Abstract: A sealable connection system is provided. The system can include a connection assembly including a housing and at least one ferrule positioned within the housing. An inner surface of the housing can be arranged to mate with and secure to an outer surface of a sensor assembly. The at least one ferrule can be arranged to engage with the sensor assembly as the housing is secured to the sensor assembly. The system can also include a fiber optic cable assembly. The fiber optic cable assembly can include a fiber optic cable extending through the housing and the at least one ferrule. The fiber optic cable can also be surrounded, at least along a length of the fiber optic cable within the connection assembly, by a fiber optic cable cover. The sealable connection system is provided to hermetically connect the fiber optic cable assembly to a sensor assembly.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for determining a categorization for each tracking tool that executes on a particular webpage based on a variety of criteria, such as the purpose of the tracking tool and its source script. The system may compare the characteristics of tracking tools on a webpage to a database of known tracking tools to determine the appropriate categorization. When a user visits the webpage, the system analyzes these categories and determines whether the tracking tool should be permitted to run based on the categories and/or other criteria, such as whether the user has consented to the use of that type of tracking tool.

Abstract: In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for mapping the existence of target data within computing systems in a manner that does not expose the target data to potential data-related incidents. In accordance with various aspects, a method is provided that comprises: receiving a source dataset that comprises a label assigned to a data element used by a data source in handling target data that identifies a type of target data and data samples gathered for the data element; determining, based on the label, that the data samples are to be anonymized; generating supplemental anonymizing data samples associated with the label that comprise fictitious occurrences of the type of the target data; generating a review dataset comprising the supplemental anonymizing data samples intermingled with the data samples; and sending the review dataset to a review computing system.

Abstract: An electronic device with a touch-sensitive display, one or more processors, and memory detects a first user input. In response to detecting the first user input, the device displays on the touch-sensitive display a user interface screen including a first affordance and a second affordance. The device detects a second user input including a contact on the touch-sensitive display. In accordance with a determination that the contact corresponds to selection of the first affordance, the electronic device is caused to turn off. In accordance with a determination that the contact corresponds to selection of the second affordance, the device causes initiation of a telephone call to a determined number.

Abstract: In particular embodiments, a sensitive data management system is configured to remove sensitive data after a period of non-use. Credentials used to access remote systems and/or third-party systems are stored with metadata that is updated with each use of the credentials. After a period of non-use, determined based on credential metadata, the credentials are deleted. Personal data retrieved to process a consumer request is stored with metadata that is updated with each use of the personal data. After a period of non-use, determined based on personal data metadata, the personal data is deleted. The personal data is also deleted if the system determines that the process or system that caused the personal data to be retrieved is no longer in use. An encrypted version of personal data may be stored for later use in verifying proper consumer request fulfillment.

Abstract: A method of operating an exoskeleton system that includes obtaining a first set of sensor data from one or more sensors associated with one or more leg actuator units of an exoskeleton system during a user activity, the first set of sensor data indicating a first configuration state of the one or more actuator units; determining, based at least in part on the first set of obtained sensor data, to change configuration of the one or more leg actuator units to a second configuration state to support a user during the user activity; and introducing fluid to one or more fluidic actuators of the one or more leg actuator units to generate the second configuration state by causing the one or more fluidic actuators to apply force at the one or more actuator units.

Abstract: Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for identifying data processing activities associated with various data assets based on data discovery results. In accordance various aspects, a method is provided comprising: identifying and scanning data assets to detect a subset of the data assets, wherein each asset of the subset is associated with a particular data element used for target data; generating a prediction for each pair of data assets of the subset on the target data flowing between the pair; identifying a data flow for the target data based on the prediction generated for each pair; and identifying a data processing activity associated with handling the target data based on a correlation identified for the particular data element, the subset, and/or the data flow with a known data element, subset, and/or data flow for the data processing activity.

Abstract: A method includes determining an operational condition associated with an unmanned aerial vehicle (UAV). The method includes, responsive to determining the operational condition, causing the UAV to perform a pre-flight check. The pre-flight check includes hovering the UAV above a takeoff location. The pre-flight check includes, while hovering the UAV, moving one or more controllable components of the UAV in accordance with a predetermined sequence of movements. The pre-flight check includes obtaining, by one or more sensors of the UAV, sensor data indicative of a flight response of the UAV to moving the one or more controllable components while hovering the UAV. The pre-flight check includes comparing the sensor data to expected sensor data associated with an expected flight response to the predetermined sequence of movements while hovering the UAV. The pre-flight check includes, based on comparing the sensor data to the expected sensor data, evaluating performance of the UAV.

Abstract: A method of developing a charging profile for charging a lithium-ion battery. A first phase of charging is at a constant current level, with the constant current level selected on the basis of battery resistance during charging and differential voltage (dV/dQ) analysis. A switch point is selected on the basis of a state of charge (SOC) of the battery when dV/DQ values increase. Next is an increasing voltage charging phase, with the voltage rate selected on the basis of charge acceptance and charge time.

Abstract: Various embodiments provide methods, apparatus, systems, computing devices, computing entities, and/or the like for identifying targeted data for a data subject across a plurality of data objects in a data source. In accordance with one embodiment, a method is provided comprising: receiving a request to identify targeted data for a data subject; identifying a first data object using metadata for a data source that identifies the first data object as associated with a first targeted data type for a data portion from the request; identifying a first data field from a graph data structure of the first data object that identifies the first data field as used for storing data having the first targeted data type; and querying the first data object based on the first data field and the data for the first targeted data type to identify a first targeted data portion for the data subject.

