1,720,992 research outputs found
Improving patient’s medical history classification using a feature construction approach based on situation awareness and granular computing
No full textHealthcare decision support systems aid physicians in disease classification by analyzing patients’ medical histories to suggest preliminary diagnoses. As physicians largely base their analysis on anamnesis, integrating this process into an automated recommendation system can expedite decision-making and transition to relevant clinical investigations, thus enhancing efficiency in diagnosing potential pathologies. In this research, an innovative method for feature construction is introduced, drawing on the concepts of Situation Awareness and Granular Computing. The aim of this method is to enhance the performance of out-of-the-box classification algorithms used in machine learning. The approach is specifically tailored to mimic physicians’ cognitive processes when analyzing a patient’s medical history, resulting in the generation of new, information-dense features that can be used for classification tasks. By employing this strategy, a deeper comprehension of the data can be achieved, as well as a more precise categorization of anamneses in relation to possible medical conditions. To authenticate the efficacy of the proposed technique, three major disease categories, namely cardiac, gastrointestinal, and thyroid, were considered. The dataset comprised 1213 medical histories. The experimental results indicate that the study’s six classifiers attained a balanced accuracy exceeding 90%. Among these, the SVM classifier demonstrated the highest balanced accuracy at 93%. Overall, the proposed approach resulted in an average increase of 16 percentage points in balanced accuracy, representing an improvement over the traditional methods commonly employed in machine learning. This approach could be integrated into a clinical decision support system, aiding physicians in accurately identifying necessary investigations and expediting diagnosis
Knowledge-driven fuzzy consensus model for team formation
Get PDFThe correct allocation of human resources is of utmost importance for any kind of enterprise and organization. Many approaches have been defined so far to support team formation leveraging on different techniques, from knowledge engineering to operational research and computational intelligence. Unfortunately, these approaches are often specifically thought for large organizations owning the right set of technological assets and human resources able to manage and use these approaches. In this work, we propose an original approach to team formation, namely the KnowMIS-Team approach, specifically designed for knowledge-intensive small and medium enterprises. This is a lightweight hybrid approach that combines three different techniques: a knowledge-driven technique for finding the most competent team for a given project based on a lightweight semantic model of knowledge, skills and attitudes; a top-down, leader-selected approach wherein the competent members selected in the previous phase can propose their candidate teams; a bottom-up fuzzy consensus-based mechanism in which the employees of the organization can express their preferences on the candidate teams. A conceptual architecture of an intelligent system implementing the approach is also presented. The KnowMIS-Team approach is the overall result of many years of experience in team formation and management for a research center and embeds all the best practices therein adopted, and it has been experimented in the same center and in other university spin-offs for many years, contributing to the realization of successful projects
Augmented Reality to Increase Interaction and Participation: A Case Study of Undergraduate Students in Mathematics Class
No full textThis work focuses on the Augmented Reality trying to improve students’ interaction and participation in the educational dialogue, preventing the drop out, tested with university mathematics courses. Students often have difficulties on some topics related to the transition between different representations, within the same representations and language, for example when dealing with the study of two-variable functions, but also about the exact differential forms and the identification of the domain to integrate a function of several variables. These difficulties lead to a decrease in interaction and participation, and sometimes to dropping out of the course.Augmented Reality has been used to overcome some of these difficulties, also with the use of some technological tools (3D glasses, computers, tablets) and innovative methodologies. In order to evaluate the impact of this approach on students’ interaction and participation, an experimentation with an e-learning platform based on Augmented Reality was carried out evaluating some affective and interaction parameters, computed through a Fuzzy Cognitive Map
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
Fuzzy cognitive analysis in undergraduate mathematics class on engagement, motivation, and participation during covid-pandemic
No full textInternational audienceThis work focuses on Distance Learning during the COVID-19 pandemic to improve undergraduate students' motivation, participation, and engagement. Experimentation in a Mathematics STEM class evaluated the impact of Distance Learning on students' motivation, participation, and engagement levels, computed through a Fuzzy Cognitive Map. It was performed on some affective and interaction parameters derived from using an adaptive e-learning platform and from the answers of a semistructured questionnaire. The results have been analyzed through Technological Pedagogical Content Knowledge and Instrumental Genesis theories
The Impact of Covid-19 Pandemic on Undergraduate Students: the Role of an Adaptive Situation-Aware Learning System
No full textIn the context of the emergency of COVID-19, students have experienced moments of strong emotional stress,
with the risk of generating a state of frustration and discouraging them from studying. The proposed adaptive e-learning system, based on situational awareness, and remodeled teaching were essential in limiting this phenomenon. The system has been designed and developed according to the design principles of Situation Awareness. The feedback selection process, updated through the years to face the emergency situation, is driven by a Fuzzy Cognitive Map, implemented to identify the learners’ situation, defined through their levels of engagement, motivation, and participation. The experimentation was conducted using the SAGAT methodology, involving students participating in classes during the courses held over the academic years 2018/2019, 2019/2020, and 2020/2021. The results show that the system is capable of increasing the level of situation awareness of the students even in a context of emergency
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
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