Communities and emerging semantics in semantic link network:discovery and learning

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.

Municipal benchmarking:organisational learning and network performance in the public sector

The main purpose of this dissertation is to assess the relation between municipal benchmarking and organisational learning with a specific emphasis on benchlearning and performance within municipalities and between groups of municipalities in the building and housing sector in the Netherlands. The first and main conclusion is that this relation exists, but that the relative success of different approaches to dimensions of change and organisational learning are a key explanatory factor for differences in the success of benchlearning. Seven other important conclusions could be derived from the empirical research. First, a combination of interpretative approaches at the group level with a mixture of hierarchical and network strategies, positively influences benchlearning. Second, interaction among professionals at the inter-organisational level strengthens benchlearning. Third, stimulating supporting factors can be seen as a more important strategy to strengthen benchlearning than pulling down barriers. Fourth, in order to facilitate benchlearning, intrinsic motivation and communication skills matter, and are supported by a high level of cooperation (i.e., team work), a flat organisational structure and interactions between individuals. Fifth, benchlearning is facilitated by a strategy that is based on a balanced use of episodic (emergent) and systemic (deliberate) forms of power. Sixth, high levels of benchlearning will be facilitated by an analyser or prospector strategic stance. Prospectors and analysers reach a different learning outcome than defenders and reactors. Whereas analysers and prospectors are willing to change policies when it is perceived as necessary, the strategic stances of defenders and reactors result in narrow process improvements (i.e., single-loop learning). Seventh, performance improvement is influenced by functional perceptions towards performance, and these perceptions ultimately influence the elements adopted. This research shows that efforts aimed at benchlearning and ultimately improved service delivery, should be directed to a multi-level and multi-dimensional approach addressing the context, content and process of dimensions of change and organisational learning.

Professionalism and quality in European business courses:utilising research to enhance student learning and promote employability - a pan-European study

This..paper provides a comparative analysis of Quality Management and standards in four European countries, (the UK, Austria, Slovenia and Romania) and in doing so addresses the gap in academic knowledge about how the introduction and implementation of Quality Management Strategies can both facilitate and enhance student learning within Universities.

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both.

Learning to be different:heterogeneity and efficiency in distributed smart camera networks

In this paper we study the self-organising behaviour of smart camera networks which use market-based handover of object tracking responsibilities to achieve an efficient allocation of objects to cameras. Specifically, we compare previously known homogeneous configurations, when all cameras use the same marketing strategy, with heterogeneous configurations, when each camera makes use of its own, possibly different marketing strategy. Our first contribution is to establish that such heterogeneity of marketing strategies can lead to system wide outcomes which are Pareto superior when compared to those possible in homogeneous configurations. However, since the particular configuration required to lead to Pareto efficiency in a given scenario will not be known in advance, our second contribution is to show how online learning of marketing strategies at the individual camera level can lead to high performing heterogeneous configurations from the system point of view, extending the Pareto front when compared to the homogeneous case. Our third contribution is to show that in many cases, the dynamic behaviour resulting from online learning leads to global outcomes which extend the Pareto front even when compared to static heterogeneous configurations. Our evaluation considers results obtained from an open source simulation package as well as data from a network of real cameras. © 2013 IEEE.

Stochastic control strategies and adaptive critic methods

Adaptive critic methods have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, nonlinear and nonstationary environments. In this study, a novel probabilistic dual heuristic programming (DHP) based adaptive critic controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) adaptive critic method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterized by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the critic network is then calculated and shown to be equal to the analytically derived correct value.

Internationalization of emerging Indian multinationals:linkage, leverage and learning (LLL) perspective

The multi-polar world in which we now live and work demands re-examination and refinement of the traditional understanding of the internationalization strategies and competitive advantages of multinational firms by incorporating the characteristics of firms from emerging economies. Based on interviews in four Indian multinationals in different industry segments, we present the "voices" of Indian corporate leaders to provide preliminary evidence on the primary motives behind the internationalization process of emerging multinationals from the perspective of linkage, leverage and learning (LLL). We show how the case study organizations have evolved themselves to become credible global players by leveraging on their learning through targeted acquisitions in developed markets to acquire intangible assets and/or following global clients in search of new markets and competitive advantages.

Firms’ innovation objectives and knowledge acquisition strategies:a comparative analysis

External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.

Learning from a deceptively spacious policy discourse

In this chapter, the way in which varied terms such as Networked learning, e-learning and Technology Enhanced Learning (TEL) have each become colonised to support a dominant, economically-based world view of educational technology is discussed. Critical social theory about technology, language and learning is brought into dialogue with examples from a corpus-based Critical Discourse Analysis (CDA) of UK policy texts for educational technology between1997 and 2012. Though these policy documents offer much promise for enhancement of people’s performance via technology, the human presence to enact such innovation is missing. Given that ‘academic workload’ is a ‘silent barrier’ to the implementation of TEL strategies (Gregory and Lodge, 2015), analysis further exposes, through empirical examples, that the academic labour of both staff and students appears to be unacknowledged. Global neoliberal capitalist values have strongly territorialised the contemporary university (Hayes & Jandric, 2014), utilising existing naïve, utopian arguments about what technology alone achieves. Whilst the chapter reveals how humans are easily ‘evicted’, even from discourse about their own learning (Hayes, 2015), it also challenges staff and students to seek to re-occupy the important territory of policy to subvert the established order. We can use the very political discourse that has disguised our networked learning practices, in new explicit ways, to restore our human visibility.