60,822 research outputs found

    Sponsorship image and value creation in E-sports

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    .E-sports games can drive the sports industry forward and sponsorship is the best way to engage consumers of this new sport. The purpose of this study is to examine the effect of sponsorship image and consumer participation in co-creation consumption activities on fans’ sponsorship response (represented by the variables interest, purchase intention and word of mouth) in e-sports. Four antecedent variables build sponsorship image (i.e., ubiquity of sport, sincerity of sponsor, attitude to sponsor and team identification). A quantitative approach is used for the purposes of this study. Some 445 questionnaires were filled in by fans who watch e-sports in Spain; these are analyzed using partial least squares structural equation modeling (PLS-SEM). The outcomes show that sponsor antecedents are crucial factors if a sponsor wants to change their sponsorship image and influence sponsorship response, and that it is also possible to use participation to improve responsesS

    Analysis of reliable deployment of TDOA local positioning architectures

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    .Local Positioning Systems (LPS) are supposing an attractive research topic over the last few years. LPS are ad-hoc deployments of wireless sensor networks for particularly adapt to the environment characteristics in harsh environments. Among LPS, those based on temporal measurements stand out for their trade-off among accuracy, robustness and costs. But, regardless the LPS architecture considered, an optimization of the sensor distribution is required for achieving competitive results. Recent studies have shown that under optimized node distributions, time-based LPS cumulate the bigger error bounds due to synchronization errors. Consequently, asynchronous architectures such as Asynchronous Time Difference of Arrival (A-TDOA) have been recently proposed. However, the A-TDOA architecture supposes the concentration of the time measurement in a single clock of a coordinator sensor making this architecture less versatile. In this paper, we present an optimization methodology for overcoming the drawbacks of the A-TDOA architecture in nominal and failure conditions with regards to the synchronous TDOA. Results show that this optimization strategy allows the reduction of the uncertainties in the target location by 79% and 89.5% and the enhancement of the convergence properties by 86% and 33% of the A-TDOA architecture with regards to the TDOA synchronous architecture in two different application scenarios. In addition, maximum convergence points are more easily found in the A-TDOA in both configurations concluding the benefits of this architecture in LPS high-demanded applicationS

    Recent Hong Kong cinema and the generic role of film noir in relation to the politics of identity and difference

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    This thesis identifies a connection in Hong Kong cinema with classical Hollywood film noir and examines what it will call a 'reinvestment' in film noir in recent films. It will show that this reinvestment is a discursive strategy that both engages the spectator-subject in the cinematic practice and disengages him or her from the hegemony of the discourse by decentring the narrative. The thesis argues that a cinematic practice has occurred in the recent reinvestment of film noir in Hong Kong, which restages the intertextual relay of the historical genre that gives rise to an expectation of ideas about social instability. The noir vision that is seen as related to the fixed categories of film narratives, characterizations and visual styles is reassessed in the course of the thesis using Derridian theory. The focus of analysis is the way in which the constitution of meanings is dependent on generic characteristics that are different. Key to the phenomenon is a film strategy that destabilizes, differs and defers the interpretation of crises-personal, social, political and/or cultural-by soliciting self-conscious re-reading of suffering, evil, fate, chance and fortune. It will be argued that such a strategy evokes the genre expectation as the film invokes a network of ideas regarding a world perceived by the audience in association with the noirish moods of claustrophobia, paranoia, despair and nihilism. The noir vision is thus mutated and transformed when the film device differs and defers the conception of the crises as tragic in nature by exposing the workings of the genre amalgamation and the ideological function of the cinematic discourse. Thus, noirishness becomes both an affect and an agent that contrives a self-reflexive re-reading of the tragic vision and of the conventional comprehension of reality within the discursive practice. The film strategy, as an agent that problematizes the film form and narrative, gives rise to what I call a politics of difference, which may also be understood as the Lyotardian 'language game' or a practice of 'pastiche' in Jameson's terminology. Under the influence of the film strategy, the spectator is enabled to negotiate his or her understanding of recent Hong Kong cinema diegetically and extra-diegetically by traversing different positions of cinematic identification. When the practice of genre amalgamation adopts the visual impact of the noirish film form, the film turns itself into a playing field of 'fatal' misrecognition or a site of question. Through cinematic identification and alienation from the identification, the spectator-subject is enabled to experience the misrecognition as the film slowly foregrounds the way in which the viewer's presence is implicated in the narrative. This thesis demonstrates that certain contemporary Hong Kong films introduce this selfconscious mode of explication and interpretation, which solicits the spectator to negotiate his or her subject-position in the course of viewing. The notions of identity and subjectivity under scrutiny will thus be reread. With reference to The Private Eye Blue, Swordsman II, City a/Glass and Happy Together, the thesis shall explore the ways in which the Hong Kong films enable and facilitate a negotiation of cultural identity

    Speciation of organoarsenicals in aqueous solutions by Raman spectrometry and quantum chemical calculations

