33 resultados para Network Graph and RAN Model
em Aston University Research Archive
Resumo:
The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.
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This thesis includes analysis of disordered spin ensembles corresponding to Exact Cover, a multi-access channel problem, and composite models combining sparse and dense interactions. The satisfiability problem in Exact Cover is addressed using a statistical analysis of a simple branch and bound algorithm. The algorithm can be formulated in the large system limit as a branching process, for which critical properties can be analysed. Far from the critical point a set of differential equations may be used to model the process, and these are solved by numerical integration and exact bounding methods. The multi-access channel problem is formulated as an equilibrium statistical physics problem for the case of bit transmission on a channel with power control and synchronisation. A sparse code division multiple access method is considered and the optimal detection properties are examined in typical case by use of the replica method, and compared to detection performance achieved by interactive decoding methods. These codes are found to have phenomena closely resembling the well-understood dense codes. The composite model is introduced as an abstraction of canonical sparse and dense disordered spin models. The model includes couplings due to both dense and sparse topologies simultaneously. The new type of codes are shown to outperform sparse and dense codes in some regimes both in optimal performance, and in performance achieved by iterative detection methods in finite systems.
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Sales leadership research has typically taken a leader-focused approach, investigating key questions from a top-down perspective. Yet considerable research outside sales has advocated a view of leadership that takes into account the fact that employees look beyond a single designated individual for leadership. In particular, the social networks of leaders have been a popular topic of investigation in the management literature, although coverage in the sales literature remains rare. The present paper conceptualizes the sales leadership role as one in which the leader must manage a network of simultaneous relationships; several types of sales manager relationships, such as the sales-manager-to-top-manager and the sales-manager-to-sales manager relationships, have received limited attention in the sales literature to date. Taking an approach based on social network theory, we develop a conceptualization of the sales manager as a "network engineer," who must manage multiple relationships, and the flows between them. Drawing from this model, we propose a detailed agenda for future sales research. © 2012 PSE National Educational Foundation. All rights reserved.
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It has been suggested that, in order to maintain its relevance, critical research must develop a strong emphasis on empirical work rather than the conceptual emphasis that has typically characterized critical scholarship in management. A critical project of this nature is applicable in the information systems (IS) arena, which has a growing tradition of qualitative inquiry. Despite its relativist ontology, actor–network theory places a strong emphasis on empirical inquiry and this paper argues that actor–network theory, with its careful tracing and recording of heterogeneous networks, is well suited to the generation of detailed and contextual empirical knowledge about IS. The intention in this paper is to explore the relevance of IS research informed by actor–network theory in the pursuit of a broader critical research project as de? ned in earlier work.
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This paper builds on Granovetter's distinction between strong and weak ties [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol. 78(6) 1360–1380] in order to respond to recent calls for a more dynamic and processual understanding of networks. The concepts of potential and latent tie are deductively identified, and their implications for understanding how and why networks emerge, evolve, and change are explored. A longitudinal empirical study conducted with companies operating in the European motorsport industry reveals that firms take strategic actions to search for potential ties and reactivate latent ties in order to solve problems of network redundancy and overload. Examples are given, and their characteristics are examined to provide theoretical elaboration of the relationship between the types of tie and network evolution. These conceptual and empirical insights move understanding of the managerial challenge of building effective networks beyond static structural contingency models of optimal network forms to highlight the processes and capabilities of dynamic relationship building and network development. In so doing, this paper highlights the interrelationship between search and redundancy and the scope for strategic action alongside path dependence and structural influences on network processes.
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This paper presents a simple three-sector model that seeks to establish links between structural change in employment and the level of economic development. The model is a modified version of that of Rowthorn - Wells (1987). The theoretical analysis is supplemented with simple econometric tests which illustrate how the modified Rowthorn - Wells model can be used (i) to motivate empirical estimates of the link between the level of development and structures of employment, and (ii) to illustrate structural distortions under command economies.
