A system for managing a web application is disclosed. The system is programmed to enable graphically building a web application having one webpage with multiple views, where a view can have multiple sections and can contain a section from another view. The web application includes a hierarchical structure of nodes respectfully for generating the multiple views. Each node can be accessed separately and each node can reference certain other nodes.
Computing systems methods, and non-transitory storage media are provided for receiving a monitoring request. The monitoring request includes one or more entities or attributes to be monitored, one or more rules to be evaluated with respect to the entities or attributes, and one or more downstream actions to be selectively triggered based on the evaluation. Next, data regarding the entities or the attributes is obtained. Next, a log is generated. The log includes changes or updates, relative to a previous iteration, of the entities or the attributes. The changes or updates correspond to the rules. Next, the changes or the updates are evaluated against the one or more rules and based on the log. Next, one or more actions are selectively implemented based on the evaluation of the changes or the updates.
A computing system and methods are provided for georeferencing stabilization. An exemplary method includes: obtaining a video stream capturing an area from a camera of a drone, where the video stream includes a plurality of frames, each including a field of view of the image capturing device and metadata of the image capturing device when the frame is captured; constructing a geographic (geo) lattice for the field of view in each of the plurality of frames, the geo lattice comprises a plurality of points, each being associated with raw coordinates determined based on the corresponding metadata; and building a lattice map with stabilized geo coordinates by (1) aligning the frames, (2) averaging the raw geo coordinates for given intersection points, and (3) building the lattice map based on the averaged geo coordinates of the intersection points.
H04N 23/68 - Control of cameras or camera modules for stable pick-up of the scene, e.g. compensating for camera body vibrations
B64C 39/02 - Aircraft not otherwise provided for characterised by special use
B64U 101/30 - UAVs specially adapted for particular uses or applications for imaging, photography or videography
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06T 7/35 - Determination of transform parameters for the alignment of images, i.e. image registration using statistical methods
A computing system generates user interface data renderable to display an interactive graphical user interface including a cell-based grid having a first axis and a second axis. The first axis corresponds to one or more assets. The second axis corresponds to one or more time periods. The cell-based grid comprises a plurality of cells indicating values of the one or more assets for the one or more time periods. The interactive graphical user interface displays information relating to the value indicated in the selected cell responsive to a user selection.
Systems and methods are disclosed herein for reducing a risk of associating with a client that may engage in illegal activity. A system accesses data associated with an entity for a given context, applies a plurality of AI models to the data based on the context to generate a plurality of AI assessments. Data for showing risk factors, assessments of the risk factors, and data for evaluating risk factors can be transmitted for rendering in a user interface in a display device. Analyst feedback can be received and used to update the AI models.
Various systems and methods are provided that display various geographic maps and depth graphs in an interactive user interface in substantially real-time in response to input from a user in order to determine information related to measured data points, depth levels, and geological layers and provide the determined information to the user in the interactive user interface. For example, a computing device may be configured to retrieve data from one or more databases and generate one or more interactive user interfaces. The one or more interactive user interfaces may display the retrieved data in a geographic map, a heat map, a cross-plot graph, or one or more depth graphs. The user interface may be interactive in that a user may manipulate any of the graphs to identify trends or current or future issues.
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
G06F 3/04842 - Selection of displayed objects or displayed text elements
A system is described for controlling access to resources using an object model. Users can specify use cases for accessing resources. The user may be granted access if the user satisfies qualifications required for accessing the resource, selected a use case permissible for accessing the resource, and satisfies qualifications required for the use case. Use cases, qualifications, resources, and/or links between them can be implemented using an object model. The system can be used in addition to authentication and authorization.
Computing systems methods, and non-transitory storage media are provided for receiving a first representation of an unstructured data entity. The first representation includes an indication of a detection. The unstructured data entity is part of a corpus. Next, second representations of the unstructured data entity are received and resolved according to a consensus. Next, any discrepancies between the first representation and the resolved second representations are determined. The any discrepancies include any difference in an existence or an absence of the detection, in a relative position of the detection, or in a type or a classification of the detection. Next, feedback regarding the any discrepancy is received. Next, the first representation is selectively modified, or selectively prompted to be modified, based on the any discrepancy and the feedback.
A system for managing firewall rules between different services. In certain instances, the method includes receiving a discovery graph comprising a plurality of services and at least one application programming interface (API) dependency, wherein the plurality of services comprises a first service and a second service. In some instances, the method further includes determining whether the second service is permitted to receive an initial communication from the first service based upon the at least one API dependency included in the discovery graph. And, in response to determining the second service is permitted to receive the initial communication from the first service, the method can include establishing a first rule for a firewall between the first service and the second service, the first rule allowing the second service to receive the initial communication from the first service.
A method of persisting results of executing search queries across multiple data sources comprises obtaining a first data object as a result of executing a first search query against one or more data sources of a plurality of heterogeneous data sources; receiving a first request to store the first data object in a repository, a specific data source of the one or more data sources and the repository having different data models; determining that a repository data object with which the first data object resolves does not exist; generating a specific repository data object as a stub data object for the first data object, comprising: creating a unique identifier based on one or more data object properties that uniquely identify the first data object; and utilizing the unique identifier in the repository as a key or index value for the specific repository data object; storing the specific repository data object.
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 16/9535 - Search customisation based on user profiles and personalisation
In some examples, systems and methods for managing cloud resources (e.g., distributed resources) are provided. For example, a method includes: receiving a request to create a data bucket from a client application, the request including a bucket template; generating a cryptographic key for the data bucket; generating the data bucket in a cloud platform based at least in part on the bucket template; associating the cryptographic key to the generated data bucket; generating metadata associated with the generated data bucket; and providing the metadata associated with the generated data bucket to the client application.
Systems and methods for georegistration are provided. An example method includes receiving a video stream including a plurality of video frames collected by an image sensor, presenting the video stream via a video player, and receiving user input associated with a first video frame of the plurality of video frames and a reference image. In some examples, the first video frame includes incomplete telemetry data. In some examples, the method further includes determining one or more coordinates associated with the first video frame based on user input associated with the first video frame and the reference image, determining the incomplete telemetry data associated with the first video frame based on the one or more determined coordinates, and generating a georegistration transform based on the determined telemetry data and the reference image.
