12,225 research outputs found

    Towards a sociology of conspiracy theories: An investigation into conspiratorial thinking on Dönmes

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    This thesis investigates the social and political significance of conspiracy theories, which has been an academically neglected topic despite its historical relevance. The academic literature focuses on the methodology, social significance and political impacts of these theories in a secluded manner and lacks empirical analyses. In response, this research provides a comprehensive theoretical framework for conspiracy theories by considering their methodology, political impacts and social significance in the light of empirical data. Theoretically, the thesis uses Adorno's semi-erudition theory along with Girardian approach. It proposes that conspiracy theories are methodologically semi-erudite narratives, i.e. they are biased in favour of a belief and use reason only to prove it. It suggests that conspiracy theories appear in times of power vacuum and provide semi-erudite cognitive maps that relieve alienation and ontological insecurities of people and groups. In so doing, they enforce social control over their audience due to their essentialist, closed-to-interpretation narratives. In order to verify the theory, the study analyses empirically the social and political significance of conspiracy theories about the Dönme community in Turkey. The analysis comprises interviews with conspiracy theorists, conspiracy theory readers and political parties, alongside a frame analysis of the popular conspiracy theory books on Dönmes. These confirm the theoretical framework by showing that the conspiracy theories are fed by the ontological insecurities of Turkish society. Hence, conspiracy theorists, most readers and some political parties respond to their own ontological insecurities and political frustrations through scapegoating Dönmes. Consequently, this work shows that conspiracy theories are important symptoms of society, which, while relieving ontological insecurities, do not provide politically prolific narratives

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

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    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

    Post-Millennial Queer Sensibility: Collaborative Authorship as Disidentification in Queer Intertextual Commodities

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    This dissertation is examining LGBTQ+ audiences and creatives collaborating in the creation of new media texts like web shows, podcasts, and video games. The study focuses on three main objects or media texts: Carmilla (web series), Welcome to Night Vale (podcast), and Undertale (video game). These texts are transmedia objects or intertextual commodities. I argue that by using queer gestures of collaborative authorship that reaches out to the audience for canonical contribution create an emerging queer production culture that disidentifies with capitalism even as it negotiates capitalistic structures. The post-millennial queer sensibility is a constellation of aesthetics, self-representation, alternative financing, and interactivity that prioritizes community, trust, and authenticity using new technologies for co-creation. Within my study, there are four key tactics or queer gestures being explored: remediation, radical ambiguity and multi-forms as queer aesthetics, audience self-representation, alternative financing like micropatronage & licensed fan-made merchandise, and interactivity as performance. The goal of this project is to better understand the changing conceptions of authorship/ownership, canon/fanon (official text/fan created extensions), and community/capitalism in queer subcultures as an indicator of the potential change in more mainstream cultural attitudes. The project takes into consideration a variety of intersecting identities including gender, race, class, and of course sexual orientation in its analysis. By examining the legal discourse around collaborative authorship, the real-life production practices, and audience-creator interactions and attitudes, this study provides insight into how media creatives work with audiences to co-create self-representative media, the motivations, and rewards for creative, audiences, and owners. This study aims to contribute towards a fuller understanding of queer production cultures and audience reception of these media texts, of which there is relatively little academic information. Specifically, the study mines for insights into the changing attitudes towards authorship, ownership, and collaboration within queer indie media projects, especially as these objects are relying on the self-representation of both audiences and creatives in the formation of the text

