EDUCATIONAL DATA MINING AND ITS USES TO PREDICT THE MOST PROSPEROUS LEARNING ENVIRONMENT

The use of technology and data analysis within the classroom has been a resourceful tool in order to collect, study, and compare a student's level of success. With the large amount of regularly collected data from student behaviors, and course structure there is more than enough resources in order to find student success with data analysis. A method of data analysis within a learning environment is called Educational Data Mining (EDM), which has proven to be an emerging trend when it involves the development of exploration techniques and the analysis of educational data. EDM has been able to contribute to the understanding of student behavior, as well as factors that influence both student actions and their success. The study of student success within EDM has focused on student learning patterns, student to teacher culture, and teaching techniques. In this research we will look at uses of technology and data mining in an EDM setting and compare the success of findings. Using past experience of other research we will determine which method would be best in order to look at a learning environment, and try to find which factors will affect a student's academic performance

Titanium dioxide nanoparticles enhance mortality of fish exposed to bacterial pathogens

Nano-TiO2 is immunotoxic to fish and reduces the bactericidal function of fish neutrophils. Here, fathead minnows (Pimephales promelas) were exposed to low and high environmentally relevant concentration of nano-TiO2 (2 ng g−1 and 10 μg g−1 body weight, respectively), and were challenged with common fish bacterial pathogens, Aeromonas hydrophila or Edwardsiella ictaluri. Pre-exposure to nano-TiO2 significantly increased fish mortality during bacterial challenge. Nano-TiO2 concentrated in the kidney and spleen. Phagocytosis assay demonstrated that nano-TiO2 has the ability to diminish neutrophil phagocytosis of A. hydrophila. Fish injected with TiO2 nanoparticles displayed significant histopathology when compared to control fish. The interplay between nanoparticle exposure, immune system, histopathology, and infectious disease pathogenesis in any animal model has not been described before. By modulating fish immune responses and interfering with resistance to bacterial pathogens, manufactured nano-TiO2 has the potential to affect fish survival in a disease outbreak

Mixed methods in pre-hospital research : understanding complex clinical problems

Healthcare is becoming increasingly complex. The pre-hospital setting is no exception, especially when considering the unpredictable environment. To address complex clinical problems and improve quality of care for patients, researchers need to use innovative methods to create the necessary depth and breadth of knowledge. Quantitative approaches such as randomised controlled trials and observational (e.g. cross-sectional, case control, cohort) methods, along with qualitative approaches including interviews, focus groups and ethnography, have traditionally been used independently to gain understanding of clinical problems and how to address these. Both approaches, however, have drawbacks: quantitative methods focus on objective, numerical data and provide limited understanding of context, whereas qualitative methods explore more subjective aspects and provide perspective, but can be harder to demonstrate rigour. We argue that mixed methods research, where quantitative and qualitative methods are integrated, is an ideal solution to comprehensively understand complex clinical problems in the pre-hospital setting. The aim of this article is to discuss mixed methods in the field of pre-hospital research, highlight its strengths and limitations and provide examples. This article is tailored to clinicians and early career researchers and covers the basic aspects of mixed methods research. We conclude that mixed methods is a useful research design to help develop our understanding of complex clinical problems in the pre-hospital setting

Comparative Capitalism without Capitalism, and Production without Workers: The Limits and Possibilities of Contemporary Institutional Analysis

The aim of this paper is to consider the extent to which the comparative capitalism literature fully reflects the available empirical evidence in its attempts to model different versions of capitalism and, in particular, whether it adequately captures the roles of diverse stakeholders within the capitalist system. In doing so, particular attention is accorded to the varieties of capitalism literature, business systems theory and regulation theory. In addition, there is reflection in the paper on whether any strand of the literature is able to deal effectively with the recent economic crisis and systemic change. It is argued that more attention needs to be devoted to exploring the structural causes of change and the marginalization of the interests of key social groupings, most notably workers, from the process of institutional redesign

The EUPEMEN (EUropean PErioperative MEdical Networking) Protocol for Bowel Obstruction: recommendations for perioperative care

Mechanical bowel obstruction is a common symptom for admission to emergency services, diagnosed annually in more than 300,000 patients in the States, from whom 51% will undergo emergency laparotomy. This condition is associated with serious morbidity and mortality, but it also causes a high financial burden due to long hospital stay. The EUPEMEN project aims to incorporate the expertise and clinical experience of national clinical specialists into development of perioperative rehabilitation protocols. Providing special recommendations for all aspects of patient perioperative care and the participation of diverse specialists, the EUPEMEN protocol for bowel obstruction, as presented in the current paper, aims to provide faster postoperative recovery and reduce length of hospital stay, postoperative morbidity and mortality rate

Dominant ethnicity: from minority to majority

This article argues that the world is in the midst of a long-term transition from dominant minority to dominant majority ethnicity. Whereas minority domination was common in premodern societies, modernity (with its accent on democracy and popular sovereignty) has engendered a shift to dominant majority ethnicity. The article begins with conceptual clarifications. The second section provides a broad overview of the general patterns of ethnic dominance that derive from the logic of modern nationalism and democratisation. The third section discusses remnants of dominant minorities in the modern era and suggests that their survival hinges on peculiar historical and social circumstances coupled with resistance to democratisation. The fourth section shifts the focus to dominant majorities in the modern era and their relationship to national identities. The article ends with a discussion of the fortunes of dominant ethnicity in the West

Children and Virtual Reality: Emerging Possibilities and Challenges

Virtual Reality is fast becoming a reality, with estimates that over 200m headsets will have been sold by 2020, and the market value for VR hardware and software reaching well over $20bn by then. Key players in the market currently include PlayStation with PSVR, Facebook with Oculus Rift, Google Cardboard and Daydream, Mattel with Viewmaster, and many other brands investing in content production for various audiences. One of those audiences is young people and children. “Children and Virtual Reality” is a collaboration between Dubit, Turner, WEARVR and the COST (European Cooperation in Science and Technology) Action DigiLitEY. Dubit, Turner and WEARVR are companies that specialise in digital, TV and VR content, with an interest in developing best practices around VR and children. DigiLitEY is a five year (2013-2017) academic network that focuses on existing and emerging communicative technologies for young children. This includes wearable technologies, 3D printers, robots, augmented reality, toys and games and relevant aspects of the Internet of Things. This report brings together industry research into the effects of VR on 8 to 12 year olds, and ideas that arose from a COST funded Think Tank to explore what the research findings might mean for the use of VR by under 8s

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars