In recent years the concept of emergence has captured significant attention in the field of complex systems. However, the inability to predict and control emergent phenomena prevents us from exploring its full potential. The research effort in this paper focuses on exploring emergent behaviors by proposing a framework for analysis of systems that exhibit such behaviors. The framework provides a platform for simulating and analyzing behaviors in multi-agent system, including detection and classification of emergence into different types. In this paper, we follow the classification of emergent behaviors according to Fromm's taxonomy. In addition, the paper presents a scenario implementation using swarms of Unmanned Aerial Vehicles (UAVs) to demonstrate the applicability of the proposed approach. Since this is a part of on-going research, future direction is also discussed.

The need for active orbital debris remediation has increasingly gained acceptance throughout the space community throughout the last decade as the threat to our assets has also increased. While there have been a wide variety of conceptual solutions proposed, a debris removal system has yet to be put in place. The challenges that stand in the way of action are formidable and range from technical to political to economic.

Defining the Core Body of Knowledge (CorBoK) for a Graduate Program in Systems Engineering: A Work in ProgressAbstractAs part of the Body of Knowledge and Curriculum to Advance Systems Engineering (BKCASE™) project, a Graduate Reference Curriculum for Systems Engineering (GRCSE™) is being developed to assist in the improvement of existing or development of new graduate programs in systems engineering. The goal of GRCSE is to provide a curriculum framework to institutions for both developing and communicating their system engineering graduate program content so that there is a more common understanding of the content that is addressed within the programs and more consistency across the programs. Yet the framework is also designed so that institutions can preserve their unique specialties and university-­‐specific requirements. One of the many challenges in defining GRCSE has beenidentifying a feasible approach for defining the core body of systems engineering knowledge thatevery graduate student should be exposed to prior to graduating from the program. GRCSE defines this core body of knowledge (CorBoK) as the set of core topics recommended for inclusion in every professional Masters program; with the intent that mastery of the content of these core topics is required of all graduates. The CorBoK is comprised of two parts: 1) the truly common part: the core foundation to be learned by everyone who goes through a master’s program, and 2) a core concentration that favors one of several emphases. An institution can choose to implement one or more of the concentration areas. The idea is that a student would select an available concentration area and learn the corresponding extension of core knowledge in that area, in addition to the knowledge in the core foundation, as part of the CorBoK of the program. GRCSE intentionally limits the CorBoK to no more than 50% of the total knowledge conveyed in a graduate systems engineering program in order to encourage and enable wide variation across institutions and to accommodate unique emphases in other areas. This paper describes the approach used to define the CorBoK in the version 0.5 draft of GRCSE released in December 2011; the challenges associated with developing the approach; and the strengths and weaknesses of the approach. The paper then describes considerations and future plans under development for defining the final CorBoK for the version 1.0 release of the GRCSE scheduled for public release in December 2012.

A software-based test battery was developed for cursor control device evaluation. Five tasks were taken from ISO 9241-9, and four from studies conducted at NASA. The tasks focus on basic movements such as pointing, clicking, and dragging. The test battery allows for standardized comparisons across input devices through use of a standard suite of basic tasks and data collection software. The test battery can also be used for other types of investigations (e.g., gloved vs. ungloved performance). The demonstration will showcase the software and give the audience the opportunity to operate various cursor control devices using the tasks in the test battery.

Circadian rhythms cause alertness declines at night, producing performance decrements across cognitive domains and tasks. Building on the learning mechanisms for declarative knowledge instantiated in the ACT-R cognitive architecture, this research seeks to explain the effects of circadian rhythms on performance of an orientation task performed repeatedly across two weeks by participants working either day or night shifts. The differences in performance between the two groups are best explained by varying the decay rate in declarative knowledge as a function of the time of day the task was performed. The model accounts well for task learning reflected in decreases in response times across days, as well as differences in learning between the day and night shift conditions.

