149 resultados para Feature Classification
Resumo:
This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.
Resumo:
Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.
Resumo:
We investigated the roles of top-down task set and bottom-up stimulus salience for feature-specific attentional capture. Spatially nonpredictive cues preceded search arrays that included a color-defined target. For target-color singleton cues, behavioral spatial cueing effects were accompanied by cueinduced N2pc components, indicative of attentional capture. These effects were only minimally attenuated for nonsingleton target-color cues, underlining the dominance of top-down task set over salience in attentional capture. Nontarget-color singleton cues triggered no N2pc, but instead an anterior N2 component indicative of top-down inhibition. In Experiment 2, inverted behavioral cueing effects of these cues were accompanied by a delayed N2pc to targets at cued locations, suggesting that perceptually salient but task-irrelevant visual events trigger location-specific inhibition mechanisms that can delay subsequent target selection.
Resumo:
The dynamics of inter-regional communication within the brain during cognitive processing – referred to as functional connectivity – are investigated as a control feature for a brain computer interface. EMDPL is used to map phase synchronization levels between all channel pair combinations in the EEG. This results in complex networks of channel connectivity at all time–frequency locations. The mean clustering coefficient is then used as a descriptive feature encapsulating information about inter-channel connectivity. Hidden Markov models are applied to characterize and classify dynamics of the resulting complex networks. Highly accurate levels of classification are achieved when this technique is applied to classify EEG recorded during real and imagined single finger taps. These results are compared to traditional features used in the classification of a finger tap BCI demonstrating that functional connectivity dynamics provide additional information and improved BCI control accuracies.
Resumo:
This article extends the traditions of style-based criticism through an encounter with the insights that can be gained from engaging with filmmakers at work. By bringing into relationship two things normally thought of as separate: production history and disinterested critical analysis, the discussion aims to extend the subjects which criticism can appreciate as well as providing some insights on the creative process. Drawing on close analysis, on observations made during fieldwork and on access to earlier cuts of the film, this article looks at a range of interrelated decision-making anchored by the reading of a particular sequence. The article examines changes the film underwent in the different stages of production, and some of the inventions deployed to ensure key themes and ideas remained in play, as other elements changed. It draws conclusions which reveal perspectives on the filmmaking process, on collaboration, and on the creative response to material realities. The article reveals elements of the complexity of the process of the construction of image and soundtrack, and extends the range of filmmakers’ choices which are part of a critical dialogue. Has a relationship to ‘Sleeping with half open eyes: dreams and realities in The Cry of the Owl’, Movie: A Journal of Film Criticism, 1, (2010) which provides a broader interpretative context for the enquiry.
Resumo:
Deep Brain Stimulation (DBS) is a treatment routinely used to alleviate the symptoms of Parkinson's disease (PD). In this type of treatment, electrical pulses are applied through electrodes implanted into the basal ganglia of the patient. As the symptoms are not permanent in most patients, it is desirable to develop an on-demand stimulator, applying pulses only when onset of the symptoms is detected. This study evaluates a feature set created for the detection of tremor - a cardinal symptom of PD. The designed feature set was based on standard signal features and researched properties of the electrical signals recorded from subthalamic nucleus (STN) within the basal ganglia, which together included temporal, spectral, statistical, autocorrelation and fractal properties. The most characterized tremor related features were selected using statistical testing and backward algorithms then used for classification on unseen patient signals. The spectral features were among the most efficient at detecting tremor, notably spectral bands 3.5-5.5 Hz and 0-1 Hz proved to be highly significant. The classification results for determination of tremor achieved 94% sensitivity with specificity equaling one.