USMA Digital Commons (United States Military Academy, West Point)
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Remarks on the Occasion of the Retirement of Distinguished Professor Guillermo Owen
Get PDFThe article is a tribute to Distinguished Professor Guillermo Owen who recently retired from the Naval Postgraduate School after 40 years of service
Algorithmic Methods for Covering Arrays of Higher Index
Get PDFCovering arrays are combinatorial objects used in testing large-scale systems to increase confidence in their correctness. To do so, each interaction of at most a specified number t of factors is represented in at least one test; that is, the covering array has strength t and index 1. For certain systems, the outcome of running a test may be altered by variability of the interaction effect or by measurement error of the test result. To improve the efficacy of testing, one can ensure that each interaction of t or fewer factors is represented in at least λ tests. When λ \u3e 1, this leads to covering arrays of higher index. We explore two algorithmic methods for constructing covering arrays of higher index. One is based on the in-parameter-order algorithm, and the other employs a conditional expectation paradigm. We compare these two by performing experiments on real-world benchmarks and on uniform parameter sets
The West Point Landscape: 1802–1830
Get PDFThis book chronicles the landscape history of the United States Military Academy\u27s first three decades. Major buildings at West Point are described and maps and illustrations highlight the changes made during the period.https://digitalcommons.usmalibrary.org/books/1043/thumbnail.jp
Cohesion in human–autonomy teams: an approach for future research
No full textCohesion is an important property of teams that can affect individual teammates and team outcomes. However, cohesion in teams that include autonomous systems as teammates is an underexplored topic. We examine the extant literature on cohesion in human teams, then build on that foundation to advance the understanding of cohesion in human–autonomy teams, both similarities and differences. We describe team cohesion, the various definitions, factors, dimensions and associated benefits and detriments. We discuss how that element may be affected when the team includes an autonomous teammate with each description. Finally, we identify specific factors of human–autonomy interaction that may be relevant to cohesion, then articulate future research questions critical to advancing science for effective human–autonomy teams. Relevance Statement: The human team literature has provided a foundation onto which human–autonomy team research can build, but the team dynamics, and subsequent states, established in multi-human teams are expected to differ in human–autonomy teams. This manuscript focuses on cohesion, one such state and synthesises elements of human team cohesion and human–autonomy interaction to detail expectations for cohesion in human–autonomy teams. These expectations can serve as a launch point for future research
Application of Topology Optimization to Design a Structural Panel Subjected to Blast Loading
No full textThe purpose of this study is to apply topology optimization to the design of a protective underbody panel for armored combat vehicles subjected to improvised explosive devices (IEDs). The increased use of IEDs by terrorist organizations over the last two decades has led to the death of thousands of soldiers and imposed critical damage to vehicles. There is interest in developing a protective panel that minimizes deflection and mass. The goal of this study is to design a lightweight, modular, and affordable panel, which provides increased protection to the vehicle occupants. Topology optimization may be used to create unique structures through a subtractive formulation. As additive manufacturing capabilities improve, topology optimization enables the design of efficient structures that are difficult to manufacture using traditional methods. Eight topology optimization studies were conducted and produced unique structural designs that were compared to established designs. The deflection, strain energy, and stress of optimized models from were compared to a hollow structural section (HSS) of equivalent mass and height. Results indicated the performance of optimized models were dependent on the topology optimization design goal. The methodology presented may be used in the future for projects which aim to minimize mass and maximize stiffness
Detecting and Classifying Self-Deleting Windows Malware Using Prefetch Files
