Search results for "programming."

showing 10 items of 3035 documents

Electronic Mail as a Forum for Argumentative Interaction in Higher Education Studies

1998

This article reports a study in which thirty-one undergraduate students practiced academic argumentation by electronic mail (e-mail). In the two “tutorled” e-mail study groups the discussion topics were selected by the tutor, while in the two self-directed “student-led” groups selection was by the students. The quantity and quality of student-student interaction, and the factors associated with this were investigated. The results indicated that 42 percent of the students' messages (n = 441) were interactive in nature, indicating at least one reference to fellow students' messages. When difficult contents were addressed, interaction in the tutor-led groups was more common than in the studen…

ArgumentativeHigher educationComputer sciencebusiness.industrymedia_common.quotation_subjectTeaching methodElectronic mailComputer Science ApplicationsEducationArgumentation theoryPedagogyMathematics educationQuality (business)Computer-mediated communicationTUTORbusinesscomputermedia_commoncomputer.programming_languageJournal of Educational Computing Research
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Argumentation Course by Electronic Mail

1997

Abstract This article examines the question of whether electronic‐mail (e‐mail) discussions provide university students with an appropriate and profitable environment for practising argumentation and critical thinking skills. An experiment in which 31 undergraduate students and two tutors engaged in argumentative e‐mail discussions is described. The discussions were related to two set books on the sociology of education. The participants’ perceptions of the discussions and of e‐mail as a study method were evaluated by means of a student questionnaire and tutor interviews. Most of the students found that the discussions included a lot of constructive critique, mutual encouragement and constr…

ArgumentativeHigher educationbusiness.industryTeaching methodEducational technologyElectronic mailEducationArgumentation theoryPedagogyComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationbusinessPsychologyTUTORSociology of Educationcomputercomputer.programming_languageScandinavian Journal of Educational Research
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Temperature dependence of the rate constant of hydrogen isotope interactions with a lithium capillary-porous system under reactor irradiation

2013

Abstract Experiments with a sample of a lithium capillary-porous system (CPS) were performed at the reactor IVG-1.M of the Institute of Atomic Energy NNC RK to study the effects of neutron irradiation on the parameters of hydrogen isotope interactions with a lithium CPS. The absorption technique was used during the experiments, and this technique allowed the temperature dependences of the hydrogen isotope interaction rate constants with the lithium CPS to be obtained under various reactor powers. The obtained dependencies were used to determine the main interaction parameters: the activation energies and the pre-exponents of the Arrhenius dependence of the hydrogen interaction rate constant…

Arrhenius equationMaterials scienceHydrogenCapillary actionMechanical EngineeringDivertortechnology industry and agricultureAnalytical chemistrychemistry.chemical_elementcomplex mixturessymbols.namesakeReaction rate constantNuclear Energy and EngineeringchemistrysymbolsAstrophysics::Solar and Stellar AstrophysicsComputer Science::Programming LanguagesGeneral Materials ScienceLithiumPhysics::Atomic PhysicsIrradiationAbsorption (chemistry)Civil and Structural EngineeringFusion Engineering and Design
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Robust adaptive neural backstepping control for a class of nonlinear systems with dynamic uncertainties

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/658671 Open Access This paper is concerned with adaptive neural control of nonlinear strict-feedback systems with nonlinear uncertainties, unmodeled dynamics, and dynamic disturbances. To overcome the difficulty from the unmodeled dynamics, a dynamic signal is introduced. Radical basis function (RBF) neural networks are employed to model the packaged unknown nonlinearities, and then an adaptive neural control approach is developed by using backstepping technique. The proposed controller guarantees semiglobal boundedness of all the signals in the…

Article SubjectArtificial neural networklcsh:MathematicsApplied MathematicsSIGNAL (programming language)Basis functionAnalysis; Applied Mathematicslcsh:QA1-939Class (biology)VDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Nonlinear systemControl theoryBacksteppingNeural controlAnalysisMathematics
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Multilanguage Semantic Interoperability in Distributed Applications

2013

JOSI is a software framework that tries to simplify the development of such kinds of applications both by providing the possibility of working on models for representing such semantic information and by offering some implementations of such models that can be easily used by software developers without any knowledge about semantic models and languages. This software library allows the representation of domain models through Java interfaces and annotations and then to use such a representation for automatically generating an implementation of domain models in different programming languages (currently Java and C++). Moreover, JOSI supports the interoperability with other applications both by …

Article SubjectJavaProgramming languageComputer sciencebusiness.industryMechanical EngineeringGeneral Chemical EngineeringRepresentation (arts)Domain modelSemantic interoperabilitycomputer.software_genreIndustrial and Manufacturing EngineeringSoftware frameworkSoftwareHardware and Architecturelcsh:TA1-2040Domain analysisElectrical and Electronic Engineeringbusinesslcsh:Engineering (General). Civil engineering (General)computerImplementationCivil and Structural Engineeringcomputer.programming_languageJournal of Engineering
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Artificial intelligence techniques for cancer treatment planning

1988

An artificial intelligence system, NEWCHEM, for the development of new oncology therapies is described. This system takes into account the most recent advances in molecular and cellular biology and in cell-drug interaction, and aims to guide experimentation in the design of new optimal protocols. Further work is being carried out, aimed to embody in the system all the basic knowledge of biology, physiopathology and pharmacology, to reason qualitatively from first principles so as to be able to suggest cancer therapies.

