960 research outputs found

    Transformative interventions. An ecological-enactive approach to art practices

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    Starting from an ecological-enactive approach to human cognition (Rietveld, Kiverstein 2014) I have articulated a series of transformative interventions whose purpose is to explore how art practices can reorganize our form of life (Noë, 2015; Rietveld, 2019). To do this, I discuss how a plethora of heterogeneous tools traceable in the performing arts, such as masks, puppets, and hybrid costumes, can help us, through what I call monstrous practices, to explore imaginative dimensions that our own bodies "cannot afford." This is the core of the transformative chain that I will define monster-monstrous-Monster: we feed imaginative “monsters” to become “monstrous”– that is, to pool and cross-fertilize our abilities – to confront the "Monsters" in our lives. My main interest is in analyzing how it is possible to create or collect new affordances so as to transfigure one's repertoire of possibilities and transform a shared practice. Each transformative intervention is not only defined through written words but is also developed through unorthodox sociomaterial invitations, usually not used in philosophical practice: storyboards, visual ethnographies, performance projects, and installations, which I will define more properly through an enriched notion of real-life thinking model (Rietveld; RAAAF)

    Internet and Biometric Web Based Business Management Decision Support

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    Internet and Biometric Web Based Business Management Decision Support MICROBE MOOC material prepared under IO1/A5 Development of the MICROBE personalized MOOCs content and teaching materials Prepared by: A. Kaklauskas, A. Banaitis, I. Ubarte Vilnius Gediminas Technical University, Lithuania Project No: 2020-1-LT01-KA203-07810

    The universe without us: a history of the science and ethics of human extinction

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    This dissertation consists of two parts. Part I is an intellectual history of thinking about human extinction (mostly) within the Western tradition. When did our forebears first imagine humanity ceasing to exist? Have people always believed that human extinction is a real possibility, or were some convinced that this could never happen? How has our thinking about extinction evolved over time? Why do so many notable figures today believe that the probability of extinction this century is higher than ever before in our 300,000-year history on Earth? Exploring these questions takes readers from the ancient Greeks, Persians, and Egyptians, through the 18th-century Enlightenment, past scientific breakthroughs of the 19th century like thermodynamics and evolutionary theory, up to the Atomic Age, the rise of modern environmentalism in the 1970s, and contemporary fears about climate change, global pandemics, and artificial general intelligence (AGI). Part II is a history of Western thinking about the ethical and evaluative implications of human extinction. Would causing or allowing our extinction be morally right or wrong? Would our extinction be good or bad, better or worse compared to continuing to exist? For what reasons? Under which conditions? Do we have a moral obligation to create future people? Would past “progress” be rendered meaningless if humanity were to die out? Does the fact that we might be unique in the universe—the only “rational” and “moral” creatures—give us extra reason to ensure our survival? I place these questions under the umbrella of Existential Ethics, tracing the development of this field from the early 1700s through Mary Shelley’s 1826 novel The Last Man, the gloomy German pessimists of the latter 19th century, and post-World War II reflections on nuclear “omnicide,” up to current-day thinkers associated with “longtermism” and “antinatalism.” In the dissertation, I call the first history “History #1” and the second “History #2.” A main thesis of Part I is that Western thinking about human extinction can be segmented into five distinction periods, each of which corresponds to a unique “existential mood.” An existential mood arises from a particular set of answers to fundamental questions about the possibility, probability, etiology, and so on, of human extinction. I claim that the idea of human extinction first appeared among the ancient Greeks, but was eclipsed for roughly 1,500 years with the rise of Christianity. A central contention of Part II is that philosophers have thus far conflated six distinct types of “human extinction,” each of which has its own unique ethical and evaluative implications. I further contend that it is crucial to distinguish between the process or event of Going Extinct and the state or condition of Being Extinct, which one should see as orthogonal to the six types of extinction that I delineate. My aim with the second part of the book is to not only trace the history of Western thinking about the ethics of annihilation, but lay the theoretical groundwork for future research on the topic. I then outline my own views within “Existential Ethics,” which combine ideas and positions to yield a novel account of the conditions under which our extinction would be bad, and why there is a sense in which Being Extinct might be better than Being Extant, or continuing to exist

    PhD students´day FMST 2023

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    The authors gave oral presentations of their work online as part of a Doctoral Students’ Day held on 15 June 2023, and they reflect the challenging work done by the students and their supervisors in the fields of metallurgy, materials engineering and management. There are 82 contributions in total, covering a range of areas – metallurgical technology, thermal engineering and fuels in industry, chemical metallurgy, nanotechnology, materials science and engineering, and industrial systems management. This represents a cross-section of the diverse topics investigated by doctoral students at the faculty, and it will provide a guide for Master’s graduates in these or similar disciplines who are interested in pursuing their scientific careers further, whether they are from the faculty here in Ostrava or engineering faculties elsewhere in the Czech Republic. The quality of the contributions varies: some are of average quality, but many reach a standard comparable with research articles published in established journals focusing on disciplines of materials technology. The diversity of topics, and in some cases the excellence of the contributions, with logical structure and clearly formulated conclusions, reflect the high standard of the doctoral programme at the faculty.Ostrav

