Abstract: A method includes detecting, by a first data storage device, an error when reading data from the first data storage device. The method further includes correcting a portion of the error, by a controller of a host system, using host-level outer codes; and communicating, by the controller, error correction information to the first data storage device in response to correcting the portion of the error using the host-level outer codes.

Abstract: A method includes receiving, by a data storage device, a read command. The method further includes reading a first set of outer code stored to a magnetic recording medium of the data storage device and storing the first set of outer code to memory. The method further includes receiving a write command to write data to the magnetic recording medium and writing a second set of outer code to the magnetic recording medium in connection with the write command.

Abstract: Described is an earth scraper including multiple buckets to receive earth scraped by a scraper blade. A lifter mechanism is provided to move one of the buckets between elevated and lowered positions.

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: A method includes receiving, by a data storage device, a read command. The method further includes reading a first set of outer code stored to a magnetic recording medium of the data storage device and storing the first set of outer code to memory. The method further includes receiving a write command to write data to the magnetic recording medium and writing a second set of outer code to the magnetic recording medium in connection with the write command.

Abstract: A method includes detecting, by a first data storage device, an error when reading data from the first data storage device. The method further includes correcting a portion of the error, by a controller of a host system, using host-level outer codes; and communicating, by the controller, error correction information to the first data storage device in response to correcting the portion of the error using the host-level outer codes.

Abstract: A data storage system can connect a data storage controller to a host and a data storage device. A first reference state corresponding to a first zone of the data storage device can be incremented in response to a first version of data being assigned to the first zone by the data storage controller. A second version of the data may be written to a second zone of the data storage device prior to populating a recently freed list with the first zone having an incorrect reference state. The first zone can be allocated by the data storage controller for new data without altering the incorrect reference state that is subsequently written to the first zone as directed by the data storage controller.

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 a system, non-transitory computer readable medium, and method for monitoring and replaying packets. A network tap forwards packets from a first network to a second network. At least one node in the first network has the same IP address as a node in the second network. The packets are replayed in the second network.

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: Systems and methods are disclosed for multiple duration deduplication entries. A processor may be configured to perform data deduplication operations, including setting a first indicator for first metadata stored to a hash database identifying a first time interval to maintain the first metadata in the database, and setting a second indicator for second metadata stored to the database identifying a second time interval to maintain the second metadata in the database longer than the first time interval. The processor may remove the first metadata from the database when no duplicative data is detected for the first metadata within the first time interval, and remove the second metadata from the database when no duplicative data is detected for the second metadata within the second time interval.

Abstract: Each disk drive in an array includes a housing that encloses a motor and at least one magnetic disk. The housing also encloses first and second actuators each with respective first and second heads that independently access the magnetic disk. The first actuator is mapped to a first logical unit and the second actuator is mapped to a second logical unit. A host interface of each disk drive facilitates access to the first and second logical units. A system includes a first storage controller attached to all of the first logical units as a first active server and attached to all of the second logical units as a first passive server. A second storage controller operates redundantly with the first storage controller. The second storage controller is attached to all of the second logical units as a second active server and attached to all of the first logical units as a second passive server.

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 data storage erasure system may have a host connected to a plurality of data storage devices via a network controller with each of the plurality of data storage devices and the network controller connected to a pods controller and each of the plurality of the data storage devices having a device controller. A rebuild strategy can be generated with a rebuild module connected to the plurality of data storage devices, the network controller, and the pods controller. The rebuild strategy may be directed to minimize data rebuild times in the event of a failure in the plurality of data storage devices by executing the rebuild strategy in response to a detected or predicted failure in at least one data storage device of the plurality of data storage devices.

Abstract: Use of a deduplication module remote from a storage system for storage of data subject to deduplication by the remote deduplication module. The storage system may generate a hash of target data and send the hash of the target data to the remote deduplication module. The remote deduplication module may access a hash database corresponding to the storage system and apply a deduplication algorithm on the hash. In turn, information regarding a deduplication result may be returned to the storage system which may either store the unique target data or update a mapping between the target data and duplicate existing data in a persistent storage of the storage device. The remote deduplication module may be executed by scalable cloud resources such that the computational resources dedicated to the deduplication module may be scaled.

Abstract: A data storage erasure system may have a host connected to a plurality of data storage devices via a network controller with each of the plurality of data storage devices and the network controller connected to a pods controller and each of the plurality of the data storage devices having a device controller. A rebuild strategy can be generated with a rebuild module connected to the plurality of data storage devices, the network controller, and the pods controller. The rebuild strategy may be directed to minimize data rebuild times in the event of a failure in the plurality of data storage devices by executing the rebuild strategy in response to a detected or predicted failure in at least one data storage device of the plurality of data storage devices.

Abstract: Each disk drive in an array includes a housing that encloses a motor and at least one magnetic disk. The housing also encloses first and second actuators each with respective first and second heads that independently access the magnetic disk. The first actuator is mapped to a first logical unit and the second actuator is mapped to a second logical unit. A host interface of each disk drive facilitates access to the first and second logical units. A system includes a first storage controller attached to all of the first logical units as a first active server and attached to all of the second logical units as a first passive server. A second storage controller operates redundantly with the first storage controller. The second storage controller is attached to all of the second logical units as a second active server and attached to all of the first logical units as a second passive server.