In a fully automated manufacturing environment, instant detection of condition state of the cutting tool is essential to the improvement of productivity and cost effectiveness. In this paper, a tool condition monitoring system (TCM) via machine learning (ML) and machine ensemble (ME) approach was developed to investigate the effectiveness of multisensor fusion when machining 4340 steel with multi-layer coated and multi-flute carbide end mill cutter. Feature- and decision-level information fusion models utilizing assorted combinations of sensors were studied against selected ML algorithms and their majority vote ensemble to classify gradual and transient tool abnormalities. The criterion for selecting the best model does not only depend on classification accuracy but also on the simplicity of the implemented system where the number of features and sensors is kept to a minimum to enhance the efficiency of the online acquisition system. In this study, 135 different features were extracted from sensory signals of force, vibration, acoustic emission and spindle power in the time and frequency domain by using data acquisition and signal processing modules. Then, these features along with machining parameters were evaluated for significance by using different feature reduction techniques. Specifically, two feature extraction methods were investigated: independent component analysis (ICA), and principal component analysis (PCA) and two feature selection methods were studied, chi square and correlation-based feature selection (CFS). For various multi-sensor fusion models, an optimal feature subset is computed. Finally, ML algorithms using support vector machine (SVM), multilayer perceptron neural networks (MLP), radial basis function neural network (RBF) and their majority voting ensemble were studied for selected features to classify not only flank wear but also breakage and chipping. In this research, it has been found that utilizing the multisensor feature fusion technique under majority vote ensemble gives the highest classification performance. In addition, SVM outperformed other ML algorithms while CFS feature selection method surpassed other reduction techniques in improving classification performance and producing optimal feature sets for different models.

Web-based service providers have long been required to deliver high quality services in accordance with standards and customer requirements. Increasingly, however, providers are required to think beyond service quality and develop a deeper understanding of their customers’ Quality of Experience (QoE). Whilst models exist that assess the QoE of Web Application, significant challenges remain in defining QoE factors from a Web engineering perspective, as well as mapping between so called ‘objective’ and ‘subjective’ factors of relevance. Specifically, the following challenges are considered as general fundamental problems for assessing QoE: (1) Quantifying the relationship between QoE factors; (2) predicting QoE as well as dealing with the limited data available in relation to subjective factors; (3) optimising and controlling QoE; and (4) perceiving QoE. In response, this research presents a novel model, called QoEWA (and associated software instantiation) that integrates factors through Key Performance Indicators (KPIs) and Key Quality Indicators (KQIs). The mapping is incorporated into a correlation model that assesses QoE, in particular, that of Web Application, with a consideration of defining the factors in terms of quality requirements derived from web architecture. The data resulting from the mapping is used as input for the proposed model to develop artefacts that: quantify, predict, optimise and perceive QoE. The development of QoEWA is framed and guided by Design Science Research (DSR) approach, with the purpose of enabling providers to make more informed decisions regarding QoE and/or to optimise resources accordingly. The evaluation of the designed artefacts is based on a build-and-evaluate cycle that provides feedback and a better understanding of the utilised solutions. The key artefacts are developed and evaluated through four iterations: Iteration 1 utilises the Actual Versus-Target approach to quantify QoE, and applies statistical analysis to evaluate the outputs. Iteration 2: utilises a Machine Learning (ML) approach to predict QoE, and applies statistical tests to compare the performance of ML algorithms. Iteration 3 utilises the Multi-Objective Optimisation (MOO) approach to optimise QoE and control the balance between resources and user experience. Iteration 4 utilises the Agent-Based Modelling approach to perceive and gain insights into QoE. The design of iteration 4 is rigorously tested using verified and validated models.

