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This paper develops a systems engineering-based framework to assist in the design of an online engineering course. Specifically, the purpose of the framework is to provide a structured methodology for the design, development and delivery of a fully online course, either brand new or modified from an existing face-to-face course. The main strength Systems Engineering provides to online course design and delivery is the holistic worldview and the life-cycle approach. Adopting the life-cycle approach ensures a smooth transition for faculty members who are in the process of modifying their curriculum to meet student and industry demands. The effectiveness and function of the framework is discussed with respect to results from a brand new fully online course that was designed and developed for the Engineering Management Program at University of Houston Clear Lake, including a survey of students on Blackboard efficiency. The paper concludes with a discussion of implications of the framework for online education and future research.

This paper develops a systems engineering-based framework to assist in the design of an online engineering course. Specifically, the purpose of the framework is to provide a structured methodology for the design, development and delivery of a fully online course, either brand new or modified from an existing face-to-face course. The main strength Systems Engineering provides to online course design and delivery is the holistic worldview and the life-cycle approach. Adopting the life-cycle approach ensures a smooth transition for faculty members who are in the process of modifying their curriculum to meet student and industry demands. The effectiveness and function of the framework is discussed with respect to results from a brand new fully online course that was designed and developed for the Engineering Management Program at University of Houston Clear Lake, including a survey of students on Blackboard efficiency. The paper concludes with a discussion of implications of the framework for online education and future research.

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

309 pages : 25 cm

Systems Engineering Retraining, orientation event

Systems Engineering Retraining, orientation event

Systems Engineering Retraining, orientation event

Systems Engineering Retraining, orientation event

Systems Engineering Retraining, orientation event

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No Description

Approved F 1i f i 20MA 1 i1? 31AjRDa.~& 3~- X4000100020026-1 r? INTELLIGENCE ENGINE}-?,RING SYSTIMS ANALYSIS COURSE QUESTIONNAIRE Name _~ Phone Ex. Room No. Educational History Please answer the following questions concerning the attached subject material: in which topical areas do you feel the strongest? 2. In which topical areas do you feel the weakest? 3. What further topical. areas would you suggest for inclusion, if any? Return this Questionnaire to:''I 603 Amos Buy ing Approved For Release 2005/11/21 : CIA-RDP78-03576A000100020026-1 Office/Branch Approved For Release 2005/11/21 : CIA-RDP78-03576A000100020026-1 TOPICAL AREAS I. Vectorial Representation of Variables: matrix formats; manipulations; vectorial- products; orthogonality; independence; Fourier Series; Laplace representation convolution; Walsh Functions. .II. Linear System Variables: .convolution; Laplace Manipulations; applications to linear differential equations; damping considerations; impulse responses; system flow diagram; 7 `t'ransforms; sampling; numerical methods; Gauss' elimination; matrix inversion; pictorial matripes; manipulation. III. Probability and Statistics: concepts of discrete and continuous variables; sample,space; union; intersection; independence; definitions; density function; distri- bution function, expectancy operator; moments; confidence limits. IV. Stochastic Processes (I): stationary processes; approximations to Gaussian; filtering and averaging; correlation; convolution; cross--correlation; covariance matrix.; power spectral estimates; bandlimiting effects. V. Stochastic Processes (II) : general review and exercise of modeling tools presented to date; concepts of signals and interference; properties of space and time variables in single dimension case; conditional probability; Baysian approaches. VI. Detector Subsystems: one dimensional signal and noise; detection, decision threshold; optimum processing; receiver operating characteristics; interference effects from ambient noise, system noise, doppler_, reverberation, channel uncertainty in a variety of applications. VII. Detector Subsystems: optimum detection, prewhitening; Markov noise.; detectability criteria; coherent processing; energy detection; confidence measures. VIII. Space--Time Processing Subsystems: multisensor arrays; signal and noise matrices;' prewhitening; matched filters; detection, averaging schemes. IX. Spatial Processors: optimal.. arrays; lobes in time and -space; coherency; detectabi l-ity for several configura- tions; near field/far field considerations; non-planar wavefronts. Approved For Release 2005/11/21 : CIA-RDP78-03576A000100020026-1 Approved For Release 2005/11/21 : CIA-RDP78-03576A000100020026-1 X. Servomechanism Subsystems: -Linear models; closed loop and open loop response; root locus; Bode and Nyquist criteria; optimal control; common nonlinear. i_ties; phase--plane approach. XI. Modulation Subsystems -- Analog: amplitude, phase and frequency modulation models; deterministic. vectorial. and frequency models, noise consideration in design;-sideband considerations; convolutions; demodulation schemes. Xi_i. Modulation Subsystems - Pulsed: PPM, PCM, PWM, etc. and other pulsed models were treated. Relationships between deterministic and band noise-limited cases; system noise and environmental noise budgets. Approved For Release 2005/11/21 : CIA-RDP78-03576A000100020026-1

