Abstract: A battery assembly, a battery pack and a vehicle are provided. The battery assembly includes: multiple cells; a connecting member, where the cells is electrically connected to each other through the connecting member; and a thermally conductive member, where the cell has a housing, the thermally conductive member is provided between the connecting member and the housing, and the thermally conductive member is thermally conductively connected to the connecting member and the housing.

Abstract: Data integrity checks for reducing communication latency is described. A transmitting endpoint transmits data to a receiving endpoint by generating an integrity tag for a first subset of data blocks and a second integrity tag for a second subset of data blocks. In implementations, the first and second integrity tags overlap at least one data block and are offset based on computational complexities of generating the integrity tags. A receiving endpoint generates comparison tags for each of the integrity tags and uses the comparison tags to validate an authenticity of received data. In response to validating the first and second integrity tags, data blocks covered by both the first and second integrity tags are released for use. Additional integrity tags are generated and validated for subsequent subsets of data blocks during data communication, thus reducing latency by offsetting times at which comparison tags are generated and validated.

Abstract: Disclosed are a method and an apparatus of processing image. The method includes: obtaining an initial bone segmentation result; and fusing the initial bone segmentation result based on characteristics of and correspondences between a plurality of bone segmentation results in the initial bone segmentation result, to obtain a target bone segmentation result. The initial bone segmentation result includes the plurality of bone segmentation results generated by a plurality of different deep learning models. Methods in the embodiments of the present application can improve precision of a fusion result of the plurality of bone segmentation results.

Abstract: A processing method for image tensor data, which can greatly reduce the number of free parameters in the model, limit the weight layer flexibly, and can be applied to any order of image tensor data. In this processing method for image tensor data, TTRBM model of Restricted Boltzmann machine with tensor train format is introduced. The input and output data of this method are both represented by tensors, and the weight of the middle layer is also represented by tensors, and the restricted weight has the structure of tensor train. The number of free parameters in the middle layer is controlled by adjusting the rank of tensor train decomposition. The rank of TT decomposition is adjusted, and different feature representations with the same size are expressed.

Abstract: A processing method for high-order tensor data, which can avoid that the vectorization process of the image observation sample set damage the internal structure of the data, simplify the large amount of redundant information in the high-order tensor data in the image observation sample set, and improve the image processing speed. In this processing method for high-order tensor data, the high-order tensor data are divided into three parts: the shared subspace component, the personality subspace component and the noise part; the shared subspace component and the personality subspace component respectively represent the high-order tensor data as a group of linear combination of the tensor base and the vector coefficient; the variational EM method is used to solve the base tensor and the vector coefficient; design a classifier to classify the test samples by comparing the edge distribution of samples.

Abstract: A processing method for image tensor data, which can greatly reduce the number of free parameters in the model, limit the weight layer flexibly, and can be applied to any order of image tensor data. In this processing method for image tensor data, TTRBM model of Restricted Boltzmann machine with tensor train format is introduced. The input and output data of this method are both represented by tensors, and the weight of the middle layer is also represented by tensors, and the restricted weight has the structure of tensor train. The number of free parameters in the middle layer is controlled by adjusting the rank of tensor train decomposition. The rank of TT decomposition is adjusted, and different feature representations with the same size are expressed.

Abstract: A processing method for high-order tensor data, which can avoid that the vectorization process of the image observation sample set damage the internal structure of the data, simplify the large amount of redundant information in the high-order tensor data in the image observation sample set, and improve the image processing speed. In this processing method for high-order tensor data, the high-order tensor data are divided into three parts: the shared subspace component, the personality subspace component and the noise part; the shared subspace component and the personality subspace component respectively represent the high-order tensor data as a group of linear combination of the tensor base and the vector coefficient; the variational EM method is used to solve the base tensor and the vector coefficient; design a classifier to classify the test samples by comparing the edge distribution of samples.

Abstract: The present disclosure provides a method for processing data on Internet of Vehicles, a server, and a terminal. In a technical solution of the present disclosure, the server first acquires the historical travel data, and then performs training on the historical travel data to obtain the program script used to analyze the driving behavior of the user, and finally sends the program script to the terminal. The driving behavior of the user is dynamically analyzed according to the program script and the travel data, which resolves a problem that algorithm accuracy decreases because an algorithm is not updated in time, ensures accuracy of analyzing the driving behavior of the user, and further decreases additional costs brought by updating terminal firmware.

Abstract: Methods and systems for providing targeted recommendations are provided. A user model is generated from user data. Feed candidates are generated based on the user model. The generated feed candidates are ranked on a predetermined scale. At least one targeted recommendation from the ranked feed candidates. The at least one targeted recommendation feed is provided to a user associated with the user data.

Abstract: The technology described herein provides an efficient mechanism for quickly analyzing huge amounts of media content to find media content (hereafter “content” or “media content”) that is relevant to a user. The technology analyzes features of a curator to classify curators by interest and/or find curators with similar content recommendations. The curator data can be used to make curator recommendations to users based on the user's interests. The technology described herein collects curator data from multiple content sites and analyzes the data to identify curators that recommend similar content on different content sites.

