Engineering Systems

In this paper, a structured approach for collecting lessons learned information obtained from system development projects is discussed. To aid in the analysis of lessons learned, the collection framework incorporates techniques associated with approximate reasoning. The primary goal of collecting lessons learned is to improve organizational and project performance. Therefore, this approach concentrates on focusing the collection of lessons learned on this goal. This approach ties the collection of lessons learned to the process model used by the organization. This model is typically based on capability models such as the Systems Engineering Capability Maturity Model (SE-CMM 1 ) and Software CMM (SW-CMM), as well as process standards such as ISO 9000 and the organizations standard engineering practices. This approach utilizes the organizations process framework to provide a structured, lessons learned program which can be used by projects during and at the completion of their execution.

In previous work we developed techniques for modeling software development processes quantitatively in terms of development cost, product quality, and project schedule using simulation. This work has predominately been applied to the software project management planning function. The goal of our current work is to develop a "forward looking" approach that integrates metrics with simulation models of the software development process in order to support the software project management controlling function. This "forward-looking" approach provides predictions of project performance and the impact of various management decisions. It can be used to assess the project's conformance to planned schedule and resource consumption. This paper reports on work with a leading software development firm to create an approach, that includes a flexible metrics repository and a discrete event simulation model.

In this paper, we present a "forward-looking" decision support framework that integrates timely metrics data with simulation models of the software development process in order to support the software project management control function. This forward-looking approach provides predictions of project performance and the impact of various management decisions. Tradeoffs among performance measures are accomplished using Outcome Based Control Limits (OBCLs) and are augmented using multi-criteria utility functions and financial measures of performance to evaluate various process alternatives. The decision support framework enables the program manager to take corrective action as necessary on a project with the simulation model providing insight on potential performance impacts of the proposed corrective actions. A real world example is presented.

Intrusion detection is a concern for any asset worth protecting. Having the capability to perform such detection can help to prevent the theft of, damage to, tampering with, or destruction of a wide range of valuable assets. These assets could be objects stored within a location such as a vault or room, or they could be an entire building containing valuable objects, a campus consisting of several buildings, or even something as large as a national border. This paper presents a concept for an intrusion detection system based on the use of infrasound, a technology well suited for this purpose due to its ability to distinguish between different types of sound sources occurring within a given area. The paper also includes a discussion of a methodology, based on principles of game theory, for optimizing the resources used in the intrusion detection process.

In this study, we investigated the development of clinical disease and immune responses in the development of an experimental model of flea allergy dermatitis. Dogs were randomly divided into four treatment groups and were infested with fleas on two different feeding schedules (continuous and episodic). Group 1 consisted of four non-exposed dogs (negative controls) and Group 2 consisted of six dogs exposed to fleas continually. Groups 3 and 4 consisted of 14 dogs each that were exposed to fleas on an episodic schedule (two consecutive days every other week for 12 weeks). Group 4 also received intraperitoneal injections of a low dose of lectin (ricin) with immunomodulatory properties. The purpose of Group 4 was to investigate the effects of ricin on enhancing the development of clinical signs, flea antigen-specific IgE levels and altering the number of CD4þ and CD8þ T cell subsets in peripheral blood. Clinical signs developed in all flea exposed dogs, however, the dermatology lesion scores were less and shorter in duration for continuously exposed dogs compared to episodic exposed dogs, independent of ricin treatment. Lesion development was concentrated in the flea triangle and consisted principally of erythema, followed by alopecia, excoriation, papules, and crusts. CD4þ and CD8þ lymphocyte subsets or IgE levels were not altered by ricin treatment. Flea antigen-specific IgE values were highest in dogs exposed to fleas on a continuous basis compared to those episodically exposed. A greater percentage of clinical responder dogs with negative flea-specific IgE titers or negative intradermal test (IDT) were present in the episodic exposure groups than in the continuous exposure group. IgE titers corresponded slightly better with clinical responders than the IDT. The agreement between the IgE titers and IDT was good (weighted k ¼ 0:67). Histopathology of skin samples were consistent with a Type I hypersensitivity. In conclusion, we were able to develop a model of flea allergy dermatitis by experimentally exposing dogs to fleas on an episodic and continuous feeding schedule. In this study, continuously exposed dogs did not develop immunotolerance, and ricin did not enhance the development of FAD. #