G06V 10/24 - Aligning, centring, orientation detection or correction of the image
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
Systems and methods for georegistration are provided. An example method includes receiving a video stream including a plurality of video frames collected by an image sensor, presenting the video stream via a video player, and receiving user input associated with a first video frame of the plurality of video frames and a reference image. In some examples, the first video frame includes incomplete telemetry data. In some examples, the method further includes determining one or more coordinates associated with the first video frame based on user input associated with the first video frame and the reference image, determining the incomplete telemetry data associated with the first video frame based on the one or more determined coordinates, and generating a georegistration transform based on the determined telemetry data and the reference image.
Systems and methods for analyzing data stored using a data model. The system can receive a user selection of a first object type indicating to perform filtering operations on a first set of data objects, generate a list of object types linked to the first object type based on an ontology, receives a user selection of a second object type, generate a list of properties of the second object type based on an ontology, receive a user selection of a first property from the list of properties, perform a data query determining values associated with the first property, receive a user selection of a first value, and displays information of a subset of data objects being a portion of the first set of data objects that are linked to data objects in the second set of data objects that have a first property value of the first value.
Systems and methods for data propagation and mapping are provided. In an aspect, one or more data entries storing changed information in a first database using a first storage format are identified. The identified data entries are received by the data propagation and mapping system. The received data entries may be filtered to generate a subset of filtered data entries. The filtered data entries are transmitted to a mapping pipeline configured to map a data entry stored in the first storage format to a data entry stored in a second storage format. The mapped data entries are transmitted to a recipient second database storing data entries using the second storage format.
A computer system can receive one or more edits to be made to a canonical dataset and can temporarily store the one or more edits in a buffer. In response to receipt of a query of the canonical dataset, the computer system can rewrite the query to read from the canonical dataset and the buffer; combine the one or more edits from the buffer with the canonical dataset to form a combined dataset based on resolution policies to avoid conflicts between data; rewrite the query to execute on the combined dataset in lieu of the canonical dataset to optimize query performance; and execute the query on the combined dataset.
A pipeline task verification method and system is disclosed, and may use one or more processors. The method may comprise providing a data processing pipeline specification, wherein the data processing pipeline specification defines a plurality of data elements of a data processing pipeline. The method may further comprise identifying from the data processing pipeline specification one or more tasks defining a relationship between a first data element and a second data element. The method may further comprise receiving for a given task one or more data processing elements intended to receive the first data element and to produce the second data element. The method may further comprise verifying that the received one or more data processing elements receive the first data element and produce the second data element according to the defined relationship.
Computing systems methods, and non-transitory storage media are provided for obtaining images, extracting layers from each of the images, extracting segments from each of the layers, generating a compressed version of the segments by storing a single copy of each segment and metadata to reconstruct the layers from the segments and the images from the layers, and simulating a reconstruction of the image from the compressed version.
A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.
An example method of enforcing granular access policy for embedded artifacts comprises: detecting an association of an embedded artifact with a resource container; associating the embedded artifact with at least a subset of an access control policy associated with the resource container; and responsive to receiving an access request to access the embedded artifact, applying the access control policy associated with the resource container for determining whether the access request is grantable.
A computer-implemented method enforces data security constraints in a data pipeline. The data pipeline takes one or more source datasets as input and performs one or more data transformations on them. The method includes using data defining one or more data security constraints to configure the data pipeline to perform a data transformation on a restricted subset of entries of the source datasets. The restriction is defined by the data defining one or more data security constraints. The method further includes performing the data transformation according to the configuration to produce one or more transformed datasets. The method further includes using the data defining one or more data security constraints to perform a verification on one or more of the transformed datasets to ensure that entries in the one or more of the transformed datasets are restricted as defined by the one or more data security constraints.
An artificial intelligence system can be used to respond to natural language inputs (e.g., user submitted inputs) where the response involves a data processing workflow involving language models. The artificial intelligence system can use “profiles” associated with a user, role, cohort, and/or organization to bring additional operational context into user interactions within the artificial intelligence system.
A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.
H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
Computer-implemented systems and methods are disclosed, including for evaluation of computer-based models in a management framework. A computer-implemented method may include, for example, receiving one or more inputs including requesting to add an evaluation configuration to a defined modeling objective, specifying at least a first evaluation data set for the evaluation configuration, specifying at least a first evaluation library for the evaluation configuration, and specifying at least a first subset definition for the evaluation configuration. A computer-implemented method may in response to the one or more user inputs include: creating, storing, and/or updating the evaluation configuration. A computer-implemented method may include evaluating, based on the evaluation configuration, the one or more models associated with the defined modeling objective.
One or more virtual machines are launched at an application platform. At each of the one or more virtual machines, a machine learning model execution environment is instantiated for an instance of a machine learning model. A respective instance of the machine learning model is loaded to each machine learning model execution environment. Each loaded instance of the machine learning model is associated with an application programming interface (API) endpoint which can receive input data for the loaded instance of the machine learning model from a client device and return output data produced by the loaded instance of the machine learning model based on the input data.
Systems and methods are provided for data migration. The system may comprise one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to migrate at least one first table of a first database schema to at least one second table of a second database schema, determine a query for modifying the first table during the migration, modify the second table based at least in part on the query, and update a mutation table to describe the modification, wherein the mutation table at least describes the modification.
This disclosure relates to a system and method for data analysis. According to a first aspect, there is described a method, the method being performed using one or more processors, comprising: receiving one or more user inputs indicative of one or more relationships between data in a plurality of datasets; determining, based on the one or more user inputs, at least one object view for visualizing the data in the plurality of datasets; generating, based on the one or more user inputs, metadata comprising: an object graph indicative of the one or more relationships between two or more of the plurality of datasets; and information identifying the at least one object view; and in response to a query relating to the plurality of datasets, using the metadata to determine how response data responding to the query should be provided.
Systems, methods, and non-transitory computer readable media are provided for recursively searching a plurality of workspaces of the system for linked data associated with the seed data, initiating an endpoint process for each the seed data and the linked data, and, upon completion of the search, delete the seed data and the linked data identified based at least in part on the endpoint process. The process may be automatically repeated at a predetermined time interval to identify and remove future data that is stored in the plurality of datasets.