398 p., plates : 34 cm

Systems engineering is vital for the acquisition of systems for the Department of the Navy (DON). As systems engineering is a relatively young discipline, no professional engineer occupational series exists under which systems engineers can be classified from a human resources perspective. In addition to the lack of an occupational designation, there is no official competency model to form the basis for employee selection and career development. In order for a competency model to be used for employee selection, it must be validated under the Uniform Guidelines for employee selection. Once validated, the model can be used to create systems engineering position descriptions and related career development plans that would be specifically used for systems engineers within the DON and perhaps for DOD. A baseline competency model is the first step in performing a validation process in accordance with the Uniform Guidelines. In order to begin to address this situation, a system engineering competency model was developed to provide a baseline. This model was designed specifically for the DON, though it should also be useable in any organization that employs system engineers. The core of the model is based on the knowledge, skills, and abilities (KSAs) that a systems engineer needs to develop competency in across varying career levels. These KSAs are defined using Bloom’s Taxonomy to describe, the cognitive and affective aspects needed for achievement of the respective competencies. The research also identifies whether these KSAs are best attained through specific methods, such as undergraduate education, graduate education, professional training, or through on-the-job experience. Furthermore, the model can inform the development of graduate and undergraduate curricula in systems engineering, since using Bloom’s Taxonomy describes the KSAs in terms that lend themselves to direct use as curriculum related learning objectives. The outcome is called the Competency Model for the Profession of Systems Engineering (COMPOSE) model. The COMPOSE model can be used by the DON and several other organizations as a means to formulate career development plans for the professional development of systems engineers.

Systems engineering is vital for the acquisition of systems for the Department of the Navy (DON). As systems engineering is a relatively young discipline, no professional engineer occupational series exists under which systems engineers can be classified from a human resources perspective. In addition to the lack of an occupational designation, there is no official competency model to form the basis for employee selection and career development. In order for a competency model to be used for employee selection, it must be validated under the Uniform Guidelines for employee selection. Once validated, the model can be used to create systems engineering position descriptions and related career development plans that would be specifically used for systems engineers within the DON and perhaps for DOD. A baseline competency model is the first step in performing a validation process in accordance with the Uniform Guidelines. In order to begin to address this situation, a system engineering competency model was developed to provide a baseline. This model was designed specifically for the DON, though it should also be useable in any organization that employs system engineers. The core of the model is based on the knowledge, skills, and abilities (KSAs) that a systems engineer needs to develop competency in across varying career levels. These KSAs are defined using Bloom’s Taxonomy to describe, the cognitive and affective aspects needed for achievement of the respective competencies. The research also identifies whether these KSAs are best attained through specific methods, such as undergraduate education, graduate education, professional training, or through on-the-job experience. Furthermore, the model can inform the development of graduate and undergraduate curricula in systems engineering, since using Bloom’s Taxonomy describes the KSAs in terms that lend themselves to direct use as curriculum related learning objectives. The outcome is called the Competency Model for the Profession of Systems Engineering (COMPOSE) model. The COMPOSE model can be used by the DON and several other organizations as a means to formulate career development plans for the professional development of systems engineers.

Systems engineering is vital for the acquisition of systems for the Department of the Navy (DON). As systems engineering is a relatively young discipline, no professional engineer occupational series exists under which systems engineers can be classified from a human resources perspective. In addition to the lack of an occupational designation, there is no official competency model to form the basis for employee selection and career development. In order for a competency model to be used for employee selection, it must be validated under the Uniform Guidelines for employee selection. Once validated, the model can be used to create systems engineering position descriptions and related career development plans that would be specifically used for systems engineers within the DON and perhaps for DOD. A baseline competency model is the first step in performing a validation process in accordance with the Uniform Guidelines. In order to begin to address this situation, a system engineering competency model was developed to provide a baseline. This model was designed specifically for the DON, though it should also be useable in any organization that employs system engineers. The core of the model is based on the knowledge, skills, and abilities (KSAs) that a systems engineer needs to develop competency in across varying career levels. These KSAs are defined using Bloom’s Taxonomy to describe, the cognitive and affective aspects needed for achievement of the respective competencies. The research also identifies whether these KSAs are best attained through specific methods, such as undergraduate education, graduate education, professional training, or through on-the-job experience. Furthermore, the model can inform the development of graduate and undergraduate curricula in systems engineering, since using Bloom’s Taxonomy describes the KSAs in terms that lend themselves to direct use as curriculum related learning objectives. The outcome is called the Competency Model for the Profession of Systems Engineering (COMPOSE) model. The COMPOSE model can be used by the DON and several other organizations as a means to formulate career development plans for the professional development of systems engineers.

Systems engineering is vital for the acquisition of systems for the Department of the Navy (DON). As systems engineering is a relatively young discipline, no professional engineer occupational series exists under which systems engineers can be classified from a human resources perspective. In addition to the lack of an occupational designation, there is no official competency model to form the basis for employee selection and career development. In order for a competency model to be used for employee selection, it must be validated under the Uniform Guidelines for employee selection. Once validated, the model can be used to create systems engineering position descriptions and related career development plans that would be specifically used for systems engineers within the DON and perhaps for DOD. A baseline competency model is the first step in performing a validation process in accordance with the Uniform Guidelines. In order to begin to address this situation, a system engineering competency model was developed to provide a baseline. This model was designed specifically for the DON, though it should also be useable in any organization that employs system engineers. The core of the model is based on the knowledge, skills, and abilities (KSAs) that a systems engineer needs to develop competency in across varying career levels. These KSAs are defined using Bloom’s Taxonomy to describe, the cognitive and affective aspects needed for achievement of the respective competencies. The research also identifies whether these KSAs are best attained through specific methods, such as undergraduate education, graduate education, professional training, or through on-the-job experience. Furthermore, the model can inform the development of graduate and undergraduate curricula in systems engineering, since using Bloom’s Taxonomy describes the KSAs in terms that lend themselves to direct use as curriculum related learning objectives. The outcome is called the Competency Model for the Profession of Systems Engineering (COMPOSE) model. The COMPOSE model can be used by the DON and several other organizations as a means to formulate career development plans for the professional development of systems engineers.

Effective application of systems engineering in rapid response environments has been difficult, particularly those where large, complex brownfield systems or systems of systems exist and are constantly being updated with both short and long term software enhancements. This paper proposes a general case for solving this problem by combining a services approach to systems engineering with a kanban-based scheduling system. It provides the basis for validating the approach with agent-based simulations.

