2,379 research outputs found

    The representational systems for object and agent in new world monkeys

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    Representing the environment in its most basic components, namely objects and agents, is a fundamental feature of human cognition which we may share to different extents with nonhuman animals. This thesis explored some manifestations of these abilities in two new world monkey species, squirrel monkeys and capuchin monkeys. We first investigated squirrel monkeys’ ability of individuating object by spatiotemporal and property/kind information with a “magic box” paradigm using both manual search and looking time measures (chapter 2). The squirrel monkeys failed both tasks with both measures, whereas capuchin monkeys showed individuating competence with exactly the same tasks and apparatus in a previous study. Chapter 3 tested and explored the possibility that squirrel monkeys failed the “magic box” tasks that capuchin monkeys passed because they acted so fast that they didn’t form or use this type of object representations to guide their actions. In fact, in a touchscreen-based object tracking/catching game (Whack-a-cricket task), the squirrel monkeys were slower to “catch” a moving “cricket” compared to capuchin monkeys. In chapter 4, we tested squirrel monkeys with another individuation task that included two separate barriers instead of a single box. The squirrel monkeys preferred to search the last- visited-location first when either spatiotemporal or property/kind information suggested that only one object was present. This preference disappeared when either information indicated that there were two objects, one behind each barrier. We conclude that squirrel monkeys are therefore able to individuate objects using both kinds of information when tested with an appropriate task. In the last chapter, we investigated whether capuchin monkeys can locate a causal agent based on an event that he initiated from a hidden location. Capuchin monkeys located the hidden agent when they saw an object pushed, raked, rolled, or thrown across a table seemingly by the experimenter behind one of two screens (agentive trials), but not when they saw an object roll down a ramp or fall off a block after a shake of the table (arbitrary control trials) that contained no information about the agent’ location. This result suggests capuchin monkeys can use motion events to infer the location of a causal agent, an ability also demonstrated by human infants. Taken together, our studies show that squirrel monkeys and capuchin monkeys have some core abilities to represent some of the fundamental properties of objects and agents, comparable to those demonstrated by human infants, which supports the core knowledge view that such representational systems may have a long evolutionary history and exist widely in primates

    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

    More-than-words: Reconceptualising Two-year-old Children’s Onto-epistemologies Through Improvisation and the Temporal Arts

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    This thesis project takes place at a time of increasing focus upon two-year-old children and the words they speak. On the one hand there is a mounting pressure, driven by the school readiness agenda, to make children talk as early as possible. On the other hand, there is an increased interest in understanding children’s communication in order to create effective pedagogies. More-than-words (MTW) examines an improvised art-education practice that combines heterogenous elements: sound, movement and materials (such as silk, string, light) to create encounters for young children, educators and practitioners from diverse backgrounds. During these encounters, adults adopt a practice of stripping back their words in order to tune into the polyphonic ways that children are becoming-with the world. For this research-creation, two MTW sessions for two-year-old children and their carers took place in a specially created installation. These sessions were filmed on a 360˚ camera, nursery school iPad and on a specially made child-friendly Toddler-cam (Tcam) that rolled around in the installation-event with the children. Through using the frameless technology of 360˚ film, I hoped to make tangible the relation and movement of an emergent and improvised happening and the way in which young children operate fluidly through multiple modes. Travelling with posthuman, Deleuzio-Guattarian and feminist vital material philosophy, I wander and wonder speculatively through practice, memory, and film data as a bag lady, a Haraway-ian writer/artist/researcher-creator who resists the story of the wordless child as lacking and tragic; the story that positions the word as heroic. Instead, through returning to the uncertainty of improvisation, I attempt to tune into the savage, untamed and wild music of young children’s animistic onto-epistemologies

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Exploring the effects of robotic design on learning and neural control

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    The ongoing deep learning revolution has allowed computers to outclass humans in various games and perceive features imperceptible to humans during classification tasks. Current machine learning techniques have clearly distinguished themselves in specialized tasks. However, we have yet to see robots capable of performing multiple tasks at an expert level. Most work in this field is focused on the development of more sophisticated learning algorithms for a robot's controller given a largely static and presupposed robotic design. By focusing on the development of robotic bodies, rather than neural controllers, I have discovered that robots can be designed such that they overcome many of the current pitfalls encountered by neural controllers in multitask settings. Through this discovery, I also present novel metrics to explicitly measure the learning ability of a robotic design and its resistance to common problems such as catastrophic interference. Traditionally, the physical robot design requires human engineers to plan every aspect of the system, which is expensive and often relies on human intuition. In contrast, within the field of evolutionary robotics, evolutionary algorithms are used to automatically create optimized designs, however, such designs are often still limited in their ability to perform in a multitask setting. The metrics created and presented here give a novel path to automated design that allow evolved robots to synergize with their controller to improve the computational efficiency of their learning while overcoming catastrophic interference. Overall, this dissertation intimates the ability to automatically design robots that are more general purpose than current robots and that can perform various tasks while requiring less computation.Comment: arXiv admin note: text overlap with arXiv:2008.0639

