Comprehensive strategic plan for elementary and secondary education, 2005 /

Pursuant to Public Act 93-1036, the Illinois State Board of Education has developed a five year comprehensive strategic plan for elementary and secondary education in Illinois. The plan focuses on three primary goal areas: enhancing literacy; improving educator quality for all children; and expanding data-driven management and school support practices.

Comprehensive strategic plan for elementary and secondary education progress report /

Pursuant to Public Act 93-1036, the Illinois State Board of Education has developed a five year comprehensive strategic plan for elementary and secondary education in Illinois. The plan focuses on three primary goal areas: enhancing literacy; improving educator quality for all children; and expanding data-driven management and school support practices.

Collaborative Change: A Survey of Collaborations in Museums to Address Social Issues

Thesis (Master's)--University of Washington, 2016-06

Information extraction from clinical and radiology notes for liver cancer staging

Thesis (Ph.D.)--University of Washington, 2016-06

Educational Systems for Maximizing Learning Online and in the Classroom

Thesis (Ph.D.)--University of Washington, 2016-06

OMERACT-OARSI Initiative: Osteoarthritis Research Society International set of responder criteria for osteoarthritis clinical trials revisited.

Background: The OARSI Standing Committee for Clinical Trials Response Criteria Initiative had developed two sets of responder criteria to present the results of changes after treatment in three symptomatic domains (pain, function, and patient's global assessment) as a single variable for clinical trials (1). For each domain, a response was defined by both a relative and an absolute change, with different cut-offs with regard to the drug, the route of administration and the OA localization. Objective: To propose a simplified set of responder criteria with a similar cut-off, whatever the drug, the route or the OA localization. Methods: Data driven approach: (1) Two databases were considered The 'elaboration' database with which the formal OARSI sets of responder criteria were elaborated and The 'revisit' database. (2) Six different scenarios were evaluated: The two formal OARSI sets of criteria Four proposed scenarios of simplified sets of criteria Data from clinical randomized blinded placebo controlled trials were used to evaluate the performances of the two formal scenarios with two different databases ('elaboration' versus 'revisit') and those of the four proposed simplified scenarios within the 'revisit' database. The placebo effect, active effect, treatment effect, and the required sample arm size to obtain the placebo effect and the active treatment effect observed were the performances evaluated for each of the six scenarios. Experts' opinion approach: Results were discussed among the participants of the OMERACT VI meeting, who voted to select the definite OMERACT-OARSI set of criteria (one of the six evaluated scenarios). Results: Data driven approach: Fourteen trials totaling 1886 CA patients and fifteen studies involving 8164 CA patients were evaluated in the 'elaboration' and the 'revisit' databases respectively. The variability of the performances observed in the 'revisit' database when using the different simplified scenarios was similar to that observed between the two databases ('elaboration' versus 'revisit') when using the formal scenarios. The treatment effect and the required sample arm size were similar for each set of criteria. Experts' opinion approach: According to the experts, these two previous performances were the most important of an optimal set of responder criteria. They chose the set of criteria considering both pain and function as evaluation domain and requiring an absolute change and a relative change from baseline to define a response, with similar cut-offs whatever the drug, the route of administration or the CA localization. Conclusion: This data driven and experts' opinion approach is the basis for proposing an optimal simplified set of responder criteria for CA clinical trials. Other studies, using other sets of CA patients, are required in order to further validate this proposed OMERACT - OARSI set of criteria. (C) 2004 OsteoArthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

A flexible, extensible object oriented real-time near photorealistic visualization system:the system framework design

In this paper we describe a novel, extensible visualization system currently under development at Aston University. We introduce modern programming methods, such as the use of data driven programming, design patterns, and the careful definition of interfaces to allow easy extension using plug-ins, to 3D landscape visualization software. We combine this with modern developments in computer graphics, such as vertex and fragment shaders, to create an extremely flexible, extensible real-time near photorealistic visualization system. In this paper we show the design of the system and the main sub-components. We stress the role of modern programming practices and illustrate the benefits these bring to 3D visualization. © 2006 Springer-Verlag Berlin Heidelberg.

Exchange rate forecasting using a combined parametric and nonparametric self-organising modelling approach

Financial prediction has attracted a lot of interest due to the financial implications that the accurate prediction of financial markets can have. A variety of data driven modellingapproaches have been applied but their performance has produced mixed results. In this study we apply both parametric (neural networks with active neurons) and nonparametric (analog complexing) self-organisingmodelling methods for the daily prediction of the exchangerate market. We also propose acombinedapproach where the parametric and nonparametricself-organising methods are combined sequentially, exploiting the advantages of the individual methods with the aim of improving their performance. The combined method is found to produce promising results and to outperform the individual methods when tested with two exchangerates: the American Dollar and the Deutche Mark against the British Pound.

