924 resultados para Social engineering


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The research investigates the processes of adoption and implementation, by organisations, of computer aided production management systems (CAPM). It is organised around two different theoretical perspectives. The first part is informed by the Rogers model of the diffusion, adoption and implementation of innovations, and the second part by a social constructionist approach to technology. Rogers' work is critically evaluated and a model of adoption and implementation is distilled from it and applied to a set of empirical case studies. In the light of the case study data, strengths and weaknesses of the model are identified. It is argued that the model is too rational and linear to provide an adequate explanation of adoption processes. It is useful for understanding processes of implementation but requires further development. The model is not able to adequately encompass complex computer based technologies. However, the idea of 'reinvention' is identified as Roger's key concept but it needs to be conceptually extended. Both Roger's model and definition of CAPM found in the literature from production engineering tend to treat CAPM in objectivist terms. The problems with this view are addressed through a review of the literature on the sociology of technology, and it is argued that a social constructionist approach offers a more useful framework for understanding CAPM, its nature, adoption, implementation, and use. CAPM it is argued, must be understood on terms of the ways in which it is constituted in discourse, as part of a 'struggle for meaning' on the part of academics, professional engineers, suppliers, and users.

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This thesis considers four broad areas:(i) ANALYSIS OF THE STRESS FIELD.(a) research studies, relevant to the British Social Services considering the cultural setting, and the rigor with which they were conducted; (b) models of stress, specifically examining the theoretical soundness and practical application of the Medical, Engineering and Transactional models;(c) organisational models of stress relating specifically to human service organisations.(ii) QUALITATIVE AND QUANTITATIVE RESEARCH METHODOLOGIES.(a) the appropriate application of each respective methodology and the particular usefulness of qualitative research designs; (b) the relevance of understanding the language and terminology associated with the subject area prior to the implementation of survey methods; (iii) FIELDWORK.(a) Phase 1. By use of focus groups, in-depth interviews and diary keeping amongst a small range of teams and managers, the Researcher develops a basic conceptual framework of stress within a Social Services context. In addition a small scale personality inventory was administered to participants.(b) Phase 2. This consisted of three key elements: 6 case studies in which the Researcher implements and appraises the impact of a range of intervention strategies designed to assist teams and their managers in dealing more effectively with stress; the administration of a large scale survey to all the field social work teams within the Social Services Department; an analysis of the user role within the stress process by way of two focus groups.(iv) THEORETICAL DEVELOPMENT.

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Background: Stereotypically perceived to be an ‘all male’ occupation, engineering has for many years failed to attract high numbers of young women [1,2]. The reasons for this are varied, but tend to focus on misconceptions of the profession as being more suitable for men. In seeking to investigate this issue a participatory research approach was adopted [3] in which two 17 year-old female high school students interviewed twenty high school girls. Questions focused on the girls’ perceptions of engineering as a study and career choice. The findings were recorded and analysed using qualitative techniques. The study identified three distinctive ‘influences’ as being pivotal to girls’ perceptions of engineering; pedagogical; social; and, familial. Pedagogical Influences: Pedagogical influences tended to focus on science and maths. In discussing science, the majority of the girls identified biology and chemistry as more ‘realistic’ whilst physics was perceived to more suitable for boys. The personality of the teacher, and how a particular subject is taught, proved to be important influences shaping opinions. Social Influences: Societal influences were reflected in the girls’ career choice with the majority considering medical or social science related careers. Although all of the girls believed engineering to be ‘male dominated’, none believed that a woman should not be engineer. Familial Influences: Parental influence was identified as key to career and study choice; only two of the girls had discussed engineering with their parents of which only one was being actively encouraged to pursue a career in engineering. Discussion: The study found that one of the most significant barriers to engineering is a lack of awareness. Engineering did not register in the girls’ lives, it was not taught in school, and only one had met a female engineer. Building on the study findings, the discussion considers how engineering could be made more attractive to young women. Whilst misconceptions about what an engineer is need to be addressed, other more fundamental pedagogical barriers, such as the need to make physics more attractive to girls and the need to develop the curriculum so as to meet the learning needs of 21st Century students are discussed. By drawing attention to the issues around gender and the barriers to engineering, this paper contributes to current debates in this area – in doing so it provides food for thought about policy and practice in engineering and engineering education.

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In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.