No full textMalware detection and analysis can be a burdensome task for incident responders. As such, research has turned to machine learning to automate malware detection and malware family classification. Existing work extracts and engineers static and dynamic features from the malware sample to train classifiers. Despite promising results, such techniques assume that the analyst has access to the malware executable file. Self-deleting malware invalidates this assumption and requires analysts to find forensic evidence of malware execution for further analysis. In this paper, we present and evaluate an approach to detecting malware that executed on a Windows target and further classify the malware into its associated family to provide semantic insight. Specifically, we engineer features from the Windows prefetch file, a file system forensic artifact that archives process information. Results show that it is possible to detect the malicious artifact with 99% accuracy; furthermore, classifying the malware into a fine-grained family has comparable performance to techniques that require access to the original executable. We also provide a thorough security discussion of the proposed approach against adversarial diversity
System-of-Systems for Remote Situational Awareness: Integrating Unattended Ground Sensor Systems with Autonomous Unmanned Aerial System and Android Team Awareness Kit
No full textThis paper proposes a system-of-systems (SoS) consisting of a set of unattended ground sensor (UGS) system and a quadrotor unmanned aerial system (UAS) to detect and localize an object in a large area. In this work, acoustic and seismic sensors were employed to detect the physical presence of the object in the area being monitored. The directional information of the moving object was inferred from the simple geometry of the locations of these acoustic and seismic sensors. Communication from UGS system to quadrotor UAS was established via android tactical assault kit (ATAK). In addition, based on the message transmissions from the UGS system, ATAK was used to dispatch the quadrotor UAS to search, identify, and visualize the target and further obtain a more accurate target location. This work describes the integration of heterogeneous technology devices between UGS system and quadrotor UAS to provide humans with real-time visual information for remote situational awareness. Through the experiment, we validate the proposed system configurations and network architecture are viable and robust for use in the real-world application
Transfer Learning for Raw Network Traffic Detection
No full textTraditional machine learning models used for network intrusion detection systems rely on vast amounts of network traffic data with expertly engineered features. The abundance of computational and expert resources at the enterprise level allow for the employment of such models; however, these resources quickly dwindle in edge network scenarios. As Internet of Battlefield Things (IoBT) networks become common place in tactical environments, there is a need for improved and distributed models trained without these enterprise resources. Transfer learning – which allows us to take information learned in one domain and apply it to another – provides one way to create and distribute these models towards the edge. Using neural networks, we demonstrate the feasibility of transfer learning for intrusion detection using only raw network traffic in computationally limited environments. Our results show that with a transferred one-dimensional convolutional neural network model combined with a retrained random forest model, we obtain over 96% accuracy with only 5000 training samples on edge devices with an edge training time of approximately 67 s
Phenotypic differences between people varying in muscularity.
No full textBACKGROUND: Body mass is the primary metabolic compartment related to a vast number of clinical indices and predictions. The extent to which skeletal muscle (SM), a major body mass component, varies between people of the same sex, weight, height, and age is largely unknown. The current study aimed to explore the magnitude of muscularity variation present in adults and to examine if variation in muscularity associates with other body composition and metabolic measures.
METHODS: Muscularity was defined as the difference (residual) between a person\u27s actual and model-predicted SM mass after controlling for their weight, height, and age. SM prediction models were developed using data from a convenience sample of 492 healthy non-Hispanic (NH) White adults (ages 18-80 years) who had total body SM and SM surrogate, appendicular lean soft tissue (ALST), measured with magnetic resonance imaging and dual-energy X-ray absorptiometry, respectively; residual SM (SM
RESULTS: The SM, on average, constituted the largest fraction of body weight in men and women up to respective BMIs of 35 and 25 kg/m
CONCLUSIONS: Muscle mass is the largest body compartment in most adults without obesity and is widely variable in mass across people of similar body size and age; and high muscularity is accompanied by distinct body composition and metabolic characteristics. This previously unrecognized heterogeneity in muscularity in the general population has important clinical and research implications
Too Late for Russia to Stop the Foreign Volunteer Army
No full textThe Kremlin makes dark threats about the fate of foreign volunteers captured on the battlefield, but these are likely to rebound. Vladimir Putin’s war on Ukraine has produced some strange and unexpected results, not least the rush among Western citizens to join President Volodymyr Zelenskyy’sarmed forces