6,192 research outputs found
Displacement and the Humanities: Manifestos from the Ancient to the Present
This is the final version. Available on open access from MDPI via the DOI in this recordThis is a reprint of articles from the Special Issue published online in the open access journal Humanities (ISSN 2076-0787) (available at: https://www.mdpi.com/journal/humanities/special_issues/Manifestos Ancient Present)This volume brings together the work of practitioners, communities, artists and other researchers from multiple disciplines. Seeking to provoke a discourse around displacement within and beyond the field of Humanities, it positions historical cases and debates, some reaching into the ancient past, within diverse geo-chronological contexts and current world urgencies. In adopting an innovative dialogic structure, between practitioners on the ground - from architects and urban planners to artists - and academics working across subject areas, the volume is a proposition to: remap priorities for current research agendas; open up disciplines, critically analysing their approaches; address the socio-political responsibilities that we have as scholars and practitioners; and provide an alternative site of discourse for contemporary concerns about displacement. Ultimately, this volume aims to provoke future work and collaborations - hence, manifestos - not only in the historical and literary fields, but wider research concerned with human mobility and the challenges confronting people who are out of place of rights, protection and belonging
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Valuing Low Carbon Energy - Insights for Fusion Commercialisation
The proponents of nuclear fusion believe that a small modular approach has the potential to achieve a viable source of energy in timescales smaller than those projected for the large scale multinational ITER/DEMO programme. If the numerous technical challenges can be overcome, the question still remains as to whether fusion small modular reactors (SMRs) will be commercially viable. This thesis aims to provide insight into this question and to identify whether approaches other than the generation of electricity to the grid have the potential to increase the value of a fusion SMR or a fleet of SMRs to a developer.
The work has three main components. Firstly, the Net Present Value (SMR) of a fusion SMR supplying electricity for sale to the grid in the UK was evaluated. This showed that there are combinations of electricity prices, capital cost and discount rates that will result in positive NPVs.
In the second component of the work, an existing approach to engineering flexibilities / real options has been extended and applied to the production of hydrogen from methane with carbon capture and storage. The results of this work demonstrate that the application of engineering flexibilities / real options has the potential to increase the value of a project.
In the final stage of the thesis, an engineering flexibility / real options approach has been combined with a portfolio approach to a fleet of fusion SMRs. This demonstrated that this approach has the potential to increase the value of a fleet of fusion SMRs to a developer.
The thesis has demonstrated that it is possible that fusion SMRs may be commercially viable. It has also demonstrated that the use of techniques such as engineering flexibilities and portfolio theory has the potential to increase the value to a developer of a fleet of fusion SMRs based on a tokomak design.</br
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Cancer Care in Pandemic Times: Building Inclusive Local Health Security in Africa and India
This is a book about improving cancer care in Africa and India that is a child of its pandemic times. It has been collaboratively researched and written by colleagues in Kenya, Tanzania, India and the UK, working within a cross-country, multidisciplinary research project, Innovation for Cancer Care in Africa (ICCA). Since this was a health-focused research project, ICCA researchers during the pandemic not only continued to work on the cancer research project but were also called upon by their governments to respond to immediate pandemic needs. In combining these two concerns, for improving cancer care and responding to pandemic needs, our original project aims have been challenged, deepened and reworked. ICCA’s initial collaborative research focus included—against the grain of most global health literature—the potential role of enhanced local production of essential healthcare supplies for improving cancer care in African countries. The pandemic experience has strikingly validated these earlier findings on the importance of industrial development for health care. The pandemic crystallised for researchers and policymakers an often overlooked phenomenon: global health security is built on the foundations of strong local health security. We argue in this book that new analytical thinking from social scientists and others is required on how to build local health security. We use the “lens” of original research on cancer care in East Africa and India to build up an understanding of the scope for the development of stronger synergies between local health industries and health care, in order to strengthen local health security and develop tools for policy making. The rethinking and reimagining presented here is required for different African countries, for India and the wider world, and this research on cancer care has taught us that this imperative goes much wider than infectious diseases
