ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / This paper describes a service-based Intelligent Agent (IA) approach for machine learning and data mining of distributed heterogeneous data streams. We focus on an open architecture framework that enables the programmer/analyst to build an IA suite for mining, examining and evaluating heterogeneous data for semantic representations, while iteratively building the probabilistic model in real-time to improve predictability. The Framework facilitates model development and evaluation while delivering the capability to tune machine learning algorithms and models to deliver increasingly favorable scores prior to production deployment. The IA Framework focuses on open standard interoperability, simplifying integration into existing environments.

The past two decades have produced a substantial amount of research about the teaching and learning of evolution; however, recent research often lacks a theoretical foundation. Application of a new theoretical framework could help fill the void and improve research about student concepts of evolution. This study seeks to show that a resource-based framework (Hammer et al., 2005) can improve research into student concepts of natural selection. Concepts of natural selection from urban community college students were assessed via qualitative (interviews, written open-response questions, and write/think aloud procedures) and quantitative methods (coded open response analysis, Concept Inventory for Natural Selection (CINS)(Anderson, Fisher, & Norman, 2002). Results showed that students demonstrate four important aspects of resource-based framework: the multi-faceted construction of concepts, context sensitivity/ concept flexibility, at-the-moment activation of resources, and perceptual frames. In open response assessment, evolutionary-gain responses produced significantly different responses than evolutionary-loss questions with: 1) significantly more correct answers for the gain than loss question (Wilcoxon signed rank test, z = -3.68, p=0.0002); 2) more Lamarckian responses to loss than the gain question (Fisher exact, p=0.0039); and significantly different distributions in expanded need vs basic need answers (Fishers exact, p = 0.02). Results from CINS scores showed significant differences in post activity scores between students that held different naive concepts associated with origin of variation, origin of species, differential reproduction, and limited survival suggesting that some naive ideas facilitate learning. Outcomes also suggest that an everyday or self-experience typological perceptual frame is an underlying source of many incorrect ideas about evolution. Interview and write/think aloud assessments propose four process resources applied by students as they explain evolutionary change: list what I know, why story, compare past to present, mapping self-experience. The study concludes that a resource-based framework is a valuable tool to advance the study student concepts of natural selection.

The creation of systems for Internet use is usually susceptible to problems such as complicated implementation and inefficient exploitation of money and time. The main problem is a discordant needs of customers and system developers: customers want to have a system, which works properly at the lowest price, while system developers want to maintain a high quality in development and to put the product on the market as soon as possible. To solve these problems we offer a framework, which is created according to principles of component based software engeneering combined with pattern oriented software architecture. A framework can be used as a foundation for extensible, flexible, easy to maintain and user-friendly systems for Internet use.

This research addresses the need for efficient and effective management of water during any part of a crisis lifecycle, which is paramount if the negative impact on human health and quality of life is to be minimised. The unique contribution to knowledge is expressed through the creation of a framework for application of four key elements: Crisis Management, Knowledge Management, Public Health and Human Security within the realms of water resource utilisation during humanitarian crises. Through secondary data collection, the four key elements were identified. Primary data was subsequently gathered from subject experts in the form of semi-structure interviews that utilised a questionnaire to guide participants through the identified problem domain. This resulted in the creation of a draft framework that was critiqued by domain experts through both questionnaire and interview. A final framework was then constructed that took into consideration the needs expressed by all participants. The final framework was then tested against the historic crisis of Hurricane Katrina, for which a plethora of data and information was readily available, to ascertain its validity and applicability. Further work was identified as being the creation of an interactive toolbox of resources, which could be utilised in times of crisis based on need and applicability.

The key objectives of this research were to develop an integrated design and analysis methodology for sheet-metal product development based on agent-based technology, feature-based design, optimization and finite element analysis techniques, and to study the performance of prototype systems developed based on such a methodology. To achieve the research objectives, an agent-based framework was proposed for integrating and coordinating activities of participants involved in sheet-metal product development based on the investigation of the industrial requirements and the procedures of the development of sheet-metal products. Prototype systems were developed based on the proposed framework to answer research problems outlined for the design and implementation of agent-based systems, such as agent encapsulation, system architecture, agent communication and agent coordination. The performance of such prototype systems demonstrates that communication and coordination among domain agents can facilitate product development and reduce product cost. An agent-based optimization approach based on an "A-Teams" approach (Talukdar et al, 1996) was proposed for process optimization in the tooling design stage to combine the utilization of the traditional optimization techniques used to solve sheet-metal forming problems and agent-based approaches. Three test cases were used of varying complexity from a rectangular cup to the NUMISHEET'99 automobile front door panel simulation benchmark for the determination of optimal drawbead restraining forces and blankholder forces when designing draw dies for stamped parts. A network of software agents, each implementing a different numerical optimization technique, was used in combination with metal forming simulation software to optimize process variables. It was found that the performance of each agent (and optimization technique) depended strongly on the complexity of the problem. For a given amount of computational effort, a network of collaborating agents using different optimization techniques always outperformed agents using a single technique in terms of both the best solution found and the variance of the collection of best solutions. To provide guidance for the design and implementation of real applications, static and dynamic attributes and metrics of such agent-based collaborative systems, which can be evaluated in the preliminary system design stage and the system implementation stage, were proposed to study the impact of system architectures and coordination strategies on system performance. In addition, real-time system performance was statistically studied based on the data collected by the visualiser agent generated with the agent building toolkit. The results of case studies for system performance evaluation demonstrate the applicability of evaluation strategies proposed and can be used as a reference model for performance and scalability analysis on agent-based sheet-metal product development systems. The proposed evaluation strategies are applicable to general applications for product development by taking into consideration other performance indicators. / Thesis / Doctor of Philosophy (PhD)

