Search results for " Computer Science"

showing 10 items of 3983 documents

Computational thinking in programming with Scratch in primary schools: A systematic review

2020

Computer programming is being introduced in educational curricula, even at the primary school level. One goal of this implementation is to teach computational thinking (CT), which is potentially applicable in various computational problem-solving situations. However, the educational objective of CT in primary schools is somewhat unclear: curricula in various countries define learning objectives for topics, such as computer science, computing, programming or digital literacy but not for CT specifically. Additionally, there has been confusion in concretely and comprehensively defining and operationalising what to teach, learn and assess about CT in primary education even with popular programm…

Primary (chemistry)General Computer ScienceComputer sciencelaskennallinen ajatteluassessmentComputational thinkingGeneral EngineeringajatteluScratchmatemaattinen ajatteluprogrammingohjelmointikieletprimary schoolEducationperusopetuscomputational thinkingScratchComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationohjelmointicomputercomputer.programming_languageComputer Applications in Engineering Education
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3D chain interactive

2014

With constant evolution of technology, 3D scanners are providing more and more data with ever greater precision. However, the substantial increase of the data size is problematic. Files become very heavy and can cause problems in data transmission or data storage. Therefore, most of the time, the data obtained by the 3d scanners will be analyzed, processed and simplify; this is called 3D acquisition chain.This manuscript presents an approach which digitize objects dynamically by adapting point density during the acquisition depending on the object complexity, without informations on object shape. This system allows to avoid the use of the classic 3D chain. This system do not calculate a den…

Primitives extractionExtraction de primitives[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Acquisition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]3D chainChaine 3D[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSimplification[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Pelagic species identification by using a PNN neural network and echo-sounder data

2017

For several years, a group of CNR researchers conducted acoustic surveys in the Sicily Channel to estimate the biomass of small pelagic species, their geographical distribution and their variations over time. The instrument used to carry out these surveys is the scientific echo-sounder, set for different frequencies. The processing of the back scattered signals in the volume of water under investigation determines the abundance of the species. These data are then correlated with the biological data of experimental catches, to attribute the composition of the various fish schools investigated. Of course, the recognition of the fish schools helps to produce very good results, that is very clo…

Probabilistic neural networkComputer Science (all)ClassificationPelagic species identificationTheoretical Computer Science
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Coherence Checking and Propagation of Lower Probability Bounds

2003

In this paper we use imprecise probabilities, based on a concept of generalized coherence (g-coherence), for the management of uncertain knowledge and vague information. We face the problem of reducing the computational difficulties in g-coherence checking and propagation of lower conditional probability bounds. We examine a procedure, based on linear systems with a reduced number of unknowns, for the checking of g-coherence. We propose an iterative algorithm to determine the reduced linear systems. Based on the same ideas, we give an algorithm for the propagation of lower probability bounds. We also give some theoretical results that allow, by suitably modifying our algorithms, the g-coher…

Probability boxMathematical optimizationSettore MAT/06 - Probabilita' E Statistica MatematicaPosterior probabilitynon relevant gainLaw of total probabilityConditional probabilitybasic setsbasic sets; basic sets.; g-coherence checking; lower conditional probability bounds; non relevant gains; propagationCoherence (statistics)Conditional probability distributiong-coherence checking; lower conditional probability bounds; non relevant gainsImprecise probabilityTheoretical Computer Sciencelower conditional probability boundRegular conditional probabilitynon relevant gainspropagationlower conditional probability boundsGeometry and Topologyg-coherence checkingSoftwareMathematics
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Structural Knowledge Extraction from Mobility Data

2016

Knowledge extraction has traditionally represented one of the most interesting challenges in AI; in recent years, however, the availability of large collections of data has increased the awareness that “measuring” does not seamlessly translate into “understanding”, and that more data does not entail more knowledge. We propose here a formulation of knowledge extraction in terms of Grammatical Inference (GI), an inductive process able to select the best grammar consistent with the samples. The aim is to let models emerge from data themselves, while inference is turned into a search problem in the space of consistent grammars, induced by samples, given proper generalization operators. We will …

Process (engineering)Computer scienceGeneralizationmedia_common.quotation_subjectInference02 engineering and technologyMachine learningcomputer.software_genreTheoretical Computer ScienceGrammatical inferenceKnowledge extractionRule-based machine translation020204 information systems0202 electrical engineering electronic engineering information engineeringSearch problemmedia_commonStructural knowledgeGrammarbusiness.industryMobility dataComputer Science (all)020207 software engineeringGrammar inductionArtificial intelligencebusinesscomputerNatural language processing
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A Approach to Clinical Proteomics Data Quality Control and Import

2011

International audience; Biomedical domain and proteomics in particular are faced with an increasing volume of data. The heterogeneity of data sources implies heterogeneity in the representation and in the content of data. Data may also be incorrect, implicate errors and can compromise the analysis of experiments results. Our approach aims to ensure the initial quality of data during import into an information system dedicated to proteomics. It is based on the joint use of models, which represent the system sources, and ontologies, which are use as mediators between them. The controls, we propose, ensure the validity of values, semantics and data consistency during import process.

