Abstract: Coordinating signal processing among computing devices in a voice-driven computing environment is provided. A first and second digital assistant can detect an input audio signal, perform a signal quality check, and provide indications that the first and second digital assistants are operational to process the input audio signal. A system can select the first digital assistant for further processing. The system can receive, from the first digital assistant, data packets including a command. The system can generate, for a network connected device selected from a plurality of network connected devices, an action data structure based on the data packets, and transmit the action data structure to the selected network connected device.

Abstract: A catheter system which provides adjustability of the length of the guidewire extending distally from the distal tip of the catheter and/or allows the guidewire to be secured relative to the catheter hub to allow the guidewire and the catheter to be steered simultaneously. The catheter system may include a catheter having an elongate shaft defining a catheter lumen, a hub assembly coupled to the proximal end of the elongate shaft and including a hub assembly lumen, a torque assembly releasably coupled to the hub assembly and including a torque assembly lumen, and a guidewire co-axially disposed within the catheter lumen, hub assembly lumen, and torque assembly lumen. In a first configuration the torque assembly may be configured to simultaneously torque the elongate shaft and the guidewire and in a second configuration the torque assembly may be configured to torque the guidewire independent of the elongate shaft.

Abstract: A register management system is coupled to a register. The register management system receives an address and functional data for a write operation to be performed on the register. The functional data includes write bits and mask bits associated with the write bits. One or more mask bits having a first logic state indicate that associated one or more write bits are to be written to the register, respectively. Based on the address, the register management system selects a first half of the register or a second half of the register to perform the write operation. Further, the register management system writes the one or more write bits associated with the one or more mask bits having the first logic state to one or more storage elements of the first half of the register or the second half of the register, respectively.

Abstract: A system and method for evaluating a fragrance product or object provided, wherein the system includes a virtual reality component configured to present a user with a product or object in a virtual reality environment; an optional biometric sensor component configured to obtain the user's biometric data; a wearable scent delivery component configured to deliver a scent to the user; and a digital controller component that synchronizes deliver of the scent with the user's interaction with the product or object in the virtual reality environment.

Abstract: A computer system is used to initiate a process to configure an external accessory for use with at least a first device management application. The computer system displays a prompt that includes an option to initiate a process to configure the external accessory for use with at least a first device management application. While displaying the prompt, the computer system optionally receives a selection and/or an input corresponding to a selection of an option to initiate a process to configure the external accessory for use with at least a first device management application.

Abstract: In various examples, audio alerts of emergency response vehicles may be detected and classified using audio captured by microphones of an autonomous or semi-autonomous machine in order to identify travel directions, locations, and/or types of emergency response vehicles in the environment. For example, a plurality of microphone arrays may be disposed on an autonomous or semi-autonomous machine and used to generate audio signals corresponding to sounds in the environment. These audio signals may be processed to determine a location and/or direction of travel of an emergency response vehicle (e.g., using triangulation). Additionally, to identify siren types—and thus emergency response vehicle types corresponding thereto—the audio signals may be used to generate representations of a frequency spectrum that may be processed using a deep neural network (DNN) that outputs probabilities of alert types being represented by the audio data.

Abstract: Some embodiments are directed to a federated learning system. A federated model is trained on respective local training datasets of respective multiple edge devices. In an iteration, an edge device obtains a current federated model, determines a model update for the current federated model based on the local training dataset, and sends out the model update. The edge device determines the model update by applying the current federated model to a training input to obtain at least a model output for the training input; if the model output does not match a training output corresponding to the training input, include the training input in a subset of filtered training inputs to be used in the iteration; and determining the model update by training the current federated model on only the subset of filtered training inputs.

Abstract: In various examples, audio alerts of emergency response vehicles may be detected and classified using audio captured by microphones of an autonomous or semi-autonomous machine in order to identify travel directions, locations, and/or types of emergency response vehicles in the environment. For example, a plurality of microphone arrays may be disposed on an autonomous or semi-autonomous machine and used to generate audio signals corresponding to sounds in the environment. These audio signals may be processed to determine a location and/or direction of travel of an emergency response vehicle (e.g., using triangulation). Additionally, to identify siren types—and thus emergency response vehicle types corresponding thereto—the audio signals may be used to generate representations of a frequency spectrum that may be processed using a deep neural network (DNN) that outputs probabilities of alert types being represented by the audio data.

Abstract: Approaches for an advanced AI-assisted vehicle can utilize an extensive suite of sensors inside and outside the vehicle, providing information to a computing platform running one or more neural networks. The neural networks can perform functions such as facial recognition, eye tracking, gesture recognition, head position, and gaze tracking to monitor the condition and safety of the driver and passengers. The system also identifies and tracks body pose and signals of people inside and outside the vehicle to understand their intent and actions. The system can track driver gaze to identify objects the driver might not see, such as cross-traffic and approaching cyclists. The system can provide notification of potential hazards, advice, and warnings. The system can also take corrective action, which may include controlling one or more vehicle subsystems, or when necessary, autonomously controlling the entire vehicle. The system can work with vehicle systems for enhanced analytics and recommendations.

Abstract: At least some embodiments are directed to an insights inference system that produces multiple insights associated with an entity. The insights inference system generates a decision tree machine learning model, assigning a first insight to a parent node of a decision tree machine learning model and assigning at least one second insight to child nodes of the decision tree machine learning model. Each child node is associated with a sequence number and a rank number. The sequence number and the rank number are indicative of a significance associated with the at least one second insight. The insight inference system responds to queries by traversing the decision tree machine learning model to compute at least one response insight based on the sequence number and the rank number associated with each child node and outputs the at least one response insight to a client terminal.

