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  Subjects -> MILITARY (Total: 109 journals)
Showing 1 - 24 of 24 Journals sorted alphabetically
Africa Conflict Monitor     Full-text available via subscription   (Followers: 8)
Armed Conflict Survey     Full-text available via subscription   (Followers: 15)
Armed Forces & Society     Hybrid Journal   (Followers: 24)
Arms & Armour     Hybrid Journal   (Followers: 10)
British Journal for Military History     Open Access   (Followers: 40)
Bulletin of the Atomic Scientists     Hybrid Journal   (Followers: 6)
Ciencia y Poder Aéreo     Open Access   (Followers: 2)
Civil Wars     Hybrid Journal   (Followers: 21)
Coleção Meira Mattos : Revista das Ciências Militares     Open Access  
Conflict, Security & Development     Hybrid Journal   (Followers: 426)
Critical Military Studies     Hybrid Journal   (Followers: 4)
CRMA Journal of Humanities and Social Sciences     Open Access   (Followers: 1)
Cuadernos de Marte     Open Access  
Defence and Peace Economics     Hybrid Journal   (Followers: 22)
Defence Science Journal     Open Access   (Followers: 40)
Defence Studies     Hybrid Journal   (Followers: 31)
Defence Technology     Open Access   (Followers: 4)
Defense & Security Analysis     Hybrid Journal   (Followers: 31)
Digital War     Hybrid Journal   (Followers: 2)
Disaster and Military Medicine     Open Access   (Followers: 5)
Doutrina Militar Terrestre em Revista     Open Access  
Eesti Sõjaajaloo Aastaraamat / Estonian Yearbook of Military History     Open Access   (Followers: 2)
EsSEX : Revista Científica     Open Access   (Followers: 1)
First World War Studies     Hybrid Journal   (Followers: 27)
Fra Krig og Fred     Open Access   (Followers: 2)
Gettysburg Magazine     Full-text available via subscription  
Great Circle: Journal of the Australian Association for Maritime History, The     Full-text available via subscription   (Followers: 7)
Headmark     Full-text available via subscription   (Followers: 2)
Human Factors and Mechanical Engineering for Defense and Safety     Hybrid Journal   (Followers: 1)
International Journal of Intelligent Defence Support Systems     Hybrid Journal   (Followers: 5)
International Peacekeeping     Hybrid Journal   (Followers: 473)
Journal for Maritime Research     Hybrid Journal   (Followers: 12)
Journal of Bioterrorism & Biodefense     Open Access   (Followers: 6)
Journal of Archives in Military Medicine     Open Access   (Followers: 3)
Journal of Conflict and Security Law     Hybrid Journal   (Followers: 20)
Journal of Conventional Weapons Destruction     Open Access   (Followers: 3)
Journal of Defense Analytics and Logistics     Open Access  
Journal of Defense Modeling and Simulation : Applications, Methodology, Technology     Hybrid Journal   (Followers: 6)
Journal of Defense Studies & Resource Management     Hybrid Journal   (Followers: 2)
Journal of Military and Strategic Studies     Open Access   (Followers: 5)
Journal of Military and Veterans Health     Full-text available via subscription   (Followers: 10)
Journal of Military Ethics     Hybrid Journal   (Followers: 11)
Journal of Military Experience     Open Access   (Followers: 7)
Journal of Military History     Full-text available via subscription   (Followers: 34)
Journal of Military Studies     Open Access   (Followers: 5)
Journal of National Security Law & Policy     Free   (Followers: 8)
Journal of Naval Architecture and Marine Engineering     Open Access   (Followers: 5)
Journal of power institutions in post-soviet societies     Open Access   (Followers: 2)
Journal of Slavic Military Studies     Hybrid Journal   (Followers: 18)
Journal of Terrorism Research     Open Access   (Followers: 26)
Journal of the Royal Army Medical Corps     Hybrid Journal   (Followers: 9)
Journal on Baltic Security     Open Access   (Followers: 3)
Martial Arts Studies     Open Access   (Followers: 1)
Media, War & Conflict     Hybrid Journal   (Followers: 15)
Medical Journal Armed Forces India     Full-text available via subscription  
Medicine, Conflict and Survival     Hybrid Journal   (Followers: 3)
Militärgeschichtliche Zeitschrift     Hybrid Journal   (Followers: 6)
Military Behavioral Health     Hybrid Journal   (Followers: 6)
Military Medical Research     Open Access   (Followers: 4)
Military Medicine     Hybrid Journal   (Followers: 9)
Military Psychology     Hybrid Journal   (Followers: 10)
Modern Information Technologies in the Sphere of Security and Defence     Open Access   (Followers: 2)
Naval Research Logistics: an International Journal     Hybrid Journal   (Followers: 3)
Nonproliferation Review     Hybrid Journal   (Followers: 5)
O Adjunto : Revista Pedagógica da Escola de Aperfeiçoamento de Sargentos das Armas     Open Access   (Followers: 2)
Perspectives on Terrorism     Open Access   (Followers: 470)
Post-Soviet Armies Newsletter     Open Access   (Followers: 1)
Problemy Mechatroniki. Uzbrojenie, lotnictwo, inżynieria bezpieczeństwa / Problems of Mechatronics. Armament, Aviation, Safety Engineering     Open Access   (Followers: 3)
Revista Agulhas Negras     Open Access   (Followers: 1)
Revista Babilônia     Open Access   (Followers: 1)
Revista Científica Fundação Osório     Open Access  
Revista Científica General José María Córdova     Open Access  
Revista Cubana de Medicina Militar     Open Access   (Followers: 1)
Revista do Exército     Open Access   (Followers: 1)
Revista Militar de Ciência e Tecnologia     Open Access   (Followers: 1)
Revista Política y Estrategia     Open Access  
Sabretache     Full-text available via subscription   (Followers: 1)
Sanidad Militar     Open Access  
Scandinavian Journal of Military Studies     Open Access   (Followers: 1)
Scientia Militaria : South African Journal of Military Studies     Open Access   (Followers: 4)
Scientific Journal of Polish Naval Academy     Open Access  
Securitologia     Open Access   (Followers: 1)
Security and Defence Quarterly     Open Access   (Followers: 7)
Security Studies     Hybrid Journal   (Followers: 48)
Signals     Full-text available via subscription   (Followers: 2)
Small Wars & Insurgencies     Hybrid Journal   (Followers: 373)
Small Wars Journal     Open Access   (Followers: 17)
Social Development & Security : Journal of Scientific Papers     Open Access   (Followers: 1)
Special Operations Journal     Hybrid Journal   (Followers: 1)
Strategic Comments     Hybrid Journal   (Followers: 6)
The Military Balance     Hybrid Journal   (Followers: 9)
The RUSI Journal     Hybrid Journal   (Followers: 17)
Transportation Research Part E: Logistics and Transportation Review     Hybrid Journal   (Followers: 22)
United Service     Full-text available via subscription   (Followers: 1)
University of Miami National Security & Armed Conflict Law Review     Open Access   (Followers: 1)
Vierteljahrshefte für Zeitgeschichte. Das zentrale Forum der Zeitgeschichtsforschung     Hybrid Journal   (Followers: 11)
Vojnotehnički Glasnik     Open Access   (Followers: 1)
War & Society     Hybrid Journal   (Followers: 26)
War in History     Hybrid Journal   (Followers: 23)
Whitehall Papers     Hybrid Journal   (Followers: 3)
Wiedza Obronna     Open Access   (Followers: 2)
Zeitschrift für Slawistik     Hybrid Journal   (Followers: 1)
선진국방연구     Open Access  

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Similar Journals
Journal Cover
Journal of Defense Modeling and Simulation : Applications, Methodology, Technology
Journal Prestige (SJR): 0.208
Citation Impact (citeScore): 1
Number of Followers: 6  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1548-5129 - ISSN (Online) 1557-380X
Published by Sage Publications Homepage  [1143 journals]
  • Traumatic brain injury risk assessment with smart technology
    • Authors: Chiming Huang, Rosa H Huang, Bani Yaghoub Majid
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Mild traumatic brain injuries (mTBIs) continue to burden our warfighters. The high-tech industry has delivered wearable Micro-Electro-Mechanical System (MEMS) head-impact sensors to monitor impact forces. So far, these MEMS sensors have categorically failed to detect mTBIs and are therefore of no clinical utility for diagnosis. Our recent studies have shown that human head kinematics is anisotropic with respect to pitch–roll–yaw degrees of freedom of the head and neck. In the present project, we generated head acceleration datasets on non-injurious impacts and mTBI events based on mean values from the literature. We then augmented the simulated data with pitch–roll–yaw information followed by machine learning with a Classification and Regression Tree analysis. Our results revealed that head angular acceleration in pitch is the best predictor. More than 81.3 % of concussive injuries had head angular accelerations in pitch exceeding 3527 rad/s2. Out of 18.6% of concussive injuries with head angular accelerations in pitch under 3527 rad/s2, 75% of these cases had head angular accelerations in roll exceeding 1679 rad/s2. This study shows that artificial intelligence and machine learning should be able to provide accurate identification of subject-specific concussive thresholds in real time and in the field, thereby moving concussion diagnosis toward precision medicine.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-04-27T09:30:00Z
      DOI: 10.1177/15485129211008529
  • Wargaming the use of intermediate force capabilities in the gray zone
    • Authors: Kyle D Christensen, Peter Dobias
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      This work reviews the development and tests of an intermediate force capability (IFC) concept development hybrid wargame aimed at examining a maritime task force’s ability to counter hybrid threats in the gray zone. IFCs offer a class of response between doing nothing and using lethal force in a situation that would be politically unpalatable. Thus, the aim of the wargame is to evaluate whether IFCs can make a difference to mission success against hybrid threats in the gray zone. This wargame series was particularly important because it used traditional game mechanics in a unique and innovative way to evaluate and assess IFCs. The results of the wargame demonstrated that IFCs have a high probability of filling the gap between doing nothing and using lethal force. The presence of IFCs provided engagement time and space for the maritime task force commander. It also identified that development of robust IFC capabilities, not only against personnel, but against systems (trucks, cars, UAVs, etc.), can also effectively counter undesirable adversarial behavior
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-04-21T05:25:56Z
      DOI: 10.1177/15485129211010227
  • Can machine learning be used to forecast the future uncertainty of
           military teams'
    • Authors: Ronald H Stevens, Trysha L Galloway
