Detection of heart pathology using deep learning methods

In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators, 13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database

A basic guide to open educational resources (OER)

133 p. : ill.Libro ElectrónicoThis Guide comprises three sections. The first – a summary of the key issues – is presented in the form of a set of ‘Frequently Asked Questions’. Its purpose is to provide readers with a quick and user-friendly introduction to Open Educational Resources (OER) and some of the key issues to think about when exploring how to use OER most effectively. The second section is a more comprehensive analysis of these issues, presented in the form of a traditional research paper. For those who have a deeper interest in OER, this section will assist with making the case for OER more substantively. The third section is a set of appendices, containing more detailed information about specific areas of relevance to OER. These are aimed at people who are looking for substantive information regarding a specific area of interestContents Acknowledgements 1 Overview of the Guide 3 A Basic Guide to Open Educational Resources: Frequently asked questions 5 What are Open Educational Resources (OER)? 5 Is OER the same as e-learning? 5 Is OER the same as open learning/open education? 6 Is OER related to the concept of resource-based learning? 7 How open is an open licence? 8 What is the difference between OER and open access publishing? 9 Shouldn’t I worry about ‘giving away’ my intellectual property? 9 Who will guarantee the quality of OER? 12 How can education benefit by harnessing OER? 13 Is OER really free? 14 Does use of OER preclude use of commercial content? 16 What policy changes are needed for institutions to make more effective use of OER? 16 What are the best ways to build capacity in OER? 17 Where do I find OER? 18 How can I share my OER with others? 19 How much can I change OER for my own purposes? 20 Making the Case for Open Educational Resources 23 Introduction 23 Defining the concept 24 The implications for educational planners and decision-makers 39 Conclusion 44 References 45 Appendix One: Overview of Open Licences 47 Introduction 47 Creative Commons Licences 48 Appendix References 52 Appendix Two: The Components of a Well-Functioning Distance Education System 53 The Components 53 The Rationale for Use of Distance Education Methods 55 Appendix Three: Technology Applications 57 iii Appendix Four: Open Source Software Applications in Education 61 References 64 Appendix Five: Mapping the OER Terrain Online 65 Introduction 65 OCW OER Repositories 65 University OCW Initiatives 70 Subject-Specific OCW OER 74 Content Creation Initiatives 78 Open Schooling Initiatives 81 OCW OER Search 84 Conclusion 85 Appendix Six: A Catalogue of OER-Related Websites 87 OCW OER Repositories 88 Open Schooling Initiatives 92 OCW OER Search 93 University OCW Initiatives 95 Subject-Specific OCW-OER 104 OER Tools 109 Other OER Sources 113 Appendix Seven: Some OER Policy Issues in Distance Education 115 Appendix Eight: OER Policy Review Process 123 Appendix Nine: Skills Requirements for Work in Open Educational Resources 13

Educational use cases from a shared exploration of e-books and iPads

E-books and e-book readers are becoming increasingly widely available, particularly for the general reader, and there have been many studies on their adoption. However, less is known about their use for educational and academic purposes. We report here on work carried out on e-books and e-book applications using iPads by academic and teaching staff. After considering pedagogical issues and reporting survey results, we identify a spiral of six key use case areas for e-books. This spiral of use cases moves from basic e-book use, through situational reading, e-books and learning, using multiple learning resources, collaborative/group learning, to e-book production. We discuss each of these use case areas and provide guidelines that will be of interest to practitioners and researchers alike

UWOMJ Volume 46, Number 1, October 1975

Schulich School of Medicine & Dentistryhttps://ir.lib.uwo.ca/uwomj/1213/thumbnail.jp

Cross-Cultural Psychology and the Rise of Academic Capitalism : Linguistic Changes in CCR and JCCP Articles, 1970-2014

Recently, several studies have investigated developments in academic language over the last four decades: An analysis of a large number of PubMed abstracts by Vinkers, Tijdink, and Otte showed a dramatic rise in use of positive words such as “innovative,” “robust,” “novel,” and “unprecedented.” In the field of psychology, Pritschet, Powell, and Horne found an increase in mentions of marginally significant statistical findings, and social psychologist Michael Billig raised concerns about a surge of technical jargon in the social sciences. All these phenomena are believed to be a consequence of higher publication pressure and the need to become visible as a researcher in an increasingly competitive climate that is often referred to as academic capitalism. In our study, we tested the aforementioned indicators of linguistic change for a sample of 1,680 research articles from the Journal of Cross-Cultural Psychology (JCCP) and 657 research articles from Cross-Cultural Research (CCR), published between 1970 and 2014. Overall, we found a consistent increase in positive framing, a rise in reports of marginally significant statistical findings, and indicators for growth in technical jargon. These findings suggest that self-marketing strategies are also on the rise in cross-cultural psychology.Peer reviewe

The People Inside

Our collection begins with an example of computer vision that cuts through time and bureaucratic opacity to help us meet real people from the past. Buried in thousands of files in the National Archives of Australia is evidence of the exclusionary “White Australia” policies of the nineteenth and twentieth centuries, which were intended to limit and discourage immigration by non-Europeans. Tim Sherratt and Kate Bagnall decided to see what would happen if they used a form of face-detection software made ubiquitous by modern surveillance systems and applied it to a security system of a century ago. What we get is a new way to see the government documents, not as a source of statistics but, Sherratt and Bagnall argue, as powerful evidence of the people affected by racism

AI in Learning: Designing the Future

AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers