218 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Brain Computations and Connectivity [2nd edition]

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    This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations. Brain Computations and Connectivity is about how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed. The aim of this book is to elucidate what is computed in different brain systems; and to describe current biologically plausible computational approaches and models of how each of these brain systems computes. Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions. This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed, and updates by much new evidence including the connectivity of the human brain the earlier book: Rolls (2021) Brain Computations: What and How, Oxford University Press. Brain Computations and Connectivity will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics

    Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

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    Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity

    5th International Conference on Advanced Research Methods and Analytics (CARMA 2023)

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    Research methods in economics and social sciences are evolving with the increasing availability of Internet and Big Data sources of information. As these sources, methods, and applications become more interdisciplinary, the 5th International Conference on Advanced Research Methods and Analytics (CARMA) is a forum for researchers and practitioners to exchange ideas and advances on how emerging research methods and sources are applied to different fields of social sciences as well as to discuss current and future challenges.Martínez Torres, MDR.; Toral Marín, S. (2023). 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023). Editorial Universitat Politècnica de València. https://doi.org/10.4995/CARMA2023.2023.1700

    Multiple View Texture Mapping: A Rendering Approach Designed for Driving Simulation

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    Simulation provides a safe and controlled environment ideal for human testing [49, 142, 120]. Simulation of real environments has reached new heights in terms of photo-realism. Often, a team of professional graphical artists would have to be hired to compete with modern commercial simulators. Meanwhile, machine vision methods are currently being developed that attempt to automatically provide geometrically consistent and photo-realistic 3D models of real scenes [189, 139, 115, 19, 140, 111, 132]. Often the only requirement is a set of images of that scene. A road engineer wishing to simulate the environment of a real road for driving experiments could potentially use these tools. This thesis develops a driving simulator that uses machine vision methods to reconstruct a real road automatically. A computer graphics method called projective texture mapping is applied to enhance the photo-realism of the 3D models[144, 43]. This essentially creates a virtual projector in the 3D environment to automatically assign image coordinates to a 3D model. These principles are demonstrated using custom shaders developed for an OpenGL rendering pipeline. Projective texture mapping presents a list of challenges to overcome, these include reverse projection and projection onto surfaces not immediately in front of the projector [53]. A significant challenge was the removal of dynamic foreground objects. 3D reconstruction systems create 3D models based on static objects captured in images. Dynamic objects are rarely reconstructed. Projective texture mapping of images, including these dynamic objects, can result in visual artefacts. A workflow is developed to resolve this, resulting in videos and 3D reconstructions of streets with no moving vehicles on the scene. The final simulator using 3D reconstruction and projective texture mapping is then developed. The rendering camera had a motion model introduced to enable human interaction. The final system is presented, experimentally tested, and future potential works are discussed

    Trusted Artificial Intelligence in Manufacturing; Trusted Artificial Intelligence in Manufacturing