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Uncertainty is a fundamental property of neural computation that becomes amplified when sensory information does not match a person’s expectations of the world. Uncertainty and hesitation are often early indicators of potential disruption, and the ability to rapidly measure uncertainty would have implications for future educational and training efforts by targeting reflective discussions about past actions, supporting in-progress corrections, and generating forecasts about future disruptions.An approach is described combining neurodynamics and machine learning to provide quantitative measures of uncertainty. Models of neurodynamic information derived from electroencephalogram (EEG) brainwaves have provided detailed neurodynamic histories of US Navy submarine navigation team members. Persistent periods (25–30 s) of neurodynamic information were seen as discrete peaks when establishing the submarine’s position and were identified as periods of uncertainty by an artificial intelligence (AI) system previously trained to recognize the frequency, magnitude, and duration of different patterns of uncertainty in healthcare and student teams. Transition matrices of neural network states closely predicted the future uncertainty of the navigation team during the three minutes prior to a grounding event.These studies suggest that the dynamics of uncertainty may have common characteristics across teams and tasks and that forecasts of their short-term evolution can be estimated.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-03-29T05:49:00Z
      DOI: 10.1177/1548512921999112
  • Channel capacity analysis of non-orthogonal multiple access and massive
           multiple-input multiple-output wireless communication networks considering
           perfect and imperfect channel state information
    • Authors: Ravi Shankar, Shovon Nandi, Ajay Rupani
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In this paper, we investigate the non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (M-MIMO) techniques and through simulation, and a comparison is given between the NOMA and orthogonal multiple access techniques. Integrating NOMA with M-MIMO is a very challenging task. In this paper, for a single-cell system, NOMA is integrated with a M-MIMO system for better spectral and energy efficiency. Investigation of the multiple user gain is the focus of this work because the multiple user gain supports simultaneous transmission of multiple users in the case of the M-MIMO system. In this way, the M-MIMO will provide a 100 times channel capacity increase, which results in very high data transmission rate. In the modern communication system, achieving multiple user gain is a very difficult task when channel estimation error is present. The performance of the orthogonal multiple access as well as NOMA system significantly reduced in the presence of channel estimation error. However, most of the current schemes do not work well with imperfect perfect channel state information conditions. Simulation results closely agree with the theoretical outcomes.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-03-29T05:46:16Z
      DOI: 10.1177/15485129211000139
  • Analysis of NOMA-OFDM 5G wireless system using deep neural network
    • Authors: Sharnil Pandya, Manoj Ashok Wakchaure, Ravi Shankar, Jagadeeswara Rao Annam
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In this work, a multiple user deep neural network-based non-orthogonal multiple access (NOMA) receiver is investigated considering channel estimation error. The decoding of the symbol in the case of the NOMA system follows the sequential order and decoding accuracy depends on the detection of the previous user. Without estimating the throughput, a deep neural network-based NOMA orthogonal frequency division multiplexing (OFDM) system is proposed to decode the symbols from the users. Firstly, the deep neural network is trained. Secondly, the data are trained and lastly, the data are tested for various users. In this work, for various values of signal to noise ratio, the performance of the deep neural network is investigated, and the bit error rate (BER) is calculated on a per subcarrier basis. The simulation results show that the deep neural network is more robust to symbol distortion due to inter-symbol information and will obtain knowledge of the channel state information using data testing.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-03-29T05:44:21Z
      DOI: 10.1177/1548512921999108
  • Application of a terminal-ballistics model for estimating munition lethal
           radius on mortar projectiles and rocket warheads
    • Authors: Catovic Alan, Kljuno Elvedin
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In our previous work, we developed a new terminal-ballistics model developed for artillery high explosive projectiles with natural fragmentation. Lethal radius is here defined as the distance from the detonation point where the effective fragment (80 J) density is 1 frag/m2. In the model, the vertical position of the projectile upon impact is assumed, which means that the lethal radius defines a circular lethal zone (maximum lethal zone of the projectile on the ground).In the research, presented in this paper, we have applied the model to mortar projectiles and rocket warheads, which have different designs compared with classic artillery projectiles. The results from the model, compared to the available experimental results from the quarter-circular arena (used in our country), showed satisfactory accuracy for these types of munitions.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-03-17T05:27:38Z
      DOI: 10.1177/1548512921998798
  • Joint sparsity-biased variational graph autoencoders
    • Authors: Lane Lawley, Will Frey, Patrick Mullen, Alexander D Wissner-Gross
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      To bring the full benefits of machine learning to defense modeling and simulation, it is essential to first learn useful representations for sparse graphs consisting of both key entities (vertices) and their relationships (edges). Here, we present a new model, the Joint Sparsity-Biased Variational Graph AutoEncoder (JSBVGAE), capable of learning embedded representations of nodes from which both sparse network topologies and node features can be jointly and accurately reconstructed. We show that our model outperforms the previous state of the art on standard link-prediction and node-classification tasks, and achieves significantly higher whole-network reconstruction accuracy, while reducing the number of trained parameters.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-03-10T04:51:52Z
      DOI: 10.1177/1548512921996828
  • Numerical study of theanti-penetration performance of sandwich composite
           armor containing ceramic honeycomb structures filled with aluminum alloy
    • Authors: Hongwei Zhu, Changfang Zhao
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The aim of this work was to study the anti-penetration effect of sandwich composite armor with ceramic honeycomb structures filled with aluminum alloy under the impact of high-speed projectiles. The finite element software ABAQUS was used to conduct numerical simulation research on the process of a standard 12.7-mm projectile penetrating sandwich composite armor. The armor-piercing projectile model was simplified as a rigid body. The numerical simulation models were applied to three different sandwich composite armor structures (A, B, and C), each with a total armor thickness of 25 mm. The penetration resistance of the three kinds of composite armor was studied. We obtained velocity curves for the rigid projectile penetrating the different structures. The failure forms and penetration resistance characteristics of the three composite armor structures adopted in this paper were analyzed. In addition, the velocity reduction ratio is proposed as an index to evaluate the penetration resistance performance of the armor. The simulation results revealed decreasing rates of projectile speed in the structures A, B, and C of 69.6%, 91.1%, and 100%, respectively. The third composite armor (structure C) designed here has excellent penetration resistance and can block the penetration of a high-speed (818m/s) rigid projectile. This study can provide some reference for the application of laminated armor material in anti-penetration protection structures.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-02-27T07:11:58Z
      DOI: 10.1177/1548512921995923
  • Real-time simulation of a fragmenting explosion for cylindrical warheads
    • Authors: David Felix, Ian Colwill, Paul Harris
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Explosion models based on finite element analysis (FEA) can be used to simulate how a warhead fragments. However, their execution times are extensive. Active protection systems need to make very fast predictions, before a fast attacking weapon hits the target. Fast execution times are also needed in real-time simulations where the impact of many different computer models is being assessed. Hence, FEA explosion models are not appropriate for these real-time systems. As a trade-off between accuracy and execution time, this paper creates a simulation of fragments from a warhead’s explosion, using simple analytical equations. The results are verified against explosion experimental data and FEA results. The developed model then can be made available for real-time simulation and fast computation.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-02-27T07:10:25Z
      DOI: 10.1177/1548512921995560
  • Training data augmentation for deep learning radio frequency systems
    • Authors: William H Clark, Steven Hauser, William C Headley, Alan J Michaels
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Applications of machine learning are subject to three major components that contribute to the final performance metrics. Within the category of neural networks, and deep learning specifically, the first two are the architecture for the model being trained and the training approach used. This work focuses on the third component, the data used during training. The primary questions that arise are “what is in the data” and “what within the data matters'” looking into the radio frequency machine learning (RFML) field of automatic modulation classification (AMC) as an example of a tool used for situational awareness, the use of synthetic, captured, and augmented data are examined and compared to provide insights about the quantity and quality of the available data necessary to achieve desired performance levels. Three questions are discussed within this work: (1) how useful a synthetically trained system is expected to be when deployed without considering the environment within the synthesis, (2) how can augmentation be leveraged within the RFML domain, and, lastly, (3) what impact knowledge of degradations to the signal caused by the transmission channel contributes to the performance of a system. In general, the examined data types each make useful contributions to a final application, but captured data germane to the intended use case will always provide more significant information and enable the greatest performance. Despite the benefit of captured data, the difficulties and costs that arise from live collection often make the quantity of data needed to achieve peak performance impractical. This paper helps quantify the balance between real and synthetic data, offering concrete examples where training data is parametrically varied in size and source.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-02-22T05:15:31Z
