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Three Things Leaders Need to Know Before Investing in Artificial Intelligence
No full textArtificial intelligence (AI) solution vendors pitch multiple AI capabilities that have the potential to revolutionize the Department of Defense (DoD). How do leaders sift through the “snake oil” and find real applications? How can leaders navigate organizational challenges and identify their best use cases for AI? The truth is, “AI can find answers, but humans have to ask the right [kind of] questions. This article explains three steps that every leader needs to know before they invest in AI. The three steps are finding the best use cases for AI, readying data for AI, and ensuring a comprehensive data solution. It concludes with recommendations for the DoD’s future to achieve AI literacy in the workforce
Using Side Channel Information and Artificial Intelligence for Malware Detection
No full textCybersecurity continues to be a difficult issue for society especially as the number of networked systems grows. Techniques to protect these systems range from rules-based to artificial intelligence-based intrusion detection systems and anti-virus tools. These systems rely upon the information contained in network packets and downloaded executables to function. Side channel information leaked from hardware has been shown to reveal secret information in systems such as encryption keys. Computers provide many side channels such as temperature, access rates, operational frequencies, and voltages that can provide insight into what is running on a system. This work demonstrates that this side channel information can be used to detect malware running on a computing platform without access to the code involved
Modeling Supply Chain Disruptions During a Pandemic: A System Dynamics Approach
No full textThe COVID-19 Pandemic of 2020 uniquely impacted the janitorial supply industry with shocks in both demand and supply. Some products experienced massive increases in demand leading to shortages, while the closing of public spaces caused a decrease in demand of other products. The industry experienced delays in shipping and production because of factory closings. Changing public policies for hygiene standards in public buildings, schools, and government buildings has led to a sustained increase in demand for certain products. The janitorial supply chain is a dynamic system that continues to experience change as the pandemic and the public response to it evolves. This research uses a System Dynamics approach to model a small janitorial supply business’ inventory both before and during the pandemic using Vensim. The model focuses on the main categories of products the business sells (Paper Products, Chemicals, Aerosols, and Garbage Bags) and how their respective flows of supply and demand are affected. The business purchases some products directly from manufacturers and others from larger distributors. It sells primarily to the following categories of customers: government contracts, factories, businesses, and individual walk-in sales. Ultimately, this model explores practical policies the store could implement to make them more resilient to the extreme levels of uncertain supply and demand caused by the pandemic. Implementing inventory minimums for sales and safety stocks for orders improved the number of sales and increased revenue for the business during pandemic simulations. Safety stocks and inventory minimums prove to be useful policies for small businesses to consider to become more resilient and survivable to a pandemic
The Effects of Increasing the Size of the Infantry Squad
No full textAfter major conflicts, the United States Army re-evaluates the optimal size of its infantry squads, given changes in military technology and enemy strategy. The Army is currently evaluating changing the size of the infantry squad from nine to thirteen. This analysis sets out to analyze the change in soldier survivability and lethality from this change. The Lanchester equations, the standard attrition models used in military modeling, provided initial insight into these changes. The Lanchester equations indicated that the squad would have an increase in survivability and mission effectiveness. A more detailed analysis used the Infantry Warrior Simulation (IWARS) to simulate four standard infantry missions and evaluate the overall changes in mission performance. This model indicated that across the mission sets the infantry squad saw an increase in lethality and a decrease in survivability when shifting from nine to thirteen soldiers
Sharpening the Blunt Tool: Why Deterrence Needs an Update in the Next U.S. National Security Strategy
No full textThe 2017 U.S. National Security Strategy appeared to bring deterrence back: departing from its predecessor, the document prioritized the concept by including “preserving peace through strength” as a vital national interest. From nuclear weapons to cyberspace, the strategy emphasized the logics of denial and punishment, which were hallmarks of the classical deterrence theory that emerged after World War II. However, recent thinking on deterrence has evolved beyond these simple logics. Now emerging concepts such as tailored deterrence, cross-domain deterrence, and dissuasion offer new ideas to address criticisms of deterrence in theory and practice. Therefore, the most vital question for the new administration is: how should the U.S. revise its deterrence policy to best prevent aggression in today’s complex environment? A review of the problems and prospects in deterrence thinking reveals that in addition to skillfully tailoring threats and risks across domains, U.S. policymakers should dissuade aggression by offering opportunities for restraint to reduce the risk of escalation
Resting Energy Expenditure: From Cellular to Whole-Body Level, a Mechanistic Historical Perspective.
