I think that, when attempting to model the nervous system, it is important not to overlook the fact that the nervous system has an immense organized complexity.doi:10.1007/978-1-4899-6323-9_7Samuel BogochSpringer US
There are some interpretations of vulnerability that seek its root cause in the creation of risk by political and economic systems that make investment and locational decisions for the benefit of small elites without regard for how these decisions affect the majority. Finally, whatever succe...
However, inherent uncertainties, the significant number of interactive subsystems and feedback loops [74] constrain the reliability of model projections. This is particularly true in the case of models that incorporate human behavior, as research has shown that structural decisions in terms of how ...
The @model directive allows access to the list of movies that the controller passed to the view by using a Model object that's strongly typed. For example, in the Index.cshtml view, the code loops through the movies with a foreach statement over the strongly typed Model object:...
the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. Wit...
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We focus on three aspects that determine whether a model is fit-for-purpose from a decision-maker's perspective: relevance of the model outcome, stakeholder acceptance and timeliness in the decision-making process. Relevance of the model outcome relates to the processes that are modelled and ...
Since the SHM features a multitude of feedback loops, locating errors was very tedious with the original monolithic model. Systematic debugging became only possible when we isolated the different parts of the system, such as the baroreceptors, and subjected them to controlled input signals to obser...
Focus on bringing high value through quality investment with customer satisfaction, reliability, efficiency and agile feedback loops. We continue to refine our strategy and platform applications to materialize our vision for autonomous quality in AI model productization. As we implement, ...
Stochastic input is exploited for training, which consists of the observed partial state vector as the first and its immediate future as the second component so that the neural machine regards the latter as the future state of the former. In the testing (deployment) phase, the immediate-future...