Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: An electric drive system has a group transmission with a main group and a range group with a planetary gear set. First and second input shafts of the main group are respectively coupled with first and second electric engines. An output shaft of the main group is coupled with a first element of the planetary gear set and a second element of the planetary gear set is coupled with an output drive shaft of the group transmission. Two idler wheels are disposed coaxially to the first input shaft and two further idler wheels are disposed coaxially to the second input shaft. The first and second input shafts are coupled with the output shaft via two fixed gears. A first fixed gear engages with the first and third idler wheels and a second fixed gear engages with the second and fourth idler wheels.

Abstract: A group transmission device includes an upshift assembly with a first transmission element, a second transmission element and a third transmission element. A downshift assembly has a first transmission element, a second transmission element and a third transmission element. A main shaft is arranged coaxially to the upshift assembly and a layshaft is arranged parallel to the main shaft. A first idler gear is arranged coaxially to the main shaft and axially between the upshift assembly and the downshift assembly and is connectable to the main shaft for conjoint rotation by a first shift unit. The first idler gear is connectable to the third transmission element of the downshift assembly for conjoint rotation by a second shift unit.

Abstract: A group transmission device includes a main transmission which has a main shaft, a countershaft and a spur gear pair which includes a first spur gear arranged coaxially and axially overlapping with the main shaft and a second spur gear arranged coaxially and axially overlapping with the countershaft. A range group has a first shaft non-rotationally connected to the main shaft, a second shaft non-rotationally connected to a transmission output shaft, a third shaft and a blocking switching unit. A first switching unit non-rotationally connects the third shaft to a housing. A second switching unit has an axially shiftable switching element and non-rotationally connects the third shaft to the first spur gear. The main shaft is coupled non-rotationally to a transmission input shaft. A third switching unit has an axially shiftable further switching element and non-rotationally connects the first spur gear to the first shaft of the range group.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effective for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: Systems, methods and products for intelligent delivery of communications, where a machine learning engine is trained to identify an output channel for delivery of a communication based on received context information and intended recipient information and to route the communication to the selected channel. An intelligent delivery task in a communication flow model is performed by the machine learning engine, which receives customer/recipient data such as age, region, gender, etc., and context data such as communication type, time of day, working hours, etc., and uses this data to determine which of a set of different channels is likely to be most effecting for sending the communication to the recipient. A user therefore does not have to build a complex static communication flow, but simply adds an intelligent delivery task to the flow. The output channel is dynamically selected and may vary for different recipients and communications.

Abstract: A range-change transmission device, which is a splitter transmission, includes an input shaft, an output shaft, a countershaft, at least one planetary gear set, and a torque adjustment device. A first transmission element of the planetary gear set is arranged coaxially to the output shaft. A second transmission element of the planetary gear set is or can be directly coupled to the countershaft. A third transmission element of the planetary gear set is permanently coupled to the input shaft in a rotationally fixed manner. The countershaft is or can be coupled to the torque adjustment device. The range-change transmission device has a first switching unit, which is provided to couple the countershaft to the output shaft.

Abstract: An electric drive for a motor vehicle includes a housing, an output shaft, an electric engine, which has a stator and a rotor rotatable relative to the stator, a planetary gear set arranged in the housing, which has a sun gear, a ring gear and a planetary carrier, which is non-rotatably connected to the output shaft, having a first switching element, by means of which the ring gear can be non-rotatably coupled to the rotor, and a second switching element, by means of which the ring gear can be non-rotatably coupled to the housing. The first switching element and the second switching element are coupled to each other via a first coupling element and thereby can be operated together by a single first actuator common to the first switching element and the second switching element.

Abstract: A range-change transmission device includes an input shaft, an intermediate shaft, a countershaft, a transmission output shaft, and a first planetary gear set. A first transmission element of the first planetary gear set is permanently coupled to the intermediate shaft in a rotationally fixed manner. A second transmission element of the first planetary gear set is coupled to the transmission output shaft. A first switching unit is provided to arrange a third transmission element of the first planetary gear set to be fixed to the housing in at least one switching position. The range-change transmission device also includes a second planetary gear set. A third transmission element of the second planetary gear set is permanently coupled to the intermediate shaft in a rotationally fixed manner.

Abstract: A range-change transmission device includes a main shaft, an output shaft, and a range-change unit. The range-change unit has at least one planetary gearbox, which includes at least one first gearbox element, at least one second gearbox element, and at least one third gearbox element. The range-change unit also has at least one shifting device, which is provided at least for the selective connection of the main shaft to the first gearbox element and/or to the second gearbox element.

Abstract: An example system includes a probe to generate ultrasound scans; a user interface to receive inputs from and to provide outputs to a user; and a controller to receive selection of an objective value for each of a plurality of lung sectors of a patient and present an objective lung assessment to the user through the user interface.

Abstract: An example system includes a probe to generate ultrasound scans; a user interface to receive inputs from and to provide outputs to a user; and a controller to receive selection of an objective value for each of a plurality of lung sectors of a patient and present an objective lung assessment to the user through the user interface.

Abstract: In a motor vehicle transmission with a power take-off drive, an auxiliary drive clutch in the form of a jaw clutch is arranged in the torque flow downstream of the transmission input clutch for coupling the power take-off drive to the transmission input shaft under the control of the drive motor clutch while the transmission is disconnected.

Abstract: In a motor vehicle transmission with a power take-off drive, an auxiliary drive clutch in the form of a jaw clutch is arranged in the torque flow downstream of the transmission input clutch for coupling the power take-off drive to the transmission input shaft under the control of the drive motor clutch while the transmission is disconnected.

Abstract: A diagnostic system with a single diagnostic protocol server and multiple data source modules for an electronically controlled internal combustion engine.