Around the world bridges are ageing. In Europe approximately two thirds of all railway bridges are over 50 years old. As these structures age, it becomes increasingly important that they are properly maintained. If damage remains undetected this can lead to premature replacement which can have major financial and environmental costs. It is also imperative that bridges are kept safe for the people using them. Thus, it is necessary for damage to be detected as early as possible. This research investigates an unsupervised, model-free damage detection method which could be implemented for continuous structural health monitoring. The method was based on past research by Gonzalez and Karoumi (2015), Neves et al. (2017) and Chalouhi et al. (2017). An artificial neural network (ANN) was trained on accelerations from the healthy structural state. Damage sensitive features were defined as the root mean squared errors between the measured data and the ANN predictions. A baseline healthy state could then be established by presenting the trained ANN with more healthy data. Thereafter, new data could be compared with this reference state. Outliers from the reference data were taken as an indication of damage. Two outlier detection methods were used: Mahalanobis distance and the Kolmogorov-Smirnov test. A model steel bridge with a span of 5 m, width of 1 m and height of approximately 1.7 m was used to study the damage detection method. The use of an experimental model allowed damaged to be freely introduced to the structure. The structure was excited with a 12.7 kg rolling mass at a speed of approximately 2.1 m/s (corresponding to a 20.4 ton axle load moving at 47.8 km/h in full scale). Seven accelerometers were placed on the structure and their locations were determined using an optimal sensor placement algorithm. The objectives of the research were to: identify a number of single damage cases, distinguish between gradual damage cases and identify the location of damage. The proposed method showed promising results and most damage cases were detected by the algorithm. Sensor density and the method of excitation were found to impact the detection of damage. By training the ANN to predict correlations between accelerometers the sensor closest to the damage could be detected, thus successfully localising the damage. Finally, a gradual damage case was investigated. There was a general increase in the damage index for greater damage however, this did not progress smoothly and one case of ‘greater’ damage showed a decrease in the damage index.

A construção de material didático é bastante difícil, mas avaliá-lo é ainda mais complexo. Saber como o aluno absorveu o conteúdo, como reagiu a ele e quanto tempo foi gasto durante o uso de cada objeto de aprendizagem pode ajudar a refletir se o conteúdo está adequado às necessidades deste aluno. Além disso, considerar as diferentes características cognitivas de aprendizado e, conseqüentemente, possibilitar adaptações através de ajustes no conteúdo didático digital auxiliaria a avaliação do professor em um curso disponível através da web. Este trabalho propõe um sistema de acompanhamento (MSys) que, através do monitoramento do nível de utilização das atividades desenvolvidas pelos alunos, deverá apresentar para o professor, assim como para o próprio aluno, resultados resumidos e comparativos do acompanhamento. Apesar de diversos ambientes do tipo LMS (Learning Management System) em uso atualmente estarem bastante difundidos, não tem sido dado a importância devida para este tipo de ferramenta capaz de oferecer um acompanhamento detalhado de atividades dos alunos. Este trabalho discute como a ferramenta aqui proposta foi concebida, desde sua arquitetura, que utiliza padrões atuais de construção de conteúdo digital, definindo requisitos funcionais para o seu desenvolvimento e exibindo resultados de uma simulação que comprova esta concepção. Além disso, é apresentado um protótipo da ferramenta, validando as interfaces de captura e exibição dos resultados e mostrando que é possível integrá-la a sistemas de aprendizado eletrônico, trazendo benefícios à avaliação do professor. / E-learning content creation is not an easy task, but its evaluation is even more complex. In order to evaluate if the content is adequate to the students needs, it would be helpful to know how the student assimilated the learning content, how he reacted to it and the period of time spent on the learning object. Besides, considering the different cognitive features of learning and the possibility of adjustment of the didactic content, it could help teacher\'s evaluation in an available online course. This work describes a monitoring system (Msys) that tracks the level of utilization of student\'s activities, and presents summarized and comparative results to the teacher and the student. Even though the widespread use of several LMS (Learning Management System) environments today, the importance of tools capable of offering a detailed monitoring of student\'s activities has not been recognized. This work focus on how the tool was created using current standards on digital content construction, defining functional requirements to its development and presenting simulation results that is a proof-ofconcept. Also, it is presented a prototype of the tool, validating the interfaces of capture and results presentation, showing that is possible to integrate it to online learning systems, bringing benefits to the teacher evaluation.

