A device for determining normalized occupancy of one or more spaces in a building is disclosed. The device includes a memory and a processor coupled to the memory. The processor is configured to: poll one or more people counting sensors associated with access points to a defined region of the building to obtain counts data from the one or more people counting sensors for a specified time period and historical calibration data for the one or more people counting sensors; and process the counts data and the historical calibration data to determine a normalized occupancy of the defined region during the specified time period.

A system and method for processing data by accessing data sets for a plurality of variables in at least one data store; associating a plurality of the data sets as at least one variable type; storing in a data store a plurality of operation definitions defining a plurality of operations on at least one of said at least one variable type; receiving from a user interface a selection of at least one operation definition and at least one data set of said at least one variable type operated on by the selected at least one operation definition; and processing the at least one data set in response to the selection according to the at least one operation definition to generate a derived data set.

There is provided a method of using a bitmap filter to filter a data source as part of a join operation. A set bit at a bit location of the bitmap filter is associated with an entry of the data source that comprises an identifier that matches a filter parameter. A row identifier of a row in another data source that corresponds to the identifier is determined based on a sum of a number of bits set in bit locations that are between the bit location of the set bit associated with the entry of the data source and a bit location in the bitmap filter corresponding to a different, known, row identifier of a different row in the another data source. The row of the another data source corresponding to the determined row identifier is interrogated to obtain information defining the identifier that matches the filter parameter.

Introduced here are various embodiments for selectively assigning a query to an expert. A network-accessible server system may receive a query from a client device indicating a question or project proposal. The query text may be parsed and attributes of the query may be determined by inspecting the parsed query text. The query attributes may be compared with attributes associated with a pool of experts with various specialties and expertise in various fields. The network-accessible server system may match the query attributes with attributes associated with a first expert with a similarity that exceeds a threshold similarity level to identify that an expertise of the first expert matches the requested expertise in the query. The first expert may be assigned to the query and prompted to provide a response to the query.

A search query relating to a search for people and including one or more search terms is received. A search graph for the search is created from a previously created graph which is a directional graph in which people are represented by nodes and content is represented by nodes or edges. The search graph is generated by filtering out nodes or edges that represent content that is determined not to be relevant to the search terms in the search query; and, for the remaining content that is determined to be relevant to the search terms in the search query, adding to the graph a measure of the relevance of the content to the search terms. The search results are generated by operating on the search graph to identify people in the search graph who are sources of content that is relevant to the search terms.

Apparatus and methods are disclosed herein for remote, direct memory access (RDMA) technology that enables direct memory access from one host computer memory to another host computer memory over a physical or virtual computer network according to a number of different RDMA protocols. In one example, a method includes receiving remote direct memory access (RDMA) packets via a network adapter, deriving a protocol index identifying an RDMA protocol used to encode data for an RDMA transaction associated with the RDMA packets, applying the protocol index to a generate RDMA commands from header information in at least one of the received RDMA packets, and performing an RDMA operation using the RDMA commands.

Provided are a machine learning system and method, an integration server, an information processing apparatus, a program, and an inference model creation method capable of suppressing a variation in learning data in federated learning and suppressing a variation in an inference accuracy of a model. The integration server receives an input that designates a data search condition and transmits the designated search condition to a plurality of client terminals. Each client terminal performs searching within a medical institution system to which each terminal belongs and transmits a totalization result of the number of pieces of data that matches the search condition to the integration server. The integration server receives an input that designates the required number of pieces of learning data and distributes the number of pieces of learning data used for learning on each client terminal based on the designated required number and on the received totalization result. The client terminal executes machine learning of a local model to be trained using the data in the medical institution system according to the designated type and number of pieces of learning data and transmits the learning result to the integration server. The integration server integrates the received learning results to update a master model.

Technologies are described herein for executing queries expressed with reference to a structured query language against unstructured data. A user issues a structured query through a traditional structured data management (“SDM”) application. Upon receiving the structured query, an SDM driver analyzes the structured query and extracts a data structure from the unstructured data, if necessary. The structured query is then converted to an unstructured query based on the extracted data structure. The converted unstructured query may then be executed against the unstructured data. Results from the query are reorganized into structured data utilizing the extracted data structure and are then presented to the user through the SDM application.

Methods, systems, and computer-readable media for query language interoperability in a graph database are disclosed. Data elements are inserted into a graph database using one or more of a plurality of graph database query languages. The graph database query languages comprise a first graph database query language associated with a first data model and a second graph database query language associated with a second data model. The data elements are stored in the graph database using an internal data model that differs from the first and second data models. One or more of the data elements are retrieved from the graph database based at least in part on a query. The query is expressed using a different graph database query language than the graph database query language used to insert the one or more retrieved data elements.

Techniques are described herein for providing search features within a carousel. A request may be received to display a network page (e.g., a user profile page). The carousel may present a subset of items of a set of items (e.g., items associated with the user profile). User input indicating a scrolling action within the carousel can be received. In response, a user interface (UI) element associated with conducting a search may be presented in an expanded form overlaid atop the carousel. After a predefined period of time has elapsed, the UI element may transition to a collapsed form. If the UI element is selected, the user may be navigated to the end of the carousel where a statically-positioned presentation of the UI element is presented. A search may be conducted from the statically-positioned presentation. The search may be performed against the set of items associated with the user profile.