PETRA: Process Evolution using a TRAce-based system on a maintenance platform

To meet increasing needs in the field of maintenance, we studied the dynamic aspect of process and services on a maintenance platform, a major challenge in process mining and knowledge engineering. Hence, we propose a dynamic experience feedback approach to exploit maintenance process behaviors in real execution of the maintenance platform. An active learning process exploiting event log is introduced by taking into account the dynamic aspect of knowledge using trace engineering. Our proposal makes explicit the underlying knowledge of platform users by means of a trace-based system called “PETRA”. The goal of this system is to extract new knowledge rules about transitions and activities in maintenance processes from previous platform executions as well as its user (i.e. maintenance operators) interactions. While following a Knowledge Traces Discovery process and handling the maintenance ontology IMAMO, “PETRA” is composed of three main subsystems: tracking, learning and knowledge capitalization. The capitalized rules are shared in the platform knowledge base in order to be reused in future process executions. The feasibility of this method is proven through concrete use cases involving four maintenance processes and their simulation

Energy Yield and Electricity Management of Thin-Film and Crystalline Silicon Solar Cells:from Devices to Systems

In the case of high photovoltaic (PV) penetration into the electricity grid, the energy produced by a PV system that is effectively used (useful energy) depends on the energy yield and on how this energy is managed to avoid detrimental effects occurring at high PV injection, e.g. during the midday peak. The overall goal of this thesis is to provide guidelines for maximizing the useful energy of a PV system by quantifying losses incurred during operation at both the solar cell device and the system levels. Solar cells are usually optimized for the standard test conditions (STC). However, the conditions are generally different during operation. This work assesses how solar cell materials and designs can be optimized to maximize the energy yield for specific operating condition. We mainly focus on thin-film silicon solar cells because of their challenging metastable behavior. The temperature dependence of the performance of thin-film amorphous silicon (a-Si:H) and microcrystalline silicon solar cells is thus measured for different deposition parameters and cell designs. We observe that, by tuning the intrinsic layer thickness of a-Si:H cells, the cells with the best (STC) efficiency do not necessarily provide the highest energy output. We also explain the presence of a maximum in the value of the fill factor as a function of temperature. The temperature dependence study is then extended to thin-film silicon multi-junction, crystalline silicon heterojunction (SHJ) and other crystalline silicon solar cells. For thin-film silicon solar cells, spectral effects and degradation or recovery effects due to the metastable character of a-Si:H (due to the Staebler-Wronski effect) significantly impact the energy yield. Based on indoor and outdoor degradation/recovery experiments, we show that it is challenging to describe this metastability with a diode model. However, such a model with a current loss term and an additional temperature dependence for the saturation current and ideality factors accurately reproduces the current-voltage characteristics of a-Si:H solar cells over a wide range of irradiance levels and operating temperatures. On the system level, we model a PV system with local storage to evaluate several strategies to reduce the detrimental midday injection peaks. The impact of such measures on the useful energy is also investigated. We develop a simple control algorithm that minimizes the losses due to a feed-in limit and maximizes self-consumption without the need of a production forecast. We show that heat storage using a boiler or a heat pump performs as well as battery storage. In general, a feed-in limit reduces significantly peak injection but only a relatively small storage capacity is needed to reduce losses (due to this limit). Changes in tilt and orientation of modules also reduce losses resulting from feed-in limits and shrink the winter/summer production ratio by more than a factor of two. We also develop a statistical method that estimates - from loads measured every 15 min - when different electrical appliances in a household are commonly used. This model indicates that about 8% of the total load could be shifted easily to the midday period, thereby reducing the midday injection peak. Finally, we combine device and system aspects to show that varying cell technology (e.g. with different temperature response) has a limited but not negligible impact on system output

A multi-fold assessment framework for virtualized collaborative and social learning scenarios

Proposem un procés de virtualització de sessions col·laboratives en directe a partir de fòrums de discussió i xats web amb l'objectiu de produir recursos d'aprenentatge en línia interactius per a ser utilitzats pels alumnes i generar un efecte positiu en la participació de l'alumne. Per tal de millorar encara més la implicació de l'aprenentatge, vam dotar al nostre procés de virtualització d'un marc d'avaluació múltiple que proporciona la consciència efectiva i la retroalimentació constructiva als alumnes de la col·laboració original amb interaccions entre els membres del grup. La investigació presentada es centra en l'avaluació electrònica d'aprenentatge col·laboratiu i social i s'estén amb analítiques d'aprenentatge i tècniques d'anàlisi de xarxa social que són capaces d'analitzar i representar les interaccions cognitives i socials amb sessions de col·laboració en viu subjacents.Proponemos un proceso de virtualización de sesiones colaborativas en directo a partir de foros de discusión y chats web con el objetivo de producir recursos de aprendizaje en línea interactivos para ser utilizados por los alumnos y generar un efecto positivo en la participación del alumno. Con el fin de mejorar aún más la implicación del aprendizaje, dotamos a nuestro proceso de virtualización de un marco de evaluación múltiple que proporciona la conciencia efectiva y la retroalimentación constructiva a los alumnos de la colaboración original con interacciones entre los miembros del grupo. La investigación presentada se centra en la evaluación electrónica de aprendizaje colaborativo y social y se extiende con analíticas de aprendizaje y técnicas de análisis de red social que son capaces de analizar y representar las interacciones cognitivas y sociales con sesiones de colaboración en vivo subyacentes.We propose a virtualization process of live collaborative sessions from Web discussion forums and chats with the aim to produce interactive and attractive online learning resources to be used by learners, thus having a positive effect in learner engagement. In order to enhance further learning engagement, we endow our virtualization process with a multifold assessment framework that provides effective awareness and constructive feedback to learners from the original collaborative interactions among group members. The research presented focuses on e-assessment of collaborative and social learning and extends it with Learning Analytics and Social Network Analysis techniques that are able to analyse and represent cognitive and social interactions underlying live collaborative sessions