A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.
Systems and methods for generating, managing, and/or providing notifications are provided. In some embodiments, a method includes displaying a map corresponding to a map security level to a user, receiving an indication of a geospatial area on the map, receiving a data stream, the data stream corresponds to a data security level, determining if the data security level satisfies a first security level threshold, in response to determining that the data security level satisfies the first security level threshold, in response to detecting the entity that satisfies the notification condition, generating a geospatial notification including information representing the geospatial area and the entity, determining if a user security level for the user satisfies a second security level threshold, and in response to determining that the user security level satisfies the second security level threshold, presenting the geospatial notification to the user.
A system may receive a natural language query. A system may receive indications of one or more data object types, wherein each of the one or more data object types is associated with a respective one or more properties. A system may receive references to one or more data sets, wherein the one or more data sets are each associated with at least a respective data object type. A system may transmit a prompt to a large language model (“LLM”), the prompt comprising at least: the natural language query, the indications of the one or more data object types, and the references to the one or more data sets. A system may receive, from the LLM, a response to the prompt, wherein the response includes indications of: at least a first reference to a first data set and a query to be applied to the first data set.
Computer-implemented systems and methods are disclosed, including for integration and management of computer-based models in a model management. A computer-implemented method may include, for example, receiving one or more inputs including requesting to add a first model to a defined modeling objective, specifying a first model location, and/or providing a first model adapter configuration. In response to the one or more user inputs, the method may further include storing or providing access to information associated with the first model, associating the first model with a defined modeling objective, and/or implementing the first model adapter configuration to provide communication with the first model.
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
34.
SECURING LARGE LANGUAGE MODEL OUTPUT BY PROPAGATING PERMISSIONS
Computer-implemented systems and methods are disclosed, including for determining permissions for nondeterministic model output. A computer-implemented method may include, for example, receiving one or more user inputs including a first user input providing at least a portion of a first prompt for a query for a first nondeterministic model. A computer-implemented method may in response to receiving the one or more user inputs include: executing the query, by the first nondeterministic model, to generate an output, determining a first one or more data inputs used by the first nondeterministic model during execution of the query, determining a first set of permissions associated with the first one or more data inputs; and applying a second set of permissions to at least a first portion of the output based on the first set of permissions.
The disclosure is directed to methods and systems for improving interactions with a Large Language Model (LLM). An artificial intelligence system (AIS) can receive user inputs via a graphical user interface indicating a task to be performed by the LLM, one or more tools which may be accessed by the AIS in response to tool calls from the LLM, and an output schema for structuring a format of a response from the LLM. The AIS can generate a prompt for the LLM based on the user input. The prompt can include indications of the one or more tools, one or more example tool operations, the task to be performed, and an indication of the output schema. The AIS can include a debugging application or module enabling rich debugging of language model interactions in a single view.
Systems and methods for correlating data (e.g., sensor data) with entities and/or tracking entities are provided. In some embodiments, a method includes displaying one or more indications of one or more entities, receiving a first input to select the target entity from the one or more entities, in response to receiving the first input, displaying an interactive element for associating one or more sensors to the target entity, displaying the one or more sensors that are active, receiving a second input associated with the interactive element, in response to receiving the second input, creating a link between the target entity and at least one sensor of the one or more sensors, and updating one or more entity properties of the target entity based on sensor data of the at least one sensor and the created link.
Systems and methods for managing and/or using observation schemas are provided. In some embodiments, a method includes receiving a data stream from one or more data sources; accessing a first observation schema including one or more built-in fields and one or more custom fields associated with the received data stream; receiving a configuration associated with at least one of the one or more custom fields; and generating a second observation schema based on the configuration and the first observation schema.
A method comprises receiving, at a host, a request to set new service configuration information for a target service in a distributed computing environment; retrieving a current revision identifier of a current revision of service configuration information for the target service from a revision index key in a local replica of a configuration store, the revision index key storing one or more key-value pairs, a key in a specific key-value pair identifying the target service; assigning a new revision identifier based on the current revision identifier; writing the new service configuration information into a new revision of the service configuration information in the local replica; updating the revision index key in an atomic compare-and-swap operation, the compare comprising verifying that the current revision identifier in the revision index key has remained the same since the retrieving, the swap comprising updating the specific key-value pair with the new revision identifier.
G06F 9/48 - Program initiatingProgram switching, e.g. by interrupt
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
H04L 41/5054 - Automatic deployment of services triggered by the service manager, e.g. service implementation by automatic configuration of network components
39.
SYSTEMS AND METHODS FOR GENERATING AND MANAGING SECURITY LEVEL-AWARE MAP
Systems and methods for generating and/or managing maps are provided. In some embodiments, a method includes receiving a map request from a first user to generate a map with a map security level, in response to determining that the map security level satisfies the first security level threshold, generating the map with the map security level, receiving a query from the first user, identifying a data feed associated with the query, receiving the data feed from a data source, the data feed including a plurality of data items and each data item corresponding to a corresponding data security level, for each data item of the plurality of data items, determining whether the data item satisfies a second security condition, and adding one or more data items of the plurality of data items that satisfy the second security condition on the map.
A system may receive a natural language query and receive an indication of a format of a first computer language as well as an indication of one or more computer-based tools stored in and/or accessible by the system. The system can transmit a prompt to a large language model (“LLM”). The prompt may include the natural language query, the indication of the format, and the indication of the one or more computer-based tools. The system can receive, from the LLM, a response to the prompt in the format of the first computer language. The system can parse the response in the first computer language to identify at least: a computer-based tool of the one or more computer-based tools. The system can generate a second query in a second computer language and provide the second query in the second computer language to the computer-based tool.
An artificial intelligence system can be used to respond to natural language inputs. The AI System may, for example, receive a first user input for a LLM, generate a first prompt based on the first user input, transmit the first prompt to an LLM, receive an output from the LLM, and evaluate the output from the LLM with reference to one or more validation tests. Responsive to determining that the output from the LLM is not validated, generate a second prompt for the LLM, where the second prompt indicates at least an aspect of the output that caused the output to not be evaluated (e.g., a portion of the output that may need to be updated or corrected), transmit the second prompt to the LLM, and receive an updated output from the LLM. The AI system can include an application for testing functions that utilize interactions with language models.
