9,775 research outputs found

    Modified Theories of Gravity and Cosmological Applications

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    This reprint focuses on recent aspects of gravitational theory and cosmology. It contains subjects of particular interest for modified gravity theories and applications to cosmology, special attention is given to Einstein–Gauss–Bonnet, f(R)-gravity, anisotropic inflation, extra dimension theories of gravity, black holes, dark energy, Palatini gravity, anisotropic spacetime, Einstein–Finsler gravity, off-diagonal cosmological solutions, Hawking-temperature and scalar-tensor-vector theories

    Psychographic And Behavioral Segmentation Of Food Delivery Application Customers To Increase Intention To Use

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThis study presents a framework for segmenting Food Delivery Application (FDA) customers based on psychographic and behavioral variables as an alternative to existing segmentation. Customer segments are proposed by applying clustering methods to primary data from an electronic survey. Psychographic and behavioral constructs are formulated as hypotheses based on existing literature, and then evaluated as segmentation variables regarding their discriminatory power for customer segmentation. Detected relevant variables are used in the application of clustering techniques to find adequate boundaries within customer groupings for segmentation purposes. Characterization of customer segments is performed and enriched with implications of findings in FDA marketing strategies. This paper contributes to theory by providing new findings on segmentation that are relevant for an online context. In addition, it contributes to practice by detailing implications of customer segments in an online sales strategy, allowing marketing managers and FDA businesses to capitalize knowledge in their conversion funnel designs

    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

    Defining Service Level Agreements in Serverless Computing

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    The emergence of serverless computing has brought significant advancements to the delivery of computing resources to cloud users. With the abstraction of infrastructure, ecosystem, and execution environments, users could focus on their code while relying on the cloud provider to manage the abstracted layers. In addition, desirable features such as autoscaling and high availability became a provider’s responsibility and can be adopted by the user\u27s application at no extra overhead. Despite such advancements, significant challenges must be overcome as applications transition from monolithic stand-alone deployments to the ephemeral and stateless microservice model of serverless computing. These challenges pertain to the uniqueness of the conceptual and implementation models of serverless computing. One of the notable challenges is the complexity of defining Service Level Agreements (SLA) for serverless functions. As the serverless model shifts the administration of resources, ecosystem, and execution layers to the provider, users become mere consumers of the provider’s abstracted platform with no insight into its performance. Suboptimal conditions of the abstracted layers are not visible to the end-user who has no means to assess their performance. Thus, SLA in serverless computing must take into consideration the unique abstraction of its model. This work investigates the Service Level Agreement (SLA) modeling of serverless functions\u27 and serverless chains’ executions. We highlight how serverless SLA fundamentally differs from earlier cloud delivery models. We then propose an approach to define SLA for serverless functions by utilizing resource utilization fingerprints for functions\u27 executions and a method to assess if executions adhere to that SLA. We evaluate the approach’s accuracy in detecting SLA violations for a broad range of serverless application categories. Our validation results illustrate a high accuracy in detecting SLA violations resulting from resource contentions and provider’s ecosystem degradations. We conclude by presenting the empirical validation of our proposed approach, which could detect Execution-SLA violations with accuracy up to 99%

    Innovative Hybrid Approaches for Vehicle Routing Problems

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    This thesis deals with the efficient resolution of Vehicle Routing Problems (VRPs). The first chapter faces the archetype of all VRPs: the Capacitated Vehicle Routing Problem (CVRP). Despite having being introduced more than 60 years ago, it still remains an extremely challenging problem. In this chapter I design a Fast Iterated-Local-Search Localized Optimization algorithm for the CVRP, shortened to FILO. The simplicity of the CVRP definition allowed me to experiment with advanced local search acceleration and pruning techniques that have eventually became the core optimization engine of FILO. FILO experimentally shown to be extremely scalable and able to solve very large scale instances of the CVRP in a fraction of the computing time compared to existing state-of-the-art methods, still obtaining competitive solutions in terms of their quality. The second chapter deals with an extension of the CVRP called the Extended Single Truck and Trailer Vehicle Routing Problem, or simply XSTTRP. The XSTTRP models a broad class of VRPs in which a single vehicle, composed of a truck and a detachable trailer, has to serve a set of customers with accessibility constraints making some of them not reachable by using the entire vehicle. This problem moves towards VRPs including more realistic constraints and it models scenarios such as parcel deliveries in crowded city centers or rural areas, where maneuvering a large vehicle is forbidden or dangerous. The XSTTRP generalizes several well known VRPs such as the Multiple Depot VRP and the Location Routing Problem. For its solution I developed an hybrid metaheuristic which combines a fast heuristic optimization with a polishing phase based on the resolution of a limited set partitioning problem. Finally, the thesis includes a final chapter aimed at guiding the computational evaluation of new approaches to VRPs proposed by the machine learning community