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In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

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This positional paper proposes a conceptual framework and methodological approach for use in a PhD study investigating the longer term educational and social impact of 'active' engineering focused interventions for children age 8-10 in the UK. The study will critically analyse how a child's participation in an engineering education activity contributes to the Engineering Capital that the child possesses; focusing on how the child's awareness and perceptions about engineering are affected. To achieve this aim it is proposed that Grounded Theory methodology be used to enable an in-depth analysis of participation from the perspective of the child participant. The study proposed will be longitudinal, taking place over three formative years for the education and career aspirations of the child, from age 8-10 to 11-13. Although the research is in its infancy, this paper will provide the opportunity to develop theory in an underdeveloped area of engineering education research.

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The aim of this paper is to propose a conceptual framework for studying the knowledge transfer problem within the supply chain. The social network analysis (SNA) is presented as a useful tool to study knowledge networks within supply chain, to visualize knowledge flows and to identify the accumulating knowledge nodes of the networks. © 2011 IEEE.

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This paper focuses upon the argument that the role played by the engineering profession within today's society has changed markedly over the past several years from providing the foundations for contemporary life to leading societal change and becoming one of the key driver's of future social development. Coining the term 'Engineering-Sociology' this paper contributes to engineering education and engineering education research by proposing a new paradigm upon which future engineering education programmes and engineering education research might build. Developed out of an approach to learning and teaching practice, Engineering-Sociology encapsulates both traditional and applied approaches to engineering education and engineering education research. It suggests that in order to meet future challenges there is a need to bring together what are generally perceived to be two diametrically opposed paradigms, namely engineering and sociology. Building on contemporary theoretical and pedagogical arguments in engineering education research, the paper concludes that by encouraging engineering educators to 'think differently', Engineering-Sociology can provide an approach to learning and teaching that both enhances the student experience and meets the changing needs of society.

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In recent years, a surprising new phenomenon has emerged in which globally-distributed online communities collaborate to create useful and sophisticated computer software. These open source software groups are comprised of generally unaffiliated individuals and organizations who work in a seemingly chaotic fashion and who participate on a voluntary basis without direct financial incentive. ^ The purpose of this research is to investigate the relationship between the social network structure of these intriguing groups and their level of output and activity, where social network structure is defined as (1) closure or connectedness within the group, (2) bridging ties which extend outside of the group, and (3) leader centrality within the group. Based on well-tested theories of social capital and centrality in teams, propositions were formulated which suggest that social network structures associated with successful open source software project communities will exhibit high levels of bridging and moderate levels of closure and leader centrality. ^ The research setting was the SourceForge hosting organization and a study population of 143 project communities was identified. Independent variables included measures of closure and leader centrality defined over conversational ties, along with measures of bridging defined over membership ties. Dependent variables included source code commits and software releases for community output, and software downloads and project site page views for community activity. A cross-sectional study design was used and archival data were extracted and aggregated for the two-year period following the first release of project software. The resulting compiled variables were analyzed using multiple linear and quadratic regressions, controlling for group size and conversational volume. ^ Contrary to theory-based expectations, the surprising results showed that successful project groups exhibited low levels of closure and that the levels of bridging and leader centrality were not important factors of success. These findings suggest that the creation and use of open source software may represent a fundamentally new socio-technical development process which disrupts the team paradigm and which triggers the need for building new theories of collaborative development. These new theories could point towards the broader application of open source methods for the creation of knowledge-based products other than software. ^

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Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

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In spite of tremendous efforts, women are still under-represented in the field of science. Post-graduate education and early tenure track employment are part of the academic career establish-ment in research and development during periods that usually overlap with family formation. Though women tend to leave science mainly after obtaining their PhD, and the timing of mother-hood plays a vital role in a successful research career, qualitative data on this life period are scarce. Our paper focuses on how the normative and institutional contexts shape female PhD engineering students’ family plans. The research was based on intersections of life course and risk and uncertainty theories. Using qualitative interviews we explored how contradicting social norms of childbearing cause tensions in postgraduate students’ lives, and how the different uncer-tainties and risks permeate young researchers’ decisions on early life events. We concluded that, despite the general pattern of delaying motherhood among higher educated women, these students struggle against this postponement, and they hardly have any good options to avoid risk stem-ming from uncertainties and from some characteris-tics of studying and working in engineering. Find-ings of this research may call the attention of stake-holders to possible intervention points.

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Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

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Based on an original and comprehensive database of all feature fiction films produced in Mercosur between 2004 and 2012, the paper analyses whether the Mercosur film industry has evolved towards an integrated and culturally more diverse market. It provides a summary of policy opportunities in terms of integration and diversity, emphasizing the limiter role played by regional policies. It then shows that although the Mercosur film industry remains rather disintegrated, it tends to become more integrated and culturally more diverse. From a methodological point of view, the combination of Social Network Analysis and the Stirling Model opens up interesting research tracks to analyse creative industries in terms of their market integration and their cultural diversity.

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This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)