Abstract: An amplifier module includes a module substrate with a mounting surface, a signal conducting layer, a ground layer, and a ground terminal pad at the mounting surface. A thermal dissipation structure extends through the module substrate. A ground contact of a power transistor die is coupled to a surface of the thermal dissipation structure. Encapsulant material covers the mounting surface of the module substrate and the power transistor die, and a surface of the encapsulant material defines a contact surface of the amplifier module. A ground terminal is embedded within the encapsulant material. The ground terminal has a proximal end coupled to the ground terminal pad, and a distal end exposed at the contact surface. The ground terminal is electrically coupled to the ground contact of the power transistor die through the ground terminal pad, the ground layer of the module substrate, and the thermal dissipation structure.

Abstract: A device assembly includes a functional substrate having one or more electronic components formed there. The functional substrate has a cavity extending from a first surface toward a second surface of the functional substrate at a location that lacks the electronic components. The device assembly further includes a semiconductor die placed within the cavity with a pad surface of the semiconductor die being opposite to a bottom of the cavity. The functional substrate may be formed utilizing a first fabrication technology and the semiconductor die may be formed utilizing a second fabrication technology that differs from the first fabrication technology.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for managing implementation of machine-learning models within computing environments according to system requirements frameworks via common data objects. The disclosed system generates a common data object to represent an implementation of a machine-learning model with a data process. For example, the disclosed system determines attribute values of the common data object according to data objects representing the machine-learning model and related datasets. Furthermore, the disclosed system utilizes the common data object to validate the machine-learning model according to a digital representation of a system requirements framework that includes usage requirements for machine-learning models to store, process, transmit, or otherwise handle specific data types in specific ways for the one or more data processes within a computing environment.

Abstract: A device assembly includes a functional substrate having one or more electronic components formed there. The functional substrate has a cavity extending from a first surface toward a second surface of the functional substrate at a location that lacks the electronic components. The device assembly further includes a semiconductor die placed within the cavity with a pad surface of the semiconductor die being opposite to a bottom of the cavity. The functional substrate may be formed utilizing a first fabrication technology and the semiconductor die may be formed utilizing a second fabrication technology that differs from the first fabrication technology.

Abstract: An RF amplifier includes at least one harmonic trap filter with an array of shunt filter legs having a non-uniform resonance frequency distribution. The harmonic trap filter is configured to suppress frequencies in a suppression frequency range that includes harmonic frequencies of carrier frequencies in a range of carrier frequencies. Each of the shunt filter legs includes a capacitor and inductor coupled in series, and an intermediate node coupled between the capacitor and the inductor. Each intermediate node of the shunt filter leg is coupled to at least one other intermediate node of another shunt filter leg of the filter with a dampening resistor. Shunt filters at or near edges of the array are configured to have lower resonance frequencies than those at or near the center of the array to suppress excess current flow at edges of the RF amplifier.

Abstract: Various embodiments provide methods, apparatus, systems, computing devices, computing entities, and/or the like for identifying targeted data for a data subject across a plurality of data objects in a data source. In accordance with one embodiment, a method is provided comprising: receiving a request to identify targeted data for a data subject; identifying a first data object using metadata for a data source that identifies the first data object as associated with a first targeted data type for a data portion from the request; identifying a first data field from a graph data structure of the first data object that identifies the first data field as used for storing data having the first targeted data type; and querying the first data object based on the first data field and the data for the first targeted data type to identify a first targeted data portion for the data subject.

Abstract: System and methods are disclosed for redacting analyzing unstructured data in a request for data associated with a data subject to determine whether the unstructured data is relevant to the request. The relevancy of pieces of the unstructured data may be determined by determining a categorization for each such piece of unstructured data and comparing them to known personal data associated with the data subject having the same categorization. Pieces of the unstructured data that do not match known personal data having the same categorization are redacted from the request before the request is processed.

Abstract: In general, various aspects provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for performing data discovery on a target computing system. In various aspects, a third party computing connects, via a public data network, to an edge node of the target computing system and instructs the target computing system to execute jobs to discover target data stored in data repositories in a private data network in the target computing system. In some aspects, the third party computing system may schedule the jobs on the target computing system based on computing resource availability on the target computing system.

Abstract: Embodiments of RF amplifiers and packaged RF amplifier devices each include an amplification path with a transistor die, and an output-side impedance matching circuit having a T-match circuit topology. The output-side impedance matching circuit includes a first inductive element (e.g., first wirebonds) connected between the transistor output terminal and a quasi RF cold point node, a second inductive element (e.g., second wirebonds) connected between the quasi RF cold point node and an output of the amplification path, and a first capacitance connected between the quasi RF cold point node and a ground reference node. The RF amplifiers and devices also include a baseband termination circuit connected to the quasi RF cold point node, which includes an envelope resistor, an envelope inductor, and an envelope capacitor coupled in series between the quasi RF cold point node and the ground reference node.

Abstract: Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for identifying data processing activities associated with various data assets based on data discovery results. In accordance various aspects, a method is provided comprising: identifying and scanning data assets to detect a subset of the data assets, wherein each asset of the subset is associated with a particular data element used for target data; generating a prediction for each pair of data assets of the subset on the target data flowing between the pair; identifying a data flow for the target data based on the prediction generated for each pair; and identifying a data processing activity associated with handling the target data based on a correlation identified for the particular data element, the subset, and/or the data flow with a known data element, subset, and/or data flow for the data processing activity.