Barriers to technology integration are not a new phenomenon for educators, however resolving the issues surrounding the barriers necessitates the use of appropriate methods to accurately identify them. The purpose of this study is to investigate (a) whether or not Gilberts Behavioral Engineering Model is an appropriate instrument for identifying barriers to technology integration in an educational setting, particularly a public school and (b) can Gilberts Behavioral Engineering model be used in a public school to identify barriers to technology integration. The research and design methods were conducted in two phases. In Phase I, a model usability study was conducted through an online Cause Analysis survey based on Chevalier's updated model. The survey was administered to 80 teachers and four administrators in a public school. In phase II, two expert reviewers validated the process used to implement the Behavior Engineering Model. The data from the Cause Analysis indicated that participants believed there was a lack of financial and non-financial incentives for integrating technology and that the management and reporting system did not adequately track the use of technology. The expert reviewers both agreed that Gilberts model was implemented correctly identified barriers to technology integration and revealed a performance gap. They also agreed that Gilberts model is appropriate to use in a public school setting. / Ed. D.

Professionals called upon to design and deliver online professional development face unique challenges in fulfilling those roles when they may have little or no training experience within the online medium. Using research-based recommendations from the literature via a design and development methodology, this study operationalizes findings into Gilbert's (1978) Behavior Engineering Model to create guidelines for designing and delivering continuing professional development within the online medium. An expert review serves to validate and lead the revision process for the guidelines. This study describes the literature, guideline development, experts' reviews, and the validation of the guidelines. / Doctor of Philosophy / Often, individuals in the workforce are asked to design and teach professional development that is not delivered in a face to face setting. It is a challenging task that could be made easier by following guidance that has been developed by instructional designers and researchers. As such, this study highlights the techniques and best practices located within the publications from the fields of professional development, online learning, and instructional design. These techniques and best practices have been organized into a performance improvement model established by Thomas F. Gilbert entitled The Behavior Engineering Model (1978) and follows the research method known as development research. The findings of this study were reviewed by three experts who research the areas of online learning, performance improvement, and instructional design.

<p>Model Predictive Control (MPC) is traditionally designed assuming no model mismatch and tuned to provide acceptable behavior when mismatch occurs. This thesis extends the MPC design to account for explicit mismatch in the control and optimization of a wide range of uncertain dynamic systems with feedback, such as in process control and supply chain optimization.</p> <p>The major contribution of the thesis is the development of a new MPC method for robust performance, which offers a general framework to optimize the uncertain system behavior in the closed-loop subject to hard bounds on manipulated variables and soft bounds on controlled variables. This framework includes the explicit handling of correlated, time-varying or time-invariant, parametric uncertainty appearing externally (in demands and disturbances) and internally (in plant/model mismatch) to the control system. In addition, the uncertainty in state estimation is accounted for in the controller.</p> <p> For efficient and reliable real-time solution, the bilevel stochastic optimization formulation of the robust MPC method is approximated by a limited number of (convex) Second Order Cone Programming (SOCP) problems with an industry-proven heuristic and the classical chance-constrained programming technique. A closed-loop uncertainty characterization method is also developed which improves real-time tractability by performing intensive calculations off-line.</p> <p>The new robust MPC method is extended for process control problems by integrating a robust steady-state optimization method addressing closed-loop uncertainty. In addition, the objective function for trajectory optimization can be formulated as nominal or expected dynamic performance. Finally, the method is formulated in deviation variables to correctly estimate time-invariant uncertainty.</p> <p>The new robust MPC method is also tailored for supply chain optimization, which is demonstrated through a typical industrial supply chain optimization problem. The robust MPC optimizes scenario-specific safety stock levels while satisfying customer demands for time-varying systems with uncertainty in demand, manufacturing and transportation. Complexity analysis and computational study results demonstrate that the robust MPC solution times increase with system scale moderately, and the method does not suffer from the curse of dimensionality.</p> / Thesis / Doctor of Philosophy (PhD)

Information systems often hold data of considerable value. Their continuing development or maintenance will often necessitate evolution of the system and migration of the data from one version to the next: a process that may be expensive, time-consuming, and prone to error. That such a process remains a source of challenges, is recognized by both academia and industry. In current practice, data migration is often considered only in the later stages of development, leaving critical data to be transformed and loaded by hand-written scripts, long after the design process has been completed. The advent of model-driven engineering offers an opportunity to consider the question of information system evolution and data migration earlier in the development process. A precise account of the proposed changes to an existing system model can be used to predict the consequences for existing data, and to generate the necessary data migration implementation. This dissertation shows how automatic data migration can be achieved by extending the definition of a data modeling language to include model level operations, each of which corresponds to the addition, modification, or deletion of a model component. Using the Unified Modeling Language (UML) notation as an example, we show how the specification of these operations may be translated into an abstract program in the Abstract Machine Notation (AMN), employed in the B-method, and then formally checked for consistency and applicability prior to translation into a concrete programming notation, such as Structured Query Language (SQL).

