The proceedings contain 19 papers. The topics discussed include: a high performance computing framework for physics-based modeling and simulation of military ground vehicles;rolling partial prefix-sums to speedup eval...
ISBN:
(纸本)9780819486349
The proceedings contain 19 papers. The topics discussed include: a high performance computing framework for physics-based modeling and simulation of military ground vehicles;rolling partial prefix-sums to speedup evaluation of uniform and affine recurrence equations;accelerating sparse linear algebra using graphics processing units;high-level GPU computing with jacket for MATLAB and C/C++;roles and assessment methods for models of sensor data exploitation algorithms;multi-frame atmospheric compensation under moving camera conditions;power versus performance tradeoffs of GPU-accelerated backprojection-based synthetic aperture radar image formation;a hardware-in-the-loop simulation program for ground-based radar;an agile acquisition decision-support workbench for evaluating ISR effectiveness;modeling of hybrid organic/inorganic dual RF-photonic slot waveguide modulator;and improved representation of situational awareness within a dismounted small combat unit constructive simulation.
Robotic systems are no longer simply built and designed to perform sequential repetitive tasks primarily in a static manufacturing environment. systems such as autonomous vehicles make use of intricate machine learnin...
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Robotic systems are no longer simply built and designed to perform sequential repetitive tasks primarily in a static manufacturing environment. systems such as autonomous vehicles make use of intricate machine learning algorithms to adapt their behavior to dynamic conditions in their operating environment. These machine learning algorithms provide an additional attack surface for an adversary to exploit in order to perform a cyberattack. Since an attack on robotic systems such as autonomous vehicles have the potential to cause great damage and harm to humans, it is essential that detection and defenses of these attacks be explored. This paper discusses the plausibility of direct and indirect cyberattacks on a machine learning model through the use of a virtual autonomous vehicle operating in a simulation environment using a machine learning model for control. Using this vehicle, this paper proposes various methods of detection of cyberattacks on its machine learning model and discusses possible defense mechanisms to prevent such attacks.
High energy lasers (HELs) are evolving to provide an effective solution for air and missile defense. The emergence of this technology comes at a similar time to the development of cooperative and collaborative defense...
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High energy lasers (HELs) are evolving to provide an effective solution for air and missile defense. The emergence of this technology comes at a similar time to the development of cooperative and collaborative defensesystems that collect and communicate data to inform decisions. This paper proposes a stochastic jump method for modeling the performance of networked HELs, defending against aerial threats which follow a queueing methodology. By drawing on an existing method that quantifies performance using the sum of sojourn times in a stochastic jump process, the model can predict the probability of survival when multiple effectors are tasked in defending against an arbitrary number of threats. The model can be applied more generally to processes with both waiting time-dependent service and finite existence. Furthermore, a new HEL counteraction probability model is developed to enable the demonstration and comparison of three different system collaboration methods in a future warfare application. Results suggest the prevailing superimposing laser strategy may be less effective than simple one-to-one allocation of lasers to threats. There may also be merit in targeting separate components of a threat's structure.
This paper demonstrates an approach for the use of agent-based simulation, supported by model-based systems engineering products, to analyze interoperability. To demonstrate the approach, a representative maritime sea...
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This paper demonstrates an approach for the use of agent-based simulation, supported by model-based systems engineering products, to analyze interoperability. To demonstrate the approach, a representative maritime search-and-rescue (SAR) operation is simulated in the agent-based simulation program Map-Aware Non-Uniform Automata (MANA). The MANA SAR model is used to assess interoperability decisions at organizational, operational, and technical levels and to highlight dependencies between decisions at each level of interoperability. Analysis indicates that, within the MANA SAR model, organizational interoperability decisions have the largest impact on operational performance but that organizational challenges may be overcome with substantial investment at both the operational and technical levels of interoperability.
Fault-tolerance and dependable digital systems are now used in a diverse set of safety critical and cyber physical systems (CPSs) applications like healthcare instrumentation and control (I&C) devices, aerospace, ...
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Fault-tolerance and dependable digital systems are now used in a diverse set of safety critical and cyber physical systems (CPSs) applications like healthcare instrumentation and control (I&C) devices, aerospace, smart cities, and military systems. The architectural design principles required for achieving dependability in these systems vary as much as the safety-critical CPS system formal requirements and specifications. CPSs are composed of embedded hardware, specialized software, algorithms, and computation-based models interconnected to integrate computational and physical components. In this paper, we present the design, modeling and simulation of a reliable and secure microcontroller-based hardware architecture using a heterogenous design approach that combines concepts from computer-based architectural system design, state machine diagram, and traditional fault-tolerance, and defense in depth techniques. The proposed dependable architecture consists of a variety of software and hardware components: a sensing unit, a processing unit, and an actuating unit, interconnected to monitor the status of different physical quantities such as temperature, water and gas physical quantities. The simulation-based experimental results demonstrate the resilient operation of the proposed fault-tolerant hardware CPS system that achieves the highest reliability 0.999833345 with the failure-rate 0.03 failure per hour at the time equal to 15 min and how it is used in executing safety and security tasks. The reliability level of the TMR system remains high in the three different failure rate assumptions and is not less than 0.98. Consequently, we think that using such fault tolerant hardware architectures with the failure rate 0.03 failure per hour in embedded systems will lead to strengthen the reliability of next generation smart-home CPS applications.
