1,721,287 research outputs found
Machine Learning Models for Predicting Emotional Valence from Brain Activity and Physiological Responses
No full textIn this study, we developed machine learning models to predict the valence class and valence rating of emotions experienced by participants based on their brain activity and physiological responses. The ICBHI 2024 Scientific Challenge involves using a rich dataset comprising pre-processed functional Magnetic Resonance Imaging (fMRI), photoplethysmography (PPG), and respiratory data from 20 participants. Each participant watched emotion-provoking video clips categorized into three valence classes (positive, negative, neutral) and rated them on a nine-level scale. Our approach integrates Convolutional Neural Networks (CNNs) for analyzing fMRI data and CNNs + Long Short-Term Memory (LSTM) networks for handling PPG and respiratory data. The models were trained to classify the valence class and predict the valence level, using a categorical cross-entropy as loss functions. Initial results show promising trends, indicating the model’s potential for accurate emotion prediction. fMRI model training and validation accuracy are 0.99 and 0.98 respectively. PPG and respiratory models accuracy are 0.86 and 0.66 on training and 0.80 and 0.56 on validation. However, further fine-tuning and architectural adjustments are necessary to enhance performance. This work aims to contribute to understanding how brain activity and physiological responses can be used to decode emotional states, with potential applications in psychological assessment and therapeutic interventions
CRM Implementation: A Descriptive Study of the Service Industry in Pakistan
Full text linkIn service industries, the customer relationship has become a core issue for achieving competitive advantage. The firms prefer to invest in the technology based Customer Relationship Management (CRM). However, mere implementing the CRM applications does not itself ensure success until the consequent factors of the CRM are considered by the enterprises concerned. This study provides the descriptive analysis of the CRM implementation and two important factors: customer knowledge and customization. The aim is to analyze the degree to which service firms utilize CRM technology, customize services and store customer knowledge. The results show that CRM application is extensively used in the firms who store and manage customer knowledge. This helps in increasing organizational performance. However, customization is not always the practice of the service firms
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Insights in Data Generation: A Synthetic Data Approach for Enabling Small Datasets in Atrial Fibrillation Research
No full textThis study explores the Gaussian Copula Synthesizer’s (GCS) utility in addressing the limitations of a small dataset (58 real patient records) in Atrial Fibrillation (AF) research, focusing on Heart Rate Variability (HRV). Leveraging this method, we generated a realistic synthetic dataset of 1, 000 records, replicating the features observed in the original records. The GCS effectively expands dataset size while maintaining HRV pattern realism. This aids in developing and refining models used in AF research, overcoming challenges associated with limited sample sizes. Emphasizing privacy considerations, this approach showcases the potential of classic statistical methods in synthetic data generation for advancing AF research within the constraints of small datasets
Variations on the Author
Full text link“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
Full text linkWe 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
Application of 2D Materials for Adsorptive Removal of Air Pollutants
No full textAir pollution is on the priority list of global safety issues, with the concern of fatal environmental and public health deterioration. 2D materials are potential adsorbent materials for environmental decontamination, owing to their high surface area, manageable interlayer binding, large surface-to-volume ratio, specific binding capability, and chemical, thermal, and mechanistic stability. Specifically, graphene oxide and reduced graphene oxide have been attracting attention, taking advantage of their low cost synthesis, excessive oxygen containing surface functionalities, and intrinsic aqueous dispersibility, making them desirable for the development of cost-effective, high performance air filters. Many different material designs have been proposed to expand their filtration capability, including the functionalization and integration with other metals and metal oxides, which act not only as binding agents to the target pollutants but also as antimicrobial agents. This review highlights the advantages and drawbacks of 2D materials for air filtration and summarizes the interrelationships among various strategies and the resultant filtration performance in terms of structural engineering, morphology control, and material compositions. Finally, potential future directions are suggested toward the idealized designs of 2D material based air filters.
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
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