Robot path planning algorithms for finding a goal in a unknown environment focus on completeness rather than optimality. In this paper, we investigate several strategies for using map information, however incomplete or approximate, to reduce the cost of the robot’s traverse. The strategies are based on optimistic, pessimistic, and average value assumptions about the unknown portions of the robo...

Multi–granulation is an improvement of the classical rough set theory since it uses a family of binary relations instead of of a single indiscernibility relation for the constructing of approximation. In this paper, the multi–granulation rough set approach is further generalized into fuzzy environment. A family of fuzzy T–similarity relations are used to define the optimistic and pessimistic fu...

This paper establishes an approach to forecast air cargo demand related to terminal capacity expansion. To balance capacity and demand, it is required to forecast the future demand based on optimistic and pessimistic projections to decide when and how much, the airport should expand the capacity. System dynamics simulation model can provide reliable forecast and generate scenarios to test alter...

ÐPast research in message logging has focused on studying the relative overhead imposed by pessimistic, optimistic, and causal protocols during failure-free executions. In this paper, we give the first experimental evaluation of the performance of these protocols during recovery. Our results suggest that applications face a complex trade-off when choosing a message logging protocol for fault to...

Perceived risk can influence health behaviors. Studies using various populations and breast cancer risk bias assessment methods have identified both risk over- and underestimation. Among 1803 women in primary care settings, 47 percent were at average epidemiologic risk (Gail calculated relative risk ±50 percent of age-adjusted population average) and 55 percent perceived themselves to be at ave...

In this paper the application of uncertainty modeling to convolutional neural networks is evaluated. A novel method for adjusting the network’s predictions based on uncertainty information is introduced. This allows the network to be either optimistic or pessimistic in its prediction scores. The proposed method builds on the idea of applying dropout at test time and sampling a predictive mean a...

Future servers will be equipped with thousands of CPU cores and deep memory hierarchies. Traditional concurrency control (CC) schemes -both optimistic and pessimistic -slow down orders of magnitude in such environments for highly contended workloads. Optimistic CC (OCC) scales the best for workloads with few conflicts, but suffers from clobbered reads for high conflict workloads. Although pessi...

We consider whether sentiment affects the validity of CAPM. We hypothesize that pessimistic periods have low levels of noise trading because costly short-selling mutes trading on negative sentiment. On the other hand optimistic sentiment stimulates long positions that are easier to establish, and optimistic periods may also attract more naïve investors, stimulating greater noise trading. Thus, ...