Abstract: A system for determining adverse effects associated with a substance includes a side-effect recognizer, a relationship extractor, a processor, and a reporting system. The side-effect recognizer utilizes a first recurrent neural network (RNN) to identify a first portion of received data associated with an adverse effect to thereby determine the adverse effect associated with the received data. The relationship extractor utilizes a second RNN to identify a second portion of the received data associated with a substance and a third portion of the received data that indicates a relationship between the substance and the adverse effect to thereby determine the substance associated with the received data and the relationship between the substance and the adverse effect. The processor is in communication with the adverse effect recognizer and the substance relationship extractor and aggregates and relates the adverse effect, substance, and relationship.

Abstract: A platform may obtain, for a first set of entities involved in a money laundering investigation, target entity information for a target entity and related entity information for a set of related entities. The platform may analyze the target entity information and the related entity information to identify money laundering candidates. The platform may determine one or more relationships indicating a degree of similarity between the target entity and the one or more related entities. The platform may generate a graph data structure that associates the target entity and the one or more related entities using the one or more relationships. The platform may determine a score for the target entity and one or more scores for the one or more related entities. The platform may provide a recommendation indicating whether the target entity and/or the one or more related entities are likely to be engaging in money laundering.

Abstract: A device may receive multimedia data, metadata, and/or policy data. The device may process the policy data using a first set of techniques to determine a first set of embeddings for the policy data. The device may process the multimedia data or the metadata using a second set of techniques to determine a second set of embeddings for the multimedia data or the metadata. The device may process the first set of embeddings and the second set of embeddings using a knowledge graph to determine whether the multimedia content or the access by the user violates the policy. The device may perform an action based on a result of processing the first set of embeddings and the second set of embeddings. The action may relate to the multimedia content or the access to the multimedia content by the user.

Abstract: A device may receive, from one or more other devices, one or more images that depict one or more events occurring at a location. The device may detect an event of the one or more events depicted in the one or more images. The device may determine a first score that indicates a first likelihood that the event is an anomalous event. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the one or more other devices. The device may determine a third score based on the first score and the second score. The third score may indicate a second likelihood that the event is the anomalous event. The device may perform an action based on the third score.

Abstract: A device may receive a plurality of data objects from a plurality of sources; identify text data, image data, and location data of the plurality of data objects; identify relevant data objects, of the plurality of data objects, based on the text data, and/or based on the image data, based on the location data, and/or based on comparing the text data, the image data, and the location data to a predefined element that identifies values relevant to a particular group or subject area; assign scores to the relevant data objects based on the text data, the image data, and the location data; aggregate the scores, as one or more aggregated scores, with regard to one or more users associated with the relevant data objects; and/or perform one or more actions based on the one or more aggregated scores associated with the one or more users.

Abstract: A device may receive information associated with a user that is to be classified. The information may be associated with multiple data formats. The device may identify a set of entities based on the information associated with the user that is to be classified. The device may generate a first graph data structure based on the set of entities. The device may determine a similarity score associated with the first graph data structure and a second graph data structure. The second graph data structure may be associated with a set of classified users. The device may provide information that identifies the similarity score to permit and/or cause an action to be performed.

Abstract: A device may receive a plurality of data objects from a plurality of sources; identify text data, image data, and location data of the plurality of data objects; identify relevant data objects, of the plurality of data objects, based on the text data, and/or based on the image data, based on the location data, and/or based on comparing the text data, the image data, and the location data to a predefined element that identifies values relevant to a particular group or subject area; assign scores to the relevant data objects based on the text data, the image data, and the location data; aggregate the scores, as one or more aggregated scores, with regard to one or more users associated with the relevant data objects; and/or perform one or more actions based on the one or more aggregated scores associated with the one or more users.

Abstract: A device may receive data associated with an event. The device may identify a context of the event based on receiving the data. The device may identify a similar event based on performing a comparison of the context of the event and a context of the similar event. The device may determine a set of pre-events associated with the event based on identifying a pre-event that occurred before the similar event. The set of pre-events may include at least one pre-event similar to the pre-event that occurred before the similar event. The device may determine a set of post-events associated with the event based on determining the set of pre-events and identifying a post-event that occurred after the similar event. The set of post-events may include at least one post-event similar to the post-event. The device may perform an action based on the set of post-events.

Abstract: A Coriolis-based bulk acoustic wave gyroscope includes a center-supported resonating element with capacitively-coupled drive, sense, and control electrodes. The resonating element has a first substantially solid or perforated region which is connected to the center-support by a second region characterized by a plurality of spokes or beams. When operating in a resonance state, the first region undergoes a bulk acoustic mode of vibration while the second region undergoes a flexural mode of vibration. Energy losses associated with the flexural mode of vibration reduce the overall quality factor (Q) at high resonance frequencies creating a large bandwidth and a fast response time without needing vacuum.

Abstract: A device may receive, from another device, an image that depicts one or more events occurring at a location. The device may detect an event of the one or more events depicted in the image. The device may determine a first score that indicates a likelihood that the event is an anomalous event. The first score may be based on first data received from the other device. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the other device. The second data may comprise data from a sensor, a wearable device, a mobile device, and/or a handheld device. The device may perform an action based on the first score or the second score.

