Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for large-scale systems. Nonetheless, a critical obstacle, which needs to be overcome in MPC, is the large computational burden when a large-scale system is considered or a long prediction horizon is involved. In order to solve this problem, we use an adaptive prediction accuracy (APA) approach that can reduce the computational burden almost by half. The proposed MPC scheme with this scheme is tested on the northern Dutch water system, which comprises Lake IJssel, Lake Marker, the River IJssel and the North Sea Canal. The simulation results show that by using the MPC-APA scheme, the computational time can be reduced to a large extent and a flood protection problem over longer prediction horizons can be well solved.

Coastal Marine Mapping as an Ecosystem Based Management - the case study of the Baixada Santista Region - São Paulo, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Conservation of the Cinereous Vulture Aegypius monachus in Spain (1966–2011): a bibliometric review of threats, research and adaptive management

Detecting and quantifying threats and researching and implementing management actions are key to improving the conservation status of endangered species. Bibliometric analysis can constitute a useful tool for the evaluation of such questions from a long-term perspective. Taking as a case study the Cinereous Vulture Aegypius monachus in Spain, we tested relationships between population dynamics, research efforts, existing threats and conservation milestones. The population growth of the species (from 206 pairs in 1976 to 2,068 in 2011) was parallelled by the increase in the total number of publications, the number of articles in SCI journals and the number of published works dealing with aspects of conservation, threats and management. These results are discussed in terms of cause-effect relationships taking into account that the influence of other non-mutually exclusive factors could also probably explain such associations. Similarly, we analysed the trend of the Cinereous Vulture breeding population with respect to different threats and indices of food availability, obtaining a positive correlation with the increase in big-game hunting bags in Spain. With respect to conservation milestones, we concluded that the current situation is positive in terms of the protection of the species and its habitat, with the situation in relation to food availability being unclear. Finally, we reviewed the main conservation actions that have been taken for the species in Spain and how these have been progressively modified based on new scientific and technical evidence, as an example of adaptive management applied to conservation.

AUTOFLY-Aid: Flight Deck Automation Support with Dynamic 4D Trajectory Management for Responsive and Adaptive Airborne Collision Avoidance

AUTOFLY-Aid Project aims to develop and demonstrate novel automation support algorithms and tools to the flight crew for flight critical collision avoidance using “dynamic 4D trajectory management”. The automation support system is envisioned to improve the primary shortcomings of TCAS, and to aid the pilot through add-on avionics/head-up displays and reality augmentation devices in dynamically evolving collision avoidance scenarios. The main theoretical innovative and novel concepts to be developed by AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck’s perspective, as seen/measured/informed by the aircraft flying in SESAR 2020, b) design and development of a dynamic trajectory planning algorithm that can generate at real-time (on the order of seconds) flyable (i.e. dynamically and performance-wise feasible) alternative trajectories across the evolving stochastic composite airspace picture (which includes new conflicts, blunder risks, terrain and weather limitations) and c) development and testing of the Collision Avoidance Automation Support System on a Boeing 737 NG FNPT II Flight Simulator with synthetic vision and reality augmentation while providing the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures.

Adaptive management and its role in managing Great Barrier Reef water quality

Adaptive management is the pathway to effective conservation, use and management of Australia’s coastal catchments and waterways. While the concepts of adaptive management are not new, applications involving both assessment and management responses are indeed limited at the national and regional scales. This paper outlines the components of a systematic framework for linking scientific knowledge, existing tools, planning approaches and participatory processes to achieve healthy regional partnerships between community, industry, government agencies and science providers to overcome institutional barriers and uncoordinated monitoring. The framework developed by the Coastal CRC (www.coastal.crc.org.au/amf/amf_index.htm) is hierarchical in the way it displays information to allow associated frameworks to be integrated, and represents a construct in which processes, information, decision tools and outcomes are brought together in a structured and transparent way for adaptive catchment and coastal management. This paper proposes how an adaptive management approach could be used to benefit the implementation of the Reef Water Quality Protection Plan (RWQPP).

Goal-based modeling of dynamically adaptive system requirements

Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such as ecosystem monitoring and disaster management. One key challenge posed by Dynamically Adaptive Systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. Berry et al. previously identified four levels of RE that should be performed for a DAS. In this paper, we propose the Levels of RE for Modeling that reify the original levels to describe RE modeling work done by DAS developers. Specifically, we identify four types of developers: the system developer, the adaptation scenario developer, the adaptation infrastructure developer, and the DAS research community. Each level corresponds to the work of a different type of developer to construct goal model(s) specifying their requirements. We then leverage the Levels of RE for Modeling to propose two complementary processes for performing RE for a DAS. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed to monitor the River Ribble in Yorkshire, England.

Adaptive SOA Infrastructure Based on Variability Management

In order to exploit the adaptability of a SOA infrastructure, it becomes necessary to provide platform mechanisms that support a mapping of the variability in the applications to the variability provided by the infrastructure. The approach focuses on the configuration of the needed infrastructure mechanisms including support for the derivation of the infrastructure variability model.

Temperature management for heterogeneous multi-core FPGAs using adaptive evolutionary multi-objective approaches

Heterogeneous multi-core FPGAs contain different types of cores, which can improve efficiency when used with an effective online task scheduler. However, it is not easy to find the right cores for tasks when there are multiple objectives or dozens of cores. Inappropriate scheduling may cause hot spots which decrease the reliability of the chip. Given that, our research builds a simulating platform to evaluate all kinds of scheduling algorithms on a variety of architectures. On this platform, we provide an online scheduler which uses multi-objective evolutionary algorithm (EA). Comparing the EA and current algorithms such as Predictive Dynamic Thermal Management (PDTM) and Adaptive Temperature Threshold Dynamic Thermal Management (ATDTM), we find some drawbacks in previous work. First, current algorithms are overly dependent on manually set constant parameters. Second, those algorithms neglect optimization for heterogeneous architectures. Third, they use single-objective methods, or use linear weighting method to convert a multi-objective optimization into a single-objective optimization. Unlike other algorithms, the EA is adaptive and does not require resetting parameters when workloads switch from one to another. EAs also improve performance when used on heterogeneous architecture. A efficient Pareto front can be obtained with EAs for the purpose of multiple objectives.

Adaptive management, international co-operation and planning for marine conservation hotspots in a changing climate

Acknowledgements This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (Grant reference HR09011) and contributing institutions.

Adaptive management, international co-operation and planning for marine conservation hotspots in a changing climate

Acknowledgements This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (Grant reference HR09011) and contributing institutions.

Linking the ecosystem service approach to social preferences and needs in integrated coastal land use management - a planning approach

Coastal zones with their natural and societal subsystems are exposed to rapid changes and pressures on resources. Scarcity of space and impacts of climate change are prominent drivers of land use and adaptation management today. Necessary modifications to present land use management strategies and schemes influence both the structures of coastal communities and the ecosystems involved. Approaches to identify the impacts and account for (i) the linkages between social references and needs and (ii) ecosystem services in coastal zones have been largely absent. The presented method focuses on improving the inclusion of ecosystem services in planning processes and clarifies the linkages with social impacts. In this study, fourteen stakeholders in decisionmaking on land use planning in the region of Krummhörn (northwestern Germany, southern North Sea coastal region) conducted a regional participative and informal process for local planning capable to adapt to climate driven changes. It is argued that scientific and practical implications of this integrated assessment focus on multifunctional options and contribute to more sustainable practices in future land use planning. The method operationalizes the ecosystem service approach and social impact analysis and demonstrates that social demands and provision of ecosystem services are inherently connected.