723 research outputs found

    An examination of the verbal behaviour of intergroup discrimination

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    This thesis examined relationships between psychological flexibility, psychological inflexibility, prejudicial attitudes, and dehumanization across three cross-sectional studies with an additional proposed experimental study. Psychological flexibility refers to mindful attention to the present moment, willing acceptance of private experiences, and engaging in behaviours congruent with one’s freely chosen values. Inflexibility, on the other hand, indicates a tendency to suppress unwanted thoughts and emotions, entanglement with one’s thoughts, and rigid behavioural patterns. Study 1 found limited correlations between inflexibility and sexism, racism, homonegativity, and dehumanization. Study 2 demonstrated more consistent positive associations between inflexibility and prejudice. And Study 3 controlled for right-wing authoritarianism and social dominance orientation, finding inflexibility predicted hostile sexism and racism beyond these factors. While showing some relationships, particularly with sexism and racism, psychological inflexibility did not consistently correlate with varied prejudices across studies. The proposed randomized controlled trial aims to evaluate an Acceptance and Commitment Therapy intervention to reduce sexism through enhanced psychological flexibility. Overall, findings provide mixed support for the utility of flexibility-based skills in addressing complex societal prejudices. Research should continue examining flexibility integrated with socio-cultural approaches to promote equity

    Design of decorative 3D models: from geodesic ornaments to tangible assemblies

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    L'obiettivo di questa tesi è sviluppare strumenti utili per creare opere d'arte decorative digitali in 3D. Uno dei processi decorativi più comunemente usati prevede la creazione di pattern decorativi, al fine di abbellire gli oggetti. Questi pattern possono essere dipinti sull'oggetto di base o realizzati con l'applicazione di piccoli elementi decorativi. Tuttavia, la loro realizzazione nei media digitali non è banale. Da un lato, gli utenti esperti possono eseguire manualmente la pittura delle texture o scolpire ogni decorazione, ma questo processo può richiedere ore per produrre un singolo pezzo e deve essere ripetuto da zero per ogni modello da decorare. D'altra parte, gli approcci automatici allo stato dell'arte si basano sull'approssimazione di questi processi con texturing basato su esempi o texturing procedurale, o con sistemi di riproiezione 3D. Tuttavia, questi approcci possono introdurre importanti limiti nei modelli utilizzabili e nella qualità dei risultati. Il nostro lavoro sfrutta invece i recenti progressi e miglioramenti delle prestazioni nel campo dell'elaborazione geometrica per creare modelli decorativi direttamente sulle superfici. Presentiamo una pipeline per i pattern 2D e una per quelli 3D, e dimostriamo come ognuna di esse possa ricreare una vasta gamma di risultati con minime modifiche dei parametri. Inoltre, studiamo la possibilità di creare modelli decorativi tangibili. I pattern 3D generati possono essere stampati in 3D e applicati a oggetti realmente esistenti precedentemente scansionati. Discutiamo anche la creazione di modelli con mattoncini da costruzione, e la possibilità di mescolare mattoncini standard e mattoncini custom stampati in 3D. Ciò consente una rappresentazione precisa indipendentemente da quanto la voxelizzazione sia approssimativa. I principali contributi di questa tesi sono l'implementazione di due diverse pipeline decorative, un approccio euristico alla costruzione con mattoncini e un dataset per testare quest'ultimo.The aim of this thesis is to develop effective tools to create digital decorative 3D artworks. Real-world art often involves the use of decorative patterns to enrich objects. These patterns can be painted on the base or might be realized with the application of small decorative elements. However, their creation in digital media is not trivial. On the one hand, users can manually perform texture paint or sculpt each decoration, in a process that can take hours to produce a single piece and needs to be repeated from the ground up for every model that needs to be decorated. On the other hand, automatic approaches in state of the art rely on approximating these processes with procedural or by-example texturing or with 3D reprojection. However, these approaches can introduce significant limitations in the models that can be used and in the quality of the results. Instead, our work exploits the recent advances and performance improvements in the geometry processing field to create decorative patterns directly on surfaces. We present a pipeline for 2D and one for 3D patterns and demonstrate how each of them can recreate a variety of results with minimal tweaking of the parameters. Furthermore, we investigate the possibility of creating decorative tangible models. The 3D patterns we generate can be 3D printed and applied to previously scanned real-world objects. We also discuss the creation of models with standard building bricks and the possibility of mixing standard and custom 3D-printed bricks. This allows for a precise representation regardless of the coarseness of the voxelization. The main contributions of this thesis are the implementation of two different decorative pipelines, a heuristic approach to brick construction, and a dataset to test the latter