Abstract: A device may receive, from one or more other devices, one or more images that depict one or more events occurring at a location. The device may detect an event of the one or more events depicted in the one or more images. The device may determine a first score that indicates a first likelihood that the event is an anomalous event. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the one or more other devices. The device may determine a third score based on the first score and the second score. The third score may indicate a second likelihood that the event is the anomalous event. The device may perform an action based on the third score.

Abstract: A device may receive, from another device, an image that depicts one or more events occurring at a location. The device may detect an event of the one or more events depicted in the image. The device may determine a first score that indicates a likelihood that the event is an anomalous event. The first score may be based on first data received from the other device. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the other device. The second data may comprise data from a sensor, a wearable device, a mobile device, and/or a handheld device. The device may perform an action based on the first score or the second score.

Abstract: Disclosed are methods and a sensor architecture that utilizes the residual quadrature error in a gyroscope to achieve and maintain perfect mode-matching, i.e., ˜0 Hz split between the drive and sense mode frequencies, and to electronically control sensor bandwidth. In a reduced-to-practice embodiment, a 6 mW, 3V CMOS ASIC and control algorithm are interfaced to a mode-matched MEMS tuning fork gyroscope to implement an angular rate sensor with bias drift as low as 0.15°/hr and angle random walk of 0.003°/?hr, which is the lowest recorded to date for a silicon MEMS gyroscope. The system bandwidth can be configured between 0.1 Hz and 1 kHz.

Abstract: A Coriolis-based bulk acoustic wave gyroscope includes a center-supported resonating element with capacitively-coupled drive, sense, and control electrodes. The resonating element has a first substantially solid or perforated region which is connected to the center-support by a second region characterized by a plurality of spokes or beams. When operating in a resonance state, the first region undergoes a bulk acoustic mode of vibration while the second region undergoes a flexural mode of vibration. Energy losses associated with the flexural mode of vibration reduce the overall quality factor (Q) at high resonance frequencies creating a large bandwidth and a fast response time without needing vacuum.

Abstract: Disclosed are methods and a sensor architecture that utilizes the residual quadrature error in a gyroscope to achieve and maintain perfect mode-matching, i.e., ˜0 Hz split between the drive and sense mode frequencies, and to electronically control sensor bandwidth. In a reduced-to-practice embodiment, a 6 mW, 3V CMOS ASIC and control algorithm are interfaced to a mode-matched MEMS tuning fork gyroscope to implement an angular rate sensor with bias drift as low as 0.15°/hr and angle random walk of 0.003°/?hr, which is the lowest recorded to date for a silicon MEMS gyroscope. The system bandwidth can be configured between 0.1 Hz and 1 kHz.

Abstract: Disclosed are methods and a sensor architecture that utilizes the residual quadrature error in a gyroscope to achieve and maintain perfect mode-matching, i.e., ˜0 Hz split between the drive and sense mode frequencies, and to electronically control sensor bandwidth. In a reduced-to-practice embodiment, a 6 mW, 3V CMOS ASIC and control algorithm are interfaced to a mode-matched MEMS tuning fork gyroscope to implement an angular rate sensor with bias drift as low as 0.15°/hr and angle random walk of 0.003°/?hr, which is the lowest recorded to date for a silicon MEMS gyroscope. The system bandwidth can be configured between 0.1 Hz and 1 kHz.

Abstract: Disclosed are methods and a sensor architecture that utilizes the residual quadrature error in a gyroscope to achieve and maintain perfect mode-matching, i.e., ˜0 Hz split between the drive and sense mode frequencies, and to electronically control sensor bandwidth. In a reduced-to-practice embodiment, a 6 mW, 3V CMOS ASIC and control algorithm are interfaced to a mode-matched MEMS tuning fork gyroscope to implement an angular rate sensor with bias drift as low as 0.15°/hr and angle random walk of 0.003°/?hr, which is the lowest recorded to date for a silicon MEMS gyroscope. The system bandwidth can be configured between 0.1 Hz and 1 kHz.

Abstract: Disclosed are resonant vibratory gyroscopes and fabrication methods relating thereto. The angular motion sensor comprises a resonating star gyroscope which comprises a vibratory solid or shell-type structure for rate sensing or measuring angle of rotation. The structure formed as a merged superposition of two square entities, yields in-plane degenerate flexural modes that are used to sense rotation around the axis perpendicular to the substrate. The resonating star gyroscope may be implemented using the primary flexural degenerate modes. Such an implementation has been successfully demonstrated by the authors using trench-refilled polysilicon and epitaxial polysilicon as the structural material. It is also possible to use a solid star-shaped resonator (with or without perforations) for the gyroscope. The authors also suggest the operation of the resonating star gyroscope employing the higher-order flexural modes.

Abstract: A microstructure comprising an in-plane solid-mass electrically conductive tuning fork gyroscope and fabrication methods. The gyroscope is formed using substrate material having lower and upper layers sandwiching a sacrificial insulating layer. An exemplary gyroscope comprises a low-resistivity single-crystal silicon substrate having a lower support layer and an upper flexible support layer. Two opposed proof masses that are separated from the lower support layer lie in and are supported by the upper flexible support layer. Two drive electrodes are disposed adjacent to the proof masses and are insulatably supported by the lower support layer and are separated from the upper flexible support layer. Sense, balance and tuning electrodes are disposed adjacent to the proof masses and are insulatably supported by the lower support layer and are separated from the upper flexible support layer.