The present disclosure relates to user authentication using a contactless payment instrument. The contactless payment instrument includes a contactless chip and a gesture control module. The user makes one or more gestures at an access device during a card-present transaction scenario and the gestures are validated and the authentication status is determined by matching the gesture made by the user at the time of the transaction with one or more predefined gestures. If the authentication is successful, the payment instrument transmits the payment information required for conducting the transaction.

A video is provided to viewers using a web-based platform without restricted audio, such as a copyrighted soundtrack. To do so, a video comprising at least two audio layers is received. The audio layers can include separate and distinct audio layers or a mix of audio from separate sources. A restricted audio element is identified in a first audio layer and a speech element is identified in a second audio layer. A stitched text string can be generated by performing speech-to-text on both audio layers and removing the text corresponding to the restricted audio element of the second audio layer. When playing back the video, a portion of the video is muted based on the restricted audio element. A voice synthesizer is employed to generate audible sound during the muted portion using the stitched text string.

Illustrative embodiments of the present disclosure relate to a method, a wearable device, an electronic device, and a computer program product for monitoring a user. The method includes verifying an identity of the user by analyzing user data related to the user and obtained by a wearable device, the user data including at least a first image of a part of the user's body. The method further includes monitoring a relative position of the wearable device with respect to the user based on sensor data obtained by the wearable device if the verification on the identity of the user succeeds; monitoring a surrounding environment of the user based on a second image of the surrounding environment obtained by the wearable device; and monitoring behaviors of the user based at least in part on the monitored relative position and the monitored surrounding environment.

The disclosed embodiments relate to a system that compactly stores time-series sensor signals. During operation, the system receives original time-series signals comprising sequences of observations obtained from sensors in a monitored system. Next, the system formulizes the original time-series sensor signals to produce a set of equations, which can be used to generate synthetic time-series signals having the same correlation structure and the same stochastic properties as the original time-series signals. Finally, the system stores the formulized time-series sensor signals in place of the original time-series sensor signals.

Systems and methods for identifying golf equipment. The system may include one or more performance tracking devices, such as an optical sensor system or a radar sensor system for tracking at least one of a golf club swing or a golf ball flight. The system also may include at least one processor and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations. The operations include receiving current dynamic input for a golf shot from a golfer and current static input for the golfer. The operations also include executing a trained machine-learning model based on the received current dynamic input and current static input to generate predicted golf club properties and/or predicted golf ball properties for the golfer. The predicted golf club properties and/or predicted golf ball properties are displayed on a connected display.

The present invention provides methods and systems using optogenetic assays to identify features in measured neuronal activity that can be used to characterize neural disorders and potential therapeutic treatments.

Systems and methods for implementing dynamic graph analysis (DGA) to detect anomalous network traffic are provided. The method includes processing communications and profile data associated with multiple devices to determine dynamic graphs. The method includes generating features to model temporal behaviors of network traffic generated by the multiple devices based on the dynamic graphs. The method also includes formulating a list of prediction results for sources of the anomalous network traffic from the multiple devices based on the temporal behaviors.

Various embodiments of the present invention provide systems and method for identifying three-dimensional zone areas for use in relation to the monitoring of physical movement of a target monitor device.

Methods, devices and computer program products for data analysis are provided. For example, a method comprises: in response to receiving target data from a target sensor at a first time, determining one or more reference sensors based on location information of a neighbor sensor adjacent to the target sensor and a second time of receiving the latest data from the neighbor sensor; determining reference estimation data of the one or more reference sensors at the first time based on historical sensor data obtained from the one or more reference sensors; determining target estimation data of the target sensor at the first time based on the reference estimation data; and detecting abnormity of the target data based on the target data and the target estimation data. In this way, abnormity of the sensor data may be detected efficiently and accurately.

Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.