80 resultados para Collaborative learning and applications


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With recent expansions in technology, mobile computing continues to play a vital role in all aspects of our lives. Digital technology tools such as Web browsing, media tracking, social media, and emailing have made mobile technology more than just a means of communication but has widespread use in business and social networks. Developments in Technologies for Human-Centric Mobile Computing and Applications is a comprehensive collection of knowledge and practice in the development of technologies in human –centric mobile technology. This book focuses on the developmental aspects of mobile technology; bringing together researchers, educators, and practitioners to encourage readers to think outside of the box.

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We have UV-inscribed and theoretically and experimentally analyzed fiber gratings with the structure tilted at 45° and implemented this type of devices as an in-fiber polarizer. A systematic investigation has been carried out on the characterization of 45° tilted fiber gratings (45° TFGs) in terms of the polarization-dependant loss (PDL) and thermal response. The detailed theoretical modeling has revealed a linear correlation between the grating length and the PDL, which has been proved by the experimental results. For the first time, we have examined the UV beam diffraction from a tilted phase mask and designed the UV-inscription system to suit the 45° TFG fabrication. Experimentally, a 24 mm long 45° TFG UV-inscribed in standard telecom single-mode fiber exhibited around 25 dB PDL at 1530 nm and an over ~300 nm bandwidth of PDL spectrum. By the concatenation method, a 44 mm long grating showed a PDL as high as 40 dB that is close to the high polarization extinction ratio of commercial products. Moreover, we have revealed that the PDL of 45° TFGs has low thermal influence, which is desirable for real application devices. Finally, we experimentally demonstrated an all-fiber twist sensor system based on a 45° and an 81° TFG.

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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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It is a great pleasure to be Guest Editor for this issue – I hope that the papers which are included will be stimulating and support you in your ongoing research activities. A number of guiding principles were adopted in selecting the papers for inclusion in this issue. Firstly, the papers cover a wide range of logistics and supply chain management (SCM) topics. This is a reflection of the evolution of the field in recent years. In terms of the “buy-make-store-move-sell” model of SCM all the main constituent areas are addressed. Secondly, it is important that the conference issue of this Journal reflects the emphasis and content of the conference itself. I have tried to achieve this in terms of the papers included. One interesting point to note is that outsourcing is a theme which is a major issue in a number of papers. This reflects the increasing importance of this issue to organisations of all kinds and sizes. Economic globalisation and the trend towards vertical disintegration of supply chain architectures have sharpened the focus on outsourcing as a key element of supply chain strategy. The need to move beyond the notion that sourcing of certain activities can be some kind of panacea in evident from the relevant contributions. Thirdly, the LRN Annual Conference has become a more international event in recent years...the number of delegates and papers presented from outside the UK has continued to grow. The papers collected in this issue reflect this internationalization. Two papers are worthy of particular comment from an LRN perspective. The contribution by Jaafar and Rafiq has been developed from the submission which won the best paper prize at the LRN 2004 event. The paper by Pettit and Beresford is based on research which was supported by LRN seed corn funding. It was developed form the final report on this work submitted to CITL (UK) via the LRN. The seed corn funding is an important mechanism whereby the LRN supports research in innovative aspects of logistics in UK universities. In many ways, the LRN2004 event in Dublin seems like a long time ago. From my point of view it was one of the most professionally rewarding activities in which I have been involved in my career. It was a time to meet old friends and new and to keep abreast of the multitude of interesting projects being undertaken in over 20 countries. There are too many people to thank for the smooth running of the event. However, my colleague John Mee does warrant a special mention. His logistical skills were seriously put to the test in the weeks and months leading up to September 9th. 2004. I want to acknowledge his particular contribution to the success of the event. Since then we have had the 2005 event at the University of Plymouth. This was again a great opportunity to network with colleagues and many congratulations are due to John Dinwoodie and his team. We now look forward to LRN 2006 in Newcastle...form my part I hope and trust that this issue provides some useful perspectives and insights into the range of topics addressed.

