419 research outputs found

    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    The effect of broadband noise on dynamic decision-making and the moderators that influence this effect

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    Noise and workload are both stressors. Stressors are known to affect cognitive performance. While the effect of workload on cognition is widely known, the effect of noise is less understood. Broadband noise at moderate levels (<85 dBA) is typical in many workplaces. Dynamic decision-making (DDM), a complex cognitive task, is required in many workplace settings where moderate broadband noise is present. Understanding how stressors such as noise affect DDM is essential, especially in safety critical professions such as aviation and emergency response. Therefore, the aim of the present research was to understand the effect of moderate broadband noise on DDM and the moderators that can influence the extent of that effect. Study 1, the first of the three studies, was a systematic review for the effect of moderate broadband noise on cognition such as reaction time, attention, short-term memory, long-term memory and high(er)-order cognitive tasks such as DDM. The findings showed that no previous studies investigated the effect of moderate broadband noise on DDM. Study 2, the first of two empirical studies examined the link between noise at 75 dBA, sex, workload, and session on DDM (performance and learning). Study 3 introduced the moderator of financial incentive and additional instructions. The results indicated females’ performance in DDM was affected by noise at low workload, but not high workload. Males were overall unaffected by noise regardless of the workload level. In terms of learning, noise initially impaired females’ performance, however this was overcome in Day 2. The added instruction had the same positive effect on learning performance, as it neutralised the noise effect. Monetary incentives did not moderate the noise stressor. These results highlight the detrimental effect of the stressor noise on DDM, and how its effect on sex can be offset by clear training instructions. The effect of noise can be beneficial to performance in the presence of another stressor, such as high workload, which is supported by theories such as Arousal Theory and Maximal Adaptability Theory. From applied perspective, this finding implies that noise can be a tool to facilitate performance in high workload

    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

    The influence of vision on the perceptual compensation for reverberation in simulated environments

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    In typical listening environments, auditory signals arrive at the ear as a fusion of the direct energy from sound sources and the indirect reflections via reverberation. The listener thus cannot directly access the source and reverberation components individually, highlighting that the perceptual separation of these components can be subject to ambiguity. Accurate expectations of reverberation have been shown to reduce such ambiguity. The visible features of the physical environment (e.g., spatial and surface properties) can reveal aspects of reverberation that inform such expectations, suggesting an inferential role of vision in disambiguating the source and reverberation components. The aim of this thesis was to evaluate the degree to which visual information from simulated environments can affect the expectations of reverberation to consequently improve judgements of sound sources. To investigate this aim, we conducted three behavioural studies that assessed perception in audiovisual environments via online simulations created from a database of real-world locations. Chapter 3 assessed whether visual cues to the environment could inform of the reverberant properties of physical locations in an audiovisual congruence task. The results indicated a greater impression of congruence when reverberant cues were identical or similar to those represented by the depicted environment, demonstrating a capacity for vision to inform meaningful expectations of reverberation. Chapter 4 evaluated the degree to which vision contributed to the identification of speech sources within reverberation by prior exposure to visual environments. We found that exposure to the visual environment had hardly any effect on improving the identification of reverberant speech sources in this context. Chapter 5 investigated if a concurrent visual depiction of the environment would affect the tendency for estimates of sound source duration to be consistent despite varying reverberation. The results showed that source duration estimates were influenced by the degree of reverberation present, and were seemingly unaffected by any visual exposure. Taken together, the findings of this thesis suggest that scene understanding from vision contributes to the overall spatial understanding of environments and their reverberant properties, but appears to contribute little to enhancing the perceptual separation of source and reverberation components used to improve judgements of auditory sources

    The Fifteenth Marcel Grossmann Meeting

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    The three volumes of the proceedings of MG15 give a broad view of all aspects of gravitational physics and astrophysics, from mathematical issues to recent observations and experiments. The scientific program of the meeting included 40 morning plenary talks over 6 days, 5 evening popular talks and nearly 100 parallel sessions on 71 topics spread over 4 afternoons. These proceedings are a representative sample of the very many oral and poster presentations made at the meeting.Part A contains plenary and review articles and the contributions from some parallel sessions, while Parts B and C consist of those from the remaining parallel sessions. The contents range from the mathematical foundations of classical and quantum gravitational theories including recent developments in string theory, to precision tests of general relativity including progress towards the detection of gravitational waves, and from supernova cosmology to relativistic astrophysics, including topics such as gamma ray bursts, black hole physics both in our galaxy and in active galactic nuclei in other galaxies, and neutron star, pulsar and white dwarf astrophysics. Parallel sessions touch on dark matter, neutrinos, X-ray sources, astrophysical black holes, neutron stars, white dwarfs, binary systems, radiative transfer, accretion disks, quasars, gamma ray bursts, supernovas, alternative gravitational theories, perturbations of collapsed objects, analog models, black hole thermodynamics, numerical relativity, gravitational lensing, large scale structure, observational cosmology, early universe models and cosmic microwave background anisotropies, inhomogeneous cosmology, inflation, global structure, singularities, chaos, Einstein-Maxwell systems, wormholes, exact solutions of Einstein's equations, gravitational waves, gravitational wave detectors and data analysis, precision gravitational measurements, quantum gravity and loop quantum gravity, quantum cosmology, strings and branes, self-gravitating systems, gamma ray astronomy, cosmic rays and the history of general relativity

    CLARIN

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    The book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium

    Vocal emotions on the brain: the role of acoustic parameters and musicality

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    The human voice is a powerful transmitter of emotions. This dissertation addresses three main gaps in the field of vocal emotion perception. The first is the quantification of the relative contribution of fundamental frequency (F0) and timbre cues to the perception of different emotions and their associated electrophysiological correlates. Using parameter-specific voice morphing, the results show that both F0 and timbre carry unique information that allow emotional inferences, although F0 seems to be relatively more important overall. The electrophysiological data revealed F0- and timbre-specific modulations in several ERP components, such as the P200 and the N400. Second, it was explored how musicality affects the processing of emotional voice cues, by providing a review on the literature linking musicality to emotion perception and subsequently showing that musicians have a benefit in vocal emotion perception compared to non-musicians. The present data offer original insight into the special role of pitch cues: musicians outperformed non-musicians when emotions were expressed by the pitch contour only, but not when they were expressed by vocal timbre. Although the electrophysiological patterns were less conclusive, they imply that musicality may modulate brain responses to vocal emotions. Third, this work provides a critical reflection on parameter-specific voice morphing and its suitability to study the processing of vocal emotions. Distortions in voice naturalness resulting from extreme acoustic manipulations were identified as one of the major threats to the ecological validity of the stimulus material produced with this technique. However, the results suggested that while voice morphing does affect the perceived naturalness of stimuli, behavioral measures of emotion perception were found to be remarkably robust against these distortions. Thus, the present data advocate parameter-specific voice morphing as a valid tool for vocal emotional research

    Conference Proceedings of the Euroregio / BNAM 2022 Joint Acoustic Conference

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    Introduction to Psycholiguistics

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