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods

    BECOMEBECOME - A TRANSDISCIPLINARY METHODOLOGY BASED ON INFORMATION ABOUT THE OBSERVER

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    ABSTRACT Andrea T. R. Traldi BECOMEBECOME A Transdisciplinary Methodology Based on Information about the Observer The present research dissertation has been developed with the intention to provide practical strategies and discover new intellectual operations which can be used to generate Transdisciplinary insight. For this reason, this thesis creates access to new knowledge at different scales. Firstly, as it pertains to the scale of new knowledge generated by those who attend Becomebecome events. The open-source nature of the Becomebecome methodology makes it possible for participants in Becomebecome workshops, training programmes and residencies to generate new insight about the specific project they are working on, which then reinforce and expand the foundational principles of the theoretical background. Secondly, as it pertains to the scale of the Becomebecome framework, which remains independent of location and moment in time. The method proposed to access Transdisciplinary knowledge constitutes new knowledge in itself because the sequence of activities, described as physical and mental procedures and listed as essential criteria, have never been found organised 6 in such a specific order before. It is indeed the order in time, i.e. the sequence of the ideas and activities proposed, which allows one to transform Disciplinary knowledge via a new Transdisciplinary frame of reference. Lastly, new knowledge about Transdisciplinarity as a field of study is created as a consequence of the heretofore listed two processes. The first part of the thesis is designated ‘Becomebecome Theory’ and focuses on the theoretical background and the intellectual operations necessary to support the creation of new Transdisciplinary knowledge. The second part of the thesis is designated ‘Becomebecome Practice’ and provides practical examples of the application of such operations. Crucially, the theoretical model described as the foundation for the Becomebecome methodology (Becomebecome Theory) is process-based and constantly checked against the insight generated through Becomebecome Practice. To this effect, ‘information about the observer’ is proposed as a key notion which binds together Transdisciplinary resources from several studies in the hard sciences and humanities. It is a concept that enables understanding about why and how information that is generated through Becomebecome Practice is considered of paramount importance for establishing the reference parameters necessary to access Transdisciplinary insight which is meaningful to a specific project, a specific person, or a specific moment in time

    Interactive Sonic Environments: Sonic artwork via gameplay experience

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    The purpose of this study is to investigate the use of video-game technology in the design and implementation of interactive sonic centric artworks, the purpose of which is to create and contribute to the discourse and understanding of its effectiveness in electro-acoustic composition highlighting the creative process. Key research questions include: How can the language of electro-acoustic music be placed in a new framework derived from videogame aesthetics and technology? What new creative processes need to be considered when using this medium? Moreover, what aspects of 'play' should be considered when designing the systems? The findings of this study assert that composers and sonic art practitioners need little or no coding knowledge to create exciting applications and the myriad of options available to the composer when using video-game technology is limited only by imagination. Through a cyclic process of planning, building, testing and playing these applications the project revealed advantages and unique sonic opportunities in comparison to other sonic art installations. A portfolio of selected original compositions, both fixed and open are presented by the author to complement this study. The commentary serves to place the work in context with other practitioners in the field and to provide compositional approaches that have been taken

    Studies of strategic performance management for classical organizations theory & practice

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    Nowadays, the activities of "Performance Management" have spread very broadly in actually every part of business and management. There are numerous practitioners and researchers from very different disciplines, who are involved in exploring the different contents of performance management. In this thesis, some relevant historic developments in performance management are first reviewed. This includes various theories and frameworks of performance management. Then several management science techniques are developed for assessing performance management, including new methods in Data Envelopment Analysis (DEA) and Soft System Methodology (SSM). A theoretical framework for performance management and its practical procedures (five phases) are developed for "classic" organizations using soft system thinking, and the relationship with the existing theories are explored. Eventually these results are applied in three case studies to verify our theoretical development. One of the main contributions of this work is to point out, and to systematically explore the basic idea that the effective forms and structures of performance management for an organization are likely to depend greatly on the organizational configuration, in order to coordinate well with other management activities in the organization, which has seemingly been neglected in the existing literature of performance management research in the sense that there exists little known research that associated particular forms of performance management with the explicit assumptions of organizational configuration. By applying SSM, this thesis logically derives some main functional blocks of performance management in 'classic' organizations and clarifies the relationships between performance management and other management activities. Furthermore, it develops some new tools and procedures, which can hierarchically decompose organizational strategies and produce a practical model of specific implementation steps for "classic" organizations. Our approach integrates popular types of performance management models. Last but not least, this thesis presents findings from three major cases, which are quite different organizations in terms of management styles, ownership, and operating environment, to illustrate the fliexbility of the developed theoretical framework