      DOI: 10.1177/1548512921991245
  • Siting strategy for co-locating windfarms and radars considering
           interference constraints
    • Authors: Ashish Sharma, Ajay Kumar, Sushabhan Choudhury
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      As the energy sector moves away from use of fossil fuels towards clean renewable energy alternatives, the technical impediment of windfarm interference with radars has dented the deployment of windfarms. This paper provides a step-by-step siting methodology for co-locating windfarms and radars with the support of simulation tools. A procedural framework for co-locating windfarms and radars is suggested. The proposed methodology identifies crucial variables, such as azimuth, frequency, and topographical features affecting the co-existence of radars and windmills. The effect of variables on radar cross-section for feasible radar frequency ranges between 0.1 GHz and 10 GHz is calculated. The siting methodology suggests use of digital terrain maps for evaluating the interference impact due to terrain screening. In case of inextricable circumstances, where radar needs to be sited in high impact zones near windfarms, suitable mitigation techniques are suggested.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-02-08T06:04:49Z
      DOI: 10.1177/1548512921989824
  • A tutorial on cooperative non-orthogonal multiple access networks
    • Authors: Bhanu Pratap Chaudhary, Ravi Shankar, Ritesh Kumar Mishra
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In this paper, we explore the possibilities and advantages of cooperative relaying with the addition of non-orthogonal multiple access (NOMA). First, the possibilities of NOMA for fifth-generation (5G) and beyond networks is discussed followed by the generalized structures for the cooperative NOMA. Then, advanced NOMA communication is investigated where NOMA is integrated with advanced transmission technologies for the further improvement in cooperative NOMA. Hereinafter, resource allocation is investigated and, finally, the major challenges and issues are highlighted.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-02-08T05:31:29Z
      DOI: 10.1177/1548512920986627
  • AFSIM’s pseudo-realtime hybrid simulation software design
    • Authors: J Scott Thompson, Douglas D Hodson
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Simulation approaches generally fall into two categories: discrete time or discrete event. For military modeling and simulation needs, the two approaches typically align with virtual simulation, which implies human interaction with the simulation program, and constructive simulation, which implies no human interaction. The Air Force Research Laboratory develops and distributes AFSIM (Advanced Framework for Simulation, Integration, and Modeling) to a user community that uses both virtual and constructive simulation. This paper documents the software design and primary algorithms that provide AFSIM’s support for both modes, which is termed a hybrid simulation.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-01-28T10:01:25Z
      DOI: 10.1177/1548512920985269
  • The Situation Awareness Window: a Hidden Markov Model for analyzing
           Maritime Surveillance missions
    • Authors: Terry Caelli, Joyanto Mukerjee, Andy McCabe, David Kirszenblat
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In recent years, the use of Maritime Surveillance (MS) systems has increased in both defense and civilian domains. A demanding workload is placed upon operators of these systems, including the need to perform simultaneous information fusion from a number of sources to enable rapid decision throughput based upon Situation Awareness (SA). We have developed a method to objectively encode, summarize, and analyze airborne MS crew activities to gain insights into what is attended to in the execution of surveillance requirements. We label this method the “Situation Awareness Window” (SAW), which integrates sensor and tactical information with kinematics to define key attention and decision components of the operators that emerge over the surveillance mission. The SAW is defined with respect to the objects that are surveyed, the surveillance activities, and their chronological order. A SAW Hidden Markov Model (SAW-HMM) operates upon the surveillance mission activity encoder, resulting in a probabilistic relationship between the attention switching across sensor types and surveyed objects over the entire mission. That is, to implement the SAW-HMM we encoded the selection of sensors and surveillance decisions using a novel “encoder-interface” that allows users to probe many different features, observations, and states of a given mission. Ultimately the SAW will provide automated, objective, and insightful post mission debriefing technologies for operators and mission planners to encapsulate task demands and SA features over the mission.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-01-22T05:11:20Z
      DOI: 10.1177/1548512920984370
  • A dual U-Net algorithm for automating feature extraction from satellite
    • Authors: Samuel Humphries, Trevor Parker, Bryan Jonas, Bryan Adams, Nicholas J Clark
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Quick identification of building and roads is critical for execution of tactical US military operations in an urban environment. To this end, a gridded, referenced, satellite images of an objective, often referred to as a gridded reference graphic or GRG, has become a standard product developed during intelligence preparation of the environment. At present, operational units identify key infrastructure by hand through the work of individual intelligence officers. Recent advances in Convolutional Neural Networks, however, allows for this process to be streamlined through the use of object detection algorithms. In this paper, we describe an object detection algorithm designed to quickly identify and label both buildings and road intersections present in an image. Our work leverages both the U-Net architecture as well the SpaceNet data corpus to produce an algorithm that accurately identifies a large breadth of buildings and different types of roads. In addition to predicting buildings and roads, our model numerically labels each building by means of a contour finding algorithm. Most importantly, the dual U-Net model is capable of predicting buildings and roads on a diverse set of test images and using these predictions to produce clean GRGs.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-01-15T05:32:22Z
      DOI: 10.1177/1548512920983549
  • Real-time calculation of the initial angle of projection for fragments in
           cylindrical warheads
    • Authors: David Felix, Ian Colwill, Paul Harris
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      This paper presents an improvement in the speed and accuracy of calculating the initial angle of projection of fragments for exploding cylindrical shells. It is a fast tool that can be used by designers, where existing approaches, such as computationally intensive Finite Element Analysis, are preventively slow. An enhanced Taylor equation is presented using available experimental data and the effect of the changing shape of the warhead’s cylindrical casing on the fragment’s initial projection angle. The resulting equation is computationally fast as it uses uncomplicated equations and provides improved accuracy for estimating a fragment’s initial angle of projection in comparison to existing work.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-01-08T06:20:38Z
      DOI: 10.1177/1548512920982673
  • Sum rate capacity of non-orthogonal multiple access scheme with optimal
           power allocation
    • Authors: Lokesh Bhardwaj, Ritesh Kumar Mishra, Ravi Shankar
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In this work, the performance of the downlink non-orthogonal multiple access (NOMA) technique is investigated for two users considering optimal power allocation factors. The power domain NOMA differentiates the users based on channel gains by providing different power levels and it is demonstrated that optimal power allocation is only possible when the gain ratio is maximum. Further, the range of optimal power levels is derived for the strong user having better channel conditions. Furthermore, the outage probability (OP) has been derived for ordered NOMA in the downlink through the cumulative density function-based approach. The simulation results demonstrate the improvement in sum rate capacity for optimal power allocation as compared to random power allocation, and the OP reduces with the signal-to-noise ratio more sharply for the stronger user.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-01-08T06:20:13Z
      DOI: 10.1177/1548512920983531
  • Simplified reliability-based load design factors for explosive blast
           loading, weapons effects, and its application to collateral damage
    • Authors: Mark G Stewart
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The paper describes a simplified approach to quantifying a reliability-based design load factor (RBDF) for the variability of explosive blast loading. The user can select range and explosive mass variability and model errors to derive RBDFs for pressure and impulse. These algorithms may be easily programmed into a spreadsheet, computer code, or other numerical method. There is a need by military planners to increase the predictive accuracy of collateral damage estimation (CDE) to ensure maximum damage to the target while minimizing harm to nearby civilians. This present paper uses the CDE damage criterion adopted by the USA and NATO to assess damage and safety risks and recommend safe collateral damage distances. Hence, the present paper utilizes RBDFs to simulate collateral damage risks to a hypothetical reinforced concrete residential building from a 2000 lb bomb using the 99th percentile of blast loads, engineering models, and Monte Carlo simulation analysis that considers variabilities of load and resistance. It was found that CDE is sensitive to airblast model errors and variability of structural resistance. It is recommended that these considerations be incorporated into CDE methodology since existing CDE methodology may be non-conservative, resulting in higher risks of collateral damage.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2021-01-04T10:21:20Z
      DOI: 10.1177/1548512920977737
  • Modeling the effect of skidded timber bunches on forest soil compaction
    • Authors: Igor Grigorev, Olga Kunickaya, Albert Burgonutdinov, Olga Burmistrova, Varvara Druzyanova, Nikolay Dolmatov, Anna Voronova, Alexey Kotov
