Abstract: Systems and methods for implementing a reinforcement machine learning framework for dynamic demand forecasting. A method includes generating estimated booking data for an initial time with a demand model trained using a training set of historical booking data. A variance is detected between the estimated booking data and transient booking data observed at the initial time that exceeds a defined threshold. In response to detecting the variance, a reinforcement learning service is activated. An updated training set including enhanced booking data observed at a subsequent time is created after activating the reinforcement learning service. A parameter of the demand model is updated by training the demand model using the updated training set.

Abstract: Systems and methods for implementing a machine learning framework for demand shock detection for dynamic demand forecasting. A method includes generating predicted booking observations with a demand model trained using a training set of historical booking data. Transient booking observations are obtained from an active database. An observed likelihood score is computed from the transient booking observations based on the demand model trained on the historical booking data. A demand shock threshold is computed based on the statistical relationship between a time to detection of the demand shock event and at least one shock detection criterion. An occurrence of a demand shock event is determined by comparing the observed likelihood score to the demand shock threshold.

Abstract: Regulators and/or parts or components thereof useful, for example, in systems for powering pneumatic tools. In certain embodiments, dual-stage regulators wherein each stage of the regulators is adjustable and/or tunable. In certain preferred embodiments, tunable and/or adjustable dual-stage regulators which are capable of being used, selectively as desired, in low and/or high pressure applications, shot-type and/or continuous flow delivery applications, and/or low and/or high volume applications (or any combination thereof). In certain additional embodiments, in combination with or separate from the features of other embodiments described herein, regulators which exhibit stable performance regardless of, for example, cylinder supply pressure.

Abstract: A graphics driver and method is provided that facilitates graphics rendering time partitioning to provide improved resource allocation between multiple windows and/or multiple graphics clients. The graphics driver receives high level graphics data from multiple graphics clients and outputs a time-partitioned chain of graphics primitives to the graphics processor. The graphics driver includes a partitioning controller, a graphics translator, and a chain builder. The partitioning controller allocates processing time among the multiple graphics clients, with each of the multiple graphics clients being allocated a periodic budget. The graphics translator translates high level graphics commands received from the graphics clients into graphics primitives that can be processed by the graphics processor. The chain builder creates chains of the graphics primitives that are configured to give each graphics client its associated periodic budget in the graphics processor.