1,720,986 research outputs found
Chapter 11 - EEG signal processing with deep learning for alcoholism detection
No full textAlcoholism affects a large population and millions of people are suffering from various neurological or social issues due to excessive consumption of alcohol. Identification of alcoholism has been a challenge and many of the laboratory-based methods have their limitation. Electroencephalogram (EEG) is a technique to record the brain signals of a person and these signals have been shown to help identify a person as an alcoholic or nonalcoholic. This chapter discusses some of the common techniques for EEG signal processing and also provides an overview of multimodal signal processing in the context of EEG analysis. Different statistical and machine learning techniques have been used for signal classification, but deep neural networks have been shown to be more effective than other approaches. We provide an overview of these techniques with a focus on deep neural networks and their optimization for EEG signal classification. We also discussed prevalent issues in preprocessing and feature engineering of EEG signals with an aim of broadening the understanding of the pipeline in EEG classification for alcoholism or any other domain
Review of EEG Signals Classification Using Machine Learning and Deep-Learning Techniques
No full textElectroencephalography (EEG) signals have been widely used for the prognosis and diagnosis of several disorders, such as epilepsy, schizophrenia, Parkinson’s disease etc. EEG signals have been shown to work with machine learning techniques in the literature. However, they require manual extraction of features beforehand which may change from dataset to dataset or depending on the disease application. Deep learning, on the other hand, have the ability to process the raw signals and classify data without requiring any domain knowledge or manually extracted features but lacks a good understanding and interpretability. This chapter will discuss different techniques of machine learning including features extraction and selection methods from filtered signals and classification of these selected features for clinical applications. We have also discussed two case studies i.e., epilepsy and schizophrenia detection. These case studies use an architecture which combines deep learning with traditional ML techniques and compare their results. Using this hybrid model, an accuracy of 94.9% is obtained based on EEG signals obtained from epileptic and normal subjects, while an accuracy of 98% accuracy is achieved in schizophrenia detection using only three EEG channels. The latter result is significant as it is comparable to other state of art techniques while requiring less data and computational power.</p
Chapter 2 - Artificial intelligence techniques for human-machine interaction
No full textThis chapter provides a broad overview of various artificial intelligence (AI) techniques employed in human-machine interaction (HMI). It explores a multitude of HMI techniques, each with its unique application area and AI approaches considered for its implementation. This chapter also delves into multimodal interaction and multimodal signal processing, integral parts of HMI. The techniques discussed range in their applications from personal experiences with machines to industrial use cases. Each technique's application area is examined, highlighting how AI enhances efficiency and effectiveness in these areas. Furthermore, the article delves into the AI-specific contemporary approaches used in HMI, such as neural networks and deep learning. This exploration provides an understanding of the integral role AI plays in advancing HMI, paving the way for future research and development in this dynamic field
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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