Abstract: A method for constructing a general probability model of a harmonic emission level for an industrial load is provided. The method establishes, based on harmonic data monitored by a power quality monitoring system, a general probability model by combining a parametric estimation method based on a normal distribution function and a lognormal distribution function with a nonparametric estimation method represented by a kernel density estimation method, taking a degree of approximation between the general probability model and an actual probability distribution of each harmonic current as an objective function based on parameters required by the general probability model, and optimizing and solving the parameters of the proposed general probability model by using a multiplier method to determine parameters of the general probability model to finally obtain a general probability model applicable to different industrial loads.

Abstract: Apparatuses and methods for evaluating the risk factors of a proposed vehicle maneuver using remote data are disclosed. In embodiments, a computer-assisted/autonomous driving vehicle communicates with one or more remote data sources to obtain remote sensor data, and process such remote sensor data to determine the risk of a proposed vehicle maneuver. A remote data source may be authenticated and validated, such as by correlation with other remote data sources and/or local sensor data. Correlation may include performing object recognition upon the remote data sources and local sensor data. Risk evaluation is performed on the validated data, and the results of the risk evaluation presented to a vehicle operator or to an autonomous vehicle navigation system.

Abstract: Technologies for providing a cognitive capacity test for autonomous driving include a compute device. The compute device includes circuitry that is configured to display content to a user, prompt a message to the user to turn user’s attention to another activity that needs situational awareness, receive a user response, and analyze the user response to determine an accuracy of the user response and a response time, wherein the accuracy and response time are indicative of a cognitive capacity of the user to assume control of an autonomous vehicle when the autonomous vehicle encounters a situation that the vehicle is unable to navigate.

Abstract: Technologies for providing a cognitive capacity test for autonomous driving include a compute device. The compute device includes circuitry that is configured to display content to a user, prompt a message to the user to turn user's attention to another activity that needs situational awareness, receive a user response, and analyze the user response to determine an accuracy of the user response and a response time, wherein the accuracy and response time are indicative of a cognitive capacity of the user to assume control of an autonomous vehicle when the autonomous vehicle encounters a situation that the vehicle is unable to navigate.

Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous vehicle incident management, are disclosed herein. In some embodiments, a vehicle incident management system includes a main system controller to determine whether a vehicle hosting the apparatus is involved in a vehicle incident; if so, whether another vehicle is involved; and if so, whether the other vehicle is equipped to exchange incident information; and an inter-vehicle communication subsystem to exchange incident information with the other vehicle, on determination that the vehicle is involved in a vehicle incident involving the other vehicle, and the other vehicle is equipped to exchange incident information. Other embodiments are also described and claimed.

Abstract: In one embodiment, a computing device includes processing circuitry to predict outcomes of unresolved customer support cases. For example, the processing circuitry: receives a request to predict an outcome of an unresolved customer support case; extracts a set of features from a case record for the unresolved case, including a set of categorical features and a set of textual features; encodes the set of categorical and textual features into numerical representations; predicts the outcome of the unresolved customer support case using a trained case prediction model, wherein the trained case prediction model generates a predicted outcome based on the encoded categorical and textual features; and performs a corresponding customer support action based on the predicted outcome of the unresolved customer support case.

Abstract: Technologies for providing a cognitive capacity test for autonomous driving include a compute device. The compute device includes circuitry that is configured to display content to a user, prompt a message to the user to turn user's attention to another activity that needs situational awareness, receive a user response, and analyze the user response to determine an accuracy of the user response and a response time, wherein the accuracy and response time are indicative of a cognitive capacity of the user to assume control of an autonomous vehicle when the autonomous vehicle encounters a situation that the vehicle is unable to navigate.

Abstract: Methods and apparatus for detecting and/or predicting emergency events based on vehicle occupant behavior data are disclosed. An apparatus includes at least one of a camera and an audio sensor, and further includes an event detector, a notification generator, and a radio transmitter. The camera is to capture image data associated with an occupant inside of a vehicle. The audio sensor is to capture audio data associated with the occupant inside of the vehicle. The event detector is to at least one of predict or detect an emergency event based on the at least one of the image data and the audio data. The notification generator is to generate notification data in response to an output of the event detector. The radio transmitter is to transmit the notification data.

Abstract: Apparatuses and methods for evaluating the risk factors of a proposed vehicle maneuver using remote data are disclosed. In embodiments, a computer-assisted/autonomous driving vehicle communicates with one or more remote data sources to obtain remote sensor data, and process such remote sensor data to determine the risk of a proposed vehicle maneuver. A remote data source may be authenticated and validated, such as by correlation with other remote data sources and/or local sensor data. Correlation may include performing object recognition upon the remote data sources and local sensor data. Risk evaluation is performed on the validated data, and the results of the risk evaluation presented to a vehicle operator or to an autonomous vehicle navigation system.

Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous vehicle incident management, are disclosed herein. In some embodiments, a vehicle incident management system includes a main system controller to determine whether a vehicle hosting the apparatus is involved in a vehicle incident; if so, whether another vehicle is involved; and if so, whether the other vehicle is equipped to exchange incident information; and an inter-vehicle communication subsystem to exchange incident information with the other vehicle, on determination that the vehicle is involved in a vehicle incident involving the other vehicle, and the other vehicle is equipped to exchange incident information. Other embodiments are also described and claimed.