The goal of this thesis is to develop an easily modifiable sensor system. To achieve this goal SensorML (an XML based sensor language) is combined with Java Beans (a component model language). An important part of SensorML is its process model. Each sensor in the real world is depicted in SensorML by a process model, whereas the connections between the sensors are shown by a process chain. This thesis presents a translator that reads these documents and converts them to Java Beans. Through testing the Translator is proved more efficient than the convenient Object Oriented approach. / UOIT

abstract: Video denoising has been an important task in many multimedia and computer vision applications. Recent developments in the matrix completion theory and emergence of new numerical methods which can efficiently solve the matrix completion problem have paved the way for exploration of new techniques for some classical image processing tasks. Recent literature shows that many computer vision and image processing problems can be solved by using the matrix completion theory. This thesis explores the application of matrix completion in video denoising. A state-of-the-art video denoising algorithm in which the denoising task is modeled as a matrix completion problem is chosen for detailed study. The contribution of this thesis lies in both providing extensive analysis to bridge the gap in existing literature on matrix completion frame work for video denoising and also in proposing some novel techniques to improve the performance of the chosen denoising algorithm. The chosen algorithm is implemented for thorough analysis. Experiments and discussions are presented to enable better understanding of the problem. Instability shown by the algorithm at some parameter values in a particular case of low levels of pure Gaussian noise is identified. Artifacts introduced in such cases are analyzed. A novel way of grouping structurally-relevant patches is proposed to improve the algorithm. Experiments show that this technique is useful, especially in videos containing high amounts of motion. Based on the observation that matrix completion is not suitable for denoising patches containing relatively low amount of image details, a framework is designed to separate patches corresponding to low structured regions from a noisy image. Experiments are conducted by not subjecting such patches to matrix completion, instead denoising such patches in a different way. The resulting improvement in performance suggests that denoising low structured patches does not require a complex method like matrix completion and in fact it is counter-productive to subject such patches to matrix completion. These results also indicate the inherent limitation of matrix completion to deal with cases in which noise dominates the structural properties of an image. A novel method for introducing priorities to the ranked patches in matrix completion is also presented. Results showed that this method yields improved performance in general. It is observed that the artifacts in presence of low levels of pure Gaussian noise appear differently after introducing priorities to the patches and the artifacts occur at a wider range of parameter values. Results and discussion suggesting future ways to explore this problem are also presented. / Dissertation/Thesis / M.S. Electrical Engineering 2013

Alarming K-12 nationwide teacher attrition statistics have led reform efforts to focus on teacher retention (Olsen & Anderson, 2007), especially in urban schools where teacher burnout and attrition are high (Darling-Hammond, 1998). It was not until recently, however, that teacher resiliency, a strengths based framework (Henderson & Milstein, 2003), was viewed as an alternate lens of reform in achieving higher teacher retention. This study utilized a Likert survey to quantify if 284 elementary teachers in sixteen, public urban elementary schools in two urban school districts in southern California agree or disagree with the six most significant school factors linked to teacher resiliency. The six school factors known as collegiality/ collaboration, professional development, leadership, shared power, commitment to students, and teacher efficacy were identified by synthesizing the current literature on teacher resiliency and retention. The two most significant predictors of teacher resiliency from the literature, as found by multiple regression analyses, were commitment and values and shared power. This study also investigated whether resilient elementary teachers in urban schools self-reported any additional school factors linked to teacher resiliency, not originally identified in the literature. The significant additional school factors found in this study linked to resiliency were urban school dynamics, intrinsic motivation, and community.

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The overall goal of the dissertation is to contribute to the growing literature on the activity-based framework by focusing on the modeling of choices that are influenced by land-use and travel environment attributes. An accurate characterization of activity-travel patterns requires explicit consideration of the land-use and travel environment (referred to as travel environment from here on). There are two important categories of travel environment influences: direct (or causal) and indirect (or self-selection) effects. The direct effect of travel environment refers to how travel environment attributes causally influence travel choices. This direct effect may be captured by including travel environment variables as exogenous variables in travel models. Of course, determining if a travel environment variable has a direct effect on an activity/travel choice of interest is anything but straightforward. This is because of a potential indirect effect of the influence of the travel environment, which is not related to a causal effect. That is, the very travel environment attributes experienced by a decision maker (individual or household) is a function of a suite of a priori travel related choices made by the decision maker. The specific emphasis of the current dissertation is on moving away from considering travel environment choices as purely exogenous determinants of activity-travel models, and instead explicitly modeling travel environment decisions jointly along with activity-travel decisions in an integrated framework. Towards this end, the current dissertation formulates econometric models to analyze multidimensional choices. The multidimensional choice situations examined (and the corresponding model developed) in the research effort include: (1) reason for residential relocation and associated duration of stay (joint multinomial logit model and a grouped logit model), (2) household residential location and daily vehicle miles travelled (Copula based joint binary logit and log-linear regression model), (3) household residential location, vehicle type and usage choices (copula based Generalized Extreme Value and log-linear regression model) and (4) activity type, travel mode, time period of day, activity duration and activity location (joint multiple discrete continuous extreme value (MDCEV) model and multinomial logit model (MNL) with sampling of alternatives). The models developed in the current dissertation are estimated using actual field data from Zurich and San Francisco. A variety of policy exercises are conducted to illustrate the advantages of the econometric models developed. The results from these exercises clearly underline the importance of incorporating the direct and indirect effects of travel environment on these choice scenarios. / text