Methods, apparatuses and computer programs are for executing complex computing tasks in a computing platform are provided. According to one aspect, a method comprises receiving, by a planning agent, a use case input indicating an objective for completion in the computing platform. The planning agent decomposes, by the planning agent, the use case input into a plurality of tasks for achieving the objective. The planning agent provides each of the plurality of tasks to a respective task agent for execution. For each task of the plurality of tasks, the respective task agent identifies a tool suitable for performing the task from a plurality of tools. The task agent uses the identified tool to execute an operation corresponding to the respective task in the computing platform.
A method of contextual modification of data sharing constraints is disclosed. The method comprises receiving a data sharing request to share a first data model with a database associated with a second data model; generating a shareable version of the first data model in response to the data sharing request; determining a parameter value used to perform a data model merging operation to merge the shareable version of the first data model with the second data model, the parameter value indicating whether to execute or skip a particular process during the data model merging operation; determining context data for the data model merging operation based on the generating; modifying the parameter value based on the context data; performing the data model merging operation using the modified parameter value.
G06F 7/14 - Merging, i.e. combining at least two sets of record carriers each arranged in the same ordered sequence to produce a single set having the same ordered sequence
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G06F 16/9535 - Search customisation based on user profiles and personalisation
44.
MACHINE LEARNING AND LANGUAGE MODEL-ASSISTED GEOSPATIAL DATA ANALYSIS AND VISUALIZATION
Methods and systems for site prospecting includes the operations of: receiving a site request indicating a required use for a site; generating a plurality of capacity scores corresponding to a plurality of land parcels using a first machine learning model; filtering the plurality of land parcels into a subset of land parcels based on the plurality of capacity scores; and for at least one land parcel in the subset of land parcels: generating a parcel potential description using a first language model based at least in part on geographic information associated with the at least one land parcel; generating a parcel potential score using a second machine learning model based at least in part on the parcel potential description; and presenting the parcel potential description and the parcel potential score.
G06F 16/387 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
G06F 16/335 - Filtering based on additional data, e.g. user or group profiles
G06F 16/383 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
45.
SYSTEMS AND METHODS FOR CROSS-DOMAIN SOFTWARE PRODUCT AND SOFTWARE PRODUCT METADATA DELIVERY
Systems and methods for software product deployment and/or compliance management are provided. In some embodiments, a method includes: receiving an indication of a first payload of a software deployment package; performing a first software scan of the first payload; generating a first integrity file including an indication of integrity based upon the first software scan; and triggering a transfer of the first payload and the first integrity file from a first network domain to a second network domain different from the first network domain.
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
A computing device, such as a server, has a sealed housing and runs one or more data extraction agents. In some embodiments, the computing device includes one or more processors and memory located inside the sealed housing, the memory stores instructions that when executed by the one or more processors causes the one or more processors to: authenticate with a data recipient system using a prestored security engine and using a shared registration secret uniquely associating the computing device with the data recipient system; retrieve an extraction job specification from an extraction job specification repository associated with the data recipient system; and using the extraction job specification, communicate to one or more client computing devices associated with a client system to extract data records from one or more data stores of the client system. Related methods are also disclosed.
Systems and methods are provided for improved auditing of user actions associated with a software application. The system includes functionality to log user actions in a structured, standardized way. The system includes interactive user interfaces for analyzing the logs. The logging is based on a well-defined categorization of available actions. The log information includes (and distinguishes among) user details, context details, user inputs, and/or system outputs (including identification of data objects). The interactive user interfaces enable a user to view structured log data in an efficient manner, such as by presenting logs in a tabular format, executing queries on the log data, and/or presenting visualizations that summarize the log data. The interactive user interfaces provide functionality that allows a user to investigate and/or audit user interactions with a data object. The interactive interfaces present log entries associated with the object(s) for further review by the reviewer.
A data analysis system presents a user interface to allow a user to provide a natural language query pertaining to a dataset, wherein the dataset is associated with a data object model comprising a plurality of objects and receives, via the user interface, user input specifying the natural language query. The data analysis system further modifies, in the user interface, the user input to visually indicate one or more portions of the natural language query that each represent one of the plurality of objects and presents, in the user interface, a response to the natural language query, the response being based on data from the dataset, the data corresponding to the one of the plurality of objects.
A system may receive a representation of a process, wherein the representation of the process includes: a plurality of states, and one or more transitions among states of the plurality of states. A system may receive a plurality of data objects, wherein each of the data objects is associated with a respective set of properties. A system may determine for each of the plurality of data objects, respective state information associated with the data objects. A system may cause generation of an interactive graphical user interface including: a graph-based visualization of at least a portion of the plurality of states and the one or more transitions, wherein the graph-based visualization is generated based at least in part on at least a portion of the plurality of data objects and associated properties and state information.
A system may receive a representation of a process, wherein the representation of the process includes: a plurality of states, and one or more transitions among states of the plurality of states. A system may receive a plurality of data objects, wherein each of the data objects is associated with a respective set of properties. A system may determine for each of the plurality of data objects, respective state information associated with the data objects. A system may cause generation of an interactive graphical user interface including: a graph-based visualization of at least a portion of the plurality of states and the one or more transitions, wherein the graph-based visualization is generated based at least in part on at least a portion of the plurality of data objects and associated properties and state information.
Systems and methods for visual navigation are provided. An example method includes receiving a plurality of video frames from an image sensor disposed on an aircraft, and generating an image-based transform based on the plurality of video frames. In some examples, the image-based transform is associated with a movement of one or more image features and a movement of the image sensor. In some examples, the method further includes: determining an image-based motion associated with the aircraft based on the image-based transform, generating a georegistration transform based on at least one video frame of the plurality of video frames and a reference image, determining a georegistration-based geolocation associated with the aircraft based on the georegistration transform, and determining an aircraft geolocation by applying a non-linear Kalman filter to the image-based motion and the georegistration-based geolocation,
A system with an interactive user interface for a plurality of users to author an electronic document simultaneously is described. The system displays visual feedback on the interface to prevent the users from interfering with one another. The system displays data from a remote database linked into the document based on unique identifiers. The data is displayed as an “artifact.” The system monitors and tracks each user's access category level, as well as the access category level of each piece of data pulled from the remote database. The system compares a user's category level to the data from the database to make visible only the portions of the document the user has the appropriate access category level to view and/or modify. The portions of the document that have a higher category level than the user will be hidden from the user either in part or completely. Also, there may be an indicator to the user of such redacted or hidden content from the user's viewer.