This paper presents a systems engineering entrepreneurship approach to developing projects at a university that are complex, multi-disciplinary in nature, integration oriented, and that may span departments, colleges, and have long completion schedules. Fundamental systems engineering principles are used to manage cost, schedule, and performance aspects of projects as well as to manage and control project risk. Entrepreneurial principles are used as part of the cost-benefit analysis in project evaluation. As an illustrative example, we present a project to develop an adaptive optics and atmospheric turbulence compensation system for a 0.8 meter optical telescope. A system engineering approach is used to identify and document stakeholder requirements, establish a project baseline, and use a requirements driven methodology to manage and control the project throughout its system development life-cycle. This approach is most suitable for technically complex projects that require collaboration and integration of diverse activities and resources as is often the case for multi-disciplinary projects or activities in centers of excellence or multiuniversity research initiatives.

By implementing student teams and incorporating a systems engineering approach, we have developed a unique video game-based product that combines the entertaining aspects of a popular video game set in a magical world, with dynamic, adaptable, multi-disciplinary instructional material. The video game knowledge module (VGKM) system integrates the fun NeverWinter Nights TM role-playing video game environment with educational knowledge modules, an entertaining story line, and out-of-game activities to build and demonstrate a compelling, interactive, collaborative, multi-disciplinary learning tool. Different knowledge modules can be built by interested faculty, educators, or entrepreneurial development teams, emphasizing different subject matter and integrated to produce a tailored course of study, correct academic deficiencies, or assist with training and certification, qualification, or assessment programs. Knowledge modules can span disciplines, departments, and even colleges and universities. A built-in assessment and rewards and punishment capability is included in the VGKM. The knowledge modules have a variety of dynamic features such as multiple or single user capable, directed in-game interaction by an educator, remote site multi-user interaction over the internet, localized WLAN/LAN networks, and asynchronous learning. A significant aspect of VGKM is character persistence. This allows the student to transfer a character from module to module, and game to game while maintaining the characters attributes, "possessions", experience, accumulated items, abilities, and ingame treasures.

In sheared coherent beam interferometric imaging, an estimate of the average reflectivity profile of the object can be computed from measurements of point to point phase differences in the far field interference pattern and a suitable phase reconstruction technique. The phase difference information is encoded in the irradiance of three identical, shifted and superimposed speckled laser beam patterns. A minimum variance phase reconstruction technique is presented to estimate the phase of the field in the measurement plane from the phase differences and evaluate its performance. Prior knowledge of the phase covariance is used in the minimum variance reconstructor. Analytic calculations and computer simulations are used to evaluate phase reconstruction errors as a function of object coherence area and spatial sample spacing in the measurement plane. The performance of the minimum variance reconstructor is compared to two least squares reconstructor implementations. Theoretical performance comparisons are made between the minimum variance reconstructor and a new implementation of the least squares formalism. The new least squares reconstructor uses the same error metric as the minimum variance reconstructor but does not use any statistical information in estimating the measurement plane phase function. Comparisons of the minimum variance reconstructor with a conventional implementation of the least squares formalism are also made. The performance of the minimum variance reconstructor is demonstrated for objects which are optically smooth as well as optically rough. A small random double point source object is used to demonstrate the near diffraction limited resolution of the minimum variance wavefront reconstructor. Phase and image reconstructions are demonstrated for extended objects.

Phase differences in the far field of a coherently illuminated object are used to estimate the twodimensional phase in the measurement plane of an imaging system. A previously derived phasecorrelation function is used in a minimum-variance phase-estimation algorithm to map phase-difference measurements optimally to estimates of the phase on a grid of points in the measurement plane. Theoretical and computer-simulation comparisons between the minimum-variance phase estimator and conventional least-squares estimators are made. The minimum-variance phase estimator produces a lower aperture-averaged mean-square phase error for all values of a sampling parameter ␤.