    The empty space in abstract photography: a psychoanalytical perspective

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    The aim of the research that this thesis is based on is to explore the theoretical problems raised by the concept of photographic abstraction. These consist in the tension between the two aspects of the photographic sign, the indexical and iconic, and are examined in the context of the particular exploration of the empty space in abstract photography which I have pursued through my practice. The investigation draws mainly upon the psychoanalytic theory of transitional phenomena as proposed by Winnicott, as well as other art theories (Deleuze & Guattari, Ehrenzweig, Fer, Fuller, Greenberg, Joselit, Kuspit, Leider, Worringer) of abstraction. It explores the relationship of the abstract photographic image to notions of exteriority and interiority as these relate to the transition from the unconscious to conscious reality. The development of this research suggests the psychoanalytical concept of potential space as a contribution to an aesthetic model of abstraction. This concept is employed as a methodological tool in the development of the practical work and creates a framework for its interpretation. The concept of potential space is based on Winnicott's ideas around "playing with the real" in an intermediate area of experience between the internal and external reality, where creativity originates as a zone of fictive play that facilitates the subject's journey from "what is subjectively conceived of' to "what is objectively perceived. " The outcome of this investigation constitutes the production of a series of photographs describing an empty abstract space, one that is invested with a psychic dimension that produces the effect of ambiguity between its representational and abstract readings. It provides a redefinition of abstraction in a space of tension between the iconic and indexical aspects of the sign and opens up the space of abstraction in photography as one in which the relationship between inner and outer reality can be performed and can become a space of action and intervention

    Anytime algorithms for ROBDD symmetry detection and approximation

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    Reduced Ordered Binary Decision Diagrams (ROBDDs) provide a dense and memory efficient representation of Boolean functions. When ROBDDs are applied in logic synthesis, the problem arises of detecting both classical and generalised symmetries. State-of-the-art in symmetry detection is represented by Mishchenko's algorithm. Mishchenko showed how to detect symmetries in ROBDDs without the need for checking equivalence of all co-factor pairs. This work resulted in a practical algorithm for detecting all classical symmetries in an ROBDD in O(|G|³) set operations where |G| is the number of nodes in the ROBDD. Mishchenko and his colleagues subsequently extended the algorithm to find generalised symmetries. The extended algorithm retains the same asymptotic complexity for each type of generalised symmetry. Both the classical and generalised symmetry detection algorithms are monolithic in the sense that they only return a meaningful answer when they are left to run to completion. In this thesis we present efficient anytime algorithms for detecting both classical and generalised symmetries, that output pairs of symmetric variables until a prescribed time bound is exceeded. These anytime algorithms are complete in that given sufficient time they are guaranteed to find all symmetric pairs. Theoretically these algorithms reside in O(n³+n|G|+|G|³) and O(n³+n²|G|+|G|³) respectively, where n is the number of variables, so that in practice the advantage of anytime generality is not gained at the expense of efficiency. In fact, the anytime approach requires only very modest data structure support and offers unique opportunities for optimisation so the resulting algorithms are very efficient. The thesis continues by considering another class of anytime algorithms for ROBDDs that is motivated by the dearth of work on approximating ROBDDs. The need for approximation arises because many ROBDD operations result in an ROBDD whose size is quadratic in the size of the inputs. Furthermore, if ROBDDs are used in abstract interpretation, the running time of the analysis is related not only to the complexity of the individual ROBDD operations but also the number of operations applied. The number of operations is, in turn, constrained by the number of times a Boolean function can be weakened before stability is achieved. This thesis proposes a widening that can be used to both constrain the size of an ROBDD and also ensure that the number of times that it is weakened is bounded by some given constant. The widening can be used to either systematically approximate an ROBDD from above (i.e. derive a weaker function) or below (i.e. infer a stronger function). The thesis also considers how randomised techniques may be deployed to improve the speed of computing an approximation by avoiding potentially expensive ROBDD manipulation
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