Abstract: The present disclosure provides a battery, a separator for a battery and a method for preparing the separator, where the separator for a battery includes a base film and a coating structure disposed on the base film, the coating structure includes a plurality of material layers, and each material layer contains one-dimensional nanomaterials, and average lengths of one-dimensional nanomaterials in respective material layers are decreased layer by layer in a direction away from the base film.

Abstract: A data compression method includes providing one or more data block sets, where each data block set includes a plurality of data blocks with a same fingerprint; providing one or more compression groups based on a similarity degree between a plurality of data blocks included in each data block set, where one compression group includes a plurality of similar data blocks, the plurality of similar data blocks are a subset of data blocks included in the one or more data block sets, and a similarity degree between the plurality of similar data blocks meets a specific similarity condition; and compressing the plurality of similar data blocks included in the compression group.

Abstract: Embodiments of this disclosure provide for a data compression method and a related data compression apparatus. In the method, to-be-compressed data and a length limit value for data compression are obtained. When the length of the data obtained by compressing the to-be-compressed data is greater than the length limit value, the to-be-compressed data is segmented based on the length limit value during compression. After the to-be-compressed data is segmented, the to-be-compressed data includes at least two compressed files after compression and a length of each compressed file is less than the length limit value.

Abstract: In an example embodiment, a first machine learned model is trained to produce output, and a second machine learned model is then trained using training data that has been labeled, at least partially, using the output of the first machine learned model. The first machine learned model is trained to output a measure of how strong a positive signal in the training data really is. Specifically, this measure indicates the level of intention of a user who has engaged in a first user interface action with respect to a piece of content to engage in a subsequent second user interface action with the same piece of content.

Abstract: In a method for compressing data, a storage system determines whether deduplication can be performed on a target data block. When deduplication cannot be performed on the target data block, the storage system obtaining a similar fingerprint of the target data block, and determines, based on the similar fingerprint, a combined data block group to which the target data block belongs. The storage system then performs similar compression on the target data block based on a reference block in the combined data block group.

Abstract: This disclosure relates to a video compression method, apparatus, and device, and a medium. The method includes: obtaining a video frame, where the video frame includes a first dynamic group of pictures and a second dynamic group of pictures; extracting a first I frame in the first dynamic group of pictures, and extracting a second I frame in the second dynamic group of pictures; deleting duplicate data between the first I frame and the second I frame, to obtain a target I frame; and compressing the target I frame. The duplicate data between the first I frame and the second I frame is deleted, and this does not affect integrity of data of the video frame.

Abstract: A data reduction method, apparatus, and computing device and a storage medium are provided. The method includes: when reduction is to be performed on a to-be-reduced data block, obtaining a fingerprint of the to-be-reduced data block; forming an index set based on the fingerprint of the to-be-reduced data block by using index information of data blocks with identical fingerprints; and performing, in the to-be-reduced data block based on the fingerprint of the to-be-reduced data block, data reduction processing on a data block to which index information in a same index set belongs.

Abstract: A method for obtaining a storage system capacity is provided. An available capacity that is of a storage system and that is associated with each stripe length is obtained based on an obtained stripe length that can be effectively configured. Therefore, an available capacity of a system is optimally selected.

Abstract: In a method of storing data block, a storage device has stored a plurality of data block groups, each data block group having a common part that is contained in another data block in that group. For a target block to be stored, the storage device selects from the data block groups a target data block group has one data block whose common part is identical to a part of the target data block. The storage device then saves the target block by storing a target reference block of the target data block group and differential data between the target data block and the target reference block.

Abstract: In an example embodiment, a first machine learned model is trained to produce output, and a second machine learned model is then trained using training data that has been labeled, at least partially, using the output of the first machine learned model. The first machine learned model is trained to output a measure of how strong a positive signal in the training data really is. Specifically, this measure indicates the level of intention of a user who has engaged in a first user interface action with respect to a piece of content to engage in a subsequent second user interface action with the same piece of content.

Abstract: The present disclosure discloses a photovoltaic array fault diagnosis method and apparatus based on a random forest algorithm. A strong classifier is constructed with many weak classifiers by integrating a plurality of decision trees, diagnosis results are generated by voting, and even if the diagnosis result of the most votes is wrong, the diagnosis results of the second and third more votes can be taken for reference of maintenance personnel, thereby improving the maintenance efficiency, and shortening the fault time of a system. The method and the apparatus resolve the problems of large data volume, long training time and the like of the conventional neural network algorithm, and can simply and quickly complete a diagnosis task and quickly implement the fault diagnosis of a small photovoltaic array, especially a 3×2 photovoltaic array.

