A robotic vehicle (10) may include a chassis supporting a storage tank in which an aqueous solution is contained, a mobility assembly operably coupled to the chassis to provide mobility for the robotic vehicle about a service area (20), a positioning module (60) configured to provide guidance for the robotic vehicle (10) during transit of the robotic vehicle (10) over the service area (20), a spray assembly (90) and control circuitry (12).

The invention concerns a storage method for storing, on data servers (3, 4), data file (5, 61 to 64) slices (51 to 58) from the execution of a plurality of processes (65 to 68) of one or more applications (83, 85), comprising: distributing the stored data file (5, 61 to 64) slices (51 to 58) over different data servers (3, 4), characterized in that: this distribution is carried out in such a way that the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) are stored on different data servers (3, 4) so as to reduce the subsequent access, to each of all or part of these data servers (3, 4) by too many application (83, 85) processes (65 to 68) simultaneously, and in that: the determination of the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) has been carried out, during a prior phase of executing these application (83, 85) processes (65 to 68), by observing the behavior of these application (83, 85) processes (65 to 68) in order to access these stored data file (5, 61 to 64) slices (51 to 58) over time.

The invention concerns a storage method for storing, on data servers (3, 4), data file (5, 61 to 64) slices (51 to 58) from the execution of a plurality of processes (65 to 68) of one or more applications (83, 85), comprising: distributing the stored data file (5, 61 to 64) slices (51 to 58) over different data servers (3, 4), characterized in that: this distribution is carried out in such a way that the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) are stored on different data servers (3, 4) so as to reduce the subsequent access, to each of all or part of these data servers (3, 4) by too many application (83, 85) processes (65 to 68) simultaneously, and in that: the determination of the data file (5, 61 to 64) slices (51 to 58) likely to be subsequently accessed simultaneously by different application (83, 85) processes (65 to 68) has been carried out, during a prior phase of executing these application (83, 85) processes (65 to 68), by observing the behavior of these application (83, 85) processes (65 to 68) in order to access these stored data file (5, 61 to 64) slices (51 to 58) over time.

Embodiments of the present invention provide a method for powering an electronic device with a battery or other backup power supply when an external power source is removed from the electronic device. The method determines if the ambient temperature of an electronic device is below a threshold and if the ambient temperature is below the threshold adjusting a minimum state of charge of the battery to prolong the life of the battery.

Improved mechanisms for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, atmospheric liquid water content, or precipitable water and other atmospheric-based phenomena, for example presence and intensity of fog, based upon these sensor readings, predicting future precipitation and atmospheric-based phenomena, and estimating effects of the atmospheric-based phenomena on visibility, for example by calculating runway visible range (RVR) estimates and forecasts based on the atmospheric-based phenomena.

Improved mechanisms for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, atmospheric liquid water content, or precipitable water and other atmospheric-based phenomena, for example presence and intensity of fog, based upon these sensor readings, predicting future precipitation and atmospheric-based phenomena, and estimating effects of the atmospheric-based phenomena on visibility, for example by calculating runway visible range (RVR) estimates and forecasts based on the atmospheric-based phenomena.

A computing system includes at least one processor, and a memory communicatively coupled to the at least one processor. The processor is configured to receive at least two successive radar images of precipitation data, generate a motion vector field using the at least two successive radar images, forecast linear prediction imagery of future precipitation using the motion vector field, and generate corrected output imagery corresponding to the forecasted linear prediction imagery of the future precipitation corrected by a first neural network. In addition, the processor is further configured to receive, by a second neural network, the linear prediction imagery, and one of observed imagery and the corrected output imagery, and distinguish, by the second neural network, between the corrected output imagery and the observed imagery to produce conditioned output imagery. The processor is also configured to display the conditioned output imagery on a display.

A computing system includes at least one processor, and a memory communicatively coupled to the at least one processor. The processor is configured to receive at least two successive radar images of precipitation data, generate a motion vector field using the at least two successive radar images, forecast linear prediction imagery of future precipitation using the motion vector field, and generate corrected output imagery corresponding to the forecasted linear prediction imagery of the future precipitation corrected by a first neural network. In addition, the processor is further configured to receive, by a second neural network, the linear prediction imagery, and one of observed imagery and the corrected output imagery, and distinguish, by the second neural network, between the corrected output imagery and the observed imagery to produce conditioned output imagery. The processor is also configured to display the conditioned output imagery on a display.

A system gathers data from a plurality of sources across a wide geographic region, and produces from the gathered information output to a user, which output indicates to the user factors that may influence supply of product to, and/or operation of, a supply chain. Illustrative embodiments are able to determine that data in a previously received dataset has been changed by its corresponding data source, and subsequently update a corresponding data record maintained by the system. Illustrative embodiments train and employ one or more neural networks to identify anomalies in large datasets, and in some embodiments to predict the impact of various factors on crop production.

A system gathers data from a plurality of sources across a wide geographic region, and produces from the gathered information output to a user, which output indicates to the user factors that may influence supply of product to, and/or operation of, a supply chain. Illustrative embodiments are able to determine that data in a previously received dataset has been changed by its corresponding data source, and subsequently update a corresponding data record maintained by the system. Illustrative embodiments train and employ one or more neural networks to identify anomalies in large datasets, and in some embodiments to predict the impact of various factors on crop production.