Data Science in Healthcare

Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management

Multi-objective Search-based Mobile Testing

Despite the tremendous popularity of mobile applications, mobile testing still relies heavily on manual testing. This thesis presents mobile test automation approaches based on multi-objective search. We introduce three approaches: Sapienz (for native Android app testing), Octopuz (for hybrid/web JavaScript app testing) and Polariz (for using crowdsourcing to support search-based mobile testing). These three approaches represent the primary scientific and technical contributions of the thesis. Since crowdsourcing is, itself, an emerging research area, and less well understood than search-based software engineering, the thesis also provides the first comprehensive survey on the use of crowdsourcing in software testing (in particular) and in software engineering (more generally). This survey represents a secondary contribution. Sapienz is an approach to Android testing that uses multi-objective search-based testing to automatically explore and optimise test sequences, minimising their length, while simultaneously maximising their coverage and fault revelation. The results of empirical studies demonstrate that Sapienz significantly outperforms both the state-of-the-art technique Dynodroid and the widely-used tool, Android Monkey, on all three objectives. When applied to the top 1,000 Google Play apps, Sapienz found 558 unique, previously unknown crashes. Octopuz reuses the Sapienz multi-objective search approach for automated JavaScript testing, aiming to investigate whether it replicates the Sapienz’ success on JavaScript testing. Experimental results on 10 real-world JavaScript apps provide evidence that Octopuz significantly outperforms the state of the art (and current state of practice) in automated JavaScript testing. Polariz is an approach that combines human (crowd) intelligence with machine (computational search) intelligence for mobile testing. It uses a platform that enables crowdsourced mobile testing from any source of app, via any terminal client, and by any crowd of workers. It generates replicable test scripts based on manual test traces produced by the crowd workforce, and automatically extracts from these test traces, motif events that can be used to improve search-based mobile testing approaches such as Sapienz

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

Citizen Science

Citizen science, the active participation of the public in scientific research projects, is a rapidly expanding field in open science and open innovation. It provides an integrated model of public knowledge production and engagement with science. As a growing worldwide phenomenon, it is invigorated by evolving new technologies that connect people easily and effectively with the scientific community. Catalysed by citizens’ wishes to be actively involved in scientific processes, as a result of recent societal trends, it also offers contributions to the rise in tertiary education. In addition, citizen science provides a valuable tool for citizens to play a more active role in sustainable development. This book identifies and explains the role of citizen science within innovation in science and society, and as a vibrant and productive science-policy interface. The scope of this volume is global, geared towards identifying solutions and lessons to be applied across science, practice and policy. The chapters consider the role of citizen science in the context of the wider agenda of open science and open innovation, and discuss progress towards responsible research and innovation, two of the most critical aspects of science today

Who are we and how do we fit in? – Fostering international students’ positive identity and sense of belonging in British society.

This is an extended conference abstract for the Netnocon 2024 Conference.N/

Digital work in the planetary market

Many of the world’s most valuable companies rely on planetary networks of digital work that underpin their products and services. This important book examines implications for both work and workers when jobs are commodified and traded beyond local labor markets. For instance, Amazon’s contractors in Costa Rica, India, and Romania are paid to structure, annotate, and organize conversations captured by ‘Alexa’ to train Amazon’s speech recognition systems. Findings show that despite its planetary connections, labor remains geographically “sticky” and embedded in distinct contexts. The research emphasizes the globe-spanning nature of contemporary networks without resorting to an understanding of “the global” as a place beyond space.Aujourd’hui, de nombreux emplois peuvent être exercés depuis n’importe où. La technologie numérique et la connectivité Internet généralisée permettent à presque n’importe qui, n’importe où, de se connecter à n’importe qui d’autre pour communiquer et interagir à l’échelle planétaire. Ce livre examine les conséquences, tant pour le travail que pour les travailleurs, de la marchandisation et de l’échange des emplois au-delà des marchés du travail locaux. Allant au-delà du discours habituel sur la mondialisation « le monde est plat », les contributeurs examinent à la fois la transformation du travail lui-même et les systèmes, réseaux et processus plus larges qui permettent le travail numérique dans un marché planétaire, en offrant des perspectives empiriques et théoriques. Les contributeurs - des universitaires et des experts de premier plan issus de diverses disciplines - abordent une variété de questions, notamment la modération du contenu, les véhicules autonomes et les assistants vocaux. Ils se penchent d’abord sur la nouvelle expérience du travail et constatent que, malgré ses connexions planétaires, le travail reste géographiquement collé et intégré dans des contextes distincts. Ils examinent ensuite comment les réseaux planétaires de travail peuvent être cartographiés et problématisés, ils discutent de la multiplicité productive et de l’interdisciplinarité de la réflexion sur le travail numérique et ses réseaux et, enfin, ils imaginent comment le travail planétaire pourrait être réglementé. Les directeurs Mark Graham est professeur de géographie de l’Internet à l’Oxford Internet Institute et chargé de cours à l’Alan Turing Institute. Il est l’éditeur du livre Digital Economies at Global Margins (MIT Press et CRDI, 2019). Fabian Ferrari est un candidat au doctorat à l’Oxford Internet Institute

Harnessing Twitter and crowdsourcing to augment aurora forecasting

The aurora borealis and aurora australis are beautiful space weather driven events whose sighting is typically based on luck given that forecasting is not spatially or temporally precise. To help increase the accuracy and timeliness of auroral forecasting, we have designed a multi-faceted system called Aurorasaurus. This system allows crisis management specialists to test reactions to rare event notifications, space weather scientists to get direct sighting information of auroras (complete with pictures), and science education researchers to evaluate the impact of educational materials about the aurora and the physics surrounding this unique phenomenon. Through manual tweet verification and directly reported aurora borealis or aurora australis sightings, everyday users help make space weather and aurora forecasting more accurate

Introduction to Development Engineering

This open access textbook introduces the emerging field of Development Engineering and its constituent theories, methods, and applications. It is both a teaching text for students and a resource for researchers and practitioners engaged in the design and scaling of technologies for low-resource communities. The scope is broad, ranging from the development of mobile applications for low-literacy users to hardware and software solutions for providing electricity and water in remote settings. It is also highly interdisciplinary, drawing on methods and theory from the social sciences as well as engineering and the natural sciences. The opening section reviews the history of “technology-for-development” research, and presents a framework that formalizes this body of work and begins its transformation into an academic discipline. It identifies common challenges in development and explains the book’s iterative approach of “innovation, implementation, evaluation, adaptation.” Each of the next six thematic sections focuses on a different sector: energy and environment; market performance; education and labor; water, sanitation and health; digital governance; and connectivity. These thematic sections contain case studies from landmark research that directly integrates engineering innovation with technically rigorous methods from the social sciences. Each case study describes the design, evaluation, and/or scaling of a technology in the field and follows a single form, with common elements and discussion questions, to create continuity and pedagogical consistency. Together, they highlight successful solutions to development challenges, while also analyzing the rarely discussed failures. The book concludes by reiterating the core principles of development engineering illustrated in the case studies, highlighting common challenges that engineers and scientists will face in designing technology interventions that sustainably accelerate economic development. Development Engineering provides, for the first time, a coherent intellectual framework for attacking the challenges of poverty and global climate change through the design of better technologies. It offers the rigorous discipline needed to channel the energy of a new generation of scientists and engineers toward advancing social justice and improved living conditions in low-resource communities around the world