Infrasound signals of interest (SOI) have been collected from various sources including boats, aircraft and personal watercraft during a recent field exercise. The designed experiment specifically located infrasound sensors to gather the SOIs and process them using a developmental methodology. This custom pre-processing, and exploitation suite allows for the extraction of SOIs from experimental data sets that might be sub-optimal due to the presence of noise or interfering (undesired) sources. The on-going development of the infrasound sensor suite and the SOI signal processing and analysis is supported by this work.

Infrasound signals of interest (SOI) have been collected from various sources including boats, aircraft and personal watercraft during a recent field exercise. The designed experiment specifically located infrasound sensors to gather the SOIs and process them using a developmental methodology. This custom pre-processing, and exploitation suite allows for the extraction of SOIs from experimental data sets that might be sub-optimal due to the presence of noise or interfering (undesired) sources. The on-going development of the infrasound sensor suite and the SOI signal processing and analysis is supported by this work.

in Engineering Physics. He holds an M.S. degree in Electrical Engineering from the University of New Mexico and a B.S. degree in Electrical Engineering from Virginia Tech. He is currently an Associate Professor in the Engineering Systems Department at the Florida Institute of Technology. His research interests include adaptive optics, signal processing, image processing, and applied systems engineering. He worked for 20 years for the United States Air Force as a scientist, engineer, educator, and acquisitions officer prior to his academic career. Jihan Dinally, Florida Institute of Technology Jihan Dinally recently graduated with her Master of Science Systems Engineering degree at Florida Institute of Technology with a Bachelor of Science degree in Mechanical Engineering. As an Engineering Technician for Research Triangle Institute International, she developed custom, two-dimensional interpolation schemes, employing the ArcView Geographic Information System, and MatLab environment. During the beginning of her Master's in Systems Engineering program, she worked as a Test and Mechanical Engineer for Mnemonics, Inc.

Phase differences in the far field of a coherently illuminated object are used to estimate the twodimensional phase in the measurement plane of an imaging system. A previously derived phasecorrelation function is used in a minimum-variance phase-estimation algorithm to map phase-difference measurements optimally to estimates of the phase on a grid of points in the measurement plane. Theoretical and computer-simulation comparisons between the minimum-variance phase estimator and conventional least-squares estimators are made. The minimum-variance phase estimator produces a lower aperture-averaged mean-square phase error for all values of a sampling parameter ␤.

in Engineering Physics. He holds an M.S. degree in Electrical Engineering from the University of New Mexico and a B.S. degree in Electrical Engineering from Virginia Tech. He is currently an Associate Professor in the Engineering Systems Department at the Florida Institute of Technology. His research interests include adaptive optics, signal processing, image processing, and applied systems engineering. He worked for 20 years for the United States Air Force as a scientist, engineer, educator, and acquisitions officer prior to his academic career.

The basis of this paper was to investigate the system engineering applications on petrochemical facilities layout designs. This work aims to facilitate and introduce the application of Facility Layout Problems to industrial case studies based on system engineering methodologies and performance measurements. Additionally, an effort was made to present a state-of-the-art literature review of industrial layout problems that exhibits scarcity of system engineering role in the design and implementations of industrial Facility Layout Problems. Facility Layout is one of the demanding large-scale optimization problems. Upon the completion of this report, we found a great sense of vitality of system engineering approach together with necessity for more involvement in the total facilities layout life cycle stages. 4. Conclusion .

Accurate density estimation methodologies play an integral role in a variety of scientific disciplines, with applications including simulation models, decision support tools, and exploratory data analysis. In the past, histograms and kernel density estimators have been the predominant tools of choice, primarily due to their ease of use and mathematical simplicity. More recently, the use of wavelets for density estimation has gained in popularity due to their ability to approximate a large class of functions, including those with localized, abrupt variations. However, a well-known attribute of wavelet bases is that they can not be simultaneously symmetric, orthogonal, and compactly supported. Multiwavelets-a more general, vector-valued, construction of wavelets-overcome this disadvantage, making them natural choices for estimating density functions, many of which exhibit local symmetries around features such as a mode. We extend the methodology of wavelet density estimation to use multiwavelet bases and illustrate several empirical results where multiwavelet estimators outperform their wavelet counterparts at coarser resolution levels.