A method and apparatus may include receiving a signal from a motor. The signal is received while the motor is operating. The method also includes performing a pre-processing of the signal. The method also includes inputting the signal to a 1D convolutional neural network. The method also includes detecting a fault of the motor based on the output of the neural network.

An approach is provided for testing an Internet of Things device. First data captured on video and indicating visual device output and second data indicating non-visual device output are received during testing of the device. An event log of the device is received. Human interactions with the device are received. The first and second data, the event log entries, and indications of the human interactions are overlaid onto frames of the video that include the device, so that timings of the frames are correlated with timestamps of the overlaid items. Based on the overlaid items, performance, functionality, and usability issues are detected and markers of the issues are generated and overlaid onto a timeline of the video. Responsive to a user selection of one of the markers, the computer locating and displaying a frame of the video that depicts the issue that corresponds to the selected marker.

An approach is provided for testing an Internet of Things device. First data captured on video and indicating visual device output and second data indicating non-visual device output are received during testing of the device. An event log of the device is received. Human interactions with the device are received. The first and second data, the event log entries, and indications of the human interactions are overlaid onto frames of the video that include the device, so that timings of the frames are correlated with timestamps of the overlaid items. Based on the overlaid items, performance, functionality, and usability issues are detected and markers of the issues are generated and overlaid onto a timeline of the video. Responsive to a user selection of one of the markers, the computer locating and displaying a frame of the video that depicts the issue that corresponds to the selected marker.

In some examples, an integrated circuit comprises: a TDI input, a TDO output, a TCK input and a TMS input; a TAP state machine (TSM) having an input coupled to the TCK input, an input coupled to the TMS input, an instruction register control output, a TSM data register control (DRC) output, and a TSM state output; an instruction register having an input coupled to the TDI input, an output coupled to the TDO output, and a control input coupled to the instruction register control output of the TAP state machine; router circuitry including a TSM DRC input coupled to the TSM DRC output, a control DRC input coupled to the TSM state output, and a router DRC output; and a data register having an input coupled to the TDI input, an output coupled to the TDO output, and a data register DRC input coupled to the router DRC output.

In some examples, an integrated circuit comprises: a TDI input, a TDO output, a TCK input and a TMS input; a TAP state machine (TSM) having an input coupled to the TCK input, an input coupled to the TMS input, an instruction register control output, a TSM data register control (DRC) output, and a TSM state output; an instruction register having an input coupled to the TDI input, an output coupled to the TDO output, and a control input coupled to the instruction register control output of the TAP state machine; router circuitry including a TSM DRC input coupled to the TSM DRC output, a control DRC input coupled to the TSM state output, and a router DRC output; and a data register having an input coupled to the TDI input, an output coupled to the TDO output, and a data register DRC input coupled to the router DRC output.

An integrated vehicle health management (IVHM) system to resolve equipment-fault related anomalies detected by cyber intrusion detection system (IDS). A benefit of the present system is that it can result in fewer alerts that need manual analysis. A combination of cyber and monitoring with integrated vehicle health management (IVHM) may be a high value differentiator. As a solution gets more mature through a learning loop, it may be customized for different customers in a cost-effective manner, something that might be expensive to develop on their own for most original equipment manufacturers (OEMs). An IVHM symptom pattern recognition matrix may link a pattern of reported symptoms to known equipment failures. This matrix may be initialized from the vehicle design data but its entries may get updated by a learning loop that improves a correlation by incorporating results of investigations.

The present disclosure provides, in an aspect, computer-implemented method for generating data associated with a vehicle event, the method including obtaining vehicle event data for a vehicle event associated with a vehicle; identifying a parameter associated with the vehicle event; emulating the parameter based on simulating the vehicle event with the vehicle event data and a model of the parameter, and extrapolating parameter data based on the simulated vehicle event.

Disclosed are hardware and techniques for testing computer processes in a network system by simulating computer process faults and identifying risk associated with correcting the simulated fault and identifying computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a risk matrix having a risk score and non-functional requirement score. An analysis of the risk score and non-functional requirement score accounts for interdependencies between computer processes and identified corrective actions that may be used to determine an optimal network environment. The optimal network environment may be updated dynamically based on changing computer process interdependencies and the determined risk and robustness scores.

Disclosed herein are vector index registers for storing or loading indexes of true and/or false results of conditional operations using multiple lane processing in vector processors. Each of the vector index registers store multiple addresses for accessing multiple positions in operand vectors in various types of operations that can leverage multi-lane processing.

Disclosed herein are vector index registers for storing or loading indexes of true and/or false results of conditional operations using multiple lane processing in vector processors. Each of the vector index registers store multiple addresses for accessing multiple positions in operand vectors in various types of operations that can leverage multi-lane processing.