Abstract: A firearm heater system for warming a scope of a firearm. The firearm heater system comprising an upper portion, a lower portion, a pocket portion and an edge portion. The upper portion is attached to the pocket portion. The lower portion is attached to the pocket portion. The edge portion is attached to the pocket portion. The edge portion comprise one or more dial apertures. The one or more dial apertures configured to allow access to portions of the scope. The pocket portion comprise a pocket. The pocket is configured to receive a portion of a hand warmer. The firearm heater system configured to wrap around a portion of the scope and hold a portion of the hand warmer against the scope.

Abstract: A firearm heater system for warming a scope of a firearm. The firearm heater system comprising an upper portion, a lower portion, a pocket portion and an edge portion. The upper portion is attached to the pocket portion. The lower portion is attached to the pocket portion. The edge portion is attached to the pocket portion. The edge portion comprise one or more dial apertures. The one or more dial apertures configured to allow access to portions of the scope. The pocket portion comprise a pocket. The pocket is configured to receive a portion of a hand warmer. The firearm heater system configured to wrap around a portion of the scope and hold a portion of the hand warmer against the scope.

Abstract: A system, method, and apparatus for detecting drones are disclosed. An example method includes receiving a digital sound sample and partitioning the digital sound sample into segments. The method also includes applying a frequency and power spectral density transformation to each of the segments to produce respective sample vectors. For each of the sample vectors, the example method determines a combination of drone sound signatures and background sound signatures that most closely match the sample vector. The method further includes determining, for the sample vectors, if the drone sound signatures in relation to the background sound signatures that are included within the respective combinations are indicative of a drone. Conditioned on determining that the drone sound signatures are indicative of a drone, an alert message indicative of the drone is transmitted.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for detecting drones are disclosed. An example method includes receiving a digital sound sample and partitioning the digital sound sample into segments. The method also includes applying a frequency and power spectral density transformation to each of the segments to produce respective sample vectors. For each of the sample vectors, the example method determines a combination of drone sound signatures and background sound signatures that most closely match the sample vector. The method further includes determining, for the sample vectors, if the drone sound signatures in relation to the background sound signatures that are included within the respective combinations are indicative of a drone. Conditioned on determining that the drone sound signatures are indicative of a drone, an alert message indicative of the drone is transmitted.

Abstract: Methods are provided for detecting a wireless coexistence scenario in which two peer devices in communication with each other are both operating a coexistence management mechanism. The detection of this wireless coexistence scenario may be used to provide a trigger to change the coexistence management mechanism so as to prevent interference.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: A system, method, and apparatus for drone detection and classification are disclosed. An example method includes receiving a sound signal in a microphone and recording, via a sound card, a digital sound sample of the sound signal, the digital sound sample having a predetermined duration. The method also includes processing, via a processor, the digital sound sample into a feature frequency spectrum. The method further includes applying, via the processor, broad spectrum matching to compare the feature frequency spectrum to at least one drone sound signature stored in a database, the at least one drone sound signature corresponding to a flight characteristic of a drone model. The method moreover includes, conditioned on matching the feature frequency spectrum to one of the drone sound signatures, transmitting, via the processor, an alert.

Abstract: Thermal management of display systems including LCD systems is provided. The LCD systems may utilize LEDs as a light source. The LEDs may be supported on a heat pipe. The heat pipe facilitates conduction and dissipation of heat generated by the LEDs which may otherwise damage components of the display system.

Abstract: Thermal management of optical systems including illumination systems is provided. The optical systems may utilize LEDs as a light source. The LEDs may be supported on a heat pipe. The heat pipe facilitates conduction and dissipation of heat generated by the LEDs which may otherwise damage components of the optical system.

Abstract: A golf putter, which is weighted with a positionable weight by means of which the center of gravity of the putter can be changed to accommodate the requirements of the user. This result is achieved by a weight, which can be slidably positioned along a pair of rods, which run between the faceplate and the back plate of the putter. The plate can be positioned slidably along the rods either against the faceplate or back plate or at any position there between. When the weight has been placed in the desired position, it can be locked in this position by screws, which fit through the weight and abut against the rods.

Abstract: A lift wheel assembly for attachment to a farm implement to selectively position the implement between a working condition in which the tools of the implement engage with and work soil in a field, and a transport condition in which the tools are elevated above the soil surface permitting the farm implement to be repositioned. The lift wheel assembly is attachable to a toolbar of the implement by a bracket. It includes a lift beam that has a ground wheel at one end and is pivotally attached to the bracket by a pivot arm at a second end. An actuator operates to pivotally displace the lift beam and ground wheel to selectably position the ground wheel aft of the implement's center in a transport state and forward of the center of gravity in a working state.

Abstract: A switch/power conditioning module may be added to a hybrid vehicle to selectively supply power from an AC power bus to a load, providing on-vehicle standby power generating capability with a minimum of added hardware and/or when the vehicle is stationary.