Plan for Development Clause Samples
Plan for Development. A. Process • SAC and RAC will meet jointly for purposes of developing the AMP. • SAC /RAC will collaborate with faculty alliance, and faculty alliance will collaborate with each faculty senate to provide input to SAC during development. • The process of developing the AMP will be open, collaborative, transparent and inclusive. • All ideas and proposals brought to SAC/RAC through the Faculty Alliance or other councils and committees will be considered. • Existing resource materials will be utilized in development of the AMP. Those resources include, but are not limited to, mission statements; vision statements, strategic plans, and academic plans that already exist at each MAU. • SAC/RAC will seek guidance and input from other SW councils and other MAU committees and councils as appropriate. • Additional ad hoc committees may be convened by SAC/RAC in the interest of efficiency as development of the AMP proceeds. • Final approval of the AMP will be by consensus of the SAC/RAC. Faculty Alliance representatives to SAC/RAC will be voting members of the committee for development and approval of the AMP. • The final plan will be presented to each faculty senate for their consideration prior to being forwarded by SAC to the President’s Cabinet and Board of Regents.
B. Time line • Dec 15: Charge approved by Faculty Alliance, SAC/RAC, VP for Academic Affairs • Dec 15 – Mar 31: SAC/RAC meets to develop plan. Meetings will be held frequently (every 2 weeks), ad hoc committees may be formed, additional input from SW Councils and Faculty Senates will be sought • Mar 31: Draft AMP will be presented to all three Faculty Senates • April : Faculty senates will respond through their formal representatives to SAC/RAC • May 1: Final changes will be presented to all three Faculty Senates and Faculty Alliance for their consideration. • May 15: AMP presented to President’s Cabinet • June 1: AMP presented to BOR
Plan for Development. A proposed ordering for the development of the scripts that comprise the DSE module is shown graphically in Figure 6. The plan consists of five columns, one for each of the script classes previously introduced, and the boxes on each line represent the method that will encoded in the a script and that point with time flowing from top to bottom. The ordering of the method developing is based upon a breadth first approach, preferring to have a set of scripts that spans from the driver through to the presentation of results before, for example, implementing all DSE search algorithms. It is hoped that this will best facilitate the adoption of the DSE module by the WP1 partners and therefore improve the flow of feedback. The plan is split into three years, with each year ending with a blue line labelled. ▇▇, ▇▇ and Y3 respectively. In year 1 we see the completed scripts for exhaustive DSE search and the singular version of the ▇▇▇ handler have been completed (gree bounding box), we also see the simple objective script bounded in yellow, which is the current focus of our developments. Finally for this year we see that we intend to implement a Pareto ranking method and HTML presentation of the results. This will give us a complete, is computationally intensive, set of DSE methods. In year 2, two more efficient DSE driver methods will be implemented, these are the genetic approach and space culling, along with further objective eval- uation methods to both support the WP1 case studies and to allow the space culling approach to work. In terms of presentation, feedback on the search progress will be developed and importantly results feedback will be integrated with the INTO-CPSapp, along with the definition of DSE parameters. Since the DSE script is not integrated with the ▇▇▇, as it effectively is in the Crescendo tool, this opens up the possibility of running parallel simulations on multiple hosts which would have the effect of dramatically increasing the speed at which the design space could be explored. Such remote simula- tions could either be on spare machines or potentially using cloud based services. In the final year, further DSE algorithms will be implemented along with more complex constraint checking and support for user defined ranking func- tions. These time lines are conservative and it is hoped that items from year 3 may be brought forward to year, thus increasing the opportunity to respond to WP1 feedback and produce well founded guidelines. [BFG+12]...