Abstract: Systems and methods are disclosed for using a hub to automate recovery.

Abstract: Aspects of the disclosure relate to computing platforms that utilize improved natural language processing techniques for claims processing. A computing platform may receive an audio file and determine one or more utterance segments based on the audio file. The computing platform may generate and send one or more audio chunks based on the one or more utterance segments to an audio transcription system. The computing platform may receive one or more text segments in response and may generate an audio transcription file accordingly. The computing platform may assign a category to each word in the audio transcription file, and may send user interface information to a user device along with one or more commands directing the user device to generate a user interface based on the user interface information, which may cause the user device to display the user interface.

Abstract: A turn detection system is configured to determine headings or a course of a vehicle over a period of time and evaluate whether the vehicle has registered a turn based on these headings/course. In some arrangements, upon detecting a turn, sensor data may be collected to determine one or more characteristics or attributes of the turn. Such data may indicate a loss event associated with the turn and be used to calculate a probability or risk of loss given the various characteristics of the turn. These probabilities may further be applied to determine various costs and premiums.

Abstract: A microwave oven container may include a body for containing a liquid, an agitator projecting through a bottom wall of the body to agitate the liquid contained in the body, where the agitator includes a first end located in the body and a second end located exterior to the body. The second end of the agitator is able to couple with a turntable drive of a microwave oven to power movement of the agitator in response to rotation of the turntable drive. The container may also include a cage located within the body that substantially surrounds the first end of the agitator and includes a plurality of openings to allow liquid contained in the body to pass through the cage.

Abstract: Embodiments may monitor utilization of a machine. A risk relationship data store may contain electronic records that represent a plurality of risk relationships with an enterprise. A device located proximate to the machine includes a plurality of sensors, each sensor configured to monitor at least one parameter (e.g., acceleration, speed, mileage, run-time and location sensors, etc.). A back-end application computer server may calculate an operator behavior score and a machine operation score based on sensor signals. The computer server may also determine a machine characteristics score and an amount of utilization associated with the machine. A risk relationship identifier associated with the machine is identified, and the computer server may automatically and dynamically update a resource amount associated with the risk relationship identifier based on the operator behavior score, the machine operation score, the machine characteristics score, and the amount of utilization associated with the machine.

Abstract: Embodiments may monitor utilization of a machine. A risk relationship data store may contain electronic records that represent a plurality of risk relationships with an enterprise. A device located proximate to the machine includes a plurality of sensors, each sensor configured to monitor at least one parameter (e.g., acceleration, speed, mileage, run-time and location sensors, etc.). A back-end application computer server may calculate an operator behavior score and a machine operation score based on sensor signals. The computer server may also determine a machine characteristics score and an amount of utilization associated with the machine. A risk relationship identifier associated with the machine is identified, and the computer server may automatically and dynamically update a resource amount associated with the risk relationship identifier based on the operator behavior score, the machine operation score, the machine characteristics score, and the amount of utilization associated with the machine.

Abstract: Aspects of the disclosure relate to computing platforms that utilize improved natural language processing techniques for claims processing. A computing platform may receive an audio file and determine one or more utterance segments based on the audio file. The computing platform may generate and send one or more audio chunks based on the one or more utterance segments to an audio transcription system. The computing platform may receive one or more text segments in response and may generate an audio transcription file accordingly. The computing platform may assign a category to each word in the audio transcription file, and may send user interface information to a user device along with one or more commands directing the user device to generate a user interface based on the user interface information, which may cause the user device to display the user interface.

Abstract: A system, includes at least one processor and memory storing instructions that, when executed by the at least one processor, cause the system to perform operations. The operations include receiving, from a sensor associated with an object, sensor data; determining, based on the sensor data, a damage model indicating a severity of one or more damage elements; determining, based on the sensor data, scene data identifying a geographic location; and generating, by at least one machine classifier, event interpretation data for each of the one or more damage elements, wherein the event interpretation data is based on the sensor data, the damage model, and the scene data.

Abstract: Embodiments may monitor utilization of a machine. A risk relationship data store may contain electronic records that represent a plurality of risk relationships with an enterprise. A device located proximate to the machine includes a plurality of sensors, each sensor configured to monitor at least one parameter (e.g., acceleration, speed, mileage, run-time and location sensors, etc.). A back-end application computer server may calculate an operator behavior score and a machine operation score based on sensor signals. The computer server may also determine a machine characteristics score and an amount of utilization associated with the machine. A risk relationship identifier associated with the machine is identified, and the computer server may automatically and dynamically update a resource amount associated with the risk relationship identifier based on the operator behavior score, the machine operation score, the machine characteristics score, and the amount of utilization associated with the machine.

Abstract: Systems, methods, and computer-readable media, are disclosed in which a variety of data describing the condition of an object can be obtained and probabilistic likelihoods of causes and/or value of damages to the object can be calculated. In a variety of embodiments, data obtained from third-party systems can be utilized in these calculations. Any of a number of machine classifiers can be utilized to generate the probabilistic likelihoods and confidence metrics in the calculated liabilities. A variety of user interfaces for efficiently obtaining and visualizing the object, the surrounding geographic conditions, and/or the probabilistic likelihoods can further be utilized as appropriate to the requirements of specific applications of embodiments of the invention.

Abstract: An turn detection system is configured to determine headings or a course of a vehicle over a period of time and evaluate whether the vehicle has registered a turn based on these headings/course. In some arrangements, upon detecting a turn, sensor data may be collected to determine one or more characteristics or attributes of the turn. Such data may indicate a loss event associated with the turn and be used to calculate a probability or risk of loss given the various characteristics of the turn. These probabilities may further be applied to determine various costs and premiums.

Abstract: An turn detection system is configured to determine headings or a course of a vehicle over a period of time and evaluate whether the vehicle has registered a turn based on these headings/course. In some arrangements, upon detecting a turn, sensor data may be collected to determine one or more characteristics or attributes of the turn. Such data may indicate a loss event associated with the turn and be used to calculate a probability or risk of loss given the various characteristics of the turn. These probabilities may further be applied to determine various costs and premiums.

Abstract: Systems and methods are disclosed for using a hub to automate recovery.

Abstract: Systems and methods for utilizing statistical relational learning techniques in order to predict factors for nodes of a node graph, such as a node graph that represents attacks and incidents to a computing system, are described. In some embodiments, the systems and methods identify certain nodes (of a node graph) as representing malicious attributes of an email or other threat artifact received by a computing system or network and utilize relational learning to predict the maliciousness of attributes represented by other nodes (of the node graph).

Abstract: Systems and methods are disclosed for detecting vehicular accidents based on sensor data, such as data from a mobile device in a vehicle or data from the vehicle's sensors. If an accident is detected, the system may determine whether to collect sensor data from additional sources, such as additional vehicle sensors or additional mobile devices (e.g., a pedestrian's mobile device or a mobile device within a vehicle). The system may also determine whether to collect data from traffic devices or from contextual data sources. The data may be used by the system to determine which party is at fault in the accident. The data may also be used to generate a visualization of the accident.

Abstract: Systems and methods are disclosed for using a hub to automate recovery after a critical event during shared mobility services. One method may include, receiving, by a computing device and from a user device, a notification of a critical event during a shared mobility service; receiving natural language input associated with a first aspect of the critical event; parsing the natural language input and identifying a first value corresponding to the first aspect; determining, based on the first value, a second aspect (e.g., severity of damage) of the critical event; requesting the user device to send images of the second aspect; after receiving the images, determining a second value corresponding to the second aspect; generating, by the computing device and via a user interface of the user device, a representation of the critical event; receiving, from the user device, an approval of the representation; and generating a damage assessment.

Abstract: The present invention relates to an extruded bar soap composition. It more particularly relates to a soap bar composition which exhibits better bloom (perfume impact) and better deposition of actives as compared to conventional soap bars. This is obtained by ensuring that the amount of oleate soap is kept low while incorporating some amount of ricinoleate soap.

Abstract: The present invention relates to an extruded bar soap composition. It more particularly relates to a soap bar composition which exhibits better bloom (perfume impact) and better deposition of actives as compared to conventional soap bars. This is obtained by ensuring that the amount of oleate soap is kept low while incorporating some amount of ricinoleate soap.

Abstract: Systems and methods are disclosed for detecting vehicular accidents based on sensor data, such as data from a mobile device in a vehicle or data from the vehicle's sensors. If an accident is detected, the system may determine whether to collect sensor data from additional sources, such as additional vehicle sensors or additional mobile devices (e.g., a pedestrian's mobile device or a mobile device within a vehicle). The system may also determine whether to collect data from traffic devices or from contextual data sources. The data may be used by the system to determine which party is at fault in the accident. The data may also be used to generate a visualization of the accident.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze movement data and determine driving trips based on the received data. The driving trips may be used along with the movement data to authenticate drivers based on a determined driver profile.