A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.

Provided is a driving control apparatus that can control relaxation of force in an actuator. The driving control apparatus is provided with: a driving control unit configured to control driving of the actuator according to a driving control signal; and a pressure control unit configured to control, according to a pressure control signal, involvement of the driving control signal in control of pressure to be generated by the actuator.

A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.

Provided is a process including: receiving a tank-nearly-full message indicating that a tank at an oil or gas related facility is or will be ready for a truck to unload and transport fluid accumulating in the tank; in response to the tank-nearly-full message, creating a tank-run record; sending a description of the tank-run to a mobile device of a driver of an oilfield truck; receiving, from the mobile device of the driver of the oilfield truck, a tank-run claimed message indicating that the driver will drive to the oil or gas related facility and transport at least some of the fluid accumulating in the tank; and after the tank-run claimed message, performing steps including: confirming that the tank-run has not yet been claimed; after the confirmation, designating the tank-run as claimed by the driver; and sending confirmation to the mobile device of the driver.

A board-level assembly that is useful to expand functions of a valve positioner on a valve assembly. The board-level assembly can incorporate a main circuit board and a peripheral smart circuit board. The main circuit board may be configured to communicate with the smart circuit board, find a storage memory on the second circuit board, retrieve data from the storage memory, and use the data to configure functions on the first circuit board. In one implementation, the smart circuit board can release and engage the main circuit board. This configuration can allow different configurations of the smart circuit board to swap into the board-level assembly, each of the different configurations providing data the main circuit board can exploit to change the functions of the valve positioner.

A method and system for use with actuation system to control a plurality of vanes disposed within a turbine engine, wherein a vane position sensor provides a vane position signal corresponding to a vane position of the plurality of vanes, the actuation system includes a plurality of motors engaged in response to the vane position signal, and a differential gearbox having a plurality of inputs operatively coupled to the plurality of motors and an output operatively coupled to the plurality of vanes, wherein an output speed of the output is a sum of a plurality of input speeds of the plurality of inputs.

A system is provided to automatically monitor and control the operation of a microfluidic device using machine learning technology. The system receives images of a channel of a microfluidic device collected by a camera during operation of the microfluidic device. Upon receiving an image, the system applies a classifier to the image to classify the operation of the microfluidic device as normal, in which no adjustment to the operation is needed, or as abnormal, in which an adjustment to the operation is needed. When an image is classified as normal, the system may make no adjustment to the microfluidic device. If, however, an image is classified as abnormal, the system may output an indication that the operation is abnormal, output an indication of a needed adjustment, or control the microfluidic device to make the needed adjustment.

A method of controlling opening of a valve in an HVAC system is provided. The method includes controlling the opening of a six-way-valve according to a default control mode in dependence of a default sensor signal, the six-way-valve fluidicly coupling an inlet side and an outlet side of the heat exchanger alternatively with a first fluidic circuit in a first default control mode or a second fluidic circuit in a second default control mode; selecting a selected default control mode from the first default control mode and the alternative second default control mode; determining, while controlling the valve in the selected default control mode, whether the sensor signal is faulty; and switching, in case the signal is faulty, to controlling the opening according to a first fallback control mode or an alternative second fallback control mode, where the opening is controlled independently of the faulty sensor signal.

A system for controlling a plurality of actuators is disclosed. The system includes at least one device for operating the plurality of actuators, at least one processor in communication with the device, and a memory coupled the processor. The memory stores data comprising program code that, when executed by the at least one processor, causes the system to receive as input a profile number indicating a specific test being performed by the system and a profile row indicating a load exerted by the plurality of actuators. The system is further caused to select a predetermined gain output based on the profile number and the profile row from a gain array. The gain array is a matrix containing a plurality of gain values, and the predetermined gain output is selected based on the profile number and the profile row. The system is further caused to determine a control value.

The present disclosure is directed towards a method of controlling opening of a valve (10) in an HVAC system (100). The method includes controlling the opening of the valve (10) according to a default control mode in dependence of a default sensor signal. The method further includes determining, while controlling the opening of the valve (10) according to the default control mode, whether the default sensor signal is faulty and switching, in case of the default sensor signal being faulty, to controlling the opening of the valve (10) according to a fallback control mode, with the opening of the valve (10) being controlled independently of the faulty sensor signal in the fallback control mode. The present invention is further directed towards a corresponding control device opening of a valve (10) in an HVAC system as well as a corresponding computer program product.