Integrative Use of Information Extraction, Semantic Matchmaking and Adaptive Coupling Techniques in Support of Distributed Information Processing and Decision-Making

In order to press maximal cognitive benefit from their social, technological and informational environments, military coalitions need to understand how best to exploit available information assets as well as how best to organize their socially-distributed information processing activities. The International Technology Alliance (ITA) program is beginning to address the challenges associated with enhanced cognition in military coalition environments by integrating a variety of research and development efforts. In particular, research in one component of the ITA ('Project 4: Shared Understanding and Information Exploitation') is seeking to develop capabilities that enable military coalitions to better exploit and distribute networked information assets in the service of collective cognitive outcomes (e.g. improved decision-making). In this paper, we provide an overview of the various research activities in Project 4. We also show how these research activities complement one another in terms of supporting coalition-based collective cognition

Analysis of Vehicle Use Patterns during Military Field Exercises to Identify Potential Roads

Military training is an intensive land use and can cause negative environmental effects. Many studies conducted under Integrated Training Area Management (ITAM) for quantifying the impact resulted from the military training exercise found that off-road vehicular activities during training exercises cause the major impact to the training land. Vehicle land use patterns at a certain location affect the impact severity: concentrated and repeated traffic create more serious damage to the land compared to the dispersed offroad vehicle movements. Those areas heavily disturbed by off-road traffic may require a longer period of time or special treatments for the land to return to its pre-disturbed status. Based on the impact severity and the shape of the disturbed area, some areas can be considered as potential roads, defined as the roads newly formed by concentrated offroad traffic during the military training exercises, or the roads currently exist but have not been mapped. Potential roads need to be rehabilitated, have traffic dispersed to return the land to its natural status, or to be included in the established road construction and maintenance programs. As Global Positioning System (GPS) has been used for monitoring vehicles\u27 activities during military training exercises; it enables the analysis of vehicle movement patterns. The vehicle movement patterns are characterized as the percentage of vehicle travel every day, vehicles\u27 on and off road travel, the frequencies of vehicle\u27s off-road velocity and turning radius. GPS vehicle tracking data collected during an eight-day reconnaissance training exercises in Yakima Training Center (YTC) in October 2001 were analyzed for vehicle movement patterns. Comparison of the on-road and off-road movement patterns indicates that potential roads may exist on the locations where the concentrated traffic or a high speed movement occurred. Based on the analysis of the movement patterns, factors were extracted to characterize the special movement patterns that indicate the vehicles moved on a potential road. The YTC was divided into small study units, and a multicriteria method was developed to determine if a study unit is a portion of a potential road. The multicriteria method was evaluated by comparing the predictions to the site visit results on 34 selected road segments that met different criteria levels. Results show that locations met higher criteria levels have higher possibilities to be roads: the location met all five criteria has an approximately 91% possibility for road existence; those met four criteria has an approximately 55% possibility; and for those met criteria level two or three, there is an approximately 14% probability for road existence. The analysis of updated off-road shows the percentage of vehicle off-road movement drops from 20.0% to 15.8% after excluding the potential road moving data. As an alternative method, a neural network approach for identifying the potential roads was introduced and compared to the multicriteria method. The neural network method obtained an approximately 85% accuracy when tested by on-road grids, successfully identified the high-way segment as road, and predicted approximately 31% off-road grids as potential road grids. Results show that the neural network method, although emphasized in factors different from the multicriteria method, has approximately 78% accuracy for identifying the potential road locations. The prediction from the neural network method was found highly correlated to the one of the criterion: vehicles travel in different directions. Simplified methods were also developed to identify potential roads by investigating the GPS point density, vehicle velocity, and the number of passes within a study unit. A simple linear relationship was found between the number of passes and the possibility for road existence. Although using vehicle velocity for identifying the potential roads may not be the best choose, velocity is still considered as one of the most important features to characterize vehicle movements and to locate special movement patterns. Considering the discrete situation in the predicted potential road areas, a kernel smoothing technique was introduced and applied to smooth the results to improve the continuity of the potential roads. The application found the kernel smoothing technique was able to obtain continuous potential road grids by selecting reasonable bandwidth

Handbook of Emergency Management For State-Level Transportation Agencies, MTI Report 09-10

The Department of Homeland Security has mandated specific systems and techniques for the management of emergencies in the United States, including the Incident Command System, the National Incident Management System, Emergency Operations Plans, Emergency Operations Centers, Continuity of Government Plans and Continuity of Operations Plans. These plans and systems may be applied to the state-level transportation agency�s disaster response systems to enhance efficiency and effectiveness. Specific guidance and management techniques are provided to aid emergency planning staff to create DHS-compliant systems

