Matching Items (14)
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- All Subjects: ios
- Creators: Computer Science and Engineering Program
Description
This project explores how modern mobile technology can be used to provide support for domestic violence victims. The goal of the project is to create a proof-of-concept iOS mobile application that maintains a discreet safety front and provides domestic violence victims with resources and safety planning. The design and implementation are disguised as a hair salon app to maintain a low profile on the user’s phone. The HairHelp app features quick exit navigation, a secure database to store a user’s private and personal documents in case of emergency, and a checklist of safety planning measures. The steps taken in this project serve as the foundation for a larger project in the long term.
ContributorsShovkovy, Sophia (Author) / Balasooriya, Janaka (Thesis director) / Wilkey, Douglas (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
When planning a road trip today, there are solutions that let the user know what comes along their route, but the user is often presented with too much information, which can overwhelm the user. They are provided suggestions all along the route, not just at those times when they would be needed. RoutePlanner simply takes all that information and only presents that data to the user, that they would need at a particular time. Gas station suggestions would show when the gas tank range is going to be hit soon, and restaurant suggestions would only be shown around lunch time. The iOS app takes in the users origin and destination and provides the user the route as given by GoogleMaps, and then various stop suggestions at their given time. Each route that is obtained, is broken down into a number of steps, which are basically a connection of coordinate points. These coordinate point collections are used to point to a location at a certain distance or duration away from the origin. Given a coordinate, we query the APIs for places of interest and move to the next stop, until the end of the route.
ContributorsDamania, Harsh Abhay (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-12
Description
As technology's influence pushes every industry to change, healthcare professionals must move to a more connected model. The nearly ubiquitous presence of smartphones presents a unique opportunity for physicians to collect and process data from their patients more frequently. The Mayo Clinic, in partnership with the Barrett Honors College, has designed and developed a prototype smartphone application targeting palliative care patients. The application collects symptom data from the patients and presents it to the doctors. This development project serves as a proof-of-concept for the application, and shows how such an application might look and function. Additionally, the project has revealed significant possibilities for the future of the application.
ContributorsGaney, David Howard (Author) / Balasooriya, Janaka (Thesis director) / Lipinski, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The face of computing is constantly changing. Wearable computers in the form of glasses or watches are becoming more and more common. These devices have very small screens (measured in millimeters), and users often interact with them through voice input and audio feedback. Weather is one of the most regularly checked app category on smart devices, but weather results on these devices are often limited to raw data, canned responses, or sentence templates with numbers plugged in. The goal for this project was to build a system that could generate weather forecast text, which could then be read to a user through text-to-speech. By using methods in language generation, the system can generate weather forecast text in millions of different ways. This is all computed locally, and it covers every possible weather case. In order to generate natural weather forecast texts, the system retrieved raw weather data from a weather API and created the text through six methods: content determination, document structuring, sentence aggregation, lexical choice, referring expression generation, and text realization. Content determination is the process of deciding on what information to include in a computer generated text. The document structuring phase deals with the order and structure of the information. Sentence aggregation is the merging of similar sentences to improve readability and to reduce redundancy. Lexical choice is the process of putting words to concepts. Referring expression generation is the process of identifying objects, regions, time periods, and locations within a text. Finally text realization involves creating sentences with proper syntax, morphology, and orthography. Through these six stages, a system was developed that could generate unique weather forecast text from raw data accurately and efficiently. It was built for iOS devices with Apple's new programming language, Swift, and it will be ported to the Apple Watch when the API is fully opened to developers.
ContributorsJorgensen, Jacob Paul (Author) / Baral, Chitta (Thesis director) / Faucon, Christophe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Finding applications on Apple’s iOS device Home screen is a difficult task since applications are arranged in a disorganized grid of icons and small labels. By “jailbreaking” an iOS device, it is possible to install third party “tweaks” that modify the operating system to customize and fix annoying aspects of iOS. Current jailbreak tweaks exist that can launch applications differently than Apple’s stock Home screen, but they leave much to be desired in terms of functionality, usability, and aesthetics. HomeList is a watchOS-inspired tweak I created to add an easy to read, quick to navigate, and visually appealing list of applications integrated directly into the Home screen. Research into Apple’s private iOS frameworks was used to figure out how to perform tasks required by an app launcher as well as match iOS design aesthetics.
