Search results for "e learning"
showing 10 items of 2703 documents
Translating EU text in the English BA programme: exploring teachers' views and practices
2014
Recent research into using translation as a communicative and functional activity in foreign language learning and teaching has pointed out a wide range of benefits for advanced language learners. The research reported in this paper involved teachers teaching translation in the EU-specialisation module integrated into the English bachelor’s degree programme in Hungary. The survey set out to explore teachers’ instructional practices as well as their views and experiences regarding translation. Results indicate that translation in this pedagogical setting is used not merely as a tool to develop language competence and other generic skills, but is regarded as a useful skill in its own right. T…
Deadline-based QoS Algorithms for High-performance Networks
2007
Quality of service (QoS) is becoming an attractive feature for high-performance networks and parallel machines because it could allow a more efficient use of resources. Deadline-based algorithms can provide powerful QoS provision. However, the cost associated with keeping ordered lists of packets makes them impractical for high-performance networks. In this paper, we explore how to adapt efficiently the earliest deadline first family of algorithms to the high-speed networks environments. The results show excellent performance using just two virtual channels, FIFO queues, and a cost feasible with today's technology.
The Early Bird gets the Word
2019
Success in an increasingly globalized world sets requirements for versatile communication skills and understanding about other cultures. One of the keys to success is versatile language skills, on which the European Commission spoke out as early as in 1995, recommending that every European citizen should learn two foreign languages in addition to their mother tongue. Now, more than twenty years later, the launch of early A1 language teaching that is to begin in the first grade in Finland, in January 2020, is a significant step towards this goal. Studies show that early foreign language learning needs to be carefully carried out in order to achieve positive effects and the effects that have …
The Nature Tour Mobile Learning Application. Implementing the Mobile Application in Finnish Early Childhood Education Settings
2014
This paper explores the process and impact of the implementation of the Nature Tour mobile learning application in Finnish early childhood education settings. The interest is to explore whether the concept of Nature Tour mobile application meets the needs of early childhood education in field trips. The idea of the mobile application is to help recording and comparing nature observations as well as to arouse children’s interest in nature. The feasibility of the mobile application was evaluated through a theoretical framework, which includes the core aspects of mobile learning. The evaluation framework consists of two levels titled core level and medium level. Three of the core level aspects…
Early handling effect on female rat spatial and non-spatial learning and memory
2014
This study aims at providing an insight into early handling procedures on learning and memory performance in adult female rats. Early handling procedures were started on post-natal day 2 until 21, and consisted in 15 min, daily separations of the dams from their litters. Assessment of declarative memory was carried out in the novel-object recognition task; spatial learning, reference- and working memory were evaluated in the Morris water maze (MWM). Our results indicate that early handling induced an enhancement in: (1) declarative memory, in the object recognition task, both at 1h and 24h intervals; (2) reference memory in the probe test and working memory and behavioral flexibility in the…
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…
Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform
2021
Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…
Advances in Kernel Machines for Image Classification and Biophysical Parameter Retrieval
2017
Remote sensing data analysis is knowing an unprecedented upswing fostered by the activities of the public and private sectors of geospatial and environmental data analysis. Modern imaging sensors offer the necessary spatial and spectral information to tackle a wide range problems through Earth Observation, such as land cover and use updating, urban dynamics, or vegetation and crop monitoring. In the upcoming years even richer information will be available: more sophisticated hyperspectral sensors with high spectral resolution, multispectral sensors with sub-metric spatial detail or drones that can be deployed in very short time lapses. Besides such opportunities, these new and wealthy infor…
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 …
Development of an Earth observation processing chain for crop biophysical parameters at local and global scale
2017
[ES] Reseña de tesis doctoral defendida el 17 de Julio de 2017. Lugar: Facultat de Física, Universitat de València.