A construção de material didático é bastante difícil, mas avaliá-lo é ainda mais complexo. Saber como o aluno absorveu o conteúdo, como reagiu a ele e quanto tempo foi gasto durante o uso de cada objeto de aprendizagem pode ajudar a refletir se o conteúdo está adequado às necessidades deste aluno. Além disso, considerar as diferentes características cognitivas de aprendizado e, conseqüentemente, possibilitar adaptações através de ajustes no conteúdo didático digital auxiliaria a avaliação do professor em um curso disponível através da web. Este trabalho propõe um sistema de acompanhamento (MSys) que, através do monitoramento do nível de utilização das atividades desenvolvidas pelos alunos, deverá apresentar para o professor, assim como para o próprio aluno, resultados resumidos e comparativos do acompanhamento. Apesar de diversos ambientes do tipo LMS (Learning Management System) em uso atualmente estarem bastante difundidos, não tem sido dado a importância devida para este tipo de ferramenta capaz de oferecer um acompanhamento detalhado de atividades dos alunos. Este trabalho discute como a ferramenta aqui proposta foi concebida, desde sua arquitetura, que utiliza padrões atuais de construção de conteúdo digital, definindo requisitos funcionais para o seu desenvolvimento e exibindo resultados de uma simulação que comprova esta concepção. Além disso, é apresentado um protótipo da ferramenta, validando as interfaces de captura e exibição dos resultados e mostrando que é possível integrá-la a sistemas de aprendizado eletrônico, trazendo benefícios à avaliação do professor. / E-learning content creation is not an easy task, but its evaluation is even more complex. In order to evaluate if the content is adequate to the students needs, it would be helpful to know how the student assimilated the learning content, how he reacted to it and the period of time spent on the learning object. Besides, considering the different cognitive features of learning and the possibility of adjustment of the didactic content, it could help teacher\'s evaluation in an available online course. This work describes a monitoring system (Msys) that tracks the level of utilization of student\'s activities, and presents summarized and comparative results to the teacher and the student. Even though the widespread use of several LMS (Learning Management System) environments today, the importance of tools capable of offering a detailed monitoring of student\'s activities has not been recognized. This work focus on how the tool was created using current standards on digital content construction, defining functional requirements to its development and presenting simulation results that is a proof-ofconcept. Also, it is presented a prototype of the tool, validating the interfaces of capture and results presentation, showing that is possible to integrate it to online learning systems, bringing benefits to the teacher evaluation.

A method that uses machine learning to detect and localize damage in railway bridges under various environmental conditions is proposed and validated in this work. The developed algorithm uses vertical and lateral deck accelerations as damage- sensitive features. Indeed, an Artificial Neural Network (ANN) is trained to predict deck accelerations in undamaged condition given: previous vibration data, air temperature and characteristics of the train crossing the bridge (speed, load position and load magnitude). After an appropriate training period, the comparison between ANN-predicted and measured accelerations allows to compute prediction errors. A Gaussian Process is then used to stochastically characterize prediction errors in undamaged conditions using train speed as independent variable. Recorded vibration data leading to abnormal prediction errors are flagged as damage. The method is validated both on a simple numerical example and on data recorded on a real structure. In the latter case, an appropriate algorithm was developed with the aim of extracting vehicles characteristics from the acceleration time histories. Together with this part of the algorithm for the pre-processing of recorded accelerations, the novelty of the developed method is the addition of air temperature to the input. It allows separating between structure responses that can be flagged as damage from those only affected by environmental conditions.

