis director) / Moore, Aaron (Committee member) / School of International Letters and Cultures (Contributor) / Computer Science and Engineering Program (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Company X has developed RealSenseTM technology, a depth sensing camera that provides machines the ability to capture three-dimensional spaces along with motion within these spaces. The goal of RealSense was to give machines human-like senses, such as knowing how far away objects are and perceiving the surrounding environment. The key issue for Company X is how to commercialize RealSense's depth recognition capabilities. This thesis addresses the problem by examining which markets to address and how to monetize this technology. The first part of the analysis identified potential markets for RealSense. This was achieved by evaluating current markets that could benefit from the camera's gesture recognition, 3D scanning, and depth sensing abilities. After identifying seven industries where RealSense could add value, a model of the available, addressable, and obtainable market sizes was developed for each segment. Key competitors and market dynamics were used to estimate the portion of the market that Company X could capture. These models provided a forecast of the discounted gross profits that could be earned over the next five years. These forecasted gross profits, combined with an examination of the competitive landscape and synergistic opportunities, resulted in the selection of the three segments thought to be most profitable to Company X. These segments are smart home, consumer drones, and automotive. The final part of the analysis investigated entrance strategies. Company X's competitive advantages in each space were found by examining the competition, both for the RealSense camera in general and other technologies specific to each industry. Finally, ideas about ways to monetize RealSense were developed by exploring various revenue models and channels.
ContributorsDunn, Nicole (Co-author) / Boudreau, Thomas (Co-author) / Kinzy, Chris (Co-author) / Radigan, Thomas (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / WPC Graduate Programs (Contributor) / Department of Psychology (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Department of Economics (Contributor) / School of Mathematical and Statistical Science (Contributor) / W. P. Carey School of Business (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05