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments

    Real-time Ultrasound Signals Processing: Denoising and Super-resolution

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    Ultrasound acquisition is widespread in the biomedical field, due to its properties of low cost, portability, and non-invasiveness for the patient. The processing and analysis of US signals, such as images, 2D videos, and volumetric images, allows the physician to monitor the evolution of the patient's disease, and support diagnosis, and treatments (e.g., surgery). US images are affected by speckle noise, generated by the overlap of US waves. Furthermore, low-resolution images are acquired when a high acquisition frequency is applied to accurately characterise the behaviour of anatomical features that quickly change over time. Denoising and super-resolution of US signals are relevant to improve the visual evaluation of the physician and the performance and accuracy of processing methods, such as segmentation and classification. The main requirements for the processing and analysis of US signals are real-time execution, preservation of anatomical features, and reduction of artefacts. In this context, we present a novel framework for the real-time denoising of US 2D images based on deep learning and high-performance computing, which reduces noise while preserving anatomical features in real-time execution. We extend our framework to the denoise of arbitrary US signals, such as 2D videos and 3D images, and we apply denoising algorithms that account for spatio-temporal signal properties into an image-to-image deep learning model. As a building block of this framework, we propose a novel denoising method belonging to the class of low-rank approximations, which learns and predicts the optimal thresholds of the Singular Value Decomposition. While previous denoise work compromises the computational cost and effectiveness of the method, the proposed framework achieves the results of the best denoising algorithms in terms of noise removal, anatomical feature preservation, and geometric and texture properties conservation, in a real-time execution that respects industrial constraints. The framework reduces the artefacts (e.g., blurring) and preserves the spatio-temporal consistency among frames/slices; also, it is general to the denoising algorithm, anatomical district, and noise intensity. Then, we introduce a novel framework for the real-time reconstruction of the non-acquired scan lines through an interpolating method; a deep learning model improves the results of the interpolation to match the target image (i.e., the high-resolution image). We improve the accuracy of the prediction of the reconstructed lines through the design of the network architecture and the loss function. %The design of the deep learning architecture and the loss function allow the network to improve the accuracy of the prediction of the reconstructed lines. In the context of signal approximation, we introduce our kernel-based sampling method for the reconstruction of 2D and 3D signals defined on regular and irregular grids, with an application to US 2D and 3D images. Our method improves previous work in terms of sampling quality, approximation accuracy, and geometry reconstruction with a slightly higher computational cost. For both denoising and super-resolution, we evaluate the compliance with the real-time requirement of US applications in the medical domain and provide a quantitative evaluation of denoising and super-resolution methods on US and synthetic images. Finally, we discuss the role of denoising and super-resolution as pre-processing steps for segmentation and predictive analysis of breast pathologies

    The Benefits of Extended Reality for Technical Communication : Utilizing XR for Maintenance Documentation Creation and Delivery

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    The main goal of this dissertation is to explore the benefits of extended reality for technical communication. Both of these fields offer opportunities and also pose challenges to each other, and this dissertation provides insight into this relationship. The research was initiated by the author’s personal interest in both fields and also human-technology interaction and user needs in general. Even though this is an academic dissertation, it is first and foremost a practitioner’s view of these evolving technologies and their potential uses in industry and, specifically, in industrial maintenance and technical communication. Under the umbrella of extended reality and technical communication, this dissertation focuses on two main themes. The first part studies virtual reality as a technology to facilitate collaboration and digital content creation for technical documentation in industrial companies, and the second part explores the possibilities of augmented reality and smart glasses as a delivery channel for maintenance instructions. The developed concepts were tested by domain experts in user tests. The overall results of testing were positive, and domain experts expressed enthusiasm toward the concepts and technologies in general. The technical documentation process is an inherently collaborative process involving stakeholders from different teams and organizations, and virtual reality was evaluated to have a positive effect on that process, especially in the case of globally scattered teams. The developed tools were also rated positively for digital content creation. Therefore, virtual reality offers many benefits for technical documentation creation, an area where it has not been utilized until now. On the augmented reality side, domain experts were generally enthusiastic about the use of smart glasses even though the technologies are not yet mature enough for field use in industrial maintenance. Furthermore, the results show that content created in the technical communications industry standard, DITA XML, works well when delivered to smart glasses, and the same content can be single sourced to other delivery channels. The use of DITA XML, therefore, eliminates the need to tailor content for each delivery channel separately, and offers an effective way to create and update content for AR applications in industrial companies. This, in turn, can advance the use of AR technologies and related devices in field operations in industrial companies. In conclusion, the findings of this dissertation show that the fields of technical communication and extended reality have a significant amount of synergy. In this dissertation I establish use cases and guidelines for these areas
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