Abstract: Various embodiments described herein are directed to providing cohesive related searches with dynamically generated titles. One or more related queries are retrieved for a search query and are grouped into one or more groupings based on a predefined relationship between the search query and a subset of the related queries. A dynamically generated first title is retrieved for a first grouping from the predefined relationship between the search query and the related queries in first grouping. The first title and the related queries in the first grouping are presented. A selection pivot is provided to select a second grouping, where the selection pivot contains an indicator of the predefined relationship between the search query and the related queries in the second grouping. Upon selecting the second grouping, a dynamically generated second title is retrieved, and the second title and the related queries in the second grouping are presented.

Abstract: The technology described herein provides an efficient mechanism for generating image tags. Image data from a plurality of sources may be analyzed to identify relevant text items from the aggregated data. The relevant text items may be keywords describing a subject of an image, an entity of an image, a location of an image, or the like. From the aggregated image data, one or more image tags may be generated and stored as an offline dataset with an image identifier. Upon detecting a prompt such as a user issuing a search query for an image, the image identifier is used to perform a look up of the image and associated image tags to be provided.

Abstract: Methods and systems for providing targeted recommendations are provided. A user model is generated from user data. Feed candidates are generated based on the user model. The generated feed candidates are ranked on a predetermined scale. At least one targeted recommendation from the ranked feed candidates. The at least one targeted recommendation feed is provided to a user associated with the user data.

Abstract: A pull-out basket for kitchen cupboard, having a basket and two sliding rail structures on which the two sliding rail structures are mounted; each of the sliding rail structures contains a fixed slot; a middle section of the fixed slot is mounted with a hydraulic damper; an outer side of the second sliding gear rack is provided with a position limiting guiding slot; the position limiting guiding slot is connected with a first sliding gear rack through a gear; the first sliding gear rack is mounted with a sliding slot; the hydraulic damper has a cylinder; an end of the cylinder is connected with a piston rod; the piston rod and a tensile resilient member is connected with a connection block; the connection block is connected with a locking block; a hanging hook is connected onto the sliding slot.

Abstract: A user query may be evaluated to provide a result set. In case the results do not reflect the user's intent, the device may provide recourse options for adjusting the query in a manner that yields more desirable results, e.g., a suggestion at the top of the result set for a different spelling, or recommendations at the end of the results set for additional query techniques that may yield more accurate results. However, such presentation of recourse options may clutter the user interface and/or go unnoticed by the user. Instead, an adjusted query may be identified with an interpreted probability of reflecting the intent of the query. An adjustment option describing the adjusted query may be inserted into the result set, between a higher-probability first result and a lower-probability second result. Selection of the adjustment option may cause the adjusted query to be evaluated on behalf of the user.

Abstract: Various embodiments described herein are directed to providing cohesive related searches with dynamically generated titles. One or more related queries are retrieved for a search query and are grouped into one or more groupings based on a predefined relationship between the search query and a subset of the related queries. A dynamically generated first title is retrieved for a first grouping from the predefined relationship between the search query and the related queries in first grouping. The first title and the related queries in the first grouping are presented. A selection pivot is provided to select a second grouping, where the selection pivot contains an indicator of the predefined relationship between the search query and the related queries in the second grouping. Upon selecting the second grouping, a dynamically generated second title is retrieved, and the second title and the related queries in the second grouping are presented.

Abstract: The technology described herein provides an efficient mechanism for generating image tags. Image data from a plurality of sources may be analyzed to identify relevant text items from the aggregated data. The relevant text items may be keywords describing a subject of an image, an entity of an image, a location of an image, or the like. From the aggregated image data, one or more image tags may be generated and stored as an offline dataset with an image identifier. Upon detecting a prompt such as a user issuing a search query for an image, the image identifier is used to perform a look up of the image and associated image tags to be provided.

Abstract: The present disclosure provides a method for processing data on Internet of Vehicles, a server, and a terminal. In a technical solution of the present disclosure, the server first acquires the historical travel data, and then performs training on the historical travel data to obtain the program script used to analyze the driving behavior of the user, and finally sends the program script to the terminal. The driving behavior of the user is dynamically analyzed according to the program script and the travel data, which resolves a problem that algorithm accuracy decreases because an algorithm is not updated in time, ensures accuracy of analyzing the driving behavior of the user, and further decreases additional costs brought by updating terminal firmware.

Abstract: The technology described herein provides an efficient mechanism for quickly analyzing huge amounts of media content to find media content (hereafter “content” or “media content”) that is relevant to a user. The technology analyzes features of a curator to classify curators by interest and/or find curators with similar content recommendations. The curator data can be used to make curator recommendations to users based on the user's interests. The technology described herein collects curator data from multiple content sites and analyzes the data to identify curators that recommend similar content on different content sites.

Abstract: A user query may be evaluated to provide a result set. In case the results do not reflect the user's intent, the device may provide recourse options for adjusting the query in a manner that yields more desirable results, e.g., a suggestion at the top of the result set for a different spelling, or recommendations at the end of the results set for additional query techniques that may yield more accurate results. However, such presentation of recourse options may clutter the user interface and/or go unnoticed by the user. Instead, an adjusted query may be identified with an interpreted probability of reflecting the intent of the query. An adjustment option describing the adjusted query may be inserted into the result set, between a higher-probability first result and a lower-probability second result. Selection of the adjustment option may cause the adjusted query to be evaluated on behalf of the user.