Computational problems that involve dynamic data have been an important subject of study in programming languages. Recent advances in self-adjusting computation have developed techniques that enable programs to respond automatically and efficiently to dynamic changes in their inputs. But these techniques have required an explicit programming style, where the programmer must use specific monadic...

providing a high-quality service for transmission and playing real-time voice conversations (voice streaming) over wireless ad-hoc networks is no mean feat. buffering together with adjusting the playout time of the packets is a receiver-side solution to overcome this challenge. in this paper, a new adaptive playout adjustment algorithm is proposed to stream the voice conversations over wireless...

A soft linen emulsion rate intelligent control system based on the domain interpolation algorithm with self adjusting is introduced. In the hemp textile industry, soft linen deal processes can directly affect its following process. We take the lead to use the fuzzy control method applied in soft linen emulsion rate of Intelligent Control System. In the research process, the improvement of produ...

Performance and development are based on hard work, experience and learning. Learning how to change different behaviors is crucial to successful talent management plans. Within the brain there are complex connected circuits that can identify threats. The brain reacts to change as a threat. There is also a collection of brain structures tied to a natural reward system that are involved in the re...

Self-adjusting computation is a language-based approach to writing programs that respond dynamically to input changes by maintaining a trace of the computation consistent with the input, thus also updating the output. For monotonic programs, i.e. where localized input changes cause localized changes in the computation, the trace can be repaired efficiently by insertions and deletions. However, ...

We approach concept learning as a heuristic search through a space of concepts for a concept that satisfies the learning task at hand The heuristics represent bias that the concept learning program employs when forming an inductive generalization. We present a model of bias adjustment and report our experience with an implementation of the model. A major objective in research on inductive conce...