Systems and methods for visual navigation are provided. An example method includes receiving a plurality of video frames from an image sensor disposed on an aircraft, and generating an image-based transform based on the plurality of video frames. In some examples, the image-based transform is associated with a movement of one or more image features and a movement of the image sensor. In some examples, the method further includes: determining an image-based motion associated with the aircraft based on the image-based transform, generating a georegistration transform based on at least one video frame of the plurality of video frames and a reference image, determining a georegistration-based geolocation associated with the aircraft based on the georegistration transform, and determining an aircraft geolocation by applying a non-linear Kalman filter to the image-based motion and the georegistration-based geolocation.
G06V 20/17 - Terrestrial scenes taken from planes or by drones
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
54.
Display screen or portion thereof with graphical user interface
Systems, methods, and non-transitory computer readable media configured to provide three-dimensional representations of routes. Locations for a planned movement may be obtained. The location information may include tridimensional information of a location. Route information for the planned movement may be obtained. The route information may define a route of one or more entities within the location. A three-dimensional view of the route within the location may be determined based on the location information and the route information. An interface through which the three-dimensional view of the route within the location is accessible may be provided.
In some examples, systems and methods for multiple-sensor object tracking are provided. For example, a method includes: receiving a first sensor feed and a second sensor feed from a plurality of sensors respectively. The first sensor feed includes a set of first images. The second sensor feed includes a set of second images. In some examples, the method further includes generating an image transformation based on at least one first image in the set of first images and at least one second image in the set of second images, applying the image transformation to the set of second images, aggregating the set of first images and the set of transformed second images to generate a set of aggregated images, and applying a multiple object tracking model to the set of aggregated images to identify a plurality of objects.
A method performed by one or more processors comprises displaying code, receiving user selection of a portion of code, determining one or more settable data items, generating a template, displaying the template, receiving a user input value for the settable data items by the template, and executing the code with each of the settable data items set to the received user input value. A data processing pipeline is configured to pass a data item to a first transformer to provide first transformed data, store the first transformed data in a temporary memory, write the first transformed data to the data storage system, and pass the transformed data from the temporary memory to a second transformer.
A computer system provides shared access to electronic data assets. The system may perform operations including: receiving, from a first user, a request to access a shared data asset, wherein: the shared data asset is associated with a shared data asset object, and the shared data asset object identifies at least a second user authorized to approve sharing of the shared data asset; in response to receiving the request from the first user: generating a data access request object including at least an identification of the first user and an identification of the shared data asset object; and providing an indication of the data access request object to the second user associated with the shared data asset object; receiving, from the second user, an approval of the request; and in response to receiving the approval of the request from the second user: granting the first user access to the shared data asset associated with the shared data asset object.
Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for searching a large corpus of data. A computer-implemented method may include: receiving a first user input comprising a natural language query; vectorizing the first user input into a query vector; executing, using the query vector, a similarity search in a document search model to identify one or more similar document portions, where the document search model includes a plurality of vectors corresponding to a plurality of portions of a set of documents; generating a first prompt for a large language model (“LLM”), the first prompt including at least the first user input, and the one or more similar document portions; transmitting the first prompt to the LLM; receiving a first output from the LLM in response to the first prompt; and providing, via a user interface, the first output from the LLM.
A system for indexing changes to an ontology into multiple databases and related methods are disclosed. The system is programmed to receive original data from data sources, transform the original data to ontology data, represent the ontology data in multiple forms respectively in the multiple databases, and process requests to access the ontology data from user accounts using the multiple databases. The system is programmed to subsequently merge changes to the ontology data based on updates from the data sources and edits from user accounts, create index data for the merged changes, and transmit the index data to the multiple databases.
A system for resolving conflicts between data source updates and user edits to an ontology before applying the resulting changes to the ontology and related methods are disclosed. The system is programmed to receive data source updates from data sources and transform the data source updates to updates to ontology data. The system is also programmed to receive edits to ontology data from user accounts. The system is programmed to review these updates or edits to the ontology and resolve conflicts according to a predetermined strategy, such as prioritizing a user edit over a data source update. The resulting changes are incorporated to one or more databases where representations of the ontology data are stored.
A system for enabling granular access control over ontology data and related methods are disclosed. The system is programmed to receive data source updates from data sources having respective sets of permissions for access control, transform the data source updates to changes to an ontology, and control access to the ontology based on the sets of permissions. The system is further programmed to receive a specification of one or more rules referencing attributes of user accounts or properties of ontology entities and corresponding one or more lists of permissions. The system is programmed to then enforce a security policy based on the specification to further control access to the ontology.
Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for generating data objects and/or updating an ontology. A computer-implemented method may include: employing one or more large language models (“LLMs”) to generate at least a data triple and a classified triple; executing, using the classified triple, a similarity search with reference to an ontology to determine that the classified triple at least partially matches one or more data object types defined in the ontology; in response to the determination, adding into a first database at least a first data object of a first data object type that represents a first entity in the data triple and a second data object of a second data object type that represents a second entity in the data triple.
G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
64.
LANGUAGE MODEL-BASED TABULAR DATA OBJECT EXTRACTION AND VISUALIZATION
Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for creating and/or updating an ontology. A computer-implemented method may include: receiving tabular data from one or more data sources; generating an interactive graphical representation of at least a portion of the tabular data and connections between the portion of the tabular data; providing, via a user interface, the interactive graphical representation; receiving a user operation via the user interface, updating an ontology and/or generating transformations for adding data objects into a database.
