Defense planning is a crucial part of the defense process. It identifies the capabilities required for the future defense environment, analyzes the capability shortfalls, prioritizes them, and provides the fundamental inputs for their development. Modeling and simulation may significantly contribute to the success of defense planning. However, neither the theory nor the tools are mature enough to fulfill the defense planning requirements. Various types of simulation tools, such as static, dynamic, deterministic, stochastic, closed, discrete, continuous, and symbiotic, in multiple levels of resolution and fidelity are needed to support the different stages and phases. The verification and validation of the models and the analysis of the input and output data are critical. Yet another challenge is that the uncertainties related to the contemporary defense scenarios are mostly not in aleatory but in the epistemic domain. In this paper, we briefly present a new computer-assisted defense planning process. Then, we introduce the service-oriented cloud approach for the modeling and simulation support to the process.
Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-defined network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. We conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.
Reverse engineering is a cyber defense task used to investigate malware, reconstruct functionality of compiled software, and identify vulnerabilities from closed-source software code already being used in operational contexts. While research in this area has mainly focused on techniques to extract information from binary code, it is also important to understand the capabilities and limitations of the human involved in the reverse engineering process (both defensively and offensively), so we can design better information representations and effectively allocate appropriate tasks to autonomous agents. In this paper, we describe our introductory work in developing agent models of reverse engineering. We review what is known about reverse engineers’ mental models, then describe and characterize four human–computer interaction patterns involved in reverse engineering from a cognitive task analysis. Finally, we present a category theoretic model to describe how reverse engineers trace information flow when performing static analysis. Our approach is a first step in modeling, simulating, and optimizing the human interaction components of these tasks to increase the speed, scale, and accuracy of cyber defense efforts.
Modern missions of government and private organizations rely on computer networks to operate. As evidenced by several well-publicized cyber breaches, these missions are under attack. Several cyber defensive measures have been proposed to mitigate this threat, some are meant to protect individual hosts on the network, and others are designed to protect the network at large. From a qualitative perspective, these mitigations seem to improve security, but there is no quantitative assessment of their effectiveness with respect to a complete network system and a cyber-supported mission for which the network exists. The purpose of this paper is to examine network-level cyber defensive mitigations and quantify their impact on network security and mission performance. Testing such mitigations in an live network environment is generally not possible due to the expense, and thus a modeling and simulation approach is utilized. Our approach employs a modularized hierarchical simulation framework to model a complete cyber system and its relevant dynamics at multiple scales. We conduct experiments that test the effectiveness of network-level mitigations from the perspectives of security and mission performance. Additionally, we introduce a novel, unified metric for mitigation effectiveness that takes into account both of these perspectives and provides a single measurement that is convenient and easily accessible to security practitioners.
Full-mission simulators (FMSs) are considered the most critical simulation tool belonging to the flight simulator family. FMSs include a faithful reproduction of fighter aircraft. They are used by armed forces for design, training, and investigation purposes. Due to the criticality of their timing constraints and the high computation cost of the whole simulation, FMSs need to run in a high-performance computing system. Heterogeneous distributed systems are among the leading computing platforms and can guarantee a significant increase in performance by providing a large number of parallel powerful execution resources. One of the most persistent challenges raised by these platforms is the difficulty of finding an optimal mapping of n tasks on m processing elements. The mapping problem is considered a variant of the quadratic assignment problem, in which an exhaustive search cannot be performed. The mapping problem is an NP-hard problem and solving it requires the use of meta-heuristics, and it becomes more challenging when one has to optimize more than one objective with respect to the timing constraints. Multi-objective evolutionary algorithms have proven their efficiency when tackling this problem. Most of the existent works deal with the task mapping by considering either a single objective or homogeneous architectures. Therefore, the main contribution of this paper is a framework based on the model-driven design paradigm allowing us to map a set of intercommunicating real-time tasks making up the FMS model onto the heterogeneous distributed multi-processor system model. We propose a multi-objective approach based on the well-known optimization algorithm "Non-dominated Sorting Genetic Algorithm-II" satisfying the tight timing constraints of the simulation and minimizing makespan, communication cost, and memory consumption simultaneously.
Modeling and simulation continues to improve the ability to evaluate future complex concepts and conduct early systems analysis. While the systems engineering community now advocates model-based systems engineering, the actual integrated methods and tools need to be refined. This research synthesizes descriptive architectural depictions of multi-domain (air and space) concepts, simulates these concepts through a physics-based model, collects several performance metrics, and integrates them using value-focused thinking. The proposed method enables the assessment of alternatives whose value can increase or decrease over time, depending on the design properties and operational scenario. Three surveillance concepts are proposed, made up of a low-earth orbit satellite constellation, with varying payloads, and extended by an unmanned air system flying waypoints in the area of interest. Uniquely, this method shows promise of depicting time-variant value assessments of these concepts across the simulation.
Medical readiness requires Department of Defense medical clinics to be robust to changes in patient demand. Minor fluctuations in patient demand occur on a regular basis, but major increases can also occur. Major demand increases can result from a number of occurrences, including mass military deployments, medical incidents, outbreaks, and overflow from Veterans’ Affairs clinics. This research evaluates a system of clinics at Wright-Patterson Air Force Base in order to determine its ability to handle a 200% surge in patient demand. In addition, this study evaluates the relative effectiveness of six different staffing mix options to minimize patient wait times, also under the surge demand conditions. This evaluation is conducted using discrete-event simulation to estimate patient wait times and includes a sensitivity analysis of the increased patient demand, as well as a cost–benefit analysis to determine the most cost-effective alternative scenario. The study finds that adjustments to staffing mix enable cost savings while meeting current demands. In addition, the study finds that adjusting the staffing mix will not have a negative impact on patient wait time in the surge conditions, relative to the current staffing mix.
The Army and Marine Corps have a need to increase infantry squad capabilities to improve tactical effectiveness while managing casualties. The Squad Overmatch (SOvM) project focused on the development and execution of a curriculum to incorporate Tactical Combat Casualty Care (TC3) coordination and decision-making into squad-level training, expanding a 2013 effort to enhance existing training methods and technologies with more realistic combat exercises and experiences. An integrated training approach (ITA), including knowledge and skills training for improving advanced situational awareness (ASA), resilience, TC3, medical skills/decision-making, and team performance was developed to help teams make better decisions from a tactical and teamwork perspective. Squads received foundation training in an instructor-led classroom setting, and then were given practice opportunities in scenario-based gaming and live scenarios. The ITA was designed to allow TC3 providers and squad leadership to practice and improve targeted skills in unit-level casualty scenarios balancing tactical and medical requirements. This paper examines the degree to which the ITA scenario training technologies provided the fidelity necessary to support SOvM-TC3 learning objectives. The results allow training designers to carefully assess how different technologies can impact training effectiveness.
