Abstract: A Fit-For-Duty network system and method that integrates several drowsiness detection devices with software analytics engine to more accurately predict, monitor and/or detect an actual unfit-for-duty condition or “positive event” in real time. The system monitors behavior based on changing operational conditions (such as speed of vehicle and pre-defined conditions, such as time of day and geographic conditions) to dynamically estimate both seriousness and probability of a positive event. Moreover, based on estimated seriousness and probability of a positive event the system self-initiates different levels of alerts ranging from light and sound, to connection to a third party intervener (an operations center), to stopping the vehicle.

Abstract: An electric power system protection and control system, including, a plurality of protection controllers, each for executing protection and control of an electric power system by inputting a status quantity of the electric power system and for converting the status quantity into digital data, and a display controller connected to each of the protection controllers via a communication network, for displaying and controlling an operation and status of each of the protection controllers for monitoring. The display controller is provided with a program module sending unit for sending out a program module corresponding to contents for display control in the display controller to one of the protection controllers via the communication network, respectively.

Abstract: A method for teaching movements to a robot (12) is disclosed. The robot (12) includes a fixture (14) for cooperating with a workpiece (16), at least one sensor (18) for sensing a spatial relationship of the robot fixture (14) relative to the workpiece (16), at least one motor (20), and a microprocessor (22) for controlling motion of the robot (12) relative to the workpiece (16).

Abstract: An improvement in an industrial controller having a processor with a memory holding an I/O table used for storing inputs and outputs transmitted between the industrial controller and a controlled process, via multiple I/O devices, uses templates associated with each I/O device to define the partitioning of the I/O table for the data. The templates define data types and ordering of data required for the particular I/O device permitting the space in the I/O table to be efficiently and intuitively allocated. The templates also relate physical addresses in the I/O table to program variables used by the control program.

Abstract: A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model and an independent dynamic model. The static model is a rigorous predictive model that is trained over a wide range of data, whereas the dynamic model is trained over a narrow range of data. The gain K of the static model is utilized to scale the gain k of the dynamic model. The forced dynamic portion of the model referred to as the b.sub.i variables are scaled by the ratio of the gains K and k. The b.sub.i have a direct effect on the gain of a dynamic model. This is facilitated by a coefficient modification block. Thereafter, the difference between the new value input to the static model and the prior steady-state value is utilized as an input to the dynamic model. The predicted dynamic output is then summed with the previous steady-state value to provide a predicted value Y. Additionally, the path that is traversed between steady-state value changes.

Abstract: Received data is applied in units of blocks to an error correcting unit and a data holding unit. If the error correcting unit normally performs error correction, the output from the error correcting unit is stored in a frame buffer. If the error correcting unit does not normally perform error correction, the data in the data holding unit is stored in the frame buffer. In this manner the first error correction processing is performed. Bit data is sequentially read out in units of bits from each block stored in the frame buffer, subjected to the second error correction processing, and returned to the frame buffer. The third error correction processing is further performed for the data sequentially output in units of blocks from the frame buffer.