Generally speaking, the mobile robot is capable of sensing its surrounding environment, interpreting the sensed information to obtain the knowledge of its location and the environment, and planning a real-time trajectory to reach the object.
Making predictions about our environment – interpreting what we see and hear, say, on the basis of only partial information – could once have been essential to our survival, and indeed still often is, for example when crossing the road.
These new models are only instantiated by the simulation environment interpreting the SED-ML file.
In the meantime, teeth are load-bearing structures; and they are capable of sensing mechanical stimuli in their local environment, interpreting these stimuli, and responding in a biologically appropriate fashion in the routine mastication [ 4– 6].
Their fusion of conventional structural materials with aspects of information technology, offerss the prospect of engineering systems which can sense their local environment, interpret changes in this environment and respond appropriately.
The uppermost 1-m part of the sequence represents a destabilized depositional environment interpreted as reflecting an increased influence of brackish water due to the approaching coastline during the Littorina transgression.
Cognitive radio (CR) technology can address those issues, providing to femto-BS capabilities to sense the environment, interpret the received signal from the macro-BS and the surrounding femto-BSs, and intelligently allocate spectrum resources while cross-tier and the intra-tier interference are controlled.
Achieving this goal, which is important from both fundamental and practical standpoints, requires measuring the rates of enzyme reactions in their native environment and interpreting these measurements using simple but realistic mathematical models — the two elements which served as the cornerstones for Michaelis' and Menten's seminal 1913 paper.
In our study, we performed the steps from exploring the environment to interpreting the different scenarios.
Based on extensive micro- and biofacies documentation, five lithofacies associations were defined and their respective depositional environments were interpreted.