    Procedural Constraint-based Generation for Game Development

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    Embedded SLAM algorithm based on ORB-SLAM2

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    The goal of this dissertation was to present a comprehensive analysis of the ORB-SLAM2 algorithm. By introducing the basis of points triangulation and ORB features, the whole structure of the algorithm has been analyzed, with a centralized focus on the graph-based optimization involved, as well as the place recognition mechanism. Additionally, the original code has been analyzed and optimized, resulting in a substantial increase in time performance while keeping a similar accuracy to the original one, proved by several simulations performed. The final goal of this thesis has been the testing of the obtained algorithm on a real quadcopter and the analysis of its outcomes: the results were affected by the limited computational resources available in the vehicle, obtaining a lower accuracy with respect to the simulation, but still proving the efficiency of the improvements applied on the original code

    Beyond Quantity: Research with Subsymbolic AI

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    How do artificial neural networks and other forms of artificial intelligence interfere with methods and practices in the sciences? Which interdisciplinary epistemological challenges arise when we think about the use of AI beyond its dependency on big data? Not only the natural sciences, but also the social sciences and the humanities seem to be increasingly affected by current approaches of subsymbolic AI, which master problems of quality (fuzziness, uncertainty) in a hitherto unknown way. But what are the conditions, implications, and effects of these (potential) epistemic transformations and how must research on AI be configured to address them adequately

    Expectations and expertise in artificial intelligence: specialist views and historical perspectives on conceptualisation, promise, and funding

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    Artificial intelligence’s (AI) distinctiveness as a technoscientific field that imitates the ability to think went through a resurgence of interest post-2010, attracting a flood of scientific and popular expectations as to its utopian or dystopian transformative consequences. This thesis offers observations about the formation and dynamics of expectations based on documentary material from the previous periods of perceived AI hype (1960-1975 and 1980-1990, including in-between periods of perceived dormancy), and 25 interviews with UK-based AI specialists, directly involved with its development, who commented on the issues during the crucial period of uncertainty (2017-2019) and intense negotiation through which AI gained momentum prior to its regulation and relatively stabilised new rounds of long-term investment (2020-2021). This examination applies and contributes to longitudinal studies in the sociology of expectations (SoE) and studies of experience and expertise (SEE) frameworks, proposing a historical sociology of expertise and expectations framework. The research questions, focusing on the interplay between hype mobilisation and governance, are: (1) What is the relationship between AI practical development and the broader expectational environment, in terms of funding and conceptualisation of AI? (2) To what extent does informal and non-developer assessment of expectations influence formal articulations of foresight? (3) What can historical examinations of AI’s conceptual and promissory settings tell about the current rebranding of AI? The following contributions are made: (1) I extend SEE by paying greater attention to the interplay between technoscientific experts and wider collective arenas of discourse amongst non-specialists and showing how AI’s contemporary research cultures are overwhelmingly influenced by the hype environment but also contribute to it. This further highlights the interaction between competing rationales focusing on exploratory, curiosity-driven scientific research against exploitation-oriented strategies at formal and informal levels. (2) I suggest benefits of examining promissory environments in AI and related technoscientific fields longitudinally, treating contemporary expectations as historical products of sociotechnical trajectories through an authoritative historical reading of AI’s shifting conceptualisation and attached expectations as a response to availability of funding and broader national imaginaries. This comes with the benefit of better perceiving technological hype as migrating from social group to social group instead of fading through reductionist cycles of disillusionment; either by rebranding of technical operations, or by the investigation of a given field by non-technical practitioners. It also sensitises to critically examine broader social expectations as factors for shifts in perception about theoretical/basic science research transforming into applied technological fields. Finally, (3) I offer a model for understanding the significance of interplay between conceptualisations, promising, and motivations across groups within competing dynamics of collective and individual expectations and diverse sources of expertise