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    .Knowledge about the existence and stability of different species of organoarsenicals in solution is of the most significant interest for fields so different as chemical, environmental, biological, toxicological and forensic. This work provides a comparative evaluation of the Raman spectra of four organoarsenicals (o-arsanilic acid, p-arsanilic acid, roxarsone and cacodylic acid) in aqueous solutions under acidic, neutral and alkaline conditions. Speciation of some of these organoarsenicals is possible by Raman spectrometry at different selected pHs. Further, we examine the proficiency of computational chemistry to obtain the theoretical Raman spectra of the four organoarsenicals compounds. To this end, we employ a computational protocol that includes explicit water molecules and conformational sampling, finding that the calculated organoarsenicals spectra agree reasonably well with those experimentally obtained in an aqueous solution in the whole pH range covered. Finally, we highlight the effectiveness of quantum chemical calculations to identify organoarsenicals in an aqueous solution.S

    Combined vehicle to building (V2B) and vehicle to home (V2H) strategy to increase electric vehicle market share

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    .Buildings are one of the most important energy consumers in modern economy countries. The massive use of electrical vehicles could help decarbonizing the economy by using electricity produced using renewable energy. Combined use of Vehicle to Grid (V2G), Vehicle to Home (V2H) and Vehicle to Building (V2B) is one of the strategies to increase the number of electrical vehicles, ensure a better coupling between energy generation and consumption, reducing peak demand and increasing global energy efficiency. This research presents a novel approach of combined use of V2H and V2B that can be applied in different scenarios such as when the building workers own EVs, company shared car fleets or leasing, among others. Recharged energy at workers homes during night hours is delivered in the building during daily working hours lowering peak demand, reducing carbon intensity and energy cost savings. The results show that the methodology is feasible and can be extended to other cases and greatly contribute to better energy efficiency, reduces peak demand in buildings and increase electric vehicles penetration in transport to workplaces.S

    Facial expression recognition and intensity estimation.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.Facial Expression is one of the profound non-verbal channels through which human emotion state is inferred from the deformation or movement of face components when facial muscles are activated. Facial Expression Recognition (FER) is one of the relevant research fields in Computer Vision (CV) and Human-Computer Interraction (HCI). Its application is not limited to: robotics, game, medical, education, security and marketing. FER consists of a wealth of information. Categorising the information into primary emotion states only limit its performance. This thesis considers investigating an approach that simultaneously predicts the emotional state of facial expression images and the corresponding degree of intensity. The task also extends to resolving FER ambiguous nature and annotation inconsistencies with a label distribution learning method that considers correlation among data. We first proposed a multi-label approach for FER and its intensity estimation using advanced machine learning techniques. According to our findings, this approach has not been considered for emotion and intensity estimation in the field before. The approach used problem transformation to present FER as a multilabel task, such that every facial expression image has unique emotion information alongside the corresponding degree of intensity at which the emotion is displayed. A Convolutional Neural Network (CNN) with a sigmoid function at the final layer is the classifier for the model. The model termed ML-CNN (Multilabel Convolutional Neural Network) successfully achieve concurrent prediction of emotion and intensity estimation. ML-CNN prediction is challenged with overfitting and intraclass and interclass variations. We employ Visual Geometric Graphics-16 (VGG-16) pretrained network to resolve the overfitting challenge and the aggregation of island loss and binary cross-entropy loss to minimise the effect of intraclass and interclass variations. The enhanced ML-CNN model shows promising results and outstanding performance than other standard multilabel algorithms. Finally, we approach data annotation inconsistency and ambiguity in FER data using isomap manifold learning with Graph Convolutional Networks (GCN). The GCN uses the distance along the isomap manifold as the edge weight, which appropriately models the similarity between adjacent nodes for emotion predictions. The proposed method produces a promising result in comparison with the state-of-the-art methods.Author's List of Publication is on page xi of this thesis

    Thermal performance enhancement of nanofluids based parabolic trough solar collector (NPTSC) for sustainable environment

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    Due to rapid industrialization and urbanization, upward rise in carbon emissions in the atmosphere, and depletion of fossil fuel and gas reserves have forced to find alternative renewable energy resources, where solar energy is one of the most promising source. Parabolic trough solar collectors (PTCs) can effectively transfer high temperature in the tube of receiver upto 400 ¬įC. In this study, Computational Fluid Dynamics (CFD) analysis is used to analyse the effect of multiple working fluids on efficiency of the PTC. Two different types of nanofluids used for analyising the thermal efficiency of PTC through CFD simulations, are Alumina and Copper-oxide nanofluids. The concentration of Copper Oxide and Alumina was kept to 0.01% in the nanofluids. The efficiency for PTC is calculated at two different mass flow rates i.e., 0.0112 Kg/s and 0.0224 Kg/s. The highest efficiency is 13.01 and 13.1% using Al2O3 as nanofluids at 0.0112 Kg/s and 0.0224 Kg/s flow rates, while CuO has an efficiency of 13.92% and 14.79% for these flow rates. The behaviour of absorber tube material on temperature distribution for steel, copper and aluminum as absorber tube material was also investigated. Changing the material from steel to copper and aluminum increased the outlet temperature of the fluid. The maximum output temperature was achieved for copper is 311 K while steel and aluminum showed lower temperature of 307 K and 308 K of the fluid at the outlet. Furthermore, the impact of the receiver tube's length on the working fluid's temperature is also studied. Copper Oxide nanofluid has higher temperature at the outlet for both mass flow rates as compared to alumina nanofluid. Accordingly, a comparison was made for the CFD results with the experimental findings from literature. The nanofluids based PTCs system is promising method for the sustainable environment applications
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