We describe a class of quantum algorithms to generate models of propositional logic with equal probability. We consider quantum stochastic flows that are the quantum analogues of classical Markov chains and establish a relation between fixed points on the two flows. We construct chains inspired by von Neumann algorithms using uniform measures as fixed points to construct the corresponding irreversible quantum stochastic flows. We formulate sampling models of propositions in the framework of adiabatic quantum computing and solve the underlying satisfiability instances. Satisfiability formulation is an important and successful technique in modeling the decision theoretic problems in a classical context. We discuss some features of the proposed algorithms tested on an existing quantum annealer D-Wave II extending the simulation of decision theoretic problems to a quantum context.
Humeral head intraosseous (HHIO) infusion is the process of injecting fluids directly into the marrow of the humerus, or upper arm bone, to provide a non-collapsible entry point into the circulatory system. This technique provides fluids and medication quickly when intravenous (IV) access is not feasible in emergency situations. As of 2010, Tactical Combat Casualty Care guidelines recommend using intraosseous (IO) infusion in any resuscitation scenario where IV access is not feasible. The US Army Center for Pre-Hospital Medicine (CPHM) provides pre-deployment training to Roles I, II, and III medical providers. In addition, the CPHM provides training for deploying Forward Surgical Teams and en route care via the Critical Care Flight Paramedic Program. The Army’s Program of Instruction currently lacks an adequate simulation-based training model for the HHIO procedure and relies on live tissue training. The US Army Research Laboratory, Human Research and Engineering Directorate, Advanced Training and Simulation Division, developed a capability (i.e., Partial Task Trainer, or PTT) to train this procedure. This study assessed the usability of the PTT device for training on the IO procedure. Specifically, this paper seeks to identify statistically significant differences among the usability ratings of the PTT for paramedics and emergency medicine physicians.
Although studies on simulation of rare complications have become more common in the trauma and obstetric literature, there is a paucity of studies on simulation of rare laparoscopic emergencies. High-fidelity models, virtual reality systems, and porcine labs are available; however, their cost limits wider use and repetition of skills. A low-cost, laparoscopic entry and emergency model was created using on-hand base parts. A convenience sample of obstetrics/gynecology and general surgery residents and attending surgeons completed a laparoscopic entry and emergency scenario using an innovative model in the multidisciplinary simulation center. A total of 29 gynecology, urology, and general surgery residents, fellows, and attending surgeons participated in the laparoscopic emergency simulation drill. Of the 29 participants of the laparoscopic emergency simulation drill using the model, 27 (93.1%) agreed or strongly agreed that the simulated drill approximates the stress of a vascular injury during laparoscopy and 27 (93.1%) agreed or strongly agreed that the model set up appears appropriate for approximating a retroperitoneal hematoma. The reusable, laparoscopic simulation model and emergency drill were rated favorably by participants. The model and drill have the potential to be used for multidisciplinary drills that include anesthesiologists, surgical nurses, surgical technologists, and surgeons.
Unmanned systems, with and without a human-in-the loop, are being deployed in a range of military and civilian applications spanning air, ground, sea-surface and undersea environments. Large investments, particularly in robotics, electronic miniaturization, sensors, network communication, information technology and artificial intelligence are likely to further accelerate this trend. The operation of unmanned systems, and of applications that use these systems, are heavily dependent on cyber systems that are used to collect, store, process and communicate data, making data a critical resource. At the same time, undesirable elements of our society and adversarial states have also realized the high value of this resource. While enormous efforts have been made to secure data and cyber systems, lack of rigorous threat modeling and risk analysis can lead to more specific, rather than generic, security solutions relevant to the cyber system to be protected. This scenario has created an urgent need to develop a holistic process for protecting data and cyber systems. This paper deals with the development of different pieces of this process. We first identify the security requirements of unmanned autonomous systems, and follow this up with modeling how attacks achieve their objectives. We argue that a large number of threats that can materialize as attacks and the costs of managing these attacks in cost effective ways require ranking threats using cyber threat modeling and cyber risk analysis techniques. The last segment of the paper describes a structured approach to mitigate high-risk threats.
The federal aviation administration has estimated that by the year 2020, the United States will have over 30,000 drones. Nowadays, drones, also known as unmanned aerial vehicles (UAVs), are ubiquitous and have numerous uses beyond military applications. This is because UAVs can be used in hazardous missions, since they exclude the risk factors involved in manned vehicles. Despite their benefits, UAVs are prone to attacks as they are equipped with numerous on-board sensors to gather data and this exposes them to various vulnerabilities. More precisely, in the absence of manual control, an attacker can gain access to sensitive sensory data and feed fraudulent information to the UAV. As a result, it can be reprogrammed to an undesirable effect and this can cause irreversible damage. This paper provides a general overview of current hacking methods, and defense and trust strategies to overcome cyber attacks on UAVs. To further highlight the importance of the requirement of developing new methods to avoid any intrusion, a hacking procedure is implemented on a commercially available UAV and its severe results are demonstrated. It is shown that the hacker can make irreparable damage and take complete control over the UAV by compromising the communication link between the operator and UAV and uses Robot Operating System-based tools to alter the flight path.
Military air forces have a significant demand for fuel, but increasing costs force them to use their fuel as efficiently as possible. We investigated the suitability of Data Envelopment Analysis (DEA) to measure C-17 airlift fuel efficiency for the United States Air Mobility Command (AMC). Airlift missions constitute the decision-making units in our study. Seven respective inputs and outputs were used and three different DEA models were contrasted. The results show that DEA provides an effective ability to identify fuel usage inefficiencies. A slack-based DEA measure proved superior at differentiating inefficiencies to an established index in use by AMC planners.
The United States Department of Defense medical planners need survival-time estimates for anticipated patient streams associated with projected combat scenarios. Survival-time estimates should be grounded in empirical observations. Unfortunately, research in this domain has been limited to a single paper describing the development of died-of-wounds curves for combat casualties with life-threatening injuries. The curves developed from that research were based on a small dataset (n = 160, with 26 deaths and 134 survivors) of forward surgical (Role II) casualties and subject matter experts’ judgments. This paper reports the first empirically based time-to-death curves for combat casualties based on a large sample. The results indicate that survival time varied across roles of care at which casualties died but was at most weakly associated with injury severity. Time-to-death curves were, therefore, developed for the overall study population of valid times to death and for Role I, Role II and Role III care. The log-logistic probability distribution provided the best representation of the survival times for the overall study population, while the log-normal distribution was the best choice for Role I, Role II and Role III care. The proposed time-to-death curves should refine the survival-time estimates used in combat medical logistics planning.