Army senior military leaders are invested in acquiring modernized aerial platforms and equipment to augment the US Army's ability to overcome Anti-Access Area Denial (A2AD) threats imposed by modern Integrated Air...
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Army senior military leaders are invested in acquiring modernized aerial platforms and equipment to augment the US Army's ability to overcome Anti-Access Area Denial (A2AD) threats imposed by modern Integrated Air defensesystems (IADS). A prominent element of this modernization effort is the employment of autonomous drones to defeat IADS threats while minimizing risk to Army Soldiers. This research utilizes a framework for classifying the levels of autonomous capability along three dimensions: the ability to act alone, the ability to cooperate, and the ability to adapt. A virtual combat model, created using the Advanced Framework for simulation, Integration, and modeling (AFSIM), simulates the engagement between an enemy IADS and a friendly formation comprised of autonomous drones, attack helicopters, and a Long Range Precision Fires (LRPF) capability. A designed experiment evaluates drone performance with varying levels of autonomy. The experimental results reveal that low levels of autonomy yield a 20.74% increase in survivability and a 5.52% increase in lethality.
This article advances the geographic grid approach to military unmanned aircraft systems (UAS) routing featured in the existing literature. Its contributions are twofold. First, it demonstrates an empirical scoring sy...
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This article advances the geographic grid approach to military unmanned aircraft systems (UAS) routing featured in the existing literature. Its contributions are twofold. First, it demonstrates an empirical scoring system to determine the most important areas for maritime domain awareness-focused intelligence, surveillance, and reconnaissance collection, applying the method to the South China Sea. Second, it introduces what we call the "team orienteering problem with prize-dependent loitering times" (TOP-PDLT) and uses that model to identify optimal UAS collection routes in the South China Sea. Compared with other grid-based UAS routing schemes that use service time-dependent profits, TOP-PDLT is shown to be particularly applicable to military use-cases.
Kinetic modeling of biochemical reactions and bioreactor systems can enhance and quantify knowledge gained from cell culture experiments and has many applications in bioprocess design and optimization. The Microbial a...
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Kinetic modeling of biochemical reactions and bioreactor systems can enhance and quantify knowledge gained from cell culture experiments and has many applications in bioprocess design and optimization. The Microbial and Algal Growth modeling Application (MAGMA) is a user-friendly MATLAB-based software for streamlining the development of kinetic models for various bioreactor systems. This study details the MAGMA workflow by demonstrating the creation of kinetic models with systems of ordinary differential equations (ODEs), model fitting by solving inverse problems, statistical evaluation of model fitting quality, and visual display of simulation results. Two case studies (microalgae growth and Rhodococcus jostii plastic fermentation) have been provided to validate MAGMA applicability. It also includes a proof-of-concept for utilizing OpenAI GPT-4o's graph interpretation capability to automate tabulation of time course culture data from figures/plots in relevant literature, which can be used to calibrate model parameters. MAGMA is open source and compiled with MATLAB Runtime.
Discrete global grid systems (DGGS), which provide the reference framework for next-generation Digital Earth, recursively divide the Earth's surface into discrete multi-resolution hierarchies and support multi-sou...
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Discrete global grid systems (DGGS), which provide the reference framework for next-generation Digital Earth, recursively divide the Earth's surface into discrete multi-resolution hierarchies and support multi-source spatial data fusion and location-related event simulation. Existing DGGS research has primarily focused on cell centers, and therefore lacks rigorous mathematical modeling of multi-structural elements that comprise centers, edges, and vertices, resulting in inefficient data exchange and inaccurate data modeling. To this end, a unified mathematical modeling method was proposed for hexagonal multi-structural elements of grid systems based on triangles. The code operation principles and indexing conversion relationships for multi-structural elements were also deduced. The proposed method provides a unified mathematical model which reveals the mathematical essence of hexagonal multi-structural elements and has theoretical significance for future research on hierarchical data structures. Furthermore, conversion between multi-structural elements of triangles and hexagons, was achieved with low algorithmic complexity. Finally, the use of multi-structural elements can improve the accuracy of data modeling and spatial analysis, which has important applications for the representation of geospatial location data.
In this paper, an innovative discrete dynamical model is presented, which is used to predict the kind of strategic behavior the participants should adopt to win a battle. For study purposes, a computer model is develo...
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In this paper, an innovative discrete dynamical model is presented, which is used to predict the kind of strategic behavior the participants should adopt to win a battle. For study purposes, a computer model is developed to reveal the most critical factors that strategically affect combat and the relationship of dependence between the warring parties. Besides, it can predict the outcome of a battle under specific scenarios. Furthermore, the proposed dynamical system is applied in Midway's air-naval battle, which was one of the most decisive battles of World War II (WWII). It was a significant turning point in the history of naval warfare in the Pacific Ocean since the victory of the United States marked an end to Japanese expansionist policy, and these are the reason this battle was chosen. The numerical results of the analysis were presented, and the key factors (e.g., persons, decisions, and weather conditions represented by the critical values of model parameters) were highlighted, defining the outcome of the conflict.
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