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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.
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.
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.
"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."
problems can be executed exponentially faster than the current classical computers we have in use today. While there is tremendous research and development in the creation of quantum computers, there is a fundamental challenge that exists in the quantum world. Due to the fragility of the quantum world, error correction methods have originated since 1995 to tackle the giant problem. Since the birth of the idea that these powerful computers can crunch and process numbers beyond the limit of the current computers, there exist several mathematical error correcting codes that could potentially give the required stability in the fragile and fault tolerant quantum world. While there has been a multitude of possible solutions, there is no one single error correcting code that is the key to solving the problem. Almost every solution presented has shared with it a limiting factor or an issue that prevents it from becoming the breakthrough that is desperately needed.
This paper gives an introductory knowledge of what is the quantum world and why there is a need for error correcting topologies. Finally, it introduces one recent topology that could be added to the list of possible solutions to this central problem. Rather than focusing on the mathematical frameworks, the paper introduces the main concepts so that most readers even outside the major field of computer science can understand what the main problem is and how this topology attempts to solve it.
