Search results for "e learning"
showing 10 items of 2703 documents
Effectiveness of local feature selection in ensemble learning for prediction of antimicrobial resistance
2008
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift (CD), complicates the task of learning a robust model. Different ensemble learning (EL) approaches (that instead of learning a single classifier try to learn and maintain a set of classifiers over time) have been shown to perform reasonably well in the presence of concept drift. In this paper we study how much local feature selection (FS) can improve ensemble performance for da…
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.
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…
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…
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…
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.
An Optimized Design of Choice Experiments: A New Approach for Studying Decision Behavior in Choice Task Experiments
2014
In this paper, we present a new approach for the optimal experimental design problem of generating diagnostic choice tasks, where the respondent's decision strategy can be unambiguously deduced from the observed choice. In this new approach, we applied a genetic algorithm that creates a one-to-one correspondence between a set of predefined decision strategies and the alternatives of the choice task; it also manipulates the characteristics of the choice tasks. In addition, this new approach takes into account the measurement errors that can occur when the preferences of the decision makers are being measured. The proposed genetic algorithm is capable of generating diagnostic choice tasks eve…
Incremental linear model trees on massive datasets
2013
The existence of massive datasets raises the need for algorithms that make efficient use of resources like memory and computation time. Besides well-known approaches such as sampling, online algorithms are being recognized as good alternatives, as they often process datasets faster using much less memory. The important class of algorithms learning linear model trees online (incremental linear model trees or ILMTs in the following) offers interesting options for regression tasks in this sense. However, surprisingly little is known about their performance, as there exists no large-scale evaluation on massive stationary datasets under equal conditions. Therefore, this paper shows their applica…
Educating reflective Enterprise Systems practitioners: a design research study of the iterative building of a teaching framework
2013
This research paper reports on the iterative design of a teaching framework developed for teaching Enterprise Systems ES classes for Information Systems IS graduates. These systems embed technical complexity and create organizational challenges when implemented in organizations. Therefore, teaching good ES classes is pedagogically challenging for faculty, and ES curricula are difficult for students. We have gradually designed and rebuilt curricula and teaching frameworks over 8years. This has also resulted in a set of eight design principles. We report from our design and evaluation process and present our final artefact, the teaching framework. The aim is to educate reflective practitioner…
Romanian Folk Literature in Our Classes: A Proposal for the Development of Intercultural Competence
2015
Abstract The present research highlights the ways in which folk literature, this valuable tool that contributes to students’ formation from both a human and literary perspective, can promote intercultural competence in class and foster a better integration within the community, while consolidating favorable attitudes towards interculturality. We share Rodriguez Almodovar's view (2009), according to which the folk story makes the geographic space expand; it channels affectivity, while guiding the learning process towards the acceptance of social values that are representative for each culture. The objectives of our study are focused, on the one hand, on improving intercultural competence amo…