Abstract: A method for non-destructively determining a mechanical property of a solid rocket motor propellant grain may comprise applying a force to a surface of the solid rocket motor propellant grain, wherein a deformation is formed on the surface of the solid rocket motor propellant grain in response to the applying, and calculating a value of the mechanical property of the solid rocket motor propellant grain based on the deformation. This process may be performed over time to determine a lifespan of the propellant grain.

Abstract: A method for non-destructively determining a mechanical property of a solid rocket motor propellant grain may comprise applying, via a gas, a force to a surface of the solid rocket motor propellant grain, wherein a deformation is formed on the surface of the solid rocket motor propellant grain in response to the applying, and measuring a pressure of the gas. This process may be performed over time to determine a lifespan of the propellant grain.

Abstract: A method for non-destructively determining a mechanical property of a solid rocket motor propellant grain may comprise applying a force to a surface of the solid rocket motor propellant grain, wherein a deformation is formed on the surface of the solid rocket motor propellant grain in response to the applying, and calculating a value of the mechanical property of the solid rocket motor propellant grain based on the deformation. The force may be applied by moving a liquid into the perforation. This process may be performed over time to determine a lifespan of the propellant grain.

Abstract: A method for non-destructively determining a mechanical property of a solid rocket motor propellant grain may comprise applying a force to a surface of the solid rocket motor propellant grain, wherein a deformation is formed on the surface of the solid rocket motor propellant grain in response to the applying, and calculating a value of the mechanical property of the solid rocket motor propellant grain based on the deformation. This process may be performed over time to determine a lifespan of the propellant grain.

Abstract: The described embodiments transfer an activity from a source electronic device to a companion electronic device. The source electronic device receives activity information describing an activity performed in a first application at the source electronic device, determines an activity identifier for the activity information, and broadcasts an activity advertisement comprising the activity identifier. Upon receiving the activity advertisement, the companion electronic device determines whether a second application that is associated with the first application is available at the companion electronic device. If the second application is available, the companion electronic device requests extended activity data from the source electronic device. The source electronic device responds by sending extended activity data from the first application to the companion electronic device.

Abstract: A compound represented by Li?Co(1-x-2y)Mex(M1M2)yO?, (Formula (I)) wherein Me, is one or more of Li, Mg, Al, Ca, Ti, Zr, V, Cr, Mn, Fe, Ni, Cu, Zn, Ru and Sn, and wherein 0?x?0.3, 0<y?0.4, 0.95???1.4, and 1.90???2.10 is disclosed. Further, particles including such compounds are described.

Abstract: A compound represented by Li?Co(1-x-2y)Mex(M1M2)yO?, (Formula (I)) wherein Me, is one or more of Li, Mg, Al, Ca, Ti, Zr, V, Cr, Mn, Fe, Ni, Cu, Zn, Ru and Sn, and wherein 0?x?0.3, 0<y?0.4, 0.95???1.4, and 1.90???2.10 is disclosed. Further, particles including such compounds are described.

Abstract: A cathode active material includes a plurality of cathode active compound particles and a coating disposed over each of the cathode active compound particles. The coating includes a lithium (Li)-ion conducting oxide containing lanthanum (La) and titanium (Ti).

Abstract: Cathode active materials are provided. The cathode active material can include a plurality of cathode active compound particles. A coating is disposed over each of the cathode active compound particles. The coating can include at least one of ZrO2, La2O3, a mixture of Al2O3 and ZrO2 or a mixture of Al2O3 and La2O3. The battery cells that include the cathode active material are also provided.

Abstract: A solid rocket motor propellant grain arrangement may comprise a case, a propellant grain disposed within the case, and an integrated rocket motor aging sensor disposed outward from the propellant grain, wherein the integrated rocket motor aging sensor is configured to measure data corresponding to a plurality of distinct locations of the propellant grain. The integrated rocket motor aging sensor may comprise a resistive screen matrix (RSM).

Abstract: An object size model filters false positive results in systems using artificial intelligence engines in connection with video cameras and associated video data streams. The system obtains a video data stream and accesses an object size model that has been previously computed for the camera from which the video data stream is obtained. An object is detected in the video stream and a preliminary identification thereof is made. A size range for the identified object is calculated using the object size model. The object size range is compared to an observed size of the object. If observed size of the object is not within the size range for the identified object, the object is deemed to be a false positive.

