Search results for "learning."

showing 10 items of 6527 documents

Drug Activity Characterization Using One-Class Support Vector Machines with Counterexamples

2013

The problem of detecting chemical activity in drugs from its molecular description constitutes a challenging and hard learning task. The corresponding prediction problem can be tackled either as a binary classification problem (active versus inactive compounds) or as a one class problem. The first option leads usually to better prediction results when measured over small and fixed databases while the second could potentially lead to a much better characterization of the active class which could be more important in more realistic settings. In this paper, a comparison of these two options is presented when support vector models are used as predictors.

Chemical activitybusiness.industryCharacterization (mathematics)Machine learningcomputer.software_genreClass (biology)Task (project management)Support vector machineDrug activityBinary classificationArtificial intelligencebusinesscomputerMathematicsCounterexample
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Microstructure–property relation and machine learning prediction of hole expansion capacity of high-strength steels

2021

Abstract The relationship between microstructure features and mechanical properties plays an important role in the design of materials and improvement of properties. Hole expansion capacity plays a fundamental role in defining the formability of metal sheets. Due to the complexity of the experimental procedure of testing hole expansion capacity, where many influencing factors contribute to the resulting values, the relationship between microstructure features and hole expansion capacity and the complexity of this relation is not yet fully understood. In the present study, an experimental dataset containing the phase constituents of 55 microstructures as well as corresponding properties, su…

Chemical contentMaterials scienceRelation (database)business.industryProperty (programming)Mechanical EngineeringMachine learningcomputer.software_genreMicrostructuremicrostructure constituents hole expansion capacity statistical analysis machine learningMechanics of MaterialsPhase (matter)Solid mechanicsFormabilityGeneral Materials ScienceStatistical analysisArtificial intelligencebusinesscomputerJournal of Materials Science
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The Uniqueness of Teaching and Learning Chemistry

2009

Unfortunately, the current perception of Chemistry held by many students and the general public alike appears to be in stark contrast to its true nature. Although chemistry is ubiquitous in all aspects of our daily lives it continues to be perceived as highly theoretical and of little relevance. A clearer understanding of the fundamental Nature of Chemistry will be needed if students are to recognize its true importance and character. It is not possible to fully understand, and as a consequence accept on an intuitive basis, the 'mystery' and fascinations arising from the transformation of matter, without first adopting a convincing sub-microscopic view, able to connect observed macroscopic …

Chemistry LearningECTNCHEMISTRYMICROSCOPIC APPROACHEDUCATIONHigher EducationSettore CHIM/02 - Chimica Fisica
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Mapping the Teaching of History of Chemistry in Europe

2016

Recent developments in the field of history of chemistry have introduced new topics, challenges, and connections to a broad range of scientific, political, cultural, economic, and environmental issues. New audiences for the history of chemistry have emerged along with new topics, protagonists, spaces, and historical narratives. This paper summarizes the main results of a recent survey to map the current situation of the teaching of history of chemistry in Europe. We review how and where history of chemistry is taught in Europe, considering not only graduate students in science programs, but also other audiences such as science teachers, and the general public. This paper also provides updat…

Chemistry education010405 organic chemistryConcept map05 social sciences050301 educationGeneral ChemistryHistory of ideas01 natural sciences0104 chemical sciencesEducationPoliticsConstructivism (philosophy of education)Learning theoryEngineering ethicsNarrativeChemistry (relationship)0503 educationJournal of Chemical Education
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Modeller i kjemiundervisning - et eksempel på hvordan de kan bidra til læring og feillæring

2021

We discuss the use of analogical models in science education using examples from online learning resources.  We have conducted a teaching program for a group of 7th grade pupils and a group of science teacher students, and the main theme of this program is the use of models in chemistry. Specifically, we study the effect of an analogical model that is designed to promote understanding of the properties of molecules, related to a paper chromatography experiment. Our research indicates that analogical models can be a useful tool to convey understanding of abstract concepts and non-visible phenomena, but they hold serious pitfalls that can lead to misunderstandings amongst students if not used…

Chemistry educationAnalogical modelsOnline learningmedia_common.quotation_subjectMODELLERScience educationEducationComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationConversationChemistry (relationship)Psychologymedia_commonTheme (narrative)Nordic Studies in Science Education
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Testing <em>Drosophila</em> Olfaction with a Y-maze Assay