ContributorsBoxberger, Blake Palmer (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Philippe Christophe (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Less than half of all premedical applicants get accepted into a medical school, 39.3% of applicants to be precise, and that statistic is based on the number of matriculants out of the total applicants in 2015. With such a discouraging acceptance rate, many students who start out as premed are often not towards the end of their undergraduate career and post-graduation because they do not feel prepared for medical school. It’s difficult for premed students to find all the information they need in one place rather than going from place to place or school website to school website. Additionally, it can be a hassle for premeds to keep track of all their coursework and calculate separate GPAs for each category especially due to how annoying Excel spread sheets can be. This is where the conceptualization of Premed Portfolio comes in. Premed Portfolio is a prototype mobile application. Premed Portfolio aims to streamline the process of preparing for medical school by guiding students to create a portfolio aimed to address the most important aspects of a medical school application. Students will be able to keep track of their cumulative GPA, BCPM (also known as science/math) GPA, MCAT Scores, prerequisite coursework and many more targeted areas of medical school. Premed Portfolio will also hope to use the stats that students provide and educate them on their chances of getting into medical school.
ContributorsSiddique, Shabab (Co-author, Co-author) / Rahman, Ahnaf (Co-author) / Patel, Dhruv (Co-author) / Sarwat Abdelghany Aly Elsayed, Mohamed (Thesis director) / Coursen, Jerry (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to properly dispose of the material. Some searches will show locations of facilities near users that collect certain materials and dispose of the materials properly. This is a full stack software project that explores open source software and APIs, UI/UX design, and iOS development.
ContributorsTran, Nikki (Author) / Ganesh, Tirupalavanam (Thesis director) / Meuth, Ryan (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Charleston, South Carolina currently faces serious annual flooding issues due to tides and rainfall. These issues are expected to get significantly worse within the next few decades reaching a projected 180 days a year of flooding by 2045 (Carter et al., 2018). Several permanent solutions are in progress by the City of Charleston. However, these solutions are years away at minimum and faced with development issues. This thesis attempts to treat some of the symptoms of flooding, such as navigation, by creating an iPhone application which predicts flooding and helps people navigate around it safely. Specifically, this thesis will take into account rainfall and tide levels to display to users actively flooded areas of downtown Charleston and provide routing to a destination from a user’s location around these flooded areas whenever possible.
ContributorsSalisbury, Mason (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Even in the largest public university in the country, computer related degrees such as Computer Science, Computer Systems Engineering and Software Engineering have low enrollment rates and high dropout rates. This is interesting because the careers that require these degrees are marketed as the highest paying and most powerful. The goal of this project was to find out what the students of Arizona State University (ASU) thought about these majors and why they did or did not pick them. A total of 206 students were surveyed from a variety of sources including upper level classes, lower level classes and Barrett, the Honors College. Survey questions asked why the students picked their current major, if they had a previous major and why did they switch, and if the students had considered one of the three computer related degrees. Almost all questions were open ended, meaning the students did not have multiple choice answers and instead could write as short or as long of a response as needed. Responses were grouped based on a set of initial hypotheses and any emerging trends. These groups were displayed in several different bar graphs broken down by gender, grade level and category of student (stayed in a computer related degree, left one, joined one or picked a non-computer related degree). Trends included students of all grade levels picking their major because they were passionate or interested in the subject. This may suggest that college students are set in their path and will not switch majors easily. Students also reported seeing computer related degrees as too difficult and intimidating. However, given the low (when compared to all of ASU) number of students surveyed, the conclusions and trends given cannot be representative of ASU as a whole. Rather, they are just representative of this sample population. Further work on this study, if time permitted, would be to try to survey more students and question some of the trends established to find more specific answers.
ContributorsMeza, Edward L (Author) / Meuth, Ryan (Thesis director) / Miller, Phillip (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
This project serves as an extra learning tool for students enrolled in HEB 101 (Hebrew) at Arizona State University. This tool was developed using Axure Prototyping Software and can be used by anyone. The tool follows the HEB 101 course curriculum which also works alongside the textbook for the class (Hebrew From Scratch part 1). The tool fully covers the seven units that students learn in HEB 101. Each unit follows a standard structure. There is a unit title page which lays out the major concepts covered in the unit (i.e. personal pronouns, question words, prepositions, etc.) and links to different pages within the unit. Each unit has seven to ten lesson pages which introduce Hebrew concepts and provide exercises and examples to help the students practice the material they learned both in class and in the tool. Each unit also has links to Quizlet pages that have the units' vocab set up in a flashcard format so that they can study for upcoming quizzes and exams in the class. The Quizlet page for each unit also provides a randomly generated vocab quiz for the students. There is also a unit quiz for every unit which tests the students on the major concepts of the unit. There are also unit vocab pages that provide all the vocab covered in the unit. This tool provides students with numerous ways of practicing and mastering the material covered in the lectures. The main benefit of this tool for students is that it provides audio files for each vocabulary word learned in HEB 101 which will allow them to have quick access to the pronunciation of the words they are learning. This tool will be used in future HEB 101 classes.
ContributorsOsuna, Esteban Rene (Author) / Shemer, Judith (Thesis director) / Mirguet, Francoise (Committee member) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05