50,230 research outputs found

    Adaptive Governance and Evolving Solutions to Natural Resource Conflicts

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    New Zealand is facing increasing challenges in managing natural resources (land, freshwater, marine space and air quality) under pressures from domestic (population growth, agricultural intensification, cultural expectations) and international (climate change) sources. These challenges can be described in terms of managing ‘wicked problems’; i.e. problems that may not be understood fully until they have been solved, where stakeholders have different world views and frames for understanding the problem, the constraints affecting the problem and the resources required to solve it change over time, and no complete solution is ever actually found. Adaptive governance addresses wicked problems through a framework to engage stakeholders in a participative process to create a long term vision. The vision must identify competing goals and a process for balancing them over time that acknowledges conflicts cannot always be resolved in a single lasting decision. Circumstances, goals and priorities can all vary over time and by region. The Resource Management Act can be seen as an adaptive governance structure where frameworks for resources such as water may take years to evolve and decades to fully implement. Adaptive management is about delivery through an incremental/experimental approach, limits on the certainty that governments can provide and stakeholders can demand, and flexibility in processes and results. In New Zealand it also requires balancing central government expertise and resources, with local authorities which can reflect local goals and knowledge, but have varying resources and can face quite distinct issues of widely differing severity. It is important to signal the incremental, overlapping, iterative and time-consuming nature of the work involved in developing and implementing adaptive governance and management frameworks. Managing the expectations of those involved as to the nature of the process and their role in it, and the scope and timing of likely outcomes, is key to sustaining participation.Adaptive capacity; governance; resilience

    Applications of Soft Computing in Mobile and Wireless Communications

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    Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications
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