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- Creators: Barrett, The Honors College
- Creators: Doupe, Adam
Description
Stress for college students is nothing new and as more kids go to college the number of cases are on the rise. This issue is apparent at colleges across the nation including Arizona State University. StreetWise aims to help students prevent or appropriately deal with stress through interactive lessons teaching students life skills, social skills, and emotional intelligence.<br/>In order to prove the value of our service, StreetWise conducted a survey that asked students about their habits, thoughts on stress, and their future. Students from Arizona State University were surveyed with questions on respondent background, employment, number one stressor, preferred learning method, and topics that students were interested in learning. We found that students’ number one stressor was school but was interested in learning skills that would prepare them for their future after graduation. We used the results to make final decisions so that StreetWise could offer lessons that students would get the most value out of. This led to us conducting a second survey which included mock ups of the website, examples of interactive lesson plans, and an overview of the app. Students from the first survey were surveyed in addition to new respondents. This survey was intended for us to ensure that our service would maintain its value to students with the aesthetic and interface that we envisioned.
ContributorsCompton, Katherine May (Co-author) / Ahir, Hiral (Co-author) / Ward, William (Co-author) / Byrne, Jared (Thesis director) / Hall, Rick (Committee member) / Dean, W.P. Carey School of Business (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Stress for college students is nothing new and as more kids go to college the number of cases are on the rise. This issue is apparent at colleges across the nation including Arizona State University. StreetWise aims to help students prevent or appropriately deal with stress through interactive lessons teaching students life skills, social skills, and emotional intelligence.<br/>In order to prove the value of our service, StreetWise conducted a survey that asked students about their habits, thoughts on stress, and their future. Students from Arizona State University were surveyed with questions on respondent background, employment, number one stressor, preferred learning method, and topics that students were interested in learning. We found that students’ number one stressor was school but was interested in learning skills that would prepare them for their future after graduation. We used the results to make final decisions so that StreetWise could offer lessons that students would get the most value out of. This led to us conducting a second survey which included mock ups of the website, examples of interactive lesson plans, and an overview of the app. Students from the first survey were surveyed in addition to new respondents. This survey was intended for us to ensure that our service would maintain its value to students with the aesthetic and interface that we envisioned.
ContributorsAhir, Hiral V (Co-author) / Compton, Katherine (Co-author) / Ward, William (Co-author) / Byrne, Jared (Thesis director) / Hall, Rick (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Some of the most talented, innovative, and experimental artists are students, but they are often discouraged by the price of higher education and lack of scholarship or funding opportunities. Additionally, the art industry has become stagnant. Traditional brick-and-mortar galleries are not willing to represent young, unknown artists. Their overhead is simply too high for risky choices.
The Student Art Project is art patronage for the 21st century—a curated online gallery featuring exceptional student artists. The Student Art Project is a highly curated experience for buyers. Only five artists are featured each month. Buyers are not bombarded with thousands of different products and separate artists “shops”. They can read artists bios and find art they connect with.
Student artists apply through an online form. Once accepted to the program, artists receive a $200 materials stipend to create an exclusive collection of 5-10 pieces. Original artwork and limited edition prints are sold through our website. These collections can potentially fund an entire year of college tuition, a life-changing amount for many students.
Brick-and-mortar galleries typically take 40-60% of the retail price of artwork. The Student Art Project will only take 30%, which we will use to reinvest in future artists. Other art websites, like Etsy, require the artists to ship, invoice, and communicate with customers. For students, this means less time spent in the classroom and less time developing their craft. The Student Art Project handles all business functions for our artists, allowing them to concentrate on what really matters, their education.
The Student Art Project is art patronage for the 21st century—a curated online gallery featuring exceptional student artists. The Student Art Project is a highly curated experience for buyers. Only five artists are featured each month. Buyers are not bombarded with thousands of different products and separate artists “shops”. They can read artists bios and find art they connect with.
Student artists apply through an online form. Once accepted to the program, artists receive a $200 materials stipend to create an exclusive collection of 5-10 pieces. Original artwork and limited edition prints are sold through our website. These collections can potentially fund an entire year of college tuition, a life-changing amount for many students.
Brick-and-mortar galleries typically take 40-60% of the retail price of artwork. The Student Art Project will only take 30%, which we will use to reinvest in future artists. Other art websites, like Etsy, require the artists to ship, invoice, and communicate with customers. For students, this means less time spent in the classroom and less time developing their craft. The Student Art Project handles all business functions for our artists, allowing them to concentrate on what really matters, their education.