This research topic (RT-48) focuses on a Vision held by NAVAIR s leadership to assess the technical feasibility of creating/leveraging a more holistic Model-Based Systems Engineering (MBSE) approach. The expected capability of such an approach would enable mission-based analysis and engineering that reduces the typical time by at least 25 percent from what is achieved today for large-scale air vehicle systems. The research need includes the evaluation of emerging system design through computer (i.e., digital) models. The first phase of the effort began investigating the technical feasibility of moving to a complete model-driven lifecycle and includes four key tasks that can be summarized as follows: Surveying Industry, Government and Academia to understand the state-of-the-art of a holistic approach to MBSE Develop a common lexicon for MBSE, including model types, levels, uses, representation, visualizations, etc. Model the Vision, but also relate it to the As Is process Integrate a Risk Management framework with the Vision This report provides details about each task, the focus of the research questions, accomplishments, and the plans for the Phase II efforts, which are to continue under RT-118.

The U.S. Army s mission reflects a strong impetus to provide flexible and adaptable ground vehicles that are rapidly fieldable. Emerging manufacturing technology, such as three-dimensional (3D) printing, is making mass customization possible in commercial industry. If the Army could produce tailored military ground vehicles that incorporate mission-specific tactics, it would outperform generic systems. To produce such systems, a new systems engineering (SE) process should be developed. Virtual environments are central to the proposed SE/2025 process because they provide a sandbox where soldiers and engineers might directly collaborate to codevelop tactics and technologies simultaneously. The authors intent is to describe how ground vehicle systems might be developed in 2025 as well as to describe current efforts underway to shape the future. In the past, the United States Army has been able to anticipate capability gaps and needs based on a relatively static threat, but that model has disintegrated over the past two decades (United States Army, 2013). Figure 1 illustrates pictorially the range and complexity of the current defense landscape. Constantly shifting mission requirements will likely remain the norm in the foreseeable future. As such, combatant commanders will need ground vehicles, including robots that are flexible, adaptable, and rapidly deployable. Additionally, some of the most promising future warfighting technologies, such as robotics, computing, and advanced communications, will be readily available for non-State actors and nations to purchase from the global commercial market. To maintain a military advantage, the United States needs to develop a process that enables the lucid and rapid production of mission-tailored platforms that do not rely solely on cutting-edge technology. Just as radar stealth and drones were game changers in the past, the acquisition process itself could become a game-changing technology in the future.

Projects often seek to deliver new or improved capabilities within complex, poorly defined and changing contexts. The application of MBSE under such circumstances can be problematic and in this paper we discuss these issues, and suggest approaches for their mitigation. A particular system solution might be envisaged as a combination of subsystems connected through a common architecture. Systems thinking suggests that given clear requirements and a solution concept, one can move forward through the definition of subsystem capabilities and the system architecture where MBSE is particularly useful. However, in many applications the degree of turbulence or evolution within the requirements that can be expected means that close human intervention is necessary to keep the solution fit for purpose. Moreover, this human intervention must be based on significant experience and domain knowledge so as to cope with the many Soft System issues that are likely to be present. At University College London (UCL) Centre for Systems Engineering we propose five principles that we believe should underpin all SE development projects. In this work we discuss these principles and their application to MBSE within a Soft System context.

Projects often seek to deliver new or improved capabilities within complex, poorly defined and changing contexts. The application of MBSE under such circumstances can be problematic and in this paper we discuss these issues, and suggest approaches for their mitigation. A particular system solution might be envisaged as a combination of subsystems connected through a common architecture. Systems thinking suggests that given clear requirements and a solution concept, one can move forward through the definition of subsystem capabilities and the system architecture where MBSE is particularly useful. However, in many applications the degree of turbulence or evolution within the requirements that can be expected means that close human intervention is necessary to keep the solution fit for purpose. Moreover, this human intervention must be based on significant experience and domain knowledge so as to cope with the many Soft System issues that are likely to be present. At University College London (UCL) Centre for Systems Engineering we propose five principles that we believe should underpin all SE development projects. In this work we discuss these principles and their application to MBSE within a Soft System context.

