Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.Uno de los principales problemas de la interacción de los robots autónomos es el conocimiento de la escena. El reconocimiento es fundamental para solventar este problema y permitir a los robots interactuar en un escenario no controlado. En este documento, presentamos una aplicación práctica de captura del objeto, normalización y clasificación de señales triangulares y circulares. El sistema es introducido en el robot Aibo de Sony para mejorar el comportamiento de la interacción del robot. La metodología presentada ha sido testeada en simulaciones y problemas de categorización reales, como es la clasificación de señales de tráfico, con resultados muy prometedores.One of the main problems of autonomous robots interaction is the scene knowledge. Recognition is concerned to deal with this problem and to allow robots to interact in uncontrolled environments. In this paper, we present a practical application for object fitting, normalization and classification of triangular and circular signs. The system is introduced in the Aibo robot of Sony to increase the robot interaction behaviour. The presented methodology has been tested in real simulations and categorization problems, as the traffic signs classification, with very promising results.Nota: Aquest document conté originàriament altre material i/o programari només consultable a la Biblioteca de Ciència i Tecnologia

Cultural and linguistic struggles and solidarities of Emirati learners in online classes during the COVID-19 pandemic

The ongoing global COVID-19 pandemic has caused unprecedented shifts in higher education worldwide, with some nations more adversely affected than others. Since the onset of the crisis, almost all education abruptly moved to ‘emergency remote teaching and learning’. While the United Arab Emirates has been praised for its swift and effective responses, unique cultural and linguistic dynamics in this region present additional challenges for teaching and learning. This article presents empirical data from a qualitative phenomenological case study investigating female Emirati university students’ ( n = 69) perspectives on the use of video cameras and microphones in online classes. Students’ reflective writing and researcher observations in autumn 2020 revealed discomfort using video cameras and microphones due to a range of cultural and linguistic factors. Such factors include Islamic beliefs relating to modesty, home as a gendered space, noise considerations, concerns about privacy, struggles with language in their English-medium instruction university and fear of judgement from peers. Data are interpreted thematically using intersectionality together with Goffman’s theories of everyday interaction, stigma and relative deprivation, through which complexities of learner identities are explored. Practical suggestions are made on ways to adapt online learning to better suit the cultural and sociolinguistic realities of periphery and Global South contexts. It is argued that greater efforts need to be made toward inclusion of marginalized learners during the COVID-19 period

A study of the design expertise for plants handling hazardous materials

A study of the design expertise for plants handling hazardous material

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

Information Seeking from Web-Based Resources: Sensemaking Strategies and Implications for Interaction Design

The internet has made an enormous volume of information available, and there has been substantial research into how users look for information. However, there has been much less research about how they make sense of what they find, and how sensemaking is shaped by the tasks they are trying to achieve. This research addresses that gap, with empirical studies of sensemaking during web-based information tasks. Two main studies are presented, which aimed to expose the relationship between information seeking and information comprehension and use. The first study explored the actions of experienced information processors (in this case, doctoral students) as they undertook research-related web-based tasks related to their own work. The second study observed experienced users as they undertook an unfamiliar topic comprehension task. In both studies participants were encouraged to ‘think-aloud’ as they completed web-based tasks. Audio-recording was used in Study-1 with video-recording in Study-2. In addition to the task session, background questionnaires and sample interviews were applied. A detailed, iterative inductive analysis was undertaken for each study. The analysis produced a framework that models the users’ process in terms of five categories of information interactions: seeking, evaluating for selection, evaluating for use, compilation, and planning. A range of visual representations were developed to capture the user sessions, expressing facets such as how resources were used over time and in combination, and the sequences of user behaviours. Attention was given to the use of representation throughout this process. Sensemaking goals and strategies were inferred from users’ behaviours and utterances, and were related to their activity and output. The intertwined nature of information seeking and sensemaking activity was revealed, and planning (not addressed in previous literature) was identified as a significant behaviour that drives strategy and binds the other behaviours to the task-in-hand. These findings have implications for interaction design and for tools to support sensemaking

The Road to General Intelligence

Humans have always dreamed of automating laborious physical and intellectual tasks, but the latter has proved more elusive than naively suspected. Seven decades of systematic study of Artificial Intelligence have witnessed cycles of hubris and despair. The successful realization of General Intelligence (evidenced by the kind of cross-domain flexibility enjoyed by humans) will spawn an industry worth billions and transform the range of viable automation tasks.The recent notable successes of Machine Learning has lead to conjecture that it might be the appropriate technology for delivering General Intelligence. In this book, we argue that the framework of machine learning is fundamentally at odds with any reasonable notion of intelligence and that essential insights from previous decades of AI research are being forgotten. We claim that a fundamental change in perspective is required, mirroring that which took place in the philosophy of science in the mid 20th century. We propose a framework for General Intelligence, together with a reference architecture that emphasizes the need for anytime bounded rationality and a situated denotational semantics. We given necessary emphasis to compositional reasoning, with the required compositionality being provided via principled symbolic-numeric inference mechanisms based on universal constructions from category theory. • Details the pragmatic requirements for real-world General Intelligence. • Describes how machine learning fails to meet these requirements. • Provides a philosophical basis for the proposed approach. • Provides mathematical detail for a reference architecture. • Describes a research program intended to address issues of concern in contemporary AI. The book includes an extensive bibliography, with ~400 entries covering the history of AI and many related areas of computer science and mathematics.The target audience is the entire gamut of Artificial Intelligence/Machine Learning researchers and industrial practitioners. There are a mixture of descriptive and rigorous sections, according to the nature of the topic. Undergraduate mathematics is in general sufficient. Familiarity with category theory is advantageous for a complete understanding of the more advanced sections, but these may be skipped by the reader who desires an overall picture of the essential concepts This is an open access book

Trust in Public Health within Black African and Caribbean Communities: Grounded Theory as applied to the COVID-19 Vaccine Uptake

Trust plays a critical role in public health, encouraging community unity and cooperation with health initiatives. Despite substantial research on trust, its relationship with race and power dynamics remains under-explored. To address this research gap, the study focused on exploring the relationship between race and trust, particularly within Black African and Caribbean populations that have historically faced discrimination and exclusion in society and healthcare. The study aimed to understand the unique experiences and perspectives of these communities, especially in the context of the COVID-19 pandemic and vaccination efforts in the UK. The study utilised a critical grounded theory methodology, influenced by Community Psychology values, to conduct interviews with 15 self-identified Black African and Caribbean individuals. The discussion explored their public health experiences and their perceptions of trust, with emphasis on the COVID-19 pandemic. The study developed an ecological model to conceptualise the dynamic nature of trust in public health within these communities. The model highlights the influence of social power and structural societal factors, acknowledging that historical marginalisation, colonial injustices, and political distrust contribute to avoidance and scepticism towards public health measures. It proposes that trust in public health is community-driven, highlighting the role of communities in fostering trust, improving health outcomes, and ensuring care continuity and safety. The research advocates for tailored multi-level interventions centred on community engagement and trust to effect enduring change in health outcomes for these communities. It calls for a paradigm shift in public health to promote research, training, and clinical approaches that address systemic biases and encourage the decolonisation of health-related knowledge. The study's implications extend to public health policy, clinical practice, training, and future research. In conclusion, the study underscores the importance of consistent, trustworthy, and transparent actions and accountable processes in public health initiatives, fostering partnerships with marginalised communities to promote equitable and inclusive health practices