Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 36-39).

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 257-268). Also available on the World Wide Web.

This study aims to investigate the naturalistic decision-making role of business intelligence (BI) in the oil and gas (O&G) industry. O&G organisations spend a lot of time, effort and resources in maximising their operations to gain a competitive advantage. With the introduction of technological solutions, BI provides organisations with the ability to collect, sort, analyse and transform data into timely intelligence. However, the industry is characteristically competitive, difficult to predict and continuously changing with decision-makers sometimes faced with naturalistic decisions necessitating quick decisions under pressure, strict timeframes and with incomplete data. Literature on the role BI in the O&G industry has been minimal, with the focus being on how BI is used to assist rational decision-making. This study relies on data collected from two O&G organisations operating in different streams of the industry. Using a dynamic model of situated cognition, this study employs an interpretive, qualitative approach to data analysis in an attempt to fill the gap in the literature and determine whether BI plays any role in facilitating the decision-making process in response to naturalistic decisions. A dynamic model of situated cognition has been employed because of its strong correlation with naturalistic decision-making (NDM). The findings of this study indicate that different naturalistic decisions exist in the two streams of the industry and these decisions vary in their levels of complexity and domains. Furthermore, the findings show that while BI plays a major role NDM, this role is mitigated by the cognitive capabilities of individual decision-makers and their areas of expertise.

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The use of robotics in hazardous environments is becoming more common, where autonomy can handle the dull, dirty and dangerous jobs that humans have previously supported. This thesis focuses on the design of a helicopter deployable unmanned ground vehicle for use in hazardous environments, and presents the benefits of heterogeneous unmanned vehicle teams for operation in beyond line-of-site hazardous environments. The design of a ground robot that is capable of being flown on the undercarriage of a Yamaha RMAX unmanned air vehicle is presented. The robot is size, weight, and power limited and must be capable of traversing rough, unstructured terrain. The results of testing show that the design criteria for size, weight, and mobility are met. A path planning algorithm is developed using the A* search algorithm for the planning of optimal paths through rough terrain. The algorithm makes use of a vehicle/terrain interaction model to compute the cost of path traversal. In the CONOPS, the terrain model is generated real-time during a mission through the use of a stereovision system carried on the helicopter, which station-keeps above the ground robot. The algorithm simulates the robot on the terrain and presents the best feasible path to the operator to aid in teleoperated robot navigation. Simulations of the planning algorithm provided feasible paths over a rough terrain environment. A user study was conducted that evaluates the abilities of both mono- and stereo-vision systems in providing the teleoperator with adequate situational awareness with the intent of proving that stereovision data is more effective at aiding the user in making timely navigation decisions. The results of the study showed that the helicopter-mounted stereovision system was more efficient than the monovision system with respect to navigation time, the number of invalid moves, and total moves required for navigation of a simulated rough terrain environment. / Master of Science

Orbital debris is a current and growing threat to reliable space operations and new space vehicle traffic. As space traffic increases, so does the economic impact of orbital debris on the sustainability of systems that increasingly support national security and international commerce. Much of the debris collision risk is concentrated in specific high-density debris clusters in key regions of Low Earth Orbit (LEO). A potential long-term solution is to employ a constellation of observation satellites within these debris clusters to improve monitoring and characterization efforts, and engage in Laser Debris Removal (LDR) as means of collision mitigation. Here we adapted and improved a previous methodology for evaluating such designs. Further, we performed an analysis on the observer constellations' effectiveness over a range of circular, elliptical, and self-maneuvering designs. Our results show that increasingly complex designs result in improved performance of various criteria and that the proposed method of observation could significantly reduce the threat orbital debris poses to space operations and economic growth. / Master of Science / Orbital debris is defined as all non-operational, man-made objects currently in space. US national space regulations require every new satellite to have a de-orbit plan to prevent the creation of new debris, but fails to address the thousands of derelict objects currently hindering space operations. As space traffic increases, so does the economic impact of orbital debris on the sustainability of systems that increasingly support national security and commercial growth. While orbital debris is usually assessed by looking at the full volume of space, most massive debris objects are concentrated in high-density clusters with a higher than normal probability for collision. A potential solution to the growing orbital debris problem is to place a group of observation satellites within these debris clusters to both improve monitoring capabilities and provide a means for preventing potential collisions by engaging with debris via Laser Debris Removal (LDR). This research presents a methodology for comparing and contrasting different observer satellite constellation designs. Our results show that increasingly complex orbit designs improve various performance criteria, but ultimately orbits that more closely match those of the debris objects provide the best coverage. The proposed method of observation and engagement could significantly reduce the threat orbital debris poses to space operations and economic growth.

