Abstract: A method for providing recommendations to a user includes assigning one or more item tags from a known set of tags to one or more items of a plurality of items; assigning one or more user tags from the known set of tags to a user; determining at least one taste cluster having one or more cluster tags from the known set of tags, wherein the taste cluster shares at least one shared tag with the one or more user tags and with the one or more item tags; affiliating at least one item of the plurality of items with the taste cluster based on the shared tag; affiliating the user with the taste cluster based on the shared tag; and presenting to the user at least one presented item of the plurality of items affiliated with the taste cluster.

Abstract: The fine-tuning of a machine learning model in a protected environment. Input (e.g., training data) received from the tune initiator system that instructs the tuning occur is received over a channel that is visible to the tune initiator system. Proprietary input is received from another party over a secure connection that is not visible to the tune initiator system. These inputs are then used to fine-tune a machine learning model to thereby form a fine-tuned machine learning model. The resulting fine-tuned machine learning model is then stored in the protected environment such that the fine-tuned machine learning model is available for the tune initiator system to provide input data to and receive output data from, but such that the tuned model cannot be directly accessed by the tune initiator system.

Abstract: Disclosed in the present disclosure are a flood event identification method and apparatus, an electronic device, and a readable storage medium. The method includes: obtaining runoff time sequence data; obtaining initial peak occurrence time by using N continuous first-order difference values in a first-order difference sequence of the runoff time sequence data; obtaining initial start and end time by using M continuous first-order difference values in the first-order difference sequence; and screening out determined peak occurrence time from the initial peak occurrence time, and screening out start and end time corresponding to the peak occurrence time from the initial start and end time. With the technical solution provided by the present disclosure, flood events can be automatically selected with high efficiency and accuracy.

Abstract: The present disclosure relates to the technical field of batteries, and in particular, to a modified lithium ion negative electrode material, and preparation therefor and use thereof. The preparation method includes the following steps: dropwise adding a mixed solution of a titanium source and a lithium source into a mixed solution of an iron salt and an organic acid, adjusting the pH to 5.0-7.0, and stirring to obtain a wet gel; drying and crushing the wet gel, and then calcinating to obtain a LiFeTiO4 composite oxide; and reducing the LiFeTiO4 composite oxide to obtain the modified lithium ion negative electrode material. In the present disclosure, a spinel modified negative electrode material lithium iron titanium oxide is synthesized by using a citric acid sol-gel method, thereby not only greatly improving the charging and discharging capacity thereof, but also improving the large-current charging and discharging capability thereof.

Abstract: A method for providing recommendations to a user includes assigning one or more item tags from a known set of tags to one or more items of a plurality of items; assigning one or more user tags from the known set of tags to a user; determining at least one taste cluster having one or more cluster tags from the known set of tags, wherein the taste cluster shares at least one shared tag with the one or more user tags and with the one or more item tags; affiliating at least one item of the plurality of items with the taste cluster based on the shared tag; affiliating the user with the taste cluster based on the shared tag; and presenting to the user at least one presented item of the plurality of items affiliated with the taste cluster.

Abstract: The present disclosure relates to the technical field of batteries, and in particular, to a modified lithium ion negative electrode material, and preparation therefor and use thereof. The preparation method includes the following steps: dropwise adding a mixed solution of a titanium source and a lithium source into a mixed solution of an iron salt and an organic acid, adjusting the pH to 5.0-7.0, and stirring to obtain a wet gel; drying and crushing the wet gel, and then calcinating to obtain a LiFeTiO4 composite oxide; and reducing the LiFeTiO4 composite oxide to obtain the modified lithium ion negative electrode material. In the present disclosure, a spinel modified negative electrode material lithium iron titanium oxide is synthesized by using a citric acid sol-gel method, thereby not only greatly improving the charging and discharging capacity thereof, but also improving the large-current charging and discharging capability thereof.

Abstract: Automated uploading of user and system data from one or more source computing systems to one or more destination storage repositories is provided. A data uploader module is installed on each computing system or is accessible by each computing system from which user and/or system data may need to be exported to a destination repository. Upon command, a data uploader module reads desired user data or system data from the computing system. The read data is transformed, if required, and the data is then exported to a destination storage repository. The exported data may be stored and analyzed at the destination storage repository from which it may be subsequently exported to other destinations, including back to the source computing system from which it was originally extracted.

Abstract: Automated uploading of user and system data from one or more source computing systems to one or more destination storage repositories is provided. A data uploader module is installed on each computing system or is accessible by each computing system from which user and/or system data may need to be exported to a destination repository. Upon command, a data uploader module reads desired user data or system data from the computing system. The read data is transformed, if required, and the data is then exported to a destination storage repository. The exported data may be stored and analyzed at the destination storage repository from which it may be subsequently exported to other destinations, including back to the source computing system from which it was originally extracted.

Abstract: Automated uploading of user and system data from one or more source computing systems to one or more destination storage repositories is provided. A data uploader module is installed on each computing system or is accessible by each computing system from which user and/or system data may need to be exported to a destination repository. Upon command, a data uploader module reads desired user data or system data from the computing system. The read data is transformed, if required, and the data is then exported to a destination storage repository. The exported data may be stored and analyzed at the destination storage repository from which it may be subsequently exported to other destinations, including back to the source computing system from which it was originally extracted.

Abstract: Automated monitoring and reporting of the uploading transmission and the completeness of data uploading from one or more source locations to one or more destination locations is provided. A data uploader module is installed on each computing system or is accessible by each computing system from which user and/or system data may need to be exported to a destination repository. Test data is passed via a data uploader from each source system to one or more designated storage repositories to monitor data upload connectivity, as well as, proper operation of the data uploader module. In addition, data extracted from a source is periodically compared with data received by a destination to analyze and report completeness of data exported from a source system to a destination system. Errors in either transmission or export completeness are reported and corrected as needed.

Abstract: Automated uploading of user and system data from one or more source computing systems to one or more destination storage repositories is provided. A data uploader module is installed on each computing system or is accessible by each computing system from which user and/or system data may need to be exported to a destination repository. Upon command, a data uploader module reads desired user data or system data from the computing system. The read data is transformed, if required, and the data is then exported to a destination storage repository. The exported data may be stored and analyzed at the destination storage repository from which it may be subsequently exported to other destinations, including back to the source computing system from which it was originally extracted.