Published Article / Although deterministic models still dominate hydrological modelling, there is a notable paradigm shift in catchment response modelling. An approach to represent the daily rainfall-flow (R-F) relationship using Data-Based Mechanistic (DBM) modelling is presented. DBM modelling is an inductive empirical transfer function (TF) approach relating input to output. The study used secondary data from the Department of Water Affairs and Forestry for the Upper Vaal water management area at station C1H007. The R-F model identification and optimisation was implemented in the CAPTAIN Toolbox in MATLAB. The best estimated R-F model was a 2nd order TF with an input lag of one day and R 2T= 56%. In mechanistic interpretation, three parallel flow pathways were discerned; the fast flow, slow flow and the loss component each constituting 49.8%, 24% and 26.2% of the modelled flow respectively. The study demonstrates that the approach adopted herein produces reasonably satisfactory results with a minimum of the readily available catchment data.

This study was conducted to explorer the relationships between teachers’ perceptions of educational data use, their school’s capacity as a learning organization, and the performance of students at their school. This study employed a quantitative research design featuring a Web-based online survey and collected data from a stratified random sample of 112 middle schools and junior high schools nested in nine school districts in Texas. I used the Dimensions of the Learning Organization Questionnaire (Watkins & Marsick, 1993, 1996) to measure the schools’ capacity as a learning organizations and the Survey of Educator Data Use (Wayman, Cho, & Shaw, 2009b) to measure teachers’ educational data use. I also used the student performance data provided by Texas Education Agency. For the data analysis, I employed the statistical techniques of multivariate analysis of covariance (MANCOVA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). I found that educational data use and support did relate to the schools’ organizational learning capacity, and that this dynamic acts as an important factor in enhancing campus performance. This finding gives a clear indication that data use and support has an indirect effect on campus performance, and that this effect is mediated by organizational learning. This research is significant in that it reveals that organizational learning worked as a crucial mediating variable in enhancing student achievement through effective use of data. This finding can give meaningful direction to the pursuit of school improvement through data use in school sites, a practice that began as simple top-down policy implementation. / text

O projeto de controladores baseado em dados tem como finalidade o ajuste dos parâ- metros de controle através de experimentos realizados no sistema, sem considerar mode- los que descrevem a dinâmica ou identificação do processo. Na literatura existem diferen- tes abordagens para este tipo de controle, e a análise e a aplicação de um destes métodos é o propósito desta dissertação. O objetivo deste trabalho é apresentar uma melhoria ao mé- todo de sintonia de controladores baseado em Referência Virtual (VRFT) para sistemas multivariáveis (MIMO), visto que a metodologia apresentada na literatura limita a apli- cação do método a uma classe restrita de processos. A metodologia de controle baseado em dados pode ser considerada consolidada para implementação em sistemas monovariá- veis, porém a extensão desta metodologia a sistemas MIMO é uma necessidade a fim de acrescentar a aplicabilidade em processos cujas diferentes variáveis a serem controladas interferem umas nas outras. Diferente do método apresentado na literatura, o método pro- posto neste trabalho permite a aplicação do VRFT em sistemas MIMO onde os requisitos de desempenho podem ser escolhidos de forma específica para cada variável. Além disso, a utilização de variável instrumental e/ou um filtro mostram-se adequadas para estimar os controladores quando os dados são afetados por ruído. Considerando que a eficácia da metodologia depende de fatores como as características da planta, o modelo de referên- cia e estrutura do controlador escolhidos, e a presença ou não de ruído, realiza-se uma comparação de resultados a fim de avaliar as melhorias obtidas. Finalmente, testes foram conduzidos em uma planta de nível do laboratório de controle, implementado o método proposto, o qual apresentou um desempenho satisfatório mostrando a aplicabilidade desta metodologia em sistemas reais. / Data-driven control methods are a variety of control designs that are developed to use batches of input-output data collected, from the process to be controlled without mak- ing explicitly use of parametric models of these processes. Although data driven control methods have been largely used in SISO systems, the extent of this methodology to mul- tivariable processes is yet a necessity, considering that the control design must take into account the multivariable nature of the process, that is, the interaction between different variables involved. The analysis and application of one of these methods is the main objective of this work, which is intended to present and improvement to the existing Virtual Reference Feedback Tuning Method (VRFT) for Multivariable systems, since the methodology disclosed in the literature restricts the application to a limited class of pro- cesses. Moreover, in this work it is proposed an extension of the VRFT method to the MIMO case, which does not present restrictions and closed loop performance of each variable can be determined accordingly. The method can be used to tune a centralized or decentralized controller. Furthermore, when the signals are corrupted by noise the use of an instrumental variable and/or an appropriate filter is proposed. All these contributions are demonstrated through simulations as well as tests conducted in a real plant, which showed satisfactory performance demonstrating the applicability of this method in real systems.

O projeto de controladores baseado em dados tem como finalidade o ajuste dos parâ- metros de controle através de experimentos realizados no sistema, sem considerar mode- los que descrevem a dinâmica ou identificação do processo. Na literatura existem diferen- tes abordagens para este tipo de controle, e a análise e a aplicação de um destes métodos é o propósito desta dissertação. O objetivo deste trabalho é apresentar uma melhoria ao mé- todo de sintonia de controladores baseado em Referência Virtual (VRFT) para sistemas multivariáveis (MIMO), visto que a metodologia apresentada na literatura limita a apli- cação do método a uma classe restrita de processos. A metodologia de controle baseado em dados pode ser considerada consolidada para implementação em sistemas monovariá- veis, porém a extensão desta metodologia a sistemas MIMO é uma necessidade a fim de acrescentar a aplicabilidade em processos cujas diferentes variáveis a serem controladas interferem umas nas outras. Diferente do método apresentado na literatura, o método pro- posto neste trabalho permite a aplicação do VRFT em sistemas MIMO onde os requisitos de desempenho podem ser escolhidos de forma específica para cada variável. Além disso, a utilização de variável instrumental e/ou um filtro mostram-se adequadas para estimar os controladores quando os dados são afetados por ruído. Considerando que a eficácia da metodologia depende de fatores como as características da planta, o modelo de referên- cia e estrutura do controlador escolhidos, e a presença ou não de ruído, realiza-se uma comparação de resultados a fim de avaliar as melhorias obtidas. Finalmente, testes foram conduzidos em uma planta de nível do laboratório de controle, implementado o método proposto, o qual apresentou um desempenho satisfatório mostrando a aplicabilidade desta metodologia em sistemas reais. / Data-driven control methods are a variety of control designs that are developed to use batches of input-output data collected, from the process to be controlled without mak- ing explicitly use of parametric models of these processes. Although data driven control methods have been largely used in SISO systems, the extent of this methodology to mul- tivariable processes is yet a necessity, considering that the control design must take into account the multivariable nature of the process, that is, the interaction between different variables involved. The analysis and application of one of these methods is the main objective of this work, which is intended to present and improvement to the existing Virtual Reference Feedback Tuning Method (VRFT) for Multivariable systems, since the methodology disclosed in the literature restricts the application to a limited class of pro- cesses. Moreover, in this work it is proposed an extension of the VRFT method to the MIMO case, which does not present restrictions and closed loop performance of each variable can be determined accordingly. The method can be used to tune a centralized or decentralized controller. Furthermore, when the signals are corrupted by noise the use of an instrumental variable and/or an appropriate filter is proposed. All these contributions are demonstrated through simulations as well as tests conducted in a real plant, which showed satisfactory performance demonstrating the applicability of this method in real systems.