Resumo:
In this paper we present a simple three-sector model explaining the structural change in employment, which is a modified version of Rowthorn-Wells (1987). We supplement the theoretical analysis with simple econometric tests, which illustrate how the modified Rowthorn-Wells model can be used to (i) motivate empirical estimates of the link between the level of development and structures of employment, (ii) illustrate structural distortions under the command economies, and the structural adjustment that happened during the post-Communist transition. We demonstrate that in the case of these economies, the transition process leads to an adjustment to the employment structures predicted by the model.
Resumo:
Cell-wall components (cellulose, hemicellulose (oat spelt xylan), lignin (Organosolv)), and model compounds (levoglucosan (an intermediate product of cellulose decomposition) and chlorogenic acid (structurally similar to lignin polymer units)) have been investigated to probe in detail the influence of potassium on their pyrolysis behaviours as well as their uncatalysed decomposition reaction. Cellulose and lignin were pretreated to remove salts and metals by hydrochloric acid, and this dematerialized sample was impregnated with 1% of potassium as potassium acetate. Levoglucosan, xylan and chlorogenic acid were mixed with CHCOOK to introduce 1% K. Characterisation was performed using thermogravimetric analysis (TGA) and differential thermal analysis (DTA). In addition to the TGA pyrolysis, pyrolysis-gas chromatography-mass spectrometry (PY-GC-MS) analysis was introduced to examine reaction products. Potassium-catalysed pyrolysis has a huge influence on the char formation stage and increases the char yields considerably (from 7.7% for raw cellulose to 27.7% for potassium impregnated cellulose; from 5.7% for raw levoglucosan to 20.8% for levoglucosan with CHCOOK added). Major changes in the pyrolytic decomposition pathways were observed for cellulose, levoglucosan and chlorogenic acid. The results for cellulose and levoglucosan are consistent with a base catalysed route in the presence of the potassium salt which promotes complete decomposition of glucosidic units by a heterolytic mechanism and favours its direct depolymerization and fragmentation to low molecular weight components (e.g. acetic acid, formic acid, glyoxal, hydroxyacetaldehyde and acetol). Base catalysed polymerization reactions increase the char yield. Potassium-catalysed lignin pyrolysis is very significant: the temperature of maximum conversion in pyrolysis shifts to lower temperature by 70 K and catalysed polymerization reactions increase the char yield from 37% to 51%. A similar trend is observed for the model compound, chlorogenic acid. The addition of potassium does not produce a dramatic change in the tar product distribution, although its addition to chlorogenic acid promoted the generation of cyclohexane and phenol derivatives. Postulated thermal decomposition schemes for chlorogenic acid are presented. © 2008 Elsevier B.V. All rights reserved.
Resumo:
This review aims to systematically evaluate the empirical literature relating to the interpersonal functioning of those with eating disorder psychopathology and presents a preliminary model to help the formulation of patients' problems. Following a thorough literature search, 35 papers were included in this systematic review. The vast majority of studies indicate a strong association between eating psychopathology and certain maladaptive personality traits. The origins of social anxiety and poor social support that have been described as maintaining eating disorders appear to differ according to diagnostic groups. Interpersonal difficulties in people with restrictive behaviors such as anorexia appear to be related to the avoidance of expressing feelings to others and to giving priority to other people's feeling over their own. While interpersonal difficulties in patients with bulimia nervosa appear to be more related to interpersonal distrust and negative interaction and conflict with others. These concepts are presented in a preliminary model of interpersonal functioning in the eating disorders. © 2012 Elsevier Ltd.
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This paper explores the results of a consensus development exercise that explored diverse perspectives and sought to identify key principles for the development of user involvement in a cancer network. The exercise took place within one of 34 UK cancer networks and was a collaboration between the NHS, two universities and two voluntary sector organizations. The paper explores professionals’ and users’ perspectives on user involvement with reference to the current sociopolitical context of user participation. British policy documents have placed increasing emphasis on issues of patient and public participation in the evaluation and development of health services, and the issue of lay participation represents an important aspect of a critical public health agenda. The project presented here shows that developing user involvement may be a complex task, with lack of consensus on key issues representing a significant barrier. Further, the data suggest that professional responses can partly be understood in relation to specific occupational standpoints and strategies that potentially allow professionals to define and limit users’ involvement. The implications of these findings and the impact of the consensus development process itself are discussed.
