Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: A facility for optimizing machine learning models is described. The facility obtains a description of a machine learning model and a hardware target for the machine learning model. The facility obtains optimization result data from a repository of optimization result data. The facility optimizes the machine learning model for the hardware target based on the optimization result data.

Abstract: An auto bias system, device and/or method for automatically controlling the bias or quiescent point of at least one vacuum tube including separating bias current flow from signal current flow for controlling the bias/quiescent point by algorithmically adjusting the grid bias voltage whilst monitoring the cathode current to establish the correct bias current.

Abstract: A blood component collection system with data manipulation and optimization capabilities. The system comprises a central database, a data manipulation device, and a communication subsystem connected to the central database and the data manipulation device, and one or more extracorporeal blood processing machines. The central database maintains records of total donation volumes contributed by a donor during selected time periods as communicated by the blood processing machine and as determined by the data manipulation device. The records comprise a total red blood cell donation volume and a total plasma donation volume.

Abstract: An apparatus and a method for separating at least two discrete volumes of a composite liquid into at least two components. Independent microprocessors are provided on a rotor of a centrifugal separation apparatus, which respond to commands from a control computer, gather sensor data and independently control devices on the rotor to process one or more volumes of a composite liquid such as blood. Multiple microprocessors communicate with the control computer across a single communication channel, such as a pair of slip rings or an infrared communications link.

Abstract: A blood component collection system with manipulation and optimization capabilities. In one embodiment, process parameters are derived from an input/configured predetermined blood component yield and which is based upon the maximization of at least one process parameter. Thereafter, the blood component collection procedure is performed with these derived process control parameters. In another embodiment, process parameters are derived from an input total procedure time from a maximized value for at least one of the other process control parameters so as to maximize blood component yield in this fixed time. Thereafter, the blood component collection procedure is performed with these derived parameters.

Abstract: A blood component collection system with manipulation and optimization capabilities. Process parameters are derived from an input/configured predetermined blood component yield and which is based upon the maximization of at least one process parameter. Thereafter, the blood component collection procedure is performed with these derived process control parameters. Also, process parameters are derived from an input total procedure time from a maximized value for at least one of the other process control parameters so as to maximize blood component yield in this fixed time. Thereafter, the blood component collection procedure is performed with these derived parameters.

Abstract: A blood component collection system with data manipulation and optimization capabilities. The system comprises a central database, a data manipulation device, and a communication subsystem connected to the central database and the data manipulation device, and one or more extracorporeal blood processing machines. The central database maintains records of total donation volumes contributed by a donor during selected time periods as communicated by the blood processing machine and as determined by the data manipulation device. The records comprise a total red blood cell donation volume and a total plasma donation volume.

Abstract: A blood component collection system with data manipulation and/or optimization capabilities. In one embodiment, process parameters are derived from an input and/or configured predetermined blood component yield and which is based upon the maximization of at least one process parameter. Thereafter, the blood component separation and collection procedure is performed with these derived process control parameters. In another embodiment, process parameters are derived from an input total procedure time from a maximized value for at least one of the other process control parameters so as to maximize blood component yield in this fixed time. Thereafter, the blood component separation and collection procedure is performed with these derived parameters.

Abstract: Containers, methods and systems for treating blood or blood component products; whereby the containers are adapted to contain blood products and the containers have connected thereto respective information/identification chips for use in maintaining information about the blood products which may be contained within the containers and whereby the information/identification chips are adapted for having information written to and read from the information/identification chips including the writing of information to an information/identification chip that the respective blood product was subjected to a pathogen inactivation process.

Abstract: A blood component collection system with manipulation and optimization capabilities. In one embodiment, process parameters are derived from an input/configured predetermined blood component yield and which is based upon the maximization of at least one process parameter. Thereafter, the blood component collection procedure is performed with these derived process control parameters. In another embodiment, process parameters are derived from an input total procedure time from a maximized value for at least one of the other process control parameters so as to maximize blood component yield in this fixed time. Thereafter, the blood component collection procedure is performed with these derived parameters.

Abstract: A method and apparatus for occlusion monitoring in a flow circuit using pressure waveform analysis. The flow circuit includes a first conduit and a second conduit which fluidly interconnects a fluid supply with the first conduit. A pump is disposed in an intermediate portion of the second conduit. Monitoring of the pressure in the first conduit is used to identify any occlusions in that portion of the second conduit which is disposed between the pump and the fluid supply.

Abstract: A method for correcting the effect of transducer temperature variations in an ultrasonic flowmeter. The method includes the steps of providing ultrasonic transducers having resonant frequencies that are approximately linear functions of temperature, and applying to those transducers bursts of ultrasonic drive pulses having a frequency that is independent of temperature. The method further includes the steps of calibrating said apparatus at a temperature approximately equal to the nominal temperature if said transducers, and using sample measurements taken at an unknown temperature to define a linear representation of how sample measurements vary during the course of bursts. Finally, the method includes the step of using the linear representation to correct fluid flow values calculated from the sample measurements.

Abstract: An ultrasonic flowmeter for measuring the rate of flow of a fluid by means of bursts of ultrasonic drive pulses that are alternately transmitted and received by first and second ultrasonic transducers. A driver circuit is suitably coupled to the first and second transducers to cause the latter to alternately transmit ultrasonic signals in first and second directions through the fluid to be measured. A receiver circuit is coupled to the first and second transducers to cause the latter to alternately receive ultrasonic signals in first and second directions through the fluid to be measured. First and second driver switching means, preferably including tri-state buffers, allow the same driver circuit to drive both transducers. The driver and receiver circuits are directly coupled to the transducers and share a common ground.