This paper first introduces two different types of complexity: (i) complexity by design and (ii) the intrinsic complexity of multi-disciplinarity, from the viewpoint of knowledge structure.
Big data add two further dimensions of complexity: (i) being "very" source specific, and for this we adopt the interesting UNECE classification, and (ii) being highly unstructured and schema-less, often without golden standards to refer to or very difficult to access.
Big data add two further dimensions to such complexity: (i) being "very" source specific, and for this we have adopted the UNECE classification, and (ii) being highly unstructured and schema-less, often without golden standards to refer to or very difficult to access.
To reduce the complexity, i.e., search time and computation complexity, this work also develops an efficient search algorithm.
The papers [14, 40] give lower bounds in the sense of worst case complexity; i.e., lower distance bounds.
In this paper I investigate whether simplified, deterministic PDE models of landform evolution also exhibit fractal behavior and other features of complexity (i.e. deterministic chaos).
Beating Moore's Law Moore's Law states that every two years, microchips double in complexity (i.e., number of transistors) while maintaining minimum cost.
The implications of these findings for two most widely-used models of task complexity, i.e. Cognition Hypothesis (Robinson, 2007) and Limited Capacity model (Skehan, 2009) are discussed.
The main evolutionary mechanisms leading to increases in genome complexity (i.e. gene duplication and transposon proliferation) can all potentially produce increases in DNA clustering.
It presents a framework based on Bayes networks to use available data at multiple levels of complexity (i.e. components, subsystem, etc).
Overall, as design complexity (i.e., number of degrees of freedom) increases, the power to achieve a certain flap deflection decreases.
