Abstract: A system for analyzing a multiphase production fluid, the system including a pipeline, an inlet divider having a set of analyzing apertures with densitometers and a set of production apertures, a fluidic separation chamber with flowmeters, a pressure control valve, and a fluidic control unit. Each analyzing aperture of the set of analyzing apertures disposed on a vertically-oriented axis of the inlet divider. The pipeline is configured to supply the multiphase production fluid to the inlet divider. The inlet divider is configured to provide an analysis portion of the multiphase production fluid to the set of analyzing apertures. The inlet divider is configured to provide a production portion of the multiphase production fluid to the set of production apertures. The set of analyzing apertures is configured to provide the analysis portion to the fluidic separation chamber.

Abstract: The disclosed system obtains KPIs and configuration parameters associated with the mature and the immature network. A physical layer of the mature wireless telecommunication network corresponds to a physical layer of the immature wireless telecommunication network. The system combines KPIs of the immature network and KPIs of the mature network to obtain multiple KPIs. The system predicts an attribute associated with the immature wireless telecommunication network, where the attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the configuration parameters to a machine learning model trained on data associated with the mature wireless telecommunication network. The machine learning model predicts the value of the attribute associated with the immature wireless telecommunication network based on the multiple key performance indicators and the configuration parameters.

Abstract: The system obtains multiple KPIs and multiple configuration parameters directly from a wireless telecommunication network. The multiple KPIs indicate an observed performance associated with the wireless telecommunication network. The multiple configuration parameters indicate a configuration of the wireless telecommunication network. The system predicts a value of a difficult to predict attribute of the wireless telecommunication network, where the difficult to predict attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the multiple configuration parameters to a machine learning model. The machine learning model predicts the value of the difficult to predict attribute associated with the wireless telecommunication network based on multiple key performance indicators and the multiple configuration parameters.

Abstract: The disclosed system obtains KPIs and configuration parameters associated with the mature and the immature network. A physical layer of the mature wireless telecommunication network corresponds to a physical layer of the immature wireless telecommunication network. The system combines KPIs of the immature network and KPIs of the mature network to obtain multiple KPIs. The system predicts an attribute associated with the immature wireless telecommunication network, where the attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the configuration parameters to a machine learning model trained on data associated with the mature wireless telecommunication network. The machine learning model predicts the value of the attribute associated with the immature wireless telecommunication network based on the multiple key performance indicators and the configuration parameters.

Abstract: The system obtains a recording of an interaction between a UE and a representative of a network. The system obtains a summary associated with the interaction, where the summary includes an indication of a topic representing a portion of the interaction, a time when the topic was present in the interaction, and a generator of the portion of the interaction associated with the topic. The system obtains multiple inputs associated with the multiple UEs and multiple representatives. The system provides the summary of the interaction and the multiple inputs to an AI configured to predict a likelihood of a predetermined action associated with the UE. The system receives from the AI the likelihood of the predetermined action. Based on the likelihood of the predetermined action, the system performs an action within a network prior to an occurrence of the predetermined action associated with the UE.

Abstract: The system obtains an undesirable action associated with the UE from multiple undesirable actions, including disassociating from the wireless telecommunication network or seeking another interaction with a representative of the wireless telecommunication network. The system obtains multiple key performance indices (KPIs) associated with the UE or the representative of the wireless telecommunication network. The system obtains multiple groups of representatives configured to connect to the UE, where a first group among the multiple groups is associated with fewer occurrences of the undesirable action than a second group among the multiple groups. Based on the KPIs associated with the UE, the system determines whether a likelihood of the undesirable action occurring is above a predetermined threshold. Upon determining that the likelihood of the undesirable action occurring is above the predetermined threshold, the system connects the UE with a representative from the first group.

Abstract: A system and a method for accepting a payment on an application is provided. The method is implemented by a processor. The processor receives login information from a client to activate a banking application; selects quick accept entry points associated with the client's business banking demand deposit account (DDA) based on determining that the client is eligible for the quick accept entry points in response to the login information; sets up a payment receiving option for receiving a payment via the banking application; causes the banking application to receive transaction amount data corresponding to a transaction between the client and a customer; causes the banking application to process the transaction amount data; and automatically updates the DDA to reflect receipt of the transaction amount data.