Leveraging virtual reality (VR) technology to enhance engineering design reviews has been an area of significant interest for researchers since the advent of modern VR. The ability to interact meaningfully with 3D engineering models in these VR design reviews is an important, though often neglected, capability due to the difficulty of performing data translation between native CAD data and VR compatible file formats. A bi-directional interface was developed between a VR design review environment and a commercial CAD package that streamlines the data translation process. By transmitting both geometric data and selected metadata from the CAD system an improved format for the VR model was achieved and enhanced model interaction tools were added to the VR design review application. The suite of model interaction tools developed include component hiding, exploded views, and the ability to parametrically update the model directly from the VR environment. Preliminary user experiments were performed once an early prototype of the system was in place. These experiments guided the remainder of the development and the experimental setup for the final set of experiments. Final user experiments were performed to validate the usefulness of the bi-directional interface concept and the system developed, as well as to establish the importance of enhanced model interaction in VR engineering design reviews. The experiments performed were composed of two tasks: One task aimed at exploring how CAD integration and advanced interaction tools in VR design reviews aid understanding of model geometry and design comprehension and a second task that explores how the ability to preview design changes from the VR design review environment improves decision making. In the first task participants were shown a model of a complex gearbox and asked to count the number of gears. Participants performed this test on two different models: once with the enhanced toolset and once with a baseline toolset representative of the current state of the art that only allows users to pan, rotate, and scale a shaded monochrome version of the model. In the second task participants were given a model of a four cylinder internal combustion engine and asked to determine the feasibility of three proposed design changes based on whether the changes would cause interference in the model. Again, participants performed this test with two different models, once with each toolset. The analysis of the data from these experiments showed that participants were significantly more successful at understanding the geometry of the model when using the enhanced toolset. The data also showed that the enhanced toolset often boosts users' confidence in their understanding, and can help users to understand the design more quickly. Data from the second task showed that the enhanced environment can also help users to better and more confidently understand the implications of a proposed design change, which can lead to improved decision making. The work presented here builds the foundation for the bi-directional interface concept to be extended to further applications that can enable advanced interaction with a diversity of engineering data in VR.

Dieser Beitrag untersucht Potenziale des Einsatzes von MBE-Ansätzen bei der Validierung von Fahrerassistenzsystemen. Ziel ist die Untersuchung der Machbarkeit des Aufbaus einer Validierungsumgebung zur Automatisierung von Tests im Rahmen der kontinuierlichen Validierung von Fahrerassistenzsystemen. [... aus der Einleitung]

In the thesis, two different model predictive control (MPC) strategies are investigated for linear systems with uncertainty in the presence of constraints: namely robust MPC and stochastic MPC. Firstly, a Youla Parameter is integrated into an efficient robust MPC algorithm. It is demonstrated that even in the constrained cases, the use of the Youla Parameter can desensitize the costs to the effect of uncertainty while not affecting the nominal performance, and hence it strengthens the robustness of the MPC strategy. Since the controller u = K x + c can offer many advantages and is used across the thesis, the work provides two solutions to the problem when the unconstrained nominal LQ-optimal feedback K cannot stabilise the whole class of system models. The work develops two stochastic tube approaches to account for probabilistic constraints. By using a semi closed-loop paradigm, the nominal and the error dynamics are analyzed separately, and this makes it possible to compute the tube scalings offline. First, ellipsoidal tubes are considered. The evolution for the tube scalings is simplified to be affine and using Markov Chain model, the probabilistic tube scalings can be calculated to tighten the constraints on the nominal. The online algorithm can be formulated into a quadratic programming (QP) problem and the MPC strategy is closed-loop stable. Following that, a direct way to compute the tube scalings is studied. It makes use of the information on the distribution of the uncertainty explicitly. The tubes do not take a particular shape but are defined implicitly by tightened constraints. This stochastic MPC strategy leads to a non-conservative performance in the sense that the probability of constraint violation can be as large as is allowed. It also ensures the recursive feasibility and closed-loop stability, and is extended to the output feedback case.