Abstract: Technologies for determining performance gains for content item delivery based on modifications to content item selection parameters are provided. The disclosed techniques include implementing a multi-objective optimization model for content item selection using a value for a parameter. The model generates a first plurality of scores and a first ranking for content items. Subset of content items is selected for delivery based on the first ranking. New values for the parameter are identified and for each new value, the content item selection event is replayed. A second plurality of scores and a second ranking is generated for the content items, where the second ranking is different from the first ranking. A third plurality of scores and a third ranking is generated where the third ranking matches the second ranking. A set of gains is calculated for each new value, where each gain corresponds to a different objective of the model.

Abstract: Techniques for generating cross features using a data driven approach are provided. Multiple possible splits of a numerical feature are identified. For each split, the numerical feature is transformed into a second feature based on the split, a cross feature is generated based on the second feature and a third (e.g., categorial) feature that is different than the first feature and the second feature, a predictive power of the cross feature is estimated, and the predictive power is added to a set of estimated predictive powers. After each split is considered, a cross feature that is associated with the highest estimated predictive power in the set of estimated predictive powers is selected. That first cross feature corresponds to a particular split from the multiple possible splits. The numerical feature is split based on the particular split to generate a bucketized version of the numerical feature.

Abstract: Technologies for determining performance gains for content item delivery based on modifications to content item selection parameters are provided. The disclosed techniques include implementing a multi-objective optimization model for content item selection using a value for a parameter. The model generates a first plurality of scores and a first ranking for content items. Subset of content items is selected for delivery based on the first ranking. New values for the parameter are identified and for each new value, the content item selection event is replayed. A second plurality of scores and a second ranking is generated for the content items, where the second ranking is different from the first ranking. A third plurality of scores and a third ranking is generated where the third ranking matches the second ranking. A set of gains is calculated for each new value, where each gain corresponds to a different objective of the model.

Abstract: The disclosed embodiments provide a system for performing an experiment strategy for member-based ramping. During operation, the system divides members of an online system into a control group and a treatment group. Next, the system configures delivery of content to the control group over a first set of channels that charge for actions related to the content and delivery of the content to the treatment group over a second set of channels that charge for the actions related to the content, wherein the second set of channels is smaller than the first set of channels. The system then performs a first experiment that selects an adjustment factor for content delivered over the second set of channels to the treatment group to achieve revenue neutrality and/or engagement neutrality between the treatment and control groups.

Abstract: Disclosed are systems and methods for managing queries on on-line advertisement data. The system includes a query engine device for receiving queries from and outputting query results to query client devices and a training engine for generating and adjusting a model for predicting an estimation of resource usage for execution of each received query based on each query's corresponding feature vector having values pertaining to the query and a system status. The query engine device is further configured to provide the estimation of resource usage for each query to the corresponding query client device and, in response, receive input from such corresponding query client device and specifying whether to proceed with the corresponding query. A database system receives input from each query's corresponding query client device as to whether to proceed with the query and, in response, initiates or inhibits execution of such query with respect to a database storage system.

Abstract: A flash memory error correction method and apparatus is provided. The method includes determining a first data bit in a flash memory page, where the first data bit corresponds to different data respectively in the data obtained by reading the flash memory page using the (n+1)th read voltage threshold and the data obtained by reading the flash memory page using the mth read voltage threshold; and then reducing a confidence level of the first data bit in the data obtained by reading the flash memory page using the (n+1)th read voltage threshold; and performing, according to an adjusted confidence level of the first data bit, error correction decoding on the data obtained by reading the flash memory page using the (n+1)th read voltage threshold. Present disclosure effectively improves a success rate of error correction decoding, thereby significantly improving performance of an SSD storage system.

Abstract: Embodiments of the present invention address deficiencies of the art in respect to context sensitive resource recommendations and provide a method, system and computer program product for activity sensitive context sensitive resource recommendations. In an embodiment of the invention, an activity-centric resource recommendation method can be provided. The method can include inferring an activity from a workspace in a graphical user interface, identifying resources from amongst a set of resources that are relevant to the inferred activity, and displaying the identified resources in the graphical user interface.

Abstract: A method for obtaining a storage system capacity is provided. An available capacity that is of a storage system and that is associated with each stripe length is obtained based on an obtained stripe length that can be effectively configured. Therefore, an available capacity of a system is optimally selected.

Abstract: The present disclosure discloses a photovoltaic array fault diagnosis method and apparatus based on a random forest algorithm, belonging to the field of photovoltaic technology. Based on the idea of data driving, the method constructs a photovoltaic array fault diagnosis model by using the random forest algorithm, which is suitable for the characteristics of an actual photovoltaic array. A strong classifier is constructed with many weak classifiers by integrating a plurality of decision trees, diagnosis results are generated by voting, and even if the diagnosis result of the most votes is wrong, the diagnosis results of the second and third more votes can be taken for reference of maintenance personnel, thereby improving the maintenance efficiency, and shortening the fault time of a system.