This paper describes distributed simulation of MIL-STD-1553B Serial Data Bus interface and protocol based on the Data Distribution Service (DDS) middleware standard. The 1553 bus connects avionics system components, and transports information among them in an aircraft. It is important for system designers to be able to evaluate and verify their component interfaces early in the design phase. The 1553 data bus requires specialized hardware and wiring to operate; thus it is complicated and expensive to verify component interfaces. Therefore modeling the bus on commonly available hardware and networking infrastructure is desirable for early evaluation and verification of designed interfaces. The DDS middleware provides publish/subscribe based communications and facilitates the implementation of distributed systems by providing an abstraction layer over the networking interfaces of the operating systems. This work takes the advantage of the DDS middleware to implement an extensibility 1553 serial data bus simulation tool. The tool is verified using a case study involving a scenario based on the MIL-STD-1760 standard.
This paper reports important parameters that affect water ricochet studies for artillery projectiles. The factors affecting ricochet are critical angle and critical velocity of impact. This study has developed mathematical models for ricochet studies and derived expressions for critical angle and critical velocity. Simulations have been carried out for standard bullets, the data for which are available in open literature. The effects of mass, diameter, and length of the projectile on critical velocity and angle are studied through two non-dimensional parameters, µ and . The results suggest how ricochet conditions can be avoided by defining initial data at launch.
There has been much attention for many years on reducing U.S. fuel imports in order to improve energy independence. The transportation sector is one of the most important components with its share of 28% of total U.S. energy consumption. In this research, compressed natural gas (CNG) is examined as an alternative fuel for the U.S. transportation sector. To be able to answer this question it is essential to understand both the supply and demand sides of the problem. This research aims to exhibit the availability and adequacy of CNG as a full or partial fuel replacement for U.S. transportation sector needs, the factors that prevent CNG from being a widely used transportation fuel, the cost–benefit of using CNG as a vehicle fuel, and feasible changes to make CNG more cost effective. In conjunction with putting forth this information for consideration, the best short- and long-term scenarios for CNG use in the transportation sector, provided through the application of analytic hierarchy process (AHP), is proposed.
In the effort to provide electrical power service and the sustaining fuel required to run generators at forward-deployed bases in Afghanistan and Iraq over more than 10 years, the US military spent billions of dollars and a paid a heavy toll in terms of human casualties. The green energy linear program for optimizing deployments (GELPOD) proof-of-concept model showed that a linear program could be used to optimize combat deployment of energy generation systems to minimize cost and casualties. Results indicated that reduction in both cost and casualties for renewable energy sources was highly dependent on fuel cost and deployment length. Neglected in the decision making process, however, were factors that impact the operational success of the mission. When deploying combat units, commanders must not only consider potential costs and casualties, they must also contend with battlefield mobility requirements, maintenance capability (or lack thereof), weather, and anticipated hostile action that could affect operational performance. This paper leverages the simple multi-attribute rating technique (SMART), pioneered by Edwards, to attempt to address this deficiency. The resulting simple multi-attribute rating technique for renewable energy deployment decisions (SMART REDD) model allows commanders to take mission attributes into consideration when making decisions on which energy source is most appropriate for the mission as well as providing information on operations costs, expected transportation requirements, and expected casualties.
The article presents a concept of design, using the methods of simulation results, automatic analysis, and taking into account expert knowledge, and visualization of communication problems in the developed Tactical Player. The main emphasis is on the segment of simulation results evaluation on the basis of fuzzy sets, from which we have developed rules, the combination of which is used for evaluation of the quality of communication parameters between tactical radio stations. A special note should also be taken of the concept of modeling a tactical radio network and its characteristics, the mode of communication between radio stations, hierarchic organization, the problems of manual analysis of simulation results, etc. We present our solution for automatic analysis and the solution for visualization of problematic segments in the course of communication. The reader is acquainted with the problems of wireless communications and the key parameters influencing the connection between communicating entities, such as radio visibility, message transfer success, packet loss, deterioration of the signal–noise relation, etc. Because visualization of problematic time frames of the simulated communication on a virtual simulation field directly depends on the automatic analysis precision, we also used mathematical procedures (probability theory and possibility theory) as the basis of the fuzzy logic used. For a better understanding of the modeled prototype’s functioning, we also include a block scheme in the form of a process scheme, on the basis of which we can show the segments that are new and are a scientific contribution in the field of simulation techniques.
On the modern battlefield cordon and search missions (also known as village searches) are conducted daily. Creating resource allocations that link search teams (e.g. soldiers, robots, unmanned aerial vehicles, military working dogs) to target buildings is difficult and time consuming in the static planning environment and is even more challenging in a time-constrained dynamic environment. Conducting dynamic resource allocation during the execution of a military village search mission is beneficial especially when the time to develop a static plan is limited and hence the quality of the plan is relatively poor. Dynamic heuristics can help improve the static plan because they are able to incorporate current state information that is unavailable prior to mission execution and thus produce more accurate results than static heuristics alone can achieve. There are currently no automated means to create these dynamic resource allocations for military use. Using robustness concepts, this paper proposes and compares dynamic resource allocation heuristics that create mission plans that are resilient against uncertainty in the environment and that save valuable time for military planning staff.
In a social network analysis the output provided includes many measures and metrics. For each of these measures and metrics, the output provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning disrupting or deceiving a given network. All is fine when all the measures indicate the same node as the key or influential node. What happens when the measures indicate different key nodes? Our goal in this paper is to explore two methodologies to identify the key players or nodes in a given network. We apply two procedures to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We use data envelopment analysis as a method to optimize efficiency of the nodes over all criteria and use the analytical hierarchy process (AHP) as a process to consider both subjective and objectives inputs through pairwise comparison matrices. We illustrate our results using two common networks from the literature: the kite network and the information flow network. We discuss some basic sensitivity analysis that can be applied to the methods. We find the AHP method as the most flexible method to weight the criterion based upon the decision makers’ inputs or the topology of the network.
Fuel conservation and carbon reduction are important issues in current naval operations. Optimal ship route (i.e. minimum fuel consumption) depends on specific ship platform characteristics and near real-time environment such as weather, ocean waves, and ocean currents. The environmental impact of shipping can be measured on different spatial and temporal scales. As a vital component of the smart voyage planning (SVP) decision aid, the US Navy’s meteorological and oceanographic (METOC) forecast systems play an important role in optimal ship routing, which enables fuel savings in addition to the aid of heavy weather avoidance. This study assesses the impact of METOC ensemble forecast systems on optimal ship route. Tests of the SVP decision aid tool are also conducted for operational fleet use and concept of operations for the USS Princeton guided missile cruiser (CG)-59 in a sea trial test following the 2012 Rim of the Pacific exercises.
