Welcome to USMA Athena
USMA Athena is a secure digital service managed by the United States Military Academy Library to make the work of USMA scholars freely available, while also ensuring these resources are organized to preserve the legacy of USMA scholarship. The mission of USMA Athena is to showcase the academic impact and intellectual capital that has become synonymous with the celebrated heritage of educational prowess attributed to the Long Gray Line. Scholarship submitted to USMA Athena benefits from added visibility and discoverability via Google Scholar in addition to the use of persistent URLs that will provide enduring access to the work over time.
Recent Submissions
Item Link Quality Estimation in Ad Hoc and Mesh Networks: A Survey and Future Directions(Springer (Publisher of Wireless Personal Communications), 2017-09-01)Higher layer applications, such as routing protocols and robot navigation systems, commonly depend upon link quality (LQ) estimates for improving the efficiency and reliability of wireless communications. LQ estimation is especially critical for maintaining connectivity in mobile ad hoc networks, which tend to be less reliable than infrastructure networks due to their decentralized and dynamic nature. However, estimating LQ for applications higher than the physical layer is challenging due to the underlying dynamics of wireless propagation and the mismatched temporal perspectives between the layers. Due to its relevance and difficulty, a significant research effort has been devoted to developing empirical methods for accurately estimating LQ. The goal of this survey is to provide a comprehensive review of the existing approaches to LQ estimation in IEEE 802.11-based ad hoc and mesh networks, with some exceptions that include sensor networks. The survey organizes the literature according to the different fundamental techniques, and also compares them in terms in terms of strengths and weaknesses. Finally, we conclude with the latest developments in LQ estimation, which involve machine learning, and provide recommendations for future work in the field.Item Teaching Embedded Systems with a Robotics Theme using ROS on the Raspberry Pi(ASEE (American Society for Engineering Education), 2018-04-27)Many courses teaching the principles of embedded systems primarily focus on programming microcontrollers. However, the domain of embedded systems is a broad domain that encompasses other processor types including single-board computers (SBCs) with operating systems. SBCs are often overlooked in the curriculum of embedded systems despite their ability to meet the computational requirements of more sophisticated applications, such as robot controllers and network routers. To address this gap, we restructured our course to include coverage on SBCs while also maintaining some lessons and projects devoted to the register-level programming of microcontrollers. This paper discusses how we integrated SBCs, in the form of the Raspberry Pi 3 (RPI3), into our project-based, undergraduate course. Furthermore, the paper reviews how we introduce the fundamentals of the Robot Operating System (ROS) using a series of projects that are now feasible because of the incorporation of SBCs and a Linux distribution into our curriculum.Item Expediting the targeting process responsibly using artificial intelligence(SPIE, 2022-06-06)Absent the use of artificial intelligence (AI), each stage of the targeting process requires human input, which consumes time – a precious resource during high-intensity conflict. To counter that problem, the application of AI and related technologies could rapidly automate certain steps within the targeting process. The challenge, however, becomes how to responsibly speed up the process using AI, while also maintaining appropriate levels of human oversight based on level of risk acceptable to the commander. We address this challenge with the introduction of a fuzzy logic controller that is designed to automatically adapt and optimize the level of human-machine interaction based on the current targeting conditions. The logic controller uses the confidence of the AI algorithm at each stage of the targeting process, as well as the commander’s risk tolerance at the time, to automatically determine what stages of the targeting process can be trusted for AI to accelerate and which ones require explicit human verification. The final stage of verifying and authorizing a fire mission is reserved for humans only to make.Item Mindset and Motivation(2014)Mindset and motivation are foundational drivers of human behavior, performance, and well-being across academic, professional, and personal domains. This paper synthesizes decades of research in positive psychology, educational psychology, and motivation theory to examine how fixed and growth mindsets shape individual achievement, resilience, and happiness. Drawing on the work of Carol Dweck, Mihaly Csikszentmihalyi, Malcolm Gladwell, Angela Duckworth, and others, the paper argues that mindset is a primary determinant of motivation, influencing whether individuals pursue extrinsic rewards or intrinsic fulfillment through growth, relationships, purpose, and mastery. The role of stress, identity, labels, and stereotypes is explored, highlighting how chronic stress and fixed beliefs can undermine motivation and performance, while malleable beliefs foster perseverance, grit, and adaptability. Central to the discussion is the concept of intentional activity and its connection to autotelic experiences, or “flow,” which serve as a powerful mechanism for sustained motivation and happiness. Through applications in education, leadership development, and military training, the paper emphasizes that mindset is malleable and can be intentionally cultivated. Ultimately, the paper concludes that fostering a growth mindset—supported by high standards, nurturing environments, and intrinsic motivation—enables individuals to maximize potential, enhance performance, and achieve lasting personal and professional fulfillment.Item Using Artificial Intelligence to Disrupt Terrorist Operations(NATO Centre of Excellence Defence Against Terrorism (COE-DAT), 2025-04-01)This chapter examines how artificial intelligence can play a role in a counterterrorist deterrent strategy by disrupting the stages of the terrorist attack cycle. By leveraging AI’s capabilities, security forces can detect subtle signs of terrorist activities that were previously difficult for humans to identify. The chapter recommends a revolution in counterterror affairs that considers revisions to AI architecture to combine multiple algorithms to improve decision-making and predictive accuracy.
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