Cognitive Inhibition as a Core Component of Executive Functions:Exploring Intra- and Interindividual Differences
Cognitive inhibition is an essential executive function that we use in our everyday lives. Numerous factors have been claimed to influence this construct including video gaming, exercise and expertise in musical instruments. However, in this thesis, I focus on an understudied factor, the alignment of chronotype and testing time, and a heavily studied yet controversial factor, bilingualism. Throughout this thesis, with one exception, I present a series of experiments which have been conducted online. In the first empirical chapter, I examined a relatively novel Faces task which the authors have claimed to measure three cognitive processes, including two different forms of inhibition and task switching (Chapter 2). Based on this chapter's findings, I decided to use the Faces task in Chapters 3, 4 and 6. The next two chapters determined whether the alignment of time of testing and chronotype influences inhibition and task switching among the young adult (Chapter 3) and older adult (Chapter 4) population. Afterwards, I explored how conflict is resolved through a mouse tracking paradigm and by extension, whether this paradigm can be used for a variety of inhibition tasks (Chapter 5). For the final empirical chapter, I identified whether training inhibition in a verbal domain impacts inhibition in a non-verbal domain (i.e., far transfer effects). To achieve this, I investigated whether bilingualism, which can be seen as a form of cognitive training within the verbal domain, influences performance in non-verbal tasks which index inhibition (Chapter 6). The main findings of this thesis suggest that cognitive inhibition is not substantially impacted by synchrony effects nor by bilingualism. Furthermore, the findings imply that mouse tracking could be a promising tool to use to examine cognitive inhibition
Fairness-aware Machine Learning in Educational Data Mining
Fairness is an essential requirement of every educational system, which is reflected in a variety of educational activities. With the extensive use of Artificial Intelligence (AI) and Machine Learning (ML) techniques in education, researchers and educators can analyze educational (big) data and propose new (technical) methods in order to support teachers, students, or administrators of (online) learning systems in the organization of teaching and learning. Educational data mining (EDM) is the result of the application and development of data mining (DM), and ML techniques to deal with educational problems, such as student performance prediction and student grouping. However, ML-based decisions in education can be based on protected attributes, such as race or gender, leading to discrimination of individual students or subgroups of students. Therefore, ensuring fairness in ML models also contributes to equity in educational systems. On the other hand, bias can also appear in the data obtained from learning environments. Hence, bias-aware exploratory educational data analysis is important to support unbiased decision-making in EDM.
In this thesis, we address the aforementioned issues and propose methods that mitigate discriminatory outcomes of ML algorithms in EDM tasks. Specifically, we make the following contributions:
We perform bias-aware exploratory analysis of educational datasets using Bayesian networks to identify the relationships among attributes in order to understand bias in the datasets. We focus the exploratory data analysis on features having a direct or indirect relationship with the protected attributes w.r.t. prediction outcomes.
We perform a comprehensive evaluation of the sufficiency of various group fairness measures in predictive models for student performance prediction problems. A variety of experiments on various educational datasets with different fairness measures are performed to provide users with a broad view of unfairness from diverse aspects.
We deal with the student grouping problem in collaborative learning. We introduce the fair-capacitated clustering problem that takes into account cluster fairness and cluster cardinalities. We propose two approaches, namely hierarchical clustering and partitioning-based clustering, to obtain fair-capacitated clustering.
We introduce the multi-fair capacitated (MFC) students-topics grouping problem that satisfies students' preferences while ensuring balanced group cardinalities and maximizing the diversity of members regarding the protected attribute. We propose three approaches: a greedy heuristic approach, a knapsack-based approach using vanilla maximal 0-1 knapsack formulation, and an MFC knapsack approach based on group fairness knapsack formulation.