Artificial Intelligence SystemKnowledge representation and reasoningbusiness.industryAnimals Antineoplastic Combined Chemotherapy Protocols; administration /&/ dosage/pharmacology Clinical Protocols Computer Simulation Drug Therapy; Computer-Assisted Expert Systems Humans Medical Oncology; methods Programming Languages Software Design Therapy; Computer-AssistedExpert SystemsMedical OncologyDrug Therapy Computer-AssistedmethodsCancer treatmentComputer-AssistedBasic knowledgeadministration /&/ dosage/pharmacologyClinical ProtocolsDrug TherapySoftware DesignTherapy Computer-AssistedAntineoplastic Combined Chemotherapy ProtocolsAnimalsHumansComputer SimulationProgramming LanguagesTherapyArtificial intelligenceAutomated reasoningbusinessMedical Informatics
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Exploring the use of multi-gene genetic programming in regional models for the simulation of monthly river runoff series

2023

The use of new data-driven approaches based on the so-called expert systems to simulate runoff generation processes is a promising frontier that may allow for overcoming some modeling difficulties related to more complex traditional approaches. The present study highlights the potential of expert systems in creating regional hydrological models, for which they can benefit from the availability of large database. Different soft computing models for the reconstruction of the monthly natural runoff in river basins are explored, focusing on a new class of heuristic models, which is the Multi-Gene Genetic Programming (MGGP). The region under study is Sicily (Italy), where a regression based rain…

Artificial Neural NetworkSoft computingEnvironmental EngineeringRegional Runoff ModelSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaGenetic ProgrammingEnvironmental ChemistryEvolutionary OptimizationSafety Risk Reliability and QualityGeneral Environmental ScienceWater Science and Technology
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State classification for autonomous gas sample taking using deep convolutional neural networks

2017

Despite recent rapid advances and successful large-scale application of deep Convolutional Neural Networks (CNNs) using image, video, sound, text and time-series data, its adoption within the oil and gas industry in particular have been sparse. In this paper, we initially present an overview of opportunities for deep CNN methods within oil and gas industry, followed by details on a novel development where deep CNN have been used for state classification of autonomous gas sample taking procedure utilizing an industrial robot. The experimental results — using a deep CNN containing six layers — show accuracy levels exceeding 99 %. In addition, the advantages of using parallel computing with GP…

Artificial neural networkComputer sciencebusiness.industryProperty (programming)Feature extraction0102 computer and information sciences02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesConvolutional neural networklaw.inventionImage (mathematics)Industrial robot020401 chemical engineeringComputer engineering010201 computation theory & mathematicslawProbability distributionArtificial intelligenceState (computer science)0204 chemical engineeringbusinesscomputer2017 25th Mediterranean Conference on Control and Automation (MED)
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Why Cortices ? Neural Computation in the Vertebrate Visual System

1989

We propose three high level structural principles of neural networks in the vertebrate visual cortex and discuss some of their computational implications for early vision: a) Lamination, average axonal and dendritic domains, and intrinsic feedback determine the spatio-temporal interactions in cortical processing. Possible applications of the resulting filters include continuous motion perception and the direct measurement of high-level parameters of image flow, b) Retinotopic mapping is an emergent property of massively parallel connections. With a local intrinsic operation in the target area, mapping combines to a space-variant image processing system as would be useful in the analysis of …

Artificial neural networkComputer sciencebusiness.industryProperty (programming)Optical flowPattern recognitionImage processingVisual cortexmedicine.anatomical_structureModels of neural computationmedicineMotion perceptionArtificial intelligencebusinessMassively parallel
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Educational Software Based on Matlab GUIs for Neural Networks Courses

2016

Neural Networks (NN) are one of the most used machine learning techniques in different areas of knowledge. This has led to the emergence of a large number of courses of Neural Networks around the world and in areas where the users of this technique do not have a lot of programming skills. Current software that implements these elements, such as Matlab®, has a number of important limitations in teaching field. In some cases, the implementation of a MLP requires a thorough knowledge of the software and of the instructions that train and validate these systems. In other cases, the architecture of the model is fixed and they do not allow an automatic sweep of the parameters that determine the a…

Artificial neural networkComputer sciencebusiness.industrycomputer.software_genreMATLABSoftware engineeringbusinesscomputerEducational softwarecomputer.programming_language
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