Abstract: The disclosed system obtains KPIs and configuration parameters associated with the mature and the immature network. A physical layer of the mature wireless telecommunication network corresponds to a physical layer of the immature wireless telecommunication network. The system combines KPIs of the immature network and KPIs of the mature network to obtain multiple KPIs. The system predicts an attribute associated with the immature wireless telecommunication network, where the attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the configuration parameters to a machine learning model trained on data associated with the mature wireless telecommunication network. The machine learning model predicts the value of the attribute associated with the immature wireless telecommunication network based on the multiple key performance indicators and the configuration parameters.

Abstract: The disclosed system obtains KPIs and configuration parameters associated with the mature and the immature network. A physical layer of the mature wireless telecommunication network corresponds to a physical layer of the immature wireless telecommunication network. The system combines KPIs of the immature network and KPIs of the mature network to obtain multiple KPIs. The system predicts an attribute associated with the immature wireless telecommunication network, where the attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the configuration parameters to a machine learning model trained on data associated with the mature wireless telecommunication network. The machine learning model predicts the value of the attribute associated with the immature wireless telecommunication network based on the multiple key performance indicators and the configuration parameters.

Abstract: The system obtains multiple KPIs and multiple configuration parameters directly from a wireless telecommunication network. The multiple KPIs indicate an observed performance associated with the wireless telecommunication network. The multiple configuration parameters indicate a configuration of the wireless telecommunication network. The system predicts a value of a difficult to predict attribute of the wireless telecommunication network, where the difficult to predict attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the multiple configuration parameters to a machine learning model. The machine learning model predicts the value of the difficult to predict attribute associated with the wireless telecommunication network based on multiple key performance indicators and the multiple configuration parameters.

Abstract: The disclosed system obtains KPIs and configuration parameters associated with the mature and the immature network. A physical layer of the mature wireless telecommunication network corresponds to a physical layer of the immature wireless telecommunication network. The system combines KPIs of the immature network and KPIs of the mature network to obtain multiple KPIs. The system predicts an attribute associated with the immature wireless telecommunication network, where the attribute depends on multiple other attributes associated with the wireless telecommunication network. To make the prediction, the system provides the multiple key performance indicators and the configuration parameters to a machine learning model trained on data associated with the mature wireless telecommunication network. The machine learning model predicts the value of the attribute associated with the immature wireless telecommunication network based on the multiple key performance indicators and the configuration parameters.

Abstract: A system and a method for accepting a payment on an application is provided. The method is implemented by a processor. The processor receives login information from a client to activate a banking application; selects quick accept entry points associated with the client's business banking demand deposit account (DDA) based on determining that the client is eligible for the quick accept entry points in response to the login information; sets up a payment receiving option for receiving a payment via the banking application; causes the banking application to receive transaction amount data corresponding to a transaction between the client and a customer; causes the banking application to process the transaction amount data; and automatically updates the DDA to reflect receipt of the transaction amount data.

Abstract: One example method includes receiving an IO request from an application, determining if an affinity policy applies to the application that transmitted the IO request, when an affinity policy applies to the application, directing the IO request to a specified site of a replication system, when no affinity policy applies to the application, determining if a lag in replication of the IO request from a primary site to a replication site is acceptable, if a lag in replication of the IO request is acceptable, processing the IO request using performance based parameters and/or load balancing parameters, and if a lag in replication of the IO request is not acceptable, either directing the IO request to a most up to date replica site, or requesting a clone copy of a volume to which the IO request was initially directed and directing the IO request to the cloned copy.

Abstract: The present disclosure describes various embodiments related to methods for determining salinity of water in a borehole of a formation and the water in the formation. Various methods may use inelastic and capture gamma-ray spectra obtained from a pulsed neutron logging tool. Various embodiments may use a ratio of chlorine from a capture spectrum to oxygen from an inelastic spectrum for a near and a far detector to calculate apparent salinity ratios for water in a borehole and a formation. From the apparent salinity ratios, a borehole salinity and a formation salinity may be calculated using a tool characterization database and without using formation water saturation for the calculation. Other embodiments may be disclosed or claimed.