Digital control system programming from process control diagrams

A graphical process control language has been developed as a means of defining process control software. The user configures a block diagram describing the required control system, from a menu of functional blocks, using a graphics software system with graphics terminal. Additions may be made to the menu of functional blocks, to extend the system capability, and a group of blocks may be defined as a composite block. This latter feature provides for segmentation of the overall system diagram and the repeated use of the same group of blocks within the system. The completed diagram is analyzed by a graphics compiler which generates the programs and data structure to realise the run-time software. The run-time software has been designed as a data-driven system which allows for modifications at the run-time level in both parameters and system configuration. Data structures have been specified to ensure efficient execution and minimal storage requirements in the final control software. Machine independence has been accomodated as far as possible using CORAL 66 as the high level language throughout the entire system; the final run-time code being generated by a CORAL 66 compiler appropriate to the target processor.

Design of an expandable manufacturing simulator through the application of object-oriented principles

In analysing manufacturing systems, for either design or operational reasons, failure to account for the potentially significant dynamics could produce invalid results. There are many analysis techniques that can be used, however, simulation is unique in its ability to assess detailed, dynamic behaviour. The use of simulation to analyse manufacturing systems would therefore seem appropriate if not essential. Many simulation software products are available but their ease of use and scope of application vary greatly. This is illustrated at one extreme by simulators which offer rapid but limited application whilst at the other simulation languages which are extremely flexible but tedious to code. Given that a typical manufacturing engineer does not posses in depth programming and simulation skills then the use of simulators over simulation languages would seem a more appropriate choice. Whilst simulators offer ease of use their limited functionality may preclude their use in many applications. The construction of current simulators makes it difficult to amend or extend the functionality of the system to meet new challenges. Some simulators could even become obsolete as users, demand modelling functionality that reflects the latest manufacturing system design and operation concepts. This thesis examines the deficiencies in current simulation tools and considers whether they can be overcome by the application of object-oriented principles. Object-oriented techniques have gained in popularity in recent years and are seen as having the potential to overcome any of the problems traditionally associated with software construction. There are a number of key concepts that are exploited in the work described in this thesis: the use of object-oriented techniques to act as a framework for abstracting engineering concepts into a simulation tool and the ability to reuse and extend object-oriented software. It is argued that current object-oriented simulation tools are deficient and that in designing such tools, object -oriented techniques should be used not just for the creation of individual simulation objects but for the creation of the complete software. This results in the ability to construct an easy to use simulator that is not limited by its initial functionality. The thesis presents the design of an object-oriented data driven simulator which can be freely extended. Discussion and work is focused on discrete parts manufacture. The system developed retains the ease of use typical of data driven simulators. Whilst removing any limitation on its potential range of applications. Reference is given to additions made to the simulator by other developers not involved in the original software development. Particular emphasis is put on the requirements of the manufacturing engineer and the need for Ihe engineer to carrv out dynamic evaluations.

Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

Is there life in the old dogs yet? Making break-tests work on financial contagion

Many tests of financial contagion require a definition of the dates separating calm from crisis periods. We propose to use a battery of break search procedures for individual time series to objectively identify potential break dates in relationships between countries. Applied to the biggest European stock markets and combined with two well established tests for financial contagion, this approach results in break dates which correctly identify the timing of changes in cross-country transmission mechanisms. Application of break search procedures breathes new life into the established contagion tests, allowing for an objective, data-driven timing of crisis periods.

One date, one break?

This paper demonstrates that the conventional approach of using official liberalisation dates as the only existing breakdates could lead to inaccurate conclusions as to the effect of the underlying liberalisation policies. It also proposes an alternative paradigm for obtaining more robust estimates of volatility changes around official liberalisation dates and/or other important market events. By focusing on five East Asian emerging markets, all of which liberalised their financial markets in the late, and by using recent advances in the econometrics of structural change, it shows that (i) the detected breakdates in the volatility of stock market returns can be dramatically different to official liberalisation dates and (ii) the use of official liberalisation dates as breakdates can readily entail inaccurate inference. In contrast, the use of data-driven techniques for the detection of multiple structural changes leads to a richer and inevitably more accurate pattern of volatility evolution emerges in comparison with focussing on official liberalisation dates.