Disclosed herein is a method of providing feedback to a machine learning model. The method includes allowing a user to observe an output of a trained machine learning model; allowing the user to input feedback to the machine learning model based on the output, wherein the feedback is on at least one of a model level or on a training dataset level; and incorporating the feedback into the machine learning model to improve the machine learning model, wherein the method is performed using one or more processors. Disclosed herein are one or more computer-readable storage media including computer executable instructions which when executed by the one or more processors cause the one or more processors to perform the method. Disclosed herein is a computer system which includes one or more processors and one or more computer-readable storage media which include computer executable instructions which when executed by the one or more processors cause the one or more processors to perform the method.
A plurality of images is obtained, whether as separate images or part of a video. The plurality of images is used to generate a three-dimensional (3D) model of the imagery. The 3D model is registered to a geographic coordinate system as a first registered 3D model. The first registered 3D model is merged with a second registered 3D model to generate a merged 3D model. A request including a value corresponding to a location within the geographic coordinate system that includes at least a portion of the merged 3D model is received from a client device. A message identifying at least a subset of points in the portion of the merged 3D model is sent to the client device, each point in the subset having a three-dimensional coordinate.
Systems and methods are provided for obtaining a request for a data object or a data structure from a client; determining an access level of the client and one or more access permissions of the requested data object or data structure; determining whether to transmit the requested data object or data structure to the client based on the access level of the client and the one or more access permissions; and transmitting the requested data object or data structure to the client.
In some examples, systems and methods for multiple-sensor object tracking are provided. For example, a method includes: receiving a model permission requirement; receiving a training corpus; segmenting the training corpus into a segmented training corpus based at least in part on the model permission requirement; training a machine learning model using the segmented training corpus; and associating the trained machine learning model with the model permission requirement.
In some examples, systems and methods for user-assisted object detection are provided. For example, a method includes: receiving a first image frame in a sequence of image frames, performing object tracking using an object tracker to identify a first object of interest and a second object of interest in the first image frame based at least in part on one or more first templates associated with the first object of interest, one or more second templates associated with the second object of interest, and a spatial relationship between the first object of interest and the second object of interest, outputting a first indicator associated with a first image portion corresponding to the identified first object of interest, and outputting a second indicator associated with a second image portion corresponding to the identified second object of interest.
A package manager used with a containerization platform can organize code portions into immutable layers. Collections of layers can be organized and saved together as an executable unit. Disclosed solutions recognize that because layers do not change, they can be reused by the same user and can also serve as shared building blocks for multiple environments running simultaneously. To facilitate sharing layers, a system can analyze which ones are common to multiple environments and allow multiple simultaneous environments to share common layers. Layer compression and dominator algorithms can be used to address inherent layer constraints. To facilitate use of existing layers for efficient start-up, code packages can be organized into base layers and additional layers, and commonly-used layers can be cached. New or unique environment requests can combine previously-cached base layers and additional layers to avoid redundant calculations. A just-in-time approach can combine layers into new images on the fly and cache the new images for later use.
A data orchestration system can be used to respond to natural language prompts (e.g., user submitted prompts) where the response involves a data processing workflow being executed using one or more data processing services (e.g., microservices of a data processing platform or software). This can provide for execution of data processing workflows (e.g., complex workflows) without a user needing to specify the particular data processing services that are included in the data processing workflows. This can cause new functionality to be available to a user (e.g., to a user who lacks the technical skillset to specify the relevant data processing services without use of the systems and methods disclosed herein), and/or can dramatically reduce the time required to orchestrate the data processing services that are included in the data processing workflows.
Systems and methods including a framework for migration of live data. The method may comprised, by one or more hardware processors executing program instructions, receiving, at a migration proxy of the framework, code for reading data and writing data compatible with each of a plurality of states of a migration of data in a data store, wherein a service is at least intermittently reading data from and writing data to the data store; determining, by a migration runner of the framework, to perform the migration of the data; initiating, by the migration runner, the migration of the data, wherein the migration comprises a plurality of stages; storing, as the migration progresses through the plurality of stages, and at a migration data store of the framework, a current stage of the migration; and during the migration, using the migration proxy to read data from and write data to the data store.
A fuzzy matching system matching data records in one or more data sets based on user-customized selection of multiple fuzzy matching algorithms. Possible matches may be displayed to a user, who provides feedback on the accuracy of the matches, which may then be used by a machine learning algorithm to update weightings and parameters of the multiple fuzzy matching algorithms, such as based on machine learning analysis of the matching results and the user feedback.
A computing system and methods are provided for georeferencing stabilization. An exemplary method includes: obtaining a video stream capturing an area from a camera of a drone, where the video stream includes a plurality of frames, each including a field of view of the image capturing device and metadata of the image capturing device when the frame is captured; constructing a geographic (geo) lattice for the field of view in each of the plurality of frames, the geo lattice comprises a plurality of points, each being associated with raw coordinates determined based on the corresponding metadata; and building a lattice map with stabilized geo coordinates by (1) aligning the frames, (2) averaging the raw geo coordinates for given intersection points, and (3) building the lattice map based on the averaged geo coordinates of the intersection points.
H04N 23/68 - Control of cameras or camera modules for stable pick-up of the scene, e.g. compensating for camera body vibrations
B64C 39/02 - Aircraft not otherwise provided for characterised by special use
B64U 101/30 - UAVs specially adapted for particular uses or applications for imaging, photography or videography
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06T 7/35 - Determination of transform parameters for the alignment of images, i.e. image registration using statistical methods
A system and method for authenticating users of a data processing platform stores a mapping of a unique user platform identifier to multiple user identity provider identifiers associated with multiple realms for a same user. In some examples, the method includes receiving a request from a client device to establish an access session to perform one or more actions on data of the data processing platform and receiving, from at least one of the first external identity provider of the first realm or the second external identity provider of the second realm, a user identity provider identifier associated with the request. In certain examples, the method includes granting permission to perform the one or more actions on the data of the data processing platform based at least in part on the received user identity provider identifier.
The systems, methods, and devices of the present disclosure may provide, among other features, high-performance, interactive geographical and/or data object map capabilities in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. In various embodiments, an interactive geographical map display system may enable rapid and deep analysis of various objects, features, and/or metadata by the user by aggregating and clustering large sets of data into aggregate values and clusters. The user can select various clusters, via the user interface, to interact with the data, clusters, and map.