Abstract: The present disclosure describes various embodiments related to methods for determining salinity of water in a borehole of a formation and the water in the formation. Various methods may use inelastic and capture gamma-ray spectra obtained from a pulsed neutron logging tool. Various embodiments may use a ratio of chlorine from a capture spectrum to oxygen from an inelastic spectrum for a near and a far detector to calculate apparent salinity ratios for water in a borehole and a formation. From the apparent salinity ratios, a borehole salinity and a formation salinity may be calculated using a tool characterization database and without using formation water saturation for the calculation. Other embodiments may be disclosed or claimed.

Abstract: An airfoil (10) for a gas turbine engine in which the airfoil (10) includes an internal cooling system (14) with one or more internal cavities having an insert (18) contained within an aft cooling cavity (76) to form nearwall cooling channels having enhanced flow patterns is disclosed. The flow of cooling fluids in the nearwall cooling channels may be controlled via a plurality of cooling fluid flow controllers (22) extending from the outer wall (24) forming the generally hollow elongated airfoil (26). The cooling fluid flow controllers (22) may be collected into spanwise extending rows. In at least one embodiment, the cooling fluid flow controllers (22) may be positioned within a pressure side nearwall cooling channel (48) and a suction side nearwall cooling channel (50) that are both in fluid communication with a trailing edge channel (30). The trailing edge channel (30) may also include cooling fluid flow controllers (22) extending between the outer walls (12, 13) forming the pressure and suction sides.

Abstract: An airfoil (10) for a gas turbine engine in which the airfoil (10) includes an internal cooling system (14) with one or more internal cavities (16) having an insert (18) contained therein that forms nearwall cooling channels (20) having enhanced flow patterns is disclosed. The flow of cooling fluids in the nearwall cooling channels (20) may be controlled via a plurality of cooling fluid flow controllers (22) extending from the outer wall (24) forming the generally hollow elongated airfoil (26). The cooling fluid flow controllers (22) may be collected into spanwise extending rows (28), and the internal cooling system (14) may include one or more bypass flow reducers (30) extending from the insert (18) toward the outer wall (24) to direct the cooling fluids through the channels (20) created by the cooling fluid flow controllers (22), thereby increasing the effectiveness of the internal cooling system (14).

Abstract: An airfoil (10) for a gas turbine engine in which the airfoil (10) includes an internal cooling system (14) with one or more internal cavities (16) having an insert (18) contained therein that forms nearwall cooling channels (20) having enhanced flow patterns is disclosed. The flow of cooling fluids in the nearwall cooling channels (20) may be controlled via a plurality of cooling fluid flow controllers (22) extending from the outer wall (24) forming the generally hollow elongated airfoil (26). The cooling fluid flow controllers (22) may be collected into spanwise extending rows (28), and the internal cooling system (14) may include one or more bypass flow reducers (30) extending from the insert (18) toward the outer wall (24) to direct the cooling fluids through the channels (20) created by the cooling fluid flow controllers (22), thereby increasing the effectiveness of the internal cooling system (14).

Abstract: An airfoil (10) for a gas turbine engine in which the airfoil (10) includes an internal cooling system (14) with one or more internal cavities having an insert (18) contained within an aft cooling cavity (76) to form nearwall cooling channels having enhanced flow patterns is disclosed. The flow of cooling fluids in the nearwall cooling channels may be controlled via a plurality of cooling fluid flow controllers (22) extending from the outer wall (24) forming the generally hollow elongated airfoil (26). The cooling fluid flow controllers (22) may be collected into spanwise extending rows. In at least one embodiment, the cooling fluid flow controllers (22) may be positioned within a pressure side nearwall cooling channel (48) and a suction side nearwall cooling channel (50) that are both in fluid communication with a trailing edge channel (30). The trailing edge channel (30) may also include cooling fluid flow controllers (22) extending between the outer walls (12, 13) forming the pressure and suction sides.

Abstract: An Advanced Biopsy Needle is disclosed that provides both fine needle aspiration and core biopsy with a single insertion, thus reducing trauma and pain to the patient. An inner needle for aspiration and an outer needle for core biopsy are in coaxial relation to each other, thus providing both histology and cytology functions with a single medical device and also with a single insertion. Lateral cutting edges along fenestration openings in the outer needle ensure that adequate tissue samples are taken. A syringe is attached to the inner needle for collection of aspirate.