The increased focus of the United States Department of Defense (DoD) on irregular warfare and counterinsurgency has served to identify the lack of credible models and simulations to represent the relevant civilian populations – the centers of gravity of such operations. While agent-based models (ABMs) have enjoyed widespread use in the social science community, many senior DoD officials are skeptical that agent-based models can provide useful tools to underpin DoD analysis, training, and acquisition needs mainly because of validation concerns. This paper uses docking and other forms of alignment that enable the linking of the Epstein civil violence agent-based model results to other models. These examples of model-to-model analysis could serve to assist and encourage DoD ABM human domain model validation efforts.
Fuel requirements on the battlefield impose direct costs associated with the resources necessary to transport the fuel and protect logistics assets, in addition to indirect energy security costs. Estimating the enterprise-wide demand for fuel associated with fuel consumption on the battlefield is a challenging, but necessary, step to making good decisions. This paper presents a modeling framework for estimating the enterprise-wide fuel requirements associated with a multistage fuel supply chain, demonstrating a multiplicative increase in fuel demand with additional stages, and examining the fuel impact of protecting the supply chain.
Deploying flare decoys against heat-seeking threats involves various parameters such as flare timing, flare ejection velocity, direction of ejection and the number of flares used. In this study, an attempt has been made to identify the key parameters among these that impact the performance of flares the most. For this, engagement studies involving six-degrees-of-freedom models for an air-to-air heat-seeking missile and a fighter aircraft were carried out using the CADAC++ simulation environment. The effect of flare parameters was studied using their impact on missile envelopes. Studies show that the effectiveness of the flare decoys is a strong function of the flare timing and the number of flares used.
Among top-level defense managers, there is a general belief that a better information system should be able to resolve the endemic problem of lapsed funding, that is, funding that goes unspent at the end of a fiscal year. We argue against this point of view by modeling the decision process for activity expenditures as a two-stage process where some of the cost uncertainty is resolved before the end of the year. Our main result is that an improved information system cannot eliminate lapsed funding, and may in fact have very little impact at all.
We consider an Approximate Dynamic Programming heuristic to support the selection of defense projects when projects have different values and are originated intermittently but fairly frequently. We show that a simple policy reserving a positive fraction of the available budget for high-value projects not yet originated is superior to a greedy knapsack approach.
This paper addresses the constraints preventing full utilization of an aircraft’s cargo compartment. The fact that many sorties are flown with less than the maximum allowable weight or volume results in more airlift sorties being required to move the same amount of cargo. Various solutions are investigated to more efficiently fill the volume while simultaneously maximizing against the weight constraint. Solving the problem of the inefficient utilization of the airlift cargo compartment space can increase aircraft and aircrew availability, reduce fuel consumption for a given level of output, and reduce the number of flights required into constrained airfields. We recommend a pallet stacking solution moving cargo from Dover Air Force Base to Ramstein Air Force Base that we estimate would reduce C-17 sorties 31.4% when aggregated over a three calendar day period saving over eight million dollars per year.
Given finite resources, organizations are in a constant struggle to satisfy conflicting demands for resource allocation. Finding the right number of response units needed to respond to an incident in a given area is one such problem. Different geographical areas have different characteristics that further complicate the problem. For example, Canada’s Arctic waters is a large area with many islands and where varying ice coverage conditions are the norm. These impediments complicate what would otherwise be a straightforward application of the Circle Packing or Circle Covering Problem. The authors propose to call such a problem the Impediment Induced Variable Shape Covering Problem and present the Incident Response Model that determines the minimum number of units needed to respond to an incident anywhere in a given Area of Interest within a predetermined response time while avoiding or accounting for impediments.
Past research has shown that multi-modal sensory cues can reduce the workload of the user while simultaneously increasing performance capacity. This study looks to examine how performance is impacted in a multi-modal sensory cueing target detection task in which the cueing automation is imperfect. Twenty-seven undergraduate participants volunteered to take part in the present multi-modal sensory automation target detection task. The independent variables were trial (i.e., three five-minute trial blocks) and the cueing method (i.e., tactile, auditory or a combination of tactile and auditory cueing) used to assist visual search for target detection across three screens. Dependent variables included each participant’s response time and rate of accuracy. Results illustrate a significant decrease in response in the final trial when compared with the first trial. Results also illustrated a decrease in response time in each successive trial compared with the previous, each reflective of learning effects. A one-trial block exposure (5 minutes) to imperfect automation resulted in a response time decrease of 24%, while a two-trial block exposure (10 minutes) resulted in a response time decrease of 38%. Errors of omission results showed significantly lower miss rates in the final trial block when compared with the first trial block. In addition, errors of omission were lower in each successive trial compared with the previous. A one-trial block exposure (5 minutes) to imperfect automation resulted in a decrease in misses of 45%, while a two-trial block exposure (10 minutes) to imperfect automation resulted in a decrease of 65% in such misses. Our results suggest that interchanging multi-modal cues create stronger learning trends in a human–automation system than uni-modal cues. Results also showed that in spite of the automation used, automation failure resulted in a significant performance decrement. Auditory automation cueing failure produced a sevenfold increase in response time, while tactile automation cueing failure and a combination of auditory and tactile automation cueing failure produced a fourfold increase in response time. A speed–accuracy trade-off is not the cause of these results, because auditory automation cueing failure produces a twofold decrease in accuracy, and a combination of auditory and tactile automation cueing failure produced a threefold decrease in accuracy.
The cost of a single zero-day network worm outbreak on the global Internet has been estimated at US$2.6 billion. In addition, zero-day network worm outbreaks have been observed that spread at a significant pace across the Internet, with an observed infection proportion of more than 90% of vulnerable hosts within 10 minutes. The threat posed by such fast-spreading malware to defence systems and national security is therefore significant, particularly given the fact that network operator/administrator intervention is not likely to take effect within the typical epidemiological timescale of such infections.
An accepted technology that is used to research the security threat presented by zero-day worms is that of simulation systems; however, only a subset of these focus on the Internet and issues persist regarding how representative these are of the Internet. The design of a novel simulator developed to address these issues, the Internet Worm Simulator (IWS), is presented along with experimental results for a selection of previous worm outbreaks compared against observed, empirical data and hypothetical outbreak scenarios. Based on a finite state machine for each network host, the IWS incorporates the dynamic, heterogeneous characteristics of the Internet and, on a single workstation, is able to simulate an IPv4-sized network.