ContributorsDangler, Rebecca Leigh (Author) / Trujillo, Rhett (Thesis director) / Coleman, Sean (Committee member) / Barrett, The Honors College (Contributor) / Herberger Institute for Design and the Arts (Contributor) / Department of Management (Contributor)
Created2015-05
Description
A primary goal in computer science is to develop autonomous systems. Usually, we provide computers with tasks and rules for completing those tasks, but what if we could extend this type of system to physical technology as well? In the field of programmable matter, researchers are tasked with developing synthetic materials that can change their physical properties \u2014 such as color, density, and even shape \u2014 based on predefined rules or continuous, autonomous collection of input. In this research, we are most interested in particles that can perform computations, bond with other particles, and move. In this paper, we provide a theoretical particle model that can be used to simulate the performance of such physical particle systems, as well as an algorithm to perform expansion, wherein these particles can be used to enclose spaces or even objects.
ContributorsLaff, Miles (Author) / Richa, Andrea (Thesis director) / Bazzi, Rida (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
This thesis is a technical project management overview of development of software for a student startup venture named TableTop. There were many changes made throughout the process in order to address new conditions as to keep the vision of the project on the most direct and reasonable path. Development followed the agile product development model in order to adapt as the concept pivoted or as hurdles presented themselves. The goal at the end of the project was to have a well-defined business model based off of the lean startup business model canvas. The business model would shape development of the software that needed to be functional and ready for testing by the completion of the thesis. Functional was defined as having completed the user and merchant side of the application including communication between both. Ultimately, a user needed to be able to complete a transaction that a merchant had submitted on the software.
ContributorsMaloney, Ryan Daniel (Author) / Mayron, Liam (Thesis director) / Peck, Sidnee (Committee member) / Barrett, The Honors College (Contributor) / School of Arts, Media and Engineering (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
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
This paper presents work that was done to create a system capable of facial expression recognition (FER) using deep convolutional neural networks (CNNs) and test multiple configurations and methods. CNNs are able to extract powerful information about an image using multiple layers of generic feature detectors. The extracted information can be used to understand the image better through recognizing different features present within the image. Deep CNNs, however, require training sets that can be larger than a million pictures in order to fine tune their feature detectors. For the case of facial expression datasets, none of these large datasets are available. Due to this limited availability of data required to train a new CNN, the idea of using naïve domain adaptation is explored. Instead of creating and using a new CNN trained specifically to extract features related to FER, a previously trained CNN originally trained for another computer vision task is used. Work for this research involved creating a system that can run a CNN, can extract feature vectors from the CNN, and can classify these extracted features. Once this system was built, different aspects of the system were tested and tuned. These aspects include the pre-trained CNN that was used, the layer from which features were extracted, normalization used on input images, and training data for the classifier. Once properly tuned, the created system returned results more accurate than previous attempts on facial expression recognition. Based on these positive results, naïve domain adaptation is shown to successfully leverage advantages of deep CNNs for facial expression recognition.
ContributorsEusebio, Jose Miguel Ang (Author) / Panchanathan, Sethuraman (Thesis director) / McDaniel, Troy (Committee member) / Venkateswara, Hemanth (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Many programmable matter systems have been proposed and realized recently, each often tailored toward a particular task or physical setting. In our work on self-organizing particle systems, we abstract away from specific settings and instead describe programmable matter as a collection of simple computational elements (to be referred to as particles) with limited computational power that each perform fully distributed, local, asynchronous algorithms to solve system-wide problems of movement, configuration, and coordination. In this thesis, we focus on the compression problem, in which the particle system gathers as tightly together as possible, as in a sphere or its equivalent in the presence of some underlying geometry. While there are many ways to formalize what it means for a particle system to be compressed, we address three different notions of compression: (1) local compression, in which each individual particle utilizes local rules to create an overall convex structure containing no holes, (2) hole elimination, in which the particle system seeks to detect and eliminate any holes it contains, and (3) alpha-compression, in which the particle system seeks to shrink its perimeter to be within a constant factor of the minimum possible value. We analyze the behavior of each of these algorithms, examining correctness and convergence where appropriate. In the case of the Markov Chain Algorithm for Compression, we provide improvements to the original bounds for the bias parameter lambda which influences the system to either compress or expand. Lastly, we briefly discuss contributions to the problem of leader election--in which a particle system elects a single leader--since it acts as an important prerequisite for compression algorithms that use a predetermined seed particle.
ContributorsDaymude, Joshua Jungwoo (Author) / Richa, Andrea (Thesis director) / Kierstead, Henry (Committee member) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05