Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics

Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products.Agro-scientific Researc

Increasing resilience to natural hazards through crowd-sourcing in St. Vincent and the Grenadines

In this project we aim to demonstrate how volcanic environments exposed to multiple hazards tend to be characterised by a lack of relevant data available both in real time and over the longer term (e.g. months to years). This can be at least partially addressed by actively involving citizens, communities, scientists and other key stakeholders in the collection, analysis and sharing of observations, samples and measurements of changes in the environment. Such community monitoring and co-production of knowledge over time can also build trusting relationships and resilience (Stone et al. 2014). There are more than 100 institutions worldwide that monitor volcanoes and other natural hazards, contribute to early warning systems and are embedded in communities. They have a key role in building resilience alongside civil protection/emergency management agencies. In this report, we propose that such institutions are involved in big data initiatives and related research projects. In particular, we suggest that tools for crowd-sourcing may be of particular value. Citizen science, community monitoring and analysis of social media can build resilience by supporting: a) coordination and collaboration between scientists, authorities and citizens, b) decision-making by institutions and individuals, c) anticipation of natural hazards by monitoring institutions, authorities and citizens, d) capacity building of institutions and communities, and e) knowledge co-production. We propose a mobile phone app with a supporting website as an appropriate crowd-sourcing tool for St Vincent and the Grenadines. The monitoring institution is the key contact for users and leads on the required specifications based on local knowledge and experience. Remote support is provided from the UK on technical issues, research integration, data management, validation and evaluation. It is intended that the app facilitates building of long-term relationships between scientists, communities and authorities. Real-time contributions and analysis of social media support early warning, real-time awareness and real-time feedback enhancing the response of scientists and authorities. The app has potential to facilitate, for example, discussions on new or revised hazards maps, multiple hazard analysis and could contribute to real-time risk monitoring. Such an approach can be scaled up to facilitate regional use – and is transferable to other countries. Challenges of such an approach include data validation and quality assurance, redundancy in the system, motivating volunteers, managing expectations and ensuring safety. A combination of recruiting a core group of known and reliable users, training workshops, a code of conduct for users, identifying information influx thresholds beyond which external support might be needed, and continuing evaluation of both the data and the process will help to address these issues. The app is duplicated on the website in case mobile phone networks are down. Development of such approaches would fit well within research programmes on building resilience. Ideally such research should be interdisciplinary in acknowledgement of the diversity and complexity of topics that this embraces. There may be funding inequality between national monitoring institutions and international research institutions but these and other in-country institutions can help drive innovation and research if they are fully involved in problem-definition and research design. New innovations arising from increasing resolution (temporal and spatial) of EO products should lead to useful near-real time products from research and operational services. The app and website can ensure such diverse products from multiple sources are accessible to communities, scientists and authorities (as appropriate). Other innovations such as machine learning and data mining of time-series data collected by monitoring institutions may lead to new insights into physical processes which can support timely decision-making by scientists in particular (e.g. increasing alert levels)

Is undergraduate programme accreditation influenced by educational public policy quality indicators? An exploratory study of the Chilean Higher Education quality assurance system

In Chile, as well as in most of Latin America, public policies for higher education have recently adopted a focus on quality assurance and accreditation systems. Uncertainty, however, still exists in terms of the quality assurance consistency in the current Chilean accreditation system, especially in terms of the relation between public policy quality indicators for higher education and their relation to accreditation outcomes. Therefore, the aim of this study was to make a first explorative attempt to investigate the relationships between these indicators and the results of undergraduate programme accreditation. We hypothesised that the public policy quality indicators of first-year drop-out rate, employment at graduation and ratio of actual to expected time to graduation would be strongly correlated to undergraduate programme accreditation as well as largely explaining its accreditation-year variance. By means of correlation and multiple regression analyses, we found small-sized associations, being first-year drop-out the only significant predictor of programme accreditation, explaining a 9.4% of its variance. These results raise questions regarding the consistency between the aims of public policy for higher education and the current accreditation system. This study should be of value to policy makers, managers and curriculum developers in terms of this initial analysis of the consistency between quality indicators and the accreditation system. Further research is necessary to make a systematic and in-depth assessment of the impact of quality assurance mechanisms to provide better rationale for making important decisions such as when defining the characteristics of the accrediting institutions as well as for establishing effective ways to achieve the proposed public policy objectives

Harmonised Principles for Public Participation in Quality Assurance of Integrated Water Resources Modelling

The main purpose of public participation in integrated water resources modelling is to improve decision-making by ensuring that decisions are soundly based on shared knowledge, experience and scientific evidence. The present paper describes stakeholder involvement in the modelling process. The point of departure is the guidelines for quality assurance for `scientific` water resources modelling developed under the EU research project HarmoniQuA, which has developed a computer based Modelling Support Tool (MoST) to provide a user-friendly guidance and a quality assurance framework that aim for enhancing the credibility of river basin modelling. MoST prescribes interaction, which is a form of participation above consultation but below engagement of stakeholders and the public in the early phases of the modelling cycle and under review tasks throughout the process. MoST is a flexible tool which supports different types of users and facilitates interaction between modeller, manager and stakeholders. The perspective of using MoST for engagement of stakeholders e.g. higher level participation throughout the modelling process as part of integrated water resource management is evaluate

The future of corporate reporting: a review article

Significant changes in the corporate external reporting environment have led to proposals for fundamental changes in corporate reporting practices. Recent influential reports by major organisations have suggested that a variety of new information types be reported, in particular forward-looking, non-financial and soft information. This paper presents a review and synthesis of these reports and provides a framework for classifying and describing suggested information types. The existence of academic antecedents for certain current proposals are identified and the ambiguous relationship between research and practice is explored. The implications for future academic research are discussed and a research agenda is introduced

Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach

Goals are first-class entities in a self-adaptive system (SAS) as they guide the self-adaptation. A SAS often operates in dynamic and partially unknown environments, which cause uncertainty that the SAS has to address to achieve its goals. Moreover, besides the environment, other classes of uncertainty have been identified. However, these various classes and their sources are not systematically addressed by current approaches throughout the life cycle of the SAS. In general, uncertainty typically makes the assurance provision of SAS goals exclusively at design time not viable. This calls for an assurance process that spans the whole life cycle of the SAS. In this work, we propose a goal-oriented assurance process that supports taming different sources (within different classes) of uncertainty from defining the goals at design time to performing self-adaptation at runtime. Based on a goal model augmented with uncertainty annotations, we automatically generate parametric symbolic formulae with parameterized uncertainties at design time using symbolic model checking. These formulae and the goal model guide the synthesis of adaptation policies by engineers. At runtime, the generated formulae are evaluated to resolve the uncertainty and to steer the self-adaptation using the policies. In this paper, we focus on reliability and cost properties, for which we evaluate our approach on the Body Sensor Network (BSN) implemented in OpenDaVINCI. The results of the validation are promising and show that our approach is able to systematically tame multiple classes of uncertainty, and that it is effective and efficient in providing assurances for the goals of self-adaptive systems