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No. of bitstreams: 1 lucianatoquinidelimasilva.pdf: 1503407 bytes, checksum: f19f0499ae2bed7fe2d0aba5da08adaf (MD5) Previous issue date: 2014-08-22 / O presente trabalho tem como objetivo analisar a implementação do Programa de Recuperação Paralela, entre os anos de 2009 e 2012, em duas escolas rurais deEnsino Fundamental I, sendo vinculada uma à outra, situadas na cidade de Limeira, estado de São Paulo. A finalidade desse programa é recuperar a defasagem de aprendizagem dos alunos, evitando tanto a promoção automática sem a efetiva aquisição dos conhecimentos desejáveis a cada ano de escolaridade, quanto à reprovação no final dos ciclos, constituindo-se em uma estratégia importante para superar os desafios educacionais relacionados ao fracasso escolar.Para tanto, fez-se necessário verificar a ação dos atores envolvidos na prática, identificar quais os fatores relacionados à gestão se configuram como entraves ao Programa no que se relaciona à legítima qualidade da recuperação da aprendizagem dos alunos, além de investigar os efeitos sobre o seu desempenho. A intenção, a partir das informações investigadas, foi elaborar uma proposta de intervenção para aperfeiçoamento e monitoramento do Programa nas respectivas unidades escolares, visando à melhoria do processo de recuperação de aprendizagem, visto que os resultados das avaliações externas apresentaram declínio das médias nos anos pesquisados. O referencial metodológico para a coleta de dados pautou-se na abordagem qualitativa e quantitativa, sendo utilizados documentos oficiais normatizadores e reguladores referentes ao Programa de Recuperação Paralela, assim como registros intraescolares. Como instrumentos de pesquisa foram utilizados questionários com os professores da classe regular e entrevistas semiestruturadas com o professor da classe de recuperação paralela, professor coordenador pedagógico e vice-diretor. O embasamento teórico desta pesquisa tem como autores principais Heloísa Luck eThelma Polon, que abordam a temática das ações gestoras relacionadas ao monitoramento do desempenho dos alunos, Danilo Gandin eAraujo, que retratam a importância do planejamento participativo, visando ao trabalho colaborativo. Ainda, foram utilizados os estudos de Isabel Alarcão eJosé Carlos Libâneo naquilo que se relaciona à formação continuada inserida no contexto escolar. O resultado da pesquisa demonstrou que as ações dos atores envolvidos, especialmente do gestor escolar, denunciam a falta de planejamento organizado de forma participativa, sobre a perspectiva da cultura colaborativae a ausência de efetivo monitoramento do desempenho discente e de ações de formação continuada dentro do contexto escolar, o que requer desenvolvimento de ações que revertam a situação identificada e possibilitem maior eficiência e eficácia do Programa de Recuperação Paralela. / The present study aims to analyze the implementation of the Recovery Program Parallel, between the years 2009 and 2012 in two rural elementary schools Teaching I, being linked to each other, located in the city of Limeira, São Paulo state. The purpose of this program is to recover the gap of student learning, avoiding both the automatic promotion without the effective acquisition of desirable each year of schooling knowledge, as to fail at the end of cycles, thus becoming an important strategy to overcome the challenges education related to school failure. To this end, it was necessary to check the action of the actors involved in the practice, identify the factors related to management are configured as barriers to program, as it relates to the lawful recovery of quality of student performance, and to investigate the effects on performance . The intention, from the information investigated, was to draft a proposal for intervention for improvement and monitoring program in their school units in order to improve the recovery of the learning process, since the results of external evaluations show a decline in the years surveyed. The methodological framework for data collection was based on qualitative and quantitative approach, standard-setters and regulators official documents relating to Parallel Recovery Program, as well as intra school records being used. The research tools used questionnaires to teachers of regular classes and semi-structured interviews with the teacher of the class of parallel recovery, teacher pedagogical coordinator and deputy director were used. The theoretical basis of this study's main authors Heloise Luck and Thelma Polon, addressing the theme of management actions related to monitoring of student performance, and DaniloGandin Araujo that depict the importance of participatory planning, aiming to collaborative work. Still, studies Alarcão Isabel and Jose Carlos Libâneo in what relates to the inserted continuing education in the school context were used. The research result showed that the actions of the actors involved, especially the school manager, points to the lack of organized planning in a participatory way, from the perspective of collaborative culture and the absence of effective monitoring of student performance and actions of continuing education within the context school, which requires development of actions to reverse the situation identified and could improve the efficiency and effectiveness of the Recovery Program Parallel.