In short, the findings described in this thesis demonstrate the importance of fairness-aware ML in educational settings. We show that bias-aware data analysis, fairness measures, and fairness-aware ML models are essential aspects to ensure fairness in EDM and the educational environment.Ministry of Science and Culture of Lower Saxony/LernMINT/51410078/E
Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation
Trustworthy Artificial Intelligence (AI) is based on seven technical
requirements sustained over three main pillars that should be met throughout
the system's entire life cycle: it should be (1) lawful, (2) ethical, and (3)
robust, both from a technical and a social perspective. However, attaining
truly trustworthy AI concerns a wider vision that comprises the trustworthiness
of all processes and actors that are part of the system's life cycle, and
considers previous aspects from different lenses. A more holistic vision
contemplates four essential axes: the global principles for ethical use and
development of AI-based systems, a philosophical take on AI ethics, a
risk-based approach to AI regulation, and the mentioned pillars and
requirements. The seven requirements (human agency and oversight; robustness
and safety; privacy and data governance; transparency; diversity,
non-discrimination and fairness; societal and environmental wellbeing; and
accountability) are analyzed from a triple perspective: What each requirement
for trustworthy AI is, Why it is needed, and How each requirement can be
implemented in practice. On the other hand, a practical approach to implement
trustworthy AI systems allows defining the concept of responsibility of
AI-based systems facing the law, through a given auditing process. Therefore, a
responsible AI system is the resulting notion we introduce in this work, and a
concept of utmost necessity that can be realized through auditing processes,
subject to the challenges posed by the use of regulatory sandboxes. Our
multidisciplinary vision of trustworthy AI culminates in a debate on the
diverging views published lately about the future of AI. Our reflections in
this matter conclude that regulation is a key for reaching a consensus among
these views, and that trustworthy and responsible AI systems will be crucial
for the present and future of our society.Comment: 30 pages, 5 figures, under second revie
A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases
In recent years, 3D virtual indoor and outdoor urban modelling has become an essential geospatial information framework for civil and engineering applications such as emergency response, evacuation planning, and facility management. Building multi-sourced and multi-scale 3D urban models are in high demand among architects, engineers, and construction professionals to achieve these tasks and provide relevant information to decision support systems. Spatial modelling technologies such as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication between BIM and GIS do not fully provide rich semantic and geometric information exchange of BIM into GIS or vice-versa. This research study proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graph databases. The suggested solution's originality and novelty come from combining the advantages of integrating BIM and GIS models into a semantically unified data model using a semantic framework and ontology engineering approaches. The new model will be named Integrated Geospatial Information Model (IGIM). It is constructed through three stages. The first stage requires BIMRDF and GISRDF graphs generation from BIM and GIS datasets. Then graph integration from BIM and GIS semantic models creates IGIMRDF. Lastly, the information from IGIMRDF unified graph is filtered using a graph query language and graph data analytics tools. The linkage between BIMRDF and GISRDF is completed through SPARQL endpoints defined by queries using elements and entity classes with similar or complementary information from properties, relationships, and geometries from an ontology-matching process during model construction. The resulting model (or sub-model) can be managed in a graph database system and used in the backend as a data-tier serving web services feeding a front-tier domain-oriented application. A case study was designed, developed, and tested using the semantic integrated information model for validating the newly proposed solution, architecture, and performance
An exploration of the attitudes and beliefs of teacher trainers and teacher trainees concerning the use of the L1 in the EFL classroom
One important conflict within English language teaching methodology is concerning the use or exclusion of learners’ first languages (L1) when learning English. Perspectives on the topic range from those in favour of complete avoidance of the L1 in the EFL classroom, constantly striving for an exclusively L2 classroom to those who believe in the value and learning benefit of allowing and, to some extent, encouraging the use of all manner of languages available to the learner. This thesis conducted interviews and surveys in order to provide an in-depth exploration of the attitudes and beliefs of teacher trainers and teacher trainees in North Rhine Westphalia concerning the use of the L1, as well as other potential languages, in the English language classroom. Although the two groups of participants held many similar attitudes and beliefs concerning L1 use, some significant and interesting differences were found. Teacher trainees showed themselves to be more open concerning the use of the L1 than their more experienced counterparts. It remains, however, unclear what exactly the reason for these differences is. A further aspect which became apparent is how the pressures of language choice and of exclusive L2 instruction in the EFL classroom during observed and examination lessons is felt by teacher trainees. This is potentially adding to the overall burden of the teacher training period in NRW. The thesis concludes that an increase in evidence-based teacher education, concerning not only the aspect of L1 use in the EFL classroom but also many other aspects of language teaching could be prudent in the continued development of well-informed best-practice approaches. This thesis holds the standpoint that complete eradication of the L1 in the EFL classroom is counterproductive to successful language learning. Judicious use of the L1 and the development of a more plurilingusitic attitude to language learning, enabling learners to make use of any available linguistic resources, can offer both learners and teachers helpful scaffolding which can facilitate the successful learning of further languages
Systemic Circular Economy Solutions for Fiber Reinforced Composites
This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials
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