Process (engineering)Computer sciencemedia_common.quotation_subject02 engineering and technologyOntology (information science)Proteomicscomputer.software_genreDomain (software engineering)03 medical and health sciences020204 information systems[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM]0202 electrical engineering electronic engineering information engineeringInformation systemQuality (business)[ SDV.BIBS ] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]030304 developmental biologymedia_common0303 health sciences[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]Data science[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Data qualityData mining[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]computer
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Academic and Administrative Tandems in European Projects

2017

International audience; Building and maintaining the sustainability of European projects requires advanced communication and team investment, shared working methods, common decisions and symbiosis in key items such as selection requirement and process, terms of mobility between consortium members or teaching content. It requires jointness in various perspectives, aspects and scales, with their own conditions and challenges. This abstract describes this prerequisite of jointness through the local campus of Le Creusot (University of Burgundy) for our International Programme in Computer Vision and Robotics (VIBOT). The main challenge can be summarized in one single question: How to maintain an…

Process (engineering)joint programme[SPI.AUTO]Engineering Sciences [physics]/Automatic[ SPI.AUTO ] Engineering Sciences [physics]/AutomaticPolitical science0502 economics and business[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]employabilityErasmus MundusErasmus+Sustainable developmentfunding[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]05 social sciences050301 educationsustainabilityJointnessInvestment (macroeconomics)European programmeEngineering management[SPI.AUTO] Engineering Sciences [physics]/Automaticadministrative workVIBOTSustainability0503 educationErasmus+050203 business & management2017 27th EAEEIE Annual Conference (EAEEIE)
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MAVIE-Lab Sports: a mHealth for Injury Prevention and Risk Management in Sport

2018

International audience; Smart-phones technology and the development of mHealth (Mobile Health) applications offer an opportunity to design intervention tools to influence health behavior changes. The MAVIE-Lab is a mHealth application including a DSS (Desicion Support System) to assist in the personalized evaluation of HLIs (Home, Leisure and Sport Injuries) risk and to promote the adoption of prevention measures. MAVIE-Lab Sports will be the first module of the mobile application. The purpose of this PhD project is to improve a particular module of MAVIE-Lab, devoted to sports (MAVIE-Lab Sports), in different aspects: statistical modeling, design and ergonomics. It also aims to evaluate sy…

Process managementComputer scienceInjury030501 epidemiologyMathematics of computing[STAT.CO] Statistics [stat]/Computation [stat.CO][ INFO.INFO-LG ] Computer Science [cs]/Machine Learning [cs.LG]Bayesian networks BN03 medical and health sciences[STAT.ML]Statistics [stat]/Machine Learning [stat.ML][INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][STAT.AP] Statistics [stat]/Applications [stat.AP]Personal digital assistantsInjury preventioneHealthInjury Epidemiology[STAT.CO]Statistics [stat]/Computation [stat.CO]mHealthRisk managementComputingMilieux_MISCELLANEOUS[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML][ STAT.CO ] Statistics [stat]/Computation [stat.CO][STAT.AP]Statistics [stat]/Applications [stat.AP]030505 public healthHome and leisure injuries[STAT.ME] Statistics [stat]/Methodology [stat.ME]business.industryHLIs[ STAT.AP ] Statistics [stat]/Applications [stat.AP]Human factors and ergonomicsUsability[ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG]Human-centered computing[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]Intervention (law)Bayesian networks[ STAT.ME ] Statistics [stat]/Methodology [stat.ME][SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologieHuman-centered computing[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologieeHealth0305 other medical sciencebusinessAppPrediction[STAT.ME]Statistics [stat]/Methodology [stat.ME]
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A Pilot Study on Offensive Success in Soccer Based on Space and Ball Control – Key Performance Indicators and Key to Understand Game Dynamics

2017

Abstract The intention of Key Performance Indicators (KPI) is to map complex system-behaviour to single values for scaling, rating and ranking systems or system components. Very often, however, this mapping only reduces important information about tactical behaviour or playing dynamics without replacing it by useful ones. The presented approach tries to bridge the gap between complex dynamics and numerical indicators in the case of offensive effectiveness in soccer in two steps. First, a model is developed which visualises offensive actions in a process-oriented way by using information units to represent offensive performance – i.e. Key Performance Indicators. Second, this model is organis…

Process managementGame dynamicsGeneral Computer ScienceComputer scienceBiomedical EngineeringOffensive030229 sport sciencesPhysical education03 medical and health sciences0302 clinical medicineBall (bearing)Performance indicator030217 neurology & neurosurgerySimulationInternational Journal of Computer Science in Sport
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Diary as dialogue in papermill process control

2000

Process managementGeneral Computer ScienceComputer scienceProcess controlCommunications of the ACM
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