Abstract: Systems and methods for automated path-based recommendation for risk mitigation are provided. An entity assessment server, responsive to a request for a recommendation for modifying a current risk assessment score of an entity to a target risk assessment score, accesses an input attribute vector for the entity and clusters of entities defined by historical attribute vectors. The entity assessment server assigns the input attribute vector to a particular cluster and determines a requirement on movement from a first point to a second point in a multi-dimensional space based on the statistics computed from the particular cluster. The first point corresponds to the current risk assessment score and the second point corresponds to the target risk assessment score. The entity assessment server computes an attribute-change vector so that a path defined by the attribute-change vector complies with the requirement and generates the recommendation from the attribute-change vector.

Abstract: A system of object detection for a trailer. In one example, the system includes a camera configured to capture images of the trailer, where the images include an object other than the trailer. The system also includes a sensor configured to capture sensor data, a display configured to display images from the perspective of the camera, and a controller on the vehicle. The controller includes an electronic processor configured to receive the image data from the camera, receive the sensor data from the sensor, determine a blind spot, analyze the sensor data for radar data associated with the object, calculate the position of the object relative to the blind spot and the trailer, determine that the object is within the blind spot using an object detection algorithm, and in response to the determining that the object is within the blind spot, generate an augmented image.

Abstract: The present invention provides compositions comprising peptide-coupled biodegradable poly(lactide-co-glycolide) (PLG) particles. In particular, PLG particles are surface-functionalized to allow for coupling of peptide molecules to the surface of the particles (e.g., for use in eliciting induction of immunological tolerance).

Abstract: In some aspects, a computing system can generate and optimize a machine learning model to estimate an unobservable capacity of a target system or entity. The computing system can access training vectors which include training predictor variables, training performance indicators, and task quantities. A training performance indicator indicating performance outcome corresponding to the predictor variables and a task quantity associated with a task assigned to the target entity that leads to the training performance indicator. The machine learning model can be trained by performing adjustments of parameters of the machine learning model to minimize a loss function defined based on the training vectors. The trained machine learning model can be used to estimate the capacity of the target system or entity for handling tasks and be used in assigning tasks to the target entity according to the determined capacity.

Abstract: Various aspects involve explainable machine learning based on time-series transformation. For instance, a computing system accesses time-series data of a predictor variable associated with a target entity. The computing system generates a first set of transformed time-series data instances by applying a first family of transformations on the time-series data. Any non-negative linear combination of the first family of transformations forms an interpretable transformation of the time-series data. The computing system determines a risk indicator for the target entity indicating a level of risk associated with the target entity by inputting the first set of transformed time-series data instances into a machine learning model. The computing system transmits, to a remote computing device, a responsive message including the risk indicator. The risk indicator is usable for controlling access to one or more interactive computing environments by the target entity.

Abstract: The present invention provides compositions comprising peptide-coupled biodegradable poly(lactide-co-glycolide) (PLG) particles. In particular, PLG particles are surface-functionalized to allow for coupling of peptide molecules to the surface of the particles (e.g., for use in eliciting induction of immunological tolerance).

Abstract: Provided herein are fluorescent dyes possessing abroad range of silyl modifications, which can be used, for example, for enabling brighter dyes, red-shifting of fluorescence, and as handles, e.g., for the introduction of sensors and/or targeting groups, including no-wash fluorogenic labeling agents for nuclear DNA, SnapTag® proteins, and HaloTag® proteins. The fluorescent dyes have the following structure: or a tautomer thereof, or a salt of the foregoing, wherein values for the variables (e.g., X, Z1, Z2, R3, R6, R7, R11) are as described herein.

Abstract: A system and method for operating a rotatable knob module with adjustable tactile feedback. The rotatable knob module includes a knob configured to continuously rotate about a center axis and an electronic processor. The electronic processor is configured to determine a current trailer angle, define a virtual center position of the knob based on the current trailer angle, and adjust a rotational torque of the knob when the knob is rotated from a first rotational position to a second rotational position based on a relative virtual rotational distance of the second rotational position from the virtual center position.

Abstract: Techniques are described herein for applying natural language processing (NLP) techniques to time series data to derive attributes of an object for use with a machine-learning model. In one example, a system can receive a time series associated with an object over a time window, where the time series includes a set of discrete values. The system can then generate a time series encoding based on the time series. The system can provide the time series encoding as input to a trained natural language processing (NLP) model, which can generate one or more output embeddings based on the time series encoding. Next, the system can determine at least one attribute associated with the object based on the one or more output embeddings. The system can then provide the attributes for use with a machine-learning model, which may for example be configured to predict a future characteristic of the object.