O projeto de controladores baseado em dados tem como finalidade o ajuste dos parâ- metros de controle através de experimentos realizados no sistema, sem considerar mode- los que descrevem a dinâmica ou identificação do processo. Na literatura existem diferen- tes abordagens para este tipo de controle, e a análise e a aplicação de um destes métodos é o propósito desta dissertação. O objetivo deste trabalho é apresentar uma melhoria ao mé- todo de sintonia de controladores baseado em Referência Virtual (VRFT) para sistemas multivariáveis (MIMO), visto que a metodologia apresentada na literatura limita a apli- cação do método a uma classe restrita de processos. A metodologia de controle baseado em dados pode ser considerada consolidada para implementação em sistemas monovariá- veis, porém a extensão desta metodologia a sistemas MIMO é uma necessidade a fim de acrescentar a aplicabilidade em processos cujas diferentes variáveis a serem controladas interferem umas nas outras. Diferente do método apresentado na literatura, o método pro- posto neste trabalho permite a aplicação do VRFT em sistemas MIMO onde os requisitos de desempenho podem ser escolhidos de forma específica para cada variável. Além disso, a utilização de variável instrumental e/ou um filtro mostram-se adequadas para estimar os controladores quando os dados são afetados por ruído. Considerando que a eficácia da metodologia depende de fatores como as características da planta, o modelo de referên- cia e estrutura do controlador escolhidos, e a presença ou não de ruído, realiza-se uma comparação de resultados a fim de avaliar as melhorias obtidas. Finalmente, testes foram conduzidos em uma planta de nível do laboratório de controle, implementado o método proposto, o qual apresentou um desempenho satisfatório mostrando a aplicabilidade desta metodologia em sistemas reais. / Data-driven control methods are a variety of control designs that are developed to use batches of input-output data collected, from the process to be controlled without mak- ing explicitly use of parametric models of these processes. Although data driven control methods have been largely used in SISO systems, the extent of this methodology to mul- tivariable processes is yet a necessity, considering that the control design must take into account the multivariable nature of the process, that is, the interaction between different variables involved. The analysis and application of one of these methods is the main objective of this work, which is intended to present and improvement to the existing Virtual Reference Feedback Tuning Method (VRFT) for Multivariable systems, since the methodology disclosed in the literature restricts the application to a limited class of pro- cesses. Moreover, in this work it is proposed an extension of the VRFT method to the MIMO case, which does not present restrictions and closed loop performance of each variable can be determined accordingly. The method can be used to tune a centralized or decentralized controller. Furthermore, when the signals are corrupted by noise the use of an instrumental variable and/or an appropriate filter is proposed. All these contributions are demonstrated through simulations as well as tests conducted in a real plant, which showed satisfactory performance demonstrating the applicability of this method in real systems.

Current research suggests schools face many barriers in effectively monitoring student's response to behavioral interventions in the classroom. The purpose of this study was to evaluate the FastBridge - Direct Behavior Rating (FastBridge-DBR), a brief, novel progress monitoring measure, designed to assess student behavioral change in response to a classroom behavioral intervention. Twenty-four elementary teacher-student dyads implemented a daily progress report intervention to promote positive student behavior during pre-specified classroom activities. FastBridge-DBR data were then collected for three target behaviors (i.e., Academic Engagement, Disruptive Behavior, Withdrawal) and compared to Systematic Direct Observation (SDO) data. Five change metrics (i.e., absolute change, percent of change from baseline, improvement rate difference, Tau-U, effect size; Gresham, 2005) were used to examine sensitivity to change. The Usage Rating Profile - Assessment (URP-A) was used to evaluate teacher acceptability of FastBridge-DBR. FastBridge-DBR scores were highly correlated with SDO data, demonstrating evidence of concurrent validity. FastBridge-DBR change metrics were significantly correlated with SDO change metrics. Additionally, while teachers provided high acceptability ratings for FastBridge-DBR, there was a lack of association between teachers' ratings of acceptability and student behavioral change. Implications for practice, study limitations, and areas of future research are discussed.