There are many calamitous events such as earthquakes, hurricanes, tsunamis etc. that occur suddenly and cause great loss of life, damage, or hardship. Hurricanes cause significant damage to power distribution systems, resulting in prolonged customer outages and excessive delays in the reconstruction efforts. Accordingly, predicting the effects of power outages on the performance of power distribution systems is of major importance to government agencies, utilities, and customers. Unfortunately, the current tools to predict the performance of power distribution systems during catastrophic events are limited in both the performance measures considered, as well as in their ability to model real systems. The main goal of this research is to develop a methodology for simulating hurricanes of different intensity on power distribution systems of small and medium size cities. Our study includes a detailed comparison between the engineering-based and connectivity-based models of power distribution systems, as well as the impact of power re-routing algorithms on the system reliability. Our approach is based on fragility curves that capture the ability of the system to withstand a range of wind speeds. In addition, we develop a multiscale approach that facilitates efficient computation of fragility curves for large cities. With this approach, hurricanes are simulated over small zones of a city and fragility curves are obtained. These are used to estimate the damage for identical zones throughout the city. To validate our techniques, two testbeds, Micropolis and Mesopolis, were used. Micropolis is synthetic model for a small city and Mesopolis for a big city. Obtained results have validated our approach and have shown that they can be used to effectively predict hurricane damage.

Reuse has often been claimed in the software engineering literature to improve thequality and reduce the cost of software. Motivated by the idea that these gains canbe multiplied if reuse can be achieved earlier in the software life-cycle, a subset ofthe requirements engineering literature has focused, since the inception of the field,on investigating approaches to reuse at the requirements level. A wide array of differentapproaches now exist within this space. However, these approaches offer varyingdegrees of generality and utility. Generality is important because it enables a requirementsengineer to utilise the same reuse library across multiple projects. Utility isimportant because it is a measure of the extent to which effort is reduced by utilising areuse approach. This thesis presents Reuse-Oriented Requirements Engineering (RORE): a systematicframework to support the production of requirements models by reuse. RORE aimsto improve on existing requirements-reuse approaches in respect of the generalityutilitytrade-off. RORE seeks to do this by bringing together the strengths of two existingrequirements-level reuse approaches: The Domain Theory and Problem-OrientedSoftware Engineering (POSE - a refinement of Jackson’s Problem Frames Approach).This thesis evaluates RORE with respect to both generality and utility, and comparesRORE against both frameworks. The major conclusion of the thesis is that while ROREimproves on each framework in respect of some, but not all, evaluation metrics, ROREdoes succeed in offering a level of generality which compares favourably to existinghighly general approaches, and without significantly reducing the utility of the approach.

In the present PhD work, three sophisticated models based on the "Engineering" modeling approach have been utilized to conveniently describe and thoroughly analyze details of Lightning events at the CN Tower. Both the CN Tower and the Lightning Channel are represented by a number of connected in series Transmission Line sections in order to account for the variations in the shape of the tower and for plasma processes that take place within the Lightning Channel. A sum of two Heidler functions is used to describe the "uncontaminated" Return Stroke current, which is injected at the attachment point between the CN Tower and the Lightning Channel. Reflections and refractions at all points of mismatched impedances are considered until their contribution becomes less than 1% of the originally injected current wave. In the proposed models, the problem with the current discontinuity at the Lightning Channel front, commonly taken care of by introducing a "turn-on" term when computing radiation fields, is uniquely treated by introducing reflected and transmitted components. For the first time, variable speed of propagation of the Return Stroke current front has been considered and its influence upon the predicted current distributions along the whole Lightning Channel path and upon the radiated distant fields analyzed. Furthermore, as another novelty, computation of the electromagnetic field is accomplished in Cartesian Coordinates. This fact permits to relax the requirement on the verticality of the Lightning Channel, normally imposed in Cylindrical Coordinates. Therefore, it becomes possible to study without difficulty the influence of a slanted Lightning Channel upon the surrounding electromagnetic field. Since the proposed sophisticated Five-Section Model has the capability to represent very closely the structure of the CN Tower and to emulate faithfully the shape of, as well as physical processes within the Lightning Channel, it is believed to have the potential of truthfully reproducing observed fields. The developed modeling approach can be easily adapted to study the anticipated radiated fields at tall structures even before construction.