    Socio-endocrinology revisited: New tools to tackle old questions

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    Animals’ social environments impact their health and survival, but the proximate links between sociality and fitness are still not fully understood. In this thesis, I develop and apply new approaches to address an outstanding question within this sociality-fitness link: does grooming (a widely studied, positive social interaction) directly affect glucocorticoid concentrations (GCs; a group of steroid hormones indicating physiological stress) in a wild primate? To date, negative, long-term correlations between grooming and GCs have been found, but the logistical difficulties of studying proximate mechanisms in the wild leave knowledge gaps regarding the short-term, causal mechanisms that underpin this relationship. New technologies, such as collar-mounted tri-axial accelerometers, can provide the continuous behavioural data required to match grooming to non-invasive GC measures (Chapter 1). Using Chacma baboons (Papio ursinus) living on the Cape Peninsula, South Africa as a model system, I identify giving and receiving grooming using tri-axial accelerometers and supervised machine learning methods, with high overall accuracy (~80%) (Chapter 2). I then test what socio-ecological variables predict variation in faecal and urinary GCs (fGCs and uGCs) (Chapter 3). Shorter and rainy days are associated with higher fGCs and uGCs, respectively, suggesting that environmental conditions may impose stressors in the form of temporal bottlenecks. Indeed, I find that short days and days with more rain-hours are associated with reduced giving grooming (Chapter 4), and that this reduction is characterised by fewer and shorter grooming bouts. Finally, I test whether grooming predicts GCs, and find that while there is a long-term negative correlation between grooming and GCs, grooming in the short-term, in particular giving grooming, is associated with higher fGCs and uGCs (Chapter 5). I end with a discussion on how the new tools I applied have enabled me to advance our understanding of sociality and stress in primate social systems (Chapter 6)

    Fetal growth, birth size and energetic cost of gestation in southern right whales

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    The cost of reproduction greatly affects a species’ life history strategy. Baleen whales exhibit some of the fastest offspring growth rates in the animal kingdom. We quantified the energetic cost of gestation for southern right whales (Eubalaena australis) by combining whaling catch records of pregnant females with photogrammetry data on southern right whale mothers and calves from two breeding grounds in Argentina and Australia. The relationship between calf birth size and maternal length was determined from repeated measurements of individual females before and after giving birth. Fetal growth was determined from generalized linear models fitted to fetal length data from whaling operations between 1961 and 1967. Fetal length was converted to volume and mass, using the volume-to-length relationship of newborn southern right whales calves, and published tissue composition and energy content estimates. Fetal maintenance costs (heat of gestation) and the energy content of the placenta were predicted from published relationships and added to the fetal growth cost to calculate the total cost of gestation. Our findings showed that fetal growth rates and birth size increased linearly with maternal length, with calves being born at ∼35% maternal length. Fetal length increased curvilinearly through gestation, which resulted in an exponential increase in fetal volume and mass. Consequently, the cost of gestation was very low during the first (0.1% of total cost) and second trimester (4.9%), but increased rapidly during the last trimester (95.0%). The heat of gestation incurred the highest cost for pregnant females (73.8%), followed by fetal growth (21.2%) and the placental energy content (5.0%)

    Development of Evidence Based Factors to Enhance Safety Behaviour in Oil and Gas Industry in the Niger Delta Region of Nigeria

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    The Nigeria’s economy has benefited enormously from its oil and gas sector. However, despite the economic impact accrued to the nation from the sector, there are still safety and health concerns among its employees. Unsafe behaviour mainly influenced by poor safety culture escalates the risk of injuries and accidents at workplaces and requires proper management. This study aimed to evaluate safety behaviour and its impact on safety performance among Nigeria oil and gas workers. To achieve this aim, both quantitative and qualitative research methods were adopted. Validated questionnaires used in studies 1 and 2 were distributed via JISC Survey (Bristol online survey) platform and self-administration. For the first study, 462 frontline employees participated in the survey. Structural equation modelling was perform using the data set and, the out from the analysis found safety management practices had a significant relationship with both safety participation (p 0.109). Quantitative survey was undertaken to achieve the second study objectives. At the end of the survey, 1004 frontline workers drawn from 14 oil and gas companies took part in the survey. Data were analysed by performing structural equation modelling and findings revealed that management commitment, safety communication, safety motivation, and employee involvement were found to have a significant relationship (p = <0.005) to both safety compliance and safety participation, except for only safety training and safety participation where no relationship was established. A qualitative face to face interview was conducted among twelve different employees (both management and frontline employees) drawn from the industries. Thematic analysis of the qualitative data based on the interview reveal gaps around the different elements of safety culture in the industry and how it impacts safety performance of employees. Based on the paucity of data within the study area, the work has advanced up to date data around the impact of safety culture on workers behaviour in oil and gas industry in Nigeria. In addition, the study is considered timely and relevant. Based on internet research, it has covered the research gap within the region and advanced tangible recommendation around the establishment of safety leading indicators for employee’s safety performance in Nigeria oil and gas industry. The study concludes that timely strengthening of workplace safety culture and visible management approach to safety is important for occupational safety improvement in the industry. In addition to this, there is the need for policy realignment to aid in the promotion of safety culture and adherence to safety standards within the industry as practiced in other countries
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