Based on the analysis presented, the authors conclude that the IWS has the capability to simulate zero-day worm epidemiology on the dynamic, heterogeneous Internet for a variety of scenarios. These include simulating previous worm outbreaks that demonstrate random-scanning and hit list behaviour, as well as hypothetical scenarios that include a large susceptible populous and stealth-like behaviour.
This paper describes building information modeling (BIM) research by students and faculty of the University of Nebraska’s Peter Kiewit Institute (PKI). The paper also describes work in conjunction with the United States Strategic Command (USSTRATCOM), located at Offutt Air Force Base in Omaha, Nebraska, USA. The objective of this on-going research is to create a virtual modeling environment where architects and planners can present building concepts and design options to customers in a way that is more easily envisioned by the client. The proposed environment would integrate BIM and virtual environments by allowing a free exchange of data between applications. The specific research mentioned in this paper focuses on visualization and editing of interior room configurations for use by USSTRATCOM. The software used for this research project was Autodesk® Revit, Autodesk® 3DS Max, and a proprietary gaming engine called Unity, developed by Unity Technologies and based in San Francisco, California, USA. This paper covers the development of a system architecture in which BIM will be integrated with a virtual simulation environment built in Science Applications International Corporation’s (SAIC’s) On-Line Interactive Virtual Environment (OLIVE) and discusses research results to date.
The engineering community faces multiple challenges as it moves toward a future that will consist of virtual reality, model-based enterprises, and a heavy reliance on simulation for requirements development, design, manufacturing, assembly, and training for future products. The focus on model-based activities (e.g. design, systems engineering, manufacturing) is seen as a way to better reuse knowledge, ensure higher quality, and reduce costs through virtual design and testing. However, the combination of discipline-focused decomposition, the functional to physical progression, proprietary data formats, and poor communication between disciplines due to different language and contexts leads to longer development times, increased rework, and a failure in product realization. Raytheon has been researching aspects of this future, targeted at shortening the product development lifecycle by an order of magnitude. One such recent Raytheon-funded study has indicated that a potentially more complete approach might be to address the problem from an information sciences perspective and the adoption of "product" models as the primary representation. In particular, the development of a workable rapid engineering environment will require an information architecture-leveraging product ontology designed specifically for this type of approach.
Quantum Key Distribution (QKD) is a revolutionary security technology that exploits the laws of quantum mechanics to achieve information-theoretic secure key exchange. QKD enables two parties to "grow" a shared secret key without placing any limits on an adversary’s computational power. Error reconciliation protocols have been developed that preserve security while allowing a sender and receiver to reconcile the errors in their respective keys. The most famous of these is the Cascade protocol, which is effective but suffers from a high communication complexity and low throughput. The Winnow protocol reduces the communication complexity over Cascade, but has the disadvantage of introducing errors. Finally, Low Density Parity Check (LDPC) codes have been shown to reconcile errors at rates higher than those of Cascade and Winnow, but with greater computational complexity. In this paper we evaluate the effectiveness of LDPC codes by comparing the runtime, throughput and communication complexity empirically with the Cascade and Winnow algorithms. The effects of inaccurate error estimation, non-uniform error distribution and varying key length on all three protocols are evaluated for identical input key strings. Analyses are performed on the results in order to characterize the strengths and weaknesses of each protocol.
Extraction of energy from the trailing wakes of aircraft is discussed. The objective is to reduce the fuel burn for trailing aircraft in a formation. Past formation flight experiments showing the feasibility of the concept are reviewed. Results from a series of C-17 mission simulations are shown that provide fuel savings estimates for various mission lengths. The effects of operational constraints such as holding times for landing and formation joining, fuel reserve requirement, and spacing between origin and destination bases are also shown.
A requirement of an Agent-based Simulation (ABS) is that the agents must be able to adapt to their environment. Many ABSs achieve this adaption through simple threshold equations due to the complexity of incorporating more sophisticated approaches. Threshold equations are when an agent behavior changes because a numeric property of the agent goes above or below a certain threshold value. Threshold equations do not guarantee that the agents will learn what is best for them. Reinforcement learning is an artificial intelligence approach that has been extensively applied to multi-agent systems but there is very little in the literature on its application to ABS. Reinforcement learning has previously been applied to discrete-event simulations with promising results; thus, reinforcement learning is a good candidate for use within an Agent-based Modeling and Simulation (ABMS) environment. This paper uses an established insurgency case study to show some of the consequences of applying reinforcement learning to ABMS, for example, determining whether any actual learning has occurred. The case study was developed using the Repast Simphony software package.
Since 2000, claims of hearing loss by warfighters have doubled. It is the most frequently identified combat-related disability. Conventional audibility enhancement relies heavily on hearing aids, which do not provide sufficient sound intelligibility for a sizable subset of the hearing-impaired population. For them, there is a surgical option called a ‘cochlear implant’, a device which bypasses the damaged portions of the inner ear (cochlea) and provides direct neural stimulation. In this paper, we review the current state of the art in hearing aids and cochlear implants. A new device which has the potential for high spectral and temporal fidelity, the optical cochlear implant, is currently being tested in the laboratory. The projected development timeline spans many years: from point testing in the laboratory, through the approval process for limited human testing, with control gates for application to human candidates. A model-based development approach could potentially shorten this timeline. In this paper, we describe models and simulations that we developed to extend laboratory measurements in order to evaluate intelligibility impacts. Specifically, we describe our development of the Cochlear Laser Transduction Model, a physics-based simulator that evaluates tonotopic specificity; the Optical Cochlear Implant Simulator (OCIS), which can extend the laboratory measurements via simulation using the results of the Cochlear Laser Transduction Model; and the configuration of an off-the-shelf speech recognition tool to quickly assess intelligibility impacts, predicting system level impacts of varying optical cochlear implant design parameters. Results from the system-level modeling and simulation approach indicate that significant intelligibility improvements could be realized with the optical cochlear implant, with potential to offer upwards of 40 channels of spectral resolution compared with 10 channels with electrode-based implants.
Systems engineering (SE) addresses the six interrogatives who, what, where, when, why, and how. Architecture artifacts provide static descriptions addressing the first three interrogatives: who, what, and where. Executable architectures add the interrogative when, allowing for a dynamic evaluation of system performance. We propose an approach that takes the evaluation process further by addressing the final interrogatives why and how: embedding executable system architectures into an executable context (EC), creating a scenario in which to evaluate the system in the operational role and evaluate mission effectiveness. Combining existing contributions into an executable context simulation framework allows for a holistic evaluation of systems that are models based on engineering specifications in operationally relevant contexts. We have successfully implemented a prototype to demonstrate feasibility and usefulness of this recommended new approach.