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      An increasing demand for forest products incites a large number of log transportation operations, which may lead to negative consequences for the soil and the ecosystem as a whole. This paper presents a mathematical model to estimate the soil deformation and compaction processes under the influence of individual components of the skidding system, such as the forwarder, limbs, butts, and tops of tree-lengths in high latitudes, permafrost soil, and forests of the cryolithic zone. The effectiveness of the proposed model was evaluated according to experimental results. Comparative analysis showed that the calculated data differ from the experimental data by no more than 10%. The deformation of the soil by the bunch of tree-length logs occurs due to shearing processes. It has been established that the initial vertical stress exceeds the radial stress by 30–40%. The result of estimating the dependency of the shelterbelt width on the number of tree-length logs showed that the limit values for logs amount to 4–6 units for the mild, medium, and solid soil categories. The obtained results and the developed model will allow for a qualitative and quantitative assessment of the technological impact on the soil during the projecting of maps for logging operations.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-12-29T11:16:51Z
      DOI: 10.1177/1548512920978700
  • End-to-end improved convolutional neural network model for breast cancer
           detection using mammographic data
    • Authors: Pradeep Kumar, Subodh Srivastava, Ritesh Kumar Mishra, Y Padma Sai
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Any disease is curable if it is diagnosed at the early stages with the help of a little human effort. The disease breast cancer is the second leading cause of death among women after lung cancer. Mammography is one of the most mainstream clinical imaging modalities that are utilized for early recognition of breast cancer. Early breast cancer detection helps to alleviate unnecessary treatments as well as saving women’s lives. The speedy development in deep learning and some of the strategies of machine learning have invigorated abundant enthusiasm for their application to clinical imaging issues. This paper presents an improved convolutional neural network (CNN) model that consists of three convolutional layers where the starting layer searches for low-level features and the ending layer searches for high-level features. Two activation functions, that is, the Rectified Linear Unit and sigmoid functions, are utilized for the detection of breast cancer using digitized film mammograms from the Digital Database for Screening Mammography. The proposed convolutional neural system for identifying breast malignancy on mammogram imaging achieved praiseworthy execution on examination with prior models. The experimentation found that the model achieved has a true positive rate of 99% (accuracy = 97.20%, precision = 99%, true negative rate = 96%, F-score = 0.99, balanced classification rate = 0.975, Youden’s index = 0.95). The proposed improved CNN model can be used as a second opinion of doctors to detect breast cancer.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-12-09T05:54:52Z
      DOI: 10.1177/1548512920973268
  • Integrated methodology for substantiation of the rational district
           placement of the evacuated population
    • Authors: Yernar Zh Akimbayev, Zhumabek Kh Akhmetov, Murat S Kuanyshbaev, Aleksandr I Mazanik, Asylbek T Abildin
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The paper formulates the scientific task of substantiating a rational area for the location of an evacuated population. The relevance of the study is due to the importance of the topic for national defence. The leading approach is the individual methodology developed using the scenario-logic-feasibility approach, which, as part of an integrated methodology, allows the rational location of the evacuated population in any administrative territory to be determined by the integrated indicator of opportunity. The paper considers approaches to the organization of population protection in modern conditions, conducting an analysis of the scientific and methodological apparatus in the field, and developing a new integrated methodology to justify the rational area of the evacuated population according to the integrated indicator of opportunity. The materials of the paper can be useful both for training students of military departments and for their practical value if the evacuation of a population is necessary.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-11-27T07:49:11Z
      DOI: 10.1177/1548512920974101
  • Stacked generalizations in imbalanced fraud data sets using resampling
    • Authors: Kathleen R Kerwin, Nathaniel D Bastian
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Predicting fraud is challenging due to inherent issues in the fraud data structure, since the crimes are committed through trickery or deceit with an ever-present moving target of changing modus operandi to circumvent human and system controls. As a national security challenge, criminals continually exploit the electronic financial system to defraud consumers and businesses by finding weaknesses in the system, including in audit controls. This study uses stacked generalization using meta or super learners for improving the performance of algorithms in step one (minimizing the algorithm error rate to reduce its bias in the learning set) and then in step two the results are input into the meta learner with its stacked blended output (with the weakest algorithms learning better). A fundamental key to fraud data is that it is inherently not systematic, and an optimal resampling methodology has yet not been identified. Building a test harness, for all permutations of algorithm sample set pairs, demonstrates that the complex, intrinsic data structures are all thoroughly tested. A comparative analysis on fraud data that applies stacked generalizations provides useful insight to find the optimal mathematical formula for imbalanced fraud data sets necessary to improve upon fraud detection for national security.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-11-25T06:31:42Z
      DOI: 10.1177/1548512920962219
  • Determination of integral indicators characterizing the possibility of
           accommodating the evacuated population in the territory of the Republic of
    • Authors: Yernar Zh Akimbayev, Zhumabek Kh Akhmetov, Murat S Kuanyshbaev, Arman T Abdykalykov, Rashid V Ibrayev
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Studying the historical facts of past wars and armed conflicts and natural and man-made emergencies, today in the Republic of Kazakhstan one of the most important security issues is the preparation and organization of the evacuation of the population from possible dangerous zones, taking into account the emergence of new threats to the country’s security. The paper presents an algorithm for constructing universal scales of the distribution function of opportunities by types of support and rebuilding them into subject scales using display functions. The purpose of the paper is to determine the integral indicators characterizing the possibility of accommodation of the evacuated population and the impact on resources during relocation. On the subject scales of cities and districts of the region, indicators of the possibility of relocation of a certain amount of the evacuated population by types of support and indicators characterizing the impact on the district’s resources during resettlement of a certain amount of the evacuated population are determined. It was concluded that the use of integrated indicators allows the selection of areas to accommodate the evacuated population without the use of statistical data, in conditions of incomplete and inaccurate information. The presented method does not replace traditional methods based on classical methods of territory assessment by the level of life sustenance, but also allows their reasonable combination with the experience of specialists in this field, taking into account the incompleteness, uncertainty, and inconsistency of the initial data of the study area, which does not allow the application of existing methods.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-11-25T06:31:29Z
      DOI: 10.1177/1548512920970288
  • Investigation of low-density parity check codes concatenated multi-user
           massive multiple-input multiple-output systems with imperfect channel
           state information
    • Authors: Lokesh Bhardwaj, Ritesh Kumar Mishra, Ravi Shankar
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In this era of communication technology, it is desirable to increase the data rate while minimizing the error to improve the system’s reliability. One of these techniques is massive multiple-input multiple-output (mMIMO), which increases the spectral efficiency by providing the data to multiple users simultaneously through spatial multiplexing. The mMIMO system processes the received signal by prior estimation of the channel, which has a finite variance leading to imperfect channel state information (ICSI) at the receiver. In the fifth-generation technology, spectral efficiency using mMIMO may decrease as the number of subscribers increases, resulting in more interference and affecting system capacity. The ICSI provides another challenge, as the processed data at the receiver’s output may now be more erroneous. Thus, this article provides an insight into the impact of an increase in the number of users on the variation in bit error rate with the signal-to-noise ratio in multi-user mMIMO (MU-mMIMO) and low-density parity check (LDPC) codes concatenated MU-mMIMO systems having ICSI at the receiver for quadrature amplitude modulation (QAM) and 16-QAM as modulation techniques. It has been shown that the performance of the concatenated scheme outperforms the conventional mMIMO system.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-11-17T06:22:41Z
      DOI: 10.1177/1548512920968639
  • A multiresolution simulation system and simulation development processes
    • Authors: Young-Jun Jee, Tae-Gyung Lee, Sang-Ho Park, Jun-Ho Cho, Hee-Soo Kim, Tae-Eog Lee
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Defense modeling and simulation often should run multiple simulation models together to share information on their combat entity states and battlefields and to interact with each other. However, most simulation models were developed by various parties with different purposes, modeling views, and model resolutions. Therefore, it has been challenging to identify differences between the models, transform one’s information for the other models, and manage interoperation between the models. There have been numerous works on multiresolution modeling (MRM) and simulation. However, we yet should have more systematic and integrated methods for designing, managing, and executing the interoperation processes of different simulation models.In this paper, we propose an integrated multiresolution simulation system for designing, developing, simulating, and managing multiple simulation models with different modeling views and resolutions. We propose an architecture, component functions, and processes, including model resolution conversion and management processes, and their Unified Modeling Language models. We also extend the Distributed Simulation Engineering and Execution Processes standard to incorporate MRM design and development processes. Finally, we present a case of MRM design and development of war game models by using the proposed system.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-11-04T05:44:02Z