    Subjective Excess: Aesthetics, Character, and Non-Normative Perspectives in Serial Television After 2000

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    This dissertation aims to fill gaps in contemporary television scholarship with regards to aesthetics and character subjectivity. By analyzing eight series that have all aired after 2000, there is a marked trend in series that use an excessive visual and aural style to not only differentiate themselves from other programming, but also to explore non-normative perspectives. Now more willing to explore previously taboo topics such as mental health, addiction, illness, and trauma, the shows featured in this dissertation show how a seemingly excessive televisual aesthetic works with television’s seriality to create narrative complexity and generate character development. Chapters are arranged by mode of production with the first chapter focusing on the series Grey’s Anatomy and Hannibal as a means of exploring the production and distribution practices surrounding network TV. The second chapter examines the basic cable series Crazy Ex-Girlfriend and Legion and posits how the narrowcasting of cable allows for more nuanced character representations through aesthetics. In the third chapter, the impact HBO has had on the television medium is explored through Carnivàle and Euphoria. The final chapter looks at contemporary series The Boys and Unbreakable Kimmy Schmidt as a way to better understand how the medium’s production and distribution has shifted during the convergence era. Ultimately, this dissertation will argue that in addition to further explorations of aesthetics, television studies is in need of a medium specific vernacular for creating meaningful textual analyses that avoid an overreliance on cinematic terminology

    A new global media order? : debates and policies on media and mass communication at UNESCO, 1960 to 1980

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    Defence date: 24 June 2019Examining Board: Professor Federico Romero, European University Institute (Supervisor); Professor Corinna Unger, European University Institute (Second Reader); Professor Iris Schröder, Universität Erfurt (External Advisor); Professor Sandrine Kott, Université de GenèveThe 1970s, a UNESCO report claimed, would be the “communication decade”. UNESCO had started research on new means of mass communication for development purposes in the 1960s. In the 1970s, the issue evolved into a debate on the so-called “New World Information and Communication Order” (NWICO) and the democratisation of global media. It led UNESCO itself into a major crisis in the 1980s. My project traces a dual trajectory that shaped this global debate on transnational media. The first follows communications from being seen as a tool and goal of national development in the 1960s, to communications seen as catalyst for recalibrated international political, cultural and economic relations. The second relates to the recurrent attempts, and eventual failure, of various actors to engage UNESCO as a platform to promote a new global order. I take UNESCO as an observation post to study national ambitions intersecting with internationalist claims to universality, changing understandings of the role of media in development and international affairs, and competing visions of world order. Looking at the modes of this debate, the project also sheds light on the evolving practices of internationalism. Located in the field of a new international history, this study relates to the recent rediscovery of the “new order”-discourses of the 1970s as well as to the increasingly diversified literature on internationalism. With its focus on international communications and attempts at regulating them, it also contributes to an international media history in the late twentieth century. The emphasis on the role of international organisations as well as on voices from the Global South will make contributions to our understanding of the historic macro-processes of decolonisation, globalisation and the Cold War

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    A robotic platform for precision agriculture and applications