The purpose of this thesis is to study the manning and maintainability requirements of a submarine unmanned undersea vehicle (UUV) program. This case study reviews current commercial and military applications of UUVs and applies their principles to the missions of the Navy's submarine force. Past and current UUV efforts are lacking requirements documents and the formal systems engineering process necessary to produce a successful program of record. Therefore, they are not being funded for use by the war-fighter. The Navy must develop formal concepts of operations (CONOPS) for the missions and systems that it wants to produce and allow industry to begin development for a formal future UUV program. Furthermore, the military has developed countless unmanned systems that have been developed for use in the water, on the ground and in the air, from which the Navy can apply important lessons learned. Lastly, analysis suggests that the Navy should continue to support the use of a submarine detachment for operation and maintainability of future vehicle programs.

The purpose of this thesis is to study the manning and maintainability requirements of a submarine unmanned undersea vehicle (UUV) program. This case study reviews current commercial and military applications of UUVs and applies their principles to the missions of the Navy's submarine force. Past and current UUV efforts are lacking requirements documents and the formal systems engineering process necessary to produce a successful program of record. Therefore, they are not being funded for use by the war-fighter. The Navy must develop formal concepts of operations (CONOPS) for the missions and systems that it wants to produce and allow industry to begin development for a formal future UUV program. Furthermore, the military has developed countless unmanned systems that have been developed for use in the water, on the ground and in the air, from which the Navy can apply important lessons learned. Lastly, analysis suggests that the Navy should continue to support the use of a submarine detachment for operation and maintainability of future vehicle programs.

Designing a distributed simulation environment across multiple domains that typically have disparate middleware transport protocols, data exchange formats and applications increases the difficulty of capturing and linking system design decisions to the resultant implementation. Systems engineering efforts for distributed simulation environments are typically based on the middleware transport used, the applications available and the constraints placed on the technical team including network, computer and personnel limitations. To facilitate community re-use, systems engineering should focus on integrated operational function decomposition. This links data elements produced within the simulation to the functional capabilities required by the user. The system design should be captured at a functional level and subsequently linked to the technical design. Doing this within a data-driven systems engineering infrastructure allows generative programming techniques to assist accurate, flexible and rapid architecture development. This paper describes the MATREX program systems engineering process, infrastructure and path forward.

This thesis presents a new systems engineering based approach to naval ship concept design for the Republic of Korea (R.O.K.) Navy. The R.O.K. Navy currently uses a traditional naval architecture approach in concept design. Naval architects focus only on naval architecture issues such as speed, range, and displacement; combat systems engineers focus on the performance of combat systems, weapons, and sensors. This design process creates some integration problems in the late design stage and during construction. For this reason, there is a growing interest in the systems engineering approach design concept in the R.O.K. Navy. Naval ship design is an aggregate of engineering, computer science, management, and even strategy and policy. Naval ship engineers should consider not only naval architecture issues such as hull form, stability, structure, maneuverability and propulsion, but also mission needs, effectiveness, cost/risk benefits, and integration with all combat systems. Naval architecture and combat systems engineering are a part of the design process, and they must be considered simultaneously a systems engineering approach to combatant ship design. To properly design a naval ship, engineers should consider how each of the systems combines optimally into a system of systems. The resulting process focuses on the systems engineering process applied to naval combatant design. Two systems engineering based naval ship concept design processes, one from NATO and the other from the U.S. Navy's Total Ship Systems Engineering (TSSE) program at the Naval Postgraduate School (NPS), are presented. The difference between the concept design process in the R.O.K Navy and the TSSE processes is studied. Based on the above studies and comparison of the processes, a new concept design process is proposed for the R.O.K. Navy. Finally, the Future Frigate (FFX) case study is performed using the newly proposed concept design process.