In a dynamically monitored environment the analyst team need timely and accurate information to conduct proactive action over complex situations. Typically, there are thousands of reported activities in a real time operation, therefore steps are taken to direct the analyst’s attention to the most important activity. The data fusion community have introduced the information fusion model, with multiple situational assessments. Each process lends itself to ranking the most important activities into a predetermined order. Unfortunately, the capability of a real time system can be hindered by the knowledge limitation problem, particularly when the underlying system is processing multiple sensor information. Consequently, the situational awareness domains may not rank the identified situation as perfect, as desired by the decision-making resources. This thesis presents advanced research carried out to evaluate the ranking capability of information from the situational awareness domains: perception, comprehension and projection. The Ranking Capability Score (RCS) has been designed for evaluating the prioritisation process. The enhanced (RCS) has been designed for addressing the knowledge representation problem in the user system relation under a situational assessment where the proposed number of tracking activities are dynamically shifted. Finally, the Scheduling Capability Score was designed for evaluating the scheduling capability of the situational awareness system. The proposed performance metrics have been successful in fulfilling their objectives. Furthermore, they have been validated and evaluated using an analytical approach, through conducting a rigorous analysis of the prioritisation and scheduling processes, despite any constraints related to a domain-specific configuration.

In a dynamically monitored environment the analyst team need timely and accurate information to conduct proactive action over complex situations. Typically, there are thousands of reported activities in a real time operation, therefore steps are taken to direct the analyst’s attention to the most important activity. The data fusion community have introduced the information fusion model, with multiple situational assessments. Each process lends itself to ranking the most important activities into a predetermined order. Unfortunately, the capability of a real time system can be hindered by the knowledge limitation problem, particularly when the underlying system is processing multiple sensor information. Consequently, the situational awareness domains may not rank the identified situation as perfect, as desired by the decision-making resources. This thesis presents advanced research carried out to evaluate the ranking capability of information from the situational awareness domains: perception, comprehension and projection. The Ranking Capability Score (RCS) has been designed for evaluating the prioritisation process. The enhanced (RCS) has been designed for addressing the knowledge representation problem in the user system relation under a situational assessment where the proposed number of tracking activities are dynamically shifted. Finally, the Scheduling Capability Score was designed for evaluating the scheduling capability of the situational awareness system. The proposed performance metrics have been successful in fulfilling their objectives. Furthermore, they have been validated and evaluated using an analytical approach, through conducting a rigorous analysis of the prioritisation and scheduling processes, despite any constraints related to a domain-specific configuration.

The world's shipping lanes are an area of intense focus in the Global War on Terror. Every day millions of tons of cargo are shipped through thousands of ports. Most cargo is harmless, however, some ships carry the weapons and human operators of terrorist organizations. To prevent the spread of weapons and terror suspects on the sea lanes, the cargo, passengers, and crew of these vessels must be subject to a level of scrutiny that is orders of magnitude greater than current efforts. The ability to rapidly extend a network and provide virtual expert services to Visit, Board, Search and Seizure (VBSS) boarding teams is crucial to protecting the United States and its allies from seaborne terror attacks and infiltration. This thesis uses scenario-based experimentation to examine the methods for implementing near-real-time collaborative work spaces in a virtual environment able to support VBSS operation anywhere in the world, limited only by network connectivity. The use of collaborative tools vastly increases the amount, type, and accuracy of information that can be processed. Radiation detection or classification and biometric fusion are among the hundreds of virtual collaborative sources that can be leveraged as force multipliers to bring network centric warfare to the maritime security domain.

CHDS State/Local / Many organizations believe they are prepared for the next terrorist event by wrongly assuming there is a predictable threat that can be managed with the purchase of new equipment. Unless organizations develop a resilient response strategy that can adapt organizational and operational elements to respond to new terrorist incidents, they will find themselves with the same difficulties emergency responders did on 9/11. As terrorist attacks unfold, organizations are pushed beyond their normal capabilities. How quickly organizations adapt to the uncertainty of a new crisis is critical. Organizations that cannot adapt to new threats of large, complex terrorist events will be less likely to respond effectively to future attacks. This paper recommends a resilient response strategy that is flexible enough to adapt to complex incidents. It proposes policy recommendations that address organizational strategy and operational crisis management to deal with the initial critical hours of a terrorist attack. Organizational strategy defines core competencies and what happens when competencies are pushed beyond their capacity. Operational crisis management will examine situational awareness requirements, flexible decision-making and innovation. Command resiliency is achieved by overcoming organizational bias and integrating organizational preparedness and operational adaptability into a synergistic response network. / Deputy Assistant Chief, Fire Department City of New York