Informal communication networks and the diffusion of innovations in UK construction projects: A research design

The UK industry has been criticised for being slow to adopt construction process innovations. Research shows that the idiosyncrasies of participants, their roles in the system and the contextual differences between sections of the industry make this a highly complex problem. There is considerable evidence that informal social networks play a key role in diffusion of innovations. The aim is to identify informal communication networks of project participants and the role these play in the diffusion of construction innovations. The characteristics of this network will be analysed in order to understand how they can be used to accelerate innovation diffusion within and between projects. Social Network Analysis is used to determine informal communication routes. Control and experiment case study projects are used within two different organizations. This allows informal communication routes concerning innovations to be mapped, whilst testing if the informal routes can facilitate diffusion. Analysis will focus upon understanding the combination of informal strong and weak ties, and how these impede or facilitate the diffusion of the innovation. Initial work suggests the presence of an informal communication network. Actors within this informal network, and the organization's management are unaware of its' existence and their informal roles within it. Thus, the network remains an untapped medium regarding innovation diffusion. It is proposed that successful innovation diffusion is dependent upon understanding informal strong and weak ties, at project, organization and industry level.

Technology sourcing, knowledge management and governance in international inter-organizational innovation networks

This conceptual paper aims to improve our understanding of how internationalised firms use outsourcing and offshoring strategies to manage knowledge and information through the life-cycle of integrated product-service solutions. More precisely, we identify the appropriate theoretical framework for this analysis and investigate through in-depth case studies how UK engineering firms organise, coordinate, and incentivise work that is executed in globally distributed teams. Our research focuses on their UK and India offices to study the organisation and governance of distributed teams. The research has several theoretical dimensions - organization; geography; time and knowledge - that it addresses as boundary challenges.

Teachers' networks in and out of school

A 'mapping task' was used to explore the networks available to head teachers, school coordinators and local authority staff. Beginning from an ego-centred perspective on networks, we illustrate a number of key analytic categories, including brokerage, formality, and strength and weakness of links with reference to a single UK primary school. We describe how teachers differentiate between the strength of network links and their value, which is characteristically related to their potential impact on classroom practice.

Simulating global properties of electroencephalograms with minimal random neural networks

The human electroencephalogram (EEG) is globally characterized by a 1/f power spectrum superimposed with certain peaks, whereby the "alpha peak" in a frequency range of 8-14 Hz is the most prominent one for relaxed states of wakefulness. We present simulations of a minimal dynamical network model of leaky integrator neurons attached to the nodes of an evolving directed and weighted random graph (an Erdos-Renyi graph). We derive a model of the dendritic field potential (DFP) for the neurons leading to a simulated EEG that describes the global activity of the network. Depending on the network size, we find an oscillatory transition of the simulated EEG when the network reaches a critical connectivity. This transition, indicated by a suitably defined order parameter, is reflected by a sudden change of the network's topology when super-cycles are formed from merging isolated loops. After the oscillatory transition, the power spectra of simulated EEG time series exhibit a 1/f continuum superimposed with certain peaks. (c) 2007 Elsevier B.V. All rights reserved.

Stability criteria for the contextual emergence of macrostates in neural networks

More than thirty years ago, Amari and colleagues proposed a statistical framework for identifying structurally stable macrostates of neural networks from observations of their microstates. We compare their stochastic stability criterion with a deterministic stability criterion based on the ergodic theory of dynamical systems, recently proposed for the scheme of contextual emergence and applied to particular inter-level relations in neuroscience. Stochastic and deterministic stability criteria for macrostates rely on macro-level contexts, which make them sensitive to differences between different macro-levels.

The automatic identification and prioritisation of criminal networks from police crime data

The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.

Supporting ad hoc collaborations in peer-to-peer networks

Traditionally, applications and tools supporting collaborative computing have been designed only with personal computers in mind and support a limited range of computing and network platforms. These applications are therefore not well equipped to deal with network heterogeneity and, in particular, do not cope well with dynamic network topologies. Progress in this area must be made if we are to fulfil the needs of users and support the diversity, mobility, and portability that are likely to characterise group work in future. This paper describes a groupware platform called Coco that is designed to support collaboration in a heterogeneous network environment. The work demonstrates that progress in the p development of a generic supporting groupware is achievable, even in the context of heterogeneous and dynamic networks. The work demonstrates the progress made in the development of an underlying communications infrastructure, building on peer-to-peer concept and topologies to improve scalability and robustness.

Wireless sensor networks

This paper provides an introduction to Wireless Sensor Networks (WSN), their applications in the field of control engineering and elsewhere and gives pointers to future research needs. WSN are collections of stand-alone devices which, typically, have one or more sensors (e.g. temperature, light level), some limited processing capability and a wireless interface allowing communication with a base station. As they are usually battery powered, the biggest challenge is to achieve the necessary monitoring whilst using the least amount of power.