2014

Detecting signals from the environment is essential for animals to ensure their survival. To this aim, they use environmental cues such as vision, mechanoreception, hearing, and chemoperception through taste, via direct contact or through olfaction, which represents the response to a volatile molecule acting at longer range. Volatile chemical molecules are very important signals for most animals in the detection of danger, a source of food, or to communicate between individuals. Drosophila melanogaster is one of the most common biological models for scientists to explore the cellular and molecular basis of olfaction. In order to highlight olfactory abilities of this small insect, we describ…

ChemoperceptionGeneral Immunology and MicrobiologybiologyGeneral Chemical EngineeringGeneral NeuroscienceMaze learningOlfactionDrosophila melanogasterbiology.organism_classificationDrosophilaSensory cueNeuroscienceGeneral Biochemistry Genetics and Molecular BiologyJournal of Visualized Experiments
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Using Chinese in China - challenges and opportunities : a case study of three Finnish sojourners

2016

Despite the growing attention on interaction between language learners/sojourners and host community, there has been little research on second language (L2) using experience by adopting case study approach, by which each individual’s voice is valued. Grounded in sociocultural theory (SCT), the present study explores challenges and opportunities of international sojourners when they use Chinese in China by investigating three Finnish sojourners’ experiences in using Chinese. Coleman’s concentric circles model is adopted to illustrate sojourners’ different language choices and reasons with compatriots, international people and host community. Narratives and interview data are analyzed and dis…

Chinese L2 learningsociocultural theoryKiinaagencyopiskelukulttuurierotChinese L2 useresidence abroadTapaustutkimuskiinan kielityö
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Project-based learning in the Chinese heritage language course/class in Finnish comprehensive education

2023

With the trend of global mobility and immigration, the Finnish government has been promoting integration and multiculturality since 1990. According to the Finnish National Agency for Education (FNAE), Heritage Language (oma äidinkieli) lessons aim to protect and develop immigrant students’ competencies in their heritage languages and cultures. This article shares a pilot 4-week PBL (Project-based Learning) module for a group of advanced Chinese language learners. It discusses the opportunities and challenges during the PBL and suggests possible improvements. nonPeerReviewed

Chinese as a heritage languagekieltenopetusheritage language teachingprojektioppiminenproject-based learning (PBL)Finland Suomi Chineseäidinkielikiinan kieli
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Chlorophyll Concentration Retrieval by Training Convolutional Neural Network for Stochastic Model of Leaf Optical Properties (SLOP) Inversion

2020

Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation health. The objective of this study was to develop a novel approach for retrieving chlorophyll a and b values from remotely sensed data by inverting the stochastic model of leaf optical properties using a one-dimensional convolutional neural network. The inversion results and retrieved values are validated in two ways: A classical machine learning val…

Chlorophyll boptical propertiesChlorophyll aklorofylli010504 meteorology & atmospheric sciencesCorrelation coefficientStochastic modelling0211 other engineering and technologiesconvolutional neural network02 engineering and technologyneuroverkotoptiset ominaisuudet01 natural sciencesConvolutional neural networkchemistry.chemical_compoundchlorophylllcsh:Scienceoptical properties; convolutional neural network; deep learning; chlorophyll; stochastic modeling; physical parameter retrieval; forestry021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingstokastiset prosessitbusiness.industryDeep learningspektrikuvausforestryHyperspectral imagingdeep learningmetsänarviointikoneoppiminenchemistryChlorophyllGeneral Earth and Planetary Scienceslcsh:QArtificial intelligencekaukokartoitusmetsänhoitobusinessphysical parameter retrievalstochastic modelingRemote Sensing; Volume 12; Issue 2; Pages: 283
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A computer program suitable for analysis of choice of categories in biomedical data recognition problems.

1980

The optimum choice of categories in problems of medical data recognition is governed by the choice of categories, the selection of appropriate features, and by the choice of a loss function. Under these circumstances it is often difficult to find out the suitable classification scheme. The computer program described here serves for the design of the optimum recognition procedure. The Bayes rule is used as decision rule. A criterion for the comparison of different choice of categories is given. The program can be performed after estimation of the underlying prior probabilities and the conditional densities obtained from a training set, and before testing the decision rule with real data.

Choice setComputer programComputer sciencebusiness.industryComputersDecision theoryMedicine (miscellaneous)Decision ruleFunction (mathematics)Machine learningcomputer.software_genreClassificationBayes' theoremDecision TheoryBiomedical dataResearch DesignData miningArtificial intelligencebusinesscomputerSelection (genetic algorithm)Computer programs in biomedicine
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