G06F 16/9537 - Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06F 16/20 - Information retrievalDatabase structures thereforFile system structures therefor of structured data, e.g. relational data
G06F 16/387 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
G06F 16/58 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
G09B 29/00 - MapsPlansChartsDiagrams, e.g. route diagrams
Systems and methods for creating filtered data using graphical methodology. Stored data relationally-linked by an ontology are representable in rows and columns format. The system receives a first input selecting a first data source, displays a portion of the first data source in a first chart, receives a second input identifying a portion of the first chart, generates a first filter based on the identified portion, receives a third input selecting a linked object set, displays an indicator of the linked object set in a second sidebar, displays a portion of the linked object set in a second chart depicting information of the linked object set filtered by the first filter, receives a fourth input identifying a portion of the second chart, generates a second filter based on the identified portion, and displays fields of the linked object set, filtered by the first and second filter, in a third chart.
Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.
In some examples, systems and methods for object tracking are provided. For example, a method includes: receiving an image frame in a sequence of image frames; identifying an object of interest in the image frame using a single-object tracker (SOT) based upon one or more templates associated with the object of interest in a template repository; generating a SOT output based on the identified object of interest; and detecting one or more objects in the image frame using a multiple-object tracker (MOT). In some examples, the MOT including a machine-learning model. In some examples, the method further includes conducting a matching between the SOT output and each detected object of the one or more detected objects to generate a match result; and generating a tracker output based at least in part on the SOT output, the one or more detected objects, and the match result.
A method, performed by one or more processors, includes: receiving an indication of a desired modification to a cybersecurity event detector that is being contemporaneously used for the detection of potential cybersecurity events in a production environment; modifying, in a sandbox environment, the cybersecurity event detector based on the indication of the desired modification to the cybersecurity event detector; and for each system event in a set of system events, determining, in the sandbox environment, whether the respective system event is indicative of a potential cybersecurity event using the modified cybersecurity event detector. Related apparatus are also disclosed.
G06F 21/55 - Detecting local intrusion or implementing counter-measures
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
81.
SYSTEMS AND METHODS FOR OBJECT TRACKING WITH RETARGETING INPUTS
In some examples, systems and methods for user-assisted object detection are provided. For example, a method includes: receiving a first image frame of a sequence of image frames, performing object detection using an object tracker to identify an object of interest in the first image frame, based upon one or more templates associated with the object of interest in a template repository, outputting a first indicator associated with a first image portion corresponding to the identified object of interest, and receiving a user input associated with the object of interest. In some examples, the user input indicates an identified image portion in the image frame. In some examples, the method further includes generating a retargeted template, based at least in part on the identified image portion, and determining a second image portion associated with the object of interest in a second image frame of the sequence of image frames using the object tracker, based at least in part on the retargeted template. In some examples, the second image frame is after the first image frame in the sequence of image frames, and the second image portion is different from the first image portion.
In some examples, systems and methods for user-assisted object detection are provided. For example, a method includes: receiving an input image, and performing object detection by a software detector to identify a set of detected objects. The software detector includes a machine-learning model. The method further includes outputting one or more indicators of the set of detected objects. Each detected object in the set of detected objects is associated with a confidence level. The method further includes receiving a user input; identifying a template including an image portion associated with the user input; determining a similarity metric between the template and an object in the set of detected objects; modifying a confidence level of the object based at least in part on the determined similarity metric; and generating an output including an indicator of the object based at least in part on the modified confidence level.
G06V 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human interventionEvaluation of the quality of the acquired patterns
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
83.
Systems and methods for managing firewall rules and connections between different services
A system for managing firewall rules between different services. In certain instances, the method includes receiving a discovery graph comprising a plurality of services and at least one application programming interface (API) dependency, wherein the plurality of services comprises a first service and a second service. In some instances, the method further includes determining whether the second service is permitted to receive an initial communication from the first service based upon the at least one API dependency included in the discovery graph. And, in response to determining the second service is permitted to receive the initial communication from the first service, the method can include establishing a first rule for a firewall between the first service and the second service, the first rule allowing the second service to receive the initial communication from the first service.
In some embodiments, systems and methods for visualizing one or more datasets include importing a plurality of root objects, each root object including linked data attributes and obtaining a joined dataset based on the plurality of root objects, that includes for each or the plurality of root objects, a plurality of rows of related attribute data linked to each root object as a result of a join operation. The systems and methods perform an aggregation computation on the plurality of rows of related attribute data corresponding to each of the plurality of root objects to produce a corresponding single aggregation row of consolidated data for each root object and present a user interface that shows each of the plurality of root objects with their corresponding single aggregation row of consolidated data resulting from the aggregation computation, in a one-to-one manner.
A system enables analysis of retroactively changing datasets and/or of various versions of logics. In an example, the system determines a first version of data and/or a first version of a logic and a second version of the data and/or a second version of the logic, wherein at least some of the second version of the data was retroactively added. The system determines two outputs each derived from one of a) applying the first version of the logic to the first version of the data, b) applying the second version of the logic to the first version of the data, c) applying the first version of the logic to the second version of the data, or d) applying the second version of the logic to the second version of the data. The system compares the outputs and determines one or more differences between the outputs.
A cryptography administration system facilitates secure, user-friendly and auditable cryptography. The system can generate an encrypted data value from raw data values with a user-selected cryptography algorithm. The encrypted data value can comprise a pointer configured to access a location in storage comprising a cryptography key for decrypting the encrypted data value. The system can generate a license comprising one or more permissions of a user to decrypt the encrypted data value. The system can store the license in the location in storage accessible by the pointer of the encrypted data value.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
G06F 21/10 - Protecting distributed programs or content, e.g. vending or licensing of copyrighted material
Aspects of the present disclosure relate to performing agnostic data integrity checks on source data, and based on the data integrity checks, generating a human-readable report that may be useable to identify specific errors or anomalies within the source data. Example embodiments involve systems and methods for performing the data integrity checks and generating the human-readable reports. For example, the method may include operations to ingest data from a source database through a data pipeline and into a local database, access the data from the data pipeline, determine a data type of the data, determine subtypes of data elements which make up the data, determine a count of each subtype, and generate a human-readable report, to be displayed at a client device.