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    Agricultural techniques have been improved over the centuries to match with the growing demand of an increase in global population. Farming applications are facing new challenges to satisfy global needs and the recent technology advancements in terms of robotic platforms can be exploited. As the orchard management is one of the most challenging applications because of its tree structure and the required interaction with the environment, it was targeted also by the University of Bologna research group to provide a customized solution addressing new concept for agricultural vehicles. The result of this research has blossomed into a new lightweight tracked vehicle capable of performing autonomous navigation both in the open-filed scenario and while travelling inside orchards for what has been called in-row navigation. The mechanical design concept, together with customized software implementation has been detailed to highlight the strengths of the platform and some further improvements envisioned to improve the overall performances. Static stability testing has proved that the vehicle can withstand steep slopes scenarios. Some improvements have also been investigated to refine the estimation of the slippage that occurs during turning maneuvers and that is typical of skid-steering tracked vehicles. The software architecture has been implemented using the Robot Operating System (ROS) framework, so to exploit community available packages related to common and basic functions, such as sensor interfaces, while allowing dedicated custom implementation of the navigation algorithm developed. Real-world testing inside the university’s experimental orchards have proven the robustness and stability of the solution with more than 800 hours of fieldwork. The vehicle has also enabled a wide range of autonomous tasks such as spraying, mowing, and on-the-field data collection capabilities. The latter can be exploited to automatically estimate relevant orchard properties such as fruit counting and sizing, canopy properties estimation, and autonomous fruit harvesting with post-harvesting estimations.Le tecniche agricole sono state migliorate nel corso dei secoli per soddisfare la crescente domanda di aumento della popolazione mondiale. I recenti progressi tecnologici in termini di piattaforme robotiche possono essere sfruttati in questo contesto. Poiché la gestione del frutteto è una delle applicazioni più impegnative, a causa della sua struttura arborea e della necessaria interazione con l'ambiente, è stata oggetto di ricerca per fornire una soluzione personalizzata che sviluppi un nuovo concetto di veicolo agricolo. Il risultato si è concretizzato in un veicolo cingolato leggero, capace di effettuare una navigazione autonoma sia nello scenario di pieno campo che all'interno dei frutteti (navigazione interfilare). La progettazione meccanica, insieme all'implementazione del software, sono stati dettagliati per evidenziarne i punti di forza, accanto ad alcuni ulteriori miglioramenti previsti per incrementarne le prestazioni complessive. I test di stabilità statica hanno dimostrato che il veicolo può resistere a ripidi pendii. Sono stati inoltre studiati miglioramenti per affinare la stima dello slittamento che si verifica durante le manovre di svolta, tipico dei veicoli cingolati. L'architettura software è stata implementata utilizzando il framework Robot Operating System (ROS), in modo da sfruttare i pacchetti disponibili relativi a componenti base, come le interfacce dei sensori, e consentendo al contempo un'implementazione personalizzata degli algoritmi di navigazione sviluppati. I test in condizioni reali all'interno dei frutteti sperimentali dell'università hanno dimostrato la robustezza e la stabilità della soluzione con oltre 800 ore di lavoro sul campo. Il veicolo ha permesso di attivare e svolgere un'ampia gamma di attività agricole in maniera autonoma, come l'irrorazione, la falciatura e la raccolta di dati sul campo. Questi ultimi possono essere sfruttati per stimare automaticamente le proprietà più rilevanti del frutteto, come il conteggio e la calibratura dei frutti, la stima delle proprietà della chioma e la raccolta autonoma dei frutti con stime post-raccolta

    Navigation Sensor Stochastic Error Modeling and Nonlinear Estimation for Low-Cost Land Vehicle Navigation

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    The increasing use of low-cost inertial sensors in various mass-market applications necessitates their accurate stochastic modeling. Such task faces challenges due to outliers in the sensor measurements caused by internal and/or external factors. To optimize the navigation performance, robust estimation techniques are required to reduce the influence of outliers to the stochastic modeling process. The Generalized Method of Wavelet Moments (GMWM) and its Multi-signal extensions (MS-GMWM) represent the latest trend in the field of inertial sensor error stochastic analysis, they are capable of efficiently modeling the highly complex random errors displayed by low-cost and consumer-grade inertial sensors and provide very advantageous guarantees for the statistical properties of their estimation products. On the other hand, even though a robust version exists (RGMWM) for the single-signal method in order to protect the estimation process from the influence of outliers, their detection remains a challenging task, while such attribute has not yet been bestowed in the multi-signal approach. Moreover, the current implementation of the GMWM algorithm can be computationally intensive and does not provide the simplest (composite) model. In this work, a simplified implementation of the GMWM-based algorithm is presented along with techniques to reduce the complexity of the derived stochastic model under certain conditions. Also, it is shown via simulations that using the RGMWM every time, without the need for contamination existence confirmation, is a worthwhile trade-off between reducing the outlier effects and decreasing the estimator efficiency. Generally, stochastic modeling techniques, including the GMWM, make use of individual static signals for inference. However, it has been observed that when multiple static signal replicates are collected under the same conditions, they maintain the same model structure but exhibit variations in parameter values, a fact that called for the MS-GMWM. Here, a robust multi-signal method is introduced, based on the established GMWM framework and the Average Wavelet Variance (AWV) estimator, which encompasses two robustness levels: one for protection against outliers in each considered replicate and one to safeguard the estimation against the collection of signal replicates with significantly different behaviour than the majority. From that, two estimators are formulated, the Singly Robust AWV (SR-AWV) and the Doubly Robust (DR-AWV) and their model parameter estimation efficiency is confirmed under different data contamination scenarios in simulation and case studies. Furthermore, a hybrid case study is conducted that establishes a connection between model parameter estimation quality and implied navigation performance in those data contamination settings. Finally, the performance of the new technique is compared to the conventional Allan Variance in a land vehicle navigation experiment, where the inertial information is fused with an auxiliary source and vehicle movement constraints using the Extended and Unscented Kalman Filters (EKF/UKF). Notably, the results indicate that under linear-static conditions, the UKF with the new method provides a 16.8-17.3% improvement in 3D orientation compared to the conventional setting (AV with EKF), while the EKF gives a 7.5-9.7% improvement. Also, in dynamic conditions (i.e., turns), the UKF demonstrates an 14.7-17.8% improvement in horizontal positioning and an 11.9-12.5% in terms of 3D orientation, while the EKF has an 8.3-12.8% and an 11.4-11.7% improvement respectively. Overall, the UKF appears to perform better but has a significantly higher computational load compared to the EKF. Hence, the EKF appears to be a more realistic option for real-time applications such as autonomous vehicle navigation
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