199 research outputs found
Investigating consumer adoption, usage and impact of broadband: UK households
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Despite a large investment, the majority of countries especially the UK demonstrate a slow adoption of broadband. In order to enhance the adoption and use of broadband this research examines the factors influencing the decisions of household consumers. This research aims to address the two main areas of concern: first, to investigate consumer-level factors affecting the adoption of broadband in UK households; and second, to understand the usage of broadband and its impact upon household consumers in the UK. This research adopted a quantitative approach that was executed in the following steps. First, it developed a conceptual model by selecting and justifying relevant constructs from appropriate theories and models related to technology adoption, usage and impact. Second, it operationalised the constructs by developing and validating the research instrument by employing the content validity, reliability and construct validity approach. Finally, it empirically validated and refined the conceptual model by employing a survey research approach.
The findings suggested that all the constructs included in the conceptual model, except knowledge, significantly influence the consumers when adopting broadband in a UK household. The significant constructs include relative advantage, utilitarian outcomes, hedonic outcomes, primary influence, facilitating conditions resources and self-efficacy. The rate and variety of Internet usage is significantly higher for broadband consumers than narrowband ones. It was also found that significantly more numbers of broadband consumers perceived changes in time allocation patterns on various daily life activities than narrowband ones. This research contributes towards theory, practice and policy. The contribution of this research towards theory is that it integrates and determines the appropriate information systems (IS) literature in order to enhance knowledge of technology adoption from the consumers' perspectives. An added contribution to theory is the development and validation of a research instrument that future studies can utilise to examine broadband and other similar technologies in household context. Considering the slow adoption of broadband, this research also provides implications for policy makers and the providers of broadband in order to encourage and promote homogenous adoption and usage
Preference prediction through feature-based collaborative filtering of textual reviews
No full textText reviews are often used by users to decide whether to buy a product or watch a movie or dine in a restaurant. Most of these reviews are raw text and lack a formal structure. Computers cannot easily understand and interpret these reviews to analyze and aggregate them. Users have to manually read through these reviews to find the useful information about the concerned restaurant. We use the topical and sentimental information compiled from raw textual reviews to understand user preferences. We use these preferences to cluster similar users together and then predict users' topical feelings towards the restaurants for which they may be requesting information and to make suitable recommendations. Users have similarities in their preferences for particular topics under which the restaurants have been reviewed. Therefore, we can soft-cluster them using these similarities extracted from their reviewing history. These cluster membership probabilities help us make predictions about the user's sentiments in each topic for the target restaurant. Our results show our accuracy for predicting these sentiments and show that we can provide recommendations to users in most topics for the target restaurant.M.S.Includes bibliographical referencesIncludes vitaby Yogesh Kakodka
Learning API mappings for programming platforms
No full textSoftware developers often need to port applications written for a source platform to a target platform. One of the key tasks here is to find matching API calls in the target platform for the given API calls in the source platform. This task involves exhaustive reading in target platform API (Application Programming Interface) documentation to identify API methods corresponding to the given API methods of the source platform. We introduce an approach to the problem of inferring mapping between the APIs of a source and target platforms. It is constructed based on independently developed applications on source and target platforms performing similar functionality. We observe that in building these applications, developers exercised knowledge of the corresponding APIs. We develop two dynamic analysis techniques to systematically harvest this knowledge and infer likely mappings between the Graphical APIs of JavaME and Android Graphical platform. Rosetta Mapper: A tool which provides a ranked list of target API methods or method sequences that likely map to each source API method or method sequences. Rosetta Classifier: A supervised learning tool which classifies whether the given mapping between source API and target API is true or false using support vector machines.M.S.Includes bibliographical referencesby Yogesh Padmanaba