The present disclosure relates to systems and techniques for developing APIs that utilize multiple pre-existing APIs. The present disclosure also relates to a user interface that allows for chaining APIs together as a function of multiple pre-existing APIs. The present disclosure also relates to security and authorization of a user to execute one or more APIs as part of an API chain.
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
89.
METHOD AND APPARATUS FOR PROVIDING SECURE DEBUG INFORMATION
A method and apparatus provides debug information and employs a central debug service in a management environment that issues, to a client debug agent in a client environment, a cryptographically secure signed request for access to debug information that is generated by code executing in the client environment. The request is signed using a private key of a public/private key pair associated with the central debug service. The central debug service receives from the client debug agent, a request that requests the public key of public/private key pair associated with the central debug service and provides the public key of the central debug service to the client debug agent, in response to the request, for verification of approval to access debug information in the client environment. The central debug service receives the requested debug information from the client debug agent, in response to a successful signature verification by the client debug agent.
H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
G06F 11/36 - Prevention of errors by analysis, debugging or testing of software
Apparatus and methods receive input descriptive of a retention policy; evaluate one or more datasets against the retention policy to determine one or more deletable data elements in the one or more datasets; and delete the one or more deletable data elements from a data store.
A method comprises listening for changes to a plurality of configuration files respectively of a plurality of service applications, each configuration file indicating a resource item type and one or more user actions, the listening comprising determining whether a configuration file is updated, disabled, or enabled by a corresponding service application; detecting a change to a specific configuration file of a specific service application; updating, in response to the change to the specific configuration file, mapping data in a central catalogue that associates a specific resource item type and one or more specific user actions with the specific service application; detecting a change to a particular resource item; determining that the particular resource item has a first resource item type that matches the specific resource item type; transmitting the particular resource item to the specific service application; storing metadata information regarding the particular resource item in the central catalogue.
Systems and methods for preparing and analyzing data related to geo-spatial properties. A system generates from a first data source, based on an ontology, a geographic dataset including first data objects representative of first data from the first data source and at least one geo-spatial reference based on respective location information from the first data source that corresponds to the first data. The system can also generate a vector map data tile layer based on the ontology using the geographic dataset and including vector map data tiles, having map geometry data linked to the first data objects by a geo-spatial reference, and corresponding to a portion of a geographic area represented by the vector map data tile layer. In response to requests from the front-end system application for first data related to a geo-spatial feature, tiles can be provided and first data corresponding to selected geo-spatial references can be displayed.
A computer-implemented method for generating a monitor for at least one software service from a monitor template, includes, in at least some aspects: providing a monitor template. Further, in certain instances, the method includes determining one or more endpoints included in code for a first software service of the at least one software service. In addition, in some aspects, the method includes generating a first monitor for the first software service code using the monitor template based at least upon a first endpoint of the one or more endpoints included in the first software service code.
Systems and methods are provided for determining a set of objects, the objects corresponding to a given case or application of a deletion/retention policy; determining at least one object in the set of objects to be scheduled for deletion, the at least one object being associated with a given state that specifies a deletion and/or retention type and schedule for the at least one object; and scheduling data corresponding to the at least one object for deletion from one or more data sources based at least in part on the deletion and/or retention type and schedule specified in the object state.
A method for management of a production pipeline is disclosed. The method may comprise accessing a data model which comprises a plurality of data objects, including one or more assembly objects, each assembly object representing a part to undergo one or more production events to be performed on a part at a first party facility for providing to a second party facility and one or more production event objects, each production event object representing a particular production event and having a plurality of properties, including an associated start time property and an end time property. The method may also comprise receiving selection of one or more production event objects to be linked to a first assembly object and an indication of values for at least the start time property and end time property of the one or more production event objects and receiving input of one or more alert conditions to be linked to the first assembly object. The method may also comprise receiving first input data in relation to one or more of the production event objects that modifies one or both of the start and end time values and determining that the modification meets an alert condition linked to the assembly object. The method may also comprise issuing an alert to a user interface responsive to the determination.
A method, performed by one or more processors, includes: receiving, from search engine software, first data. In some examples, the first data includes one or more data records. In some examples, the method further includes deriving, based on the first data, a data access query for locating second data using data extracted from the one or more data records. In some examples, the second data includes one or more data objects. In some examples, the method further includes sending, to data access software, the data access query to cause the data access software to locate the second data stored in a second data store different from a first data store storing the first data.
Example embodiments relate to a network-based workflow system, employed for receiving workflows, defining one or more data-object types based on the workflows, generating data-objects, assigning a workflow from among the one or more workflows to the data-object, and managing the data-object through various states of based on the workflow. As discussed, a “workflow” refers to orchestrated and repeatable patterns enabled by a systematic organization of resources into processes that transform and modify presentations of data-objects based on corresponding data-object states. A workflow may therefore comprise a set of states, wherein each state is linked to another state by one or more transitions, and wherein the transitions are associated with a set of events which may occur at each state.
This disclosure describes a computing system and method that allows developing and hosting third party widgets for building web or mobile applications. An exemplary method includes receiving, within a sandbox environment, source code for generating a widget and generating a live preview of the widget based on the source code; receiving a publishing command to publish the widget and executing an automatic pipeline to run tests on the widget; publishing the widget to a repository that is accessible through a no-code application builder; receiving, from the no-code application builder, a request to integrate the widget into an application; generating a configuration user interface for customizing the widget; and integrating the customized widget into an application by at least loading an ontology data corresponding to the application into the widget.
Systems and methods for video georegistration are provided. An example method includes receiving an input video including a plurality of video frames; calibrating a first set of video frames selected from the plurality of video frames to generate a first set of calibrated video frames using a calibration transform; and performing one or more reference georegistrations to a second set of video frames selected from the plurality of video frames to generate a video georegistration transform using the second set of video frames. The second set of video frames have fewer video frames than the first set of video frames. The method further includes generating an output video using the calibration transform and the video georegistration transform.
Computer implemented systems and methods are disclosed for importing data from electronic data files. In accordance with some embodiments, a file format is assigned to a source electronic data files by a data importation system. The data importation system may further identify a file type identifier associated with the source electronic data file and map the source electronic data file to a transformation template. The data importation system may further store the file format, file type identifier, and an indication of the transformation template as a file type profile associated with the source electronic data file in a database.