      DOI: 10.1177/1548512920966107
  • An agent-based modeling approach for simulating the impact of small
           unmanned aircraft systems on future battlefields
    • Authors: Carsten Christensen, John Salmon
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The increasing proliferation of small unmanned aircraft systems (sUASs) is forcing a paradigm shift in military doctrine surrounding counter-sUAS and sUAS deployment tactics. This work describes an agent-based model that incorporates established infantry small unit tactics with the ability to deploy sUASs to aid in surveillance and indirect fire targeting. The model is based on current military doctrine and real warfighter experiences and is presented as a foundation from which additional simulation capabilities and analyses may be created. A series of randomly generated situations sets a defending force with the potential to have sUAS capabilities against a superior attacking force without sUAS capabilities. A control case considers defenders without sUAS capabilities. In six experimental cases, defending forces deploy a single sUAS in one of six patrol patterns as a surveillance and indirect fire targeting tool. Subsequent analysis reveals that sUASs generally increase the odds of defender survival during an engagement and that short-range, concentrated patrol patterns lead to higher odds of defender survival and increased indirect fire opportunities. A battery of analyses showcase the model’s capabilities in terms of exploring novel sUAS implementation strategies and illustrating the impact of those strategies over a range of combat effectiveness metrics.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-29T10:00:15Z
      DOI: 10.1177/1548512920963904
  • How AI founders on adversarial landscapes of fog and friction
    • Authors: Rodrick Wallace
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Formal analysis, based on the asymptotic limit theorems of control and information theories, uncovers sufficient conditions for punctuated failure across the full spectrum of real-time cognitive process – essentially a generalization of the Yerkes-Dodson law – challenging recent assertions that instabilities in AI deep learning paradigms can be easily remedied, permitting their use in real-world critical systems. A temperature analog for cognition that is itself an order parameter is determined by rates of internal information transmission, sensory or intelligence input, and material resource availability. Phase transitions driven by the synergisms of such parameters express symmetry-breaking changes in groupoids characteristic of cognition at and across scales and levels of organization, significantly extending models abducted from physical theory. No modifications of current – or future – AI or other cognitive systems can or will be immune to failure when facing sophisticated adversarial challenge under conditions of friction and the fog-of-war. We indicate how to reconfigure these results for study of long-term conflict on ‘Sun Zu Landscapes’ of deception, deceit, and subtle influence under Lamarckian selection.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-29T09:59:59Z
      DOI: 10.1177/1548512920962227
  • Methods to measure and track population perception and support within a
           manual wargame
    • Authors: Jeremy Smith, Stephen Barker
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The outcomes of military campaigns depend to a large extent on the support of local and other wider population groups, so it is important to understand their perceptions. Here we briefly describe the approach used to represent support for organizations and factions in a professional wargame designed to represent military campaigns. This specific approach was developed originally using a simple marker track system that used a basic quantified set of relationships between military campaign effects and changes to the track levels. This marker track system was developed for military campaign wargames in the UK as a means to portray support or dissent in population groups relevant to the operations, but there was originally no mechanism to drive changes other than by expert judgment. Our improved approach continues the use of marker tracks but attempts to develop a more defensible method based on Maslow’s hierarchy of needs for linking events to changes and levels on the tracks. We conducted experiments to quantify the relative importance of each element in Maslow’s hierarchy. We then continued by conducting a further experiment to identify the impact of a set of effects seen in a wargame against the Maslow elements. This has led to a set of quantified scores that may be used to drive the modifications to the marker tracks when wargame events occur. These scores are based on our initial experiments and may be updated for a specific application, perhaps for a specific setting or location in the world. The revised or enhanced approach aims to produce a transparent solution that can be understood by a military or security analyst, thus facilitating refinement, updating, and change.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-16T06:08:46Z
      DOI: 10.1177/1548512920963203
  • White noise jammer mathematical modelling and simulation
    • Authors: Theodoros G Kostis
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The radar equation is the fundamental mathematical model of the basic function of a radar system. Moreover, there are many versions of the radar equation, which correspond to particular radar operations, like low pulse repetition frequency (PRF), high PRF, or surveillance mode. In many cases, all these expressions of the radar equation exist in their combined forms, giving little information to the actual physics and signal geometry between the radar and the target involved in the process. In this case study, we divide the radar equation into its major steps and present a descriptive mathematical modelling of the radar and other related equations utilizing the free space loss and target gain concepts to simulate the effect of a white noise jammer on an adversary radar. We believe that this work will be particularly beneficial to instructors of radar courses and to radar simulation engineers because of its analytical block approach to the main equations related to the fields of radar and electronic warfare. Finally, this work falls under the field of predictive dynamics for radar systems using mathematical modelling techniques.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-09T06:43:28Z
      DOI: 10.1177/1548512920962224
  • Engineering resilient systems cloud computing architecture (ECCA): a
           collaborative and secure analysis framework
    • Authors: Collin T Blakley, Letitia W Li, Greg Eakman, Brent C Baker
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Design and tradespace analysis of increasingly complex systems often require proprietary models from multiple industrial sources. These multi-partner collaborations require assurances that each company’s intellectual property will remain protected from unauthorized access or disclosure to competitors. In this paper, we present the security risks and considerations for these collaborations, and propose a cloud-based framework to address these concerns. The Engineering Resilient Systems (ERS) Cloud Computing Architecture (ECCA) system enables secure collaboration in the Department of Defense community, providing an infrastructure restricting access to connectable containerized assets: models and simulations, each of which remain isolated and maintained on the owner’s own cloud. ECCA further prevents unauthorized access to sensitive assets and infection by malicious media with an access control system supported by secure gRPC messaging and access agreements. We demonstrate the capability to connect disparate models for a simplified combat simulation and then how the new multi-model scenario enables additional capabilities in tradespace analysis.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-09T06:43:12Z
      DOI: 10.1177/1548512920960539
  • LVC Allocator: Aligning training value with scenario design for envisioned
           LVC training of fast-jet pilots
    • Authors: Sanna Aronsson, Henrik Artman, Mikael Mitchell, Robert Ramberg, Rogier Woltjer
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Live virtual constructive (LVC) flight simulations mix pilots flying actual aircraft, pilots flying in simulators, and computer-generated forces, in joint scenarios. Training resources invested in LVC scenarios must give a high return, and therefore pilots in both live aircraft and simulators need to experience training value for the extensive resources invested in both, an aspect not emphasized in current LVC research. Thus, there is a need for a function, in this article described as LVC Allocator, which assures that complex LVC training scenarios include aspects of training value for all participants, and, thus, purposefully align scenario design with training value. A series of workshops were carried out with 16 fast-jet pilots articulating the training challenges that LVC could contribute to solving, and allocating LVC entities in a training scenario design exercise. The training values for LVC included large scenarios, weapon delivery, flight safety, adversary performance, and weather dependence. These values guided the reasoning of how to allocate different entities to L, V, or C entities. Allocations were focused on adversaries as V, keeping entity types together, weather dependence, low-altitude and supersonic flying requirements, and to let L entities handle and lead complex tasks to keep the human in the loop.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-07T07:31:23Z
      DOI: 10.1177/1548512920958079
  • Cybersecurity threats and experimental testbed for a generator system
    • Authors: Aaron W Werth, SueAnne N Griffith, Jesse R Hairston, Thomas H Morris
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In this work, a high-fidelity virtual testbed modeling a networked diesel generator, similar to those used commercially and by the military, is described. This testbed consists of a physical system model of a generator, a digital control system, a remote monitoring system, and physical and networked connections. The virtual testbed allows researchers to emulate a cyber-physical system and perform cyber attacks against the system without the monetary and safety risks associated with a testbed created from physical components. The testbed was used to feasibly simulate network, hardware Trojan, and software Trojan attacks against the diesel generator, and to observe the cyber and physical outcomes.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-10-07T07:31:08Z
      DOI: 10.1177/1548512920960537
  • Transitioning from testbeds to ships: an experience study in deploying the
           TIPPERS Internet of Things platform to the US Navy
