Probabilistic fault identification using vibration data and neural networks

Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

Implications of changes in trophic diversity and food webs on fisheries and the environment

Most of the earth's ecosystems are experiencing slight to catastrophic losses of biodiversity, caused by habitat destruction, alien species introduction, climate change and pollution (Wilcove et al., 1998). These human effects have led to the extinction of native fish species, the collapse of their populations and the loss of ecological integrity and ecosystem functioning (Ogutu-Ohwayo & Hecky, 1991; Witte et al. , 1992a; Mills et al., 1994; Vitousek et al., 1996). Food webs are macro-descriptors of community feeding interactions that can be used to map the flow of materials and nutrients in ecosystems (Jepsen & Winemiller, 2002). Comparative food web studies have been used to address theoretical questions such as 'does greater trophic connectivity increase stability?' (Cohen et al., 1990), and 'does the number of trophic levels increase with productivity?' (Briand & Cohen, 1987). Answers to such questions have obvious applications for natural resources management. From a multi-species fisheries standpoint, there is a need to understand consumer-resource dynamics within complex trophic networks.

Demersal fish biodiversity: species-level indicators and trends-based targets for the Marine Strategy Framework Directive

The maintenance of biodiversity is a fundamental theme of the Marine Strategy Framework Directive. Appropriate indicators to monitor change in biodiversity, along with associated targets representing "good environmental status" (GES), are required to be in place by July 2012. A method for selecting species-specific metrics to fulfil various specified indicator roles is proposed for demersal fish communities. Available data frequently do not extend far enough back in time to allow GES to be defined empirically. In such situations, trends-based targets offer a pragmatic solution. A method is proposed for setting indicator-level targets for the number of species-specific metrics required to meet their trends-based metric-level targets. This is based on demonstrating significant departures from the binomial distribution. The procedure is trialled using North Sea demersal fish survey data. Although fisheries management in the North Sea has improved in recent decades, management goals to stop further decline in biodiversity, and to initiate recovery, are yet to be met.

Response of farmland biodiversity to the introduction of bioenergy crops: effects of local factors and surrounding landscape context

The recent growth in bioenergy crop cultivation, stimulated by the need to implement measures to reduce net CO emissions, is driving major land-use changes with consequences for biodiversity and ecosystem service provision. Although the type of bioenergy crop and its associated management is likely to affect biodiversity at the local (field) scale, landscape context and its interaction with crop type may also influence biodiversity on farms. In this study, we assessed the impact of replacing conventional agricultural crops with two model bioenergy crops (either oilseed rape Brassica napus or Miscanthus × giganteus) on vascular plant, bumblebee, solitary bee, hoverfly and carabid beetle richness, diversity and abundance in 50 sites in Ireland. We assessed whether within-field biodiversity was also related to surrounding landscape structure. We found that local- and landscape-scale variables correlated with biodiversity in these agricultural landscapes. Overall, the differences between the bioenergy crops and the conventional crops on farmland biodiversity were mostly positive (e.g. higher vascular plant richness in Miscanthus planted on former conventional tillage, higher solitary bee abundance and richness in Miscanthus and oilseed rape compared with conventional crops) or neutral (e.g. no differences between crop types for hoverflies and bumblebees). We showed that these crop type effects were independent of (i.e. no interactions with) the surrounding landscape composition and configuration. However, surrounding landscape context did relate to biodiversity in these farms, negatively for carabid beetles and positively for hoverflies. Although we conclude that the bioenergy crops compared favourably with conventional crops in terms of biodiversity of the taxa studied at the field scale, the effects of large-scale planting in these landscapes could result in very different impacts. Maintaining ecosystem functioning and the delivery of ecosystem services will require a greater understanding of impacts at the landscape scale to ensure the sustainable development of climate change mitigation measures.

Identity and Link Reliability in Social Networks

This paper considers a non-cooperative network formation game where identity is introduced as a single dimension to capture the characteristics of a player in the network. Players access to the benefits from the link through direct and indirect connections. We consider cases where cost of link formation paid by the initiator. Each player is allowed to choose their commitment level to their identities. The cost of link formation decreases as the players forming the link share the same identity and higher commitment levels. We then introduce link imperfections to the model. We characterize the Nash networks and we find that the set of Nash networks are either singletons with no links formed or separated blocks or components with mixed blocks or connected.

Location-Awareness for Radios and Networks: Part I

The papers in this special issue focus on the topic of location awareness for radio and networks. Localization-awareness using radio signals stands to revolutionize the fields of navigation and communication engineering. It can be utilized to great effect in the next generation of cellular networks, mining applications, health-care monitoring, transportation and intelligent highways, multi-robot applications, first responders operations, military applications, factory automation, building and environmental controls, cognitive wireless networks, commercial and social network applications, and smart spaces. A multitude of technologies can be used in location-aware radios and networks, including GNSS, RFID, cellular, UWB, WLAN, Bluetooth, cooperative localization, indoor GPS, device-free localization, IR, Radar, and UHF. The performances of these technologies are measured by their accuracy, precision, complexity, robustness, scalability, and cost. Given the many application scenarios across different disciplines, there is a clear need for a broad, up-to-date and cogent treatment of radio-based location awareness. This special issue aims to provide a comprehensive overview of the state-of-the-art in technology, regulation, and theory. It also presents a holistic view of research challenges and opportunities in the emerging areas of localization.

Transnational Culture Wars

The well-known ‘culture wars’ clash in the United States between civil society actors has now gone transnational. Political science scholarship has long detailed how liberal human rights non-governmental organizations NGOs engage in extensive transnational activity in support of their ideals. More recently, US conservative groups (including faith-based NGOs) have begun to emulate these strategies, promoting their convictions by engaging in transnational advocacy. NGOs thus face off against each other politically across the globe. Less well known is the extent to which these culture wars are conducted in courts, using conflicting interpretations of human rights law. Many of the same protagonists, particularly NGOs that find themselves against each other in US courts, now find new litigation opportunities abroad in which to fight their battles. These developments, and their implications, are the focus of this article. In particular, the extent to which US faith-based NGOs have leveraged the experience gained transnationally to use international and foreign jurisprudence in interventions before the US Supreme Court is assessed.

Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.

Migration, Space and Transnational Identities: The British in South Africa

This timely text explores the lives, histories and identities of white British-born immigrants in South Africa, twenty years after the post-apartheid Government took office. Drawing on over sixty in depth biographical interviews and ethnographic work in Johannesburg, Pietermaritzburg and Cape Town, Daniel Conway and Pauline Leonard analyse how British immigrants' relate to, participate in and embody South Africa's complex racial and political history. Through their everyday lives, political and social attitudes, relationships with the places and spaces of South Africa, as well as their expectations of the future, the complexities of their transnational, raced and classed identities and senses of belonging are revealed. Migration, Space and Transnational Identities makes an important contribution to sociological, geographical, political and anthropological debates on transnational migration, whiteness, Britishness and lifestyle, tourism and labour migration.

Análisis de la incidencia del principio de neutralidad en la conformación de las redes transnacionales de defensa de las Zonas Humanitarias y de Biodiversidad de Curvaradó y Jiguamiandó (1997- 2003)

El presente trabajo analiza cómo a través de la constitución de redes transnacionales de defensa los planteamientos en torno a la neutralidad activa se visibilizan por medio de las campañas de mediatización del caso en las comunidades de Curvaradó y Jiguamiandó