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This paper relates the concept of network learning - learning by a group of organizations as a group - to change and notions of change management. Derived initially from a review of literature on organizational learning (OL) and interorganizational networks, and secondary cases of network learning, the concept was evaluated and developed through empirical investigation of five network learning episodes in the group of organizations that comprises the English prosthetics service. We argue that the notion of network learning enables a richer understanding of developments in networks over extended periods of time than can be afforded through more established concepts of change and change management alone.
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This study re-examines the one-dimensional equilibrium model of Gibilaro and Rowe (1974) for a segregating gas fluidized bed. The model was based on volumetric jetsam concentration and divided the bed contents into bulk and wake phases, taking account of bulk and wake flux, segregation, exchange between the bulk and wake phases, and axial mixing. Due to the complex nature of the model and its unstable solution, the lack of computing power at the time prevented the authors from doing little more than the analytical solutions to specific cases of this model. This paper provides a numerical total solution and allows the effect of the respective parameters to be compared for the first time. There is also a comparison with experimental results, which showed a reasonable agreement.
Learning and change in interorganizational networks:the case for network learning and network change
Resumo:
The ALBA 2002 Call for Papers asks the question ‘How do organizational learning and knowledge management contribute to organizational innovation and change?’. Intuitively, we would argue, the answer should be relatively straightforward as links between learning and change, and knowledge management and innovation, have long been commonly assumed to exist. On the basis of this assumption, theories of learning tend to focus ‘within organizations’, and assume a transfer of learning from individual to organization which in turn leads to change. However, empirically, we find these links are more difficult to articulate. Organizations exist in complex embedded economic, political, social and institutional systems, hence organizational change (or innovation) may be influenced by learning in this wider context. Based on our research in this wider interorganizational setting, we first make the case for the notion of network learning that we then explore to develop our appreciation of change in interorganizational networks, and how it may be facilitated. The paper begins with a brief review of lite rature on learning in the organizational and interorganizational context which locates our stance on organizational learning versus the learning organization, and social, distributed versus technical, centred views of organizational learning and knowledge. Developing from the view that organizational learning is “a normal, if problematic, process in every organization” (Easterby-Smith, 1997: 1109), we introduce the notion of network learning: learning by a group of organizations as a group. We argue this is also a normal, if problematic, process in organizational relationships (as distinct from interorganizational learning), which has particular implications for network change. Part two of the paper develops our analysis, drawing on empirical data from two studies of learning. The first study addresses the issue of learning to collaborate between industrial customers and suppliers, leading to the case for network learning. The second, larger scale study goes on to develop this theme, examining learning around several major change issues in a healthcare service provider network. The learning processes and outcomes around the introduction of a particularly controversial and expensive technology are described, providing a rich and contrasting case with the first study. In part three, we then discuss the implications of this work for change, and for facilitating change. Conclusions from the first study identify potential interventions designed to facilitate individual and organizational learning within the customer organization to develop individual and organizational ‘capacity to collaborate’. Translated to the network example, we observe that network change entails learning at all levels – network, organization, group and individual. However, presenting findings in terms of interventions is less meaningful in an interorganizational network setting given: the differences in authority structures; the less formalised nature of the network setting; and the importance of evaluating performance at the network rather than organizational level. Academics challenge both the idea of managing change and of managing networks. Nevertheless practitioners are faced with the issue of understanding and in fluencing change in the network setting. Thus we conclude that a network learning perspective is an important development in our understanding of organizational learning, capability and change, locating this in the wider context in which organizations are embedded. This in turn helps to develop our appreciation of facilitating change in interorganizational networks, both in terms of change issues (such as introducing a new technology), and change orientation and capability.
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This paper models how the structure and function of a network of firms affects their aggregate innovativeness. Each firm has the potential to innovate, either from in-house R&D or from innovation spillovers from neighboring firms. The nature of innovation spillovers depends upon network density, the commonality of knowledge between firms, and the learning capability of firms. Innovation spillovers are modelled in detail using ideas from organizational theory. Two main results emerge: (i) the marginal effect on innovativeness of spillover intensity is non-monotonic, and (ii) network density can affect innovativeness but only when there are heterogeneous firms.