No full textThe basis of heat generated by the human body has been a source of speculation and research for more than 2,000 years. Basal heat production, now usually referred to as resting energy expenditure (REE), is currently recognized as deriving from biochemical reactions at subcellular and cellular levels that are expressed in the energy expended by the body\u27s 78 organs and tissues. These organs and tissues, and the 11 systems to which they belong, influence body size and shape. Connecting these subcellular-/cellular-level reactions to organs and tissues, and then on to body size and shape, provides a comprehensive understanding of individual differences in REE, a contemporary topic of interest in obesity research and clinical practice. This review critically examines these linkages, their association with widely used statistical and physiological REE prediction formulas, and often-unappreciated aspects of measuring basal heat production in humans
Simultaneous Estimation and Modeling of Robotic Systems with Non-Gaussian State Belief
No full textThis paper develops a probabilistic simultaneous estimation and modeling (SEAM) framework for estimating a robot’s state and correcting its motion model parameters. This is done by incorporating model uncertainty in state prediction and correcting parameters via optimization. In the proposed technique, belief about a state being estimated is represented by arbitrary multi-dimensional non-Gaussian probability distribution functions. The approach is validated in proof-of-concept for second-order simulated systems whose models are poorly estimated. Given sufficient state observations, the proposed framework reliably reduces and usually converges model parameter error. In comparison with existing advanced estimators, robotic state estimation is enhanced under this framework when model uncertainty is high and state belief is highly unstructured and non-Gaussian. This work holds promise for challenging robotic localization, estimation, and prediction problems across many complex domains
A Methodology for Assessing the Feasibility of Pumped Hydroelectric Storage within Existing USACE Facilities
Get PDFVariable, renewable energy (VRE) generation such as solar power has seen a rapid increase in usage over the past decades. These power generation sources offer benefits due to their low marginal costs and reduced emissions. However, VRE assets are not dispatchable, which can result in a mismatch of the electric supply and demand curves. Pumped-storage hydropower (PSH) seeks to solve this by pumping water uphill during times of excess energy production and releasing the water back downhill through turbines during energy shortages, thus serving as a rechargeable battery. Creating new PSH systems, however, requires a large amount of capital and suitable locations. The United States Army Corps. of Engineers (USACE) is the largest producer of hydroelectric power within the United States, and as such, may have favorable sites for the addition of PSH. This study seeks to develop a method for evaluating these existing hydroelectric facilities using techno-economic methods to assess the potential for adding PSH. Each USACE facility was evaluated based on site specific characteristics from previously unpublished data to estimate the power generation and energy storage potential. The temporal nature of local wholesale electricity prices was accounted for to help estimate the financial feasibility of varying locations. Sensitivity analysis was performed to highlight how the method would identify the viability of facilities with different operational conditions. The methodologies detailed in this study will inform decision-making processes, and help enable a sustainable electric grid
Error Reduction for the Determination of Transverse Moduli of Single-Strand Carbon Fibers via Atomic Force Microscopy
Get PDFPeakForce Atomic Force Microscopy (AFM) Quantitative Nanomechanical Measurement (QNM) is utilized to measure the transverse fiber modulus of single strand carbon fibers to less than 5% error for eleven types of carbon fibers, manufactured by Mitsubishi, Toray, and HEXCEL, with longitudinal moduli between 924-231 GPa, including export-controlled fibers. A positive linear correlation between the longitudinal and transverse modulus with an R^2=0.76 is found. Statistical and physical criterion for outlier removal are studied and established to improve the quality of data to exclude outlier measurement points in an image based on the peak force, adhesion force, and indentation depth. Statistical and physical criterion are also developed to exclude outlier images within the sample set. Three alternative methods for calculating the transverse modulus using the raw instrument data were studied. The first method approximated the indentation force curve using the peak force and adhesion force values. This method calculated moduli lower than that reported by the instrument and with no correlation between the transverse and longitudinal modulus. The second method approximated the indentation force curve using the peak force and net force zero point. This method found values larger than that reported by the instrument and no correlation between the transverse and longitudinal modulus. The final method performs a linear fit to the measured indentation force curves at each indentation point. This method also found values lower than reported by the instrument. Pitch-based fibers are found to exhibit lower measurement error than PAN-based fibers. Additionally, PAN fibers exhibited no apparent modulus correlation when the Pitch fibers are excluded. Underlying reasons for this lack of correlation are explored, with the most likely reasons being the difference in long-range order in the fiber microstructure and aging effects due to the different sourcing and storage methods used for the PAN fibers. Low uncertainty characterization of the transverse modulus supports greater understanding of fiber mechanical behavior, and would allow fiber manufacturers to certify their fibers in both the longitudinal and transverse axes. Additionally, it would improve the confidence in engineering estimates used by industry and defense programs for transverse performance of carbon fiber-reinforced composites
Toward Measures of Human-robot Teaming Effectiveness
No full textAs robot capabilities rapidly evolve, the dynamics of human-robot teams will change. Autonomous, intelligent technologies will come to serve in roles that more closely resemble those of teammates, as opposed to tools. This will require humans to adapt and remain agile in developing novel strategies and tactics for employing these systems in complex, real-world scenarios. Building on previous work that presented a novel data set collected from teams of humans and robots playing capture the flag, the current research aims to identify measures capable of predicting successful teaming that lead to a winning outcome. Three case studies highlight the difficulty in characterizing human-robot interaction and game play to create an objective score