Abstract: A security device that can be activated or deactivated on the interior side of a door or window or other passageway barricade, and that can be activated or deactivated on the exterior side of the door with a special mechanism, such as a key, tool, transmitter, etc. The security device may be mounted to the hinge-side of a door, the knob-side of a door or in a scenario that includes a non-mullion double door, to the two adjoining portions of the doors at the middle joint.

Abstract: A security device that can be activated or deactivated on the interior side of a door or window or other passageway barricade, and that can be activated or deactivated on the exterior side of the door with a special mechanism, such as a key, tool, transmitter, etc. The security device may be mounted to the hinge-side of a door, the knob-side of a door or in a scenario that includes a non-mullion double door, to the two adjoining portions of the doors at the middle joint.

Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.

Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.

Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.

Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.

Abstract: A drone which can be piloted autonomously or by a user. The drone has an air treatment dispenser for spraying, or otherwise treating, a target area with one or more desired air treatments. The drone may operate as deemed desirable by a user, upon a predetermined schedule or in response to a demand signal from one or more target areas. By delivering the air treatments from an elevated position, the target area can be more uniformly and efficiently treated.

Abstract: The present disclosure relates generally to a data enrichment service that extracts, repairs, and enriches datasets, resulting in more precise entity resolution and correlation for purposes of subsequent indexing and clustering. As the data enrichment service can include a visual recommendation engine and language for performing large-scale data preparation, repair, and enrichment of heterogeneous datasets. This enables the user to select and see how the recommended enrichments (e.g., transformations and repairs) will affect the user's data and make adjustments as needed. The data enrichment service can receive feedback from users through a user interface and can filter recommendations based on the user feedback.

Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.

Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.

Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.

Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.

Abstract: The present disclosure relates to a cleaning article that includes at least two sheets and an adhesive. Each of the at least two sheets has a first layer having melamine-formaldehyde foam. Each of the at least two sheets has at least five sides, each of which has a length and a width. At least one of the three sides is a sheet attachment side. The adhesive is in contact with the sheet attachment side of each of the at least two sheets such that each of the at least two sheets is removably attached to the cleaning article by the adhesive. The adhesive is discontinuous along the length of the sheet attachment side of each of the at least two sheets. Additionally, the present disclosure encompasses methods for cleaning hard surfaces with a cleaning article according to the present disclosure.

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

Abstract: A spirometer for correlating test results with other user date to indicate a relationship, said spirometer comprising: (a) a processor; (b) memory operatively connected to said processor and configured with instruction to instruct the processor to perform the following steps: (i) recording spirometer results of a user; (ii) correlating said results with user data, said user data comprising at least one of a medication log, a medical diary, a baseline performance for said user provided by a healthcare provider, or other results from other testing devices; and (iii) indicating a relationship between said results and said user data.