21,516 research outputs found

    The Time Devil runs amok: How I improved my creative practice by adopting a multimodal approach for a specific audience.

    Get PDF
    This research illustrates how teacher-writers can improve their craft and pedagogy by writing for a specific audience, namely school children. It also illustrates why they might do so. It interrogates what was learnt from an innovative collaboration between a university teacher-education department, an inner-city secondary school and the United Kingdom’s National Maritime Museum (NMM). Multimodality (Barnard 2019) inspired the project: local spaces, institutional settings, historical objects, photographs, pictures, time-travelling films and narratives motivated the teacher-writer and participants to read and respond imaginatively to the world. The author found that the project caused him to “remediate” his own practice: to transfer “existing skills in order to tackle new genres” (Barnard 2019: 121). This process enabled him to become a more effective writer and teacher. The research shows that the problem of multimodal overload – having too much choice regarding what to write about and the many forms writing can take – can be circumnavigated if participants are given both autonomy and constraints. It illustrates in some depth how the concept of reciprocity is vital to adopt if writers are to improve their craft

    Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting

    Get PDF
    Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statistical models that are often too costly, both computationally and budgetary, or are not applied to downstream applications. Therefore, approaches that use Machine Learning algorithms in conjunction with time-series data are being explored as an alternative to overcome these drawbacks. To this end, this study presents a comparative analysis using simplified rainfall estimation models based on conventional Machine Learning algorithms and Deep Learning architectures that are efficient for these downstream applications. Models based on LSTM, Stacked-LSTM, Bidirectional-LSTM Networks, XGBoost, and an ensemble of Gradient Boosting Regressor, Linear Support Vector Regression, and an Extra-trees Regressor were compared in the task of forecasting hourly rainfall volumes using time-series data. Climate data from 2000 to 2020 from five major cities in the United Kingdom were used. The evaluation metrics of Loss, Root Mean Squared Error, Mean Absolute Error, and Root Mean Squared Logarithmic Error were used to evaluate the models' performance. Results show that a Bidirectional-LSTM Network can be used as a rainfall forecast model with comparable performance to Stacked-LSTM Networks. Among all the models tested, the Stacked-LSTM Network with two hidden layers and the Bidirectional-LSTM Network performed best. This suggests that models based on LSTM-Networks with fewer hidden layers perform better for this approach; denoting its ability to be applied as an approach for budget-wise rainfall forecast applications

    Efficacy of the RtI Model in the treatment of reading learning disabilities

    Get PDF
    p.1-25Background: The response to intervention (RtI) model makes possible the early detection of reading problems and early intervention for students at risk. The purpose of this study is to analyze the effective measures that identify struggling readers and the most effective practices of the RtI model in reading in Primary Education. Method: A systematic review of the literature published between 2010 and 2020 was performed, analyzing in the 31 selected articles, the identification and monitoring methods and the interventions at the different tiers of the RtI model. Results: There are different methods to identify struggling readers, and there is no consensus on the matter. There are also many differences in the implementation of the different tiers of the RtI model; however, its effectiveness is demonstrated. Conclusions: The implementation of the RtI model in a flexible way adapted to the circumstances of each moment, and can be considered as a highly effective resource in the prevention and early detection of reading learning problemsS

    Facial expression recognition and intensity estimation.

    Get PDF
    Doctoral Degree. University of KwaZulu-Natal, Durban.Facial Expression is one of the profound non-verbal channels through which human emotion state is inferred from the deformation or movement of face components when facial muscles are activated. Facial Expression Recognition (FER) is one of the relevant research fields in Computer Vision (CV) and Human-Computer Interraction (HCI). Its application is not limited to: robotics, game, medical, education, security and marketing. FER consists of a wealth of information. Categorising the information into primary emotion states only limit its performance. This thesis considers investigating an approach that simultaneously predicts the emotional state of facial expression images and the corresponding degree of intensity. The task also extends to resolving FER ambiguous nature and annotation inconsistencies with a label distribution learning method that considers correlation among data. We first proposed a multi-label approach for FER and its intensity estimation using advanced machine learning techniques. According to our findings, this approach has not been considered for emotion and intensity estimation in the field before. The approach used problem transformation to present FER as a multilabel task, such that every facial expression image has unique emotion information alongside the corresponding degree of intensity at which the emotion is displayed. A Convolutional Neural Network (CNN) with a sigmoid function at the final layer is the classifier for the model. The model termed ML-CNN (Multilabel Convolutional Neural Network) successfully achieve concurrent prediction of emotion and intensity estimation. ML-CNN prediction is challenged with overfitting and intraclass and interclass variations. We employ Visual Geometric Graphics-16 (VGG-16) pretrained network to resolve the overfitting challenge and the aggregation of island loss and binary cross-entropy loss to minimise the effect of intraclass and interclass variations. The enhanced ML-CNN model shows promising results and outstanding performance than other standard multilabel algorithms. Finally, we approach data annotation inconsistency and ambiguity in FER data using isomap manifold learning with Graph Convolutional Networks (GCN). The GCN uses the distance along the isomap manifold as the edge weight, which appropriately models the similarity between adjacent nodes for emotion predictions. The proposed method produces a promising result in comparison with the state-of-the-art methods.Author's List of Publication is on page xi of this thesis