    • Authors: Dave Archer, Michael A August, Georgios Bouloukakis, Christopher Davison, Mamadou H Diallo, Dhrubajyoti Ghosh, Christopher T Graves, Michael Hay, Xi He, Peeter Laud, Steve Lu, Ashwin Machanavajjhala, Sharad Mehrotra, Gerome Miklau, Alisa Pankova, Shantanu Sharma, Nalini Venkatasubramanian, Guoxi Wang, Roberto Yus
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      This paper describes the collaborative effort between privacy and security researchers at nine different institutions along with researchers at the Naval Information Warfare Center to deploy, test, and demonstrate privacy-preserving technologies in creating sensor-based awareness using the Internet of Things (IoT) aboard naval vessels in the context of the US Navy’s Trident Warrior 2019 exercise. Funded by DARPA through the Brandeis program, the team built an integrated IoT data management middleware, entitled TIPPERS, that supports privacy by design and integrates a variety of Privacy Enhancing Technologies (PETs), including differential privacy, computation on encrypted data, and fine-grained policies. We describe the architecture of TIPPERS and its use in creating a smart ship that offers IoT-enabled services such as occupancy analysis, fall detection, detection of unauthorized access to spaces, and other situational awareness scenarios. We describe the privacy implications of creating IoT spaces that collect data that might include individuals’ data (e.g., location) and analyze the tradeoff between privacy and utility of the supported PETs in this context.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-09-23T05:16:56Z
      DOI: 10.1177/1548512920956383
  • Virtual testbed for monocular visual navigation of small unmanned aircraft
    • Authors: Kyung Kim, Robert C Leishman, Scott L Nykl
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Monocular visual navigation methods have seen significant advances in the last decade, recently producing several real-time solutions for autonomously navigating small unmanned aircraft systems without relying on the Global Positioning System (GPS). This is critical for military operations that may involve environments where GPS signals are degraded or denied. However, testing and comparing visual navigation algorithms remains a challenge since visual data is expensive to gather. Conducting flight tests in a virtual environment is an attractive solution prior to committing to outdoor testing. This work presents a virtual testbed for conducting simulated flight tests over real-world terrain and analyzing the real-time performance of visual navigation algorithms at 31 Hz. This tool was created to ultimately find a visual odometry algorithm appropriate for further GPS-denied navigation research on fixed-wing aircraft, even though all of the algorithms were designed for other modalities. This testbed was used to evaluate three current state-of-the-art, open-source monocular visual odometry algorithms on a fixed-wing platform: Direct Sparse Odometry, Semi-Direct Visual Odometry, and ORB-SLAM2 (with loop closures disabled).
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-09-23T05:13:46Z
      DOI: 10.1177/1548512920954545
  • Machine learning in cybersecurity: a comprehensive survey
    • Authors: Dipankar Dasgupta, Zahid Akhtar, Sajib Sen
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Today’s world is highly network interconnected owing to the pervasiveness of small personal devices (e.g., smartphones) as well as large computing devices or services (e.g., cloud computing or online banking), and thereby each passing minute millions of data bytes are being generated, processed, exchanged, shared, and utilized to yield outcomes in specific applications. Thus, securing the data, machines (devices), and user’s privacy in cyberspace has become an utmost concern for individuals, business organizations, and national governments. In recent years, machine learning (ML) has been widely employed in cybersecurity, for example, intrusion or malware detection and biometric-based user authentication. However, ML algorithms are vulnerable to attacks both in the training and testing phases, which usually leads to remarkable performance decreases and security breaches. Comparatively, limited studies have been conducted to understand the essence and degree of the vulnerabilities of ML techniques against security threats and their defensive mechanisms. It is imperative to systematize recent works related to cybersecurity using ML to seek the attention of researchers, scientists, and engineers. Therefore, in this paper, we provide a comprehensive survey of the works that have been carried out most recently (from 2013 to 2018) on ML in cybersecurity, describing the basics of cyber-attacks and corresponding defenses, the basics of the most commonly used ML algorithms, and proposed ML and data mining schemes for cybersecurity in terms of features, dimensionality reduction, and classification/detection techniques. In this context, this article also provides an overview of adversarial ML, including the security characteristics of deep learning methods. Finally, open issues and challenges in cybersecurity are highlighted and potential future research directions are discussed.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-09-19T11:48:45Z
      DOI: 10.1177/1548512920951275
  • Examination of a non-orthogonal multiple access scheme for next generation
           wireless networks
    • Authors: Ravi Shankar
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Non-orthogonal multiple access (NOMA) is an important technique that enables fifth-generation (5G) wireless systems to satisfy the heterogeneous requirements of enhanced fairness, huge connectivity, high performance, low latency, and high reliability. In this work, the NOMA technique for 5G wireless communication is investigated, and considering user fairness limitations, the channel capacity has been optimized. Also, bandwidth efficiency (BE) is examined and the relationship between BE and energy efficiency (EE) is derived. Simulation results show that without wasting power the near user gets preference in power allocation when the target rate is greater than 6.4 bps/Hz. Also, when the target rate [math] 6.4 bps/Hz, the outage performance of the near user will improve and the performance of the far user will remain the same. Also, it is demonstrated that cooperative NOMA outperforms all other techniques. Simulation outcomes confirm that NOMA performs better than conventional multiple access techniques in terms of EE and BE.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-09-14T07:53:02Z
      DOI: 10.1177/1548512920951277
  • Actor–critic-based decision-making method for the artificial
           intelligence commander in tactical wargames
    • Authors: Junfeng Zhang, Qing Xue
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In a tactical wargame, the decisions of the artificial intelligence (AI) commander are critical to the final combat result. Due to the existence of fog-of-war, AI commanders are faced with unknown and invisible information on the battlefield and lack of understanding of the situation, and it is difficult to make appropriate tactical strategies. The traditional knowledge rule-based decision-making method lacks flexibility and autonomy. How to make flexible and autonomous decision-making when facing complex battlefield situations is a difficult problem. This paper aims to solve the decision-making problem of the AI commander by using the deep reinforcement learning (DRL) method. We develop a tactical wargame as the research environment, which contains built-in script AI and supports the machine–machine combat mode. On this basis, an end-to-end actor–critic framework for commander decision making based on the convolutional neural network is designed to represent the battlefield situation and the reinforcement learning method is used to try different tactical strategies. Finally, we carry out a combat experiment between a DRL-based agent and a rule-based agent in a jungle terrain scenario. The result shows that the AI commander who adopts the actor–critic method successfully learns how to get a higher score in the tactical wargame, and the DRL-based agent has a higher winning ratio than the rule-based agent.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-09-14T07:52:43Z
      DOI: 10.1177/1548512920954542
  • A review of the use and utility of industrial network-based open source
           simulators: functionality, security, and policy viewpoints
    • Authors: Uchenna Daniel Ani, Jeremy McKendrick Watson, Madeline Carr, Al Cook, Jason RC Nurse
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Simulation can provide a useful means to understand issues linked to industrial network operations. For transparent, collaborative, cost-effective solutions development, and to attract the broadest interest base, simulation is critical and open source suggested, because it costs less to access, install, and use. This study contributes new insights from security and functionality characteristics metrics to underscore the use and effectiveness of open source simulators. Several open source simulators span applications in communications and wireless sensor networks, industrial control systems, and the Industrial Internet of Things. Some drivers for their use span are as follows: supported license types; programming languages; operating systems platforms; user interface types; documentation and communication types; citations; code commits; and number of contributors. Research in these simulators is built around performance and optimization relative to flexibility, scalability, mobility, and active user support. No single simulator addresses all these conceivable characteristics. In addition to modeling contexts that match real-world scenarios and issues, an effective open source simulator needs to demonstrate credibility, which can be gained partly through actively engaging experts from interdisciplinary teams along with user contributions integrated under tight editorial controls. Government-led policies and regulations are also necessary to support their wider awareness and more productive use for real-world purposes.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-09-10T05:59:52Z
      DOI: 10.1177/1548512920953499
  • An Analytic Hierarchy Process approach using multiple raters for the
           selection of complex technologies
    • Authors: James B Wood, Jessica L Mason, Alessandra Bianchini
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The Department of Defense utilizes complex technologies in numerous fields; each technology must comply with specific parameters and system capabilities. In this selection of a complex technology best meeting prescribed capabilities, the parameter set includes nine areas, which have sub-areas. To handle the complexity of the process, the team identified the Analytical Hierarchy Process (AHP), a methodology providing a reliable solution. The AHP produced an importance coefficient for each area and sub-area, which were combined in the final phase of the ranking process. Users and technical support personnel agreed that the selected system met the requirements, field operational needs, and maintenance requisites. The AHP approach represents a viable tool to handle group decisions in support of technology management and related selection processes.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-08-26T05:52:57Z
      DOI: 10.1177/1548512920949911
  • Multicriteria analysis of firefighter routes in buildings in the case of a
    • Authors: Hai T Nguyen, Nikolay G Topolsky, Denis V Tarakanov, Alexander V Mokshantsev
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In buildings, in case of fire, the forming of routes is of primary importance and will make it possible to identify areas that collapse or allow smoke to spread, eliminating potential threats. These include locations with people who were in the building at the beginning of the fire or explosive objects of mainly domestic use. The purpose of the research is to determine the main criteria when the route of firefighter groups is based on minimizing the likelihood of getting into dangerous situations and increasing the efficiency of firefighting. It mainly used the simulation method, which required setting the problem in conditions when not only were the foci of smoke spread and the fire itself not completely known, but also situations where another firefighter group could stay in the building. It was determined that the criteria that must be taken into account when forming the firefighters’ route in the building, met the requirements for the route formation in the event of a collision with other firefighter groups and determined the likelihood of synchronous movement when detecting dangers not previously anticipated when monitoring factors.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-08-26T05:52:30Z
      DOI: 10.1177/1548512920948611
  • Size and History Combine in Allometry Relation of Technology Systems
    • Authors: Bruce J. West, Damien West, Alexander Kott
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Complex systems often exhibit amazingly regular behavior through allometry relations (ARs) between their functional attributes and their size. An empirical allometry relation (EAR) between two properties of a complex system relates the average functionality [math] and the average size [math][math] = a[math] where the allometry coefficient a and allometry exponent b are empirical constants fit to data. This EAR is a static relation and is found in every sub-discipline of Natural History. Herein we establish, both empirically and theoretically, that for some classes of evolving technology systems, the empirical allometry coefficient a is not constant, but is strongly dependent on the historical time at which the technology system originated. Specifically, we construct an EAR with a time-dependent coefficient, using the evolution of a broad class of military systems, over the last ten centuries, ranging from a medieval bowman to a modern rifleman, from a horse-drawn cannon to a tank. This time-dependent EAR is derived from fundamental considerations involving complexity, scaling, and renormalization group theory. The theory entails an information as well as complexity generalization of the traditional allometry coefficient that combines system size with the technology knowledge of the new system’s developers (time-dependence). It relates technology ARs to technology evolution relations, such as Moore’s Law, with implications for technology drawn from biological evolution analysis.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-07-27T10:53:38Z
      DOI: 10.1177/1548512920942327
  • Modeling fast jet infrared countermeasures: Pseudo-imaging seekers with an
           ultraviolet guard band
    • Authors: A Glover, M A Richardson, N Barlow
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In 2012, a study looking back 35 years indicated that 90% of all aircraft losses in battle were caused by infrared (IR) guided missiles. Man portable air defense systems are a cheap and prolific resource for both state and non-state actors that enables the employment of IR guided missiles. As such, significant time is required to be invested in developing effective countermeasures to ensure a fast jet can attain and sustain air superiority in operations.This article will provide a summary of the thesis by Glover (Glover AX. Electro-optic countermeasure modelling in a fast jet environment: rosette scanning seekers with an ultraviolet guard band. Thesis, Cranfield University, 2019) that aimed to develop a myriad of IR-based countermeasure techniques. Specifically, when pseudo imaging, a rosette scan IR seeker is employed against a fast jet with an ultraviolet guard band counter-countermeasure.A series of seven trials was simulated using Chemring’s CounterSim program to produce a spread of results based on the developed technique’s effectiveness. Several of these trials produced outcomes with a probability of escaping hit greater than 97% across a range of altitudes. The successful techniques involve an assortment of concepts, including employment of spectral flares, aircraft maneuvering, multi-flare patterns, and the notion of masking.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-07-15T09:59:16Z
      DOI: 10.1177/1548512920938876
  • Layout optimization of a military operations center using a genetic
    • Authors: Wenbi Wang
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      A genetic algorithm was developed to support the spatial layout design of military operations centers. Based on an abstract representation of the workplace, the algorithm uses a textual string as the genetic encoding method, two genetic operations (i.e., selection and swap) for simulating an evolution process, a fitness function that reflects a human factors characterization of workplace layout requirements, and an elitist strategy for improving its search efficiency. The effectiveness of the algorithm was demonstrated in the design of a mid-sized operations center that involved a team of 68 operators. This algorithm expands the human factors practitioners’ toolkit and enhances their ability to examine layout options of complex workplaces using modeling and simulation.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-07-14T08:54:28Z
      DOI: 10.1177/1548512920937077
  • Methodology for analysis of heavy vehicle trafficability in deformable
    • Authors: Elias Dias Rossi Lopes, André Flora Alves Pinto, Moisés Xavier Guimarães Valentim, Pedro Siciliano Peixoto, Gustavo Simão Rodrigues, Ricardo Teixeira da Costa Neto
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Heavy vehicles have a wide range of applicability in our daily lives: buses, commercial trucks, and even defense vehicles are important to transport people and goods and provide protection. However, this field is not widely covered by the scientific literature in many aspects regarding their dynamic behavior, as most works tend to focus on personal vehicles (cars). This article elaborates on heavy vehicle trafficability on many different terrains or their capacity to operate in those soils, using an analysis based on the Wong–Reece method with deformable soil–rigid tire approximation. It also develops a dynamic model, using MATLAB SimulinkTM software, to show how heavy vehicle performance both kinematically and dynamically is influenced by the soil. To test both models, a numerical case study was conducted, using common parameters for wheeled heavy vehicles as inputs for the dynamic. Results indicate that heavy vehicles are often incapable of operating in highly deformable soils, sinking deeply into the ground; the soil also affects heavily the vehicle maximum velocity and gear from almost [math] km/h in Greenville Loam soil to less than [math] km/h in Upland Sandy Loam soil.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-06-29T08:33:18Z
      DOI: 10.1177/1548512920934549
  • Estimation of cyber network risk using rare event simulation
    • Authors: Alexander L Krall, Michael E Kuhl, Shanchieh J Yang
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Inherent vulnerabilities in a cyber network’s constituent machine services can be exploited by malicious agents. As a result, the machines on any network are at risk. Security specialists seek to mitigate the risk of intrusion events through network reconfiguration and defense. When dealing with rare cyber events, high-quality risk estimates using standard simulation approaches may be unattainable, or have significant attached uncertainty, even with a large computational simulation budget. To address this issue, an efficient rare event simulation modeling and analysis technique, namely, importance sampling for cyber networks, is developed. The importance sampling method parametrically amplifies certain aspects of the network in order to cause a rare event to happen more frequently. Output collected under these amplified conditions is then scaled back into the context of the original network to provide meaningful statistical inferences. The importance sampling methodology is tailored to cyber network attacks and takes the attacker’s successes and failures as well as the attacker’s targeting choices into account. The methodology is shown to produce estimates of higher quality than standard simulation with greater computational efficiency.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-06-27T08:35:10Z
      DOI: 10.1177/1548512920934551
  • Command and its discontents: Instabilities of institutional anytime
           algorithms on a Clausewitz landscape
    • Authors: Rodrick Wallace
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      It has long been understood that the inevitably time-constrained cognitive processes of command on a Clausewitz landscape of uncertainty and imprecision are subject to gross instabilities. Even very experienced, capable, and intelligent command teams lose wars. Using formal approaches from control and information theories, we show how failure to understand and recognize underlying structure and dynamics in organized conflict expresses itself as increased “noise,” eventually triggering strategic collapse, often in a highly punctuated manner
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-06-18T12:31:16Z
      DOI: 10.1177/1548512920931597
  • Modelling militarized interstate disputes using data mining techniques:
           Prevention and prediction of conflicts
    • Authors: Petr Stodola, Jozef Vojtek, Libor Kutěj, Jiří Neubauer
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The use of modern data mining techniques on large datasets has become a recent phenomenon across a broad range of applications. One of the most frequent tasks is to build statistical models using historical data and utilize them to predict new, so far unclassified, cases. This article examines the problem of predicting a military interstate dispute between two states (dyad) by employing selected data mining techniques. Suitable methods are identified and applied to the existing dataset of politically relevant dyads. The result is the building of statistical models for the classification of potential dyadic conflicts. The overall performance of these models is verified and cost analysis is done based on the different impacts of incorrect classification. The results are compared with those of other published research studies in the field of conflict prediction; the models created by data mining techniques significantly outperform all rival algorithms and approaches. Finally, the last part of the article presents the results of applying data mining techniques to association, i.e. to discovering relationships and dependencies in the data.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-05-28T06:20:51Z