    From visuomotor control to latent space planning for robot manipulation

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    Deep visuomotor control is emerging as an active research area for robot manipulation. Recent advances in learning sensory and motor systems in an end-to-end manner have achieved remarkable performance across a range of complex tasks. Nevertheless, a few limitations restrict visuomotor control from being more widely adopted as the de facto choice when facing a manipulation task on a real robotic platform. First, imitation learning-based visuomotor control approaches tend to suffer from the inability to recover from an out-of-distribution state caused by compounding errors. Second, the lack of versatility in task definition limits skill generalisability. Finally, the training data acquisition process and domain transfer are often impractical. In this thesis, individual solutions are proposed to address each of these issues. In the first part, we find policy uncertainty to be an effective indicator of potential failure cases, in which the robot is stuck in out-of-distribution states. On this basis, we introduce a novel uncertainty-based approach to detect potential failure cases and a recovery strategy based on action-conditioned uncertainty predictions. Then, we propose to employ visual dynamics approximation to our model architecture to capture the motion of the robot arm instead of the static scene background, making it possible to learn versatile skill primitives. In the second part, taking inspiration from the recent progress in latent space planning, we propose a gradient-based optimisation method operating within the latent space of a deep generative model for motion planning. Our approach bypasses the traditional computational challenges encountered by established planning algorithms, and has the capability to specify novel constraints easily and handle multiple constraints simultaneously. Moreover, the training data comes from simple random motor-babbling of kinematically feasible robot states. Our real-world experiments further illustrate that our latent space planning approach can handle both open and closed-loop planning in challenging environments such as heavily cluttered or dynamic scenes. This leads to the first, to our knowledge, closed-loop motion planning algorithm that can incorporate novel custom constraints, and lays the foundation for more complex manipulation tasks

    Using pooled CRISPR screens to study gene regulation.

