Search results for "Ensemble"
showing 10 items of 162 documents
Unstable feature relevance in classification tasks
2011
Climate and extreme rainfall events in the Mono river basin (West Africa): investigating future changes with Regional Climate Models.
2020
This study characterizes the future changes in extreme rainfall and air temperature in the Mono river basin where the main economic activity is weather dependent and local populations are highly vulnerable to natural hazards, including flood inundations. Daily precipitation and temperature from observational datasets and Regional Climate Models (RCMs) output from REMO, RegCM, HadRM3, and RCA were used to analyze climatic variations in space and time, and fit a GEV model to investigate the extreme rainfalls and their return periods. The results indicate that the realism of the simulated climate in this domain is mainly controlled by the choice of the RCMs. These RCMs projected a 1 to 1.5 °
Inducing Rules of Ensemble Music Performance : A Machine Learning Approach
2013
Previous research in expressive music performance has described how solo musicians intuitively shape each note in relation to local/global score contexts. However, expression in ensemble performances, where each individual voice is played simultaneously with other voices, has been little explored. We present an exploratory study in which the performance of a string quartet is recorded and analysed by a computer. We use contact microphones to acquire four audio signals from which a set of audio descriptors is extracted individually for each musician. Moreover, we use motion capture to extract bowing descriptors (bow velocity/force) from each of the four performers. The gathered multimodal da…
Experimentelle Untersuchungen zur Reproduzierbarkeit von Ensemble-gemittelten elektromyographischen Ganganalysedaten im Bereich der experimentellen u…
2004
With suitable application and signal processing methods, surface electromyography is a comparatively simple instrument for investigating the temporal pattern of the muscular activity of a walking subject. The influence of changes both in the external experimental conditions (e.g. orthopedic shoe design) and in the human locomotor system (due to disease or therapy) on the individual muscular gait characteristics can be documented in this way. The usefulness of this kind of investigation is basically limited by the reproducibility of the gait analytical findings of the subject, who is examined at different times with unchanged bodily state and under identical experimental conditions unchanged…
An EEMD Aided Comparison of Time Histories and Its Application in Vehicle Safety
2017
In the context of signal processing, the comparison of time histories is required for different purposes, especially for the model validation of vehicle safety. Most of the existing metrics focus on the mathematical value only. Therefore, they suffer the measuring errors, disturbance, and uncertainties and can hardly achieve a stable result with a clear physical interpretation. This paper proposes a novel scheme of time histories comparison to be used in vehicle safety analysis. More specifically, each signal for comparison is decomposed into a trend signal and several intrinsic mode functions (IMFs) by ensemble empirical mode decomposition. The trend signals reflect the general variation a…
The role of polaronic states in the enhancement of CO oxidation by single-atom Pt/CeO2
2023
Single Atom Catalysts (SACs) have shown that the miniaturization of the active site implies new phenomena like dynamic charge transfer between isolated metal atoms and the oxide. To obtain direct proof of this character is challenging, as many experimental techniques provide averaged properties or have limitations with poorly conductive materials, leaving kinetic measurements from catalytic testing as the only reliable reference. Here we present an integrated Density Functional Theory-Microkinetic model including ground and metastable states to address the reactivity of Pt1/CeO2 for CO oxidation. Our results agree with experimentally available kinetic data in the literature and show that CO…
ENSEMBLE METHODS FOR RANKING DATA
2017
The last years have seen a remarkable flowering of works about the use of decision trees for ranking data. As a matter of fact, decision trees are useful and intuitive, but they are very unstable: small perturbations bring big changes. This is the reason why it could be necessary to use more stable procedures, as ensemble methods, in order to find which predictors are able to explain the preference structure. In this work ensemble methods as BAGGING and Random Forest are proposed, from both a theoretical and computational point of view, for deriving classification trees when ranking data are observed. The advantages of these procedures are shown through an example on the SUSHI data set.
Ensemble methods for ranking data with and without position weights
2020
The main goal of this Thesis is to build suitable Ensemble Methods for ranking data with weights assigned to the items’positions, in the cases of rankings with and without ties. The Thesis begins with the definition of a new rank correlation coefficient, able to take into account the importance of items’position. Inspired by the rank correlation coefficient, τ x , proposed by Emond and Mason (2002) for unweighted rankings and the weighted Kemeny distance proposed by García-Lapresta and Pérez-Román (2010), this work proposes τ x w , a new rank correlation coefficient corresponding to the weighted Kemeny distance. The new coefficient is analized analitically and empirically and represents the main…
Dealing with a small amount of data : developing Finnish sentiment analysis
2022
Sentiment analysis has been more and more prominently visible among all natural language processing tasks. Sentiment analysis entails information extraction of opinions, emotions, and sentiments. In this paper, we aim to develop and test language models for low-resource language Finnish. We use the term “low-resource” to describe a language lacking in available resources for language modeling, especially annotated data. We investigate four models: the state-of-the-art FinBERT [1], and competitive alternative BERT models Finnish ConvBERT [2], Finnish Electra [3], and Finnish RoBERTa [4]. Having a comparative framework of multiple BERT variations is connected to our use of additional methods …
Constant inner potential DFT for modelling electrochemical systems under constant potential and bias
2021
Electrochemical interfaces and reactions play a decisive role in e.g. clean energy conversion but understanding their complex chemistry remains an outstanding challenge. Constant potential or grand canonical ensemble (GCE) simulations are indispensable for unraveling the properties of electrochemical processes as a function of the electrode potential. Currently, constant electrode potential calculations at the density functional theory (DFT) level are carried out by fixing the Fermi level of the simulation cell. However, the Fermi level from DFT calculations does does not always reflect the experimentally controlled electrode potential or describe the thermodynamic independent variable in G…