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174 DESIGN OF ALGORITHMS 1741 From Subtask to Algorithm Each step or subtask can recursively be divided further into more detailed subtasks The decision where to stop recursion and develop decision aids makes up the difference between a problem-oriented approach, a planner-oriented approach, and a mimicking approach The ideal of a problem-oriented approach is to nd the optimal solution to the integral problem Hence, it aims at a decision aid supporting a large set of subproblems or subtasks of the planner and is focused on improving the quality of the solution The ideal of a mimicking approach is an increased speed of nding an acceptable solution It emulates the behavior of the planner as well as possible, resulting in the same quality as a manual solution but achieved within shorter time.





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Thus, in contrast to the temperature variations of differently colored materials exposed to a source that emits radiation in the latter regions, all materials exposed to uorescent UV radiation attain the same (ambient) temperature For materials that vary in their sensitivity to heat, stability rankings can differ from those based on exposure to solar or solar-simulated radiation The uorescent UV sources are typically incorporated into uorescent UV/condensation devices in which dark periods with condensation are alternated with periods of UV radiation The temperature is generally controlled at different levels during each of these periods The devices may also incorporate periodic water spray on the front surface of the samples during exposure to radiation but do not control relative humidity Some of the modern types of these devices have capabilities for irradiance control Procedures for exposing polymeric materials in.

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Hence, a mimicking approach continues the recursion process until the process can be automated in an algorithm Finally, the ideal of a planner-oriented approach, proposed in this chapter, is to support the planner in his task of achieving high-quality solutions within the available time We therefore do not simply emulate the manual decision process, but stop recursion where we identify subtasks that cost a lot of effort to the planner without being very important for the acceptability of the solution Decision aids should both be able to perform these subtasks in a shorter time than manually and include intelligence on the larger problem, resulting in a higher quality of the nal solution achieved In a planner-oriented approach, identi cation of subtasks that are candidates for algorithmic support depends on the efforts associated with a speci c subtask.

The priorities that are generated for opportunities in the analysis and evaluation process can be interpreted in much the same way as risk priorities, with the focus of action being on capturing and exploiting the opportunities rather than avoiding or mitigating the problems Extreme opportunity: detailed planning is warranted at senior levels to prepare for and capture the opportunity High opportunity: senior executive management attention is appropriate and management responsibility should be specified Medium opportunity: manage by specific monitoring or response procedures Low opportunity: manage by routine procedures that are unlikely to need the specific application of resources Treatment options for risks having positive outcomes (opportunities) are similar in concept to those for treating risks with negative outcomes, although the interpretation and implications are clearly different.

The more frequently the subtask is repeated, the more time can be saved by using a decision aid However, repetition is not the only factor Subtasks that require many well-described but time-consuming administrative tasks, such as storing and retrieving information, and performing calculations, are also candidate for inclusion in decision aids Table 171 shows an example of our detailed task analysis of steps 2 and 4 It provides the pseudo-codes for the activities performed manually by the planner and shows the three subtasks that we identi ed, two of them occurring in both steps..

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