The third way in which we address Brundtland-type sustainability is making intertemporal comparisons through discounting.
There are subtle issues with regard to the elimination of these forces, which we address in this paper.
This is Ok if we are content with incremental progress, but we are not and we need to change the very basis in which we address climate change.
One important puzzle, which we address, is the following: How could effective RES-policies be introduced against the political opposition of fossil-fuel interest groups in the past?
Accordingly, speech detection translates to the question of how to properly fuse the audio and video signals, which we address within the framework of deep learning.
Due to the large dimensions of these capillaries, simulation of such systems faces considerable difficulties which we address in this paper.
Likewise, an implicit temporal discretization is used for the parabolic terms including Navier Stokes viscosity which we address separately through the development of a method for solving the heat diffusion equations.
Previous approaches focus on collecting either ratings or pairwise comparisons of items from the crowd, but little study has been done in combining the two crowd interfaces, which we address in this paper.
These pipelined solutions, however, can suffer from significantly increased latency, and this motivates the latency-constrained resynchronization problem, which we address for a restricted class of graphs that permit efficient computation of latency.
We present a pepper-pot design in which we address the problem of penetration by high energy particle, deriving analytical expressions and performing GEANT4 simulations for the estimation of the error introduced by a long (thick) pepper-pot.
The addition of the temporal dimension to the explored space makes the exploration task a never-ending data-gathering process, which we address by application of information-theoretic exploration techniques to world representations that model the uncertainty of environment states as probabilistic functions of time.
