Abstract: An embodiment of the present invention monitors a process across a plurality of systems associated with a supply chain. A context is determined for an order, where at least one of the features of the context includes information from a networked sensing device. One or more first machine learning models identify a plurality of orders of an order history having features corresponding to the order. A second machine learning model is trained with the identified plurality of orders to predict the monitoring interval for the order. The second machine learning model predicts the monitoring interval for the order based on the context of the order. The monitoring interval for the order is dynamically adjusted based on the predicted monitoring interval, and the order is monitored through an order fulfillment process across the plurality of systems associated with the supply chain in accordance with the adjusted monitoring interval.

Abstract: An embodiment of the present invention monitors a process across a plurality of systems associated with a supply chain. A context is determined for an order, where at least one of the features of the context includes information from a networked sensing device. One or more first machine learning models identify a plurality of orders of an order history having features corresponding to the order. A second machine learning model is trained with the identified plurality of orders to predict the monitoring interval for the order. The second machine learning model predicts the monitoring interval for the order based on the context of the order. The monitoring interval for the order is dynamically adjusted based on the predicted monitoring interval, and the order is monitored through an order fulfillment process across the plurality of systems associated with the supply chain in accordance with the adjusted monitoring interval.

Abstract: A predictive engine on a computer environment comprising a shared pool of configurable computing resources is executed to perform a predictive analysis on data pipelined into the computer environment, the data received from a plurality of sources and in a plurality of different formats, the predictive engine generating a network level cost information based on the predictive analysis on a dynamic and continuous basis. Asynchronous communication comprising the network level cost information from the predictive engine is received and a set of candidate nodes for order fulfillment is generated based on the network level cost information and a defined distance between the set of candidate nodes and a target destination. An optimization engine on the computer environment is invoked that filters the set of candidate nodes. A number of fulfillment nodes that meet one or more of a constraint and preconfigured rule is output.

Abstract: An artifact processing system and method for ranking artifacts is provided.

Abstract: A predictive engine on a computer environment comprising a shared pool of configurable computing resources is executed to perform a predictive analysis on data pipelined into the computer environment, the data received from a plurality of sources and in a plurality of different formats, the predictive engine generating a network level cost information based on the predictive analysis on a dynamic and continuous basis. Asynchronous communication comprising the network level cost information from the predictive engine is received and a set of candidate nodes for order fulfillment is generated based on the network level cost information and a defined distance between the set of candidate nodes and a target destination. An optimization engine on the computer environment is invoked that filters the set of candidate nodes. A number of fulfillment nodes that meet one or more of a constraint and preconfigured rule is output.

Abstract: A method of determining an amount of dissolved gas in a fluid sample is disclosed. The method includes hydraulically confining and expanding the sample while measuring pressure and volume. A first volume and pressure are determined at which the rate of change in pressure with respect to volume deviates from a linear relationship. A second volume and pressure at which continued expansion of the fluid causes substantially no change in pressure is determined. The first pressure and volume are extrapolated by the linear relationship to intersect an extrapolation from the second volume and pressure at no change in pressure, thereby determining a bubble point comprising a bubble point pressure and a bubble point volume. A third pressure corresponding to measured pressure of the fluid sample at the bubble point volume is determined.

Abstract: The present invention is a sample tank for storing and transporting a fluid sample withdrawn from an earth formation by a formation fluid sampling tool. The sample tank includes a storage cylinder adapted to withstand high internal pressure. The storage cylinder is selectively hydraulically connected to the sampling tool for conducting the fluid sample into the storage cylinder. A fusible metal substantially surrounds the storage cylinder. The fusible metal has a melting temperature not more than the temperature of the fluid sample, so that solidification of the fusible metal maintains the fluid sample substantially at the melting temperature of the fusible metal during solidification of the fusible metal as the tool is withdrawn from the wellbore and cooled. The fusible metal is surrounded by an outer housing which contains the fusible metal when it is in a liquid state.