12,718 research outputs found

    NF-Atlas: Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping

    Full text link
    LiDAR Mapping has been a long-standing problem in robotics. Recent progress in neural implicit representation has brought new opportunities to robotic mapping. In this paper, we propose the multi-volume neural feature fields, called NF-Atlas, which bridge the neural feature volumes with pose graph optimization. By regarding the neural feature volume as pose graph nodes and the relative pose between volumes as pose graph edges, the entire neural feature field becomes both locally rigid and globally elastic. Locally, the neural feature volume employs a sparse feature Octree and a small MLP to encode the submap SDF with an option of semantics. Learning the map using this structure allows for end-to-end solving of maximum a posteriori (MAP) based probabilistic mapping. Globally, the map is built volume by volume independently, avoiding catastrophic forgetting when mapping incrementally. Furthermore, when a loop closure occurs, with the elastic pose graph based representation, only updating the origin of neural volumes is required without remapping. Finally, these functionalities of NF-Atlas are validated. Thanks to the sparsity and the optimization based formulation, NF-Atlas shows competitive performance in terms of accuracy, efficiency and memory usage on both simulation and real-world datasets

    Identifying and responding to people with mild learning disabilities in the probation service

    Get PDF
    It has long been recognised that, like many other individuals, people with learningdisabilities find their way into the criminal justice system. This fact is not disputed. Whathas been disputed, however, is the extent to which those with learning disabilities arerepresented within the various agencies of the criminal justice system and the ways inwhich the criminal justice system (and society) should address this. Recently, social andlegislative confusion over the best way to deal with offenders with learning disabilities andmental health problems has meant that the waters have become even more muddied.Despite current government uncertainty concerning the best way to support offenders withlearning disabilities, the probation service is likely to continue to play a key role in thesupervision of such offenders. The three studies contained herein aim to clarify the extentto which those with learning disabilities are represented in the probation service, toexamine the effectiveness of probation for them and to explore some of the ways in whichprobation could be adapted to fit their needs.Study 1 and study 2 showed that around 10% of offenders on probation in Kent appearedto have an IQ below 75, putting them in the bottom 5% of the general population. Study 3was designed to assess some of the support needs of those with learning disabilities in theprobation service, finding that many of the materials used by the probation service arelikely to be too complex for those with learning disabilities to use effectively. To addressthis, a model for service provision is tentatively suggested. This is based on the findings ofthe three studies and a pragmatic assessment of what the probation service is likely to becapable of achieving in the near future

    Elite perceptions of the Victorian and Edwardian past in inter-war England

    Get PDF
    It is often argued by historians that members of the cultivated Elite after 1918 rejected the pre-war past. or at least subjected it to severe denigration. This thesis sets out to challenge such a view. Above all, it argues that inter-war critics of the Victorian and Edwardian past were unable to reject it even if that was what they felt inclined to do. This was because they were tied to those periods by the affective links of memory, family, and the continually unfolding consequences of the past in the present. Even the severest critics of the pre-war world, such as Lytton Strachey, were less frequently dismissive of history than ambivalent towards it. This ambivalence, it is argued, helped to keep the past alive and often to humanise it. The thesis also explores more positive estimation of Victorian and Edwardian history between the wars. It examines nostalgia for the past, as well as instances of continuity of practice and attitude. It explores the way in which inter-war society drew upon aspects of Victorian and Edwardian history both as illuminating parallels to contemporary affairs and to understand directly why the present was shaped as it was. Again, this testifies to the enduring power of the past after 1918. There are three parts to this thesis. Part One outlines the cultural context in which writers contemplated the Victorian and Edwardian past. Part Two explores some of the ways in which history was written about and used by inter-war society. Part Three examines the ways in which biographical depictions of eminent Victorians after 1918 encouraged emotional negotiation with the pas

    Imagination as Thought in Aristotle\u27s De Anima

    Get PDF
    Aristotle appears to indicate in various passages in the De Anima that imagination is a kind of thought, and my thesis attempts to make some sense out of this claim. I examine three possible interpretations of the claim that imagination is a kind of thought and eliminate two of them. The first states that Aristotle only calls imagination a kind of thought in a superficial “in name only” sense. The second, more radical interpretation, identifies images as the most basic kind of thoughts. My final chapter defends a more moderate position—inspired by Avempace and the early Averroes—which steers between the superficial and radical interpretations, by construing the formal content of images as a sort of quasi-corporeal substrate for the generation of learned thoughts

    Implementing Health Impact Assessment as a Required Component of Government Policymaking: A Multi-Level Exploration of the Determinants of Healthy Public Policy

