The Fourth Industrial Revolution’s Wave Crashes Upon the Shores of Accounting: The Value Metric for the Fourth Industrial Revolution

Financial Management / Faculty ReportAcquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsAlmost 30 years ago, Elliott (1992) shared several critical insights about the inadequacies of the field of accounting to account for radical changes in the ways businesses develop and execute strategy based on the fundamental opportunities that had come about due to information age technology. Accounting has remained virtually unchanged for over 500 years and society has now entered what Schwab (2015) referred to as the “Fourth Industrial Revolution” where technology advancements follow an exponential growth curve introduces a reality that combines technology across the physical, digital, and biological domains. The Fourth Industrial Revolution has the potential to change both public and private sector organizations, and society itself, however, the accounting practices are not positioned to take advantage of these changes. With this phenomenon in mind, this study seeks to address a gap in the literature that the current accounting practices are insufficient to meet the challenges of the Fourth Industrial Revolution as they do not provide a raw, non-monetized common unit of value, that can measure productivity on a ratio scale for non-profit organizations or at the sub-corporate level in for-profit organization. Through a discussion guided by the literature, this study seeks to generate a scholastic dialogue on how to address this problem.Approved for public release; distribution is unlimited

and Cost/Benefits Opportunities

Acquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsThe acquisition of artificial intelligence (AI) systems is a relatively new challenge for the U.S. Department of Defense (DoD). Given the potential for high-risk failures of AI system acquisitions, it is critical for the acquisition community to examine new analytical and decision-making approaches to managing the acquisition of these systems in addition to the existing approaches (i.e., Earned Value Management, or EVM). In addition, many of these systems reside in small start-up or relatively immature system development companies, further clouding the acquisition process due to their unique business processes when compared to the large defense contractors. This can lead to limited access to data, information, and processes that are required in the standard DoD acquisition approach (i.e., the 5000 series). The well-known recurring problems in acquiring information technology automation within the DoD will likely be exacerbated in acquiring complex and risky AI systems. Therefore, more robust, agile, and analytically driven acquisition methodologies will be required to help avoid costly disasters in acquiring these kinds of systems. This research provides a set of analytical tools for acquiring organically developed AI systems through a comparison and contrast of the proposed methodologies that will demonstrate when and how each method can be applied to improve the acquisitions lifecycle for AI systems, as well as provide additional insights and examples of how some of these methods can be applied. This research identifies, reviews, and proposes advanced quantitative, analytically based methods within the integrated risk management (IRM)) and knowledge value added (KVA) methodologies to complement the current EVM approach. This research examines whether the various methodologies—EVM, KVA, and IRM—could be used within the Defense Acquisition System (DAS) to improve the acquisition of AI. While this paper does not recommend one of these methodologies over the other, certain methodologies, specifically IRM, may be more beneficial when used throughout the entire acquisition process instead of within a portion of the system. Due to this complexity of AI system, this research looks at AI as a whole and not specific types of AI.Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

A Comparative Analysis of Advanced Methodologies to Improve the Acquisition of Information Technology in the Department of Defense for Optimal Risk Mitigation and Decision Support Systems to Avoid Cost and Schedule Overruns

This study examines five advanced decision support methodologies—Lean Six Sigma (LSS), Balanced Score Card (BSC), Integrated Risk Management (IRM), Knowledge Value Added (KVA), and Earned Value Management (EVM)—in terms of how each can support the information technology (IT) acquisition process. In addition, the study provides guidance on when each methodology should be applied during the acquisition life cycle of IT projects. This research includes an in-depth review of each methodology in the context of the acquisition life cycle. All acquisition projects within the Department of Defense must go through the acquisition life cycle. While each acquisition project is unique, all must pass a series of common hurdles to succeed. Understanding how and when the methodologies can be applied to an IT acquisition is fundamental to its success. The study concludes with a set of recommendations for the use of each methodology in the acquisition life cycle of IT projects.Prepared for the Naval Postgraduate School, Monterey, CA 93943.Naval Postgraduate SchoolApproved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Acquiring Artificial Intelligence Systems: Development Challenges, Implementation Risks, and Cost/Benefits Opportunities

The acquisition of artificial intelligence (AI) systems is a relatively new challenge for the U.S. Department of Defense (DoD). Given the potential for high-risk failures of AI system acquisitions, it is critical for the acquisition community to examine new analytical and decision-making approaches to managing the acquisition of these systems in addition to the existing approaches (i.e., Earned Value Management). In addition, many of these systems reside in small start-up or relatively immature system development companies, further clouding the acquisition process due to their unique business processes when compared to the large defense contractors. This can lead to limited access to data, information, and processes that are required in the standard DoD acquisition approach. The well-known recurring problems in acquiring information technology automation within the DoD will likely be exacerbated in acquiring complex and risky AI systems. Therefore, more robust, agile, and analytically driven acquisition methodologies will be required to help avoid costly disasters in acquiring AI systems. This research provides a set of analytical tools for acquiring organically developed AI systems through a comparison and contrast of the proposed methodologies that will demonstrate when and how each method can be applied to improve the acquisitions life cycle for AI systems.Prepared for the Naval Postgraduate School, Monterey, CA 93943.Naval Postgraduate SchoolApproved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

4EBP-Dependent Signaling Supports West Nile Virus Growth and Protein Expression

West Nile virus (WNV) is a (+) sense, single-stranded RNA virus in the Flavivirus genus. WNV RNA possesses an m7GpppNm 5′ cap with 2′-O-methylation that mimics host mRNAs preventing innate immune detection and allowing the virus to translate its RNA genome through the utilization of cap-dependent translation initiation effectors in a wide variety of host species. Our prior work established the requirement of the host mammalian target of rapamycin complex 1 (mTORC1) for optimal WNV growth and protein expression; yet, the roles of the downstream effectors of mTORC1 in WNV translation are unknown. In this study, we utilize gene deletion mutants in the ribosomal protein kinase called S6 kinase (S6K) and eukaryotic translation initiation factor 4E-binding protein (4EBP) pathways downstream of mTORC1 to define the role of mTOR-dependent translation initiation signals in WNV gene expression and growth. We now show that WNV growth and protein expression are dependent on mTORC1 mediated-regulation of the eukaryotic translation initiation factor 4E-binding protein/eukaryotic translation initiation factor 4E-binding protein (4EBP/eIF4E) interaction and eukaryotic initiation factor 4F (eIF4F) complex formation to support viral growth and viral protein expression. We also show that the canonical signals of mTORC1 activation including ribosomal protein s6 (rpS6) and S6K phosphorylation are not required for WNV growth in these same conditions. Our data suggest that the mTORC1/4EBP/eIF4E signaling axis is activated to support the translation of the WNV genome

male

Angiomatoid fibrous histiocytoma (AFH) is a rare disease that is often misdiagnosed initially. Patients can present with a clinical picture concerning for other diseases, and pathologic review is not always revealing. Molecular diagnostics are increasingly being utilized to detect gene fusions characteristic for AFH. Surgery remains the mainstay of management, and can effectively control local recurrences and metastases. Herein we describe a case report of a 25-year-old gentleman whose presentation was concerning for lymphoma. Subsequently we review of the relevant literature