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Context traditionally has been regarded in vision research as a determinant for the interpretation of sensory information on the basis of previously acquired knowledge. Here we propose a novel, complementary perspective by showing that context also specifically affects visual category learning. In two experiments involving sets of Compound Gabor patterns we explored how context, as given by the stimulus set to be learned, affects the internal representation of pattern categories. In Experiment 1, we changed the (local) context of the individual signal classes by changing the configuration of the learning set. In Experiment 2, we varied the (global) context of a fixed class configuration by changing the degree of signal accentuation. Generalization performance was assessed in terms of the ability to recognize contrast-inverted versions of the learning patterns. Both contextual variations yielded distinct effects on learning and generalization thus indicating a change in internal category representation. Computer simulations suggest that the latter is related to changes in the set of attributes underlying the production rules of the categories. The implications of these findings for phenomena of contrast (in)variance in visual perception are discussed.

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IPO underpricing has been attributed to valuation uncertainty, which can be at least partially resolved by the indirect learning associated with IPO clustering [Benveniste, L.M., Ljungqvist, A., Wilhelm, W.J., Yu, X.Y., 2003. Evidence of information spillovers in the production of investment banking services. Journal of Finance 58, 577–608]. We examine why firms might choose not to issue their IPOs contemporaneously with clusters of similar firms, forgoing opportunities to learn from their peers. We find that the willingness to file an IPO without the benefit of indirect learning from peer firm IPOs is directly related to insiders’ needs for portfolio diversification and the firm’s need to raise capital.

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Bio-impedance analysis (BIA) provides a rapid, non-invasive technique for body composition estimation. BIA offers a convenient alternative to standard techniques such as MRI, CT scan or DEXA scan for selected types of body composition analysis. The accuracy of BIA is limited because it is an indirect method of composition analysis. It relies on linear relationships between measured impedance and morphological parameters such as height and weight to derive estimates. To overcome these underlying limitations of BIA, a multi-frequency segmental bio-impedance device was constructed through a series of iterative enhancements and improvements of existing BIA instrumentation. Key features of the design included an easy to construct current-source and compact PCB design. The final device was trialled with 22 human volunteers and measured impedance was compared against body composition estimates obtained by DEXA scan. This enabled the development of newer techniques to make BIA predictions. To add a ‘visual aspect’ to BIA, volunteers were scanned in 3D using an inexpensive scattered light gadget (Xbox Kinect controller) and 3D volumes of their limbs were compared with BIA measurements to further improve BIA predictions. A three-stage digital filtering scheme was also implemented to enable extraction of heart-rate data from recorded bio-electrical signals. Additionally modifications have been introduced to measure change in bio-impedance with motion, this could be adapted to further improve accuracy and veracity for limb composition analysis. The findings in this thesis aim to give new direction to the prediction of body composition using BIA. The design development and refinement applied to BIA in this research programme suggest new opportunities to enhance the accuracy and clinical utility of BIA for the prediction of body composition analysis. In particular, the use of bio-impedance to predict limb volumes which would provide an additional metric for body composition measurement and help distinguish between fat and muscle content.

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This study presents a meta-analysis synthesizing the existing research on the effectiveness of workplace coaching. We exclusively explore workplace coaching provided by internal or external coaches and therefore exclude cases of manager-subordinate and peer coaching. We propose a framework of potential outcomes from coaching in organizations, which we examine meta-analytically (k = 17). Our analyses indicated that coaching had positive effects on organizational outcomes overall (δ = 0.36), and on specific forms of outcome criteria (skill-based δ = 0.28; affective δ = 0.51; individual-level results δ = 1.24). We also examined moderation by a number of coaching practice factors (use of multisource feedback; type of coach; coaching format; longevity of coaching). Our analyses of practice moderators indicated a significant moderation of effect size for type of coach (with effects being stronger for internal coaches compared to external coaches) and use of multisource feedback (with the use of multisource feedback resulting in smaller positive effects). We found no moderation of effect size by coaching format (comparing face-to-face, with blended face-to-face and e-coaching) or duration of coaching (number of sessions or longevity of intervention). The effect sizes give support to the potential utility of coaching in organizations. Implications for coaching research and practice are discussed.

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Editorial

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The quantum Jensen-Shannon divergence kernel [1] was recently introduced in the context of unattributed graphs where it was shown to outperform several commonly used alternatives. In this paper, we study the separability properties of this kernel and we propose a way to compute a low-dimensional kernel embedding where the separation of the different classes is enhanced. The idea stems from the observation that the multidimensional scaling embeddings on this kernel show a strong horseshoe shape distribution, a pattern which is known to arise when long range distances are not estimated accurately. Here we propose to use Isomap to embed the graphs using only local distance information onto a new vectorial space with a higher class separability. The experimental evaluation shows the effectiveness of the proposed approach. © 2013 Springer-Verlag.

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