Monitoring spatial sustainable development: Semi-automated analysis of satellite and aerial images for energy transition and sustainability indicators

Solar panels are installed by a large and growing number of households due to the convenience of having cheap and renewable energy to power house appliances. In contrast to other energy sources solar installations are distributed very decentralized and spread over hundred-thousands of locations. On a global level more than 25% of solar photovoltaic (PV) installations were decentralized. The effect of the quick energy transition from a carbon based economy to a green economy is though still very difficult to quantify. As a matter of fact the quick adoption of solar panels by households is difficult to track, with local registries that miss a large number of the newly built solar panels. This makes the task of assessing the impact of renewable energies an impossible task. Although models of the output of a region exist, they are often black box estimations. This project's aim is twofold: First automate the process to extract the location of solar panels from aerial or satellite images and second, produce a map of solar panels along with statistics on the number of solar panels. Further, this project takes place in a wider framework which investigates how official statistics can benefit from new digital data sources. At project completion, a method for detecting solar panels from aerial images via machine learning will be developed and the methodology initially developed for BE, DE and NL will be standardized for application to other EU countries. In practice, machine learning techniques are used to identify solar panels in satellite and aerial images for the province of Limburg (NL), Flanders (BE) and North Rhine-Westphalia (DE).Comment: This document provides the reader with an overview of the various datasets which will be used throughout the project. The collection of satellite and aerial images as well as auxiliary information such as the location of buildings and roofs which is required to train, test and validate the machine learning algorithm that is being develope

Internet basierte Ausbildungssupervision

Ausbildungssupervision ist ein wertvoller Bestandteil der Praxisbegleitung in Studiengängen der Sozialen Arbeit und darüber hinaus. Befinden sich Supervisand und Supervisor räumlich weit voneinander entfernt, ist das Internet meist die einzige Möglichkeit, die supervisorische Begleitung sicher zu stellen. Der Autor zeigt Wege auf, wie dies mit Hilfe von E-Mail und Internettelefonie gelingen kann, evaluiert die Verfahren und gewinnt so wertvolle Erkenntnisse für die Weiterentwicklung Internet basierter Supervision. (DIPF/Orig.

Dosage en ligne d'une molécule d'origine naturelle dans le CO2 supercritique à l'aide d'une cellule à haute pression équipée de fibres optiques couplant un spectrophotomère IRTF à un extracteur à fluide supercritique

Peer reviewe

SMALL SAMPLE SIZE CAPABILITY INDEX FOR ASSESSING VALIDITY OF ANALYTICAL METHODS

peer reviewedaudience: researcher, professional, studentAnalytical method’s capability evaluation can be a useful methodology to assess the fitness of purpose of these methods for their future routine application. However, care on how to compute the capability indices has to be made. Indeed, the commonly used formulas to compute capability indices such as Cpk, will highly overestimate the true capability of the methods. Especially during methods validation or transfer, there are only few experiments performed and, using in these situations the commonly applied capability indices to declare a method as valid or as transferable to a receiving laboratory will conduct to inadequate decisions. In this work, an improved capability index, namely Cpk-tol and the corresponding estimator of proportion of non conforming results (tolCpk−π) is proposed. Through Monte-Carlo simulations, they have been shown to greatly increase the estimation of analytical methods capability in particular in low sample size situations as encountered during methods validation or transfer. Additionally, the usefulness of this capability index is illustrated through several case studies

Determination of fenofibrate, ciprofibrate and bezafibrate in mixtures by FTIR spectroscopy

Peer reviewe

A novel TOF-PET MRI detector for diagnosis and follow up of the prostate cancer

Prostate cancer is the most common disease in men and the second leading cause of death from cancer. Generic large imaging instruments used in cancer diagnosis have sensitivity, spatial resolution, and contrast inadequate for the task of imaging details of a small organ such as the prostate. In addition, multimodality imaging can play a significant role merging anatomical and functional details coming from simultaneous PET and MRI. Indeed, multi-parametric PET/MRI was demonstrated to improve diagnosis, but it suffers from too many false positives. In order to address the above limits of the current techniques, we have proposed, built and tested, thanks to the TOPEM project funded by Italian National Institute of Nuclear Phisics a prototype of an endorectal PET-TOF/MRI probe. In the applied magnification PET geometry, performance is dominated by a high-resolution detector placed closer to the source. The expected spatial resolution in the selected geometry is about 1.5 mm FWHM and efficiency a factor of 2 with respect to what obtained with the conventional PET scanner. In our experimental studies, we have obtained timing resolution of ~ 320 ps FWHM and at the same time Depth of Interaction (DOI) resolution of under 1 mm. Tests also showed that mutual adverse PET-MR effects are minimal. In addition, the matching endorectal RF coil was designed, built and tested. In the next planned studies, we expect that benefiting from the further progress in scintillator crystal surface treatment, in SiPM technology and associated electronics would allow us to significantly improve TOF resolutio