Abstract: A method and apparatus for generating a NLFM signal in real time, and a computer storage medium are disclosed, including: determining a signal parameter of a signal according to a system parameter, the signal parameter includes: a signal bandwidth, a signal pulse width and a PSLR; determining a power spectrum density function according to PSLR; calculating the power spectrum density function to obtain a group delay vector; calculating a frequency axial vector according to a system sampling rate; calculating a time axial vector according to the signal pulse width; performing linear interpolation calculation on the group delay vector to obtain an instantaneous frequency vector; integrating the instantaneous frequency vector to obtain a phase vector; determining a signal time domain discrete vector; and generating a digital signal according to the signal time domain discrete vector, and performing digital-to-analog conversion on the digital signal to obtain the NLFM signal.

Abstract: Disclosed is catalyst preparation method for liquid phase hydrogenation of acetophenone in preparation of ?-phenylethanol. The method includes adding water, small alcohol, Gemini surfactant and organic pore-forming agent to reactor. Then adding silica sol and stirring to prepare aqueous dispersion of silica sol; preparing alkaline precipitant and mixed solution containing salts of copper containing compound, zinc containing compound, rare-earth metal containing compound and alkaline-earth metal containing compound, adding alkaline precipitant and mixed solution together to aqueous dispersion, followed by precipitation, ageing, filtration, washing, drying, calcination and molding to obtain catalyst.

Abstract: A method and apparatus for generating a NLFM signal in real time, and a computer storage medium are disclosed, including: determining a signal parameter of a signal according to a system parameter, the signal parameter includes: a signal bandwidth, a signal pulse width and a PSLR; determining a power spectrum density function according to PSLR; calculating the power spectrum density function to obtain a group delay vector; calculating a frequency axial vector according to a system sampling rate; calculating a time axial vector according to the signal pulse width; performing linear interpolation calculation on the group delay vector to obtain an instantaneous frequency vector; integrating the instantaneous frequency vector to obtain a phase vector; determining a signal time domain discrete vector; and generating a digital signal according to the signal time domain discrete vector, and performing digital-to-analog conversion on the digital signal to obtain the NLFM signal.

Abstract: Disclosed is a preparation method of a catalyst for liquid phase hydrogenation of acetophenone in preparation of ?-phenylethanol, including: adding water, a small alcohol, a Gemini surfactant and an organic pore-forming agent to a reactor, followed by adding a silica sol and stirring well to prepare an aqueous dispersion of silica sol; preparing an alkaline precipitant and a mixed solution containing salts of a copper containing compound, a zinc containing compound, a rare-earth metal containing compound and an alkaline-earth metal containing compound, adding the alkaline precipitant and the mixed solution together to the aqueous dispersion of silica sol, followed by precipitation, ageing, filtration, washing, drying, calcination and molding to obtain the catalyst.

Abstract: Various embodiments of the present technology may comprise a method and apparatus for vignette and out-of-focus correction. The method and apparatus may be configured to reposition an adjustable lens during a series of image captures to direct light to the center and the outer edges and/or corners of the image sensor to focus various areas of an object and/or scene. The method and apparatus may further substitute image data from a first image capture with image data from subsequent image captures.

Abstract: Various embodiments of the present technology may comprise a method and apparatus for vignette and out-of-focus correction. The method and apparatus may be configured to reposition an adjustable lens during a series of image captures to direct light to the center and the outer edges and/or corners of the image sensor to focus various areas of an object and/or scene. The method and apparatus may further substitute image data from a first image capture with image data from subsequent image captures.

Abstract: The present invention is directed to a method and apparatus for learning call routing information in a communication system. A switching architecture is presented. The switch may be implemented in a centralized architecture or a distributed architecture. In addition, the switch may be implemented in a variety of networks such as a circuit-switched network or a packet-switched network. The switch includes a policy server and a self-learning application server. The policy server includes routing information for routing calls across the switch. The routes for incoming and outgoing calls are analyzed as they pass through the switch. The self-learning application server uses artificial intelligence techniques and caching algorithms to learn new more-efficient routing paths or initial routing paths based on the incoming and outgoing calls. The self-learning application server then updates the policy server with the new learned routes.

Abstract: The present invention is directed to a method and apparatus for learning call routing information in a communication system. A switching architecture is presented. The switch may be implemented in a centralized architecture or a distributed architecture. In addition, the switch may be implemented in a variety of networks such as a circuit-switched network or a packet-switched network. The switch includes a policy server and a self-learning application server. The policy server includes routing information for routing calls across the switch. The routes for incoming and outgoing calls are analyzed as they pass through the switch. The self-learning application server uses artificial intelligence techniques and caching algorithms to learn new more-efficient routing paths or initial routing paths based on the incoming and outgoing calls. The self-learning application server then updates the policy server with the new learned routes.

Abstract: The present invention is directed to a method and apparatus for learning call routing information in a communication system. A switching architecture is presented. The switch may be implemented in a centralized architecture or a distributed architecture. In addition, the switch may be implemented in a variety of networks such as a circuit-switched network or a packet-switched network. The switch includes a policy server and a self-learning application server. The policy server includes routing information for routing calls across the switch. The routes for incoming and outgoing calls are analyzed as they pass through the switch. The self-learning application server uses artificial intelligence techniques and caching algorithms to learn new more-efficient routing paths or initial routing paths based on the incoming and outgoing calls. The self-learning application server then updates the policy server with the new learned routes.

Abstract: The present invention is directed to a method and apparatus for learning call routing information in a communication system. A switching architecture is presented. The switch may be implemented in a centralized architecture or a distributed architecture. In addition, the switch may be implemented in a variety of networks such as a circuit-switched network or a packet-switched network. The switch includes a policy server and a self-learning application server. The policy server includes routing information for routing calls across the switch. The routes for incoming and outgoing calls are analyzed as they pass through the switch. The self-learning application server uses artificial intelligence techniques and caching algorithms to learn new more-efficient routing paths or initial routing paths based on the incoming and outgoing calls. The self-learning application server then updates the policy server with the new learned routes.