Abstract: This disclosure provides a downhole debris removal apparatus, a method for operating a downhole debris removal apparatus, and a well system including the same. The downhole debris removal apparatus, in one aspect, includes an inner pipe positioned within a tubular, and a filtration member substantially encircling the inner pipe. The downhole debris removal apparatus, in this aspect, further includes a cleaning assembly positioned radially about at least a portion of the filtration member, the cleaning assembly configured to move relative to the filtration member to dislodge particulate matter from the filtration member.

Abstract: This disclosure provides a downhole debris removal apparatus, a method for operating a downhole debris removal apparatus, and a well system including the same. The downhole debris removal apparatus, in one aspect, includes an inner pipe positioned within a tubular, and a filtration member substantially encircling the inner pipe. The downhole debris removal apparatus, in this aspect, further includes a cleaning assembly positioned radially about at least a portion of the filtration member, the cleaning assembly configured to move relative to the filtration member to dislodge particulate matter from the filtration member.

Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.

Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.

Abstract: Methods, systems, and devices for providing matching security between data stores are described. In a database system, an operational data store may store transactional datasets and an analytical data store may store analytics datasets generated based on the transactional datasets. For these analytics datasets to efficiently inherit the security configurations of the transactional datasets, security information may be embedded in datasets retrieved from the operational data store during a data acquisition procedure. This security information may be converted into an embedded multiple-value field for storage in the analytical data store. The analytical data store may receive a query for data in a dataset, and may determine security descriptors associated with the user sending the query. The analytical data store may then filter the data based on comparing these determined security descriptors with the security information in the multiple-value field, and may transmit a query response with the filtered data.

Abstract: A brake control unit includes a processor, a first high side driver and a second high side driver. The processor sends signals to the first high side driver and the second high side driver. The first and second high side drivers process the signals independent of each other. The processor diagnoses faults and locations of faults based on feedback from the high side drivers. The first high side driver controls the braking of a first trailer brake. The second high side driver controls the braking of a second trailer brake.

Abstract: A method comprising: providing a unique identification code corresponding to a single tree; acquiring aerial image data, the aerial image data comprising image data of the tree; extracting the image data of the tree; and providing the image data of the tree to a client associated with the unique identification code.

Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.

Abstract: Disclosed herein are systems and methods for controlling electronic devices based on detected brain activity. For example, a system includes a wearable over-the-ear electronic device has a set of dry EEG sensors, a camera, a processor, and programming instructions. The programming instructions cause the processor to receive images from the camera, process the images to identify features corresponding to a known device, and receive brain-wave signals from the EEG sensors. The system compares the brain-wave signals to measure a level of brain activity. Upon detection of both (a) a feature corresponding to the known device and (b) a level of brain activity that deviates from a baseline by at least a threshold level, the system generates a command signal configured to cause the known device to actuate and transmits the command signal to a controller for the known device.

Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.

Abstract: A towed vehicle controller combines a trailer brake controller and lighting driver. The towed vehicle controller can include a trailer battery charging circuit. The towed vehicle controller operates towed vehicle braking, towed vehicle lighting and towed vehicle battery charge functions.

Abstract: Disclosed herein are systems and methods for methods of developing a database of controllable objects in an environment. For example, a method includes a mobile device having a camera to capture images of objects in an environment. For each object, the method includes, in response to receiving a user selection of the object, training a machine-learning model to recognize the object. The method includes receiving a command associated with the object and receiving a plurality of images of the object and training the machine-learning model to recognize the object based on the plurality of images. The method further includes transmitting the trained model and the command to a wearable electronic device causing the wearable electronic device to save the trained machine-learning model to a data store and to associate the command with the trained machine-learning model.

Abstract: Disclosed herein are systems and methods for controlling electronic devices based on detected brain activity. For example, a system includes a wearable over-the-ear electronic device has a set of dry EEG sensors, a camera, a processor, and programming instructions. The programming instructions cause the processor to receive images from the camera, process the images to identify features corresponding to a known device, and receive brain-wave signals from the EEG sensors. The system compares the brain-wave signals to measure a level of brain activity. Upon detection of both (a) a feature corresponding to the known device and (b) a level of brain activity that deviates from a baseline by at least a threshold level, the system generates a command signal configured to cause the known device to actuate and transmits the command signal to a controller for the known device.

Abstract: This disclosure provides a downhole debris removal apparatus, a method for operating a downhole debris removal apparatus, and a well system including the same. The downhole debris removal apparatus, in one aspect, includes an inner pipe positioned within a tubular, and a filtration member substantially encircling the inner pipe. The downhole debris removal apparatus, in this aspect, further includes a cleaning assembly positioned radially about at least a portion of the filtration member, the cleaning assembly configured to move relative to the filtration member to dislodge particulate matter from the filtration member.

Abstract: Methods, systems, and devices for providing matching security between data stores are described. In a database system, an operational data store may store transactional datasets and an analytical data store may store analytics datasets generated based on the transactional datasets. For these analytics datasets to efficiently inherit the security configurations of the transactional datasets, security information may be embedded in datasets retrieved from the operational data store during a data acquisition procedure. This security information may be converted into an embedded multiple-value field for storage in the analytical data store. The analytical data store may receive a query for data in a dataset, and may determine security descriptors associated with the user sending the query. The analytical data store may then filter the data based on comparing these determined security descriptors with the security information in the multiple-value field, and may transmit a query response with the filtered data.

Abstract: A brake control unit includes a processor, a first high side driver and a second high side driver. The processor sends signals to the first high side driver and the second high side driver. The first and second high side drivers process the signals independent of each other. The processor diagnoses faults and locations of faults based on feedback from the high side drivers. The first high side driver controls the braking of a first trailer brake. The second high side driver controls the braking of a second trailer brake.

Abstract: A brake control unit includes a processor, a first high side driver and a second high side driver. The processor sends signals to the first high side driver and the second high side driver. The first and second high side drivers process the signals independent of each other. The processor diagnoses faults and locations of faults based on feedback from the high side drivers. The first high side driver controls the braking of a first trailer brake. The second high side driver controls the braking of a second trailer brake.

Abstract: Methods, systems, and devices for providing matching security between data stores are described. In a database system, an operational data store may store transactional datasets and an analytical data store may store analytics datasets generated based on the transactional datasets. For these analytics datasets to efficiently inherit the security configurations of the transactional datasets, security information may be embedded in datasets retrieved from the operational data store during a data acquisition procedure. This security information may be converted into an embedded multiple-value field for storage in the analytical data store. The analytical data store may receive a query for data in a dataset, and may determine security descriptors associated with the user sending the query. The analytical data store may then filter the data based on comparing these determined security descriptors with the security information in the multiple-value field, and may transmit a query response with the filtered data.

Abstract: A brake control unit includes a processor, a first high side driver and a second high side driver. The processor sends signals to the first high side driver and the second high side driver. The first and second high side drivers process the signals independent of each other. The processor diagnoses faults and locations of faults based on feedback from the high side drivers. The first high side driver controls the braking of a first trailer brake. The second high side driver controls the braking of a second trailer brake.

Abstract: A method for data processing is described. The method may include configuring a connection template that defines a data extraction flow for a first data source and transmitting from an analytics application server a controller application programming interface (API) call based on a query request for data stored at the first data source. The method may further include instantiating a connector microservice based on the controller API call and the connection template, where the connector microservice is configured with a first data connector with the analytics application server and a second data connector with the first data source that is specific to the first data source. The method may further include retrieving at the analytics application server the data from the first data source based on the connector microservice.