Search results for "kr"
showing 10 items of 7011 documents
Is privatization of education beneficial for Morocco? : evaluation of Morocco's privatization policy on the basis of a cross-sectional study of quali…
2016
The aim of this thesis was to evaluate Morocco’s privatization policy based on the opinions of final-year high-school students (n = 103) that were studying in either public or private schools. This was examined using a cross-sectional study design in which a structured, Likert scale questionnaire was administered at a night school in Casablanca, Morocco, where highschool students can take extra classes in preparation for their final year exam. The results were analyzed quantitatively by comparing the group means with an independent samples ttest, using an alpha level of 0.05. The results of the study indicated that socioeconomic status was significantly higher for students studying in priva…
"Barnehagen er ingen søndagsskole ..." Religion i barnehager med forskjellige livssynsvedtekter
2021
How do a sample of headteachers and pedagogical leaders understand the parts of the learning area ‘ethics, religion and philosophy’ (ERF) related to religion and religious heritage and tradition in early childhood education? And how do they implement them in practice? We have interviewed employees from 19 kindergartens in Agder and Oslo, and analyzed relevant pedagogical documents, to get answers. The informants came from both public kindergartens and private kindergartens with special objectives. In the private kindergartens, most informants expressed that religion and religious heritage and tradition were integrated in the pedagogical day to day work, with use of a large degree of a didac…
A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data
2021
The current exponential increase of spatiotemporally explicit data streams from satellite-based Earth observation missions offers promising opportunities for global vegetation monitoring. Intelligent sampling through active learning (AL) heuristics provides a pathway for fast inference of essential vegetation variables by means of hybrid retrieval approaches, i.e., machine learning regression algorithms trained by radiative transfer model (RTM) simulations. In this study we summarize AL theory and perform a brief systematic literature survey about AL heuristics used in the context of Earth observation regression problems over terrestrial targets. Across all relevant studies it appeared that…
Statistical biophysical parameter retrieval and emulation with Gaussian processes
2019
Abstract Earth observation from satellites poses challenging problems where machine learning is being widely adopted as a key player. Perhaps the most challenging scenario that we are facing nowadays is to provide accurate estimates of particular variables of interest characterizing the Earth's surface. This chapter introduces some recent advances in statistical bio-geophysical parameter retrieval from satellite data. In particular, we will focus on Gaussian process regression (GPR) that has excelled in parameter estimation as well as in modeling complex radiative transfer processes. GPR is based on solid Bayesian statistics and generally yields efficient and accurate parameter estimates, a…
Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine
2021
For the last decade, Gaussian process regression (GPR) proved to be a competitive machine learning regression algorithm for Earth observation applications, with attractive unique properties such as band relevance ranking and uncertainty estimates. More recently, GPR also proved to be a proficient time series processor to fill up gaps in optical imagery, typically due to cloud cover. This makes GPR perfectly suited for large-scale spatiotemporal processing of satellite imageries into cloud-free products of biophysical variables. With the advent of the Google Earth Engine (GEE) cloud platform, new opportunities emerged to process local-to-planetary scale satellite data using advanced machine …
Testing Multi-Sensors Time Series of Lai Estimates to Monitor Rice Phenology: Preliminary Results
2018
Timely and accurate information on crop growth and seasonal dynamics are increasingly needed to develop monitoring systems aimed to detect seasonal anomalies, support site specific management and estimate crop yield at the end of the season. In particular, frequent decametric information nowadays being provided exploiting the new generation of Earth Observation (EO) platforms are fundamental for farm level monitoring. This study presents an analysis aimed at fully exploiting dense time series of EO data derived from the combined use of ESA Sentinel-2A and NASA Landsat-7/8 imageries for crop phenological monitoring. Decametric Leaf Area Index (LAI) maps were generated for the year 2016 by in…
Slow Infection due to Lowering the Amount of Intact versus Empty Particles Is a Characteristic Feature of Coxsackievirus B5 Dictated by the Structura…
2019
Enterovirus B species typically cause a rapid cytolytic infection leading to efficient release of progeny viruses. However, they are also capable of persistent infections in tissues, which are suggested to contribute to severe chronic states such as myocardial inflammation and type 1 diabetes. In order to understand the factors contributing to differential infection strategies, we constructed a chimera by combining the capsid proteins from fast-cytolysis-causing echovirus 1 (EV1) with nonstructural proteins from coxsackievirus B5 (CVB5), which shows persistent infection in RD cells. The results showed that the chimera behaved similarly to parental EV1, leading to efficient cytolysis in both…
A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins
2018
Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The Europea…
Evolutionary trends in arvicolids and the endemic murid Mikrotia - New data and a critical overview
2014
Abstract The study of evolutionary rates dates back to the work of Simpson and Haldane in the 1940s. Small mammals, especially Plio-Pleistocene arvicolids (voles and lemmings), are particularly suited for such studies because they have an unusually complete fossil record and exhibit significant evolutionary change through time. In recent decades, arvicolids have been the focus of intensive research devoted to the tempo and mode of evolutionary change and the identification of trends in dental evolution that can be used to correlate and date fossil sites. These studies have raised interesting questions about whether voles and lemmings had unique evolutionary trajectories, or show convergent …