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 subject matter described herein relates to table detection in a spreadsheet. According to implementations of the subject matter described herein, there is proposed a solution for determining a table in a spreadsheet. In the solution, respective multiple attributes of multiple cells comprised in the spreadsheet may be extracted. Respective features of the multiple cells may be determined based on the extracted multiple attributes. The multiple cells may be divided into at least one candidate area based on the features. At least one candidate table in the spreadsheet may be determined based on the at least one candidate area. By means of the solution, respective features of the multiple cells comprised in the spreadsheet may be determined based on the respective attributes of the multiple cells, and further, a candidate region where a table might exist may be determined based on the respective features of the multiple cells.

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 from 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: A method of controlling an extreme ultraviolet (EUV) lithography system is disclosed. The method includes irradiating a target droplet with EUV radiation, detecting EUV radiation reflected by the target droplet, determining aberration of the detected EUV radiation, determining a Zernike polynomial corresponding to the aberration, and performing a corrective action to reduce a shift in Zernike coefficients of the Zernike polynomial.

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 system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time.

Abstract: The subject matter described herein relates to table detection in a spreadsheet. According to implementations of the subject matter described herein, there is proposed a solution for determining a table in a spreadsheet. In the solution, respective multiple attributes of multiple cells comprised in the spreadsheet may be extracted. Respective features of the multiple cells may be determined based on the extracted multiple attributes. The multiple cells may be divided into at least one candidate area based on the features. At least one candidate table in the spreadsheet may be determined based on the at least one candidate area. By means of the solution, respective features of the multiple cells comprised in the spreadsheet may be determined based on the respective attributes of the multiple cells, and further, a candidate region where a table might exist may be determined based on the respective features of the multiple cells.

Abstract: A method of controlling an extreme ultraviolet (EUV) lithography system is disclosed. The method includes irradiating a target droplet with EUV radiation, detecting EUV radiation reflected by the target droplet, determining aberration of the detected EUV radiation, determining a Zernike polynomial corresponding to the aberration, and performing a corrective action to reduce a shift in Zernike coefficients of the Zernike polynomial.

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: According to an embodiment, an apparatus and method for generating distribution information may include periodically generating GNSS information including GNSS positioning information and a positioning time, generating image information including an image of at least one or more facility object, at the positioning time, while a vehicle drives, obtaining precise positioning information for a capturing position at the positioning time based on the image information, a high-definition map, and the GNSS information, calculating a positioning difference which is a difference between the GNSS positioning information and the precise positioning information, and generating distribution information including the GNSS information, the positioning difference, and the precise positioning information. The high-definition map includes information for feature point spatial coordinates and a property for each facility object.

Abstract: According to implementations of the present disclosure, there is provided a solution for auto-formatting of a data table. A computer-implemented method comprises obtaining values of at least one attribute for a plurality of cells in a data table, the values of the at least one attribute indicating at least one of a semantic meaning of data filled in the cells or a structure of the data table, the cells being arranged in rows and columns in the data table; extracting a feature representation of the values of the at least one attribute In using a first learning network; and determining respective formats for the cells based on the feature representation using at least the first learning network. In this way, it is possible to implement automatic mapping from attribute settings of cells to cell formats by using a learning network, thereby achieving auto-formatting of the data table.

Abstract: A method of controlling an extreme ultraviolet (EUV) lithography system is disclosed. The method includes irradiating a target droplet with EUV radiation, detecting EUV radiation reflected by the target droplet, determining aberration of the detected EUV radiation, determining a Zernike polynomial corresponding to the aberration, and performing a corrective action to reduce a shift in Zernike coefficients of the Zernike polynomial.

Abstract: According to an embodiment, an apparatus for precise position correction using a positioning difference comprises a first distribution information obtaining unit gathering first distribution information from an external terminal, a global navigation satellite system (GNSS) receiver obtaining a GNSS positioning value of the apparatus based on a GNSS, and a positioning correcting unit obtain a corrected location of the apparatus by correcting the GNSS positioning value using the gathered first distribution information. The first distribution information includes a GNSS positioning value of the external terminal, a GNSS positioning time, a precise positioning value, and a positioning difference between the GNSS positioning value and the precise positioning value.

Abstract: The subject matter described herein relates to table detection in a spreadsheet. According to implementations of the subject matter described herein, there is proposed a solution for determining a table in a spreadsheet. In the solution, respective multiple attributes of multiple cells comprised in the spreadsheet may be extracted. Respective features of the multiple cells may be determined based on the extracted multiple attributes. The multiple cells may be divided into at least one candidate area based on the features. At least one candidate table in the spreadsheet may be determined based on the at least one candidate area. By means of the solution, respective features of the multiple cells comprised in the spreadsheet may be determined based on the respective attributes of the multiple cells, and further, a candidate region where a table might exist may be determined based on the respective features of the multiple cells.

Abstract: According to an embodiment, an apparatus and method for generating distribution information may include periodically generating GNSS information including GNSS positioning information and a positioning time, generating image information including an image of at least one or more facility object, at the positioning time, while a vehicle drives, obtaining precise positioning information for a capturing position at the positioning time based on the image information, a high-definition map, and the GNSS information, calculating a positioning difference which is a difference between the GNSS positioning information and the precise positioning information, and generating distribution information including the GNSS information, the positioning difference, and the precise positioning information. The high-definition map includes information for feature point spatial coordinates and a property for each facility object.

Abstract: According to an embodiment, an apparatus for precise position correction using a positioning difference comprises a first distribution information obtaining unit gathering first distribution information from an external terminal, a global navigation satellite system (GNSS) receiver obtaining a GNSS positioning value of the apparatus based on a GNSS, and a positioning correcting unit obtain a corrected location of the apparatus by correcting the GNSS positioning value using the gathered first distribution information. The first distribution information includes a GNSS positioning value of the external terminal, a GNSS positioning time, a precise positioning value, and a positioning difference between the GNSS positioning value and the precise positioning value.

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 from 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: 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: 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 from 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: 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.