Abstract: Signal-to-noise ratios are calculated for cellphones in a process that may be implemented in processing elements of the cellphones or in a SIM card. A signal for a cellular device is obtained, such as a voice stream, a message, or a data stream. The voice stream, for example, may be received as a part of a telephone call, as part of a voicemail message, as part of a VoIP call, or as part of a video messaging service, etc. The noise data is determined in the signal using a machine learning algorithm. The cellphone may include a model based on the identification of signals as desired signals or as noise. The model on the cellphone may be learned and updated incrementally, based on the identification of new signals as desired signals or as noise and based on the identification of signals by other systems.

Abstract: Changes in sizes of objects over long periods of time are detected. The objects may be detected in the field of view of a camera that is used in systems having artificial intelligence engines in connection with video cameras and associated video data streams. A video processor identifies different elements in the video stream. Segments are created around the different elements identified. The video processor identifies an algorithm for each segment. An object is identified in the video stream. The video processor uses the created segments and the identified algorithms to detect changes in the object over time.

Abstract: Segments are generated with respect to images and rules are correlated to the segments. The images may be associated with the field of view of a camera that is used in systems having artificial intelligence engines in connection with video cameras and associated video data streams. A video processor identifies element in a video stream, examples of which include various regions in a view, such as sky, vegetation, buildings, etc. The elements may be identified based on elements that were previously identified for other cameras and can be updated in response to the view changing. Segments are created around the different identified elements. Rules are assigned to the segments. The rules and segments may be stored for later reference when analyzing events within the view of the video camera.

Abstract: Artificial intelligence (AI) models are switched, tuned and retrained. This process may be performed with respect to systems having artificial intelligence engines in connection with video cameras and associated video data streams. An AI model is obtained for a video camera based on, for example, historic video streams from the camera for the past day, week, month, year, or any other time period. The AI model is then modified for the camera after the system obtains, for example, data internal to the video camera, data external to the video camera and data related to objects of interest for the video camera. As the AI model is modified, a processor associated with the system may adopt linear regression algorithms to regress conditions to the modified model and other available models.

Abstract: Multiple input feeds are used to make a pathway determination in systems using artificial intelligence engines in connection with video cameras, associated video streams, and other sensors. The system obtains a video stream and information specifying a location of the video stream. An event is detected in the video stream, such as movement of an individual, movement of an automobile, criminal activity, an emergency situation, etc. The system also obtains a detection signal and location thereof, such as information from a sensor in a heat detecting device, a sound detecting device, or a camera. Based on the foregoing information, the system identifies a possible future location for an event, such as the movement of the detected individual, automobile, etc.

Abstract: An interactive virtualization management system provides an assessment of proposed or existing virtualization schemes. A Virtual Technology Overhead Profile (VTOP) is created for each of a variety of configurations of host computer systems and virtualization technologies by measuring the overhead experienced under a variety of conditions. The multi-variate overhead profile corresponding to each target configuration being evaluated is used by the virtualization management system to determine the overhead that is to be expected on the target system, based on the particular set of conditions at the target system. Based on these overhead estimates, and the parameters of the jobs assigned to each virtual machine on each target system, the resultant overall performance of the target system for meeting the performance criteria of each of the jobs in each virtual machine is determined, and over-committed virtual machines and computer systems are identified.

Abstract: The disclosed embodiments relate to the manufacture of a precursor co-precipitate material for a cathode active material composition. During manufacture of the precursor co-precipitate material, an aqueous solution containing at least one of a manganese sulfate and a cobalt sulfate is formed. Next, a NH4OH solution is added to the aqueous solution to form a particulate solution comprising irregular secondary particles of the precursor co-precipitate material. A constant pH in the range of 10-12 is also maintained in the particulate solution by adding a basic solution to the particulate solution.

Abstract: A technique facilitates valve operations in many applications including well related applications. A valve utilizes a piston which moves along an arc. The valve has an outer housing and an inner housing spaced to create an arcuate pressure chamber which extends along the arc. A piston is mounted in the arcuate pressure chamber for movement along the arc. A hydraulic force or other force may be selectively applied directly against an end of the arcuate piston to shift the arcuate piston along the arc. In some applications, the piston comprises a cutting edge oriented to enable performance of a cutting operation.