Reimbursable research at NPS

CRUSER TechCon 2018 Research at NPS. Wednesday 1: SensingThe rapid development in autonomous vehicles and artificial intelligence over the last decade has left most analysts and scholars convinced that the armed forces are facing a large scale change of technology, doctrine and organization. But few if any have addressed the question of how large this change will be and in what areas the change will come. It used to be the case that robots were made to perform repetitive and manual tasks, mainly replacing low-skilled workers. This latest version of automation is however being driven by new achievements in artificial intelligence and machine learning, and access to big data. This has the potential to not only change what kind of jobs our robots do, but also what kind of job the humans do. The aim of this paper is to quantify the amount of change and identify where that change will most likely occur. In this paper I use the US Navy as a case study to gain insights into the wider consequences for the armed forces. By using methodology developed for studying the computerization of the US economy, I am able to assess over 1,500 different occupations in the Navy. The 173 military specific occupations have not yet been assessed. The 1,500 occupations are assessed along three critical dimensions: the need for discerning perception and manipulation in task execution, the need for creative intelligence and the need for social intelligence. A task that requires little complexity in perception and manipulation, does not need to creativity and does not interact in a complex manner with others, is thus deemed likely to be computerized and replaced by robots and algorithms. Taking advantage of the extreme detail in the available descriptions of the different occupations, each occupation is thus assigned a probability of being replaced within the next two decades. Around a quarter of the occupations, 400, are found to have a higher than 70 percent chance of being computerized, while 850 have a lower than 30 percent chance of being computerized. More than half of the occupations in the Navy are thus not likely to be directly affected of the coming of the robots. Almost all of the occupations deemed having a high risk of being automated are in support services. Typical examples are culinary specialist, data transcriber, accounting, and a range of occupations involved in maintenance operation of equipment. Surprisingly large shares of the occupations that are deemed to have a high likelihood are either officer's occupations or warrant officer's occupations. Enlisted and civilians are almost unrepresented in this group. Based on these findings there is reason to believe that the potential for computerization is somewhat lower in the armed forces than in the economy as a whole. The occupations that have been assigned a high probability still represent a tantalizing opportunity for the Navy and the armed forces as a whole, and the potential benefits from seeking computerization in these low hanging fruits might be large. Scholars and military planners alike should train their eyes on this topic to get a better understanding of the dynamics and implications of the coming change

Exploitation of a Surface Current Mapping Network based on High Frequency Radar in support of the Central and Northern CA Ocean Observing System

Sponsored Research ArticleNaval Postgraduate School Cyber Academic Grou

Derailed locomotive? Petrobras investments and economic growth in Brazil

[EN] Petrobras is the largest firm in Brazil and one of the largest in the world. Its investment plans are among the biggest in the oil and gas industry, focused in Brazil and on E&P. Petrobras is responsible for a large share of gross capital formation and gross domestic product (GDP) growth in the country. The correlation between its investments and the country investment and GDP growth is above 0.8 and shows the dependency of the economy to Petrobras activity. At the same time, as a state enterprise it has been a tool of macroeconomic policy. In the 2010´s its gasoline and diesel prices were frozen to keep inflation down. The recent crisis in the company, including corruption scandals and oil price slump increased debt levels and reduced its capital expenditures. The sale of assets directive since 2016 is required to reduce its net debt. While a medium to long term survival strategy, the change in Petrobras’ investment profile may decrease the prospects of GDP growth in the Brazilian economy.We acknowledge the support from Labecopet/Poli/UFRJ and comments and suggestions from Eduardo Pontual Ribeiro (IE/UFRJ).Yabiko, RF.; Bone, RB. (2018). Derailed locomotive? Petrobras investments and economic growth in Brazil. International Journal of Production Management and Engineering. 6(1):47-55. https://doi.org/10.4995/ijpme.2018.8758SWORD475561Blanchard, O. (2011). Macroeconomia, 5th Edition. São Paulo: Ed. Pearson.Damodaran, A. (1997). Avaliação de Investimentos: Ferramentas e técnicas para a determinação do valor de qualquer ativo, 1st Edition. Rio de Janeiro: Qualitymark.Gujarati, D. N. (2001). Basic Econometrics, 4th Edition. São Paulo: McGraw-Hill Company.Paduan, Roberta (2016) Petrobras: uma história de orgulho e vergonha. Rio de Janeiro: Ed. Objetiva.Ribeiro, E. P., de Almeida, W. F., & Bone, R. B. (2016). Stock Market Firm Value Effects of Research and Development Expenditures in the Oil and Gas Industry. Engineering Systems and Networks, 61-67. doi:10.1007/978-3-319-45748-2_

