Abstract: A method for optimizing a Polar-RNNA quantizer of MLC NAND flash based on deep learning comprises the following steps: Step S1: transforming an MLC flash detection task into a deep learning task, and obtaining three hard-decision read thresholds based on a neural network; Step S2: expanding six soft-decision read thresholds based on the three hard-decision read thresholds; Step S3: constructing an LLR mapping table, and obtaining new LLR information of MLC flash based on the LLR mapping table; Step S4: symmetrizing an MLC flash channel, and performing density evolution; and Step S5: optimizing the soft-decision read thresholds based on a genetic algorithm to obtain an optimal quantization interval. According to the invention, polar codes can be directly used for MLC flash channels without the arduous work of MLC flash channel modeling, so that the reliability of MLC flash is effectively improved.

Abstract: A method includes machining a raw surface of a metal component to remove first native oxide from a metal base of the metal component to generate an as-machined surface of the metal component. A second native oxide is formed on the metal base of the as-machined surface of the metal component subsequent to the machining. The method further includes, subsequent to the machining, performing operations to generate a finished surface of the metal component. The operations include a surface machining of the as-machined surface of the metal component to remove the second native oxide.

Abstract: The present disclosure provides a technical solution related to establishing a characterized chatbot with personality. On one hand, a corpus database matched with a specific character may be established, and a generated regular/conventional response messages may be converted into a characterized response messages with character's features during conversation, so that the conversation style of a chatbot may be characterized with a certain character's features. On the other hand, a chatbot may select a response message with a specific emotion by using an emotion conversation table corresponding to a personality when generating the response message against a content of a conversation input by a user, so that a chatbot may be characterized and have certain personality.

Abstract: A method for optimizing a Polar-RNNA quantizer of MLC NAND flash based on deep learning comprises the following steps: Step S1: transforming an MLC flash detection task into a deep learning task, and obtaining three hard-decision read thresholds based on a neural network; Step S2: expanding six soft-decision read thresholds based on the three hard-decision read thresholds; Step S3: constructing an LLR mapping table, and obtaining new LLR information of MLC flash based on the LLR mapping table; Step S4: symmetrizing an MLC flash channel, and performing density evolution; and Step S5: optimizing the soft-decision read thresholds based on a genetic algorithm to obtain an optimal quantization interval. According to the invention, polar codes can be directly used for MLC flash channels without the arduous work of MLC flash channel modeling, so that the reliability of MLC flash is effectively improved.

Abstract: The present disclosure provides a method, switch and system for updating a route, relating to computer network technologies. The method comprises detecting, by a current device, link states of at least two neighbor devices; when the current device detects that a link state of a first neighbor device is unreachable, setting, by the current device, a state of a routing item with an initial state being reachable among all routing items corresponding to the first neighbor device in an internal routing table to be unreachable; and detecting, by the current device, whether states of all routing items corresponding to each target subnet in the internal routing table are all unreachable, respectively; if yes, sending a route updating message to another neighbor device except the first neighbor device.

Abstract: Taught herein is an integragted narrow bandpass filter array and a method of its fabrication. The filter array is a Fabry-Perot type of filter array, wherein the pass band changes with the thickness of the spacer layer. The integrated filter array comprises a substrate, a lower mirror stack, a spacer array, and an upper mirror stack. The spacer array is an array of varied thicknesses formed using a combinatorial deposition technique. The spacer array is used to control the pass band of each mini-size narrow bandpass filter and realizes the integration of narrow bandpass filters with different pass bands on a single substrate. The merit of this technique lies in its fabrication efficiency and finished product rate which are much higher than for conventional methods. The filter array is completely matched with detector arrays and functional in most of the important optical ranges.

Abstract: Taught herein is an integragted narrow bandpass filter array and a method of its fabrication. The filter array is a Fabry-Perot type of filter array, wherein the pass band changes with the thickness of the spacer layer. The integrated filter array comprises a substrate, a lower mirror stack, a spacer array, and an upper mirror stack. The spacer array is an array of varied thicknesses formed using a combinatorial deposition technique. The spacer array is used to control the pass band of each mini-size narrow bandpass filter and realizes the integration of narrow bandpass filters with different pass bands on a single substrate. The merit of this technique lies in its fabrication efficiency and finished product rate which are much higher than for conventional methods. The filter array is completely matched with detector arrays and functional in most of the important optical ranges.