Organisationen haben Strukturen und Prozesse, in denen ihre Führungskräfte Self-Monitoring betreiben, um sich möglichst situationsangemessen zu verhalten. Die These: Self-Monitoring kann wissenschaftlich nicht nur als Eigen-schaft von der Person der Führ-ungskraft aus gedacht werden. Es wird die These begründet, dass Self-Monitoring in Führungsprozessen vor allem vom jeweiligen organisationalen Kontext aus bestimmt werden muss. Der Ansatz: In einer qualitativ-explorativen Studie wird das aus der Psychologie kommende Konzept des Self-Monitoring nach Snyder (1986) untersucht. Das Ziel ist die Erkundung der relevanten Einflussfaktoren und Bedingungen von Self-Monitoring bei Führungskräften in der Bundeswehr. Mit dieser Voraussetzung lässt sich ein strategisches und werteorientiertes Kompetenzmanagement gestalten.

La question générale envisagée dans cette recherche est le développement d'une représentation de scénarios d'apprentissage adaptable et facile à utiliser sous la forme d'une table (considéré comme un artefact de facile manipulation par les enseignants), associée à un modèle informatique sous la forme d'en arbre (comme un moyen d'intégrer des services avancés). Cette représentation permet à des enseignants sans entraînement méthodologique et ayant des compétences technologiques de base d'éditer et mettre en œuvre des scénarios d'apprentissage à partir d'une interface graphique intuitive et flexible. Bien que cette thèse soit centrée sur des scénarios collaboratifs, l'approche basée sur un modèle table-arbre (nommé T2) que nous proposons présente un intérêt plus général. Dans une première phase, nous avons développé à partir de ce modèle un éditeur de scénarios d'apprentissage (nommé ediT2) proposant des notions de modélisation utilisées dans les scénarios collaboratifs. Dans une seconde phase, nous avons considéré des questions de généralisation à travers l'extension de l'implémentation initiale, de telle manière à permettre aux utilisateurs d'éditer les notions et leurs attributs. Nous avons examiné à travers des études et expériences comment des enseignants ont utilisé notre proposition en tenant en compte comme objectifs/critères d'évaluation: (1) son expressivité pédagogique, i.e., si des éditeurs basés sur tables peuvent représenter une large gamme de scénarios d'apprentissage ; (2) sa facilité et son intuitivité ; (3) son expressivité informatique, i.e., si l'approche permet l'implémentation de services demandant des manipulations informatiques complexes ; et (4) sa flexibilité informatique, i.e., s'il est facile d'adapter l'éditeur à des besoins locaux. / The general issue considered in this research is the development of an adaptable and easy-to-use representation of learning scenarios in the form of a table (considered as an artefact of easy manipulation by teachers) associated with a computational model as a tree (as a way to integrate advanced services). In this way, teachers with basic technological skills and without methodological training can edit and operationalize learning scenarios from flexible and friendly graphical interfaces. Although this thesis has its focus on CSCL scripts, the table-tree-based approach (named T2) presents a more general interest. In a first moment, we implemented from this model a learning scenario editor (named ediT2) using notions from CSCL scripts. In a second moment, we considered generalization issues through the extension of the initial implementation, in order to allow teachers to edit their own notions and respective attributes. We investigated from different studies and experiments how teachers used our proposal considering as objectives/evaluation criteria the following features: (1) pedagogical expressiveness (can table-based editors represent a wide range of learning scenarios?); (2) usability (do teachers find the editor easy to use and intuitive?); (3) computational expressiveness (does the approach allow implementation of advanced services?), and; (4) computational flexibility (is the editor easy to adapt to local needs?).