Abstract: Method, device and computer program product for wireless communication are provided. A method includes: receiving, by a wireless communication terminal, a first release message; and releasing, by the wireless communication terminal, at least one small data transmission, SDT, configuration stored in the wireless communication terminal according to a cell where the first release message is received or according to information of SDT configuration carried by the first release message.

Abstract: According to implementations of the present disclosure, there is proposed a solution for analyzing a data table in response to a user input. In this solution, a user input in a cell of a data table is determined. The data table comprises a plurality of cells arranged in rows and columns. An analysis operation for the data table is determined based on semantics of the data table and the user input, the analysis operation corresponding to the user input. Further, a result of the analysis operation is presented in a region of the data table related to the cell. In this way, grid characteristics of the data table can be utilized to provide the result of the analysis operation as desired by a user and simple, efficient and user-friendly data analysis can be facilitated.

Abstract: Implementations of the present disclosure provide a solution for spreadsheet table transformation. In this solution, one or more header areas and a data area of a spreadsheet table are detected. A hierarchical structure of each of the header areas is determined by analysis of cell merging and/or indents in the header area, and/or a function relationship between data items in corresponding cells of the data area. The spreadsheet table can be transformed to a relational table based on recognition of the hierarchical structure of the header area. In this way, by facilitating understanding of header structures based on the header hierarchy, it is possible to achieve automated transformation from spreadsheet tables to relational tables.

Abstract: The present invention provides an LED illumination device, including: a light source carrier including a base, an accommodating space formed on the base; a light emitting unit including a light emitter and a lamp board fixed to the light source carrier; and an optical member covering or at least partially covering the light emitting unit. The light emitting unit and the optical member are both disposed in the accommodating space. The optical member includes a first light distribution unit and a second light distribution unit. At least 70% of a luminous flux generated by the light emitter in operation is directly emitted from the LED illumination device through the second light distribution unit.

Abstract: A computing apparatus of an insight interfacing system receives from a user a request for a dataset comprising a plurality of subspaces of a multi-dimensional data structure. Insights are received based on the received request then presented on a display device. Also, a chart may be presented based on the received request. The computing apparatus receives a selection of at least a portion of the presented one or more insights or a portion of the chart, then receives contextual insights based on the selected portion and presents the contextual insights on the display device.

Abstract: An LED lighting device includes a seat, a light source, an electric power source and an optical assembly. The seat has a baseplate, a sidewall and an end wall. The first end of the sidewall connects to a periphery of the baseplate and forms a chamber with the baseplate, the second end of the sidewall connects to the end wall and forms a receiving space with the end wall. The chamber is separated from the receiving space by the sidewall. The light source is disposed in the chamber and attached to a surface of the baseplate. The light source comprises a plurality of LED arrays. The electric power source is disposed in the receiving space and the optical assembly is disposed on the light source. The optical assembly comprises a plurality of first optical members and a plurality of second optical members corresponding to the first optical members. Each one of the first optical members covers one of the LED arrays.

Abstract: The fixing structure includes a first structure part and a second structure part. The first structure part is capable of sleeving over an end of the LED tube lamp and engages with the second structure part. The first structure part includes: a receiving opening capable of being inserted by the end of the LED tube lamp; a position through hole penetrating a back wall of the receiving opening, an area of the position through hole on the back wall being smaller than an area of the bottom wall of the receiving opening, the position through hole capable of engaging with a position part on the end of the LED tube lamp; at least two pins disposed on an outer surface of the back wall; and two convex walls disposed on two opposite outer surfaces of the first structure part. Each of the convex wall forms a coupling structure with the first structure part. The second structure part includes a first wall, a second wall, a third wall and a fourth wall.

Abstract: A set of adversarial training examples for training a query interpreter are generated by: obtaining a target data table for a natural language query; identifying a primary entity of the target data table; for a target domain of the target data table, generating a set of candidate identifiers that are each semantically associated with an identifier of the target domain; for each candidate identifier, providing a premise-hypothesis pair to an NLI model to generate an entailment score; selecting a first subset of candidate identifiers from among the set of candidate identifiers based on the entailment score generated for each premise-hypothesis pair; for each candidate identifier of the first subset, applying the candidate identifier to an instance of the target data table as a table perturbation to generate a perturbed data table; and outputting each perturbed data table as part of an adversarial training example.

Abstract: The LED lighting device includes a seat comprising a baseplate and a sidewall, the sidewall forming a chamber with the baseplate; a light source disposed in the chamber and attached to a surface of the baseplate, the light source comprising a plurality of LED arrays; an electric power source disposed in the chamber and electrically connecting to the light source and an optical assembly disposed on the light source. The optical assembly comprises an optical unit and an installing unit, the installing unit connects to the periphery of the optical unit, wherein the optical unit comprises a plurality of first optical members and a plurality of second optical members, one of the first optical members covers one of the LED arrays and the second optical members interposed between two adjacent first optical members.

Abstract: According to implementations of the subject matter described herein, there is proposed a solution for automatic analysis of a difference between multi-dimensional datasets. In this solution, an analysis request is received for a first dataset and a second dataset, each of which including data items corresponding to a plurality of dimensions. In response to the analysis request, data items corresponding to a first dimension in the first and second datasets are compared. Based on the comparison, a first set of influence factors associated with the first dimension are determined, each influence factor indicating a reason for a difference between the first and second datasets from a respective perspective. An analysis result related to the difference between the first and second datasets is presented based on the first set of influence factors. In this way, it is possible to achieve automatic and efficient analysis of the difference between the different datasets.

