Investigation into the use of satellite remote sensing data products as part of a multi-modal marine environmental monitoring network

In this paper it is investigated how conventional in-situ sensor networks can be complemented by the satellite data streams available through numerous platforms orbiting the earth and the combined analyses products available through services such as MyOcean. Despite the numerous benefits associated with the use of satellite remote sensing data products, there are a number of limitations with their use in coastal zones. Here the ability of these data sources to provide contextual awareness, redundancy and increased efficiency to an in-situ sensor network is investigated. The potential use of a variety of chlorophyll and SST data products as additional data sources in the SmartBay monitoring network in Galway Bay, Ireland is analysed. The ultimate goal is to investigate the ability of these products to create a smarter marine monitoring network with increased efficiency. Overall it was found that while care needs to be taken in choosing these products, there was extremely promising performance from a number of these products that would be suitable in the context of a number of applications especially in relation to SST. It was more difficult to come to conclusive results for the chlorophyll analysis

The Psychosocial Work Environment, Employee Mental Health and Organizational Interventions: Improving Research and Practice by Taking a Multilevel Approach

Although there have been several calls for incorporating multiple levels of analysis in employee health and wellbeing research, studies examining the interplay between individual, workgroup, organizational and broader societal factors in relation to employee mental health outcomes remain an exception rather than the norm. At the same time, organizational intervention research and practice also tends to be limited by a single-level focus, omitting potentially important influences at multiple levels of analysis. The aims of this conceptual paper are to help progress our understanding of work-related determinants of employee mental health by: (i) providing a rationale for routine multilevel assessment of the psychosocial work environment; (ii) discussing how a multilevel perspective can improve related organizational interventions and (iii) highlighting key theoretical and methodological considerations relevant to these aims. We present five recommendations for future research, relating to using appropriate multilevel research designs, justifying group level constructs, developing group-level measures, expanding investigations to the organizational level, and developing multilevel approaches to intervention design, implementation and evaluation

Place effects on environmental views

How people respond to questions involving the environment depends partly on individual characteristics. Characteristics such as age, gender, education, and ideology constitute the well-studied social bases of environmental concern, which have been explained in terms of cohort effects or of cognitive and cultural factors related to social position. It seems likely that people\u27s environmental views depend not only on personal characteristics but also on their social and physical environments. This hypothesis has been more difficult to test, however. Using data from surveys in 19 rural U.S. counties, we apply mixed-effects modeling to investigate simple place effects with respect to locally focused environmental views. We find evidence for two kinds of place effects. Net of individual characteristics, specific place characteristics have the expected effect on related environmental views. Local changes are related to attitudes about regulation and growth. For example, respondents more often perceive rapid development as a problem, and favor environmental rules that restrict development, in rural counties with growing populations. Moreover, they favor conserving resources for the future rather than using them now to create jobs in counties that have low unemployment. After we controlled for county growth, unemployment and jobs in resource based industries, and individual social-position and ideological factors, there remains significant place-to-place variation in mean levels of environmental concern. Even with both kinds of place effects in the models, the individual level predictors of environmental concern follow patterns expected from previous research. Concern increases with education among Democrats, whereas among Republicans, the relationship is attenuated or reversed. The interaction marks reframing of environmental questions as political wedge issues, through nominally scientific counterarguments aimed at educated, ideologically receptive audiences. © 2010, by the Rural Sociological Society

Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case

Trust and risk are often seen in proportion to each other; as such, high trust may induce low risk and vice versa. However, recent research argues that trust and risk relationship is implicit rather than proportional. Considering that trust and risk are implicit, this paper proposes for the first time a novel approach to view trust and risk on a basis of a W3C PROV provenance data model applied in a healthcare domain. We argue that high trust in healthcare domain can be placed in data despite of its high risk, and low trust data can have low risk depending on data quality attributes and its provenance. This is demonstrated by our trust and risk models applied to the BII case study data. The proposed theoretical approach first calculates risk values at each workflow step considering PROV concepts and second, aggregates the final risk score for the whole provenance chain. Different from risk model, trust of a workflow is derived by applying DS/AHP method. The results prove our assumption that trust and risk relationship is implicit

The Voyage of the Beagle in Innovation Systems Land. Explorations on Sectors, Innovation, Heterogeneity and Selection

The aim of the paper is to assess heterogeneity of the innovation process. Using exploratory factor analysis on micro data from the third Community Innovation Survey in 13 countries, we identify four factors that that can be interpreted as research, user, external and production ingredients of innovation. All too often it is assumed that the differences between the rates at which these factors are found in firms' innovation strategies can be accounted for by differences across sectors and/or countries. To put this proposition under scrutiny, we partition variability of the innovation process into components identified by the different levels. The analysis shows that sectors and countries matter to a certain extent, but far most of the variance is given by heterogeneity among firms within either sectors or countries. On the other hand, a grouping of firms produced by cluster analysis accounts for a much higher share of the variance, which implies that the most relevant contextual factors cut across the established boundaries between sectors and countries. We discuss the implications of these findings for the literature on national and sectoral systems of innovation, and for the way in which evolutionary economics has analyzed the role of selection.Innovation, heterogeneity, sectoral systems of innovation, factor analysis, variance components analysis.

Partnerships in implementing sustainability policies theoretical considerations and experiences from Spain

The greening of economic and industrial activities requires that new relationships be formed between private actors who often never met before on the business or policy arenas. To initiate and give direction to the sustainability transition, public actors may choose to become involved in partnerships for policy implementation, next to industrial prime movers. After having catalyzed the process, new forms of public-private partnerships may emerge, in the transition towards ‘green private-private partnerships’.\ud This paper presents theoretical considerations regarding the types and evolution of publicprivate partnerships (PPPs) involved in the implementation of sustainability policies. The central argument is that PPPs are themselves in a process of transition, with changes in the types of activity, types of investment and types of financing on which partnerships focus. Empirically, the paper analyses the greening of the electricity industry in Spain and looks specifically at the cases of wind electricity and biomass technologies’ diffusion. The evolution of PPPs shows clearly that there is a transition from ‘project-vehicle-partnerships’ to ‘technology-specific-partnerships’ to ‘renewables-development-partnerships’. In parallel there is a transition from ‘internally-financed-partnerships’ towards ‘bank-financedpartnerships’ with a substantially higher diffusion potential. Finally, another transition was observed from ‘learning-partnerships’ towards ‘commercialization-partnerships’. As the greening of the electricity industry advances, there is a gradual retreat of public actors and an increase in new green private-private-partnerships. Through these analyses, the paper fits into the conference theme regarding the dynamics for public-private partnerships. In the same time it is relevant for the theme regarding the implementation of public policies and technologies to promote sustainable development. Understanding the metamorphosis of partnerships supports policy-makers to design policies facilitating wider engagement in PPPs, a more secure operation environment and a faster transition towards new green private-private partnerships in industrial activities. The paper draws in postdoctoral research and is aimed for oral presentation in the workshop “Dynamics of public-private partnerships in implementing sustainability policies”

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN