Land re-use, complexity and actor-networks: a framework for research

This paper will present a conceptual framework for the examination of land redevelopment based on a complex systems/networks approach. As Alvin Toffler insightfully noted, modern scientific enquiry has become exceptionally good at splitting problems into pieces but has forgotten how to put the pieces back together. Twenty-five years after his remarks, governments and corporations faced with the requirements of sustainability are struggling to promote an ‘integrated’ or ‘holistic’ approach to tackling problems. Despite the talk, both practice and research provide few platforms that allow for ‘joined up’ thinking and action. With socio-economic phenomena, such as land redevelopment, promising prospects open up when we assume that their constituents can make up complex systems whose emergent properties are more than the sum of the parts and whose behaviour is inherently difficult to predict. A review of previous research shows that it has mainly focused on idealised, ‘mechanical’ views of property development processes that fail to recognise in full the relationships between actors, the structures created and their emergent qualities. When reality failed to live up to the expectations of these theoretical constructs then somebody had to be blamed for it: planners, developers, politicians. However, from a ‘synthetic’ point of view the agents and networks involved in property development can be seen as constituents of structures that perform complex processes. These structures interact, forming new more complex structures and networks. Redevelopment then can be conceptualised as a process of transformation: a complex system, a ‘dissipative’ structure involving developers, planners, landowners, state agencies etc., unlocks the potential of previously used sites, transforms space towards a higher order of complexity and ‘consumes’ but also ‘creates’ different forms of capital in the process. Analysis of network relations point toward the ‘dualism’ of structure and agency in these processes of system transformation and change. Insights from actor network theory can be conjoined with notions of complexity and chaos to build an understanding of the ways in which actors actively seek to shape these structures and systems, whilst at the same time are recursively shaped by them in their strategies and actions. This approach transcends the blame game and allows for inter-disciplinary inputs to be placed within a broader explanatory framework that does away with many past dichotomies. Better understanding of the interactions between actors and the emergent qualities of the networks they form can improve our comprehension of the complex socio-spatial phenomena that redevelopment comprises. The insights that this framework provides when applied in UK institutional investment into redevelopment are considered to be significant.

Learning in neural networks and stochastic approximation methods with averaging

The problem of adjusting the weights (learning) in multilayer feedforward neural networks (NN) is known to be of a high importance when utilizing NN techniques in various practical applications. The learning procedure is to be performed as fast as possible and in a simple computational fashion, the two requirements which are usually not satisfied practically by the methods developed so far. Moreover, the presence of random inaccuracies are usually not taken into account. In view of these three issues, an alternative stochastic approximation approach discussed in the paper, seems to be very promising.

Communication mechanisms and middleware for distributed video surveillance

A new generation of advanced surveillance systems is being conceived as a collection of multi-sensor components such as video, audio and mobile robots interacting in a cooperating manner to enhance situation awareness capabilities to assist surveillance personnel. The prominent issues that these systems face are: the improvement of existing intelligent video surveillance systems, the inclusion of wireless networks, the use of low power sensors, the design architecture, the communication between different components, the fusion of data emerging from different type of sensors, the location of personnel (providers and consumers) and the scalability of the system. This paper focuses on the aspects pertaining to real-time distributed architecture and scalability. For example, to meet real-time requirements, these systems need to process data streams in concurrent environments, designed by taking into account scheduling and synchronisation. The paper proposes a framework for the design of visual surveillance systems based on components derived from the principles of Real Time Networks/Data Oriented Requirements Implementation Scheme (RTN/DORIS). It also proposes the implementation of these components using the well-known middleware technology Common Object Request Broker Architecture (CORBA). Results using this architecture for video surveillance are presented through an implemented prototype.

Antecedents of attitude and intention towards counterfeit symbolic and experiential products

This paper investigates the impact of price consciousness, perceived risk, and ethical obligation on attitude and intention towards counterfeit products. Data were collected from a sample of 200 respondents via an online questionnaire. A conceptual model was derived and tested via structural equation modelling in the contexts of symbolic and experiential counterfeit products. Findings show differences in the factors (and weight thereof) impacting attitude and purchase intention in the two product contexts. Specifically, ethical obligation and perceived risk are found to be significant predictors of attitude towards both symbolic and counterfeit products, while price consciousness is found to predict only attitude towards experiential products, but not purchase intention in either counterfeit product context.

Innovation in construction: a sociology of technology approach

An alternative approach to understanding innovation is made using two intersecting ideas. The first is that successful innovation requires consideration of the social and organizational contexts in which it is located. The complex context of construction work is characterized by inter-organizational collaboration, a project-based approach and power distributed amongst collaborating organizations. The second is that innovations can be divided into two modes: ‘bounded’, where the implications of innovation are restricted within a single, coherent sphere of influence, and ‘unbounded’, where the effects of implementation spill over beyond this. Bounded innovations are adequately explained within the construction literature. However, less discussed are unbounded innovations, where many firms' collaboration is required for successful implementation, even though many innovations can be considered unbounded within construction's inter-organizational context. It is argued that unbounded innovations require an approach to understand and facilitate the interactions both within a range of actors and between the actors and technological artefacts. The insights from a sociology of technology approach can be applied to the multiplicity of negotiations and alignments that constitute the implementation of unbounded innovation. The utility of concepts from the sociology of technology, including ‘system building’ and ‘heterogeneous engineering’, is demonstrated by applying them to an empirical study of an unbounded innovation on a major construction project (the new terminal at Heathrow Airport, London, UK). This study suggests that ‘system building’ contains outcomes that are not only transformations of practices, processes and systems, but also the potential transformation of technologies themselves.