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    Die Genregulation ist ein komplexer Prozess, bei dem Zellen die Menge der Genprodukte steuern, um ihre Identität auszubilden und auf Umweltveränderungen zu reagieren. Die CRISPR-Technologie hat genetische Screens revolutioniert und ermöglicht es, mehrere Transkripte gleichzeitig zu untersuchen. In dieser Arbeit werden die Vorteile und Herausforderungen gepoolter CRISPR-Screens zur Erforschung der Genregulation untersucht. Es wird ein CRISPR-ko-Screen in embryonalen Mausstammzellen (mESCs) beschrieben, der pluripotenzerhaltende Transkriptionsfaktoren identifiziert. Es zeigte sich, dass ein Screening mit einer kleinen Bibliothek den Großteil des biologischen Signals eines genomweiten Screens erfasst und die Identifizierung von Genkandidaten mit kleinen Effektgrößen verbessert. Nachfolgend wird CRISPTimeR, eine neue Methode für die Analyse von Zeitreihen von CRISPR-Screens, vorgestellt. Sie basiert auf gemischten linearen Modellen und ermöglicht es, Treffer zu identifizieren und gleichzeitig zeitlich zu klassifizieren. Als Nächstes wurde CRISPRi verwendet, um für die Pluripotenz von mESCs relevante lncRNAs zu untersuchen, was aufgrund ihrer schlechten Annotation und niedrigen Expressionsniveaus schwierig ist. Eine mögliche Lösung ist eine manuell verfeinerte Annotation von Transkriptionsstartstellen und kleinere Bibliotheks-Screens mit empfindlicherer phänotypischer Auslesung. Zudem wurde ein Sättigungsscreen genomischer Regionen rund um den PHOX2B-Lokus, zur Identifikation cis-regulierender Elemente, durchgeführt. Dabei wurden CRISPRa-reaktive Elemente identifiziert, die Gene in der PHOX2B-TAD regulieren, und mit diesen mittels Einzelzell RNA-seq in Verbindung gebracht. Zusammenfassend zeigt diese Arbeit den Wert gepoolter CRISPR-Screens für die Erforschung der Genregulation und Herausforderungen der Analyse nicht-kodierender Elemente. Zusätzlich beschreibt sie ein neues Tool für die Analyse von kodierenden und nicht-kodierenden CRISPR-Screens in Zeitreihen.Gene regulation is a complex process in which cells control gene product levels to establish identity and respond to environmental changes. CRISPR technology has revolutionized genetic screening, enabling researchers to study multiple transcripts simultaneously. This thesis explores the advantages and challenges of using pooled CRISPR screens to study gene regulation. First, I describe a CRISPR-ko screen in mouse embryonic stem cells (mESCs) to identify transcription factors involved in pluripotency maintenance. I show that a small-library screen captures most of the biological signal observed in a genome-wide screen, and it improves the identification of candidate genes with small effect sizes. Next, introduce CRISPTimeR, a novel method for the analysis time-series CRISPR screens. CRISPTimeR is based on mixed linear models; it allows to use information from a time-series experiment to identify, and simultaneously perform temporal classification on, hits. Next, I use CRISPRi to study lncRNAs relevant to pluripotency in mESCs. Targeting lncRNAs poses challenges due to poor annotation and low expression levels. I suggest to address these issues by using a hand-refined annotation of transcription start sites and by designing small-library screens with more sensitive phenotypic readout. Finally, I describe a saturation screen targeting large genomic regions around the PHOX2B locus, to identify putative cis-regulatory elements. I identified CRISPRa responsive elements involved in regulating the expression of genes within the PHOX2B TAD, which were then matched with the genes they control using single-cell RNA-seq. Overall, in this thesis I demonstrate the value of CRISPR pooled screens for studying gene regulation, while highlighting the challenges associated with targeting non-coding elements and suggesting possible approaches to address these challenges. Moreover, I introduce a novel tool for the analysis of both coding and non-coding time-series CRISPR screens

    2023-2024 Boise State University Undergraduate Catalog

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    This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State

    LASSO – an observatorium for the dynamic selection, analysis and comparison of software

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    Mining software repositories at the scale of 'big code' (i.e., big data) is a challenging activity. As well as finding a suitable software corpus and making it programmatically accessible through an index or database, researchers and practitioners have to establish an efficient analysis infrastructure and precisely define the metrics and data extraction approaches to be applied. Moreover, for analysis results to be generalisable, these tasks have to be applied at a large enough scale to have statistical significance, and if they are to be repeatable, the artefacts need to be carefully maintained and curated over time. Today, however, a lot of this work is still performed by human beings on a case-by-case basis, with the level of effort involved often having a significant negative impact on the generalisability and repeatability of studies, and thus on their overall scientific value. The general purpose, 'code mining' repositories and infrastructures that have emerged in recent years represent a significant step forward because they automate many software mining tasks at an ultra-large scale and allow researchers and practitioners to focus on defining the questions they would like to explore at an abstract level. However, they are currently limited to static analysis and data extraction techniques, and thus cannot support (i.e., help automate) any studies which involve the execution of software systems. This includes experimental validations of techniques and tools that hypothesise about the behaviour (i.e., semantics) of software, or data analysis and extraction techniques that aim to measure dynamic properties of software. In this thesis a platform called LASSO (Large-Scale Software Observatorium) is introduced that overcomes this limitation by automating the collection of dynamic (i.e., execution-based) information about software alongside static information. It features a single, ultra-large scale corpus of executable software systems created by amalgamating existing Open Source software repositories and a dedicated DSL for defining abstract selection and analysis pipelines. Its key innovations are integrated capabilities for searching for selecting software systems based on their exhibited behaviour and an 'arena' that allows their responses to software tests to be compared in a purely data-driven way. We call the platform a 'software observatorium' since it is a place where the behaviour of large numbers of software systems can be observed, analysed and compared
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