THE EFFECT OF UNREPORTED DEMAND ON THE ​F/A-18’S SUPPLY CHAIN

This research investigates the causes of unreported demand associated with F/A-18 aircraft components during the execution of cannibalization and the issuance of repairable parts from the Stricken Aircraft Reclamation and Disposal Program (SARDIP). The current transition to the F-35 Joint Strike Fighter across the entire Marine Corps F/A-18 Type Model Series (TMS) platform provides an opportunity to research and analyze various aspects of the divestiture process. During the divestiture period of the F/A-18 platform, missing demand signals lead to inaccuracies in demand forecasting. This inaccurate demand capture increases stress on the supply system and future funding requirements within the organization. This study analyzes five years of demand data gathered from the Navy Enterprise Resource Planning (ERP) system in order to identify causes and sources of lost demand associated with cannibalization and SARDIP issues. In addition, this study presents an analysis of current Marine Corps aviation supply policies and cannibalization actions to identify shortfalls in demand reporting. The data gathered suggest that unreported demand leads to increases in demand variability and the ability to allocate funds for F/A-18 components. Although the impacts of unreported demand for the F/A-18 will disappear once the platform is no longer in service, unreported demand will continue to affect all aircraft remaining in service.Captain, United States Marine CorpsCaptain, United States Marine CorpsMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

SIMULATING CONSUMABLE ORDER FULFILLMENT VIA ADDITIVE MANUFACTURING TECHNOLOGIES

Operational availability of naval aircraft through material readiness is critical to ensuring combat power. Supportability of aircraft is a crucial aspect of readiness, influenced by several factors including access to 9B Cognizance Code (COG) aviation consumable repair parts at various supply echelons. Rapidly evolving additive manufacturing (AM) technologies are transforming supply chain dynamics and the traditional aircraft supportability construct. As of June 2022, there are 595 AM assets within the Navy’s inventory—all for research and development purposes. This report simulates 9B COG aviation consumable fulfillment strategies within the U.S. Indo-Pacific sustainment network for a three-year span, inclusive of traditional supply support avenues and a developed set of user-variable capability inputs. Simulated probabilistic demand configurations are modeled from historical trends that exploit a heuristic methodology to assign a “printability” score to each 9B COG requirement, accounting for uncertainty, machine failure rates, and other continuous characteristics of the simulated orders. The results measure simulated lead time across diverse planning horizons in both current and varied operationalized AM sustainment network configurations. This research indicates a measurable lead time reduction of approximately 10% across all 9B order lead times when AM is employed as an order fulfillment source for only 0.5% of orders.NPS Naval Research ProgramThis project was funded in part by the NPS Naval Research Program.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Cognisance as a Human Factor in Military Cyber Defence Education

The authors may share the final published article on public non-commercial sites in the terms of the Creative Commons CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/. Additionally, the authors may use the article in a subsequent compilation of their work, or extend it to book length form, or include it in a thesis or dissertation, or otherwise to use or re-use portions or excerpts in other works, for both commercial and non-commercial purposes. All copies of the article should link to the original publication in IFAC PapersOnline via its DOI and have a copyright statement and a reference to the CC-BY-NC-ND license. Except for such uses, IFAC has the exclusive right to make or sub-license commercial useCyber Defence Exercises (CDX) are common training and learning tools. A recently discussed challenge in cyber defence teaching and training is the gap between the fast technological advancement accompanied by rapidly changing demands on future cyber defence operators, and the lack of science-based teaching and training methods. A growing body of evidence suggests a crucial role of human factors as a central predictor for human performance in sociotechnical systems. While this has been acknowledged in a wide range of safety-critical applied fields, there is still a lack of knowledge about the impact of human factors on cyber defence performance. The lack of conventional metrics of performance and learning progress contribute to this deficit. To address this gap, the Norwegian Defence Cyber Academy (NDCA) follows a science-based educational approach that identified in a series of empirical studies cognitive-psychological predictors for learning success of future cyber defence operators. These predictors and elements of a human factors research program are deeply embedded into educational practice and include processes such as metacognition, self-regulation, coping, communication and shared mental modelling. Slow education methods and mentoring are fundamental to enabling the advancement of human factors cognisance among military cyber cadets. As a tool for efficient training, the NDCA developed and implemented a mentoring concept that involves a cyber defence retrospective timeline analysis involving expert and practitioner level mentors. The timeline differentiates between performance relevant hard-and soft-skills and leads progressively towards an alignment of Security Operation Centre (SOC)-and expert judgments of performance. The NDCA argues that this educational concept facilitates educational benefits based on insight, accurate self-perception, motivation and decreased team workloads following more efficient collaboration.publishedVersio

A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

Modeling Transnational Terrorists\u27 Center of Gravity: An Elements of Influence Approach

Since the September 11th terrorist attack, there has been an increased emphasis on understanding and modeling terrorists groups. While several efforts have focused on identifying transnational terrorists\u27 centers of gravity (COGs), most of these efforts have proposed COGs using a traditional nation-state paradigm. In today\u27s global village , terrorist groups are no longer limited by locality and national boundaries. With the increasing threats from transnational terrorist groups, new paradigms and models are necessary to properly analyze today\u27s, and tomorrow\u27s, conflict. Analysis should be based on the identified and quantified transnational terrorists\u27 COGs and their associated interactions. Unfortunately, not all of the transnational terrorists\u27 COGs and their interconnected cause and effect relationships are fully known or understood. This research effort suggests a single COG, Public Support as the transnational terrorists\u27 key driver. An influence diagram-like approach was used to collect, organize, and display the COG and its key elements of value. These qualitative influence diagrams serve as a basis to develop a system dynamics model where quantitative measures were applied to the interactions. A prototype model capable of capturing and utilizing time-persistent and higher order effects that provides insight to decision makers regarding alternative strategic policies and courses of action (COA) against transnational groups has been developed and illustrated against a notional transnational terrorist group