Role of Tidal Forcing in Determining the Internal Wave Spectrum in the Littoral Ocean

LONG-TERM GOALS: The long-range goals of this project are to understand the environmental factors that define the level of internal wave activity in the littoral oceans and to develop re-locatable models capable of predicting these levels. The hypothesis is that energy due to internal tides generated through interactions with complex coastal topography is both predictable, using high-resolution primitive equation numerical models, and responsible for setting energy levels of the broader-frequency internal wave spectrum.Award #: N00014–97WR–3000

Introduction to High-Frequency Radar: Reality and Myth

The article of record as published may be found at https://www.jstor.org/stable/43924791Purpose – The purpose of this paper is to help optimize sustainment logistics for US Army brigade combat teams, which may face challenges in transporting their assigned assets. Design/methodology/approach – This paper develops a simulation framework with an integrated integer programming optimization model. The integer-programming model optimizes sustainment outcomes of supported battalions on a daily basis, whereas the simulation framework analyzes risk associated with shortfalls that may arise over the entire duration of a conflict. Findings – This work presents a scenario reflecting the steady resupply of an infantry brigade combat team during combat operations and presents an in-depth risk analysis for possible fleet compositions. Originality/value – The risk curves obtained allow decision-makers and commanders to optimize vehicle fleet design in advance of a conflict.Office of Naval ResearchThe editors of this special issue on High Frequency Radar Remote Sensing gratefully acknowledge the continued support of the Office of Naval Research through grants N00014-91-J-1775 (HIRES), 92-J-1807 (REINAS), 94-1-1016 (DUCK94), 95-3-0022 (MRY BA Y), 96-1-1065 (COPE), and 97-1-0348 (SHOALING WAVES).The editors of this special issue on High Frequency Radar Remote Sensing gratefully acknowledge the continued support of the Office of Naval Research through grants N00014-91-J-1775 (HIRES), 92-J-1807 (REINAS), 94-1-1016 (DUCK94), 95-3-0022 (MRY BA Y), 96-1-1065 (COPE), and 97-1-0348 (SHOALING WAVES)

Mapping Surface Currents In Monterey Bay with CODAR-Type HF Radar

The article of record as published may be found at https://www.jstor.org/stable/43924794Office of Naval ResearchThis work was supported by the ONR REINAS project and by ONR contract N0001495WR30022

Modeling the Response of Monterey Bay to Diurnal

LONG TERM GOALS: Long-term goals of this project are to improve high-resolution numerical models of the ocean circulation for the regions with complex bottom topography, coastlines and multi-scale physical fields using enhanced grid technology, nested open boundary and, ultimately, data assimilation of new observational data type like current maps from High Frequency (HF) radar installations.Award number: N0001497WR30065TER

Role of Tidal Forcing in Determining the Internal Wave Spectrum in the Littoral Ocean

The long-range goals of this project are to understand the environmental factors that define the level of internal wave activity in the littoral oceans and to develop re-locatable models capable of predicting these levels. The hypothesis is that energy due to internal tides generated through interactions with complex coastal topography is both predictable, using high-resolution primitive equation numerical models, and responsible for setting energy levels of the broader-frequency internal wave spectrum.Award #: N00014–97WR–3000