"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."
This thesis proposes a new steering system for agricultural machinery with the aim of improving the automation capabilities of farming robots. Accurate and reliable autonomous machinery has the potential to provide significant benefits to the efficiency of farming operations, but the existing systems for performing one of the most essential automation functions, autonomous steering to keep machinery on the proper course, each have drawbacks that impact their usability in various scenarios. In order to address these issues, a new lidar-based system was developed for automatic steering in a typical farm field. This approach uses a two-dimensional lidar unit to scan the ground in front of the robot to detect and steer based on farm tracks, a common feature in many farm fields. This system was implemented and evaluated, with results demonstrating that the system is capable of providing accurate steering corrections.