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    The successful deployment of AI solutions in manufacturing environments hinges on their security, safety and reliability which becomes more challenging in settings where multiple AI systems (e.g., industrial robots, robotic cells, Deep Neural Networks (DNNs)) interact as atomic systems and with humans. To guarantee the safe and reliable operation of AI systems in the shopfloor, there is a need to address many challenges in the scope of complex, heterogeneous, dynamic and unpredictable environments. Specifically, data reliability, human machine interaction, security, transparency and explainability challenges need to be addressed at the same time. Recent advances in AI research (e.g., in deep neural networks security and explainable AI (XAI) systems), coupled with novel research outcomes in the formal specification and verification of AI systems provide a sound basis for safe and reliable AI deployments in production lines. Moreover, the legal and regulatory dimension of safe and reliable AI solutions in production lines must be considered as well. To address some of the above listed challenges, fifteen European Organizations collaborate in the scope of the STAR project, a research initiative funded by the European Commission in the scope of its H2020 program (Grant Agreement Number: 956573). STAR researches, develops, and validates novel technologies that enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, the project researches and delivers approaches that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. This book is co-authored by the STAR consortium members and provides a review of technologies, techniques and systems for trusted, ethical, and secure AI in manufacturing. The different chapters of the book cover systems and technologies for industrial data reliability, responsible and transparent artificial intelligence systems, human centered manufacturing systems such as human-centred digital twins, cyber-defence in AI systems, simulated reality systems, human robot collaboration systems, as well as automated mobile robots for manufacturing environments. A variety of cutting-edge AI technologies are employed by these systems including deep neural networks, reinforcement learning systems, and explainable artificial intelligence systems. Furthermore, relevant standards and applicable regulations are discussed. Beyond reviewing state of the art standards and technologies, the book illustrates how the STAR research goes beyond the state of the art, towards enabling and showcasing human-centred technologies in production lines. Emphasis is put on dynamic human in the loop scenarios, where ethical, transparent, and trusted AI systems co-exist with human workers. The book is made available as an open access publication, which could make it broadly and freely available to the AI and smart manufacturing communities

    History of Construction Cultures Volume 1

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    History of Construction Cultures Volume 1 contains papers presented at the 7ICCH – Seventh International Congress on Construction History, held at the Lisbon School of Architecture, Portugal, from 12 to 16 July, 2021. The conference has been organized by the Lisbon School of Architecture (FAUL), NOVA School of Social Sciences and Humanities, the Portuguese Society for Construction History Studies and the University of the Azores. The contributions cover the wide interdisciplinary spectrum of Construction History and consist on the most recent advances in theory and practical case studies analysis, following themes such as: - epistemological issues; - building actors; - building materials; - building machines, tools and equipment; - construction processes; - building services and techniques ; -structural theory and analysis ; - political, social and economic aspects; - knowledge transfer and cultural translation of construction cultures. Furthermore, papers presented at thematic sessions aim at covering important problematics, historical periods and different regions of the globe, opening new directions for Construction History research. We are what we build and how we build; thus, the study of Construction History is now more than ever at the centre of current debates as to the shape of a sustainable future for humankind. Therefore, History of Construction Cultures is a critical and indispensable work to expand our understanding of the ways in which everyday building activities have been perceived and experienced in different cultures, from ancient times to our century and all over the world

    Fire performance of residential shipping containers designed with a shaft wall system

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    seven story building made of shipping containers is planned to be built in Barcelona, Spain. This study mainly aimed to evaluate the fire performance of one of these residential shipping containers whose walls and ceiling will have a shaft wall system installed. The default assembly consisted of three fire resistant gypsum boards for vertical panels and a mineral wool layer within the framing system. This work aimed to assess if system variants (e.g. less gypsum boards, no mineral wool layer) could still be adequate considering fire resistance purposes. To determine if steel temperatures would attain a predetermined temperature of 300-350ÂşC (a temperature value above which mechanical properties of steel start to change significantly) the temperature evolution within the shaft wall system and the corrugated steel profile of the container was analysed under different fire conditions. Diamonds simulator (v. 2020; Buildsoft) was used to perform the heat transfer analysis from the inside surface of the container (where the fire source was present) and within the shaft wall and the corrugated profile. To do so gas temperatures near the walls and the ceiling were required, so these temperatures were obtained from two sources: (1) The standard fire curve ISO834; (2) CFD simulations performed using the Fire Dynamics Simulator (FDS). Post-flashover fire scenarios were modelled in FDS taking into account the type of fuel present in residential buildings according to international standards. The results obtained indicate that temperatures lower than 350ÂşC were attained on the ribbed steel sheet under all the tested heat exposure conditions. When changing the assembly by removing the mineral wool layer, fire resistance was found to still be adequate. Therefore, under the tested conditions, the structural response of the containers would comply with fire protection standards, even in the case where insulation was reduced.Postprint (published version
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