Abstract: A method for authenticating a user is presented. Responsive to a request for access to a computer resource, a computer system prompts the user making the request to access the computer resource to perform a new motion in an environment in which the user is monitored by a sensor system. Detected biometric data in the new motion performed by the user is identified by the computer system. A determination is made as to whether the user performing the new motion is an authenticated user based on comparing the detected biometric data with stored biometric data for a prior motion performed by the authenticated user. The computer system provides access to the computer resource when the user is identified as the authenticated user.

Abstract: A system and a method of managing a manufacturing process includes receiving production data relating to the manufacturing process and determining an operational mode associated with the manufacturing process using historical, multivariate senor data. The method may further determine a recommended action to affect production based on the determined operational mode. The operational mode may be based on at least one of: a level of operation in a continuous flow process relating to a joint set of process variables, a representation of a joint dynamic of the set of process variables over a predefined length, and a joint configuration of an uptime/downtime of a plurality of units comprising a process flow.

Abstract: Systems, computer-implemented methods, and computer program products to generate virtual motion sensor data from computer animations are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a tracker component that can track virtual location data corresponding to a feature of a computer animated character in a virtual environment. The computer executable components can further comprise a virtual motion sensor component that, based on the virtual location data, can generate virtual motion sensor data.

Abstract: A system includes a virtual reality system configured to enable a user to interact with a virtual environment, a plurality of biofeedback sensors configured to monitor a user, and a computer system including a virtual reality module configured to generate at least a view of the virtual environment, a biofeedback module configured to fuse output of the plurality of biofeedback sensors with a plurality of events within the virtual environment, a training module configured to generate a model of user behavior, wherein the training module executed by the computer system enables the computer system to make a prediction of a user response of the user based on a corpus of biofeedback data, and an alert module configured to generate at least one alert to the user via the virtual reality system based on the user response predicted by the computer system.

Abstract: Whether to train a new neural network model can be determined based on similarity estimates between a sample data set and a plurality of source data sets associated with a plurality of prior-trained neural network models. A cluster among the plurality of prior-trained neural network models can be determined. A set of training data based on the cluster can be determined. The new neural network model can be trained based on the set of training data.

Abstract: Systems, computer-implemented methods, and computer program products to generate virtual motion sensor data from computer animations are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a tracker component that can track virtual location data corresponding to a feature of a computer animated character in a virtual environment. The computer executable components can further comprise a virtual motion sensor component that, based on the virtual location data, can generate virtual motion sensor data.

Abstract: A technique relates to structuring a semiconductor device. First empty cells are placed against hierarchical boundaries of a macro block. Functional cells are added in the macro block. Remaining areas are filled with second empty cells in the macro block. Shape requirements are determined for the first empty cells and the second empty cells. The first and second empty cells are replaced with determined shape requirements.

Abstract: The disclosure is directed to a smart charging cable that enables dynamically and remotely controlled charging of a battery such as may be found in an electric vehicle (EV). The EV charging cable is not specific to any particular manufacturer or brand of electric vehicle thereby facilitating unrestricted application and access to vehicular charging. The EV charging cable includes a processor arranged to execute instructions stored on a memory along with a communication module for wireless communication between the cable and a remote source. A car emulator may be used to simulate the presence of a vehicle to allow switched high power sources like standard installed EV chargers as well as a power meter for measuring the flow electricity passing through the cable. The aforementioned may be housed in a control box arranged between two portions of the cable to receive and deliver power from a source to a battery.

Abstract: A system and method of operating a system for controlling charging of a battery of a user's electric vehicle from a power source is based upon intervening in a controlled manner between the power source and the electric vehicle and dynamically controlling a level for charging of the vehicle's electric energy storage system. The level potentially being different from a maximum available charging power from the power source. The controlled intervention occurs in accordance with a charging schedule determined by the server and transmitted by the server to the charging cable. The charging cable then operates according to the charging schedule resulting in a corresponding controlled charging of the vehicle's electric energy storage system.

Abstract: Systems, computer-implemented methods, and computer program products to generate virtual motion sensor data from computer animations are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a tracker component that can track virtual location data corresponding to a feature of a computer animated character in a virtual environment. The computer executable components can further comprise a virtual motion sensor component that, based on the virtual location data, can generate virtual motion sensor data.

Abstract: Techniques facilitating using a blockchain system that integrates the trustworthiness of the blockchain concept with open scientific research by generating a blockchain of the experiments formed, data collected, analyses performed, and results achieved are provided herein. In an example, the blockchain system can form a blockchain representing a research project, wherein the blockchain comprises a first block of research data and a second block of analysis data representing a log of an analysis performed on the research data. Summary blocks and correction blocks can also be added to the blockchain representing the post analysis of the research results. One or more of the subsequent blocks can be linked to the preceding blocks using information in block headers that can also serve to determine whether modifications to the blocks have been performed.

Abstract: A computer-implemented method for data labeling is provided. The computer-implemented method assigns pseudo-labels to unlabeled examples of data using a similarity metric on an embedding space to produce pseudo-labeled examples. A curriculum learning model is trained using the pseudo-labeled examples. The curriculum learning model trained with the pseudo-labeled examples is employed in in a fine-tuning task to enhance classification accuracy of the data.

Abstract: Techniques for assessing the proficiency of artificial intelligence agents and users in a given knowledge domain are described. A plurality of proficiency agents can be initialized with a plurality of proficiency scores, by performing a plurality of assessments between pairs of proficiency agents selected from the plurality of proficiency agents. A first client device associated with a first user is matched with a first proficiency agent of the plurality of proficiency agents, based on a first proficiency score associated with the first user and a second proficiency score of the plurality of proficiency scores corresponding to the first proficiency agent. Assessments results of an assessment performed between the first client device and the first proficiency agent are received, and a rating system update function is used to update the first proficiency score and the second proficiency score, based on the assessment results.