The invention relates to a firearm analysis device for determining parameters which are indicative for a firearm from a shot which has been discharged from the weapon, as well as a corresponding method, a corresponding firearm and a computer program product. The device comprises a voltage generating unit which generates an alternating voltage (Ue) during a counter-recoil travel and/or recoil travel of a movable weapon part occurring during a firing. The device is characterized by a signal processing unit which generates a measurement signal (IN.sub.+) from the generated AC voltage (Ue), a signal evaluation unit which determines a first time point and a second time point during the counter-recoil travel and/or recoil travel of the movable weapon part, and a time determination unit which determines a time period duration between the first time point and the second time point.

The invention relates to a firearm analysis device for determining parameters which are indicative for a firearm from a shot which has been discharged from the weapon, as well as a corresponding method, a corresponding firearm and a computer program product. The device comprises a voltage generating unit which generates an alternating voltage (Ue) during a counter-recoil travel and/or recoil travel of a movable weapon part occurring during a firing. The device is characterized by a signal processing unit which generates a measurement signal (IN.sub.+) from the generated AC voltage (Ue), a signal evaluation unit which determines a first time point and a second time point during the counter-recoil travel and/or recoil travel of the movable weapon part, and a time determination unit which determines a time period duration between the first time point and the second time point.

The present disclosure relates to a system for detecting characteristics of a moving element. The system may include a tubular housing having a tubular first portion having a first end and a second end, with the first end forming an input port and the second end forming an output port. A source of wireless electromagnetic energy projects a wireless electromagnetic energy signal, travelling in a first direction, into the input port and through an interior area defined by the tubular first portion. A signal processing subsystem detects at least one characteristic of the signal after the signal is reflected back to the first end after having interacted with the element as the element moves past the output port of the housing.

A method of determining an uncertainty estimate of an estimated velocity of an object includes, determining the uncertainty with respect to a first estimated coefficient and a second estimated coefficient of the velocity profile equation of the object. The first estimated coefficient being assigned to a first spatial dimension of the estimated velocity and the second estimated coefficient being assigned to a second spatial dimension of the estimated velocity. The velocity profile equation represents the estimated velocity in dependence of the first estimated coefficient and the second estimated coefficient. The method also includes determining the uncertainty with respect to an angular velocity of the object, a first coordinate of the object in the second spatial dimension, and a second coordinate of the object in the first spatial dimension.

A method, system, and apparatus for determining the location of a tool traveling down a wellbore by measuring a first borehole magnetic anomaly with respect to time at two known locations on a tool, comparing the time difference between the two measurements, then calculating the velocity of the tool based on the comparison, then further calculating the distance traveled by the tool in the wellbore based on the velocity calculation, then executing a series of commands at a predetermined location in the wellbore.

A method, system, and apparatus for determining the location of a tool traveling down a wellbore by measuring a first borehole magnetic anomaly with respect to time at two known locations on a tool, comparing the time difference between the two measurements, then calculating the velocity of the tool based on the comparison, then further calculating the distance traveled by the tool in the wellbore based on the velocity calculation, then executing a series of commands at a predetermined location in the wellbore.

A compound bow includes a riser, an upper limb, and a lower limb, the upper limb and lower limbs coupled to the riser. The compound bow may include a draw sensor. The compound bow includes a performance module coupled to the riser, the performance module operatively coupled to the draw sensor. A compound bow may include an arrow chronometer assembly. A method may include determining draw weight or length based on measurements of the draw sensor. A method may include determining arrow speed based on measurements of the arrow chronometer assembly.

A method, system, and apparatus for determining the location of a tool traveling down a wellbore by measuring a first borehole magnetic anomaly with respect to time at two known locations on a tool, comparing the time difference between the two measurements, then calculating the velocity of the tool based on the comparison, then further calculating the distance traveled by the tool in the wellbore based on the velocity calculation, then executing a series of commands at a predetermined location in the wellbore.

A method, system, and apparatus for determining the location of a tool traveling down a wellbore by measuring a first borehole magnetic anomaly with respect to time at two known locations on a tool, comparing the time difference between the two measurements, then calculating the velocity of the tool based on the comparison, then further calculating the distance traveled by the tool in the wellbore based on the velocity calculation, then executing a series of commands at a predetermined location in the wellbore.

A method of location determination with a WiFi transceiver and an AI model includes jointly training, based on various losses: a feature extractor, a location classifier, and a domain classifier. The domain classifier may include a first domain classifier and a second domain classifier. The losses used for training tend to cause feature data from the feature extractor to cluster even if a physical object in an environment has moved after training is completed. Then, the location classifier is able to accurately estimate the position of, for example, a person in a room, even if a door or window has changed from open to close or close to open between the time of training and the time of estimating the person's position.