Abstract: A solution for spreadsheet table transformation is provided. In this solution, one or more header areas and a data area of a spreadsheet table are detected. A hierarchical structure of each of the header areas is determined by analysis of cell merging and/or indents in the header area, and/or a function relationship between data items in corresponding cells of the data area. The spreadsheet table can be transformed to a relational table based on recognition of the hierarchical structure of the header area. In this way, by facilitating understanding of header structures based on the header hierarchy, it is possible to achieve automated transformation from spreadsheet tables to relational tables.

Abstract: The present disclosure relates to systems, methods, and computer-readable media for training and implementing pipeline error detection models to facilitate automated detection of data quality (DQ) issues within recurring data pipelines. For example, systems described herein involve training a pipeline error detection model by first constructing a plurality of DQ constraints for a recurring data pipeline based on ranges of values observed over a history of pipeline executions. The systems may further train the model to predict DQ issues by synthetically applying data variants to historical executions of the recurring data pipeline or to data pipelines having similar characteristics thereto. Once trained, the pipeline error detection model(s) can be applied to new executions of the data pipeline as they become available to quickly and efficiently predict whether a given execution includes a predicted DQ issue therein.

Abstract: A computing apparatus of an insight interfacing system receives from a user a request for a dataset comprising a plurality of subspaces of a multi-dimensional data structure. Insights are received based on the received request then presented on a display device. Also, a chart may be presented based on the received request. The computing apparatus receives a selection of at least a portion of the presented one or more insights or a portion of the chart, then receives contextual insights based on the selected portion and presents the contextual insights on the display device.

Abstract: Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights form the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance. Insights include those having multiple pipelined attributes and other insights include multiple insights identified as having some relationship for the included insights.

Abstract: An LED lighting device includes a seat, an optical assembly and a light source, according to one embodiment of the present invention. The seat has a baseplate and a sidewall. A chamber is formed between the baseplate and the sidewall. The optical assembly completely covers a light-emitting side of the LED lighting device. The light source is disposed in the chamber of the seat and includes multiple LED arrays. Each of the LED arrays includes an LED chip. The optical assembly includes an optical unit. The optical unit includes multiple first optical members and multiple second optical members corresponding to the first optical members. The LED arrays correspond to the first optical members. Each of the second optical members includes a set of optical walls. The set of optical walls surrounds one of the first optical members.

Abstract: In accordance with the implementations of the subject matter described herein, there is provided a solution for reusing infographics. In this solution, a group of visual element units is determined from a visual element set comprised in the original infographic. A visual element unit in the group represents an information item in the original infographic. A first correlation between a visual element contained in the visual element unit and the information item and a second correlation between the visual element unit and a further visual element unit in the group are determined. A description for the original infographic is generated based on the first and second correlations. A target infographic is generated by updating the group of visual element units at least based on the description and the target information. In this way, infographics can be converted into reusable templates, thereby simplifying reuse of such infographics and improving user experience.

Abstract: Embodiments of the present invention disclose a key exchange method and apparatus. A network device acquires a first key, and sends a message including the first key to a second user equipment, so that the second user equipment uses, when communicating with a first user equipment by using a D2D link, the first key to protect transmitted information.

Abstract: The present invention provides an LED illumination device, including: a light source carrier including a base, an accommodating space formed on the base; a light emitting unit including a light emitter and a lamp board fixed to the light source carrier; and an optical member covering or at least partially covering the light emitting unit. The light emitting unit and the optical member are both disposed in the accommodating space. The optical member includes a first light distribution unit and a second light distribution unit. At least 70% of a luminous flux generated by the light emitter in operation is directly emitted from the LED illumination device through the second light distribution unit.

Abstract: According to implementations of the subject matter described herein, there is provided a solution for automatic recommendation of analysis for a dataset. In this solution, dimension feature information of dimensions of a dataset and operation feature information of candidate analysis operations are extracted. Respective metrics of candidate combinations of the dimensions and candidate analysis operations being suitable for defining an analysis pattern for the dataset are determined based on the dimension and operation feature information. The analysis pattern comprises at least one dimension to be analyzed and at least one analysis operation to be performed on the at least one dimension. A recommendation on an analysis pattern for the dataset is provided based on the determined respective metrics, to indicate a candidate combination. In this way, it is possible to assess and provide a suitable analysis pattern for a given dataset, thereby facilitating quick completion of the data analysis task.

Abstract: According to implementations of the subject matter described herein, there is proposed a solution for automatic analysis of a difference between multi-dimensional datasets. In this solution, an analysis request is received for a first dataset and a second dataset, each of which including data items corresponding to a plurality of dimensions. In response to the analysis request, data items corresponding to a first dimension in the first and second datasets are compared. Based on the comparison, a first set of influence factors associated with the first dimension are determined, each influence factor indicating a reason for a difference between the first and second datasets from a respective perspective. An analysis result related to the difference between the first and second datasets is presented based on the first set of influence factors. In this way, it is possible to achieve automatic and efficient analysis of the difference between the different datasets.