Secondly, using the framework, we designed prototype learning tools and presented case study examples to Indigenous knowledge and curriculum experts in the field then performed one-on-one interviews using open-ended questioning techniques to gather data.
We experimentally study the performance of several specialized algorithms designed using the framework and implemented using MPI.
The practical was designed using the framework of Legitimation Code Theory, with the aim of stimulating active links between the theoretical and practical (in this case pump and piping networks, head loss and application of the energy equation), through a group-based competitive, informal, interactive learning event.
Phases 1 and 2: Interviews will be fully transcribed and data subjected to thematic analysis using the Framework approach, 52 which is designed to address applied policy-related questions.
We used the framework when designing a scientific collaboratory system.
Finally, we offer implications for policy makers who can use the framework to design the regulations in a way that will stimulate appropriate incubator creation and hence sustain local entrepreneurship, as well as for incubator managers who can follow the findings to position their incubation model in line with their resources, capabilities and objectives.
In this paper, a method for environmental observation network design using the framework of spatial modeling with copulas is proposed.
Possible extensions of the transactive energy value mapping approach to upstream and downstream activities and to different energy sectors, as well as the advantages of using the framework in regulatory and policy design, are discussed.
Using the framework of gain functions, we design several optimization criteria for decoding this model and describe resulting decoding algorithms, ranging from the traditional Viterbi and posterior decoding to block-based decoding algorithms tailored to our model.
This paper introduces a grid-enabled framework for the multi-objective optimisation of computationally expensive problems, before using the framework in the multi-objective evolutionary design of a robust lateral stability controller for a real-world aircraft using H∞ loop shaping.