Social network analysis (SNA) is a rapidly growing field with numerous applications in industry and government. However, the field still lacks means to generate random social networks with certain desired properties, thus inhibiting their ability to test new SNA algorithms and metrics. Available random graph generation algorithms suffer from tendencies to generate disconnected graphs and sometimes induce undesirable network properties. In this paper, we present an algorithm, the prescribed node degree, connected graph (PNDCG) algorithm, designed to generate weakly connected social networks. Extensions to the PNDCG algorithm allow one to create random graphs that control the clustering coefficient and degree correlation within the generated networks. Empirical test results demonstrate the capability of the PNDCG algorithm to produce networks with the desired properties.
A survivability model can be a useful component of a tactical support system able to aid fighter pilots to assess the risk of getting hit by enemy fire from ground-based threats. This work identifies three desirable properties of such a model: it should allow for evaluating actions; it should enable domain experts to incorporate their knowledge; and it should represent uncertainties both regarding the locations of the threats as well as their future actions. A survivability model is suggested, which calculates the probability that the aircraft can fly a route unharmed and allows for routes of different lengths to be compared. A domain expert can describe the threats by specifying the risk of getting hit at a position of the route without having to consider the earlier actions of the aircraft and the threats. Three different threat models are suggested and compared. The influence of uncertainties regarding the positions of the threats is studied by calculating the probability density function for the survivability. Different representations that take into account both the uncertainty regarding the present and future situation are discussed. The results indicate that the suggested survivability model could be a useful component of a future tactical support system, even though some further development is needed.
To support the missions and tasks of mixed robotic/human teams, future robotic systems will need to adapt to the dynamic behavior of both teammates and opponents. One of the basic elements of this adaptation is the ability to exploit both long- and short-term temporal data. This adaptation allows robotic systems to predict/anticipate, as well as influence, future behavior for both opponents and teammates and will afford the system the ability to adjust its own behavior in order to optimize its ability to achieve the mission goals. This work is a preliminary step in the effort to develop online entity behavior models through a combination of learning techniques and observations. As knowledge is extracted from the system through sensor and temporal feedback, agents within the multi-agent system attempt to develop and exploit a basic movement model of an opponent. For the purpose of this work, extraction and exploitation is performed through the use of a discretized two-dimensional game. The game consists of a predetermined number of sentries attempting to keep an unknown intruder agent from penetrating their territory. The sentries utilize temporal data coupled with past opponent observations to hypothesize the probable locations of the opponent and thus optimize their guarding locations.
Field experiments were used to evaluate three different indirect fire models: the cookie cutter and the Carleton damage functions and a simplified physical model for fragmenting ammunition. Data from three field tests, in which a total of 66 mortar bombs (120 mm high explosive) were fired in flat terrain, is used for validation.
The results imply that no universal parameters, that would fit the results, can be found for the damage function models while the physical model predicted the field test results consistently without parameter fitting.
The US Department of Defense (DoD) requires all models and simulations that it manages, develops, and/or uses to be verified, validated, and accredited. Critical to irregular warfare (IW) modeling are interactions between combatants and the indigenous population. Representation of these interactions (human behavior representation (HBR)) requires expertise from several of the many fields of social science. As such, the verification, validation, and accreditation (VVA) of these representations will require adaptation and, in some cases, enhancement of traditional DoD VVA techniques. This paper suggests validation best practices for the DoD modeling community to address new challenges of modeling IW.
The research proposes the development of a simulation framework for assessing the effectiveness and efficiency of different alternative command, control, communications and computers (C4) solutions in an urban environment affected by asymmetric warfare. The authors present their approach in developing intelligent agents computer-generated forces (IA-CGF) in a non-conventional framework related to the project named CGF C4 IT. In the current military context, characterized by new asymmetric threats (i.e. terrorism, biological attacks) and affected by new technologies solutions, it is critical to measure the effectiveness of different command and control (C2) maturity models involving local and coalition forces, police and other resources in an overseas urban framework. As a matter of fact, this is one of the main goals of the CGF C4 IT project which is devoted to investigating alternative C2 models for guaranteeing agility in complex scenarios. The CGF C4 IT federation is a high level architecture simulator, designed by the authors, and currently devoted to supporting Italian Army simulation capabilities. This represents an innovative and effective solution for investigating, by experimental analysis, the C2 agility concepts within a complex framework with special attention to human behavior models.
This paper presents a framework for integrated executable architectures, which is the integration of architecture modelling tools and simulation tools. This framework allows the use of executable architectures during the conceptual analysis and design phases in order to address system complexity at an early stage of the development. The proposed concept of integrated executable architecture enables a dynamic combination of the formerly separated and static areas of business processes, system design and resource modelling. It provides time-based, dynamic visualisation of system behaviour by combining business process simulation, system simulation and synthetic environments. This allows an early understanding of emergent behaviour, time-dependent behaviour and performance estimation of the architecture.
The criticality of the United States Air Force nuclear enterprise demands that commanders have the best possible understanding of system performance, both in the aggregate and at the drill-down levels, sufficient to make timely corrective actions when warranted. We propose a new strategy-linked measurement system for nuclear enterprise sustainment, which includes a set of performance metrics and a new Aggregation h method for aggregating the metrics. Our metrics use United States Air Force approved or adapted metrics that accommodate weighting and enable performance comparisons between organizations or performance within the same organization over time. We demonstrate our method with generated performance data designed to test the sensitivity of our method. Our Aggregation h method provides a simple, intuitive measurement approach that enables unity of effort and influences behavior at each hierarchical level towards achieving strategic goals, and is extendable to performance measurement for other complex sustainment systems.
Today, many military software intensive systems such as command and control systems, military simulations and decision support systems require the same military knowledge found in the operation plans and orders, which are mostly imported to the system in an application specific form. Due to the increased need for interoperability among those systems, many domain specific languages arise in order to formalize the inputs and outputs to obtain machine processable knowledge. A major domain specific language is the Coalition Battle Management Language (C-BML), which is currently under development. In this work, a scenario is developed and a coalition combat organization that has unmanned surface vehicle (USV) units under its command is created for fighting piracy. The orders and reports related to the patrol mission for the USVs are set up and modelled using C-BML. In order to model the orders, functional and temporal analyses of the actions in the orders are performed. The representativeness of the military orders, reports and requests in the scope of the scenario domain in C-BML is examined. Discussions about the expressiveness of C-BML are offered from a C-BML adopter perspective. Furthermore, we anticipate that this study will serve as a guideline for further C-BML studies.
‘Data farming’ is based on the idea that simulation models run thousands of times can provide insights into the possible consequences of different options. However, the validity of the models used for data farming, especially in the context of HSCB (human, social, cultural and behavioural) modelling for decision-making and future studies, is at least questionable. This paper first reflects on the epistemological aspects of this predicament in order to illustrate its fundamental severity. Then, a possible solution is presented that is based on the notion of ‘bad models’, the concept of plausibility, and the method of simulation-based weak point analysis. The approach can be complemented by interactive war gaming. Such a systematic approach appears more defendable than most attempts to use HSCB models for affirmative purposes, and is methodologically easier to implement since it solely requires focusing on the validation of empirically amenable micro-processes.
During mission execution in military applications, the US Army Training and Doctrine Command Pamphlet 525-66 Battle Command and Battle Space Awareness capabilities prescribe expectations that networked teams will perform in a reliable manner under changing mission requirements, varying resource availability and reliability, resource faults, etc. In this paper, a command and control structure is presented that allows for computer-aided execution of the networked team decision-making process, control of force resources, shared-resource dispatching, and adaptability to change based on battlefield conditions. A mathematically justified networked computing environment is provided called the Discrete Event Control (DEC) framework. DEC has the ability to provide the logical connectivity among all team participants, including mission planners, field commanders, warfighters, and robotic platforms. The proposed data management tools are developed and demonstrated with a simulation study on a realistic military ambush attack. The results show that the tasks of multiple missions are correctly sequenced in real time, and that shared resources are suitably assigned to competing tasks under dynamically changing conditions without conflicts and bottlenecks.
Computer games are increasingly being used by armed forces to supplement conventional training methods. However, despite considerable anecdotal claims about their training effectiveness, empirical evidence is lacking. This paper critically reviews major studies conducted in the past decade that have examined game-based training with dismounted soldiers. The findings indicate that these studies are characterized by methodological limitations and that the evidence regarding the effectiveness of game-based training for this military population is not compelling. Furthermore, due to methodological limitations with the studies, the possibility of negative training effects cannot be discounted. The paper concludes with implications for the scientific and military communities, as well as recommendations for the conduct of future studies in this area.
As unmanned aerial vehicles (UAVs) become more prevalent on the battlefield, ground forces will increasingly have to rely on them for intelligence, surveillance and reconnaissance, as well as target marking and overwatch operations. This paper presents the use of the Situational Awareness for Surveillance and Interdiction Operations simulation analysis tool in conjunction with the design and analysis of experiments to study aspects of UAVs’ surveillance characteristics in conjunction with ground-based interdiction teams to aid in increasing the number of targets cleared from the area of interest. Different teaming strategies and coordination measures between searching and interdicting assets are studied in order to understand the effectiveness of the interdictor possessing an organic tracker UAV. The objective of this research is to quantify the benefit or penalty of an additional UAV asset that is organic to a quick reaction force in the context of the overall surveillance and interdiction operation.
For combat personnel in urban operations, situational awareness is critical and of major importance for a safe and efficient performance. One way to train situational awareness is to adopt video games. Twenty military and 20 civilian subjects played the game "Close Combat: First to Fight" on two different platforms, Xbox and PC, wearing an eye tracker. The purpose was to investigate if the visual search strategies used in a game correspond to live training, and how military-trained personnel search for visual information in a game environment. A total of 27,081 fixations were generated through a centroid mode algorithm and analyzed frame-by-frame, 48% of them from military personnel. Military personnel’s visual search strategies were different from those of civilians. Fixation durations were, however, equally short, that is, about 170 ms, for both groups. Surprisingly, the military-trained personnel’s fixation patterns were less orientated towards tactical objects and areas of interest than the civilians’; the underlying mechanisms remaining unclear. Military training was apparently not advantageous with respect to playing "Close Combat: First to Fight". Further research within the area of gaming, military training and visual search strategies is warranted.
Key aspects of the verification performed on US Army Dugway Proving Ground (DPG) WeatherServer (WXS) are described. WXS is a Test and Training Enabling Architecture (TENA)-based modeling and simulation that distributes three-dimensional meteorological data over time to participants in a distributed test event or joint exercise environment. The verification features an iterative process as an effective measure to reduce time and costs while still allowing a comprehensive review. In addition, the unique role that WXS serves in efficiently providing real-time meteorological data to support Test and Evaluation (TE) exercises is discussed.
The verification process demonstrated the fidelity of the WXS output and the correctness of the coded technical algorithms (e.g., altitude-to-pressure conversions). The iterative process involved cycles of testing and improved software builds that continued until a build of WXS was developed that functioned as designed. Insights obtained during the iterative process applied to the WXS verification included realizing the full benefits of (1) periodic communications and issue resolution among the developer, verification team, and sponsor; (2) allocating sufficient budget for the software developer’s time to support the verification process; and (3) strategically customizing the verification process to allow for an efficient testing and review process following applicable standards.
The Generic Methodology for Verification and Validation (GM-VV) is a generic and comprehensive methodology for structuring, organizing and managing the verification and validation (V&V) of modelling and simulation (M&S) assets. The GM-VV is an emerging recommended practice within the Simulation Interoperability Standards Organization (SISO). The GM-VV provides a technical framework to efficiently develop arguments to justify why M&S assets are acceptable or unacceptable for a specific intended use. This argumentation supports M&S stakeholders in their acceptance decision-making process regarding the development, application and reuse of such M&S assets. The GM-VV technical framework assures that during the execution of the V&V work the decisions, actions, information and evidence underlying such acceptance arguments will be traceable, reproducible, transparent and documented. Since the GM-VV is a generic (i.e. abstract) methodology it must be tailored to fit the specific V&V needs of a M&S organization, project or application domain. Therefore, V&V practitioners must incorporate specific V&V techniques within the generic architectural template offered by the GM-VV in order to properly assess the M&S assets under review. The first part of this paper provides an introductory overview of the GM-VV basic principles, concepts, methodology components and their interrelationships. The second part of the paper focuses on how the GM-VV may be tailored for a specific simulation application. This effort is illustrated with some results and lessons learned from several technology demonstration programs of the Dutch Ministry of Defence.
The operational range and manoeuvrability of the modern infantry soldier is restricted by the overall load and bulk of equipment ranging from 50 to 75 kg. Today’s soldiers rely heavily on batteries to meet their power requirements, which make up 25% of the overall load. This results in a significant increase on soldier’s physical stress and cognitive burden. Recent developments in renewable energy, and more particularly the evolution of very thin and flexible wearable photovoltaic devices, provide promising solutions for the application of such technologies on the infantry soldier. However, since these flexible substrate devices are still under development or produced at a very small scale, their application and use has to be simulated prior to integrating to the infantry soldier. Such simulations need to take into account the specific requirements and different fields of operation of the infantry soldier, in the context of weather, date and time, global location and for different military mission environments. This paper presents a number of simulations performed for a wide range of scenarios in the context of the Solar Soldier project. It discusses the key results, offering a set of guidelines for the positioning and integration of such renewable energy technology on the modern infantry soldier. Moreover, this paper suggests future improvements on the methodology and optimisation of the procedures.