    Viability of patent insurance in Spain

    Get PDF
    M-24609-2013Since 1975 the FUNDACIÓN MAPFRE has involved itself in activities serving the general interests of society in different areas of business and culture along with activities aimed at improving the economic and social conditions of the least advantaged members and sectors of society. Within this framework, the FUNDACIÓN MAPFRE’s Institute of Insurance Science promotes and undertakes educational and research activities in the fields of insurance and risk management. In the area of education, its activities include specialized, post-graduate academic training carried out in association with the Pontifical University of Salamanca and courses and seminars for professionals held in Spain and Latin America. These activities have been expanded into other geographic regions thanks to cooperation with a series of institutions in Spain and other countries and an Internet training programme. The Institute offers grants for research in risk and insurance science and operates a specialized insurance and risk management Documentation Centre as support for its activities. The Institute routinely sponsors and draws up reports and publishes books dealing with insurance and risk management to improve our understanding of these fields. Some are intended as reference materials for those starting out in the study or practice of insurance affairs, while others are intended as information sources for undertaking research into specialized issues in greater depth. One of these activities is the publication of this volume, the outcome of research carried out by Drs. Pérez Carrillo and Cuypers in 2011 and 2012, under the guidance of José Antonio Aventín Arroyo

    Los géneros discursivos prototípicos de la Licenciatura en Administración de Empresas : conformación de un corpus textual con fines pedagógicos

    Get PDF
    Especialización en Didáctica de la Lenguas ExtranjerasEn el contexto de enseñanza de lectura comprensiva en lengua extranjera en el nivel superior, la selección textual para conformar un corpus pedagógico representa un aspecto fundamental, dado que este constituye la base de los materiales didácticos con los que se organiza la enseñanza (Hurtado Albir, 2011). En este sentido, dicho corpus debería incluir géneros prototípicos de las comunidades disciplinares (Bhatia, 1993; Cassany, 2008; Hyland, 2002) sobre temáticas de interés para los estudiantes atendiendo también a la opinión de los especialistas del área disciplinar. El presente trabajo aborda la problemática del diseño de materiales de comprensión lectora en inglés en el ámbito universitario. En cuanto al propósito principal, este estudio procura contribuir al mejoramiento de las prácticas pedagógicas en dicho contexto, a través de la descripción de los géneros y temáticas afines a la disciplina para la conformación del corpus pedagógico del nuevo manual para Lengua Inglesa II de la Licenciatura en Administración de Empresas, UCC. La problemática planteada es abordada desde un enfoque teórico que articula el concepto de lectura comprensiva en el nivel superior y los aportes de la teoría del género, según la Escuela de Inglés con Fines Específicos, y de la lingüística textual de base germánica. La presente investigación de alcance descriptivo y con un enfoque predominantemente cualitativo se desarrolló entre el segundo semestre de 2018 y el primer semestre de 2019. El proceso metodológico se organizó en torno a tres instrumentos clave para la recolección de datos, a saber, la ficha bibliográfica, el cuestionario a estudiantes y el cuestionario a docentes. A su vez, la información recolectada a partir de estas herramientas permitió realizar la selección textual y el consiguiente análisis multinivel de los textos del corpus. Los resultados obtenidos han permitido sugerir no solo una propuesta de corpus ejemplar con fines pedagógicos para el contexto educativo mencionado, sino también algunos posibles lineamientos que podrían considerarse para conducir una futura ampliación del corpus ejemplar.Fil: Cardini, María Natalia. Universidad Nacional de Córdoba. Facultad de Lenguas; Argentina

    Exploring the Impact of Living with Fanconi Anaemia & Diamond-Blackfan Anaemia: A Systemic Consideration

    Get PDF
    Aims: Amidst a growing body of medical research, little is yet known about the psychological impact of living with two rare life-limiting conditions, Fanconi Anaemia (FA) and Diamond Blackfan Anaemia (DBA). One might expect some level of impact on well-being as indicated by wider literature on other childhood illnesses. At present, understanding of this impact is limited in being generalised from other research, as therefore are the supports available. This research seeks to begin a consideration of the psychological impact, and to consider how support has been deemed. Method: Using semi-structured interviews, parents and individuals living with FA or DBA were interviewed regarding their experiences. Thematic analysis was used to achieve an overview of these experiences. Results: Themes identified for individuals included: 1. ‘Knowledge’, which outlined the impact of lack of knowledge and 2. ‘Illness Concept’ relating to one’s relationship to FA/DBA and how this is socially mediated. For parents, themes identified were: 1. ‘Knowledge’, which centered on uncertainty and 2. ‘Social Responses’ which related to areas of support and strain. These themes indicated an impact on individual well-being. Two joint themes were identified: 1. ‘Family Dynamics’ which outlined how relationships and family well-being may be impacted and 2. ‘Mental Health Care as Necessary but Inadequate’. Conclusion: There was a clear impact articulated regarding the well-being of family members, individually and collectively in concerns regarding relational dynamics. There was also clear demand for psychological support which, in its current form, was generally considered inadequate. Research must be responsive in furthering efforts to establish clear and adequate pathways and a standard of care for the well-being of all families living with FA/DBA
    corecore