Abstract: Systems and methods for automated path-based recommendation for risk mitigation are provided. An entity assessment server, responsive to a request for a recommendation for modifying a current risk assessment score of an entity to a target risk assessment score, accesses an input attribute vector for the entity and clusters of entities defined by historical attribute vectors. The entity assessment server assigns the input attribute vector to a particular cluster and determines a requirement on movement from a first point to a second point in a multi-dimensional space based on the statistics computed from the particular cluster. The first point corresponds to the current risk assessment score and the second point corresponds to the target risk assessment score. The entity assessment server computes an attribute-change vector so that a path defined by the attribute-change vector complies with the requirement and generates the recommendation from the attribute-change vector.

Abstract: A trailer tow assist system including a camera that captures a rearward image of the trailer and its surroundings, a human machine interface that displays the rearward image, an input device that receives user input, and an electronic processor. The electronic processor receives the rearward image, identifies a target-space within the surroundings, determines a vehicle orientation relative to the target-space, determines a trailer angle relative to the vehicle, determines a trailer trajectory within the surroundings, and displays the trailer trajectory and rearward image on the human machine interface. The electronic processor also controls, in response to the user input, the vehicle to follow the trailer trajectory along a centerline of the trailer trajectory.

Abstract: Systems and computer-implemented methods for displaying a user interface for contactless in-person transaction via sound are provided herein. The system includes a sender device configured to generate and transmit sound signals that encode a package associated with a transaction request through speakers of the sender device. The system also includes a receiver device having a graphical user interface configured to display one or more graphical elements to guide a user to align the receiver device in a physical orientation that aligns a microphone of the receiver device with a speaker of a sender device, and a wave progressing in a direction that aligns with the speaker's broadcast direction of the sound signals.

Abstract: Systems and computer-implemented methods for generating and transmitting transaction requests are provided herein. The system includes a sender device that generates an audio signal encoding a package associated with the transaction request, and a receiver device that receives the audio signal and decodes the audio signal with an application to access the transaction request.

Abstract: Embodiments relate to a computer-implemented method for generating a cryptographic key for a user. A user signal associated with the user is input to a machine learning model. The machine learning model has multiple layers and the applied input generates outputs at each of these layers. A vector is extracted from one or more outputs of one or more layers of the machine learning model. A cryptographic key is generated from the vector. The same cryptographic key is generated for different vectors produced by different variations of the user signal from the same user, but different cryptographic keys are generated for user signals from different users. The cryptographic key may be used for various purposes, including authenticating the user, encrypting/decrypting data, and controlling access to resources.

Abstract: Embodiments relate to a computer-implemented method for generating a cryptographic key for a user. A user signal associated with the user is input to a machine learning model. The machine learning model has multiple layers and the applied input generates outputs at each of these layers. A vector is extracted from one or more outputs of one or more layers of the machine learning model. A cryptographic key is generated from the vector. The same cryptographic key is generated for different vectors produced by different variations of the user signal from the same user, but different cryptographic keys are generated for user signals from different users. The cryptographic key may be used for various purposes, including authenticating the user, encrypting/decrypting data, and controlling access to resources.

Abstract: The present invention provides compositions comprising peptide-coupled biodegradable poly(lactide-co-glycolide) (PLG) particles. In particular, PLG particles are surface-functionalized to allow for coupling of peptide molecules to the surface of the particles (e.g., for use in eliciting induction of immunological tolerance).

Abstract: A universal junction box includes an upper body having a first connecting feature. A lower body releasably connects to the upper body having a second connecting feature configured to mate with the first connecting feature. The upper body and lower body forming a housing to receive an electrical connection. A first mounting feature is configured to selectively secure the housing to an associated frame or to an unassociated frame or other support structure.

Abstract: Systems and methods for automated path-based recommendation for risk mitigation are provided. An entity assessment server, responsive to a request for a recommendation for modifying a current risk assessment score of an entity to a target nsk assessment score, accesses an input attribute vector for the entity and clusters of entities defined by historical attribute vectors. The entity assessment server assigns the input attribute vector to a particular cluster and determines a requirement on movement from a first point to a second point in a multi-dimensional space based on the statistics computed from the particular cluster. The first point corresponds to the current risk assessment score and the second point corresponds to the target risk assessment score. The entity assessment server computes an attribute-change vector so that a path defined by the attribute-change vector complies with the requirement and generates the recommendation from the attribute-change vector.

Abstract: A mobile application for integrating a location sharing event with a messaging platform such as a text messaging or email platform allows users to be prompted about location sharing when at least a part of the message includes location or time information. In one embodiment, the mobile application takes the form of an integrated location sharing application that parses the message to discern the relevant location or time information. The application may also provide a notification of a future event and may optionally generate a location sharing event based on the notification. In another embodiment, the application permits interactive route sharing between at least two computing devices.

Abstract: A host computing system determines a wavelet transform that represents time-series values of predictor data samples. The host computing system applies the wavelet transform to the predictor data samples to generate wavelet predictor variable data comprising a first set and a second set of shift value input data for a first scale and a second scale. The host computing system computes a set of probabilities for a target event by applying a set of timing-prediction models to the first set and the second set of shift value input data. The host computing system determines an event prediction from the set of probabilities and modifies a host system operation based on the determined event prediction.