Controladores PID são amplamente utilizados no controle de processos industriais. Estes controladores precisam necessariamente ser ajustados adequadamente a fim de garantir a correta operação do processo controlado. A fim de suprir esta necessidade surgiram os chamados métodos de ajuste para controladores PID, inicialmente propostos por John Ziegler e Nathaniel B. Nichols em 1942. Desde então muitos outros métodos de ajuste baseados nas idéias de Ziegler e Nichols foram propostos, surgindo assim uma família de métodos afins. Em vista da simplicidade de implementação e do consequente baixo custo computacional envolvido, estes métodos mostraram-se adequados para serem incorporados ao firmware de controladores PID industriais de baixo custo. Estes métodos acabaram por gerar um legado tal que sua utilização persiste intensamente até os dias de hoje. No entanto, frente à crescente oferta de microcontroladores de baixo custo e alto desempenho, o custo computacional de um método de ajuste vem perdendo relevância. Isso abre margem para explorar outros métodos que proporcionem melhor desempenho e robustez, mas, por ventura, demandem mais recursos computacionais. Dessa forma, este trabalho propõe-se a avaliar métodos alternativos que sejam compatíveis com os recursos computacionais atuais. Métodos com maior custo computacional, como o Virtual Reference Feedback Tuning (VRFT), Iterative Feedback Tuning (IFT) e Iterative Correlation-based Tuning (ICbT), são apresentados como candidatos para serem incorporados ao firmware de controladores PID industriais. Tratam-se de métodos diretos de ajuste baseado em dados onde os parâmetros do controlador são determinados de forma que o comportamento do sistema em malha fechada seja tal que minimize um critério de desempenho definido a priori. Através deste critério de desempenho pode-se definir o comportamento desejado para o sistema em malha fechada. Neste trabalho são analisadas as principais características destes métodos, resultados obtidos e custo computacional. Com base nos resultados desta análise é mostrado que os métodos VRFT, IFT e ICbT podem ser utilizados como alternativa para o ajuste (incorporado ao firmware) de controladores PID industriais. / PID controllers are widely used in industrial process control. These controllers must necessarily be properly tuned to ensure the correct operation of the controlled process. In order to meet this need, the so-called tuning methods for PID controllers have emerged, initially proposed by John Ziegler and Nathaniel B. Nichols in 1942. Since then many other controller design methods based on the ideas of Ziegler and Nichols have been proposed, giving rise to a family of related methods. Given the simplicity of implementation and the low computational effort involved, these methods are suitable to be incorporated into the firmware of low cost industrial PID controllers. These methods have generated such a legacy that its use remains intense until the present day. However, with the growing offer of low cost and high performance microcontrollers, the computational effort of a tuning method is becoming less important. This opens up scope for exploring other methods that provide better performance and robustness, possibly at the cost of demanding more computational resources. This study aims to evaluate alternative methods that are compatible with current computational resources. Methods with higher computational effort, such as Virtual Reference Feedback Tuning (VRFT), Iterative Feedback Tuning (IFT) and Iterative Correlation based Tuning (ICbT) are presented as candidates to be incorporated into the firmware of industrial PID controllers. These are direct data-based methods for the adjustment of controllers where the parameters are determined such that the behavior of the closed-loop system is such as to minimize a performance criterion defined a priori. Through this performance criterion one can specify the desired behavior for the closed-loop system. This work analyzes the main characteristics of these methods, results and computational effort. Based on the results of this analysis it is shown that the methods VRFT, IFT and ICbT can be used as an alternative to the adjustment (build into the firmware) of industrial PID controllers.

The aim of the Reading First grant program was to (a) increase quality and consistency of instruction in K-3 classrooms; (b) conduct timely and valid assessments of student reading growth in order to identify students experiencing reading difficulties; and (c) provide high quality, intensive interventions to help struggling readers catch up with their peers (Torgesen, 2002). In the State of Florida, school districts must incorporate the use of an assessment tool called the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) to qualify for Reading First grant funding. Though DIBELS has been found to be a valid and reliable assessment for screening, monitoring, and evaluating student outcomes in early literacy skills, very little discussion or research has been conducted concerning teacher use and attitudes about DIBELS within a Reading First program. The present study involved a qualitative analysis of teachers' perceptions and use of the DIBELS within a Reading First context. Fourteen teachers (seven kindergarten and seven first grade teachers), Reading Coaches, non-teaching Specialists, and DIBELS experts participated in the present study. Results were aggregated for comparisons across multiple data sources. Results suggest teacher's perceptions may not be easily classified on a simple dichotomous range; rather their reported benefits and concerns on the use of the DIBELS were found to be varied and highly situational. Results were further interpreted in the context of research literature on data utilization and analysis in schools.

