Human activity recognition is the task of identifying a person’s movement from sensors in a wearable device, such as a smartphone, smartwatch, or a medical-grade device. A great method for this task is machine learning, which is the study of algorithms that learn and improve on their own with the help of massive amounts of useful data. These classification models can accurately classify activities with the time-series data from accelerometers and gyroscopes. A significant way to improve the accuracy of these machine learning models is preprocessing the data, essentially augmenting data to make the identification of each activity, or class, easier for the model. <br/>On this topic, this paper explains the design of SigNorm, a new web application which lets users conveniently transform time-series data and view the effects of those transformations in a code-free, browser-based user interface. The second and final section explains my take on a human activity recognition problem, which involves comparing a preprocessed dataset to an un-augmented one, and comparing the differences in accuracy using a one-dimensional convolutional neural network to make classifications.

The NBA yields billions of dollars each year and serves as a pastime and hobby for millions of Americans. However, many people do not have the time to watch several 2-hour games every week, especially when only a fraction of the game is actually exciting footage. The goal of Sports Summary is to take the ``fluff'' out of these games and create a distilled summary that includes only the most exciting and relevant events. The Sports Summary model records visual and auditory data, camera angles, and game clock readings and correlates it with the game's play-by-play data. On average, a game of more than 2 hours long is shortened to a summary of less than 20 minutes. This summary is then uploaded to the Sports Summary website, where users can filter by the type of event, giving more autonomy and a more comprehensive viewing experience than highlight reels. Additionally, the website allows for users to submit footage they would like to watch for processing and later viewing. Sports Summary creates an enjoyable and accessible way to watch games.

Contraceptive methods are vital in maintaining women’s health and preventing unintended pregnancy. When a woman uses a method that reflects her personal preferences and lifestyle, the chances of low adoption and misuse decreases. The research aim of this project is to develop a web-based decision aid tailored to college women that assists in the selection of contraceptive methods. For this reason, My Contraceptive Choice (MCC) is built using the gaps identified in existing resources provided by Planned Parenthood and Bedsider, along with feedback from a university student focus group. The tool is a short quiz that is followed by two pages of information and resources for a variety of different contraceptive methods commonly used by college women. The evaluation phase of this project includes simulated test cases, a Google Forms survey, and a second focus group to assess the tool for accuracy and usability. From the survey, 130 of the 150 (80.7%) responses believe that the recommendations provided can help them select a birth control method. Furthermore, 136 of the 150 (90.0%) responses believe that the layout of the tool made it easy to navigate. The second focus group feedback suggests that the MCC tool is perceived to be accurate, usable, and useful to the college population. Participants believe that the MCC tool performs better overall compared to the Planned Parenthood quiz in creating a customized recommendation and Bedsider in overall usability. The test cases reveal that there are further improvements that could be made to create a more accurate recommendation to the user. In conclusion, the new MCC tool accomplishes the aim of creating a beneficial resource to college women in assisting with the birth control selection process.

Generating an astounding $110.7 billion annually in domestic revenue alone [1], the world of accounting is one deceptively lacking automation of its most business-critical processes. While accounting tools do exist for the common person, especially when it is time to pay their taxes, such innovations scarcely exist for many larger industrial tasks. Exceedingly common business events, such as Business Combinations, are surprisingly manual tasks despite their $1.1 trillion valuation in 2020 [2]. This work presents the twin accounting solutions TurboGAAP and TurboIFRS: an unprecedented leap into these murky waters in an attempt to automate and streamline these gigantic accounting tasks once entrusted only to teams of experienced accountants.
A first-to-market approach to a trillion-dollar problem, TurboGAAP and TurboIFRS are the answers for years of demands from the accounting sector that established corporations have never solved.

As much as SARS-CoV-2 has altered the way humans live since the beginning of 2020,<br/>this virus's deadly nature has required clinical testing to meet 2020's demands of higher<br/>throughput, higher accuracy and higher efficiency. Information technology has allowed<br/>institutions, like Arizona State University (ASU), to make strategic and operational changes to<br/>combat the SARS-CoV-2 pandemic. At ASU, information technology was one of the six facets<br/>identified in the ongoing review of the ASU Biodesign Clinical Testing Laboratory (ABCTL)<br/>among business, communications, management/training, law, and clinical analysis. The first<br/>chapter of this manuscript covers the background of clinical laboratory automation and details<br/>the automated laboratory workflow to perform ABCTL’s COVID-19 diagnostic testing. The<br/>second chapter discusses the usability and efficiency of key information technology systems of<br/>the ABCTL. The third chapter explains the role of quality control and data management within<br/>ABCTL’s use of information technology. The fourth chapter highlights the importance of data<br/>modeling and 10 best practices when responding to future public health emergencies.