      DOI: 10.1177/1548512920925178
  • Model of an alternative navigation system for high-precision weapons
    • Authors: Vitalii Savchenko, Volodymyr Tolubko, Liubov Berkman, Anatolii Syrotenko, Pavlo Shchypanskyi, Oleksander Matsko, Vitalii Tiurin, Pavlo Open’ko
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The article explores the problem of alternative navigation support for high-precision weapons that use guidance based on signals from global navigation systems. It proposes the use of an autonomous navigation system replacing satellite navigation in the case where major Global Positioning System-like systems are unavailable. It suggests the idea and the model of a moving navigation field that can move along the weapon trajectory. The model of accuracy for the pseudolite navigation system uses the least squares method as its basis. The study looks into the accuracy parameters of the moving navigation field. The results of the study show the advantages of a moving field when compared with a stationary navigation field in case of autonomous use. This research also shows the possibility of using an autonomous system for Special Forces, search and rescue operations, and robotic and unmanned aerial, ground, and sea-based vehicles.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-05-27T09:09:20Z
      DOI: 10.1177/1548512920921955
  • Immediate decisions based on long-term consequence evaluation for a
           radiological event
    • Authors: Tercio Brum, Sergio X Lima, José Carlos C Amorim, Ricardo M Stenders, Matjaž Prah, Helio C Vital, Edson R Andrade
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      This validation study focuses on potential risks and subsequent challenges, such as family dismemberment due to the response to an off-site radiological release. Threats that may drive early decisions from a long-term perspective, such as cancer development, were discussed. In order to provide radiation doses, environmental measurements were performed by using a military helicopter. Such data was then inserted into the BEIR VII equations to evaluate the excess relative risk (ERR) of leukemia. However, there may be an issue in the initial phase of the response. Family dismemberment becomes practical due to the different radiation sensitiveness, which is a function of age and sex. Such a situation may arise from requirements posed both by the immediate response and future concerns (ERR). Evaluation of the results suggests that children and young women are more vulnerable than adults. A more detailed study focused on the most appropriate mathematical method to determine the moment in which family dismemberment, if necessary, should be conducted. This sensitive issue is very important during the early phase of the response due to the fact that it can greatly influence future decisions by anticipating possible consequences that have a large potential to influence the evolution of future costs.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-03-06T10:55:28Z
      DOI: 10.1177/1548512920908665
  • Adaptive leader election for control of tactical microgrids
    • Authors: Robert S Jane, Steven Y Goldsmith, Gordon G Parker, Wayne W Weaver, Denise M Rizzo
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      An adaptive leader election protocol (LEP) was developed to control both stationary and mobile generation assets (generators and vehicles), achieved using an energy management system (EMS). The LEP algorithm adapts to changes in both topology and the asset inventory using the longevity criterion (available fuel, future availability), used to compute a desirability index, for election of a leader. The leader then implemented an optimal power flow EMS to ensure sufficient and optimal power flow within the electrical network was maintained in the presence of a complex electrical load, regardless of the asset mix. Both the LEP and EMS algorithms were distributed to the generation assets. This capability supports stationary grid-tied, vehicle-to-grid, and mobile vehicle-to-vehicle-based applications. Simulated case studies illustrate that the adaptive LEP was resistive to deterministic events (maintenance, available fuel), which could yield an inoperable asset, compromising grid stability. The use of the adaptive LEP resulted in a communication complexity of at most [math]; in contrast, a fully connected communication system requires [math] communications, limiting the scalability of the network. The EMS was optimized, resulting in a computationally efficient and scalable optimal power flow algorithm that can be extended for more general stationary or mobile energy networks.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-03-06T10:53:12Z
      DOI: 10.1177/1548512920904785
  • How the enemy gets a vote: Fog-of-war, friction, and the cultural
           riverbanks of the Clausewitz landscape
    • Authors: Rodrick Wallace
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Institutions are not “simply” cognitive entities composed of shifting, tunable networked coalitions of cognitive subcomponents. Institutions are cultural artifacts that, through the epigenetic modes of historical trajectory and the Lamarckian heritage of doctrine, have distinct cultural identities. Individual sleep patterns, hypothalamic–pituitary–adrenal axis and immune responses, and so on, are powerfully modulated by culture. Institutional responses to patterns of stress or affordance are no less culturally influenced, and, we suggest, using mathematical and statistical models based on the asymptotic limit theorems of information and control theories can be manipulated to punctuated failure by appropriate “messages.” Outcomes then revolve not only around the balance of effort and effect between combatants, but on the ability to generate and enlist fog-of-war and friction as effective weapons. However, cultural riverbanks work both ways, and the US national security enterprise remains severely constrained by its own set.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-02-29T09:11:29Z
      DOI: 10.1177/1548512920906471
  • Atmospheric turbulence model for direct fire ballistics
    • Authors: Tomas Bober, Thomas Recchia
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      Modern system accuracy studies require high fidelity representations of environmental phenomena in order to accurately predict the down range performance of a gun system. One component of the atmosphere that has not been studied in great detail within the ballistic domain is turbulence. The current portrayal of wind leveraged by system analysis efforts ignores this element of atmospheric motion completely and thus its effects on down range dispersion have not been quantified. As a first step in addressing this deficiency, this study develops a methodology for generating synthetic turbulent wind signals along the flight path of a projectile. This goal is accomplished by integrating the work of several authors, developing techniques to fill knowledge gaps, and tailoring the solution to the direct fire domain. The significant contributions of the presented effort include mean flow direction agnostic spectral functions, provisions to account for the non-homogeneity of turbulence parameters along a trajectory, and a higher fidelity signal generation method than was used in previous work. The new information is applied to a sample engagement scenario in order to demonstrate the realization of the given techniques within the small caliber direct fire domain.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-02-26T06:23:57Z
      DOI: 10.1177/1548512920906476
  • Mean wind model for direct fire ballistics
    • Authors: Tomas Bober, Thomas Recchia
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      The depiction of wind used in modern system accuracy studies directly influences the design of precision-oriented weapon platforms. Therefore, the primary objective of the effort presented within was to develop a literature-supported definition of the battlefield wind environment relevant to direct fire combat engagements. This goal was accomplished by incorporating modern micrometeorological theory into the ballistic domain in order to define the mean wind along the flight path of a projectile. This information was then further leveraged to develop a description of the generic battlefield mean wind environment. The final portion of the effort compared the new and legacy wind models within a sample engagement scenario in order to quantify the differences between the two portrayals of atmospheric motion within the quasi-combat domain. The results of the work conducted indicate that the traditional view of wind tends to overestimate its contribution to the outcome of an engagement. While this single study does not completely invalidate the legacy approach to wind modeling in direct fire ballistics, it does warrant further investigation into the topic, as a more rigorous representation of atmospheric motion would ultimately lead to the production of more accurate weapon systems.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-02-19T09:39:35Z
      DOI: 10.1177/1548512920902265
  • Emerging approaches to support dynamic mission planning: survey and
           recommendations for future research
    • Authors: Matthew Henchey, Scott Rosen
      Abstract: The Journal of Defense Modeling and Simulation, Ahead of Print.
      In the Department of Defense, unmanned aerial vehicle (UAV) mission planning is typically in the form of a set of pre-defined waypoints and tasks, and results in optimized plans being implemented prior to the beginning of the mission. These include the order of waypoints, assignment of tasks, and assignment of trajectories. One emerging area that has been recently identified in the literature involves frameworks, simulations, and supporting algorithms for dynamic mission planning, which entail re-planning mid-mission based on new information. These frameworks require algorithmic support for flight path and flight time approximations, which can be computationally complex in nature. This article seeks to identify the leading academic algorithms that could support dynamic mission planning and recommendations for future research for how they could be adopted and used in current applications. A survey of emerging UAV mission planning algorithms and academic UAV flight path algorithms is presented, beginning with a taxonomy of the problem space. Next, areas of future research related to current applications are presented.
      Citation: The Journal of Defense Modeling and Simulation
      PubDate: 2020-02-07T10:00:30Z
      DOI: 10.1177/1548512919898750
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