Search results for "Application"
showing 10 items of 5559 documents
High Performance FOC for Induction Motors with Low Cost ATSAM3X8E Microcontroller
2018
In this paper the Authors present the Arduino Due board application for an induction motor field oriented control (FOC) algorithm. The low cost Arduino Due board is equipped with a ATSAM3X8E microcontroller that performs the algorithm calculation, data processing, current signals and speed/position data acquisition. The control algorithm has been developed with the help of the open source Arduino integrated development environment, whereas a user friendly control interface, used to manage the speed or position set point, has been developed in Java language by means of an other open source software, namely, Processing. An experimental test bed has been set up in order to validate the FOC sys…
Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications
2019
The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed …
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review
2015
Abstract: Forthcoming superspectral satellite missions dedicated to land monitoring, as well as planned imaging spectrometers, will unleash an unprecedented data stream. The processing requirements for such large data streams involve processing techniques enabling the spatio-temporally explicit quantification of vegetation properties. Typically retrieval must be accurate, robust and fast. Hence, there is a strict requirement to identify next-generation bio-geophysical variable retrieval algorithms which can be molded into an operational processing chain. This paper offers a review of state-of-the-art retrieval methods for quantitative terrestrial bio-geophysical variable extraction using op…
Technology-Supported Guidance Models Stimulating the Development of Critical Thinking in Clinical Practice: Protocol for a Mixed Methods Systematic R…
2020
BackgroundCritical thinking is an essential skill that nursing students need to develop. Technological tools have opened new avenues for technology-supported guidance models, but the challenges and facilitators of such guidance models, as well as how they stimulate the development of critical thinking, remain unclear.ObjectiveWe developed a protocol for a mixed methods systematic review to investigate the use of technology-supported guidance models that stimulate the development of critical thinking in nursing education clinical practice.MethodsA convergent integrated design following the Joanna Briggs Institute Manual for Evidence Synthesis will be employed. A pair of authors will select t…
Guiding the modeller: organizing and selecting experimental data for single cell models using the CoCoDat database
2003
Collating, organizing and selecting quantitative experimental data are time-consuming tasks necessary for building and constraining biophysically realistic neuronal models. The CoCoDat (Collation of Cortical Data) database has been designed as an advanced environment for storing, organizing and retrieving detailed, uninterpreted quantitative data on morphology, electrophysiology and connectivity from the published literature according to neurophysiological concepts. All experimental data are linked to exact bibliographical references and detailed records of procedures used in the experiments that produced the data. We demonstrate the usefulness of CoCoDat for implementation of an example mo…
Effectively and efficiently supporting crowd-enabled databases via NoSQL paradigms
2013
In this paper we provide an overview of the Hints From the Crowd (HFC) project, whose main goal is to build a NoSQL database system for large collections of product reviews; the database is queried by expressing a natural language sentence; the result is a list of products ranked based on the relevance of reviews w.r.t. the natural language sentence. The best ranked products in the result list can be seen as the best hints for the user based on crowd opinions (the reviews). The HFC prototype has been developed as a web application, independent of the particular application domain of the collected product reviews. Queries are performed by evaluating a text-based ranking metric for sets of re…
Storm
2003
We present Storm, a storage system which unifies the desktop and the public network, making Web links between desktop documents more practical. Storm assigns each document a permanent unique URI when it is created. Using peer-to-peer technology, we can locate documents even though our URIs do not include location information. Links continue to work unchanged when documents are emailed or published on the network. We have extended KDE to understand Storm URIs. Other systems such as GNU Emacs are able to use Storm through an HTTP gateway.
PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources.
2019
Background Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data. Results In this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTfu…
Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis
2006
Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large number of features of different types. Dimensionality reduction (DR) is one commonly applied approach. The goal of this paper is to study the impact of natural clustering--clustering according to expert domain knowledge--on DR for supervised learning (SL) in the area of antibiotic resistance. We compare several data-mining strategies that apply DR by means of feature extraction or feature selection w…
FABC: Retinal Vessel Segmentation Using AdaBoost
2010
This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…