The purpose of the study was to investigate the effects of real data based and calculator supported statistics activities on 7th grade students&amp / #8217 / statistics performance and attitudes towards statistics when the statistics performance of the students prior to the instruction and the previous mathematics grades were controlled. A quasi-experimental design was used to investigate the research problem. The research was conducted by 84 seventh grade students. There were three groups in the study. Two of them were experimental groups and one of them was control group. The first group received instruction by the traditional method (TM), the second group received instruction by real data based and calculator supported statistical activities (RDBCSSA), and the third group was instructed by real data based statistical activities (RDBSA), the number of the subjects was 28, 27 and 29 respectively. Data were collected through three different measuring instruments: 1.Statistical Performance Test 1 (SPT1) / 2.Statistical Performance Test 2 (SPT2) / 3.Statistics Attitude Scale (SAS). The SPT1 was used as a pre-test. The SPT2 was administered as a post-test. SPT1 and SPT2 were used to determine the statistics performance of the students before and after the instruction. SAS was used to determine the attitudes of the students toward statistics. The data of this study were analyzed by analysis of variance (ANOVA) and analysis of covariance (ANCOVA). The results revealed that there was no significant mean difference among the groups with respect to statistics performance. Also there was no significant mean difference among the groups with respect to attitudes towards statistics. The mean scores of the Statistics Attitude Scale items were calculated and the results revealed that the students had positive attitudes to the statements in Statistics Attitude Subscale 1 (Confidence in Learning Statistics) and they were neutral to the statements of the Statistics Attitude Subscale 2. Also the students wrote their opinions about the teaching methods and their impressions were analyzed by making a frequency table. Most of the TM students mentioned that the examples should be more attractive such that the activity sheets could contain real data based examples. However some of the students mentioned that traditional method was good and the subject was understood very well. Most of the RDBSA students mentioned that the teaching method was enjoyable. Most of the RDBCSSA students expressed that the calculators made the lessons enjoyable and the study easy.

Air Traffic Management (ATM) aims at ensuring safe and efficient movement of aircraft in the airspace. The National Airspace System is currently undergoing a comprehensive overhaul known as NextGen. With the predicted growth of air transportation, providing traffic flow managers with the tools to support decision making is essential. These tools should aid in accommodating the air traffic throughput increase, while limiting controller workload and ensuring high safety levels. In the National Airspace System (NAS), the goal of en-route Traffic Flow Management (TFM) is to balance air traffic demand against available airspace capacity, in order to ensure a safe and expeditious flow of aircraft, both under nominal and perturbed conditions. The objective of this thesis is to develop a better understanding of how to analyze, model and simulate air traffic in a given airspace, under both nominal and degraded conditions. First, a new framework for en-route Traffic Flow Management and Airspace Health Monitoring is developed. It is based on a data-driven approach for air traffic flow modeling using historical data. This large-scale 3D flow network of the Cleveland center airspace provides valuable insight on airspace complexity. A linear formulation for optimizing en-route Air Traffic is proposed. It takes into account a controller taskload model based on flow geometry, in order to estimate airspace capacity. The simulations run demonstrate the importance of sector constraints and traffic demand patterns in estimating the throughput of an airspace. To analyze airspace degradation, weather blockage maps based on vertically integrated liquid (VIL) are incorporated in the model, representing weather perturbations on the same data set used to compute the flows. Comparing the weather blockages and the network model of the airspace provides means of quantifying airspace degradation. Simulations under perturbed conditions are then run according to different objectives. The results of the simulations are compared with the data from these specific days, to identify the advantages and drawbacks of the present model.