Abstract: At least some embodiments are directed to an exemplary computer-based electronic activity tracking system that detects activity patterns receiving data values that represent at least one electronic activity. The exemplary electronic activity tracking system includes a detector of unsecure electronic activities that identifies electronic activity patterns performed by a user or non-person entity. The detector of unsecure electronic activities utilizes unsupervised machine learning techniques to detect the electronic activity patterns. The detected electronic activity patterns correspond to unsecure or malicious electronic activities. The electronic activity tracking system outputs notifications indicative of identified unsecure or malicious activity patterns and identifies entities associated with such unsecure or malicious activity patterns. The exemplary electronic activity tracking system implements a graphical user interface operated from a client computing device.

Abstract: The system may be configured to perform operations including receiving a transaction history for a consumer having transaction information associated with a plurality of transactions; detecting within the transaction information for each transaction a characteristic, resulting in a plurality of characteristics; calculating a respective value associated with each characteristic, wherein the respective value is at least one of a number or percentage of transactions having the characteristic; assigning a respective weight to each characteristic, producing an assigned respective weight for each characteristic; applying the assigned respective weight to the respective value associated with each characteristic to produce a respective weighted value for each characteristic; combining the respective weighted values of the plurality of characteristics; and/or producing a compliance score in response to the combining the respective weight values.

Abstract: Deployment of a software unit into a software application layer stack using deployment parameters including an ordering behavior parameter and a reference parameter. The deployment of the software unit may be in response to receipt of a software package for installation of the software unit. Installation of the software unit may be provided according to a hierarchical rule structure that includes determining whether the software unit comprises an upgrade or a patch to an existing software unit in the layer stack. If not an upgrade or a patch, an ordering behavior parameter may indicate a relative position to install the software unit in relation to a software unit designated by the reference parameter. If the deployment parameters are not valid, installation of the software unit may be provided according to a default rule.

Abstract: A register management system is coupled to a register. The register management system receives an address and functional data for a write operation to be performed on the register. The functional data includes write bits and mask bits associated with the write bits. One or more mask bits having a first logic state indicate that associated one or more write bits are to be written to the register, respectively. Based on the address, the register management system selects a first half of the register or a second half of the register to perform the write operation. Further, the register management system writes the one or more write bits associated with the one or more mask bits having the first logic state to one or more storage elements of the first half of the register or the second half of the register, respectively.

Abstract: A system and method for evaluating a fragrance product or object provided, wherein the system includes a virtual reality component configured to present a user with a product or object in a virtual reality environment; an optional biometric sensor component configured to obtain the user's biometric data; a wearable scent delivery component configured to deliver a scent to the user; and a digital controller component that synchronizes deliver of the scent with the user's interaction with the product or object in the virtual reality environment.

Abstract: A multi-clock domain system includes a synchronizer circuit. The synchronizer circuit includes a sequential logic circuit and a synchronizing stage. The sequential logic circuit receives a functional signal that is generated based on a first clock signal that is further associated with a first clock domain, a second clock signal that is associated with a second clock domain, and a reference signal. Based on the first and second clock signals and the reference signal, the synchronizer circuit outputs a logic signal. When the functional signal is activated, the logic signal is activated and remains activated for a predetermined time duration after the functional signal is deactivated. The synchronizing stage receives the second clock signal and further receives the logic signal from the sequential logic circuit, and outputs a synchronized functional signal.

Abstract: Deployment of a software unit into a software application layer stack using deployment parameters including an ordering behavior parameter and a reference parameter. The deployment of the software unit may be in response to receipt of a software package for installation of the software unit. Installation of the software unit may be provided according to a hierarchical rule structure that includes determining whether the software unit comprises an upgrade or a patch to an existing software unit in the layer stack. If not an upgrade or a patch, an ordering behavior parameter may indicate a relative position to install the software unit in relation to a software unit designated by the reference parameter. If the deployment parameters are not valid, installation of the software unit may be provided according to a default rule.

Abstract: Techniques are disclosed for coordinating interactions between a user device and a plurality of accessory devices. In one example, a user device receives information identifying one or more accessory devices in communication with the user device. The user device may implement accessory interaction instances for each of the identified accessories. A first accessory interaction instance can be associated with a first accessory among the identified accessories and receive a first audio input from the first accessory corresponding to a user request. The first accessory interaction instance can process a portion of the received audio input and receive a first response from a server computer. The user device may then transmit the first response to the first accessory device.

Abstract: Techniques are disclosed for connecting third-party accessories to a cellular-capable device to participate in a telephone call. In one example, a user can voice a request to make a call to an accessory device. The accessory device can transmit the request to a controller device. Upon processing the request, the controller device can identify an appropriate cellular-capable device and instruct the cellular-capable device to place the requested call. The controller device can also instruct the cellular-capable device to establish an audio connection with the accessory device to relay the call audio. In another example, the controller device can listen for a word spoken at the accessory device indicating the end of the call. Upon receiving the end of call word, the controller device can instruct the cellular-capable device to terminate the call. While in the listening state, the controller device may continue processing user requests received at other accessory devices.

Abstract: The Dynamic Asset Sector Simulator Apparatuses, Methods and Systems (“DASS”) transforms market assumptions, constraints, portfolio construction/adjustment requests inputs via DASS components into asset allocation records, portfolio allocation and graphic presentation, seasonal portfolio investment records output. The DASS includes instructions to obtain a user indication of a portfolio simulation request including user configured market assumption parameters and retrieve a user interface template including a portfolio parameter configuration widget. The DASS's seasonal portfolio construction component may obtain economic indicator data from a data provider based on the selected collection and instantiate a regression structure employing an economic indicator. The DASS's seasonal portfolio construction component may then generate a probabilistic output indicating a probability that a current economic cycle phase belongs to the first economic cycle phase upon the instantiation of the regression structure.