Study on thermal co-pyrolysis of jatropha deoiled cake and polyolefins
No full text Three plastics, high density polyethylene (HDPE), polypropylene (PP) and polystyrene (PS), were individually co-pyrolysed with deoiled cake of jatropha (JC) at 400 and 450°C in a batch reactor in the presence of nitrogen under atmospheric pressure to produce modified liquid fractions. At higher temperature (450°C), the yield of liquid fractions by the pyrolysis of plastics (HDPE, PP and PS) alone was found to increase by 11, 12.5 and 11% for HDPE, PP and PS, respectively. Furthermore, the gaseous fraction increased by 1.3 to 2.6% while the residue generation reduced by 12.3 to 15.1%. In comparison with only plastics pyrolysis, the yield of the liquid fraction improved by 2.0 to 4.9% for their co-pyrolysis with JC. Gas chromatography–mass spectrometry analyses demonstrated that the co-processing afforded a reduction of paraffin and olefins in the liquid fractions for all of the experiments. This reduction was found to be in the order of PS > PP > HDPE. Furthermore, the proportion of oxygenates in the liquid product increased in the order of PP > HDPE > PS. Physical characteristics such as oxygenates, water contents, acid values and viscosity increased during the co-pyrolysis of plastics and JC in contrast to the liquid fractions obtained from the pyrolysis of pure plastics. Furthermore, co-pyrolysis offered a reduction in calorific values. </jats:p
A Comparative Study of Business-to-Government Information Sharing Arrangements for Tax Reporting
No full textHaving tax transparency is getting more important and enforced by more and more countries around the world. To deal with tax evasion, OECD has developed an Automatic Exchange of Information (AEOI) standard. The implementation of this standard differs among countries. In this study, we explore factors explaining the differences between two information sharing arrangements in implementing the AEOI standard. In both cases, the information sharing architecture and the accompanying governance arrangement are investigated. The findings of the exploratory study show that the differences are influenced by available IT capabilities, interoperability, trust among information sharing partners, power difference, inter-organizational relationship, and perceived benefits of implementing such arrangements. Ten propositions are derived explaining the differences which can be tested in further research.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
AUGMENTED AI-KNOWLEDGE DRIVEN INTELLIGENT SYSTEMS FOR ADVERSARIAL-DYNAMIC UNCERTAINTY AND COMPLEXITY
Get PDFGoal: ISO 31000 Risk Management (RM) recently re-defined risk as the effect of uncertainty on an organization's ability to meet the objectives. Earlier, it defined risk as a combination of the probability and scope of the (predicted) consequences. The revised ISO Risk advances beyond a static world guided by prediction and pre-determination based on historical data to a dynamic world characterized by uncertainty and complexity focused on business outcomes over data inputs. Our Knowledge Management (KM) R&D adopted by global organizations such as Nasa and Big Banks is readily applicable to provide a 25-year head start to organizations in above ISO risk evolution. Results: Over the last two decades, we have developed theoretical and applied frameworks for the dynamic world characterized by uncertainty and complexity, with business outcomes as drivers of real-time performance rather than data inputs. Our forward-looking anticipation of surprise focus of KM drives future organizational adaptation, survival and competence in face of discontinuous environmental change at organizations such as Goldman Sachs. Our KM focus manages change, uncertainty and complexity as primary (outcome) targets in contrast to data-driven (input) approaches. Its focus on dynamic uncertainty is complemented by adversarial uncertainty from cyber-adversarial environments. Originality | Value: Quantum uncertainty – encapsulating the two uncertainty types – and time-space complexity from increasingly non-deterministic and statistically non-normal and non-linear environments are the focus of our KM R&D underpinning development of quantum minds. Our latest AI-Cybersecurity KM practices are advancing the future of Pentagon’s C4I-Cyber-Command-Control-Advanced Battle Management Systems and AWS Network-Centric Agile-Resilient Cloud Computing.Objetivo: A ISO 31000 Risk Management (RM) recentemente redefiniu o risco como o efeito da incerteza na capacidade de uma organização de atingir