There has been a significant amount of interest in landmine detection and, most recently, the detection of improvised explosive devices (IEDs). In this paper, current and recent papers are reviewed and explored. In addition, a model and simulation that incorporates multiple levels of detection is discussed and developed. One of the most critical points often discussed is locating and identifying concealed landmines and IEDs with a high degree of accuracy. Combining the warfighter-in-the-loop increases the accuracy of minefield detection. This concept can be applied with the addition of multiple methods, such as laser radar, metal detection, infrared imaging, ground-penetrating radar and acoustic methods. Papers on the modeling and simulation of these methods individually and fused are reviewed in this paper. A combination of methods at various levels of decision making can increase the overall accuracy of landmine detection and, more importantly, identifying false negatives (FNs). In this paper, simple modeling and simulation of landmine detection is presented by adding loops of detection systems and redundancies to increase the accuracy of detection and the effectiveness of the resources applied.
Drawing appropriate conclusions from simulation results requires a correct understanding of the accuracy and context of those results. Simulation communities often assess simulation results without considering fully uncertainties that might impact the accuracy and context of those results. This creates potential for inappropriate conclusions from simulation results. Much useful work has been done in uncertainty quantification, but most of those efforts have addressed uncertainty in particular parameters and areas. Unfortunately they have not addressed all areas of potential uncertainty that might impact simulation results. A paradigm exists that facilitates consideration of all potential sources of simulation uncertainty. This paper examines simulation uncertainties using that paradigm and indicates potential magnitude of uncertainties for simulation results in various areas. A comprehensive approach to simulation uncertainty not only reduces the likelihood of drawing inappropriate conclusions from simulation results, but it also provides information that can help determine where it is most useful to invest verification and validation resources in efforts to reduce uncertainty in simulation results (i.e., to improve the accuracy of simulation results). Comprehensive assessment of simulation uncertainty may have drawbacks. When addressed comprehensively, simulation uncertainty tends to be larger than desired, and those announcing such run the risk of being bearers of bad news. Realistic appreciation for the uncertainty associated with simulation results can also decrease the importance of those simulation results in decision processes. On the positive side, such realistic and comprehensive appreciation for simulation uncertainty provides a solid factual and logical basis for how to proceed, whether by improving simulation capabilities or by developing alternative approaches to support decision processes. A perspective from comprehensive consideration of simulation uncertainty helps to ensure a proper context for simulation results.
In this paper, we provide a framework to study trust-based coalition formation in multi-agent systems using cooperative game theory as the underlying mathematical framework. We describe how to study trust dynamics between agents as a result of their trust synergy and trust liability in cooperative coalitions. We also rigorously justify the behaviors of agents for different classes of games and discuss how to exploit the formal properties of these games for cooperative control in an unmanned military vehicle convoy.
Helicopter unmanned aerial vehicles (UAVs) can be extensively used for military missions as well as in civil operations, ranging from multi-role combat support and search and rescue, to border surveillance and forest fire monitoring. Helicopter UAVs are underactuated nonlinear mechanical systems with correspondingly challenging controller designs. This paper presents an optimal controller design for tracking of an underactuated helicopter using an adaptive critic neural network (NN) framework. The online approximator-based controller learns the infinite-horizon continuous-time Hamilton–Jacobi–Bellman (HJB) equation and then calculates the corresponding optimal control input that minimizes the HJB equation forward-in-time without using value and policy iterations. In the proposed technique, optimal tracking is accomplished by a single NN, which is tuned online using a novel weight update law. Stability analysis is performed and simulation results demonstrate the proposed control design.
The problem of tracking and monitoring moving targets using mobile sensor agents (MSAs) is relevant to a variety of applications, including monitoring of endangered species, civilian security, and military surveillance. This paper presents a new information potential field approach for computing the motion plans and control inputs of a MSA, based on the feedback obtained from a modified particle filter used for tracking multiple moving targets in a region of interest. A modified particle filter is presented that implements a new sampling method based on supporting intervals of normal probability density functions. The method accounts for the latest sensor measurements by adapting a mixture representation of the target probability density functions (PDFs). The target motion is modeled as a semi-Markov jump process, such that the target PDFs, or the PDFs of the Markov parameters, can be updated based on real-time sensor measurements by a centralized processing unit or MSAs supervisor. A new information potential method is presented that computes an artificial potential function based on the output of the modified particle filter. Using this artificial potential, the sensors compute feedback control inputs that allow them to track and monitor a maneuvering target over time, using a bounded field of view (FOV).
Developing a stress-management training (SMT) system and protocol for soldiers can help them cope better with stress experienced in theatre operations. Using 3D horror games in virtual reality (VR) can present an attractive simulation method for soldiers. This study was conducted to find out whether it is possible to stress soldiers moderately using VR and which technology is more efficient to do so. A total of 47 soldiers returning from Afghanistan played two 3D first-person shooter (FPS)/horror games (Killing Floor and Left 4 Dead) on three different types of immersive technologies (a 22-inch stereoscopic monitor, a 73-inch stereoscopic TV and a CAVE™). As a control and reference comparison of induced stress, participants were exposed to the Trier Social Stress Test (TSST), a standardized stress-inducing procedure. Results were supporting of our work, devising an effective low-cost and high-buy-in approach to assist in teaching and practicing stress-management skills. Repeated measures analyses of variance (ANOVAs) revealed statistically significant increases in the soldiers’ respiration rates and heart rates while playing the 3D games and during the TSSTs. No significant interactions were found. Increases in physiological arousal among the soldiers were significant when comparing the baseline to the immersion and to the TSST, but not when comparing both stressors. Immersion in 3D games is proposed as a practical and cost-effective option to create a context that allows practicing SMT.
In this paper we present a model for expressing attacks on control protocols that involve the exchange of messages. Attacks are modeled using the notion of an attacker who can block and/or fabricate messages. These two attack mechanisms cover a variety of scenarios ranging from power grid failures to cyber attacks on oil pipelines. The model provides a method to syntactically express communication systems and attacks, which supports the development of attack and defense strategies. For demonstration purposes, an attack instance is modeled that shows how a targeted messaging attack can result in the rupture of a gas pipeline.