The Department of Defense is exponentially increasing the acquisition of joint complex systems that deliver needed capabilities demanded by our warfighter. Systems engineering is the technical and technical management process that focuses explicitly on delivering and sustaining robust, high-quality, affordable solutions. Air Force leadership has collectively stated the need to mature a sound systems engineering process throughout the Air Force. Gaining an understanding of the past and distilling lessons learned that are then shared with others through formal education and practitioner support are critical to achieving continuous improvement. This synopsis conveys the salient results of case studies focused on the application of systems engineering principles within various programs. Salient results are conveyed as learning principles to facilitate pedagogy. But these results are also useful to practicing engineers and managers as they apply systems engineering throughout a weapon system's life cycle. The reader is encouraged to delve into the details contained in the complete case study should a particular learning principle relate to a situation on your program.

Research on Building Education & Workforce Capacity in Systems Engineering, (referred to as the SE Capstone Project), is conducting research to understand the methods through which systems engineering learning and career interest may be increased among undergraduate and graduate engineering students. This research is being conducted in the context of 14 capstone courses, in most cases as an integrative culminating, project-based course involving teams of students working together on the development of a product or prototype that addresses a real Department of Defense need. Implemented as pilot courses in eight civilian and six military universities, these 14 institutions are piloting methods, materials, and approaches to create new courses or enhance existing courses to embed, infuse, and augment systems engineering knowledge, as defined by the SPRDE-SE/PSE Competency Model, among undergraduate and graduate students. This report is a snapshot of progress and preliminary findings as reported in SE Capstone partners' interim reports as of January 2011 which, in most cases, represents the midpoint of their course implementation.

Research on Building Education & Workforce Capacity in Systems Engineering, (referred to as the SE Capstone Project), is conducting research to understand the methods through which systems engineering learning and career interest may be increased among undergraduate and graduate engineering students. This research is being conducted in the context of 14 capstone courses, in most cases as an integrative culminating, project-based course involving teams of students working together on the development of a product or prototype that addresses a real Department of Defense need. Implemented as pilot courses in eight civilian and six military universities, these 14 institutions are piloting methods, materials, and approaches to create new courses or enhance existing courses to embed, infuse, and augment systems engineering knowledge, as defined by the SPRDE-SE/PSE Competency Model, among undergraduate and graduate students. This report is a snapshot of progress and preliminary findings as reported in SE Capstone partners' interim reports as of January 2011 which, in most cases, represents the midpoint of their course implementation.

ADA031872

elligence and Information Operations have evaded the community. This thesis proposes systems engineering, combined with technical expertise, as the solution to confront the Information Operations integration problem and provide an avenue to bridge the gap between the current expertise in Signals Intelligence and Information Operations.

elligence and Information Operations have evaded the community. This thesis proposes systems engineering, combined with technical expertise, as the solution to confront the Information Operations integration problem and provide an avenue to bridge the gap between the current expertise in Signals Intelligence and Information Operations.

This thesis presents a practical method for calculating and representing entropy-based metrics for a set of bibliographic records evolving over time, in support of Dr. Michael Saboe's dissertation research which addressed the ability to measure software technology transfer. The implementation of the analysis methodology for determining the information-temperature of evolving datasets containing bibliographic records is described. The information-temperature metric is based on information entropy and is used to relate the maximum complexity of a system to the current complexity. The implementation of the analysis methodology required using data mining techniques to prepare the datasets. Additionally, since the information-temperature metric derived from Saboe's work was a new emerging concept, the data analysis methodology had to be refined several times in order to obtain the desired results. An iterative software development paradigm was used to write the application in 3 iterations using Visual Basic. At the end of the implementation the data analysis process became systemized allowing the outlining of the steps to compute the temperature of datasets, and it is estimated that the learning curve of the analysis can be reduced by 50 percent through integration and packing of the analysis functions into a stand-alone application with an intuitive user interface.