os objetivos. Anteriormente, definia o risco como uma combinação da probabilidade e do escopo das consequências (previstas). O ISO Risk revisado avança para além de um mundo estático guiado por previsão e predeterminação com base em dados históricos para um mundo dinâmico caracterizado por incerteza e complexidade focado em resultados de negócios sobre entradas de dados. Nossa P&D de Gestão do Conhecimento (KM) adotada por organizações globais como a Nasa e Big Banks é prontamente aplicável para fornecer uma vantagem inicial de 25 anos para organizações com evolução de risco acima da ISO. Resultados: Nas últimas duas décadas, desenvolvemos estruturas teóricas e aplicadas para o mundo dinâmico caracterizado pela incerteza e complexidade, com resultados de negócios como impulsionadores de desempenho em tempo real, em vez de entradas de dados. Nossa antecipação voltada para o futuro do foco surpresa de KM impulsiona a futura adaptação organizacional, sobrevivência e competência em face da mudança ambiental descontínua em organizações como a Goldman Sachs. Nosso foco em KM gerencia a mudança, a incerteza e a complexidade como alvos primários (resultados), em contraste com as abordagens baseadas em dados (entrada). Seu foco na incerteza dinâmica é complementado pela incerteza adversária do ambiente ciberadversário. Originalidade ½ Valor: A incerteza quântica – encapsulando os dois tipos de incerteza – e a complexidade do espaço-tempo de ambientes cada vez mais não determinísticos e estatisticamente não normais e não lineares são o foco de nosso desenvolvimento de P&D de KM de mentes quânticas. Nossas práticas mais recentes de IA-Cybersecurity KM estão avançando no futuro dos sistemas de gerenciamento de batalha C4I-Cyber-Command-Control-Advanced do Pentágono e da computação em nuvem ágil e resiliente centrada na rede da AWS.
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[1] All of our listed published research papers, expert papers, industry keynotes, conference presentations mentioned in this paper and many more underlying our R&D program are accessible and downloadable in full-video and full-text without any need for sharing any kind of information or any kind of registration from the following online web sites: Amazon Author Page, Biographical Page with All Links, Global CEO-CxO Networks 1, Global CEO-CxO Networks 2, Global CEO-CxO Networks 3, Global CEO-CxO Networks 4, LinkedIn Page, Publication List Page, SSRN Publications Page, YouTube Page
Polarization and acculturation in US Election 2016 outcomes – Can twitter analytics predict changes in voting preferences
Get PDFElections are among the most critical events in a national calendar. During elections, candidates increasingly use social media platforms to engage voters. Using the 2016 US presidential election as a case study, we looked at the use of Twitter by political campaigns and examined how the drivers of voter behaviour were reflected in Twitter. Social media analytics have been used to derive insights related to theoretical frameworks within political science. Using social media analytics, we investigated whether the nature of social media discussions have an impact on voting behaviour during an election, through acculturation of ideologies and polarization of voter preferences. Our findings indicate that discussions on Twitter could have polarized users significantly. Reasons behind such polarization were explored using Newman and Sheth's model of voter's choice behaviour. Geographical analysis of tweets, users, and campaigns suggests acculturation of ideologies among voting groups. Finally, network analysis among voters indicates that polarization may have occurred due to differences between the respective online campaigns. This study thus provides important and highly relevant insights into voter behaviour for the future management and governance of successful political campaigns.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
Synergetic pyrolysis of high density polyethylene and Jatropha and Karanj cakes: A thermogravimetric study
No full textThe Untold Story of USA Presidential Elections in 2016 - Insights from Twitter Analytics
No full textPart 4: Social Media and Web 3.0 for SmartnessInternational audienceElections are the most critical events for any nation and paves the path for future growth and prosperity of the economy. Due to its high impact, a lot of discussions take place among all stakeholders in social media. In this study, we attempt to examine the discussions surrounding USA Election, 2016 in Twitter. Further we highlight some of the domains influencing the voter behaviour by applying the outcome of Twitter analytics to Newman and Sheth’s model of Voter Choice. Through the analysis of 784,153 tweets from 287,838 users over 18 weeks, we present interesting findings on what may have affected the polarization of USA elections
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