The zooarchaeology of medieval Christendom: ideology, the treatment of animals and the making of medieval Europe

The formation of Christendom – of Europe – was associated with a standardized worldview expressing dominion over the natural world. While some sections of medieval society, specifically monasteries and the aristocratic class, appear to have developed this paradigm, there is also evidence for heterogeneity in practice and belief. Zooarchaeologists have accumulated vast quantities of data from medieval contexts which has enabled the ecological signatures of specific social groups to be identified, and how these developed from the latter centuries of the first millennium ad. It is possible from this to consider whether trends in animal exploitation can be associated with the Christian world view of dominion, and with the very idea of what it meant to be Christian. This may enable zooarchaeologists to situate the ecological trends of the Middle Ages within the context of Europeanization, and the consolidation of a Christian society.

Evoked prior learning experience and approach to learning as predictors of academic achievement

Background. In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students’ perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. Aim. To investigate how students’ evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Sample. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. Method. A 77-item questionnaire was used to gather students’ self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. Results. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Conclusions. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching–learning contexts are analysed using multi-variable methods.

Traditional Chinese medicine research in the post-genomic era: good practice, priorities, challenges and opportunities

Background and aims: GP-TCM is the 1st EU-funded Coordination Action consortium dedicated to traditional Chinese medicine (TCM) research. This paper aims to summarise the objectives, structure and activities of the consortium and introduces the position of the consortium regarding good practice, priorities, challenges and opportunities in TCM research. Serving as the introductory paper for the GPTCM Journal of Ethnopharmacology special issue, this paper describes the roadmap of this special issue and reports how the main outputs of the ten GP-TCM work packages are integrated, and have led to consortium-wide conclusions. Materials and methods: Literature studies, opinion polls and discussions among consortium members and stakeholders. Results: By January 2012, through 3 years of team building, the GP-TCM consortium had grown into a large collaborative network involving ∼200 scientists from 24 countries and 107 institutions. Consortium members had worked closely to address good practice issues related to various aspects of Chinese herbal medicine (CHM) and acupuncture research, the focus of this Journal of Ethnopharmacology special issue, leading to state-of-the-art reports, guidelines and consensus on the application of omics technologies in TCM research. In addition, through an online survey open to GP-TCM members and non-members, we polled opinions on grand priorities, challenges and opportunities in TCM research. Based on the poll, although consortium members and non-members had diverse opinions on the major challenges in the field, both groups agreed that high-quality efficacy/effectiveness and mechanistic studies are grand priorities and that the TCM legacy in general and its management of chronic diseases in particular represent grand opportunities. Consortium members cast their votes of confidence in omics and systems biology approaches to TCM research and believed that quality and pharmacovigilance of TCM products are not only grand priorities, but also grand challenges. Non-members, however, gave priority to integrative medicine, concerned on the impact of regulation of TCM practitioners and emphasised intersectoral collaborations in funding TCM research, especially clinical trials. Conclusions: The GP-TCM consortium made great efforts to address some fundamental issues in TCM research, including developing guidelines, as well as identifying priorities, challenges and opportunities. These consortium guidelines and consensus will need dissemination, validation and further development through continued interregional, interdisciplinary and intersectoral collaborations. To promote this, a new consortium, known as the GP-TCM Research Association, is being established to succeed the 3-year fixed term FP7 GP-TCM consortium and will be officially launched at the Final GP-TCM Congress in Leiden, the Netherlands, in April 2012.

Color adjectives and radical contextualism

Radical contextualists have observed that the content of what is said by the utterance of a sentence is shaped in far-reaching ways by the context of utterance. And they have argued that the ways in which the content of what is said is shaped by context cannot be explained by semantic theory. A striking number of the examples that radical contextualists use to support their view involve sentences containing color adjectives (“red”, “green”, etc.). In this paper, I show how the most sophisticated analysis of color adjectives within the explanatory framework of compositional truth conditional semantics—recently developed by Kennedy and McNally (Synthese 174(1):79–98 2010)—needs to be modified to handle the full range of contextual variation displayed by color adjectives.

Context-based interaction design for smart homes

This paper presents the notion of Context-based Activity Design (CoBAD) that represents context with its dynamic changes and normative activities in an interactive system design. The development of CoBAD requires an appropriate context ontology model and inference mechanisms. The incorporation of norms and information field theory into Context State Transition Model, and the implementation of new conflict resolution strategies based on the specific situation are discussed. A demonstration of CoBAD using a human agent scenario in a smart home is also presented. Finally, a method of treating conflicting norms in multiple information fields is proposed.

Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm

This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.