This thesis presents a practical method for calculating and representing entropy-based metrics for a set of bibliographic records evolving over time, in support of Dr. Michael Saboe's dissertation research which addressed the ability to measure software technology transfer. The implementation of the analysis methodology for determining the information-temperature of evolving datasets containing bibliographic records is described. The information-temperature metric is based on information entropy and is used to relate the maximum complexity of a system to the current complexity. The implementation of the analysis methodology required using data mining techniques to prepare the datasets. Additionally, since the information-temperature metric derived from Saboe's work was a new emerging concept, the data analysis methodology had to be refined several times in order to obtain the desired results. An iterative software development paradigm was used to write the application in 3 iterations using Visual Basic. At the end of the implementation the data analysis process became systemized allowing the outlining of the steps to compute the temperature of datasets, and it is estimated that the learning curve of the analysis can be reduced by 50 percent through integration and packing of the analysis functions into a stand-alone application with an intuitive user interface.

This thesis presents a practical method for calculating and representing entropy-based metrics for a set of bibliographic records evolving over time, in support of Dr. Michael Saboe's dissertation research which addressed the ability to measure software technology transfer. The implementation of the analysis methodology for determining the information-temperature of evolving datasets containing bibliographic records is described. The information-temperature metric is based on information entropy and is used to relate the maximum complexity of a system to the current complexity. The implementation of the analysis methodology required using data mining techniques to prepare the datasets. Additionally, since the information-temperature metric derived from Saboe's work was a new emerging concept, the data analysis methodology had to be refined several times in order to obtain the desired results. An iterative software development paradigm was used to write the application in 3 iterations using Visual Basic. At the end of the implementation the data analysis process became systemized allowing the outlining of the steps to compute the temperature of datasets, and it is estimated that the learning curve of the analysis can be reduced by 50 percent through integration and packing of the analysis functions into a stand-alone application with an intuitive user interface.

This thesis presents a practical method for calculating and representing entropy-based metrics for a set of bibliographic records evolving over time, in support of Dr. Michael Saboe's dissertation research which addressed the ability to measure software technology transfer. The implementation of the analysis methodology for determining the information-temperature of evolving datasets containing bibliographic records is described. The information-temperature metric is based on information entropy and is used to relate the maximum complexity of a system to the current complexity. The implementation of the analysis methodology required using data mining techniques to prepare the datasets. Additionally, since the information-temperature metric derived from Saboe's work was a new emerging concept, the data analysis methodology had to be refined several times in order to obtain the desired results. An iterative software development paradigm was used to write the application in 3 iterations using Visual Basic. At the end of the implementation the data analysis process became systemized allowing the outlining of the steps to compute the temperature of datasets, and it is estimated that the learning curve of the analysis can be reduced by 50 percent through integration and packing of the analysis functions into a stand-alone application with an intuitive user interface.

A central goal for the field of distributed control is to develop an underlying theory for the design and control of multiagent systems. Achieving this goal is fundamentally challenging stemming from the underlying complexity associated with a potentially large number of interacting agents and the analytical difficulties of dealing with overlapping and partial information. Game theory is beginning to emerge as a promising new direction for achieving this goal. The reason for this emergence is the similarity between the prevalent decision making architecture in social systems and the desired decision making architecture in distributed engineering systems. Accordingly, many existing game theoretic tools for analyzing behavior in social systems are immediately accessible as design tools for prescribing desirable behavior in distributed engineering systems. The applicability of game theoretic tools for this new prescriptive agenda has led to significant breakthroughs in the analysis and design of multiagent systems; however, the broader research effort connecting game theory to distributed control has ultimately fallen short of providing a systematic design methodology for multiagent coordination. The proposed research effort will address these deficiencies through the development of game engineering methodologies using an improved game theoretic framework that is better suited to handle the challenges inherent to multiagent coordination.

This briefing asks the question Can a prototyping development effort be responsive enough to react to critical needs while still benefiting from the rigor of systems engineering? The briefing looks at the problem of close air support with the stated objective: Develop, demonstrate and transition a marking solution that enables a Joint Terminal Attack Controller (JTAC) to establish a common point-of-reference with a Close Air Support (CAS) asset such that the CAS asset can attack an intended target while avoiding fratricide.

