This vulnerability assessment reveals that it is possible for the attacker to realize the given objective via the assumed grid access, and gives a finite state "trace" of one means of exploiting the vulnerability.
This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation.
Incrementally, the samples that do not conform to the given objective function (for example, their classification error is more than a threshold, or their reconstruction error is high) are collected and are used for adding new nodes to the hidden layer, with these new nodes being initialized based on those samples.
The responses from the farmers for the given objectives can be seen in Fig. 3, which shows the percentage of responses for each of the importance rankings for each of the objectives.
The single objective optimization can provide the "best" solution directly for a given objective while the multi-objective optimization provides rich information for designers to make better compromised decisions.
Additionally, we consider the following recreate operations: greedy k : insert the control points bringing the highest profit for a given objective k. closer : insert the control points that are close to the current solution, i.e. those that would induce the smallest extra traveling time.
Additionally, we consider the following recreate operations: greedy k : select the subset which brings the highest profit for a given objective k. random : randomly select a subset.
If achieving a business objective requires the functional contributions of several employees, the manager has a fundamental responsibility to identify the functional contributions needed for a given objective and to organize into a team the particular employees who will make those contributions.
In this framework, model checking can be used to compute, for example, the minimum battery capacity necessary for achieving a given objective, or the maximal achievable lifetime of a system with a given initial battery capacity.