PreviousNext No Access12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15–18 August 2011The growth of airborne gravity gradiometry – and challenges for the futureAuthors: Daniel DiFrancesco*Lockheed MartinDaniel DiFrancesco*Search for more papers by this author and Lockheed MartinSearch for more papers by this authorhttps://doi.org/10.1190/sbgf2011-104 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract In recent years there has been a continuing and growing interest in airborne gravity and gravity gradiometer capabilities. This attention implies both that significant achievements have been realized and that we have not yet arrived at the optimal capability – and that the process continues to find even better solutions. Advances in sensor systems, operational efficiency, data processing, and interpretation have all contributed to improved offerings to the market. Acceptance and interest by industry is evidenced by the numerous focused workshops, publications, and investment over the past decade. The prospect for greater usage is tempered a bit by the lack of definitive success stories and relatively high cost. The future for airborne gravity is also clouded by a number of questions: How much does airborne gravity help achieve the ultimate objective of finding more resources? What is the value of information (VOI) to the commercial market? What is lacking in order for airborne gravity to achieve full potential? With a view towards the future, it is also instructive to ask, “Where will airborne gravity be in five or ten years?” Keywords: gravity, magnetics, processing, interpretation, airborne surveys, electromagneticsPermalink: https://doi.org/10.1190/sbgf2011-104FiguresReferencesRelatedDetailsCited byFull Tensor Gradiometry 12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15–18 August 2011ISSN (online):2159-6832Copyright: 2011 Pages: 2223 publication data© 2011 Published in electronic format with permission by the Brazilian Geophysical SocietyPublisher:Society of Exploration Geophysicists HistoryPublished Online: 13 Mar 2014 CITATION INFORMATION Daniel DiFrancesco* and Lockheed Martin, (2011), "The growth of airborne gravity gradiometry – and challenges for the future," SEG Global Meeting Abstracts : 498-501. https://doi.org/10.1190/sbgf2011-104 Plain-Language Summary Keywordsgravitymagneticsprocessinginterpretationairborne surveyselectromagneticsPDF DownloadLoading ...

We propose a Deception Robust Control (DRC) for orchestrating the cyber sensors and cyber effectors present in typical enterprise information network systems operating in the ever changing situations that arise in servicing their missions. The theory and exemplar of deception control of focus here-though motivated by conventional warfare-applies to any partial information asymmetric stochastic game, including cyb er defense. We first motivate the need for automated deception reasoning in cyber defense, then provide a brief outline of the elements of a generic Deception Robust Controller (DRC), leading to the discussion on the challenges in adapting the centralized DRC to inherently distributed problems arising in cyber defense, and finally discuss our attempts to meet those challenges successfully.

Our global security environment is increasingly affected by biological systems. From the threats of pandemics and bioterrorism to the exploding cost of health care, developing the means to effectively and affordably solve problems related to biological systems is critical to our quality of life. When considering health care costs, the numbers are staggering. Approximately half of the $2.4 trillion spent annually on US health care can be categorized as preventable costs, and $300 billion of this is attributable to medical mistakes and the defensive medicine they engender. Just as the use of flight simulators and system integration concepts revolutionized the aircraft industry decades earlier, similar concepts can be applied to improve the effectiveness and efficiency of the health care industry today. Our approach is intended to leverage advanced modeling and simulation techniques to accurately represent complex clinical environments. By creating hierarchical simulated models of these systems and then validating these models against their real-world equivalents, we are able to develop a virtual system-of-systems integration laboratory for clinical environments. As with comparable tools in aviation, our goal is for simulationbased tools for health care to make analysis and training fast, safe, measureable, and reproducible. This will be a significant step forward in health care, which has trailed other fields in the adoption of software simulations, due to technological limitations and behavioral barriers. We believe that a holistic approach such as this will pave the way for the next generation of decision support aids, medical devices, and training systems for applications across the health care spectrum. In this paper, we outline our approach with detailed examples of potential savings for a number of complex clinical scenarios.