The United States Air Force is partnering with the United States Army as well as allied nations to develop a revolutionary advance in logistical support known as the Joint Precision Air Drop System (JPADS). The focus of this study is to develop a process to quantitatively analyze system sensitivities to various types of weather inputs and the corresponding effect on system accuracy. Weather balloons were used to provide representative truth to which forecast weather could be compared. Each data type was fed into the JPADS Mission Planner to produce navigation points which could then be compared statistically. The process was tested on a limited data set to provide a first look at the variables of forecast resolution and lead-time. Initial results indicate best system accuracy is achieved for lowest forecast resolution (i.e., 45 km vs. 5 km data) and shortest lead-time (i.e., 12 hrs vs. 12 hrs). This result will not only allow for better accuracy of JPADS, but also reduce bandwidth and transmission time necessary to send weather forecast data to the warfighter.

Many DoD Field Activities have been designated as In-Service Engineering Agents (ISEAs) for individual warfighting systems. As ISEA, it is crucial to periodically assess system capabilities and limitations individually, as a class, and as a strike force, as well as the technical community's ability to support the systems in question. Issues resulting from these assessments must be brought forward and addressed in an appropriate manner. From an acquisition perspective, limitations that require materiel solutions must be fed through the Navy's budgeting process so that focused and coordinated engineering efforts can be undertaken. These issues must be provided across the acquisition and technical community, including the industrial base, so that they can influence change in the design of systems. An example of this ISEA assessment is the Naval Surface Warfare Center Port Hueneme Division (NSWC PHD) Safety, Effectiveness, and Affordability Review (SEAR) process. NSWC PHD conducts In-Service Engineering (ISE) which demands the rigorous and continual application of well-structured, systematic processes that, at their core, are integrated as a Systems Engineering approach. According to the Acquisition and Capabilities Guidebook, a Systems Engineering Plan (SEP) is a mandatory milestone document that is required at milestones A, B and C and also program initiation for ships (SECNAV, 2008). One of the biggest challenges to the SEP is how to maintain the discipline for not only the Milestones but also over the systems Lifecycle, and to maintain the Safety, Effectiveness and Affordability of each system.

Many DoD Field Activities have been designated as In-Service Engineering Agents (ISEAs) for individual warfighting systems. As ISEA, it is crucial to periodically assess system capabilities and limitations individually, as a class, and as a strike force, as well as the technical community's ability to support the systems in question. Issues resulting from these assessments must be brought forward and addressed in an appropriate manner. From an acquisition perspective, limitations that require materiel solutions must be fed through the Navy's budgeting process so that focused and coordinated engineering efforts can be undertaken. These issues must be provided across the acquisition and technical community, including the industrial base, so that they can influence change in the design of systems. An example of this ISEA assessment is the Naval Surface Warfare Center Port Hueneme Division (NSWC PHD) Safety, Effectiveness, and Affordability Review (SEAR) process. NSWC PHD conducts In-Service Engineering (ISE) which demands the rigorous and continual application of well-structured, systematic processes that, at their core, are integrated as a Systems Engineering approach. According to the Acquisition and Capabilities Guidebook, a Systems Engineering Plan (SEP) is a mandatory milestone document that is required at milestones A, B and C and also program initiation for ships (SECNAV, 2008). One of the biggest challenges to the SEP is how to maintain the discipline for not only the Milestones but also over the systems Lifecycle, and to maintain the Safety, Effectiveness and Affordability of each system.

Historically Systems Engineering (SE) practitioners have focused on producing document-based artifacts to relay SE knowledge to stakeholders and developers. More recently a large part of the community has moved towards using view-based artifacts; e.g. DODAF to visually communicate SE knowledge. Documents and views are simply containers that hold objects. SE knowledge is comprised of sets (classes) of objects that are related to each other. By directly managing these objects, containers can be reproduced as desired. This paper proposes a shift in the focus of SE from documents and views to objects. We are not proposing a new SE methodology, but rather a set of principles to integrate the information created by multiple, diverse SE methods.