    Get PDF
    It is widely understood that the public policies of ‘non-health’ government sectors have greater impacts on population health than those of the traditional healthcare realm. Health Impact Assessment (HIA) is a decision support tool that identifies and promotes the health benefits of policies while also mitigating their unintended negative consequences. Despite numerous calls to do so, the Ontario government has yet to implement HIA as a required component of policy development. This dissertation therefore sought to identify the contexts and factors that may both enable and impede HIA use at the sub-national (i.e., provincial, territorial, or state) government level. The three integrated articles of this dissertation provide insights into specific aspects of the policy process as they relate to HIA. Chapter one details a case study of purposive information-seeking among public servants within Ontario’s Ministry of Education (MOE). Situated within Ontario’s Ministry of Health (MOH), chapter two presents a case study of policy collaboration between health and ‘non-health’ ministries. Finally, chapter three details a framework analysis of the political factors supporting health impact tool use in two sub-national jurisdictions – namely, Québec and South Australia. MOE respondents (N=9) identified four components of policymaking ‘due diligence’, including evidence retrieval, consultation and collaboration, referencing, and risk analysis. As prospective HIA users, they also confirmed that information is not routinely sought to mitigate the potential negative health impacts of education-based policies. MOH respondents (N=8) identified the bureaucratic hierarchy as the brokering mechanism for inter-ministerial policy development. As prospective HIA stewards, they also confirmed that the ministry does not proactively flag the potential negative health impacts of non-health sector policies. Finally, ‘lessons learned’ from case articles specific to Québec (n=12) and South Australia (n=17) identified the political factors supporting tool use at different stages of the policy cycle, including agenda setting (‘policy elites’ and ‘political culture’), implementation (‘jurisdiction’), and sustained implementation (‘institutional power’). This work provides important insights into ‘real life’ policymaking. By highlighting existing facilitators of and barriers to HIA use, the findings offer a useful starting point from which proponents may tailor context-specific strategies to sustainably implement HIA at the sub-national government level

    Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval

    Get PDF
    In computer-based search systems, similarity plays a key role in replicating the human search process. Indeed, the human search process underlies many natural abilities such as image recovery, language comprehension, decision making, or pattern recognition. The search for images consists of establishing a correspondence between the available image and that sought by the user, by measuring the similarity between the images. Image search by content is generaly based on the similarity of the visual characteristics of the images. The distance function used to evaluate the similarity between images depends notonly on the criteria of the search but also on the representation of the characteristics of the image. This is the main idea of a content-based image retrieval (CBIR) system. In this article, first, we constructed type-2 beta fuzzy membership of descriptor vectors to help manage inaccuracy and uncertainty of characteristics extracted the feature of images. Subsequently, the retrieved images are ranked according to the novel similarity measure, noted type-2 fuzzy nearness measure (IT2FNM). By analogy to Type-2 Fuzzy Logic and motivated by near sets theory, we advanced a new fuzzy similarity measure (FSM) noted interval type-2 fuzzy nearness measure (IT-2 FNM). Then, we proposed three new IT-2 FSMs and we have provided mathematical justification to demonstrate that the proposed FSMs satisfy proximity properties (i.e. reflexivity, transitivity, symmetry, and overlapping). Experimental results generated using three image databases showing consistent and significant results

    Animating potential for intensities and becoming in writing: challenging discursively constructed structures and writing conventions in academia through the use of storying and other post qualitative inquiries

    Get PDF
    Written for everyone ever denied the opportunity of fulfilling their academic potential, this is ‘Chloe’s story’. Using composite selves, a phrase chosen to indicate multiplicities and movement, to story both the initial event leading to ‘Chloe’s’ immediate withdrawal from a Further Education college and an imaginary second chance to support her whilst at university, this Deleuzo-Guattarian (2015a) ‘assemblage’ of post qualitative inquiries offers challenge to discursively constructed structures and writing conventions in academia. Adopting a posthuman approach to theorising to shift attention towards affects and intensities always relationally in action in multiple ‘assemblages’, these inquiries aim to decentre individual ‘lecturer’ and ‘student’ identities. Illuminating movements and moments quivering with potential for change, then, hoping thereby to generate second chances for all, different approaches to writing are exemplified which trouble those academic constraints by fostering inquiry and speculation: moving away from ‘what is’ towards ‘what if’. With the formatting of this thesis itself also always troubling the rigid Deleuzo-Guattarian (2015a) ‘segmentary lines’ structuring orthodox academic practice, imbricated in these inquiries are attempts to exemplify Manning’s (2015; 2016) ‘artfulness’ through shifts in thinking within and around an emerging PhD thesis. As writing resists organising, the verb thesisising comes into play to describe the processes involved in creating this always-moving thesis. Using ‘landing sites’ (Arakawa and Gins, 2009) as a landscaping device, freely creating emerging ‘lines of flight’ (Deleuze and Guattari, 2015a) so often denied to students forced to adhere to strict academic conventions, this ‘movement-moving’ (Manning, 2014) opens up opportunities for change as in Manning’s (2016) ‘research-creation’. Arguing for a moving away from writing-representing towards writing-inquiring, towards a writing ‘that does’ (Wyatt and Gale, 2018: 127), and toward writing as immanent doing, it is hoped to animate potential for intensities and becoming in writing, offering opportunities and glimmerings of the not-yet-known

    Strategies for Early Learners

    Get PDF
    Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp

    Building body identities - exploring the world of female bodybuilders

    Get PDF
    This thesis explores how female bodybuilders seek to develop and maintain a viable sense of self despite being stigmatized by the gendered foundations of what Erving Goffman (1983) refers to as the 'interaction order'; the unavoidable presentational context in which identities are forged during the course of social life. Placed in the context of an overview of the historical treatment of women's bodies, and a concern with the development of bodybuilding as a specific form of body modification, the research draws upon a unique two year ethnographic study based in the South of England, complemented by interviews with twenty-six female bodybuilders, all of whom live in the U.K. By mapping these extraordinary women's lives, the research illuminates the pivotal spaces and essential lived experiences that make up the female bodybuilder. Whilst the women appear to be embarking on an 'empowering' radical body project for themselves, the consequences of their activity remains culturally ambivalent. This research exposes the 'Janus-faced' nature of female bodybuilding, exploring the ways in which the women negotiate, accommodate and resist pressures to engage in more orthodox and feminine activities and appearances

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

    Get PDF
    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri
    • …
    corecore